Table of Content What is Augmented Reality? Why the current Navigational Systems need an update in terms of Technology? Why Augmented Reality (AR) in Navigation? How does Augmented Reality (AR) work? Augmented Reality (AR) in Car Navigation as an Application Advantages of using Augmented Reality (AR) in Car Navigation Seminal Patent Patent Data Analysis Conclusion What is Augmented Reality? Augmented reality (AR) is a technology similar to virtual reality (VR) but with more added features. AR builds the 3D reality environment by superimposing digital data. In AR technology, the real world is equipped with virtual objects. AR virtual elements can be used to enhance the users’ experience and make the experience an interactive event by features like popping instructions, messages, cartoon characters, intellectual messages, and guide with the help of arrows. AR technology can be implemented in any area of application, including but not limited to automotive, GPS, gaming, and smartphones. Some examples of AR devices are eyeglasses, lenses, scanners, gaming console equipment, and smartphones. AR uses sensory devices to build virtual characters around the object. Why the current navigational systems need an update in terms of technology? Not Accurate - The navigation system depends upon receiving signals from the map of satellites orbiting earth. If the signal is received properly from the satellites at the same time, then only the accurate position of the object will be available. On the other hand, if one of the satellites miss out sharing the grid coordinates then the accuracy of the object will not be accurate. Moreover, the atmospheric condition too affects the accuracy of the navigation system. Lack of Local Knowledge - The information related to the current place or location is available to limited extent. For example, the name of roads, the situation of roads and traffic on days like heavy rains etc. Driving Distraction - The user needs to continuously check the phone’s screen for location on map which keeps driver distracting while driving. Why Augmented Reality (AR) in Navigation? AR technology brings a lot of user-friendly features with it. It provides a feature that helps user to visualize the location in the real world with the help of augmented reality device. As the user puts a search query for a particular location, the AR device will project the road map till the searched location in front of the user. This will make the guiding system more interactive and helpful. The augmented reality annotations will display the useful information like name of the road, nearby important places names, traffic information etc. How does Augmented Reality (AR) work? The pivotal motive of the augmented reality technology in navigation systems is to assist the user in providing the useful information and directions with annotations and characters overlaid on top of the real environment. The technologies behind the augmented reality technology: SLAM (Simultaneous Location and Mapping) - The simultaneous location and mapping superimpose the virtual characters over the real-world environment. The sensors, for example, gyroscope and accelerometer for localization of the real-world objects is used. Depth Tracking - The depth tracking is used to calculate the distance of the real-world object with respect to the augmented reality’s camera. The functioning of the AR device’s camera is similar to the ordinary camera used for functions like focusing on an object or blurring the scene. Image Processing and Projection - The image processing and projection is performed once the above two processes are complete. The Augmented reality program will process the pictures according to the requirement. After processing the pictures are projected on the user’s screen. Augmented Reality (AR) in Car Navigation as an Application What if I tell you that, you can get assistance on the navigation app in the form of virtual arrows, road signs, information displaying on your mobile screen about the place, annotations depicting the temperature of the place, or some interactive cartoon characters for talking with you and giving you the information. Sounds good, isn’t it! Augmented Reality gives you these features and allows the users to get guiding information. This technology is utilized in the automotive sector also and gives wonderful results. Generally, what happens is we ask the passers-by for their advice for reaching our unknown destination. The passer-by may give you a perfect plan to reach the destination, which happens rarely or you may get to listen to a confusing set of instructions to reach the destination. And if one thinks of the 2D maps, you may just get the route with information about the fastest route. But with AR technology, the user can get additional pieces of information like when crossing in front of a building, the name of the building may be displayed on the AR device’s display, restaurant menu outside the restaurants building, name of the roads, traffic information like fastest route, speed limits instructions, and many more. All these features are available just by hovering the AR device on the respective place of interest. Advantages of using Augmented Reality (AR) in Car Navigation The information available is just a click away. Secure and trustworthy information for tourists and people in unfamiliar places. Less time consuming - People can get any information about the place by just hovering the AR device on the place of interest. Easy access to the driver - The driver need not look down for checking the phone for route maps. The HUD (Heads up display) makes it easier to focus on the road and keep going. The interactive and easy-to-understand annotations by the driver. The AR technology gives notifications to the driver upon suspecting any emergency or hazards on the road. For example, Nissan’s IV Technology (Invisible-to-visible) allows the driver to have an augmented reality co-passenger in the car, which will keep interacting with the driver and will behave like a co-pilot. Seminal Patent Title: Apparatus and method of providing road guidance based on augmented reality head-up display Patent: US9151634B2 Current Assignee: Hyundai Motor Co Priority Date: February 11, 2014 The patent teaches an arrangement that displays and helps the driver by giving directions with the help of annotations. The guidance is provided on the basis of an augmented reality head-up display (HUD). The memory unit will store instructions related to various programs. The processor will be executing the program instructions. Once the program instructions are executed, annotations will be created displaying the route towards the destination. A virtual preceding vehicle will be displayed on the HUD which will be available through the distance being covered by the driver. The virtual preceding vehicle is the graphical image representation of the driver’s car on the HUD. The turning signals will be displayed on the virtual preceding vehicle at different time instants. The turn signals will be displayed on the basis of the remaining distance of the turning point with respect to the driver’s car position. Patent Data Analysis From the above graph, we can see that the maximum number of patent families were filed in 2019. As the technology is in the development phase, we can expect that more patents will be filed in the coming years. The big companies are investing in the idea of AR in car navigation. As the research on augmented reality application in car navigation is in progress the count of patent in this area is expected to rise exponentially. A humble beginning with just 871 patents in the first year went on to 1890 patent applications in the fifth year. It is interesting to note that the peak was observed in the eighth year when the recorded patent application numbers went on to 6824. But a sudden dip was seen in the following year with 5480 patent applications which further fell to 2435 in the tenth year. This might be because of many factors like lack of funds for R&D, loopholes in technical know-how and resistance from buyers; end in the market. From the above graph, we can see that the US, China, Korea, and Europe are the biggest contributors to this technology. US filed a number of 9909 patent applications, China with total 6546 patents and Japan recorded 4829 patent applications. European Patent office and Korea saw 4096 and 3612 patent applications, respectively. WIPO recorded 2661 patent applications while Germany recorded 1060, India recorded 795, Taiwan saw 642, and Great Britain had 433 patent applications. From the above graph, we can see LG Electronics is the biggest contributor in developing this technology globally. Next is Semiconductor Energy Laboratory with 2188 patents. Samsung, Sony, and Intel have a total of 1368, 1332, and 1330 patents to their name. Qualcomm can surely do better with just 656 assigned patents. Conclusion AR technology in automobiles is going to flourish in the coming years. As people are getting used to AR devices and glasses, the time is not far when AR assistance will be available in the automobile sector. Many top automobile manufacturing companies have already started experimenting the AR technology in cars, trucks, and motorbikes. The report by Fortune Business Insights states that the market for AR in the automotive sector will swell to USD 14.4 B by 2028. The AR technology in cars can totally change the concept of navigation systems globally. The HUDs (Heads up display) is the initial stage generation technology for automobiles. However, the technology may be implemented on the vehicle’s windshields or by projecting the information on the roads visible to the driver. Although the Heads-up display is being implemented initially in the cars, the development is being done on the windshield concept too. Future AR technology will be available in all sorts of vehicles. Moreover, it is anticipated that the vehicle’s windshield will be playing the role of the AR device’s display by projecting all the necessary apps, being controlled by voice commands, and making calls. References https://www.freep.com/story/money/cars/mark-phelan/2020/02/15/augmented-reality-navigation-noise-cancellation-cars-vehicles/4742843002/ https://www.lifewire.com/augmented-reality-ar-definition-4155104 https://www.wipro.com/blogs/wipro-insights/augmented-reality-in-the-automobile-industry--driving-vision/ https://www.investopedia.com/terms/a/augmented-reality.asp https://www.forbes.com/sites/bernardmarr/2019/08/26/are-you-ready-for-augmented-reality-in-your-car/?sh=1b668b3d3144 https://www.lifewire.com/augmented-reality-ar-definition-4155104 https://www.fortunebusinessinsights.com/blog/top-augmented-reality-companies-in-automotive-industry-10599 https://thetius.com/how-do-augmented-reality-navigation-systems-work/ https://learn.g2.com/augmented-reality-technologies Copperpod helps attorneys dig deep into technology products and find evidence of patent infringement through reverse engineering, product testing, and network packet capture. Our reverse engineering and network capture analysis services have been relied upon by leading trial attorneys for negotiating over a dozen settlements and royalty agreements on behalf of technology clients. Know more about how we leverage different RE techniques to uncover even the hardest to find evidence of patent infringement.

Table of Content What is Sentiment Analysis and how does it work? Types of Sentiment Analysis Significance of Sentiment Analysis What is the Process of Sentiment Analysis? What is Sentiment Score? Patent Data Analysis Difficulties of Sentiment Analysis Conclusion Every day, millions of online users express their views and attitudes through numerous channels by posting their opinions on product features, benefits, and value. This 'opinion' or sentiment data which is sometimes generated invisibly – often contain crucial data points that can be quite useful for organizations wanting to improve their client experience, products, or services. The E-Commerce industry views social media advertising as a critical metric for success because it ensures that visitors spend a significant amount of time on the portal, searching for products they like, making purchases, posting positive reviews on social media about the products they bought, and returning to the portal for future purchases. The ability to mine vast stores of unstructured social data for actionable insights, which is a daunting task that requires sophisticated NLP (Natural Language Processing), statistics, or machine learning methods to characterize and capture the sentiment value, is the key to e-commerce success with sentiment data. What is Sentiment Analysis, and how does it work? Sentiment analysis (also known as opinion mining) is a natural language processing (NLP) technique for determining whether data is positive, negative or neutral. It is frequently used on textual data to assist organizations for a variety of purposes. Simply put, sentiment analysis aids in determining a particular person’s attitude toward a topic. Sentiment analysis software sorts the data into positive, neutral, and negative categories. Sentiment analysis, also referred as text mining that finds and extracts subjective information from the source material, allowing a company to understand better the social sentiment of its brand, product, or service while monitoring online conversations. However, most social media stream analysis is limited to simple sentiment analysis and count-based metrics. This is similar to only scratching the surface and missing out on high-value discoveries that are just waiting to be uncovered. There are a variety of approaches and procedures for analysing sentiment, which vary depending on the demands of each organization. Machine learning and its subset, Deep learning algorithms are used to develop sentiment analysis models. These models are taught to discern whether a message is positive, negative, or neutral by feeding them millions of pieces of text. Sentiment analysis breaks down a communication into topic chunks and assigns a sentiment score to each topic. Statistics or machine learning based on supervised or semi-supervised learning techniques are used at the most basic level of sentiment analysis. Humans are used to score a data set in supervised learning. Semi-supervised learning combines automated learning with occasional checks to ensure the system is doing its job correctly. Deep learning is another method for performing sentiment analysis. Machine learning uses algorithms to train computers on large amounts of data so that they can act on what they've been taught and learnt. Instead of comprehending what information means, the system learns to identify it based on patterns, keywords, and sequences. Types of Sentiment Analysis Here are a few of the most common Sentiment Analysis techniques: Standard Sentiment Analysis - It recognizes the general tone of a written text and categorizes it as positive, negative, or neutral, this is one of the most popular types of Sentiment Analysis. Fine-Grained Sentiment Analysis - This method has a more elaborate polarity range and can be utilized by organizations to gain a better grasp of client sentiment/feedback. The responses are divided into five different sentiments, ranging from 5-stars to 1-star. Aspect-Based Sentiment Analysis - This analysis goes deeper than fine-grained analysis in determining the overall polarity of your customer evaluations. It assists you in determining which features (attributes or components) of a product are being discussed. Significance of Sentiment Analysis First and foremost, sentiment analysis is critical because emotions and attitudes regarding a topic may be transformed into meaningful data in a variety of fields, including business and research. Second, it saves time and effort because the sentiment extraction process is totally automated - the algorithm analyses the sentiment datasets, so human involvement is minimal. Third, as artificial intelligence, deep learning, machine learning methodologies, and natural language processing technologies advance, it is becoming a more popular phenomenon. Fourth, as technology advances, sentiment analysis will become more accessible and affordable to the general public as well as smaller businesses. Finally, the tools are getting smarter all the time. The more data they are fed, the better and more accurate they get at extracting sentiment. Let's take a closer look at how sentiment analysis can help: Management of a Company's Image - Consumers use the Internet to discuss brands, products, and services and share their experiences and recommendations. Opinions and comments abound on social media platforms, product evaluations, blog articles, and discussion forums, can be mined to collect and analyze business data. Sentiment analysis can be used for brand monitoring to assess the web and social media chatter regarding a product, a service, a brand, or a marketing campaign when it comes to brand reputation management. Online research aids in determining a brand's reputation and how consumers perceive it. Businesses can use discussion forums, online review sites, news sites, blogs, Twitter, and other publicly available internet sources to learn about customers, media, and expert opinions about their products, services, marketing efforts, and brands. For PR professionals, brand monitoring is a crucial area of business, and sentiment analysis should be one of their go-to tools. Feedback from Customers - Customers' views are analyzed via sentiment analysis by businesses. Consumers nowadays use their social media sites to express both positive and bad brand experiences. A sentiment analysis tool can detect positive mentions indicating strengths, as well as negative mentions indicating negative reviews and problems that consumers confront and write about online. Customer support benefits from a speedy response time because the mentions are identified so rapidly. This makes customer service more attentive and responsive in some circumstances because the customer support team is informed about any nasty remarks in real-time. Any errors must be reported as soon as possible to the support team. This makes managing the customer experience much easier and more pleasurable. Market Research - Sentiment analysis provides a large amount of data, making it a valuable supplement to any market research project. Whether you're looking at entire markets, niches, sectors, products, their specific characteristics, or market buzz, sentiment research may offer you a wealth of information about what people like, dislike, and expect. All of this information allows you to conduct more focused market research, which improves the decision-making process. Crisis Prevention - Brand24, for example, is a sentiment analysis tool that also serves as a media monitoring tool. They collect real-time mentions of predetermined keywords from websites, news sites, discussion forums, and other sources. PR professionals can use such a solution to receive real-time notifications about any unfavourable content that has surfaced on the Internet. When a firm notices a poor customer sentiment remark, it can move immediately to address the issue before it becomes a social media crisis. Valuable Business Intelligence - Sentiment analysis data offers businesses useful and informative information – about the present and prospective clients, fresh business marketplaces and opportunities – from which they can develop meaningful plans. Client service representatives can utilize social media to help them uncover customer pain areas, values, and habits, which can then be used to generate targeted communications that cater to their specific needs and desires. To generate a complete picture, intelligence insights must be combined with human insights and other essential metrics. Rejuvenate the Brand - Customer views of your organization and its aims are crucial to branding, and sentiment analysis allows you to quantify these perceptions. What are the opinions of current and potential customers on products and services, their consumer journey and experience, web content, marketing, and social campaigns? In a nutshell, the brand as a whole. Businesses that completely integrate sentiment research in the future will earn higher commercial value and a distinct competitive advantage. Consistent Criteria - When it comes to determining the sentiment of a text, it's estimated that just 60-65 per cent of the time, people agree. Text sentiment tagging is a highly subjective process that is impacted by human experiences, thoughts, and beliefs. Companies can apply the same criteria to all of their data by adopting a centralized sentiment analysis system, which helps them enhance accuracy and generate better insights. What is the Process of Sentiment Analysis? The approach is based on natural language processing and machine learning algorithms that classify pieces of writing as positive, neutral, or negative. Sentiment Analysis may employ a variety of algorithms: 1. Automatic This method is entirely based on machine learning techniques and learns from the data it receives. By inputting a vast amount of text documents with pre-tagged samples, data scientists train a machine learning model to detect nouns. The model will learn what nouns "look like" using supervised and unsupervised machine learning approaches such as neural networks and deep learning. Once the model is complete, the same data scientists can use the same training procedures to create other models to recognize different bits of speech. There are two types of machine learning models: Traditional Models - This method necessitates acquiring a dataset with examples for positive, negative, and neutral classes, processing the data, and then training the algorithm using the instances. These approaches are mostly used to determine text polarity. Because of its scalability, traditional machine learning algorithms such as Naïve Bayes, Logistic Regression, and Support Vector Machines (SVM) are commonly utilized for large-scale sentiment analysis. Deep Learning Models – These include neural network models such as CNN (Convoluted Neural Network), RNN (Recurrent Neural Network), and DNN (Deep Neural Network) that produce more exact results than traditional models. Deep Neural Network One of the most significant advantages of this algorithm is the enormous amount of data it can evaluate – far more than a rule-based algorithm. Machine learning also assists data analysts in resolving difficult challenges created by natural language inconsistencies. When it comes to drawbacks, the algorithm makes it tough to explain text analysis decisions, making it impossible to tell why a paragraph was labelled as good or bad. 2. Rule-Based Following the preparation of the sentiment libraries, software developers write a set of recommendations ("rules") to assist the computer in evaluating the sentiment expressed toward a certain entity (noun or pronoun) based on its proximity to known positive and negative phrases (adjectives and adverbs). This method relies on manually generated data classification rules. To generate a score, this method uses dictionaries of words with positive or negative values to represent their polarity and sentiment strength. Expressions can also be used to offer additional functionality. Rule-based sentiment analysis algorithms can also be adjusted based on context. How it works - It counts how many positive and negative words there are in a given text. It will provide a positive attitude if the number of positives exceeds the number of negatives. It will return a neutral sentiment if both are equal. Data preprocessing steps in Rule based Sentiment Analysis: Cleaning the Text - The special characters and digits from the text should be deleted in this phase. Python's regular expression operations library can be used. Tokenization - It is the process of breaking down a large text into smaller tokens. It can be done at the sentence or word level (sentence tokenization) (word tokenization). Enrichment – POS tagging - The process of transforming each token into a tuple with the type Parts of Speech (POS) tagging (word, tag). POS tagging is required for Lemmatization and to maintain the context of the word. Stopwords removal - In English, stopwords are words that provide relatively little relevant information. As part of the text preparation, we need to get rid of them. Every language has a list of stopwords. Obtaining the stem words (Lemmatization) - A stem is a component of a word that determines its lexical meaning. Stemming and lemmatization are two typical methods for getting root/stem words. The main distinction is that, because it merely chops off certain characters at the end, stemming frequently produces useless root words. Lemmatization produces meaningful root words, but it necessitates the use of POS tags on the words. This approach is transparent and straightforward when it comes to the principles underpinning analysis. Having said that, the method also has some drawbacks. Every word combination in a sentiment library must have a rule in a rules-based system. The creation and maintenance of these standards necessitates arduous manual effort. Finally, rules will never be able to keep pace with the evolution of natural human language. The old rules of grammar have been mangled by instant messaging, and no ruleset can account for every abbreviation, acronym, double-meaning, or mistake that may arise in any given text composition. 3. Hybrid Machine learning and traditional rules are used in hybrid sentiment analysis systems to compensate for the shortcomings of each technique. For example, rules-based sentiment analysis can be an excellent technique to lay the groundwork for PoS tagging and sentiment analysis. However, as we've seen, these rule sets quickly outgrow their control. This is where machine learning may help by taking on the burden of difficult natural language processing tasks like understanding double meanings. From low-level tokenization and syntax analysis to the highest-levels of sentiment analysis, most hybrid sentiment analysis systems mix machine learning with software rules to ease operations. What is Sentiment Score? Sentiment score is one method of assessing sentiment. It's a grading system that represents the emotional depth of a text's emotions. Sentiment score recognizes emotions and assigns them sentiment ratings ranging from 0 to 10 (from the most negative to the most positive). The sentiment score simplifies the process of determining how customers feel. Patent Data Analysis Top Players IBM tops the chart because it has spent years in the field. Its flagship, The IBM Watson NLU sentiment analysis tool, tells a user whether their data has a "positive" or "negative" sentiment and assigns a score to it. It is the most sought after tool in recent times. Unaddressed biases in machine learning models do not yield desirable or accurate outcomes, and a biased algorithm can produce stereotype-informed outputs. It's critical to train AI impartial, unbiased, and unwavering as artificial intelligence continues to automate corporate activities. Following IBM's footsteps is Cognitive scale is making a mark in the AI industry by providing organizations with intelligent, transparent, and trusted AI-powered digital systems. It also recently partnered with Ascendum to deliver Trusted AI solutions for the healthcare, fintech, and retail/eCommerce verticals. CognitiveScale will provide its trusted AI software, while Ascendum will provide the services and certified developers required to build AI-powered solutions and use cases that meet the customers' unique needs within these markets. People AI helps companies improve the performance of their sales teams by surfacing insights from sales behaviour and automating sales ramping and coaching. Microsoft Technology Licensing, salesforce.com, TalkDesk and Google are also in the running but need a significant amount of focus in the field to grow further. Patent Filing Trend The patent filing in the field of AI, especially in Sentiment Analysis, is rather bumpy. After the initial three years, a sharp spike can be seen where the number of filings rose from 146 to 348 within a year. Again the fifth year saw a slight dip, after which the trend saw exponential growth with the highest number of patent applications recorded in the eighth year (1030). Following years - ninth and tenth saw a fall in numbers. Sarcasm, negations, word ambiguity, and multipolarity are some issues faced while employing sentiment analysis. The recent advancements in AI, however, have fueled the industry, and it is ready to be back on track. It is evident from the pie-chart that the US leads the domain with the highest number of patents to its name. It is the top country in Investment Monitor's first assessment of AI investor friendliness. The United States leads in eight of the 17 measures examined, including e-participation, emerging technology investment, and software spending as a percentage of GDP. Second, in line is China, with a recent boom in the AI technology sector. The private sector, university laboratories, and the military are working collaboratively in many aspects. Difficulties of Sentiment Analysis Due to the complexities of language, sentiment analysis must deal with at least a few challenges. It can be difficult to ascribe a sentiment classification to a sentence in some instances. That's where sentiment analysis based on natural language processing comes in handy, as the computer attempts to emulate natural human discourse. Contrastive Conjunction - It is a challenge that a sentiment analysis system must deal with when one piece of writing (a sentence) contains two opposing words (both positive and negative). For example, "The weather was bad, but the hike was fantastic!" Recognition of Named Entities - Another major issue that algorithms must deal with is named-entity recognition. Words have varied meanings depending on their context. For example, Is "Everest" a reference to the mountain or the film? Anaphora Resolution - The problem of references inside a sentence, also known as pronoun resolution, specifies what a pronoun or a word refers to. For example, "We went to the theatre and then to dinner. It was a disaster." Sarcasm - Is there a mechanism for detecting sarcasm in sentiment analysis? For example, "I'm so glad the plane is delayed. We doubt!" The Internet - Lousy spelling, abbreviations, acronyms, lack of capitalization, and poor grammar affect the language economy and the Internet as a medium. It just so happens that any phrase used on the Internet takes on a life of its own. Sentiment analysis algorithms may have difficulty analyzing such pieces of writing. Conclusion Due to a huge number of real-world applications where uncovering people's opinions is vital in better decision-making, the discipline of sentiment analysis is an intriguing new study direction. People have recently begun to share their ideas on the Internet, which has increased the necessity for assessing opinionated online information for a variety of real-world applications. Sentiment analysis is a rapidly developing field with a wide range of applications. Although sentiment analysis tasks are difficult due to their natural language processing origins, due to the huge demand for them, substantial progress has been made in recent years. Not only do businesses want to know how their products and services are viewed by customers (and how they compare to competitors), but customers also want to know what other people think before making a purchase. For the foreseeable future, sentiment analysis and opinion mining will be significant due to the growing demand for product insights – and the technical obstacles that the sector is currently confronting. Opinion mining systems of the future will require a stronger link between extensive information bases and reasoning processes influenced by the human mind and psychology. This will lead to a better comprehension of natural language opinions and will help people communicate more effectively and bridge the gap between unstructured data in the form of human thinking and organized data that can be studied and handled by a machine more effectively. As a result, intelligent opinion mining algorithms capable of managing semantic information, analogy, continuous learning, and emotion detection can be developed, resulting in very efficient sentiment analysis. References: https://www.ijert.org/sentiment-analysis-in-e-commerce-using-recommendation-system https://www.nabler.com/business-intelligence-consulting/articles/customer-sentiment-analysis-in-e-commerce-data-initiatives/ https://ieeexplore.ieee.org/document/8970492 https://www.aimspress.com/article/doi/10.3934/mbe.2020398?viewType=HTML https://medium.com/federatedai/sentiment-analysis-in-e-commerce-e8a06a498a75 https://www.ibm.com/blogs/watson/2020/08/solving-common-challenges-in-sentiment-analysis-with-help-from-project-debater/ https://www.cogitotech.com/blog/sentiment-analysis-types-how-it-works-why-difficult https://www.lexalytics.com/technology/sentiment-analysis#machine-learning-sentiment https://medium.com/@mariano.scandizzo/sentiment-analysis-using-machine-learning-part-i-data-collection-a0bd36c17c6e

Table of Content What exactly is Antitrust? A Brief History of Antitrust The Present Scenario The Sherman Act (15 U.S.C. § 1) Activities of the Federal Trade Commission (FTC) The Clayton Act (15 U.S.C. § 12) Antitrust Guidelines for Intellectual Property Licensing Case study: NVIDIA+ARM Merger Conclusion The robber barons dominated the American economy in the nineteenth century. A small group of people controlled more wealth and power than the entire country. For this reason, they would work together to keep the rest of the world away. As a result of their conspiracy, these robber barons deprived everyone else of a fair chance. Antitrust laws were enacted to prevent this from happening. Since antitrust law's inception in the late 1800s, the relationship between patent law and antitrust law has perplexed legal minds. One promotes monopoly, while the other discourages it. Patent law grants the power to exclude competitors, although antitrust law punishes those who do so. On the route to dominance, antitrust law identifies some prohibited types of behaviour. Monopolization or attempted monopolization is used to describe this type of behaviour. Patent law has long permitted patent holders to suppress their ideas, which means that customers will receive nothing for the duration of the patent. As a result, the commonly held belief that a patent holder is a monopolize, understates the degree of harm that we would tolerate from a patent holder. Understanding the various shades of meaning is essential for navigating the patent-antitrust junction. Antitrust enforcement agencies in the United States now acknowledge a much deeper and intertwined relationship between antitrust and intellectual property rights. What Exactly Is Antitrust? Antitrust laws are rules designed to promote competition by reducing a company's market power. This frequently entails ensuring that mergers and acquisitions do not concentrate market power, create monopolies, and dismantle monopolies. Antitrust laws also prohibit numerous businesses from collaborating or creating a cartel to stifle competition through activities like price-fixing. Antitrust law has established unique legal expertise due to the difficulty of determining what behaviours may hinder competition. A Brief History of Antitrust During the 1950s and 1960s, the pendulum swung back, and IPRs were subjected to strict antitrust investigation and were to be construed narrowly. The establishment of formalistic rules accompanied this, dubbed the "Nine No No's" by Antitrust Division officials in 1970, that barred certain licensing arrangements and other agreements involving IPRs regardless of their actual competition impact. They included outright prohibitions on: Mandatory package licensing (also known as patent pools) Tying of unpatented supplies Compulsory payment of royalties in amounts not reasonably related to sales of the patented product Mandatory grant backs Classical vertical distribution restraints such as post-sale restrictions on resale by purchasers of patented products, specifying the price licensees could charge upon resale of licensed products, and tie-outs. Fortunately, the introduction of economic rigor into antitrust research in the late 1970s and 1980s abandoned almost all of these per se norms. Patent law gave intellectual property owners additional valuable rights during the same period. The work of the newly formed Federal Circuit reflected this trend. It adopted a more systematic investigation into the anticipated competitive impacts of specific behaviour or business arrangements. The Present Scenario Currently, three federal antitrust statutes are in effect. The Federal Trade Commission and the United States Department of Justice are in charge of enforcing antitrust laws. The Sherman Act, the Federal Trade Commission Act, and the Clayton Act are the three acts in effect. The former is primarily concerned with areas of the economy where consumer spending is high. In contrast, the latter has exclusive antitrust jurisdiction over industries such as telephones, banking, railroads, and airlines and can impose criminal punishments. The Sherman Act (15 U.S.C. § 1) Outlaws "every contract, combination, or conspiracy in restraint of trade," and any "monopolization, attempted monopolization, or conspiracy or combination to monopolize." The Sherman Act, the first antitrust law, was passed in 1890 and was described as a "complete charter of economic liberty aimed at safeguarding open and unrestricted competition as the rule of commerce." It prohibits all contracts, combinations, and conspiracies that unreasonably restrain interstate trade (Section 1 violations). The Sherman Act also prohibits any efforts to monopolize any part of interstate commerce (Section 2 violations). The Sherman Act only prohibits unjustifiable trade restraints, not all restraints. Trade restrictions may be imposed by activities such as the establishment of a partnership, although they are not excessive. It carries criminal penalties of up to $100 million for corporations and $1 million for individuals, as well as a maximum sentence of 10 years in jail. If one of those amounts is more than $100 million, federal law allows the maximum fine to be enhanced to twice the amount the conspirators made from the illegal conduct or twice the money lost by the victims of the crime. Sherman Act violations can be divided into two main categories: Violations “per se” "Per se" violations are actions that virtually always restrict trade and need little research into their impact on competition. The aim of the activity does not need to be shown when prosecuting a per se offence; simply the fact that the action occurred does. Price fixing, market division schemes, bid rigging, and group boycotting are examples of this type of infringement . Violations of the “rule of reason” Some business operations require a context analysis, often known as a "rule of reason" examination. If a company conduct is judged to be unreasonably restricting commerce, it is found to be in violation of the Sherman Act under a "rule of reason" examination. Monopolies, tying, exclusive deals, and price discrimination are examples of per se Sherman Act breaches. The Federal Trade Commission Act , which established the FTC, and the Clayton Act were passed by Congress in 1914. These are the three fundamental federal antitrust statutes that still exist today, with minor changes. Antitrust laws prohibit illegal mergers and commercial practices in general, leaving it up to the courts to determine which are unlawful based on the facts of each case. Courts have applied antitrust laws to evolving marketplaces from horse and buggy days to the digital age. The Federal Trade Commission (FTC) Act (15 U.S.C §§ 41-58) bans "unfair methods of competition" and "unfair or deceptive acts or practices." According to the Supreme Court, all violations of the Sherman Act also violate the FTC Act. Although the FTC does not have the authority to enforce the Sherman Act, it can pursue actions under the FTC Act against the same illegal activities under the Sherman Act. Other acts that impair competition but do not fit neatly into the types of conduct explicitly outlawed by the Sherman Act are also covered by the FTC Act. The FTC Act allows only the FTC to file lawsuits. Activities of the Federal Trade Commission (FTC) The FTC, in conjunction with the U.S. Department of Justice Antitrust Division, enforces federal antitrust laws in the United States. Its responsibilities include: • Prosecuting companies for federal antitrust law violations • Evaluating pre-merger notifications to determine the merger’s impact on competition • Developing policy for continued protection against anticompetitive activity • Educating consumers and businesses about current laws and regulations The Clayton Act (15 U.S.C. § 12) Congress passed the Clayton Act in 1914. As the FTC explains: “With the Sherman Act in place, and trusts being broken up, business practices in America were changing. But some companies discovered merging as a way to control prices and production (instead of forming trusts, competitors united into a single company. The Clayton Act helps protect American consumers by stopping mergers or acquisitions that are likely to stifle competition.” The Clayton Act targets tactics like mergers and interlocking directorates that the Sherman Act does not expressly prohibit (the same person making business decisions for competing companies). The Clayton Act, (Section 7), forbids mergers and acquisitions that "may materially decrease competition or tend to create a monopoly." The Clayton Act, amended by the Robinson-Patman Act of 1936, prohibits certain discriminatory rates, services, and allowances in merchant dealings. The Hart-Scott-Rodino Antitrust Improvements Act of 1976 revised the Clayton Act again, requiring corporations seeking big mergers or acquisitions to notify the government in advance. When private parties are damaged by conduct that violates either the Sherman or Clayton Acts, the Clayton Act allows them to sue for triple damages and get a court order barring the anticompetitive to practise in the future. Prohibited Actions under the Clayton Act The Clayton Act adds to the Sherman Act's prohibitions by outlawing practises that are likely to stifle competition. By allowing businesses to run more effectively, many mergers enhance competition and customers. However, some mergers alter market dynamics, resulting in higher costs, fewer or lower-quality goods or services, and less innovation. The Clayton Act forbids mergers and acquisitions that have the potential to "significantly decrease competition or tend to create a monopoly." The main concern is whether the planned combination will establish or strengthen market power, or facilitate its exercise. Proposed mergers between direct competitors raise the most antitrust concerns. The Clayton Act also prohibits anti-competitive conduct which may take place through: Exclusive Dealings: requiring a buyer or seller to do buy or sell all or most of a certain product from a single supplier such that competitors are unable to compete in the market. Price Discrimination: selling similar goods to buyers at different prices. Tying & Bundling: selling a product or service on the condition that the buyer agrees to also buy a different product or service. These Acts serve three major functions. First, Section 1 of the Sherman Act forbids price fixing and cartel activity, as well as other collusive actions that restrict commerce unreasonably. Second, Section 7 of the Clayton Act prohibits organizations from merging or acquiring each other in a way that reduces competition or creates a monopoly. Third, monopolization is prohibited under Section 2 of the Sherman Act. Antitrust Guidelines for Intellectual Property Licensing The FTC and DOJ jointly issued the Antitrust Guidelines for the Licensing of Intellectual Property ("IP Guidelines") in 1995, which explain the agencies' current complementary approach to applying antitrust principles in matters involving intellectual property rights. In collaboration with the intellectual property bar, the IP Guidelines were created. Three essential elements underpin the IP Guidelines' integrated approach. To begin, antitrust regulators in the United States apply the same broad antitrust rules to conduct involving intellectual property as they do to conduct involving any other type of property. However, the agencies acknowledge that intellectual property has crucial distinguishing characteristics, such as the ease with which it might be misappropriated. Such distinctions are taken into account in antitrust investigations concerning intellectual property. Nonetheless, the antitrust principles that govern are the same. The second criterion is that the agencies do not assume that intellectual property provides market power in the antitrust context. The third principle is that the agencies often consider intellectual property licensing procompetitive. This is significant because it shows a refinement of antitrust enforcement theory from prior decades. The authorities understand that intellectual property licensing allows businesses to integrate complementary production elements. Licensing can also aid in the integration of additional intellectual property. Licensing may help consumers by increasing access to intellectual property and reducing the time and cost of bringing new products to market. The IP Guidelines apply the concepts of specific licensing procedures, such as cross-licensing, pooling, or acquisition of intellectual property, and outline fundamental principles. These examples can evaluate the analysis and see if it applies to other practices. Case Study: NVIDIA+ARM Merger The Federal Trade Commission filed a lawsuit to stop Nvidia Corp. from buying Arm Ltd., a chip design company based in the United Kingdom, for $40 billion. Nvidia Corp., Arm Ltd., and Softbank Group Corp. are named in the lawsuit. The administrative complaint was issued by a 4-0 vote of the Commission. On August 9, 2022, the administrative trial is set to commence. The acquisition was also met with opposition in China, where authorities were more likely to oppose the deal if it had received clearance elsewhere. Background Arm, which is owned by Softbank Group Corp. of Tokyo, does not manufacture or sell finished computer chips or devices. It develops and licenses microprocessor designs and architectures, referred to in the complaint as Arm Processor Technological, to other technology businesses, including Nvidia. These firms, in turn, rely on Arm Processor Technology to create computer processors that power everything from smartphones to tablets to driver-assistance systems to enormous datacenter computers. California-based Nvidia is one of the world's largest and most valuable computing companies. Nvidia is a company that creates and sells computer chips and devices. Both Nvidia and its major competitors rely on Arm's technology to produce their own competing products in these areas. The lawsuit claimed that the acquisition will stifle competition by giving Nvidia access to competitively sensitive information from Arm's licensees, some of whom are Nvidia's competitors, and that it will reduce Arm's incentive to pursue innovations that are perceived to be in competition with Nvidia's business interests. Insights Arm's licensees now routinely exchange competitively sensitive material with Arm, including Nvidia's competitors. According to the complaint, licensees rely on Arm for assistance in creating, designing, testing, debugging, troubleshooting, maintaining, and upgrading their products. Because Arm is a neutral partner, not a competitor chipmaker, licensees share competitively sensitive information with Arm. According to the complaint, the acquisition is likely to result in a significant loss of trust in Arm and its ecosystem. The acquisition is also likely to hurt innovation competitiveness by preventing Arm from pursuing breakthroughs that it would have undertaken if it weren't for Nvidia's ambitions getting in the way. If Nvidia determines that new features or innovations will harm Nvidia, the merged company will have less incentive to create or enable them, according to the complaint. In partnership with Arm, SBG also announced that Arm public offering will commence in the fiscal year ending March 31, 2023. Arm's technology and intellectual property, according to SBG, will continue to be at the forefront of mobile computing and artificial intelligence development. In partnership with Arm, SBG also announced that it will commence preparations for an Arm public offering in the fiscal year ending March 31, 2023. Arm's technology and intellectual property, according to SBG, will continue to be at the forefront of mobile computing and artificial intelligence development. Another similar case was in the news when Qualcomm dropped its $44 billion, two-year pursuit of Dutch chipmaker NXP in 2018 after failing to gain approval in China, a victim of a trade war between Beijing and Washington. Conclusion Intellectual Property and innovation have become increasingly important in our economy and, as a result, in antitrust enforcement. Several aspects of intellectual property law are being changed or expanded to adapt to new technologies. Authorities, for example, are exploring measures to strengthen intellectual property protection for factual databases and other information collections. States also strive to establish a standardized mechanism for enforcing intellectual property license agreements. Because antitrust laws and patent rights are mutually beneficial, both promote innovation and competition. However, because both patent rights and antitrust laws utilize similar terminology, it can be challenging to understand the concepts underpinning both areas of law when discussing the competition. Even though the terms are identical, their meaning is not, which confuses. Conflict emerges mainly due to this, and the laws are more generic than specific. References - https://www.ftc.gov/public-statements/1999/05/antitrust-and-intellectual-property-law-adversaries-partners https://www.justice.gov/atr/speech/antitrust-and-intellectual-property https://www.mondaq.com/unitedstates/patent/750422/ip-antitrust-know-how-2018 https://www.investopedia.com/ask/answers/09/antitrust-law.asp#:~:text=3%EF%BB%BF-,What%20Are%20Antitrust%20Laws%3F,in%20an%20open%2Dmarket%20economy . https://www.ftc.gov/tips-advice/competition-guidance/guide-antitrust-laws/antitrust-laws https://www.ftc.gov/tips-advice/competition-guidance/guide-antitrust-laws https://web.stanford.edu/dept/law/ipsc/pdf/feldman-robin.pdf https://blog.ipleaders.in/patent-rights-antitrust-laws-usa/ https://www.nowlandlaw.com/2019/03/23/famous-antitrust-cases-of-the-last-century/ https://aon.mediaroom.com/2021-07-26-Aon-and-Willis-Towers-Watson-Mutually-Agree-to-Terminate-Combination-Agreement https://www.ftc.gov/news-events/press-releases/2021/12/ftc-sues-block-40-billion-semiconductor-chip-merger https://www.nytimes.com/2021/12/02/technology/ftc-nvidia-arm-deal.html

Table of Content The Berkus Method Risk Factor Summation Method Scorecard Valuation Method Comparable Transactions Method Book Value Liquidation Value Discounted Cash Flow First Chicago Method Conclusion “A startup is a company that is in the first stage of its operations. These companies are often initially bankrolled by their entrepreneurial founders as they attempt to capitalize on developing a product or service for which they believe there is a demand. Due to limited revenue or high costs, most of these small-scale operations are not sustainable in the long term without additional funding from venture capitalists” - Investopedia As the definition from Investopedia suggests that every startup seeks for funding from either venture capital, angel investors or crowd funding, the startup valuation is a primary requirement for the funding firms. Venture capital is a type of funding for startups or growing business. It usually comes from venture capital firms that specialize in building high risk financial portfolios. Venture capital firm gives funding to the startup company in exchange for equity in the startup. An angel investor is a wealthy individual who provides funding for a startup, often in exchange for an ownership stake in the company. Crowdfunding is the use of small amounts of capital from a large number of individuals to finance a new business venture. Crowdfunding makes use of the easy accessibility of vast networks of people through social media and crowdfunding websites to bring investors and entrepreneurs together to raise the funding for a startup. For any startup to grow and get the funding, they need to prove their value (in terms of innovative technology used in their product or service, future demand of their product or service and/or financial value) to the investors. There are many standard valuation methods that can be adopted by investors to invest in a startup. 1. The Berkus Method “Pre-revenue, I do not trust projections, even discounted projections.” — Dave Berkus. This method, which is used and defined by active angel investor David Berkus, involves a lot of estimation. First, Berkus says that investors should believe the company has a potential to hit $20 million or more in revenues by the 5th year of operation. Then, he applies a scale to five components of a startup, rating each at up to $500,000. The components are: These numbers are maximums that can be “earned” to form a valuation, allowing for a pre-revenue valuation of up to $2 million (or a post rollout value of up to $2.5 million), but certainly also allowing the investor to put much lower values into each test, resulting in valuations well below that amount. 2. Risk Factor Summation Method This Method brings further risk management and governance consideration based on specific risk factors. The Ohio TechAngels describe the method as follows: “Reflecting the premise that the higher the number of risk factors, then the higher the overall risk, this method forces investors to think about the various types of risks which a particular venture must manage in order to achieve a lucrative exit. Of course, the largest is always ‘Management Risk’ which demands the most consideration and investors feel is the most overarching risk in any venture. While this method certainly considers the level of management risk it also prompts the user to assess other risk types,” including: 1. Management 2. Stage of the business 3. Legislation/Political risk 4. Manufacturing risk 5. Sales and marketing risk 6. Funding/capital raising risk 7. Competition risk 8. Technology risk 9. Litigation risk 10. International risk 11. Reputation risk 12. Potential lucrative exit Instead of assigning percentage weights and multiples, we assign the following ratings to each risk factor and do an adjustment to the average pre-money valuation per each rating: 3. Scorecard Valuation Method This method compares the target company to angel-funded startup ventures and adjusts the average valuation of recently funded companies in the region to establish a pre-money valuation of the target. Such comparisons can only be made for companies at the same stage of development. Individual accredited investors in typical angel deals put personal capital at risk for an equity share of growth-oriented, start-up companies. These angel investors generally invest $25,000 to $100,000 in a round totalling $250,000 to $1,000,000. In 2011, the valuation of pre-revenue, start-up companies is typically in the range of $1–$2 million and is established by negotiations between the entrepreneur and the angel investors. For this round of investment, the angels collectively purchase 20-40% of the equity of the company and are seeking a return on investment of 20-30X in a period of five to eight years. I. Determine the average premoney valuation of pre-revenue companies in the region and business sector of the target company. Pre-money valuation varies with the economy and with the competitive environment for startup ventures within a region. In most regions, the pre-money valuation does not vary significantly from one business sector to another. II. Evaluate the start up on the following 7 critical factors and their weightage accordingly. The investor then assigns a rating usually in the range of say 0.5 to 1.5 with 1 as a base for the normal requirement and arrives at the weighted average rating of the start-up. Suppose the investor assigns the following ratings to the start-up. III. Multiply the rating factor with the average valuation In this case: 1.15*1.25 = 1.4 Hence, the pre-money valuation of the start-up will be $1.4 million. 4. Comparable Transactions Method Comparable transactions is one of the conventional methods to value a company for sale. The main approach of the method is to look at similar or comparable transactions where the acquisition target has a similar business model and similar client base to the company being evaluated. Steps to perform precedent transaction analysis: I. Search for relevant transactions The process begins by looking for other transactions that have happened in (ideally) recent history and are in the same industry. The screening process requires setting criteria such as: · Industry classification · Type of company (public, private, etc.) · Financial metrics (revenue, EBITDA, net income) · Geography (headquarters, revenue mix, customer mix, employees) · Company size (revenue, employees, locations) · Product mix (the more similar to the company in question the better) · Type of buyer (private equity, strategic / competitor, public/private) · Deal size (value) · Valuation (multiple paid i.e. EV/Revenue, EV/EBITDA etc.) II. Analyze and refine the available transactions Once the initial screen has been performed and the data is transferred into Excel then it’s time to start filtering out the transactions that don’t fit the current situation. In order to sort and filter the transactions, an Analyst has to careful “scrub” the transactions by carefully reading the business descriptions of the companies on the list and removing any that aren’t a close enough fit. Many of the transactions will have missing and limited information if the deal terms were not publicly disclosed. The Analyst will search high and low for a press release, equity research report, or another source that contains deal metrics. III. Determine a range of valuation multiples When a short list is prepared (following steps 1 and 2) the average (or selected range) of valuation multiples can be calculated. The most common multiples for precedent transaction analysis are EV/EBITDA and EV/Revenue. An Analyst may exclude any extreme outliers such as transactions that had EV/EBITDA multiples much lower or much higher than the average (assuming there is a good justification for doing so). IV. Apply the valuation multiples to the company in question After a range of valuation multiples from past transaction has been determined, those ratios can be applied to the financial metrics of the company in question. For example, if the valuation range was: · 5x EV/EBITDA (low) · 0x EV/EBITDA (high) And the company in question has EBITDA of $150 million, The valuation ranges for the business would be: · $675 million (low) · $900 million (high) V. Graph the results (with other methods) Once a valuation range has been determined for the business that’s being valued it’s important to graph the results so they can be easily understood and compared to other methods. 5. Book Value Book value, a multiple of book value, or a premium to book value is also a method used to value manufacturing or distribution companies. Book value is total assets minus total liabilities and is commonly known as net worth. This form of valuation is based on the books of a business, where owners' equity total assets minus total liabilities is used to set a price. There are a couple of problems with this simplified approach. First step is to audit the business’ books of the company. Secondly, the value of some assets, such as buildings, equipment and furniture/fixtures, may be overstated on the books, and may not reflect the maintenance and/or replacement costs for older assets. Using the Tangible Book Value, intangible or soft assets are deducted from the total assets. 6. Liquidation Value Liquidation value is the total worth of a company's physical assets when it goes out of business or if it were to go out of business. Liquidation value is determined by assets such as real estate, fixtures, equipment and inventory. Intangible assets are not included in a company's liquidation value. Liquidation value does not include intangible assets. Intangible assets include a business's intellectual property, goodwill and brand recognition. However, if a company is sold rather than liquidated, both liquidation value and intangible assets are considered to determine the company's going concern value. Value investors look at the difference between a company's market capitalization and its going-concern value to determine whether the company's stock is currently a good buy. For an investor, the liquidation value is useful as a parameter to evaluate the risk of the investment : a higher potential liquidation value means a lower risk. For example, all other things equal, it is preferable to invest in a company that owns its equipment compared to one that leases it. If everything goes wrong and you go out of business, at least you can get some money selling the equipment, whereas nothing if you lease it. So, what is the difference between book value and liquidation value? If a startup really had to sell its assets in the case of a bankruptcy, the value it would get from the sale would likely be below its book value, due to the adverse conditions of the sales. So liquidation value < book value. Although they both account for tangible assets, the context in which those assets are valued differs. As Ben Graham points out, the liquidation value measures what the stockholders could get out of the business, while the book value measures what they have put into the business. 7. Discounted Cash Flow Discounted cash flow (DCF) is a valuation method used to estimate the value of an investment based on its future cash flows. DCF analysis finds the present value of expected future cash flows using a discount rate. A present value estimate is then used to evaluate a potential investment. If the value calculated through DCF is higher than the current cost of the investment, the opportunity should be considered. DCF is calculated as follows: I. Cash Flow (CF): It is the increase or decrease in the amount of money a business, institution, or individual has. In finance, the term is used to describe the amount of cash (currency) that is generated or consumed in a given time period. There are many types of CF, with various important uses for running a business and performing financial analysis. Types of cash flow include: · Cash from Operating Activities – Cash that is generated by a company’s core business activities – does not include cash flow from investing. This is found on the company’s Statement of Cash Flows (the first section). · Free Cash Flow to Equity (FCFE) – FCFE represents the cash that’s available after reinvestment back into the business (capital expenditures). Read more about FCFE. · Free Cash Flow to the Firm (FCFF) – This is a measure that assumes a company has no leverage (debt). It is used in financial modelling and valuation. Read more about FCFF. · Net Change in Cash – The change in the amount of cash flow from one accounting period to the next. This is found at the bottom of the Cash Flow Statement. II. Discount Rate (r): The discount rate is typically a firm’s Weighted Average Cost of Capital (WACC). Investors use WACC because it represents the required rate of return that investors expect from investing in the company. For a bond, the discount rate would be equal to the interest rate on the security. The weighted average cost of capital (WACC) is a calculation of a firm's cost of capital in which each category of capital is proportionately weighted. All sources of capital, including common stock, preferred stock, bonds, and any other long-term debt, are included in a WACC calculation. A firm’s WACC increases as the beta and rate of return on equity increase because an increase in WACC denotes a decrease in valuation and an increase in risk. 8. First Chicago Method The First Chicago Method is a situation specific business valuation approach used by venture capital and private equity investors for early stage companies. This model combines elements of market oriented and fundamental analytical methods. It is mainly used in the valuation of dynamic growth companies. Let´s go through this method step by step. I. Define different future scenarios for the Company Usually you create three scenarios for an enterprise: · Best-case · Mid-case · Worst-case First you have to set up a financial forecast (including revenues, earnings, cash flows, exit-horizon etc.) for each case. A detailed qualitative analysis of the market trends and the company are necessary in order to estimate these scenarios. In general, the mid-case scenario is the expectation of an Analyst after the Due Diligence (DD). Hence, in many businesses, which are mainly driven by the scalability factor (e.g. the market is in a “winner takes it all” situation), it is reasonable to set the worst-case equivalent to the event of total loss of the invested capital. Then again there are businesses where the market determines a natural maximum cap of the financial outcome. Still, step 1 is not easy to master and needs an extensive analytical research of the circumstances. You might even have the freedom to consider strategy-shifts in your financial forecast depending on the assumptions of each case. II. Estimate divestment price for each scenario using multiples After setting up your financial-forecast, you need to determine the Terminal Value (TV) at the time of the exit (divestment price). At this point we apply a market oriented valuation concept, Multiples. The idea is to estimate a valuation by comparing the investment to other transaction within the same peer group. Peer groups in the venture industry are characterized by: · Enterprise industry · Enterprise stage · Enterprise region There are various forms of Multiples each suitable for different asset classes. Professionals in the venture industry will use Multiples based on KPIs like EBIT, Revenues etc. The critical factor in this market oriented approach is the transaction data of the peer group. Data about Mergers & Acquisition activity in the venture industry are rare, nevertheless there are data provider on the market specializing on the venture industry. III. Determine required return and calculate valuation for each scenario Many VCs determine the required return internally. They do not trust concepts like WACC (Weighted Average Cost of Capital) and CAPM (Capital Asset Pricing Model) due to of the incompleteness of the private equity market (you can´t replicate the payoff of an investment with a portfolio of assets). However, we will give a brief introduction into WACC concept which is adjustable to the venture market. Furthermore, we will assume the absence of debt capital in the financial forecasts, which reduces the WACC to the cost of equity (not a strong assumption approaching valuation of early stage companies). IV. Estimate probabilities of scenarios and calculate weighted sum For this last step you have to allocate a probability to each scenario. This probabilities are naturally correlated to your definition of the scenarios and the number of them. Of course it is impossible to estimate precise probabilities for every scenario. The idea is take extreme outcomes into your valuation process. At the end calculate the weighted sum of the valuations depending on each scenario. Conclusion All above mentioned eight startup valuation techniques are helpful for valuation and gives the clear picture to an investor before putting their money at risk in any startup. Not all the techniques must be applied before investing in any startup as they depend on the situation of the startup (whether it is in a prototype stage, in a product stage or just an idea). The first Chicago method and Discounted Cash Flow (DCF) method gives a clear mathematical picture of the start-up’s present as well as future monetary value perspective. The Comparable Transaction method and Risk Factor Summation method gives an idea to the investor about the risk involved and how good is the start up from the other competitors in same field. References 1) https://www.investopedia.com/terms/s/startup.asp 2) https://www.angelkings.com/startup/the-berkus-method 3) https://www.angelcapitalassociation.org/blog/after-20-years-updating-the-berkus-method-of-valuation/ 4) https://berkonomics.com/?p=1214 5) https://hackernoon.com/how-angel-investors-value-pre-revenue-startups-part-iii-8271405f0774 6) https://magazine.startus.cc/berkus-risk-factor-summation-pre-money-valuation-methods-explained/ 7) https://www.finvalresearch.in/valuation-of-start-ups-the-scorecard-valuation-method.html 8) https://en.wikipedia.org/wiki/Comparable_transaction 9) https://corporatefinanceinstitute.com/resources/knowledge/valuation/precedent-transaction-analysis/ 10) https://www.canadaone.com/tools/buy_a_biz/section2e.html 11) https://www.investopedia.com/terms/l/liquidation-value.asp 12) https://www.investopedia.com/terms/w/wacc.asp 13) https://www.venionaire.com/first-chicago-method-valuation/ 14) https://businesstown.com/articles/the-book-value-approach-to-business-valuation/ 15) https://medium.com/parisoma-blog/valuation-for-startups-9-methods-explained-53771c86590e Copperpod provides Mergers and Acquisitions services. Copperpod's intellectual property audit investigates existence, ownership, and market potential for all patents, trademarks, trade secrets and other intellectual property owned by the seller. Copperpod analyzes existing hardware and software systems and processes owned by the seller to provide you a clear and detailed view of the seller's architecture, growth plans and the investment that such growth will require.

Our present generation is most defined by the advent and rise of the smartphone, which brought technology from our desktops to our hands and further to our wrists. In a fray that saw technology companies like Apple grow to be world's most valuable companies, the fight for market dominance has been fought as much in the marketplace as in patent courts - starting with Nokia attacking Apple in a series of lawsuits in 2009 and 2010. Nokia filed its first patent case against Apple, igniting the so called smartphone patent wars, on October 22, 2009 in the US District Court for Delaware. Nokia was visibly seething from the loss of its earlier prominence on the industry and as it became evident Nokia could not compete with the iPhone's rise, it looked over to its huge patent portfolio to take as big a bite from the apple as it could. In this first complaint, Nokia accused Apple of infringing on 10 patents covering essentials of the GSM, UMTS and WLAN standards. In its complaint, Nokia stated that it has not only committed billions of dollars into research and development (including helping formulate industry standards) but also has been committed to licensing its standard essential patents under Fair, Reasonable And Non Discriminatory (FRAND) terms. Nokia had declared at least some of the ten patents as being essential to the GSM, UMTS and WLAN standards - all of which were implemented in the iPhone - and was entitled to royalties from Apple, even if under FRAND terms. The questions whether the ten patents were in fact standard-essential and whether Nokia was genuinely seeking fair and reasonable royalties were hotly debated and never fully answered. As was expected, Apple responded to the first case in equal measure shortly afterward with its own patents - filing a one-up case covering 13 patents on December 11, 2009. What followed then was a series of tit-for-tat cases between Nokia and Apple - in all covering over 60 patents across 6 district cases, 2 ITC complaints and at least 3 cases in Europe, running concurrently and none betraying any sense of who had the better of the other. While Nokia and Apple battled it out in the court, however, sales continued to grow for the iPhone as well as for Android phone manufacturers such as Samsung, Motorola and HTC - and Nokia slipped further behind. Torn between its own Symbian OS and Microsoft's new Windows Phone OS, Nokia made one wrong decision after another - giving up market share to its rivals not only in the US and Europe but in the developing world as well. Sensing rightly that marketplace competition from the new Android players was far greater threat than a patent war with Nokia, Apple shifted gears as well. Having got a taste for battle from Nokia, Apple started targeting the major Android OEMs (HTC, Motorola and Samsung) with its own patent lawsuits in late 2010 and 2011 while pursuing settlement negotiations with Nokia. Nokia and Apple buried their disputes in June 2011 for an undisclosed (but presumably big) settlement including a sizable one-time payment to Nokia - and Apple could then focus on the larger fight with HTC, Motorola and the even larger fight with Samsung, the new dominant player across the globe. The fight between Apple and Samsung would rage on in multiple courts for the next 5 years - and continues even today after the recent Supreme Court ruling vacating the damages calculation by lower courts in favor of Apple - and setting new precedent for calculating damages in design infringement cases. Over the subsequent years, the smartphone patent wars drew swords from virtually every industry player - Apple, Microsoft, HTC, Motorola, Google, LG, ZTE, Ericsson, Qualcomm and Blackberry (RIM) individually as well as in cohorts like Rockstar Consortium and RPX Corporation which pumped billions of dollars in buying telecom and smartphone patents on behalf of these companies. Nokia, while relatively absent from the fray after its settlement with Apple, had not been sitting idle. It sold its dwindling phone business rather richly to Microsoft in 2015 for $7.9 billion. The overpriced acquisition is seen by industry analysts as a $10 billion mistake by Microsoft but bought Microsoft a place in the smartphone roster. Having lost its core competence, i.e. handsets, Nokia has no doubt been aching and preparing to get back into the fight. It seems to have taken two parallel approaches: First, Nokia grew its patent portfolio by over a half in a merger with another telecom powerhouse Alcatel Lucent. While staying little more than a footnote in the smartphone marketplace, Alcatel Lucent is credited with a wide number of component technologies that make smartphones a reality - as well as a sizable number of standard essential patents. Second, with its own patents, Nokia has allegedly been fighting a proxy war against Apple and Android manufacturers by transferring patent rights to multiple patent assertion entities (PAE) like Acacia Research and Conversant Property Management. These PAEs alone have sued Apple more than 12 times using former Nokia patents. Being targeted by PAEs is nothing new for Apple - but in an anti-trust complaint dated December 20, 2016, Apple finally said enough was enough. Pulling no punches, Apple accused the PAEs of "conspiring with Nokia in a scheme to diffuse and abuse [standard essential patents] and, as the PAEs and Nokia fully intended, monetize those false promises by extracting exorbitant non-FRAND royalties in way Nokia could not". Using PAEs for direct attacks against Apple was a smart, albeit sneaky, strategy for Nokia if indeed there was collusion. Since PAEs do not themselves sell any products, there would be little risk of a countersuit from Apple - as well as a general lack of commitment to FRAND licensing terms that spell lower royalties. Regardless of whether it was indeed a thought-out strategy by Nokia, the anti-trust complaint was exactly the flag Nokia had been waiting for. Over the very next couple of days, after five years of sitting on the sidelines, Nokia fired new direct shots at Apple - at least 12 new cases across the globe, covering 40 patents ranging from H.264 video encoding to RF and power management technologies used in Apple products. Regional Court, Dusseldorf, Germany - 8 patents Regional Court, Mannheim, Germany - 4 patents Regional Court, Munich, Germany - 2 patents Market Court, Helsinki, Finland - 3 patents High Court, London, UK - 3 patents Court of Turin, Italy - 4 patents Patent and Market Court, Stockholm, Sweden - 3 patents Commercial Courts, Barcelona, Spain - 1 patent District Court, The Hague, Netherlands - 3 patents High Court, Paris, France - 1 patent High Court, Hong Kong - 1 patent Tokyo District Court, Japan - 2 patents International Trade Commission, US - 8 patents US District Court for Eastern District of Texas - 18 patents The timing and range of the cases shows that Nokia was all but ready with a finger on the trigger to file the complaints that undoubtedly required months of due diligence and research. For at least some of these patents-in-suit, Nokia alleges that it has been trying to negotiate FRAND royalties with Apple - which Apple believes to be unreasonable and excessive. Apple has so far not filed a countersuit against Nokia, but has pulled all Withings (owned by Nokia) products from its stores. A fresh slew of tit-for-tat cases are no doubt on the way as well, as these things usually go. It seems unlikely that all of these different cases will reach trial and a settlement would be the most likely the endgame for both companies no matter how prolonged the battle gets. But until the two reach that elusive deal - we must remember that the human civilization is and always has been in a constant state of war with only intermittent periods of peace. This latest spat between Nokia and Apple proves that the consumer electronics industry is no exception. #nokia #apple #patents #telecom #news #electronics #licensing #software

In the current world, the design is everywhere, from our wardrobes to the websites you visit and thus, a unique design becomes an asset that needs to be protected. UI/UX (User Interface/User Experience) design is an essential part of any website and along with that, the on-screen controls you used to perform various functions on web apps, collectively make up GUI (Graphic User Interface). UI/UX is a critical part of the look and feel of any website and companies invest a lot in this as it has become an important differentiator in the marketplace and has also become a new form of intellectual property, which means that global IP protection remains fluid – and that is a major concern for companies that don’t want their designs to be copied. US Laws for Protecting UI/UX Design 1. Copyright Law Copyright automatically arises when a literary, dramatic, musical or artistic work is created. So, the original UI/UX design elements can be protected by copyright as ‘artistic works’. However, if an alleged copyright infringer makes modifications to the copyrighted design element, he/she can avoid its liability as the protection offered by copyright is limited to copying a substantial portion of the UI/UX design element. 2. Trademark Law Trademark registrations are the ideal way to protect certain easily identifiable elements of the UX that are not likely to change; for example, Instagram’s ‘Comment’ button but not the best way to protect the GUI as a whole. Further, the Trade Dress which "refers to the characteristics of the visual appearance of a product or its packaging... that signify the source of the product to consumers." can be used to protect designs that are highly recognizable and well known by people (design of a coke can). Trade dress can be difficult to obtain, and trade dress protection interacts with copyright protection in complex ways. Despite these drawbacks, trade dress may be used in some situations to supplement UI copyright, or alone if a UI element is not considered sufficiently original to be copyrighted. Trade dress, within its limitations, is also better suited to protecting the total appearance, compared to the protection of specific UI elements offered by copyright law. 3. Patent Law GUIs can be protected by way of design or utility patents. Individual patents can be written to protect the overall look and feel as well as individual design elements comprising a part of the UX. Design patents are "issued for a new, original, and ornamental design embodied in or applied to an article of manufacture." It is noteworthy that design patent protection also covers interactive UI/UX design elements, for example, "page turning" feature in Apple eBooks, is protected through U.S. design patent No. D670,713. Utility patents are "issued for the invention of a new and useful process, machine, manufacture, or composition of matter, or a new and useful improvement thereof.” According to the above mentioned pointers, it is clear that there is no single legislation to achieve complete protection for UI/UX. Instead, each IP right provides a different form of protection for the different elements of the total UX. In many ways, patents are the best tool for protecting UI/UX: Legally, patents are much better suited to protecting things that perform a function. The infringement threshold is lower. Copyright infringement requires copying, while patent infringement can be proven if a design is sufficiently similar but is not a copy. Patents do not have a fair use provision. Fair use allows limited use of copyrighted material without asking for permission; for example, if someone directly quotes some sources in an article, that's permissible under fair use, but the same practice won’t apply for patented material. Indian Laws for Protecting UI/UX Design In India, GUIs can be protected under copyright as well as design law. In Maraekat Infotech Ltd. v. Naylesh V. Kothari (2016), the Bombay High Court stated that copyright in computer programs also covers their ‘structure, sequence and organisation’, indicating that the UI/UX related to the program would also be protected. This was further corroborated by the Ministry of Electronics & Information Technology which stated, ‘Copyright protects the form of expression and can be used to protect source code and the object code of a computer programme. Furthermore, computer programmes are protected as a literary work by the Indian Copyright Act and hence, the look and feel of Graphical User Interface (GUI) can be protected under the Copyrights.’ The design protection in India is governed by the Designs Act, 2000 and the Designs Rules, 2001 as amended in 2008 to comply with the Locarno Classification system. The amendment introduced Class 14-04 dedicated to ‘Screen Displays and Icons,’ amongst others. Prior to 2009, Microsoft was granted registration over some of its designs under Class 14-99, which is the ‘Miscellaneous,’ category. However, in 2014, when Amazon sought to register a design for “graphical user interface for providing supplemental information of a digital work to a display screen” under Class 14-02 that deals with ‘Data Processing Equipment, Peripheral Apparatus & Devices’ the same was refused registration on account of not fulfilling the requirements of Section 2(a) and (d) of the Design Act about ‘article’ and ‘design’, respectively. The said section states that design protection can be obtained for a new feature of shape, configuration, pattern, etc., that is applied to an article of manufacture, through any industrial process or means. Adopting a restrictive interpretation of Section 2(a) and (d) of the Act, the Controller General of Patents, Designs and Trademarks gave the following reasons for rejecting Amazon’s application: A GUI cannot be considered as an article of manufacture under Section 2(a) of the Act, as it cannot be converted from physical input to physical output and does not have features of shape or configuration. As a GUI is not physically accessible, it cannot be sold separately as a commodity item in the market. Hence it fails to meet the provisions of Section 2(a) of the Act. A GUI is merely a function of a computer screen that is visible only when the computer turns on and thus lacks constant eye appeal as required under Section 2(d) of the Act. It does not qualify as a ‘finished article’ that is manufactured by an industrial process. This decision received a lot of criticism, concerning Amazon’s application which argued that a GUI is a part of the display device such as a computer screen, which is an article of manufacture and is sold separately. Hence, a GUI meets the requirement of Section 2(a) of the Act. Further, the GUI is applied to the computer screen with the use of a mechanical industrial process and qualifies as a ‘finished article’ as GUI is included in the article when the customer buys it and is visible once the device is switched on, thereby meeting the requirements of Section 2(d) of the act as well. After rejection of Amazon’s application, following GUIs have been registered in India under the Designs Act, 2000, such as, ‘Monitor with GUI’ registered under Class 14-02, a ‘Mobile Phone’ registered under Classes 14-03 and 14-04, and a ‘Display Screen with Graphical User Interface’ under Class 14-04. The history of GUI Design Registration in India has led to an uncertain future of GUIs. The introduction of the Draft Designs (Amendment) Rules, 2019 has provided hope by resolving the uncertainties in the field of GUIs. The Draft Rules 2019 claim to fully comply with the Locarno Classification in creating a Class 32 which shall be dedicated to “graphic Symbols, and Logos, surface patterns and ornamentation”. The latest amendment in the Draft Rules 2019 shows the intention of the legislature in making India a more GUI-friendly country. How IP Protects UI/UX Design? The range of global IP protection options is numerous, and the local oddities make the process even more frustrating. Acquiring protection for a UI/UX internationally requires a careful approach to filing across different countries with different eligibility requirements. Protecting IP is not something to take care of on your own rather it is something you should get expert help with, which is an important and smart move. Here are a few things to consider while deciding if additional help needs to be taken or not: Patents are issued for novel ideas - that's the main criterion. If you think your UI implements something no one has ever done before, you probably want to consult with an expert to assess whether it truly is unique, and to guide you through the process of protecting it under intellectual property. Those looking for venture capital funding should also investigate intellectual property protection, as investors will want some assurance that your ideas cannot be easily copied. If you are concerned that you may have infringed on a patent or copyright, an expert can advise you on what is known as freedom to operate - how similar your design can be to another company's design and/or intellectual property without risking infringement. However, if you copy someone else's design you may be at risk for copyright or patent infringement; for example, you can't download an image from Flickr and use it in a commercial product without permission. Similarly, if your user interface is substantially similar to another product (like Samsung’s designs were alleged to be substantially similar to Apple’s), you may be at risk. Again, an expert can advise you regarding freedom to operate. Generally, big companies have more to worry about and are more at risk, than alone developer who writes an app. But small- to medium-size companies do face some risk. References https://www.morningtrans.com/protecting-your-apps-gui-at-the-5-most-frequently-filed-patent-offices/ https://www.lexology.com/library/detail.aspx?g=fd26c2f9-f375-4a54-bca5-2b20abf33167 https://www.tasanet.com/Knowledge-Center/Articles/ArtMID/477/ArticleID/913419/How-to-Protect-Your-User-Interface-Intellectual-Property https://www.stephens-scown.co.uk/intellectual-property-2/protecting-your-user-interface-ui-and-user-experience-ux-designs/ https://ux.stackexchange.com/questions/23049/is-ux-copyrightable Copperpod provides portfolio analysis services that help clients to make strategic decisions such as In-licensing/Out-Licensing of patents, new R&D investments, or pruning out less critical patents. Our team provides strength parameters for each patent in a portfolio based on their technical quality, enforceability, offensive/defensive strengths & business value. Please contact us at info@copperpodip.com to know more about our services.

Table of Content: What is an OSS? BSS/OSS OSS Architecture Common OSS Products in the Market Patent Analysis OSS Future Potential and Market What is an OSS? An operations support system (OSS) is a piece of software that allows a service provider to control, analyze, manage and keep track of the services on their network. The primary goal of this technology is to increase the enterprise's operational efficiency by providing functionalities including but not limited to: Network management systems. Service delivery. Network inventory, activation, and provisioning and almost all part of the service fulfilment process. Service assurance. Customer care. OSS is critical in ensuring that consumers of communication services have a positive experience while network operators operate efficiently and profitably. Many apps are included in OSS that a service provider needs to accomplish 'back-office' tasks. The OSS ecosystem of the service provider will consist of a large number of individual OSS apps (from tens to hundreds), each responsible for a different aspect of the enterprise. BSS/OSS There must be a 'front-office' tasks if there are 'back-office' chores, and there is. These are a different group of software that support commercial, revenue, and customer relationship operations, and are more correctly referred to as Business Support Systems (BSS). When the service is turned on, the BSS applications are responsible for client-facing tasks such as appropriately recording order data, alerting the customer of charges, timeframes, and engineer visits, and initiating the billing process. The order 'flows down' from the top, through the BSS layer, OSS, and eventually to the network, where the appropriate configuration and activation modifications are implemented. Processes that are launched as a result of a network device reporting a problem are referred to as faults and these faults are directed upwards. OSS and BSS operate together to enable network operators to provide services to large numbers of users on some of the world's most complex machines, global telecommunications networks. OSS Architecture Much of the effort on OSS has been focused on defining its architecture, however it can be broken down into four core components. Processes: The wide range of events to be performed. Data: The information that has to be processed. Application : The elements that carry out data management processes. Technology: The manner in which the applications are put into action. OSS Layer: Customer satisfaction survey results are as much OSS's responsibility as a row of green lights in the network operations center. Network Engineering : The network devices are quite sophisticated, with proprietary interfaces and configuration languages frequently used. These devices may be in your firm's basement, a roadside cabinet, a customer's premises, or even virtualized in a data center. Data & Analytics: Data on the network, service, and customers must be collected, stored, and made available. This is critical infrastructure for many OSS procedures. Customer Experience: Modern service providers place a far larger emphasis on proactive customer experience improvement, with new applications developing that improve network and service quality for all consumers or focus on specific regions or even people to meet their challenges and demands. Service Fulfilment: Service Fulfillment is likely the most essential of all operational operations, accepting commands from the BSS layer and ensuring that they are deployed and enabled effectively in the network. Planning: More than any other operational duty, planning takes into account not just network capacity and capabilities, but also network cost, income potential, and dependability. Common OSS products in the market Ericson OSS : Ericsson's OSS architectural idea is guided by three main principles: service orientation, analytics and policy-driven automation, and network function virtualization and abstraction. Ericsson's OSS solutions enable digital companies across the world to fully regulate, manage, and orchestrate hybrid networks in real time, transforming traditional networks into elastic infrastructures that are lightweight, programmable, and infinitely flexible. Oracle OSS: OSS is a Kafka-compatible, secure, no-lock-in, pay-as-you-go, scalable, low-cost streaming solution that helps you to achieve the above goals with minimal effort and deployment, and you can use any Kafka API. The official confluent Kafka Java API is recommended by Oracle. Net Cracker OSS : It organizes operations in complicated hybrid systems and provides zero-touch orchestration for traditional and digital services such as SDN/NFV, cloud, IoT, and 5G. Faster service creation and delivery, increased operational agility, and lower TCO are all advantages for service providers. Large number of clients across the world have installed and used Netcracker OSS solutions to help them shift from physical to virtualized and cloud environments, embrace higher levels of Staying competitive in fast-changing marketplaces. IBM OSS : NFV is a network architectural concept that use IT virtualization to virtualize entire classes of network node functions into building blocks that form communication services. NFV specifies standards for computation, storage, and networking resources, which may be used to develop virtualized network operations. It enables CSPs and network operators to design and deploy networks based on tried-and-true software paradigms. In order to ensure agility, NFV Management and Orchestration (MANO) imposes additional expectations on OSS and BSS procedures as well as vendor solutions. HPE OSS: HPE OSS Assurance Automation enables multi-vendor hybrid telecom infrastructure to operate with zero touch. Proactive remediation is possible because to data-driven root cause investigation and automated decisions. HPE OSS adapts and supports new networks and services of any sophistication and depth as a result of the eruption of a new generation of digital services. It deals with both an increase in traffic and a drop in load at times. HPE OSS nimble at any layer (network and management functions), dependable (high availability and disaster recovery), and have a short time to productize a new network or service. Many more firms provide OSS services in a similar fashion. There has been a significant increase in the number of studies of OSS architecture in academia. Patent analysis – Total 11,816 Patents Patents by protection country The graph depicts the top nations that possess patents related to OSS. United States and China has 3,460 and 3,531 patent families in OSS technology, respectively, indicating that the technology is widely utilized in both the nations. Other nations have patents related to OSS, indicating that they use OSS in a variety of technological sectors such as digital communication, computer technology, telecommunications , and so on. Patents by Assignees (Top 10 Players) The graph depicts the top ten firms with the most patents in the field of OSS. With 1,643 patent families under its name, Ericsson has gotten its name at the top of this list, followed by Huawei. With 559 and 329 patent families, respectively, China mobile Communications and ZTE Corporations are practically on track. Technology investment trend over last 10 years According to the graph, the number of patents registered in the field of OSS increased rapidly after 2013, peaking in 2018 with over 1000 patent families submitted in a single year. OSS Future Potential and Market The market for operational support systems (OSS) has expanded and declined in the two decades since the eruption of independent software suppliers onto the scene, as communications service providers (CSPs) have attempted to optimize their procedures. Hundreds more vendors have come and gone, or have been eaten, as they innovated their way into the core of CSP operations, hoping to reproduce the magic by keeping ahead of the next technological curve. In reality, increases in operational efficiency and network performance have occasionally triggered the next curve. Both OSS and business support systems (BSS) are used in client-facing tasks including purchasing, invoicing, and customer service. When fulfilling any of these criteria is difficult, future OSS must be flexible, automated, proactive, predictive, and programmable. Components, OSS solution types, deployment style, organization size, industry vertical, and geography are all segments of the worldwide OSS & BSS market. The market is divided into solutions and services based on such components. Network planning & design, service delivery, service fulfilment, service assurance, customer & product management, billing & revenue management, network performance management, and others are the many types of OSS solutions. It is divided into small and medium-sized businesses and large businesses based on their size. It is divided into on-premise and cloud deployment models depending on the deployment methodology. IT & telecom firms, BFSI, retail, media & entertainment, government, manufacturing, and others are the different industrial verticals. REFERENCES [1] https://www.ibm.com/cloud/architecture/architectures/network-automation/ [2] https://www.hpe.com/us/en/collaterals/collateral.a00054139enw.html [3] https://en.wikipedia.org/wiki/Operations_support_system [4] https://www.oracle.com/a/ocom/docs/dc/em/tm%20forum%20fy20%20-%20oss%20report.pdf [5] https://www.alliedmarketresearch.com/OSS-BSS-software-market

Table of Contents: What is Media Streaming and Blockchain? Use of Blockchain in Media Streaming Blockchain Media Companies Patent Data Analysis of "Blockchain Technology in Media Streaming" Challenges and Issues What is Media Streaming and Blockchain? Within the last decade, multimedia, in general, and video streaming, in particular, have revolutionized the way we consume information and keep ourselves engaged. Video-streaming services are increasingly being used, thanks to recent streaming-video-on-demand services such as Netflix, YouTube, and Amazon Prime Video, which are overtaking traditional TV broadcast services in the United States. Furthermore, live-gaming video-streaming services such as Twitch and YouTube Gaming have also seen tremendous growth. Twitch alone ranks as the fourth-highest peak Internet traffic generator in the United States, with nearly one million concurrent users. Now talking about blockchain technology, it is a digital list of records, that is, blocks linked together using cryptographic algorithms. It gained a lot of attention with the introduction and high popularity of Bitcoin, a cryptocurrency based on blockchain. Its property of resistance to modification makes it a prospective and highly disruptive technology across a wide range of industries. Some of the significant advantages offered by blockchain include faster and more secure transactions, transparency, cost-effectiveness (due to the absence of middlemen), traceability, automated actions using smart contracts, and cryptographically sealed protected data, providing security and privacy. Use of Blockchain in Media Streaming Blockchain technology has the potential to assist the media streaming industry significantly. The key characteristics of blockchain's shared ledger system can assist media streaming by providing transparency, trust, efficiency, speed, security, and control for all points in a transaction process across the media supply chain. This is particularly important in the delivery, consumption, and payment of media content and in advertising. Furthermore, blockchain can aid in the prevention of ad fraud (such as clicks performed by bots rather than humans) and copyright infringement. Media streaming firms that start developing a blockchain solution today have a chance to go ahead of the competition. Blockchain technology offers a wide range of opportunities, some of which are discussed below: Empowering Creators and Artists Blockchain - Content-ownership rights are retained, and providers are free to determine the terms of use, audience, pricing, licensing, and so on. Micropayments and instant payments are based on automated smart contracts to decrease delays. Enormous third-party fees (approximately 50% for Twitch and 25% for Uber) are bypassed. The transparent system makes it impossible to lie and cheat about actual revenue, resulting in a fair and efficient process. Blockchain-based CDNs - These utilize unused storage space across multiple locations by employing decentralized networks. The last-mile problem of content delivery is alleviated. Privacy - Violations/illegal use of personal data by big corporations (such as Facebook) are prevented. While maintaining anonymity, QoE prediction models and customized solutions, such as recommendations, can be supplied. Advertisements can be targeted while ensuring that the privacy of users is not jeopardized. Piracy - This is one of the biggest challenges in the field of media streaming. Illegal copying can be tracked since the content will include ownership data that can be designed to be tamper-proof. Green Energy - Energy consumption is reduced by employing P2P decentralized networks, resulting in tremendous power savings, given that video distribution uses 80% of the Internet’s consumer bandwidth. Videos are streamed at a considerably lower energy level (for example, Flixx). Platforms can run on data centres that are underutilized or idle (in particular, VideoCoin) Blockchain Media Companies Mediachain - Using blockchain, Mediachain connects music to its creator and provides background information on the music. To provide a more transparent listening experience, the independent, decentralized music library automatically provides listeners with information about the originator, producer, and lyrics. Spotify bought Mediachain in 2017 with the intention of developing technology that more accurately identifies music to the rights holders and artists whose work is streamed on the platform. Rebel AI - Rebel AI's blockchain generates publisher identity and tracks brand media and advertising expenditures. In the future, it will also offer wallets for safe media trading. To ensure a transparent and legitimate supply chain in media contract trade, Rebel AI teamed with contract marketplace NYIAX. Fluz Fluz - On its e-commerce platform, Fluz Fluz combines blockchain and social media. While buying online, in-store, or with Fluzpay, a crypto-based pre-paid store balance card, Fluz Fluz offers cash-back options. For doing a transaction at some of the world's largest firms, such as Starbucks, Nike, Disney, and Uber, the company gives cash-back rewards. Fluz Fluz members can invite friends, exchange material, and expand their networks in order to maximize cash-back returns. Users can earn more than 8% cashback on personal and network purchases by expanding their social media networks. Steemit - Steemit is a decentralized social networking platform that rewards users for creating content and connecting with one another. The site employs STEEM tokens to encourage community socialization. The company's blockchain tracks every time a user interacts with the community or publishes content on the immutable record. Those with more STEEM tokens have more "Steem Power," which allows them to make decisions about the community and reward distributions. Since June 2018, the Steemit blockchain has tracked and paid out over $60 million to community members who have generated content and engaged with others. Furthermore, the social networking site claims to have a member base of over one million people. Civil - Civil is a journalistic community that uses blockchain technology to generate transparency and trust. Independent journalists construct newsrooms on Civil's network where they may add and share their content. The company's blockchain technology assures that every journalist owns his or her work completely, and its entire openness allows consumers to universally endorse the content's accuracy, essentially eliminating "fake news." Civil is home to a number of well-known independent and local news outlets, including Block Club Chicago, the Colorado Sun, and FAQ NYC, which all publish content on the blockchain-backed platform. Dot Blockchain Media - Dot Blockchain Media is a rights management solution for music. The blockchain maintained by the company maintains an immutable database of artist, publisher, and label rights, allowing royalty payments to be distributed equitably in real-time. Artists can use the company's blockchain technology to synchronize their songwriting and performing rights with their music on streaming sites. Dot Blockchain Media can watermark a song and give listeners access to a wealth of background information while also recording real-time streaming payments to the artist. Dot Blockchain Media has partnered with Cardstack, a platform that collects data from a variety of sources and consolidates it into one place. Both plan to use blockchain to appropriately pay musicians based on music streaming from a variety of sources. Binded - Binded is a copyrighting technology for photographers based on blockchain technology. Photographers upload their work, which is then held in a copyright vault protected by a blockchain-based unique fingerprint. Artists can share their work and track comparable photos to avoid any copyright infringements once images have been uploaded and secured. Over 350,000 photos have been recorded and safeguarded by the Binded blockchain. Furthermore, the company has made it simpler to register for Instagram photo copyright. The photo is automatically registered when a user adds the hashtag Binded to a social media post. Patent Data Analysis of "Blockchain Technology in Media Streaming" The following charts provide data about the patent families related to the use of blockchain technology in media streaming. This first graph shows the Top 14 countries with the count of patent families filed under their jurisdiction. We can see that China is leading this graph and has 3526 patent families, followed by the US and Europe with a count of 789 and 513 respectively. This can be explained by the fact that China is leading the research on Blockchain, and the Chinese central government has increasingly seen this as an opportunity, as has been the case with most emerging technologies. Since the release of the 13th five-year plan in 2016 and the first White Paper on Blockchain Technology and Application Development by the Ministry of Industry and Information Technology in the same year, the CPC has increasingly considered Blockchain as an economic, political, and geopolitical asset for the country if 'guided' well. This next graph shows the count of patent families filed in the last ten years. We can see that the growth has been exponential after the year 2015 owing to how the research in the field of blockchain in media streaming has significantly increased. In general, the interest in Blockchain technology has been increasing since the idea was coined in 2008. The reason for the interest in Blockchain is its central attributes that provide security, anonymity, and data integrity without any third-party organization in control of the transactions, and therefore it creates interesting research areas, especially from the perspective of technical challenges and limitations. The graph also shows the forecast of how the number of patent families being filed will only increase with time. Challenges and Issues Design of a scalable video-streaming platform based on blockchain: In general, video streaming involves a large number of sessions, resulting in many transactions throughout a single stream. This may result in an unusually large number of transactions, resulting in long delays and/or high computational complexity. As a result, a development platform is critical for implementing innovative strategies in a custom blockchain platform/model for video streaming in order to overcome the current challenges of longer transaction times and limited computing power. For instance, current efforts in this direction, from Play2Live, which used the Graphene platform (third-generation software with cryptographic abilities capable of performing 50,000 transactions per second), can be further explored. Payments and revenue-sharing model: An exciting and much-needed research challenge is the design of revenue models that are fair and maximize the benefits for all involved stakeholders, in particular, content producers, publishers, aggregators, technology providers, advertisers, and legal-service providers. Due to the presence of such intermediaries, artist contracts and payments are currently severely limited. Artists and creators can get their proper shares and keep control of their content by using blockchain and smart contracts to construct an automated payment system. Along with the revenue model, the design of proper SLAs and ELAs is required to assign tasks and responsibilities to each stakeholder. Protection of content owners’ rights: A thorough investigation is required to develop specific provisions and features to help track ownership and prevent illegal copying and distribution of content. Smart contracts with licensing and ownership-related elements will need to be developed for each application. These could help address DRM issues, which remain an enormous challenge for the media industry. Lack of standards and regulation: Currently, one of the most significant disadvantages of blockchain technology is uncertainty about the legal status of its applications, such as cryptocurrency, betting, and gambling. We need an international blockchain-based video-streaming standardization group comprised of both technical and legal experts from industry, academia, and regulators for the technology to evolve and be recognized by various public and private institutions. There is a need to develop video-streaming-related smart contract standards similar to the Ethereum Request for Comments-20 Ethereum Smart Contract. Other standards, such as the Interledger Protocol, are also needed to preserve interoperability between legacy and newly built blockchain-based video-streaming networks. Integration and interoperability: Integration and interoperability: To make sure of interoperability with legacy systems, more research toward the development of standard protocols and terminology is required. New network technologies are also being launched, such as fog computing, MEC, software-defined networking, and network functions virtualization. As a result, the designed solution should be compatible with emerging technologies and protocols. It is necessary to identify various influencing factors, such as QoE monitoring and control models, among others, that are designed for such applications. Furthermore, identifying such factors is required for successfully enforcing SLAs and ELAs between various stakeholders. References https://scihub.se/https://www.researchgate.net/publication/340717789_Blockchain_for_Video_Streaming_Opportunities_Challenges_and_Open_Issues https://www.ibm.com/thought-leadership/institute-business-value/report/blockchain-me https://medium.com/paradigm-fund/video-streaming-and-blockchain-a-tale-of-two-paradigm-shifts-867664c899a0 https://builtin.com/blockchain/media-social-media-entertainment-uses https://www.forbes.com/sites/seansteinsmith/2020/06/03/how-blockchain-and-crypto-can-supercharge-the-streaming-economy/?sh=5d4a1fb63a6b https://www.ibm.com/thought-leadership/institute-business-value/report/blockchain-me

In computing, source code is any collection of code, written using a human-readable programming language, usually as plain text. The source code of a program is written to facilitate the work of computer programmers, who specify the actions to be performed by a computer by writing the source code. Now just like any other intellectual property asset a company may own, source code is also a critical part of an organization’s IP which needs to be protected as when source code gets leaked, stolen, or left exposed, it becomes detrimental to the organization. How Can Source Code Be Protected Legally? The use of copyright, patents, trade secrets and other legal methods to protect important intellectual property (IP) is fundamental. They form the framework for the protection of a software source code. Legal structures of protection are important to build a strong deterrence to source code theft. These factors are especially important when considering insider threats. But these frameworks also act as vital evidence if the worst happens, and can lead to a court dispute over source code ownership. In copyright legislation around the world, the source code is considered as the intellectual property of the creator. Source code is protected in the same way as a “literary work”, which means it is copyrightable from the moment that the first line of code is created. However, if you want to enforce a copyright against someone making an unauthorized copy, you must obtain a certificate of registration of a copyrightable work from the United States Copyright Office. But copyrighting your work can prove to be problematic for a variety of reasons. For a start, you may have to publish details of your work in copyright documentation, which can give competitors an edge. This is why software and tech companies generally use patents to protect their initial idea and trade secret law to protect the sensitive aspects of it. In contrast to copyright that protects the expression of the idea, a patent protects the idea itself. Specifically, an innovator may protect inventions in software, such as the algorithms performed by the software or the architecture of the software. A lot of big companies use patent law to protect themselves not just for products they have acted in development or available on the market, but for things that they may create in the future. Now coming to trade secrets, trade secret law is a specific part of intellectual property legislation that protects vital proprietary information against unauthorized use by other parties. Companies obviously cannot register their trade secrets with government agencies, like they would for copyrights, patents, and trademarks. The only way to ensure that a trade secret remains a secret is to keep the information strictly confidential. Copyright Law Against Source Code Copying US Copyright Law Copyright protection attaches to “original works of authorship fixed in any tangible medium of expression, now known or later developed, from which they can be perceived, reproduced, or otherwise communicated, either directly or with the aid of a machine or device.” (17 U.S.C.A. § 102). Copyright functions by granting the author the right to exclude others. In the United States, computer programs are literary works, under the definition of the Copyright Act, 17 U.S.C. § 101. Copyright attaches only to original works. A work is “created” when it is fixed in a “tangible medium of expression” for the first time. 17 U.S.C. § 101. Circuits differ on what it means for a work to be fixed for copyright law and infringement analysis. India Copyright Law In India, the software can be protected under the Copyright Act, 1957 or the Patents Act, 1970, and a touch of ingenuity, too, is required to protect it correctly. It can be protected under the Patent Act only if it has a technical effect. Otherwise, it can be protected only under the Copyright Act, 1957. Section 2 (o) of the Copyright Act defines "literary work" and includes computer programs, tables, and compilations including computer databases. Thus, it is explicitly protected. Europe Copyright Law The European Union Computer Programs Directive controls the legal protection of computer programs under the copyright law of the European Union. It was issued under the internal market provisions of the Treaty of Rome. The most recent version is Directive 2009/24/EC. The first EU Directive on the legal protection of computer programs was Council Directive 91/250/EEC of 14 May 1991. It required (Art. 1) that computer programs and any associated design material be protected under copyright as literary works within the sense of the Berne Convention for the Protection of Literary and Artistic Works. China Copyright Law Copyright law is mainly governed by the Copyright Law of the People's Republic of China (PRC). Before the PRC acceded to the Berne Convention, computer software was not treated as a kind of literary work under the Copyright Law. In May 1991, the State Council passed the Computer Software Protection Rules. Based upon these rules, the Measures for Computer Software Copyright Registration were formulated by the then Ministry of Engineering Electronics Industries. These regulations provide a set of rules covering the definitions of various terms and the registration, examination, and approval of computer software programs in the PRC. At the moment both the Berne Convention and these two domestic computer regulations are co-effective. However, in the event of any inconsistencies, the Berne Convention prevails. Oracle v. Google Oracle America, Inc. v. Google LLC was a legal case within the United States related to the nature of computer code and copyright law. The dispute centered on the use of parts of Java’s application programming interfaces (APIs), which are owned by Oracle (through a subsidiary, Oracle America, Inc., originating from Sun Microsystems), within early versions of the Android operating system by Google. Google copied roughly 11,500 lines of code from a Java program. Google has admitted to using the APIs, and has since transitioned Android to a copyright-unburdened engine, but argued their original use of the APIs was within fair use. Oracle initiated the suit arguing that the APIs were copyrightable, seeking US$8.8 billion in damages from Google's sales and licensing of the earlier infringing versions of Android. While two District Court-level jury trials were found in favor of Google, the Federal Circuit court reversed both decisions, asserting APIs are copyrightable and Google's use does not fall under fair use. Google successfully petitioned the Supreme Court to hear the case in the 2019 term, focusing on the copyrightability of APIs and subsequent fair use; the case was delayed to the 2020 term due to the COVID-19 pandemic. In 2021, the Supreme Court ruled in a 6–2 decision that Google's use of the Java APIs fell within the four factors of fair use, bypassing the question on the copyrightability of the APIs. The decision reversed the Federal Circuit ruling and remanded the case for further review. Case Timeline On August 13, 2010, Oracle sued Google for copyright and patent infringement in the District Court for the Northern District of California. On April 16, 2012, the copyright phase started and consisted of several distinct claims of infringement: a nine-line range check function, several test files, the structure, sequence, and organization (SSO) of the Java (API), and the API documentation. On May 7, 2012, after two weeks of testimony, the jury found that Google had infringed on the copyright related to the code, SSO, and documentation of the APIs as well as the range check function, but was deadlocked on whether these uses fell within fair use. On May 7, 2012, the patent phase began, with the same jury. By the time of trial, Oracle's patent case comprised claims from two patents, 6,061,520 (Method and system for performing static initialization), and RE38104 (Method and apparatus for resolving data references in generated code). On May 23, 2012, the jury found non-infringement on all patent claims. On December 4, 2013, shortly following the conclusion of the District Court case, both parties attempted to file additional JMOLs on elements of the ruling which Alsup dismissed, leading to Oracle appealing the decision and Google filing a cross-appeal on the literal copying claim. Because the case involved claims related to patents, the appeal was automatically assigned to the United States Court of Appeals for the Federal Circuit. The judgment was released on May 9, 2014. In October 2014, Google petitioned the U.S. Supreme Court to hear the case; this request was denied in June 2015. On May 9, 2016, as ordered by the Appeals Court, a new district court trial began on the question of whether Google's actions were fair use given the prior ruling that the APIs were copyrightable. On May 26, 2016, the jury found that Android does not infringe Oracle-owned copyrights because its re-implementation of 37 Java APIs was protected by fair use. On October 26, 2016, Oracle officially filed its appeal. In 2017, Oracle's appeal was heard by the United States Court of Appeals for the Federal Circuit. On March 27, 2018, the Court ruled in favor of Oracle. In January 2019, Google filed a petition for writ of certiorari with the Supreme Court of the United States to challenge the two rulings that were made by the appeals court in Oracle's favor. In April 2019, the Court asked the Solicitor General of the United States to file an amicus brief to outline the government's stance on the case. On November 15, 2019, the Supreme Court granted certiorari and was expected to hear the case on March 24, 2020. However, the Supreme Court postponed its March argument session on March 16 in light of concerns surrounding COVID-19. On October 7, 2020, oral arguments were heard via teleconference due to the ongoing COVID-19 pandemic. On April 5, 2021, the Court issued its decision. In a 6–2 majority, the Court ruled that Google's use of the Java APIs was within the bounds of fair use, reversing the Federal Circuit Appeals Court ruling and remanding the case for further hearing. Key Takeaways The case has been of significant interest within the technology and software industries, as numerous computer applications and software libraries, particularly in open source, are developed by recreating the functionality of APIs from commercial or competing products to aid programmers in interoperability between different systems or platforms. But it should be noted that copying of source code or any such material should constitute a permissible “fair use” of that material because source code is an important part of a company’s IP and if big companies unfairly use the source code of small companies then that will be detrimental to the growth of small companies and also going for litigation against big companies is something small companies cannot afford. References https://en.wikipedia.org/wiki/Source_code https://www.supremecourt.gov/opinions/20pdf/18-956_d18f.pdf https://www.stop-source-code-theft.com/is-source-code-intellectual-property/ https://cycode.com/blog/why-is-source-code-so-hard-to-protect/ https://en.wikipedia.org/wiki/Computer_Programs_Directive https://en.wikipedia.org/wiki/Intellectual_property_in_China https://en.wikipedia.org/wiki/Software_copyright Copperpod provides IP consulting services such as Source Code Review, Infringement Claim Charts, Prior Art Search, Reverse Engineering and advises clients on patentability to give a clear picture of the state of the art to navigate away from the potential prior art and monetize IP assets.

What is Double Patenting? Double Patenting is the granting of two patents for the same invention, to the same patent owner. A continuing patent application is a patent application that follows and claims priority to an earlier-filed patent application. In the US, there is a prohibition in patent law against allowing an invention to be claimed twice. There are generally two types of double patenting rejections: 1. One is the “statutory-type” double patenting rejection based on 35 U.S.C. 101 which states in the singular that an inventor "may obtain a patent." In other words, for an invention, one can have one patent , not two. Statutory Double Patenting rejections are often issued by the USPTO when a claim in a continuation, divisional or continuation-in-part application is identical in scope to a claim that was also made in the parent application. 2. The second is the “nonstatutory-type” double patenting rejection based on a judicially created doctrine grounded in public policy and which is primarily intended to prevent prolongation of the patent term by prohibiting claims in a second patent not patentably distinct from claims in a first patent. The doctrine of nonstatutory double patenting also seeks to prevent the possibility of multiple suits against an accused infringer by different assignees of patents claiming patentably indistinct variations of the same invention. Nonstatutory double patenting includes rejections based on anticipation, a one-way determination of "obviousness," or a two-way determination of "obviousness." How Can an Applicant Overcome Double Patenting? To overcome a statutory double patenting rejection : In general, if the claims are actually the same, one would need to either cancel or modify them. However, even if there’s just a one-word difference, that could be enough. The general test is - can a person think of a way to infringe one of the claims but not the other? If so, they’re not actually identical. To overcome a non-statutory double patenting rejection : Compared with the statutory version, there are more options to consider with this type of rejection. 1. Holding the rejection in abeyance - When an applicant holds a non-statutory double patenting in abeyance, essentially the Applicant is telling the examiner that prosecution is open on the applicant and there is a strong chance that the claims will be amended in the future, so there is no need to discuss this matter now. Thus, the rejection will be held in “abeyance” to be dealt with at a later time, if necessary. If a double patenting rejection is held in abeyance, it is important to address this before the application is granted. If not the granted patent may be held invalid if litigated. The second way to overcome a double patenting rejection is to file a terminal disclaimer. 2. Filing a terminal disclaimer - In general, there are two reasons why the non-statutory double patenting rejection exists. The Patent Office does not allow an applicant to obtain a length-of-term benefit from having claims on the same subject matter in two different patents. Accordingly, the applicant is required to forego (i.e., “disclaim”) any potential period of time where the new patent would outlast the earlier one. The Patent Office also does not allow two different entities to be able to enforce the same patent rights. Accordingly, both of the patents are required to remain under the same ownership. Based on that, applicants usually file for a Terminal Disclaimer. It says that (a) the second patent won’t be allowed to extend its coverage for a longer time than the first one, and (b) the new patent won’t be enforceable if it’s not under the same proprietor as the first one. 3. Amending the claims - If a person doesn’t wish to proceed with the Terminal Disclaimer, then there is another way to overcome a non-statutory double patenting rejection which is by amending the claims that were rejected to include additional limitations that wouldn’t be considered obvious. However, the Federal Circuit’s decisions in Gilead Sciences, Inc. v. Natco Pharma Ltd. , 753 F.3d 1208 (Fed. Cir. 2014), and Abbvie v. Mathilda & Terence Kennedy Institute , 764 F. 3d 1366 (Fed. Cir. 2014), have reaffirmed the ODP (Obviousness-type double patenting) doctrine. Can Inventors Intentionally Cause Double Patenting Rejection in Order to Broaden Their Patent Portfolio? The answer to this would be yes, this can indeed be used as an opportunity to broaden a patent portfolio. An applicant can file for a continuation patent application claiming an invention similar to the one claimed in the first patent. In the case the applicant gets rejection, and it is a non-statutory double patenting rejection, then the applicant can file for a terminal disclaimer which will allow him to have one more patent for an invention similar to the one claimed in the first patent. Now, if a manufacturer makes, uses, sells and/or offers for sale a product that uses patented technology and infringes on the first patent, then it may also infringe on the second patent. This way patent infringement damages are increased per patent, as the product infringes multiple patents. Hence, this increases the strength of the patent portfolio. References https://www.uspto.gov/web/offices/pac/mpep/s804.html#:~:text=A%20nonstatutory%20double%20patenting%20rejection,been%20obvious%20over%2C%20the%20reference https://www.uspto.gov/web/offices/pac/mpep/s804.html#:~:text=101 )%20double%20patenting%20rejection%20can,101. http://piersonpatentlaw.com/what-is-a-terminal-disclaimer-in-patent-law-double-patenting/ https://kolitchromano.com/whats-a-double-patenting-rejection/ https://arapackelaw.com/patents/u-s-patent-law-what-is-a-double-patenting-rejection/ Uday is a research analyst at Copperpod. He has a Bachelor's degree in Electronics and Communication Engineering. His interest areas are Microcontrollers, IoT, Semiconductors , and Memory Devices. Copperpod provides Portfolio Analysis to identify high value patents in a given portfolio and their licensing opportunities. Copperpod's IP monetization team helps clients mine patent portfolios for the best patents in a given portfolio. Our portfolio analysis is built upon a deeply researched algorithm based on 40+ parameters - and ranks each patent according to a highly customized PodRank . Please contact us at info@copperpodip.com to know more about our Portfolio Analysis services.

The exponential growth of coronavirus across the globe has impacted virtually every facet of life. The stock markets have tanked, international events are postponed, sports seasons have been cancelled outright, entire countries have been put on lockdown, states of emergency have been declared, and people are waging wars over essential groceries in supermarkets. To stop the rapid spread, the governments are advising their citizens to stay at home and practice ‘social distancing’ in order to prevent person-to-person contagion. This has forced every individual to work from home and keep their businesses running. We, at Copperpod, are no exception with all our experts working from their dens. The concept of working from home was never pondered and discussed in such depths until now. Top tech companies such as Microsoft, Google, etc. are forced to build systems and processes in terms of IT infrastructure and HR policies in order to efficiently implement ‘work from home’ for their workforce. For smaller firms, particularly law firms and individual attorneys, working from home is a challenge owing to confidentiality of important documents, frequent travels, meetings and constant legal engagements. At Copperpod, we realised that our clients need the right tools/services to achieve their targets while working from home, especially in the below mentioned 5 categories. I. Collaborative Coordination Tools: The tools that allow multiple users to communicate with each other while working in a common document. Primarily, these are file storage services (storing files on cloud) which provide access to multiple users such that they can edit in a file simultaneously. For instance, a New York based patent attorney has a patent portfolio in which the patents are to be studied and analysed. So, he uploads a spreadsheet onto a file hosting service and shares a secure link to us, Copperpod for performing the analysis. Our experts open the link and edit the spreadsheet by adding our analysis. Meanwhile, the attorney can access the file in real time and see our analysis in the same spreadsheet. He can also discuss with us then and there, if need be. That saves time, money and storage space while everyone is working from home. Gone are the days when the attorneys used to keep multiple versions of each document locally in their systems and there were numerous emails with attachments. Specially, when attorneys are creating a lot of documents, they need efficient tools for managing them. For attorneys, it is of prime importance that the files be secure and confidential. Below is a list of tools/services which provide multiple users to collaborate on a document in real time: ● Tresorit (with end-to-end encryption) ● pCloud (with end-to-end encryption) ● IceDrive (with client-side encryption) ● Google Drive/Google Docs ● Microsoft OneDrive ● Dropbox (integrates with Microsoft Office Online for editing documents) ● Box ● Amazon WorkDocs ● Zoho Writer ● Citrix ShareFile ● FileCloud ● Collabora Online ● Egnyte At times, attorneys may need just a secure storage from where they can just share a document that Few tools/services provide a secure storage and do not provide the feature of multiple users editing a file simultaneously: ● Sync.com (with end-to-end encryption) ● PreVeil Drive (with end-to-end encryption) ● SpiderOak (with end-to-end encryption) ● LexWorkplace II. Content Protection: The tools and services that make the data secure by adding layers of encryption. For attorneys, this is the most important aspect of their business as a document leakage may lead to huge repercussions. Using one of these services on top of cloud storage is highly recommended. ● Accellion ● Boxcryptor ● Sookasa (end-to-end encryption for Google Drive and Dropbox) ● CloudMask (end-to-end encryption for Google Drive) ● Virtru (end-to-end encryption for Google Drive) III. Telepresence and Conference Calls: A service implementing video conferencing creating a virtual conference environment for multiple participants. It helps attorneys conduct meetings with anyone from any location. For instance, a Delaware based patent attorney may want to privately discuss an invention and possible monetization potential with a group of inventors settled in Seattle. This is where a telepresence solution would take charge to create a virtual environment where the three parties can meet and discuss just like in a real conference. Below is a list of prominent telepresence services that provide best experience for attorneys: ● Avaya Scopia ● Cisco Telepresence Systems ● Polycom RealPresence Immersive Studio ● Huawei TP Telepresence ● Highfive ● LifeSize ● VidyoConnect While the above are solutions (including hardware and software), following are standalone apps for video conferences/meetings which can be used on a personal mobile phone or desktop: ● Cisco Webex ● Google Hangouts Meet ● Microsoft Teams ● Zoom ● GoToMeeting ● RingCentral Meetings ● TeamViewer ● Zoho ● LiveStorm Meet IV. To-Do Lists/Project Planners: Tools that help in managing tasks, setting reminders and schedules. This section includes the tools where multiple users can log in and work as a team. For instance, an attorney working from home may need to track his tasks and meeting schedules over the next month. He would need his team to work on some of his tasks, such that they can view the tasks in real time and act upon them. Here he needs efficient project planners for his projects to start, execute and complete on time. Additionally, the attorneys can chat with the team, hold discussions and share documents as well. Following are the services/tools that provide an interface for attorney to log/track his schedule and set reminders to avoid missing crucial deadlines: ● Proofhub ● Zoho Projects ● Airtable ● nTask ● Quire ● Hansoft ● Asana ● Podio V. Timekeepers: Tools that measure time spent on work. Attorneys can use such tools to track and manage work hours of themselves as well as their assistants/paralegals. For instance, an attorney working from home may need to track the working hours of paralegals and sales teams to keep his business on track and achieve his targets. This is where he needs timekeepers to virtually see his team at work. Following are a few easy-to-use apps which an attorney can use on his smartphone: ● Toggl ● Clockify ● ActiTime ● BeeBole ● eBility ● Everhour ● Hyperlogs ● MinuteDock ● Jibble ● DeskTime We’ve covered the essential products and services that an attorney can use while working at home such that he can perform all the activities smoothly that he would do otherwise. Infact, we strongly believe that the above tools can help an attorney save more time and money than he would if not working from home. Note: Copperpod conducts deep technical analysis and helps attorneys substantiate infringement arguments with detailed evidence of use reports, claim charts and other licensing/litigation artifacts - while reducing overall cost of enforcement. Contact us to know more about our services, expertise and how we can help you to manage, monetize and protect your intellectual property. #workfromhome #productivity #coronavirus #pandemic

US patent law gives a patent owner the right to exclude others from making, utilizing, offering to sell, selling, or importing into the US the patented invention for a limited timeframe. A patent owner may bring a patent infringement claim against an alleged infringer in a US Federal District Court or, if the case includes the importation of allegedly infringing products, before the US International Trade Commission (ITC). In the event that a patent is found to be substantial, enforceable, and infringed in a district court action, the patent owner is entitled to financial damages of not less than a reasonable royalty and in limited circumstances, can even acquire an injunction preventing further infringement. Popular venues for patent disputes include the District of Delaware, the Eastern District of Texas, and the Northern District of California. Many districts that regularly hear patent cases have their own set of local rules for such cases. Some districts are known for the rapid pace at which they proceed to trial, while others tend to move at a slower pace. Therefore one of the most important decisions plaintiffs take, early on in their enforcement campaign, therefore is to select the appropriate venue for filing the case. The identification of the appropriate venue for starting a patent infringement or declaratory judgment action was traditionally rather straightforward. 28 U.S.C. § 1391 permitted plaintiffs to select any judicial district where the defendant conducted business, including sale of accused products, for filing a patent infringement case. The plaintiff could also file a patent infringement case in the judicial district where the defendant is resident. In TC Heartland LLC v. Kraft Foods Group Brands LLC, Case No. 16-341 (May. 22, 2017), however, the U.S. Supreme Court substantially constrained a patent owner’s choice of venue for patent infringement suits by adopting a more narrow interpretation of where a defendant “resides”. A patent owner’s choice of venue is now limited to only those judicial districts in which either (1) the defendant is incorporated or (2) the defendant has a regular and established place of business and has committed acts of infringement. 28 U.S.C. § 1400(b). The TC Heartland decision affected Non Practicing Entities (NPEs) most particularly, who had overwhelmingly preferred Eastern District Time (EDT) as their venue of choice. Years of intense patent litigation in Texas has encouraged a dense concentration of very skilled patent litigators in Texas, particularly in Dallas and Austin. These skills are difficult to build, discover and procure, hence Texas remains a popular destination for patent attorneys and for patent owners to hire outside counsel. The TC Heartland decision has also affected enforcement targeting multiple defendants. Previously, plaintiffs could effortlessly file lawsuits against multiple defendants in a single district by meeting the general venue provisions and exhibiting that every one of the defendants committed an infringing activity in the state. However, that has become difficult under the now-limited view on what “substantial business presence” entails. Plaintiffs often are not able to find one common venue for all the alleged infringers. Pursuing concurrent lawsuits in different districts requires additional time and resources, and discourages enforcement campaigns to simultaneously target multiple defendants at the same time. In re Google (2019-126) , the US Federal Court of Appeals found that a “regular and established place of business” requires the regular, physical presence of an employee or other agent of the defendant conducting the defendant’s business at the alleged “place of business.” In effect, therefore, presence of a third-party contractor or even physical servers and machines owned by a defendant may not be sufficient grounds for establishing venue at a particular district, if the defendant otherwise does not maintain a full-time staff. Patent Litigation In US Federal Courts & The ITC U.S. District Courts US federal district courts have exclusive jurisdiction over patent infringement claims. Popular districts for patent disputes include the District of Delaware, the Eastern District of Texas, and the Northern District of California. Many districts that regularly hear patent cases have special rules for patent cases. Some districts are known for the rapid pace at which they proceed to trial, while others tend to move at a slower pace. Patent cases usually last between two and four years. Top 5 Courts By Filings - 2020 A total of 3,857 district court cases were filed in 2020. As the data shows, 2,484 cases are filed in the top 5 district courts i.e. 64% of cases are filed in these courts, whereas 1,582 cases out of 2,484 cases are filed in WDT and DD making them the most preferred venue for patent litigation. ITC 337 Patent Investigations A patent owner may also seek to enforce its rights by initiating a patent investigation with the ITC under Section 337 of the Tariff Act of 1930 (19 U.S.C. § 1337). 19 U.S.C. § 1337 The importation into the United States, the sale for importation, or the sale within the United States after importation by the owner, importer, or consignee, of articles that— (i) infringe a valid and enforceable United States patent or a valid and enforceable United States copyright registered under title 17; or (ii) are made, produced, processed, or mined under, or by means of, a process covered by the claims of a valid and enforceable United States patent. ITC proceedings are presided over by Administrative Law Judges (ALJs). Discovery and the claim construction process occur similarly to district court litigation but on a compressed time frame. ITC proceedings tend to move more quickly than district court litigation. A trial-like evidentiary hearing is typically held within eight to ten months after filing, and a final decision typically issued within fifteen to eighteen months. ALJs have the power to issue exclusion orders that direct the US Customs and Border Protection to stop infringing imports at the border. There are two types of exclusion orders: limited exclusion orders (LEOs) are limited to the infringing products of the named respondents in the action, while general exclusion orders (GEOs) are broader and exclude all infringing products. How To Select The Appropriate Jurisdiction? Before filing a suit, one of the most important decisions a plaintiff will make is where to file. While certain venues tend to be more plaintiff friendly, such as the Eastern and Western districts of Texas, other venues may favor defendants, such as the Northern District of California. Federal Courts: The subject-matter jurisdiction of a court refers to the kinds of cases that it may hear. The subject-matter jurisdiction of the Federal courts is limited by Article III of the Constitution. Unlike state courts, which are usually courts of general jurisdiction (they can hear most kinds of cases) federal courts may only hear cases that are listed in Article III as within “the judicial power of the United States.” The framers included only such cases in which it was felt that there was a special need for a federal, as opposed to a state, court. Perhaps the most important grant of jurisdiction today is over cases “arising under the Constitution and laws of the United States” (often called “federal question” jurisdiction). This gives federal courts the power to interpret and enforce the United States Constitution and all laws passed by Congress. This guarantees that all citizens will enjoy the same constitutional rights as citizens in other states. Many cases brought to enforce constitutional and civil rights have been brought in the federal courts, because the parties believe that a federal judge will be more likely to issue an unpopular opinion than would a state judge who will have to run for reelection. Another, more controversial grant of jurisdiction to the federal courts is known as “diversity jurisdiction.” This applies to controversies between citizens of different states and controversies between citizens of the United States and citizens of a foreign country. The main purpose of this grant of jurisdiction is to prevent bias against an out-of-state party in favor of an in-state party. The fact that federal judges are appointed by the president and are not subject to reelection is thought to minimize the possibility of local bias. There is some question, however, about the extent of such bias, and therefore the need to have federal judges decide these cases. Most grants of jurisdiction to the federal courts, including federal questions and diversity, are concurrent, rather than exclusive. This means that the plaintiffs may bring such cases in either a federal or state court. It may happen, therefore, that a case raising a constitutional claim or based on a federal statute may end up in state court. Just as a federal judge may have to apply state law in a variety of cases, a state judge may have to apply federal law. All judges, therefore, must be familiar with both federal and state law. In concurrent jurisdiction cases, the plaintiff has the original choice of whether to bring the case in federal or state court. If the plaintiff properly brings the case in federal court, then the defendant may not transfer it to state court. If, however, the plaintiff chooses to bring a case over which both the state and federal courts have concurrent jurisdiction in a state court, the defendant may have the case transferred, or “removed” to federal court. If neither party wants it heard in federal court, then it remains in state court. With few exceptions, once a case starts in either state or federal court, the case remains in that court system throughout, including on appeal. Cases in federal court may be appealed first to the federal Court of Appeals for that particular circuit, and then by writ of certiorari to the United States Supreme Court. Cases heard in a state court must be appealed through the state court system (usually to an intermediate appellate court and then to the state supreme court). Only if a case in state court contains a significant issue of federal law may it be appealed to the United States Supreme Court after being heard by the state supreme court. Precedent And Stare Decisis When issuing decisions, all courts should follow binding precedent - that is, their decisions should follow any decisions made by courts above them. On inquiries of the interpretation of the United States Constitution and resolutions passed by Congress, the United States Supreme Court has the last say. Any other courts, both federal and state, should follow any precedent set by the Supreme Court. All United States District Courts should follow the interpretation given by the Court of Appeal for the circuit in which it sits. In some cases, various circuits arrive at conflicting outcomes on a specific issue. This implies that the Constitution may at times be deciphered contrastingly in various states. Frequently, a particular "split in the circuits" prompts the Supreme Court to grant certiorari on the issue involved, so the law will be uniform all through the country. State courts will undoubtedly follow the precedent set by the Supreme Court and by the Courts of Appeals on issues of federal law. Each state high court is allowed to decipher the laws of its state as it sees fit, as long as the interpretation doesn't violate the United States Constitution. All lower courts in the state should follow state supreme court precedent on issues of state law, and federal courts in the state should do likewise. The doctrine of stare decisis is somewhat different from that of precedent. Stare decisis is the desire of most courts to follow their own precedent, even when they are not required to. For example, once the Supreme Court has decided on an issue of federal law, they are free to change their mind in some later cases. But they are normally quite reluctant to do so, even if there has been a change of justices on the Court and the new members do not agree with the old ruling. They are much more likely to distinguish the older case when asked to apply it in a slightly different situation. In this way, the older doctrine may change, but more gradually, over time. Statutes and Case Laws 28 U.S.C. § 1391 (b) Venue in General - a civil action may be brought in : (1) a judicial district in which any defendant resides, if all defendants are residents of the State in which the district is located; (2) a judicial district in which a substantial part of the events or omissions giving rise to the claim occurred, or a substantial part of property that is the subject of the action is situated; or (3) if there is no district in which an action may otherwise be brought as provided in this section, any judicial district in which any defendant is subject to the court’s personal jurisdiction with respect to such action. (c) Residency - For all venue purposes— (1) a natural person, including an alien lawfully admitted for permanent residence in the United States, shall be deemed to reside in the judicial district in which that person is domiciled; (2) an entity with the capacity to sue and be sued in its common name under applicable law, whether incorporated, shall be deemed to reside, if a defendant, in any judicial district in which such defendant is subject to the court’s personal jurisdiction with respect to the civil action in question and, if a plaintiff, only in the judicial district in which it maintains its principal place of business; and (3) a defendant not resident in the United States may be sued in any judicial district, and the joiner of such a defendant shall be disregarded in determining where the action may be brought with respect to other defendants. Even though most studies have concluded that statistically, EDT juries are at least as much (if not more) likely to deliver a verdict for the defendants as the national average (see http://mcsmith.blogs.com/eastern_district_of_texas/), the disparity in filing statistics results from plaintiff-friendly local rules and procedures in the EDT courts that put more pressure on defendants to settle and therefore allows quick recovery of damages for the plaintiffs. 28 U.S. Code § 1400 (b) Any civil action for patent infringement may be brought in the judicial district where the defendant resides, or where the defendant has committed acts of infringement and has a regular and established place of business. TC Heartland LLC v. Kraft Foods Group Brands LLC The status quo was finally challenged in May 2017, when the United States Supreme Court ruled concerning the venues in patent infringement lawsuits in TC Heartland LLC v. Kraft Foods Group Brands LLC. TC Heartland LLC, coordinated and headquartered in Indiana, was sued by Kraft Foods for allegedly transporting infringing items into Delaware. Depending on the Federal Circuit's broadened meaning of "resides," Kraft Foods brought suit in the District of Delaware, guaranteeing that TC Heartland's transportation of products into Delaware brought "the least contacts" with the state and gave the court personal jurisdiction of the defendant. TC Heartland moved to transfer the venue to Indiana, however, the district court denied the shipping, finding the venue legitimate under Section 1391(c). After the Federal Circuit denied TC Heartland's appeal for mandamus, the Supreme Court consented to decide the issue. In hearing the TC Heartland issue, the Court decided if the importance of "resides" in the patent venue rule was broadened by Congress years prior when amendments were made to the overall venue rule. The Court took a firm stance in support of its 1957 decision, where it "completely and unambiguously" held that "resides" is restricted to only to the state wherein an organization has been organized under Section 1400(b). To explain the impact of Congress' Section 1391(c) amendment, the Court expressed that there was no sign that Congress expected changes to Section 1931(c) to have any impact on Section 1400(b). Therefore, the venue is legitimate in patent infringement suits in the states where a business is organized, or where a business has submitted acts of infringement and has a regular and established business environment. Many are left wondering about the impact of TC Heartland's ruling on the huge number of patent infringement cases that have already been filed in improper venues; others look for an explanation on what is important to show a “regular and established place of business." It is almost certain, however, that while we hang tight for answers to these questions to emerge, we will see fewer and fewer cases filed in patent-accommodating districts where just "the least contacts" exist, and an increase in states, for example, Delaware where numerous organizations have incorporated and where there is little contention about whether venue is proper. In Re: Google LLC, No. 19-126 (Fed. Cir. 2020) In re Google, the Federal Circuit further narrowed the definition of a “regular and established place of business.” The plaintiffs, Super Interconnect Technologies (SIT), filed suit against Google in the Eastern District of Texas, guaranteeing that venue was appropriate on the grounds that Google's Global Cache (GGC) workers were situated inside the district. The servers were not claimed by Google, however, were facilitated and kept up in racks by third-party Internet Service Providers (ISP). In analyzing the components set up in both TC Heartland and Cray, the court concurred that the presence of GGC servers inside the Eastern District of Texas fulfilled the principal component and that Google had a physical place within the district. In any case, in regard to the subsequent component, the court decided that residence of business requires the customary, actual presence of a representative or other specialist of the company. Expanding on this statement, the court concluded that the third-party ISP running the servers was not an agent of Google and that the venue was improper under 28 U.S.C. §1400(b). Impact Of TC Heartland on District Court Litigation Eastern District of Texas (EDT) In the Eastern District of Texas, the number of new infringement cases filed reduced drastically from 3,144 to 714 after TC Heartland. District of Delaware (DD) For courts like the District of Delaware, a dramatic rise has been noticed, i.e. from 749 to 1,721 after TC Heartland (mainly due to the fact that most companies are incorporated in Delaware). Delaware District court is also popular for filing patent cases, as most of the companies register themselves in that district. Delaware has comparatively business-friendly tax laws. For example, the people having business do not need to pay state corporate income tax. This is an advantage for the companies due to which investors prefer Delaware corporations. Delaware offers greater privacy for small businesses. For example, Delaware corporations do not need to disclose any officer or director names on their incorporation documents. Northern District Of California (NDC) The Northern District of California (NDC) has also seen a rise in filing the cases, the number increased from 316 to 474 after TC Heartland. After TC Heartland, plaintiffs have been forced towards districts that house technology companies’ headquarters. The Northern District of California, and Silicon Valley in particular, is home to a lot of technology companies. Western District Of Texas (WDT) In the Western District of Texas (WDT), the number of cases filed rocketed from 99 to 1,145 after TC Heartland. References https://www.natlawreview.com/article/tip-1-avoiding-ipr-institution-litigation-venue-selection https://www.fbm.com/publications/supreme-courts-decision-in-tc-heartland-narrows-patent-venue-selection/ https://www.mondaq.com/unitedstates/patent/981978/despite-tc-heartland-forum-selection-clause-controls-venue-in-patent-dispute https://home.ubalt.edu/shapiro/rights_course/Chapter2text.htm https://en.wikipedia.org/wiki/Procedures_of_the_Supreme_Court_of_the_United_States https://law.justia.com/cases/federal/appellate-courts/cafc/19-126/19-126-2020-02-13.html https://www.fbm.com/publications/supreme-courts-decision-in-tc-heartland-narrows-patent-venue-selection https://www.oyez.org/cases/2016/16-341 https://www.lexisnexisip.com/knowledge-center/tc-heartland-llc-v-kraft-foods-group-brands-llc/ https://www.natlawreview.com/article/tip-1-avoiding-ipr-institution-litigation-venue-selection https://home.ubalt.edu/shapiro/rights_course/Chapter2text.htm https://en.wikipedia.org/wiki/Procedures_of_the_Supreme_Court_of_the_United_States http://www.iphandbook.org/handbook/ch10/p08/ Copperpod provides patent litigation services such as Source Code Review, Infringement Claim Charts, Document Review, and advises clients to give a clear picture of the state of the art to navigate away from the potential prior art and monetize IP assets. 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