natural - Blog - Global Risk Community2024-03-28T12:09:19Zhttps://globalriskcommunity.com/profiles/blogs/feed/tag/naturalA Bird’s Eye View on the Outcome of US Elections on India’s Energy Sectorhttps://globalriskcommunity.com/profiles/blogs/a-bird-s-eye-view-on-the-outcome-of-us-elections-on-india-s2020-11-05T13:00:00.000Z2020-11-05T13:00:00.000ZChemAnalysthttps://globalriskcommunity.com/members/ChemAnalyst<div><p><a href="{{#staticFileLink}}8219694083,original{{/staticFileLink}}" target="_blank"><img src="{{#staticFileLink}}8219694083,original{{/staticFileLink}}" class="align-center" alt="8219694083?profile=original" /></a></p><p>As US heads towards Presidential Elections, the energy policy makers in India are keeping a close watch on the results which would decide its impact on the India-US ties. While Joe Biden promises strong push towards renewable energy sources, Trump’s victory may strengthen India’s oil, infra and defense sector. As soon as incumbent Donald Trump pulled US out of the Paris climate change agreement, which aims at mitigating the impact of greenhouse gas emissions on the global temperature rise, Biden launched a campaign promising the US to achieve the target of net zero emissions by 2050 and investing USD 1.7 trillion in the next ten years towards actualizing the same.</p><p><strong>Get more info : <a href="https://www.chemanalyst.com/NewsAndDeals/NewsDetails/a-birds-eye-view-on-the-outcome-of-us-elections-on-indias-energy-sector-3399">https://www.chemanalyst.com/NewsAndDeals/NewsDetails/a-birds-eye-view-on-the-outcome-of-us-elections-on-indias-energy-sector-3399</a></strong></p><p>Biden’s proposal sounds well when India has already shifted to fifth gear towards increasing its capacity of clean energy projects. Clean energy projects comprise nearly a fifth of India’s power generation capacity. By March 2022, India is aiming to produce 100 GW energy from its ongoing solar projects and 60 GW from wind power plants. Coming to the oil and gas sector, India has become the fourth largest export destination for the US crude and the fifth-largest consumer of US LNG. India has been already revisiting its crude sourcing strategy amid growing global uncertainties post the COVID-19 outbreak, aiming to protect its consumers from strong fluctuations in the international oil futures.</p><p>The India-US hydrocarbon trade was valued at USD 9.2 billion in FY20. The two countries have also mutually set up a gas task force (GTF) for discussions such as Natural Gas pricing, markets and regulation, investments on gas infrastructure and demand growth. Hydrogen has become a key area of interest for both the parties, with a public-private Hydrogen Task Force being formed towards the same to scale up technologies to produce Hydrogen from renewable energy and fossil fuel sources.</p><p>As per ChemAnalyst, "whatever the outcome, the results would pave the way for India to increase its refining capacity from 250 mtpa to 400 mtpa by 2025 and strengthen its green energy needs to establish the longest-running energy partnership between the two democracies."</p><p><strong>Source : ChemAnalyst</strong></p></div>The present and future of natural language processinghttps://globalriskcommunity.com/profiles/blogs/the-present-and-future-of-natural-language-processing2020-01-10T12:20:12.000Z2020-01-10T12:20:12.000ZKBV Researchhttps://globalriskcommunity.com/members/KBVResearch<div><p><a href="https://www.kbvresearch.com/natural-language-processing-market/">Natural Language Processing</a> (NLP) is an artificial intelligence field that enables machines to interpret, understand and infer meaning from human languages. It is a discipline that focuses on the interaction of data science and human language and scales across many industries. Today, NLP is booming due to the enormous changes in data access and the rise in computational power, which helps practitioners to produce meaningful results in fields such as education, media, banking, and human resources.</p><p>NLP is thriving within the healthcare industry. New technology improves patient delivery, diagnosis of disease, and reduces costs as healthcare facilities are rapidly embracing electronic health records. The fact that it is possible to improve clinical documentation implies that patients can be better understood and benefit from better healthcare. The aim should be to improve their experience, and this is already being achieved by several organizations.</p><p><strong>What is natural language processing?</strong></p><p><strong><a href="{{#staticFileLink}}8028305686,original{{/staticFileLink}}" target="_blank"><img src="{{#staticFileLink}}8028305686,original{{/staticFileLink}}" class="align-center" alt="8028305686?profile=original" /></a></strong></p><p>Natural Language Processing (NLP) is a sub-field of computer science, linguistics, information engineering, and artificial intelligence. All these technologies have known to be related to computer and human (natural) language interactions, especially how computers are programmed to process and analyze large amounts of natural language data.</p><p>Governments' ability to use these innovations in language processing defies restriction. Massive numbers of unstructured documents are held by governments. For the kind of deep-pattern analysis traditionally reserved for computational databases, fragmented information presented in fundamentally non-mathematical formats is now accessible at volumes far too large for human evaluation. NLP can open up new insights, more tailor-made services and faster responses to information to the public sector.</p><p><strong>Some use cases that show the power of NLP in the present era</strong></p><ul><li><strong>Natural language processing in healthcare</strong></li></ul><p>Medical services that are used to extract the conditions of the disease can handle meditation sessions and monitor treatment outcomes using clinical trial reports, electronic health records, and patient notes. This is an example of NLP in health analysis where it is possible to use NLP to predict various diseases utilizing pattern recognition methods and speech of patients and their electronic health record.</p><ul><li><strong>Sentiment analysis using natural language processing</strong></li></ul><p>Companies and organizations are now focused on various ways to get to know their customers in order to provide personalized interaction. The emotions behind the words can be calculated by using sentiment analysis (which can only be achieved using NLP). The feeling analysis has the ability to offer a lot of knowledge about the actions of the consumer and their decisions that can be taken into account as critical decisive factors.</p><ul><li><strong>Cognitive Analytics and natural language processing</strong></li></ul><p>This is the best example of different technologies working together, but both fall under Artificial Intelligence's same roof. The conversational systems that can take commands through the voice medium or the text medium are feasible using natural language processing. Using cognitive analytics, this generation of a technical ticket related to a technical issue is now possible to automate various technical processes and handle it in an automated or semi-automated manner. The application of these technologies can lead to an automated process of managing technical problems within an organization or can also provide the customer with an automated solution to certain technical problems</p><p><strong>Trends that drive the natural language processing industry</strong></p><ol><li><strong>Unsupervised and supervised learning</strong></li></ol><p>It is a common fact that machine learning provides significant support for natural language with applications of both supervised and unsupervised learning, particularly in text analytics. Once the word in a document is understood by Natural Language Processing and its parts of speech, unsupervised learning may establish mathematical relationships. Supervised learning is then based on the product of the relationship determinations of unsupervised learning.</p><ol start="2"><li><strong>Reinforcement learning</strong></li></ol><p>By reinforcement learning, a variety of natural language generation (NLG) tasks, such as text description, are being explored. Although reinforcement learning approaches show potential outcomes, they require appropriate action and state-space management, which may restrict the model's significant power and learning skills.</p><ol start="3"><li><strong>Deep learning</strong></li></ol><p>The support of natural language through Deep Learning is as significant as it is multifaceted. Techniques such as Recurrent Neural Networks will leverage to provide a very accurate classification for the use of parsing results and thus gain common grip in certain text analytics platforms for classification of documents and labeling of entities.</p><ol start="4"><li><strong>Semantic search</strong></li></ol><p>Another development expected to significantly revolutionize natural language and machine learning in the coming year is the need for semantic search. The search involves both the interpretation of natural language and the comprehension of natural language and necessitates a precise understanding of the central ideas in the text. Organizations that want to search through their document collection need the intelligence that comes from Natural Language Processing and Machine Learning into a search-based framework. This not only helps to inject back into operations but also to develop smart search or semantic search applications.</p><ol start="5"><li><strong>Cognitive communication</strong></li></ol><p>Text analytics is anticipated to remain the most extensive natural language use case in the years to come. Nonetheless, in use cases involving speech-to-text, smart chatbots, and semantic search, these technologies will also become more popular. Instigated by deep learning frameworks, unsupervised and supervised machine learning, the proliferation of natural language technologies will continue to influence cognitive computing's communication ability.</p><p><strong>The big picture</strong></p><p>The <a href="https://www.kbvresearch.com/natural-language-processing-market/">natural language processing market</a> is evolving with a wide range of growth factors such as increased adoption of smart devices and the increase in technological investments in the healthcare environment. Developments in the processing of natural language have data governance connotations. It collects enormous amounts of user data, posing critical legal issues regarding data ownership, privacy, and protection.</p><p>Big tech companies like Google, Facebook, Microsoft, Amazon, and others will take over more control of what we see and do, but they are not the government and for governments to be successful, new regulations on how data is collected and disseminated via NLP need to be developed, specifically where Natural Language Processing is linked to financial gain.</p><p> </p></div>Confronting the Tyranny of Management by Numbers: How Business Can Deliver the Results We Care About Mosthttps://globalriskcommunity.com/profiles/blogs/confronting-the-tyranny-of-management-by-numbers-how-business-can2015-03-13T02:00:00.000Z2015-03-13T02:00:00.000ZEnrique Raul Suarezhttps://globalriskcommunity.com/members/EnriqueRaulSuarez<div><p style="text-align:left;">According to professor Thomas Johnson, it’s easy to talk about the changes wrought by today’s global economy. But most such discussions fail to address the real impact of business practices in the twenty-first century. The growth of industrial societies during the past 150 years – and particularly the aggressive corporate growth strategies of the past 50 years – have done unprecedented damage to the environment and created unsustainable performance pressures on companies.</p><div>The threat to our natural and organizational systems flows from a view of business that most CEOs accept without question, but which is at odds with thousands of years of human economic activity. Our response to this threat must go beyond anything commonly proposed in policy or regulatory debates. What’s needed is a vision of the future that recognizes the potential and the constraints that govern all natural systems.</div><div>The first glimmerings of that vision – evident in some unlikely places, as we’ll soon examine – embody a way of managing that speaks to the higher aspirations of people throughout an enterprise. Such a vision offers a hopeful alternative to the mindless pursuit of growth for growth’s sake that threatens the health of the planet.</div><div>Transforming the economic system will require transforming the system of management that drives it. Dr. Thomas Johnson calls the new thinking and practices of such businesses “management by means,” or MBM (Johnson and Broms, 2000).</div><div>The assumption underlying MBM is that a business is properly run only if it operates according to principles like those that guide the operations of natural systems – as opposed to the “managing by results” approach that dominates today.</div><div>This presentation will discuss the meaning of "managing by means" and the implications for the larger ecosystem that we have the practical and moral obligation to protect.</div><p></p><p><span class="font-size-4"><a href="{{#staticFileLink}}8028230071,original{{/staticFileLink}}"><font size="2">Confronting%20the%20Tyranny.pdf</font></a></span></p><p></p><p></p></div>