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| data science in the military: Military Applications of Data Analytics Kevin Huggins, 2018-10-09 Military organizations around the world are normally huge producers and consumers of data. Accordingly, they stand to gain from the many benefits associated with data analytics. However, for leaders in defense organizations—either government or industry—accessible use cases are not always available. This book presents a diverse collection of cases that explore the realm of possibilities in military data analytics. These use cases explore such topics as: Context for maritime situation awareness Data analytics for electric power and energy applications Environmental data analytics in military operations Data analytics and training effectiveness evaluation Harnessing single board computers for military data analytics Analytics for military training in virtual reality environments A chapter on using single board computers explores their application in a variety of domains, including wireless sensor networks, unmanned vehicles, and cluster computing. The investigation into a process for extracting and codifying expert knowledge provides a practical and useful model for soldiers that can support diagnostics, decision making, analysis of alternatives, and myriad other analytical processes. Data analytics is seen as having a role in military learning, and a chapter in the book describes the ongoing work with the United States Army Research Laboratory to apply data analytics techniques to the design of courses, evaluation of individual and group performances, and the ability to tailor the learning experience to achieve optimal learning outcomes in a minimum amount of time. Another chapter discusses how virtual reality and analytics are transforming training of military personnel. Virtual reality and analytics are also transforming monitoring, decision making, readiness, and operations. Military Applications of Data Analytics brings together a collection of technical and application-oriented use cases. It enables decision makers and technologists to make connections between data analytics and such fields as virtual reality and cognitive science that are driving military organizations around the world forward. |
| data science in the military: Strengthening Data Science Methods for Department of Defense Personnel and Readiness Missions National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Board on Mathematical Sciences and Their Applications, Committee on Applied and Theoretical Statistics, Committee on Strengthening Data Science Methods for Department of Defense Personnel and Readiness Missions, 2017-03-06 The Office of the Under Secretary of Defense (Personnel & Readiness), referred to throughout this report as P&R, is responsible for the total force management of all Department of Defense (DoD) components including the recruitment, readiness, and retention of personnel. Its work and policies are supported by a number of organizations both within DoD, including the Defense Manpower Data Center (DMDC), and externally, including the federally funded research and development centers (FFRDCs) that work for DoD. P&R must be able to answer questions for the Secretary of Defense such as how to recruit people with an aptitude for and interest in various specialties and along particular career tracks and how to assess on an ongoing basis service members' career satisfaction and their ability to meet new challenges. P&R must also address larger-scale questions, such as how the current realignment of forces to the Asia-Pacific area and other regions will affect recruitment, readiness, and retention. While DoD makes use of large-scale data and mathematical analysis in intelligence, surveillance, reconnaissance, and elsewhereâ€exploiting techniques such as complex network analysis, machine learning, streaming social media analysis, and anomaly detectionâ€these skills and capabilities have not been applied as well to the personnel and readiness enterprise. Strengthening Data Science Methods for Department of Defense Personnel and Readiness Missions offers and roadmap and implementation plan for the integration of data analysis in support of decisions within the purview of P&R. |
| data science in the military: Military Applications of Data Analytics Kevin Huggins, 2018-10-09 Military organizations around the world are normally huge producers and consumers of data. Accordingly, they stand to gain from the many benefits associated with data analytics. However, for leaders in defense organizations—either government or industry—accessible use cases are not always available. This book presents a diverse collection of cases that explore the realm of possibilities in military data analytics. These use cases explore such topics as: Context for maritime situation awareness Data analytics for electric power and energy applications Environmental data analytics in military operations Data analytics and training effectiveness evaluation Harnessing single board computers for military data analytics Analytics for military training in virtual reality environments A chapter on using single board computers explores their application in a variety of domains, including wireless sensor networks, unmanned vehicles, and cluster computing. The investigation into a process for extracting and codifying expert knowledge provides a practical and useful model for soldiers that can support diagnostics, decision making, analysis of alternatives, and myriad other analytical processes. Data analytics is seen as having a role in military learning, and a chapter in the book describes the ongoing work with the United States Army Research Laboratory to apply data analytics techniques to the design of courses, evaluation of individual and group performances, and the ability to tailor the learning experience to achieve optimal learning outcomes in a minimum amount of time. Another chapter discusses how virtual reality and analytics are transforming training of military personnel. Virtual reality and analytics are also transforming monitoring, decision making, readiness, and operations. Military Applications of Data Analytics brings together a collection of technical and application-oriented use cases. It enables decision makers and technologists to make connections between data analytics and such fields as virtual reality and cognitive science that are driving military organizations around the world forward. |
| data science in the military: Strengthening Data Science Methods for Department of Defense Personnel and Readiness Missions National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Board on Mathematical Sciences and Their Applications, Committee on Applied and Theoretical Statistics, Committee on Strengthening Data Science Methods for Department of Defense Personnel and Readiness Missions, 2017-02-06 The Office of the Under Secretary of Defense (Personnel & Readiness), referred to throughout this report as P&R, is responsible for the total force management of all Department of Defense (DoD) components including the recruitment, readiness, and retention of personnel. Its work and policies are supported by a number of organizations both within DoD, including the Defense Manpower Data Center (DMDC), and externally, including the federally funded research and development centers (FFRDCs) that work for DoD. P&R must be able to answer questions for the Secretary of Defense such as how to recruit people with an aptitude for and interest in various specialties and along particular career tracks and how to assess on an ongoing basis service members' career satisfaction and their ability to meet new challenges. P&R must also address larger-scale questions, such as how the current realignment of forces to the Asia-Pacific area and other regions will affect recruitment, readiness, and retention. While DoD makes use of large-scale data and mathematical analysis in intelligence, surveillance, reconnaissance, and elsewhereâ€exploiting techniques such as complex network analysis, machine learning, streaming social media analysis, and anomaly detectionâ€these skills and capabilities have not been applied as well to the personnel and readiness enterprise. Strengthening Data Science Methods for Department of Defense Personnel and Readiness Missions offers and roadmap and implementation plan for the integration of data analysis in support of decisions within the purview of P&R. |
| data science in the military: Leveraging Big Data Analytics to Improve Military Recruiting Nelson Lim, Bruce R. Orvis, Kimberly Curry Hall, 2019-11-30 The authors identified current, desired, and prospective data-enabled practices that the U.S. Department of Defense and the services might be able to deploy in their outreach and recruiting processes. |
| data science in the military: Assessing Department of Defense Use of Data Analytics and Enabling Data Management to Improve Acquisition Outcomes Philip S. Antón, 2019 In the conference report accompanying the National Defense Authorization Act for Fiscal Year 2017, Congress expressed concern that the U.S. Department of Defense (DoD) does not sufficiently incorporate data into its acquisition-related learning and decision-making and asked six questions about the use of data analysis, measurement, and other evaluation-related methods in DoD acquisition programs. In this report, the authors decompose and measure acquisition functions, data governance, and training to assess how data and associated analytics support DoD acquisition decision making. The authors found that the DoD is applying a breadth of data analytics to acquisition. Capabilities range from simple data archives and plotting to archives integrated with commercial analytic tools. The DoD has implemented an array of data governance and management practices, but major challenges remain, including a culture against data sharing and concerns about security and oversight burden. Some commercial breakthroughs in advanced analytics sound promising for DoD acquisition, but some might not be applicable; research is ongoing. Advancement should include developing a data analytics strategy across acquisition domains, expanding data governance and data sharing, and continuing to expand and mature data collection, access, and analytic layers. Also, mechanisms are needed to authorize and ensure protected access to data for both the DoD and external analysts. Improved incentives and understanding of data analytics could encourage decision makers to make better use of capabilities -- Publisher's description. |
| data science in the military: Handbook of Military and Defense Operations Research Natalie M. Scala, James P. Howard, II, 2020-02-10 Operations research (OR) is a core discipline in military and defense management. Coming to the forefront initially during World War II, OR provided critical contributions to logistics, supply chains, and strategic simulation, while enabling superior decision-making for Allied forces. OR has grown to include analytics and many applications, including artificial intelligence, cybersecurity, and big data, and is the cornerstone of management science in manufacturing, marketing, telecommunications, and many other fields. The Handbook of Military and Defense Operations Research presents the voices leading OR and analytics to new heights in security through research, practical applications, case studies, and lessons learned in the field. Features Applies the experiences of educators and practitioners working in the field Employs the latest technology developments in case studies and applications Identifies best practices unique to the military, security, and national defense problem space Highlights similarities and dichotomies between analyses and trends that are unique to military, security, and defense problems. |
| data science in the military: Small Wars, Big Data Eli Berman, Joseph H. Felter, Jacob N. Shapiro, 2018-06-12 How a new understanding of warfare can help the military fight today’s conflicts more effectively The way wars are fought has changed starkly over the past sixty years. International military campaigns used to play out between large armies at central fronts. Today's conflicts find major powers facing rebel insurgencies that deploy elusive methods, from improvised explosives to terrorist attacks. Small Wars, Big Data presents a transformative understanding of these contemporary confrontations and how they should be fought. The authors show that a revolution in the study of conflict--enabled by vast data, rich qualitative evidence, and modern methods—yields new insights into terrorism, civil wars, and foreign interventions. Modern warfare is not about struggles over territory but over people; civilians—and the information they might choose to provide—can turn the tide at critical junctures. The authors draw practical lessons from the past two decades of conflict in locations ranging from Latin America and the Middle East to Central and Southeast Asia. Building an information-centric understanding of insurgencies, the authors examine the relationships between rebels, the government, and civilians. This approach serves as a springboard for exploring other aspects of modern conflict, including the suppression of rebel activity, the role of mobile communications networks, the links between aid and violence, and why conventional military methods might provide short-term success but undermine lasting peace. Ultimately the authors show how the stronger side can almost always win the villages, but why that does not guarantee winning the war. Small Wars, Big Data provides groundbreaking perspectives for how small wars can be better strategized and favorably won to the benefit of the local population. |
| data science in the military: The Very Long Game Heiko Borchert, |
| data science in the military: Managing Your Data Science Projects Robert de Graaf, 2019-06-07 At first glance, the skills required to work in the data science field appear to be self-explanatory. Do not be fooled. Impactful data science demands an interdisciplinary knowledge of business philosophy, project management, salesmanship, presentation, and more. In Managing Your Data Science Projects, author Robert de Graaf explores important concepts that are frequently overlooked in much of the instructional literature that is available to data scientists new to the field. If your completed models are to be used and maintained most effectively, you must be able to present and sell them within your organization in a compelling way. The value of data science within an organization cannot be overstated. Thus, it is vital that strategies and communication between teams are dexterously managed. Three main ways that data science strategy is used in a company is to research its customers, assess risk analytics, and log operational measurements. These all require different managerial instincts, backgrounds, and experiences, and de Graaf cogently breaks down the unique reasons behind each. They must align seamlessly to eventually be adopted as dynamic models. Data science is a relatively new discipline, and as such, internal processes for it are not as well-developed within an operational business as others. With Managing Your Data Science Projects, you will learn how to create products that solve important problems for your customers and ensure that the initial success is sustained throughout the product’s intended life. Your users will trust you and your models, and most importantly, you will be a more well-rounded and effectual data scientist throughout your career. Who This Book Is For Early-career data scientists, managers of data scientists, and those interested in entering the field of data science |
| data science in the military: Dialogues Concerning Science, Technology, and Intellect in American Society's and Military's Future Bruce J. West, Chris Arney, Kira Hutchinson, 2021-03-11 This book presents distinctive perspectives and voices concerning the nature, utility, and limitations of science and technology in national security, as well as outlining the nature of science and technology’s interdependency with military operations. These dialogues are particularly timely during this period of transition for the US military in which these implicit ideas are molding the Army Futures Command and similar other service agencies. The design decisions being made to equip, train, educate, deploy, and lead the future force need wisdom from experienced scientists, engineers, and innovators. This book addresses fundamental issues such as the relationship between scientific advances and technological innovation and the roles of science and technology in a modern society and the military. |
| data science in the military: Military Technology Ron Fridell, 2008 An introduction to military technology, looking at the advanced weaponry and machinery employed by military forces around the world. |
| data science in the military: The Art and Science of Military Deception Hy Rothstein, Barton Whaley, 2013-09-01 It is said that deception among people in a civilized society is something to be loathed even though it seems to be part of human nature; but deception in war is a virtue. Properly designed and executed, stratagems reduce the horrific costs of war. This book is a comprehensive collection of classic articles on deception, hand-picked and expertly introduced by well-known experts on military deception. The purpose of this book is to set in motion a renaissance for using deception as an instrument of statecraft. The various sections are designed to cumulatively provide sufficient breadth and depth on the subject to satisfy both the novice as well as the expert. Packed with expert commentary, interesting background information, and original readings, this book provides the reader with sufficient knowledge to pursue General Eisenhower’s vision for the proper role of deception in support of the national interest. |
| data science in the military: Data Analytics and AI Jay Liebowitz, 2020-08-06 Analytics and artificial intelligence (AI), what are they good for? The bandwagon keeps answering, absolutely everything! Analytics and artificial intelligence have captured the attention of everyone from top executives to the person in the street. While these disciplines have a relatively long history, within the last ten or so years they have exploded into corporate business and public consciousness. Organizations have rushed to embrace data-driven decision making. Companies everywhere are turning out products boasting that artificial intelligence is included. We are indeed living in exciting times. The question we need to ask is, do we really know how to get business value from these exciting tools? Unfortunately, both the analytics and AI communities have not done a great job in collaborating and communicating with each other to build the necessary synergies. This book bridges the gap between these two critical fields. The book begins by explaining the commonalities and differences in the fields of data science, artificial intelligence, and autonomy by giving a historical perspective for each of these fields, followed by exploration of common technologies and current trends in each field. The book also readers introduces to applications of deep learning in industry with an overview of deep learning and its key architectures, as well as a survey and discussion of the main applications of deep learning. The book also presents case studies to illustrate applications of AI and analytics. These include a case study from the healthcare industry and an investigation of a digital transformation enabled by AI and analytics transforming a product-oriented company into one delivering solutions and services. The book concludes with a proposed AI-informed data analytics life cycle to be applied to unstructured data. |
| data science in the military: Applications of Mathematics and Informatics in Military Science Nicholas Daras, 2012-08-18 Analysis, assessment, and data management are core tools required for operation research analysts. The April 2011 conference held at the Helenic Military Academy addressed these issues with efforts to collect valuable recommendations for improving analysts’ capabilities to assess and communicate the necessary qualitative data to military leaders. This unique volume is an outgrowth of the April conference and comprises of contributions from the fields of science, mathematics, and the military, bringing Greek research findings to the world. Topics cover a wide variety of mathematical methods used with application to defense and security. Each contribution considers directions and pursuits of scientists that pertain to the military as well as the theoretical background required for methods, algorithms, and techniques used in military applications. The direction of theoretical results in these applications is conveyed and open problems and future areas of focus are highlighted. A foreword will be composed by a member of N.A.T.O. or a ranking member of the armed forces. Topics covered include: applied OR and military applications, signal processing, scattering, scientific computing and applications, combat simulation and statistical modeling, satellite remote sensing, and applied informatics – cryptography and coding. The contents of this volume will be of interest to a diverse audience including military operations research analysts, the military community at large, and practitioners working with mathematical methods and applications to informatics and military science. |
| data science in the military: Information Technology and Military Power Jon R. Lindsay, 2020-07-15 Militaries with state-of-the-art information technology sometimes bog down in confusing conflicts. To understand why, it is important to understand the micro-foundations of military power in the information age, and this is exactly what Jon R. Lindsay's Information Technology and Military Power gives us. As Lindsay shows, digital systems now mediate almost every effort to gather, store, display, analyze, and communicate information in military organizations. He highlights how personnel now struggle with their own information systems as much as with the enemy. Throughout this foray into networked technology in military operations, we see how information practice—the ways in which practitioners use technology in actual operations—shapes the effectiveness of military performance. The quality of information practice depends on the interaction between strategic problems and organizational solutions. Information Technology and Military Power explores information practice through a series of detailed historical cases and ethnographic studies of military organizations at war. Lindsay explains why the US military, despite all its technological advantages, has struggled for so long in unconventional conflicts against weaker adversaries. This same perspective suggests that the US retains important advantages against advanced competitors like China that are less prepared to cope with the complexity of information systems in wartime. Lindsay argues convincingly that a better understanding of how personnel actually use technology can inform the design of command and control, improve the net assessment of military power, and promote reforms to improve military performance. Warfighting problems and technical solutions keep on changing, but information practice is always stuck in between. |
| data science in the military: Military Operations Research N.K. Jaiswal, 2012-12-06 Operations Research (OR) emerged in an effort to improve the effectiveness of newly inducted weapons and equipment during World War II. While rapid growth ofOR led to its becoming an important aid to decision making in all sectors including defense, its contribution in defense remained largely confined to classified reports. Very few books dealing with applications of quantitative decision making techniques in military have been published presumably due to limited availability ofrelevant information. The situation changed rapidly during the last few years. The recognition of the subject of Military Operations Research (MOR) gave tremendous boost to its development. Books and journals on MOR started appearing. The number of sessions on MOR at national and international conferences also registered an increase. The volume of teaching, training and research activities in the field of MOR at military schools and non-military schools enhanced considerably. Military executives and commanders started taking increasing interest in getting scientific answers to questions pertaining to weapon acquisition, threat perception and quantification, assessment of damage or casualties, evaluation of chance of winning a battle, force mix, deployment and targeting of weapons against enemy targets, war games and scenario evaluation. Most of these problems were being tackled on the basis of intuition, judgment and experience or analysis under very simple assumptions. In an increasingly sophisticated and complex defense scenario resulting in advances in equipment and communications, the need for supplementing these practices by scientific research in MOR became imperative. |
| data science in the military: Big Data Preprocessing Julián Luengo, Diego García-Gil, Sergio Ramírez-Gallego, Salvador García, Francisco Herrera, 2020-03-16 This book offers a comprehensible overview of Big Data Preprocessing, which includes a formal description of each problem. It also focuses on the most relevant proposed solutions. This book illustrates actual implementations of algorithms that helps the reader deal with these problems. This book stresses the gap that exists between big, raw data and the requirements of quality data that businesses are demanding. This is called Smart Data, and to achieve Smart Data the preprocessing is a key step, where the imperfections, integration tasks and other processes are carried out to eliminate superfluous information. The authors present the concept of Smart Data through data preprocessing in Big Data scenarios and connect it with the emerging paradigms of IoT and edge computing, where the end points generate Smart Data without completely relying on the cloud. Finally, this book provides some novel areas of study that are gathering a deeper attention on the Big Data preprocessing. Specifically, it considers the relation with Deep Learning (as of a technique that also relies in large volumes of data), the difficulty of finding the appropriate selection and concatenation of preprocessing techniques applied and some other open problems. Practitioners and data scientists who work in this field, and want to introduce themselves to preprocessing in large data volume scenarios will want to purchase this book. Researchers that work in this field, who want to know which algorithms are currently implemented to help their investigations, may also be interested in this book. |
| data science in the military: Science on a Mission Naomi Oreskes, 2021-04-19 A vivid portrait of how Naval oversight shaped American oceanography, revealing what difference it makes who pays for science. What difference does it make who pays for science? Some might say none. If scientists seek to discover fundamental truths about the world, and they do so in an objective manner using well-established methods, then how could it matter who’s footing the bill? History, however, suggests otherwise. In science, as elsewhere, money is power. Tracing the recent history of oceanography, Naomi Oreskes discloses dramatic changes in American ocean science since the Cold War, uncovering how and why it changed. Much of it has to do with who pays. After World War II, the US military turned to a new, uncharted theater of warfare: the deep sea. The earth sciences—particularly physical oceanography and marine geophysics—became essential to the US Navy, which poured unprecedented money and logistical support into their study. Science on a Mission brings to light how this influx of military funding was both enabling and constricting: it resulted in the creation of important domains of knowledge but also significant, lasting, and consequential domains of ignorance. As Oreskes delves into the role of patronage in the history of science, what emerges is a vivid portrait of how naval oversight transformed what we know about the sea. It is a detailed, sweeping history that illuminates the ways funding shapes the subject, scope, and tenor of scientific work, and it raises profound questions about the purpose and character of American science. What difference does it make who pays? The short answer is: a lot. |
| data science in the military: Rethinking Military Professionalism for the Changing Armed Forces Krystal K. Hachey, Tamir Libel, Waylon H. Dean, 2020-06-09 This book will make a first contribution to identify the gaps in current practices and provide alternative mechanisms to conceptualize professionalism that is reflective of changing requirements, culture, and demographics of the contemporary military force.The military profession promotes the development, sustainment, and embodiment of ethos, which guides conduct across operational contexts, from times of national and international crises and security challenges (e.g., war, natural disasters, and peace support operations). It is imperative for military leaders to understand how ethos and doctrine shape professional frameworks, which guide the conduct of military members. |
| data science in the military: Social Network Analysis with Applications Ian McCulloh, Helen Armstrong, Anthony Johnson, 2013-07-01 A comprehensive introduction to social network analysis that hones in on basic centrality measures, social links, subgroup analysis, data sources, and more Written by military, industry, and business professionals, this book introduces readers to social network analysis, the new and emerging topic that has recently become of significant use for industry, management, law enforcement, and military practitioners for identifying both vulnerabilities and opportunities in collaborative networked organizations. Focusing on models and methods for the analysis of organizational risk, Social Network Analysis with Applications provides easily accessible, yet comprehensive coverage of network basics, centrality measures, social link theory, subgroup analysis, relational algebra, data sources, and more. Examples of mathematical calculations and formulas for social network measures are also included. Along with practice problems and exercises, this easily accessible book covers: The basic concepts of networks, nodes, links, adjacency matrices, and graphs Mathematical calculations and exercises for centrality, the basic measures of degree, betweenness, closeness, and eigenvector centralities Graph-level measures, with a special focus on both the visual and numerical analysis of networks Matrix algebra, outlining basic concepts such as matrix addition, subtraction, multiplication, and transpose and inverse calculations in linear algebra that are useful for developing networks from relational data Meta-networks and relational algebra, social links, diffusion through networks, subgroup analysis, and more An excellent resource for practitioners in industry, management, law enforcement, and military intelligence who wish to learn and apply social network analysis to their respective fields, Social Network Analysis with Applications is also an ideal text for upper-level undergraduate and graduate level courses and workshops on the subject. |
| data science in the military: The Other Side of the Mountain: Mujahideen Tactics in the Soviet-Afghan War Ali Ahmad Jalali, 2022-05-29 The Other Side of the Mountain: Mujahadeen Tactics in the Soviet-Afghan War is a 1998 non-fiction book written by former Afghan Army Colonel Ali Ahmad Jalali and American military scholar Lester W. Grau. The book was commissioned by the United States Marine Corps Studies and Analysis Division to complement Grau's previous book, The Bear Went Over the Mountain. Jalali and Grau had planned travel into Afghanistan to interview Mujahideen fighters in late 1996, but were forced to remain in Pakistan when a Taliban offensive campaign started to seize major portions of Afghanistan, eventually capturing Kabul on September 27. Jalali interviewed approximately 40 Mujahideen during the month which the authors spent in Pakistan and an associate, Major Nasrullah Safi, conducted interviews inside Afghanistan for two months to collect additional data. |
| data science in the military: Defense Technological Innovation Bharat Rao, Adam J. Harrison, Bala Mulloth, 2020-05-29 Defense Technological Innovation describes the emerging paradigm for innovation at the US Department of Defense, and the consequent impacts on its stakeholders. Leveraging a combination of prior research, archival data, first-person observations and interviews, the authors identify practices and themes characterizing the key trends in defense innovation, describe current organizational approaches and practices, and develop a theoretical framework that elucidates the competencies required to underwrite defense innovation objectives. The findings therein are relevant to any large, technology-driven organization contending with the implications of rapid change in the high-tech landscape. |
| data science in the military: Handbook of Military and Defense Operations Research Natalie Michele Scala, James Patrick Howard (II), 2024 Operations research (OR) is a core discipline in military and defense management. Coming to the forefront initially during World War II, OR provided critical contributions to logistics, supply chains, and strategic simulation, while enabling superior decision-making for Allied forces. OR has grown to include analytics and many applications, including artificial intelligence, cybersecurity, and big data, and is the cornerstone of management science in manufacturing, marketing, telecommunications, and many other fields. This new edition of the Handbook of Military and Defense Operations Research continues to present the voices leading OR and analytics to new heights in security through research, practical applications, case studies, and lessons learned in the field-- |
| data science in the military: Doing Data Science Cathy O'Neil, Rachel Schutt, 2013-10-09 Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course. |
| data science in the military: Methods for Conducting Military Operational Analysis Andrew G. Loerch, 2007 |
| data science in the military: Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) Dhananjay Kumar, Pavel Loskot, Qingliang Chen, 2023-09-01 This is an open access book. The 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) was held on April 28–30, 2023 at the Xiamen, China. With the development of science and technology, information technology and information resources should be actively developed and fully applied in all fields of education and teaching, so as to promote the modernization of education and cultivate talents to meet the needs of society. From the technical point of view, the basic characteristics of educational informatization are digitalization, networking, intelligentization and multi-media. From the perspective of education, the basic characteristics of educational information are openness, sharing, interaction and cooperation. With the advantage of the network, it can provide students with a large amount of information and knowledge by combining different knowledge and information from various aspects in a high frequency. Therefore, we have intensified efforts to reform the traditional teaching methods and set up a new teaching concept, from the interaction between teachers and students in the past to the sharing between students. In short, it forms a sharing learning mode. For all students, strive to achieve students' learning independence, initiative and creativity. To sum up, we will provide a quick exchange platform between education and information technology, so that more scholars in related fields can share and exchange new ideas. The 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) was held on April 28-30, 2023 in Xiamen, China. IEIT 2023 is to bring together innovative academics and industrial experts in the field of Internet, Education and Information Technology to a common forum. The primary goal of the conference is to promote research and developmental activities in Internet, Education and Information Technology and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in international conference on Internet, Education and Information Technology and related areas. |
| data science in the military: Military-Age Males in Counterinsurgency and Drone Warfare Sarah Shoker, 2020-09-05 This book documents the political ecosystem that legitimized violent military action against military-age males in US military operations after September 11, 2001. It first introduces the military-age male as a category used to identify insurgent combatants who have blended into civilian environments. Though US officials maintained that military-age males were not automatically assumed to be combatants, defense and intelligence professionals nevertheless used biases related to gender, age, religion and race to interpret the battlespace. Based on an analysis of the Obama administration’s decision to exclude adolescent boys and men from drone warfare’s collateral damage count, and an examination of similar problems with combatant identification under the Bush administration, the author argues that the military-age male category contributed to the deterioration of civilian protection. The concluding chapters discusses the link between counterinsurgency, drone warfare, and emerging trends in artificial intelligence and autonomy in weapons systems, highlighting the relation between algorithmic discrimination and the misidentification of civilians as combatants. |
| data science in the military: Research Anthology on Artificial Intelligence Applications in Security Management Association, Information Resources, 2020-11-27 As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it’s important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research. |
| data science in the military: The Military Balance 2022 The International Institute for Strategic Studies (IISS), 2022-02-14 Published each year since 1959, The Military Balance is an indispensable reference to the capabilities of armed forces across the globe. It is used by academia, the media, armed forces, the private sector and government. It is an open-source assessment of the military forces and equipment inventories of 171 countries, with accompanying defence economics and procurement data. Alongside detailed country data, The Military Balance assesses important defence issues, by region, as well as key global trends, such as in defence technology and equipment modernisation. This analysis is accompanied by full-colour graphics, including maps and illustrations. With extensive explanatory notes and reference information, The Military Balance is as straightforward to use as it is extensive. The 2022 edition is accompanied by a fullcolour wall chart illustrating security dynamics in the Arctic. |
| data science in the military: Army Sustainment , 2015 The Department of the Army's official professional bulletin on sustainment, publishing timely, authoritative information on Army and Defense sustainment plans, programs, policies, operations, procedures, and doctrine for the benefit of all sustainment personnel. |
| data science in the military: Man–Machine–Environment System Engineering Shengzhao Long, Balbir S. Dhillon, 2017-08-21 These proceedings showcase the best papers selected from more than 500 submissions, introducing readers to the top research topics and the latest developmental trends in the theory and application of Man-Machine-Environment System Engineering (MMESE). This research topic was first established in China by Professor Shengzhao Long in 1981, with direct support from one of the greatest modern Chinese scientists, Xuesen Qian. In a letter to Shengzhao Long from October 22nd, 1993, Xuesen Qian wrote: “You have created a very important modern science and technology in China!” MMESE primarily focuses on the relationship between Man, Machine and Environment, studying the optimum combination of related Man-Machine-Environment systems. In this paradigm, “Man” refers to working people as the subject at the workplace (e.g. operators, decision-makers); “Machine” is the general name for any object controlled by Man (including tools, machinery, computers, systems and technologies), and “Environment” describes the specific working conditions under which Man and Machine interact (e.g. temperature, noise, vibration, hazardous gases etc.). In turn, the three goals of optimization are to ensure safety, efficiency and economy in this context. These proceedings present interdisciplinary studies on the concepts and methods of physiology, psychology, system engineering, computer science, environmental science, management, education, and other related disciplines. They offer a valuable resource for all researchers and professionals whose work involves interdisciplinary areas touching on MMESE subjects. |
| data science in the military: Implications of Modern Decision Science for Military Decision-support Systems Paul K. Davis, Jonathan Kulick, Michael Egner, 2005 A selective review of modern decision science and implications for decision-support systems. The study suggests ways to synthesize lessons from research on heuristics and biases with those from naturalistic research. It also discusses modern tools, such as increasingly realistic simulations, multiresolution modeling, and exploratory analysis, which can assist decisionmakers in choosing strategies that are flexible, adaptive, and robust. |
| data science in the military: Towers of Ivory and Steel Maya Wind, 2024-01-30 Israeli universities have long enjoyed a reputation as liberal bastions of freedom and democracy. Drawing on extensive research and making Hebrew sources accessible to the international community, Maya Wind shatters this myth and documents how Israeli universities are directly complicit in the violation of Palestinian rights. As this book shows, Israeli universities serve as pillars of Israel's system of oppression against Palestinians. Academic disciplines, degree programs, campus infrastructure, and research laboratories all service Israeli occupation and apartheid, while universities violate the rights of Palestinians to education, stifle critical scholarship, and violently repress student dissent. Towers of Ivory and Steel is a powerful expose of Israeli academia's ongoing and active complicity in Israel's settler-colonial project. |
| data science in the military: Beyond Spinoff John A. Alic, 1992 In a rapidly changing world, there needs to be a critical reappraisal of traditional military/industry relationships. This book, packed with data, industry-specific case studies, and sophisticated analysis, is such an appraisal. It will be required reading for technology managers and policymakers in industry and government, as well as those concerned with technological and economic competitiveness. |
| data science in the military: Cyber Security in the Age of Artificial Intelligence and Autonomous Weapons Mehmet Emin Erendor, 2024-11-19 Although recent advances in technology have made life easier for individuals, societies, and states, they have also led to the emergence of new and different problems in the context of security. In this context, it does not seem possible to analyze the developments in the field of cyber security only with information theft or hacking, especially in the age of artificial intelligence and autonomous weapons. For this reason, the main purpose of this book is to explain the phenomena from a different perspective by addressing artificial intelligence and autonomous weapons, which remain in the background while focusing on cyber security. By addressing these phenomena, the book aims to make the study multidisciplinary and to include authors from different countries and different geographies. The scope and content of the study differs significantly from other books in terms of the issues it addresses and deals with. When we look at the main features of the study, we can say the following: Handles the concept of security within the framework of technological development Includes artificial intelligence and radicalization, which has little place in the literature Evaluates the phenomenon of cyber espionage Provides an approach to future wars Examines the course of wars within the framework of the Clausewitz trilogy Explores ethical elements Addresses legal approaches In this context, the book offers readers a hope as well as a warning about how technology can be used for the public good. Individuals working in government, law enforcement, and technology companies can learn useful lessons from it. |
| data science in the military: Military Review , 2019 |
| data science in the military: Military Applications of Artificial Intelligence Forrest E. Morgan, Benjamin Boudreaux, Andrew J. Lohn, Christian Curriden, 2020-08-31 The authors of this report examine military applications of artificial intelligence (AI); compare development efforts in the United States, China, and Russia; and consider the ethical implications of employing military AI in war and peace. |
| data science in the military: Military Modeling Wayne P. Hughes, Marion R. Bryson, 1989 A collection of papers that explore of the use of modeling in military planning. Explores how modeling applies to a variety forms of military engagement including ground, sea, air and nuclear warfare. |
| data science in the military: Excel in Complex Variables with the Complex Variable Boundary Element Method B. D. Wilkins, T. V. Hromadka II, 2021-09-22 Using the familiar software Microsoft ® Excel, this book examines the applications of complex variables. Implementation of the included problems in Excel eliminates the “black box” nature of more advanced computer software and programming languages and therefore the reader has the chance to become more familiar with the underlying mathematics of the complex variable problems. This book consists of two parts. In Part I, several topics are covered that one would expect to find in an introductory text on complex variables. These topics include an overview of complex numbers, functions of a complex variable, and the Cauchy integral formula. In particular, attention is given to the study of analytic complex variable functions. This attention is warranted because of the property that the real and imaginary parts of an analytic complex variable function can be used to solve the Laplace partial differential equation (PDE). Laplace's equation is ubiquitous throughout science and engineering as it can be used to model the steady-state conditions of several important transport processes including heat transfer, soil-water flow, electrostatics, and ideal fluid flow, among others. In Part II, a specialty application of complex variables known as the Complex Variable Boundary Element Method (CVBEM) is examined. CVBEM is a numerical method used for solving boundary value problems governed by Laplace's equation. This part contains a detailed description of the CVBEM and a guide through each step of constructing two CVBEM programs in Excel. The writing of these programs is the culminating event of the book. Students of complex variables and anyone with an interest in a novel method for approximating potential functions using the principles of complex variables are the intended audience for this book. The Microsoft Excel applications (including simple programs as well as the CVBEM program) covered will also be of interest in the industry, as these programs are accessible to anybody with Microsoft Office. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open …
Belmont Forum Adopts Open Data Principles for Environme…
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data …
Belmont Forum Data Accessibility Statement an…
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
