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There are a limited number of intelligence analysis books available on the market. Intelligence Analysis Fundamentals is an introductory, accessible text for college level undergraduate and graduate level courses. While the principles outlined in the book largely follow military intelligence terminology and practice, concepts are presented to correlate with intelligence gathering and analysis performed in law enforcement, homeland security, and corporate and business security roles. Most of the existing texts on intelligence gathering and analysis focus on specific types of intelligence such as ‘target centric’ intelligence, and many of these, detail information from a position of prior knowledge. In other words, they are most valuable to the consumer who has a working-level knowledge of the subject. The book is general enough in nature that a lay student—interested in pursuing a career in intelligence, Homeland Security, or other related areas of law enforcement—will benefit from it. No prior knowledge of intelligence analysis, functions, or operations is assumed. Chapters illustrate methods and techniques that, over the years, have consistently demonstrate results, superior to those achieved with other means. Chapters describe such analytical methods that are most widely used in the intelligence community and serve as recognized standards and benchmarks in the practice of intelligence analysis. All techniques have been selected for inclusion for their specific application to homeland security, criminal investigations, and intelligence operations. Uses numerous hands-on activities—that can easily be modified by instructors to be more or less challenging depending on the course level—to reinforce concepts As current and active members of the intelligence community, the authors draw on their decades of experience in intelligence to offer real-world examples to illustrate concepts All methodologies reflect the latest trends in the intelligence communities assessment, analysis, and reporting processes with all presented being open source, non-classified information As such, the non-sensitive information presented is appropriate—and methods applicable—for use for education and training overseas and internationally Military-style collection and analysis methods are the primary ones presented, but all are directly correlated intelligence to current concepts, functions and practices within Homeland Security and the law communities Covers the counterterrorism environment where joint operations and investigative efforts combine military, private sector, and law enforcement action and information sharing The book will be a welcome addition to the body of literature available and a widely used reference for professionals and students alike.
There are a limited number of intelligence analysis books available on the market. Intelligence Analysis Fundamentals is an introductory, accessible text for college level undergraduate and graduate level courses. While the principles outlined in the book largely follow military intelligence terminology and practice, concepts are presented to correlate with intelligence gathering and analysis performed in law enforcement, homeland security, and corporate and business security roles. Most of the existing texts on intelligence gathering and analysis focus on specific types of intelligence such as ‘target centric’ intelligence, and many of these, detail information from a position of prior knowledge. In other words, they are most valuable to the consumer who has a working-level knowledge of the subject. The book is general enough in nature that a lay student—interested in pursuing a career in intelligence, Homeland Security, or other related areas of law enforcement—will benefit from it. No prior knowledge of intelligence analysis, functions, or operations is assumed. Chapters illustrate methods and techniques that, over the years, have consistently demonstrate results, superior to those achieved with other means. Chapters describe such analytical methods that are most widely used in the intelligence community and serve as recognized standards and benchmarks in the practice of intelligence analysis. All techniques have been selected for inclusion for their specific application to homeland security, criminal investigations, and intelligence operations. Uses numerous hands-on activities—that can easily be modified by instructors to be more or less challenging depending on the course level—to reinforce concepts As current and active members of the intelligence community, the authors draw on their decades of experience in intelligence to offer real-world examples to illustrate concepts All methodologies reflect the latest trends in the intelligence communities assessment, analysis, and reporting processes with all presented being open source, non-classified information As such, the non-sensitive information presented is appropriate—and methods applicable—for use for education and training overseas and internationally Military-style collection and analysis methods are the primary ones presented, but all are directly correlated intelligence to current concepts, functions and practices within Homeland Security and the law communities Covers the counterterrorism environment where joint operations and investigative efforts combine military, private sector, and law enforcement action and information sharing The book will be a welcome addition to the body of literature available and a widely used reference for professionals and students alike.
This book presents a comprehensive and systematic introduction to transforming process-oriented data into information about the underlying business process, which is essential for all kinds of decision-making. To that end, the authors develop step-by-step models and analytical tools for obtaining high-quality data structured in such a way that complex analytical tools can be applied. The main emphasis is on process mining and data mining techniques and the combination of these methods for process-oriented data. After a general introduction to the business intelligence (BI) process and its constituent tasks in chapter 1, chapter 2 discusses different approaches to modeling in BI applications. Chapter 3 is an overview and provides details of data provisioning, including a section on big data. Chapter 4 tackles data description, visualization, and reporting. Chapter 5 introduces data mining techniques for cross-sectional data. Different techniques for the analysis of temporal data are then detailed in Chapter 6. Subsequently, chapter 7 explains techniques for the analysis of process data, followed by the introduction of analysis techniques for multiple BI perspectives in chapter 8. The book closes with a summary and discussion in chapter 9. Throughout the book, (mostly open source) tools are recommended, described and applied; a more detailed survey on tools can be found in the appendix, and a detailed code for the solutions together with instructions on how to install the software used can be found on the accompanying website. Also, all concepts presented are illustrated and selected examples and exercises are provided. The book is suitable for graduate students in computer science, and the dedicated website with examples and solutions makes the book ideal as a textbook for a first course in business intelligence in computer science or business information systems. Additionally, practitioners and industrial developers who are interested in the concepts behind business intelligence will benefit from the clear explanations and many examples.
Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basis function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzzy integrals Examines evolutionary optimization, evolutionary learning and problem solving, and collective intelligence Includes end-of-chapter practice problems that will help readers apply methods and techniques to real-world problems Fundamentals of Computational intelligence is written for advanced undergraduates, graduate students, and practitioners in electrical and computer engineering, computer science, and other engineering disciplines.
In this seminal work, published by the C.I.A. itself, produced by Intelligence veteran Richards Heuer discusses three pivotal points. First, human minds are ill-equipped ("poorly wired") to cope effectively with both inherent and induced uncertainty. Second, increased knowledge of our inherent biases tends to be of little assistance to the analyst. And lastly, tools and techniques that apply higher levels of critical thinking can substantially improve analysis on complex problems.
In this Second Edition of Structured Analytic Techniques for Intelligence Analysis, authors Richards J. Heuer Jr. and Randolph H. Pherson showcase fifty-five structured analytic techniques—five new to this edition—that represent the most current best practices in intelligence, law enforcement, homeland security, and business analysis.
With the exponential growth in the intelligence field in the last few years, the profession has grown much larger and its mission more complex. Government and private sector security agencies have recruited intelligence analysts to process what has become a voluminous amount of raw information flowing into these agencies' data collection systems. Unfortunately, there is an unmet need for analysts who are able to process these data. For this reason there are a growing number of colleges and universities that offer intelligence training so that candidates for analyst positions can take-up their duties without protracted on-the-job instruction. Handbook of Scientific Methods of Inquiry for Intelligence Analysis offers students in such courses a way of gaining the analytic skills essential to undertake intelligence work. This book acquaints students and analysts with how intelligence fits into the larger research framework. It covers not only the essentials of applied research but also explains the function, structure, and operational methods specifically involved in intelligence work. It looks at how analysts work with classified information in a security conscious environment, as well as obtaining data via covert methods. Students are left with little doubt about what intelligence is and how it is developed using scientific methods of inquiry.
This book offers a vast conceptual and theoretical exploration of the ways intelligence analysis must change in order to succeed against today's most dangerous combatants and most complex irregular theatres of conflict. Intelligence Analysis: How to Think in Complex Environments fills a void in the existing literature on contemporary warfare by examining the theoretical and conceptual foundations of effective modern intelligence analysis—the type of analysis needed to support military operations in modern, complex operational environments. This volume is an expert guide for rethinking intelligence analysis and understanding the true nature of the operational environment, adversaries, and most importantly, the populace. Intelligence Analysis proposes substantive improvements in the way the U.S. national security system interprets intelligence, drawing on the groundbreaking work of theorists ranging from Carl von Clauswitz and Sun Tzu to M. Mitchell Waldrop, General David Petraeus, Richards Heuer, Jr., Orson Scott Card, and others. The new ideas presented here will help the nation to amass a formidable, cumulative intelligence power, with distinct advantages over any and all adversaries of the future regardless of the level of war or type of operational environment.
Since 9/11, the needs of intelligence agencies as well as the missions they conduct have increased in number, size, and complexity. As such, government and private security agencies are recruiting staff to analyze the vast amount of data collected in these missions. This textbook offers a way of gaining the analytic skills essential to undertake intelligence work. It acquaints students and analysts with how intelligence fits into the larger research framework. It covers not only the essentials of applied research, but also the function, structure, and operational methods specifically involved in intelligence work. It looks at how analysts work with classified information in a security conscious environment as well as obtain data via covert methods. Students are left with little doubt about what intelligence is and how it is developed using scientific methods of inquiry. This revised edition of the popular text has been expanded and updated significantly.
This comprehensive reference text discusses the fundamental concepts of artificial intelligence and its applications in a single volume. Artificial Intelligence: Fundamentals and Applications presents a detailed discussion of basic aspects and ethics in the field of artificial intelligence and its applications in areas, including electronic devices and systems, consumer electronics, automobile engineering, manufacturing, robotics and automation, agriculture, banking, and predictive analysis. Aimed at senior undergraduate and graduate students in the field of electrical engineering, electronics engineering, manufacturing engineering, pharmacy, and healthcare, this text: Discusses advances in artificial intelligence and its applications. Presents the predictive analysis and data analysis using artificial intelligence. Covers the algorithms and pseudo-codes for different domains. Discusses the latest development of artificial intelligence in the field of practical speech recognition, machine translation, autonomous vehicles, and household robotics. Covers the applications of artificial intelligence in fields, including pharmacy and healthcare, electronic devices and systems, manufacturing, consumer electronics, and robotics.