Intelligent Data Mining In Law Enforcement Analytics
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Intelligent Data Mining In Law Enforcement Analytics
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Author : Paolo Massimo Buscema
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-11-28
Intelligent Data Mining In Law Enforcement Analytics written by Paolo Massimo Buscema and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-28 with Social Science categories.
This book provides a thorough summary of the means currently available to the investigators of Artificial Intelligence for making criminal behavior (both individual and collective) foreseeable, and for assisting their investigative capacities. The volume provides chapters on the introduction of artificial intelligence and machine learning suitable for an upper level undergraduate with exposure to mathematics and some programming skill or a graduate course. It also brings the latest research in Artificial Intelligence to life with its chapters on fascinating applications in the area of law enforcement, though much is also being accomplished in the fields of medicine and bioengineering. Individuals with a background in Artificial Intelligence will find the opening chapters to be an excellent refresher but the greatest excitement will likely be the law enforcement examples, for little has been done in that area. The editors have chosen to shine a bright light on law enforcement analytics utilizing artificial neural network technology to encourage other researchers to become involved in this very important and timely field of study.
Investigative Data Mining For Security And Criminal Detection
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Author : Jesus Mena
language : en
Publisher: Butterworth-Heinemann
Release Date : 2003
Investigative Data Mining For Security And Criminal Detection written by Jesus Mena and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Business & Economics categories.
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Intelligent Data Mining
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Author : Da Ruan
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-08-24
Intelligent Data Mining written by Da Ruan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-08-24 with Mathematics categories.
"Intelligent Data Mining – Techniques and Applications" is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications. The main objective of this book is to gather a number of peer-reviewed high quality contributions in the relevant topic areas. The focus is especially on those chapters that provide theoretical/analytical solutions to the problems of real interest in intelligent techniques possibly combined with other traditional tools, for data mining and the corresponding applications to engineers and managers of different industrial sectors. Academic and applied researchers and research students working on data mining can also directly benefit from this book.
The Cambridge Handbook Of Policing In The United States
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Author : Tamara Rice Lave
language : en
Publisher: Cambridge University Press
Release Date : 2019-07-04
The Cambridge Handbook Of Policing In The United States written by Tamara Rice Lave and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-04 with Law categories.
A comprehensive collection on police and policing, written by experts in political theory, sociology, criminology, economics, law, public health, and critical theory.
Context Aware Machine Learning And Mobile Data Analytics
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Author : Iqbal Sarker
language : en
Publisher:
Release Date : 2021
Context Aware Machine Learning And Mobile Data Analytics written by Iqbal Sarker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
This book offers a clear understanding of the concept of context-aware machine learning including an automated rule-based framework within the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making. Thus, we have bestowed a comprehensive study on this topic that explores multi-dimensional contexts in machine learning modeling, context discretization with time-series modeling, contextual rule discovery and predictive analytics, recent-pattern or rule-based behavior modeling, and their usefulness in various context-aware intelligent applications and services. The presented machine learning-based techniques can be employed in a wide range of real-world application areas ranging from personalized mobile services to security intelligence, highlighted in the book. As the interpretability of a rule-based system is high, the automation in discovering rules from contextual raw data can make this book more impactful for the application developers as well as researchers. Overall, this book provides a good reference for both academia and industry people in the broad area of data science, machine learning, AI-Driven computing, human-centered computing and personalization, behavioral analytics, IoT and mobile applications, and cybersecurity intelligence.
Constitutional Challenges In The Algorithmic Society
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Author : Hans-W. Micklitz
language : en
Publisher: Cambridge University Press
Release Date : 2021-12-02
Constitutional Challenges In The Algorithmic Society written by Hans-W. Micklitz and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-02 with Law categories.
New technologies have always challenged the social, economic, legal, and ideological status quo. Constitutional law is no less impacted by such technologically driven transformations, as the state must formulate a legal response to new technologies and their market applications, as well as the state's own use of new technology. In particular, the development of data collection, data mining, and algorithmic analysis by public and private actors present unique challenges to public law at the doctrinal as well as the theoretical level. This collection, aimed at legal scholars and practitioners, describes the constitutional challenges created by the algorithmic society. It offers an important synthesis of the state of play in law and technology studies, addressing the challenges for fundamental rights and democracy, the role of policy and regulation, and the responsibilities of private actors. This title is also available as Open Access on Cambridge Core.
The Rise Of Big Data Policing
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Author : Andrew G. Ferguson
language : en
Publisher: NYU Press
Release Date : 2017-10-03
The Rise Of Big Data Policing written by Andrew G. Ferguson and has been published by NYU Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-03 with Law categories.
Winner, 2018 Law & Legal Studies PROSE Award The consequences of big data and algorithm-driven policing and its impact on law enforcement In a high-tech command center in downtown Los Angeles, a digital map lights up with 911 calls, television monitors track breaking news stories, surveillance cameras sweep the streets, and rows of networked computers link analysts and police officers to a wealth of law enforcement intelligence. This is just a glimpse into a future where software predicts future crimes, algorithms generate virtual “most-wanted” lists, and databanks collect personal and biometric information. The Rise of Big Data Policing introduces the cutting-edge technology that is changing how the police do their jobs and shows why it is more important than ever that citizens understand the far-reaching consequences of big data surveillance as a law enforcement tool. Andrew Guthrie Ferguson reveals how these new technologies —viewed as race-neutral and objective—have been eagerly adopted by police departments hoping to distance themselves from claims of racial bias and unconstitutional practices. After a series of high-profile police shootings and federal investigations into systemic police misconduct, and in an era of law enforcement budget cutbacks, data-driven policing has been billed as a way to “turn the page” on racial bias. But behind the data are real people, and difficult questions remain about racial discrimination and the potential to distort constitutional protections. In this first book on big data policing, Ferguson offers an examination of how new technologies will alter the who, where, when and how we police. These new technologies also offer data-driven methods to improve police accountability and to remedy the underlying socio-economic risk factors that encourage crime. The Rise of Big Data Policing is a must read for anyone concerned with how technology will revolutionize law enforcement and its potential threat to the security, privacy, and constitutional rights of citizens. Read an excerpt and interview with Andrew Guthrie Ferguson in The Economist.
Computational Intelligent Data Analysis For Sustainable Development
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Author : Ting Yu
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Computational Intelligent Data Analysis For Sustainable Development written by Ting Yu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Business & Economics categories.
Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development presents novel methodologies for automatically processing these types of data to support rational decision making for sustainable development. Through numerous case studies and applications, it illustrates important data analysis methods, including mathematical optimization, machine learning, signal processing, and temporal and spatial analysis, for quantifying and describing sustainable development problems. With a focus on integrated sustainability analysis, the book presents a large-scale quadratic programming algorithm to expand high-resolution input-output tables from the national scale to the multinational scale to measure the carbon footprint of the entire trade supply chain. It also quantifies the error or dispersion between different reclassification and aggregation schemas, revealing that aggregation errors have a high concentration over specific regions and sectors. The book summarizes the latest contributions of the data analysis community to climate change research. A profuse amount of climate data of various types is available, providing a rich and fertile playground for future data mining and machine learning research. The book also pays special attention to several critical challenges in the science of climate extremes that are not handled by the current generation of climate models. It discusses potential conceptual and methodological directions to build a close integration between physical understanding, or physics-based modeling, and data-driven insights. The book then covers the conservation of species and ecologically valuable land. A case study on the Pennsylvania Dirt and Gravel Roads Program demonstrates that multiple-objective linear programming is a more versatile and efficient approach than the widely used benefit targeting selection process. Moving on to renewable energy and the need for smart grids, the book explores how the ongoing transformation to a sustainable energy system of renewable sources leads to a paradigm shift from demand-driven generation to generation-driven demand. It shows how to maximize renewable energy as electricity by building a supergrid or mixing renewable sources with demand management and storage. It also presents intelligent data analysis for real-time detection of disruptive events from power system frequency data collected using an existing Internet-based frequency monitoring network as well as evaluates a set of computationally intelligent techniques for long-term wind resource assessment. In addition, the book gives an example of how temporal and spatial data analysis tools are used to gather knowledge about behavioral data and address important social problems such as criminal offenses. It also applies constraint logic programming to a planning problem: the environmental and social impact assessment of the regional energy plan of the Emilia-Romagna region of Italy. Sustainable development problems, such as global warming, resource shortages, global species loss, and pollution, push researchers to create powerful data analysis approaches that analysts can then use to gain insight into these issues to support rational decision making. This volume shows both the data analysis and sustainable development communities how to use intelligent data analysis tools to address practical problems and encourages researchers to develop better methods.
Urban Coastal Area Conflicts Analysis Methodology
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Author : Armando Montanari
language : en
Publisher: Sapienza Università Editrice
Release Date : 2013-12-18
Urban Coastal Area Conflicts Analysis Methodology written by Armando Montanari and has been published by Sapienza Università Editrice this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-18 with Business & Economics categories.
This volume is the completed section of the process of analytical research and methodological comparisons undertaken by SECOA, a 48-month research project selected and funded by the EU under the FP7 program. Hence, while scientifically autonomous, the volume is a natural link between the different phases of analysis within SECOA, i.e. Work Packages (WPs) 1-5, and the interpretive and predictive values that are being drawn up by WPs 7 and 8. Within the overall scope of SECOA's research activity, this volume's task was to supply answers to questions that will undergo further study by research groups. These groups will subsequently have to create methods and tools to identify the most suitable policies to effectively manage environmental conflicts, use fragile and rare resources more efficiently, and develop administrative structures capable of dealing with the needs of a continuously evolving society (the wisdom stage). It was also deemed necessary to construct possible alternative scenarios in order to contribute to an enhanced vision of sustainable urban development in coastal areas (the understanding stage). The findings of the research discussed in this volume are to be used to understand the relationships between the variables collected in the previous phases (WPs 1, 2, 3 and 4) of SECOA.
Cybersecurity And Data Science Innovations For Sustainable Development Of Heicc
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Author : Thangavel Murugan
language : en
Publisher: CRC Press
Release Date : 2025-01-30
Cybersecurity And Data Science Innovations For Sustainable Development Of Heicc written by Thangavel Murugan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-30 with Computers categories.
Cybersecurity and Data Science Innovations for Sustainable Development of HEICC: Healthcare, Education, Industry, Cities, and Communities brings together a collection of chapters that explore the intersection of cybersecurity, data science, and sustainable development across key sectors: healthcare, education, industry, cities, and communities. It delves into cybersecurity advancements and examines how innovations in cybersecurity are shaping the landscape of healthcare, education, industry, and urban environments. Data science advancements take center stage, showcasing the transformative power of data analytics in improving outcomes across HEICC sectors. Whether it’s optimizing resource allocation in healthcare, protecting patient privacy, personalizing learning experiences in education, enhancing efficiency in industry, or fostering sustainable development in cities and communities, data science offers unprecedented opportunities for innovation and progress. Key points: Healthcare system security and privacy, protecting patient data, and enabling development of novel healthcare solutions Securing educational data, improving online learning security, and harnessing data analytics for tailored education approaches Manufacturing, finance, and transportation. Diving into critical infrastructure security, detecting and mitigating cyber threats, and using data‐driven insights for better industrial operations Helping cities and communities develop sustainably, smart city security challenges, data privacy in urban environments, data analytics for urban planning, and community cybersecurity awareness This book serves as a comprehensive guide for researchers, practitioners, policymakers, and stakeholders navigating the complex landscape of cybersecurity and data science in the pursuit of sustainable development across HEICC domains.