![]() |
Welcome to Loot.co.za!
Sign in / Register |Wishlists & Gift Vouchers |Help | Advanced search
|
Your cart is empty |
||
|
Books > Computing & IT > Applications of computing
This unique, new book covers the whole field of electronic warfare modeling and simulation at a systems level, including chapters that describe basic electronic warfare (EW) concepts. Written by a well-known expert in the field with more than 24 years of experience, the book explores EW applications and techniques and the radio frequency spectrum. A detailed resource for entry-level engineering personnel in EW, military personnel with no radio or communications engineering background, technicians and software professionals, the work explains the basic concepts required for modeling and simulation that today's professionals need to understand. Practitioners find clear explanations of important mathematical concepts, such as decibel notation and spherical trigonometry, necessary for modeling and simulation. Moreover, the book describes specific types of EW equipment, how they work and how each is mathematically modeled.
The book is devoted to the analysis of big data in order to extract from these data hidden patterns necessary for making decisions about the rational behavior of complex systems with the different nature that generate this data. To solve these problems, a group of new methods and tools is used, based on the self-organization of computational processes, the use of crisp and fuzzy cluster analysis methods, hybrid neural-fuzzy networks, and others. The book solves various practical problems. In particular, for the tasks of 3D image recognition and automatic speech recognition large-scale neural networks with applications for Deep Learning systems were used. Application of hybrid neuro-fuzzy networks for analyzing stock markets was presented. The analysis of big historical, economic and physical data revealed the hidden Fibonacci pattern about the course of systemic world conflicts and their connection with the Kondratieff big economic cycles and the Schwabe-Wolf solar activity cycles. The book is useful for system analysts and practitioners working with complex systems in various spheres of human activity.
This book contains selected papers from SEB-18, the Tenth International Conference on Sustainability in Energy and Buildings, which was organised by KES International and Griffith University and held in Gold Coast, Australia in June 2018. SEB-18 invited contributions on a range of topics related to sustainable buildings and renewable energy, and explored innovative topics regarding intelligent buildings and cities. Applicable areas included the sustainable design and of buildings, neighbourhoods and cities (built and natural environment); optimisation and modelling techniques; smart energy systems for smart cities; green information communications technology; and a broad range of solar, wind, wave and other renewable energy topics. The aim of the conference was to bring together researchers and government and industry professionals to discuss the future of energy in buildings, neighbourhoods and cities from a theoretical, practical, implementation and simulation perspective. In addition, SEB-18 offered an exciting opportunity to present, interact, and learn about the latest research in Sustainability in Energy and Buildings.
This book highlights the emerging field of intelligent computing and developing smart systems. It includes chapters discussing the outcome of challenging research related to distributed computing, smart machines and their security related research, and also covers next-generation communication techniques and the networking technologies that have the potential to build the future communication infrastructure. Bringing together computing, communications and other aspects of intelligent and smart computing, it contributes to developing a roadmap for future research on intelligent systems.
As it is with building a house, most of the work necessary to build a data warehouse is neither visible nor obvious when looking at the completed product. While it may be easy to plan for a data warehouse that incorporates all the right concepts, taking the steps needed to create a warehouse that is as functional and user-friendly as it is theoretically sound, is not especially easy. That's the challenge that Building and Maintaininga Data Warehouse answers. Based on a foundation of industry-accepted principles, this work provides an easy-to-follow approach that is cohesive and holistic. By offering the perspective of a successful data warehouse, as well as that of a failed one, this workdetails those factors that must be accomplished and those that are best avoided. Organized to logically progress from more general to specific information, this valuable guide: Presents areas of a data warehouse individually and in sequence, showing how each piece becomes a working part of the whole Examines the concepts and principles that are at the foundation of every successful data warehouse Explains how to recognize and attend to problematic gaps in an established data warehouse Provides the big picture perspective that planners and executives require Those considering the planning and creation of a data warehouse, as well as those who've already built one will profit greatly from the insights garnered by the author during his years of creating and gathering information on state-of-the-art data warehouses that are accessible, convenient, and reliable.
This Festschrift is a tribute to Susan Stepney's ideas and achievements in the areas of computer science, formal specifications and proofs, complex systems, unconventional computing, artificial chemistry, and artificial life. All chapters were written by internationally recognised leaders in computer science, physics, mathematics, and engineering. The book shares fascinating ideas, algorithms and implementations related to the formal specification of programming languages and applications, behavioural inheritance, modelling and analysis of complex systems, parallel computing and non-universality, growing cities, artificial life, evolving artificial neural networks, and unconventional computing. Accordingly, it offers an insightful and enjoyable work for readers from all walks of life, from undergraduate students to university professors, from mathematicians, computers scientists and engineers to physicists, chemists and biologists.
A firewall is as good as its policies and the security of its VPN
connections. The latest generation of firewalls offers a dizzying
array of powerful options; they key to success is to write concise
policies that provide the appropriate level of access while
maximizing security.
This book shows how the web-based PhysGL programming environment (http://physgl.org) can be used to teach and learn elementary mechanics (physics) using simple coding exercises. The book's theme is that the lessons encountered in such a course can be used to generate physics-based animations, providing students with compelling and self-made visuals to aid their learning. Topics presented are parallel to those found in a traditional physics text, making for straightforward integration into a typical lecture-based physics course. Users will appreciate the ease at which compelling OpenGL-based graphics and animations can be produced using PhysGL, as well as its clean, simple language constructs. The author argues that coding should be a standard part of lower-division STEM courses, and provides many anecdotal experiences and observations, that include observed benefits of the coding work.
The recent advancements in the machine learning paradigm have various applications, however, it has shown significant results in the field of medical data analysis. The results are highly accurate and are comparable to human experts. The various research has proved the high accuracy of deep learning algorithms and has become a standard choice for analysing medical data, especially medical images, video, and electronic health records. Deep learning methods applied to electronic health records are contributing to understanding the evolution of chronic diseases and predicting the risk of developing those diseases. Researchers in industry, hospitals, and academia have published hundreds of scientific contributions in this area during a pandemic. This book is an ideal and relevant source of content for data science and healthcare professionals who want to delve into complex deep learning algorithms, calibrate models, and improve the predictions of the trained model on medical imaging. Primary audiences for this book are professionals and researchers in the fields of data science, machine learning, deep learning, and AI. Also academicians, healthcare professionals, or anyone who may have a keen interest in how the machine and deep learning algorithms are helping in the identification of solutions to medical sensor/image data analysis, event detection, segmentation, and abnormality detection, object/lesion classification, organ/region/landmark localization, object/lesion detection, organ/substructure segmentation, lesion segmentation, and medical image registration. The variety of readers in the fields of government, consulting, healthcare professionals, as well as the readers from all the social strata, can also be benefited from this book to improve understanding of the cutting-edge theory, technologies, methodologies, and applications of deep Learning algorithms for medical care.
This book proposes neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform generation, filtering, equalization, signals from arrays of sensors, and perturbations in the automatic control of industrial production processes. It also discusses the drastic changes in financial, economic, and work processes that are currently being experienced by the computational and engineering sciences community. Addresses key aspects, such as the integration of neural algorithms and procedures for the recognition, the analysis and detection of dynamic complex structures and the implementation of systems for discovering patterns in data, the book highlights the commonalities between computational intelligence (CI) and information and communications technologies (ICT) to promote transversal skills and sophisticated processing techniques. This book is a valuable resource for a. The academic research community b. The ICT market c. PhD students and early stage researchers d. Companies, research institutes e. Representatives from industry and standardization bodies
Advances in Computers remains at the forefront in presenting the
new developments in the ever-changing field of information
technology. Since 1960, Advances in Computers has chronicled the
constantly shifting theories and methods of this technology that
greatly shape our lives today.
Pattern Recognition has a long history of applications to data analysis in business, military and social economic activities. While the aim of pattern recognition is to discover the pattern of a data set, the size of the data set is closely related to the methodology one adopts for analysis. Intelligent Data Analysis: Developing New Methodologies Through Pattern Discovery and Recovery tackles those data sets and covers a variety of issues in relation to intelligent data analysis so that patterns from frequent or rare events in spatial or temporal spaces can be revealed. This book brings together current research, results, problems, and applications from both theoretical and practical approaches.
Multirate signal processing techniques are widely used in many areas of modern engineering such as communications, digital audio, measurements, image and signal processing, speech processing, and multimedia.""Multirate Filtering for Digital Signal Processing: MATLAB Applications"" covers basic and advanced approaches in the design and implementation of multirate filtering. This authoritative volume considers the role of filters in multirate systems, provides efficient solutions of finite and infinite impulse response filters for sampling rate conversion, and discusses examples of multirate multilevel filter banks, offering a must-have book for practitioners and scholars in multirate signal processing.
Talk to just about any Information Technology (IT) executive today and you're likely to hear the same complaint: "Even though we have invested millions of dollars each year in technical infrastructure and support, we don't get the results we expect." The focus of IT management over the past several decades has been on maximizing the benefit that comes from IT investments. Particular attention is paid to finding the right hardware, software, networks, and processes to allow IT to contribute to the bottom line of the business. And still, with all of this focus, IT organizations find themselves unable to meet the demands of their clients. Perhaps a shift in focus is needed. IT PEOPLE: Doing More With Less shifts the focus to the IT people. Because while it is right to focus on getting the hardware, software, networks, and processes right, people are the resources that ultimately make a difference in getting results and meeting the demands of clients. And since people costs are often the largest part of the IT budgets, and our focus has been elsewhere, it could be that a focus on IT people is long overdue. This book is intended for every IT professional (management and individual contributors) who faces the constant challenge of performing a big job with ever-shrinking departmental resources. Whether you are a manager or an individual technician, this book is for you. It will help you improve your ability to plan your work and, meet your commitments while being an effective political actor. Our aim in this book is to provide you with a tool that will not only help you deliver greater value to your organization, but do so in a way that provides a greater degree of job satisfaction andquality of life. IT PEOPLE: Doing More With Less is intended as a practical tool, not a theoretical book. The content of the book comes from the experiences of the authors, each of whom has spent years managing IT organizations and consulting with clients around the worl
Investigative Data Mining for Security and Criminal Detection is
the first book to outline how data mining technologies can be used
to combat crime in the 21st century. It introduces security
managers, law enforcement investigators, counter-intelligence
agents, fraud specialists, and information security analysts to the
latest data mining techniques and shows how they can be used as
investigative tools. Readers will learn how to search public and
private databases and networks to flag potential security threats
and root out criminal activities even before they occur. Key Features:
The book gathers the chapters of Cognitive InfoCommunication research relevant to a variety of application areas, including data visualization, emotion expression, brain-computer interfaces or speech technologies. It provides an overview of the kind of cognitive capabilities that are being analyzed and developed. Based on this common ground, it may become possible to see new opportunities for synergy among disciplines that were heretofore viewed as being separate. Cognitive InfoCommunication begins by modeling human cognitive states and aptitudes in order to better understand what the user of a system is capable of comprehending and doing. The patterns of exploration and the specific tools that are described can certainly be of interest and of great relevance for all researchers who focus on modeling human states and aptitudes. This innovative research area provides answers to the latest challenges in influence of cognitive states and aptitudes in order to facilitate learning or generally improve performance in certain cognitive tasks such as decision making. Some capabilities are purely human, while others are purely artificial, but in general this distinction is rarely clear-cut. Therefore, when discussing new human cognitive capabilities, the technological background which makes them possible cannot be neglected, and indeed often plays a central role. This book highlights the synergy between various fields that are perfectly fit under the umbrella of CogInfoCom and contribute to understanding and developing new, human-artificial intelligence hybrid capabilities. These, merged capabilities are currently appearing, and the importance of the role they play in everyday life are unique to the cognitive entity generation that is currently growing up.
Space and time are inextricably linked. Reasoning about space often involves reasoning about change in spatial configurations. Qualitative spatial information theory encompasses spatial as well as temporal representation and reasoning. Qualitative Spatio-Temporal Representation and Reasoning: Trends and Future Directions is a contribution to the emerging discipline of qualitative spatial information theory within artificial intelligence. This collection of research covers both theory and application-centric research and provides a comprehensive perspective on the emerging area of qualitative spatio-temporal representation and reasoning. This revolutionary new field is increasingly becoming a core issue within mobile computing, GIS/spatial information systems, databases, computer vision as well as knowledge discovery and data mining.
This book provides an insight into recent technological trends and innovations in solutions and platforms to improve mobility of visually impaired people. The authors' goal is to help to contribute to the social and societal inclusion of the visually impaired. The book's topics include, but are not limited to, obstacle detection systems, indoor and outdoor navigation, transportation sustainability systems, and hardware/devices to aid visually impaired people. The book has a strong focus on practical applications tested in a real environment. Applications include city halls, municipalities, and companies that must keep up to date with recent trends in platforms, methodologies and technologies to promote urban mobility. Also discuss are broader realms including education, health, electronics, tourism, and transportation. Contributors include a variety of researchers and practitioners around the world.
Multimedia security has become a major research topic, yielding numerous academic papers in addition to many watermarking-related companies. In this emerging area, there are many challenging research issues that deserve sustained studying towards an effective and practical system. Multimedia Security: Steganography and Digital Watermarking Techniques for Protection of Intellectual Property explores the myriad of issues regarding multimedia security. This book covers various issues, including perceptual fidelity analysis, image, audio, and 3D mesh object watermarking, medical watermarking, error detection (authentication) and concealment, fingerprinting, digital signature and digital right management.
This book offers a comprehensive overview of the challenges in hydrological modeling. Hydrology, on both a local and global scale, has undergone dramatic changes, largely due to variations in climate, population growth and the associated land-use and land-cover changes. Written by experts in the field, the book provides decision-makers with a better understanding of the science, impacts, and consequences of these climate and land-use changes on hydrology. Further, offering insights into how the changing behavior of hydrological processes, related uncertainties and their evolution affect the modeling process, it is of interest for all researchers and practitioners using hydrological modeling.
Order affects the results you get: Different orders of presenting material can lead to qualitatively and quantitatively different learning outcomes. These differences occur in both natural and artificial learning systems. In Order to Learn shows how order effects are crucial in human learning, instructional design, machine learning, and both symbolic and connectionist cognitive models. Each chapter explains a different aspect of how the order in which material is presented can strongly influence what is learned by humans and theoretical models of learning in a variety of domains. In addition to data, models are provided that predict and describe order effects and analyze how and when they will occur. The introductory and concluding chapters compile suggestions for improving learning through better sequences of learning materials, including how to take advantage of order effects that encourage learning and how to avoid order effects that discourage learning. Each chapter also highlights questions that may inspire further research. Taken together, these chapters show how order effects in different areas can and do inform each other. In Order to Learn will be of interest to researchers and students in cognitive science, education, machine learning. |
You may like...
Dynamic Web Application Development…
David Parsons, Simon Stobart
Paperback
Discovering Computers - Digital…
Misty Vermaat, Mark Ciampa, …
Paperback
Discovering Computers, Essentials…
Susan Sebok, Jennifer Campbell, …
Paperback
|