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Vastutah kampyootar ke bina to ham aaj ke yug mein jeena soch bhee nahin sakate.(Aided with actual photographs, readable screenshots, clear charts and tables, this book on MS Office introduces the concept of Word Processing, Microsoft Word, Microsoft, how to work with Documents, Editing, Formatting Documents....\u003c\/p\u003e","brand":"V\u0026S Publishers","offers":[{"title":"Default Title","offer_id":51597531742487,"sku":"7b666c18-a3de-4c49-923c-c0d3ffcd096c","price":395.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0679\/6918\/8119\/files\/9789371194891_3323073.png?v=1763194366"},{"product_id":"foundations-of-data-exchange-9781107779396","title":"Foundations of Data Exchange","description":"\u003cp\u003eProvides a summary of the key developments of a decade of research into the area of data exchange.\u003c\/p\u003e","brand":"Gardners","offers":[{"title":"Default Title","offer_id":52828079849751,"sku":null,"price":3503.36,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0679\/6918\/8119\/files\/9781107779396_f9c4abe0-8b33-4f21-916b-786ef1e43fb0.jpg?v=1780659197"},{"product_id":"data-intensive-computing-9781139793049","title":"Data-Intensive Computing","description":"\u003cp\u003eDescribes principles of the emerging field of data-intensive computing, along with methods for designing, managing and analyzing the big data sets of today.\u003c\/p\u003e","brand":"Gardners","offers":[{"title":"Default Title","offer_id":52871310868759,"sku":null,"price":10471.19,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0679\/6918\/8119\/files\/9781139793049.jpg?v=1780901626"},{"product_id":"web3-9781009375634","title":"Web3","description":"\u003cp\u003eWeb3\u003c\/p\u003e","brand":"Gardners","offers":[{"title":"Default Title","offer_id":52887908122903,"sku":null,"price":5629.15,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0679\/6918\/8119\/files\/9781009375634.jpg?v=1780908130"},{"product_id":"studies-in-computational-intelligence-9783031055010","title":"Studies in Computational Intelligence","description":"\u003cp\u003eThe BCI technology finds newer and newer implementations. Year by year, the number of publications in this field grows exponentially. This book attempts to describe the implementation of the brain-computer technology based on both STM32 and Arduino microcontrollers. In addition, the application of BCI technology in the field of intelligent houses, robotic lines as well as in the field of bionic prostheses was presented. One of the chapters of the monograph also discusses the issue of fMRI in the context of the possibility of analyzing images made as part of fMRI through solutions based on machine learning. A practical implementation of the TensorFlow framework was presented. The fMRI technique is also often implemented in BCI solutions. The conducted literature studies show that the technology of BCI is undoubtedly a technology of the future. However, there is a need for continuous development of biomedical signal processing methods in order to obtain the most efficient implementationsin the case of non-invasive implementation of BCI technology based on EEG. The further development of BCI technology has a huge impact on the techniques of rehabilitation of people with disabilities. Nowadays, wheelchairs are being constructed, thanks to which a disabled person is physically able to direct his position in a certain direction and at a certain speed. Thanks to BCI, it is also possible to create an individual speech synthesizer, with the help of which a paralyzed person will be able to communicate with the outside world. New limb prostheses that will replace the lost locomotor system in almost one hundred percent are still being developed. 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After first demonstrating the importance of the field using an interactive ChatGPT session, the book explores the remarkable progress and general challenges faced with real-world deployment of NLIDBs. It goes on to provide readers with a holistic understanding of the intricate anatomy, essential components, and mechanisms underlying NLIDBs and how to build them. Key concepts in representing, querying, and processing structured data as well as approaches for optimizing user queries are established for the reader before their application in NLIDBs is explored. The book discusses text to data through early relevant work on semantic parsing and meaning representation before turning to cutting-edge advancements in how NLIDBs are empowered to comprehend and interpret human languages. Various evaluation methodologies, metrics, datasets and benchmarks that play a pivotal role in assessing the effectiveness of mapping natural language queries to formal queries in a database and the overall performance of a system are explored. The book then covers data to text, where formal representations of structured data are transformed into coherent and contextually relevant human-readable narratives. It closes with an exploration of the challenges and opportunities related to interactivity and its corresponding techniques for each dimension, such as instances of conversational NLIDBs and multi-modal NLIDBs where user input is beyond natural language. 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Moreover, it also discusses how to train deep learning models in the cloud elucidating the key components andaspects necessary to train these models via different types of services offered by cloud providers.Despite the vast bibliography about cloud computing and HPC, to the best of our knowledge, no existing manuscript has comprehensively covered these topics and discussed the steps, methods and strategies to execute HPC applications in clouds. 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The resulting univariate or oblique trees are significantly smaller than those produced by standard top-down methods, an aspect that is critical for the interpretation of mined patterns by domain analysts. The approach presented here is extremely flexible and can easily be adapted to specific data mining applications, e.g. cost-sensitive model trees for financial data or multi-test trees for gene expression data. The global induction can be efficiently applied to large-scale data without the need for extraordinary resources. With a simple GPU-based acceleration, datasets composed of millions of instances can be mined in minutes. 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Secondly, cloud computing and related topics are also provided. The book has been designed to help research organisations and business leaders from across industries to transform their organisations into AI-driven disruptors. The utility of the technology in the face of massive globally interconnected complexity is explored. The significant characteristics of IEMAICLOUD are the promotion of inevitable dialogue between scientists, researchers, engineers, corporate’s and scholar’s students to mitigate the gap between academia, industry and governmental ethics which has been fostered through keynote speeches, workshops, panel discussion and oral presentations by eminent researchers in relevant field. The industry personnel depict cutting-edge researches in artificial intelligence and cloud computing to convey academia regarding real-time scenario and practical findings. 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The chapters demonstrate recent pursuits in the methodology, theory, advanced algorithms, and applications of multi-view data analytics and bring new perspectives of data interpretation. The timely book will appeal to a broad readership including both researchers and practitioners interested in gaining exposure to the rapidly growing trend of multi-view data analytics and intelligent systems.\u003c\/p\u003e","brand":"Gardners","offers":[{"title":"Default Title","offer_id":52911298347287,"sku":null,"price":18705.44,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0679\/6918\/8119\/files\/9783030952396.jpg?v=1781266764"},{"product_id":"advanced-information-networking-and-applications-9783030995874","title":"Advanced Information Networking and Applications","description":"\u003cp\u003eThis book covers the theory, design and applications of computer networks, distributed computing and information systems. Networks of today are going through a rapid evolution, and there are many emerging areas of information networking and their applications. Heterogeneous networking supported by recent technological advances in low-power wireless communications along with silicon integration of various functionalities such as sensing, communications, intelligence and actuations is emerging as a critically important disruptive computer class based on a new platform, networking structure and interface that enable novel, low-cost and high-volume applications. Several of such applications have been difficult to realize because of many interconnections problems. To fulfill their large range of applications, different kinds of networks need to collaborate, and wired and next generation wireless systems should be integrated in order to develop high-performance computing solutions to problems arising from the complexities of these networks.  The aim of the book “Advanced Information Networking and Applications” is to provide the latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and applications.\u003c\/p\u003e","brand":"Gardners","offers":[{"title":"Default Title","offer_id":52911311716631,"sku":null,"price":27463.84,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0679\/6918\/8119\/files\/9783030995874.jpg?v=1781267130"},{"product_id":"recent-advances-in-soft-computing-and-data-mining-9783031008283","title":"Recent Advances in Soft Computing and Data Mining","description":"\u003cp\u003eThis book unfolds ways to transform data into innovative solutions perceived as new remarkable and meaningful value. It offers practical views of the concepts and techniques readers need to get the most out of their large-scale research and data mining projects. It strides them through the data-analytical thinking, circumvents the difficulty in deciphering complex data systems and obtaining commercialization value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad spectrum, an interdisciplinary field of scientific methods and processes. The book, Recent Advances in Soft Computing and Data Mining, delivers sufficient knowledge to tackle a wide range of issues seen in complex systems. This is done by exploring a vast combination of practices and applications by incorporating these two domains. To thrive in these data-driven ecosystems, researchers, data analysts, and practitioners must choose the best design to approach theproblem with the most efficient tools and techniques. 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The need to connect natural language rules and numerical decisions is known since 1960s, when the need emerged to incorporate expert knowledge -- described by imprecise words like \"small\" -- into control and decision making. For this incorporation, a special \"fuzzy\" technique was invented, that led to many successful applications. 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The authors propose a deep learning-based approach to process cloud’s log data and mitigate enumeration attacks in the third chapter. The fourth chapter proposes a robust fuzzy learning model to protect IT-based infrastructure against advanced persistent threat (APT) campaigns. Advanced and fair clustering approach for industrial data, which is capable of training with huge volume of data in a close to linear time is introduced in the fifth chapter, as well as offering an adaptive deep learning model to detect cyberattacks targeting cyber physical systems (CPS) covered in the sixth chapter.    The authors evaluate the performance of unsupervised machine learning for detecting cyberattacks against industrial control systems (ICS) in chapter 7, and the next chapter presents a robust fuzzy Bayesian approach for ICS’s cyber threat hunting. This handbook also evaluates the performance of supervised machine learning methods in identifying cyberattacks against CPS. The performance of a scalable clustering algorithm for CPS’s cyber threat hunting and the usefulness of machine learning algorithms for MacOS malware detection are respectively evaluated. This handbook continues with evaluating the performance of various machine learning techniques to detect the Internet of Things malware. The  authors demonstrate how MacOSX cyberattacks can be detected using state-of-the-art machine learning models. In order to identify credit card frauds, the fifteenth chapter introduces a hybrid model. In the sixteenth  chapter, the editors propose a model that leverages natural language processing techniques for generating a mapping between APT-related reports and cyber kill chain. A deep learning-based approach to detect ransomware is introduced, as well as a proposed clustering approach to detect IoT malware in the last two chapters. This handbook primarily targets professionals and scientists working in Big Data, Digital Forensics, Machine Learning, Cyber Security Cyber Threat Analytics and Cyber Threat Hunting as a reference book. Advanced level-students and researchers studying and working in Computer systems, Computer networks and Artificial intelligence will also find this reference useful.\u003c\/p\u003e","brand":"Gardners","offers":[{"title":"Default Title","offer_id":52911352250647,"sku":null,"price":19956.64,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0679\/6918\/8119\/files\/9783030747534.jpg?v=1781268771"},{"product_id":"handbook-on-blockchain-9783031075353","title":"Handbook on Blockchain","description":"\u003cp\u003eThis handbook aims to serve as a one-stop, reliable source of reference, with curations of survey and expository contributions on the state-of-the-art in Blockchain technology. It covers a comprehensive range of topics, providing the technical and non-technical reader with fundamentals, applications, and deep details on a variety of topics. The readership is expected to span broadly from technologically-minded business professionals and entrepreneurs, to students, instructors, novices and seasoned researchers, in computer science, engineering, software engineering, finance, and data science. Though Blockchain technology is relatively young, its evolution as a field and a practice is booming in growth and its importance to society had never been more important than it is today. Blockchain solutions enable a decentralization of a digital society where people can contribute, collaborate, and transact without having to second-guess the trust and transparency factors with many geographical, financial, and political barriers removed. It is the distributed ledger technology behind the success of Bitcoin, Ethereum, and many emerging applications. The resource is divided into 5 parts. Part 1 (Foundation) walks the reader through a comprehensive set of essential concepts, protocols, and algorithms that lay the foundation for Blockchain. Part 2 (Scalability) focuses on the most pressing challenges of today’s blockchain networks in how to keep pace with real-world expectations. Part 3 (Trust and Security) provides detailed coverage on the issues of trust, reputation, and security in Blockchain.  Part 4 (Decentralized Finance) is devoted to a high-impact application of Blockchain to finance, the sector that has most benefitted from this technology. 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We will explain how we reached this phase and what historically happened to artificial intelligence in the last century. Recent advancements in machine learning, neuroscience, and artificial intelligence technology will be addressed, and new business models introduced for and by artificial intelligence research will be analyzed. Finally, we will describe the investment landscape, through the quite comprehensive study of almost 14,000 AI companies and we will discuss important features and characteristics of both AI investors as well as investments. This is the “Internet of Thinks” era. AI is revolutionizing the world we live in. It is augmenting the human experiences, and it targets to amplify human intelligence in a future not so distant from today. Although AI can change our lives, it comes also with some responsibilities. We need to start thinking about how to properly design an AI engine for specific purposes, as well as how to control it (and perhaps switch it off if needed). 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As such it offers a solid foundation for the development of new-generation data-intensive intelligent systems.  Modelling and simulation (MS) in the big data era is widely considered the essential tool in science and engineering to substantiate the prediction and analysis of complex systems and natural phenomena. MS offers suitable abstractions to manage the complexity of analysing big data in various scientific and engineering domains. Unfortunately, big data problems are not always easily amenable to efficient MS over HPC (high performance computing). Further, MS communities may lack the detailed expertise required to exploit the full potential of HPC solutions, and HPC architects may not be fully aware of specific MS requirements.   The main goal of the Summer School was to improve the participants’ practical skills and knowledge of the novel HPC-driven models and technologies for big data applications. The trainers, who are also the authors of this book, explained how to design, construct, and utilise the complex MS tools that capture many of the HPC modelling needs, from scalability to fault tolerance and beyond. In the final three chapters, the book presents the first outcomes of the school: new ideas and novel results of the research on security aspects in clouds, first prototypes of the complex virtual models of data in big data streams and a data-intensive computing framework for opportunistic networks. 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Finally, in Part VI he offers a detailed explanation of the AI-TOOLKIT, software he developed that allows the reader to test and study the examples in the book and the application of machine learning in professional environments. The author introduces core machine learning concepts and supports these with practical examples of their use, so professionals will appreciate his approach and use the book for self-study. 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The book explores granular computing as a response to the fact that learning tasks have become increasingly more complex due to the vast and rapid increase in the size of data, and that traditional machine learning has proven too shallow to adequately deal with big data.     Some popular types of traditional machine learning are presented in terms of their key features and limitations in the context of big data. Further, the book discusses why granular-computing-based machine learning is called for, and demonstrates how granular computing concepts can be used in different ways to advance machine learning for big data processing. Several case studies involving big data are presented by using biomedical data and sentiment data, in order to show the advances in big data processing through the shift from traditional machine learning to granular-computing-based machine learning. 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However, there are significant security challenges associated with peer-to-peer communication. The decentralised concept of blockchain technology ensures transparent interactions between different parties, which are more secure and reliable thanks to distributed ledger and proof-of-work consensus algorithms. Blockchains allow trustless, peer-to-peer communication and have already proven their worth in the world of financial services. The blockchain can be implanted in IoT systems to deal with the issues of scale, trustworthiness and decentralisation, allowing billions of devices to share the same network without the need for additional resources. This book discusses the latest tools and methodology and concepts in the decentralised Internet of Things. Each chapter presents an in-depth investigation of the potential of blockchains in the Internet of Things, addressing the state-of-the-art in and future perspectives of the decentralised Internet of Things. 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The authoritative insights presented within cover all aspects of the sensory subsystem required by an intelligent system to perceive the environment and act autonomously. Volume 3 (From Pattern to Object) examines object recognition, neural networks, motion analysis, and 3D reconstruction of a scene. Topics and features: •Describes the fundamental processes in the field of artificial vision that enable the formation of digital images from light energy •Covers light propagation, color perception, optical systems, and the analog-to-digital conversion of the signal •Discusses the information recorded in a digital image, and the image processing algorithms that can improvethe visual qualities of the image •Reviews boundary extraction algorithms, key linear and geometric transformations, and techniques for image restoration •Presents a selection of different image segmentation algorithms, and of widely-used algorithms for the automatic detection of points of interest •Examines important algorithms for object recognition, texture analysis, 3D reconstruction, motion analysis, and camera calibration •Provides an introduction to four significant types of neural network, namely RBF, SOM, Hopfield, and deep neural networks This all-encompassing survey offers a complete reference for all students, researchers, and practitioners involved in developing intelligent machine vision systems. The work is also an invaluable resource for professionals within the IT\/software and electronics industries involved in machine vision, imaging, and artificial intelligence. Dr. Cosimo Distante is a Research Scientist in Computer Visionand Pattern Recognition in the Institute of Applied Sciences and Intelligent Systems (ISAI) at the Italian National Research Council (CNR). Dr. Arcangelo Distante is a researcher and the former Director of the Institute of Intelligent Systems for Automation (ISSIA) at the CNR. 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It is based on adequate representation of the essential clustering problem: to group together the similar, and to separate the dissimilar. This leads to a general objective function and subsequently to a broad class of concrete implementations. Using this basis, a suboptimising procedure can be developed, together with a variety of implementations.This procedure has a striking affinity with the classical hierarchical merger algorithms, while also incorporating the stopping rule, based on the objective function. The approach resolves the cluster number issue, as the solutions obtained include both the content and the number of clusters. Further, it is demonstrated how the bi-partial principle can be effectively applied to a wide variety of problems in data analysis. The book offers a valuable resource for all data scientists who wish to broaden their perspective on basic approaches and essential problems, and to thus find answers to questions that are often overlooked or have yet to be solved convincingly. 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