Databases / Data management Books

Book SynopsisEntering the field of artificial intelligence and data science can seem daunting to beginners with little to no prior background, especially those with no programming experience. The concepts used in self-driving cars and virtual assistants like Amazon’s Alexa may seem very complex and difficult to grasp. The aim of Artificial Intelligence in Python is to make AI accessible and easy to understand for people with little to no programming experience though practical exercises. Newcomers will gain the necessary knowledge on how to create such systems, which are capable of executing tasks that require some form of human-like intelligence. This book introduces readers to various topics and examples of programming in Python, as well as key concepts in artificial intelligence. Python programming skills will be imparted as we go along. Concepts and code snippets will be covered in a step-by-step manner, to guide and instill confidence in beginners. Complex subjects in deep learning and machine learning will be broken down into easy-to-digest content and examples. Artificial intelligence implementations will also be shared, allowing beginners to generate their own artificial intelligence algorithms for reinforcement learning, style transfer, chatbots, speech, and natural language processing.Table of ContentsPart I Python.- 1 About Python.- 2 What’s Python?.- 3 An Introductory Example.- 4 Basic Python.- 5 Intermediate Python.- 6 Advanced Python.- 7 Python for data analysis.- Part II Artificial Intelligence Basics.- 8 Introduction to artificial intelligence.- 9 Data wrangling.- 10 Regression.- 11 Classification.- 12 Clustering.- 13 Association Rules.- Part III Artificial Intelligence.- Implementations.- 14 Text Mining.- 15 Image Processing.- 16 Convolutional Neural Networks.- 17 Chatbot, Speech and NLP.- 18 Deep Convolutional Generative Adversarial Network.- 19 Neural style transfer.- 20 Reinforcement learning.- 21 References.

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Book SynopsisThis book comprehensively introduces data deduplication technologies for storage systems. It first presents the overview of data deduplication including its theoretical basis, basic workflow, application scenarios and its key technologies, and then the book focuses on each key technology of the deduplication to provide an insight into the evolution of the technology over the years including chunking algorithms, indexing schemes, fragmentation reduced schemes, rewriting algorithm and security solution. In particular, the state-of-the-art solutions and the newly proposed solutions are both elaborated. At the end of the book, the author discusses the fundamental trade-offs in each of deduplication design choices and propose an open-source deduplication prototype. The book with its fundamental theories and complete survey can guide the beginners, students and practitioners working on data deduplication in storage system. It also provides a compact reference in the perspective of key data deduplication technologies for those researchers in developing high performance storage solutions.Table of ContentsPreface.- Deduplication: Beginning from Data Backup System.- Overview of Data Deduplication.- Chunking Algorithms.- Indexing Schemes.- Rewriting Algorithms.- Secure Deduplication.- Post-deduplication Delta Compression Schemes.- The Framework of Data Deduplication.- References.

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Book SynopsisThis book gives a thorough and systematic introduction to Data, Data Sources, Dimensions of Data, Privacy, and Security Challenges associated with Data, Ethics, Laws, IPR Copyright, and Technology Law. This book will help students, scholars, and practitioners to understand the challenges while dealing with data and its ethical and legal aspects. The book focuses on emerging issues while working with the Data.Table of ContentsData and its Dimensions.- Data Privacy.- Data Security.- Data Ethics.- Intellectual Property Right – Copyright.

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Book SynopsisThis book presents best selected research papers presented at the International Conference on Computer Networks, Big Data and IoT (ICCBI 2021), organized by Vaigai College Engineering, Madurai, Tamil Nadu, India, during December 9–10, 2021. The book covers original papers on computer networks, network protocols and wireless networks, data communication technologies and network security. The book is a valuable resource and reference for researchers, instructors, students, scientists, engineers, managers and industry practitioners in those important areas.Table of ContentsChapter 1. Rakshak – Prototype Application to Depict Crime Hotspot and Safest Path between locations.- Chapter 2. Block Chain Technology in Application Development and Associated Challenges.- Chapter 3. Hybrid Statistical and Deterministic Based Pedestrian Tracking Algorithm for Location-Based IoT Applications.- Chapter 4. MAC based Secure Data Transmission in Vehicular Adhoc Networks.- Chapter 5. A Study on Challenges in Data Security During Data Transformation.- Chapter 6. An Edge-based Disjoint Path Selection Scheme for FANETs.- Chapter 7. Sign Language Interpreter.- Chapter 8. Architectural Insight of Neural Information Extraction, Retrieval and Processing for Multi-Modal Neural Search.- Chapter 9. A Comparative Study Analysis on Air Monitoring and Purification Systems.- Chapter 10. Malicious Node Detection and Prevention for Secured Communication in WSN.- Chapter 11. Performance Analysis and Assessment of Various Energy Efficient Clustering based Protocols in WSN.- Chapter 12. Academic Data Analysis and Projection using Artificial Intelligence.- Chapter 13. Analysis of Factor Verification Affecting Recruitment Process through Social Dynamics.- Chapter 14. Routing Protocols in an Opportunistic Network: A Survey.- Chapter 15. K-Splits: Improved K-Means Clustering Algorithm to Automatically Detect the Number of Clusters.

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Book SynopsisThis book presents a study of the COVID-19 pandemic using computational social scientific analysis that draws from, and employs, statistics and simulations. Combining approaches in crisis management, risk assessment and mathematical modelling, the work also draws from the philosophy of sacrifice and futurology. It makes an original contribution to the important issue of the stability of society by highlighting two significant factors: the COVID-19 crisis as a catalyst for change and the rise of AI and Big Data in managing society. It also emphasizes the nature and importance of sacrifices and the role of politics in the distribution of sacrifices. The book considers the treatment of AI and Big Data and their use to both “good” and “bad” ends, exposing the inevitability of these tools being used. Relevant to both policymakers and social scientists interested in the influence of AI and Big Data on the structure of society, the book re-evaluates the ways we think of lifestyles, economic systems and the balance of power in tandem with digital transformation.Table of ContentsChapter 1. A Worldview Seen From Sacrifices.- Chapter 2. Crises, Risks and Sacrifices.- Chapter 3. A Crisis of COVID-19 and its Sacrifices.- Chapter 4. Formalizing Models on COVID-19 Pandemic.- Chapter 5. For Balancing Health Care and Economics.- Chapter 6. Five Virtues to be Digitized Norms.- Chapter 7. Synchronizing Everything to the Digitized World.- Chapter 8. A Living Way in the Digitized World.- Chapter 9. A New World in Motion.- Chapter 10. Digitized Shifts of Regime and Hegemony.- Chapter 11. On Balance of Power.- Chapter 12. For Strategies in The Age of After Corona.- Chapter 13. Conclusion.

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Book Synopsis“Smart City” programs and strategies have become one of the most dominant urban agendas for local governments worldwide in the past two decades. The rapid urbanization rate and unprecedented growth of megacities in the 21st century triggered drastic changes in traditional ways of urban policy and planning, leading to an influx of digital technology applications for fast and efficient urban management. With the rising popularity in making our cities “smart”, several domains of urban management, urban infrastructure, and urban quality-of-life have seen increasing dependence on advanced information and communication technologies (ICTs) that optimize and control the day-to-day functioning of urban systems. Smart Cities, essentially, act as digital networks that obtain large-scale real-time data on urban systems, process them, and make decisions on how to manage them efficiently. The book presents 26 chapters, which are organized around five topics: (1) Conceptual framework for smart cities and communities; (2) Technical concepts and models for smart city and communities; (3) Civic engagement and citizen participation; (4) Case studies from the Global North; and (5) Case studies from the Global South.Table of ContentsIntroduction.- Technology Talks: The Evolution and Rhetoric of Smartcities.- Projects for Smart Cities: Ecosystems, Connected Intelligence and Innovation Driving the Radical Transformation of Cities.- The Histories of New (Geo)politics of Smart Villages Communities in a Global World: A Contribution to Geographical Debate.- Identifying, Mapping and Measuring Europe’s Smart Cities and Digital Divides: Hyperlink Variations in Primary, Secondary and Tertiary Cities.- Role of Smart Dustbin in Creating a Smart Environment.- Smart Technologies and Aging Society.- Conceptual Model of Mixed-methods Civic Engagement Infrastructure Using Cloud-based Computing Combined with On-site Engagement and Action Projects.- Digital Placemaking: An Analysis of Citizen Participation in Smart Cities.- Historian for a Day: A Use Case of Augmented Reality in Civic Engagement.

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Book SynopsisThis book features a collection of high-quality, peer-reviewed papers presented at the Fifth International Conference on Intelligent Computing and Communication (ICICC 2021) organized by the Department of Computer Science and Engineering and the Department of Computer Science and Technology, Dayananda Sagar University, Bengaluru, India, on 26–27 November 2021. The book is organized in two volumes and discusses advanced and multi-disciplinary research regarding the design of smart computing and informatics. It focuses on innovation paradigms in system knowledge, intelligence and sustainability that can be applied to provide practical solutions to a number of problems in society, the environment and industry. Further, the book also addresses the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology and health care.Table of ContentsEnhancement of Image Forgery and Improvement of Image Parameters Using DWT Algorithm.- Derivation of DUS-Defined Physiological and Color Features of Okra Fruit Using Machine Vision Technology.- Application-Oriented Content Quality Analysis of Data Using Python.- An Improved Similarity Measure Based on Collaborative Filtering for Sparsity Problem in Recommender Systems.- Detection and Classification of Bird Pest Using Spectrogram, Physical Imagery, and Convolutional Neural Network.- Scatter Index: An Alternative Measure of Dispersion Based on Relative Frequency of Occurrence of Observations

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Book SynopsisThis book includes selected papers presented at International Conference on Computational Intelligence, Data Science,, and Cloud Computing (IEM-ICDC 2021), organized by the Department of Information Technology Institute of Engineering and Management, Kolkata, India, during December 22 – 24, 2021. It covers substantial new findings about AI and robotics, image processing and NLP, cloud computing and big data analytics as well as in cyber-security, blockchain and IoT, and various allied fields. The book serves as a reference resource for researchers and practitioners in academia and industry.Table of ContentsAutoDrone: Shortest Optimized Obstacle-Free Path Planning for Autonomous Drones.- Transfer Learning and Transformer Architecture for Financial Sentiment Analysis.- Feature Extraction and Machine Learning for the Classification of Fashion Materials.- Cardamom Quality Evaluation Employing Electronic Nose.- COVID-DeepNet: Deep Convolutional Neural Network Architecture Designed for Early Prognosis of COVID-19 using Post-Anterior View of Chest X-Rays.- Analytical Study on Feature Selection for Big Data using Optimization Algorithms.- A Machine Learning Approach for Predicting the Death Time and Mortality.- Prediction of Crops Production Using Random Forest Regression.- Drowsy Driving Detection based on Deep Neural Network for Accident Avoidance.- An Intelligent Fire-Extinguishing Robotic System to Combat fire in Coal Mines.

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Book SynopsisThis book presents Industry 4.0 enabler technologies and tools. It also highlights some of the existing empirical applications in the context of manufacturing. The book elucidates innovative thematic concepts of Industry 4.0 and its perspectives. It establishes routes to empirically utilize Industry 4.0 standards for manufacturing companies. The book can be used as a reference for professionals/engineers, researchers, and students.Table of ContentsIndustry 4.0 concepts, technologies and its ecosystemCyber-physical system: enabler technologies, concepts and its role in industry 4.0 The Internet of Things: success stores and challenges in manufacturing Blockchain technology and its role in industry 4.0Blockchain technology applications and challenges in Industry 4.0 Industry 4.0 technologies in product design: Virtual design and Manufacturing, Augmented reality Digital Twins and its applications Big data analytics in industry 4.0Industry 4.0 in pharmaceutical industry: Towards pharma 4.0 Industry 4.0 in military: Towards military 4.0 Towards Industry 5.0: what Cognitive cyber physical system is?

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Book SynopsisThis book features a collection of high-quality, peer-reviewed papers presented at the Second International Conference on Ubiquitous Intelligent Systems (ICUIS 2022) organized by Shree Venkateshwara Hi-Tech Engineering College, Tamil Nadu, India, during March 10–11, 2022. The book covers topics such as cloud computing, mobile computing and networks, embedded computing frameworks, modeling and analysis of ubiquitous information systems, communication networking models, big data models and applications, ubiquitous information processing systems, next-generation ubiquitous networks and protocols, advanced intelligent systems, Internet of Things, wireless communication and storage networks, intelligent information retrieval techniques, AI-based intelligent information visualization techniques, cognitive informatics, smart automation systems, health care informatics and bioinformatics models, security and privacy of intelligent information systems, and smart distributed information systems.Table of ContentsDevelopment of a Linear-Scaling Consensus Mechanism of the Distributed Data Ledger Technology.- A Six-Point Based Approach for Enhanced Broadcasting using Selective Forwarding Mechanism in Mobile Ad Hoc Networks.- Crop Price Prediction using Machine Learning Naive Bayes Algorithms.- The Performance Evaluation of Adaptive energy Conservation Scheme using IoT.- Towards the prominent use of Internet of Things(IoT) in Universities.- Depression Analysis of Real Time Tweets during Covid Pandemic.- Diabetic Retinopathy Detection Using Deep Learning.- Regional Language Translator using Natural Language Processing.- Fabric Defect Detection using Deep Learning Techniques.- Analysis of Research Paper Titles Containing Covid-19 keyword using Various Visualization Techniques.- Survey on Handwritten Characters Recognition in Deep Learning.- A Survey on Wild Creatures Alert System to Protect Agriculture Lands Domestic Creatures and People.- A Study on Surveillance System using Deep Learning Methods.- IRHA: An Intelligent RSSI based Home automation System.- A Review Paper on Machine Learning Techniques & Its Applications in Health Care Sector.- Enhanced Mask-RCNN for Ship Detection and Segmentation.- Data Scientist Job Change Prediction Using Machine Learning Classification Techniques.- Error Correction Scheme with Decimal Matrix Code for SRAM Emulation TCAMs.- Knowledge Discovery in Web usage Patterns using Pageviews and Data Mining Association.- Video Anomaly Detection using Optimization based Deep Learning.- A Fusional Cubic-Sine Map model for Secure Medical Image Transmission.- Innovative Technologies Developed for Autonomous Marine Vehicles by ENDURUNS Project.- Machine Learning Approaches to Predict Breast Cancer: Bangladesh Perspective.- A Comparative Review on Image Analysis with Machine Learning for Extended Reality (XR) Applications.- SWOT Analysis of Behavioural Recognition through Variable Modalities.- E-Mixup and Siamese Networks for Musical Key Estimation.- Microarray Data Classification using Feature Selection and Regularized Methods with Sampling Methods.- Visual Place Recognition using Region of Interest Ex-traction with Deep Learning based Technique.- Electronic Mobility Aid for Detection of Roadside Tree Trunks and Street-Light Poles.- Real Time Video Image Edge Detection System Using MyRIO.- Research Paper to Design & Develop an Algorithm for Optimization Chatbot.- Analysis of MRI Images to Discover Brain Tumor Detection Using Convolutional Neural Network and VGG-16.- Missing Data Recovery using Tensor Completion-based models for IoT-based Air Quality Monitoring System.- Stock Market Prediction through a Chatbot : A Human-Centered AI Approach.- Air Writing Recognition using Mediapipe and OpenCV.- Blockchain based Email Communication with Sha-256 Algorithm.- Sentimental Analysis on Amazon Reviews using Machine Learning.- Season based Crop Recommendation System using Transfer Learning: A Review.- Speed breaker Identification using Deep Learning Convolutional Neural Network.- Political Communication and Election Result: Facebook Account Analysis Jambi Governor Candidates in the 2020 Regional Election.- Intelligent System for Diagnosis of Pulmonary Tuberculosis using XGBoosting Method.- Web based Voice Assistant for Railways using Deep Learning Approach.- Segmentation and Classification Approach to Improve Breast Cancer Screening.- Analysis of a Software tool Developed to Determine the Activity of Anomalous Processes.- Study of Wave Models of Trajectories and Signals of Loading e ects in Computer Echolocation.- EnneaOntology: A Proposed Enneagram Ontology.- IoT based Signal Patrolling for Precision Vehicle Control.- Land use/cover Novel Dataset Based on Deep Learning: Case study of Fayoum, Egypt.- Exploring The effect of Word Embeddings and Bag-of-Words for Vietnamese Sentiment Analysis.- A Portable System for Automated Measurement of Striped Catfish Length using Computer Vision.- IoT based Automated Monitoring System for the Measurement of Soil Quality.- Pattern Recognition on Railway Points with Machine Learning: A Real Case Study.- Sustainability in Development of Grant Applications.- New Category of Equivalence Classes of Intuitionistic Fuzzy Delta-Algebras with their Applications.- Deep Neural Networks for Stock Market Price Predictions in VUCA Environments.- Building a Traffic flow Management System based on Neural Networks.- The Impact of Ruang Cerita Application on the Neuro Depression and Anxiety of Private University Students.- JobSeek Mobile Application: Helps Reduce Unemployment on the Agribusiness Sectors During New Normal.- Application's Impact on the SepuisLife Company's Insurance Sales Process During the Pandemic.- The Effect of Learning Using Videos on Online Learning of Private University during the Covid-19 Pandemic.- Implementation of Artificial Intelligence and Robotic that Replace Employee in Indonesia.- The Impact of Online Game Brain Addiction on Computers and Cellphones on College Students Who Take Online Classes.

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Book SynopsisThis book gathers selected papers presented at the KES International Symposium on Smart Transportation Systems (KES STS 2022). Modern transportation systems have undergone a rapid transformation in recent years, producing a range of technological innovations such as connected vehicles, self-driving cars, electric vehicles, Hyperloop, and even flying cars, and with them, fundamental changes in transport systems around the world. The book discusses current challenges, innovations, and breakthroughs in smart transportation systems, as well as transport infrastructure modeling, safety analysis, freeway operations, intersection analysis, and other related cutting-edge topics.

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Book SynopsisThe book contains select proceedings of the 3rd International Conference on Data, Engineering, and Applications (IDEA 2021). It includes papers from experts in industry and academia that address state-of-the-art research in the areas of big data, data mining, machine learning, data science, and their associated learning systems and applications. This book will be a valuable reference guide for all graduate students, researchers, and scientists interested in exploring the potential of big data applications.Table of Contents1. Medical Assistance Chatbot using Deep Learning.- 2. Distortion Controlled Secure Reversible Data Hiding in H.264 videos.- 3. A Method for improving Efficiency and Security of FANET using Chaotic Black Hole Optimization based Routing (BHOR) Technique.- 4. Machine Learning Techniques for Intrusion Detection System: A Survey.- 5. Software Fault Detection by using Rider Optimization Algorithm (ROA) based Deep Neural Network (DNN).- 6. An Approach for Predicting Admissions in Post Graduate Program by using Machine Learning.- 7. A Survey on Various Representation Learning of Hypergraph for Unsupervised Feature Selection.- 8. A brief study of time series forecasting technique using linear regression, SVM, LSTM, ARIMA and SARIMA.- 9. Adoption of Blockchain Technology for Storage & Verification of Educational Documents.- 10. Obstacle Collision Prediction model for Path Planning Using Obstacle Trajectory Clustering.

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Book SynopsisThis is the first of its kind book that describes key elements of enterprise data and analytics strategy, and prescribes a pragmatic approach to define the strategy for large enterprises. The book is based on successful digital transformation experience of multiple Fortune 500 and other large enterprises. It is estimated that more than 50% of data and analytics initiatives fail globally because of the inherent complexity of such initiatives. Some of the questions that enterprises struggle with are: How to define enterprise data and analytics strategy? What are the key elements that should be considered while doing so? Why one-size-fits-all approach does not work for all enterprises? How to align data and analytics initiative with the business strategy of the CEO? How to establish a futuristic technology and architecture foundation, given the exponential rate of innovation in data and analytics technologies? How to define the right data and analytics organization model? Why data and analytics organization and processes need to be different from other functions? How to manage organizational change to ensure success of data and analytics initiative? How to define a business value measurement framework and calculate ROI from data and analytics initiative? What are the key skills required in a data and analytics leader to wade through political and other challenges of a large enterprise? This book will help executives, chief digital/analytics officers, data and analytics professionals, and consultants, in answering the above questions. It will help them in addressing various dilemmas that they face every day and making their enterprises data-driven.Table of ContentsChapter 1: What is Data and Analytics Strategy Key elements that should be part of the strategy Data and Analytics Strategy and its Criticality to Drive Enterprise Digital Initiatives Data and Analytics Strategy: A Case in Point Five Elements of Data and Analytics Strategy ▪ Business capabilities ▪ Technology and architecture ▪ Team, processes, and governance ▪ Organizational change management ▪ Value measurement framework SummaryChapter 2: First Element of Strategy – Business Capabilities Taking a top-down approach to align with business strategy Aligning with Organization’s Business Priorities Establishing Enterprise Performance Management Framework ▪ A brief historical perspective on performance measurement ▪ Key performance indicators (KPIs): lagging and leading indicators ▪ KPI trees to drive enterprise performance management ▪ Challenges of implementing enterprise KPI framework ▪ KPI framework defined for scenario 1 (organization A) discussed at the beginning of this chapter Driving Enterprise Digital Strategy ▪ Approach for scenario 2 (organization B): Digital transformation leveraging data and analytics Approach for Defining Data and Analytics Strategy, Starting with Business Capabilities ▪ Step 1: Enterprise churning – “Samudra Manthan” ▪ Step 2: Defining required business capabilities and other strategy elements ▪ Step 3: Prioritizing and creating an integrated roadmap SummaryChapter 3: Second Element of Strategy – Technology and Architecture Establishing technology and architecture foundation that is futuristic and flexible How Not to Define Technology and Architecture Strategy? Understanding Non-Functional Requirements to Define Data and Analytics Architecture ▪ Data sources ▪ Mode of delivery/access (of data) ▪ Temporal ▪ Data security ▪ Data type ▪ Data atomicity ▪ Latency ▪ Data quality and integrity ▪ Business model ▪ Data usage ▪ Metadata Defining Data and Analytics Architecture Selecting Relevant Technologies after Defining Data and Analytics Architecture SummaryChapter 4: Third Element of Strategy – Team, Processes, and Governance Establishing building blocks, including an agile team, for success Why Data and Analytics Organization and Processes Need to be Different from Other IT Functions? Choosing the Right Data and Analytics Organization Model ▪ Decentralized organization ▪ Centralized organization ▪ Federated organization Defining Data and Analytics Organization and Processes▪ Governance tower▪ Business tower▪ Technology and architecture tower▪ Solution delivery tower▪ Service delivery towerWeek-in-the-Life of Data and Analytics TeamSummaryChapter 5: Fourth Element of Strategy – Organizational Change ManagementDriving and managing change across the enterprise to ensure successNeed for Change Across the Enterprise▪ Till 2010 – A brief history of MIS era▪ The 2010s – Data visualization becomes all-pervasive across enterprises▪ The latter half of 2010s - Advent of digital technologies▪ Why organizational change managementDriving Change - Focus Areas & Objectives▪ Four Focus Areas – People, Processes, Technology, and Data▪ Three OCM Objectives▪ Twelve OCM Strategy Elements for Data and AnalyticsStages of Change & Change Leadership▪ The Three Stages of Change▪ Importance of Change LeadershipSummaryChapter 6: Fifth Element of Strategy – Value Measurement FrameworkEstablishing a framework to define and measure value of data and analytics programThe Need for a Value Measurement FrameworkDefining and Measuring Business Value▪ First impact area: Revenue increase▪ Second impact area: Cost reduction▪ Third impact area: Business risk mitigation▪ Fourth impact area: Company’s image building▪ Business value measurement: Correlation does not necessarily mean causalityDefining and Measuring Operational Efficiency – Continuous Improvement▪ People performance▪ Process effectiveness▪ Technology capability▪ Data maturity▪ Operational efficiency and maturity assessmentCalculating ROI from Data and Analytics Investment▪ Calculating benefits▪ Calculating costs▪ Calculating ROISummaryChapter 7: The Profile of a Data and Analytics LeaderKey skills of a leader who can lead the enterprise to successKey Skills that any Enterprise Data and Analytics Leader Must PossessHard Skills▪ Technology▪ Data science▪ BusinessSoft Skills▪ Dealing with ambiguity▪ Team leadership▪ Innovation and risk-taking▪ Organizational change management▪ Design thinking and empathy▪ MarketingSummary

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Book SynopsisThis book includes high-quality research papers presented at 21st International Conference on Informatics in Economy (IE 2022), which is held in Bucharest, Romania, during May 2022. This book covers research results in business informatics and related computer science topics, such as IoT, mobile-embedded and multimedia solutions, e-society, enterprise and business solutions, databases and big data, artificial intelligence, data mining and machine learning, quantitative economics.Table of ContentsMicro-Services as Key Enabler of a Cloud-Native Architecture.- The Importance of Security and Safety in a Smart City.- Cyber Range Technology Stack Review.- IOT Security Challenges for Smart Homes.- An Overview of Security Issues in Smart Contracts on the Blockchain.- Agile Business Systems Development Paradigms – Technological and Human Resource Perspectives.- Identification of Qualitative Weak Signals Coming from Asset Management Working Practices to Feed Forward-Looking Investment Pensions Funds Models.- Digital Competences in the Public Sector – Challenges for Universities.- Transport System in Bucharest.- General Characteristics of the Assisted E-Learning System in Computer Science.- E-Learning in Romania: An Overview on Software Solutions from Private Initiatives.

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Book SynopsisThis book features high-quality, peer-reviewed research papers presented at the Fifth International Conference on Smart Technologies in Data Science and Communication (SMARTDSC 2022), held Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India, on 16 – 17 June 2022. It includes innovative and novel contributions in the areas of data analytics, communication and soft computing. Table of ContentsA Graph based model for Discovering Host-based hook Attacks.- E-Health Care Patient Information Retrieval and Monitoring System Using SVM.- Number Plate Recognition using Optical Character Recognition (OCA) and Connected Component Analysis (CCA).- Cartoonify an Image with Open cv using Python.- Web Design as an Important Factor in the Success of a Website.- Earlier Selection of Routes for Data Transfer in both Wired and Wireless Networks.

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Book SynopsisThis book includes selected papers presented at World Conference on Information Systems for Business Management (ISBM 2022), held in Bangkok, Thailand, during September 2–3, 2022. It covers up-to-date cutting-edge research on data science, information systems, infrastructure and computational systems, engineering systems, business information systems, and smart secure systems.Table of Contents Social Media as Communication-Transformation Tools.- Bi directional DC-DC converter-based Energy Storage Method for Electric Vehicles.- Design of Smart Irrigation System in Sone Command Area Bihar for Paddy Crop.- A Footstep to Image Deconvolution Technique for the both Known and Unknown Blur Parameter.- Secured Monitoring of Unauthorized UAV by Surveillance Drone Using NS2.

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Book SynopsisThe book presents the proceedings of the 10th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2022), held at NIT Mizoram, Aizawl, Mizoram, India during 18 – 19 June 2022. Researchers, scientists, engineers, and practitioners exchange new ideas and experiences in the domain of intelligent computing theories with prospective applications in various engineering disciplines in the book. These proceedings are divided into two volumes. It covers broad areas of information and decision sciences, with papers exploring both the theoretical and practical aspects of data-intensive computing, data mining, evolutionary computation, knowledge management and networks, sensor networks, signal processing, wireless networks, protocols and architectures. This volume is a valuable resource for postgraduate students in various engineering disciplines.Table of ContentsAgriBlockchain: Agriculture supply chain using blockchain.- A Triple Band High Gain Antenna Using Metamaterial.- Hybrid Energy Systems Integrated Power System Imbalance Cost Calculation using Moth Swam Algorithm.- Lightweight Privacy Preserving Framework at Edge Layer in IoT.- Concept drift aware analysis of learning engagement during Covid 19 pandemic using adaptive windowing.- MPA Optimized Model Predictive Controller for Optimal Control of an AVR system.- Optimal Power Flow Considering Uncertainty of Renewable Energy Sources Using Meta-Heuristic Algorithm.- Remote Sensing Image Fusion Based on PCA and Wavelets.- Physical Layer Security in MIMO Relay Based Cognitive Radio Network.- Weighted Low Rank and Sparse Matrix Decomposition Models for Separating Background and Foreground in Dynamic MRI.- A Novel Approach For Bug Triaging Using TOPSIS.- Energy Efficient Resource Allocation in Cognitive Radio Networks.- A Hybrid Feature Selection Framework for Breast Cancer Prediction using Mutual Information and AdaBoost-RFE.- Internet of Things enabled Irrigation System in Precision Agriculture.- Medical Internet of Things and Data Analytics for Post-Covid Care: An Analysis.- ECG Biometric Recognition by Convolutional Neural Networks with Transfer Learning using Random Forest Approach.- Design and Analysis of a Metamaterial Based Butterworth Microstrip Filter.- A Review of Financial Fraud Detection in E-Commerce using Machine Learning.

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Book SynopsisPreface.- Acknowledgements.- Part 1. Communication over the Gaussian channel.- Chapter 1.Overview of the book.- Chapter 2. A statistical model for additive noise channels.- Chapter 3. Additive Gaussian noise model.- Problem Set 1.- Chapter 4. Optimal receiver: maximum A Posteriori (MAP) principle.- Chapter 5. Analysis of error probability.- Chapter 6. Multiple bits transmission via pulse amplitude modulation.- Problem Set 2.- Chapter 7. Multi-shot communication.- Chapter 8. Repetition coding.- Chapter 9: Capacity of the additive white Gaussian noise channel.- Problem Set 3.- Part 2. Communication over inter-symbol interference (ISI) channels.- Chapter 10. Signal conversion from discrete to continuous time (1/2).- Chapter 11. Signal conversion from discrete to continuous time (2/2).- Chapter 12. Optimal receiver architecture.- Problem Set 4.- Chapter 13. Optimal receiver in ISI channels: maximum likelihood (ML) sequence detection.- Chapter&nb

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Book SynopsisChapter 1 Study on marketing dynamics on sales of electric vehicles and swot analysis.- Chapter 2 Stability Analysis and Backward Bifurcation of Malaria Model.- Chapter 3 Mathematical model for diabetes using fuzzy parameters.- Chapter 4 Fuzzy iterated function systems.- Chapter 5 Introduction to Interval-valued Neutrosophic Hyper-soft Expert Set.- Chapter 6 Fuzzy Fractal Dimension of Covid-19 Variant Protein.- Chapter 7 A study of Intuitionistic Fuzzy Graph using Morphological operators and its application.- Chapter 8 Edge weight-based colouring and matching in inhomogeneous random graphs.- Chapter 9 Super Domination Number of Cycle based Graphs and Comb Product of Graphs.- Chapter 10 Sum Divisor Cordial Labelling for Middle Graph and Total Graph of Some Graphs.- Chapter 11 On the Core and Noncore vertices of Singular Graphs.- Chapter 12 On C-Perfection of Modular Product of Graphs.- Chapter 13 A study on topological indices of bipartite Kneser B type-1 graphs.- Chapter 14 On jumping graph grammars.- Chapter 15 Some eigen value properties of Uniform Hyperstar Using recurrence relation.- Chapter 16 A study On Ramanujan graphs.- Chapter 17 On the exponential Diophantine equation related To the powers of Cluster Primes.- Chapter 18 Structure of different categories of Diophantine 3-tuples ap-propriate (????,??)-centred polygonal numbers.- Chapter 19 A Birth-Death Process with Temporary Growth Halts and Population Independent Death Rate.- Chapter 20 Comparison of Vacation and Mt/Mt/1 Queueing Models for Traffic Flow at Signalized Intersections.- Chapter 21 Study of Birth-Death Processes with Growth Interruptions.

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Book SynopsisWhen Gourmet Meets Technology–A Tale of Flavour Science Baked by Machine Learning.- Drawing the landscape: analysis the causes and prevention strategies of the landslide in an emblematic case of convergence of geological, climatic, and anthropic factors.- Unsupervised one class classifier model for fault detection in Wireless Sensor Networks.- Blind Bills: A Technological Approach to Increase Financial Inclusivity for Filipino Citizens.- Develop a Faster Mask Recurrent Convolutional Neural Network and Denoising Autoencoders to Enhance the EEG signals.- An Analysis of the Performance of Binary and Multiclass Models for Early Diagnosis of Skin Cancer.- Enhancing Life Quality for People Who Stutter through an AI-Driven Interactive Website - Assistance for People Who Stutter (AFPWS).- Community Health Management Using Machine Learning Algorithms.- Advancements in Machine Learning for Enhanced X-ray and Gamma Image Analysis: A Review.- Improving Tourism Image Classification with AI-Generated Descriptions: A Comparative Analysis of LLaVA and BLIP Models.- etc.

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Book SynopsisReview of Methods for Handling Class-Imbalanced in Classification Problems.- Course Material Recommendation System Using Student Learning Behavior and Course Material Complexity Score for Slow Learner Students.- A Benchmarking Investigation of Evolutionary Algorithms to resolve the COVID Sample Collection Problem.- Using OpenNLP and GraalVM to detect sentences in Kubernetes while comparing Helidon and Spring Boot's metrics.- An Efficient Hybrid Model to Summarize the Text using Transfer Learning.- Automatic Detection of Learner's Learning Style.- Construction of an Intelligent Knowledge based System using Transformer Model.- Machine Learning-Based Disease Diagnosis using Body Signals: A Review.- Finite-Difference and Finite-Volume 1D Steady-State Heat Conduction model for Machine Learning Algorithms.- Sign Language Detection Through PCANet and SVM.-  A Novel Surface Roughness Estimation and Optimization Model for Turning Process Us

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Book SynopsisDigital Innovation in Space Science.- Legal regimes for Space data.- Regulating space data management.- High Performance Computing, AI, the Metaverse and quantum computing to transform space data management.- AI applications of Space Data.- Blockchain-enabled Satellite Onboard Computing for Smart Contract: Benefits for Multi-sided Markets and IoT Applications.- On the use of available space monitoring data for improving the risk of collision avoidance.- Optimising collection, transmission and transformation of space data to take up security challenges.- A Fragile Watermarking Approach for Earth Observation Data Integrity Protection.- Deepness: Deep Neural Remote Sensing QGIS Plugin.- Earth Observation Data Transfer at Limitations of Small Satellite Missions.- Earth Observation Data Management and Offer: the experience of the ARIC.- Using satellite data to estimate NO2 concentrations in mainland UK from 2005 to 2021.- Integration of Terrestrial and Non-Terrestrial Networks: challenges and perspectives within the RESTAR project.- Estimate the ice volume of Earth's glaciers with deep learning and remote sensing.- Can life exist without water? A data driven approach.

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Book SynopsisThis book analyzes in detail the technological evolution process of databases in the era of cloud computing and explains how traditional database technology has gradually developed to cloud-native form from multiple perspectives such as architecture design, implementation mechanism, and system optimization.

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Book Synopsis.- Recommender System..- Hierarchical Review-based Recommendation with Contrastive Collaboration..- Adaptive Augmentation and Neighbor Contrastive Learning for Multi-Behavior Recommendation..- Automated Modeling of Influence Diversity with Graph Convolutional Network for Social Recommendation..- Contrastive Generator Generative Adversarial Networks for Sequential Recommendation..- Distribution-aware Diversification for Personalized Re-ranking in Recommendation..- KMIC: A Knowledge-aware Recommendation with Multivariate Intentions Contrastive Learning..- Logic Preference Fusion Reasoning on Recommendation..- MHGNN: Hybrid Graph Neural Network with Mixers for Multi-interest Session-aware Recommendation..- Mixed Augmentation Contrastive Learning for Graph Recommendation System..- Noise-Resistant Graph Neural Networks for Session-based Recommendation..- S2DNMF: A Self-supervised Deep Nonnegative Matrix Factorization Recommenda

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Book SynopsisThis open access book discusses the theory and methods of hypergraph computation. Many underlying relationships among data can be represented using graphs, for example in the areas including computer vision, molecular chemistry, molecular biology, etc. In the last decade, methods like graph-based learning and neural network methods have been developed to process such data, they are particularly suitable for handling relational learning tasks. In many real-world problems, however, relationships among the objects of our interest are more complex than pair-wise. Naively squeezing the complex relationships into pairwise ones will inevitably lead to loss of information which can be expected valuable for learning tasks. Hypergraph, as a generation of graph, has shown superior performance on modelling complex correlations compared with graph. Recent years have witnessed a great popularity of researches on hypergraph-related AI methods, which have been used in computer vision, social media analysis, etc. We summarize these attempts as a new computing paradigm, called hypergraph computation, which is to formulate the high-order correlations underneath the data using hypergraph, and then conduct semantic computing on the hypergraph for different applications. The content of this book consists of hypergraph computation paradigms, hypergraph modelling, hypergraph structure evolution, hypergraph neural networks, and applications of hypergraph computation in different fields. We further summarize recent achievements and future directions on hypergraph computation in this book.Table of Contents

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Book SynopsisThis book gathers a selection of peer-reviewed papers presented at the 4th Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2022) conference, held in Bangkok, Thailand, on December 16–17. The contributions, prepared by an international team of scientists and engineers, cover the latest advances and challenges made in the field of big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.

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Book SynopsisThe book presents papers from the 7th International Conference on Big Data and Cloud Computing Challenges (ICBCC 2022). The book includes high-quality, original research on various aspects of big data and cloud computing, offering perspectives from the industrial and research communities on addressing the current challenges in the field. This book discusses key issues and highlights recent advances in a single broad topic applicable to different sub-fields by exploring various multidisciplinary technologies. This book supports the transfer of vital knowledge to next-generation researchers, students, and practitioners in academia and industry.Table of ContentsTable of contents: Track 1: Architecture Sample topics include, - Cloud Infrastructure as a Service -Cloud Platform as a Service -Cloud federation and hybrid cloud infrastructure -Programming models and systems/tools -Green data center -Networking technologies for data center -Cloud system design with FPGA, GPU, and APU -Monitoring, management and maintenance -Economic and business models -Dynamic resource provisioning Track 2: MapReduce Sample topics include, -Performance characterization and optimization -MapReduce on multi-core, GPU -MapReduce on hybrid distributed environments -MapReduce on opportunistic / heterogeneous computing systems -Extension of the MapReduce programming model -Debugging and simulation of MapReduce systems -Data-intensive applications using MapReduce -Optimized storage for MapReduce applications -Fault-tolerance & Self-capabilities Track 3: Security and Privacy -Accountability -Audit in clouds -Authentication and authorization -Cryptographic primitives -Reliability and availability -Trust and credential management -Usability and security -Security and privacy in clouds -Legacy systems migration -Cloud Integrity and Binding Issues Track 4: Services and Applications -Cloud Service Composition -Query and discovery models for cloud services -Trust and Security in cloud services -Change management in cloud services -Organization models of cloud services -Innovative cloud applications and experiences -Business process and workflow management -Service-Oriented Architecture in clouds Track 5: Virtualization -Server, storage, network virtualization -Resource monitoring -Virtual desktop -Resilience, fault tolerance -Modeling and performance evaluation -Security aspects -Enabling disaster recovery, job migration -Energy efficient issues Track 6. HPC on Cloud -Load balancing for HPC clouds -Middleware framework for HPC clouds -Scalable scheduling for HPC clouds -HPC as a Service -Performance Modeling and Management -Programming models for HPC clouds -HPC cloud applications -Optimal cloud deployment for HPC Track 7. Big Data Science and Foundations -Novel Theoretical Models for Big Data -New Computational Models for Big Data -Data and Information Quality for Big Data -New Data Standards Track 8.Big Data Infrastructure -Cloud/Grid/Stream Computing for Big Data -High Performance/Parallel Computing Platforms for Big Data -Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment -Energy efficient Computing for Big Data -Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data -Software Techniques and Architectures in Cloud/Grid/Stream Computing Big Data Open Platforms -New Programming Models for Big Data beyond Hadoop/MapReduce, STORM -Software Systems to Support Big Data Computing Track 9. Big Data Management -Advanced database and Web Applications -Novel Data Model and Databases for Emerging Hardware -Data Preservation -Data Provenance -Interfaces to Database Systems and Analytics Software Systems -Data Protection, Integrity and Privacy Standards and Policies -Information Integration and Heterogeneous and Multi-structured Data Integration -Data management for Mobile and Pervasive Computing -Data Management in the Social Web -Crowd sourcing -Spatiotemporal and Stream Data Management -Scientific Data Management -Workflow Optimization -Database Management Challenges: Architecture, Storage, User Interfaces Track 10. Big Data Search and Mining -Social Web Search and Mining -Web Search -Algorithms and Systems for Big Data Search -Distributed, and Peer-to-peer Search -Big Data Search Architectures, Scalability and Efficiency -Data Acquisition, Integration, Cleaning, and Best Practices -Visualization Analytics for Big Data -Computational Modeling and Data Integration -Large-scale Recommendation Systems and Social Media Systems -Cloud/Grid/Stream Data Mining- Big Velocity Data -Link and Graph Mining -Semantic-based Data Mining and Data Pre-processing -Mobility and Big Data Track 11. Big Data Security & Privacy -Intrusion Detection for Gigabit Networks -Anomaly and APT Detection in Very Large Scale Systems -High Performance Cryptography -Visualizing Large Scale Security Data -Threat Detection using Big Data Analytics -Privacy Threats of Big Data -Privacy Preserving Big Data Collection/Analytics -HCI Challenges for Big Data Security & Privacy -User Studies for any of the above -Sociological Aspects of Big Data Privacy Track 12. Big Data Applications -Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance -Business, Law, Education -Transportation, Retailing, Telecommunication -Big Data Analytics in Small Business Enterprises (SMEs) -Big Data Analytics in Government, Public Sector and Society in General -Real-life Case Studies of Value Creation through Big Data Analytics -Big Data as a Service -Big Data Industry Standards -Experiences with Big Data Project Deployments Track 13. Recent trends -Semantic Cloud -Mobile Cloud -e-Healthcare Applications in Cloud -Cloud analytics for Internet of Things (IoT) -Smart Grid -Fog Computing -Edge Computing -Deep Learning -CNN

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Book SynopsisThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. The volume is a collection of peer reviewed research papers presented at Seventh International Conference on Data Management, Analytics and Innovation (ICDMAI 2023), held during 20 – 22 January, 2023 in Pune, India. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.Table of ContentsA Smart System to Classify Walking and Sitting Activity based on EEG Signal.- Monitoring urban water-logging using SAR - A Mumbai case study.- Suspicious Event Detection of Cargo Vessels based on AIS Data.- Identifying Trends using Improved Affinity Propagation (IMAP) Clustering Algorithm on Evolving Data Stream.- Graphology based behavior prediction : Case study analysis.- Statistics Driven Suspicious Event Detection of Fishing Vessels based on AIS Data.- Distributed Reduced Alphabet Representation for Predicting Proinflammatory Peptides.- Prakruti Nishchitikaran of Human Body using Supervised Machine Learning Approach.- X-ABI: Towards Parameter Efficient Multilingual Adapter Based Inference for Cross-Lingual Transfer.- Comparative Study of Depth Estimation from 2-D Scene Using Deep Learning Model.- DCNN-based Transfer Learning approaches for Gender Recognition.- Analysis of Machine Learning Algorithms for COVID Detection Using Deep Learning.- Real-time learning towards assets allocation.- Named Entity Recognition over Dialogue Dataset using Pre-trained Transformers.- A Comparative Study of Distance-based Clustering Algorithms in Fuzzy Failure Modes and Effects Analysis.- Economical Solution to Automatic Evaluation of an OMR Sheet Using Image Processing.- Defense and evaluation against covert channel based attacks in Android smartphones.- From Bricks to Clicks: The Potential of Big Data Analytics for Revolutionizing the Information Landscape in Higher Education Sector.- Data science approaches to public health: case studies using routine health data from India.- Arboviral Epidemic Disease Forecasting - A Survey on Diagnostics and Outbreak Models.- Convolution Neural Network for Weed Detection.- Machine Learning Model for Brain Stock Prediction.- Analysis of Covid-19 Genome using Continuous Wavelet Transform.

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Book SynopsisMaster the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether you’re a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.The key features of this indispensable book include: A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise. 100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension. A comprehensive guide to Sumio Watanabe’s groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians. Detailed source programs and Stan codes that will enhance readers’ grasp of the mathematical concepts presented. A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting. Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today!Table of ContentsOver view of Watanabe's Bayes.- Introduction to Watanabe Bayesian Theory.- MCMC and Stan.- Mathematical Preparation.- Regular Statistical Models.- Information Criteria.- Algebraic Geometry.- The Essence of WAOIC.- WBIC and Its Application to Machine Learning.

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Book SynopsisThis two-volume set LNAI 13995 and LNAI 13996 constitutes the refereed proceedings of the 15th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2023, held in Phuket, Thailand, during July 24–26, 2023.The 65 full papers presented in these proceedings were carefully reviewed and selected from 224 submissions. The papers of the 2 volume-set are organized in the following topical sections: Case-Based Reasoning and Machine Comprehension; Computer Vision; Data Mining and Machine Learning; Knowledge Integration and Analysis; Speech and Text Processing; and Resource Management and Optimization.Table of Contents​Case-Based Reasoning and Machine Comprehension.- On the improvement of the reasoning cycle in case-based reasoning.- Exploring incompleteness in Case-Based Reasoning: a strategy for overcoming challenge.- Leveraging both Successes and Failures in Case-Based Reasoning for Optimal Solutions.- Transfer Learning for Abnormal Behaviors Identification in Examination Room from Surveillance Videos: A Case Study in Vietnam.- A Novel Question-Context Interaction Method for Machine Reading Comprehension.- Granular Computing to Forecast Alzheimer’s Disease Distinctive Individual Development.- Computer Vision.- AdVLO: Region selection via Attention-driven for Visual LiDAR Odometry.- Intelligent Retrieval System on Legal Information.- VSNet: Vehicle State Classification for Drone Image with Mosaic Augmentation and Soft-label Assignment.- Creating High-Resolution Adversarial Images against Convolutional Neural Networks with the Noise Blowing-Up Method.- Faster Imputation Using Singular Value Decomposition for Sparse Data.- Combination of deep learning and ambiguity rejection for improving image-based disease diagnosis.- Data Mining and Machine Learning.- Towards Developing an Automated Chatbot for Predicting Legal Case Outcomes: A Deep Learning Approach.- Fuzzy-Based Factor Evaluation System for Momentum Overweight Trading Strategy.- Enhancing Abnormal-Behavior-based Stock Trend Prediction Algorithm with Cost-sensitive Learning Using Genetic Algorithms.- Leveraging Natural Language Processing in Persuasive Marketing.- Direction of the Difference between Bayesian Model Averaging and the Best-Fit Model on Scarce-Data Low-Correlation Churn Prediction.- Tree-based Unified Temporal Erasable-itemset Mining.- Design Recovery of Data Model Hidden in JSON File.- Accurate lightweight calibration methods for mobile low-cost particulate matter sensors.- Generating music for video games with real-time adaptation to gameplay pace.- Detecting Sensitive Data with GANs and Fully Convolutional Networks.- An Unsupervised Deep Learning Framework for Anomaly Detection.- Extracting top-k high utility patterns from multi-level transaction databases.- Lightweight and Efficient Privacy-Preserving Multimodal Representation Inference via Fully Homomorphic Encryption.- Neural Machine Translation with Diversity-enabled Translation Memory.- GIFT4Rec: An effective side Information Fusion Technique apply to Graph neural network for cold-start recommendation.- A Decision Support System for Improving Lung Cancer Prediction based on ANN.- Emotion detection from text in social networks.- Finite Libby-Novick Beta Mixture Model: An MML-Based Approach.- Artificial Intelligences on Automated Context-Brain Recognition with Mobile Detection Devices.- A Novel Meta-Heuristic Search Based on Mutual Information for Filter-Based Feature Selection.- Discovering prevalent co-location patterns without collecting co-location instances.- Integrating Geospatial Tools for Air Pollution Prediction: A Synthetic City Generator Framework for Efficient Modeling and Visualization.- Design of an Automated CNN Composition Scheme with Lightweight Depth-Correlated Convolution for Space-Limited Applications.

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Book SynopsisThis two-volume set LNAI 13995 and LNAI 13996 constitutes the refereed proceedings of the 15th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2023, held in Phuket, Thailand, during July 24–26, 2023. The 65 full papers presented in these proceedings were carefully reviewed and selected from 224 submissions. The papers of the 2 volume-set are organized in the following topical sections: Case-Based Reasoning and Machine Comprehension; Computer Vision; Data Mining and Machine Learning; Knowledge Integration and Analysis; Speech and Text Processing; and Resource Management and Optimization.Table of ContentsKnowledge Integration and Analysis.- A New Data Transformation and Resampling Approach for Prediction of Yield Strength of High-Entropy Alloys.- A Semi-Formal Approach to Describing Semantics of Data Modeling Patterns.- Obfuscating LLVM IR with the Application of Lambda Calculus.- Structural and Compact Latent Representation Learning on Sparse Reward Environments.- A Survey of Explainable Artificial Intelligence Approaches for Sentiment Analysis.- Social collective model of non-internet social networks.- A Data-driven Scheduling Strategy for Mobile Air Quality Monitoring Devices.- Hybrid approaches to sentiment analysis of social media data.- Integrating Ontology-based Knowledge to Improve BiomedicalMulti-Document Summarization Model.- An Improvement of Diachronic Embedding for Temporal Knowledge Graph Completion.- DCA-based weighted bagging: A new ensemble learning approach.- Deep-learning- and GCN-based Aspect-level Sentiment Analysis Methods on Balanced and Unbalanced Datasets.- Applying the Malmquist productivity index model to assess the performance of the coffee enterprise in DakLak Vietnam.- A Cluster-Constrained Graph Convolutional Network for Protein– Protein Association networks.- Fuzzy logic framework for ontology concepts alignment.- Can Ensemble Calibrated Learning enhance Link Prediction? A Study on Commonsense Knowledge.- Multi-criteria Approaches to Explaining Black Box Machine Learning Models.- Improving Loss Function for Polyp Detection Problem.- Flow Plugin Network for Conditional Generation.- Speech and Text Processing.- Investigating the Impact of Parkinson’s Disease on Brain Computations An Online Study of Healthy Controls and PD Patients.- Speech Enhancement using Dynamical Variational AutoEncoder.- Vietnamese Multidocument Summarization using Subgraph Selection-based Approach with Graph-informed Self-attention mechanism.- NegT5: A Cross-Task Text-to-Text Framework for Negation in Question Answering.- An Empirical Study on Punctuation Restoration for English, Mandarin, and Code-switching Speech.- Novel Topic Models for Parallel Topics Extraction from Multilingual Text.- Adapting Code-Switching Language Models with Statistical-Based Text Augmentation.- Improving Hotel Customer Sentiment Prediction by Fusing Review Titles and Contents.- Resource management and optimization.- In support of push-based streaming for the computing continuum.- Effective method of implementing constrained optimization problems using data instances.- Scheduling Deep Learning Training in GPU Cluster Using the Model-similarity-based Policy.

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Book SynopsisThis volume LNCS 14252 constitutes the refereed proceedings of 25th International Conference on Information and Communications Security, ICICS 2023, held in Tianjin, China, during November 18–20, 2023. The 38 full papers presented together with 6 short papers were carefully reviewed and selected from 181 submissions. The conference focuses on: Symmetric-Key Cryptography; Public-Key Cryptography; Applied Cryptography; Authentication and Authorization; Privacy and Anonymity; Security and Privacy of AI; Blockchain and Cryptocurrencies; and System and Network Security. Table of Contents​Symmetric-Key Cryptography.- SAT-aided Differential Cryptanalysis of Lightweight Block Ciphers Midori, MANTIS and QARMA.- Improved Related-Key Rectangle Attack against the Full AES-192.- Block Ciphers Classification Based on Randomness Test Statistic Value via LightGBM.- Cryptanalysis of Two White-Box Implementations of the CLEFIA Block Cipher.- PAE: Towards More Efficient and BBB-secure AE From a Single Public Permutation.- Public-Key Cryptography.- A Polynomial-time Attack on G2SIDH.- Improvements of Homomorphic Secure Evaluation of Inverse Square Root.- Oblivious Transfer from Rerandomizable PKE.- Forward Secure Lattice-based Ring Signature Scheme in the Standard Model.- Applied Cryptography.- Secure Multi-Party Computation with Legally-Enforceable Fairness.- On-demand Allocation of Cryptographic Computing Resource with Load Prediction.- Private Message Franking with After Opening Privacy.- Semi-Honest 2-Party Faithful Truncation from Two-Bit Extraction.- Outsourcing Verifiable Distributed Oblivious Polynomial Evaluation from Threshold Cryptography.- Authentication and Authorization.- PiXi: Password Inspiration by Exploring Information.- Security Analysis of Alignment-Robust Cancelable Biometric Scheme for Iris Verification.- A Certificateless Conditional Anonymous Authentication Scheme for Satellite Internet of Things.- BLAC: A Blockchain-based Lightweight Access Control Scheme in Vehicular Social Networks.- Privacy and Anonymity.- Link Prediction-Based Multi-Identity Recognition of Darknet Vendors.- CryptoMask: Privacy-preserving Face Recognition.- Efficient Private Multiset ID Protocols.- Zoomer: A Website Fingerprinting Attack against Tor Hidden Services.- An Enhanced Privacy-preserving Hierarchical Federated Learning Framework for IoV.- Security and Privacy of AI.- Revisiting the Deep Learning-based Eavesdropping Attacks via Facial Dynamics from VR Motion Sensors.- Multi-scale Features Destructive Universal Adversarial Perturbations.- Pixel-Wise Reconstruction of Private Data in Split Federated Learning.- Neural Network Backdoor Attacks Fully Controlled by Composite Natural Utterance Fragments.- Black-Box Fairness Testing with Shadow Models.- Graph Unlearning using Knowledge Distillation.- AFLOW: Developing Adversarial Examples under Extremely Noise-limited Settings.- Learning to Detect Deepfakes via Adaptive Attention and Constrained Difference.- A Novel Deep Ensemble Framework for Online Signature Verification Using Temporal and Spatial Representation.- Blockchain and Cryptocurrencies.- SCOPE: A Cross-Chain Supervision Scheme for Consortium Blockchains.- Subsidy Bridge: Rewarding Cross-blockchain Relayers with Subsidy.- Towards Efficient and Privacy-Preserving Anomaly Detection of Blockchain-based Cryptocurrency Transactions.- Blockchain based Publicly Auditable Multi-Party Computation with Cheater Detection.- BDTS: Blockchain-based Data Trading System.- Illegal Accounts Detection on Ethereum using Heterogeneous Graph Transformer Networks.- System and Network security.- DRoT: A Decentralised Root of Trust for Trusted Networks.- Finding Missing Security Operation Bugs via Program Slicing and Differential Check.- TimeClave: Oblivious In-enclave Time series Processing System.- Efficient and Appropriate Key Generation Scheme in Different IoT Scenarios.- A Fake News Detection Method Based on A Multimodal Cooperative Attention Network.

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Book SynopsisThe book is a comprehensive guide that explores the concept of data economy and its implications in today's world. The book discusses the principles and components of the ecosystem, the challenges and opportunities presented by data monetization, and the potential risks related to data privacy. Real-life examples and case studies are included to understand the concepts better. The book is suitable for individuals in data science, economics, business, and technology and for students, academics, and policymakers. It is an excellent read for anyone interested in the data economy.Table of ContentsChapter 1: Data Economy.- Chapter 2: Navigating the Data Deluge: Challenges and Opportunities.- Chapter 3: Data Monetization.- Chapter 4: Demographic Trend of Data Economy.- Chapter 5: The Economy of Data Privacy.- Chapter 6: Application of Data Economy.

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Book SynopsisThis introductory textbook teaches the simple development of geospatial applications based on the principles and software tools of geospatial data science. It introduces a new generation of geospatial technologies that have emerged from the development of the Semantic Web and the linked data paradigm, and shows how data scientists can use them to build environmental applications easily. Geospatial data science is the science of collecting, organizing, analyzing, and visualizing geospatial data. Since around 2010, there has been extensive work in the area of geospatial data science using semantic technologies and linked data, from researchers in the areas of the Semantic Web, Geospatial Databases and Geoinformatics. The main results of this research have been the publication of the OGC standard GeoSPARQL and the implementation of a number of linked data tools supporting this standard. Up to now, there has been no textbook that enables someone to teach this material to undergraduate or graduate students.The material of the book is developed in a tutorial style and it is appropriate for an introductory course on the subject. This can be an advanced undergraduate course or a graduate course offered by Computer Science or GIS faculty. It is a hands-on approach and every chapter contains exercises that help students master the material.The book is accompanied by a Web site where solutions to some of the exercises are given together with supplementary material such as datasets and code. Most of the material in the book has been tried in the "Knowledge Technologies" course taught by the first author in the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens since 2012.

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Book SynopsisThis introductory textbook teaches the simple development of geospatial applications based on the principles and software tools of geospatial data science. It introduces a new generation of geospatial technologies that have emerged from the development of the Semantic Web and the linked data paradigm, and shows how data scientists can use them to build environmental applications easily. Geospatial data science is the science of collecting, organizing, analyzing, and visualizing geospatial data. Since around 2010, there has been extensive work in the area of geospatial data science using semantic technologies and linked data, from researchers in the areas of the Semantic Web, Geospatial Databases and Geoinformatics. The main results of this research have been the publication of the OGC standard GeoSPARQL and the implementation of a number of linked data tools supporting this standard. Up to now, there has been no textbook that enables someone to teach this material to undergraduate or graduate students.The material of the book is developed in a tutorial style and it is appropriate for an introductory course on the subject. This can be an advanced undergraduate course or a graduate course offered by Computer Science or GIS faculty. It is a hands-on approach and every chapter contains exercises that help students master the material.The book is accompanied by a Web site where solutions to some of the exercises are given together with supplementary material such as datasets and code. Most of the material in the book has been tried in the "Knowledge Technologies" course taught by the first author in the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens since 2012.

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Book Synopsis1. Snowflake.- 2. The Snowflake Data Cloud.- 3. Getting Started with Snowflake SQL API.- 4. SQL Basics in Snowflake Using Snowflake SQL API.- 5. Advanced SQL Techniques using Snowflake SQL API.- 6. Data Security and Access Control.- 7. Performance Tuning and Optimization.- 8. Data Warehousing Best Practices.- 9. Working With Laravel 10.- 10. Architectural Patterns and Solutions.- 11. Community and Resources.- 12. Conclusion.

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Book SynopsisThis book is your comprehensive guide to building robust Generative AI solutions using the Databricks Data Intelligence Platform. Databricks is the fastest-growing data platform offering unified analytics and AI capabilities within a single governance framework, enabling organizations to streamline their data processing workflows, from ingestion to visualization. Additionally, Databricks provides features to train a high-quality large language model (LLM), whether you are looking for Retrieval-Augmented Generation (RAG) or fine-tuning. Databricks offers a scalable and efficient solution for processing large volumes of both structured and unstructured data, facilitating advanced analytics, machine learning, and real-time processing. In today's GenAI world, Databricks plays a crucial role in empowering organizations to extract value from their data effectively, driving innovation and gaining a competitive edge in the digital age. This book will not only help you master the Data Intelligence Platform but also help power your enterprise to the next level with a bespoke LLM unique to your organization. Beginning with foundational principles, the book starts with a platform overview and explores features and best practices for ingestion, transformation, and storage with Delta Lake. Advanced topics include leveraging Databricks SQL for querying and visualizing large datasets, ensuring data governance and security with Unity Catalog, and deploying machine learning and LLMs using Databricks MLflow for GenAI. Through practical examples, insights, and best practices, this book equips solution architects and data engineers with the knowledge to design and implement scalable data solutions, making it an indispensable resource for modern enterprises. Whether you are new to Databricks and trying to learn a new platform, a seasoned practitioner building data pipelines, data science models, or GenAI applications, or even an executive who wants to communicate the value of Databricks to customers, this book is for you. With its extensive feature and best practice deep dives, it also serves as an excellent reference guide if you are preparing for Databricks certification exams. What You Will LearnFoundational principles of Lakehouse architectureKey features including Unity Catalog, Databricks SQL (DBSQL), and Delta Live TablesDatabricks Intelligence Platform and key functionalitiesBuilding and deploying GenAI Applications from data ingestion to model servingDatabricks pricing, platform security, DBRX, and many more topicsWho This Book Is ForSolution architects, data engineers, data scientists, Databricks practitioners, and anyone who wants to deploy their Gen AI solutions with the Data Intelligence Platform. This is also a handbook for senior execs who need to communicate the value of Databricks to customers. People who are new to the Databricks Platform and want comprehensive insights will find the book accessible.

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Book SynopsisHarness the capabilities of Python and gain the expertise need to master data science techniques. This step-by-step book guides you through using Python to achieve tasks related to data cleaning, statistics, and visualization. You'll start by reviewing the foundational aspects of the data science process. This includes an extensive overview of research points and practical applications, such as the insightful analysis of presidential elections. The journey continues by navigating through installation procedures and providing valuable insights into Python, data types, typecasting, and essential libraries like Pandas and NumPy. You'll then delve into the captivating world of data visualization. Concepts such as scatter plots, histograms, and bubble charts come alive through detailed discussions and practical code examples, unraveling the complexities of creating compelling visualizations for enhanced data understanding. Statistical analysis, linear models, and advanced data preprocessing techniques are also discussed before moving on to preparing data for analysis, including renaming variables, variable rearrangement, and conditional statements. Finally, you'll be introduced to regression techniques, demystifying the intricacies of simple and multiple linear regression, as well as logistic regression. What You'll LearnUnderstand installation procedures and valuable insights into Python, data types, typecastingExamine the fundamental statistical analysis required in most data science and analytics reportsClean the most common data set problemsUse linear progression for data predictionWho This Book Is ForData Analysts, data scientists, Python programmers, and software developers new to data science.

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Book SynopsisYour MySQL instances are probably broken. Many developers face slow-running queries, issues related to database architecture, replication, or database securityand that's only the beginning. This book will deliver answers to your most pressing MySQL database questions related to performance, availability, or security by uncovering what causes databases to break in the first place. At its core, this book provides you with the knowledge necessary for you to break your database instances so you can better optimize it for performance and secure it from data breaches. In other words, you'll discover the sorts of actions, minor and major, that degrade databases so you can fix and ultimately preempt them. MySQL sometimes acts according to its own rules, and this book will help you keep it working on your terms. At the same time, you will learn to optimize your backup and recovery procedures, determine when and which data to index to achieve maximum performance, and choose the best MySQL configurations, among other essential skills. Most MySQL books focus exclusively on optimization, but this book argues that it's just as important to pay attention to the ways databases break. Indeed, after reading this book, you will be able to safely break your database instances to expose and overcome the nuanced issues that affect performance, availability, and security. What You Will LearnKnow the basics of MySQL and the storage engines innoDB and MyISAMSpot the ways you are harming your database's performance, availability and security without even realizing itFix minor bugs and issues that have surprisingly serious impactOptimize schema, data types, queries, indexes, and partitions to head off issuesUnderstand key MySQL security strategiesWho This Book Is ForDatabase administrators, web developers, systems administrators, and security professionals with an intermediary knowledge of database management systems and building applications in MySQL

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Book SynopsisMaster Oracle Database administration in both on-premises and cloud environments. This new edition covers the tasks you'll need to perform to keep your databases tuned and performing, and includes new, important innovations with AI Vector Search, JSON Duality Views, and Select AI. Since Oracle Database 23ai offers a choice of platforms with on-premises and cloud, the book also includes administrative tasks specific to cloud environments, including the Oracle Autonomous Database running in the Oracle Cloud Infrastructure. New in this edition is help for DBAs who are becoming involved in data management, and a look at the idea of a converged database and what that means in handling various data types and workloads. The book covers some of the machine learning features now in Oracle and shows how the same SQL that you know for database administration also helps you with data management tasks. The information in this book helps you to apply the right solution at the right time, mitigating risk and making robust choices that protect your data and avoid midnight phone calls. Data management is increasingly a DBA function, and DBAs are often called upon for help in getting data loaded into analytics environments such as a data lakehouse or a data mesh. This book addresses this fast-growing new role for database administrators and helps you build on your existing knowledge to make the transition into a new skill set that is in high demand. You'll learn how to look at data optimization from the standpoint of data analysis and machine learning so that you can be seen as a key player in preparing your organization's data for those type of activities. You'll know how to pull back information from a combination of relational tables and JSON structures. You'll become familiar with the tools that Oracle Database provides to make analytics easier and more straightforward. And you'll learn simpler ways to manage time-based tables that eliminate the need for painfully creating triggers to track the history of row changes over time. This book builds your skills as an Oracle Database administrator with the aim of helping you to be seen as a key player in data management as your organization pivots toward cloud computing and a greater use of machine learning and analytics technologies. What You Will LearnConfigure and manage Oracle 23ai databases both on-premises and in the cloudMeet your DBA responsibilities in the Oracle Cloud and with Database Cloud ServicesLeverage converged database capabilities to manage different workloads, structured and unstructured dataPerform administrative tasks for Autonomous Database dedicated environmentsPerform DBA tasks and effectively use data management toolsMigrate from on-premises to the Oracle Cloud InfrastructureTroubleshoot issues with Oracle 23ai databases and quickly solve performance problemsArchitect cloud, on-premises, hybrid, and multi-cloud database environmentsWho This Book Is ForOracle database administrators (DBAs) who want to be current with the new features in Oracle Database 23ai. For any DBA who is tasked with managing Oracle databases in cloud, hybrid cloud, and multi-cloud configurations. Also helpful for data architects who are designing analytic solutions in data lake house and data mesh environments.

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Book Synopsis

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