These are the proceedings of the Eleventh International Information Security Conference which was held in Cape Town, South Africa, May 1995. This conference addressed the information security requirements of the next decade and papers were presented covering a wide range of subjects including current industry expectations and current research aspects. The evolutionary development of information security as a professional and research discipline was discussed along with security in open distributed systems and security in groupware.

Signal processing captures, interprets, describes and manipulates physical phenomena. Mathematics, statistics, probability, and stochastic processes are among the signal processing languages we use to interpret real-world phenomena, model them, and extract useful information. This book presents different kinds of signals humans use and applies them for human machine interaction to communicate. Signal Processing and Machine Learning with Applications presents methods that are used to perform various Machine Learning and Artificial Intelligence tasks in conjunction with their applications. It is organized in three parts: Realms of Signal Processing; Machine Learning and Recognition; and Advanced Applications and Artificial Intelligence. The comprehensive coverage is accompanied by numerous examples, questions with solutions, with historical notes. The book is intended for advanced undergraduate and postgraduate students, researchers and practitioners who are engaged with signal processing, machine learning and the applications.

This book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world optimization problems. The ever-increasing application of the LA as a promising reinforcement learning technique in artificial intelligence makes it necessary to provide scholars, scientists, and engineers with a practical discussion on LA solutions for optimization. The book starts with a brief introduction to LA models for optimization. Afterward, the research areas related to LA and optimization are addressed as bibliometric network analysis. Then, LA's application in behavior control in evolutionary computation, and memetic models of object migration automata and cellular learning automata for solving NP hard problems are considered. Next, an overview of multi-population methods for DOPs, LA's application in dynamic optimization problems (DOPs), and the function evaluation management in evolutionary multi-population for DOPs are discussed. Highlighted benefits * Presents the latest advances in learning automata-based optimization approaches. * Addresses the memetic models of learning automata for solving NP-hard problems. * Discusses the application of learning automata for behavior control in evolutionary computation in detail. * Gives the fundamental principles and analyses of the different concepts associated with multi-population methods for dynamic optimization problems.

Digital Libraries and Multimedia brings together in one place important contributions and up-to-date research results in this fast moving area. Digital Libraries and Multimedia serves as an excellent reference, providing insight into some of the most challenging research issues in the field.

This book features selected papers presented at the 3rd International Conference on Recent Innovations in Computing (ICRIC 2020), held on 20-21 March 2020 at the Central University of Jammu, India, and organized by the university's Department of Computer Science & Information Technology. It includes the latest research in the areas of software engineering, cloud computing, computer networks and Internet technologies, artificial intelligence, information security, database and distributed computing, and digital India.

Jump-start your career as a data scientist--learn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that's dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls. You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data. This guide for data scientists differs from other instructional guides on the subject. It doesn't cover SQL broadly. Instead, you'll learn the subset of SQL skills that data analysts and data scientists use frequently. You'll also gain practical advice and direction on "how to think about constructing your dataset." Gain an understanding of relational database structure, query design, and SQL syntax Develop queries to construct datasets for use in applications like interactive reports and machine learning algorithms Review strategies and approaches so you can design analytical datasets Practice your techniques with the provided database and SQL code In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner's perspective, moving your data scientist career forward!

This book projects a futuristic scenario that is more existent than they have been at any time earlier. To be conscious of the bursting prospective of IoT, it has to be amalgamated with AI technologies. Predictive and advanced analysis can be made based on the data collected, discovered and analyzed. To achieve all these compatibility, complexity, legal and ethical issues arise due to automation of connected components and gadgets of widespread companies across the globe. While these are a few examples of issues, the authors' intention in editing this book is to offer concepts of integrating AI with IoT in a precise and clear manner to the research community. In editing this book, the authors' attempt is to provide novel advances and applications to address the challenge of continually discovering patterns for IoT by covering various aspects of implementing AI techniques to make IoT solutions smarter. The only way to remain pace with this data generated by the IoT and acquire the concealed acquaintance it encloses is to employ AI as the eventual catalyst for IoT. IoT together with AI is more than an inclination or existence; it will develop into a paradigm. It helps those researchers who have an interest in this field to keep insight into different concepts and their importance for applications in real life. This has been done to make the edited book more flexible and to stimulate further interest in topics. All these motivated the authors toward integrating AI in achieving smarter IoT. The authors believe that their effort can make this collection interesting and highly attract the student pursuing pre-research, research and even master in multidisciplinary domain.

Improve the performance of relational databases with indexes designed for today's hardware
Over the last few years, hardware and software have advanced beyond all recognition, so it's hardly surprising that relational database performance now receives much less attention. Unfortunately, the reality is that the improved hardware hasn't kept pace with the ever-increasing quantity of data processed today. Although disk packing densities have increased enormously, making storage costs extremely low and sequential read very fast, random reads are still painfully slow. Many of the old design recommendations are therefore no longer valid-the optimal point of indexing has come a long way. Consequently many of the old problems haven't actually gone away-they have simply changed their appearance.
This book provides an easy but effective approach to the design of indexes and tables. Using lots of examples and case studies, the authors describe how the DB2, Oracle, and SQL Server optimizers determine how to access data, and how CPU and response times for the resulting access paths can be quickly estimated. This enables comparisons to be made of the various designs, and helps you choose available choices for the most appropriate design.
This book is intended for anyone who wants to understand the issues of SQL performance or how to design tables and indexes effectively. With this title, readers with many years of experience of relational systems will be able to better grasp the implications that have been brought into play by the introduction of new hardware.
An Instructor's Manual presenting detailed solutions to all the problems in the book is available online from the Wiley editorial department.
An Instructor Support FTP site is also available.

Explains the basic concepts of Python and its role in machine learning Provides comprehensive coverage of feature-engineering including real-time case studies Perceive the structural patterns with reference to data science and statistics and analytics Includes machine learning based structured exercises Appreciates different algorithmic concepts of machine learning including unsupervised, supervised and reinforcement learning

This book addresses the emerging paradigm of data-driven engineering design. In the big-data era, data is becoming a strategic asset for global manufacturers. This book shows how the power of data can be leveraged to drive the engineering design process, in particular, the early-stage design. Based on novel combinations of standing design methodology and the emerging data science, the book presents a collection of theoretically sound and practically viable design frameworks, which are intended to address a variety of critical design activities including conceptual design, complexity management, smart customization, smart product design, product service integration, and so forth. In addition, it includes a number of detailed case studies to showcase the application of data-driven engineering design. The book concludes with a set of promising research questions that warrant further investigation. Given its scope, the book will appeal to a broad readership, including postgraduate students, researchers, lecturers, and practitioners in the field of engineering design.

Information Retrieval has become a very active research field in the 21st century. Many from academia and industry present their innovations in the field in a wide variety of conferences and journals. Companies transfer this new knowledge directly to the general public via services such as web search engines in order to improve their information seeking experience.

In parallel, teaching IR is turning into an important aspect of IR generally, not only because it is necessary to impart effective search techniques to make the most of the IR tools available, but also because we must provide a good foundation for those students who will become the driving force of future IR technologies.

There are very few resources for teaching and learning in IR, the major problem which this book is designed to solve. The objective is to provide ideas and practical experience of teaching and learning IR, for those whose job requires them to teach in one form or another, and where delivering IR courses is a major part of their working lives.

In this context of providing a higher profile for teaching and learning as applied to IR, the co-editor of this book, Efthimis Efthimiathis, had maintained a leading role in teaching and learning within the domain of IR for a number of years. This book represents a posthumous example of his efforts in the area, as he passed away in April 2011. This book, his book, is dedicated to his memory."

This book focuses on the implementation of AI for growing business, and the book includes research articles and expository papers on the applications of AI on decision-making, health care, smart universities, public sector and digital government, FinTech, and RegTech. Artificial Intelligence (AI) is a vital and a fundamental driver for the Fourth Industrial Revolution (FIR). Its influence is observed at homes, in the businesses and in the public spaces. The embodied best of AI reflects robots which drive our cars, stock our warehouses, monitor our behaviors and warn us of our health, and care for our young children. Some researchers also discussed the role of AI in the current COVID-19 pandemic, whether in the health sector, education, and others. On all of these, the researchers discussed the impact of AI on decision-making in those vital sectors of the economy.

This book presents the select proceedings of the International Conference on Evolution in Manufacturing (ICEM 2020), and examines a range of areas including evolution in manufacturing, intelligent networks, bio-Inspired models and algorithms, internet-of-things, and cyber manufacturing. This book intends to provide a contribution to the domain of collaborative and intelligent networks and systems to fill the gap in theories and practical applications through suitable methods and solutions applicable to a wide range of instances. Various topics covered include broad range of research challenges in the fields of artificial intelligence and addressing current and future trends in industry 4.0 oriented scenario, data analytics and big data, operation and manufacturing management. The book will be a valuable reference for beginners, researchers and professionals interested in artificial intelligence in engineering and production management and allied fields.

This book provides practical information about web archives, offers inspiring examples for web archivists, raises new challenges, and shares recent research results about access methods to explore information from the past preserved by web archives. The book is structured in six parts. Part 1 advocates for the importance of web archives to preserve our collective memory in the digital era, demonstrates the problem of web ephemera and shows how web archiving activities have been trying to address this challenge. Part 2 then focuses on different strategies for selecting web content to be preserved and on the media types that different web archives host. It provides an overview of efforts to address the preservation of web content as well as smaller-scale but high-quality collections of social media or audiovisual content. Next, Part 3 presents examples of initiatives to improve access to archived web information and provides an overview of access mechanisms for web archives designed to be used by humans or automatically accessed by machines. Part 4 presents research use cases for web archives. It also discusses how to engage more researchers in exploiting web archives and provides inspiring research studies performed using the exploration of web archives. Subsequently, Part 5 demonstrates that web archives should become crucial infrastructures for modern connected societies. It makes the case for developing web archives as research infrastructures and presents several inspiring examples of added-value services built on web archives. Lastly, Part 6 reflects on the evolution of the web and the sustainability of web archiving activities. It debates the requirements and challenges for web archives if they are to assume the responsibility of being societal infrastructures that enable the preservation of memory. This book targets academics and advanced professionals in a broad range of research areas such as digital humanities, social sciences, history, media studies and information or computer science. It also aims to fill the need for a scholarly overview to support lecturers who would like to introduce web archiving into their courses by offering an initial reference for students.

This book summarizes recent inventions, provides guidelines and recommendations, and demonstrates many practical applications of homomorphic encryption. This collection of papers represents the combined wisdom of the community of leading experts on Homomorphic Encryption. In the past 3 years, a global community consisting of researchers in academia, industry, and government, has been working closely to standardize homomorphic encryption. This is the first publication of whitepapers created by these experts that comprehensively describes the scientific inventions, presents a concrete security analysis, and broadly discusses applicable use scenarios and markets. This book also features a collection of privacy-preserving machine learning applications powered by homomorphic encryption designed by groups of top graduate students worldwide at the Private AI Bootcamp hosted by Microsoft Research. The volume aims to connect non-expert readers with this important new cryptographic technology in an accessible and actionable way. Readers who have heard good things about homomorphic encryption but are not familiar with the details will find this book full of inspiration. Readers who have preconceived biases based on out-of-date knowledge will see the recent progress made by industrial and academic pioneers on optimizing and standardizing this technology. A clear picture of how homomorphic encryption works, how to use it to solve real-world problems, and how to efficiently strengthen privacy protection, will naturally become clear.

This book describes important methodologies, tools and techniques from the fields of artificial intelligence, basically those which are based on relevant conceptual and formal development. The coverage is wide, ranging from machine learning to the use of data on the Semantic Web, with many new topics. The contributions are concerned with machine learning, big data, data processing in medicine, similarity processing in ontologies, semantic image analysis, as well as many applications including the use of machine leaning techniques for cloud security, artificial intelligence techniques for detecting COVID-19, the Internet of things, etc. The book is meant to be a very important and useful source of information for researchers and doctoral students in data analysis, Semantic Web, big data, machine learning, computer engineering and related disciplines, as well as for postgraduate students who want to integrate the doctoral cycle.

This book offers ideas to help improve digital technologies and increase their efficiency during implementation and application for researchers and practitioners. The outstanding position of the book among others is that it dwells with cyber-physical systems' progress and proposes ideas and finding around digital tools and technologies and their application. A distinguished contribution is in presenting results on Digital Twins development and application, enhancing approaches of communication and information transferring between cyber-physical systems connected within the Internet of things platforms, computer linguistic as a part of cyber-physical systems, intelligent cybersecurity and computer vision systems. The target audience of this book also includes practitioners and experts, as well as state authorities and representatives of manufacturing and industry who are interested in creating and implementing of cyber-physical systems in framework of digitalization projects.

This book addresses one of the most overlooked practical, methodological, and moral questions in the journey to secure and handle the massive amount of data being generated from smart devices interactions: the integration of Blockchain with 5G-enabled IoT. After an overview, this book discusses open issues and challenges, which may hinder the growth of Blockchain technology. Then, this book presents a variety of perspectives on the most pressing questions in the field, such as: how IoT can connect billions of objects together; how the access control mechanisms in 5G-enabled industrial environment works; how to address the real-time and quality-of-service requirements for industrial applications; and how to ensure scalability and computing efficiency. Also, it includes a detailed discussions on the complexity of adoption of Blockchain for 5G-Enabled IoT and presents comparative case studies with respect to various performance evaluation metrics such as scalability, data management, standardization, interoperability and regulations, accessibility, human-factors engineering and interfaces, reliability, heterogeneity, and QoS requirements. This book acts as a professional guide for the practitioners in information security and related topics.

This book covers a variety of smart IoT applications for industry and research. For industry, the book is a guide for considering the real-time aspects of automation of application domains. The main topics covered in the industry section include real-time tracking and navigation, smart transport systems and application for GPS domains, modern electric grid control for electricity industry, IoT prospectives for modern society, IoT for modern medical science, and IoT automation for Industry 4.0. The book then provides a summary of existing IoT research that underlines enabling technologies, such as fog computing, wireless sensor networks, data mining, context awareness, real-time analytics, virtual reality, and cellular communications. The book pertains to researchers, outcome-based academic leaders, as well as industry leaders.

This book focuses on the combination of IoT and data science, in particular how methods, algorithms, and tools from data science can effectively support IoT. The authors show how data science methodologies, techniques and tools, can translate data into information, enabling the effectiveness and usefulness of new services offered by IoT stakeholders. The authors posit that if IoT is indeed the infrastructure of the future, data structure is the key that can lead to a significant improvement of human life. The book aims to present innovative IoT applications as well as ongoing research that exploit modern data science approaches. Readers are offered issues and challenges in a cross-disciplinary scenario that involves both IoT and data science fields. The book features contributions from academics, researchers, and professionals from both fields.

Advanced Database Indexing begins by introducing basic material on storage media, including magnetic disks, RAID systems and tertiary storage such as optical disk and tapes. Typical access methods (e.g. B+ trees, dynamic hash files and secondary key retrieval) are also introduced. The remainder of the book discusses recent advances in indexing and access methods for particular database applications. More specifically, issues such as external sorting, file structures for intervals, temporal access methods, spatial and spatio-temporal indexing, image and multimedia indexing, perfect external hashing methods, parallel access methods, concurrency issues in indexing and parallel external sorting are presented for the first time in a single book. Advanced Database Indexing is an excellent reference for database professionals and may be used as a text for advanced courses on the topic.

The book highlights recent developments in human biometrics, covering a wide range of methods based on biological signals, image processing, and measurements of human characteristics such as fingerprints and iris or medical characteristics. Human Biometrics is becoming increasingly crucial in forensics security and medicine. They provide a solid basis for identifying individuals based on unique physical characteristics or diseases based on characteristic biomedical measurements. As such, the book offers an essential reference guide about biometry methods for students, engineers, designers, and technicians.

This book presents a comprehensive collection of case studies on augmented reality and virtual realty (AR/VR) applications in various industries. Augmented reality and virtual reality are changing the business landscape, providing opportunities for businesses to offer unique services and experiences to their customers. The case studies provided in this volume explore business uses of the technology across multiple industries such as healthcare, tourism, hospitality, events, fashion, entertainment, retail, education and video gaming. The book includes solutions of different maturities as well as those from startups to large enterprises thereby providing a thorough view of how augmented reality and virtual reality can be used in business.

This book constitutes the refereed proceedings of the 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, held in Costa de Caparica, Portugal, in July 2021.*The 34 papers presented were carefully reviewed and selected from 92 submissions. The papers present selected results produced in engineering doctoral programs and focus on technological innovation for industry and service systems. Research results and ongoing work are presented, illustrated and discussed in the following areas: collaborative networks; smart manufacturing; cyber-physical systems and digital twins; intelligent decision making; smart energy management; communications and electronics; classification systems; smart healthcare systems; and medical devices. *The conference was held virtually. Chapters "Characteristics of Adaptable Control of Production Systems and the Role of Self-organization Towards Smart Manufacturing" and "Predictive Manufacturing: Enabling Technologies, Frameworks and Applications" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book comprises the best deliberations with the theme "Smart Innovations in Mezzanine Technologies, Data Analytics, Networks and Communication Systems" in the "International Conference on Advances in Computer Engineering and Communication Systems (ICACECS 2020)", organized by the Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology. The book provides insights on the recent trends and developments in the field of computer science with a special focus on the mezzanine technologies and creates an arena for collaborative innovation. The book focuses on advanced topics in artificial intelligence, machine learning, data mining and big data computing, cloud computing, Internet on things, distributed computing and smart systems.