This text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing. It comprehensively covers important topics including data integration, data mining, machine learning, genetic algorithms, evolutionary computation, evolved neural networks, nature-inspired algorithms, and protein structure alignment. The text covers the application of evolutionary computations for fractal visualization of sequence data, artificial intelligence, and automatic image interpretation in modern biological systems. The text is primarily written for graduate students and academic researchers in areas of electrical engineering, electronics engineering, computer engineering, and computational biology. This book: * Covers algorithms in the fields of artificial intelligence, and machine learning useful in biological data analysis. * Discusses comprehensively artificial intelligence and automatic image interpretation in modern biological systems. * Presents the application of evolutionary computations for fractal visualization of sequence data. * Explores the use of genetic algorithms for pair-wise and multiple sequence alignments. * Examines the roles of efficient computational techniques in biology.

With the growing interest in and use of big data analytics in many industries and in many research fields around the globe, this new volume addresses the need for a comprehensive resource on the core concepts of big data analytics along with the tools, techniques, and methodologies. The book gives the why and the how of big data analytics in an organized and straightforward manner, using both theoretical and practical approaches. The book's authors have organized the contents in a systematic manner, starting with an introduction and overview of big data analytics and then delving into pre-processing methods, feature selection methods and algorithms, big data streams, and big data classification. Such terms and methods as swarm intelligence, data mining, the bat algorithm and genetic algorithms, big data streams, and many more are discussed. The authors explain how deep learning and machine learning along with other methods and tools are applied in big data analytics. The last section of the book presents a selection of illustrative case studies that show examples of the use of data analytics in industries such as health care, business, education, and social media. Research Practitioner's Handbook on Big Data Analytics will be a valuable addition to the libraries of practitioners in data collection in many industries along with research scholars and faculty in the domain of big data analytics. The book can also serve as a handy textbook for courses in data collection, data mining, and big data analytics.

Nowadays, raw biological data can be easily stored as databases in computers but extracting the required information is the real challenge for researchers. For this reason, bioinformatics tools perform a vital role in extracting and analyzing information from databases. Bioinformatics Tools and Big Data Analytics for Patient describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery for patient care. The book gives details about the recent developments in the fields of artificial intelligence, cloud computing, and data analytics. It highlights the advances in computational techniques used to perform intelligent medical tasks. Features: Presents recent developments in the fields of artificial intelligence, cloud computing, and data analytics for improved patient care. Describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery. Summarizes several strategies, analyses, and optimization methods for patient healthcare. Focuses on drug discovery and development by cloud computing and data-driven research The targeted audience comprises academics, research scholars, healthcare professionals, hospital managers, pharmaceutical chemists, the biomedical industry, software engineers, and IT professionals.

'Real science can be far stranger than science fiction, and much more satisfying' Will artificial intelligence outsmart us? Is there other intelligent life in the universe? Throughout his extraordinary career, Stephen Hawking expanded our understanding of the universe and unravelled some of its greatest mysteries. Will Artificial Intelligence Outsmart Us? considers the threat of artificial super-intelligence - as well as the likelihood of intelligent life beyond our planet. 'Modest, profound and sometimes very funny' Sunday Times Brief Answers, Big Questions: this stunning paperback series offers electrifying essays from one of the greatest minds of our age, taken from the original text of the No. 1 bestselling Brief Answers to the Big Questions.

Digital transformation is a multidimensional concept and involves many moving parts. Successful digital transformation requires a fresh approach to harnessing people, processes, technology, and data to develop new business models and digital ecosystems. One main barrier could be an overemphasis on applying technology to expand the business rather than transforming the people's mindsets to do things differently. Thus, it is important to develop a holistic view of these parts and assemble them to foster the right conditions for digital transformation to happen. Business leaders and executives must be equipped with a wide range of digital competencies to thrive in a rapidly changing digital environment. Digital Transformation: Strategy, Execution, and Technology provides an overall view on the strategy, execution, and technology for organizations aiming to transform digitally. It offers insights on how to become more successful in the digital age by explaining the importance and relevance of the various building blocks which form the foundation of a digital organization. It shows the reader how to develop these building blocks in the organization as part of the digital transformation journey from both a business and technical perspective. Highlights of the book include: Digital transformation strategy Digital governance and risk management Digital organization and change management Experimental learning and design thinking Digital product management Agile and DevSecOps Digital enterprise architecture Business applications of digital technology This practical guide is written keeping business and information technology professionals and digital transformation practitioners in mind. It is also suitable for students pursuing postgraduate degrees and participants attending executive education programs in business and information technology.

Since the invention of computers or machines, scientists and researchers are trying very hard to enhance their capabilities to perform various tasks. As a consequence, the capabilities of computers are growing exponentially day by day in terms of diverse working domains, versatile jobs, processing speed, and reduced size. Now, we are in the race to make the computers or machines as intelligent as human beings. Artificial Intelligence (AI) came up as a way of making a computer or computer software think in the similar manner the intelligent humans think. AI is inspired by the study of human brain like how humans think, learn, decide and act while trying to solve a problem. The outcomes of this study are the basis of developing intelligent software and systems or Intelligent Computing (IC). An IC system has the capability of reasoning, learning, problem solving, perception, and linguistic intelligence. The IC systems consist of AI techniques as well as other emerging techniques that make a system intelligent. The use of intelligent computing has been seen in almost every sub-domain of computer science such as networking, software engineering, gaming, natural language processing, computer vision, image processing, data science, robotics, expert systems, and security. Now a days, the use of IC can also be seen for solving various complex problems in diverse domains such as for predicting disease in medical science, predicting land fertility or crop productivity in agriculture science, predicting market growth in economics, weather forecasting and so on. For all these reasons, this book presents the advances in AI techniques, under the umbrella of IC. In this context, the book includes the recent research works have been done in the areas of machine learning, neural networks, deep learning, evolutionary algorithms, genetic algorithms, swarm intelligence, fuzzy systems and so on. This book provides theoretical, algorithmic, simulation, and implementation-based recent research advancements related to the Intelligent Computing.

This book aims to increase the visibility of data science in real-world, which differs from what you learn from a typical textbook. Many aspects of day-to-day data science work are almost absent from conventional statistics, machine learning, and data science curriculum. Yet these activities account for a considerable share of the time and effort for data professionals in the industry. Based on industry experience, this book outlines real-world scenarios and discusses pitfalls that data science practitioners should avoid. It also covers the big data cloud platform and the art of data science, such as soft skills. The authors use R as the primary tool and provide code for both R and Python. This book is for readers who want to explore possible career paths and eventually become data scientists. This book comprehensively introduces various data science fields, soft and programming skills in data science projects, and potential career paths. Traditional data-related practitioners such as statisticians, business analysts, and data analysts will find this book helpful in expanding their skills for future data science careers. Undergraduate and graduate students from analytics-related areas will find this book beneficial to learn real-world data science applications. Non-mathematical readers will appreciate the reproducibility of the companion R and python codes. Key Features: * It covers both technical and soft skills. * It has a chapter dedicated to the big data cloud environment. For industry applications, the practice of data science is often in such an environment. * It is hands-on. We provide the data and repeatable R and Python code in notebooks. Readers can repeat the analysis in the book using the data and code provided. We also suggest that readers modify the notebook to perform analyses with their data and problems, if possible. The best way to learn data science is to do it!

An Introduction to R and Python for Data Analysis helps teach students to code in both R and Python simultaneously. As both R and Python can be used in similar manners, it is useful and efficient to learn both at the same time, helping lecturers and students to teach and learn more, save time, whilst reinforcing the shared concepts and differences of the systems. This tandem learning is highly useful for students, helping them to become literate in both languages, and develop skills which will be handy after their studies. This book presumes no prior experience with computing, and is intended to be used by students from a variety of backgrounds. The side-by-side formatting of this book helps introductory graduate students quickly grasp the basics of R and Python, with the exercises providing helping them to teach themselves the skills they will need upon the completion of their course, as employers now ask for competency in both R and Python. Teachers and lecturers will also find this book useful in their teaching, providing a singular work to help ensure their students are well trained in both computer languages. All data for exercises can be found here: https://github.com/tbrown122387/r_and_python_book/tree/master/data. Key features: - Teaches R and Python in a "side-by-side" way. - Examples are tailored to aspiring data scientists and statisticians, not software engineers. - Designed for introductory graduate students. - Does not assume any mathematical background.

In recent years, there has been steady increase in the interest shown in both big data analytics and the use of information technology (IT) solutions to improve healthcare services. Despite the growing interest, there are limited materials, to addressing the needs and challenges posed by the activities and processes including the use of big data. From IT solutions' perspectives, this book aims to advance the deployment and use of big data analytics to increase patients' big data usefulness and improve healthcare service delivery. The book provides significant insights and useful guide on how to access and manage big data, in improving healthcare service delivery. The book contributes a fresh perspective, which primarily comes from the complementary use of analytics approach with actor-network theory (ANT), and other techniques, in advancing healthcare service delivery. Accessing and managing healthcare big data have always been a challenging exercise. Due to the sensitivity of the health sector, the focus on patients' big data is from either technical or social perspective. Thus, the book employs sociotechnical theories, ANT and structuration theory (ST) as lenses to examine and explain the factors that enable and constrain the use of patients' big data for health services. By doing so, the book brings a different dimension and advance health service delivery. Providing a timely and important contribution to this critical area, this book is a valuable, international resource for academics, postgraduate students and researchers in the areas of IT, big data analytics, data management and health informatics.

The only complete guide to photography designed specifically for women who want to improve their photographic skills for both pleasure and profit. With inspirational case studies and examples from professional and semi-pro female photographers, user-friendly technical explanations and image critiques, this book is a practical and useful toolkit for busy girls who enjoy photography.

Becoming an accomplished and competent photographer needs to be approached in three stages: Understand your camera and learn how to drive it; Composition - tune in and understand your subject; Post production - share and print.

Rather than explain every technical function from the outset, the aim of this book is to demystify the jargon and take you, step by step, back to the basic fundamental principals of photography; first putting you in control of the camera which will, in turn, free up the composition and creativity. The more advanced features of the camera and in-depth processes can be explored once the basic principals are understood.

This is a fun, contemporary photography book that will become your essential tool for taking your passion for photography to the next level.

Gain a thorough understanding of how modern audits are conducted in today's computer-driven business environment with INFORMATION TECHNOLOGY AUDITING, 4E. You gain valuable insights into state-of-the-art auditing issues as this leading accounting text provides you with the background you need to succeed in today's business world. This edition focuses on the latest information technology aspects of auditing with up-to-date coverage of auditor responsibilities, emerging legislation, and today's fraud techniques and detection. Expanded end-of-chapter questions, problems, and cases give you important hands-on practice for success in your future career.

This book examines third-party review sites (TPRS) and the intersection of the review economy and neoliberal public relations, in order to understand how users and organizations engage the 21st century global review economy. The author applies communication and digital media theories to evaluate contemporary case studies that challenge TPRS and control over digital reputation. Chapters analyze famous cases such as the Texas photographer who sued her clients for negative reviews and activists using Yelp to protest the hunt of "Cecil the Lion," to illustrate the complicated yet important role of TPRS in the review economy. Theories such as neoliberal public relations, digital dialogic communication and cultural intermediaries help explain the impact of reviews and how to apply lessons learned from infamous cases. This nuanced and up to date exploration of the contemporary review economy will offer insights and best practice for academic researchers and upper-level undergraduate students in public relations, digital media, or strategic communication programs.

This comprehensive guide walks readers through the entire process of getting and keeping a writing job in the games industry. It outlines exactly what a beginner needs to know about education requirements, finding opportunities, applying for roles, and acing studio interviews. Professional writers will learn how to navigate studio hierarchies, transfer roles and companies, work overseas, and keep developing their careers. Written by an experienced games writer with nearly two decades of industry knowledge, the book contains a wealth of interviews and perspectives with industry leaders, hiring managers, and developers from marginalized communities, all offering their tips and insights. Included are examples of materials such as job posts, writing samples, and portfolios, as well as chapter end challenges for readers to directly apply the skills they have learnt. This book will be of great interest to all beginner and aspiring games writers and narrative designers, as well as more experienced writers looking to hone their skills.

Designing Software Synthesizer Plugins in C++ provides everything you need to know to start designing and writing your own synthesizer plugins, including theory and practical examples for all of the major synthesizer building blocks, from LFOs and EGs to PCM samples and morphing wavetables, along with complete synthesizer example projects. The book and accompanying SynthLab projects include scores of C++ objects and functions that implement the synthesizer building blocks as well as six synthesizer projects, ranging from virtual analog and physical modelling to wavetable morphing and wave-sequencing that demonstrate their use. You can start using the book immediately with the SynthLab-DM product, which allows you to compile and load mini-modules that resemble modular synth components without needing to maintain the complete synth project code. The C++ objects all run in a stand-alone mode, so you can incorporate them into your current projects or whip up a quick experiment. All six synth projects are fully documented, from the tiny SynthClock to the SynthEngine objects, allowing you to get the most from the book while working at a level that you feel comfortable with. This book is intended for music technology and engineering students, along with DIY audio programmers and anyone wanting to understand how synthesizers may be implemented in C++.

Security, privacy, and trust in the Internet of Things (IoT) and CPS (Cyber-Physical Systems) are different from conventional security as concerns revolve around the collection and aggregation of data or transmission of data over the network. Analysis of cyber-attack vectors and the provision of appropriate mitigation techniques are essential research areas for these systems. Adoption of best practices and maintaining a balance between ease of use and security are, again, crucial for the effective performance of these systems. Recent Advances in Security, Privacy and Trust for Internet of Things (IoT) and Cyber-Physical Systems (CPS) discusses and presents techniques and methodologies, as well as a wide range of examples and illustrations, to effectively show the principles, algorithms, challenges, and applications of security, privacy, and trust for IoT and CPS. Book features: Introduces new directions for research, development, and engineering security, privacy, and trust of IoT and CPS Includes a wealth of examples and illustrations to effectively demonstrate the principles, algorithms, challenges, and applications Covers most of the important security aspects and current trends not present in other reference books This book will also serve as an excellent reference in security, privacy, and trust of IoT and CPS for professionals in this fast-evolving and critical field. The chapters present high-quality contributions from researchers, academics, and practitioners from various national and international organizations and universities.

Independent Videogames investigates the social and cultural implications of contemporary forms of independent video game development. Through a series of case studies and theoretical investigations, it evaluates the significance of such a multi-faceted phenomenon within video game and digital cultures. A diverse team of scholars highlight the specificities of independence within the industry and the culture of digital gaming through case studies and theoretical questions. The chapters focus on labor, gender, distribution models and technologies of production to map the current state of research on independent game development. The authors also identify how the boundaries of independence are becoming opaque in the contemporary game industry - often at the cost of the claims of autonomy, freedom and emancipation that underlie the indie scene. The book ultimately imagines new and better narratives for a less exploitative and more inclusive videogame industry. Systematically mapping the current directions of a phenomenon that is becoming increasingly difficult to define and limit, this book will be a crucial resource for scholars and students of game studies, media history, media industries and independent gaming.

Covers applications of various image processing techniques in thermal imaging applications for diagnosis of different medical conditions Describes the development of a computer diagnostics system (CAD) based on thermographic data Discusses customized deep learning models for accurate diagnosis of various diseases Includes new aspects in rheumatoid arthritis and diabetes research with usage of advanced analytical tools Reviews application of feature fusion algorithms and feature reduction algorithms for accurate classification of images

By proposing and forming a mobile manipulator for modern multi-floor buildings, A Robotic Framework for the Mobile Manipulator: Theory and Application helps readers visualize an end-to-end workflow for making a robot system work in a targeted environment. From a product-oriented viewpoint, this book is considered as a bridge from theories to real products, in which robotic software modules and the robotic system integration are mainly concerned. In the end, readers will have an overview of how to build and integrate various single robotic modules to execute a list of designed tasks in the real world, as well as how to make a robot system work independently, without human interventions. With references and execution guidelines provided at the end of each chapter, the book will be a useful tool for developers and researchers looking to expand their knowledge about the robotics and the robotic software.

- First book to focus on deep learning-based approaches in the field of cancer diagnostics. - Covers the state of the art across a wide-range of topics. - Topics include preprocessing data, prediction of cancer susceptibility and reoccurence, detection of different cancers, complexity and challenges.

Offers access to projects of some of the top professionals working in Real-Time Content Production today like engineering teams from "The Mandalorian" & League of Legends as well as video content designers for The Foo Fighters and Back to the Future, The Musical Includes reviews of real-time content production workflow for virtual production Features discussion from the software developers about the origins of their platforms

Monte-Carlo techniques have increasingly become a key method used in quantitative research. This book introduces engineers and scientists to the basics of using the Monte-Carlo simulation method which is used in Operations Research and other fields to understand the impact of risk and uncertainty in prediction and forecasting models. Monte-Carlo Simulation: An Introduction for Engineers and Scientists explores several specific applications in addition to illustrating the principles behind the methods. The question of accuracy and efficiency with using the method is addressed thoroughly within each chapter and all program listings are included in the discussion of each application to facilitate further research for the reader using Python programming language. Beginning engineers and scientists either already in or about to go into industry or commercial and government scientific laboratories will find this book essential. It could also be of interest to undergraduates in engineering science and mathematics, as well as instructors and lecturers who have no prior knowledge of Monte-Carlo simulations.

This book shows C# developers how to use C# 2008 and ADO.NET 3.5 to develop database applications the way the best professionals do.

After an introductory section, section 2 shows how to use data sources and datasets for Rapid Application Development and prototyping of Windows Forms applications. Section 3 shows how to build professional 3-layer applications that consist of presentation, business, and database classes. Section 4 shows how to use the new LINQ feature to work with data structures like datasets, SQL Server databases, and XML documents. And section 5 shows how to build database applications by using the new Entity Framework to map business objects to database objects.

To ensure mastery, this book presents 23 complete database applications that demonstrate best programming practices. And it's all done in the distinctive Murach style that has been training professional developers for 35 years.

Features Combines all topics into one comprehensive introduction. Explores practical applications of theory to healthcare. Can be used to accompany the NHS Modernising Scientific Careers syllabus.

Today, raw data on any industry is widely available. With the help of artificial intelligence (AI) and machine learning (ML), this data can be used to gain meaningful insights. In addition, as data is the new raw material for today's world, AI and ML will be applied in every industrial sector. Industry 4.0 mainly focuses on the automation of things. From that perspective, the oil and gas industry is one of the largest industries in terms of economy and energy. Applications of Artificial Intelligence (AI) and Machine Learning (ML) in the Petroleum Industry analyzes the use of AI and ML in the oil and gas industry across all three sectors, namely upstream, midstream, and downstream. It covers every aspect of the petroleum industry as related to the application of AI and ML, ranging from exploration, data management, extraction, processing, real-time data analysis, monitoring, cloud-based connectivity system, and conditions analysis, to the final delivery of the product to the end customer, while taking into account the incorporation of the safety measures for a better operation and the efficient and effective execution of operations. This book explores the variety of applications that can be integrated to support the existing petroleum and adjacent sectors to solve industry problems. It will serve as a useful guide for professionals working in the petroleum industry, industrial engineers, AI and ML experts and researchers, as well as students.