Computers

The goal of this book is to provide a mathematical perspective on some key elements of the so-called deep neural networks (DNNs). Much of the interest in deep learning has focused on the implementation of DNN-based algorithms. Our hope is that this compact textbook will offer a complementary point of view that emphasizes the underlying mathematical ideas. We believe that a more foundational perspective will help to answer important questions that have only received empirical answers so far.

The material is based on a one-semester course Introduction to Mathematics of Deep Learning" for senior undergraduate mathematics majors and first year graduate students in mathematics. Our goal is to introduce basic concepts from deep learning in a rigorous mathematical fashion, e.g introduce mathematical definitions of deep neural networks (DNNs), loss functions, the backpropagation algorithm, etc. We attempt to identify for each concept the simplest setting that minimizes technicalities but still contains the key mathematics.

This volume, the third of a series, consists of applications of Mathematica® to a potpourri of more advanced topics. These include differential geometry of curves and surfaces, differential equations and special functions and complex analysis. Some of the newest features of Mathematica® are demonstrated and explained and some problems with the current implementation pointed out and possible future improvements suggested.

• Contains a large number of worked out examples.
• Explains some of the most recent mathematical features of Mathematica®.
• Considers topics discussed rarely or not at all in the context of Mathematica®.
• Can be used to supplement several different courses.
• Based on actual university courses.

Scientific Computing for Scientists and Engineers is designed to teach undergraduate students relevant numerical methods and required fundamentals in scientific computing.

Most problems in science and engineering require the solution of mathematical problems, most of which can only be done on a computer. Accurately approximating those problems requires solving differential equations and linear systems with millions of unknowns, and smart algorithms can be used on computers to reduce calculation times from years to minutes or even seconds. This book explains: How can we approximate these important mathematical processes? How accurate are our approximations? How efficient are our approximations?

Scientific Computing for Scientists and Engineers covers:

• An introduction to a wide range of numerical methods for linear systems, eigenvalue problems, differential equations, numerical integration, and nonlinear problems;
• Scientific computing fundamentals like floating point representation of numbers and convergence;
• Analysis of accuracy and efficiency;
• Simple programming examples in MATLAB to illustrate the algorithms and to solve real life problems;
• Exercises to reinforce all topics.

Unlike the bulk majority of publications on philosophy of science and research ethics, which are authored by professional philosophers and intended for philosophers, this book has been written by a research practitioner and intended for research practitioners. It is distinctive by its integrative approach to methodological and ethical issues related to research practice, with special emphasis of mathematical modelling and measurement, as well as by attempted application of engineering design methodology to moral decision making. It is also distinctive by more than 200 real-world examples drawn from various domains of science and technology. It is neither a philosophical treaty nor a quick-reference guide. It is intended to encourage young researchers, especially Ph.D. students, to deeper philosophical reflection over research practice. They are not expected to have any philosophical background, but encouraged to consult indicated sources of primary information and academic textbooks containing syntheses of information from primary sources. This book can be a teaching aid for students attending classes aimed at identification of methodological and ethical issues related to technoscientific research, followed by introduction to the methodology of analysing dilemmas arising in this context.

The integration of Radio Detection and Ranging (RADAR) remote sensing and Artificial Intelligence (AI) provides a platform for understanding various Earth's surface processes and their predictive analysis. This book offers state-of-the-art techniques and applications to address real-time challenges through AI-based RADAR remote sensing. Furthermore, it explores the potential applications of AI in emerging areas of remote sensing and image processing.

This book covers innovative research topics on Metaverse, Digital Twins and Disease Screening and Precision medicines which represents the convergence of three significant technological trends, each with the potential to impact healthcare on its own. However, when combined, they could establish entirely novel avenues for delivering care, offering the potential to reduce costs significantly and greatly enhance patient outcomes. These trends include telepresence/telemedicine, the digital twin (DT), and blockchain. Telepresence refers to people's capacity to virtually be together despite physical distance. This can be achieved through virtual reality (VR, immersing the user entirely), augmented reality (AR, overlaying artificial images onto a real image), or other methods. Aside from VR and AR, distinguish two other metaverse types: lifelogging (capturing, storing, and sharing everyday experiences and information about objects and people) and the mirror world (reflecting the real world but integrating and providing external environment information). In the healthcare context, telepresence is predominantly utilized in telemedicine, which involves delivering medical services remotely.

Recent technological leaps in Artificial Intelligence have led to new types of human-machine interactions that challenge the application of our existing ethical approaches: It is not clear what status should be assigned to the new artificial systems.

With a dichotomous framework distinguishing mere tools from social agents, one has only two options – either all artificial systems are mere tools and don´t have an ethical status, or some may be treated like living agents with an ethical status. Often, assumptions concerning their abilities are made too quickly in either extreme direction, such as (over-)attributions or plain denials. This invites the idea of a gradual approach that locates them on a spectrum in between the dichotomous distinctions.

To update our ethical positions, this book argues that AI technology gives rise to phenomena that fall through our dichotomous conceptual net and proposes a new framework – inbetweenism – which offers a wide variety of categories for discussing neglected in-between phenomena.

This is highly relevant because it is likely that societal changes will alter our understanding of the status of artificial systems in our social realm, as they might soon enter this realm as a new type of social agent.

Das Standardwerk mit über 7.500 Einträgen zu den zentralen Begriffen der Informatik, der Angewandten Informatik und der Datenverarbeitung. Bearbeitet von 200 Fachleuten aus Hochschule und Industrie bietet das Lexikon fundierte und verständliche Begriffsdefinitionen. Zahlreiche Querverweise und ein Index englischsprachiger Begriffe mit Verweisen auf deutsche Einträge runden das Buch ab.

Harald Siebert studierte Philosophie in Augsburg, München und an der Sorbonne. In Paris und Berlin promovierte er in Wissenschaftsgeschichte. Er wurde 2007 mit dem Nachwuchspreis der International Academy of the History of Science ausgezeichnet.

Das Handbuch gibt einen umfassenden Überblick über grundlegende und moderne Methoden und Anwendungen der Künstlichen Intelligenz. Die Themen reichen von Kognition, Neuronale Netze, über Maschinelles Lernen bis hin zu Robotik und Software-Agenten und Anwendungen in der Industrie 4.0. Diese neue und überarbeitete 7. Auflage umfasst die neuesten Entwicklungen im Bereich der generativen KI sowohl für Sprache als auch für Bilder.

Das Buch richtet sich an Leser, die eine Einführung in Algorithmen und Datenstrukturen erhalten und an Interessierte, die sich darüber hinaus informieren möchten. Ausgangspunkt für das Buch waren ursprünglich einführende Lehrveranstaltungen über Algorithmen und Datenstrukturen. Insofern enthält das Buch alles, was für eine Einführung benötigt wird. Zusätzlich werden weiterführende Themen behandelt, wobei vor schwierigen Algorithmen, Analysen und Beweisen nicht haltgemacht wird. So enthält das Buch z.B. eine Analyse des String-Matching-Algorithmus von Boyer und Moore.

Neu in der 3. Auflage ist eine ausführliche Behandlung von Matching-Algorithmen für nicht-bipartite Graphen und ein 3. Teil über die Entwicklung von Algorithmen. Üblicherweise werden in Lehrbüchern fertige Lösungen präsentiert. Wie man auf diese Lösungen kommt, bleibt im Verborgenen. Wie entwickelt man einen Algorithmus für ein schwieriges Problem? Wie präsentiert man dann den entwickelten Algorithmus? Anhand der Implementierung der Beschleunigungsmethode von Hopcroft und Karp für Matching in nicht-bipartiten Graphen sowie anhand des Knotenüberdeckungsproblems werden diese Fragen im 3. Teil des Buches behandelt.

Enterprise Resource Planning (ERP) und Supply Chain Management (SCM) gehören zu den Kernaufgaben eines Industrieunternehmens. Sie haben sich evolutionär aus der Produktionsplanung und -steuerung (PPS) heraus entwickelt.

Ein Großteil der betriebswirtschaftlichen, administrativen und teilweise auch technischen Aufgaben eines Industrieunternehmens wird heute durch ERP- und SCM-Systeme unterstützt.

Das Buch erklärt die konzeptionellen Grundlagen der Systeme, zeigt auf, wie typische Geschäftsprozesse mit Hilfe praktischer Systeme (z.B. SAP ERP) durchgeführt werden, und behandelt aktuelle Entwicklungen wie Industrie 4.0. Fertigungsnahe und technische Anwendungssysteme werden mit ihren Schnittstellen um ERP und SCM herum platziert.

Neben den Grundlagen von ERP und SCM und der Umsetzung theoretischer Konzepte in praktischen Systemen behandelt die neue Auflage die aktuellste Entwicklungen im Bereich Industrie 4.0 und Internet der Dinge.

Der "Cormen" bietet eine umfassende und vielseitige Einführung in das moderne Studium von Algorithmen. Es stellt viele Algorithmen Schritt für Schritt vor, behandelt sie detailliert und macht deren Entwurf und deren Analyse allen Leserschichten zugänglich. Sorgfältige Erklärungen zur notwendigen Mathematik helfen, die Analyse der Algorithmen zu verstehen. Den Autoren ist es dabei geglückt, Erklärungen elementar zu halten, ohne auf Tiefe oder mathematische Exaktheit zu verzichten. Jedes der weitgehend eigenständig gestalteten Kapitel stellt einen Algorithmus, eine Entwurfstechnik, ein Anwendungsgebiet oder ein verwandtes Thema vor. Algorithmen werden beschrieben und in Pseudocode entworfen, der für jeden lesbar sein sollte, der schon selbst ein wenig programmiert hat. Zahlreiche Abbildungen verdeutlichen, wie die Algorithmen arbeiten. Ebenfalls angesprochen werden Belange der Implementierung und andere technische Fragen, wobei, da Effizienz als Entwurfskriterium betont wird, die Ausführungen eine sorgfältige Analyse der Laufzeiten der Programme mit ein schließen. Über 1000 Übungen und Problemstellungen und ein umfangreiches Quellen- und Literaturverzeichnis komplettieren das Lehrbuch, dass durch das ganze Studium, aber auch noch danach als mathematisches Nachschlagewerk oder als technisches Handbuch nützlich ist. Für die dritte Auflage wurde das gesamte Buch aktualisiert. Die Änderungen sind vielfältig und umfassen insbesondere neue Kapitel, überarbeiteten Pseudocode, didaktische Verbesserungen und einen lebhafteren Schreibstil. So wurden etwa - neue Kapitel zu van-Emde-Boas-Bäume und mehrfädigen (engl.: multithreaded) Algorithmen aufgenommen, - das Kapitel zu Rekursionsgleichungen überarbeitet, sodass es nunmehr die Teile-und-Beherrsche-Methode besser abdeckt, - die Betrachtungen zu dynamischer Programmierung und Greedy-Algorithmen überarbeitet; Memoisation und der Begriff des Teilproblem-Graphen als eine Möglichkeit, die Laufzeit eines auf dynamischer Programmierung beruhender Algorithmus zu verstehen, werden eingeführt. - 100 neue Übungsaufgaben und 28 neue Problemstellungen ergänzt. Umfangreiches Dozentenmaterial (auf englisch) ist über die Website des US-Verlags verfügbar.

In recent years, the fields of Augmented Reality (AR), Virtual Reality (VR), Internet of Things (IoT), and Artificial Intelligence (AI) have witnessed significant advancements. This edited book explores the intersection of AR, VR, IoT, and AI, and their combined applications. It delves into the latest research, trends and practical implementations, providing readers with a comprehensive understanding of this rapidly evolving landscape.

Das Lehrbuch gibt einen umfassenden Überblick über die vielseitigen Grundlagen für das Studienfach
Informatik & Gesellschaft und setzt diese in Beziehung zueinander. Das Lehrbuch hat mit seinen Grundlagen eine langlebige Beständigkeit für das Fach Informatik & Gesellschaft und bleibt durch die Kombination mit wechselnden, Anwendungsbeispielen auf der Lernplattform aktuell und flexibel einsetzbar.

This complete guide explores the potential of big data and the Internet of Things (IoT) as it examines smart city development.

Part I defines IoT and its role in creating a more efficient and livable urban environment. The fundamentals of Big Data are discussed along with "4 V's" (volume, velocity, variety, and veracity).

Part II tackles the design and architecture of IoT Big Data platforms and covers choosing the right technology stack, whether open source or proprietary solutions, ensuring the best fit for a city's needs.

Part III considers the technical aspects of core IoT principles, exploring sensors, communication networks, and how these devices function in real-world applications. It provides the knowledge to manage data pipelines, ensuring reliable data transfer, and design.

Finally, Part IV includes the real-world applications of these technologies examining the potential of IoT in smart public services, smart wastewater, and energy management, and exploring efficiency and innovation in building management.

This book arms readers with the knowledge and tools to navigate the world of smart city development. By employing the power of IoT and Big Data, cities will be more sustainable, effective, and livable in the future.

This book presents a well-researched theory that connects transcendent experience (TX) and user experience (UX). It also offers practical techniques for using the theory in designing technology to support TX. TX research focuses on the experiences and their implications without considering how technology might assist them. UX research, on the other hand, studies "techno-spiritual practices", largely overlooking the transcendent experiences that such practices can initiate. However, both fields could pay more attention to the growing interest in the connections between artificial intelligence (AI) and religion.

The author’s theory of transcendent user experience (TUX) combines insights from TX literature with interview-based research on tech and TXs. It reveals TUX as a cycle of phases, detailing their components and technology’s role. This theory leads to new design techniques. The playful "Transcendhance" game introduced here, will generate creative ideas for TUX tech; new forms of design fiction aid in exploring how ideas might enhance TUX and change lives. The book also reveals which TUX aspects are easy to design for and which are nearly impossible. The book argues that designing for TUX cannot use straightforward UX methods; it requires an oblique approach. The game and design fictions provide just this. The book concludes with advice on testing product support for transcendence and applying the techniques to broader UX. Ultimately, the framework and techniques provide vital tools for understanding transcendent user experiences and designing technology to support them

This book offers new mathematical models for software project planning methodologies, including approaches like PMI, IEEE-CS, and Scrum. It also presents a unique hybrid model that combines the IEEE-CS approach with the Scrum one. It introduces the importance of software project planning and goes into detail about the initiation and preparation phases. It covers methods for identifying and analyzing software requirements, creating core project plans, and integrating sub-plans. Additionally, it discusses software project planning using PMI, IEEE-CS, Scrum, and the hybrid approach, and provides practical case studies for each model. This structured approach gives readers a comprehensive understanding of software project planning practices, from traditional to agile approaches, and prepares them to effectively plan and manage software projects using various strategies. Based on these models, interested corporations can develop new Software Project Planning Tools to automate their software project planning function.

The field of healthcare is being transformed by artificial intelligence (AI). Professionals need to comprehend the potential impact of AI on clinical decision support and epidemiological modeling. This comprehensive guide helps bridge the gap between theory and practice, providing readers with the knowledge and skills needed to leverage AI in healthcare.

The book covers a broad range of topics, from the basics of AI and machine learning to the creation and assessment of clinical decision support systems. It also covers the use of state-of-the-art AI methods for disease surveillance and outbreak prediction. Through a mix of theoretical explanations, practical examples, and hands-on exercises, readers will learn how to prepare and manipulate clinical and epidemiological datasets, build, and implement cutting-edge AI solutions, and address the ethical considerations and challenges of applying AI in healthcare.

What makes this book unique is its combination of expert insights from a practitioner’s perspective, real-world case studies, and a practical approach to walk readers through the process of developing and implementing AI solutions. Additional online resources, like datasets, code samples, and case studies, further enrich the learning experience.

Whether you are a healthcare professional looking to enhance patient outcomes, a data scientist striving to create innovative AI solutions, or a student eager to explore the frontiers of healthcare technology, this book is an essential resource.

Spring Boot Microservices is the ultimate handbook for mastering the intricacies of microservices design, implementation, and deployment through the lens of the Spring Boot framework. This guide is tailored to equip readers with practical insights and real-world applications, ensuring they possess the skills to construct robust and scalable microservices architectures. Starting with the fundamentals of Spring Boot and exploring its main modules, readers study essential topics such as microservices architecture, configuration management, database interaction, and security measures. Through practical guidance and hands-on exercises, you will learn to document endpoints effectively, streamline development processes, and implement strategies for efficient application packaging. With its emphasis on real-world case studies and industry insights, this book is an indispensable resource for developers, architects, and IT professionals seeking to leverage microservices architecture effectively in their projects and organizations, empowering them to harness the full potential of Spring Boot for building modern, scalable applications.

Intelligent Video Analytics is a guide to mastering modern surveillance technology. This reference covers everything from the basics of CCTV systems to the latest advances in video analytics, making it an essential resource for networking and security professionals.

Part I, Foundations of CCTV Technology, explains the fundamentals of CCTV cameras, lenses, recording devices, monitors, and network design and security. Part II, Camera and Sensor Technologies discusses various camera types, image sensors, and image processing principles and optics. Part III, Advanced Concepts in Computer Vision and Deep Learning, covers CNNs, object detection, tracking, face recognition, and video content analysis. Part IV, Computing Technologies for Video Analytics, studies the essentials of GPUs, CPUs, and edge computing. Part V, Enhancing Security, Safety, and Operational Efficiency," examines the principles of physical security, and operational efficiency. In Part VI, Designing Video Analytics Platforms, covers designing robust video analytics systems with applications for smart cities and law enforcement. Part VII, The Future of Video Analytics with Generative AI," considers the role of generative AI in anomaly detection and video synthesis.

This book provides a comprehensive discussion of how quantum cryptography is changing cybersecurity. It starts by emphasizing the importance of quantum cryptography in next-generation security frameworks, focusing on the threats to classical cryptography and the economic implications of emerging technologies like AI and IoT. It then provides an overview of existing cryptographic methods and stresses the need to move to quantum-based solutions for better data protection and access control. It covers the fundamental principles of quantum cryptography, specifically its role in identity and access management and the concept of "Trust Exchange." It also discusses quantum satellite communications, quantum networks, and the creation of a quantum internet to show how these technologies improve secure communication. This is followed by a review of the development of digital signatures and digital identity systems, demonstrating how quantum algorithms are making traditional methods resistant to quantum attacks. The cybersecurity section introduces quantum-resistant cryptosystems and ledgers and contrasts classical and quantum cryptographic algorithms. Coverage concludes with a roadmap for implementing quantum cryptography in businesses, outlining the steps needed for digital transformation, change management, and the integration of quantum-based cybersecurity applications.

This comprehensive reference provides the reader with the necessary knowledge and tools to navigate the AWS cloud migration process. It covers everything from understanding of cloud computing, AWS Cloud Computing, and AWS Migration with the usage of state-of-the-art Generative AI in AWS Cloud Migration.

The book is divided into clear sections and meticulously covers essential topics such as AWS services, various migration strategies, and popular migration tools like AWS Application Discovery Service (ADS), AWS Application Migration Service (MGN), and AWS Database Migration Service (DMS).

It discusses different phases of migration, including assessment, mobilization, migration, and modernization, providing practical guidance on workload migration, data migration, and cost optimization. The book also covers two important frameworks: the AWS Cloud Adoption Framework and the AWS Well-Architected Framework. These frameworks guide the cloud adoption journey and help in building a comprehensive cloud roadmap.

In addition to technical areas, the book discusses Artificial Intelligence, Common Artificial Intelligence Workloads, and Different AWS Tools relevant to Generative AI. Exploration of the application of Generative AI in AWS cloud migration, evaluating its potential to enhance assessments and overall effectiveness.

Over 90% of cyber security incidents invoke human action, decisions, or errors. When users are unknowingly manipulated to bypass technical security controls attackers prevail. Traditional cybersecurity resources focus heavily on technical solutions, leaving non-technical vulnerabilities unaddressed. This book fills that void by providing a comprehensive guide for business and IT professionals to develop and improve cybersecurity awareness programs. It goes beyond basic compliance measures and offers practical strategies to create a security-aware culture that actively involves employees in mitigating risks. The book is designed to help organizations transition from outdated, compliance-based programs to dynamic, adaptive frameworks that prioritize human-centered defenses. This resource is the ideal guide for organizations and IT professionals looking to reduce risk, strengthen security posture, and build a more resilient workforce against cyber threats. The content is packed with practical advice and tools to drive meaningful change in organizational behavior and security practices.

Transform your Access databases from simple data repositories to powerful, automated applications with Access 2024 / Microsoft 365 Programming by Example. This isn't just another reference manual; it's a practical, step-by-step tutorial designed to guide you through the essentials of Visual Basic for Applications (VBA) within the Access environment. Built for those who already understand basic Access database design and operations, this book dives straight into practical examples and hands-on exercises. Each chapter builds upon the previous, gradually introducing you to more complex concepts and techniques. You'll learn how to automate tasks, enhance functionality, and create robust applications that streamline your workflow. Each chapter includes integrated ChatGPT sections, providing on-the-spot explanations, code examples, and answers to frequently asked questions. This AI-powered assistance transforms your learning experience, making complex concepts more accessible and helping you overcome challenges with ease. This book is perfect for Access users who are ready to take their skills to the next level. Whether you're a beginner looking to start programming or an experienced user aiming to refine your abilities, this tutorial provides a structured and approachable learning path. This book assumes you have a working knowledge of Microsoft Access, including database design, query creation, and form development with subforms and controls. Empower your Access skills today and build the applications you've always envisioned!

• Encourages readers to compare and contrast hand-written code with ChatGPT-generated code. This approach fosters discussions on code efficiency, readability, and maintainability, enhancing understanding of programming paradigms and techniques.

This book is designed for those new to Java and interested in understanding how ChatGPT/GPT-4 can enhance programming. It offers a unique approach to learning Java, combining traditional hand-written code with cutting-edge ChatGPT-generated examples. The book covers the basics of Java programming and development environments, including understanding recursion, strings, arrays, fundamental data structures, algorithm analysis, queues and stacks, and follows with the role of ChatGPT in generating, explaining, and debugging code. Companion files with source code and figures available for downloading. It’s an essential resource for those starting Java programming and for anyone curious about the applications of ChatGPT in coding.

Mit diesem, nun in der 6. Auflage vorliegenden Buch wird erstmalig ein Bogen von den Grundlagen der Digitaltechnik über den VHDL-basierten Schaltungsentwurf bis zur High-Level-Synthese aufgespannt. Es stellt somit ein aktuelles Kompendium zu rechnergestützten Methoden beim Entwurf digitaler Systeme dar.

Neben dem Verständnis des funktionellen und zeitlichen Verhaltens von Logikfunktionen und grundlegenden Implementierungskonzepten für digitale Systeme wird auch die Fertigkeit zur synthesegerechten Modellierung mit einer Hardwarebeschreibungssprache wie VHDL oder einer Programmiersprache wie C bzw. C++ vermittelt.

Mit der signifikanten Ergänzung zur High-Level Synthese wird der Tatsache Rechnung getragen, dass sich die Ergebnisqualität der zugehörigen Synthesecompiler in den letzten Jahren deutlich verbessert hat, sodass auf C/C++-Ebene beschriebene Systeme durch automatisch vorgenommene Optimierungen einen erheblichen Performancegewinn bringen, der bei Implementierungen mit Hardwarebeschreibungssprachen noch manuell hinzugefügt werden muss.

Der ausgezeichnete didaktische Aufbau unterstützt den Lernprozess: Den Kapiteln sind Lernziele vorangestellt und immer wieder werden grafische und tabellarische Übersichten sowie vertiefende Beispiele präsentiert. Eine Vielzahl von Übungsaufgaben mit Musterlösungen dient zur Lernkontrolle.

In today's rapidly evolving information technology landscape, cyber-attacks on company assets and IT systems are becoming increasingly frequent and varied. This book focuses on such security breaches, originating from diverse sources.

The book explores the complexities of security attacks and the growing number of vulnerabilities, emphasizing the importance of implementing high-quality information security practices within organizations. It introduces "Reengineering Cyber Security Process: Quality Management", a practical methodology for analyzing various information security components within an organization to develop a comprehensive quality information security management program.

This book is valuable for a wide range of professionals in the information security community, including CIOs, CEOs, CISOs, managers, IT staff, professional cybersecurity staff, and end-users. It includes relevant examples and applications, offering a fresh perspective on Cyber Security Quality Management.

The De Gruyter Handbook on Law and Digital Technologies provides a comprehensive, accessible and thought-provoking guide to the current and future regulation of digital technologies. It addresses key legal challenges such as reconceptualizing crucial, deep-rooted notions, including those of person, autonomy, democracy, the rule of law, sovereignty, constitutionalism and governance.

The handbook proposes critical explorations of the potential impact of digital technologies on new and traditional forms of governance and regulation across different and competitive normative perspectives such as law, economy, social norms and legal design. In this framework, it addresses the societal transformations brought about by digital technologies, the legal means for regulating the field, and the impact of governance in areas such as fintech, sustainability, outer space, or healthcare.

This book provides relevant information about intermediate Python 3.x for a variety of topics, such as comprehensions, iterators, generators, regular expressions, OOP, queues and stacks, and recursion. Each chapter contains an assortment of code samples that illustrate the topics in the chapter material. It assumes the reader is already familiar with Python programming and wants to expand programming skills in order to use Python in a variety of subject areas and disciplines such as business, mathematics, science, and engineering. Knowledge of other programming languages (such as Java) can also be helpful because of the exposure to programming concepts and object-oriented programming. This book includes companion files with numerous code samples, figures, and applications from the text.

Our proposed book emerges in response to the critical need for an interdisciplinary resource that encapsulates the burgeoning role of artificial intelligence (AI) in reshaping drug discovery and telemedicine. As these sectors witness transformative changes driven by AI technologies, there's a pressing demand for a comprehensive guide that navigates through these advancements, offering insights, methodologies, and practical applications to professionals at the forefront of healthcare and pharmaceutical research.

At its core, the book delves into the intricate ways in which AI and machine learning algorithms are being harnessed to streamline the drug development process, from initial discovery through to clinical trials, and how these technologies are concurrently revolutionizing the delivery of healthcare services via telemedicine. Specific focus areas include the application of deep learning in identifying novel drug candidates, AI-driven predictive models for pharmacokinetics and pharmacodynamics, automation in laboratory research, and the integration of AI in diagnostic processes, personalized medicine, and patient monitoring systems. Each chapter not only explores current state-of-the-art methodologies and case studies but also critically examines challenges, such as data privacy, ethical considerations, and the need for robust, interpretable models that can be trusted by healthcare professionals and patients alike.

Furthermore, the book places a strong emphasis on the synergistic potential of combining AI with telemedicine, illustrating how these technologies can expand access to healthcare, improve the accuracy of remote diagnoses, and enable continuous, data-driven patient care. By providing a panoramic view of current trends, technological innovations, and future directions, the book aims to serve as a pivotal reference for scientists, researchers, clinicians, and policymakers involved in drug discovery and healthcare delivery.

In conclusion, this book stands as an essential compendium for specialists seeking to navigate the complexities and harness the opportunities presented by AI in the pharmaceutical and healthcare industries. It offers a critical, in-depth exploration of the transformative impact of AI technologies, underscoring their relevance and potential to dramatically enhance drug discovery and telemedicine practices. This publication not only equips its target audience with the knowledge to lead innovation in their fields but also engages with the broader ethical, social, and practical implications of AI, making it an invaluable resource for advancing towards more effective, efficient, and accessible healthcare solutions.

The book is significant for several reasons:

Interdisciplinary Appeal: It serves as a critical resource for professionals and researchers across the fields of computer science, pharmaceutical sciences, and healthcare, facilitating a deeper understanding of AI's potential and fostering interdisciplinary collaborations.

Innovation in Drug Discovery: By highlighting novel AI methodologies in drug discovery, the book offers insights into how these technologies can shorten the development timelines, reduce costs, and increase the success rates of new therapies, which is crucial for addressing unmet medical needs.

Revolutionizing Telemedicine: The detailed discussion on AI's role in telemedicine illustrates how these advancements can enhance access to healthcare, improve the quality of care, and make healthcare systems more efficient, especially in remote and underserved areas.

Ethical and Regulatory Considerations: It likely addresses the ethical, privacy, and regulatory challenges associated with implementing AI in healthcare, offering guidelines for navigating these complexities while maximizing patient benefits.

Future Directions: By exploring current trends and future possibilities, the book not only serves as a repository of current knowledge but also as a beacon for future research and development efforts in these rapidly evolving fields.

As we stand on the brink of a new era, this book offers a comprehensive exploration of AI's ethical, social, and technological implications. It explores privacy, fairness, accountability, and the digital divide. The book features real-world case studies across diverse industries to illustrate AI's transformative power and its potential to revolutionize healthcare, education, transportation, and more. Special attention is given to the adoption of AI in emerging markets and emphasizes the importance of human-AI collaboration, where AI augments human intelligence and creativity rather than replacing it. It examines the need for human-centric design while also exploring AI governance and the role of multi-stakeholder collaboration in shaping the future of this technology. By fostering a comprehensive understanding of AI and its myriad implications, the book inspires thoughtful dialogue and responsible action to ensure a brighter, more equitable future for all. It is intended for business leaders, policymakers, academics, and curious individuals eager to understand AI’s role in shaping our world and how we can responsibly harness its power.

FEATURES
• Emphasizes human-AI symbiosis, highlighting human-centric design and responsible development
• Provides real-world examples across industries, showcasing AI's transformative impact
• Explores AI adoption in emerging economies, addressing unique challenges and opportunities

Data Science for Decision Makers is an essential guide for executives, managers, entrepreneurs, and anyone seeking to harness the power of data to drive business success. In today's fast-paced and increasingly digital world, the ability to make informed decisions based on data-driven insights is vital. This book serves as a bridge between the complex world of data science and the strategic decision-making process, providing readers with the knowledge and tools they need to leverage data effectively.

With a clear focus on practical application, this book demystifies key concepts in data science, from data collection and analysis to predictive modeling and visualization. Via real-world examples, case studies, and actionable insights, readers will learn how to extract insights from data and translate them into actionable strategies that drive organizational growth.

Written in a reader-friendly manner, this book caters to both novice and experienced professionals alike. Whether you're a seasoned executive looking to sharpen your strategic acumen or a manager seeking to enhance your team's data literacy, this essential reference provides the necessary foundation to navigate the complex landscape of data science with confidence.

• Designed for readers relatively new to working in a bash environment
• Introduces readers to three powerful command line utilities that can be combined to create simple yet powerful shell scripts for performing a multitude of tasks

Angesichts der enormen Aufmerksamkeit für das Thema künstliche Intelligenz (KI) gerät leicht in Vergessenheit, dass KI nichts anderes ist als die derzeit ausgefeilteste Form der Datenwertschöpfung.

In den Daten der Unternehmen schlummert die Erfolgsgrundlage für das KI-Zeitalter. Die europäische Wirtschaft hat jetzt die einmalige Chance, das exponentielle Wachstum industrieller und professioneller Daten zu ihrem Vorteil zu nutzen.

Dieses Potenzial auszuschöpfen, erfordert allerdings eine Transformation der Strategie, Organisation, Kultur und IT-Architektur. Dieses Praxishandbuch bietet Entscheidungsträgern in Unternehmen dafür eine konkrete Hilfe.

This book explores the synergy between Claude3, a cutting-edge AI model, and Web technologies such as HTML, CSS3, and SVG, providing both novices and experienced developers with the tools to create visually stunning Web graphics and animations. It introduces the fundamental concepts of Generative AI, the key players in the field, and the distinctive features of Claude3, while also mastering the art of prompt engineering to interact effectively with AI models. The book covers creating dynamic 3D animations with CSS3, including effects like glowing, image fading, and rotating, and demonstrates how to leverage Claude3 to generate sophisticated SVG graphics and animations, thereby enhancing Web designs with advanced visual effects.

FEATURES

• Covers generative AI fundamentals to advanced CSS3 and SVG techniques, offering comprehensive material on modern web development technologies
• Features both manually created and AI generated code samples, security issues, crafting prompts, and accessibility needs
• Balances theoretical knowledge and practical examples, so readers gain hands-on experience in implementing AI-driven design solutions using Claude-generated code
• Includes companion files with code, datasets, and images from the book -- available from the publisher for downloading (with proof of purchase)

TABLE OF CONTENTS

This book contains a fast-paced introduction to data-related tasks in preparation for training models on datasets. It presents a step-by-step, Python-based code sample that uses the kNN algorithm to manage a model on a dataset.

Chapter One begins with an introduction to datasets and issues that can arise, followed by Chapter Two on outliers and anomaly detection. The next chapter explores ways for handling missing data and invalid data, and Chapter Four demonstrates how to train models with classification algorithms. Chapter 5 introduces visualization toolkits, such as Sweetviz, Skimpy, Matplotlib, and Seaborn, along with some simple Python-based code samples that render charts and graphs. An appendix includes some basics on using awk. Companion files with code, datasets, and figures are available for downloading.

Features:

• Covers extensive topics related to cleaning datasets and working with models
• Includes Python-based code samples and a separate chapter on Matplotlib and Seaborn
• Features companion files with source code, datasets, and figures from the book

1. Describes seven novel variations of the Turing test.
2. Outlines an original definition of consciousness described as implementable specifications.
3. Introduces the concept of Mathematics as a "genetically" transmissible cognitive medium.

This book presents a groundbreaking journey into the world of Generative AI technology and offers an in-depth look at the prospect of AI achieving consciousness. The book navigates through various historical and modern perspectives on AI, from ancient myths to the Turing Test to the latest in technological advancements. It covers the theoretical and practical aspects of creating a conscious AI, including the specifications for synthetic consciousness and the integration of AI with human cognition. The book questions whether generative AI can meet the traditional criteria of consciousness and how this might be realized.

The book discusses the security and privacy issues detected during penetration testing, security assessments, configuration reviews, malware analysis, and independent research of the cloud infrastructure and Software-as-a-Service (SaaS) applications. The book highlights hands-on technical approaches on how to detect the security issues based on the intelligence gathered from the real world case studies and also discusses the recommendations to fix the security issues effectively. This book is not about general theoretical discussion rather emphasis is laid on the cloud security concepts and how to assess and fix them practically.

In the constantly changing field of artificial intelligence, effective communication and prompt engineering have become essential for developers, researchers, and tech enthusiasts to guide and improve AI. Optimizing Prompt Engineering for Generative AI provides in-depth insight into the techniques and skills needed to create prompts that enhance the performance and relevance of conversational AI systems.

Intended for AI practitioners, technology developers, and academics, this book serves as both a foundational text for newcomers and a detailed guide for experienced professionals seeking to refine their skills.

This book equips readers with the knowledge to effectively design, test, and refine AI prompts that lead to more accurate, engaging, and ethically aligned AI interactions. From the basics of prompt construction to advanced techniques for specific industries, the content covers a broad spectrum. Each chapter builds on the previous one, starting with an introduction to the fundamental concepts of prompt engineering, moving through detailed discussions on crafting effective prompts, and concluding with insights into future trends and ethical considerations.

Through a blend of theoretical explanations, practical applications, case studies, and hands-on exercises, the coverage ensures that readers not only understand the principles of prompt engineering but also know how to apply these principles effectively. By the end of this journey, readers will be equipped to enhance the capabilities of AI systems, making them more responsive, intuitive, and beneficial in a variety of real-world settings.

This book is not just a manual; it’s a pathway to mastering the art of conversational AI, designed to foster an innovative approach to AI interactions that are as transformative as they are forward-thinking.

This book offers a comprehensive guide to leveraging Python-based data visualization techniques with the innovative capabilities of Google Gemini. Tailored for individuals proficient in Python seeking to enhance their visualization skills, it explores essential libraries like Pandas, Matplotlib, and Seaborn, along with insights into the innovative Gemini platform. With a focus on practicality and efficiency, it delivers a rapid yet thorough exploration of data visualization methodologies, supported by Gemini-generated code samples. Companion files with source code and figures are available for downloading.

FEATURES:

• Covers Python-based data visualization libraries and techniques
• Includes practical examples and Gemini-generated code samples for efficient learning
• Integrates Google Gemini for advanced data visualization capabilities
• Sets up a conducive development environment for a seamless coding experience
• Includes companion files for downloading with source code and figures

This book is a fast-paced introduction to using data structures with Java. Numerous code samples and listings are included to support myriad topics. The first chapter contains a quick introduction to Java, along with Java code samples to check for leap years, find divisors of a number, and work with arrays of strings. The second chapter introduces recursion and uses code samples to check if a positive number is prime, to find the prime divisors of a positive integer, to calculate the GCD (greatest common divisor) and LCM (lowest common multiple) of a pair of positive integers. The third chapter contains Java code samples involving strings and arrays, such as finding binary substrings of a number, checking if strings contain unique characters, counting bits in a range of numbers, and how to compute XOR without using the XOR function. Chapters 4 through 6 include Java code samples involving search algorithms, concepts in linked lists, and tasks involving linked lists. Finally, Chapter 7 discusses data structures called queues and stacks, along with additional Java code samples.

Features:

• Extensive topics, code samples, and scripts related to data structures
• Covers strings, arrays, queues, and stacks, linked lists, computing the XOR function, checking for unique characters, and more
• Includes companion files with code samples from the book (available for downloading from the publisher)

As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to basic machine learning algorithms using TensorFlow 2. It is intended to be a fast-paced introduction to various “core” features of TensorFlow, with code samples that cover machine learning and TensorFlow basics. A comprehensive appendix contains some Keras-based code samples and the underpinnings of MLPs, CNNs, RNNs, and LSTMs. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge. Companion files with all of the code samples are available for downloading from the publisher by emailing proof of purchase to info@merclearning.com.

Features:

• Uses Python for code samples
• Covers TensorFlow 2 APIs and Datasets
• Includes a comprehensive appendix that covers Keras and advanced topics such as NLPs, MLPs, RNNs, LSTMs
• Features the companion files with all of the source code examples and figures (download from the publisher)

Autonomous driving is an emerging field. Vehicles are equipped with different systems such as radar, lidar, GPS etc. that enable the vehicle to make decisions and navigate without user's input, but there are still concerns regarding safety and security. This book analyses the security needs and solutions which are beneficial to autonomous driving.