الصفحة 5
الصفحة 5
End-User Development
By now, most people have become familiar with the basic functionality and interfaces of computers. However, developing new or modified applications that effectively support users' goals still requires considerable expertise in programming that cannot be expected from most people. Thus, one fundamental challenge for the coming years is to develop environments that allow users who do not have background in programming to develop or modify their own applications, with the ultimate aim of empowering people to flexibly employ advanced information and communication technologies.
Enabling things to talk : Designing IoT solutions with the IoT architectural reference model
The Internet of Things (IoT) is an emerging network superstructure that will connect physical resources and actual users. It will support an ecosystem of smart applications and services bringing hyper-connectivity to our society by using augmented and rich interfaces. Whereas in the beginning IoT referred to the advent of barcodes and Radio Frequency Identification (RFID), which helped to automate inventory, tracking and basic identification, today IoT is characterized by a dynamic trend toward connecting smart sensors, objects, devices, data and applications. The next step will be “cognitive IoT,” facilitating object and data re-use across application domains and leveraging hyper-connectivity, interoperability solutions and semantically enriched information distribution.
Enabling Semantic Web Services : The Web Service Modeling Ontology
Service-oriented computing has become one of the predominant factors in current IT research and development. Web services seem to be the middleware solution of the future for highly interoperable distributed software solutions. In parallel, research on the Semantic Web provides the results required to exploit distributed machine-processable data. To combine these two research lines into industrial-strength applications, a number of research projects have been set up by organizations like W3C and the EU. After a brief presentation of the underlying basic technologies and standards of the World Wide Web, the Semantic Web, and Web Services, they detail all the elements of WSMO from basic concepts to possible applications in e-commerce, e-government and e-banking, and they also describe its relation to other approaches like OWL-S or WSDL-S.
Electronic Devices and Circuit Design : Challenges and Applications in the Internet of Things
Offers a broad view of the challenges of electronic devices and circuits for IoT applications. The book presents the basic concepts and fundamentals behind new low power, high-speed efficient devices, circuits, and systems in addition to CMOS. It provides an understanding of new materials to improve device performance with smaller dimensions and lower costs. It also looks at the new methodologies to enhance system performance and provides key parameters for exploring the devices and circuit performance based on smart applications.
Electronic Circuit Design and Application
This textbook for core courses in Electronic Circuit Design teaches students the design and application of a broad range of analog electronic circuits in a comprehensive and clear manner. Readers will be enabled to design complete, functional circuits or systems. The authors first provide a foundation in the theory and operation of basic electronic devices, including the diode, bipolar junction transistor, field effect transistor, operational amplifier and current feedback amplifier. They then present comprehensive instruction on the design of working, realistic electronic circuits of varying levels of complexity, including power amplifiers, regulated power supplies, filters, oscillators and waveform generators. Many examples help the reader quickly become familiar with key design parameters and design methodology for each class of circuits. Each chapter starts from fundamental circuits and develops them step-by-step into a broad range of applications of real circuits and systems.
DOM Scripting : Web Design with JavaScript and the Document Object Model
There are three main technologies married together to create usable, standards-compliant web designs: XHTML for data structure, Cascading Style Sheets for styling your data, and JavaScript for adding dynamic effects and manipulating structure on the fly using the Document Object Model. This book is about the latter of the three. DOM Scripting: Web Design with JavaScript and the Document Object Model gives you everything you need to start using JavaScript and the Document Object Model to enhance your web pages with client-side dynamic effects. Jeremy Keith starts off by giving you a basic crash course in JavaScript and the DOM, then moves on to provide you with several real-world examples built up from scratch, including dynamic image galleries and dynamic menus. Then, he shows you how to manipulate web page style using the CSS DOM, and create markup on the fly.
Distributed Computing and Internet Technology ; 4th International conference, ICDCIT 2007, Bangalore, India, December, 17-20, 2007, Proceedings
The book is covering a range of issues from basic technology, through services and engineering, to applications, from development issues, through middleware support, to actual delivery of e-Society services.
Digital twin : Architectures, networks, and applications
Offers comprehensive, self-contained knowledge on digital twin (DT), which is a very promising technology for achieving digital intelligence in the next-generation wireless communications and computing networks. DT is a key technology to connect physical systems and digital spaces in Metaverse. The objectives of this book are to provide the basic concepts of DT, to explore the promising applications of DT integrated with emerging technologies, and to give insights into the possible future directions of DT. For easy understanding, this book also presents several use cases for DT models and applications in different scenarios. The book starts with the basic concepts, models, and network architectures of DT. Then, we present the new opportunities when DT meets edge computing, Blockchain and Artificial Intelligence, and distributed machine learning (e.g., federated learning, multi-agent deep reinforcement learning).
Digital image processing
Completely self-contained and heavily illustrated, this introduction to basic concepts and methodologies for digital image processing is written at a level that is suitable for seniors and first-year graduate students in almost any technical discipline
Digital fundamentals
For courses in digital circuits, digital systems (including design and analysis), digital fundamentals, digital logic, and introduction to computers Digital Fundamentals, Eleventh Edition, continues its long and respected tradition of offering students a strong foundation in the core fundamentals of digital technology, providing basic concepts reinforced by plentiful illustrations, examples, exercises, and applications.
Digital Fluency : Understanding the Basics of Artificial Intelligence, Blockchain Technology, Quantum Computing, and Their Applications for Digital Transformation
If you are curious about the basics of artificial intelligence, blockchain technology, and quantum computing as key enablers for digital transformation, Digital Fluency is your handy guide. The real-world applications of these cutting-edge technologies are expanding rapidly, and your daily life will continue to be affected by each of them. There is no better time than now to get started and become digitally fluent.
Developments in language theory ; 8th International Conference, DLT 2004, Auckland, New Zealand, December 13-17, Proceedings
Basic Notions of Reaction Systems / A Kleene Theorem for a Class of Communicating Automata with Effective Algorithms / Algebraic and Topological Models for DNA Recombinant Processes / Contributed Papers : Regular Expressions for Two-Dimensional Languages Over One-Letter Alphabet / On Competence in CD Grammar Systems / The Dot-Depth and the Polynomial Hierarchy Correspond on the Delta Levels, and other
Developing metaverse for AIU
Metaverse is the virtual world in which humans can see each other in the form of 3D and communicate with each other in a virtual place that looks exactly like the real world, but the developers of metaverse so far used these virtual worlds for profit purposes only, this is what prompted us to build a virtual world that basicly contain the university, which can help students communicate with each other, see teachers and obtain the information they need from university employees without having to travel long distances, this project provides a distance education service without dispensing the idea of interacting with teachers directly and seeing others. Our virtual world has the ability to connect with any virtual world because of it’s base structure, It’s scalable as much as we need because it’s connected to the blockchain.
Developing bus management system for AIU
To solve the problem of congestion in bus stops for students, members of the administrative and educational people at the Arab International University, an application was designed that allows the user to reserve a seat on the bus. The application provides prior reservation and enters the study time for the user, the application reminds him for the time of his going to the university. The basic functions of the application are designed according to the general analysis, The development of the application used Laravel, flutter frameworks, AI and MySQL database processing technology. The application has accomplished such functions as notification for location. The test of the application is running in good conditions. The use of the application will solve the problem of bus crowding. The efficiency of the platform makes it a very good candidate to be implemented for any person in Arab International University.
Designing big data platforms : How to use, deploy, and maintain big data systems
Provides expert guidance and valuable insights on getting the most out of Big Data systems. Helps readers understand how to process large amounts of data with well-known Linux tools and database solutions, use effective techniques to collect and manage data from multiple sources, transform data into meaningful business insights, and much more. Author Yusuf Aytas, a software engineer with a vast amount of big data experience, discusses the design of the ideal Big Data platform: one that meets the needs of data analysts, data engineers, data scientists, software engineers, and a spectrum of other stakeholders across an organization. Detailed yet accessible chapters cover key topics such as stream data processing, data analytics, data science, data discovery, and data security. This real-world manual for Big Data technologies: Provides up-to-date coverage of the tools currently used in Big Data processing and management / Offers step-by-step guidance on building a data pipeline, from basic scripting to distributed systems / Highlights and explains how data is processed at scale / Includes an introduction to the foundation of a modern data platform
Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms
Presents a comprehensive comparison of the performance of stochastic optimization algorithms / Includes an introduction to benchmarking and statistical analysis / Provides a web-based tool for making statistical comparisons of optimization algorithms / Overviews of the current approaches used to analyze algorithm performance in a range of common scenarios, while also addressing issues that are often overlooked. In turn, it shows how these issues can be easily avoided by applying the principles that have produced Deep Statistical Comparison and its variants. The focus is on statistical analyses performed using single-objective and multi-objective optimization data. At the end of the book, examples from a recently developed web-service-based e-learning tool (DSCTool) are presented. The tool provides users with all the functionalities needed to make robust statistical comparison analyses in various statistical scenarios. The book is intended for newcomers to the field and experienced researchers alike. For newcomers, it covers the basics of optimization and statistical analysis, familiarizing them with the subject matter before introducing the Deep Statistical Comparison approach. Experienced researchers can quickly move on to the content on new statistical approaches.
Deep learning pipeline : Building a deep learning model with TensorFlow
Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects. You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented instructions help you understand each step of the deep learning pipeline while you apply the most straightforward and effective tools to demonstrative problems and datasets.
Data-Driven Fault Detection and Reasoning for Industrial Monitoring
Assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring.
Data structure and algorithms using C++ : A practical implementation
Intended to flow from the basic concepts of C++ to technicalities of the programming language, its approach and debugging. The chapters of the book flow with the formulation of the problem, it's designing, finding the step-by-step solution procedure along with its compilation, debugging and execution with the output. Keeping in mind the learner’s sentiments and requirements, the exemplary programs are narrated with a simple approach so that it can lead to creation of good programs that not only executes properly to give the output, but also enables the learners to incorporate programming skills in them. The style of writing a program using a programming language is also emphasized by introducing the inclusion of comments wherever necessary to encourage writing more readable and well commented programs. As practice makes perfect, each chapter is also enriched with practice exercise questions so as to build the confidence of writing the programs for learners.
Data science in theory and practice : Techniques for big data analytics and complex data sets
Delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. Readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets
