How to Cheat at Windows Systems Administrators using Command line scripts teaches system administrators hundreds of powerful, time-saving tips for automating daily system administration tasks using Windows command line scripts.
With every new version of Windows, Microsoft is trying to ease the administration jobs by adding more and more layers of graphical user interface (GUI) or configuration wizards (dialog boxes). While these wizards are interactive and make the administrator s job easier, they are not always the most convenient and efficient way to accomplish the everyday administration tasks. These wizards are time consuming and, at times, may seem a bit confusing. The purpose of the book is to teach administrators how to use command-line scripts to complete everyday administration jobs, solve recurring network problems and at the same time improve their efficiency.
*Provides system administrators with hundreds of tips, tricks, and scripts to complete administration tasks more quickly and efficiently.
*No direct competition for a core tool for Windows administrators.
*Builds on success of other books in the series including How to Cheat at Managing Windows Small Business Server 2003 and How to Cheat at Managing Microsoft Operations Manager 2005."

With artificial neural network research being one of the new directions for new generation computers, current research suggests that open-box artificial higher order neural networks (HONNs) play an important role in this new direction.Artificial Higher Order Neural Networks for Modeling and Simulation introduces artificial Higher Order Neural Networks (HONNs) to professionals working in the fields of modeling and simulation, and explains that HONN is an open-box artificial neural network tool as compared to traditional artificial neural networks. Including details of the most popular HONN models, this book provides an opportunity for practitioners in the field of modeling and simulations to understand and know how to use HONNS in their area of expertise.

A groundbreaking, flexible approach to computer science anddata science The Deitels' Introduction to Python for ComputerScience and Data Science: Learning to Program with AI, Big Data and the Cloudoffers a unique approach to teaching introductory Python programming,appropriate for both computer-science and data-science audiences. Providing themost current coverage of topics and applications, the book is paired withextensive traditional supplements as well as Jupyter Notebooks supplements.Real-world datasets and artificial-intelligence technologies allow students towork on projects making a difference in business, industry, government andacademia. Hundreds of examples, exercises, projects (EEPs) and implementationcase studies give students an engaging, challenging and entertainingintroduction to Python programming and hands-on data science. The book's modular architecture enables instructors toconveniently adapt the text to a wide range of computer-science anddata-science courses offered to audiences drawn from many majors.Computer-science instructors can integrate as much or as little data-scienceand artificial-intelligence topics as they'd like, and data-science instructorscan integrate as much or as little Python as they'd like. The book aligns withthe latest ACM/IEEE CS-and-related computing curriculum initiatives and withthe Data Science Undergraduate Curriculum Proposal sponsored by the NationalScience Foundation.

This book highlights numerical models as powerful tools for the optimal design of Micro-Electro-Mechanical Systems (MEMS). Most MEMS experts have a background in electronics, where circuit models or behavioral models (i.e. lumped-parameter models) of devices are preferred to field models. This is certainly convenient in terms of preliminary design, e.g. in the prototyping stage. However, design optimization should also take into account fine-sizing effects on device behavior and therefore be based on distributed-parameter models, such as finite-element models. The book shows how the combination of automated optimal design and field-based models can produce powerful design toolboxes for MEMS. It especially focuses on illustrating theoretical concepts with practical examples, fostering comprehension through a problem-solving approach. By comparing the results obtained using different methods, readers will learn to identify their respective strengths and weaknesses. In addition, special emphasis is given to evolutionary computing and nature-inspired optimization strategies, the effectiveness of which has already been amply demonstrated. Given its scope, the book provides PhD students, researchers and professionals in the area of computer-aided analysis with a comprehensive, yet concise and practice-oriented guide to MEMS design and optimization. To benefit most from the book, readers should have a basic grasp of electromagnetism, vector analysis and numerical methods.

One of the infinite rewards to continuously advancing technology is an increased ease and precision in organizational techniques. Online data collection and online instruments are vital ways to electronically measure and assess organizational areas relevant to management, leadership, and human research development.Online Instruments, Data Collection, and Electronic Measurements: Organizational Advancements aims to assist researchers in both understanding and utilizing online data collection by providing methodological knowledge related to online research, and by presenting information about the empirical quality, the availability, and the location of specific online instruments. This book provides a strong focus on organizational leadership instruments while combining them with practical and ethical issues associated with online data collection. Such a combination makes this a unique contribution to the field.

In recent years, Higher Order Neural Networks (HONNs) have been widely adopted by researchers for applications in control signal generating, pattern recognition, nonlinear recognition, classification, and predition of control and recognition scenarios. Due to the fact that HONNs have been proven to be faster, more accurate, and easier to explain than traditional neural networks, their applications are limitless. Applied Artificial Higher Order Neural Networks for Control and Recognition explores the ways in which higher order neural networks are being integrated specifically for intelligent technology applications. Emphasizing emerging research, practice, and real-world implementation, this timely reference publication is an essential reference source for researchers, IT professionals, and graduate-level computer science and engineering students.

As technology continues to become more sophisticated, mimicking natural processes and phenomena becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Algorithms for Big Data Frameworks is a collection of innovative research on the methods and applications of extracting meaningful information from data using algorithms that are capable of handling the constraints of processing time, memory usage, and the dynamic and unstructured nature of data. Highlighting a range of topics including genetic algorithms, data classification, and wireless sensor networks, this book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the application of nature and biologically inspired algorithms for handling challenges posed by big data in diverse environments.

The Semantic Web combines the descriptive languages RDF (Resource Description Framework) and OWL (Web Ontology Language), with the data-centric, customizable XML (eXtensible Mark-up Language) to provide descriptions of the content of Web documents. These machine-interpretable descriptions allow more intelligent software systems to be written, automating the analysis and exploitation of web-based information.

Software agents will be able to create "automatically" new services from already published services, with potentially huge implications for models of e-Business.

"Semantic Web Technologies" provides a comprehensive overview of key semantic knowledge technologies and research. The authors explain (semi-)automatic ontology generation and metadata extraction in depth, along with ontology management and mediation. Further chapters examine how Semantic Web technology is being applied in knowledge management ("Semantic Information Access") and in the next generation of Web services.

"Semantic Web Technologies: " Provides a comprehensive exposition of the state-of-the art in Semantic Web research and key technologies. Explains the use of ontologies and metadata to achieve machine-interpretability. Describes methods for ontology learning and metadata generation. Discusses ontology management and evolution, covering ontology change detection and propagation, ontology dependency and mediation. Illustrates the theoretical concepts with three case studies on industrial applications in digital libraries, the legal sector and the telecommunication industry.

Graduate and advanced undergraduate students, academic and industrial researchers in the field will all find "Semantic WebTechnologies" an essential guide to the technologies of the Semantic Web.

Recent advances in gene sequencing technology are now shedding light on the complex interplay between genes that elicit phenotypic behavior characteristic of any given organism. In order to mediate internal and external signals, the daunting task of classifying an organism's genes into complex signaling pathways needs to be completed. The Handbook of Research on Computational Methodologies in Gene Regulatory Networks focuses on methods widely used in modeling gene networks including structure discovery, learning, and optimization. This innovative Handbook of Research presents a complete overview of computational intelligence approaches for learning and optimization and how they can be used in gene regulatory networks.

Acclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales. On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understanding of the underlying models for recommender systems and describes their historical perspective. It also analyzes their development in the content offerings and assesses their impact on user behavior.

Advances in Enterprise Information Technology Security provides a broad working knowledge of all the major security issues affecting today's enterprise IT activities. The chapters in this Premier Reference Source are written by some of the world's leading researchers and practitioners in the filed of IT security. There are no simple and complete answers to the issues of security; therefore, multiple techniques, strategies, and applications are thoroughly examined. This reference work presents the tools to address opportunities in the field, and is an all-in-one reference for IT managers, network administrators, researchers, and students.

What existential threats does humanity face? And how can we secure our future? 'The Precipice is a powerful book . . . Ord's love for humanity and hope for its future is infectious' Spectator 'Ord's analysis of the science is exemplary . . . Thrillingly written' Sunday Times We live during the most important era of human history. In the twentieth century, we developed the means to destroy ourselves - without developing the moral framework to ensure we won't. This is the Precipice, and how we respond to it will be the most crucial decision of our time. Oxford moral philosopher Toby Ord explores the risks to humanity's future, from the familiar man-made threats of climate change and nuclear war, to the potentially greater, more unfamiliar threats from engineered pandemics and advanced artificial intelligence. With clear and rigorous thinking, Ord calculates the various risk levels, and shows how our own time fits within the larger story of human history. We can say with certainty that the novel coronavirus does not pose such a risk. But could the next pandemic? And what can we do, in our present moment, to face the risks head on? A major work that brings together the disciplines of physics, biology, earth and computer science, history, anthropology, statistics, international relations, political science and moral philosophy, The Precipice is a call for a new understanding of our age: a major reorientation in the way we see the world, our history, and the role we play in it.

With the emergence of the Java 3D API, the creation of high quality 3D animated graphics for Java applications and applets becomes a possibility. With numerous aspects of the business, science, medical, and educational fields implementing this technology, the need for familiarity of Java 3D amplifies.""Interactive Web-Based Virtual Reality with Java 3D"" provides both advanced and novice programmers with comprehensive, detailed coverage of all of the important issues in Java 3D. This essential book delivers illustrations of essential keywords, syntax, and methods to provide an easy-to-read learning experience for the reader.

Processing information and analyzing data efficiently and effectively is crucial for any company that wishes to stay competitive in its respective market. Nonlinear data presents new challenges to organizations, however, due to its complexity and unpredictability. The only technology that can properly handle this form of data is artificial neural networks. These modeling systems present a high level of benefits in analyzing complex data in a proficient manner, yet considerable research on the specific applications of these intelligent components is significantly deficient. Applications of Artificial Neural Networks for Nonlinear Data is a collection of innovative research on the contemporary nature of artificial neural networks and their specific implementations within data analysis. While highlighting topics including propagation functions, optimization techniques, and learning methodologies, this book is ideally designed for researchers, statisticians, academicians, developers, scientists, practitioners, students, and educators seeking current research on the use of artificial neural networks in diagnosing and solving nonparametric problems.

Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge. Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data- including stream data, sequence data, graph structured data, social network data, and multi-relational data.

Sensor technologies play a large part in modern life, as they are present in things like security systems, digital cameras, smartphones, and motion sensors. While these devices are always evolving, research is being done to further develop this technology to help detect and analyze threats, perform in-depth inspections, and perform tracking services. Optoelectronics in Machine Vision-Based Theories and Applications provides innovative insights on theories and applications of optoelectronics in machine vision-based systems. It also covers topics such as applications of unmanned aerial vehicle, autonomous and mobile robots, medical scanning, industrial applications, agriculture, and structural health monitoring. This publication is a vital reference source for engineers, technology developers, academicians, researchers, and advanced-level students seeking emerging research on sensor technologies and machine vision.

The Internet of Things has become a major influence on the development of new technologies and innovations. When combined with smart services, the end-user experience can be significantly enhanced. Novel Design and the Applications of Smart-M3 Platforms in the Internet of Things: Emerging Research and Opportunities provides an innovative outlook on the development of open source technology for the creation of smart spaces and services. Including a range of relevant topics such as interoperability, system architecture, and information processing, this book is an ideal reference source for academics, researchers, graduate students, and practitioners interested in the latest advancements in the Internet of things.

Before the integration of expert systems in biomedical science, complex problems required human expertise to solve them through conventional procedural methods. Advancements in expert systems allow for knowledge to be extracted when no human expertise is available and increases productivity through quick diagnosis. Expert System Techniques in Biomedical Science Practice is an essential scholarly resource that contains innovative research on the methods by which an expert system is designed to solve complex problems through the automation of decision making through the use of if-then-else rules rather than conventional procedural methods. Featuring coverage on a broad range of topics such as image processing, bio-signals, and cognitive AI, this book is a vital reference source for computer engineers, information technologists, biomedical engineers, data-processing specialists, medical professionals, and industrialists within the fields of biomedical engineering, pervasive computing, and natural language processing.

Too often the suggestion of using games and virtual environments in an educational setting is met with skepticism and objections. Many traditionally-oriented educators are simply not aware of the benefits that come from implementing digital games into an instructional environment. Serious Games and Virtual Worlds in Education, Professional Development, and Healthcare seeks to counter these doubts by explaining how digital environments can easily become familiar and beneficial for educational and professional development. Highlighting techniques beyond the traditional practice, this reference source is useful for researchers, academics, professionals, and students interested in the benefits to implementing these games into various aspects of our environment.

With the ever-present growth in technology, opportunities to explore and experience technology at an early age are increasingly important in order to develop problem-solving and thinking skills. ""Technology for Early Childhood Education and Socialization: Developmental Applications and Methodologies"" provides readers with valuable and authentic research on how technology relates to early childhood growth. Including international perspectives on technology and education from expert authors, this book discusses important issues of assessment, teacher education, special education, and family involvement in terms of technology.