While doctors and physicians are more than capable of detecting diseases of the brain, the most agile human mind cannot compete with the processing power of modern technology. Utilizing algorithmic systems in healthcare in this way may provide a way to treat neurological diseases before they happen. Early Detection of Neurological Disorders Using Machine Learning Systems provides innovative insights into implementing smart systems to detect neurological diseases at a faster rate than by normal means. The topics included in this book are artificial intelligence, data analysis, and biomedical informatics. It is designed for clinicians, doctors, neurologists, physiotherapists, neurorehabilitation specialists, scholars, academics, and students interested in topics centered on biomedical engineering, bio-electronics, medical electronics, physiology, neurosciences, life sciences, and physics.

With the growing use of new technologies and artificial intelligence (AI) applications, intelligent systems can be used to manage large amounts of existing data in healthcare domains. Having more intelligent methods for accessing data allows medical professionals to more efficiently identify the best medical practices and more concrete solutions for diagnosing and treating a multitude of rare diseases. Intelligent Systems for Healthcare Management and Delivery provides relevant and advanced methodological, technological, and scientific approaches related to the application of sophisticated exploitation of AI, as well as providing insight into the technologies and intelligent applications that have received growing attention in recent years such as medical imaging, EMR systems, and drug development assistance. This publication fosters a scientific debate for new healthcare intelligent systems and sophisticated approaches for enhanced healthcare services and is ideally designed for medical professionals, hospital staff, rehabilitation specialists, medical educators, and researchers.

Learn application security from the very start, with this comprehensive and approachable guide! Alice and Bob Learn Application Security is an accessible and thorough resource for anyone seeking to incorporate, from the beginning of the System Development Life Cycle, best security practices in software development. This book covers all the basic subjects such as threat modeling and security testing, but also dives deep into more complex and advanced topics for securing modern software systems and architectures. Throughout, the book offers analogies, stories of the characters Alice and Bob, real-life examples, technical explanations and diagrams to ensure maximum clarity of the many abstract and complicated subjects. Topics include: Secure requirements, design, coding, and deployment Security Testing (all forms) Common Pitfalls Application Security Programs Securing Modern Applications Software Developer Security Hygiene Alice and Bob Learn Application Security is perfect for aspiring application security engineers and practicing software developers, as well as software project managers, penetration testers, and chief information security officers who seek to build or improve their application security programs. Alice and Bob Learn Application Security illustrates all the included concepts with easy-to-understand examples and concrete practical applications, furthering the reader's ability to grasp and retain the foundational and advanced topics contained within.

Data mapping in a data warehouse is the process of creating a link between two distinct data models' (source and target) tables/attributes. Data mapping is required at many stages of DW life-cycle to help save processor overhead; every stage has its own unique requirements and challenges. Therefore, many data warehouse professionals want to learn data mapping in order to move from an ETL (extract, transform, and load data between databases) developer to a data modeler role. Data Mapping for Data Warehouse Design provides basic and advanced knowledge about business intelligence and data warehouse concepts including real life scenarios that apply the standard techniques to projects across various domains. After reading this book, readers will understand the importance of data mapping across the data warehouse life cycle.

The book systematically introduces smart power system design and its infrastructure, platform and operating standards. It focuses on multi-objective optimization and illustrates where the intelligence of the system lies. With abundant project data, this book is a practical guideline for engineers and researchers in electrical engineering, as well as power network designers and managers in administration.

GBBS Pro is a user-friendly, highly-modifiable Bulletin Board System (BBS) for communications and entertainment. It has advanced features that can be configured by a novice, yet challenge advanced programmers. Originally released between 1980 and 1990 for Apple II computers, this new version features Y2K compatibility and improved reliability. Experience the world of BBS's from days gone by and start your own BBS system! GBBS Pro Features: Multiple Bulletin Boards, Private Electronic Mail, Full Editor, Downloads/Uploads, Voting/Survey, Expandable Features, Modem Support, and Internet-capable. Over 240 pages of expanded documentation, tutorials, GBBS development history, as well as forwards from Kevin M. Smallwood and experienced BBS sysops.

Great handbook to get you going with Ruby Programming! Skip your traditional technical books and dive right in so your proficient with programming instantly! Need to learn fast, tired of spending too much time trying to get through your standard technical books? Just want to get started and begin all your desired program development by the end of the day? Learn to set up with Ruby now All the Ruby Syntax you need immediately at your fingertips Access to all different statements And even Object oriented programming within this read! One click equals all of Ruby Programming! Get it now!

"What information do these data reveal?" "Is the information correct?" "How can I make the best use of the information?" The widespread use of computers and our reliance on the data generated by them have made these questions increasingly common and important. Computerized data may be in either digital or analog form and may be relevant to a wide range of applications that include medical monitoring and diagnosis, scientific research, engineering, quality control, seismology, meteorology, political and economic analysis and business and personal financial applications. The sources of the data may be databases that have been developed for specific purposes or may be of more general interest and include those that are accessible on the Internet. In addition, the data may represent either single or multiple parameters. Examining data in its initial form is often very laborious and also makes it possible to "miss the forest for the trees" by failing to notice patterns in the data that are not readily apparent. To address these problems, this monograph describes several accurate and efficient methods for displaying, reviewing and analyzing digital and analog data. The methods may be used either singly or in various combinations to maximize the value of the data to those for whom it is relevant. None of the methods requires special devices and each can be used on common platforms such as personal computers, tablets and smart phones. Also, each of the methods can be easily employed utilizing widely available off-the-shelf software. Using the methods does not require special expertise in computer science or technology, graphical design or statistical analysis. The usefulness and accuracy of all the described methods of data display, review and interpretation have been confirmed in multiple carefully performed studies using independent, objective endpoints. These studies and their results are described in the monograph. Because of their ease of use, accuracy and efficiency, the methods for displaying, reviewing and analyzing data described in this monograph can be highly useful to all who must work with computerized information and make decisions based upon it.

The WWW era made billions of people dramatically dependent on the progress of data technologies, out of which Internet search and Big Data are arguably the most notable. Structured Search paradigm connects them via a fundamental concept of key-objects evolving out of keywords as the units of search. The key-object data model and KeySQL revamp the data independence principle making it applicable for Big Data and complement NoSQL with full-blown structured querying functionality. The ultimate goal is extracting Big Information from the Big Data. As a Big Data Consultant, Mikhail Gilula combines academic background with 20 years of industry experience in the database and data warehousing technologies working as a Sr. Data Architect for Teradata, Alcatel-Lucent, and PayPal, among others. He has authored three books, including The Set Model for Database and Information Systems and holds four US Patents in Structured Search and Data Integration.

A variety of applications have been developed in order to engage with society. These tools have enabled computer scientists to captured large sets of unstructured data for machine learning and make the information widely available in academia. Techniques for Coding Imagery and Multimedia: Emerging Research and Opportunities is a pivotal reference source featuring the latest scholarly research on ways researchers code imagery and multimedia for research purposes, as well as describe some of the applied methods for research value. Including coverage on a wide variety of topics such as linguistic analysis, gender communication, and mass surveillance, this book is an important resource for researchers, academics, graduate students, and professionals seeking current research on best ways to globally expand multimedia research and imagery.

An intellectual property discussion is central to qualitative research projects, and ethical guidelines are essential to the safe accomplishment of research projects. Undertaking research studies without adhering to ethics may be dangerous to researchers and research subjects. Therefore, it is important to understand and develop practical techniques for handling ethics with a specific focus on qualitative projects so that researchers conducting this type of research may continue to use ethical practices at every step of the project. Data Analysis and Methods of Qualitative Research: Emerging Research and Opportunities discusses in detail the methods related to the social constructionist paradigm that is popular with qualitative research projects. These methods help researchers undertake ideal qualitative projects that are free from quantitative research techniques/concepts all while acquiring practical skills in handling ethics and ethical issues in qualitative projects. The chapters each contain case studies, learning outcomes, question and answer sections, and discuss critical research philosophies in detail along with topics such as ethics, research design, data gathering and sampling methods, research outputs, data analysis, and report writing. Featuring a wide range of topics such as epistemology, probability sampling, and big data, this book is ideal for researchers, practitioners, computer scientists, academicians, analysts, coders, and students looking to become competent qualitative research specialists.

RPG Programming at its best! Discover A Book That Tells You What You Should Do and How! Instead of jumping right into the instructions, this book will provide you first with all the necessary concepts that you need to learn in order to make the learning process a whole lot easier. This way, you're sure not to get lost in confusion once you get to the more complex lessons provided in the latter chapters. Graphs and flowcharts, as well as sample codes, are provided for a more visual approach on your learning You will also learn the designs and forms of Parallel, and what's more convenient than getting to know both sides! Want to know More? Buy Now

Fog computing is quickly increasing its applications and uses to the next level. As it continues to grow, different types of virtualization technologies can thrust this branch of computing further into mainstream use. The Handbook of Research on Cloud and Fog Computing Infrastructures for Data Science is a key reference volume on the latest research on the role of next-generation systems and devices that are capable of self-learning and how those devices will impact society. Featuring wide-ranging coverage across a variety of relevant views and themes such as cognitive analytics, data mining algorithms, and the internet of things, this publication is ideally designed for programmers, IT professionals, students, researchers, and engineers looking for innovative research on software-defined cloud infrastructures and domain-specific analytics.