Sebastián Basterrech – författare
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This book presents a key solution for current and future technological issues, adopting an integrated system approach with a combination of software engineering applications. Focusing on how software dominates and influences the performance, reliability, maintainability and availability of complex integrated systems, it proposes a comprehensive method of improving the entire process. The book provides numerous qualitative and quantitative analyses and examples of varied systems to help readers understand and interpret the derived results and outcomes. In addition, it examines and reviews foundational work associated with decision and control systems for information systems, to inspire researchers and industry professionals to develop new and integrated foundations, theories, principles, and tools for information systems. It also offers guidance and suggests best practices for the research community and practitioners alike.
The book’s twenty-two chapters examine and address current and future research topics in areas like vulnerability analysis, secured software requirements analysis, progressive models for planning and enhancing system efficiency, cloud computing, healthcare management, and integrating data-information-knowledge in decision-making.
As such it enables organizations to adopt integrated approaches to system and software engineering, helping them implement technological advances and drive performance. This in turn provides actionable insights on each and every technical and managerial level so that timely action-based decisions can be taken to maintain a competitive edge. Featuring conceptual work and best practices in integrated systems and software engineering applications, this book is also a valuable resource for all researchers, graduate and undergraduate students, and management professionals with an interest in the fields of e-commerce, cloud computing, software engineering, software & system security and analysis, data-information-knowledge systems and integrated systems.
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2 557 kr
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1 459 kr
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This book explores a range of important theoretical and practical issues in the field of computational network application tools, while also presenting the latest advances and innovations using intelligent technology approaches. The main focus is on detecting and diagnosing complex application performance problems so that an optimal and expected level of system service can be attained and maintained. The book discusses challenging issues like enhancing system efficiency, performance, and assurance management, and blends the concept of system modeling and optimization techniques with soft computing, neural network, and sensor network approaches. In addition, it presents certain metrics and measurements that can be translated into business value. These metrics and measurements can also help to establish an empirical performance baseline for various applications, which can be used to identify changes in system performance. By presenting various intelligent technologies, the book provides readers with compact but insightful information on several broad and rapidly growing areas in the computation network application domain.
The book’s twenty-two chapters examine and address current and future research topics in areas like neural networks, soft computing, nature-inspired computing, fuzzy logic and evolutionary computation, machine learning, smart security, and wireless networking, and cover a wide range of applications from pattern recognition and system modeling, to intelligent control problems and biomedical applications.
The book was written to serve a broad readership, including engineers, computer scientists, management professionals, and mathematicians interested in studying tools and techniques for computational intelligence and applications for performance analysis. Featuring theoretical concepts and best practices in computational network applications, it will also be helpful for researchers, graduate and undergraduate students with an interest in the fields of soft computing, neural networks, machine learning, sensor networks, smart security, etc.