Описание: This book aims to apply data mining and analytic techniques to past workplace accident data to discover patterns that facilitate the development of innovative models and strategies.
Описание: Internet and Distributed Computing Advancements: Theoretical Frameworks and Practical Applications is a vital compendium of chapters on the latest research within the field of distributed computing, capturing trends in the design and development of Internet and distributed computing systems that leverage autonomic principles and techniques. The chapters provided within this collection offer a holistic approach for the development of systems that can adapt themselves to meet requirements of performance, fault tolerance, reliability, security, and Quality of Service (QoS) without manual intervention.
Описание: Assembling an international team of experts, this book reports on the progress in the rapidly growing field of monolithic micro- and nanoresonators. The book opens with a chapter on photonic crystal-based resonators (nanocavities). It goes on to describe resonators in which the closed trajectories of light are supported by any variety of total internal reflection in curved and polygonal transparent dielectric structures.
The book also covers distributed feedback microresonators for slow light, controllable dispersion, and enhanced nonlinearity. A portion of coverage is dedicated to the unique properties of resonators, which are extremely efficient tools when conducting multiple applications.
Описание: This book features 21 papers spanning many different sub-fields in bioinformatics and computational biology, presenting the latest research on the practical applications to promote fruitful interactions between young researchers in different areas related to the field. Next-generation sequencing technologies, together with other emerging and diverse experimental techniques, are evolving rapidly, creating numerous types of omics data. These, in turn, are creating new challenges for the expanding fields of bioinformatics and computational biology, which seek to analyse, process, integrate and extract meaningful knowledge from such data. This calls for new algorithms and approaches from fields such as databases, statistics, data mining, machine learning, optimization, computer science, machine learning and artificial intelligence. Clearly, biology is increasingly becoming a science of information, requiring tools from the computational sciences. To address these challenges, we have seen the emergence of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific areas is, more than ever, vital to boost the research efforts in the field and contribute to the training of the new generation of interdisciplinary scientists.
Автор: V. Sathiyamoorthi, Atilla Elci Название: Challenges and Applications of Data Analytics in Social Perspectives ISBN: 1799825671 ISBN-13(EAN): 9781799825678 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 29522.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides innovative insights into the prevailing challenges in data analytics and its application on social media and focuses on various machine learning and deep learning techniques in improving practice and research. The publication examines topics that include collaborative filtering, data visualization, and edge computing.
Автор: Haldorai Anandakumar, Ramu Arulmurugan Название: Cognitive Social Mining Applications in Data Analytics and Forensics ISBN: 1522586687 ISBN-13(EAN): 9781522586685 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 18810.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. The book features research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing.
Chapter 1. Introduction.- Chapter 2. Sets, Venn diagrams, Probability and Bayes' Rule.- Chapter 3. Concept of a random variable.- Chapter 4. Multiple random variables and their Characteristics.- Chapter 5. Applications to Data Analytics and Modeling.
Описание: This book gathers the proceedings of the 8th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2020), held at NIT Surathkal, Karnataka, India, on 4-5 January 2020.
Описание: Chapter 1. What do RDMs capture in Brain Responses and Computational Models?.- Chapter 2. Challenges and solutions, in developing Convolutional Neural Networks and Long Short Term Memory networks, for industry problems.- Chapter 3. Speed, Cloth and Pose Invariant Gait recognition Based Person Identifification.- Chapter 4. Applications of Machine learning in industry 4.0.- Chapter 5. Web Semantics and Knowledge Graph.- Chapter 6. Machine Learning based Wireless Sensor Networks.- Chapter 7. AI to Machine Learning: lifeless automation and Issues.- Chapter 8. Analysis of FDIs in Different Sectors of the Indian Economy.- Chapter 9. Customer Profiling & Retention using Recommendation system and Factor Identification to predict Customer Chur In Telecom Industry.
This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine. It will combine the design and problem-solving skills of engineering with health sciences, in order to advance healthcare treatment. The book will include areas such as diagnosis, monitoring, and therapy.
The book will provide real-world case studies, gives a detailed exploration of applications in healthcare systems, offers multiple perspectives on a variety of disciplines, while also letting the reader know how to avoid some of the consequences of old methods with data sharing.
The book can be used as a reference for practitioners, researchers and for students at basic and intermediary levels in Computer Science, Electronics and Communications.
Chapter 1. Introduction.- Chapter 2. Sets, Venn diagrams, Probability and Bayes' Rule.- Chapter 3. Concept of a random variable.- Chapter 4. Multiple random variables and their Characteristics.- Chapter 5. Applications to Data Analytics and Modeling.
Описание: This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements.
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