Machine Learning For Adaptive Many Core Machines A Practical Approach
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| Author | : Noel Lopes |
| Publisher | : Springer |
| Total Pages | : 251 |
| Release | : 2014-06-28 |
| Genre | : Technology & Engineering |
| ISBN | : 3319069381 |
The overwhelming data produced everyday and the increasing performance and cost requirements of applications are transversal to a wide range of activities in society, from science to industry. In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume of data, or in other words, can handle Big Data. This book gives a concise view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit (GPU) with data scalability in mind. It presents a series of new techniques to enhance, scale and distribute data in a Big Learning framework. It is not intended to be a comprehensive survey of the state of the art of the whole field of machine learning for Big Data. Its purpose is less ambitious and more practical: to explain and illustrate existing and novel GPU-based ML algorithms, not viewed as a universal solution for the Big Data challenges but rather as part of the answer, which may require the use of different strategies coupled together.
| Author | : Aboul Ella Hassanien |
| Publisher | : Springer |
| Total Pages | : 683 |
| Release | : 2018-08-28 |
| Genre | : Technology & Engineering |
| ISBN | : 3319990101 |
This book presents the proceedings of the 4th International Conference on Advanced Intelligent Systems and Informatics 2018 (AISI2018), which took place in Cairo, Egypt from September 1 to 3, 2018. This international and interdisciplinary conference, which highlighted essential research and developments in the field of informatics and intelligent systems, was organized by the Scientific Research Group in Egypt (SRGE). The book is divided into several main sections: Intelligent Systems; Robot Modeling and Control Systems; Intelligent Robotics Systems; Machine Learning Methodology and Applications; Sentiment Analysis and Arabic Text Mining; Swarm Optimizations and Applications; Deep Learning and Cloud Computing; Information Security, Hiding, and Biometric Recognition; and Data Mining, Visualization and E-learning.
| Author | : Gurminder Singh |
| Publisher | : Elsevier |
| Total Pages | : 291 |
| Release | : 2024-09-04 |
| Genre | : Technology & Engineering |
| ISBN | : 0443221464 |
Machine Learning for Powder-based Metal Additive Manufacturing outlines machine learning (ML) methods for additive manufacturing (AM) of metals that will improve product quality, optimize manufacturing processes, and reduce costs. The book combines ML and AM methods to develop intelligent models that train AM techniques in pre-processing, process optimization, and post-processing for optimized microstructure, tensile and fatigue properties, and biocompatibility for various applications. The book covers ML for design in AM, ML for materials development and intelligent monitoring in metal AM, both geometrical deviation and physics informed machine learning modeling, as well as data-driven cost estimation by ML. In addition, optimization for slicing and orientation, ML to create models of materials for AM processes, ML prediction for better mechanical and microstructure prediction, and feature extraction by sensing data are all covered, and each chapter includes a case study. - Covers machine learning (ML) methods for additive manufacturing (AM) of metals that will improve product quality, optimize manufacturing processes, and reduce costs - Combines ML and AM methods to develop intelligent models that train AM techniques in pre-processing, process optimization, and post-processing for optimized microstructure, tensile and fatigue properties, and biocompatibility for various applications - Discusses algorithm development of ML for metal AM, metal AM process modeling and optimization, mathematical and simulation studies of metal AM, and pre- and post-processing smart methods for metal AM
| Author | : Omeraki Çekirdekci, ?ahver |
| Publisher | : IGI Global |
| Total Pages | : 556 |
| Release | : 2021-11-26 |
| Genre | : Social Science |
| ISBN | : 179988676X |
The COVID-19 pandemic shook the world to its core. After a brief pause, organizations of all kinds had to adapt to the new circumstances given to them with very little time. The presence of the pandemic caused multiple threats that caused several disruptions to the norms, beliefs, and practices in various domains of everyday life. Both from macro and micro perspectives, individuals, households, markets, institutions, and governments developed strategies to respond to the new environment—responses that hope to eliminate or at least decrease the threats of the COVID-19 pandemic. The Handbook of Research on Interdisciplinary Perspectives on the Threats and Impacts of Pandemics explores the COVID-19 pandemic from an interdisciplinary perspective and determines how future pandemics may impact society. Beginning as a health threat, the pandemic has led the way to economic, social, psychological, political, and informational crises necessitating the examination of the phenomenon from different academic disciplines. Covering topics such as distance education, human security, and predictions, this handbook of research is an essential resource for scholars, managers, media representatives, governors, health officials, government officials, policymakers, students, professors, researchers, and academicians.
| Author | : D. Binu |
| Publisher | : Academic Press |
| Total Pages | : 271 |
| Release | : 2021-02-17 |
| Genre | : Science |
| ISBN | : 0128206160 |
Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications. This book is written by experienced engineers for engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area. - Provides coverage of the fundamentals of Artificial Intelligence as applied to data mining, including computational intelligence and unsupervised learning methods for data clustering - Presents coverage of key topics such as heuristic methods for data clustering, deep learning methods for data classification, and neural networks - Includes case studies and real-world applications of AI techniques in data mining, for improved outcomes in clinical diagnosis, satellite data extraction, agriculture, security and defense
| Author | : Manuel Núñez |
| Publisher | : Springer |
| Total Pages | : 668 |
| Release | : 2015-09-09 |
| Genre | : Computers |
| ISBN | : 3319243063 |
This two-volume set (LNAI 9329 and LNAI 9330) constitutes the refereed proceedings of the 7th International Conference on Collective Intelligence, ICCCI 2014, held in Madrid, Spain, in September 2015. The 110 full papers presented were carefully reviewed and selected from 186 submissions. They are organized in topical sections such as multi-agent systems; social networks and NLP; sentiment analysis; computational intelligence and games; ontologies and information extraction; formal methods and simulation; neural networks, SMT and MIS; collective intelligence in Web systems – Web systems analysis; computational swarm intelligence; cooperative strategies for decision making and optimization; advanced networking and security technologies; IT in biomedicine; collective computational intelligence in educational context; science intelligence and data analysis; computational intelligence in financial markets; ensemble learning; big data mining and searching.
| Author | : Elisa Ricci |
| Publisher | : Springer Nature |
| Total Pages | : 582 |
| Release | : 2019-09-04 |
| Genre | : Computers |
| ISBN | : 3030306429 |
The two-volume set LNCS 11751 and 11752 constitutes the refereed proceedings of the 20th International Conference on Image Analysis and Processing, ICIAP 2019, held in Trento, Italy, in September 2019. The 117 papers presented were carefully reviewed and selected from 207 submissions. The papers cover both classic and the most recent trends in image processing, computer vision, and pattern recognition, addressing both theoretical and applicative aspects. They are organized in the following topical sections: Video Analysis and Understanding; Pattern Recognition and Machine Learning; Deep Learning; Multiview Geometry and 3D Computer Vision; Image Analysis, Detection and Recognition; Multimedia; Biomedical and Assistive Technology; Digital Forensics; Image processing for Cultural Heritage.
| Author | : Management Association, Information Resources |
| Publisher | : IGI Global |
| Total Pages | : 1988 |
| Release | : 2021-09-24 |
| Genre | : Computers |
| ISBN | : 1668436639 |
Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.
| Author | : Jong Hyuk Park |
| Publisher | : Springer |
| Total Pages | : 493 |
| Release | : 2019-02-07 |
| Genre | : Computers |
| ISBN | : 9811359075 |
This book constitutes the refereed proceedings of the 19th International Conference on CParallel and Distributed Computing, Applications and Technologies, PDCAT 2018, held in Jeju Island, South Korea, in August 2018. The 35 revised full papers presented along with the 14 short papers and were carefully reviewed and selected from 150 submissions. The papers of this volume are organized in topical sections on wired and wireless communication systems, high dimensional data representation and processing, networks and information security, computing techniques for efficient networks design, electronic circuits for communication systems.
| Author | : Gupta, P.K. |
| Publisher | : IGI Global |
| Total Pages | : 316 |
| Release | : 2018-12-28 |
| Genre | : Computers |
| ISBN | : 1522562117 |
With the recent growth of big data and the internet of things (IoT), individuals can now upload, retrieve, store, and collect massive amounts of information to help drive decisions and optimize processes. Due to this, a new age of predictive computing is taking place, and data can now be harnessed to predict unknown occurrences or probabilities based on data collected in real time. Predictive Intelligence Using Big Data and the Internet of Things highlights state-of-the-art research on predictive intelligence using big data, the IoT, and related areas to ensure quality assurance and compatible IoT systems. Featuring coverage on predictive application scenarios to discuss these breakthroughs in real-world settings and various methods, frameworks, algorithms, and security concerns for predictive intelligence, this book is ideally designed for academicians, researchers, advanced-level students, and technology developers.
