الصفحة 5
الصفحة 5
Intelligent Algorithms for Packing and Cutting Problem
Introduces intelligent solving algorithms for classical packing and cutting problem and their variants / Investigates novel methods, e.g. reinforcement learning algorithms, for rectangular and irregular packing problems / Presents practical engineering application cases in combination of theory and practice / investigates in detail the two-dimensional packing and cutting problems in the field of operations research and management science. It introduces the mathematical models and intelligent solving algorithms for these problems, as well as their engineering applications. Most intelligent methods reported in this book have already been applied in reality, which can provide reference for the engineers. The presented novel methods for the two-dimensional packing problem provide a new way to solve the problem for researchers interested in operations research or computer science. This book also introduces three new variants of packing problems and their solving methods, which offer a different research direction.
Integrating Data Science and Earth Science : Challenges and Solutions
This book presents the results of three years collaboration between earth scientists and data scientist, in developing and applying data science methods for scientific discovery. The book will be highly beneficial for other researchers at senior and graduate level, interested in applying visual data exploration, computational approaches and scientifc workflows.
Inside deep learning : Math, algorithms, models
Journey through the theory and practice of modern deep learning, and apply innovative techniques to solve everyday data problems. In Inside Deep Learning, you will learn how to: Implement deep learning with PyTorch Select the right deep learning components Train and evaluate a deep learning model Fine tune deep learning models to maximize performance Understand deep learning terminology Adapt existing PyTorch code to solve new problems Inside Deep Learning is an accessible guide to implementing deep learning with the PyTorch framework. It demystifies complex deep learning concepts and teaches you to understand the vocabulary of deep learning so you can keep pace in a rapidly evolving field. No detail is skipped--you'll dive into math, theory, and practical applications. Everything is clearly explained in plain English.
Innovative Learning Environments in STEM Higher Education : Opportunities, Challenges, and Looking Forward
As explored in this book, higher education in STEM fields is influenced by many factors, including education research, government and school policies, financial considerations, technology limitations, and acceptance of innovations by faculty and students.
Innovations in Machine Learning : Theory and Applications
Machine learning is currently one of the most rapidly growing areas of research in computer science. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. This book covers the three main learning systems; symbolic learning, neural networks and genetic algorithms as well as providing a tutorial on learning casual influences. Each of the nine chapters is self-contained. Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Postgraduate since it shows the direction of current research.
Innovations in Hybrid Intelligent Systems
Hybrid Artificial Intelligence Systems (HAIS) combines symbolic and sub-symbolic techniques to construct more robust and reliable problem solving models. This volume focused on "Hybrid Artificial Intelligence Systems" contains a collection of papers that were presented at the 2nd International Workshop on Hybrid Artificial Intelligence Systems, held in 12 - 13 November, 2007, Salamanca, Spain. This carefully edited book provides a comprehensive overview of the recent advances in the hybrid intelligent systems and covers a wide range of application areas, including data analysis and data mining, intelligent control, pattern recognition, robotics, optimization, etc. The book is aimed at researchers, practitioners and postgraduate students who are engaged in developing and applying advanced intelligent systems principles to solving real-world problems.
Innovations in Applied Artificial Intelligence ; 18th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2005, Bari, Italy, June 22-24, 2005, Proceedings
The contributions oriented to the technological aspects of AI and the quality of the papers are witness to a research activity clearly aimed at consolidating the theoretical results that have already been achieved. The c- ference program also included two invited lectures, by Katharina Morik and Roberto Pieraccini. Many people contributed in different ways to the success of the conference and to this volume. The authors who continue to show their enthusiastic interest in applied intelligence research are a very important part of our success. We highly appreciate the contribution of the members of the Program Committee, as well as others who reviewed all the submitted papers with eficiency and dedication.
Innovations for requirement analysis : From stakeholders needs to formal designs ; 14th Monterey Workshop 2007, Monterey, CA, USA, September 10-13, 2007. Revised Selected Papers
This book presents the thoroughly refereed and revised proceedings of the 14th Monterey workshop, held in Monterey, CA, USA, September 10-13, 2007. The theme of the workshop was Innovations for Requirement Analysis: From Stakeholders' Needs to Formal Designs.The 10 revised full papers included in the book were carefully selected during two rounds of reviewing and revision. These are preceded by the abstracts of the three keynote talks as well as a detailed introduction to the theme of the workshop, including a case study used by many participants to frame their analyses, and a summary of the workshop's results.
Information theory and machine learning
The recent successes of machine learning, especially regarding systems based on deep neural networks, have encouraged further research activities and raised a new set of challenges in understanding and designing complex machine learning algorithms. New applications require learning algorithms to be distributed, have transferable learning results, use computation resources efficiently, convergence quickly on online settings, have performance guarantees, satisfy fairness or privacy constraints, incorporate domain knowledge on model structures, etc. A new wave of developments in statistical learning theory and information theory has set out to address these challenges.
Information Systems Security ; 16th International Conference, ICISS 2020, Jammu, India, December 16–20, 2020, Proceedings
This book constitutes the proceedings of the 16th International Conference on Information Systems Security, ICISS 2020, held in Jammu, India, during December 16-20, 2020. The 11 regular papers, 2 short papers and 3 work-in-progress papers included in this volume were carefully reviewed and selected from a total of 53 submissions. The papers were organized in topical sections named: access control; AI/ML in security; privacy and Web security; cryptography; and systems security.
Information systems management
Intended for the technical reader who works with large volumes of data. Written by experts in information systems management, the book includes chapters on software development, cloud implementation, networking, and handling large datasets, among other topics. Blockchain and artificial intelligence (AI) are the foundations of automated systems and the authors provide their viewpoints on information management by using these fundamental domains of information technology.
Information Security Handbook
Provides a comprehensive collection of knowledge for emerging multidisciplinary research areas such as cybersecurity, IoT, Blockchain, Machine Learning, Data Science, and AI. This book brings together, in one resource, information security across multiple domains. It explores basic and high-level concepts and serves as a manual for industry while also helping beginners to understand both basic and advanced aspects in security-related issues. The handbook explores security and privacy issues through the IoT ecosystem and implications to the real world and, at the same time, explains the concepts of IoT-related technologies, trends, and future directions.
Information security and privacy ; 25th Australasian Conference, ACISP 2020, Perth, WA, Australia, November 30 – December 2, 2020, Proceedings
This book constitutes the refereed proceedings of the 25th Australasian Conference on Information Security and Privacy, ACISP 2020, held in Perth, WA, Australia, in November 2020*. The 31 revised full papers and 5 short papers presented were carefully revised and selected from 151 submissions. The papers present and discuss the latest research, trends, breakthroughs, and challenges in the domain of information security, privacy and cybersecurity on a variety of topics such as post-quantum cryptography; symmetric cipher; signature; network security and blockchain; cryptographic primitives; mathematical foundation; machine learning security, among others.
Information Retrieval Technology ; 4th Asia Infomation Retrieval Symposium, AIRS 2008, Harbin, China, January 15-18, 2008 Revised Selected Papers
This book constitutes the thoroughly refereed post-conference proceedings of the 4th Asia Information Retrieval Symposium, AIRS 2008, held in Harbin, China, in May 2008.The 39 revised full papers and 43 revised poster papers presented were carefully reviewed and selected from 144 submissions. All current issues in information retrieval are addressed: applications, systems, technologies and theoretical aspects of information retrieval in text, audio, image, video and multi-media data. The papers are organized in topical sections on IR models image retrieval.
Information Management and Big Data ; 7th Annual International Conference, SIMBig 2020, Lima, Peru, October 1–3, 2020, Proceedings
This book constitutes the refereed proceedings of the 7th International Conference on Information Management and Big Data, SIMBig 2020, held in Lima, Peru, in October 2020.* The 32 revised full papers and 7 revised short papers presented were carefully reviewed and selected from 122 submissions. The papers address topics such as natural language processing and text mining; machine learning; image processing; social networks; data-driven software engineering; graph mining; and Semantic Web, repositories, and visualization.
Information extraction : Algorithms and prospects in a retrieval context
The book focuses on content recognition in text. It elaborates on the past and current most successful algorithms and their application in a variety of domains (e.g., news filtering, mining of biomedical text, intelligence gathering, competitive intelligence, legal information searching, and processing of informal text). An important part discusses current statistical and machine learning algorithms for information detection and classification and integrates their results in probabilistic retrieval models. The book also reveals a number of ideas towards an advanced understanding and synthesis of textual content.
Information and knowledge systems : Digital technologies, artificial intelligence and decision making ; 5th International Conference, ICIKS 2021, Virtual Event, June 22–23, 2021, Proceedings
This book constitutes the thoroughly refereed proceedings of the 5th International Conference on Information and Knowledge Systems, ICIKS 2021, which was held online during June 22-23, 2021. The International Conference on Information and Knowledge Systems (ICIKS 2021) gathered both researchers and practitioners in the fields of Information Systems, Artificial Intelligence, Knowledge Management and Decision Support. ICIKS seeks to promote discussions on various organizational, technological, and socio-cultural aspects of research in the design and use of information and knowledge systems in organizations.
Information and Complexity in Statistical Modeling
The main theme in this book is to teach modeling based on the principle that the objective is to extract the information from data that can be learned with suggested classes of probability models. The intuitive and fundamental concepts of complexity, learnable information, and noise are formalized, which provides a firm information theoretic foundation for statistical modeling.
Informatics in Control, Automation and Robotics II
Informatics in Control, Automation and Robotics II is a collection of the best papers presented at the 2nd International Conference on Informatics in Control, Automation and Robotics (ICINCO). The purpose of ICINCO was to bring together researchers, engineers and practitioners interested in the application of informatics to Control, Automation and Robotics.
Inductive logic programming ; 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected Papers
The 18th International Conference on Inductive Logic Programming was held in Prague, September 10–12, 2008. ILP returned to Prague after 11 years, and it is tempting to look at how the topics of interest have evolved during that time. The ILP community clearly continues to cherish its beloved ?rst-order logic representation framework. This is legitimate, as the work presented at ILP 2008 demonstrated that there is still room for both extending established ILP approaches (such as inverse entailment) and exploring novel logic induction frameworks (such as brave induction). Besides the topics lending ILP research its unique focus.
