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Statistical language and speech processing ; 8th International Conference, SLSP 2020, Cardiff, UK, October 14–16, 2020, Proceedings
This book constitutes the proceedings of the 8th International Conference on Statistical Language and Speech Processing, SLSP 2020, held in Cardiff, UK, in October 2020. The 13 full papers presented together with one invited paper in this volume were carefully reviewed and selected from 25 submissions. They papers cover the wide spectrum of statistical methods that are currently in use in computational language or speech processing.
Statistical and Inductive Inference by Minimum Message Length
This book gives a sound introduction to the Minimum Message Length Principle and its applications, provides the theoretical arguments for the adoption of the principle, and shows the development of certain approximations that assist its practical application. MML appears also to provide both a normative and a descriptive basis for inductive reasoning generally, and scientific induction in particular. The book describes this basis and aims to show its relevance to the Philosophy of Science.
Spatially structured evolutionary algorithms : Artificial evolution in space and time
Evolutionary algorithms (EAs) is now a mature problem-solving family of heuristics that has found its way into many important real-life problems and into leading-edge scientific research. Spatially structured EAs have different properties than standard, mixing EAs. By virtue of the structured disposition of the population members they bring about new dynamical features that can be harnessed to solve difficult problems faster and more efficiently. This book describes the state of the art in spatially structured EAs by using graph concepts as a unifying theme. The models, their analysis, and their empirical behavior are presented in detail. Moreover, there is new material on non-standard networked population structures such as small-world networks.
Software engineering and data science
Data-driven software solutions are different from “traditional” software development projects, as the focus of the main development core is on managing the data (e.g., data store and data quality) and designing behavioral models with the aid of artificial intelligence and machine learning techniques. To this end, new life cycles, algorithms, methods, processes, and tools are required. This reprint is centered on the recent trends and advancements in the field of engineering data-intensive software solutions to address the challenges in developing, testing, and maintaining such data-driven systems, with a focus on the application of data-driven solutions to real-life problems and techniques and algorithms addressing the different challenges of data-driven software engineering.
Soft Computing in Industrial Applications : Recent and Emerging Methods and Techniques
Soft Computing admits approximate reasoning, imprecision, uncertainty and partial truth in order to mimic aspects of the remarkable human capability of making decisions in real-life and ambiguous environments. "Soft Computing in Industrial Applications" contains a collection of papers that were presented at the 11th On-line World Conference on Soft Computing in Industrial Applications, held in September-October 2006. This carefully edited book provides a comprehensive overview of the recent advances in the industrial applications of soft computing and covers a wide range of application areas, including data analysis and data mining, computer graphics, intelligent control, systems, pattern recognition, classifiers, as well as modeling optimization. The book is aimed at researchers and practitioners who are engaged in developing and applying intelligent systems principles to solving real-world problems. It is also suitable as wider reading for science and engineering postgraduate students.
Soft Computing Applications in Business
Soft computing techniques are widely used in most businesses. This book consists of several important papers on the applications of soft computing techniques for the business field.The soft computing techniques used in this book include (or very closely related to): Bayesian networks, biclustering methods, case-based reasoning, data mining, Dempster-Shafer theory, ensemble learning, evolutionary programming, fuzzy decision trees, hidden Markov models, intelligent agents, k-means clustering, maximum likelihood Hebbian learning, neural networks, opportunistic scheduling, probability distributions combined with Monte Carlo methods, rough sets, self organizing maps, support vector machines, uncertain reasoning, other statistical and machine learning techniques, and combinations of these techniques.
Soft Computing and Signal Processing ; Proceedings of 3rd ICSCSP 2020 ; Vol.2
Presents selected research papers on current developments in the fields of soft computing and signal processing from the Third International Conference on Soft Computing and Signal Processing (ICSCSP 2020). The book covers topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning and discusses various aspects of these topics, e.g., technological considerations, product implementation and application issues.
Soft Computing and its Engineering Applications ; 2nd International Conference, icSoftComp 2020, Changa, Anand, India, December 11–12, 2020, Proceedings
Constitutes the refereed proceedings of the Second International Conference on Soft Computing and its Engineering Applications, icSoftComp 2020, held in Changa, India, in December 2020. Due to the COVID-19 pandemic the conference was held online. The 24 full papers and 4 short papers presented were carefully reviewed and selected from 252 submissions. The papers present recent research on theory and applications in fuzzy computing, neuro computing, and evolutionary computing.
Social Computing with Artificial Intelligence
Provides a comprehensive introduction to the application of artificial intelligence in social computing, from fundamental data processing to advanced social network computing. To broaden readers’ understanding of the topics addressed, it includes extensive data and a large number of charts and references, covering theories, techniques and applications. It particularly focuses on data collection, data mining, artificial intelligence algorithms in social computing, and several key applications of social computing application, and also discusses network propagation mechanisms and dynamic analysis, which provide useful insights into how information is disseminated in online social networks. This book is intended for readers with a basic knowledge of advanced mathematics and computer science.
Smart-style studio = استوديو على الطراز الذكي
The Smart-style studio project aims to revolutionize beauty with AI-driven personalized hairstyling, virtual try-on experiences, and comprehensive hair care support. Key objectives include developing AI to suggest suitable hairstyles and chin shapes, offering realistic style previews, providing expert hair disease advice, and creating a community platform for barbers to showcase their work and facilitate bookings. Utilizing machine learning and computer vision, the project employs a GAN for virtual try-ons and an NLP-based chatbot for hair care expertise. The integrated system allows seamless appointment scheduling and enhances user satisfaction through realistic previews. Future enhancements include expanding the hairstyle database, improving real-time processing, and incorporating augmented reality.
Smart Sensing and Context ; 3rd European Conference, EuroSSC 2008, Zurich, Switzerland, October 29-31, 2008. Proceedings
This book is organized in topical sections on smart objects, spatial and human context inference, context processing and quality of context, as well as context-aware interaction and case studies.
Smart healthcare system design : Security and privacy aspects
Discusses the major challenges and issues for security and privacy aspects of smart health-care systems. Helps achieve a better integration between the work of researchers and practitioners in a single medium for capturing state-of-the-art IoT solutions in healthcare applications, and to address how to improve the proficiency of wireless sensor networks (WSNs) in healthcare. It explores possible automated solutions in everyday life, including the structures of healthcare systems built to handle large amounts of data, thereby improving clinical decisions. The 14 separate chapters address various aspects of the IoT system, such as design challenges, theory, various protocols, implementation issues, as well as several case studies.
Smart Grid and Internet of Things ; 3rd EAI International Conference, SGIoT 2019, TaiChung, Taiwan, December 5-6, 2019, Proceedings
The 10 papers presented were carefully reviewed and selected from 22 submissions and present results on how to achieve more efficient use of resources based largely on the IoT-based machine-to-machine (M2M) interactions of millions of smart meters and sensors in the smart grid specific communication networks such as home area networks, building area networks, and neighborhood area networks. The smart grid also encompasses IoT technologies, which monitor transmission lines, manage substations, integrate renewable energy generation.
Smart employee analyzer
In this project we propose an app that functions as an office helper system with a job interview ranker. To help with the hiring process, automated deception detection was performed by analyzing verbal and non-verbal cues and deploying various machine learning methods in order to detect deceit. The best results on video, audio and text were 97% , 96%, 92% respectively. Audio models used were SVM reaching 96% on the real-life dataset. Text models , SVM , NB reached 92% , 88% respectfully on Real-life dataset. Image models CNN reached 97% on real-life dataset.
Smart Buildings Digitalization : IoT and Energy Efficient Smart Buildings Architecture and Applications
Discusses various artificial intelligence and machine learning applications concerning smart buildings. It includes how renewable energy sources are integrated into smart buildings using suitable power electronic devices. The deployment of advanced technologies with monitoring, protection, and energy management features is included, along with a case study on automation. Overall, the focus is on architecture and related applications, such as power distribution, microgrids, photovoltaic systems, and renewable energy aspects. The chapters define smart building concepts and their related benefits.
Similarity Search and Applications ; 13th International Conference, SISAP 2020, Copenhagen, Denmark, September 30 – October 2, 2020, Proceedings
Constitutes the refereed proceedings of the 13th International Conference on Similarity Search and Applications, SISAP 2020, held in Copenhagen, Denmark, in September/October 2020. The conference was held virtually due to the COVID-19 pandemic. The 19 full papers presented together with 12 short and 2 doctoral symposium papers were carefully reviewed and selected from 50 submissions. The papers are organized in topical sections named: scalable similarity search; similarity measures, search, and indexing; high-dimensional data and intrinsic dimensionality; clustering; artificial intelligence and similarity;
Signal Processing Techniques for Knowledge Extraction and Information Fusion
This state-of-the-art resource brings together the latest findings from the cross-fertilization of signal processing, machine learning and computer science. The emphasis is on demonstrating synergy of different signal processing methods with knowledge extraction and heterogeneous information fusion. Issues related to the processing of signals with low signal-to-noise ratio, solving real-world multi-channel problems, and using adaptive techniques where nonstationarity, uncertainty and complexity play major roles are addressed. Particular methods include Independent Component Analysis, Support Vector Machines, Distributed and Collaborative Adaptive Filtering, Empirical Mode Decomposition, Self Organizing Maps, Fuzzy Logic, Evolutionary Algorithms and several others used frequently in these fields. Also included are both important and novel applications from telecommunications, renewable energy and biomedical engineering.
Sensors data processing using machine learning
Collects research focusing on data processing using machine learning and deep learning. We invited investigators to contribute both original and review articles, covering the research and development in the areas of data processing using machine learning (ML) and deep learning (DL). These areas include solutions that are designed for smart devices. In this reprint, leading experts in the field share their insights, research findings, and visions for the future. Together, we embark on a journey to unlock the potential of effective data processing that involves transforming data from a given format into a more usable and desirable form, rendering them more meaningful and informative. Machine learning (ML), deep learning (DL), and artificial intelligence (AI) have proven to be effective methods for this purpose. Through the utilization of machine learning algorithms, mathematical modeling, or various statistical techniques, the entire process can be automated.
Semantic web services and web process composition ; 1st International Workshop, SWSWPC 2004, San Diego, CA, USA, July 6, 2004, Revised Selected Papers
The workshop presented what can be achieved by the symbiotic s- thesis of two of the hottest R&D and technology application areas, Web services and the Semantic Web, as recognized at the 12th International World Wide Web conference (WWW 2003) and in the industry press. The emphasis of the workshop was mainly on Web services, Web processes and semantics which are important movements emerging in the World Wide Web. Web services and Web processes promise to ease several current infr- tructure challenges, such as data, application, and process integration. Web s- vices are truly platform-independent and allow the development of distributed, loosely coupled applications, a key characteristic for the success of dynamic Web processes.
Semantic Systems : The Power of AI and Knowledge Graphs ; 15th International Conference, SEMANTiCS 2019, Karlsruhe, Germany, September 9–12, 2019, Proceedings
This book cover topics such as: web semantics and linked (open) data; machine learning and deep learning techniques; semantic information management and knowledge integration; terminology, thesaurus and ontology management; data mining and knowledge discovery; semantics in blockchain and distributed ledger technologies.
