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  • 1
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    Springer Nature | Springer
    Publication Date: 2024-04-14
    Description: This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic.
    Keywords: Computer Communication Networks ; Artificial Intelligence ; Information Systems Applications (incl. Internet) ; Special Purpose and Application-Based Systems ; Computer System Implementation ; User Interfaces and Human Computer Interaction ; Computer and Information Systems Applications ; open access ; artificial intelligence ; communication systems ; computer vision ; databases ; hci ; human-computer interaction ; image processing ; Internet of Things ; IoT ; machine learning ; network protocols ; sensors ; signal processing ; software architecture ; software design ; telecommunication networks ; telecommunication systems ; user interfaces ; wireless telecommunication systems ; Network hardware ; Artificial intelligence ; Information retrieval ; Internet searching ; Expert systems / knowledge-based systems ; Systems analysis & design ; User interface design & usability ; thema EDItEUR::U Computing and Information Technology::UK Computer hardware::UKN Network hardware ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UN Databases::UNH Information retrieval ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQE Expert systems / knowledge-based systems ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYD Systems analysis and design ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYZ Human–computer interaction::UYZG User interface design and usability
    Language: English
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  • 2
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    Springer Nature | Springer
    Publication Date: 2024-04-14
    Description: This open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.
    Keywords: artificial intelligence ; communication systems ; computer hardware ; computer networks ; computer programming ; computer systems ; computer vision ; deep learning ; distributed computer systems ; image analysis ; image processing ; machine learning ; network protocols ; neural networks ; signal processing ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYZ Human–computer interaction::UYZG User interface design and usability ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQV Computer vision ; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications
    Language: English
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  • 3
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    Springer Nature | Springer
    Publication Date: 2024-04-14
    Description: This open access book constitutes the refereed proceedings of the 18th China Annual Conference on Cyber Security, CNCERT 2022, held in Beijing, China, in August 2022. The 17 papers presented were carefully reviewed and selected from 64 submissions. The papers are organized according to the following topical sections: ​​data security; anomaly detection; cryptocurrency; information security; vulnerabilities; mobile internet; threat intelligence; text recognition.
    Keywords: application service layer ; artificial intelligence ; communication systems ; computer crime ; computer networks ; computer security ; computer systems ; cryptography ; cyber security ; data communication systems ; data security ; databases ; machine learning ; network protocols ; network security ; privacy ; signal processing ; telecommunication networks ; telecommunication systems ; thema EDItEUR::U Computing and Information Technology::UR Computer security ; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBL Digital and information technologies: Legal aspects ; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTN Network security
    Language: English
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  • 4
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    Springer Nature | Springer
    Publication Date: 2024-04-14
    Description: This open access book introduces Vector semantics, which links the formal theory of word vectors to the cognitive theory of linguistics. The computational linguists and deep learning researchers who developed word vectors have relied primarily on the ever-increasing availability of large corpora and of computers with highly parallel GPU and TPU compute engines, and their focus is with endowing computers with natural language capabilities for practical applications such as machine translation or question answering. Cognitive linguists investigate natural language from the perspective of human cognition, the relation between language and thought, and questions about conceptual universals, relying primarily on in-depth investigation of language in use. In spite of the fact that these two schools both have ‘linguistics’ in their name, so far there has been very limited communication between them, as their historical origins, data collection methods, and conceptual apparatuses are quite different. Vector semantics bridges the gap by presenting a formal theory, cast in terms of linear polytopes, that generalizes both word vectors and conceptual structures, by treating each dictionary definition as an equation, and the entire lexicon as a set of equations mutually constraining all meanings.
    Keywords: Semantics ; Natural Language Processing ; Computational Linguistics ; Artificial Intelligence ; explainable AI ; Artificial Neural Nets ; lexical semantics ; word vectors ; embeddings ; dynamic embeddings ; algebraic semantic ; knowledge bases ; machine learning ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQL Natural language and machine translation ; thema EDItEUR::C Language and Linguistics::CF Linguistics::CFX Computational and corpus linguistics ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQE Expert systems / knowledge-based systems ; thema EDItEUR::D Biography, Literature and Literary studies::D Biography, Literature and Literary studies::DS Literature: history and criticism
    Language: English
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  • 5
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    Springer Nature | Springer
    Publication Date: 2024-04-14
    Description: This two-volume set LNCS 12962 and 12963 constitutes the thoroughly refereed proceedings of the 7th International MICCAI Brainlesion Workshop, BrainLes 2021, as well as the RSNA-ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge, the Federated Tumor Segmentation (FeTS) Challenge, the Cross-Modality Domain Adaptation (CrossMoDA) Challenge, and the challenge on Quantification of Uncertainties in Biomedical Image Quantification (QUBIQ). These were held jointly at the 23rd Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2020, in September 2021. The 91 revised papers presented in these volumes were selected form 151 submissions. Due to COVID-19 pandemic the conference was held virtually. This is an open access book.
    Keywords: artificial intelligence ; bioinformatics ; computer science ; computer systems ; computer vision ; education ; image analysis ; image processing ; image segmentation ; learning ; machine learning ; medical images ; neural networks ; pattern recognition ; segmentation methods ; software design ; software engineering ; software quality ; validation ; verification and validation ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYT Image processing ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence ; thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications ; thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics
    Language: English
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    OR spectrum 17 (1995), S. 55-66 
    ISSN: 1436-6304
    Keywords: Local search ; simulated annealing ; tabu search ; genetic algorithms ; machine learning ; knowledge based information systems ; Lokale Suche ; Simulated Annealing ; Tabu Search ; Genetische Algorithmen ; Maschinelles Lernen ; Wissensbasierte Informationssysteme
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Description / Table of Contents: Zusammenfassung Aus drei Gründen stellen wir diesem Sonderheft „Applied Local Search“ ein erweitertes Vorwort voran. Erstens sollen die mittlerweile bereits als klassisch zu bezeichnenden Strukturen und Ideen von dem, was derzeit unter lokaler Suche verstanden wird, vorgestellt werden. Simulated Annealing, Tabu Search and Genetische Algorithmen werden somit in ihren Grandelementen beschrieben, wobei der Schwerpunkt bewußt auf Tabu Search liegt, das sich derzeit als beste Strategie zur Lösung kombinatorischer Optimierungsprobleme etabliert hat. Neuere und mittlerweile sehr erfolgreiche aber immer noch wenig bekannte Ideen, wie die Reverse Elimination Methode und Ejection Chains, werden ebenfalls im Rahmen von Tabu Search vorgestellt. Zweites Anliegen ist, die Einbettung von lokalen Suchverfahren in einem allgemeineren Kontext wissensbasierter Informationssysteme zu beschreiben. Lokale Suche wird dabei als ein Paradigma maschinellen Lernens betrachtet. Schließlich soll dieses Vorwort ebenfalls einen kurzen Überblick der in diesem Heft enthaltenen Arbeiten geben und sie aufgrund der Verfahren und Modelle gruppieren.
    Notes: Abstract The idea of this extended foreword to the special issue on applied local search is threefold. Firstly, we provide a brief and fundamental description of what is nowadays called local search. Components which have meanwhile become an integral part of the classical aspects on simulated annealing, tabu search and genetic algorithms are reviewed. Furthermore, today tabu search can be considered as the major pillar of local search. Hence, attention is drawn to a couple of tabu search issues more recently developed such as the reverse elimination method and ejection chains. Secondly, local search based knowledge engineering is developed to constitute a substantial part of knowledge based information systems. Within this general setting local search will be considered as one particular paradigm of machine learning. Thirdly, we are going to introduce what is considered to be the main subject of this issue, local search applications. We briefly embed the contents of the subsequent papers and group them with respect to their particular methods and models within the above mentioned framework.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    Springer
    Journal of intelligent manufacturing 9 (1998), S. 161-166 
    ISSN: 1572-8145
    Keywords: Autonomous agents ; behaviours ; self-organization ; machine learning
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract During the last few years, in an attempt to provide an efficient alternative to classical methods to designing robot control structures, the behaviour-based approach has emerged. Its success has largely been a result of the bottom-up development of a number of fast, tightly coupled control processes. This new approach, however, has some important limitations because of its lack of goal directedness and flexibility. This paper describes a self-improving control system that would deal with some of these problems. The system is based on two levels of arbitration, a local level which enables the robot to survive in a particular real-world situation, and a global level which ensures that the robot reactions be consistent with the required goal. Emphasis is put on the local arbitration level: it is shown how the local priorities can be computed and learnt and some simulation results are presented.
    Type of Medium: Electronic Resource
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  • 8
    ISSN: 1572-8145
    Keywords: Neural networks ; quality engineering ; sensor integration ; machine learning
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Artificial neural networks have been shown to have a lot of potential as a means of integrating multi-sensor signals for real-time monitoring of machining processes. However, many questions still remain to be answered on how to optimize the training parameters during the training phase to optimize their subsequent performance, especially in view of the fact that the few published articles have made conflicting recommendations. This paper presents a systematic evaluation of the individual effects of training parameters — learning rate, momentum rate, number of hidden layer nodes, transfer function and learning rule-on the performance of back-propagation networks used for predicting quality characteristics of end-milled parts. Multi-sensor signatures (acoustic emission, spindle vibration, cutting force components and machining time) acquired during circular end-milling of 4140 steel and the corresponding measured quality characteristics (surface roughness and bore tolerance) were used to train the networks. The network is part of a proposed intelligent machining monitoring and diagnostic system for quality assurance of machined parts. The network performances were evaluated using four different criteria: maximum error, rms error, mean error and number of training cycles. One of the results obtained shows that the hyperbolic tangent transfer function gives a better performance than the sigmoid and sine functions respectively. Optimum combinations of training parameters have been observed. The effects of various combinations of training parameters are presented.
    Type of Medium: Electronic Resource
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  • 9
    Electronic Resource
    Electronic Resource
    Springer
    Journal of intelligent manufacturing 9 (1998), S. 323-329 
    ISSN: 1572-8145
    Keywords: Intelligent manufacturing ; machine learning ; neuro–fuzzy systems ; genetic algorithms
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract Intelligence is strongly connected with learning adapting abilities, therefore such capabilities are considered as indispensable features of intelligent manufacturing systems (IMSs). A number of approaches have been described to apply different machine learning (ML) techniques for manufacturing problems, starting with rule induction in symbolic domains and pattern recognition techniques in numerical, subsymbolic domains. In recent years, artificial neural network (ANN) based learning is the dominant ML technique in manufacturing. However, mainly because of the ‘black box’ nature of ANNs, these solutions have limited industrial acceptance. In the paper, the integration of neural and fuzzy techniques is treated and former solutions are analysed. A genetic algorithm (GA) based approach is introduced to overcome problems that are experienced during manufacturing applications with other algorithms.
    Type of Medium: Electronic Resource
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  • 10
    Electronic Resource
    Electronic Resource
    Springer
    Journal of intelligent manufacturing 5 (1994), S. 165-176 
    ISSN: 1572-8145
    Keywords: Production management ; knowledge extraction ; machine learning ; industrial databases
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: A procedure and underlying algorithm for extracting knowledge from production and inventory databases to support engineering management activities is described. The process searches for, detects and isolates behaviour patterns inherent in the data. It relates these patterns to production irregularities, suggests connections with specific causes and helps propose possible corrective or preventive actions. The approach is based on a four-phase procedure: (1) the decision-maker focuses on the subject or difficulty at issue, represented by a target concept; (2) the KEDB algorithm, based on a machine learning approach, processes the relevant database and provides knowledge characterizing and classifying the target concept; (3) the output is interpreted in Pareto fashion as a series of possible circumstances explaining the target concept behaviour; and (4) based on these causes, the decision-maker decides on possible corrective actions to improve the situation, or preventive actions to forestall unfavourable conditions. A case study based on an actual quality control database is detailed.
    Type of Medium: Electronic Resource
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