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[null,null,"Titolo",null,"Intelligent Systems and Applications : Proceedings of the 2022 Intelligent Systems Conference (IntelliSys) Volume 1 / / edited by Kohei Arai"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023"]
[null,null,"ISBN",null,"9783031160721"]
[{"$nulls":4},"9783031160714"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (832 pages)"]
[null,null,"Collana",null,"Lecture Notes in Networks and Systems, , 2367-3389 ; ; 542"]
[null,null,"Disciplina",null,"629.8"]
[{"$nulls":4},"006.3"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Automatic control"]
[{"$nulls":4},"Robotics"]
[{"$nulls":4},"Automation"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Control, Robotics, Automation"]
[{"$nulls":4},"Artificial Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Editor's Preface -- Contents -- Anomaly-Based Risk Detection Using Digital News Articles -- 1 Introduction -- 2 Background -- 2.1 Elliptic Envelope -- 2.2 Local Outlier Factor -- 2.3 Isolation Forest -- 2.4 Seasonal and Trend Decomposition Using Loess -- 2.5 Natural Language Processing -- 3 Approach -- 3.1 Data and Preprocessing -- 3.2 Anomaly Detection -- 3.3 News-Cluster Risk Analysis -- 3.4 Matching Anomalies and News-Cluster Risks -- 4 Evaluation -- 5 Results -- 6 Related Work -- 7 Conclusion -- References -- Robust Rule Based Neural Network Using Arithmetic Fuzzy Inference System -- 1 Introduction -- 2 Distending Function and Weighted Dombi Operator -- 3 Proposed Network Structure -- 3.1 Feed-Forward Calculations -- 3.2 Feedback Calculations -- 4 Training -- 5 Simulation Results and Discussion -- 5.1 Selling Price Prediction of Used Cars -- 5.2 IRIS Flower Species Classification -- 5.3 Wine Quality Dataset -- 6 Conclusion -- References -- A Hierarchical Approach for Spanish Sign "]
[{"$nulls":4},"Language Recognition: From Weak Classification to Robust Recognition System -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Data Collection -- 3.2 Followed Pipeline -- 4 Experimental Results -- 5 Discussion -- 6 Conclusion and Future Work -- References -- Deontic Sentence Classification Using Tree Kernel Classifiers -- 1 Introduction -- 2 Methodology -- 2.1 Akoma Ntoso -- 2.2 LegalRuleML -- 2.3 Tree Kernels and Tree Representation -- 3 Related Works -- 4 Data -- 5 Experiment Settings and Results -- 6 Conclusions -- References -- Sparse Distributed Memory for Sparse Distributed Data -- 1 Purpose -- 2 Background -- 3 Model -- 4 Results -- 5 Conclusions -- References -- Quantum Displacements Dictated by Machine Learning Principles: Towards Optimization of Quantum Paths -- 1 Introduction -- 2 The Quantum Mechanics Machinery -- 2.1 Discrete Case."]
[{"$nulls":4},"2.2 Continuous Case -- 2.3 Applications -- 2.4 Extraction of Propagator -- 2.5 Choice of Hamiltonian -- 2.6 Iterations Involving Propagators -- 2.7 Errors at the Energy Measurement -- 3 The Quantum Mechanics Machinery -- 4 Applications -- 4.1 Numerical Applications -- 5 Conclusion -- References -- A Semi-supervised Vulnerability Management System -- 1 Introduction -- 2 Related Work -- 3 Contributions of This Work -- 4 Problem Formulation -- 5 Algorithm -- 6 Experiments and Results -- 6.1 Database -- 6.2 Experiments -- 6.3 Preprocessing -- 6.4 Results -- 7 Analysis of Results -- 7.1 Improvement in Results -- 7.2 Word2Vec Embedding Space -- 8 Implementation Details -- 9 Model Deployment -- 9.1 Architecture -- 10 Conclusion -- References -- Evaluation of Deep Learning Techniques in Human Activity Recognition -- 1 Introduction -- 1.1 Motivation -- 1.2 Objectives -- 2 Background -- 2.1 Deep Learning -- 2.2 Deep Learning Architectures -- 2.3 Internet of Things -- 3 Methods -- 3.1 Deep Learning Models -- 3.2 Dataset -- 4 Results and Discussion -- 5 Conclusions -- References -- Siamese Neural Network for Labeling Severity of Ulcerative Colitis Video Colonoscopy: A Thick Data Approach -- 1 Introduction -- 2 The UC Video Scoring Method -- 3 Discussion and Conclusions -- References -- Self-supervised Contrastive Learning for Predicting Game Strategies -- 1 Introduction -- 2 Related Works -- 2.1 Convolutional Neural Networks -- 2.2 Self-supervised Contrastive Learning -- 3 Proposed Framework -- 3.1 Dataset -- 3.2 Modified Momentum Contrast -- 4 Experiments -- 4.1 Training -- 4.2 Evaluation -- 5 Conclusions -- References -- Stochastic Feed-forward Attention Mechanism for Reliable Defect Classification and Interpretation -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Feature Extraction -- 3.2 Feed-Forward Attention."]
[{"$nulls":4},"3.3 Uncertainty Quantification -- 4 Experiments -- 4.1 Display Manufacturing Facility Datasets -- 4.2 Results -- 5 Conclusions -- References -- Bregman Divergencies, Triangle Inequality, and Maximum Likelihood Estimates for Normal Mixtures -- 1 Introduction -- 2 Bregman Divergencies -- 3 Normal Mixtures -- 4 Reproducing Kernel Hilbert Space, Clustering, and Normal Mixtures -- 4.1 RKHS -- 4.2 Clustering -- 4.3 Clustering and Maximum Likelihood Estimates for Normal Mixtures -- 5 Conclusion -- References -- Self-supervised Learning for Predicting Invisible Enemy Information in StarCraft II -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 4 Experiments -- 4.1 Data and Experiments Setting -- 4.2 Results -- 5 Conclusions and Future Works -- References -- Measuring Robot System Agility: Ontology, System Theoretical Formulation and Benchmarking -- 1 Introduction -- 2 Related Work -- 2.1 Ontology of Robotic Systems and Components -- 2.2 Robot Autonomy -- 2.3 "]
[{"$nulls":4},"Standard for Measuring Robot Agility -- 3 Mathematical Framework for Measuring Agility -- 3.1 Systems Theoretical Approach -- 3.2 System Model -- 3.3 Formal Robot System Agility Definition -- 3.4 Time and Cost Constraints -- 3.5 Adaptability, Reactivity and Cost-Efficiency -- 4 Agility Evaluation -- 4.1 Exact Agility -- 4.2 Estimated Agility -- 4.3 Utility of Agility -- 4.4 Cost of Agility -- 5 Benchmarking -- 5.1 Different Types of Challenges -- 5.2 Adapting to Challenges -- 5.3 Benchmarking Procedures -- 6 Example Use Case: Robotic Arm Pick Operation -- 6.1 Robotic System -- 6.2 Challenges and Performance -- 6.3 Agility Evaluation -- 7 Discussion on Further Directions -- References -- A New Adoption of Cloud Computing Model for Saudi Arabian SMEs (ACCM-SME) -- 1 Introduction -- 2 Literature Review -- 3 Adoption Theories and Frameworks -- 4 Conceptual Framework."]
[{"$nulls":4},"4.1 The Technological Context -- 4.2 The Organisational Context -- 4.3 The Environmental Context -- 4.4 The Social Context -- 5 Conclusion and Future Work -- References -- A New Approach for Optimal Selection of Features for Classification Based on Rough Sets, Evolution and Neural Networks -- 1 Introduction -- 2 Materials and Methods -- 2.1 Rough Set Theory -- 2.2 Neural Networks -- 2.3 Evolutionary Strategy -- 2.4 MNIST Data Set -- 2.5 Proposed Method -- 2.6 Experimental Setup -- 3 Results and Discussion -- 3.1 Performance Evaluation -- 3.2 State of the Art-Based Comparison -- 4 Conclusions and Future Work -- References -- An Unexpected Connection from Our Personalized Medicine Approach to Bipolar Depression Forecasting -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussion -- References -- Real-Time Parallel Processing of Vibration Signals Using FPGA Technology -- 1 Introduction -- 2 The Architecture of the Acquisition System -- 2.1 Case 1: FFT Processing at the FPGA Circuit -- 2.2 Case 2: FFT Processing at the Microprocessor Level RT -- 2.3 Case 3: Processing at the PC Level -- 3 Software Development of Processing Application -- 3.1 Case 1: FFT Processing at FPGA Level -- 3.2 Case 2: FFT Processing at the Microprocessor Level RT -- 3.3 Case 3: FFT Processing at the PC Level -- 4 Experimental Results -- 4.1 Time Performance -- 4.2 Spectra View Obtained in Various Engine Scenarios -- 5 Future Work -- 6 Conclusions -- References -- Robust Control Design Solution for a Permanent Magnet Synchronous Generator of a Wind Turbine Model -- 1 Introduction -- 1.1 Related Literature Review -- 2 Wind Turbine Model -- 3 Control Scheme Implementation -- 4 Perturb and Observe Algorithm -- 5 Simulation Results -- 6 Conclusion -- References -- Knowledge Translator for Clinical Decision Support in Treating Hearing Disorders -- 1 Introduction."]
[{"$nulls":4},"1.1 Tinnitus - A Medical \"Enigma\" -- 1.2 Tinnitus Retraining Therapy (TRT) -- 1.3 Clinical Decision Support System eTRT -- 1.4 eTRT Knowledge Base -- 2 Methods -- 2.1 Association Rules -- 2.2 Action Rules -- 2.3 Knowledge Translating Procedure -- 3 Experiments and Results -- 3.1 Graphical User Interface -- 3.2 Results -- 3.3 Discussion -- 4 Conclusions -- References -- Framework for Modelling of Learning, Acting and Interacting in Systems -- 1 Introduction -- 2 Definitions and Notations -- 3 Acting and Learning -- 3.1 Motivation -- 3.2 Stochastic Approach -- 3.3 Reductions to Games -- 4 Algorithms and Architectures -- 4.1 -greedy Algorithm -- 4.2 UCB Algorithm -- 4.3 Fictitious Play -- 4.4 From Classifier to Player -- 4.5 Neural Network -- 5 Further Work -- References -- How to Reduce Emissions in Maritime Ports? An Overview of Cargo Handling Innovations and Port Services -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Scope -- 3.2 Focus -- 3.3 Sources -- 4 Overview of Means to Facilitate Energy Transition in Ports -- 4.1 Berth -- 4.2 Transport for Cargo Operations and Allocation -- 4.3 Storage Yard -- "]
[{"$nulls":4},"4.4 Port Gates -- 4.5 Port Administrative -- 4.6 Summary -- 5 Discussion -- 5.1 The Concept of a New Port -- 5.2 Extension of Port Orientation -- 5.3 Energy Transition -- 5.4 Limitations -- 6 Conclusion -- References -- Bridging the Domain Gap for Stance Detection for the Zulu Language -- 1 Introduction -- 2 Related Work -- 2.1 Domain Generalization, Adaptation, Randomization -- 2.2 Stance Detection -- 2.3 Explicit and Implicit Transfer Learning for NLP -- 3 Architecture, Methodology and Dataset -- 3.1 Step 1: Build the Training Dataset -- 3.2 Step 2: Build the Training Pipeline -- 3.3 Dataset -- 3.4 Baselines -- 4 Evaluation and Results -- 4.1 Domain Randomization -- 4.2 Domain Adaptation -- 5 Conclusions -- References."]
[{"$nulls":4},"Arcface Based Open Set Recognition for Industrial Fault."]
[null,null,null,"Sommario/riassunto","This book is a remarkable collection of chapters covering a wide domain of topics related to artificial intelligence and its applications to the real world. The conference attracted a total of 494 submissions from many academic pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer-reviewed process. Of the total submissions, 176 submissions have been selected to be included in these proceedings. It is difficult to imagine how artificial intelligence has become an inseparable part of our life. From mobile phones, smart watches, washing machines to smart homes, smart cars, and smart industries, artificial intelligence has helped to revolutionize the whole globe. As we witness exponential growth of computational intelligence in several directions and use of intelligent systems in everyday applications, this book is an ideal resource for reporting latest innovations and future of AI. Distinguished researchers have made valuable studies to understand the various bottlenecks existing in different arenas and how they can be overcome with the use of intelligent systems. This book also provides new directions and dimensions of future research work. We hope that readers find the volume interesting and valuable."]