Artificial intelligence (AI) Books

Book SynopsisThis volume set constitutes the refereed proceedings of the 16th International Conference on Knowledge Science, Engineering and Management, KSEM 2023, which was held in Guangzhou, China, during August 16–18, 2023. The 114 full papers and 30 short papers included in this book were carefully reviewed and selected from 395 submissions. They were organized in topical sections as follows: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management systems; and emerging technologies for knowledge science, engineering and management. Table of ContentsKnowledge Management Systems.- Explainable Multi-type Item Recommendation System based on Knowledge Graph.- A 2D Entity Pair Tagging Scheme for Relation Triplet Extraction.- MVARN: Multi-view attention relation network for figure question answering.- MAGNN-GC: Multi-Head Attentive Graph Neural Networks with Global Context for Session-based Recommendation.- Chinese Relation Extraction with Bi-directional Context-based Lattice LSTM.- MA-TGNN: Multiple Aggregators Graph-Based Model for Text Classification.- Multi-Display Graph Attention Network for Text Classification.- Debiased Contrastive Loss for Collaborative Filtering.- ParaSum: Contrastive Paraphrasing for Low-resource Extractive Text Summarization.- Degree-aware embedding and Interactive feature fusion-based Graph Convolution Collaborative Filtering.- Hypergraph Enhanced Contrastive Learning for News Recommendation.- Reinforcement Learning-Based Recommendation with User Reviews on Knowledge Graphs.- A Session Recommendation Model based on Heterogeneous Graph Neural Network.- Dialogue State Tracking with a Dialogue-aware Slot-Level Schema Graph Approach.- FedDroidADP: An Adaptive Privacy-Preserving Framework for Federated-Learning-based Android Malware Classification System.- Multi-level and Multi-interest User Interest Modeling for News Recommendation.- CoMeta: Enhancing Meta Embeddings with Collaborative Information in Cold-start Problem of Recommendation.- A Graph Neural Network for Cross-Domain Recommendation Based on Transfer and Inter-Domain Contrastive Learning.- A Hypergraph Augmented and Information Supplementary Network for Session-based Recommendation.- Candidate-aware Attention Enhanced Graph Neural Network for News Recommendation.- Heavy Weighting for Potential Important Clauses.- Knowledge-Aware Two-Stream Decoding for Outline-Conditioned Chinese Story Generation.- Multi-Path based Self-Adaptive Cross-Lingual Summarization.- Temporal Repetition Counting Based on Multi-Stride Collaboration.- Multi-layer Attention Social Recommendation System based on Deep Reinforcement Learning.- SPOAHA: Spark program optimizer based on Artificial Hummingbird Algorithm.- TGKT-based Personalized Learning Path Recommendation with Reinforcement Learning.- Fusion High-Order information with Nonnegative Matrix Factorization Based Community Infomax for Community Detection.- Multi-task learning based skin segmentation.- User Feedback-based Counterfactual Data Augmentation for Sequential Recommendation.- Citation Recommendation Based on Knowledge Graph and Multi-task Learning.- A Pairing Enhancement Approach for Aspect Sentiment Triplet Extraction.- The Minimal Negated Model Semantics of Assumable Logic Programs.- MT-BICN: Multi-task Balanced Information Cascade Network for Recommendation.

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Book SynopsisThis volume set constitutes the refereed proceedings of the 16th International Conference on Knowledge Science, Engineering and Management, KSEM 2023, which was held in Guangzhou, China, during August 16–18, 2023. The 114 full papers and 30 short papers included in this book were carefully reviewed and selected from 395 submissions. They were organized in topical sections as follows: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management systems; and emerging technologies for knowledge science, engineering and management. Table of ContentsEmerging technologies for Knowledge science, engineering and management.- Federated Prompting and Chain-of-Thought Reasoning for Improving LLMs Answering.- Advancing Domain Adaptation of BERT by Learning Domain Term Semantics.- Deep Reinforcement Learning for Group-Aware Robot Navigation in Crowds.- An Enhanced Distributed Algorithm for Area Skyline Computation based on Apache Spark.- TCMCoRep: Traditional Chinese Medicine data mining with Contrastive Graph Representation Learning.- Local-Global Fusion Augmented Graph Contrastive Learning Based on Generative Models.- PRACM: Predictive Rewards for Actor-Critic with Mixing Function in Multi-Agent Reinforcement Learning.- A Cybersecurity Knowledge Graph Completion Method for Scalable Scenarios.- Research on remote sensing image classification based on Transfer learning and Data Augmentation.- Multivariate Long-Term Traffic Forecasting with Graph Convolutional Network and Historical Attention Mechanism.- Multi-hop Reading Comprehension Learning Method Based on Answer Contrastive Learning.- Importance-based Neuron Selective Distillation for Interference Mitigation in Multilingual Neural Machine Translation.- Are GPT Embeddings Useful for Ads and Recommendation?.- Modal interaction-enhanced Prompt Learning by transformer decoder for Vision-Language Models.- Unveiling Cybersecurity Threats from Online Chat Groups: A Triple Extraction Approach.- KSRL: Knowledge Selection based Reinforcement Learning for Knowledge-Grounded Dialogue.- Prototype-Augmented Contrastive Learning for Few-shot Unsupervised Domain Adaptation.- Style Augmentation and Domain-aware Parametric Contrastive Learning for Domain Generalization.- Recent Progress on Text Summarisation Based on BERT and GPT.- Ensemble Strategy Based on Deep Reinforcement Learning for Portfolio Optimization.- A Legal Multi-Choice Question Answering Model Based on BERT and Attention.- Offline Reinforcement Learning with Diffusion-Based Behavior Cloning Term.- Evolutionary Verbalizer Search for Prompt-based Few Shot Text Classification.- Graph Contrastive Learning Method with Sample Disparity Constraint and Feature Structure Graph for Node Classification.- Learning Category Discriminability for Active Domain Adaptation.- Multi-Level Contrastive Learning for Commonsense Question Answering.- Efficient Hash Coding for Image Retrieval based on Improved Center Generation and Contrastive Pre-training Knowledge Model.- Univarite Time Series Forecasting via Interactive Learning.- Task Inference for Offline Meta Reinforcement Learning via Latent Shared Knowledge.- A Quantitative Spectra Analysis Framework Combining Mixup and Band Attention for Predicting Soluble Solid Content of Blueberries.- Contextualized Hybrid Prompt-Tuning for Generation-Based Event Extraction.- udPINNs: An Enhanced PDE Solving Algorithm Incorporating Domain of Dependence Knowledge.- Joint Community and Structural Hole Spanner Detection via Graph Contrastive Learning.- A Reinforcement Learning-based Approach for Continuous Knowledge Graph Construction.- A Multifactorial Evolutionary Algorithm based on Model Knowledge Transfer.- Knowledge Leadership, AI Technology Adoption and Big Data Application Ability.- RFLSem: A lightweight model for textual sentiment analysis.

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Book SynopsisThis book constitutes the refereed proceedings of the 26th International Conference on Text, Speech, and Dialogue, TSD 2023, held in Pilsen, Czech Republic, during September 4–6, 2023. The 31 full papers presented together with the abstracts of 3 keynote talks were carefully reviewed and selected from 64 submissions. The conference attracts researchers not only from Central and Eastern Europe but also from other parts of the world. One of its goals has always been bringing together NLP researchers with various interests from different parts of the world and promoting their cooperation. One of the ambitions of the conference is, not only to deal with dialogue systems but also to improve dialogue among researchers in areas of NLP, i.e., among the “text” and the “speech” and the “dialogue” people.Table of Contents​Text: Japanese How-to Tip Machine Reading Comprehension by Multi-task Learning based on Generative Model.- One model to rule them all: ranking Slovene summarizers.- Searching for Reasons of Transformers’ Success: Memorization vs Generalization.- A Dataset and Strong Baselines for Classification of Czech News Texts.- Resolving Hungarian Anaphora with ChatGPT.- Advancing Hungarian Text Processing with HuSpaCy: Efficient and Accurate NLP Pipelines.- ParaDiom - A Parallel Corpus of Idiomatic Texts.- Measuring Sentiment Bias in Machine Translation.- Mono- and multilingual GPT-3 models for Hungarian.- The Unbearable Lightness of Morph Classification.- A German Parallel Clausal Coordinate Ellipsis Corpus that Aligns Sentences from the TüBa-D/Z Treebank with Reconstructed Canonical Forms.- Speech: Identifying Subjects Wearing a Mask from the Speech by Means of Encoded Speech Representations.- Impact of Including Pathological Speech in Pre-Training on Pathology Detection.- Morphological Tagging and Lemmatization of Spoken Corpora of Czech.- HATS: An Open data set Integrating Human Perception Applied to the Evaluation of Automatic Speech Recognition Metrics.- Online Speaker Diarization Using Optimized SE-ResNet Architecture.- CML-TTS: A Multilingual Dataset for Speech Synthesis in Low-Resource Languages (Speech (in general), Corpora and Language Resources, Spe.- Developing State-of-the-Art End-to-End ASR for Norwegian.- VITS: Quality vs. Speed Analysis.- When Whisper Meets TTS: Domain Adaptation Using Only Synthetic Speech Data.- Unsupervised Learning for Automatic Speech Recognition In Air Traffic Control Environment.- The Effect of Human-Likeliness in French Robot-Directed Speech: A Study of Speech Rate and Fluency.- An online diarization approach for streaming applications based on tree-clustering and Bayesian resegmentation.- Evaluation of Speech Representations for MOS prediction.- Unified Modeling of Multi-Domain Multi-Device ASR Systems.- Voice Cloning for Voice Disorders: Impact of Phonetic Content.- Towards End-to-end Speech-to-text Summarization.- Multilingual TTS Accent Impressions for Accented ASR.- Transfer Learning of Transformer-based Speech Recognition Models from Czech to Slovak.- Automatic Pronunciation Assessment of Non-native English based on Phonological Analysis.- Language Generalization using Active Learning in the context of Parkinson’s Disease Classification.

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Book SynopsisThis book constitutes the refereed proceedings of the 5th International Conference on Logic and Argumentation, CLAR 2023, held in Hangzhou, China, during September 10-12, 2023. The 11 full papers, one short paper and one invited paper presented in this book were carefully reviewed and selected from 20 submissions. The papers focus on topics such as: ​logic and automated deduction; abstract and structured argumentation; dialogues, games and practical reasoning; and quantitative argumentation.Table of Contents​Logic and Automated Deduction.- Dynamic Modal Logic with Counting: when Reduction Axioms Work and Fail.- Solving Modal Logic Problems by Translation to Higher-order Logic.- Formalizing the Unexpected Hanging Paradox: a Classical Surprise.- Abstract and Structured Argumentation.- Weakest Link in Formal Argumentation: Lookahead and Principle-based Analysis.- A Logical Encoding for k-m-Realization of Extensions in Abstract Argumentation.- Topological Conditions and Solutions for Repairing Argumentation Frameworks.- Dialogues, Games and Practical Reasoning.- Providing personalized Explanations: a Conversational Approach.- Audience irrelevance in Strategic Argumentation Games.- A Structured Bipolar Argumentation Theory for Providing Explanations in Practical Reasoning.- Quantitative Argumentation.- A Filtering-based General Approach to Learning Rational Constraints of Epistemic Graphs.- Fuzzy Labeling Semantics for Quantitative Argumentation.- A Logic for Preference Lifting under Uncertainty and its Decidability.

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Book SynopsisThis book constitutes the refereed deadline proceedings of the 28th International Conference on Graph-Based Representation and Reasoning, ICCS 2023, held in Berlin, Germany, during September 11–13, 2023.The 9 full papers, 5 short papers and 4 Posters are included in this book were carefully reviewed and selected from 32 submissions. They were organized in topical sections as follows: Complexity and Database Theory, Formal Concept Analysis: Theoretical Advances, Formal Concept Analysis: Applications, Modelling and Explanation, Semantic Web and Graphs, Posters.Table of ContentsComplexity and Database Theory.- Functional Dependencies with Predicates: What Makes the g3-error Easy to Compute?.- Formal Concept Analysis: Theoretical Advances.- Squared symmetric formal contexts and their connections with correlation matrices.- Aggregation Functions and Extent Structure Preservation in Formal Concept Analysis.- On pseudointents in Fuzzy Formal Concept Analysis.- Maximal Ordinal Two-Factorizations.- A Note on the Number of (Maximal) Antichains in the Lattice of set Partitions.- Formal Concept Analysis: Applications.- Formal Concept Analysis for Trace Clustering in Process Mining.- Summarization of massive RDF graphs using identifier classification.- Towards a Flexible and Scalable Data Stream Algorithm in FCA.- Modelling and Explanation.- Postmodern Human-Machine Dialogues: a Pedagogical Inquiry Experiment.- Conceptual Modelling with Euler+ Diagrams.- Automatic Textual Explanations of Concept Lattices.- Semantic Web and Graphs.- Ontology Population from French Classified Ads.- Graph Extraction for Assisting Crash Simulation Data Analysis.- Posters.- Factorization of formal contexts from modal operators.- Towards confirmation measures to mixed attribute implications.- Concept lattices as a reduction tool for fuzzy relation equations.- Analysis of Slovak Court Decisions by Formal Concept Analysis and Machine Learning Methods.

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Book SynopsisThis book constitutes the refereed proceedings of the 15th International Conference on Computational Collective Intelligence, ICCCI 2023, held in Budapest, Hungary, during September 27–29, 2023.The 63 full papers included in this book were carefully reviewed and selected from 218 submissions. They are organized in topical sections as follows: collective intelligence and collective decision-making; deep learning techniques; natural language processing; data mining and machine learning; social networks and intelligent systems; cybersecurity, blockchain technology and Internet of Things; cooperative strategies for decision making and optimization; computational intelligence for digital content understanding; knowledge engineering and application for Industry 4.0; computational intelligence in medical applications; and ensemble models and data fusion.Table of ContentsCollective Intelligence and Collective Decision-Making.- Hybrid Genetic Algorithms to Determine 2-Optimality Consensus for a Collective of Ordered Partitions.- From Fragmented Data to Collective Intelligence: A Data Fabric Approach for University Knowledge Management.- An Architecture for Enabling Collective Intelligence in IoT Networks.- Self-Organizing Maps for Data Purchase Support in Data Marketplaces.- Agent based model of elementary school group learning – a case study.- Deep Learning Techniques.- Deep Reinforcement Learning for Jointly Resource Allocation and Trajectory Planning in UAV-assisted Networks.- DNGAE: Deep Neighborhood Graph Autoencoder for robust blindhyperspectral unmixing.- Unlocking the Potential of Deep Learning and Filter Gabor for Facial Emotion Recognition.- Graph Convolution Collaborative Filtering with Dense Embeddings.- Automatic Quantization for Convolutional Neural Networks Based on Enhanced Bare-Bones Particle Swarm Optimization for Chest X-ray Image Classification.- A Convolutional Autoencoder Approach for Weakly Supervised Anomaly Video Detection.- Sparsity-invariant Convolution for Forecasting Irregularly Sampled Time Series.- Efficient Sparse Networks from Watts-Strogatz Network Priors.- Natural Language Processing.- Exploring the Role of Monolingual Data in Cross-Attention Pre-Training for Neural Machine Translation.- Development of a dictionary for preschool children with weak speech skills based on the Word2Vec method.- An abstractive automatic summarization approach based on a text comprehension model of cognitive psychology.- Detecting Duplicate Multiple Choice Questions in The Large Question Bank.- A Context-Aware Approach for Improving Dialog Act Detection in a Multilingual Conversational Platform.- Data Minning and Machine learning.- Efficient Association Rules Minimization Using a Double-Stage Quine-McCluskey-Based Approach.- Complexity-Based Code Embeddings.- Differentially Private Copulas, DAG and Hybrid Methods: a Comprehensive Data Utility Study.- Analysing Android Apps Classification and Categories Validation by using Latent Dirichlet Allocation.- Staircase Recognition based on Possibilistic Feature Quality Assessment Method.- Social Networks and Intelligent Systems.- Toward effective link prediction based on local information in organizational social networks.- A new topic modeling method for tweets comparison.- Measuring gender: A machine learning approach to social media demographics and author profiling.- Crisis Detection by Social and Remote Sensing Fusion: A selective Attention Approach.- Educational Videos Recommendation System Based On Topic Modeling.- Cybersecurity, Blockchain Technology and Internet of Things.- A Two-hop Neighborhood Based Berserk Detection Algorithm for Probabilistic Model of Consensus in Distributed Ledger Systems.- Trust Assessment on Data Stream Imputation in IoT Environments.- Optimizing Merkle Tree Structure for Blockchain transactions by a DCProgramming approach.- Wearable Tag for Indoor Localization in the context of Ambient Assisted Living.- Hyperledger blockchain-enabled cold chain application for flower logistics.- A Fully Decentralized Privacy-Enabled Federated Learning System.- Cooperative Strategies for Decision Making and Optimization.- Two-dimensional Pheromone in Ant Colony Optimization.- Analysis of different reinsertion strategies in Steady State GeneticAlgorithm.- Traffic Optimization by Local Bacterial Memetic Algorithm.- Optimizing Fire Control Monitoring System in Smart Cities.- Computational Intelligence for Digital Content Understanding.- Desertification Detection in Satellite Images using Siamese Variational Autoencoder with Transfer Learning.- Speaker Identification Enhancement Using Emotional Features.- Classification of punches in Olympic boxing using static RGB cameras.- Learning Human Postures using Lab-Depth HOG Descriptors.- SemiMemes: A Semi-supervised Learning Approach for Multimodal Memes Analysis.- Extrinsic Calibration Framework for Camera-Lidar Fusion using Recurrent Residual Network.- GAN-based Data Augmentation and Pseudo-Label Refinement for Unsupervised Domain Adaptation Person Re-Identification.- Intelligent Automated Pancreas Segmentation using U-Net Model Variants.- Knowledge Engineering and Apllication for Industry 4.0.- Energy and Congestion Awareness Traffic Scheduling in HybridSoftware-Defined Network with Flow Splitting.- "Is Proton good enough?" - a performance comparison between gaming on Windows and Linux.- Complete Coverage and Path Planning for Emergency Response by UAVs in Disaster Areas.- Complete Coverage and Path Planning for Emergency Response by UAVs in Disaster Areas.- Complex layers of ranked prognostic models.- Project Team Members competences configuration: a proactive andreactive approach.- Computational Intelligence in Medical Applications.- Teeth disease recognition based on X-ray images.- Predicting Alzheimer’s Disease Diagnosis Risk over Time with Survival Machine Learning on the ADNI Cohort.- MEP: A Comprehensive Medicines Extraction System on Prescriptions.- New Approaches to Monitoring Respiratory Activity as Part of an Intelligent Model for Stress Assessment.- An Adaptive Network Model for Anorexia Nervosa: Addressing the Effects of Therapy.- ReVQ-VAE: A Vector Quantization-Variational Autoencoder for COVID-19 chest X-Ray image.- Ensemble Models and Data Fusion.- Credit Risk Scoring Using a Data Fusion Approach.- Goal-oriented Classification of Football Results.- Learning from Imbalanced Data Streams Using Rotation-based Ensemble Classifiers.- DE-Forest – optimized decision tree ensemble.- Mining multiple class imbalanced datasets using a specialized balancing algorithm and the Adaboost technique.- Investigation and prediction of Cognitive Load During Memory and Arithmetic Tasks.

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Book SynopsisThe two-volume set LNAI 14125 and 14126 constitutes the refereed conference proceedings of the 22nd International Conference on Artificial Intelligence and Soft Computing, ICAISC 2023, held in Zakopane, Poland, during June 18–22, 2023. The 84 revised full papers presented in these proceedings were carefully reviewed and selected from 175 submissions. The papers are organized in the following topical sections: Part I: Neural Networks and Their Applications; Evolutionary Algorithms and Their Applications; and Artificial Intelligence in Modeling and Simulation. Part II: Computer Vision, Image and Speech Analysis; Various Problems of Artificial Intelligence; Bioinformatics, Biometrics and Medical Applications; and Data Mining and Pateern Classification. Table of Contents​Neural Networks and Their Applications.- A novel approach to the GQR algorithm for neural networks training.- On Speeding Up the Levenberg-Marquardt Learning Algorithm.- Reinforcement Learning with Brain-Inspired Modulation Improves Adaptation to Environmental Changes.- Multi-Agent Deep Q-Network in Voxel-based Automated Electrical Routing.- Evaluation of the importance of optimizer selection in streaming neural network learning.- Training Neural Tensor Networks With Corrupted Relations.- Application of Monte Carlo Algorithms with Neural Network-Based Intermediate Area to the Thousand Card Game.- Learning representations by crystallized back-propagating errors.- Fuzzy Hyperplane based K-SVCR Multi-class Classification with Its Applications to Stock Prediction Problem.- Dynamic Hand Gesture Recognition for Human-Robot Collaborative Assembly.- Transfer of knowledge among instruments in automatic music transcription.- The Geometry of Decision Borders Between Affine Space Prototypes for Nearest Prototype Classifiers.- An Interpretable Two-Layered Neural Network Structure – Based on Component-wise Reasoning.- Viscosity Estimation of Water-PVP Solutions from Droplets using Artificial Neural Networks and Image Processing.- Pruning convolutional filters via reinforcement learning with entropy minimization.- Unsupervised Representation Learning: Target Regularization for Cross-domain Sentiment Classification.- Decentralized federated learning loop with constrained trust mechanism.- Learning Activation Functions for Adversarial Attack Resilience in CNNs.- Federated Learning for Human Activity Recognition on the MHealth Dataset.- Image Classification through Graph Neural Networks and Random Walks.- Bus Route Classification for Rural Areas using Graph Convolutional Networks.- Expansion rate parametrization and K-Fold inference with U-Net neural networks for multiclass medical image segmentation.- Transfer learning from ImageNet to the domain of pigmented nevi.- Towards Detecting Freezing of Gait Events using Wearable Sensors and Genetic Programming.- CNN-LSTM Optimized by Genetic Algorithm in Time Series Forecasting: An Automatic Method to use Deep Learning.- Authorship Attribution of Literary Texts using Named Entity Masking and MaxLogit-based Sequence Classification for Varying Text Lengths.- Gates Are Not What You Need in RNNs.- Generating Image Captions in Polish using Transformer Architecture.- Evolutionary Algorithms and Their Applications.- An hybrid NSGA-II algorithm for the Bi-objective Mobile Mammography Unit Routing Problem.- Controlled Refresh of the Population in Differential Evolution for Real-World Problems.- A new Hybrid Particle Swarm Optimization and Evolutionary Algorithm with Self-Adaptation Mechanism.- Data Mining Car Configurator Clickstream Data to Identify Potential Consumers: A Genetic Algorithm Approach.- Multi-population algorithm using surrogate models and different training plans.- Multi-population-based algorithms with different migration topologies and their improvement by population re-initialization.- Machine Learning Assisted Interactive Multi-Objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects ..- Improved Barnacles Movement Optimizer (IBMO) Algorithm for Engineering Design Problems.- Evolutionary-based generative design for electric transmission towers.- Enhanced Grey Wolf Optimizer.- Artificial Intelligence in Modeling and Simulation.- Security Intelligence for real-time security monitoring software.- Examine Effects of Class Imbalance on Conditional GAN Training.- Stochastic Model for Wildfire Simulation based on the characteristics of the Brazilian Cerrado.- Test Case Generator for Problems of Complete Coverage and Path Planning for Emergency Response by UAVs.- Application of artificial neural networks in electric arc furnace modeling.- Profiling users of the online store in terms of price sensitivity ..- Learning Bezier-Durrmeyer type descriptors for classifying curves – preliminary studies.- Prediction accuracy of direction changes with ELM, MLP and LSTM on the example of exchange rates.- Child tracking and Prediction of Violence on Children in social media using Natural Language Processing and Machine Learning.- Adequate basis for the data-driven and machine-learning-based identification.

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Book SynopsisThis book constitutes the refereed post-conference proceedings of the 15th International Conference, Évolution Artificielle, EA 2022, held in Exeter, UK, during October 31–November 2, 2022.The 15 full papers were carefully reviewed and selected from 18 submissions. The papers cover a wide range of topics in the field of artificial evolution, including, but not limited to: evolutionary computation, evolutionary optimization, coevolution, artificial life, population dynamics, theory, algorithmic and modeling, implementations.Table of ContentsOn the Active Use of an ND-Tree-Based Archive for Multi-Objective Optimisation.- HyTEA: Hybrid Tree Evolutionary Algorithm.- A Game Theoretic Decision Tree for Binary Classification.- Evaluating a New Genetic Algorithm for Automated Machine Learning in Positive-Unlabelled Learning.- Neural Network-based Virtual Analog Modeling.- Defining a Quality Measure Within Crossover: An Electric Bus Scheduling Case Study.- Maximizing the Number of Satisfied Charging Demands in Electric Vehicle Charging Scheduling Problem.- Fine-Grained Cooperative Coevolution in a Single Population: Between Evolution and Swarm Intelligence.- One-Class Ant-Miner: Selection of Majority Class Rules for Binary Rule-based Classification.- Towards a Many-Objective Optimiser for University Course Timetabling.- Empirical Investigation of MOEAs for Multi-objective Design of Experiments.- Evolutionary Continuous Optimization of Hybrid Gene Regulatory Networks.- Designing Attention based Convolutional Neural Network (CNN) Architectures for Medical Image Classification using Genetic Algorithm based on Variable Length-encoding Scheme.- A Multi-objective 3D Offline UAV Path Planning Problem with Variable Flying Altitude.- An Elitist Non-dominated Heuristic Resolution for the Dynamic Asset Protection Problem.

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Book SynopsisThis book constitutes the proceedings of the 16th Brazilian Symposium on Bioinformatics on Advances in Bioinformatics and Computational Biology, BSB 2023, which took place in Curitiba, Brazil, in June 2023. The 11 full papers and 3 short papers presented in this volume were carefully reviewed and selected from 24 submissions. The papers focus on bioinformatics, computational biology, Biological Databases, Biological Networks, Cheminformatics, Evolutionary Genomics, Computational Proteomics, Systems Biology, Drug Design, Genomics, Machine Learning applications in Bioinformatics, Metagenomics, Molecular Docking and Modeling, Molecular Evolution and Phylogenetics, Protein Structure and Modeling, Proteomics, Transcriptomics, Single-Cell Analysis, Workflows in Bioinformatics. Table of ContentsBlock Interchange and Reversal Distance on Unbalanced Genomes.- circTIS: a weighted degree string kernel with support vector machine tool for translation initiation sites prediction in circRNA.- Evaluating the molecular-electronic structure and the antiviral effect of functionalized heparin on graphene oxide through ab initio computer simulations and molecular docking.- Make No Mistake! Why Do Tools Make Incorrect Long Non-Coding Rna Classification?.- Spectrum-Based Statistical Methods for Directed Graphs with Applications in Biological Data.- Feature Selection Investigation in Machine Learning Docking Scoring Functions.- Using natural language processing for context identification in COVID-19 literature.- A framework for inference and selection of cell signaling pathway dynamic models.- Intentional Semantics for Molecular Biology.- transcAnalysis: A Snakemake Pipeline for Differential Expression and Post-Transcriptional Modification Analysis.- Peptide-protein interface classification using convolutional neural networks.- A Power Law Semantic Similarity from Gene Ontology.- Gene Networks Inference by Reinforcement Learning Approach.- Exploring Identifiability in Hybrid Models of Cell Signaling Pathways.

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Book SynopsisThis book is a revised version of the PhD dissertation written by the author at the Free University of Bozen-Bolzano in Italy. It presents a new approach to safety verification of a particular class of infinite-state systems, called Data-Aware Processes (DAPs). To do so, the developed technical machinery requires to devise novel results for uniform interpolation and its combination in the context of automated reasoning. These results are then applied to the analysis of concrete business processes enriched with real data. In 2022, the PhD dissertation won the “BPM Dissertation Award”, granted to outstanding PhD theses in the field of Business Process Management. Table of ContentsIntroduction.- 1.1 Overview.- 1.1.1 Finite-State Model Checking.- 1.1.2 Verification of Data-Aware Processes.- 1.1.3 Infinite-state Model Checking: from Parameterized Systems to SMT Verification.- 1.1.4 Main Goal of the Book.- 1.2 Related Literature.- 1.2.1 Formal Models for Data-Aware (Business) Processes.- 1.2.2 Verification of Data-Aware Processes.- 1.2.3 Model Checking for Infinite-State Systems using SMT-based Techniques.- 1.3 Contributions of the Book.- 1.3.1 Contributions of the First Part.- 1.3.2 Contributions of the Second Part.- 1.3.3 Contributions of the Third Part.- Part I Foundations of SMT-based Safety Verification of Artifact Systems.- 2 Preliminaries from Model Theory and Logic.- 3 Array-Based Artifact Systems: General Framework.- 4 Safety Verification of Artifact Systems.- 5 Decidability Results via Termination of the Verification Machinery.- 6. Preliminaries For (Uniform) Interpolation.- 7 Uniform Interpolation for Database Theories.- 8 Combination of Uniform Interpolants for DAPs Verification.- 9 MCMT: a Concrete Model Checker for DAPs.- 10 Business Process Management and Petri Nets: Preliminaries.- 11 DABs: a Theoretical Framework for Data-Aware BPMN.- 12 delta-BPMN: the operational and implemented counterpart of DABs.- 13 Catalog Object-Aware Nets.- 14 Conclusions.- References.

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Book SynopsisThis book constitutes the proceedings of the 27th European Conference on Advances in Databases and Information Systems, ADBIS 2023, held in Barcelona, Spain, during September 4–7, 2023. The 11 full papers presented in this book together with 3 keynotes and tutorials were carefully reviewed and selected from 77 submissions. The papers are organized in the following topical sections: keynote talk and tutorials; query processing and data exploration, data science and fairness and Data and Metadata QualityTable of ContentsKeynote Talk and Tutorials.- Knowledge Engineering in the Era of Artificial Intelligence.- Causality, Attribution-Scores and Repairs in Databases.- When operations research meets databases.- Query Processing and Data Exploration.- Using a Key-Value Index-Store for Cross-Model Join Queries Over Heterogeneous Data Sources.- Reconstructing Spatiotemporal Data with C-VAEs.- What Happens when Two Multi-Query Optimization Paradigms Combine.- Skyline-Based Temporal Graph Exploration.- Temporal Graph Processing in Modern Memory Hierarchies.- Data Science and Fairness.- Comparing and Improving Active Learning Uncertainty Measures for Transformer Models.- FARMUR: Fair Adversarial Retraining to Mitigate Unfairness in Robustness.- Exploring Heterogeneous Data Graphs Through their Entity Paths.- Managing Linked Nulls in Property Graphs: Tools to Ensure Consistency and Reduce Redundancy.- Assessment of Data Quality in a Data Lakehouse Through Multi-Granularity Data Profiling.- Data Ingestion Validation through Stable Conditional Metrics with Ranking and Filtering.- An Ontology for Representing and Querying Semantic Trajectories in the Maritime Domain.- Extracting Provenance of Machine Learning Experiment Pipeline Artifacts.

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Book SynopsisThis book constitutes the refereed proceedings of the 24th Annual Conference Towards Autonomous Robotic Systems, TAROS 2023, held in Cambridge, UK, during September 13–15, 2023.The 40 full papers presented in this book were carefully reviewed and selected from 70 submissions.They cover a wide range of different topics such as: agri-food robotics; autonomy; collaborative and service robotics; locomotion and manipulation; machine vision; multi-robot systems; soft robotics; tactile sensing; and teleoperation.Table of Contents​Agri-food Robotics.- Plant phenotyping using DLT method: Towards retrieving the delicate features in a dynamic environment.- Rapid Development and Performance Evaluation of a Potato Planting Robot.- An Automated Precision Spraying Evaluation System.- Smart Parking System Using Heuristic Optimization For Autonomous Transportation Robots In Agriculture.- Closed-Loop Robotic Cooking of Soups with Multi-modal Taste Feedback.- Folding Morphing-wheg Duct-entry Robot for Nuclear Characterisation.- Autonomy.- Occupancy Map Abstraction for Higher Level Mission Planning of Autonomous Robotic Exploration in Hazardous Nuclear Environments.- Spiral Sweeping Protocols for Detection of Smart Evaders.- Action Recognition for Improving Pedestrian Intent Prediction.- Evaluation of SLAM algorithms for Search and Rescue applications.- Developing an Integrated Runtime Verification for Safety and Security of Industrial Robot Inspection System.- Collaborative and Service Robotics.- Sonification of Ionising Radiation Data for Robot Operators.- Automating a Telepresence Robot for Human Detection, Tracking, and Following.- Towards Multimodal Sensing and Interaction for Assistive Autonomous Robots.- Locomotion and Manipulation.- CPG-based locomotion control of a quadruped robot with an active spine.- Low-resolution sensing for sim-to-real complex terrain robots.- Towards wait-and-catch routine of a dynamic swinging object using a prototype robotic arm manipulator.- Simultaneous Base and Arm Trajectories for Multi-Target Mobile Agri-Robot.- Design and kinematic analysis of a 3D-printed 3DOF robotic manipulandum.- Sim-to-Real Deep Reinforcement Learning with Manipulators for Pick-and-place.- Machine Vision.- Fast 3D Semantic Segmentation Using a Self Attention Network and Random Sampling.- An assessment of self-supervised learning for data efficient potato instance segmentation.- Automated 3D Mapping, localization and pavement inspection with low cost RGB-D cameras and IMUs.- Optimized Custom Dataset for Efficient Detection of Underwater Trash.- A Geometric Algebra Solution to the 3D Registration Problem.- Active Anomaly Detection for Autonomous Robots: a Benchmark.- Multi-robot Systems.- Hardware Validation of Adaptive Fault Diagnosis in Swarm Robots.- Mobile Robots For Collaborative Manipulation Over Uneven Ground Using Decentralised Impedance Control.- Multi-agent Collaborative Target Search Based on Curiosity Intrinsic Motivation.- Simulation of Collective Bernoulli-Ball System for Characterizing Dynamic Self-stability.- Soft Robotics.- Casting vs injection moulding: a comparison study for in-lab low-cost soft robot fabrication.- Estimation of Soft Body Deformation by Using Light.- Reduced-Order Modeling of a Soft Anthropomorphic Finger for Piano Keystrokes.- Tactile Sensing.- Multi-directional Force and Tactile Sensor Sleeves for Micro Catheters and Cannulas.- Towards smooth human-robot handover with a vision-based tactile sensor.- Feeling Good: Validation of Bilateral Tactile Telemanipulation for a Dexterous Robot.- Teleoperation.- Comparative study of hand-tracking and traditional control interfaces for remote palpation.- 5G-based Low-Latency Teleoperation: Two-way Timeout Approach.- Generative Model-based Simulation of Driver Behavior when Using Control Input Interface for Teleoperated Driving in Unstructured Canyon Terrains.- Implementation of a Stereo Vision System for a Mixed Reality Robot Teleoperation Simulator.

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Book SynopsisThis book constitutes the refereed proceedings of the 14th International Symposium on Frontiers of Combining Systems, FroCoS 2023, held in Prague, Czech Republic, in September 2023. The symposium was co-located with the 32nd International Conference on Automated Reasoning with Analytic Tableaux and Related Methods, TABLEAUX 2023.The 14 papers presented were thorouhgly reviewed and selected from the 22 high-quality paper submissions. They are grouped in the volume according to the following topic classification: analysis of programs and equations; unification; decidable fragments; frameworks; higher-order theorem proving.This is an open access book.Table of Contents​Analysis of Programs and Equations.- Unification.- Decidable Fragments.- Frameworks.- Higher-order Theorem Proving.

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Book SynopsisThe multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023.The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows:Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering.Part II: ​Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning.Part III: ​Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning.Part IV: ​Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning.Part V: ​Robustness; Time Series; Transfer and Multitask Learning.Part VI: ​Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval.​Part VII: Sustainability, Climate, and Environment.- Transportation & Urban Planning.- Demo.Table of ContentsRobustness.- Time Series.- Transfer and Multitask Learning.

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Book SynopsisThis open access book constitutes the proceedings of the proceedings of the 32nd International Conference on Automated Reasoning with Analytic Tableaux and Related Methods, TABLEAUX 2023, held in Prague, Czech Republic, during September 18-21, 2023. The 20 full papers and 5 short papers included in this book together with 5 abstracts of invited talks were carefully reviewed and selected from 43 submissions. They present research on all aspects of the mechanization of reasoning with tableaux and related methods. The papers are organized in the following topical sections: tableau calculi; sequent calculi; theorem proving; non-wellfounded proofs; modal logics; linear logic and MV-algebras; separation logic; and first-order logics.Table of ContentsRange-Restricted and Horn Interpolation through Clausal Tableaux.- Non-Classical Logics in Satisfiability Modulo Theories.- DefTab: A Tableaux System for Sceptical Consequence in Default Modal Logics.- Non-distributive description logic.- A new calculus for intuitionistic Strong L\"ob logic: strong termination and cut-elimination, formalized.- Some Analytic Systems of Rules.- A cut-free, sound and complete Russellian theory of definite descriptions.- Towards Proof-Theoretic Formulation of the General Theory of Term-Forming Operators.- Lemmas: Generation, Selection, Application.- Machine-Learned Premise Selection for Lean.- gym-saturation: Gymnasium environments for saturation provers (System description).- A linear perspective on cut-elimination for non-wellfounded sequent calculi with least and greatest fixed points.- Ill-founded Proof Systems For Intuitionistic Linear-time Temporal Logic.- Proof Systems for the Modal $\mu$-Calculus Obtained by Determinizing Automata.- Extensions of K5: Proof Theory and Uniform Lyndon Interpolation.- On intuitionistic diamonds (and lack thereof).- NP Complexity for Combinations of Non-Normal Modal Logics.- Resolution-based Calculi for Non-Normal Modal Logics.- Canonicity of Proofs in Constructive Modal Logic.- Proof-theoretic Semantics for Intuitionistic Multiplicative Linear Logic.- The MaxSAT problem in the real-valued MV-algebra.- The Logic of Separation Logic: Models and Proofs.- Testing the Satisfiability of Formulas in Separation Logic with Permissions.- Nested Sequents for Quantified Modal Logics.- A Naive Prover for First-Order Logic: A Minimal Example of Analytic Completeness.

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Book SynopsisThis book contains the works connected with the key advances in Industrial Artificial Intelligence presented at IITI 2023, the Seventh International Scientific Conference on Intelligent Information Technologies for Industry held on September 25-30, 2023 in St. Petersburg, Russia. The works were written by the experts in the field of applied artificial intelligence including topics such as Machine Learning, Explainable AI, Decision-Making, Fuzzy Logic, Multi-Agent and Bioinspired Systems. The following industrial application domains were touched: railway automation, cyber security, intelligent medical systems, navigation and energetic systems. The editors believe that this book will be helpful for all scientists and engineers interested in the modern state of applied artificial intelligence.Table of ContentsExplainable Document Classification via Pattern Structures.- Bayesian belief network for association between clusters of social media users with similar personality traits profiles and color characteristics of their avatar images.- Algebraic Bayesian Networks: the Generation of the Network Canonical Representation.- Quantification of Localization Uncertainty in One-stage Object Detection.- Automated Discovery of Direct Speech to Increase Quality and Battery Saving in Telephony.

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Book SynopsisThis book constitutes the refereed proceedings of the 8th International Conference on Information, Communication and Computing Technology, ICICCT 2023, held in New Delhi, India, during May 27, 2023.The 14 full papers included in this book were carefully reviewed and selected from 60 submissions. They were organized in topical sections as follows: global platform for researchers, scientists and practitioners from both academia and industry to present their research and development activities in all the aspects of Pattern Recognition and computational Intelligence techniques.Table of ContentsUsing BERT for Swiss German Sentence Prediction.- An ARIMA and XGBoost Model utilized for forecasting Municipal Solid Waste generation.- An Empirical Study of Intrusion Detection By Combining Clustering and Classification Methods.- Personalized Movie Recommendation Prediction Using Reinforcement Learning.- An Ensemble And Deep Neural Network Based Approaches For Automated Sentiment Analysis.- In-Store Product Placement using LiDAR-Assisted Discrete PSO Algorithm.- Deep Residual Variational Autoencoder for Image Super-Resolution.- Hybrid HAN Model to Investigate Depression from Twitter Posts.- Transfer Learning-Based Encoder-Decoder Model For Skin Lesion Segmentation.- A System For Liver Tumor Detection.- High Speed and Efficient Reconfigurable Histogram Equalisation Architecture for Image Contrast Enhancement.- A Practical Use For AI-Generated Images.- Homomorphic Encryption Schemes using Nested Matrices.- A Deep Learning Model for Heterogeneous Dataset Analysis - Application to Winter Wheat Crop Yield Prediction.

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Book SynopsisThis book constitutes the refereed proceedings of the 10th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2023, held in conjunction with the 26th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2023, in Vancouver, Canada, in October 2023.The 16 papers presented at OMIA 2023 were carefully reviewed and selected from 27 submissions. The papers cover various topics in the field of ophthalmic medical image analysis and challenges in terms of reliability and validation, number and type of conditions considered, multi-modal analysis (e.g., fundus, optical coherence tomography, scanning laser ophthalmoscopy), novel imaging technologies, and the effective transfer of advanced computer vision and machine learning technologies.

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Book SynopsisThe 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications. Table of ContentsA Shallow Information Enhanced Efficient Small Object Detector based on YOLOv5.- Adaptive Dehazing YOLO for Object Detection.- Adaptive Training Strategies for Small Object Detection using Anchor-based Detectors.- Automatic Driving Scenarios: A Cross-Domain Approach for Object Detection.- Dual Attention Feature Fusion for Visible-Infrared Object Detection.- Feature Sniffer: A Stealthy Inference Attacks Framework on Split Learning.- Few-Shot Object Detection via Transfer Learning and Contrastive Reweighting.- GaitFusion: Exploring the fusion of silhouettes and optical flow for gait recognition.- Gradient Adjusted and Weight Rectified Mean Teacher for Source-free Object Detection.- IMAM: Incorporating multiple attention mechanisms for 3D Object Detection from Point Cloud.- LGF2: Local and Global Feature Fusion for Text-guided Object Detection.- MLF-DET: Multi-Level Fusion for Cross-Modal 3D Object Detection.- Object Detection in Foggy Images with Transmission Map Guidance.- PE-YOLO: Pyramid Enhancement Network for Dark Object Detection.- Region Feature Disentanglement for Domain Adaptive Object Detection.- ROFusion: Efficient Object Detection using Hybrid Point-wise Radar-Optical Fusion.- SDGC-YOLOv5: A more accurate model for small object detection.- The Statistical Characteristics of P3a and P3b Subcomponents in Electroencephalography Signals.- Transforming Limitations into Advantages: Improving Small Object Detection Accuracy with SC-AttentionIoU Loss Function.- Visual-Haptic-Kinesthetic Object Recognition with Multimodal Transformer.- X-shape Feature Expansion Network for Salient Object Detection in Optical Remote Sensing Images.- Aggregate Distillation For Top-K Recommender System.- Candidate-Aware Dynamic Representation for News Recommendation.- Category Enhanced Dual View Contrastive Learning for Session-based Recommendation.- Electronic Medical Record Recommendation System Based on Deep Embedding Learning with Named Entity Recognition.- Incremental Recommendation Algorithm based on the Influence Propagation Model.- Scenic Spot Recommendation Method Integrating Knowledge Graph And Distance Cost.- A Unified Video Semantics Extraction and Noise Object Suppression Network for Video Saliency Detection.- Adaptive Token Excitation With Negative Selection For Video-Text Retrieval.- Boosting Video Super Resolution with Patch-Based Temporal Redundancy Optimization.- Bring the Noise: Introducing Noise Robustness to Pretrained Automatic Speech Recognition.- Correction while Recognition: Combining Pretrained Language Model for Taiwan-accented Speech Recognition.- Cross-Camera Prototype Learning for Intra-Camera Supervised Person Re-Identification.- ECDet: A Real-time Vehicle Detection Network for CPU-only Devices.- Gated Multi-Modal Fusion with Cross-Modal Contrastive Learning for Video Question Answering.- Learning Video Localization on Segment-Level Video Copy Detection with Transformer.- Linear Transformer-GAN: A Novel Architecture to Symbolic Music Generation.- MBMS-GAN: Multi-Band Multi-Scale Adversarial Learning for Enhancement of Coded Speech at Very Low Rate.- OWS-Seg: online weakly supervised video instance segmentation via contrastive learning.- Replay to Remember: Continual Layer-Specific Fine-tuning for German Speech Recognition.- Self-Supervised Video Object Segmentation Using Motion Feature Compensation.- Space-Time Video Super-Resolution Based on Long-Term Time Dependence.

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Book SynopsisThe 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications. Table of Contents2RDA: Representation and Relation Distillation with Data Augmentation.- A Document-Level Relation Extraction Framework with Dynamic Pruning.- A Global Feature Fusion Network for Lettuce Growth Trait Detection.- Adaptive Embedding and Distribution Re-Margin for Long-tail Recognition.- Adaptive Propagation Network Based on Multi-Scale Information Fusion.- An Efficient Approach for Improving the Recall of Rough Abstract Retrieval in Scientific Claim Verification.- An Explainable Feature Selection Approach for Fair Machine Learning.- Anchor link prediction based on trusted anchor re-identification.- Application of Data Encryption in Chinese Named Entity Recognition.- Attractor dynamics drive flexible timing in birdsong.- Boost Predominant Instrument Recognition Performance with MagiaSearch and MagiaClassifier.- Can Machine Learning Support Improvement in Effective Nutrition of patients in Critical Care Units?.- Cross-Domain Transformer with Adaptive Thresholding for Domain Adaptive Semantic Segmentation.- Delineation of prostate boundary from medical images via a mathematical formula-based hybrid algorithm.- Diversifying non-dissipative Reservoir Computing dynamics.- Efficient Reinforcement Learning using State-Action Uncertainty with Multiple Heads.- Exploring the role of feedback inhibition for the robustness against corruptions on event-based data.- Extracting feature space for synchronizing behavior in an interaction scene using unannotated data.- F-E Fusion:A Fast Detection Method of Moving UAV Based on Frame and Event Flow.- Few-shot Relational Triple Extraction based on Evaluation of Token-Level Semantic Similarity.- GII: a Unified Approach to Representation Learning in Open Set Recognition with Novel Category Discovery.- Glancing text and vision regularized training to enhance machine translation.- Global-Temporal Enhancement for Sign Language Recognition.- Global-to-contextual Shared Semantic Learning for Fine-grained Vision-language Alignment.- Gradient-based Learning of Finite Automata.- Hierarchical Contrastive Learning for CSI-based Fingerprint Localization.- Higher Education Programming Competencies: A Novel Dataset.- Higher Target Relevance Parallel Machine Translation with Low-Frequency Word Enhancement.- I^2KD-SLU: An Intra-Inter Knowledge Distillation Framework for Zero-Shot Cross-Lingual Spoken Language Understanding.- Imbalanced Few-shot Learning based on Meta-transfer Learning.- Impact Analysis of Climate Change on Floods in an Indian Region using Machine Learning.- Improving Limited Resource Speech Recognition Performance with Latent Regression Bayesian Network.- Input Layer Binarization with Bit-Plane Encoding.- Investigation of Information Processing Mechanisms in the Human Brain during Reading Tanka Poetry.- Joint Demosaicing and Denoising with Frequency Domain Features.- Knowledge Distillation with Feature Enhancement Mask.- Label-description Enhanced Network for Few-shot Named Entity Recognition.- Landslide Surface Displacement Prediction Based on VSXC-LSTM Algorithm.- LaneMP: Robust Lane Attention Detection based on Mutual Perception of Keypoints.- LE-MVSNet: Lightweight Efficient Multi-view Stereo Network.- Lightweight Reference-Less Summary Quality Evaluation via Key Feature Extraction.- Limited Information Opponent Modeling.

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Book SynopsisThe 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers and 9 short papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.Table of ContentsMEA-TransUNet: a Multiple External Attention Network for Multi-Organ Segmentation.- Membership-Grade Based Prototype Rectification for Fine-Grained Few-Shot Classification.- Multi-grained Aspect Fusion for Review Response Generation.- Multiple Object Tracking based on Variable GIoU-Embedding Matrix and Kalman Filter Compensation.- Multi-relation Identification for Few-shot Document-level Relation Extraction.- Multi-Task Learning for Mongolian Morphological Analysis.- Multi-task Pre-training for Lhasa-Tibetan Speech Recognition.- Mutual Information Dropout: Mutual Information Can Be All You Need.- Non-Outlier Pseudo-Labeling for Short Text Clustering.- Optimal Node Embedding Dimension Selection Using Overall Entropy.- PairEE: A Novel Pairing-Scoring Approach for Better Overlapping Event Extraction.- PCB Component Rotation Detection Based on Polarity Identifier Attention.- PCDialogEval: Persona and Context Aware Emotional Dialogue Evaluation.- PlantDet: A benchmark for Plant Detection in the Three-Rivers-Source Region.- PO-DARTS: Post-Optimizing the Architectures Searched by Differentiable Architecture Search Algorithms.- Predicting high vs low mother-baby synchrony with GRU-based ensemble models.- Properties of the weighted and robust implicitly weighted correlation coefficients.- PSML: Prototype-Based OSSL Framework for Multi-Information Mining.- Pure Physics-Informed Echo State Network of ODE Solution Replicator.- RegionRel:A Framework for Jointly Extracting Relational Triplets by Performing Sub-tasks by Region.- Robustness to Variability and Asymmetry of In-memory On-chip Training.- Selecting Distinctive-Variant Training Samples Base on Intra-class Similarity.- Semantic Information Mining and Fusion Method for Bot Detection.- Semilayer-Wise Partial Quantization without Accuracy Degradation or Back Propagation.- ShadowGAN for Line Drawings Shadow Generation.- Ship Attitude Prediction Based on Dynamic Sliding Window and EEMD-SSA-BiLSTM.- Solving Math Word Problem with External Knowledge and Entailment Loss.- Spatially Invariant and Frequency-Aware CycleGAN for Unsupervised MR-to-CT Synthesis.- Spatio-temporal Attention Model with Prior Knowledge for Solar Wind Speed Prediction.- Spatiotemporal model with attention mechanism for ENSO Predictions.- SPM-Diffusion for Temperature Prediction.- S-SOLVER: Numerically stable adaptive step size solver for neural ODEs.- TableSF: A Structural Bias Framework for Table-to-Text Generation.- TCS-LipNet:Temporal & Channel & Spatial Attention-based Lip Reading Network.- The Dynamic Selection of Combination Methods in Classifier Ensembles by Region of Competence.- The progressive detectors and discriminative feature descriptors combining global and local information.- Towards Better Dialogue Utterance Rewriting via a Gated Span-Copy Mechanism.- TSP Combination Optimization with Semi-local Attention Mechanism.- UDCGN: Uncertainty-Driven Cross-Guided Network for Depth Completion of Transparent Objects.- Use of Machine Learning Algorithms to Analyze the Digit Recognizer Problem in an Effective Manner.- Vulnerability Analysis of Continuous Prompts for Pre-trained Language Models.

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Book SynopsisThe 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers and 9 short papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.Table of ContentsA Comparative Study of Sentence Embedding Models for Assessing Semantic Variation.- A Deep Learning based Method for Generating Holographic Acoustic Fields from Phased Transducer Arrays.- A Depth-guided Attention Strategy for Crowd Counting.- A Noise Convolution Network for Tampering Detection.- Attention-based Feature Interaction Deep Factorization Machine for CTR Prediction.- Block-level Stiffness Analysis of Residual Networks.- CKNA: Kernel Hyperparameters Optimization Method for Group-wise CNNs.- Conditional Convolution Residual Network for Efficient Super-Resolution.- Cross Attention with Deep Local Features for Few-shot Image Classification.- Deep Video Compression Based on 3D Convolution Artifacts Removal and Attention Compression Module.- Deep-learning Based Three Channel Defocused Projection Profilometry.- Depthwise Convolution with Channel Mixer: Rethinking MLP in MetaFormer for Faster and More Accurate Vehicle Detection.- DLUIO: Detecting Useful Investor Opinions by Deep Learning.- Dynamic obstacle avoidance for unmanned aerial vehicle using dynamic vision sensor.- Empirical Study on the Effect of Residual Networks on the Expressiveness of Linear Regions.- Energy Complexity Model for Convolutional Neural Networks.- Enhancing the Interpretability of Deep Multi-Agent Reinforcement Learning via Neural Logic Reasoning.- Evidential Robust Deep Learning for Noisy Text2text Question Classification.- FBPFormer: Dynamic Convolutional Transformer for Global-Local-Contexual Facial Beauty Prediction.- Heavy-Tailed Regularization of Weight Matrices in Deep Neural Networks.- Interaction of Generalization and Out-of-Distribution Detection Capabilities in Deep Neural Networks.- Long-distance Pipeline Intrusion Warning Based on Environment Embedding From Distributed Optical Fiber Sensing.- LSA3D: Lightweight Separate Asynchronous 3D Convolutional Neural Network for Gait Recognition.- MADNet: EEG-based Depression Detection using a Deep Convolution Neural Network Framework with Multi-dimensional Attention.- Maintenance automation using deep learning methods a case study from the aerospace industry.- MCASleepNet: Multimodal channel attention-based deep neural network for automatic sleep staging.- Multi-label Image Deep Hashing with Hybrid Loss of Global Center and Local Alignment.- Multi-relation Representation Learning based Deep Network for Patent Classification.- One Hip Wonder: 1D-CNNs Reduce Sensor Requirements for Everyday Gait Analysis.- Patches Channel Attention For Human Sitting Posture Recognition.- RA-Net: A Deep Learning Approach based on Residual Structure and Attention Mechanism for Image Copy-move Forgery Detection.- Rethinking CNN Architectures in Transformer Detectors.- Robustness of Biologically-inspired filter-based ConvNet to Signal Perturbation.- Self-Supervised Graph Convolution for Video Moment Retrieval.- Siamese Network based on MLP and Multi-head Cross Attention for Visual Object Tracking.- Taper Residual Dense Network for Audio Super-Resolution.- VPNDroid: Malicious Android VPN detection using a CNN-RF method.- Who breaks early, looses: goal oriented training of deep neural networks based on port Hamiltonian dynamics.- BLR:A multi-modal sentiment analysis model.- Detecting Negative Sentiment on Sarcastic Tweets for Sentiment Analysis.- Local or Global: The Variation in the Encoding of Style Across Sentiment and Formality.- Prompt-oriented Fine-tuning Dual Bert for Aspect-Based Sentiment Analysis.- Towards Energy-Efficient Sentiment Classification with Spiking Neural Networks.- Using Masked Language Modeling to Enhance BERT-based Aspect-Based Sentiment Analysis for Affective Token Prediction.

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Book SynopsisThe 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications. Table of ContentsA Data Augmentation based ViT for Fine-Grained Visual Classification.- A Detail Geometry Learning Network for High-Fidelity Face Reconstruction.- A Lightweight Multi-Scale Large Kernel Attention Hierarchical Network for Single Image Deraining.- A Multi-Scale Method for Cell Segmentation in Fluorescence Microscopy Images.- Adaptive interaction-based multi-view 3D object reconstruction.- An auxiliary modality based Text-Image matching methodology for fake news detection.- An Improved Lightweight YOLOv5 for Remote Sensing Images.- An Improved YOLOv5 with Structural Reparameterization for Surface Defect Detection.- ASP Loss: Adaptive Sample-Level Prioritizing Loss for Mass Segmentation on Whole Mammography Images.- Cascaded Network-based Single-View Bird 3D Reconstruction.- CLASPPNet: A Cross-Layer Multi-Class Lane Semantic Segmentation Model Fused with Lane Detection Module.- Classification-based and Lightweight Networks For Fast Image Super Resolution.- CLN: Complementary Learning Network For 3D Face Reconstruction And Alignment.- Combining Edge-guided Attention and Sparse-connected U-Net for Detection of Image Splicing.- Contour-augmented Concept Prediction Network for image captioning.- Contrastive Knowledge Amalgamation for Unsupervised Image Classification.- Cross Classroom Domain Adaptive Object Detector for Student's Heads.- Diffusion-Adapter: Text Guided Image Manipulation with Frozen Diffusion Models.- DWA: Differential Wavelet Amplifier for Image Super-Resolution.- Dynamic Facial Expression Recognition in Unconstrained Real-World Scenarios Leveraging Dempster-Shafer Evidence Theory.- End-to-end Remote Sensing Change Detection of Unregistered Bi-temporal Images for Natural Disasters.- E-Patcher: A Patch-based Efficient Network for Fast Whole Slide Images Segmentation.- Exploiting Multi-modal Fusion for Robust Face Representation Learning with Missing Modality.- Extraction Method of Rotated Objects from High-resolution Remote Sensing Images.- Few-shot NeRF-based View Synthesis for Viewpoint-biased Camera Pose Estimation.- Ga-RFR: Recurrent Feature Reasoning with gated convolution for Chinese Inscriptions Image Inpainting.- Generalisation Approach for Banknote Authentication by Mobile Devices Trained on Incomplete Samples.- Image Caption with Prior Knowledge Graph and Heterogeneous Attention.- Image Captioning for Nantong Blue Calico Through Stacked Local-Global Channel Attention Network.- Improving Image Captioning with Feature Filtering and Injection.- In silico study of single synapse dynamics using a three-state kinetic model.- Interpretable Image Recognition by Screening Class-specific and Class-shared Prototypes.- Joint Edge-guided and Spectral Transformation Network for Self-Supervised X-ray Image Restoration.- Lightweight Human Pose Estimation Based On Densely Guided Self-Knowledge Distillation.- MCAPR: Multi-Modality Cross Attention for Camera Absolute Pose Regression.- MC-MLP: A Multiple Coordinate Frames MLP-Like Architecture for Vision.- Medical Image Segmentation and Saliency Detection through a Novel Color Contextual Extractor.- MedNet: A Dual-Copy Mechanism for Medical Report Generation from Images.- Ms-AMPool: Down-Sampling Method for Dense Prediction Tasks.- Multi-frame Tilt-angle Face Recognition Using Fusion Re-ranking.- Multi-scale field distillation for multi-task semantic segmentation.- Neural Field Conditioning Strategies for 2D Semantic Segmentation.- Neurodynamical Model of the Visual Recognition of Dynamic Bodily Actions from Silhouettes.- PACE: Point Annotation-Based Cell Segmentation for Efficient Microscopic Image Analysis.- Pie-UNet: A novel Parallel Interaction Encoder for Medical Image Segmentation.- Prior-SSL: A Thickness Distribution Prior and Uncertainty Guided Semi-supervised Learning Method for Choroidal Segmentation in OCT Images.- PSR-Net A Dual-Branch Pyramid Semantic Reasoning Network for Segmentation of Remote Sensing Images.

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Book SynopsisThe 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications. Table of ContentsA Further Exploration of Deep Multi-Agent Reinforcement Learning with Hybrid Action Space.- Air-to-Ground Active Object Tracking via Reinforcement Learning.- Enhancing P300 Detection in Brain-Computer Interfaces with Interpretable Post-Processing of Recurrent Neural Networks.- Group-Agent Reinforcement Learning.- Improving Generalization of Multi-agent Reinforcement Learning through Domain-Invariant Feature Extraction.- Latent-Conditioned Policy Gradient for Multi-Objective Deep Reinforcement Learning.- LIIVSR: A Unidirectional Recurrent Video Super-Resolution Framework with Gaussian Detail Enhancement and Local Information Interaction Modules.- Masked Scale-Recurrent Network for Incomplete Blurred Image Restoration.- Multi-fusion Recurrent Network for Argument Pair Extraction.- Pacesetter Learning For Large Scale Cooperative Multi-Agent Reinforcement Learning.- Stable Learning Algorithm Using Reducibility for Recurrent Neural Networks.- t-ConvESN: Temporal Convolution-Readout for Random Recurrent Neural Networks.- Adaptive Reservoir Neural Gas: An Effective Clustering Algorithm for Addressing Concept Drift in Real-Time Data Streams.- An Intelligent Dynamic Selection System Based on Nearest Temporal Windows for Time Series Forecasting.- Generating Sparse Counterfactual Explanations For Multivariate Time Series.- Graph Neural Network-Based Representation Learning for Medical Time Series.- Knowledge Forcing: Fusing Knowledge-Driven Approaches with LSTM for Time Series Forecasting.- MAGNet: Muti-scale Attention and Evolutionary Graph Structure for Long Sequence Time-Series Forecasting.- MIPCE: Generating Multiple Patches Counterfactual-changing Explanations for Time Series Classification.- Multi-Timestep-Ahead Prediction with Mixture of Experts for Embodied Question Answering.- Rethink the Top-u Attention in Sparse Self-attention for Long Sequence Time-Series Forecasting.- Temporal Attention Signatures for Interpretable Time-Series Prediction.- Time-Series Prediction of Calcium Carbonate Concentration in Flue Gas Desulfurization Equipment by Optimized Echo State Network.- WAG-NAT: Window Attention and Generator Based Non-Autoregressive Transformer for Time Series Forecasting.- A Novel Encoder and Label Assignment for Instance Segmentation.- A Transformer-based Framework for Biomedical Information Retrieval Systems.- A Transformer-Based Method for UAV-View Geo-Localization.- Cross-graph Transformer Network for Temporal Sentence Grounding.- EGCN: A Node Classification Model based on Transformer and Spatial Feature Attention GCN for Dynamic Graph.- Enhance Representational Differentiation Step By Step: A Two-Stage Encoder-Decoder Network for Implicit Discourse Relation Classification.- GenTC: Generative Transformer via Contrastive Learning for Receipt Information Extraction.- Hierarchical Classification for Symmetrized VI Trajectory Based on Lightweight Swin Transformer.- Hierarchical Vision and Language Transformer for Efficient Visual Dialog.- ICDT: Maintaining Interaction Consistency for Deformable Transformer with Multi-scale Features in HOI Detection.- Imbalanced Conditional Conv-Transformer For Mathematical Expression Recognition.- Knowledge Graph Transformer for Sequential Recommendation.- LorenTzE: Temporal Knowledge Graph Embedding based on Lorentz Transformation.- MFT: Multi-scale Fusion Transformer for Infrared and Visible Image Fusion.- NeuralODE-based Latent Trajectories into AutoEncoder Architecture for Surrogate Modelling of Parametrized High-dimensional Dynamical Systems.- RRecT: Chinese Text Recognition with Radical-enhanced Recognition Transformer.- S2R: Exploring a Double-Win Transformer-Based Framework for Ideal and Blind Super-Resolution.- Self-adapted Positional Encoding in the Transformer Encoder for Named Entity Recognition.- SHGAE: Social Hypergraph AutoEncoder for Friendship Inference.- Temporal Deformable Transformer For Action Localization.- Trans-Cycle: Unpaired Image-to-Image Translation Network by Transformer.

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Book SynopsisThis book constitutes the refereed proceedings of the 5th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2023, held in conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023. For this workshop, 21 papers from 32 submissions were accepted for publication. The accepted papers cover the fields of uncertainty estimation and modeling, as well as out of distribution management, domain shift robustness, Bayesian deep learning and uncertainty calibration.Table of ContentsUncertainty estimation and modelling.- Out of Distribution management and domain shift robustness.- Bayesian deep learning and uncertainty calibration.

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Book SynopsisThis book constitutes the proceedings of the 4th International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2023, held in conjunction with MICCAI 2023, the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention. The conference took place in Vancouver, BC, Canada, on October 8, 2023. The 19 papers presented in this book were carefully reviewed and selected from 30 submissions. They were organized in topical sections as follows:​ advanced imaging, segmentation, and ultrasound techniques; predictive analysis, learning, and classification; multimodal imaging, reconstruction, and real-time applications; diagnostic enhancements and novel ultrasound innovations.Table of ContentsAdvanced Imaging, Segmentation, and Ultrasound Techniques.- Predictive Analysis, Learning, and Classification.- Multimodal Imaging, Reconstruction, and Real-time Applications.- Diagnostic Enhancements and Novel Ultrasound Innovations.

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Book SynopsisThis book constitutes the refereed proceedings of the 8th International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2023, held in conjunction with MICCAI 2023, in Vancouver, Canada, in October 2023.The 13 full papers included in this book were carefully reviewed and selected from 16 submissions. They span a wide range of topics relevant to SASHIMI, and reflect recent developments in methods for segmentation, image-to-image translation, super-resolution, and image synthesis. Applications include MRI imaging, echocardiography, PET, and digital pathology.Table of ContentsTransformers for CT Reconstruction From Monoplanar and Biplanar Radiographs Super-resolution Segmentation network for inner-ear tissue segmentation.- Multi-Phase Liver-Specific DCE-MRI Translation via a Registration-Guided GAN.- Learned Local Attention Maps for Synthesising Vessel Segmentations from T2 MRI Physics-Aware Motion Simulation for T2*-Weighted Brain MRI.- Unsupervised heteromodal physics-informed representation of MRI data: tackling data harmonisation, imputation and domain shift.- TAI-GAN: Temporally and Anatomically Informed GAN for early-to-late frame conversion in dynamic cardiac PET motion correction.- How Good Are Synthetic Medical Images? An Empirical Study with Lung Ultrasound Unsupervised Liver Tumor Segmentation with Pseudo Anomaly Synthesis.- Improving style transfer in dynamic contrast enhanced MRI using a spatio-temporal approach Synthetic Singleplex-Image Generation in Multiplex-Brightfield Immunohistochemistry.- Digital Pathology using Deep Generative Models Self-Supervised Super-Resolution for Anisotropic MR Images with and without Slice Gap DIFF·3: A latent diffusion model for the generation of synthetic 3D echocardiographic images and corresponding labels.

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Book SynopsisAuthored by a leading expert in the field, this book introduces an innovative methodology that harnesses the power of fuzzy logic to enhance decision-making in multi-attribute scenarios. In a world of complexity and uncertainty, effective decision-making is paramount. Springer proudly presents a cutting-edge publication that revolutionizes decision analysis: "Fuzzy Decision Analysis: Multi-attribute Decision-Making Approach." This book stands at the forefront of decision analysis, introducing the integration of fuzzy logic into multi-attribute decision-making. It is a transformative journey into the realm of advanced decision analysis. It book not only equips you with the knowledge to comprehend the theoretical underpinnings but also empowers you to apply these insights in practical scenarios. This book serves as your indispensable companion. Its comprehensive coverage serves as a beacon, guiding you through the intricate maze of fuzzy logic and multi-attribute decision-making, ultimately empowering you to embrace innovation and master the art of making well-informed decisions in an ever-changing world.Table of ContentsFoundations of Decision.- Technique for Order Preferences by Similarity to Ideal Solutions (TOPSIS) in uncertainty environment.- The Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) in uncertainty environment.- The Multi-Objective Optimization Ratio Analysis (MOORA) in uncertainty environment.

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Book SynopsisThis book constitutes the refereed proceedings of the 21st International Symposium on Automated Technology for Verification and Analysis, ATVA 2023, held in Singapore, in October 2023. The symposium intends to promote research in theoretical and practical aspects of automated analysis, verification and synthesis by providing a forum for interaction between regional and international research communities and industry in related areas. The 30 regular papers presented together with 7 tool papers were carefully reviewed and selected from 150 submissions.The papers are divided into the following topical sub-headings: Temporal logics, Data structures and heuristics, Verification of programs and hardware. Table of ContentsTemporal logics.- Data structures and heuristics.- Verification of programs and hardware.- Tool papers.

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Book SynopsisThe three-volume set LNAI 14195, 14196, and 14197 constitutes the refereed proceedings of the 12th Brazilian Conference on Intelligent Systems, BRACIS 2023, which took place in Belo Horizonte, Brazil, in September 2023. The 90 full papers included in the proceedings were carefully reviewed and selected from 242 submissions. They have been organized in topical sections as follows:Part I: Best papers; resource allocation and planning; rules and feature extraction; AI and education; agent systems; explainability; AI models; Part II: Transformer applications; convolutional neural networks; deep learning applications; reinforcement learning and GAN; classification; machine learning analysis;Part III: Evolutionary algorithms; optimization strategies; computer vision; language and models; graph neural networks; pattern recognition; AI applications. Table of ContentsEmbracing data irregularities in multivariate time series with Recurrent and Graph Neural Networks.- Regulation and Ethics of Facial Recognition Systems: an analysis of cases in the Court of Appeal in the State of São Paulo.- A combinatorial optimization model and polynomial time heuristic for a problem of finding specific structural patterns in networks.- Efficient Density-Based Models for Multiple Machine Learning Solutions over Large Datasets.- Exploring Text Decoding Methods for Portuguese Legal Text Generation.- Community Detection for Multi-Label Classification.- A Monte Carlo Algorithm for Time-Constrained General Game Playing.- Alpha-MCMP: trade-offs between probability and cost in SSPs with the MCMP criterion.- Specifying Preferences over Policies using Branching Time Temporal Logic.- Logic-based Explanations for Linear Support Vector Classifiers with Reject Option.- The Multi-Attribute Fairer Cover Problem.- A Custom Bio-Inspired Algorithm for the Molecular Distance Geometry Problem.- Allocating Dynamic and Finite Resources to a Set of Known Tasks.- A Multi-algorithm approach to the optimization of thermal power plants operation.- An incremental MaxSAT-based model to learn interpretable and balanced classification rules.- d-CC Integrals: generalizing CC-integrals by restricted dissimilarity functions with applications to fuzzy-rule based systems.- FeatGeNN: Improving Model Performance for Tabular Data with Correlation-based Feature Extraction.- Hierarchical Time-aware Approach for Video Summarization.- Analyzing college student dropout risk prediction in real data using walk-forward validation.- The artificial intelligence as a technological resource in the application of tasks for the development of joint attention in children with autism.- Machine teaching: an explainable machine learning model for individualized education.- BLUEX: a benchmark based on Brazilian Leading Universities Entrance eXams.- Towards Generating P-Contrastive Explanations for Goal Selection in extended-BDI Agents.- Applying Theory of Mind to Multi-Agent Systems: A Systematic Literature Review.- A Spin-off Version of Jason for IoT and Embedded Multiagent Systems.- Hybrid Multilevel Explanation: A new approach for explaining regression models.- Explainability of COVID-19 Classification Models using Dimensionality Reduction of SHAP values.- An explainable model to support the decision about the appropriate therapy protocol for AML.- Bayes and Laplace versus the world: A new label attack approach in federated environments based on Bayesian Neural Networks.- MAT-Tree: A Tree-based Method for Multiple Aspect Trajectory Clustering.

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Book SynopsisThe three-volume set LNAI 14195, 14196, and 14197 constitutes the refereed proceedings of the 12th Brazilian Conference on Intelligent Systems, BRACIS 2023, which took place in Belo Horizonte, Brazil, in September 2023. The 90 full papers included in the proceedings were carefully reviewed and selected from 242 submissions. They have been organized in topical sections as follows:Part I: Best papers; resource allocation and planning; rules and feature extraction; AI and education; agent systems; explainability; AI models; Part II: Transformer applications; convolutional neural networks; deep learning applications; reinforcement learning and GAN; classification; machine learning analysis;Part III: Evolutionary algorithms; optimization strategies; computer vision; language and models; graph neural networks; pattern recognition; AI applications. Table of ContentsTransformer Model for Fault Detection From Brazilian Pre-Salt Seismic Data.- Evaluating Recent Legal Rhetorical Role Labeling Approaches Supported by Transformer Encoders.- Dog Face Recognition Using Vision Transformer.- Convolutional neural networks for the molecular detection of Covid-19.- Hierarchical Graph Convolutional Networks for Image Classification.- Interpreting Convolutional Neural Networks for Brain Tumor Classification: An Explainable Artificial Intelligence Approach.- Enhancing Stock Market Predictions through the Integration of Convolutional and Recursive LSTM Blocks: A Cross-Market Analysis.- Ensemble architectures and efficient fusion techniques for Convolutional Neural Networks: an analysis on resource optimization strategies.- Dog Face Recognition using Deep Feature Embeddings.- Clinical oncology textual notes analysis using machine learning and deep learning.- EfficientDeepLab For Automated Trachea Segmentation On Medical Images.- Multi-Label Classification of Pathologies in Chest Radiograph Images Using DenseNet.- Does pre-training on brain-related tasks results in better deep-learning-based brain age biomarkers.- Applying Reinforcement Learning for Multiple Functions in Swarm Intelligence.- Deep Reinforcement Learning for Voltage Control in Power Systems.- Performance Analysis of Generative Adversarial Networks and Diffusion Models for Face Aging.- Occluded Face In-painting Using Generative Adversarial Networks - A ReviewClassification of facial images to assist in the diagnosis of Autism Spectrum Disorder: a study on the effect of face detection and landmark identification algorithms.- Constructive Machine Learning and Hierarchical Multi-label Classification for Molecules Design.- AutoMMLC: An Automated and Multi-objective Method for Multi-label Classification.- Merging Traditional Feature Extraction and Deep Learning for Enhanced Hop Variety Classification: A Comparative Study Using the UFOP-HVD Dataset.- Feature Selection and Hyperparameter Fine-tuning in Artificial Neural Networks for Wood Quality Classification.- A Feature-based Out-of-Distribution Detection Approach in Skin Lesion Classification.- A framework for characterizing what makes an instance hard to classify.- Physicochemical Properties for Promoter Classification.- Critical analysis of AI indicators in terms of weighting and aggregation approaches.- Estimating Code Running Time Complexity with Machine LearningThe Effect of Statistical Hypothesis Testing on Machine Learning Model Selection.

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Book SynopsisThe three-volume set LNAI 14195, 14196, and 14197 constitutes the refereed proceedings of the 12th Brazilian Conference on Intelligent Systems, BRACIS 2023, which took place in Belo Horizonte, Brazil, in September 2023. The 90 full papers included in the proceedings were carefully reviewed and selected from 242 submissions. They have been organized in topical sections as follows:Part I: Best papers; resource allocation and planning; rules and feature extraction; AI and education; agent systems; explainability; AI models; Part II: Transformer applications; convolutional neural networks; deep learning applications; reinforcement learning and GAN; classification; machine learning analysis;Part III: Evolutionary algorithms; optimization strategies; computer vision; language and models; graph neural networks; pattern recognition; AI applications. Table of ContentsMulti-objective Genetic Algorithms Applied to the Optimization of Expanded Genetic Codes.- Genetic Algorithms with Optimality Cuts to the Max-Cut Problem.- Assessment of robust multi-objective evolutionary algorithms on robust and noisy environments.- Binary Flying Squirrel Optimizer for Feature Selection.- Fitness Landscape Analysis of TPOT using Local Optima Network.- Optimization Strategies for BERT-based Named Entity Recognition.- FlexCon-CE: A Semi-supervised Method with an Ensemble-based Adaptive Confidence.- Single Image Super-Resolution Based on Capsule Neural Networks.- Development of a Deep Learning Model for the Classification of Mosquito Larvae Images.- A Simple and Low-cost Method for Leaf Surface Dimension Estimation Based on Digital Images.- Crop Row Line Detection with Auxiliary Segmentation Task.- Multiple object tracking in native bee hives: A case study with Jataí in the field.- An Open Source Eye Gaze Tracker system to perform remote user testing evaluations.- Who Killed the Winograd Schema Challenge?Sabiá: Portuguese Large Language Models.- Disambiguation of Universal Dependencies Part-of-Speech Tags of Closed Class Words in Portuguese.- Bete: A Brazilian Portuguese Dataset for Named Entity Recognition and Relation Extraction in the Diabetes Healthcare Domain.- LegalBert-pt: A Pretrained Language Model for the Brazilian Portuguese Legal Domain.- A Framework for Controversial Political Topics Identification using Twitter Data.- Leveraging Sign Language Processing with Formal SignWriting and Deep Learning ArchitecturesA clustering validation index based on semantic description.- Detecting Multiple Epidemic Sources in Network Epidemics using Graph Neural Networks.- Prediction of cancer-related miRNA targets using an integrative heterogeneous Graph Neural Network-based method.- Time series forecasting of COVID-19 cases in Brazil with GNN and mobility networks.- Federated Learning and Mel-spectrograms for Physical Violence Detection in Audio.- Police Report Similarity Search: a case study.- Evaluating Contextualized Embeddings for Topic Modeling in Public Bidding Domain.- A Tool for Measuring Energy Consumption in Data Stream Mining.- Improved Fuzzy Decision System for Energy Bill Reduction in the Context of the Brazilian White Tariff Scenario.- Exploring Artificial Intelligence methods for the automatic measurement of a new biomarker aiming at glaucoma diagnosis.- Investigation of deep Active Self-Learning algorithms applied to named entity recognition.

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Book Synopsis​This book constitutes the refereed proceedings of the 8th International Workshop on Perinatal, Preterm and Paediatric Image Analysis, PIPPI 2023, held in conjunction with the 26th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2023, in Vancouver, Canada, in October 2023.The 10 full papers presented at PIPPI 2023 were carefully reviewed and selected from 14 submissions. PIPPI 2023 workshop complements the main MICCAI conference by providing a focused discussion on the challenges of image analysis techniques as applied to the fetal and infant settings.

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Book SynopsisThis book constitutes the refereed proceedings of the 11th Iberoamerican Conference on Applications and Usability of Interactive TV, jAUTI 2022, Cordoba, Spain, November 17–18, 2022. The 9 full papers included in this book were carefully reviewed and selected from 25 submissions. They were organized in topical sections as follows: Content Creation and Interaction, Audiovisual Consumption, e-inclusion, Digital Infrastructure. Table of Contents​Content Creation and Interaction.- Personalized Web-based Contents, generated through a Cross-media Environment, as Additional Information to Documentary Video.- MNEMOSCOPE - A model for digital co-creation and visualization of collective memories.- Dynamic configuration of panoramic virtual tours.- Audiovisual Consumption.- Personalized notifications for the TV ecosystem: field trial of an iTV solution.- Combining Text-To-Speech Services with Conventional Voiceover for News Oralization.- e-inclusion.- iTV to connect generations: a field trial of a solution to send personalized notifications.- Digital Infrastructure.- Encryption of Messages and Additional Information in Digital Terrestrial Television’s Transport Stream Using PSI/SI Tables.- On Using a Microearthquake Recognition System for an Early Warning System at Cotopaxi Volcano.- Using eye tracking to map attention in an EEG-based brainwave graphic visualization system.-Evaluating Perceived Value and Intention to Continue Using Over-the-Top Services in Latin America: A Case Study in Quito, Ecuador.

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Book SynopsisThis book constitutes the referred proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2022, Virtual Event, February 6–8, 2022. The 15 full papers included in this book were carefully reviewed and selected from 392 submissions. The purpose of VISIGRAPP is to bring together researchers and practitioners interested in both theoretical advances and applications of computer vision, computer graphics and information visualization. VISIGRAPP is composed of four co-located conferences, each specialized in at least one of the aforementioned main knowledge areas, namely GRAPP, IVAPP, HUCAPP and VISAPP. Table of ContentsPapers.- Automatic Threshold RanSaC Algorithms for Pose Estimation Tasks.- Semi-Automated Generation of Accurate Ground-Truth for 3D Object Detection.- A Quantitative and Qualitative Analysis on a GAN-based Face Mask Removal on Masked Images and Videos.- A Quantitative and Qualitative Analysis on a GAN-based Face Mask Removal on Masked Images and Videos.- Partial Alignment of Time Series for Action and Activity Prediction.- Automatic Bi-LSTM Architecture Search Using Bayesian Optimisation for Vehicle Activity Recognition.- ANTENNA: Visual Analytics of Mobility Derived from Cellphone Data.- Influence of Errors on the Evaluation of Text Classification Systems.- Autonomous Navigation Method Considering Passenger Comfort Recognition for Personal Mobility Vehicles in Crowded Pedestrian Spaces.- The Electrodermal Activity of Player Experience in Virtual Reality Games: An Extended Evaluation of the Phasic Component.- MinMax-CAM: Increasing Precision of Explaining Maps by Contrasting Gradient Signals and Regularizing Kernel Usage.- DIAR: Deep Image Alignment and Reconstruction Using Swin Transformers.- Active Learning with Data Augmentation Under Small vs Large Dataset Regimes for Semantic-KITTI Dataset.- Transformers in Unsupervised Structure-from-Motion.- A Study of Aerial Image-based 3D Reconstructions in a Metropolitan Area.

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Book SynopsisThis book constitutes the refereed proceedings of the 19th International Conference on Advanced Data Mining and Applications, ADMA 2023, held in Shenyang, China, during August 21–23, 2023.The 216 full papers included in this book were carefully reviewed and selected from 503 submissions. They were organized in topical sections as follows: Data mining foundations, Grand challenges of data mining, Parallel and distributed data mining algorithms, Mining on data streams, Graph mining and Spatial data mining.Table of ContentsPharmaceutical Data Analysis.- Drug-target interaction prediction based on drug subgraph fingerprint extraction strategy and subgraph attention mechanism.- Soft Prompt Transfer for Zero-Shot and Few-Shot Learning in EHR Understanding.- Graph Convolution Synthetic Transformer for Chronic Kidney Disease Onset Prediction.- MTFL: Multi-task feature learning with joint correlation structure learning for Alzheimer’s disease cognitive performance prediction.- Multi-Level Transformer for Cancer Outcome Prediction in Large-Scale Claims Data.- Individual Functional Network Abnormalities Mapping via Graph Representation-based Neural Architecture Search.- A novel application of a mutual information measure for analysing temporal changes in healthcare network graphs.- Drugs Resistance Analysis from Scarce Health Records via Multi-task Graph Representation.- Text Classification.- ParaNet:Parallel Networks with Pre-trained Models for Text Classification.- Open Text Classification Based on Dynamic Boundary Balance.- A Prompt Tuning Method for Chinese Medical Text Classification.- TabMentor: Detect Errors on Tabular Data with Noisy Labels.- Label-aware Hierarchical Contrastive Domain Adaptation for Cross-network Node Classification.- Semi-supervised classification based on Graph Convolution Encoder Representations from BERT.- Global Balanced Text Classification for Stable Disease Diagnosis.- Graph.- Dominance Maximization in Uncertain Graphs.- LAGCL: Towards Stable and Automated Graph Contrastive Learning.- Discriminative Graph-level Anomaly Detection via Dual-students-teacher Model.- Common-Truss-based Community Search on Multilayer Graphs.- Learning To Predict Shortest Path Distance.- Efficient Regular Path Query Evaluation with Structural Path Constraints.EnSpeciVAT: Enhanced SpeciVAT for Cluster Tendency Identification in Graphs.- Pessimistic Adversarially Regularized Learning for Graph Embedding.- M2HGCL: Multi-Scale Meta-Path Integrated Heterogeneous Graph Contrastive Learning.

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Book SynopsisThese two volumes constitute the proceedings of the 10th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2023, held in Kanazawa, Japan, during November 2-4, 2023. The 58 full papers presented were carefully reviewed and selected from 107 submissions. The papers deal with all aspects of research results, ideas, and experiences of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.Table of ContentsUncertainty Management and Decision Making.- Optimization and Statistical Methods.- Economic Application

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Book SynopsisThis book constitutes the proceedings of the 6th International Conference on Applied Informatics, ICAI 2023, which took place in Guayaquil, Ecuador, in October 2023.The 30 papers presented in this volume were carefully reviewed and selected from 132 submissions. The contributions are divided into the following thematic blocks: Artificial Intelligence; Data Analysis; Decision Systems; Enterprise Information Systems Applications; Geoinformatics; Health Care Information Systems; Interdisciplinary Information Studies; Learning Management Systems; Virtual and Augmented Reality.Table of ContentsArtificial Intelligence.- Data Analysis.- Decision Systems.- Enterprise Information Systems Applications.- Geoinformatics.- Health Care Information Systems.- Interdisciplinary Information Studies.- Learning Management Systems.- Virtual and Augmented Reality.

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Book SynopsisThis book constitutes the refereed proceedings of 7 workshops, held at the 42nd International Conference on Conceptual Modeling, ER 2023, held in Lisbon, Portugal, during November 6-9, 2023. The 28 full and 2 short papers were carefully reviewed and selected out of 53 submissions. Topics of interest span the entire spectrum of conceptual modeling, including research and practice in areas such as theories of concepts and ontologies, techniques for transforming conceptual models into effective implementations, and methods and tools for developing and communicating conceptual models. The following workshops are included in this volume: CMLS – 4th International Workshop on Conceptual Modeling for Life Sciences; CMOMM4FAIR – Third Workshop on Conceptual Modeling, Ontologies and (Meta)data Management for Findable, Accessible, Interoperable, and Reusable (FAIR) Data; EmpER – 6th International Workshop on Empirical Methods in Conceptual Modeling; JUSMOD – Second International Workshop on Digital Justice, Digital Law and Conceptual Modeling; OntoCom – 9th International Workshop on Ontologies and Conceptual Modeling; QUAMES – 4th International Workshop on Quality and Measurement of Model-Driven Software Development; SmartFood – First Workshop on Controlled Vocabularies and Data Platforms for Smart Food Systems. Table of Contents​CMLS: An Ontology for Breast Cancer Screening.- Integrating Nuclear Medicine and Radiopharmacy Data: A Conceptual Model for Precision Medicine and Enhanced Patient Care.- Comprehensive Representation of Variation Interpretation Data via Conceptual Modeling.- Enhancing Precision Medicine: An Automatic Pipeline Approach for Exploring Genetic Variant-Disease Literature.- CMOMM4FAIR: euFAIR: A Digital Tool for Assessing the FAIR Principles.- EmpER: Empirical Exploration of Open-Source Issues for Predicting Privacy Compliance.- Human-Centred Conceptual Modelling for Re-Designing Urban Planning.- Using Knowledge Graphs to Generate SQL Queries from Textual Specifications.- A Systematic Approach to Generate TOGAF Artifacts Founded on Multiple Data Sources and Ontology.- Bridging the Gap: Conceptual Modeling and Machine Learning for Web Portals.- JUSMOD: New-Generation Templates Facilitating the Shift from Documents to Data in the Italian Judiciary.- Supervised Learning, Explanation and Interpretation from Pretrial Detention Decisions by Italian and Brazilian Supreme Courts.- Few-Shot Legal Text Segmentation via Rewiring Conditional Random Fields: A Preliminary Study.- Identification and Visualization of Legal Definitions and Legal Term Relations.- Comparative Analysis of Disinformation Regulations: A Preliminary Analysis.- Privacy-Preserving Data Integration for Digital Justice.- Public Procurement Analysis with Process Discovery Techniques and Event Log Enrichment.- Formalising Legal Knowledge of Sri Lankan Civil Appellate High Court Domain from Ontological Perspective.- OntoCom: Towards Semantics for Abstractions in Ontology-Driven Conceptual Modeling.- Misalignments of Social and Numerical Identity – An Ontological Analysis.- Using an Ontology for Defining Semantics of Fractal Enterprise Model.- One Model to Rule Them All: A Demonstration of Ontology-Driven Minimum Viable Product Development for a Local Tourism Platform.- Enhancing Requirement-Information Mapping for Sustainable Buildings: Introducing the SFIR Ontology.- On the Use of ChatGPT for Classifying Domain Terms According to Upper Ontologies.- QUAMES: Exploring Understandability in Socio-Technical Models for Data Protection Analysis: Results from a Focus Group.- FlowTGE: Automating Functional Testing of Executable Business Process Models Based on BPMN.- An Approach Aligned with Model Driven Development to Evaluate the Quality of Explainable Artificial Intelligence.- SmartFood: Unveiling major Knowledge Organization Systems’ artifacts for Agriculture with network graphs.- Design Implications Towards Human-Centric Semantic Recommenders for Sustainable Food Consumption.- CoffeeWKG: A Weather Knowledge Graph for Coffee Regions in Colombia.

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Book SynopsisThis book constitutes the proceedings of the 22nd International Semantic Web Conference, ISWC 2023, which took place in October 2023 in Athens, Greece. The 58 full papers presented in this double volume were thoroughly reviewed and selected from 248 submissions. Many submissions focused on the use of reasoning and query answering, witha number addressing engineering, maintenance, and alignment tasks for ontologies. Likewise, there has been a healthy batch of submissions on search, query, integration, and the analysis of knowledge. Finally, following the growing interest in neuro-symbolic approaches, there has been a rise in the number of studies that focus on the use of Large Language Models and Deep Learning techniques such as Graph Neural Networks.

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Book SynopsisThis book constitutes the refereed proceedings of the XXIInd International Conference on AIxIA 2023 – Advances in Artificial Intelligence, AIxIA 2023, held in Rome, Italy, during November 6–10, 2023.The 33 full papers included in this book were carefully reviewed and selected from 53 submissions. They were organized in topical sections as follows: Argumentation and Logic Programming, Natural Language Processing, Machine Learning, Hybrid AI and Applications of AI.Table of Contents​Argumentation and Logic Programming.- ABALearn: An automated logic-based learning system for ABA frameworks.- Deriving Dependency Graphs from Abstract Argumentation Frameworks.- ReConf: An Automatic Context-based Software Reconfiguration Tool for Autonomous Vehicles using Answer-Set Programming.- Mining contrast sequential patterns with ASP.- Ontologies.- An ontological modelling of reason-based preferences.- A Defeasible Description Logic for Abduction.- Ontology-based Data Management in Healthcare: The Case of the Italian Arthroplasty Registry.- Planning.- A Structure-Sensitive Translation from Hybrid to Numeric Planning.- Intrinsically Motivated High-Level Planning for Agent Exploration.- Natural Language Processing.- Mining Argument Components in Essays at Different Levels.- Unraveling ChatGPT: A Critical Analysis of AI-Generated Goal-Oriented Dialogues and Annotations.- Scaling Large Language Models to the Extreme: Neural Semantic Processing of Multiple Tasks in Italian.- Named Entity Recognition and Linking for Entity Extraction from Italian Civil Judgements.- Machine Learning.- CENTAURO: an Explainable AI Approach for Customer Loyalty Prediction in Retail Sector.- Toward Novel Optimizers: A Moreau-Yosida View of Gradient-based Learning.- Mastering the Card Game of Jaipur through Zero-knowledge Self-Play Reinforcement Learning and Action Masks.- Uncovering Bias in the Face Processing Pipeline: An Analysis of Popular and State-of-the-Art Algorithms Across Demographic Groups.- A multi-label classification study for the prediction of long-covid syndrome.- PAUL-2: An Upgraded Transformer-Based Redesign of the Algorithmic Composer PAUL.- Robotics and Perception.- Understanding the Effect of Deep Ensembles in LiDAR-based Place Recognition.- Enanching LiDAR performance: Robust De-skewing Exclusively Relying o n Range Measurements.- Can Existing 3D Monocular Object Detection Methods Work in Roadside Contexts? A Reproducibility Study.- Embedding Shepard's Interpolation into CNN Models for Unguided Depth Completion.- Performance evaluation of depth completion neural networks for various RGB-D camera technologies in indoor scenario.- Hybrid AI.- Inference in Probabilistic Answer Set Programming under the Credal Semantics.- Efficient Modal Decision Trees.- Clique-TF-IDF: A New Partitioning Framework based on Dense Substructures.- Combining Contrastive Learning and Knowledge Graph Embeddings to develop medical word embeddings for the Italian language.- Applications of AI.- Recognizing the Style, Genre, and Emotion of a Work of Art Through Visual and Knowledge Graph Embeddings.- Combining genetic algorithms and temporal constraint satisfaction for recommending personalized tourist itineraries.- Towards Automatic Digitalization of Railway Engineering Schematics.- Election Manipulation in Social Networks with Single-Peaked Agents.- Learning to Prompt in the Classroom to Understand AI Limits: A pilot study.

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Book SynopsisThis three-volume set LNCS 14406-14408 constitutes the refereed proceedings of the 7th Asian Conference on Pattern Recognition, ACPR 2023, held in Kitakyushu, Japan, in November 2023. The 93 full papers presented were carefully reviewed and selected from 164 submissions. The conference focuses on four important areas of pattern recognition: pattern recognition and machine learning, computer vision and robot vision, signal processing, and media processing and interaction, covering various technical aspects.Table of Contentsartificial intelligence.- computer networks.- computer science.- computer systems.- computer vision.- databases.- education.- engineering.- image analysis.- image processing.- image segmentation.- internet learning.- machine learning.- mathematics.- neural networks.- object recognition.- pattern recognition semantics.- signal processing.

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Book SynopsisThis three-volume set LNCS 14406-14408 constitutes the refereed proceedings of the 7th Asian Conference on Pattern Recognition, ACPR 2023, held in Kitakyushu, Japan, in November 2023. The 93 full papers presented were carefully reviewed and selected from 164 submissions. The conference focuses on four important areas of pattern recognition: pattern recognition and machine learning, computer vision and robot vision, signal processing, and media processing and interaction, covering various technical aspects.Table of Contentsartificial intelligence.- computer networks.- computer science.- computer systems.- computer vision.- databases.- education.- engineering.- image analysis.- image processing.- image segmentation.- internet learning.- machine learning.- mathematics.- neural networks.- object recognition.- pattern recognition semantics.- signal processing.

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Book SynopsisThis two-volume set LNCS 14383 and LNCS 14384 constitutes the refereed proceedings of the 16th International Conference on Interactive Digital Storytelling, ICIDS 2023, held in Kobe, Japan, during November 11–15, 2023.The 30 full papers presented in this book together with 11 short papers were carefully reviewed and selected from 101 submissions. Additionally, the proceedings includes 22 Late Breaking Works.The papers focus on topics such as: theory, history and foundations; social and cultural contexts; tools and systems; interactive narrative design; virtual worlds, performance, games and play; applications and case studies; and late breaking works.Table of Contents​Virtual Worlds, Performance, Games and Play.- As If They Were Here: The Impact of Volumetric Video on Presence in Immersive Augmented Reality Storytelling Traversing Space in The Under Presents (2019), a VR Game.- ”It’s About What We Take With Us And What We Leave Behind”: Investigating the Transformative Potential of Pervasive Games with Various Stakeholders.- Communal Ritual Play: Repetition and Interpretation of Game Narratives Across Communities.- Bridging the gap between the physical and the virtual in tabletop role playing games: exploring immersive VR tabletops.- Circulation and Narrative in a Virtual Environment Detecting Player Preference Shifts in an Experience Managed Environment.- Applications and Case Studies.- ”Bury Me, My Love”: the boundary between reality and fiction in IDNs for smartphone.- Traversing boundaries when translating a literary IDN into several languages: a case study.- The Ethical Colonizer? Grand Strategy Games, Colonization, and New Ways of Engaging Moral Choices.- Gaming the System: Case Study in Investigative Journalism and Playful Interactive Narrative Design to Explain Systemic Bias in Immigration Policy.- Fostering Interdisciplinary Learning for Elementary Students through Developing Interactive Digital Stories.- Merging site recreation and museum exhibition in archaeology exhibition.- Teaching Interactive Digital Narrative Through Found Photography.- Late Breaking Works.- Figure of speech detection and generation as a service in IDN authoring support.- ChatGPT as a Narrative Structure Interpreter.- Curatorial Challenges of Exhibiting VR IDN’s in Film Festival Formats.- What really happened here? Dealing with uncertainty in The Book of Distance: a critical historiography perspective.- A theory-of-mind game for the early detection of frontotemporal dementia.- Towards Procedural Generation of Narrative Puzzles for Open World Games.- Mind Stories: a Story Making game - From Narrative Therapy to Interactive Narrative Therapy. Empathic Experiences of Visual Conditions with Virtual Reality.- The Chronicles of ChatGPT: Generating and Evaluating Visual Novel Narratives on Climate Change Through ChatGPT.- A Crossmedia Storytelling Platform to Empower Vulnerable Groups for IT Security.- Introducing the Comic Automaton: Interaction Design Options for an Interactive Comic for Higher Education.- Comic for Higher Education Dataset Collected Using Illustration Cards.- Analyzing Audience Comments: Improving Interactive Narrative with ChatGPT.- Integrating Storytelling and Making: A Case Study in Elementary School.- Designing a Language Model-Based Authoring Tool Prototype for Interactive Storytelling.- Alice Dali MR: A Mixed Reality Interactive Narrative Experience.- Exploring the Union Between Procedural Narrative and Procedural Content Generation.- A Design-Oriented Framework for Interactive Digital Narrative in Virtual Reality - Focus on Branching Narrative and Agency.- What Is Waiting for Us at the End? Inherent Biases of Game Story Endings in Large Language Models.- Breaking Bad: Unraveling Influences and Risks of User Inputs to ChatGPT for Game Story Generation.- Playing Story Creation Games With Large Language Models: Experiments With GPT-3.5.- Traversing language, the author, and the word in Amira Hanafi’s A Dictionary of the Revolution.

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Book SynopsisThis three-volume set LNCS 14406-14408 constitutes the refereed proceedings of the 7th Asian Conference on Pattern Recognition, ACPR 2023, held in Kitakyushu, Japan, in November 2023. The 93 full papers presented were carefully reviewed and selected from 164 submissions. The conference focuses on four important areas of pattern recognition: pattern recognition and machine learning, computer vision and robot vision, signal processing, and media processing and interaction, covering various technical aspects.Table of Contentsartificial intelligence.- computer networks.- computer science.- computer systems.- computer vision.- databases.- education.- engineering.- image analysis.- image processing.- image segmentation.- internet learning.- machine learning.- mathematics.- neural networks.- object recognition.- pattern recognition semantics.- signal processing.

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Book SynopsisThis book constitutes the refereed proceedings of the 5th Iberoamerican Conference and 4th Indo-American Conference on Knowledge Graphs and Semantic Web, KGSWC 2023, held jointly in Zaragoza, Spain, during November 13–15, 2023.The 18 full and 2 short papers presented were carefully reviewed and selected from 50 submissions. They focus on the following topics: knowledge representation; natural language processing/text mining; and machine/deep learning research.Table of ContentsAn ontology for Tuberculosis Surveillance System.- Should I Stay or Should I Go: A New Reasoner for Description Logic.- An Intelligent Article Knowledge Graph Formation Framework using BM25 Probabilistic Retrieval Model.- Defeasible Reasoning with Knowledge Graphs.- Recommendation of Learning Paths based on Open Educational Resources.- An enterprise architecture for interpersonal activity knowledge management.- Unlocking the Power of Semantic Interoperability in Industry 4.0: A Comprehensive Overview.- On the Representation of Dynamic BPMN Process Executions in Knowledge Graphs.- Towards a Framework for Seismic Data.- Using Pregel to create Knowledge Graphs subsets described by non-recursive Shape Expressions.- ITAQ : Image Tag Recommendation Framework for Aquatic Species integrating Semantic Intelligence via Knowledge Graph.- Automatic Semantic Typing of Pet E-Commerce Products Using Crowdsourced Reviews: An Experimental Study.- A Modular Ontology for MODS – Metadata Object Description Schema.- A Topic Model for the Data Web.- Automating the Generation of Competency Questions for Ontologies with AgOCQs.- KnowWhereGraph-Lite: A Perspective of the KnowWhereGraph.- Ontology-Based Models of Chatbots for Populating Knowledge Graphs.- An Ontology for Reasoning about Fairness in Regression and Machine Learning.- SCIVO: Skills to Career with Interests and Values Ontology.- Topic Modeling for Skill Extraction from Job Postings.

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Book SynopsisThis book constitutes the refereed proceedings of the 5th Multidisciplinary International Symposium on Disinformation in Open Online Media, MISDOOM 2023, which was held in Amsterdam, The Netherlands, during November 21–22, 2023.The 13 full papers presented in this book were carefully reviewed and selected from 19 submissions. The papers focus on misinformation, disinformation, hate speech, disinformation campaigns, social network analysis, large language models, generative AI, and multi-modal embeddings.Table of ContentsGenerative AI for Explainable Automated Fact Checking on the FactEx: a New Benchmark Dataset.- Multi-Modal Embeddings for Isolating Cross-Platform Coordinated Information Campaigns on Social Media.- faKy: A Feature Extraction Library to Detect the Truthfulness of a Text.- From sharing misinformation to debunking it: How Coordinated Image Text Sharing Behaviour is used in political campaigns on Facebook.- The Information Disorder Level (IDL) Index: A Human-Based Metric to Assess the Factuality of Machine-Generated Content.- Lost in Transformation: Rediscovering LLM-generated Campaigns in Social Media.- The Effect of Misinformation Intervention: Evidence from Trump’s Tweets and the 2020 Election.- Coordinated Information Campaigns on Social Media: A Multifaceted Framework for Detection and Analysis.- Unveiling Truth Amidst the Pandemic: Multimodal Detection of COVID-19 Unreliable News.- Holistic Analysis of Organised Misinformation Activity in Social Networks.- Towards Multimodal Campaign Detection: Including Image Information in Stream Clustering to Detect Social Media Campaigns.- ChatGPT as a commenter to the news: can LLMs generate human-like opinions?.- Is foreign language news more or less credible than native language news? Examining the foreign language effect on credibility perceptions.

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Book SynopsisThe two-volume proceedings set LNAI 14338 and 14339 constitutes the refereed proceedings of the 25th International Conference on Speech and Computer, SPECOM 2023, held in Dharwad, India, during November 29–December 2, 2023.The 94 papers included in these proceedings were carefully reviewed and selected from 174 submissions. They focus on all aspects of speech science and technology: ​automatic speech recognition; computational paralinguistics; digital signal processing; speech prosody; natural language processing; child speech processing; speech processing for medicine; industrial speech and language technology; speech technology for under-resourced languages; speech analysis and synthesis; speaker and language identification, verification and diarization.Table of Contents​Industrial Speech and Language Technology.- Analysing Breathing Patterns in Reading and Spontaneous Speech.- Audio-Visual Speaker Verification via Joint Cross Attention.- A Novel Scheme to Classify Read and Spontaneous Speech.- Analysis of a Hinglish ASR System’s Performance for Fraud Detection.- Anomaly Detection in Speech: A Comprehensive Approach for Enhanced Speech Analysis.- CAPTuring Accents: An Approach to Personalize Pronunciation Training for Learners with Different L1 Backgrounds.- Speech Technology for Under-Resourced Languages.- Improvements in Language Modeling, Voice Activity Detection, and Lexicon in OpenASR21 Low Resource Languages.- Phone Durations Modeling for Livvi-Karelian ASR.- Significance of Indic Self-Supervised Speech Representations for Indic Under-Resourced ASR.- Study of Various End-to-End Keyword Spotting Systems on the Bengali language under Low-Resource Condition.- Bridging the Gap: Towards Linguistic Resource Development for the Low-Resource Lambani Language.- Studying the Effect of Frame-Level Concatenation of GFCC and TS-MFCC Features on Zero-Shot Children’s ASR.- Code-Mixed Text-to-Speech Synthesis under Low-Resource Constraints.- An End-to-End TTS Model in Chhattisgarhi, a Low-Resource Indian Language.- An ASR Corpus in Chhattisgarhi, a Low Resource Indian Language.- Cross Lingual Style Transfer using Multiscale Loss Function for Soliga: A Low Resource Tribal Language.- Preliminary Analysis of Lambani Vowels and Vowel Classification using Acoustic Feature.- Curriculum Learning based Approach for Faster Convergence of TTS Model.- Rhythm Measures and Language Endangerment: the Case of Deori.- Konkani Phonetic Transcription System 1.0.- Speech Analysis and Synthesis.- E-TTS: Expressive Text-to-Speech Synthesis for Hindi using Data Augmentation.- Direct vs Cascaded Speech-to-Speech Translation using Transformer.- Deep Learning based Speech Quality Assessment Focusing on Noise Effects.- Quantifying the Emotional Landscape of Music with Three Dimensions.- Analysis of Mandarin vs. English Language for Emotional Voice Conversion.- Audio DeepFake Detection Employing Multiple Parametric Exponential Linear Units.- A Comparison of Learned Representations with Jointly Optimized VAE and DNN for Syllable Stress Detection.- On the Asymptotic Behaviour of the Speech Signal.- Improvement of Audio-Visual Keyword Spotting System Accuracy using Excitation Source Feature.- Developing a Question Answering System on the material of Holocaust survivors’ testimonies in Russian.- Enhancing Children’s Short Utterance based ASV using Data Augmentation Techniques and Feature Concatenation Approach.- Studying the Effectiveness of Data Augmentation and Frequency-Domain Linear Prediction Coefficients in Children’s Speaker Verification under Low-Resource Conditions.- Constant-Q based Harmonic and Pitch Features for Normal vs Pathological Infant Cry Classification.- Robustness of Whisper Features for Infant Cry Classification.- Speaker and Language Identification, Verification, and Diarization.- I-MSV 2022: Indic-Multilingual and Multi-Sensor Speaker Verification Challenge.- Multi-Task Learning over Mixup Variants for the Speaker Verification Task.- Exploring the Impact of Different Approaches for Spoken Dialect Identification of Konkani Language.- Adversarially Trained Hierarchical Attention Network for Domain-Invariant Spoken Language Identification.- Ensemble of Incremental System Enhancements for Robust Speaker Diarization in Code-Switched Real-Life Audios.- Enhancing Language Identification in Indian Context through Exploiting Learned Features with Wav2Vec2.0.- Design and Development of Voice OTP Authentication System.- End-to-End Native Language Identification using a Modified Vision Transformer(ViT) from L2 English Speech.- Dialect Identification in Ao using Modulation-based Representation.- Self-Supervised Speaker Verification Employing Augmentation Mix and Self-Augmented Training-based Clustering.

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