10756nam 22004693 450 99660156080331620240603084507.03-031-61137-3(MiAaPQ)EBC31359060(Au-PeEL)EBL31359060(CKB)32200397700041(EXLCZ)993220039770004120240603d2024 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierBioinspired Systems for Translational Applications 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, Olhâo, Portugal, June 4-7, 2024, Proceedings, Part II1st ed.Cham :Springer,2024.©2024.1 online resource (553 pages)Lecture Notes in Computer Science Series ;v.146753-031-61136-5 Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Machine Learning in Computer Vision and Robotics -- Unsupervised Detection of Incoming and Outgoing Traffic Flows in Video Sequences -- 1 Introduction -- 2 Methodology -- 3 Experimental Results -- 3.1 Methods -- 3.2 Datasets -- 3.3 Results -- 4 Conclusions -- References -- A Decentralized Collision Avoidance Algorithm for Individual and Collaborative UAVs -- 1 Introduction -- 2 State of Art -- 3 Methodology -- 3.1 Collision Avoidance -- 3.2 System Formation -- 4 Experiments and Results -- 5 Conclusions -- References -- Improved Surface Defect Classification from a Simple Convolutional Neural Network by Image Preprocessing and Data Augmentation -- 1 Introduction -- 2 Materials -- 2.1 The NEU Dataset -- 2.2 Image Preprocessing -- 2.3 Data Augmentation -- 3 Methodology -- 3.1 Simple Convolutional Neural Network -- 3.2 Training Strategy -- 4 Results and Discussion -- 5 Conclusions -- References -- Prediction of Optimal Locations for 5G Base Stations in Urban Environments Using Neural Networks and Satellite Image Analysis -- 1 Introduction -- 2 Methodology -- 2.1 Segmentation of Satellite Images -- 2.2 Base Station Deployment -- 3 Experiments -- 3.1 Convolutional Neural Networks -- 3.2 Dataset -- 3.3 Evaluation -- 3.4 Results -- 4 Conclusions -- References -- Enhanced Cellular Detection Using Convolutional Neural Networks and Sliding Window Super-Resolution Inference*-6pt -- 1 Introduction -- 2 Methodology -- 3 Experiments -- 3.1 Dataset -- 3.2 Super-Resolution Model -- 3.3 Object Detection Models -- 3.4 Results -- 4 Conclusions and Future Lines -- References -- Exploring Text-Driven Approaches for Online Action Detection -- 1 Introduction -- 2 Related Works -- 2.1 Online Action Detection -- 2.2 Vision-Language Models -- 3 Methodology -- 4 Experiments.4.1 Experimental Setup -- 4.2 Zero-Shot/Few-Shot Action Detection -- 4.3 Comparison with State-of-the-Art Methods -- 5 Conclusion -- References -- Deep Learning for Assistive Decision-Making in Robot-Aided Rehabilitation Therapy -- 1 Introduction -- 2 Materials and Methods -- 2.1 Subjects -- 2.2 Experimental Setup and Data Collection -- 2.3 Data Processing -- 2.4 Model Architecture -- 3 Results and Discussion -- 4 Conclusion -- References -- Text-Driven Data Augmentation Tool for Synthetic Bird Behavioural Generation -- 1 Introduction -- 2 Related Works -- 2.1 Birds Datasets -- 2.2 Generative Models -- 3 Synthetic Video Generation -- 3.1 Enhancing Captions -- 3.2 Generative Video Models -- 4 Results -- 5 Conclusions -- References -- Deep Learning for Enhanced Risk Assessment in Home Environments -- 1 Introduction -- 2 Related Work -- 2.1 Risks Assessment -- 2.2 Object Detection -- 2.3 Video Captioning -- 3 Methodology -- 3.1 Objects Extraction -- 3.2 Risks Identification -- 4 Experiments -- 4.1 Setup and Data -- 4.2 Results -- 5 Conclusion -- References -- Lightweight CNNs for Advanced Bird Species Recognition on the Edge -- 1 Introduction -- 2 Related Works -- 2.1 Bird Species Recognition -- 2.2 Edge Computing -- 3 Methodology -- 3.1 Datasets -- 3.2 Training -- 4 Experiments -- 4.1 Setup -- 4.2 Results -- 5 Conclusion -- References -- Learning Adaptable Utility Models for Morphological Diversity -- 1 Introduction -- 2 Motivational System for Open-Ended Learning -- 2.1 Novelty-Based Intrinsic Motivation. Enhancing Exploration -- 2.2 Frustration-Based Intrinsic Motivation. Preventing Learning Stagnation -- 3 Deliberative Decision-Making with World and Utility Models -- 3.1 World Model Learning -- 3.2 Utility Model Learning -- 4 Experimental Setup: EMERGE Robot -- 5 Experimental Results -- 6 Conclusion -- References.Deep Learning-Based Classification of Invasive Coronary Angiographies with Different Patch-Generation Techniques -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Data Preprocessing -- 3 Experimental Results -- 3.1 Training and Experiments Description -- 3.2 Results -- 4 Conclusions -- References -- Bio-inspired Computing Approaches -- Refinement of Protein Structures with a Memetic Algorithm. Examples with SARS-CoV-2 Proteins -- 1 Introduction -- 2 Methods -- 2.1 Rosetta Relax Process -- 2.2 Relax-DE -- 3 Results -- 3.1 Setup of the Refinement Approaches -- 3.2 Refinement of Predicted Structures -- 4 Conclusions -- References -- Evolutionary Algorithms for Bin Packing Problem with Maximum Lateness and Waste Minimization -- 1 Introduction -- 2 Problem Definition -- 3 The Solution Method -- 4 Evolutionary Algorithms -- 4.1 Genetic Programming -- 4.2 Genetic Algorithm -- 5 Experimental Analysis -- 5.1 Set up -- 5.2 Results -- 6 Conclusions and Future Work -- References -- Stationary Wavelet Entropy and Cat Swarm Optimization to Detect COVID-19 -- 1 Introduction -- 2 Background -- 3 Dataset -- 4 Methodology -- 4.1 Feed-Forward Neural Network -- 4.2 Stationary Wavelet Entropy -- 4.3 Cat Swarm Optimization -- 4.4 K-Fold Cross-Validation -- 4.5 Evaluation -- 5 Experiment and Discussion -- 5.1 Statistical Evaluation -- 5.2 Comparison to State-of-the-Art Methods -- 5.3 ROC Curve -- 6 Conclusion and Future Research -- References -- Private Inference on Layered Spiking Neural P Systems -- 1 Introduction -- 2 Related Work -- 3 Layered Spiking Neural P Systems -- 4 Private Inference -- 4.1 The Protocol -- 4.2 Security Discussion -- 5 Conclusions and Further Directions of Research -- References -- Cooperative Multi-fitness Evolutionary Algorithm for Scientific Workflows Scheduling -- 1 Introduction -- 2 The Scientific Workflow Scheduling Model.2.1 Workflow Scheduling Problem Overview -- 3 Overview of the Genetic Algorithm Approach -- 4 Cooperative Multi-fitness Functions Evaluation -- 5 Experimental Study -- 5.1 Benchmark Instances -- 5.2 Benchmark Platform -- 5.3 Efficiency of the Cooperative Multi-fitness Approach -- 6 Conclusion -- References -- A Genetic Approach to Green Flexible Job Shop Problem Under Uncertainty -- 1 Introduction -- 2 Problem Definition -- 3 Solving Methodology -- 4 Experimental Results -- 5 Conclusion -- References -- Social and Civil Engineering Through Human AI Translations -- AI Emmbedded in Drone Control -- 1 Introduction -- 2 Drone Operations Supported by AI Algorithms -- 2.1 Delivery Systems -- 2.2 Optimization and Complexity Associated with Cargo and Resources -- 2.3 Emergency Situations -- 2.4 Drone Identification and Detection -- 2.5 Flight Control and Safety -- 2.6 Agricultural Operations -- 3 Conclusions and Future Work -- References -- Dual-System Recommendation Architecture for Adaptive Reading Intervention Platform for Dyslexic Learners -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data and Exploratory Analysis -- 2.2 Description of the Intervention Trial -- 2.3 Word Generator -- 2.4 Embedded Intra/Inter-user Recommender Engines -- 2.5 Surmounting Cold Start and Limited Data Hurdles -- 3 Results -- 4 Conclusions -- References -- Accurate LiDAR-Based Semantic Classification for Powerline Inspection -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Online Segmentation -- 3.2 Full Map Refinement -- 4 Validation -- 5 Conclusions -- References -- RESISTO Project: Automatic Detection of Operation Temperature Anomalies for Power Electric Transformers Using Thermal Imaging -- 1 Introduction -- 1.1 Introduction to the RESISTO Project -- 1.2 Mitigating Transformer Risks in Electricity Networks -- 2 Materials and Methods.2.1 Thermographic Data Acquisition -- 2.2 Thermal Anomalies Detection System -- 2.3 Synthetic Data Generation -- 3 Results and Discussion -- 3.1 Simulation Results -- 3.2 Registered Temperature Time Series -- 4 Conclusions -- References -- RESISTO Project: Safeguarding the Power Grid from Meteorological Phenomena -- 1 Introduction -- 1.1 Objectives -- 1.2 Project Innovations -- 2 Proposed Solution -- 2.1 Electrical Resilience Platform: GridWatch -- 2.2 Automatic Detection of Operation Temperature Anomalies Using Thermal Imaging -- 2.3 Fleet of Drones -- 3 Discussion -- 4 Conclusions -- References -- Multi-UAV System for Power-Line Failure Detection Within the RESISTO Project -- 1 Introduction -- 2 System Description -- 2.1 Planner Description -- 2.2 Software Implementation -- 2.3 Hardware Implementation -- 3 Validation -- 3.1 Planning Approach Simulation -- 3.2 Test Flights -- 4 Conclusions and Future Works -- References -- Smart Renewable Energies: Advancing AI Algorithms in the Renewable Energy Industry -- Machine Learning Health Estimation for Lithium-Ion Batteries Under Varied Conditions -- 1 Introduction -- 2 Methods -- 2.1 Experimental Design and Data Processing -- 3 Results and Discussion -- 4 Conclusions -- References -- Energy Flux Prediction Using an Ordinal Soft Labelling Strategy -- 1 Introduction -- 2 Data Description and Processing -- 2.1 Buoys Measurements and Reanalysis Data -- 2.2 Obtaining Ordinal Labels -- 3 Experimental Settings -- 3.1 Compared Methodologies -- 3.2 Model Training -- 4 Results and Discussion -- 5 Conclusions -- References -- Medium- and Long-Term Wind Speed Prediction Using the Multi-task Learning Paradigm -- 1 Introduction -- 2 Data Description -- 2.1 Wind Speed Data -- 2.2 Predictive Variables -- 3 Multi-task Artificial Neural Networks -- 4 Experimental Settings -- 5 Results and Discussion -- 6 Conclusions.References.Lecture Notes in Computer Science SeriesFerrández Vicente José Manuel1740228Val Calvo Mikel1740229Adeli Hojjat784299MiAaPQMiAaPQMiAaPQBOOK996601560803316Bioinspired Systems for Translational Applications4165664UNISA03689nam 2200709 a 450 991095685450332120200520144314.01-282-16299-3978661216299290-272-9876-910.1075/slcs.46(CKB)1000000000579102(EBL)622229(OCoLC)665835070(SSID)ssj0000276899(PQKBManifestationID)11237842(PQKBTitleCode)TC0000276899(PQKBWorkID)10226508(PQKB)11585315(MiAaPQ)EBC622229(DE-B1597)720073(DE-B1597)9789027298768(EXLCZ)99100000000057910219990113d1999 uy 0engur|n|---|||||txtccrAnimacy and reference a cognitive approach to corpus linguistics /Mutsumi Yamamoto1st ed.Amsterdam ;Philadelphia J. Benjamins Pub.c19991 online resource (299 p.)Studies in language companion series,0165-7763 ;v. 46Description based upon print version of record.1-55619-932-5 90-272-3049-8 Includes bibliographical references and index.Ch. 1. What is 'Animacy'? --Ch. 2. What Does Animacy Do to Human Language? --Ch. 3. Hierarchy of Persons and Animacy in English and Japanese --Ch. 4. Degree of Individuation and Encoding of Animacy --Ch. 5. Agency and Animacy --Ch. 6. A Neverending Story of Animacy --Appendix. Lists of Human/Animate Noun Phrases in Corpus. Case Study 1. Yukio Mishima, Hyaku-man Yen Senbei ('One Million Yen Rice Cracker' or 'Three Million Yen'). Case Study 2. Agatha Christie, Murder on the Orient Express. Case Study 3. Asahi Shinbun and Asahi Evening News. Case Study 4. Newsweek. Case Study 5. The Transactions of the Institute of Electronics, Information and Communication Engineers and Systems and Computers in Japan. Case Study 6. Scientific American. Case Study 7. 'Tetsuko no Heya'. Case Study 8. Viewpoints.The concept of 'animacy' concerns the fundamental and cognitive question of the extent to which we recognize and express living things as saliently human-like or animal-like.In Animacy and Reference Mutsumi Yamamoto pursues two main objectives: First, to establish a conceptual framework of animacy, and secondly, to explain how the concept of animacy can be reflected in the use of referential expressions. Unlike previous studies on the subject focussing on grammatical manifestations, Animacy and Reference sheds light upon the conceptual properties of animacy itself and its rStudies in language companion series ;v. 46.Grammar, Comparative and generalAnimacyReference (Linguistics)English languageAnimacyJapanese languageAnimacyEnglish languageGrammar, ComparativeJapaneseJapanese languageGrammar, ComparativeEnglishGrammar, Comparative and generalAnimacy.Reference (Linguistics)English languageAnimacy.Japanese languageAnimacy.English languageGrammar, ComparativeJapanese.Japanese languageGrammar, ComparativeEnglish.415Yamamoto Mutsumi1942-673584MiAaPQMiAaPQMiAaPQBOOK9910956854503321Animacy and reference1273663UNINA