LEADER 11129nam 2200565 450 001 996464444503316 005 20231110231816.0 010 $a3-030-89820-2 035 $a(CKB)4950000000280570 035 $a(MiAaPQ)EBC6788038 035 $a(Au-PeEL)EBL6788038 035 $a(OCoLC)1281957733 035 $a(PPN)258296488 035 $a(EXLCZ)994950000000280570 100 $a20220713d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in soft computing $e20th Mexican international conference on artificial intelligence, MICAI 2021, Mexico City, Mexico, October 25-30, 2021, proceedings, part II /$fIldar Batyrshin, Alexander Gelbukh and Grigori Sidorov 210 1$aCham, Switzerland :$cSpringer,$d[2021] 210 4$d©2021 215 $a1 online resource (380 pages) 225 1 $aLecture Notes in Computer Science ;$vv.13068 311 $a3-030-89819-9 327 $aIntro -- Preface -- Conference Organization -- Contents - Part II -- Contents - Part I -- Natural Language Processing Supervised -- Supervised Machine Learning for Automatic Assessment of Free-Text Answers -- 1 Introduction -- 2 Related Work -- 3 Our Methodology -- 4 Experimental Results -- 4.1 RQ1 Coverage: How Many Answers Can Be Automatically Assessed? -- 4.2 RQ2 Accuracy: How Accurate Is the Suggested Assessment? -- 5 Conclusion and Future Work -- References -- Towards Multilingual Image Captioning Models that Can Read -- 1 Introduction -- 2 State of the Art -- 2.1 Summary of the State-of-the-Art -- 3 Data and Methods -- 3.1 TextCaps Dataset -- 3.2 Automatic Translation of TextCaps -- 3.3 M4C-Captioner -- 3.4 Multilingual M4C-Captioner -- 3.5 Experimental Setup -- 4 Results -- 5 Conclusions and Future Work -- 6 Declarations -- References -- Best Paper Award, Second Place -- Question Answering for Visual Navigation in Human-Centered Environments -- 1 Introduction -- 2 Related Works -- 3 HISNav VQA Dataset -- 3.1 Images -- 3.2 Human-Asked Questions -- 3.3 Synthetic Questions -- 3.4 Dataset Analysis -- 4 Vector Semiotic Architecture Baseline -- 5 Experiments -- 5.1 Neural Network Baseline -- 5.2 Vector Semiotic Architecture -- 6 Discussion -- 7 Conclusion -- A Appendix: Data Labeling -- B Appendix: Examples -- References -- Improving a Conversational Speech Recognition System Using Phonetic and Neural Transcript Correction -- 1 Introduction -- 2 Background -- 3 Approach and Implementation -- 4 NLU Preprocessing Module -- 4.1 Phonetic Correction -- 4.2 Neural Classification Module -- 5 Experiments -- 6 Results and Discussion -- 7 Conclusions and Future Work -- References -- Estimation of Imageability Ratings of English Words Using Neural Networks -- 1 Introduction -- 2 Data and Method -- 3 Result -- 4 Result Interpretation -- 5 Conclusion. 327 $aReferences -- Hypernyms-Based Topic Discovery Using LDA -- 1 Introduction -- 2 Preliminaries -- 2.1 Latent Dirichlet Allocation -- 2.2 Latent Semantic Analysis -- 2.3 Probabilistic Latent Semantic Analysis -- 2.4 WordNet -- 3 Related Work -- 4 The Proposed Method -- 4.1 Datasets -- 5 Results -- 5.1 Experimental Results -- 6 Conclusions -- References -- Virality Prediction for News Tweets Using RoBERTa -- 1 Introduction -- 2 Related Works -- 3 Our Method -- 3.1 Corpus -- 3.2 Tweet Influence Formula -- 3.3 Method Overview -- 3.4 Method Description -- 4 Results and Discussion -- 4.1 Results -- 4.2 Findings -- 5 Conclusion -- References -- Sentiment Analysis on Twitter About COVID-19 Vaccination in Mexico -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Extraction -- 3.2 Data Transformation and Export Resulting Dataset -- 3.3 Data Labeling -- 3.4 Text Processing and Feature Extraction -- 3.5 Machine Learning Models -- 3.6 Experiments -- 3.7 Machine Learning Model Selection -- 4 Results and Discussion -- 5 Conclusions -- References -- Text-Independent Speaker Identification Using Formants and Convolutional Neural Networks -- 1 Introduction -- 2 Previous Work -- 3 Proposal -- 3.1 Converting Speech Signals into Images Disregarding Time -- 3.2 Convolutional Neural Network (CNN) -- 4 Experiments -- 5 Conclusions and Future Work -- References -- Nahuatl Neural Machine Translation Using Attention Based Architectures: A Comparative Analysis for RNNs and Transformers as a Mobile Application Service -- 1 Introduction -- 2 State of the Art -- 2.1 How Big is Nahuatl? -- 2.2 NMT Related Works -- 2.3 NLP Nahuatl Related Works -- 2.4 Related Nahuatl and Translation Services -- 3 Models Description -- 3.1 Nahuatl -- 3.2 Bi-directional Recurrent Neural Network Plus Attention -- 3.3 Transformer -- 3.4 Bilingual Evaluation Understudy and FuzzyWuzzy. 327 $a3.5 Axolotl -- 3.6 JW -- 3.7 SentencePiece Tokenization -- 3.8 Main Technologies -- 4 Implementation and Experiments -- 4.1 RNN -- 4.2 Transformer -- 4.3 The Application -- 4.4 Model Evaluation and Comparative -- 4.5 Comparatives Among and with Another Models -- 4.6 Emerging Behaviors -- 5 Conclusions -- 5.1 Future Work -- References -- STClass: A Method for Determining the Sensitivity of Documents -- 1 Introduction -- 2 Related Work -- 3 STClass: Method for Determining the Sensitivity of Documents -- 4 Datasets and Experimental Methodology -- 5 Conclusion -- References -- Plagiarism Detection in Students' Answers Using FP-Growth Algorithm -- 1 Introduction -- 2 Related Works -- 3 Dataset and Features -- 4 Methodology -- 5 Experiment -- 6 Results -- 7 Conclusion -- 8 Future Work -- References -- Determining the Relationship Between the Letters in the Voynich Manuscript Splitting the Text into Parts -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Experiment -- 5 Result -- 6 Conclusion -- References -- Intelligent Applications and Robotics -- The Comparative Approach to Solving Temporal-Constrained Scheduling Problem Under Uncertainty -- 1 Introduction -- 2 Solving the Problem of Network Activity Planning in a Non-fuzzy Formulation -- 3 Solving the Problem of Network Planning in a Probabilistic Formulation -- 4 Solution of the Problem of Network Activity Planning in Fuzzy-Interval Formulation -- 5 Conclusion -- References -- A Tourist Recommendation System: A Study Case in Mexico -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Collection -- 3.2 Collaborative-Based Filtering -- 3.3 Demographic-Based Filtering -- 4 Experimental Results -- 5 Conclusions and Future Work -- References -- Detecting Traces of Self-harm in Social Media: A Simple and Interpretable Approach -- 1 Introduction. 327 $a2 gSC: A One-Class Approach for Detecting Mental Disorders -- 2.1 Mass Assignment to Users -- 3 Experimental Settings -- 3.1 Dataset -- 3.2 Text Representations -- 3.3 Self-harm Vocabulary for Mass Calculation -- 3.4 Parameters' Tuning -- 4 Results -- 4.1 Error Analysis -- 5 Decision-Making Support Tool -- 6 Conclusions -- References -- Finite-Field Parallel Adder Circuit Over Prime Numbers Based on Spiking Neural P Systems -- 1 Introduction -- 2 An Introduction to the Finite-Field Addition Over GF(p) -- 3 Proposal of a Finite-Field Neural Adder Circuit -- 4 Experiment and Results -- 5 Conclusions and Future Work -- References -- A Rapid HMI Prototyping Based on Personality Traits and AI for Social Connected Thermostats -- 1 Introduction -- 2 Material and Methods -- 2.1 New Dataset Creation as a Result of the Survey -- 3 Methodology -- 3.1 Two-Layer Feed-Forward ANN Classification -- 3.2 Rapid Prototyping Using Arduino UNO and MATLAB/Simulink -- 4 Proposed Framework -- 4.1 Knowledge Base -- 4.2 Decision System -- 4.3 Evaluation -- 5 Results: Arduino Prototype -- 6 Discussion -- 7 Conclusion -- References -- Machine Learning Framework for Antalgic Gait Recognition Based on Human Activity -- 1 Introduction -- 1.1 Related Work -- 1.2 Problem Statement and Solution Proposal -- 1.3 Paper Organization -- 2 Antalgic Gait Recognition Framework -- 2.1 Data Acquisition -- 2.2 Preprocessing -- 2.3 Feature Extraction and Selection -- 2.4 Training Model -- 2.5 Classification -- 3 Results and Discussion -- 4 Conclusions -- References -- A New Approach for the Automatic Connection of Sensors to an IoT Platform -- 1 Introduction -- 2 Background and Related Work -- 2.1 Internet of Things -- 2.2 FIWARE Platform -- 2.3 Related Work -- 3 Overview of Our Approach Proposed -- 4 Our Approach for the Automatic Connection of Sensors to an IoT Platform. 327 $a4.1 Management Module -- 4.2 Code Generation Module for Communication with FIWARE -- 4.3 Code Generation Module for Capturing Data from Sensors -- 5 Software System for the Automatic Connection of Sensor to FIWARE IoT Platform -- 6 Conclusions and Future Work -- References -- A Hybrid Model for the Prediction of Air Pollutants Concentration, Based on Statistical and Machine Learning Techniques -- 1 Introduction -- 2 Methodology -- 2.1 Data -- 2.2 AI/ML Methods -- 3 Results -- 3.1 PM10 -- 3.2 PM2.5 -- 3.3 O3 -- 4 Summary and Conclusions -- References -- Mexican Automotive Industry Sales Behavior During the COVID-19 Pandemic -- 1 Introduction -- 2 Related Work -- 3 Description of the Proposal -- 3.1 Exploration of Variables and Data Sources -- 3.2 Model Analysis and Selection -- 3.3 Experimentation -- 4 Results and Discussion -- 5 Conclusions -- References -- Modeling Self-efficacy and Self-regulated Learning in Gamified Learning Environments Through Educational Data Mining -- 1 Introduction -- 2 Data Mining in Education -- 3 ITS and Gamification -- 4 Data-Driven Construction of a Gamified ITS -- 5 Conclusions and Future Work -- References -- Parallelization of the Array Method Using OpenMP -- 1 Introduction -- 1.1 Contributions of the Paper -- 2 Basic Definitions -- 3 Related Works -- 3.1 Parallel Application Design -- 4 Array Method Parallelization Using OpenMP -- 4.1 Arrays of the Array Method -- 5 Results -- 5.1 Experiments to Evaluate the Makespan Metric -- 5.2 Experiments to Evaluate the Waiting Time Metric -- 5.3 Experiments to Evaluate the Quality of Assignments When Experimenting with the Makespan Metric -- 5.4 Time to Search for Resources in the Clusters for the Assignment of Tasks -- 6 Conclusions -- 7 Future Works -- References -- Best Paper Award, Third Place -- Sign Language Translation Using Multi Context Transformer -- 1 Introduction. 327 $a2 Related Work. 410 0$aLecture Notes in Computer Science 606 $aSoft computing 606 $aSoft computing$vCongresses 606 $aArtificial intelligence 615 0$aSoft computing. 615 0$aSoft computing 615 0$aArtificial intelligence. 676 $a006.3 700 $aBatyrshin$b I. Z$g(Il?dar Zakirzi?anovich),$01250755 702 $aSidorov$b Grigori 702 $aGelbukh$b Alexander 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996464444503316 996 $aAdvances in soft computing$92899379 997 $aUNISA LEADER 03649oam 2200733Ka 450 001 9910779750303321 005 20190503073414.0 010 $a0-262-31268-9 010 $a0-262-52748-0 010 $a0-262-31267-0 035 $a(CKB)2550000001094493 035 $a(EBL)3339630 035 $a(SSID)ssj0000915477 035 $a(PQKBManifestationID)11506854 035 $a(PQKBTitleCode)TC0000915477 035 $a(PQKBWorkID)10868664 035 $a(PQKB)10733900 035 $a(CaBNVSL)mat06554353 035 $a(IDAMS)0b00006481dbdd45 035 $a(IEEE)6554353 035 $a(OCoLC)849928726 035 $a(MdBmJHUP)muse46464 035 $a(OCoLC)849928726$z(OCoLC)851157227$z(OCoLC)868204323$z(OCoLC)881288837$z(OCoLC)923251995$z(OCoLC)964598875 035 $a(OCoLC-P)849928726 035 $a(MaCbMITP)8009 035 $a(Au-PeEL)EBL3339630 035 $a(CaPaEBR)ebr10722732 035 $a(CaONFJC)MIL500050 035 $a(OCoLC)923251995 035 $a(MiAaPQ)EBC3339630 035 $a(PPN)259020672 035 $a(EXLCZ)992550000001094493 100 $a20130624d2013 uy 0 101 0 $aeng 135 $aur|||||||nn|n 181 $ctxt 182 $cc 183 $acr 200 00$aComputability $eTuring, Go?del, Church, and beyond /$fedited by Jack Copeland, Carl Posy, and Oron Shagrir 210 $aCambridge, Massachusetts $cThe MIT Press$d[2013] 215 $a1 online resource (373 p.) 300 $aDescription based upon print version of record. 311 $a0-262-01899-3 311 $a1-299-68800-4 320 $aIncludes bibliographical references and index. 327 $a""11 Is Quantum Mechanics Falsifiable? A Computational Perspective on the Foundations of Quantum Mechanics""""About the Authors""; ""Index"" 330 3 $a"In the 1930s a series of seminal works published by Alan Turing, Kurt Go?del, Alonzo Church, and others established the theoretical basis for computability. This work, advancing precise characterizations of effective, algorithmic computability, was the culmination of intensive investigations into the foundations of mathematics. In the decades since, the theory of computability has moved to the center of discussions in philosophy, computer science, and cognitive science. In this volume, distinguished computer scientists, mathematicians, logicians, and philosophers consider the conceptual foundations of computability in light of our modern understanding. Some chapters focus on the pioneering work by Turing, Go?del, and Church, including the Church-Turing thesis and Go?del's response to Church's and Turing's proposals. Other chapters cover more recent technical developments, including computability over the reals, Go?del's influence on mathematical logic and on recursion theory and the impact of work by Turing and Emil Post on our theoretical understanding of online and interactive computing; and others relate computability and complexity to issues in the philosophy of mind, the philosophy of science, and the philosophy of mathematics." 606 $aComputational complexity 606 $aMathematics$xPhilosophy 610 $aCOMPUTER SCIENCE/General 610 $aMATHEMATICS & STATISTICS/General 610 $aPHILOSOPHY/General 615 0$aComputational complexity. 615 0$aMathematics$xPhilosophy. 676 $a511.3/52 702 $aCopeland$b B. Jack$f1950- 702 $aPosy$b Carl J. 702 $aShagrir$b Oron$f1961- 801 0$bOCoLC-P 801 1$bOCoLC-P 906 $aBOOK 912 $a9910779750303321 996 $aComputability$93844499 997 $aUNINA