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Titolo: |
Applied Technologies : First International Conference, ICAT 2019, Quito, Ecuador, December 3–5, 2019, Proceedings, Part II / / edited by Miguel Botto-Tobar, Marcelo Zambrano Vizuete, Pablo Torres-Carrión, Sergio Montes León, Guillermo Pizarro Vásquez, Benjamin Durakovic
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Pubblicazione: | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
Edizione: | 1st ed. 2020. |
Descrizione fisica: | 1 online resource (XX, 669 p. 389 illus., 325 illus. in color.) |
Disciplina: | 005.7 |
004 | |
Soggetto topico: | Computers |
Architecture, Computer | |
Machine learning | |
Computer communication systems | |
Optical data processing | |
Application software | |
Information Systems and Communication Service | |
Computer System Implementation | |
Machine Learning | |
Computer Communication Networks | |
Computer Imaging, Vision, Pattern Recognition and Graphics | |
Computer Applications | |
Persona (resp. second.): | Botto-TobarMiguel |
Zambrano VizueteMarcelo | |
Torres-CarriónPablo | |
Montes LeónSergio | |
Pizarro VásquezGuillermo | |
DurakovicBenjamin | |
Nota di contenuto: | Intro -- Preface -- Organization -- Contents - Part II -- Intelligent Systems -- Evaluation of WhatsApp to Promote Collaborative Learning in the Use of Software in University Professionals -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Materials -- 2.2 Method -- 3 Results -- 3.1 Results of the Questionnaire -- 3.2 Results Obtained in WhatsApp Statistics -- 4 Discussions and Conclusions -- References -- Deep Learning for Weather Classification from a Meteorological Device -- 1 Introduction -- 2 Previous Works -- 3 Materials and Method -- 3.1 Requirements -- 3.2 Method -- 4 Development and Experiments -- 4.1 Architecture Design -- 4.2 Dataset -- 4.3 Data Comparison -- 4.4 Classification Algorithms -- 4.5 Experiments -- 4.6 Analysis of Results -- 5 Conclusions and Future Work -- References -- Resource Management Strategy in Case of Disaster Based on Queuing Theory -- Abstract -- 1 Introduction -- 2 Disaster Management -- 3 Queuing Theory Applied to Disaster Management -- 4 Proposed Algorithm for Management of the Disaster Attention and Collection Center (DACC) -- 5 Testing -- 6 Conclusions -- References -- Application of Techniques Based on Artificial Intelligence for Predicting the Consumption of Drugs and Substances. A Systematic Mapping Review -- Abstract -- 1 Introduction -- 1.1 Theoretical Context of Fields of Knowledge -- 1.2 Previous Literature Reviews -- 2 Methodology -- 2.1 Research Questions -- 2.2 Inclusion, Exclusion and Quality Criteria -- 2.3 Semantic Search Structure -- 3 Results -- 3.1 RQ1: How Many Studies are in the WOS and Scopus Databases from 2015 to 2019? -- 3.2 RQ2: What are the Papers with More Cites? -- 3.3 RQ3. What is the Geographical Distribution of the Authors? -- 3.4 RQ4: What are the Journals with More Publications on This Line of Research? -- 3.5 RQ5: In What Contexts are These Studies Developed?. |
3.6 RQ6: What are the Main Topics Addressed in This Line of Research? -- 4 Conclusions -- References -- Generating Individual Gait Kinetic Patterns Using Machine Learning -- 1 Introduction -- 2 Material and Method -- 2.1 Dataset -- 2.2 Baseline -- 2.3 Input and Output -- 2.4 Data Preparation -- 2.5 Feedforward Neural Network -- 2.6 Train -- 2.7 Test -- 2.8 Evaluation Metrics -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Knee Injured Recovery Analysis Using Extreme Learning Machine -- Abstract -- 1 Introduction -- 2 Material and Method -- 2.1 ML Algorithms for Gait Analysis -- 2.2 Indices for Gait Analysis -- 2.3 Data Collection -- 2.4 Generation of Knee Joint Pattern Using ELM -- 2.5 Patterns Comparison -- 3 Results -- 4 Discussion -- 5 Conclusions -- Compliance with Ethical Standards -- References -- Driving Mode Estimation Model Based in Machine Learning Through PID's Signals Analysis Obtained From OBD II -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Experimental Overview -- 2.2 OBD-II Data Acquisition Though Data Logger Device -- 2.3 Signal Filtering -- 3 Results -- 3.1 Experimentation Results -- 3.2 Machine Learning Architectures Application -- 4 Conclusions -- Acknowledgment -- References -- Deep Learning Methods in Natural Language Processing -- Abstract -- 1 Introduction -- 2 Distributed Representations of Words -- 3 Word2Vec -- 3.1 Skip-Gram Network Architecture -- 3.2 Hidden Layer -- 3.3 Word2Vec - Output Layer -- 3.4 Negative Sampling -- 4 Recurrent Neural Networks (RNN) -- 4.1 Long Term Dependency Problem -- 4.2 Long Short Term Memory (LSTM) Networks -- 4.3 Gated Recurrent Unit (GRU) -- 4.4 Dropout -- 4.5 Bidirectional LSTM (BiLSTM) -- 5 Convolutional Neural Networks (CNN) for Language Tasks -- 5.1 Convolution Function -- 5.2 Pooling Function -- 5.3 Convolutional Neural Networks in NLP. | |
6 Generalized Language Models (GLM) -- 6.1 ULMFiT [9]/MultiFiT [10] -- 6.2 BERT/GPT-2 - Transformer Model -- 7 Conclusions -- References -- Comparison of Attenuation Coefficient Estimation in High Intensity Focused Ultrasound Therapy for Cancer Treatment by Levenberg Marquardt and Gauss-Newton Methods -- Abstract -- 1 Introduction -- 2 Methodology -- 2.1 Levenberg Marquardt Method -- 2.2 Gauss-Newton Method -- 3 Results and Discussions -- 4 Conclusions -- Disclosure Statement -- References -- Machine Learning for Optimizing Technological Properties of Wood Composite Filament-Timberfill Fabricated by Fused Deposition Modeling -- Abstract -- 1 Introduction -- 1.1 Additive Manufacturing: Fused Deposition Modelling -- 1.2 Computational Intelligence: Machine Learning -- 2 Material and Method -- 2.1 Material and Sample Preparation -- 2.2 Design of Experiments -- 2.3 Machine Learning Algorithm: ANFIS -- 3 Results -- 3.1 Experimental Results -- 3.2 ANFIS Results -- 4 Discussions -- 4.1 Experimental Results -- 4.2 ANFIS Results -- 5 Conclusions -- Acknowledgements -- References -- Automated Systems for Detecting Volcano-Seismic Events Using Different Labeling Techniques -- 1 Introduction -- 2 Seismic-Signal Catalogs -- 2.1 Original Data-Set -- 2.2 STA/LTA -- 3 Seismic-Event Detector Based on Machine Learning -- 3.1 Pre-processing -- 3.2 Labeling -- 3.3 Feature Extraction -- 3.4 Machine Learning Classifiers -- 4 Results -- 4.1 Parameter Space Study -- 4.2 Artificial Neural Networks -- 4.3 Support Vector Machines -- 4.4 Overall Performance -- 5 Conclusions -- References -- Fraud Prediction in Smart Supply Chains Using Machine Learning Techniques -- 1 Introduction -- 2 Related Work -- 3 Overview of Machine Learning Algorithms for Fraud Prediction -- 3.1 Rpart Method -- 3.2 C5.0 Algorithm -- 3.3 Random Forest Model -- 3.4 Support Vector Machine (SVM). | |
4 Proposed Approach -- 4.1 Work Environment -- 4.2 Data Source -- 4.3 Processing of Data Set -- 4.4 Dimensionality Reduction -- 4.5 Machine Learning Algorithms Application -- 5 Experimental Results -- 6 Discussion -- 7 Conclusions and Perspectives -- References -- Selection of Mental Tasks for Brain-Computer Interfaces Using NASA-TLX Index -- Abstract -- 1 Introduction -- 1.1 Mental Workload -- 1.2 Mental Workload Index -- 2 Materials and Methods -- 2.1 Equipment Description -- 2.2 Description of Users -- 2.3 Pre-processing -- 2.4 Selection Based on Silhoutt's Distance -- 2.5 Performance Metrics -- 2.6 Description of Mental Tasks -- 2.7 Active Learning -- 3 Results -- 4 Conclusions and Discussions -- References -- Algorithms for the Management of Electrical Demand Using a Domotic System with Classification of Electrical Charges -- Abstract -- 1 Introduction -- 2 State of the Art -- 3 Materials and Methods/Methodology -- 3.1 Embedded System -- 3.2 Electrical Characteristics -- 3.3 Learning Machines -- 3.4 Implementation of the Load Characterization System on the Embedded Platform -- 3.5 Implementation of Control Algorithms -- 4 Results and Discussion -- 5 Conclusions -- References -- Cluster Analysis for Abstemious Characterization Based on Psycho-Social Information -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Cluster Analysis -- 3 Results -- 4 Discussion -- 5 Conclusions -- Acknowledgement -- References -- Toward Automatic and Remote Monitoring of the Pain Experience: An Internet of Things (IoT) Approach -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Physiological Parameters -- 2.2 Network Protocols -- 2.3 Data Acquisition and Preprocessing -- 2.4 Data Transmission and Protocol Implementations -- 2.5 Performance Indexes and Testing Methods -- 3 Results and Discussion -- 4 Conclusion -- References. | |
Enterprise Architecture an Approach to the Development of IoT Services Oriented to Building Management -- 1 Introduction -- 2 Related Literature -- 3 Methodology of System Design -- 3.1 Defining Context of the Problem -- 3.2 Architecture Design -- 3.3 Architecture Implementation -- 4 Case of Study -- 5 Implementation of Proposed Methodology -- 5.1 Definition of Problem Context -- 5.2 Architecture Design -- 5.3 Architecture Implementation -- 6 Conclusions -- References -- Characterization of Functions Using Artificial Intelligence to Reproduce Complex Systems Behavior -- Abstract -- 1 Introduction -- 2 Methodology for Characterizing Functions of Order 2 Using TSK to Reproduce Cardiac PQRST Complex -- 2.1 Theoretical Framework -- 2.2 Standardization of Data -- 2.3 Structuring Fuzzy Inference System -- 3 Results and Discussions -- 4 Conclusions -- References -- Snake Hunting System Supplied with Solar Energy Based on Cages Installed in the Jungle for Strictly Curative Purposes, Promoting Ancestral Knowledge, Natural Medicine and Indigenous Cultural Products from Rural Areas -- Abstract -- 1 Introduction -- 2 Location of Research -- 3 Mathematical Modeling -- 3.1 Photovoltaic System -- 4 Blocks Diagram -- 5 Results and Discussions -- References -- SMCS: Automatic Real-Time Classification of Ambient Sounds, Based on a Deep Neural Network and Mel Frequency Cepstral Coefficients -- Abstract -- 1 Introduction -- 1.1 Preliminary -- 2 Material and Method -- 2.1 Deep Neural Network (DNN) -- 2.2 Data Normalization -- 2.3 Extraction of MFCC -- 3 Results -- 4 Discussions -- 5 Conclusions -- References -- Artificial Intelligence Techniques to Detect and Prevent Corruption in Procurement: A Systematic Literature Review -- Abstract -- 1 Introduction -- 1.1 Related Systematic Review of Literature -- 2 Method -- 2.1 Method for SLR -- 2.2 Research Questions. | |
2.3 Quality Inclusion and Exclusion Protocols. | |
Sommario/riassunto: | This second volume of the three-volume set (CCIS 1193, CCIS 1194, and CCIS 1195) constitutes the refereed proceedings of the First International Conference on Applied Technologies, ICAT 2019, held in Quito, Ecuador, in December 2019. The 124 full papers were carefully reviewed and selected from 328 submissions. The papers are organized according to the following topics: technology trends; computing; intelligent systems; machine vision; security; communication; electronics; e-learning; e-government; e-participation. . |
Titolo autorizzato: | Applied technologies ![]() |
ISBN: | 3-030-42520-7 |
Formato: | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910410036303321 |
Lo trovi qui: | Univ. Federico II |
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