Artificial intelligence, computer and software engineering advances : proceedings of the CIT 2020 / / Miguel Botto-Tobar, Henry Cruz and Angela Díaz Cadena (editors)

• Pubblicazione: Cham, Switzerland : , : Springer, , [2021]; ©2021
• Descrizione fisica: 1 online resource (503 pages) : illustrations
• Disciplina: 006.3
• Soggetto topico: Computational intelligence; Cyber-physical systems, IoT; Artificial intelligence; Intel·ligència computacional; Enginyeria de programari; Sistemes informàtics
• Soggetto genere / forma: Congressos; Llibres electrònics
• Persona (resp. second.): CruzHenry; Diaz CadenaAngela; Botto TobarMiguel
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Intro -- Preface -- Organization -- General Chairs -- Organizing Committee -- Steering Committee -- Publication Chair -- Program Chairs -- Life Sciences -- Earth and Construction Sciences -- Energy and Mechanics -- Electrical and Electronic -- Computer Science -- Human and Social Science -- Security and Defense -- Economic and Administrative Sciences -- Social -- Local Committee -- Research Department -- Sede Latacunga -- Program Committee -- Organizing Institutions -- Contents -- Artificial intelligence, Communications, Security and Cryptography, and Software Engineering -- Prediction of Parkinson's Disease Severity Based on Gait Signals Using a Neural Network and the Fast Fourier Transform -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset Description -- 2.2 Pre-processing of Data -- 2.3 Information Extraction (Features) -- 2.4 Model Structure of the Proposed Artificial Neural Network -- 2.5 Performance of the Proposed Model -- 3 Results and Discussion -- 3.1 Evaluation of the Backpropagation Algorithm -- 3.2 Prediction of Parkinson's Stages -- 3.3 Comparison with Similar Studies -- 3.4 Study Limitation -- 4 Conclusions and Future Perspectives -- References -- An Analysis of Deep Learning Architectures for Cancer Diagnosis -- 1 Introduction -- 2 Materials and Methods -- 2.1 Materials -- 2.2 Methods -- 3 Results -- 3.1 Impact of Deep Learning in Cancer Diagnosis -- 3.2 Training the CNN Network -- 3.3 Testing the CNN Network -- 4 Discussion -- 5 Future Work and Conclusions -- References -- Identifying Similar Groups of Countries According to the Impact of Corona Virus (COVID-19) by a Two-Layer Clustering Method -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Data Clustering -- 3 Results and Discussion -- 3.1 First Clustering -- 3.2 Second Clustering -- 3.3 Final Results -- 4 Conclusions and Recommendations. ; References -- ToraxIA: Virtual Assistant for Radiologists Based on Deep Learning from Chest X-Ray -- 1 Introduction -- 2 Methodology -- 2.1 Data Set -- 2.2 Annotation Process -- 2.3 Deep Learning Model -- 3 Experimental Results -- 3.1 Library Performance -- 3.2 Deep Learning Model Results -- 3.3 COVID-19 Dataset -- 3.4 Toraxia™Output -- 4 Discussion -- 5 Conclusion and Future Work -- References -- Classification of Andean Chocho (Lupinus Mutabilis Sweet) by Shape and Color Using Artificial Vision -- 1 Introduction -- 2 Materials and Methods -- 2.1 Artificial Vision System -- 2.2 Image Segmentation -- 2.3 Feature Extraction -- 2.4 System Tests -- 3 Results and Discussion -- 4 Conclusions -- References -- Deep Learning for Edge Computing: A Survey -- 1 Introduction -- 2 Materials and Methods -- 2.1 Materials -- 2.2 Methods -- 3 Results -- 3.1 Impact of Deep Learning on Edge Computing -- 3.2 Deep Learning Algorithm Summary -- 3.3 Edge Computing Summary -- 4 Discussion -- 5 Future Work and Conclusion -- References -- SIR Model Parameter Fitting of SARS-CoV-2 Basic Reproduction Number in Venezuela and Ecuador Epidemic -- 1 Introduction -- 2 Methodology -- 2.1 Database -- 2.2 SIR Model -- 2.3 Parameter Fitting -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- Machine Learning and Color Treatment for the Forest Fire and Smoke Detection Systems and Algorithms, a Recent Literature Review -- 1 Introduction -- 2 The Forest Fire Detection Systems Applied and Acquisition Information Methodology -- 2.1 The Main Systems Used to Detect Fire and Smoke in the Forest -- 2.2 Procedure for Acquiring and Classifying Information -- 3 Forest Fire Detection Methods Through Machine Learning Algorithms and Color Features Extraction -- 3.1 Fire Forest Detection Using Machine Learning Methods -- 3.2 Fire Forest Detection Through Color Treatment. ; 3.3 Fire Forest Detection to UAV's/UAS -- 4 Forest Smoke Detection Methods and Techniques -- 4.1 Combined Methods to Smoke Forest Detection -- 4.2 Smoke Detection Using Combined Methods Applied to UAS/UAV's -- 5 Conclusions and Future Work -- References -- Dimensionality Reduction Using PCA and CUR Algorithm for Data on COVID-19 Tests -- 1 Introduction -- 2 Materials and Methods -- 2.1 Description of Data -- 2.2 Techniques for the Analysis -- 2.3 Effectiveness -- 3 Results and Discussions -- 3.1 Principal Component Analysis on Data Matrix -- 3.2 CUR Algorithm on Data Matrix -- 3.3 Effectiveness -- 4 Conclusions -- References -- Ensuring Traceability and Orchestration in the Food Supply Chain -- 1 Introduction -- 2 Characteristics of the Food Supply Chain -- 3 Technology Review -- 4 Technological Proposal -- 5 Platform Architecture -- 6 Conclusions -- References -- Network Neutrality: The Case of Five South American Countries -- 1 Introduction -- 2 Methodology -- 3 The General Context of Network Neutrality in South America -- 4 Net Neutrality Policies in South America -- 4.1 Chile -- 4.2 Colombia -- 4.3 Brazil -- 4.4 Ecuador -- 4.5 Argentine -- 5 Results and Discussion -- 6 Conclusions -- References -- Design Techniques of FTTH-GPON Networks for Segmentation and Data Traffic Relief -- 1 Introduction -- 2 Related Work -- 2.1 Architecture, Access Mode, and Encapsulation -- 2.2 Data Frame Download Operation -- 2.3 Data Frame Upload Operation -- 3 Case Study and Method -- 3.1 Case Study -- 3.2 Methodology -- 4 Results and Discussion -- 5 Conclusions and Future Works -- References -- Processing of Voice Signals in Telecommunications Systems Using MATLAB -- 1 Introduction -- 2 General Analysis -- 2.1 Acoustic of the Voice -- 2.2 Characteristics of the Organs that Make up the Voice -- 2.3 Voice Capture in Matlab -- 2.4 Analysis in the Time Domain. ; 2.5 Analysis in the Frequency Domain -- 2.6 Spectrum of the Voice Signal -- 3 Lineal Prediction of the Voice -- 3.1 FIR Filter -- 3.2 Stimation Theory -- 3.3 Identification of a System -- 3.4 Lineal Prediction in MATLAB -- 4 Compression of the Voice and Vocoders in Cellular Telephony -- 5 Case Analysis and Discussion -- 6 Conclusions -- References -- Prototype of a Centralized Alert and Emergency System for Digital Terrestrial Television in Ecuador -- 1 Introduction -- 1.1 Core of the Early Warning System for Digital Terrestrial Television -- 2 Common Alert Protocol -- 3 CAP Implementation -- 3.1 Development Tools -- 3.2 CAP Module Integration to SDI -- 3.3 Advantages and Disadvantages of the CAP System -- 4 Results -- 4.1 Generation of Codes Through the Use of SDI for the Transmission of Information Through DTT -- 4.2 Generating an Alert Using the CAP Module -- 5 Discussion -- 6 Conclusions -- References -- Implementation of a Basic Risk Guide for Interactive Digital Terrestrial Television Using Learning Objects -- 1 Introduction -- 1.1 Learning Objects -- 1.2 Related Works -- 2 Materials and Methods -- 2.1 Methodology of Application Development -- 3 Results and Discussions -- 3.1 Results -- 3.2 Discussions -- 4 Conclusions -- References -- Using H5P Services to Enhance the Student Evaluation Process in Programming Courses at the Universidad Politécnica Salesiana (Guayaquil, Ecuador) -- 1 Introduction -- 1.1 Evaluation Strategies for an Active Learning Processes -- 1.2 Technology Supported Learning and Interactive Evaluations -- 2 Materials and Methods -- 2.1 Python Experimental Educational Platforms -- 3 Results and Discussion -- 4 Conclusions -- References -- Embedded System for Fall Detection in Activities of Daily Living ADLs: A Time Window Analysis -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Naïve Bayes Training (Offline). ; 3.2 Acquisition and Data Processing in the Embedded System -- 3.3 Naive Bayes in the Embedded System -- 4 Test and Results -- 5 Conclusions -- References -- Parallel CPU-Based Processing for Automatic Crop Row Detection in Corn Fields -- 1 Introduction -- 2 Materials and Methods -- 2.1 Image Dataset -- 2.2 Algorithm Parallelization -- 2.3 Acceleration of the Algorithm -- 2.4 Processing Equipment -- 2.5 Statistical Tests -- 3 Results y Discussion -- 4 Conclusions -- References -- Detection of Suspected of Breast Cancer Using Thermal Images -- 1 Introduction -- 2 Methodology -- 2.1 Image Acquisition -- 2.2 Image Processing -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- IoT-Based Sensor Nodes for Structural Health Monitoring of Bridges -- 1 Introduction -- 2 Related Works -- 3 System Architecture and Methodology -- 3.1 Base Station -- 3.2 Video Monitoring System -- 3.3 Sensor Node -- 3.4 Synchronization -- 3.5 Monitoring Software -- 4 Experimental Evaluation and Results -- 4.1 Structural Health Data Acquisition -- 4.2 System Performance Evaluation -- 5 Conclusions -- References -- Software Architecture for IoT-Based Solutions -- 1 Introduction -- 2 Related Work -- 3 Description of the Proposed Software Architecture -- 3.1 Perception Layer -- 3.2 Storage Layer -- 3.3 Processing Layer -- 3.4 Presentation Layer -- 4 Analysis of Results -- 5 Conclusions -- References -- Bootstrap as a Tool for Web Development and Graphic Optimization on Mobile Devices -- 1 Introduction -- 1.1 Evolution of Online Computer Systems -- 2 Materials and Methods -- 2.1 Bootstrap for the Production of Web Systems -- 2.2 Screen Adaptation on Mobile Devices -- 2.3 Preparing Bootstrap for Web Development -- 3 Implementation of Bootstrap in the EAC EducArte Community Web System -- 4 Results and Discussions -- 5 Conclusions -- References. ; Remote Variable Monitoring App for Mechanical Ventilators Used in COVID-19.
• Titolo autorizzato: Artificial intelligence, computer and software engineering advances
• ISBN: 3-030-68080-0
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910484016703321
• Lo trovi qui: Univ. Federico II
• Serie: Advances in Intelligent Systems and Computing