International Conference on Applied Technologies : 5th International Conference on Applied Technologies, ICAT 2023, Samborondon, Ecuador, November 22-24, 2023, Revised Selected Papers, Part II

• Autore: Botto-Tobar Miguel
• Pubblicazione: Cham : , : Springer International Publishing AG, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (288 pages)
• Altri autori: Zambrano VizueteMarcelo Montes LeónSergio Torres-CarriónPablo DurakovicBenjamin
• Nota di contenuto: Intro -- Preface -- Organization -- Contents - Part II -- Intelligent Systems -- Neural Network Model to Classify a Tweet According to Its Sentiment -- 1 Introduction -- 1.1 Current Status -- 2 Method -- 2.1 Data Selection -- 2.2 Data Preparation -- 2.3 Model Development -- 2.4 Model Training -- 3 Discussion of Results -- 3.1 Tweet Classification Model -- 3.2 Architecture of the Web Application -- 3.3 Model Evaluation -- 4 Conclusions -- References -- Virtual Assistant for the Registration of Clinical Histories Using Natural Language Processing in the Health Sector -- 1 Introduction -- 2 Related Works -- 3 Methods -- 3.1 Methodology -- 3.2 Integrated Architecture -- 3.3 Programming -- 3.4 Mobile Application Interface -- 4 Experiments and Results -- 4.1 Preparation Protocol -- 4.2 Definition of Indicators -- 4.3 Test Scenario -- 4.4 Evaluation of Indicators -- 5 Analysis and Discussion of Results -- 6 Conclusions -- References -- Physicochemical and Microbiological Characterization of Drinking Water from the Luz de América parish, Ecuador: Statistical Approach -- 1 Introduction -- 2 Materials and Methods -- 2.1 Study Area -- 2.2 Data Collection -- 2.3 Physicochemical and Microbiological Assays -- 2.4 Data Analysis -- 3 Results and Discussions -- 4 Conclusions -- References -- Machine Learning Models for Identifying Patterns in GNSS Meteorological Data -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- Development of Animal Morphology Measurement Tool with Convolutional Neural Networks and Single-View Metrology Algorithms -- 1 Introduction -- 2 Theoretical Framework -- 2.1 Related Studies -- 3 Conceptual Framework -- 3.1 YOLO (You Only Look Once) -- 3.2 Trap Cameras -- 3.3 Single View Metrology Algorithms -- 4 Methodology -- 5 Development -- 5.1 Stage 1: Data Selection. ; 5.2 Stage 2: Data Preprocessing -- 5.3 Stage 3: Data Transformation -- 5.4 Stage 4: Data Integration -- 5.5 Stage 5: Implementation -- 6 Results -- 7 Conclusions -- References -- Rose Plant Disease Detection Using Image Processing and Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Steps to Detect Plant Disease -- 4 Techniques on Image Processing -- 5 Results and Discussion -- 6 Conclusion -- References -- A Fine-Tuned Transfer Learning Approach for Parkinson's Disease Detection on New Hand PD Dataset -- 1 Introduction -- 2 Literature Review -- 3 Dataset Description and Preprocessing -- 3.1 Dataset Description -- 3.2 Dataset Preprocessing -- 4 Methodology -- 4.1 Hardware and Memory Optimization -- 4.2 Model Training and Evaluation -- 5 Results and Discussion -- 6 Conclusion -- References -- Smart Guide for Pedestrian Traffic Light Status Identification -- 1 Introduction -- 2 Methodology -- 2.1 3D Modeling of Protective Structure -- 2.2 Operation of the Artificial Vision Algorithm Model -- 2.3 Development of the Dataset or Database -- 2.4 Training of the Artificial Neural Network -- 2.5 Object Detection Model -- 2.6 Image Classification Model -- 2.7 Voice Notifications -- 2.8 General Architecture of the Prototype -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Conversion of MRI into CT Images Using Novel Dual Generative Adversarial Model -- 1 Introduction -- 2 Background -- 3 Proposed Model -- 4 Experimental Result -- 4.1 PSNR and SSIM Index -- 4.2 Experimental Environment -- 4.3 Results -- 5 Conclusion -- References -- Accurate and Fast Segmentation of MRI Images Using Multibranch Residual Fusion Network -- 1 Introduction -- 2 Background -- 3 Proposed Method -- 3.1 Residual Matter Dense Particles -- 3.2 Residual Error Fusion Module -- 3.3 An Attention Multiplier Dispersed Throughout the Brain -- 4 Results. ; 4.1 Ablation Study -- 5 Conclusion -- References -- Voice Pathology Detection Demonstrates the Integration of AI and IoT in Smart Healthcare -- 1 Introduction -- 2 Background -- 2.1 Cyst -- 2.2 A Benign Growth on the Vocal Folds -- 2.3 Nodules -- 2.4 Paralysis -- 2.5 Sulcus -- 3 Proposed VPD System -- 4 Results -- 4.1 Database -- 5 Conclusion -- References -- Impact of AI Infused Leadership on Subordinate Employee's Job Satisfaction: A Study Across Select Successful IT Companies in Bengaluru City -- 1 Introduction -- 2 Review of Literature -- 2.1 AI Infused Leadership -- 2.2 Research Gap -- 2.3 Research Objectives -- 3 Research Methodology -- 4 Results and Discussion -- 4.1 Demographic Profile of the Respondents -- 4.2 Descriptive Statistics -- 4.3 Relationship Between AI Infused Leadership and Employee Job Satisfaction -- 5 Suggestions and Conclusions -- References -- Uncovering AI Potential Techniques for Infectious Disease: A Comprehensive Exploration of Surveying, Classifying, and Predicting Models -- 1 Introduction -- 2 Protocols for the Selection of Studies Related to Covid19 -- 2.1 Covid19, Machine Learning as Well as Deep Learning Methods -- 2.2 Machine Learning Methodologies -- 2.3 Deep Neural Network -- 2.4 Hybrid Approach Merging Deep Learning and Machine Learning -- 3 COVID 19 Datasets -- 4 Outcomes of the Study -- 5 Conclusions -- References -- A Survey: Detection of Heart-Related Disorders Using Machine Learning Approaches -- 1 Introduction -- 1.1 Angina -- 1.2 Coronary Heart Disease -- 1.3 Unstable Angina -- 1.4 Heart Failure -- 1.5 Heart Attack -- 1.6 Congenital Heart Conditions -- 2 The Used Techniques and Approaches -- 2.1 K - Nearest Neighbor -- 2.2 Support Vector Machine -- 2.3 Naïve Bayes -- 2.4 Decision Tree -- 2.5 Random Forest -- 3 Literature Review -- 4 Findings -- 5 Conclusion -- References. ; Technological and Other Motivating Factors Behind Purchase Intention for Organic Processed Food -- 1 Introduction -- 2 Methodology -- 3 Research Objective -- 4 Factors Impacting Decisions to Buy Organic Processed Food -- 5 Technology as a Motivating Factors Behind Purchase Intention for Organic Processed Food -- 6 Discussion and Conclusion -- References -- Conversational AI-Based Technological Solution for Intelligent Customer Service -- 1 Introduction -- 2 Related Works -- 2.1 Conversational AI-Based Technological Solutions -- 2.2 Technologies that Support Development of Virtual Assistant -- 3 Method -- 3.1 Architecture of the Project for the Development -- 3.2 Benchmarking and Choosing Criteria of the Framework -- 3.3 Web Implementation -- 3.4 Virtual Assistant Implementation -- 3.5 Virtual Assistant Integration -- 4 Experimental Setting -- 5 Results -- 5.1 Usability Dimension -- 5.2 Functionality Dimension -- 5.3 Customer Satisfaction Dimension -- 6 Conclusion -- References -- Detecting the Use of Safety Helmets on Construction Sites -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Business Understanding -- 3.2 Data Understanding -- 3.3 Data Preparation -- 4 Proposed Work -- 4.1 Modeling -- 4.2 Evaluation -- 4.3 Deployment -- 5 Results and Discussion -- 6 Conclusions and Future Work -- References -- Preventing Diabetes: Substituting Processed Foods and Nutritional Chatbot Assistance -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data -- 2.2 Foods Clustering and Distance Matrix -- 2.3 Foods, Dietary Guidelines, and Users Knowledge Graph -- 2.4 FoodSub: System Architecture -- 2.5 Processed Foods Substitution Method and Recommendation -- 2.6 Nutritional Information Chatbot -- 3 Results and Discussion -- 3.1 Evaluation Participants -- 3.2 FoodSub: Usability Evaluation with SUS -- 3.3 Chatbot: Usability Evaluation with CUQ. ; 3.4 Expert Verification for Substitution Recommendations -- 4 Conclusions and Future Work -- References -- Attack Classification Using Machine Learning Techniques in Software-Defined Networking -- 1 Introduction -- 2 Literature Review -- 3 The Proposed Method -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Feature Selections -- 4 Evaluations and Experiments Results -- 4.1 Software and Hardware Specifications -- 4.2 Model Selection -- 4.3 Experiments Results -- 5 Conclusion -- References -- Classification of Toxic Comments on Social Networks Using Machine Learning -- 1 Introduction -- 2 Materials and Methods -- 2.1 Materials -- 2.2 Analytical Description -- 2.3 Methods -- 3 Results -- 3.1 Understanding the Business -- 3.2 Understanding the Data -- 3.3 Data Preparation -- 3.4 Modeling -- 3.5 Evaluation -- 3.6 Correlation Matrix -- 3.7 Evaluation of Validity -- 4 Discussion -- 5 Conclusions -- References -- Author Index.
• Titolo autorizzato: International Conference on Applied Technologies
• ISBN: 3-031-58953-X
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910864188503321
• Lo trovi qui: Univ. Federico II
• Serie: Communications in Computer and Information Science Series