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

• Autore: Botto-Tobar Miguel
• Pubblicazione: Cham : , : Springer International Publishing AG, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (301 pages)
• Altri autori: Zambrano VizueteMarcelo Montes LeónSergio Torres-CarriónPablo DurakovicBenjamin
• Nota di contenuto: Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Contents - Part III -- Intelligent Systems -- Mobile Application for Calorie Control Using Machine Learning -- 1 Introduction -- 2 Related Works -- 2.1 Machine Learning Algorithms -- 2.2 Similar Solutions -- 3 Material and Method -- 3.1 Data Preparation -- 3.2 SVM Model Training -- 3.3 Mobile Application Development -- 3.4 User Experimentation -- 3.5 Analysis of Experiment -- 4 Result and Discussion -- 4.1 Percentage of Caloric Recommendation Satisfaction (PCRS) -- 4.2 Percentage of Accepted Recommendations (PAR) -- 4.3 Percentage of Usage Satisfaction (PUS) -- 4.4 General Results -- 4.5 Discussion of the Results -- 5 Conclusions -- References -- Application of Machine Learning for Air Quality Analysis -- 1 Introduction -- 2 Materials and Methods -- 2.1 Problem Analysis -- 2.2 Understanding Data -- 2.3 Data Preparation -- 2.4 Machine Learning Design -- 2.5 Modeling -- 2.6 Model Implementation and Validation -- 3 Results -- 4 Discussion -- 5 Limitations and Future Work -- 6 Conclusion -- References -- Unsupervized Techniques to Identify Patterns in Gynecologic Information -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Preprocessing -- 2.3 Algorithms -- 2.4 Metrics -- 2.5 Calculate the Number of Clusters -- 2.6 Tools -- 3 Results -- 3.1 K-means Results -- 3.2 Hierarchical Clustering Results -- 3.3 DBSCAN Results -- 3.4 PCA and DBSCAN Results -- 4 Discussion -- 4.1 Conclusion -- References -- Web Application for Early Cataract Detection Using a Deep Learning Cloud Service -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Web Application Architecture Design -- 3.2 Deep Learning Model Implementation -- 3.3 Web Application Development -- 3.4 Deploy -- 4 Results and Discussions -- 4.1 Experiment Protocol -- 4.2 Results -- 4.3 Discussions -- 4.4 Limitations. ; 5 Conclusions and Future Work -- 5.1 Conclusions -- 5.2 Future Work -- References -- Analyze and Implement a Reinforced AI Chatbot in Guayaquil to Improve Mental Health in Adolescents with the Use of the Neural Generative Models -- 1 Introduction -- 2 Related Work -- 2.1 Chatbots in Mental Health -- 2.2 AI and Healthcare -- 2.3 Key Concepts -- 3 Methodology -- 3.1 Chatbot Development -- 3.2 Methodological Design -- 4 Implementation -- 5 Evaluation -- 5.1 Model Validation -- 5.2 Chatbot Usability Measurement -- 5.3 Usability Study Results (According to CUQ) -- 5.4 Mobile Application Usability -- 6 Conclusions, Limitations, and Future Work -- References -- Detection of Ovarian Cancer Using Improved Deep Learning Model -- 1 Introduction -- 2 Material and Method -- 2.1 Dataset -- 2.2 Data Augmentation -- 2.3 The Improved VGG-16 Model -- 3 Results and Discussion -- 3.1 Implementation -- 3.2 Evaluation Metrics -- 3.3 Hyper Parameter Tuning -- 3.4 Results -- 4 Conclusion -- References -- Navigating the Chatbot Terrain: AI-Driven Conversational Interfaces -- 1 Introduction -- 2 Evolution of Chatbots -- 3 Chatbot System Process -- 3.1 Chatbot Architecture -- 3.2 Types of Chatbots -- 3.3 Applications of Chatbots -- 3.4 Challenges in Chatbot Development -- 3.5 Techniques to Improve Responses -- 4 Chatbot in Different Fields -- 4.1 Healthcare -- 4.2 E-Commerce -- 4.3 Education -- 4.4 Social Media Management -- 5 Future Trends in AI Chatbots -- 6 Conclusion -- References -- Intelligent Virtual Assistant for Elevators Powered by Facial Recognition and Voice Commands -- 1 Introduction -- 2 Methodology -- 2.1 System Architecture -- 2.2 Assistant Design -- 2.3 Facial Recognition Algorithm -- 2.4 Voice Command Algorithm -- 2.5 Embedded System -- 2.6 Actuator Parameterization and Connectivity -- 3 Results -- 4 Discussion -- 5 Conclusions -- References. ; Otsu Segmentation and Deep Learning Models for the Detection of Melanoma -- 1 Introduction -- 2 Background and Related Works -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- Hybrid Residual Network and XGBoost Method for the Accurate Diagnosis of Lung Cancer -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Methods for Identifying Lung Nodules -- 3.2 Negative Mining -- 3.3 Refining Process -- 4 Experiments and Result -- 5 Conclusion -- References -- Generic Framework of New Era Artificial Intelligence and Its Applications -- 1 Introduction -- 2 Related Work -- 3 Proposed AI Framework -- 3.1 Evaluation of Chatbots Tools -- 3.2 Framework Design Evaluation -- 3.3 Research Assessment Framework is Being Roll-Out and Pilot Test -- 3.4 Humanizer BOT (RANS) in Education Sector -- 4 Bot Testing -- 4.1 Test Case 0 -- 4.2 Test Case 1 -- 4.3 Test Case 2 -- 4.4 Test Case 3 -- 4.5 Contact Model Test Case 4 -- 4.6 Contact Model Test Case 5 -- 4.7 Contact Model Test Case 6 -- 4.8 RANBOT Test Case 7 -- 5 Results and Discussion -- 6 Conclusion -- References -- Exploring the Molecular Diversity of SARS, Ebola, MERS, and SAR-COV-2 Viruses Using Genomics Virus Classification Algorithm: ViroGen -- 1 Introduction -- 2 Literature Review -- 3 Genome Based on Artificial Intelligence Technology -- 4 Results and Discussion -- 5 Conclusions -- References -- Improving Dynamic Behavior of Vehicular Ad Hoc Networks by Integrating Game Theory Technique -- 1 Introduction -- References -- Machine Learning to Investigate Determinants of Intention to Purchase Organic Food -- 1 Introduction -- 2 Problem Statements -- 3 Literature Review -- 4 Theoretical Framework -- 5 Methods -- 6 Machine Learning Model for Finding Determinants Intention to Purchase Organic Food -- 7 Data Analysis -- 8 Discussion -- References. ; Influence Analysis of Driving Style on the Energy Consumption of an Electric Vehicle Through PID Signals Study -- 1 Introduction -- 2 Materials and Methods -- 2.1 On Route Data Acquisition -- 2.2 Test Route -- 2.3 Longitudinal Vehicle Dynamics -- 3 Results and Discussion -- 3.1 Energy Consumption Calculus -- 3.2 Acceleration Analysis Respect to the Route Driving Modes -- 3.3 Most Important Predictors in the Study from Decision Trees (Random Forest) -- 3.4 Training and Validation of the Neural Network from the Predictors -- 4 Conclusions -- References -- Prediction of Academic Outcomes Using Machine Learning Techniques: A Survey of Findings on Higher Education -- 1 Introduction -- 2 Importance of Academic Performance Prediction -- 3 Methodology -- 4 Results -- 4.1 Factors Affecting the Student's Academic Performance -- 4.2 Machine Learning Algorithms for Predicting Students' Performance -- 4.3 Challenges of Machine Learning for Academic Performance -- 5 Conclusions -- References -- Identification of Factors and Teacher Profile Associated with Student Performance Using Fuzzy Techniques and Data Mining -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Academic Performance Dataset -- 3.2 Teaching Profile Data -- 3.3 Data Preparation -- 4 Results -- 4.1 Identification of Factors Affecting Academic Performance -- 4.2 Identification of the Teaching Profile as a Factor of Academic Performance -- 5 Conclusions -- References -- Predictive Model for Accurate Horticultural Product Pricing Using Machine Learning -- 1 Introduction -- 2 Related Works -- 3 Main Contribution -- 4 Methodology -- 5 Experiments -- 6 Results -- 7 Conclusion and Perspective -- References -- Analysis of Driving Style and Its Influence on Fuel Consumption for the City of Quito, Ecuador: A Data-Driven Study -- 1 Introduction -- 2 Material and Methods -- 2.1 OBD Signal Acquisition. ; 2.2 Test Vehicle -- 2.3 Road Tests -- 2.4 Exploratory Analysis of Variables -- 2.5 Data Classification -- 3 Results and Discussions -- 3.1 Relationship Between Variables of Interest and Driving Style -- 3.2 Differences in Fuel Consumption -- 3.3 Development of the Calculation Algorithm -- 3.4 Testing the Classifier Model on a Normal Route -- 3.5 Classifier Model Testing in an RDE Cycle -- 4 Conclusions -- References -- Preventing Drug Interactions in Diabetic Patients: The Role of a Mobile Conversational Agent -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Store -- 2.2 Conversation Engine -- 2.3 Core Services -- 2.4 External Devices -- 3 Results and Discussion -- 3.1 Usability -- 3.2 Expert Judgment -- 4 Conclusions and Future Work -- References -- Author Index.
• Titolo autorizzato: International Conference on Applied Technologies
• ISBN: 3-031-58956-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910864193403321
• Lo trovi qui: Univ. Federico II
• Serie: Communications in Computer and Information Science Series