Kooperativer Bibliotheksverbund

UID:

Umfang: 1 online resource (293 pages)

Ausgabe: 1st ed. 2024.

ISBN: 9783031602184 , 3031602188

Serie: Lecture Notes in Networks and Systems, 986

Inhalt: This book is composed by a selection of articles from the 12th World Conference on Information Systems and Technologies (WorldCIST'24), held between 26 and 28 of March 2024, at Lodz University of Technology, Lodz, Poland. WorldCIST is a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences and challenges of modern Information Systems and Technologies research, together with their technological development and applications. The main and distinctive topics covered are: A) Information and Knowledge Management; B) Organizational Models and Information Systems; C) Software and Systems Modeling; D) Software Systems, Architectures, Applications and Tools; E) Multimedia Systems and Applications; F) Computer Networks, Mobility and Pervasive Systems; G) Intelligent and Decision Support Systems; H) Big Data Analytics and Applications; I) Human-Computer Interaction; J) Ethics, Computers and Security; K) Health Informatics; L) Information Technologies in Education; M) Information Technologies in Radiocommunications; and N) Technologies for Biomedical Applications. The primary market of this book are postgraduates and researchers in Information Systems and Technologies field. The secondary market are undergraduates and professionals as well in Information Systems and Technologies field.

Anmerkung: Maritime Management Ensemble Learning System -- Stock Market Prediction Integrating Explainable AI with Conv2D Models for Candlestick Image Analysis -- Resources optimization and value based prioritization for at risk cultural heritage assets management -- Expert Systems in Information Security A Comprehensive Exploration of Awareness Strategies Against Social Engineering Attacks -- Collaborative filtering recommendation systems based on deep learning An Experimental Study -- Assessment of LSTM and GRU models to predict the electricity production from biogas in a Wastewater Treatment Plant -- Fusing Temporal and Contextual Features for Enhanced Traffic Volume Prediction -- Target vs One and Target vs All classification of epilepsy using deep learning technique.

Weitere Ausg.: ISBN 9783031602177

Weitere Ausg.: ISBN 303160217X

Sprache: Englisch

DOI: 10.1007/978-3-031-60218-4

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Umfang: 1 online resource (293 pages)

Ausgabe: 1st ed.

ISBN: 3-031-60218-8

Serie: Lecture Notes in Networks and Systems Series ; v.986

Anmerkung: Intro -- Preface -- Organization -- Contents -- Intelligent and Decision Support Systems -- MAGNAT: Maritime Management Ensemble Learning System -- 1 Introduction -- 2 Related Work -- 3 MAGNAT -- 3.1 Principle -- 3.2 Model Architecture Design -- 3.3 Intelligent Aggregation -- 4 Performance Evaluation -- 5 Discussions -- 6 Conclusion -- References -- Stock Market Prediction: Integrating Explainable AI with Conv2D Models for Candlestick Image Analysis -- 1 Introduction -- 1.1 Objectives of the Research -- 2 Related Work -- 3 Method -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Model Architecture -- 4.3 Explainable AI Techniques -- 4.4 Evaluation Metrics -- 4.5 Experimental Design -- 4.6 Model Training and Accuracy -- 5 Discussion -- 5.1 Explainability -- 5.2 Insights Gained -- 5.3 Limitations and Future Work -- 6 Conclusion -- References -- Resources Optimization and Value-Based Prioritization for at Risk Cultural Heritage Assets Management -- 1 Introduction -- 2 Literature Review -- 3 Optimization of the Rescue and Recovery Process for Cultural Heritage Assets -- 4 Results and Discussion -- 5 Conclusion -- References -- Expert Systems in Information Security: A Comprehensive Exploration of Awareness Strategies Against Social Engineering Attacks -- 1 Introduction -- 2 Social Engineering -- 2.1 Social Engineering Attacks -- 3 Snowball: Strategy -- 4 Results -- 4.1 Summary Introduction to Results -- 4.2 Overview of Seed Articles -- 5 Discussion -- 6 Conclusion -- 7 Recommendations for Future Research -- References -- Multi-class Model to Predict Pain on Lower Limb Intermittent Claudication Patients -- 1 Introduction -- 2 Case Study -- 2.1 Feature Extraction and Correlation -- 2.2 Pain Prediction Models -- 3 Results -- 3.1 Classification Tree Models -- 3.2 7-Nearest Neighbors Models -- 4 Discussions -- 5 Conclusions and Future Work -- References. , Collaborative Filtering Recommendation Systems Based on Deep Learning: An Experimental Study -- 1 Introduction -- 2 Deep Learning-Based Recommender System -- 2.1 Deep Learning-Based Collaborative Filtering Recommender Systems -- 2.2 Deep Learning Models -- 2.3 Challenges of Collaborative Filtering Recommender Systems Based on Deep Learning -- 3 Results -- 3.1 Experimentl Setup -- 3.2 Experimental Results -- 4 Conclusions and Future Work -- References -- Assessment of LSTM and GRU Models to Predict the Electricity Production from Biogas in a Wastewater Treatment Plant -- 1 Introduction -- 2 Material and Methods -- 3 Experiments -- 4 Results and Discussion -- 5 Conclusions -- References -- Fusing Temporal and Contextual Features for Enhanced Traffic Volume Prediction -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 LSTM for Traffic Data Prediction -- 3.4 LSTM and Categorical Features Integration in a Hybrid Neural Network -- 3.5 Evaluation Metrics -- 4 Experimental Results -- 4.1 Training -- 4.2 Performance Comparison for Traffic Volume Prediction -- 4.3 Feature Influence Analysis -- 5 Conclusion and Future Work -- References -- Target-vs-One and Target-vs-All Classification of Epilepsy Using Deep Learning Technique -- 1 Introduction -- 2 Epilepsy Seizure and Computational Techniques -- 2.1 Epilepsy Seizure (ES) -- 2.2 Computational Techniques to Classify the ES -- 3 Propose Framework and Evaluation Setup -- 3.1 Subject Dataset and Preprocessing -- 3.2 Model Evaluation Setup -- 3.3 TvO Strategy for ES Using Deep Learning -- 3.4 TvA Strategy for ES Using Deep Learning -- 4 Results and Discussion -- 5 Conclusion -- References -- Health Informatics -- OralDentalSoft: Open-Source Web Application for Dental Office Management -- 1 Introduction -- 2 Related Work. , 3 Description of the Proposed Methodology for Open-Source Development: OSCRUM -- 4 Case Study -- 5 Case Study Results -- 6 Discussion of Results -- 7 Conclusion and Future Work -- References -- A Scoping Review of the Use of Blockchain and Machine Learning in Medical Imaging Applications -- 1 Introduction -- 2 Methods -- 3 Results -- 3.1 Studies' Selection -- 3.2 Demographic Characteristics -- 3.3 Purposes of the Studies -- 3.4 Experimental Characteristics of the Studies -- 4 Discussion and Conclusion -- References -- The Role of Electronic Health Records to Identify Risk Factors for Developing Long COVID: A Scoping Review -- 1 Introduction -- 2 Methods -- 3 Results -- 3.1 Studies' Selection -- 3.2 Geographical Distribution -- 3.3 Studies' Design -- 3.4 Risk Factors -- 4 Discussion -- 5 Conclusion -- References -- Machine Learning Approaches to Support Medical Imaging Diagnosis of Pancreatic Cancer - A Scoping Review -- 1 Introduction -- 2 Methods -- 2.1 Databases Search -- 2.2 Inclusion and Exclusion Criteria -- 2.3 Selection Procedures -- 2.4 Synthesis and Reporting -- 3 Results -- 3.1 Selection Process -- 3.2 Demographic Characteristics of the Included Studies -- 3.3 Experimental Characteristics of the Included Studies -- 4 Discussion -- 5 Conclusion -- References -- Virtual Reality in the Pain Management of Pediatric Burn Patients, A Scoping Review -- 1 Introduction -- 2 Methods -- 3 Results -- 3.1 Selection of the Studies -- 3.2 Geographical Distribution -- 3.3 Studies' Design and Participants -- 3.4 VR Interventions -- 3.5 Clinical Outcomes -- 4 Discussion and Conclusion -- References -- Defining the "Smart Hospital": A Literature Review -- 1 Introduction -- 2 Literature Review -- 2.1 Theoretical Background -- 2.2 Smart Hospital Equipment and Systems -- 2.3 Smart Hospital Services -- 3 A Comparison of Terms -- 3.1 Agile Hospital. , 3.2 Green Hospital -- 3.3 Hybrid Hospital -- 4 Conclusions and Future Thoughts -- References -- Deep Learning for Healthcare: A Web-Microservices System Ready for Chest Pathology Detection -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Front-End Development -- 3.2 Back-End Development -- 3.3 AI Model Integration and Pathology Prediction -- 4 Results -- 4.1 Performance Evaluation of the Model -- 4.2 AI Explainability Integration -- 5 Discussion -- 6 Conclusions -- 7 Future Works -- References -- Risk Factors in the Implementation of Information Systems in a Federal University Hospital -- 1 Introduction -- 2 Related Work -- 3 Theoretical Framework -- 3.1 Information Technology Risk -- 3.2 Hospital Information System -- 3.3 Implementation of the Management Application for University Hospitals - AGHU -- 3.4 Description of the Risk Factors Identified in the Literature and Presented by Santos et al. (2020) -- 4 Methodology -- 5 Results -- 5.1 Profile of Specialists by Length of Service -- 5.2 Risk Factor (FR1): Change of Environment -- 5.3 Risk Factor (FR2): Difficulty in Using the System -- 5.4 Risk Factor (FR3): Data Manipulation Failure -- 5.5 Risk Factor (FR4): Lack of Resources -- 5.6 Risk Factor (FR5): Emergence of New Requirements -- 5.7 Risk Factor (FR6): Installation Problem -- 5.8 Risk Factor (FR7): Crashing and Restart Issues -- 5.9 Risk Factor (FR8): Testers Don't Do a Good Job -- 5.10 Risk Factor (RF9): Effect on the Environment -- 5.11 Risk Factor (FR10): Too Many Software Failures -- 5.12 Risk Factor (FR11): User's Resistance to Change -- 5.13 Other Risk Factors Identified -- 5.14 Relative Frequency by Response Category -- 5.15 Degree of Agreement of Answers -- 5.16 TreeMap: Percentage of Comparison of the Risk Factors Found in the Literature in Relation to the Risk Factors Identified in the Implementation of the AGHU. , 6 Conclusion -- References -- The Challenges of Blockchain in Healthcare Entrepreneurship -- 1 Introduction -- 2 Theories and Concepts -- 3 Applications of Blockchain to Entrepreneurial Health Projects -- 4 Challenges -- 5 Discussion -- 6 Conclusion and Further Research -- References -- Determinants Associated with Treatment Discontinuation in Tacna Health Network Tuberculosis Patients -- 1 Introduction -- 2 Method -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- Comprehensive Analysis of Feature Extraction Methods for Emotion Recognition on Motor Imagery from Multichannel EEG Recordings -- 1 Introduction -- 2 Related Work -- 3 Background and Theory -- 3.1 Notch Filtering -- 3.2 High-Pass Filtering -- 3.3 Down-Sampling Filter -- 3.4 CAR Montage Filter -- 3.5 Statistical Features -- 3.6 Wavelet Analysis Features -- 3.7 Higher Order Spectra Features -- 3.8 Hjorth Features -- 3.9 Fractal Dimension Features -- 3.10 GSVM Classifier -- 3.11 CART Classifier -- 4 Methodology -- 4.1 Dataset -- 4.2 Design -- 4.3 Implementation -- 5 Experiments and Results -- 5.1 Experimental Setup -- 5.2 Evaluation Metrics -- 5.3 Results -- 6 Discussion -- 7 Conclusion -- References -- Control of Respiratory Ventilators Using Boussignac Valve -- 1 Introduction -- 2 Model of Respirator-Human Interaction Using Boussignac Valve Simulator -- 2.1 Model of the Boussignac Valve and Control System -- 2.2 Compartment Model of Lung -- 2.3 System Control Based on Boussignac Valve -- 3 Conclusion -- References -- Deep Learning Brain MRI Segmentation and 3D Reconstruction: Evaluation of Hippocampal Atrophy in Mesial Temporal Lobe Epilepsy -- 1 Introduction -- 2 Subjects and MR Imagining -- 3 Proposed Approach for the 2D Image Segmentation and 3D Objects Asymmetry Analysis -- 3.1 Preprocessing and Data Augmentation -- 3.2 Post-processing. , 3.3 Hippocampus Volume and Asymmetry Index Computing.

Weitere Ausg.: ISBN 3-031-60217-X

Sprache: Englisch

UID:

Umfang: XXI, 274 p. 75 illus., 57 illus. in color. , online resource.

Ausgabe: 1st ed. 2024.

ISBN: 9783031602184

Serie: Lecture Notes in Networks and Systems, 986

Inhalt: This book is composed by a selection of articles from the 12th World Conference on Information Systems and Technologies (WorldCIST'24), held between 26 and 28 of March 2024, at Lodz University of Technology, Lodz, Poland. WorldCIST is a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences and challenges of modern Information Systems and Technologies research, together with their technological development and applications. The main and distinctive topics covered are: A) Information and Knowledge Management; B) Organizational Models and Information Systems; C) Software and Systems Modeling; D) Software Systems, Architectures, Applications and Tools; E) Multimedia Systems and Applications; F) Computer Networks, Mobility and Pervasive Systems; G) Intelligent and Decision Support Systems; H) Big Data Analytics and Applications; I) Human-Computer Interaction; J) Ethics, Computers and Security; K) Health Informatics; L) Information Technologies in Education; M) Information Technologies in Radiocommunications; and N) Technologies for Biomedical Applications. The primary market of this book are postgraduates and researchers in Information Systems and Technologies field. The secondary market are undergraduates and professionals as well in Information Systems and Technologies field.

Anmerkung: Maritime Management Ensemble Learning System -- Stock Market Prediction Integrating Explainable AI with Conv2D Models for Candlestick Image Analysis -- Resources optimization and value based prioritization for at risk cultural heritage assets management -- Expert Systems in Information Security A Comprehensive Exploration of Awareness Strategies Against Social Engineering Attacks -- Collaborative filtering recommendation systems based on deep learning An Experimental Study -- Assessment of LSTM and GRU models to predict the electricity production from biogas in a Wastewater Treatment Plant -- Fusing Temporal and Contextual Features for Enhanced Traffic Volume Prediction -- Target vs One and Target vs All classification of epilepsy using deep learning technique.

In: Springer Nature eBook

Weitere Ausg.: Printed edition: ISBN 9783031602177

Weitere Ausg.: Printed edition: ISBN 9783031602191

Sprache: Englisch

DOI: 10.1007/978-3-031-60218-4

URL: https://doi.org/10.1007/978-3-031-60218-4