Kooperativer Bibliotheksverbund

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Format: 1 online resource (570 pages)

Edition: First edition.

ISBN: 3-031-56950-4

Series Statement: Lecture Notes in Networks and Systems Series ; Volume 956

Note: Intro -- Preface -- ACR'2024 -- Contents -- Data Analytics Engineering -- Evaluating Study Between Vision Transformers and Pre-trained CNN Learning Algorithms to Classify Breast Cancer Histopathological Images -- 1 Introduction -- 1.1 Breast Cancer Statistics in KSA -- 1.2 Computer-Aided Methods are Needed to Diagnose Cancer -- 1.3 Comparing Vision Transformers and CNN -- 2 Literature Review -- 2.1 The Transformers -- 2.2 The Vision Transformer (ViT) -- 2.3 The Residual Network -- 2.4 Related Work -- 3 The Dataset -- 4 The Synthesis and Analysis Phases -- 5 Research Results and Discussions -- 5.1 ResNet18 vs ViT16 -- 5.2 ViT16 With Augmentation vs ViT 16 Without Augmentation -- 6 Conclusions -- 7 Future Work -- References -- TNEST: Training Sparse Neural Network for FPGA Based Edge Application -- 1 Introduction -- 2 Literature Review -- 3 Motivation for Edge Computing -- 4 Constrained Neural Architecture Generator -- 5 Methodology -- 5.1 Sparsity Mechanism -- 5.2 Connections Re-wiring -- 5.3 Layer Size Tuning -- 6 Experiments Evaluation -- 6.1 Experiment Testbench -- 6.2 Software Implementation -- 6.3 FPGA Implementation -- 7 Conclusion -- References -- Public Policy Decision Making: Confirmatory Factor Analysis -- 1 Introduction -- 2 Public Policy Decision Making -- 2.1 Sample and Descriptive Statistics -- 3 Reliability of the Scales -- 3.1 Confirmatory Factor Analysis -- 4 Conclusion -- References -- An Analytical Study of Traffic Accidents in Connecticut, USA Using Python -- 1 Introduction -- 2 Background -- 3 Method -- 3.1 Data Collection -- 3.2 Data Inspection -- 3.3 Data Cleaning and Preprocessing -- 4 Results -- 4.1 Temporal Analysis -- 4.2 Town-Wise Analysis -- 4.3 Hourly Analysis -- 4.4 Vehicle Color Analysis -- 4.5 Driver Age Analysis -- 5 Conclusion -- References -- Improving the Efficiency of Multimodal Approach for Chest X-Ray. , 1 Introduction -- 2 Literature Review -- 3 Data -- 4 Methods -- 4.1 Image Submodel -- 4.2 Text Submodel -- 4.3 Multimodal Fusion Techniques -- 4.4 Modification for Enhanced Comparison -- 4.5 Model Improvement -- 4.6 Training Parameters -- 4.7 Output Activation Function -- 5 Model Evaluation Metrics -- 6 Results and Discussion: Proposed Model vs Baseline Model -- 7 Conclusion -- References -- Wrist Crack Classification Using Deep Learning and X-Ray Imaging -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Dataset Descriptions -- 3.2 Data Preprocessing -- 3.3 Proposed CNN -- 3.4 Training Process of Proposed Method -- 3.5 Methodology -- 4 Results and Discussions -- 4.1 Results Analysis -- 5 Conclusions and Future Work -- References -- Improving Weeds Detection in Pastures Using Illumination Invariance Techniques -- 1 Introduction -- 1.1 Motivations and Objectives -- 1.2 The Data Description -- 2 Methodology -- 2.1 Methods -- 2.2 Image Thresholding Technique -- 2.3 Pre-processing Technique -- 2.4 Framework -- 2.5 Training -- 2.6 The Support Vector Machine (SVM) Algorithm -- 2.7 Cross Validation -- 2.8 Confusion Matrix -- 3 Results -- 4 Discussion -- 4.1 Future Work -- 5 Conclusion -- References -- Credit Card Batch Processing in Banking System -- 1 Introduction -- 1.1 Batch Processing -- 1.2 Credit Card Transaction -- 1.3 Customer Profile Analyzer/Database -- 2 Literature Review -- 3 Key Findings and Context -- 3.1 Credit Card Fraud and Recent Trends -- 3.2 Pyspark and Apache Airflow -- 4 Result and Discussion -- 5 Conclusion -- References -- Irregular Frame Rate Synchronization of Multi-camera Videos for Data-Driven Animal Behavior Detection -- 1 Introduction -- 2 Related Work -- 2.1 Software-Based Methods -- 2.2 Hardware-Based Methods -- 2.3 Summary of Literature Studies. , 3 Proposed Irregular Frame Rate Synchronization Method for Pre-recorded Multi-camera Videos -- 3.1 Overview of Our Multi-camera Video setup and Irregular Frame Rate Problem -- 3.2 SIFT-Based Synchronization Experiment -- 3.3 Proposed Timestamp-Based Irregular Frame Rate Synchronization -- 3.4 Results and Discussion -- 4 Conclusions and Future Work -- References -- Increasing the Accuracy of a Deep Learning Model for Traffic Accident Severity Prediction by Adding a Temporal Category -- 1 Introduction and Related Work -- 1.1 Introduction -- 1.2 Related Work -- 2 Methodology -- 2.1 Dataset -- 2.2 Pre-processing Data -- 2.3 Temporal Features -- 2.4 Post-processing Data -- 2.5 New CNN-2D Model -- 2.6 Comparison Metrics -- 2.7 Comparison Models -- 3 Results -- 3.1 Liverpool -- 3.2 Southwark -- 3.3 Comparison Summary -- 4 Conclusions -- References -- 2ARTs: A Platform for Exercise Prescriptions in Cardiac Recovery Patients -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 The Classification Model -- 4.1 The Dataset, Data Cleaning and Pre-processing -- 4.2 Modeling -- 4.3 Evaluation -- 5 Development of the 2ARTs Digital Platform -- 5.1 Main Software Features -- 5.2 AI Model and Digital Platform Integration -- 6 Discussion and Conclusion -- References -- Understanding Consumers Attitudes Towards Sustainability -- 1 Introduction -- 2 Related Literature -- 2.1 Brand Strategy Methodology -- 2.2 Sustainability in Business -- 2.3 Related Works -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Overview -- 3.3 Tensor-Based Clustering Method -- 3.4 Results -- 4 Conclusion -- References -- Enriching Ontology with Named Entity Recognition (NER) Integration -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Entity Selection Process -- 3.2 Dataset -- 3.3 Data Preprocessing -- 3.4 BERT -- 3.5 DistilBERT -- 3.6 RoBERTa -- 4 Results and Discussion. , 5 Conclusion and Future Work -- References -- Data Transfer Methods and Strategies: Unified Replication Model Using Trees -- 1 Introduction -- 1.1 Primary-Backup Replication (PBR) -- 1.2 Chain Replication (CR) -- 1.3 Unidirectional Replication (UR) -- 1.4 Dealing with the Failure of a Replica -- 2 Proposed Enhancement -- 2.1 Using Binary Trees in Unified Replication -- 2.2 Using AVL Trees in Unified Replication Structure -- 2.3 Using a Replicated AVL Tree -- 2.4 Tree-Based Replication Using AVL has Many Benefits -- 2.5 Effective Replication Using AVL Trees for Updates -- 3 Comparison and Results -- 4 Case Study and Discussion -- 4.1 Implementing an AVL Tree (Case Study 1) -- 4.2 Implementing a Binary Tree (Case Study 2) -- 5 Conclusion -- References -- Optimized Vehicle Repair Cost by Means of Smart Repair Distribution Model -- 1 Introduction -- 2 Methodology -- 2.1 Experimental Setup -- 3 Results and Discussion -- 3.1 Feature Selection -- 3.2 Interpretation -- 4 Conclusions -- References -- Classification of Eye Disorders Using Deep Learning and Machine Learning Models -- 1 Introduction -- 2 Dry Eye Disease Overview -- 2.1 Cause, Risk Factors, and Symptoms -- 2.2 Dry Eye Disease Subtypes -- 2.3 Methods Used for DED Diagnosis -- 3 Related Work -- 4 Our Work -- 4.1 Data Source and Preprocessing -- 4.2 Experimentation -- 4.3 Evaluation Metrics -- 4.4 Results -- 5 Discussion -- 6 Conclusion -- References -- Effects of Parallel and Distributed Learning on CNN Performance for Lung Disease Classification -- 1 Introduction -- 2 Material and Methods -- 2.1 Convectional Neural Network -- 2.2 Data Acquisition and Preprocesssing -- 3 Results and Discussion -- 4 Conclusions -- References -- A Federated Learning Anomaly Detection Approach for IoT Environments -- 1 Introduction -- 2 Related Work -- 3 Federated Learning Anomaly Detection (FLAD) Approach. , 3.1 Problem Formulation in Federated Learning -- 3.2 Anomaly Detection in Federated Setting -- 4 Data Preparation -- 5 Experiment and Results -- 5.1 Experiment Setting -- 5.2 Evaluation Metrics -- 5.3 Results and Analysis -- 6 Conclusion and Future Work -- References -- Taxonomy of AR to Visualize Laparoscopy During Abdominal Surgery -- 1 Introduction -- 2 Literature Review -- 3 Proposed System Components -- 4 Proposed System Components Evaluation and Validation -- 5 Discussion -- 6 Conclusion -- References -- Cybersecurity Engineering -- Open Platform Infrastructure for Industrial Control Systems Security -- 1 Introduction -- 1.1 ICS Testbed and Training Workbench -- 1.2 Contributions to ICS Security Training -- 2 Background and Related Works -- 2.1 Prior and Similar Works -- 2.2 Digital Twins of Industrial Control Systems -- 2.3 Open Platform Infrastructure -- 3 ICS Open Platform Infrastructure (ICS-OPI) Development -- 3.1 Virtualized PLCs and ICS Protocols -- 3.2 Small Footprint in Isolation -- 3.3 Realization of an IT-OT Network Infrastructure -- 3.4 Development of ICS Digital Twins -- 3.5 Human Machine Interface for the ICS -- 3.6 Simulating ICS Security Attacks and Defense -- 4 Deployment and Dissemination -- 5 Conclusion and Future Directions -- References -- Towards Hybrid NIDS: Combining Rule-Based SIEM with AI-Based Intrusion Detectors -- 1 Introduction, Problem Statement and Research Questions -- 1.1 Background and Context -- 1.2 Problem Statement -- 1.3 Research Questions -- 2 Related Works -- 3 Proposition of the Combined SIEM-AI Approach -- 3.1 High-Level Architecture of the Proposed Combined SIEM-AI Approach -- 3.2 SIEM Rule-Based Approach -- 3.3 AI-Based Intrusion Detectors -- 4 Experimental Setup and Results -- 5 Discussion and Way Forward -- 5.1 Discussion -- 5.2 Threats to Validity -- 5.3 Future Work -- 6 Conclusions -- References. , Security Challenges and Solutions in Smart Cities.

Additional Edition: ISBN 3-031-56949-0

Language: English