Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications

11th International Conference on Future Data and Security Engineering, FDSE 2024, Binh Duong, Vietnam, November 27-29, 2024, Proceedings, Part I
Herausgegeben:Dang, Tran Khanh; Küng, Josef; Chung, Tai M.

• Broschiertes Buch

Produktbeschreibung

This two-volume set CCIS 2309-2310 constitutes the refereed proceedings of the 11th International Conference on Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications, FDSE 2024, held in Binh Duong, Vietnam, during November 27-29, 2024.

The 44 full papers, 12 short papers and 1 keynote paper were carefully reviewed and selected from 189 submissions. They were organized in topical sections as follows: advances in machine learning for big data analytics; security and privacy engineering; data analytics and healthcare systems; smart city and industry 4.0 applications; big data query processing and optimization; and short papers; security and data engineering.

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Produktdetails

• Communications in Computer and Information Science 2309
• Verlag: Springer / Springer Nature Singapore / Springer, Berlin
• Artikelnr. des Verlages: 978-981-96-0433-3
• Seitenzahl: 396
• Erscheinungstermin: 27. November 2024
• Englisch
• Abmessung: 235mm x 155mm x 22mm
• Gewicht: 598g
• ISBN-13: 9789819604333
• ISBN-10: 9819604338
• Artikelnr.: 71902747

Inhaltsangabe

.- Advances in Machine Learning for Big Data Analytics.
.- Parameters Identification Based on Deep Neural Networks for the Microplane Material Model of UHPC under Uni-axial Compression.
.- Predicting Bitcoin's Price: A Critical Review of Forecasting Models and Method.
.- Enhancing Explainable Herbal Recognition with Vision Transformer Features and SVM.
.- Session-based Product Recommendation using Graph Neuron Net-works.
.- Improving The Polyp Image Segmentation Based on Parallel Reverse Attention Network.
.- Security and Privacy Engineering.
.- Adversarial Perturbations for License Plate Information Privacy.
.- IU-VecCert: A Scalable Credentials Issuance Protocol Using Non-Interactive Vector Commitment Scheme.
.- A Study on Deep Graph Neural Networks for Security Vulnerabilities Detection in Web Applications.
.- Secure as a Service VNF: A Proposed VNF Architecture for Proac-tive Malware Detection during File Downloads in Enterprises.
.- Data Analytics and Healthcare Systems.
.- Enhancing Efficiency of Multi-Label X-Ray Image Classification with Self Supervised Learning Based on Compact Swin Transformers.
.- Curated Colon Disease Diagnosis using Principal Component Analy-sis and Deep Learning with Integrated Gradient.
.- Clinical Data-Driven Explainable AI for COVID-19 Treatment Out-come Analysis.
.- Medical Signal Analysis for Early ECG Classification using Machine Learning Models.
.- Detection and Classification of Liver Lesions Using Vision Trans-former and Active Learning.
.- Detection and Classification of Osteoarthritis using Vision Trans-former in Distributed Environment.
.- Smart City and Industry 4.0 Applications.
.- Legal-Onto Model for Efficient Land Law Updates in Vietnam.
.- Exploring Distillation Models for Cultural Heritage Preservation: Traditional Vietnamese Instruments.
.- Optimizing Customer Feedback Analysis with BERT - based Senti-ment Classification: A Case Study of Toyota Dong Sai Gon.
.- Estimating Traffic Density Using Convolutional Neural Networks Based on Crowd Counting.
.- MedQAS: A Medical Question Answering System Based on Finetun-ing Large Language Models.
.- Machine Learning UHF-RFID to Support Video Tracking and Rec-ommendation for Attendance System.
.- Short Papers: Security and Data Engineering.
.- A Pronunciation Practice System Based on Pre-Trained Deep Learn-ing Models.
.- An Automatic System Architecture Applying XAI for Dataset Fea-ture Selection in Supervised Learning.
.- Entity Labeling and Data Analysis Framework.
.- SVSD: A Comprehensive Framework for Vietnamese Sentiment Analysis.
.- A YoloX-based Approach for Detecting Human and Classifying their own pet to Monitor and Improve Services at the Veterinary clinic.
.- Intrusion detection in Internet of Medical Things.