Titlebook: Big Data Technologies and Applications; 13th EAI Internation Zhiyuan Tan,Yulei Wu,Min Xu Conference proceedings 2024 ICST Institute for Com

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书目名称Big Data Technologies and Applications被引频次学科排名




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书目名称Big Data Technologies and Applications年度引用学科排名




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书目名称Big Data Technologies and Applications读者反馈学科排名

不法行为

Can Federated Models Be Rectified Through Learning Negative Gradients?e clients. However, FL is vulnerable to malicious attacks, such as poisoning attacks, and is challenged by the GDPR’s “right to be forgotten”. This paper introduces a negative gradient-based machine learning technique to address these issues. Experiments on the MNIST dataset show that subtracting lo

披肩

erythema

STLGCN: Spatial-Temporal Graph Convolutional Network for Long Term Traffic Forecasting reasonable travel plans. Current mainstream traffic forecasting models are developed based on spatial-temporal graph convolutional neural networks, in which appropriate graph structures must be generated in advance. However, most existing graph generation approaches learn graph structures based on

制度

甜得发腻

Revocable Attribute-Based Encryption Scheme with Cryptographic Reverse Firewallss become a viable option to tackle this problem. Using a set of attributes, data owners can encrypt data with ABE, and data is only accessible by users with the required attributes and authorization. However, there are various limitations associated with the traditional CP-ABE scheme, such as embedd

健壮

Dysarthria

A Bibliometric Analysis and Systematic Review of a Blockchain-Based Chain of Custody for Digital Eviten prone to security and integrity issues. In recent years, the use of blockchain technology has emerged as a promising solution to enhance the security, transparency, and integrity of digital evidence. This systematic review critically evaluates the current state of research on blockchain-based ch

inventory

Forest Fire Prediction Using Multi-Source Deep Learningydrometric and weather) in the probability prediction of forest fires using deep learning. The results showed that the weather model had the best predictive power (average .). The lightning model had an average ., while the hydrometric model had an average .. The single-source models were then merge

MOTTO

Research on Preprocessing Process for Improved Image Generation Based on Contrast Enhancement information about the object‘s shape and size. These phenomena also decrease the quality of image data, with outdoor quality being significantly lower than indoor quality. As deep learning-based object recognition algorithms heavily rely on image quality, a preprocessing process is required to impr