E-learning systems improve day by day. Therefore, it is important to monitor and evaluate student performance to provide targeted content. This paper focuses on a model for intelligent E-learning systems that can iden...
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This document thoroughly explores the Elastic Stack, comprising Elasticsearch, Logstash, Kibana, and Beats, emphasizing its effectiveness in real-time data analysis, log handling, and visualization. It examines the es...
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This paper uses a method based on the YOLOv5s network to study the real-time traffic light detection task in the vehicle-mounted intelligent system. Due to the limitation of computing resources on the actual vehicle a...
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The proceedings contain 299 papers. The topics discussed include: research on lightning fault analysis and lightning protection application of 500 kV transmission line;algorithm-based optimization of YOLOv5s model for...
ISBN:
(纸本)9798350374315
The proceedings contain 299 papers. The topics discussed include: research on lightning fault analysis and lightning protection application of 500 kV transmission line;algorithm-based optimization of YOLOv5s model for robot trajectory detection study;boosting the feature extraction power of convolutional networks via mixed-weighting;deep learning based optimization of UAV orbital paths;fault prediction for distribution transformers based on stacking;electric field distribution and optimization design of XLPE cable joints under typical defect;research on auxiliary terminal system of power communication operation and maintenance based on augmented reality technology;an improved path planning algorithm for ship track planning based on grey wolf algorithm;and optimizing motion capture data in animation sequences using machine learning techniques.
Federated Learning (FL) has gained popularity for its ability to improve model training while protecting user privacy. However, recent studies have shown that. FL can be vulnerable to active reconstruction attacks by ...
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ISBN:
(纸本)9798350312935
Federated Learning (FL) has gained popularity for its ability to improve model training while protecting user privacy. However, recent studies have shown that. FL can be vulnerable to active reconstruction attacks by dishonest servers. Specifically, a dishonest server can obtain users' private data in numerous ways via gradient inversion based on the core neural network concept of neuron activation. Addressing this style of attack is imperative to preserve user privacy and remains a major challenge due to its sophisticated nature. In this paper, we examine various active reconstniction attacks by a dishonest server and provide comprehensive evaluations to demonstrate their effectiveness and practicality, highlighting the risks associated with FL systems.
With the rapid advancement of data transmission and communication technology, there has been a parallel increase in concerns surrounding privacy and security. Many encryption techniques were introduced to reduce the r...
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As power systems become more intelligent, the intelligent structure of two-ticket system in power grids is key to improving efficiency and safety. This paper investigates the integration of edge computing, artificial ...
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Multimedia datasystems manage complex data types such as text, images, audio, and video. Extensive research and development efforts in multimedia data management systems have been carried out since the1980s. Furtherm...
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ISBN:
(纸本)9798350323856
Multimedia datasystems manage complex data types such as text, images, audio, and video. Extensive research and development efforts in multimedia data management systems have been carried out since the1980s. Furthermore, significant progress has been made on securing such systems. For example, techniques for multilevel security for such systems as well as enforcing access control policies have been developed. More recently, with the advent of big data technologies, data science and Artificial Intelligence, there is a need for managing, analyzing, and securing massive datasystems with heterogeneous data types. This paper first describes the progress that has been made on securing multimedia datasystems and then describes our vision for securing such systems in the era of Artificial Intelligence.
As big data continues to rise, the fusion of information emerges as one of the primary concerns in the fields of computer vision and intelligent transportation systems. A multi-view driver action recognition system ca...
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ISBN:
(纸本)9798350351491;9798350351484
As big data continues to rise, the fusion of information emerges as one of the primary concerns in the fields of computer vision and intelligent transportation systems. A multi-view driver action recognition system can be a key to road safety, especially at nighttime. In fact, driver monitoring from a single view is one of the most challenging task due to the high amount of issues present including occlusion and illumination variation. A multiview driver action recognition system can provide more abundant and complementary driver behavior information which helps to prevent dramatic traffic injuries. In this work, we introduce a multi-viewpoint information fusion system that reliably classifies drivers' actions at nighttime. Experiments on the public and unique realistic dataset, 3MDAD, demonstrate that our proposed approach achieves high recognition accuracy compared to state-of-the-art methods.
With the rise of big data, efficient data handling techniques have become increasingly crucial. Hard drive failure prediction is a critical domain where accurate and timely data handling is paramount. This research pa...
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