Design of Online Monitoring System for High-voltage Power Transmission Equipment Based on LoRa Technology by WANG Yang, XU Yang, LIU Yang, XUE Yifeng, GAO Kun, WANG Jihong

“…The real-time transmission of online monitoring data for high-voltage transmission equipment in remote areas is a difficult problem in practical applications due to the lack of network. …”
Get full text

Research on intelligent routing with VAE-GAN in the internet of body. by Song Qian, Tianping Zhang, Siping Hu

“…It achieves load balancing of the entire network and avoids network congestion. The average throughput is much higher than that of traditional routing, and the advantage is more obvious under high load.…”
Get full text

Bearing Remaining Useful Life Prediction Based on AdCNN and CWGAN under Few Samples by Junfeng Man, Minglei Zheng, Yi Liu, Yiping Shen, Qianqian Li

“…Firstly, a novel prognostic framework is proposed, which is comprised of conditional Wasserstein distance-based generative adversarial networks (CWGAN) and adversarial convolution neural networks (AdCNN), which can stably generate high-quality training samples to augment the bearing degradation dataset and solve the problem of few samples. …”
Get full text

D2D cooperative caching strategy based on graph collaborative filtering model by Ningjiang CHEN, Linming LIAN, Pingjie OU, Xuemei YUAN

“…A D2D cooperative caching strategy based on graph collaborative filtering model was proposed for the problem of difficulty in obtaining sufficient data to predict user preferences in device-to-device (D2D) caching due to the limited signal coverage of base stations.Firstly, a graph collaborative filtering model was constructed, which captured the higher-order connectivity information in the user-content interaction graph through a multilayer graph convolutional neural network, and a multilayer perceptron was used to learn the nonlinear relationship between users and content to predict user preferences.Secondly, in order to minimize the average access delay, considering user preference and cache delay benefit, the cache content placement problem was modeled as a Markov decision process model, and a cooperative cache algorithm based on deep reinforcement learning was designed to solve it.Simulation experiments show that the proposed caching strategy achieves optimal performance compared with existing caching strategies for different content types, user densities, and D2D communication distance parameters.…”
Get full text

ABAC access control policy generation technique based on deep learning by Aodi LIU, Xuehui DU, Na WANG, Rui QIAO

“…To solve the problem of automatic generation of access control policies, an access control policy generation framework based on deep learning was proposed.Access control policy based on attributes could be generated from natural language texts.This technology could significantly reduce the time cost of access control policy generation and provide effective support for the implementation of access control.The policy generation problem was decomposed into two core tasks, identification of access control policy sentence and access control attribute mining.Neural network models such as BiGRU-CNN-Attention and AM-BiLSTM-CRF were designed respectively to realize identification of access control policy sentence and access control attribute mining, so as to generate readable and executable access control policies.Experimental results show that the proposed method has better performance than the benchmark method.In particular, the average F1-score index can reach 0.941 in the identification task of access control policy sentence, which is 4.1% better than the current state-of-the-art method.…”
Get full text

Novel quality of service-oriented Spark job scheduler by HE Yulin, MO Peiheng, Fournier-Viger Philippe, HUANG Zhexue

“…These clusters are required to efficiently handle the Spark job scheduling problem so as to meet the QoS requirements of various users, such as reducing the cost of resource usage and shortening the job response time. …”
Get full text

A novel quality of service-oriented Spark job scheduler by HE Yulin, MO Peiheng, Fournier-Viger Philippe, HUANG Zhexue

“…These clusters are required to efficiently handle the Spark job scheduling problem so as to meet the QoS requirements of various users, such as reducing the cost of resource usage and shortening the job response time. …”
Get full text

Optimization of a Semiflexible Demand-Responsive Feeder System in Suburban Areas Using a Memetic Algorithm by Fabio Sartori Vieira, Kenneth Sorensen, Pieter Vansteenwegen

“…A memetic algorithm is developed to optimize this demand-responsive system. For a network with 25 bus stops served hourly by three lines and with an average demand of 20 requests per hour, the memetic algorithm is demonstrated to reduce the passenger waiting time with almost 50% in comparison with a traditional system operating in the same network with fixed routes and timetable.…”
Get full text

Data poisoning attack detection approach for quality of service aware cloud API recommender system by Zhen CHEN, Wenchao QI, Taiyu BAO, Limin SHEN

“…To solve the problem that existing studies usually assumed that the QoS data of cloud API recommender system was reliable, ignoring the data poisoning attack on cloud API recommender system by malicious users in open network environment, a data poisoning attack detection approach based on multi-feature fusion was proposed.Firstly, a user connected network graph was constructed based on the designed similarity function, and users’ neighborhood features were captured using Node2vec.Secondly, sparse auto-encoder was used to mine user QoS deep feature, and user interpretation feature based on QoS data weighted average deviation was designed.Furthermore, a fake user detection model based on support vector machine was established by integrating user neighborhood feature, QoS deep feature, and interpretation feature, the model parameters were learned using grid search and alternating iterative optimization strategy to complete fake user detection.Finally, the effectiveness and superiority of the proposed approach were verified through extensive experiments, realizing the poison attack defense against QoS aware cloud API recommender system at the data side.…”
Get full text

A Recognition Model Based on Multiscale Feature Fusion for Needle-Shaped <i>Bidens</i> L. Seeds by Zizhao Zhang, Yiqi Huang, Ying Chen, Ze Liu, Bo Liu, Conghui Liu, Cong Huang, Wanqiang Qian, Shuo Zhang, Xi Qiao

“…The results show that the average accuracy and average F1-score of the multiscale feature fusion deep residual network on the test set are 93.81% and 94.44%, respectively, and the numbers of floating-point operations per second (FLOPs) and parameters are 5.95 G and 6.15 M, respectively. …”
Get full text

Two-Timescale Cross-Layer Design for URLLC Over Parallel Fading Channels With Imperfect CSI by Hongsen Peng, Meixia Tao

“…Specifically, we formulate a two-timescale total average power minimization problem under reliability, latency, and peak power constraints. …”
Get full text

Inversion model of stress state reconstruction for geological hazard pipelines based on digital twin by Xue Luning, Tian Mingliang, Zhao Juncheng

Get full text

Enhancing Portfolio Optimization: A Two-Stage Approach with Deep Learning and Portfolio Optimization by Shiguo Huang, Linyu Cao, Ruili Sun, Tiefeng Ma, Shuangzhe Liu

“…The portfolio selection problem has been a central focus in financial research. …”
Get full text

Hydrological Response to Climate Change: McGAN for Multi-Site Scenario Weather Series Generation and LSTM for Streamflow Modeling by Jian Sha, Yaxin Chang, Yaxiu Liu

“…This study focuses on the impacts of climate change on hydrological processes in watersheds and proposes an integrated approach combining a weather generator with a multi-site conditional generative adversarial network (McGAN) model. The weather generator incorporates ensemble GCM predictions to generate regional average synthetic weather series, while McGAN transforms these regional averages into spatially consistent multi-site data. …”
Get full text

multi-objective mathematical model for optimizing the collection and recycling of urban waste under conditions of uncertainty(The subject of study : Karaj city) by Mohsen Bijanpoor, Reza Ehtesham Rasi, Davood Gharakhany

“…In order to design the network, a mixed integer programming problem is designed, which includes two economic and social objectives. …”
Get full text

Strategic deployment of roadside units for effective vehicle-to-infrastructure communication to limit road accidents by Paule Kevin Nembou Kouonchie, Willy Stephen Tounsi Fokui, Danube Kirt Ngongang Wandji

“…The Kilimani–Hurlingham road network, a section of the Nairobi Road network, is used to test this model. …”
Get full text

Research on license plate recognition based on graphically supervised signal-assisted training by Dianwei Chi, Zehao Jia, Lizhen Liu

“…We use the License Plate Recognition Network (LPRNet) as the base model. To enhance its accuracy, we incorporate graphically supervised signals for assisted training. …”
Get full text

MHOE-DETR: A Ship Detection Method for Small and Fuzzy Targets Based on Satellite Remote Sensing Image Data by Zhuhua Hu, Xiyu Fan, Yaochi Zhao, Wei Wu, Jie Liu

“…The network groups and processes input features in parallel, integrating both low-dimensional and high-dimensional features to alleviate the information bottleneck problem. …”
Get full text

Intelligent optimization method for hazardous materials transportation routing with multi-mode and multi-criterion collaborative constraints by Fan Chen, Qing Zhu

“…Abstract Hazardous materials transportation route optimization problem is a pressing issue, and multi-dimensional evaluation criteria and diversified transportation modes complicate the problem. …”
Get full text

Propagating and Stationary Bright Knots in the Quiet Solar Corona by Shaoxuan Tong, Jun Zhang

“…The stationary knots are located at the locations of network fields with an average flux density of 14.4 Gauss. …”
Get full text