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Xingjuan Cai
Researcher at Taiyuan University of Science and Technology
Publications - 101
Citations - 3921
Xingjuan Cai is an academic researcher from Taiyuan University of Science and Technology. The author has contributed to research in topics: Particle swarm optimization & Multi-swarm optimization. The author has an hindex of 25, co-authored 86 publications receiving 2408 citations. Previous affiliations of Xingjuan Cai include Tongji University.
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Detection of Malicious Code Variants Based on Deep Learning
TL;DR: A novel method that used deep learning to improve the detection of malware variants using a convolutional neural network that could extract the features of the malware images automatically was proposed.
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A Hybrid BlockChain-Based Identity Authentication Scheme for Multi-WSN
TL;DR: A blockchain based multi-WSN authentication scheme for IoT is proposed and the analysis of security and performance shows that the scheme has comprehensive security and better performance.
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Personalized Recommendation System Based on Collaborative Filtering for IoT Scenarios
TL;DR: A novel recommendation model based on time correlation coefficient and an improved K-means with cuckoo search (CSK-me means) called TCCF is proposed, which can provide a higher quality recommendation by analyzing the user's behaviors and cluster similar users together for further quick and accurate recommendation.
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Optimal LEACH protocol with modified bat algorithm for big data sensing systems in Internet of Things
TL;DR: Simulation results prove that the bat algorithm with weighted harmonic centroid (WHCBA) strategy is superior to other algorithms and can save more energy compared to the standard LEACH protocol.
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An under‐sampled software defect prediction method based on hybrid multi‐objective cuckoo search
TL;DR: A hybrid multi‐objective cuckoo search under‐sampled software defect prediction model based on SVM (HMOCS‐US‐SVM) is proposed to solve synchronously above two problems of class imbalance in datasets and parameter selection of Support Vector Machine.