Chromatic Dispersion, Nonlinear Parameter, and Modulation Format Monitoring Based on Godard's Error for Coherent Optical Transmission Systems by Lin Jiang, Lianshan Yan, Anlin Yi, Yan Pan, Ming Hao, Wei Pan, Bin Luo, Yves Jaouen

Subjects: “…Digital signal processing…”
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DSC-SeNet: Unilateral Network with Feature Enhancement and Aggregation for Real-Time Segmentation of Carbon Trace in the Oil-Immersed Transformer by Liqing Liu, Hongxin Ji, Junji Feng, Xinghua Liu, Chi Zhang, Chun He

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Ultrasonic guided wave nondestructive testing of anchorage quality of rebar resin bolt based on EMD-PCA by Kesong Fan, Ao Yan, Shaowei Liu, Can Zhang, Youliang Feng, Mengxiong Fu, Deyin He

Subjects: “…Signal analysis and processing…”
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Quantifying Post-Purchase Service Satisfaction: A Topic–Emotion Fusion Approach with Smartphone Data by Peijun Guo, Huan Li, Xinyue Mo

Subjects: “…natural language processing…”
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Abnormal link detection algorithm based on semi-local structure by Haoran SHI, Lixin JI, Shuxin LIU, Gengrun WANG

“…With the research in network science, real networks involved are becoming more and more extensive.Redundant error relationships in complex systems, or behaviors that occur deliberately for unusual purposes, such as wrong clicks on webpages, telecommunication network spying calls, have a significant impact on the analysis work based on network structure.As an important branch of graph anomaly detection, anomalous edge recognition in complex networks aims to identify abnormal edges in network structures caused by human fabrication or data collection errors.Existing methods mainly start from the perspective of structural similarity, and use the connected structure between nodes to evaluate the abnormal degree of edge connection, which easily leads to the decomposition of the network structure, and the detection accuracy is greatly affected by the network type.In response to this problem, a CNSCL algorithm was proposed, which calculated the node importance at the semi-local structure scale, analyzed different types of local structures, and quantified the contribution of edges to the overall network connectivity according to the semi-local centrality in different structures, and quantified the reliability of the edge connection by combining with the difference of node structure similarity.Since the connected edges need to be removed in the calculation process to measure the impact on the overall connectivity of the network, there was a problem that the importance of nodes needed to be repeatedly calculated.Therefore, in the calculation process, the proposed algorithm also designs a dynamic update method to reduce the computational complexity of the algorithm, so that it could be applied to large-scale networks.Compared with the existing methods on 7 real networks with different structural tightness, the experimental results show that the method has higher detection accuracy than the benchmark method under the AUC measure, and under the condition of network sparse or missing, It can still maintain a relatively stable recognition accuracy.…”
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DualAD: Dual adversarial network for image anomaly detection⋆ by Yonghao Wan, Aimin Feng

“…The method incorporates the FC module during the reconstruction training process to impose constraints on the latent space of images, thereby yielding feature representations more conducive to anomaly detection. …”
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Human face localization and detection in highly occluded unconstrained environments by Abdulaziz Alashbi, Abdul Hakim H.M. Mohamed, Ayman A. El-Saleh, Ibraheem Shayea, Mohd Shahrizal Sunar, Zieb Rabie Alqahtani, Faisal Saeed, Bilal Saoud

“…Furthermore, the limited availability of comprehensive datasets containing substantially obscured faces exacerbates the problem, impeding the efficacy of face detection programs. This study presents a new methodology, which incorporates an advanced occluded face detection (OFD) model, in order to enhance feature extraction and detection network. …”
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Laser radiation detection of the fluctuation alpha particle tracks in PADC by R.B. Alkhayat, Ammar T. Zakar, Mushtaq Abed Al-Jubbori, Hana Ihsan Hasan

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Green Apple Detector Based on Optimized Deformable Detection Transformer by Qiaolian Liu, Hu Meng, Ruina Zhao, Xiaohui Ma, Ting Zhang, Weikuan Jia

“…In the process of smart orchard construction, accurate detection of target fruit is an important guarantee to realize intelligent management of orchards. …”
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Research on Fire Detection of Cotton Picker Based on Improved Algorithm by Zhai Shi, Fangwei Wu, Changjie Han, Dongdong Song

“…According to the physical characteristics of cotton and the work characteristics of cotton pickers in the field, during the picking process, there is a risk of cotton combustion. The cotton picker working environment is complex, cotton ignition can be hidden, and fire is difficult to detect. …”
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A privacy-enhanced framework with deep learning for botnet detection by Guangli Wu, Xingyue Wang

“…And most methods are combined with machine learning and deep learning technologies, which require a large amount of training data to obtain high-precision detection models. Therefore, preventing malicious persons from stealing data to infer privacy during the botnet detection process has become an issue worth pondering. …”
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Research on malicious behavior detection based on iOS system by Yuliang WANG, Xiaodong CHEN, Tun WU

“…Firstly,the cases of malicious application of multiple iOS platforms were enumerated.The main malicious behavior of mobile application under iOS platform was analyzed by dissecting the misuse of crime and the bad influence.The key technologies of malicious behavior detection process were studied.The iOS application malicious behavior detection model was put forward.Finally,iOS application malicious behavior detection solution was given.…”
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Research on malicious behavior detection based on iOS system by Yuliang WANG, Xiaodong CHEN, Tun WU

“…Firstly,the cases of malicious application of multiple iOS platforms were enumerated.The main malicious behavior of mobile application under iOS platform was analyzed by dissecting the misuse of crime and the bad influence.The key technologies of malicious behavior detection process were studied.The iOS application malicious behavior detection model was put forward.Finally,iOS application malicious behavior detection solution was given.…”
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Locomotive Maintenance Management System for Crack Detection Standard Operating by 王铁城

“…In order to ensure safe production needs of railway locomotive maintenance system, we develop a set of software of locomotive maintenance management system for crack detection standard operating. The system makeup, field operations control procedure and data process has been introduced. …”
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Survey on model checking based hardware Trojan detection technology by Qizhi ZHANG, Yiqiang ZHAO, Ya GAO, Haocheng MA

“…Hardware Trojan is malicious tampering to the original circuit, which has become the most important security threat of integrated circuit.In order to ensure the safety and reliability of ICs, many hardware Trojan detection methods are proposed.As one of the formal verification methods, model checking can effectively detect the hardware Trojan in the design phase.Firstly, the working principle and process of model checking were described.Secondly, the research progress of hardware Trojan detection technology based on model checking was introduced.Finally, the bottlenecks faced by the current technology were pointed out and the potential research direction was discussed.…”
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An Approach for Prediction of Acute Hypotensive Episodes via the Hilbert-Huang Transform and Multiple Genetic Programming Classifier by Dazhi Jiang, Liyu Li, Bo Hu, Zhun Fan

“…Finally, the multiple genetic programming (Multi-GP) is used to build the classification models for detection of AHE. …”
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Intrusion detection model based on fuzzy theory and association rules by Jianwu ZHANG, Jiasen HUANG, Di ZHOU

“…An intrusion detection model based on fuzzy theory and improved Apriori algorithm was proposed.The BV-Apriori algorithm was used to generate the matching rule base,and the problem of excessive boundary in the continuous data partitioning process was solved by fuzzy set technology.The real-time analysis of the relationship between features and the update of the rule base were completed,and the intrusion detection model BVA-IDS (Boolean vector Apriori-intrusion detection system) was built.The results show that the mining efficiency of the BV-Apriori algorithm is significantly improved when compared with the existing Apriori-BR algorithm,in addition,the BVA-IDS model also performs well on intrusion detection indicators with high detection accuracy,and low false positive rate and false negative rate.…”
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Intrusion detection model based on fuzzy theory and association rules by Jianwu ZHANG, Jiasen HUANG, Di ZHOU

“…An intrusion detection model based on fuzzy theory and improved Apriori algorithm was proposed.The BV-Apriori algorithm was used to generate the matching rule base,and the problem of excessive boundary in the continuous data partitioning process was solved by fuzzy set technology.The real-time analysis of the relationship between features and the update of the rule base were completed,and the intrusion detection model BVA-IDS (Boolean vector Apriori-intrusion detection system) was built.The results show that the mining efficiency of the BV-Apriori algorithm is significantly improved when compared with the existing Apriori-BR algorithm,in addition,the BVA-IDS model also performs well on intrusion detection indicators with high detection accuracy,and low false positive rate and false negative rate.…”
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Detection of selfish nodes based on credit mechanism in opportunistic networks by Zuo-yong TANG, Yi-jia YUAN, Yong-qiang DONG, Guo-xin WU

“…The existence of selfish nodes seriously affects the routing performance of opportunistic networks(OppNet).To protect the OppNet against the nodes’ selfish behavior,a credit-based selfish nodes detection mechanism was proposed to make it possible to keep away from such nodes during the process of message forwarding.The mechanism leverages 2-ACK messages to observe the nodes’behavior.Then the credit value was calculated based on the observation information and accordingly acts as the metric to distinguish the selfish nodes.Simulation results show that,when coupled with various routing algorithms,the mechanism could detect selfish nodes out accurately,and improve network performance effectively in terms of delivery rate and traffic load.…”
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Target Maneuver Detection Method Based on Likelihood Ratio Test by Shao Lei, He Yangchao, Zhao Jin

“…Aiming at the target maneuver detection in antagonistic process, a detection method is proposed based on likelihood ratio test. …”
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