An Oracle Normalized Least Mean Square (NLMS) Algorithm and a Simple Bayesian Detection NLMS Algorithm Robust to Impulse Noise by Hadi Zayyani, Yaser Attar

“…This paper suggests an oracle normalized least-mean-square (NLMS) algorithm and a simple Bayesian detection NLMS impulse noise detection algorithm as an effective adaptive algorithm against impulsive noises. …”
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Fog Visibility Detection of Highway Based on Improved Dark Channel Prior Algorithm by Huiqi Zhang, Yong Liu, Chenxi Wu

“…This paper presents an algorithm for detecting fog visibility in expressway based on improved dark channel prior method, which transforms the difficult problem of detecting visibility through image processing into the problem of calculating atmospheric extinction coefficient. …”
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Research on hybrid intrusion detection based on improved Harris Hawk optimization algorithm by Pengzhen Zhou, Huifu Zhang, Wei Liang

“…Aiming at the problem of low detection accuracy of network traffic data types by traditional intrusion detection methods, we propose an improved Harris Hawk hybrid intrusion detection method to enhance the detection capability. …”
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Outlier detection algorithm based on fast density peak clustering outlier factor by Zhongping ZHANG, Sen LI, Weixiong LIU, Shuxia LIU

“…For the problem that peak density clustering algorithm requires human set parameters and high time complexity, an outlier detection algorithm based on fast density peak clustering outlier factor was proposed.Firstly, k nearest neighbors algorithm was used to replace the density peak of density estimate, which adopted the KD-Tree index data structure calculation of k close neighbors of data objects, and then the way of the product of density and distance was adopted to automatic selection of clustering centers.In addition, the centripetal relative distance and fast density peak clustering outliers were defined to describe the degree of outliers of data objects.Experiments on artificial data sets and real data sets were carried out to verify the algorithm, and compared with some classical and novel algorithms.The validity and time efficiency of the proposed algorithm are verified.…”
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Outlier detection algorithm based on fast density peak clustering outlier factor by Zhongping ZHANG, Sen LI, Weixiong LIU, Shuxia LIU

“…For the problem that peak density clustering algorithm requires human set parameters and high time complexity, an outlier detection algorithm based on fast density peak clustering outlier factor was proposed.Firstly, k nearest neighbors algorithm was used to replace the density peak of density estimate, which adopted the KD-Tree index data structure calculation of k close neighbors of data objects, and then the way of the product of density and distance was adopted to automatic selection of clustering centers.In addition, the centripetal relative distance and fast density peak clustering outliers were defined to describe the degree of outliers of data objects.Experiments on artificial data sets and real data sets were carried out to verify the algorithm, and compared with some classical and novel algorithms.The validity and time efficiency of the proposed algorithm are verified.…”
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Loop-Reduction LLL Algorithm and Architecture for Lattice-Reduction-Aided MIMO Detection by Chun-Fu Liao, Li-Wei Chai, Yuan-Hao Huang

“…We propose a loop-reduction LLL (LR-LLL) algorithm for lattice-reduction-aided (LRA) multi-input multioutput (MIMO) detection. …”
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HRDA-Net: image multiple manipulation detection and location algorithm in real scene by Ye ZHU, Yilin YU, Yingchun GUO

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Auto forensic detecting algorithms of malicious code fragment based on TensorFlow by Binglong LI, Jinlong TONG, Yu ZHANG, Yifeng SUN, Qingxian WANG, Chaowen CHANG

“…In order to auto detect the underlying malicious code fragments in complex，heterogeneous and massive evidence data about digital forensic investigation, a framework for malicious code fragment detecting algorithm based on TensorFlow was proposed by analyzing TensorFlow model and its characteristics.Back-propagation training algorithm was designed through the training progress of deep learning.The underlying binary feature pre-processing algorithm of malicious code fragment was discussed and proposed to address the problem about different devices and heterogeneous evidence sources from storage media and such as AFF forensic containers.An algorithm which used to generate data set about code fragments was designed and implemented.The experimental results show that the comprehensive evaluation index F₁of the method can reach 0.922, and compared with CloudStrike, Comodo, FireEye antivirus engines, the algorithm has obvious advantage in dealing with the underlying code fragment data from heterogeneous storage media.…”
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Community detection algorithm of hybrid node analysis and edge analysis in complex networks by Kun DENG, Qingfeng JIANG, Xingyan LIU

“…The community detection of hybrid node analysis and edge analysis in complex networks (CDHNE), a novel community detection algorithm, was proposed aiming at the problem that both edge community detection and node-based community detection algorithms had corresponding shortcomings in the process of detecting communities, which affected the quality of complex network community detection.The relatively stable characteristics of the edge in the networks were firstly used by the algorithm to construct a more accurate community structure through edge community detection at the early stage of algorithm execution.Then, after the formation of the edge communities, the flexible characteristics of the node were used to accurately detect the boundary of edge communities, so as to more accurately detect the community structure in the complex networks.In the computer-generated network experiments, when the community structure of the network gradually became fuzzy, the number of overlapping nodes and the number of communities to which the overlapping nodes belonged kept increasing.Compared to traditional algorithms, the accuracy of community detection and overlapping nodes detection were improved by an average of 10% and 15%, respectively, by the CDHNE algorithm.In the real network experiments, the tightness of the community structure detected by the CDHNE algorithm was better.Especially when facing large-scale networks with more than 100 000 nodes, the detection task was completed by the CDHNE algorithm with high quality, and the EQ value reached 0.412 1.The experimental results show that the CDHNE algorithm has advantages in operational stability and handling large-scale networks.…”
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A novel pedestrian detection algorithm based on data fusion of face images by Jianhu Zheng, Jinshuan Peng

“…To address this issue, we propose a novel pedestrian detection algorithm with multisource face images, which involves a face recognition algorithm based on the conjugate orthonormalized partial least-squares regression analysis under a complex lighting environment. …”
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Decomposition-Based Multiobjective Evolutionary Algorithm for Community Detection in Dynamic Social Networks by Jingjing Ma, Jie Liu, Wenping Ma, Maoguo Gong, Licheng Jiao

“…A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. …”
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A fault detection and location algorithm for the LVDC interconnection network in rural area by Chengwei Liu, Joan Marc Rodriguez‐Bernuz, Di Liu, Saizhao Yang, Yitong Li, Qiteng Hong, Adrià Junyent‐Ferré

“…However, the identification of the fault is challenging due to the fast fault transients and equipment limitations, where there are no sensors and DC circuit breakers (DCCBs) in the lines. To solve this problem, this article proposes a fault detection and location algorithm without requiring extra sensors and DCCBs in lines. …”
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Infrared small target detection algorithm with U-shaped multiscale transformer network by DUAN Peipei, ZHANG Yan, LUO Mingshi, YAN Xiaoying

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Fan Blade Crack Detection Algorithm Based on Multi-Scale Feature Fusion by Yongjun Qi, Hailin Tang, Altangerel Khuder

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A Novel Quadrilateral Contour Disentangled Algorithm for Industrial Instrument Reading Detection by Xiang Li, Changchang Zeng, Yong Yao, Jide Qian, Haiding Zhang, Sen Zhang, Suixian Yang

“…Finally, the experimental results on the instrument dataset demonstrate that QCDNet outperforms existing quadrilateral detection algorithms, with improvements of 4.07%, 1.8%, and 2.89% in Precision, Recall, and F-measure, respectively. …”
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Optimization of the Naive Bayes Algorithm with SMOTETomek Combination for Imbalance Class Fraud Detection by Arief Tri Arsanto, Arif Faizin, Moch lutfi, Zulfatun Nikmatus Saadah

“…The focus of this research is card fraud classification. Detection of imbalanced datasets or imbalanced classes is carried out using the Naive Bayes method as a classification algorithm. …”
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A parallel algorithm for network traffic anomaly detection based on Isolation Forest by Xiaoling Tao, Yang Peng, Feng Zhao, Peichao Zhao, Yong Wang

“…To solve these problems, we propose a parallel algorithm based on Isolation Forest and Spark for network traffic anomaly detection. …”
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Small target detection in coal mine underground based on improved RTDETR algorithm by Feng Tian, Cong Song, Xiaopei Liu

“…Abstract Aiming at the problem of low detection accuracy of small targets such as helmets and self-rescuers in complex scenarios in coal mines, a small target detection method based on improved Real-Time DEtection TRansformer (RTDETR) for underground coal mines is proposed. …”
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Deep Learning-Based Intelligent Detection Algorithm for Surface Disease in Concrete Buildings by Jing Gu, Yijuan Pan, Jingjing Zhang

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GCB‐YOLO: A Lightweight Algorithm for Wind Turbine Blade Defect Detection by Zhiming Zhang, Chaoyi Dong, Ze Wei, Xiaoyan Chen, Weidong Zan, Yao Xue

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