Reliable selfish node detection algorithm for opportunistic networks by Zhi REN, Yong-yin TAN, Ji-bi LI, Qian-bin CHEN

“…To address the problem of detection accuracy affected by situations like the omission of node receiving wrong frame and failure of monitoring beyond nodes'communication range during the consideration of the ex ing selfish node detection algorithms in opportunistic networks,a novel and reliable selfish node detection algorithm——RSND algorithm for opportunistic networks was proposed.It employs wrong frame analysis based on cross-layer monitoring mechanism,information excavation based on node encounter and node distance estimation based on RSSI three new mechanisms to eliminate the influence of node's selfishness detection due to wrong frame and failure of monitoring beyond nodes' communication range,improving the reliability of detection.Theoretical analysis verifies the effectiveness of RSND,and simulation results show that RSND can improve selfish node detection accuracy ratio and network throughput at least 6% and 4%,as compared to the existing selfish node detection algorithm based on 2-ACK and watchdog detection algorithm.…”
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ADOS-CFAR Algorithm for Multibeam Seafloor Terrain Detection by Weidong Du, Tian Zhou, Haisen Li, Baowei Chen, Bo Wei

“…This paper first discusses the principles and existing problems of the OS-CFAR and K-FINDER algorithms and then suggests the ADOS-CFAR algorithm and its fast calculation method for those problems. …”
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Weak Signal Detection Algorithm Based on Particle Filtering by Mao Senpeng, Wang Pengfei, Chen Wei, Guo Lei

“…In the traditional particle filter algorithm, there exist problems such as poor robustness against noise and clutter, and difficulty in balancing the detection probability and false alarm probability. …”
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A survey of 3D object detection algorithms by Zhe HUANG, Yongcai WANG, Deying LI

“…3D object detection is a fundamental problem in autonomous driving，virtual reality，robotics，and other applications.Its goal is to extract the most accurate 3D box characterizing interested targets from the disordered point clouds，such as the closest 3D box surrounding the pedestrians or vehicles.The target 3D box's location，size，and orientation are also output.Currently，there are two primary approaches for 3D object detection: (1) pure point cloud based 3D object detection，in which the point clouds are created by binocular vision，RGB-D camera，and lidar; (2) fusion-based 3D object detection based on the fusion of image and point cloud.The various representations of 3D point clouds were introduced.Then representative methods were introduced from three aspects: traditional machine learning techniques; non-fusion deep learning based algorithms; and multimodal fusion-based deep learning algorithms in progressive relation.The algorithms within and across each category were examined and compared，and the differences and connections between the various methods were analyzed thoroughly.Finally，remaining challenges of 3D object detection were discussed and explored.And the primary datasets and metrics used in 3D object detection studies were summarized.…”
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Machine Learning Algorithms Performance Evaluation for Intrusion Detection by Shyla ., Kapil Kumar, Vishal Bhatnagar

“…In this paper authors introduces Intrusion detection system (IDS) framework that is deployed over KDD Cup99 dataset by using machine learning algorithms as Support Vector Machine (SVM), Naïve Bayes and Random Forest for the purpose of improving the precision, accuracy and recall value to compute the best suited algorithm.…”
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Phishing detection algorithm based on attention and feature fusion by ZHANG Sirui, YAN Zhiwei, DONG Kejun, YUCHI Xuebiao

“…To address the problem of escalating adversarial phishing technologies, a phishing detection algorithm based on the attention mechanism and feature fusion was proposed, and a hierarchical classification model was established. …”
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COMBINATORIAL ALGORITHM FOR OBJECT CONTOURS DETECTION OF DIGITAL IMAGES by B. A. Zalesky

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Machine learning algorithm for intelligent detection of WebShell by Hua DAI, Jing LI, Xin-dai LU, Xin SUN

“…WebShell is a common tool for network intrusions,which has the characteristics of great harm and good concealment.The current detection method is relatively simple,and easy to be bypassed,so it is difficult to deal with complex and flexible WebShell.To solve these problems,a supervised machine learning algorithm was put forward to detect WebShell intelligently.By learning the features of existing WebShell and non-existing WebShell pages,the algorithm can make prediction of the unknown pages,and the flexibility and adaptability were both very good.Compared with the traditional WebShell detection methods,the experiment proves that the algorithm has higher detection efficiency and accuracy,and at the same time there is a certain probability to detect new types of WebShell.…”
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Algorithms for Integrated Object Detection in Wireless Sensor Networks by V. I. Parfenov, T. T. Bui

“…Wireless sensor networks can be used to solve various economic problems, including detection of objects (phenomena) of interest. …”
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An Improved YOLOv9s Algorithm for Underwater Object Detection by Shize Zhou, Long Wang, Zhuoqun Chen, Hao Zheng, Zhihui Lin, Li He

“…However, the complex marine environment, poor resolution, color distortion in underwater optical imaging, and limited computational resources all affect the accuracy and efficiency of underwater object detection. To solve these problems, the YOLOv9s-SD underwater target detection algorithm is proposed to improve the detection performance in underwater environments. …”
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Improved cell search algorithm for 5G NR by Baojiang DONG, Chen PENG, He LU

“…The era of 5G NR has higher requirements for speed, capacity and user experience.In 5G NR physical layer, cell search is an indispensable process.Cell search mainly includes primary synchronization signal (PSS) detection algorithm and secondary synchronization signal (SSS) detection algorithm.The traditional PSS detection algorithm and SSS detection algorithm can’t satisfy the basic requirements of 5G NR.In order to solve this problem, an improved PSS detection algorithm based on the traditional M-segment cross-correlation detection algorithm was proposed.When the channel environment is bad, the traditional SSS detection algorithm will also fail.The improved SSS detection algorithm proposed can solve this problem.Finally, the traditional algorithm and the improved algorithm were compared and analyzed.The simulation results show that the detection performance of the proposed algorithm is significantly improved, and the detection efficiency and overall performance are also improved.…”
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An Intrusion Detection Approach based on the Combination of Oversampling and Undersampling Algorithms by Ahmet Okan Arık, Gülsüm Çiğdem Çavdaroğlu

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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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Research on Track Irregularity Detection Algorithm Based on Data Fusion by Yi LI, Huan BAI, Yuanming LIU

“…Aiming at the problem of track irregularity detection method and accuracy, a strap-down inertial navigation technology was proposed. …”
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False Matches Removing in Copy-Move Forgery Detection Algorithms by muthana salih mahdi, Saad N. Alsaad

“…This paper presents an algorithm of the Copy-Move forgery detection using the SIFT algorithm with an effective method to remove the false positives by rejecting all key-points in matches list that own a neighbor less than the threshold. …”
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Garbage classification detection system based on the YOLOv8 algorithm by Yan Zhou, Lixiong Lin, Tong Wang

“…Subsequently, the YOLOv8 algorithm is studied, applied to garbage detection and classification, and used for practical verification in unmanned vehicles. …”
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A traffic pattern detection algorithm based on multimodal sensing by Yanjun Qin, Haiyong Luo, Fang Zhao, Zhongliang Zhao, Mengling Jiang

“…Although much work has been done on transportation mode detection problem, the accuracy is not sufficient. …”
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SIFT Feature-Based Video Camera Boundary Detection Algorithm by Lingqiang Kong

“…Aiming at the problem of low accuracy of edge detection of the film and television lens, a new SIFT feature-based camera detection algorithm was proposed. …”
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Topology of Complex Networks and Performance Limitations of Community Detection Algorithms by Muhammad Qasim Pasta, Faraz Zaidi

“…In this paper, we attempt to highlight this problem by studying networks with different topologies and evaluate the performance of community detection algorithms in the light of these topological changes. …”
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Research on Dual Mode Target Detection Algorithm for Embedded Platform by Li Zhang, Shaoqiang Wang, Hongwei Sun, Yifan Wang

“…The experimental results show that it has a more obvious advantage in detection accuracy than the single-band target detection model while the decision-level fusion target detection model meets the real-time requirements and also verifies the effectiveness of the above algorithm.…”
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