Network intrusion detection based on improved KNN algorithm by Hongsheng Bao, Jie Gao

“…An initial K-nearest neighbor algorithm based on representative points is proposed. …”
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Decentralized Algorithm for Sensors Fault Detection in HVAC Systems by Wang Shiqiang, Jiang Ziyan, Xing Jianchun, Dai Yunchuang, Yang Qiliang

“…Due to the poor instantaneity and adaptability, the current methods for sensors fault detection are still less applied in practical project. …”
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Low complexity uplink multiuser MIMO detecting algorithm by HEI Yong-qiang1, LI Xiao-hui1, YI Ke-chu1, YANG Hong2

“…Aiming at the uplink multiuser MIMO system,a new space-time detecting algorithm was proposed,in which a linear recombination strategy was imposed on the received signal first,and then the matched filter vectors orthogonal to each users’ interference sets were used to eliminate the interference among users.Finally the signal of each user was line-arly space-time decoded by means of the orthogonal equivalent channel.The design of the algorithm under imperfect channel scenario was also provided.Theory analysis and simulation results reveal that the proposed algorithm has the advantages of low complexity and good robustness,and is superior to other detecting algorithms.…”
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Android malware detection using random forest algorithm by Samson Isaac, Abdullahi Tanimu, Mohammed Shamsuddeen Tukur, Jacob Isaac, Amina Bala Ja'afaru

“…Specifically, the research investigates the performance of various ML algorithms, with a focus on Random Forest, in detecting malware on the android platform. …”
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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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Feature-based enhanced boosting algorithm for depression detection by Muhammad Sadiq Rohei, Kasturi Dewi Varathan, Shivakumara Palaiahnakote, Nor Badrul Anuar

Subjects: “…Feature-based enhanced boosting algorithm…”
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Unidirectional-link detection algorithms in wireless sensor networks by SANG Jun-jun, SHI Sheng-fei, LI Jiang-zhong, XIONG Shu-guang

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Clustering and Detecting Network Intrusion Based on Fuzzy Algorithms by Manar Kashmola, Bayda Khaleel

Subjects: “…network intrusion detection…”
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Deep Learning-Based Algorithm for Road Defect Detection by Shaoxiang Li, Dexiang Zhang

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Fake News Detection using the Random Forest Algorithm by Rahmat Dipo Setyadin, Reza Handaru Winasis, Gandung Triyono

“…This study aims to develop an effective fake news detection system using the Random Forest algorithm approach. …”
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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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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

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Surprisal-based algorithm for detecting anomalies in categorical data by Ossama Cherkaoui, Houda Anoun, Abderrahim Maizate

“…Although many algorithms have been proposed to address anomaly detection for numerical datasets, categorical and mixed datasets remain a significant challenge, primarily because a natural distance metric is lacking. …”
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GaLAM: Two-Stage Outlier Detection Algorithm by Xiaojun Lu, Zhe Yan, Ziyun Fan

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Clustering Algorithm by Boundary Detection Base on Entropy of KNN by Jiaman Ding, Jinyuan Yin, Lianyin Jia, Xiaodong Fu, Hongbin Wang

“…Clustering analysis has been widely applied in various fields, and boundary detection based clustering algorithms have shown effective performance. …”
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A Novel Tornado Detection Algorithm Based on XGBoost by Qiangyu Zeng, Guoxiu Zhang, Shangdan Huang, Wenwen Song, Jianxin He, Hao Wang, Yin Liu

“…The characteristics associated with the velocity attributes, reflectivity, velocity spectrum width, differential reflectivity, and correlation coefficient are used in the algorithm to achieve real-time tornado detection. Experimental evaluations have demonstrated that the proposed algorithm significantly improves tornado detection rates and leading times. …”
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Evaluating Subpixel Target Detection Algorithms in Hyperspectral Imagery by Yuval Cohen, Yitzhak August, Dan G. Blumberg, Stanley R. Rotman

“…We demonstrate our ability to evaluate detectors and find the best settings for their free parameters by comparing our results using the following stochastic algorithms for target detection: the constrained energy minimization (CEM), generalized likelihood ratio test (GLRT), and adaptive coherence estimator (ACE) algorithms. …”
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Reliable selfish node detection algorithm for opportunistic networks by Zhi REN, Yong-yin TAN, Ji-bi LI, Qian-bin CHEN

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COMBINATORIAL ALGORITHM FOR OBJECT CONTOURS DETECTION OF DIGITAL IMAGES by B. A. Zalesky

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