Overview of detection techniques for malicious social bots by Rong LIU, Bo CHEN, Ling YU, Ya-shang LIU, Si-yuan CHEN

“…The attackers use social bots to steal people’s privacy,propagate fraud messages and influent public opinions,which has brought a great threat for personal privacy security,social public security and even the security of the nation.The attackers are also introducing new techniques to carry out anti-detection.The detection of malicious social bots has become one of the most important problems in the research of online social network security and it is also a difficult problem.Firstly,development and application of social bots was reviewed and then a formulation description for the problem of detecting malicious social bots was made.Besides,main challenges in the detection of malicious social bots were analyzed.As for how to choose features for the detection,the development of choosing features that from static user features to dynamic propagation features and to relationship and evolution features were classified.As for choosing which method,approaches from the previous research based on features,machine learning,graph and crowd sourcing were summarized.Also,the limitation of these methods in detection accuracy,computation cost and so on was dissected.At last,a framework based on parallelizing machine learning methods to detect malicious social bots was proposed.…”
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Overview of detection techniques for malicious social bots by Rong LIU, Bo CHEN, Ling YU, Ya-shang LIU, Si-yuan CHEN

“…The attackers use social bots to steal people’s privacy,propagate fraud messages and influent public opinions,which has brought a great threat for personal privacy security,social public security and even the security of the nation.The attackers are also introducing new techniques to carry out anti-detection.The detection of malicious social bots has become one of the most important problems in the research of online social network security and it is also a difficult problem.Firstly,development and application of social bots was reviewed and then a formulation description for the problem of detecting malicious social bots was made.Besides,main challenges in the detection of malicious social bots were analyzed.As for how to choose features for the detection,the development of choosing features that from static user features to dynamic propagation features and to relationship and evolution features were classified.As for choosing which method,approaches from the previous research based on features,machine learning,graph and crowd sourcing were summarized.Also,the limitation of these methods in detection accuracy,computation cost and so on was dissected.At last,a framework based on parallelizing machine learning methods to detect malicious social bots was proposed.…”
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Analyzing and Classifying Risks Arising During Innovation Project Implementation in Aircraft Motor-Building by T. B. Timofeeva, E. A. Ozdoeva

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Fast Visual Tracking With Robustifying Kernelized Correlation Filters by Qianbo Liu, Guoqing Hu, Md Mojahidul Islam

“…Occlusion and fast motion problems can be effectively solved by the expansion of the search area. …”
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Small target detection in UAV view based on improved YOLOv8 algorithm by Xiaoli Zhang, Guocai Zuo

“…Firstly, a bi-directional feature pyramid network (BiFPN) is introduced to enhance the fusion capability of the features. …”
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Review of Multivariate Time Series Clustering Algorithms by ZHENG Desheng, SUN Hanming, WANG Liyuan, DUAN Yaoxin, LI Xiaoyu

“…Initially, based on classification standards such as feature extraction methods, similarity measurement algorithms, and clustering partition frameworks, this paper conducts a comparative analysis of existing multivariate time series clustering algorithms. …”
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DScanNet: Packaging Defect Detection Algorithm Based on Selective State Space Models by Yirong Luo, Yanping Du, Zhaohua Wang, Jingtian Mo, Wenxuan Yu, Shuihai Dou

“…For this reason, an improved target detection model, DScanNet, is proposed in this paper. To address the problem that the model’s detailed feature extraction for small target defects is not sufficient and thus leads to low detection accuracy, the MEFE module, the local feature extraction module (LFEM Block), and the PCR module of the multi-scale convolution and feature enhancement strategy are proposed to enhance the model’s capability of capturing defective features and focusing on specific features, and to improve the detection accuracy. …”
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KNEE OSTEOARTHRITIS STAGE CLASSIFICATION BASED ON HYBRID FUSION DEEP LEARNING FRAMEWORK by Delveen Luqman Abd Alnabi, Shereen Sh Ahmed, Nisreen Luqman Abd Alnabi

“…The feature-level, decision-level, score-level, and meta-based fusion technologies were also performed on the outputs of the best three trained models to minimize the individual models’ errors. …”
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WCANet: An Efficient and Lightweight Weight Coordinated Adaptive Detection Network for UAV Inspection of Transmission Line Accessories by Jiawei Chen, Pengfei Shi, Mengyao Xu, Yuanxue Xin, Xinnan Fan, Jinbo Zhang

“…The network is designed with a plug-and-play WCA module that can effectively identify dense small targets, retain information in each channel, and reduce computational overheads, while incorporating Sim-AFPN with a skip-connection structure into the network aggregate feature information layer by layer, enhancing the ability to capture key features, and achieving a lightweight network structure. …”
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Enhanced Plant Leaf Classification over a Large Number of Classes Using Machine Learning by Ersin Elbasi, Ahmet E. Topcu, Elda Cina, Aymen I. Zreikat, Ahmed Shdefat, Chamseddine Zaki, Wiem Abdelbaki

“…Features are extracted based on the margin, texture, and shape of the leaves. …”
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Valences identitaires de la charge variétale dans la traduction by Mioara CODLEANU

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DAPSS: A Novel Network for DOM Assisted Oblique Photography Point Cloud Semantic Segmentation by Zhenzhen Song, Mingqiang Guo, Liang Wu, Heng Liu, Ying Huang, Zheng Liu

“…DAPSS not only effectively addresses the recognition of small-scale surface features, but also resolves the occlusion problems associated with projection-based methods.…”
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An Innovative Method of Monitoring Cotton Aphid Infestation Based on Data Fusion and Multi-Source Remote Sensing Using Unmanned Aerial Vehicles by Chenning Ren, Bo Liu, Zhi Liang, Zhonglong Lin, Wei Wang, Xinzheng Wei, Xiaojuan Li, Xiangjun Zou

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Is There Really Root-and-Pattern Morphology? Evidence from Classical Arabic by Dominique Bobeck

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A Multiangle MIMO-SAR Fusion Imaging Method Based on Improved Range Migration Algorithm and Improved Geographic Information Scale Invariant Feature Transform Algorithm by Fang Zhou, Zhikuan Jiao, Guoqing Shen, Mengdao Xing, Marina Gashinova

“…Finally, an improved method of geographic information-scale invariant feature transform is used to achieve the efficiency fusion of multi-angle imaging results. …”
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A Feature Extraction Method of Ship Underwater Noise Using Enhanced Peak Cross-Correlation Empirical Mode Decomposition Method and Multi-Scale Permutation Entropy by Peng Liu, Chen Dai, Shuaiqiang Li, Hui Jin, Xinfu Liu, Guijie Liu

“…A feature extraction method based on the combination of improved empirical modal decomposition (IEMD) and multi-scale permutation entropy (MPE) is proposed to address the problem of inaccurate recognition and classification of ship noise signals under complex environmental conditions. …”
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Linear Time Train Contraction Minor Labeling for Railway Line Capacity Analysis by Qinglun Zhong, Ruihua Xu

“…Abstract When no more than one train is feasibly contained in the separation headway times of two other trains, a triangular gap problem-based method is used to compute the consumed capacity in linear time. …”
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The integration of a new waste-to-energy plant: Waste flows modelling and pricing strategies for financial sustainability by Lucie Němcová, Jaroslav Pluskal, Radovan Šomplák

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3D geometric moment invariants from the point of view of the classical invariant theory by L. P. Bedratyuk, A. I. Bedratyuk

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Education in Post-Conflict Societies: Angola and Mozambique’s Path to an Accessible and Sovereign Education System by GRIBANOVA Valentina Valerievna, GRISHINA Nina Vladimirovna

“…Colonial education was modeled on the metropolis, and its characteristic feature was the almost complete exclusion of the indigenous population from the system of education. …”
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