Method of detecting IRC Botnet based on the multi-features of traffic flow by Jian-en YAN, Chun-yang YUAN, Hai-yan XU, Zhao-xin ZHANG

“…To resolve the problem of detecting IRC Botnet,a method based on traffic flow characteristics was proposed.The characteristics of Botnet channel traf?…”
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Cotton Disease Detection Using TensorFlow Machine Learning Technique by Sandeep Kumar, Rajeev Ratan, J. V. Desai

“…In this paper, the CNN algorithm is used to create the prediction model by leveraging the TensorFlow’s Keras API. …”
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Gradient Flow Decoding by Tadashi Wadayama, Lantian Wei

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Research on the Computed Tomography Pebble Flow Detecting System for HTR-PM by Xin Wan, Ximing Liu, Jichen Miao, Peng Cong, Yuai Zhang, Zhifang Wu

“…To investigate it more authentically, a computed tomography pebble flow detecting (CT-PFD) system has been constructed, in which a three-dimensional model is simulated according to the ratio of 1 : 5 with the core of HTR-PM. …”
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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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Lightweight detection algorithms for small targets on unmanned mining trucks by Shuoqi CHENG, Yilihamu·YAERMAIMAITI, Lirong XIE, Xiyu LI, Ying MA

“…Therefore, to address the issues of high parameter count, large model size, and low detection accuracy for small and occluded targets in open-pit mining scenarios, we propose the Lightweight Unmanned Mining Truck Detection Algorithm LWHP (Lightweight High-Precision). …”
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Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…The YOLOv5 algorithm adopted in this study excels at detecting small targets and provides multi-scale detection, strong versatility, fast training, inference speeds, and adaptable fine-tuning capabilities. …”
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Multi-Search Strategy-based Improved Water Flow Optimizer Algorithm for Cluster Analysis by Prateek Thakral, Yugal Kumar

“…Hence, this work presents an improved water flow optimizer (IWFO) algorithm for cluster analysis that can address the issues of traditional and heuristic algorithms. …”
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Design of Jitter Compensation Algorithm for Robot Vision Based on Optical Flow and Kalman Filter by B. R. Wang, Y. L. Jin, D. L. Shao, Y. Xu

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Histogram of Maximal Optical Flow Projection for Abnormal Events Detection in Crowded Scenes by Ang Li, Zhenjiang Miao, Yigang Cen, Tian Wang, Viacheslav Voronin

“…In this paper, based on a novel motion feature descriptor, that is, the histogram of maximal optical flow projection (HMOFP), we propose an algorithm to detect abnormal events in crowded scenes. …”
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Redundancy and conflict detection method for label-based data flow control policy by Rongna XIE, Xiaonan FAN, Suzhe LI, Yuxin HUANG, Guozhen SHI

“…To address the challenge of redundancy and conflict detection in the label-based data flow control mechanism, a label description method based on atomic operations has been proposed.When the label is changed, there is unavoidable redundancy or conflict between the new label and the existing label.How to carry out redundancy and conflict detection is an urgent problem in the label-based data flow control mechanism.To address the above problem, a label description method was proposed based on atomic operation.The object label was generated by the logical combination of multiple atomic tags, and the atomic tag was used to describe the minimum security requirement.The above label description method realized the simplicity and richness of label description.To enhance the detection efficiency and reduce the difficulty of redundancy and conflict detection, a method based on the correlation of sets in labels was introduced.Moreover, based on the detection results of atomic tags and their logical relationships, redundancy and conflict detection of object labels was carried out, further improving the overall detection efficiency.Redundancy and conflict detection of atomic tags was based on the relationships between the operations contained in different atomic tags.If different atomic tags contained the same operation, the detection was performed by analyzing the relationship between subject attributes, environmental attributes, and rule types in the atomic tags.On the other hand, if different atomic tags contained different operations without any relationship between them, there was no redundancy or conflict.If there was a partial order relationship between the operations in the atomic tags, the detection was performed by analyzing the partial order relationship of different operations, and the relationship between subject attribute, environment attribute, and rule types in different atomic tags.The performance of the redundancy and conflict detection algorithm proposed is analyzed theoretically and experimentally, and the influence of the number and complexity of atomic tags on the detection performance is verified through experiments.…”
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An efficient fire detection algorithm based on Mamba space state linear attention by Yuming Li, Yongjie Wang, Xiaorui Shao, Anbo Zheng

“…To enhance the performance of visual fire detection technologies and provide a novel approach, this paper proposes an efficient fire detection algorithm based on the YOLOv9 architecture and introduces multiple key techniques to design a high-performance fire detection model leveraging the Mamba attention mechanism. …”
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An Algorithm for Motion Estimation Based on the Interframe Difference Detection Function Model by Tengfei Zhang, Huijuan Kang

“…The different computational schemes are designed for the flow of multiframe target detection from background removal to noise reduction, to single-frame detection, and finally to multiframe detection, respectively. …”
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Performance Evaluation of Magnetic Wireless Sensor Networks Algorithm for Traffic Flow Monitoring in Chaotic Cities by Haji Said Fimbombaya, Nerey H. Mvungi, Ndyetabura Y. Hamisi, Hashimu U. Iddi

“…The algorithm extracts traffic flow information from resulting magnetic field distortions sensed by magnetic wireless sensor nodes located on the sides of the road. …”
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DNFE: Directed network flow entropy for detecting tipping points during biological processes. by Xueqing Peng, Rui Qiao, Peiluan Li, Luonan Chen

“…Numerical simulation results demonstrate that the DNFE algorithm is robust across various noise levels and outperforms existing methods in detecting tipping points. …”
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Adaptive Anomaly Detection in Network Flows With Low-Rank Tensor Decompositions and Deep Unrolling by Lukas Schynol, Marius Pesavento

“…We first propose a novel block-successive convex approximation algorithm based on a regularized model-fitting objective where the normal flows are modeled as low-rank tensors and anomalies as sparse. …”
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Fixed/Mobile Collaborative Traffic Flow Detection Study Based on Wireless Charging of UAVs by Hao Wu, Mingbo Niu, Biao Wang, Kai Yan, Yuxuan Li, Hanyu Pang

“…To address this issue, it is essential to obtain precise vehicle data as a reliable reference for managing traffic flow during peak periods. In this paper, we propose an intelligent detection scheme using an improved YOLOv8n target recognition algorithm combined with a ByteTrack multi-target tracking algorithm. …”
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Diagnostic algorithm for the detection of carbapenemases and extended-spectrum β-lactamases in carbapenem-resistant Pseudomonas aeruginosa by Stefano Mancini, Laia Garcia-Verellen, Helena M. B. Seth-Smith, Peter M. Keller, Natalia Kolesnik-Goldmann, Muhammad Ali Syed, Irfan Ullah, Vladimira Hinic, Tim Roloff, Adrian Egli, Oliver Nolte

“…We also included a lateral flow immunoassay (Carba-5, NG-Biotech) for confirmation of MBL production and double disc synergy testing (DDST) to improve ESBL detection. …”
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Machine learning algorithms to detect patient–ventilator asynchrony: a feasibility study by Guillermo Gutierrez, Kendrew Wong, Arun Jose, Jeffrey Williams

“…We explored the feasibility of using machine learning algorithms to replicate the assessment of breathing patterns by experienced clinicians, based on airway flow and pressure signals. …”
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Anomaly detection algorithm based on fractal characteristics of large-scale network traffic by XU Xiao-dong1, ZHU Shi-rui2, SUN Ya-min1

“…Based on the fractal structure of the large-scale network traffic aggregation, anomalies were analyzed qualitatively and quantitatively from perspective of the global and local scaling exponents.Multi-fractal singular spectrum and Lipschitz regularity distribution were used to analyze the fractal parameters of abnormal flow, trying to identify the relationship between the changes of these parameters and the emergence of anomalies.Experimental results show that the emergence of anomalies has obvious signs on the singular spectrum and Lipschitz regularity distribution.Using this feature, a new multi-fractal-based anomaly detection algorithm and a new detection framework were constructed.On the DARPA/Lincoln laboratory intrusion detection evaluation data set 1999, this algorithm’s detection rate is high at low false alarm rate, which is better than EMERALD.…”
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