RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements by Tianyu Li, Xuanrui Xiong, Yuan Zhang, Xiaolin Fan, Yushu Zhang, Haihong Huang, Dan Hu, Mengting He, Zhanjun Liu

“…This study proposes an occluded object detection algorithm, RE-YOLOv5, based on receptive field enhancement to assist with the difficult identification of occluded objects in complex road environments. …”
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Thermal damage detection of EAST internal component based on machine learning by Zhongfang Guan, Bin Zhang, Jian Liu, Jinping Qian, Xianzu Gong, Runze Chen, Zuhao Wang, Binfu Gao, Yutong Guo, Chuannan Xuan, Cong Cao, Tianqi Jia, Pan Li, Wenbin Liu, Wei Wang, Yunchan Hu, Yifan He, Kangjia Yang, Wenyi Lu, Chunyu He, the EAST team

“…To address the challenge of identifying thermal damage to internal components of the first wall during the Experimental Advanced Superconducting Tokamak (EAST) discharges, we introduce the YOLOv8 model for hotspot detection on EAST and present the customized EAST- You Only Look Once (YOLO) algorithm, derived from an enhanced YOLOv8 framework. …”
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Clustering of ECG Signals Based on Fuzzy Neural Network with Initial Weights Generated by Genetic Algorithm by Elaheh Sayari, Mahdi Yaghoobi

“…Early detection of heart diseases/abnormalities can prolong life and enhance the quality of living through appropriate treatment. …”
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A novel framework for identifying fishing grounds from AIS data containing vessels of unknown types by Changhai Huang, Jialong Kong, Jian Zheng, Yuli Chen, Jingen Zhou

“…Firstly, the Speed-Direction-Based Stops and Moves of Trajectories (SDB-SMOT) algorithm is proposed. Based on this algorithm, a fishing behavior detection model is developed to identify fishing activity trajectories from AIS data that encompasses vessels of unknown types. …”
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Comparative Analysis of MFO, GWO and GSO for Classification of Covid-19 Chest X-Ray Images by Asraa M. Mohammad, Hussien Attia, Yossra H. Ali

“…This study examines a comparison analysis of k-nearest neighbors (KNN), Extreme Gradient Boosting (XGboost), and Support-Vector Machine (SVM) are some classification approaches for feature selection in this domain using The Moth-Flame Optimization algorithm (MFO), The Grey Wolf Optimizer algorithm (GWO), and The Glowworm Swarm Optimization algorithm (GSO). …”
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Distribution of urinary neutrophil gelatinase-associated lipocalin and post-translationally modified fetuin-A in outpatients with acute kidney disease detected using a nationwide a... by Ya-Chi Lin, I-Wen Ting, David Ray Chang, Ya-Luan Hsiao, Yu-Ting Lin, Mei-Chuan Hsieh, Shu-Woei Ju, Jie-Sian Wang, Chang-Cheng Jiang, Hsuan-Jen Lin, Cheng-Ting Lu, Che-Chen Lin, Tzu-Ling Tseng, Hung-Chieh Yeh, Hsiu-Yin Chiang, Chin-Chi Kuo

“…Conclusions: The high proportion of elevated uNGAL and its positive association with CKO risk provide biological evidence to support the AKIDS's data algorithm in detecting AKDOPT. Similarly, uPTM-FetA demonstrated comparable characteristics to uNGAL in reflecting kidney injury in the context of AKD.…”
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BiFormer for Scene Graph Generation Based on VisionNet With Taylor Hiking Optimization Algorithm by S. Monesh, N. C. Senthilkumar

“…The nodes in the graph are signified as detected objects and the detected action is represented by edges. …”
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Can Government Incentive and Penalty Mechanisms Effectively Mitigate Tacit Collusion in Platform Algorithmic Operations? by Yanan Wang, Yaodong Zhou

“…Algorithmic collusion essentially constitutes a form of monopolistic agreement that utilizes algorithms as tools for signaling collusion, making it particularly challenging for both consumers and antitrust enforcement agencies to detect. …”
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Diagnostic algorithm of patients’ with pathology of endocrine system examination which demand simultaneous operative treatment by S. N. Zavgorodnii, A. I. Rylov, M. B. Daniluk, O. S. Dolya, A. I. Marusii

“…Diagnostic algorithm of examination of patients with pathology of endocrine system that will permit to detect combined surgical pathology is needed.…”
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Design and Test of an Embedded Real-Time Compact Voltage Fingerprinting Algorithm for Enhanced Automotive Cybersecurity by Pierpaolo Dini, Ettore Soldaini, Sergio Saponara

“…This algorithm detects cyber-attacks through statistical analysis of voltage samples from the protocol’s physical layer. …”
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Impact of Machine Learning on Intrusion Detection Systems for the Protection of Critical Infrastructure by Avinash Kumar, Jairo A. Gutierrez

“…This paper investigates the efficacy of various machine learning algorithms for anomaly detection within critical infrastructure, using the Secure Water Treatment (SWaT) dataset, a comprehensive collection of time-series data from a water treatment testbed, to experiment upon and analyze the findings. …”
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Adaptive Multi-Radar Anti-Bias Track Association Algorithm Based on Reference Topology Features by Shaoming Wei, Xuan Zhou, Jun Wang, Rui Pang, Xueqing Li, Qiang Liu

“…To address the track association problem in multi-radar systems, particularly the challenges posed by offset bias, this paper proposes an adaptive multi-radar anti-bias track association algorithm based on reference topological features (RETs) that achieves accurate association despite offset bias and radar missed detections. …”
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Modern Approaches to Detect and Classify Comment Toxicity Using Neural Networks by Sergey V. Morzhov

“…It is a non-trivial task even if the word “understand” here means only “to classify”. the rapid evolution of machine learning technologies has led to ubiquitous implementation of new algorithms. A lot of tasks, which for many years were considered almost impossible to solve, are now quite successfully solved using deep learning technologies. this article considers algorithms built using deep learning technologies and neural networks which can successfully solve the problem of detection and classification of toxic comments. …”
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Breast Cancer Screening Using a Modified Inertial Projective Algorithms for Split Feasibility Problems by Pennipat Nabheerong, Warissara Kiththiworaphongkich, Watcharaporn Cholamjiak

“…To detect breast cancer in mammography screening practice, we modify the inertial relaxed CQ algorithm with Mann’s iteration for solving split feasibility problems in real Hilbert spaces to apply in an extreme learning machine as an optimizer. …”
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Integrating Sentiment Analysis With Machine Learning for Cyberbullying Detection on Social Media by Maram Fahaad Almufareh, Noor Zaman Jhanjhi, Mamoona Humayun, Ghadah Naif Alwakid, Danish Javed, Saleh Naif Almuayqil

“…This paper presents a unique framework that integrates sentiment analysis with machine learning algorithms to enhance the detection of cyberbullying on social media. …”
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Target Detection Technology of Mechanical, Electrical, and Plumbing Components Based on CV by Guohua Wei, Ding Zhou, Xiaojun Yuan

“…The developed system uses deep learning algorithms for real-time data collection to enhance monitoring efficiency and accuracy, as well as advanced object detection algorithms to compare real-time construction images with BIMs. …”
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A Survey of Dense Object Detection Methods Based on Deep Learning by Yang Zhou, Hui Li

“…In recent years, thanks to the development and advancement of deep learning methods, object detection algorithms and frameworks have made significant breakthroughs, allowing many detection methods to be applied to real-world scenarios. …”
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Image Based Detection of Coating Wear on Cutting Tools with Machine Learning by Jan Wolf, Nithin Kumar Bandaru, Martin Dienwiebel, Hans-Christian Möhring

“…Based on cutting experiments conducted with a TiN/AlTiN-coated cutting tool, an image dataset was generated and pre-processed using multiple algorithms, such as Canny edge detection and Hough line transforms. …”
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ENHANCING CYBERSECURITY THROUGH MALWARE DETECTION BASED ON MACHINE LEARNING TECHNIQUE by Amer Mohamed Shhatha, Omar Ibrahim Alsaif

“…The algorithms are assessed in this study using an assembly command dataset and a static and dynamic analysis approach to improve the detection rate and stability. …”
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Comparative study of IoT- and AI-based computing disease detection approaches by Wasiur Rhmann, Jalaluddin Khan, Ghufran Ahmad Khan, Zubair Ashraf, Babita Pandey, Mohammad Ahmar Khan, Ashraf Ali, Amaan Ishrat, Abdulrahman Abdullah Alghamdi, Bilal Ahamad, Mohammad Khaja Shaik

“…However, no comprehensive survey has been conducted on integrated IoT- and computing-based systems that deploy deep learning for disease detection. This study evaluated different machine learning and deep learning algorithms and their hybrid and optimized algorithms for IoT-based disease detection, using the most recent papers on IoT-based disease detection systems that include computing approaches, such as cloud, edge, and fog. …”
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