Histopathological Image Analysis Using Machine Learning to Evaluate Cisplatin and Exosome Effects on Ovarian Tissue in Cancer Patients by Tuğba Şentürk, Fatma Latifoğlu, Çiğdem Gülüzar Altıntop, Arzu Yay, Zeynep Burçin Gönen, Gözde Özge Önder, Özge Cengiz Mat, Yusuf Özkul

“…A set of 177 Local Binary Pattern (LBP) features were extracted from histopathological images, followed by feature selection using Lasso regression. …”
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Evaluation of machine learning algorithms in tunnel boring machine applications: a case study in Mashhad metro line 3 by Morteza Abbasi, Amir Hossein Namadchi, Mehdi Abbasi, Mohsen Abbasi

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A fine-grained human facial key feature extraction and fusion method for emotion recognition by Shiwei Li, Jisen Wang, Linbo Tian, Jianqiang Wang, Yan Huang

“…Finally, a two-branch convolutional neural network is designed to integrate both global and local facial feature datasets, enhancing the model’s ability to recognize facial characteristics accurately. …”
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A Dual-Strategy Framework for Cyber Threat Detection in Imbalanced, High-Dimensional Data Across Heterogeneous Networks by T. Saranya, S. Indra Priyadharshini

“…As cyber threats grow in complexity, ensuring robust network security has become increasingly critical. …”
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Quantitative assessment of brain glymphatic imaging features using deep learning-based EPVS segmentation and DTI-ALPS analysis in Alzheimer’s disease by Fenyang Chen, Tiantian Heng, Qi Feng, Rui Hua, Jiaojiao Wu, Feng Shi, Zhengluan Liao, Keyin Qiao, Zhiliang Zhang, Jianliang Miao

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Evaluating Deep Learning Architectures for Breast Tumor Classification and Ultrasound Image Detection Using Transfer Learning by Christopher Kormpos, Fotios Zantalis, Stylianos Katsoulis, Grigorios Koulouras

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LEO mega-constellation network:networking technologies and state of the art by Quan CHEN, Lei YANG, Jianming GUO, Xingchen LI, Yong ZHAO, Xiaoqian CHEN

“…The emerging low earth orbit (LEO) mega-constellation network (MCN) represented by Starlink and OneWeb were studied.The system architecture and basic working modes were introduced, and the main features of the emerging broadband MCN were summarized.Based on the system architecture of MCN, the methodology and research progress of five key technologies were investigated and summarized, including network topology dynamics management, space-ground handover scheme, high-efficiency routing algorithm design, gateway placement design, network simulation and performance evaluation.The focus was on recent mega-constellation-related studies.The challenges caused by the large scale and complexity of MCN and the applicability of existing techniques and solutions in MCN were analyzed.…”
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I2DNet - Design and real-time evaluation of an appearance-based gaze estimation system by L R D Murthy, Siddhi Brahmbhatt, Somnath Arjun, Pradipta Biswas

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Ultra Wideband radar-based gait analysis for gender classification using artificial intelligence by Adil Ali Saleem, Hafeez Ur Rehman Siddiqui, Muhammad Amjad Raza, Sandra Dudley, Julio César Martínez Espinosa, Luis Alonso Dzul López, Isabel de la Torre Díez

“…A dataset comprising 163 participants was collected, and the radar signals underwent preprocessing, including clutter suppression and peak detection, to isolate meaningful gait cycles. Spectral features extracted from these cycles were transformed using a novel integration of Feedforward Artificial Neural Networks and Random Forests , enhancing discriminative power. …”
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High-throughput end-to-end aphid honeydew excretion behavior recognition method based on rapid adaptive motion-feature fusion by Zhongqiang Song, Jiahao Shen, Qiaoyi Liu, Wanyue Zhang, Ziqian Ren, Kaiwen Yang, Xinle Li, Jialei Liu, Fengming Yan, Wenqiang Li, Yuqing Xing, Lili Wu

“…Simultaneously, the RT-DETR detection model underwent deep optimization: a spline-based adaptive nonlinear activation function was introduced, and the Kolmogorov-Arnold network was integrated into the deep feature stage of the ResNet50 backbone network to form the RK50 module. …”
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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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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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Distributed denial of service (DDoS) classification based on random forest model with backward elimination algorithm and grid search algorithm by Mohamed S. Sawah, Hela Elmannai, Alaa A. El-Bary, Kh. Lotfy, Osama E. Sheta

“…The DDoS-SDN dataset was used for training and evaluation, with feature selection via Backward Elimination (BE) and hyperparameter tuning using Grid Search with 5-fold Cross-Validation (CV = 5). …”
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Hyperspectral Image Classification With Re-Attention Agent Transformer and Multiscale Partial Convolution by Junding Sun, Hongyuan Zhang, Jianlong Wang, Haifeng Sima, Shuanggen Jin

“…Convolutional neural networks (CNNs) focus solely on extracting local features, lacking the ability to capture global spectral-spatial information. …”
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Research on SPAD Inversion of Rice Leaves at a Field Scale Based on Machine Vision and Leaf Segmentation Techniques by Bailin Yue, Yong Jin, Shangrong Wu, Jieyang Tan, Youxing Chen, Hu Zhong, Guipeng Chen, Yingbin Deng

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Evaluation of Post Hoc Uncertainty Quantification Approaches for Flood Detection From SAR Imagery by Jakob Ludwig, Ronny Hansch

“…In particular when these predictions are used by human decision makers in high stake scenarios, e.g., during detection and monitoring of natural disasters, trustworthiness is a necessary feature. In the context of flood detection from SAR imagery, this work evaluates a variety of uncertainty quantification methods that are applicable to already trained models (i.e., post hoc approaches) and provides detailed experiments evaluating the quantification quality of the different methods. …”
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EVALUATION OF OPERATIONAL RELIABILITY AND EFFICIENCY OF PRIMARY DESIGNS OF PULSE SUPERCHARGERS USING HYDRAULIC SHOCK ENERGY by A. N. Makeev

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Creating a Novel Attention-Enhanced Framework for Video-Based Action Quality Assessment by Wenhui Gong, Wei Li, Huosheng Hu, Zhijun Song, Zhiqiang Zeng, Jinhua Sun, Yuping Song

“…Our approach segments video data into clips, extracts features using the I3D network, and applies attention mechanisms to highlight salient features while suppressing irrelevant ones. …”
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Remaining useful life prediction of li-ion batteries based on an improved transformer model by Qingsong Wang, Annuo Yu, Hao Ding, Ming Cheng, Giuseppe Buja

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A High-Performance and Lightweight Maritime Target Detection Algorithm by Shidan Sun, Zhiping Xu, Xiaochun Cao, Jiachun Zheng, Jiawen Yang, Ni Jin

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