RF-SFAD: A RANDOM FOREST MODEL FOR SELECTIVE FORWARDING ATTACK DETECTION IN MOBILE WIRELESS SENSOR NETWORKS by N Usha Bhanu, Soubhagya Ranjan Mallick, Sreenivasa Rao Chappidi, K Sangeethalakshmi

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Interpreting CNN models for musical instrument recognition using multi-spectrogram heatmap analysis: a preliminary study by Rujia Chen, Akbar Ghobakhlou, Ajit Narayanan

“…Visual heatmap analysis and statistical metrics, including Difference Mean, KL Divergence, JS Divergence, and Earth Mover’s Distance, were utilized to assess feature importance and model interpretability.ResultsOur findings highlight the strengths and limitations of each spectrogram type in capturing distinctive features of different instruments. …”
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Carbon additives to improve polymer performance in energy applications using machine learning by Juan Chen, Khidhair Jasim Mohammed, Elimam Ali, Riadh Marzouki

“…Feature importance analysis revealed that carbon fiber length and input voltage were the dominant factors influencing thermal-electrical performance. …”
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Feature-Driven EnsembleX: An Advanced Ensemble Framework for Enhanced MRI Abdomen Image Classification Using Feature Refinement and Boosting Techniques by Snehal V. Laddha, Rohini S. Ochawar

“…The model&#x2019;s effectiveness was assessed using statistically validated performance metrics across 5-fold cross-validation, achieving an accuracy of 98.84% <inline-formula> <tex-math notation="LaTeX">$\pm ~0.12$ </tex-math></inline-formula>%, a precision of 99.03% <inline-formula> <tex-math notation="LaTeX">$\pm ~0.10$ </tex-math></inline-formula>%, a recall of 99.51% <inline-formula> <tex-math notation="LaTeX">$\pm ~0.10$ </tex-math></inline-formula>%, specificity of 80.00% <inline-formula> <tex-math notation="LaTeX">$\pm ~0.18$ </tex-math></inline-formula>%, an F1-score of 99.27% <inline-formula> <tex-math notation="LaTeX">$\pm ~0.10$ </tex-math></inline-formula>%, and a ROC-AUC score of 89.76% <inline-formula> <tex-math notation="LaTeX">$\pm ~0.32$ </tex-math></inline-formula>%, demonstrating its effectiveness in accurately classifying liver tissue into healthy and unhealthy categories based on MRI T1 water-only images. …”
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LitePipeNet: Research on a Lightweight and Efficient Segmentation Model for UAV Pipeline Inspection in Mining Areas by Huang Yong, Xiao Shengwang, Xia Xing, Huang Qiu

“…The main contributions are: 1) construction of the MinePipe-UAV dataset for UAV-based pipeline inspection; 2) design of the compact, high-performance LitePipeNet model; 3) systematic validation of our approach&#x2019;s effectiveness and scalability in industrial visual edge applications.…”
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Prediction of Breakdown Voltage of Long Air Gaps Under Switching Impulse Voltage Based on the ISSA-XGBoost Model by Zisheng Zeng, Bin Song, Shaocheng Wu, Yongwen Li, Deyu Nie, Linong Wang

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DGSS-YOLOv8s: A Real-Time Model for Small and Complex Object Detection in Autonomous Vehicles by Siqiang Cheng, Lingshan Chen, Kun Yang

“…To address these issues, this paper introduces DGSS-YOLOv8s, a model designed to enhance detection accuracy and high-FPS performance within the You Only Look Once version 8 small (YOLOv8s) framework. …”
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Real-Time Object Detection Model for Electric Power Operation Violation Identification by Xiaoliang Qian, Longxiang Luo, Yang Li, Li Zeng, Zhiwu Chen, Wei Wang, Wei Deng

“…The You Only Look Once (YOLO) object detection model has been widely applied to electric power operation violation identification, owing to its balanced performance in detection accuracy and inference speed. …”
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Pre-Treatment and Pre-Brachytherapy MRI first-order Radiomic Features by a Commercial software as survival predictors in radiotherapy for cervical cancer Objectives by Wiwatchai Sittiwong, Pittaya Dankulchai, Pitchayut Wongsuwan, Tissana Prasartseree, Wajana Thaweerat, Nerisa Thornsri, Pongpop Tuntapakul

“…The highest prediction model performance was for the combined clinical and radiomics from PreRx and PreBT.…”
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Developing a machine learning model with enhanced performance for predicting COVID‐19 from patients presenting to the emergency room with acute respiratory symptoms by Maha Mesfer Alghamdi, Naael H. Alazwary, Waleed A. Alsowayan, Mohmmed Algamdi, Ahmed F. Alohali, Mustafa A. Yasawy, Abeer M. Alghamdi, Abdullah M. Alassaf, Mohammed R. Alshehri, Hussein A. Aljaziri, Nujoud H. Almoqati, Shatha S. Alghamdi, Norah A. Bin Magbel, Tareq A. AlMazeedi, Nashaat K. Neyazi, Mona M. Alghamdi, Mohammed N. Alazwary

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PERFORMANCE EVALUATION OF THE INDF.JK STOCK PRICE MOVEMENT PREDICTION MODEL USING RANDOM FOREST METHOD WITH GRID SEARCH CROSS VALIDATION OPTIMIZATION by Della Zaria, Evy Sulistianingsih, Shantika Martha, Wirda Andani

“…The research pipeline includes descriptive statistics, preprocessing, feature and target variables determination, data split, model formation without and with optimization, testing accompanied by performance evaluation, and comparison of the formed model. …”
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Machine learning's model-agnostic interpretability on the prediction of students' academic performance in video-conference-assisted online learning during the covid-19 pandemic by Eka Miranda, Mediana Aryuni, Mia Ika Rahmawati, Siti Elda Hiererra, Albert Verasius Dian Sano

“…Objective: This study aims to develop machine learning (ML) model-agnostic interpretability that could predict students' academic performance in VCAOL. …”
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A Large-Scale Empirical Study of Aligned Time Series Forecasting by Polina Pilyugina, Svetlana Medvedeva, Kirill Mosievich, Ilya Trofimov, Alina Kostromina, Dmitry Simakov, Evgeny Burnaev

“…From our large-scale empirical study, we draw the following main conclusions: boosting-based methods, which are often overlooked, have a strong performance; the global modeling approach is promising because it provides competitive performance with a small computational cost; meta-learning via portfolio selection performs better than one based on meta-features. …”
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Towards an Efficient Remote Sensing Image Compression Network with Visual State Space Model by Yongqiang Wang, Feng Liang, Shang Wang, Hang Chen, Qi Cao, Haisheng Fu, Zhenjiao Chen

“…To alleviate this issue, we propose a learned remote sensing image compression network with visual state space model named VMIC to achieve a better trade-off between computational complexity and performance. …”
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Learning Part-Based Features for Vehicle Re-Identification with Global Context by Rajsekhar Kumar Nath, Debjani Mitra

“…Learning part-based features augmented with one or more global features is an efficient approach for enhancing the performance of re-identification networks. …”
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User recommendation method integrating hierarchical graph attention network with multimodal knowledge graph by Xiaofei Han, Xiaofei Han, Xin Dou

“…The model consists of four key components: a collaborative knowledge graph neural layer, an image feature extraction layer, a text feature extraction layer, and a prediction layer. …”
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Predicting breast cancer recurrence using deep learning by Deepa Kumari, Mutyala Venkata Sai Subhash Naidu, Subhrakanta Panda, Jabez Christopher

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Deep context-attentive transformer transfer learning for financial forecasting by Ling Feng, Ananta Sinchai

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Cross-dataset micro-expression identification based on facial ROIs contribution quantification by Yu Kun, Guo Chunfeng

“…Next calculate the optical-flow field of the image sequence, and extract the improved Main Directional Mean Optical-flow feature. Finally, the learned group sparse model is used as the classifier to predict the label information of the unmarked target samples, so as to complete the category recognition of micro-expressions. …”
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Research on Creep Constitutive Model for High Temperature Reactor Based on Neural Network by ZHANG Fan, DAI Shoutong

“…The model predicts the long-term creep features with an improved accuracy. …”
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