Employing combined spatial and frequency domain image features for machine learning-based malware detection by Abul Bashar

“…To this end, three image-based datasets, namely, Dex, Manifest, and Composite, derived from the information security centre of excellence (ISCX) Android Malware dataset, were leveraged to evaluate the optimal data source for botnet classification. Popular ML classifiers, including naive Bayes (NB), multilayer perceptron (MLP), support vector machine (SVM), and random forest (RF), were employed for the classification task. …”
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A Machine Learning Platform for Isoform-Specific Identification and Profiling of Human Carbonic Anhydrase Inhibitors by Lisa Piazza, Miriana Di Stefano, Clarissa Poles, Giulia Bononi, Giulio Poli, Gioele Renzi, Salvatore Galati, Antonio Giordano, Marco Macchia, Fabrizio Carta, Claudiu T. Supuran, Tiziano Tuccinardi

“…<b>Methods:</b> By integrating four molecular representations with four ML algorithms, we built 64 classification models, each extensively optimized and validated. …”
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A detailed analysis of game statistics of professional tennis players: An inferential and machine learning approach. by Michal Bozděch, Dominik Puda, Pavel Grasgruber

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A Portable Real-Time Electronic Nose for Evaluating Seafood Freshness Using Machine Learning by Muhammad Rafi Mahfuz Setyagraha, Hurul Aini Nurqamaradillah, Laksamana Mikhail Hermawan, Nyoman Raflly Pratama, Ledya Novamizanti, Dedy Rahman Wijaya

“…This study presents an electronic nose (e-nose) system designed to assess seafood freshness using gas sensors and machine learning (ML) algorithms. The system detects volatile organic compounds (VOCs) released during spoilage and employs hyperparameter-optimized ML models for both classification (fresh vs. not fresh) and regression (shelf-life prediction). …”
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Strategies for Automated Identification of Food Waste in University Cafeterias: A Machine Vision Recognition Approach by Yongxin Li, Chaolong Zhang, Hui Xu, Yuantong Yang, Han Lu, Lei Deng

“…To ensure the effective implementation of food waste reduction in college cafeterias, Capital Normal University developed an automatic plate recognition system based on machine vision technology. The system operates by obtaining images of plates (whether clean or not) and the diners’ faces through multi-directional monitoring, then employs several deep learning models for the automatic localization and identification of the plates. …”
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Machine learning approaches reveal methylation signatures associated with pediatric acute myeloid leukemia recurrence by Yushuang Dong, HuiPing Liao, Feiming Huang, YuSheng Bao, Wei Guo, Zhen Tan

“…Incremental Feature Selection was performed to evaluate these results, and optimal subsets were identified using Decision Tree and Random Forest methods. …”
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Mechanisms of external magnetic field influence on electrical discharge machining of SiCp/Al composites by Tengfei Han, Kan Wang, Jinlai Wang, Guangyang Xin, Yong Liu, Qinhe Zhang

“…This study investigates how external magnetic fields influence EDM of SiCp/Al composites through mathematical modeling, simulations, and machining experiments. Analysis of external magnetic field interactions reveals that the field modifies particle trajectories, increases discharge energy, and alters the pinch effect. …”
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Enhancing Performance and Quality of Transmission Through Knowledge-Driven Machine Learning-Based FWM Mitigation by Sudha Sakthivel, Muhammad Mansoor Alam, Aznida Abu Bakar Sajak, Mazliham Mohd Su'ud, Mohammad Riyaz Belgaum

“…Firstly, machine learning optimizes parameters at the transmitter end to identify FWM monitoring factors, predict QoT based on subscriber requirements, and create a comprehensive database for training Machine Learning (ML) models. …”
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Multi-Source Satellite Imagery and Machine Learning for Detecting Geological Formations in Cameroon’s Western Highlands by Kacoutchy Jean Ayikpa, Valère-Carin Jofack Sokeng, Abou Bakary Ballo, Pierre Gouton, Koffi Fernand Kouamé

“…These observations highlight the potential of geographic and geological parameters associated with suitable models to improve classification. The multi-source approach thus proves optimal for more robust and precise results.…”
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Experimental and machine learning based analysis of pervious concrete enhanced with fly ash and silica fume by Siva Shanmukha Anjaneya Babu Padavala, Siva Avudaiappan, Venkatesh Noolu

“…It also resulted in a 4.7 % reduction in CO₂ emissions and 6.19 % lower material costs, supporting its suitability for sustainable infrastructure applications. Machine learning (ML) models were also created in order to predict compressive strength based on mix composition and curing age using Orange Data Mining software version 3.36. …”
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A fully automated machine-learning-based workflow for radiation treatment planning in prostate cancer by Jan-Hendrik Bolten, David Neugebauer, Christoph Grott, Fabian Weykamp, Jonas Ristau, Stephan Mende, Elisabetta Sandrini, Eva Meixner, Victoria Navarro Aznar, Eric Tonndorf-Martini, Kai Schubert, Christiane Steidel, Lars Wessel, Jürgen Debus, Jakob Liermann

“…In this study, we assess the clinical feasibility of a fully automated machine learning (ML)-based “one-click” workflow that combines ML-based segmentation and treatment planning. …”
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Development of a Three-Dimensional Geometry Optimization Method for Turbomachinery Applications by Steffen Kämmerer, Jürgen F. Mayer, Heinz Stetter, Meinhard Paffrath, Utz Wever, Alexander R. Jung

“…Physical parameters such as stagger angle, stacking line, and chord length are part of the model. Constraints guarantee the requirements for cooling, casting, and machining of the blades.…”
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Optimization and Simulation of Loading and Unloading Robot Structure Parameter of Production Line by Chuan Liao, Yinghua Liao, Jun Xie

“…The working space is a constraint condition， and the optimal section of the main section of the manipulator workspace is the objective function， and the structural parameter optimization model is established. …”
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Structural Optimization and Cutting Simulation Analysis of BAT Deep-hole Drilling by WU Xue-feng, MA Lu, YUAN Zhong-liang, YANG Shu-cai

“…Structures and angles of tools are the main factors that influence the machining quality and machining efficiency. Because the processing of deep-hole drilling is not visible，it is very difficult to optimize structure and angles of tool through the experiment method. …”
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Structure design, analysis, and optimization of 12-pole radial magnetic bearing by Penghui Zhang, Yuexin Feng, Peng Wen, Jinbin Zou, Zigang Deng

“…This study fills this gap by systematically investigating the structural design and optimization of the 12-pole RMB. A mathematical model using an equivalent magnetic circuit is developed, validated by Finite Element Method (FEM) simulations, showing strong agreement. …”
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An Optimized 1-D CNN-LSTM Approach for Fault Diagnosis of Rolling Bearings Considering Epistemic Uncertainty by Onur Can Kalay

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Leveraging LLMs for optimised feature selection and embedding in structured data: A case study on graduate employment classification by Radiah Haque, Hui-Ngo Goh, Choo-Yee Ting, Albert Quek, M.D. Rakibul Hasan

“…Further transformation with BERT-based embeddings raised the highest accuracy to 85% using the BERT classifier. Finally, the optimal accuracy of 88% was obtained by applying feature selection before and after embedding, with the BERT-Boruta model. …”
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The Role of Artificial Intelligence in Predicting and Managing Pediatric Fracture Overgrowth: A Comprehensive Review by Daniela Alessia Marletta, Matteo Nanni, Gabriele Giuca, Ilaria Sanzarello, Biagio Zampogna, Danilo Leonetti

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Joined Spatial and Spectral Segmentation of Hyperspectral Datasets on Historical Art Objects by Lingxi Liu, Aurore Malmert, Emeline Pouyet, Silvia Mirri, Giovanni Delnevo

“…This research highlights the potential of machine learning in aiding artwork diagnostics, conservation, and restoration, with transferable models for similar scenarios.…”
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Integrating Gut Microbiome and Metabolomics with Magnetic Resonance Enterography to Advance Bowel Damage Prediction in Crohn&amp;rsquo;s Disease by Huang L, Meng J, Lin S, Peng Z, Zhang R, Shen X, Zheng W, Zheng Q, Wu L, Wang X, Wang Y, Mao R, Sun C, Li X, Feng ST

“…The relationships between microbial/metabolic factors and MRE features were explored using correlation and mediation analyses. Seven machine learning algorithms, each paired with seven distinct combinations of multi-omics features, were evaluated using nested 5-fold cross-validation to construct an optimal prediction model. …”
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