Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques by Yadigar Imamverdiyev, Elshan Baghirov, John Chukwu Ikechukwu

“…The analysis revealed vital features significantly impacting malware detection, such as process services, active services, file handles, registry keys, and callback functions. …”
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Cross-Layer Feature Fusion and Decentration Aberration Correction of Circular Points for Automated Guided Vehicle Terminal Positioning by Guiyang Zhang, Lanyu Yang, Kunkang Cao, Zengguang Man, Jian Wu, Boning Li

“…To address the visual detection and positioning challenge of the Automated Guided Vehicle (AGV) terminal, this study proposed a high-precision target recognition and positioning strategy based on cross-layer feature fusion and eccentricity error correction. …”
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Exploratory integration of near-infrared spectroscopy with clinical data: a machine learning approach for HCV detection in serum samples by Eloy Pérez-Gómez, José Gómez, José Gómez, Jennifer Gonzalo, Sergio Salgüero, Daniel Riado, María Luisa Casas, María Luisa Gutiérrez, Elena Jaime, Enrique Pérez-Martínez, Rafael García-Carretero, Javier Ramos, Conrado Fernández-Rodríguez, Conrado Fernández-Rodríguez, Myriam Catalá, Myriam Catalá, Luca Martino, Óscar Barquero-Pérez

“…Feature importance analysis highlighted specific wavelengths near 1,150 nm, 1,410 nm, and 1,927 nm, associated with water molecular states and liver function biomarkers (GPT, GOT, GGT), reinforcing the biological relevance of this approach.ConclusionsThese findings suggest that integrating NIRS and clinical data through machine learning enhances HCV diagnostic capabilities, offering a scalable and non-invasive alternative for early detection and risk assessment.…”
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Machine Learning Approaches for Fault Detection in Internal Combustion Engines: A Review and Experimental Investigation by A. Srinivaas, N. R. Sakthivel, Binoy B. Nair

“…This paper concludes with a review of the progress in fault identification in ICE components and prospects, highlighted by an experimental investigation using 16 machine learning algorithms with seven feature selection techniques under three load conditions to detect faults in a four-cylinder ICE. …”
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Advanced genetic algorithm (GA)-independent component analysis (ICA) ensemble model for predicting trapped humans through hybrid dimensionality reduction by Enoch Adama Jiya, Ilesanmi B. Oluwafemi

“…The features are sent into the classifiers for technique analysis based on their class variants. …”
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Enhancing Kármán Vortex Street Detection via Auxiliary Networks Incorporating Key Atmospheric Parameters by Yihan Zhang, Zhi Zhang, Qiao Su, Chaoyue Wu, Yuqi Zhang, Daoyi Chen

“…To overcome this limitation, this study presents an innovative auxiliary network framework that integrates essential atmospheric physical parameters to bolster the detection performance of Kármán vortex streets. Utilizing reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF-ERA5), representative atmospheric features are extracted and subjected to feature permutation importance (PFI) analysis to quantitatively evaluate the influence of each parameter on the detection task. …”
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Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning by Jie Huang, Yanli Zhao, Zhanxiao Tian, Wei Qu, Xia Du, Jie Zhang, Meng Zhang, Yunlong Tan, Zhiren Wang, Shuping Tan

“…The effects of different emotional stimuli and the fusion of demographic information and MFCCs on schizophrenia detection were examined. Results The discriminant analysis results showed superior performance for neutral emotional stimuli compared to positive and negative stimuli. …”
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A Fast and Cost-Effective Electronic Nose Model for Methanol Detection Using Ensemble Learning by Bilge Han Tozlu

“…The Voting Classifier achieved 85.88% classification accuracy before and 81.85% after feature selection. With its cost effectiveness, fast processing time, and practicality, the recommended system shows great potential for detecting methanol, which threatens human health in counterfeit drink production.…”
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Rock fracture type recognition based on deep feature learning of microseismic signals by LI Dianze, XU Huajie, ZHANG Bo

“…Microseismic monitoring has been widely used for detecting rock fractures. However, conventional machine learning methods for microseismic signal analysis exhibited limited feature extraction capabilities and were highly susceptible to noise, leading to reduced classification accuracy and poor generalization performance. …”
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Identifying candidate biomarkers for detecting bronchogenic carcinoma stages using metaheuristic algorithms based on information fusion theory by Bagher Khalvati, Kaveh Kavousi, Amir Hosein Keyhanipour, Masoud Arabfard

“…This study aims to identify non-invasive biomarkers for detecting bronchogenic carcinoma and its various stages by analyzing gene expression data using bioinformatics and machine learning techniques. …”
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Long short‐term memory on abstract syntax tree for SQL injection detection by Z. Zhuo, T. Cai, X. Zhang, F. Lv

“…However, major bottlenecks still remain in detecting SQLIA with bypassing techniques, getting access to source code and requiring an additional manual operation to extract features. …”
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Spatiotemporal distribution and detection of spatial clusters of tuberculosis in Hubei Province, China using FleXScan (2017–2023) by Lina Wang, Yaru Li, Ji Chen, Danfei Zhang, Zhengbin Zhang, Xiang Li

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Optimizing Heart Disease Prediction: A Comparative Analysis of Tree-Based Ensembles With Feature Expansion and Selection by K. Aswini, Kriti Arya

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Analysis of Factors Affecting Random Measurement Error in LiDAR Point Cloud Feature Matching Positioning by Guoliang Liu, Wang Gao, Shuguo Pan

“…Therefore, this work draws on the random measurement error analysis method of GNSS observations to study the impact of factors such as distance, angle, and feature accuracy on the random measurement error of LiDAR. …”
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A discriminant analysis of the P3b wave with electroencephalogram by feature‐electrode pairs in schizophrenia diagnosis by Juan I. Arribas, Luis M. San‐José‐Revuelta

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Framework for Mapping Sublimation Features on Mars’ South Polar Cap Using Object-Based Image Analysis by Racine D. Cleveland, Vincent F. Chevrier, Jason A. Tullis

“…This study applies object-based image analysis (OBIA) to automate the detection and measurement of SCFs using High-Resolution Imaging Science Experiment (HiRISE) images spanning five Martian years. …”
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GB-SAR Engineering Interference Suppression Method Integrating Amplitude-Phase Feature Analysis and Robust Regression by Wenting Zhang, Tao Lai, Yuanhui Mo, Haifeng Huang, Qingsong Wang, Zhihua Zhou

“…Current research on addressing engineering interference in GB-SAR deformation monitoring remains preliminary, with existing methods exhibiting limitations in interference pattern coverage, feature extraction, and algorithm robustness. To address these challenges, this article proposes a joint processing method integrating amplitude-phase feature analysis and robust regression. …”
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Automatic Segmentation and Characterization of Structure Planes From Borehole Images Based on Deep Learning by Shuangyuan Chen, Zengqiang Han, Yi Cheng, Chao Wang

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Guided wave signal‐based sensing and classification for small geological structure by Hongyu Sun, Jiao Song, Shanshan Zhou, Qiang Liu, Xiang Lu, Mingming Qi

“…Utilising this method, advanced detection of geological anomalies hidden in coal seams was achieved. …”
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Feature Extraction and Identification of Rheumatoid Nodules Using Advanced Image Processing Techniques by Azmath Mubeen, Uma N. Dulhare

“…Background/Objectives: Accurate detection and classification of nodules in medical images, particularly rheumatoid nodules, are critical due to the varying nature of these nodules, where their specific type is often unknown before analysis. …”
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