Enhanced SVM-based model for predicting cyberspace vulnerabilities: Analyzing the role of user group dynamics and capital influx. by Yicheng Long

“…A standardized data preprocessing pipeline is constructed, including redundancy elimination, feature selection, and sample balancing, to ensure data representativeness and compatibility. …”
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Improved Algorithm for Vehicle Bottom Safety Detection Based on YOLOv8n: PSP-YOLO by Di Zhao, Yulin Cheng, Sizhe Mao

“…Finally, the Partial Convolution (PConv) lightweight module was also added to the feature fusion network, effectively reducing the model’s parameters and computational load, conserving computing resources, and improving detection speed and accuracy. …”
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RESTORATION OF THE CONSTRUCTION AND ROAD MACHINES’ DETAILS FROM GREY CAST IRON: IMPROVEMENT OF THE REPAIR DIMENSIONS’ METHOD EFFICIENCY by V. E. Ovsyannikov, V. I. Vasilyev

“…Considering that the contacting parts in these units take the load mainly by surface layers. The operability looses at relatively small values of dimensional wear. …”
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Transgenic overexpression of LARGE induces α-dystroglycan hyperglycosylation in skeletal and cardiac muscle. by Martin Brockington, Silvia Torelli, Paul S Sharp, Ke Liu, Sebahattin Cirak, Susan C Brown, Dominic J Wells, Francesco Muntoni

“…However this remained a subclinical feature as no pathology was observed in older mice in any muscles including the diaphragm, which is sensitive to mechanical load-induced damage.…”
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Type I Interferons Direct Gammaherpesvirus Host Colonization. by Cindy S E Tan, Clara Lawler, Janet S May, Gabrielle T Belz, Philip G Stevenson

“…Murine cytomegalovirus also showed a capacity to pass through IFN-I-responding cells, arguing that this is a core feature of herpesvirus host colonization.…”
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STRAIN CONCENTRATION IN APICES OF RADIAL CRACKS IN A THIN COATED PIPE WALL by M. M. Payzulaev, E. L. Rashidova, B. V. Sobol'

“…Its solution is determined by the collocation method with a pre-selected feature. The ultimate goal of the study is to determine the values of the strain intensity coefficient at the apices of the crack.…”
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The relationships between impulsivity and mood in bipolar disorder: An ecological momentary assessment study. by Almudena Ramírez-Martín, Lea Sirignano, Jerome C Foo, Fabian Streit, Josef Frank, Stephanie H Witt, Marcella Rietschel, Fermin Mayoral-Cleries, Berta Moreno-Küstner, Jose Guzmán-Parra

“…<h4>Background</h4>Impulsivity is a key feature of bipolar disorder (BD) associated with various negative outcomes. …”
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High‐Impedance Fault Detection in Distribution Networks Based on Support Vector Machine and Wavelet Transform Approach (Case Study: Markazi Province of Iran) by Mohammad Sadegh Attar, Mohammad Reza Miveh

“…Then, DWT decomposes it to extract the features of each sample in the data set. The extracted features from this part are used as input to the SVM classification algorithm. …”
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Critical Factors Governing the Frictional Coefficient in Mg Alloys—Learn From Machine Learning by Negar Bagherieh, Moslem Noori, Dongyang Li, Meisam Nouri

“…Our findings highlight the importance of normal load, elastic modulus, and content of Zn in determining the COF in magnesium alloys, which helps improve materials and mechanical system design for effective COF control.…”
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How the size of the to-be-learned material influences the encoding and later retrieval of associative memories: A pupillometric assessment. by Péter Pajkossy, Mihály Racsmány

“…During retrieval, the pupil instantly begun to dilate, as a sign of increased processing load accompanying the retrieval of the target memory. …”
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Secure edge-based smart grid communication using lightweight authentication modeling with autoencoders and real-world data by Omar Abdullah Saleh, Mesut Cevik

“…Temporal sequencing and feature normalization are utilized to optimize the model to enhance detection accuracy while minimizing computational complexity. …”
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Trustworthy AI and Federated Learning for Intrusion Detection in 6G-Connected Smart Buildings by Rosario G. Garroppo, Pietro Giuseppe Giardina, Giada Landi, Marco Ruta

“…The proposed data pre-processing and engineering system significantly reduces the amount of data to be processed by the CNN, helping to limit the processing load and associated energy consumption towards more sustainable Artificial Intelligence (AI) techniques. …”
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Machine Learning for Predicting Required Cross-Sectional Dimensions of Circular Concrete-Filled Steel Tubular Columns by Anton Chepurnenko, Samir Al-Zgul, Vasilina Tyurina

“…The third model showed high efficiency over the entire range of wall thicknesses (correlation coefficient R = 0.99974). Feature importance analysis using SHAP values confirmed the key role of bending moment and axial force in predicting geometric parameters.…”
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A Lightweight Transformer Edge Intelligence Model for RUL Prediction Classification by Lilu Wang, Yongqi Li, Haiyuan Liu, Taihui Liu

“…To address this issue, we propose TBiGNet, a lightweight Transformer-based classification network model for RUL prediction. TBiGNet features an encoder–decoder architecture that outperforms traditional Transformer models by achieving over 15% higher accuracy while reducing computational load, memory access, and parameter size by more than 98%. …”
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The pathogenesis and therapeutic implications of metabolic reprogramming in renal cell carcinoma by Yifan Zhang, Shengli Zhang, Hongbin Sun, Luwei Xu

“…Crucially, RCC exhibits metabolic heterogeneity across histological subtypes and intratumoral regions—a feature increasingly recognized as a determinant of therapeutic resistance. …”
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Modeling and control of automatic voltage regulation for a hydropower plant using advanced model predictive control by Ebunle Akupan Rene, Willy Stephen Tounsi Fokui

“…This study examined the modeling and control of AVR in hydroelectric power plants using model predictive control (MPC), which utilizes an extensive mathematical model of the voltage regulation system to optimize the control actions over a defined prediction horizon. This predictive feature enables MPC to minimize voltage deviations while accounting for operational constraints, thereby improving stability and performance under dynamic conditions. …”
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An online multi-camera multi-vehicle tracking using lightweight YOLO11 and improved association strategies by Feijiang Huang, Jialong Yao, Chengyue Su, Sheng Xu

“…While existing offline algorithms offer high accuracy, their heavy computational load and lack of real-time performance limit practical use. …”
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Predicting Wastewater Characteristics Using Artificial Neural Network and Machine Learning Methods for Enhanced Operation of Oxidation Ditch by Igor Gulshin, Nikolay Makisha

“…This forecasting capability aims to optimize the operational regime of aeration tanks by adjusting the specific load on organic pollutants through active sludge dosage modulation. …”
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Hybrid mechanism‐data‐driven iron loss modelling for permanent magnet synchronous motors considering multiphysics coupling effects by Lin Liu, Wenliang Yin, Youguang Guo

“…Purely mechanistic models require detailed theoretical knowledge and exact parameters, often struggling to accurately describe complex systems, while purely data‐driven methods lack interpretability, which are susceptible to data noise and outliers in feature extraction and complicated pattern recognition. …”
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Temporal Logical Attention Network for Log-Based Anomaly Detection in Distributed Systems by Yang Liu, Shaochen Ren, Xuran Wang, Mengjie Zhou

“…Our approach makes three key contributions: (1) a temporal logical attention mechanism that explicitly models both time-series patterns and logical dependencies between log events across distributed components, (2) a multi-scale feature extraction module that captures system behaviors at different temporal granularities while preserving causal relationships, and (3) an adaptive threshold strategy that dynamically adjusts detection sensitivity based on system load and component interactions. …”
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