Evaluating Communication Performance in Rotating Electrical Machines Using RSSI Measurements and Artificial Intelligence by Sonia Ben Brahim, Samia Dardouri, Hanen Lajnef, Amel Ben Slimane, Ridha Bouallegue, Tan-Hoa Vuong

“…The methodology comprises several stages, including data collection, preprocessing, feature extraction, and model training. Various machine learning models are implemented and evaluated. …”
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TGEL-transformer: Fusing educational theories with deep learning for interpretable student performance prediction. by Yuhao Gong, Fei Wang, Yuchen Zhang, Jiaqi Geng

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The Importance of Rhythm Activity in Epilepsy EEG Signal Classification (An Educational Article) by Negin Melek

“…It cannot be overlooked that among the four methods used for performance evaluation in the designed model, the classification success of frequency domain features was more successful than that of time domain features. …”
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The Role of Performance Metrics in Estimating Market Values of Footballers in Europe's Top Five Leagues by Murat Işık, Mehmet Ali Yalçınkaya

“…The results indicate that performance metrics significantly contribute to estimating football players' market values, and models based on these metrics can assist clubs in making more informed, data-driven decisions during transfers.…”
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Performance of Fine-Tuning Techniques for Multilabel Classification of Surface Defects in Reinforced Concrete Bridges by Benyamin Pooraskarparast, Son N. Dang, Vikram Pakrashi, José C. Matos

“…Machine learning models often face challenges in bridge inspections, especially in handling complex surface features and overlapping defects that make accurate classification difficult. …”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. …”
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GTMALoc: prediction of miRNA subcellular localization based on graph transformer and multi-head attention mechanism by Xindi Huang, Jipu Jiang, Lifen Shi, Cheng Yan

“…Next, a multi-head attention mechanism is implemented to combine miRNA features from multiple networks, allowing the model to capture deeper feature relationships and enhance prediction performance. …”
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General regression and representation model for classification. by Jianjun Qian, Jian Yang, Yong Xu

“…In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR) for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients) and the specific information (weight matrix of image pixels) to enhance the classification performance. …”
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Tractor Path Tracking Control Method Based on Prescribed Performance and Sliding Mode Control by Liwei Zhu, Weiming Sun, Qian Zhang, En Lu, Jialin Xue, Guohui Sha

“…In addressing the challenges of low path tracking accuracy and poor robustness during tractor autonomous operation, this paper proposes a path tracking control method for tractors that integrates prescribed performance with sliding mode control (SMC). A key feature of this control method is its inherent immunity to system parameter perturbations and external disturbances, while ensuring path tracking errors are constrained within a predefined range. …”
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Enhancing and monitoring the environmental performance of complex industrial projects: a communication-based approach by Joseph Mansour Salamé, Isabelle Nicolaï, Michael Saidani, Yann Leroy

“…Lasswell's model bolsters existing assessment frameworks by incorporating the sharing aspect among stakeholders that they lack.The proposed method is used to select environmental performance indicators for monitoring rail infrastructure projects. …”
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Finding excesses in model parameter space by Kierthika Chathirathas, Torben Ferber, Felix Kahlhoefer, Alessandro Morandini

“…Abstract Simulation-based inference (SBI) makes it possible to infer the parameters of a model from high-dimensional low-level features of the observed events. …”
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Enhancing cross entropy with a linearly adaptive loss function for optimized classification performance by Jae Wan Shim

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An integrative modelling approach to the mitochondrial cristae by Chelsea M. Brown, Marieke S. S. Westendorp, Rubi Zarmiento-Garcia, Jan A. Stevens, Bart M. H. Bruininks, Sarah L. Rouse, Siewert J. Marrink, Tsjerk A. Wassenaar

“…Our coarse-grained representation of a crista shows how various experimentally determined features of organelles can be combined with molecular modelling to give insights into the interactions and dynamics of complicated biological systems. …”
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The Effectiveness of Hybrid Beamforming in Enhancing the Performance of NOMA-mmWave and Massive MIMO Systems by Oubassghir Mourtada, Boulouird Mohamed

“…This study aims to examine the performance of this integration in terms of SE and EE by employing a system model featuring a single base station equipped with multiple antennas that generate distinct beams serving multiple users using max-min fairness power allocation. …”
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Procedural Content Graphs for Urban Modeling by Pedro Brandão Silva, Elmar Eisemann, Rafael Bidarra, António Coelho

“…While shape grammars are a popular example of effectiveness in architectural modeling, they have clear limitations regarding readability, manageability, and expressive power when addressing a variety of complex structural designs. …”
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Dynamic Analysis of Resilient Rocking Wall Structures: A Numerical Study on Performance Demands by Soheil Assadi, Ashkan Hashemi, Nicholas Chan, Pierre Quenneville

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Attention dual transformer with adaptive temporal convolutional for diabetic retinopathy detection by Mishmala Sushith, Ajanthaa Lakkshmanan, M. Saravanan, S. Castro

“…Experimentation of the proposed model using DRIVE and Diabetic Retinopathy datasets demonstrates the better performance of proposed ADTATC model with an accuracy of 98.2% on DRIVE and 97.7% on Diabetic Retinopathy datasets compared to conventional deep learning models.…”
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A synthetic data-driven machine learning approach for athlete performance attenuation prediction by Mauricio C. Cordeiro, Ciaran O. Cathain, Ciaran O. Cathain, Lorcan Daly, Lorcan Daly, David T. Kelly, David T. Kelly, Thiago B. Rodrigues

“…Our findings emphasize that this approach increased data availability and improved model performance in specific scenarios.DiscussionSeveral limitations remain: (1) there is limited framework transferability to sports with different physiological demands; (2) the Synthetic Data Generation (SDG) does not currently enforce feature constraints, and future implementations must ensure the procedure respects domain-specific feature limits; and (3) TVAE faced data fidelity challenges with certain variables, such as VO2max. …”
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Modeling of acute radiation syndrome in experiment by A. A. Popova, L. A. Chipiga, D. N. Maystrenko, A. A. Stanzhevskiy, O. E. Molchanov, D. N. Nikolaev, T. E. Ponezha, Yu. N. Vinogradova, E. B. Ioffe

“…The aim of the current study was to create a new and easily reproducible method of modeling acute radiation syndrome, representing the features of the clinical flow of this disease. …”
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An Integrated Building Energy Model in MATLAB by Marco Simonazzi, Nicola Delmonte, Paolo Cova, Roberto Menozzi

“…In the general context of the development of integrated energy district models to guide the evolution and planning of smart energy grids for increased efficiency, resilience, and sustainability, this work describes in detail the development and use of an IBEM for a university campus building featuring a heat pump-based heating/cooling system and PV generation. …”
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