A Novel Fault Diagnosis of Induction Motor by Using Various Soft Computation Techniques: BESO-RDFA by Kapu V. Sri Ram Prasad, K. Dhananjay Rao, Guruvulu Naidu Ponnada, Umit Cali, Taha Selim Ustun

“…This paper presents a hybrid prediction technique for fault detection of induction machines. The established hybrid forecast scheme signifies the combined execution of Bald-Eagle- Search-Optimization (BESO) and Random-Decision-Forest-Algorithm (RDFA), called as BESO-RDFA prediction scheme. …”
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Terahertz Spectroscopy for Food Quality Assessment: A Comprehensive Review by Jie Yang, Xue Bai, Mingji Wei, Hui Jiang, Leijun Xu

“…By integrating spectral data preprocessing, reconstruction algorithms, and machine learning model optimization strategies, this paper further analyzes the advantages and challenges of this technology in enhancing detection accuracy and efficiency. …”
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An efficient IoT-based crop damage prediction framework in smart agricultural systems by Nermeen Gamal Rezk, Abdel-Fattah Attia, Mohamed A. El-Rashidy, Ayman El-Sayed, Ezz El-Din Hemdan

“…The key contributions of this innovative work include the design of a low-cost, power-efficient, and scalable crop damage prediction system, the integration of real-time IoT data with optimized ensemble learning, and a comprehensive evaluation of imputation techniques to enhance model robustness. …”
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Advancing named entity recognition in interprofessional collaboration and education by Rui Zhang, Yifeng Shan, MengZhe Zhen

“…While traditional methods, such as rule-based systems and machine learning models, have achieved moderate success in various domains, they often struggle with the dynamic, context-sensitive nature of IPC scenarios. …”
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Web-based nutrient management with the software webBESyD–Scientific principles, software architecture and model validation by Joseph Donauer, Marco Luthardt, Christiane Peter, Michael Grunert, Aurelia Ostermaier-Welz, Frank Leßke, Kurt-Jürgen Hülsbergen

“…All data concerning crop and livestock production is stored centrally in a clearly structured farm model. The modular design allows two different modes of operation: Users can utilize webBESyD directly via a graphical user interface or use specific modules from external systems via a machine-readable application interface. …”
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A Deep Learning Framework for Enhanced Detection of Polymorphic Ransomware by Mazen Gazzan, Bader Alobaywi, Mohammed Almutairi, Frederick T. Sheldon

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Internet of Things and Artificial Intelligence for Secure and Sustainable Green Mobility: A Multimodal Data Fusion Approach to Enhance Efficiency and Security by Manuel J. C. S. Reis

“…Using publicly available datasets, including METR-LA for traffic flow and OpenWeatherMap for environmental context, the framework integrates machine learning models for congestion prediction and reinforcement learning for dynamic route optimization. …”
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Region versus query based instance segmentation models: application to the estimation of aggregated TiO2 particles size distribution measured by SEM by Paul Monchot, Loïc Coquelin, Nicolas Fischer

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Artificial intelligence in electroencephalography analysis for epilepsy diagnosis and management by Chenxi Wang, Chenxi Wang, Xinyue Yuan, Wei Jing

“…However, challenges persist, such as limited model interpretability, data quality constraints, and barriers to clinical translation. …”
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Predictive framework of vegetation resistance in channel flow by Fengcong Jia, Weijie Wang, Yu Han, Jiayu Du, Yue Zhang, Zihan Liu, Hairong Gao

“…Although numerous empirical models are available, they often fail to generalize across different environmental conditions, leading to inaccurate predictions. …”
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New hybrid features extracted from US images for breast cancer classification by Gigi Tăbăcaru, Simona Moldovanu, Dan Munteanu, Marian Barbu

“…In this context, two different AutoML, PyCaret and TPOT (Tree-based Pipeline Optimization Tool) were proposed, and the optimal model for hybrid features included in the classification process was identified during the tuning process. …”
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Evolution of plastic deformation during multi-pass ECAP of an AA6060 aluminum alloy – An experimental flow line analysis by Nadja Berndt, Nadja A. Reiser, Martin F.-X. Wagner

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Evaluating a Large Language Model’s Ability to Synthesize a Health Science Master’s Thesis: Case Study by Pål Joranger, Sara Rivenes Lafontan, Asgeir Brevik

“… Abstract BackgroundLarge language models (LLMs) can aid students in mastering a new topic fast, but for the educational institutions responsible for assessing and grading the academic level of students, it can be difficult to discern whether a text has originated from a student’s own cognition or has been synthesized by an LLM. …”
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Exploring high entropy alloys: A review on thermodynamic design and computational modeling strategies for advanced materials applications by Peter Ifeolu Odetola, Bukola Joseph Babalola, Ayodeji Ebenezer Afolabi, Ufoma Silas Anamu, Emmanuel Olorundaisi, Mutombo Christian Umba, Thabang Phahlane, Olusoji Oluremi Ayodele, Peter Apata Olubambi

“…This review focuses on intricate thermodynamic and computational modeling to guide the design and optimization of HEAs. …”
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Enhancing Daylight and Energy Efficiency in Hot Climate Regions with a Perforated Shading System Using a Hybrid Approach Considering Different Case Studies by Basma Gaber, Changhong Zhan, Xueying Han, Mohamed Omar, Guanghao Li

“…A hybrid approach integrating parametric modeling, machine learning, multi-criteria decision-making (MCDM), and genetic algorithm (GA) is used to optimize the design incorporating architects’ preferences. …”
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A Risk Warning Model for Anemia Based on Facial Visible Light Reflectance Spectroscopy: Cross-Sectional Study by Yahan Zhang, Yi Chun, Hongyuan Fu, Wen Jiao, Jizhang Bao, Tao Jiang, Longtao Cui, Xiaojuan Hu, Ji Cui, Xipeng Qiu, Liping Tu, Jiatuo Xu

“…We integrated multiple machine learning classification models to identify the optimal model and developed Shapley additive explanations (SHAP) for personalized risk assessment. …”
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3D FEM Simulation and Experiment Research for Milling Process of Hardened Curved Mold by YUE Cai-xu, HAO Sheng-yu, HUANG Cui, WANG Yan-wu

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Opportunities and Limitations of Wrist-Worn Devices for Dyskinesia Detection in Parkinson’s Disease by Alexander Johannes Wiederhold, Qi Rui Zhu, Sören Spiegel, Adrin Dadkhah, Monika Pötter-Nerger, Claudia Langebrake, Frank Ückert, Christopher Gundler

“…Each representation was assessed on public datasets to identify the best-performing machine learning model and subsequently applied to our own collected dataset to assess generalizability. …”
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Testing an inverse modeling approach with gradient boosting regression for stroke volume estimation using patient thermodilution data by Vasiliki (Vicky) Bikia, Dionysios Adamopoulos, Dionysios Adamopoulos, Dionysios Adamopoulos, Marco Roffi, Marco Roffi, Georgios Rovas, Stéphane Noble, Stéphane Noble, François Mach, François Mach, Nikolaos Stergiopulos

“…We developed a modified method for SV estimation that combines a validated 1-D model of the systemic circulation with machine learning. …”
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Enhancing mechanical and bioinspired materials through generative AI approaches by Silvia Badini, Stefano Regondi, Raffaele Pugliese

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