Intelligent power control strategy based on self-tuning fuzzy MPPT for grid-connected hybrid system by H. Chaib, S. Hassaine, Y. Mihoub, S. Moreau

“…This study presents a thorough evaluation of intelligent control methods for MPPT in HRESs, emphasizing their potential to optimize energy supply under varying conditions. …”
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Educational game for conflict mediation training in wartime conditions using large language models by Sophia V. Ilkova, Pavlo V. Merzlykin, Natalia V. Moiseienko

“…We implemented the system using the Gemini 1.5 Flash LLM and conducted experiments to optimize model parameters and evaluate the effectiveness of different mediation strategies. …”
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Multilayer Gas-Bearing System and Productivity Characteristics in Carboniferous–Permian Tight Sandstones: Taking the Daning–Jixian Block, Eastern Ordos Basin, as an Example by Ming Chen, Bo Wang, Haonian Tian, Junyi Sun, Lei Liu, Xing Liang, Benliang Chen, Baoshi Yu, Zhuo Zhang

“…These factors increase displacement and median pressures, resulting in inferior reservoir quality. By comparing and evaluating the gas production effects under different extraction methods, targeted optimization recommendations are provided to offer both theoretical support and practical guidance for the efficient development of this block.…”
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Developing Multicriteria Rating Scale for Assessment of Communicative Competence in LSP Oral Presentation by Vesna M. Petrović, Ana S. Jovanović, Marija R. Đukić

“…For this purpose, the prevailing contemporary theoretical models of communicative competence and specific purpose language ability were explored and five different models of multicriteria rating scales were generated. …”
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A validity of phenomenological models of turbulence in experimental studies by A. G. Gorelik, S. F. Kolomiets

“…In particular, a method of turbulent dissipation rate measurement by means of two (or more) filters with different bandpasses applied to signals in two points of cross-correlation measurements and an approach to the physically clear description of the optimal number of Fourier-terms in the representation of the signal passed the filter are outlined as well as the approach to a turbulence spectral shape evaluation. …”
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A Security and Privacy-Preserving Consortium Blockchain-Based Accessing Control in Mobile Crowdsensing by Abdulrahman Alamer

“…However, because the blockchain is a decentralized database, a malicious MCS-server will be able to disclose the privacy of participating mobile devices by linking multiple blocks generated for the same device while it performs different tasks. …”
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FADA-SMOTE-Ms: Fuzzy Adaptative Smote-Based Methods by Roudani Mohammed, El Moutaouakil Karim

“…However, it has three shortcomings: <xref ref-type="disp-formula" rid="deqn1">(1)</xref> it may cause the over-generalization problem due to oversampling of noisy samples, <xref ref-type="disp-formula" rid="deqn2">(2)</xref> over-sampling of uninformative samples, and <xref ref-type="disp-formula" rid="deqn3">(3)</xref> increasing the overlaps between different classes around the class boundaries. Different approaches SMOTE based have been proposed to handle these problems, but most of them implement hyperparameters and tend to generate noise because the synthetic sample is generated, randomly, in the area delimited by current random minority data. …”
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Designing a Cross-Platform Application That Employs Multi-Criteria Decision Making for Estimating the Value of Monumental Trees by Katerina Kabassi, Konstantinos Asiklaris, Aristotelis Martinis, Charikleia Minotou, Athanasios Botonis

“…The system uses and combines three different multi-criteria decision-making theories, namely, analytical hierarchy process (AHP), simple additive weighting (SAW), and multicriteria optimization and compromise solution (VIKOR) and evaluates olive trees based on tangible and intangible criteria. …”
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Comparison of One-Drill Protocol to Sequential Drilling In Vitro and In Vivo by Sihana Rugova, Marcus Abboud

“…This study compares the heat generated during bone drilling using different protocols and implant systems, first in vitro and then in vivo with an animal model. …”
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Sustainable innovation in foamed concrete using waste sanitary ware as fine aggregate for properties enhancement by Mydin, Md Azree Othuman, Sor, Nadhim Hamah, Al Bakri Abdullah, Mohd Mustafa, Isleem, Haytham F., Dulaimi, Anmar, Awoyera, Paul O., Fadugba, Olaolu George, Tawfik, Taher A.

“…The solid waste generated by the waste sanitary ware (WSW) sector is of considerable magnitude on a global scale. …”
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Coordinated Multimodal Transportation Infrastructure Planning in Megacities: An Agent-AI-Discrete Network Design Problem Approach Based on Chat-GPT by Jin Guo, Chenyang Wang, Linxiu Wang

“…These metrics are then used to evaluate the suitability of different infrastructure planning strategies. …”
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Methodological approach to the ex vivo expansion and detection of T. cruzi-specific T cells from chronic Chagas disease patients. by Gonzalo R Acevedo, Silvia A Longhi, Alcinette Bunying, Nazila Sabri, Augusto Atienza, María P Zago, Radleigh Santos, Valeria A Judkowski, Clemencia Pinilla, Karina A Gómez

“…The aim of the present work was to optimize a protocol for the generation of parasite-specific memory T cell lines, representative of their in vivo precursor populations and capable of responding to parasite antigens after long-term culture. …”
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Depression Classification From Tweets Using Small Deep Transfer Learning Language Models by Muhammad Rizwan, Muhammad Faheem Mushtaq, Urooj Akram, Arif Mehmood, Imran Ashraf, Benjamin Sahelices

“…&#x2018;severe&#x2019;, &#x2018;moderate&#x2019;, and &#x2018;mild&#x2019; by downstream fine-tuning the parameters. Evaluation metrics such as accuracy, F1, precision, recall, and specificity are calculated to evaluate the performance of the models. …”
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Methodological Validation of Machine Learning Models for Non-Technical Loss Detection in Electric Power Systems: A Case Study in an Ecuadorian Electricity Distributor by Carlos Arias-Marín, Antonio Barragán-Escandón, Marco Toledo-Orozco, Xavier Serrano-Guerrero

“…One of the challenges lies in managing the different variables in the training data and choosing appropriate evaluation metrics. …”
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Achieving tip-based down-milling forming of nanograting structures with variable heights through precise control of nano revolving trajectories by Bo Xue, Huilin Yan, Zhengchang Liu, Yongda Yan, Yanquan Geng

“…Three distinct types of revolving trajectories are filtered out according to five quantitative evaluation indicators for machining performance, namely material plastic deformation, grating profile consistency, grating height consistency, machining forces, and area transforming height, and then are compared in processing nanogratings with different heights. …”
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Large Language Model–Assisted Risk-of-Bias Assessment in Randomized Controlled Trials Using the Revised Risk-of-Bias Tool: Usability Study by Jiajie Huang, Honghao Lai, Weilong Zhao, Danni Xia, Chunyang Bai, Mingyao Sun, Jianing Liu, Jiayi Liu, Bei Pan, Jinhui Tian, Long Ge

“…ObjectiveThis study aims to evaluate the accuracy of LLMs in RoB2 assessments to explore their potential as research assistants for bias evaluation. …”
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KERF: a knowledge-enhanced relearning framework for tailings pond detection from high-resolution remote sensing images by Bingjie Liu, Wei Wu, Hao Wu, Ailong Ma, Shaohua Hu, Nianchun Du, Xuan Cui, Junyang Xie

“…An augmented feature pyramid network and multi-stage detectors are introduced to generate proposals with feature enhancement and location optimization. …”
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Machine learning framework for oxytetracycline removal using nanostructured cupric oxide supported on magnetic chitosan alginate biocomposite by Hassan Rasoulzadeh, Hossein Azarpira, Mojtaba Pourakbar, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

“…Prior to applying machine learning models, preprocessing steps were performed, including normalization using Min–Max Scaling to confine all features within the [0,1] range, outlier detection and removal of anomalous values, correlation analysis to avoid redundancy and multicollinearity, and data splitting into training and testing sets at an 80:20 ratio, along with K-fold cross-validation (k = 5) for robust model evaluation. The study assesses the accurate predictions of specific models, including Tikhonov Regularization, Yandex Boosting, and Particle Swarm Optimization (PSO), to improve removal efficiency and provide analysis of the components influencing the method. …”
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Self-Supervised Neural Networks for Precoding in MIMO Rate Splitting Multiple Access Systems by Dheeraj Raja Kumar, Carles Anton-Haro, Xavier Mestre

“…The intention is to explore several alternatives to conventional iterative precoding benchmarks like Weighted Minimum Mean Square Error (WMMSE) which are computationally intensive algorithms. We evaluate the different precoding policies learnt by the neural network architectures by closely studying the respective radiation patterns. …”
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Cytotoxicity and Exposure Assessment of PM2.5 in a Residential Home during COVID-19 Lockdown by Ummi Sabariah Mahamud, Armania Nurdin, Eliani Ezani

“…Due to the limited yield of indoor and outdoor PM2.5, further optimization on the extraction of PM2.5 should be carried out to evaluate further the mechanism of cytotoxicity of indoor PM2.5 on the lung cells.…”
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