Spatiotemporal analysis of thermal islands in a semi-arid city: A case study of Kermanshah, Iran using machine learning and remote sensing by Peyman Karami, Seyed-Mohsen Mousavi

“…Topographic, topoclimate, and biophysical variables, along with machine learning methods and the chi-square test, were employed to model and evaluate LST variation across different LULCs.The results demonstrate a significant increase in HIs, particularly in the city's periphery, driven by rapid urbanization, impervious surface expansion, and reduced green cover. …”
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Optimal allocation of renewable energy resources in a smart grid under neutrosophic credibility-based uncertainty by Muhammad Zafar Abbas, Rukhshanda Anjum, Muhammad Umar Mirza, Abdulrahman A. Almehizia, Amir Hussain

“…Modern research in renewable energy systems faces many challenges in dealing with uncertain data and inconsistent expert evaluations, particularly in the context of smart grid systems. …”
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Artificial Intelligence in Healthcare: Innovation and Impact in Medical Practice by Amelia-Maria ISAC, Corina VERNIC

“…One limitation of this study is the variability in dataset sizes and the potential lack of standardization in feature selection across different AI models. …”
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G4 & the balanced metric family – a novel approach to solving binary classification problems in medical device validation & verification studies by Andrew Marra

“…Results Simulated datasets encompassing different prevalence rates of the minority class were analyzed under a multi-reader-multi-case study design. …”
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An Assessment of the Seasonal Uncertainty of Microwave L-Band Satellite Soil Moisture Products in Jiangsu Province, China by Chuanxiang Yi, Xiaojun Li, Zanpin Xing, Xiaozhou Xin, Yifang Ren, Hongwei Zhou, Wenjun Zhou, Pei Zhang, Tong Wu, Jean-Pierre Wigneron

“…The results indicate that all four SM products exhibit significant seasonal differences when evaluated against in situ observations between 2016 and 2022, with most products achieving their highest correlation (R) and unbiased root-mean-square difference (<i>ub</i>RMSD) scores during the autumn. …”
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Automated chest CT three-dimensional quantification of body composition: adipose tissue and paravertebral muscle by Akinori Hata, Yohei Muraguchi, Minoru Nakatsugawa, Xinan Wang, Jiyeon Song, Noriaki Wada, Takuya Hino, Kota Aoyagi, Masami Kawagishi, Takuo Negishi, Vladimir I. Valtchinov, Mizuki Nishino, Akihiro Koga, Naoki Sugihara, Masahiro Ozaki, Gary M. Hunninghake, Noriyuki Tomiyama, Mark L. Schiebler, Yi Li, David C. Christiani, Hiroto Hatabu

“…Muscle area, mean attenuation value, and intermuscular adipose tissue percentage (IMAT%) were calculated in the paravertebral muscle segmentation. The AI algorithm was trained on the training sets, and its performance was evaluated on the test sets. …”
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Sensitivity of Spiking Neural Networks Due to Input Perturbation by Haoran Zhu, Xiaoqin Zeng, Yang Zou, Jinfeng Zhou

“…Then, the sensitivity algorithm of an entire SNN is derived iteratively from the sensitivity of each individual neuron. …”
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Selection and validation of reference genes for gene expression studies in Pseudomonas brassicacearum GS20 using real-time quantitative reverse transcription PCR. by Bianxia Bai, Jiahong Ren, Fenling Bai, Lin Hao

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Machine learning-assisted early detection of keratoconus: a comparative analysis of corneal topography and biomechanical data by Arkadiusz Syta, Arkadiusz Podkowiński, Tomasz Chorągiewicz, Robert Karpiński, Jakub Gęca, Dominika Wróbel-Dudzińska, Katarzyna E Jonak, Dariusz Głuchowski, Marcin Maciejewski, Robert Rejdak, Kamil Jonak

“…Various machine learning algorithms were trained and evaluated on datasets containing different parameters obtained using the Pentacam device. …”
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Quantum AI: A Cognitive Machine Learning Technique based on Nurturing Food Security Sustainability Predictive Analysis for Life Science - Bioengineering in Healthcare by Senthil G.A., Monica K.M., Prabha R., Prinslin L., Elavarasi R.

“…Individualized and accurate evaluation of nutrient intake is essential for good health. …”
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Hybrid Attention-Enhanced Xception and Dynamic Chaotic Whale Optimization for Brain Tumor Diagnosis by Aliyu Tetengi Ibrahim, Ibrahim Hayatu Hassan, Mohammed Abdullahi, Armand Florentin Donfack Kana, Amina Hassan Abubakar, Mohammed Tukur Mohammed, Lubna A. Gabralla, Mohamad Khoiru Rusydi, Haruna Chiroma

“…Our proposed method was evaluated on benchmark datasets achieving remarkable accuracies of 99.67%, 99.09%, and 99.67% compared to the classical algorithms.…”
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A Metaheuristic Framework for Cost-Effective Renewable Energy Planning: Integrating Green Bonds and Fiscal Incentives by Juan D. Saldarriaga-Loaiza, Johnatan M. Rodríguez-Serna, Jesús M. López-Lezama, Nicolás Muñoz-Galeano, Sergio D. Saldarriaga-Zuluaga

“…We apply a flexible investment model that helps to find the most cost-effective financing strategies for different renewable technologies. To do this, we use three optimization techniques to identify solutions that lower electricity generation costs: Teaching Learning, Harmony Search, and the Shuffled Frog Leaping Algorithm. …”
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Embedded implementation of phase imbalance faults in three-phase inverters: The impact of MOSFET conduction resistance variations by Oussama Idbouhouch, Mourad Zegrari, Nabila Rabbah, Ibtihal Ait Abdelmoula, Hicham Oufettoul, Saad Motahhir

“…Results from SIL and PIL are consistent with those obtained from MIL simulation, therefore validating the robustness of the control algorithm through different testing stages. The comparative analysis emphasizes the distinct impacts of localized and distributed faults on inverter stability and performance. …”
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Modelling distillate output of a solar distiller with eco-friendly wood-based steam generation basin using machine learning model and starling murmuration optimizer by Mohammed Azmi Al-Betar, Otto L. Muskens, Karrar A. Hammoodi, Mohamed Abd Elaziz, Qusai Yousef Shambour, Salam Fraihat, Ammar H. Elsheikh

“…The predicted data of all models was evaluated using different error measures. These models were standalone LSTM and LSTM optimized by an artificial hummingbird algorithm (AHA) or manta ray foraging optimizer (MRFO). …”
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Comparison Between Broadband and Personal Exposimeter Measurements for EMF Exposure Map Development Using Evolutionary Programming by Alberto Nájera, Rocío Sánchez-Montero, Jesús González-Rubio, Jorge Guillén-Pina, Ricardo Chocano-del-Cerro, Pablo-Luis López-Espí

“…The aim of this research was to determine the necessary adjustments to the measurements made with personal exposimeters to obtain RF-EMF exposure maps equivalent to those made with broadband meters. We evaluated different possibilities to obtain the best equivalence of measurements between both devices. …”
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Identification of PET/CT radiomic signature for classification of locally recurrent rectal cancer: A network-based feature selection approach by Sara Dalmonte, Maria Adriana Cocozza, Dajana Cuicchi, Daniel Remondini, Lorenzo Faggioni, Paolo Castellucci, Andrea Farolfi, Emilia Fortunati, Alberta Cappelli, Riccardo Biondi, Arrigo Cattabriga, Gilberto Poggioli, Stefano Fanti, Gastone Castellani, Francesca Coppola, Nico Curti

“…The whole analysis was conducted separately for CT and PET images to evaluate their different predictive power. Radiomic features were extracted from suspected lesion volumes identified by physicians and the most relevant radiomic features were selected to predict the presence or absence of LRRC. …”
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Enhancing the performance of grid-connected DFIG systems using prescribed convergence law by Hichem Itouchene, Fayssal Amrane, Zoubir Boudries, Saad Mekhilef, Habib Benbouhenni, Nicu Bizon

“…The effectiveness of the proposed control approach is evaluated through simulations conducted in the MATLAB/Simulink environment and validated via hardware-in-the-loop (HIL) testing under different operating conditions, where the performance and effectiveness are compared with that of the conventional proportional-integral (PI) controller, 1-SMC, and IBCS approaches. …”
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A Study of NEWS Vital Signs in the Emergency Department for Predicting Short- and Medium-Term Mortality Using Decision Tree Analysis by Serena Sibilio, Gianni Turcato, Bastiaan Van Grootven, Marta Ziller, Francesco Brigo, Arian Zaboli

“…Decision tree analysis (CHAID algorithm) was used to identify predictors of mortality; 10-fold cross-validation was applied to avoid overfitting. …”
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Deep learning-based technique for investigating the behavior of MEMS systems with multiwalled carbon nanotubes and electrically actuated microbeams by Muhammad Amir, Jamshaid Ul Rahman, Ali Hasan Ali, Ali Raza, Zaid Ameen Abduljabbar, Husam A. Neamah

“…The primary aim of this study is to investigate the nonlinear vibration properties of MEMS oscillators, specifically those related to nanotubes and electrically actuated microbeams, using DNN algorithms. Different optimizers are used to analyze the performance and capability of these non-linear dynamical models. …”
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A CT-based machine learning model for using clinical-radiomics to predict malignant cerebral edema after stroke: a two-center study by Lingfeng Zhang, Gang Xie, Yue Zhang, Yue Zhang, Junlin Li, Junlin Li, Wuli Tang, Wuli Tang, Ling Yang, Ling Yang, Kang Li

“…Ultimately, the efficacy of these models was evaluated by measuring the operating characteristics of the subjects through their area under the curve (AUCs).ResultsLogistic regression (LR) was found to be the most effective machine learning algorithm, for forecasting the MCE. …”
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