Explainable AI for enhanced accuracy in malaria diagnosis using ensemble machine learning models by Olushina Olawale Awe, Peter Njoroge Mwangi, Samuel Kotva Goudoungou, Ruth Victoria Esho, Olanrewaju Samuel Oyejide

“…Ensemble methods, namely Random Forest, AdaBoost, Gradient Boost, XGBoost, and CatBoost, were employed after addressing class imbalance through oversampling techniques. …”
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Circadian and social cues regulate ion channel trafficking. by Michael R Markham, M Lynne McAnelly, Philip K Stoddard, Harold H Zakon

“…Here we show that the gymnotiform electric fish Sternopygus macrurus rapidly boosts signal amplitude by 40% at night and during social encounters. …”
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Evaluation of mesoporous silica synthesized for green adsorption by modeling via machine learning and mass transfer by Minge Yang, Qiqing Yue, Junyi He

“…Our objective was to develop predictive models for C using three distinct base models: decision tree (DT), support vector regression (SVR), and Gaussian process regression (GPR). To enhance the predictive performance of these base models, we employed the ensemble method AdaBoost, which combines their outputs to yield more accurate predictions. …”
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Enhancing Student Mathematical Proficiency through Planimetry and Digital Technologies by Liudmyla Hetmanenko

“…The further development direction of the examined field of study is the fine-tuning of the approaches to using technology-enhanced learning activities to boost the efficiency of the teaching-learning process. …”
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An Empirical Evaluation of Ensemble Models for Python Code Smell Detection by Rajwant Singh Rao, Seema Dewangan, Alok Mishra

“…Five ensemble learning methods—Bagging, Gradient Boost, Max Voting, AdaBoost, and XGBoost—were employed to detect code smells within these datasets. …”
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Code-Switching as a Pedagogical Tool in English as a Foreign Language (Efl) Classrooms by Hammad Mushtaq, Rida Rabbani

“…The analysis of responses revealed that a limited, deliberate and controlled use of code-switching in EFL classrooms benefits both teachers and learners as it considerably supports the pedagogical process and boosts EFL students’ success …”
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Ensemble ecological niche modeling of West Nile virus probability in Florida. by Sean P Beeman, Andrea M Morrison, Thomas R Unnasch, Robert S Unnasch

“…Ecological Niche Modeling is a process by which spatiotemporal, climatic, and environmental data are analyzed to predict the distribution of an organism. …”
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Prediction of BTEX concentrations in the air of Southern East Azerbaijan province, Iran using ensemble machine learning and feature analysis by Mansour Baziar, Negar Jafari, Ali Oghazyan, Amir Mohammadi, Ali Abdolahnejad, Ali Behnami

“…In this study, we introduce the MLs (XGBRegressor, AdaBoostRegressor, ExtraTreesRegressor, and CatBoost)-Stacked-Extra Trees ensemble, an innovative machine learning approach to predict BTEX concentrations. …”
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Data driven tensile strength prediction for fiber-reinforced rubberized recycled aggregate concrete using machine learning by Avijit Pal, Khondaker Sakil Ahmed, Nur Yazdani

“…In this study, nine machine learning models—Random Forest, K-Nearest Neighbors, Support Vector Regression, Decision Tree, Artificial Neural Network, AdaBoost, Gradient Boost, CatBoost, and Extreme Gradient Boost—were trained and tested using a dataset of 346 samples representing various mix proportions. …”
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Energías renovables y agricultura campesina en México by Diana Xóchitl González-Gómez, Jozelin María Soto-Alarcón

“…The world energy transition has broadened renewable energy megaprojects. In Mexico, their boost has generated socio-environmental conflicts. …”
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Repeated harvest enables efficient production of VSV-GP by Rebecca Habisch, Peter Neubauer, Jorge Soza-Ried, Eva Puschmann

“…This shows that repeated harvests or perfusion have the potential to boost viral yields and should be considered when deciding on a process format for production.…”
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Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data by Abu Bakker Siddique, Tanveer Alam Munshi, Nazmul Islam Rakin, Mahamudul Hashan, Sushmita Sarker Chnapa, Labiba Nusrat Jahan

“…PCA significantly speeds up the entire process by lowering the number of dimensions, hence enhancing the cost-effectiveness of the procedure. …”
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A multidimensional machine learning framework for LST reconstruction and climate variable analysis in forest fire occurrence by Hatef Dastour, Quazi K. Hassan

“…On the test set, for LST-Day data, CatBoost and XGBoost achieved Median Absolute Errors (MedAE) of approximately 1.434 °C and 1.425 °C, respectively. …”
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Editorial by Maria de Nazaré de Oliveira Fraga

“…The results of some important advances in the health field boosted the survival of the population, as preventive measures and vaccines, for example. …”
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AN EVALUATION OF PHOTOVOLTAIC SYSTEMS MPPT TECHNIQUES UNDER THE CHARACTERISTICS OF OPERATIONAL CONDITIONS by I. A. Elzein, Yu. N. Petrenko

“…Precisely, PV systems are constituted from arrays of photovoltaic cells, choppers (mainly buck-boost or boost DC/DC converter), MPPT control systems and storage devices and/or grid connections. …”
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Predictive modeling of hydrogen production and methane conversion from biomass-derived methane using machine learning and optimisation techniques by Adegboyega Bolu Ehinmowo, Bright Ikechukwu Nwaneri, Joseph Oluwatobi Olaide

“…However, there is the need to optimise this process for better efficiency and improved hydrogen production from biomass sources. …”
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Progress and Potential Drawbacks of Modern Agricultural Technologies: A Literature Review by Prodipto Bishnu Angon, Pujan Aich

“…The production of agriculture has undergone new modifications as a result of agricultural technologies. These not only boost agricultural output but may also significantly raise the caliber of produced food, cut labor expenses, boost farmers' incomes, and achieve agricultural modernization. …”
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Evaluating machine learning-based intrusion detection systems with explainable AI: enhancing transparency and interpretability by Vincent Zibi Mohale, Ibidun Christiana Obagbuwa

“…By incorporating XAI techniques such as LIME, SHAP, and ELI5, we demonstrated that XAI-enhanced models provide actionable insights into feature importance and decision processes. The experimental results revealed that XGBoost and CatBoost achieved the highest accuracy of 87%, with a false positive rate of 0.07 and a false negative rate of 0.12. …”
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Enhancing Photovoltaic System Efficiency Through Fuzzy Logic-Based Maximum Power Point Tracking by N. A. Yusri, S. N. H. M. Tarmizi, M. I. Zakaria, S. F. M. Hussein, A. R. A. A. Emhemed

“…The FLC continuously processes these inputs to adjust the duty cycle of the DC-DC boost converter, ensuring that the PV system operates at its highest energy generation potential. …”
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Design of a Controller for Supercapacitor’s Bidirectional High-Gain Interleaved Converter by Jessica C. A. Sousa, Thiago M. Soares, Jonathan M. Tabora, Hugo G. Lott

“…Simulations were conducted using PSIM software, version 2023.1, with a power flow of 1 kW, a 48 V DC bus (buck mode), and a 162 V supercapacitor module (boost mode), operating at 500 kHz. The performance of the controllers was evaluated during both the charging and discharging processes of the supercapacitor, analyzing the dynamic response and behavior in the continuous mode, even in the presence of system disturbances.…”
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