PERFORMANCE COMPARISON OF DECISION TREE AND LOGISTIC REGRESSION METHODS FOR CLASSIFICATION OF SNP GENETIC DATA by Adi Setiawan, Febi Setivani, Tundjung Mahatma

“…This research was conducted to compare the accuracy when decision tree and logistic regression methods are used on some data. …”
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Cooling Load Forecasting Method for Central Air Conditioning Systems in Manufacturing Plants Based on iTransformer-BiLSTM by Xiaofeng Huang, Xuan Zhou, Junwei Yan, Xiaofei Huang

“…Experimental validation on a cooling load dataset from a welding workshop in a manufacturing plant, including ablation studies and comparative analyses with other algorithms, demonstrates that the proposed method achieves superior performance compared to traditional approaches in forecasting accuracy. …”
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Development and calibration of roundabout safety performance functions using machine learning: a case study from Amman, Jordan by Diana Al-Nabulsi, Aya Hassouneh

“…A comprehensive dataset was assembled, incorporating annual average daily traffic (AADT) and a suite of geometric parameters including inscribed diameter, entry width, number of legs, circulating width, and splitter island radius. Comparative modeling was conducted using ordinary least squares regression and Random Forest Regressor algorithms. …”
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A Systematic Literature Review of Machine Learning-Based Personality Trait Detection Using Electroencephalographic Data by Celina Rieck, Pascal Penava, Ricardo Buettner

“…The integration of machine and deep learning algorithms has improved automated trait classification but the comparative reliability of these approaches remains unclear. …”
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A pregeneration–recognition method of detecting weak seafloor echoes for full-waveform airborne LiDAR bathymetry by Yadong Guo, Wenxue Xu, Yanxiong Liu, Fanlin Yang, Xue Ji, Yikai Feng, Qiuhua Tang

“…First, a two-stage local maximum algorithm is developed to identify potential seafloor echoes in waveforms and to pregenerate points. …”
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Estimation of Leaf Chlorophyll Content of Maize from Hyperspectral Data Using E2D-COS Feature Selection, Deep Neural Network, and Transfer Learning by Riqiang Chen, Lipeng Ren, Guijun Yang, Zhida Cheng, Dan Zhao, Chengjian Zhang, Haikuan Feng, Haitang Hu, Hao Yang

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Digital innovation in healthcare: quantifying the impact of digital sepsis screening tools on patient outcomes—a multi-site natural experiment by Sarah Tonkin-Crine, Graham Cooke, Anthony C Gordon, Anthony Gordon, Shashank Patil, Runa Lazzarino, Andrew Brent, Kate Honeyford, Céire E Costelloe, Anne Kinderlerer, John Welch, Peter Ghazal, Claire Burnett, Alf Timney, Andrew Jonathan Brent, Cerie Costelloe, Pippa Goodman Ben Glampson

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Enhancements on the Latitudinal and Seasonal Bias Corrections in the SMOS Debiased Non-Bayesian Sea Surface Salinity Retrieval by Aina Garcia-Espriu, Estrella Olmedo, Veronica Gonzalez-Gambau, Cristina Gonzalez-Haro, Antonio Turiel, Yoann Rey-Ricord, Eric Jeansou, Roberto Sabia, Raffaele Crapolicchio, Roger Oliva

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A Step-by-Step Harmonization Process for Nutritional Epidemiology Purposes: A Methodological Work of the Collaborative PROMED-COG Pooled Cohorts Study by Federica Prinelli, Silvia Conti, Claire T. McEvoy, Caterina Trevisan, Stefania Maggi, Giuseppe Sergi, Marianna Noale

“…In particular, the challenge was the harmonization procedure for dietary habits that required several steps: (i) access to documentation from the original studies, (ii) discussion with the researchers responsible for each dataset; (iii) exploration of each dataset before the final harmonization; (iv) agreement on portion size and food frequency standardization, and food classification for healthy dietary pattern computation; (v) name, definition, and categorization of the harmonized common variable and the original variables, for each study; (vi) development and application of the algorithm to obtain the harmonized variables from the original ones; and (vii) final pooled dataset preparation. …”
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Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data by W. Bang, J. T. Carlin, K. Kim, A. V. Ryzhkov, A. V. Ryzhkov, G. Liu, G. Lee

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Identification of Global Extended Pseudo Invariant Calibration Sites (EPICS) and Their Validation Using Radiometric Calibration Network (RadCalNet) by Juliana Fajardo Rueda, Larry Leigh, Cibele Teixeira Pinto

“…The K-means identified 160 distinct clusters, with Cluster 13 Global Temporally Stable (Cluster 13-GTS) showing significant improvements in temporal stability. Compared to Cluster 13 Global (Cluster 13-G) from earlier research, Cluster 13-GTS reduced the coefficient of variation by up to 1% and increased the number of calibration locations from 23 to over 50. …”
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Assessing the spatial relationship between mandibular third molars and the inferior alveolar canal using a deep learning-based approach: a proof-of-concept study by Wenjie Lyu, Shang Lou, Jieying Huang, Zelun Huang, Haoran Zheng, Huangan Liao, Yu Qiao, Kexiong OuYang

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Leveraging Harris Hawks Optimization for Enhanced Multi-Objective Optimal Power Flow in Complex Power Systems by Fahad Alsokhiry

“…Experimental results reveal that solutions derived from HHO exhibit superior convergence, enhanced diversity maintenance, and higher quality Pareto-optimal solutions compared to the MOEA/D trail algorithms. The research breaks new ground in the application of the Harris Hawks Optimization (HHO) algorithm to the Multi-Objective Optimal Power Flow (MaO-OPF) problem. …”
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Detection of Silent Type I Choroidal Neovascular Membrane in Chronic Central Serous Chorioretinopathy Using En Face Swept-Source Optical Coherence Tomography Angiography by Magdy Moussa, Mahmoud Leila, Hagar Khalid, Mohamed Lolah

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A Lyapunov Optimization-Based Approach to Autonomous Vehicle Local Path Planning by Ziba Arjmandzadeh, Mohammad Hossein Abbasi, Hanchen Wang, Jiangfeng Zhang, Bin Xu

“…Autonomous vehicles (AVs) offer significant potential to improve safety, reduce emissions, and increase comfort, drawing substantial attention from both research and industry. A critical challenge in achieving SAE Level 5 autonomy, full automation, is path planning. …”
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A novel energy pattern factor-based optimized approach for assessing Weibull parameters for wind power applications by Ghulam Abbas, Arshad Ali, Mohamed Tahar Ben Othman, Muhammad Wasim Nawaz, Ateeq Ur Rehman, Habib Hamam

“…., Weibull distribution (WD), that fits well with the wind speed data must be known. In this research, we proposed a novel optimized energy pattern factor method (NOEPFM) based on the trust-region-dogleg algorithm and applied it to wind speed data of four cities of the Southern region of Punjab, Pakistan, to determine WD parameters, i.e., shape k and scale c parameters. …”
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Model of a Novel PCB Coil for High-Sensitivity Metal Detector by Han Zhang, Mingxing Song, Yuejiu Zhu, Xianze Xu, Fengqiu Xu

“…An optimization problem is constructed from the numerical model, and the optimal design parameters of the receiving coil are determined via a heuristic algorithm. Experimental results indicate that the newly designed prototype exhibits superior sensitivity compared to commercial differential detectors of comparable size. …”
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An Improvement of the Load Transfer Method for Energy Piles Under Thermo-Mechanical Loads by Haofan Yang, Haowen Pan, Chenfeng Zong, Ziyi Wang, Gang Jiang

“…This study investigates the underlying causes of this discrepancy and proposes an iterative method to eliminate unbalanced forces at the pile head, based on the displacement coordination algorithm for energy pile load transfer. The calculated results at the pile head show an 18% reduction in error compared to previous studies. …”
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MEASUREMENT OF THE AMPLITUDE OF PERIODIC SIGNALS USING THE FIBONACCI METHOD by V. S. Petrushak

“…The aim of the study was to create a new amplitude meter for high-frequency periodic signals based on the Fibonacci method without converting the AC voltage into an equivalent parameter.Based on the developed algorithm and the equation for converting the amplitude of periodic signals into code using the Fibonacci method, a functional scheme of the amplitude converter has been developed. …”
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Automatic Diagnosis of Microgrid Networks’ Power Device Faults Based on Stacked Denoising Autoencoders and Adaptive Affinity Propagation Clustering by Fan Xu, Xin Shu, Xiaodi Zhang, Bo Fan

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