Predicting indoor temperature of solar green house by machine learning algorithms: A comparative analysis and a practical approach by Wenhe Liu, Tao Han, Cong Wang, Feng Zhang, Zhanyang Xu

“…This performance significantly exceeded that of LSTM, Random Forest (RF), Support Vector Regression (SVR), and Multiple Linear Regression (MLR), with GRU reducing the root mean squared error (RMSE) by 12.3 %–27.5 % compared to LSTM in long-term predictions. …”
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A New Breast Cancer Discovery Strategy: A Combined Outlier Rejection Technique and an Ensemble Classification Method by Shereen H. Ali, Mohamed Shehata

“…It achieves 0.987 accuracy, 0.013 error, 0.98 recall, 0.984 precision, and a run time of 3 s, outperforming all other methods from the literature.…”
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Psychometric properties of screening tools for mild cognitive impairment in older adults based on COSMIN guidelines: a systematic review by Shasha Wen, Dongmei Cheng, Nana Zhao, Xinyu Chen, Xianying Lu, Yue Li, Huanle Liu, Jing Gao, Chaoming Hou, Ran Xu

“…No data were found on cross-cultural validity/measurement invariance, measurement error, or responsiveness. The final three instruments, AV-MoCA, HKBC, and Qmci-G, received class A recommendations and were recommended for use. …”
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Degradation of tartrazine dye using advanced oxidation process: Application of response surface methodology for optimization by Fetcia Jackulin, P. Senthil Kumar, Gayathri Rangasamy

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Influencing Factor on School-Age Children’s Holistic Health Care Who Using Online Media by Working-Age Parents in Northeast Thailand by Atchariya Wonginchan, Juraporn Tangpukdee, Suphasak Wonginchan, Sureeporn Kearttiwongkru, Sujitra Konggungong

“…Materials and Methods. This research was a descriptive study, with a sample of parent amount 222. …”
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Community alcohol sales and opioid poisoning deaths: Alcohol serving space as a harm reduction opportunity by Cory M. Morton, Kristen Gilmore Powell, Michael Routhier, N. Andrew Peterson

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Flexural strengthening of reinforced concrete beams using engineered cementitious composite panels using artificial pozzolan, glass mesh, and grooving method by Davood Mostofinejad, Alireza Saljoughian, Ebrahim Sadeghi, Hadi Bahmani

“…This research investigates, for the first time, the effects of high-silica synthetic pozzolan as a primary component in the mixing design of engineered cementitious composites (ECC). …”
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Evaluasi Curah Hujan Berbasis Data Global pada DAS Wae Mese, Labuan Bajo by Maria Kalista Hadia Sabu, Doddi Yudianto, Obaja Triputera Wijaya

“…Evaluation is carried out using an assessment matrix which includes Root Mean Square Error (RMSE), Nash-Sutcliffe Efficiency (NSE), correlation (r), and Relative Bias (RB). …”
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Development of Recurrent Neural Networks for Thermal/Electrical Analysis of Non-Residential Buildings Based on Energy Consumptions Data by Elisa Belloni, Flavia Forconi, Gabriele Maria Lozito, Martina Palermo, Michele Quercio, Francesco Riganti Fulginei

“…Extensive research has focused on optimizing energy consumption in residential buildings based on indoor thermal conditions. …”
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Investigation of the Mechanical Properties and Durability of Fiber-Reinforced Geopolymer Mortars Containing Metakaolin and Glass Powder by Mir Alimohammad Mirgozar Langaroudi, Mohammad Mohtasham Moein, Ashkan Saradar, Moses Karakouzian

“…The increasing global emphasis on sustainable construction practices has spurred significant international research into developing durable and eco-friendly concrete materials. …”
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COMPARISON BETWEEN BAYESIAN QUANTILE REGRESSION AND BAYESIAN LASSO QUANTILE REGRESSION FOR MODELING POVERTY LINE WITH PRESENCE OF HETEROSCEDASTICITY IN WEST SUMATRA by Lilis Harianti Hasibuan, Ferra Yanuar, Dodi Devianto, Maiyastri Maiyastri, Rudiyanto Rudiyanto

“…The two methods are compared with the aim of seeing which method produces the smallest error. Bayesian quantile regression is one method that can model data assuming heteroscedasticity violations. …”
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GANs for data augmentation with stacked CNN models and XAI for interpretable maize yield prediction by Ishaan Seshukumar Pothapragada, Sujatha R

“…The model outperformed baseline methods with an R2 of 0.9165 and mean squared error (MSE) of 0.6893, significantly outperforming conventional approaches for optimizing production in variable growing conditions.…”
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Tourism Potential Zone Mapping Using MCDM and Machine Learning Models in The State of Madhya Pradesh India by Shrinwantu Raha, Sayan Deb

“…We followed the ROC-AUC (Area Under Curve) and Root Mean Squared Error (RMSE) as evaluation measures. The findings reveal a landscape of promise, with each model with accuracy levels ranging from 81.4% to 90.6%. …”
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Genomic prediction for potato (Solanum tuberosum) quality traits improved through image analysis by Muyideen Yusuf, Michael D. Miller, Thomas R. Stefaniak, Darrin Haagenson, Jeffrey B. Endelman, Asunta L. Thompson, Laura M. Shannon

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An Analysis of WiFi Coverage Modeling for a Hotspot in the Parish of Checa Employing Deterministic and Empirical Propagation Models by Iván Sánchez, Fabricio Vallejo, Pablo Palacios Játiva, Ali Dehghan Firoozabadi

“…This study presents the analysis and comparison of Wi-Fi coverage modeling for a hotspot using deterministic and empirical propagation models developed by researchers from the Universidad de Las Américas in Quito, Ecuador. …”
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Evaluation of hydraulic fracturing using machine learning by Ali Akbari, Ali Karami, Yousef Kazemzadeh, Ali Ranjbar

“…Among the tested models, RF outperformed others by achieving the highest coefficient of determination (R2 = 0.9804), alongside the lowest Mean Absolute Deviation (MAD) and Root Mean Square Error (RMSE) for both training and testing phases. …”
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Assessing above ground biomass of Wunbaik Mangrove Forest in Myanmar using machine learning and remote sensing data by Win Sithu Maung, Satoshi Tsuyuki, Takuya Hiroshima, San San Htay

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Advanced 3D Artistic Image Generation with VAE-SDFCycleGAN by Dorcas Oladayo Esan, Pius Adewale Owolawi, Chunling Tu

“…The model produced a peak signal noise ratio (PSNR) of 31.35, mean square error (MSE) of 65.32, and structural similarity index measure (SSIM) of 0.772 which indicates the improved quality of the generated images. …”
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Robotic-assisted vs. traditional medial patellofemoral ligament reconstruction: a comparative study of surgical precision and clinical outcomes by Hongzhi Fang, Zhenghui Shang, Tianli Du

“…The primary endpoints included the error margin between the femoral tunnel entry point, a predefined reference landmark, and the quantity of intraoperative fluoroscopic exposures. …”
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Management of threats to the financial stability of enterprises in interactive mode by N. M. Levchenko, К. D. Pavlov

“…The article states that during the years of independence, the energy sector has gone through a thorny path of trial and error, since at the initial stages of its formation, Ukrainian energy enterprises did not have sufficient knowledge and practical skills in managing financial sustainability. …”
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