Mining hypertension predictors using decision tree: Baseline data of Kharameh cohort study by abbas Rezaianzadeh, Samane Nematolahi, maryam jalali, Shayan Rezaeianzadeh, Masoumeh Ghoddusi Johari, Seyed Vahid Hosseini

“…The study included 2510 hypertensive and 7840 non-hypertensive individuals. 70% of the cases were randomly allocated to the training dataset for establishing the decision tree, while the remaining 30% were used as the testing dataset for performance evaluation of the decision-tree. Two models were assessed. …”
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Neural network quantification for solar radiation prediction: An approach for low power devices by Brenda Alejandra Villamizar-Medina, Angelo Joseph Soto Vergel, Byron Medina-Delgado, Darwin Orlando Cardozo-Sarmiento, Dinael Guevara-Ibarra, Oriana Alexandra Lopez-Bustamante

“…Experimental design allows detailed performance evaluation of quantized neural networks, demonstrating that the TensorFlow Lite Quantized Aware model is suitable for solar radiation prediction. …”
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Optimal sizing and performance assessment of stand-alone PV systems using optimum hybrid sizing strategy by Mohamad Abed, Amarendra Reddy B, T.R. Jyothsna, Nabil Mohammed

“…In the performance assessment stage, the designed SAPVS undergoes a rigorous performance evaluation to ensure compliance with technical requirements before the practical implementation on the site. …”
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Evaluating GRU Algorithm and Double Moving Average for Predicting USDT Prices: A Case Study 2017-2024 by RAHMAT, Munirul ula, Zara Yunizar

“…DMA, in contrast, is a statistical method that filters market noise to identify long-term trends, making it more reliable for stable market conditions. Performance evaluation shows DMA achieving lower errors (MAE: 5.494, MAPE: 0.0339%) than GRU (MAE: 5.984, MAPE: 0.0369%), suggesting higher accuracy for trend-based predictions. …”
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Employee Motivation and Job Performance in the Public Service of Uganda: The Case of the Office of the Director of Public Prosecutions by Batson, Baguma

“…The adjustment on workload is required in order to improve the work-life balance factor; that a clear procedure of performance evaluation process be instituted and reward/recognition factor should be considered good; ODPP needs to maintain and improve it in order to increase the motivation level of the employees in order to enhance their performance. …”
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Automated Audit and Self-Correction Algorithm for Seg-Hallucination Using MeshCNN-Based On-Demand Generative AI by Sihwan Kim, Changmin Park, Gwanghyeon Jeon, Seohee Kim, Jong Hyo Kim

“…Two publicly available datasets were used in developing the ASHSC algorithm: 280 CT scans from the TotalSegmentator dataset for training and 274 CT scans from the Cancer Imaging Archive (TCIA) dataset for performance evaluation. The ASHSC algorithm utilizes a two-stage on-demand strategy with mesh-based convolutional neural networks and generative artificial intelligence. …”
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Study on the Performance of Filters Under Biogas Slurry Drip Irrigation Systems by Shuaijie Wang, Haitao Wang, Xuefeng Qiu, Jiandong Wang, Shuji Wang, Hang Wang, Tao Shen

“…This study provides a comprehensive performance evaluation of two common filter types and their combinations, considering various flow rates and biogas slurry-to-water ratios under drip irrigation conditions. …”
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Predictive model for abdominal liposuction volume in patients with obesity using machine learning in a longitudinal multi-center study in Korea by Hyunji Sang, Jaeyu Park, Soeun Kim, Myeongcheol Lee, Hojae Lee, Sun-Ho Lee, Dong Keon Yon, Sang Youl Rhee

“…Fifteen variables related to patient profiles were integrated and applied to various ML algorithms, including random forest, support vector, XGBoost, decision tree, and AdaBoost regressors. Performance evaluation employed mean absolute error (MAE), root mean square error (RMSE), and R-squared (R2) score. …”
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Comparison of principal component analysis algorithms for imputation in agrometeorological data in high dimension and reduced sample size. by Valter Cesar de Souza, Sergio Augusto Rodrigues, Luís Roberto Almeida Gabriel Filho

“…This cycle was repeated 100 times, and average performance indicators were calculated. Statistical performance evaluation utilized the following indicators: correlation coefficient (r), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), Normalized Root Mean Square Error (nRMSE), Willmott Index (d), and performance index (c). …”
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A Systematic Review of Urban Vegetation Research during 2000–2023: A Bibliometric Analysis by Hassan Boukita, Fathalah Elwahab, Mohamed El Ammari, Abdelazziz Chemchaoui, Boutaina Benchahid, Youssef Haouazine, Najiba Brhadda, Rabea Ziri

“…After being exported in CSV format, these data were analyzed using VOSviewer for data visualization, Scopus Analytics for performance evaluation, MS Excel for organizing data in graphical form, and CiteSpace for examining the emergence of keywords. …”
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Optimal selection of machine learning algorithms for ciprofloxacin prediction based on conventional water quality indicators by Shenqiong Jiang, Xiangju Cheng, Baoshan Shi, Dantong Zhu, Jun Xie, Zhihong Zhou

“…The performance evaluations were R2= 0.936, NSE= 0.915, RMSE= 3.150 ng/L, and MAPE= 30.909 %. …”
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Rockburst prediction based on multi-featured drilling parameters and extreme tree algorithm for full-section excavated tunnel faces by Wenhao Yi, Mingnian Wang, Qinyong Xia, Yongyi He, Hongqiang Sun

“…The effects of Bayesian optimization and the number of drilling parameter features on the model performance were analyzed using the accuracy, precision, recall and F1 value of the prediction set as the model performance evaluation indices. The results show that the Bayesian optimized model with 42 drilling parameter features as inputs performs best, with an accuracy of 91.89%. …”
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Penerapan Metode Extreme Programming pada Rancang Bangun Sistem Analisis Sentimen Portal Berita by I Gede Bagus Premana Putra, Made Sudarma, Ida Bagus Gede Manuaba

“…The existence of a sentiment analysis system can be used as an alternative solution for individuals and organizations to carry out sentiment analysis, so that it can assist in the decision-making a process and performance evaluation. …”
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Enhanced Forecasting and Assessment of Urban Air Quality by an Automated Machine Learning System: The AI‐Air by Jiayu Yang, Huabing Ke, Sunling Gong, Yaqiang Wang, Lei Zhang, Chunhong Zhou, Jingyue Mo, Yan You

“…Abstract An automated air quality forecasting system (AI‐Air) was developed to optimize and improve air quality forecasting for different typical cities, combined with the China Meteorological Administration Unified Atmospheric Chemistry Environmental Model (CUACE), and used in a typical inland city of Zhengzhou and a coastal city of Haikou in China. The performance evaluation results show that for the PM2.5 forecasts, the correlation coefficient (R) is increased by 0.07–0.13, and the mean error (ME) and root mean square error (RMSE) is decreased by 3.2–3.5 and 3.8–4.7 μg/m³. …”
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Evaluating the Impact of Data Transformation Techniques on the Performance and Interpretability of Software Defect Prediction Models by Yu Zhao, Zhiqiu Huang, Lina Gong, Yi Zhu, Qiao Yu, Yuxiang Gao

“…Through empirical research on (i) six classification techniques (random forest, decision tree, logistic regression, Naive Bayes, K-nearest neighbors, and multilayer perceptron), (ii) six performance evaluation indicators (Accuracy, Precision, Recall, F1, MCC, and AUC), (iii) two interpretable methods (permutation and SHAP), (iv) two feature importance measures (Top-k feature rank overlap and difference), and (v) three datasets (Promise, Relink, and AEEEM), our results show that the data transformation methods can significantly improve the performance of the SDP models and greatly affect the variation of the most important features. …”
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To intubate or to resuscitate: the effect of simulation-based training on advanced airway management during simulated paediatric resuscitations by C. Donath, A. Leonhardt, T. Stibane, S. Weber, N. Mand

“…Airway management was assessed using a performance evaluation checklist. Time to initiate ventilation, frequency, and timing of endotracheal intubation (ETI), and its influence on other life support interventions were assessed. …”
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NIR Triggered Bionic Bilayer Membrane-Encapsulated Nanoparticles for Synergistic Photodynamic, Photothermal and Chemotherapy of Cervical Cancer by Ding J, Zhang X, Guo L, Xiong J, Zhang C, Du Z, Zhu L, Alifu N, Dong B

“…For in vivo analysis, the antitumor properties of the nanoparticles were explored in a mouse subcutaneous tumor model.Results: RBC@ICG-DOX NPs were successfully prepared with strong safety and good blood compatibility, which can effectively reduce drug leakage and prolong drug circulation time in the body. In vitro performance evaluation showed that RBC@ICG-DOX NPs obtained excellent photothermal conversion ability and well reactive oxygen generation performance under near-infrared laser irradiation. …”
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Implementasi Latent Dirichlet Allocation (LDA) untuk Klasterisasi Cerita Berbahasa Bali by Ngurah Agus Sanjaya ER

“…The research stages include story digitization, tokenization, case-folding, stemming, topic search with LDA, document representation and agglomerative hierarchical clustering. Performance evaluation was carried out using 100 Balinese folklores data obtained from online sites and the Bali Provincial Cultural Office to calculate the accuracy of the clustering results. …”
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Multivariate description of gait changes in a mouse model of peripheral nerve injury and trauma. by Bilal A Naved, Shuling Han, Kyle M Koss, Mary J Kando, Jiao-Jing Wang, Craig Weiss, Maya G Passman, Jason A Wertheim, Yuan Luo, Zheng J Zhang

“…<h4>Conclusion</h4>This is the first performance evaluation of a multivariate approach to gait analysis and the first demonstration of superior performance as compared to univariate gait analysis in animals. …”
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Data-driven machine learning approaches for simultaneous prediction of peak particle velocity and frequency induced by rock blasting in mining by Yewuhalashet Fissha, Prashanth Ragam, Hajime Ikeda, N. Kushal Kumar, Tsuyoshi Adachi, P.S. Paul, Youhei Kawamura

“…This work compares five machine learning models (XGBoost, Catboost, Bagging, Gradient Boosting, and Random Forest Regression) to choose the most efficient performance model. The performance evaluation of each five machine learning models demonstrates each model achieved a performance of more than 0.90 during the testing phase, there was a strong correlation observed between the actual and the predicted ones. …”
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