Evaluating machine and deep learning techniques in predicting blood sugar levels within the E-health domain by Beniamino Di Martino, Antonio Esposito, Gennaro Junior Pezzullo, Tien-Hsiung Weng

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Prediction of the thermophysical properties of Ag-reduced graphene oxide-water/ethylene-glycol hybrid nanofluids using different machine learning methods by Huaguang Li, Ali B.M. Ali, Rasha Abed Hussein, Narinderjit Singh Sawaran Singh, Barno Abdullaeva, Zubair Ahmad, Soheil Salahshour, Mohammadreza Baghoolizadeh, Mostafa Pirmoradian

“…In addition, optimization is done by the Non-dominated Sorting Genetic Algorithm-II (NSGA-Ⅱ) algorithm and the impact results of different mutation and combination rates are examined. …”
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Self-organizing maps to evaluate optimal strategies for balancing binary class distributions: a methodological approach by Alberto Nogales, Diego Guadalupe, Álvaro J. García-Tejedor

“…Abstract Since machine learning algorithms rely on data, the way datasets are collected significantly impacts their performance. …”
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A Preliminary Investigation into the Design of Driver Evaluator Using a Physics-Assisted Machine Learning Technique by Mingke Hou, Francis Assadian

“…This paper applies this concept and focuses on the design of a driver evaluator using physics-assisted unsupervised learning, which serves as a virtual reference generator that provides different driving modes for vehicles equipped with active actuators. …”
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Performance Evaluation of Uplink Cell-Free Massive MIMO Network Under Weichselberger Rician Fading Channel by Birhanu Dessie, Javed Shaikh, Georgi Iliev, Maria Nenova, Umar Syed, K. Kiran Kumar

“…However, estimating the channel with high-performance, low-cost computational methods is still a problem. Different algorithms have been developed to address these challenges in channel estimation. …”
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Machine Learning–Based Calibration and Performance Evaluation of Low-Cost Internet of Things Air Quality Sensors by Mehmet Taştan

“…To improve sensor accuracy, eight different machine learning (ML) algorithms were applied: Decision Tree (DT), Linear Regression (LR), Random Forest (RF), k-Nearest Neighbors (kNN), AdaBoost (AB), Gradient Boosting (GB), Support Vector Machines (SVM), and Stochastic Gradient Descent (SGD). …”
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%diag_test: a generic SAS macro for evaluating diagnostic accuracy measures for multiple diagnostic tests by Jacques K. Muthusi, Peter W. Young, Frankline O. Mboya, Samuel M. Mwalili

“…We also used the macro to reproduce results of published work on evaluating performance of multiple classification machine learning algorithms for predicting coronary artery disease. …”
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Accuracy Evaluation of Multi-Source Precipitation Data in Mountain Flood Simulation in Guoning Village， Xiahe County by Wubin HUANG, Jing FU, Runxia GUO, Junxia ZHANG, Yu LEI

“…From 22:00 on September 6， 2023 to 04:00 （Beijing Time） on September 7， Xiahe County in Gansu Province experienced severe convective weather， with short-term heavy rainfall in some areas， causing flash floods in Guoning Village， Xiahe County， resulting in casualties.In this study， the characteristics of Radar Quantitative Precipitation Estimation （Radar-QPE）， FengYun 4B Quantitative Precipitation Estimation （FY4B-QPE）， and CMA Multi-source Precipitation Analysis （CMPA） precipitation products were contrastive analyzed based on meteorological station observations.These precipitation data were used to drive the hydrodynamic hydrological model and evaluate the effect of different precipitation data in the flash flood simulation.The results showed that： （1） Among the 12-hour cumulative precipitation amounts， CMPA demonstrated higher accuracy in terms of the position of large value areas and differences in local precipitation levels； Radar-QPE was closer to AWS （Automatic Weather Station） in terms of cumulative precipitation level but showed significant differences in spatial distribution； FY4B-QPE overestimated the cumulative precipitation level by 33.8%.（2） In terms of hourly distribution， CMPA was most similar to AWS in terms of temporal evolution， spatial distribution， and precipitation level； Radar-QPE's peak values were smaller， and the peak times were lagged， with negative deviations in precipitation being dominant； FY4B-QPE's peak values and peak times were consistent with reality， but there were deviations in the start and end times of precipitation， with positive deviations in precipitation being dominant.（3） In the hydrological simulation study， CMPA， Radar-QPE， and FY4B-QPE all overestimated water levels， but the timing of water level peaks was more consistent with AWS.CMPA performed best in terms of RMSE （Root Mean Square Error）， NSE （Nash Efficiency Coefficient）， and Bias （Relative Deviation）， followed by Radar-QPE， and FY4B-QPE performed relatively poorly.Although existing site-observed precipitation cannot fully meet the needs of research and early warning for small and medium scale mountain floods， the high precision of CMPA data could effectively supplement the deficiencies of traditional meteorological observation stations to some extent.Meanwhile， the algorithms and accuracy of Radar-QPE and FY4B-QPE needed to be further improved and enhanced.…”
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RETRACTED ARTICLE: Machine learning intelligent based hydromagnetic thermal transport under Soret and Dufour effects in convergent/divergent channels: a hybrid evolutionary numeric... by Muhammad Naeem Aslam, Nadeem Shaukat, Arshad Riaz, Ilyas Khan, Shafiullah Niazai

“…To optimize the weights and biases of artificial neural networks (ANNs), employ a hybridization of advanced evolutionary optimization algorithms, specifically the artificial bee colony (ABC) optimization integrated with neural network algorithms (NNA). …”
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A Systematic Review and Meta-Analysis of Implicit Stigma Toward People with Mental Illness Among Different Groups: Measurement, Extent, and Correlates by Ren Y, Wang S, Fu X, Shi X

“…Twenty-eight studies calculated the implicit effect using an improved algorithm, while thirty-eight examined the correlations between implicit and explicit measures. …”
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Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

“…The scientific study of algorithms and statistical models are used by computer systems that use patterns and inference to perform tasks rather than using clear instructions. …”
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Unequal relational travel patterns of long-distance rail trips between different levels of settlement hierarchies – Case study from Hungary by Vilmos Oszter, István Kövesdi, László Sipos

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Development and evaluation of a mobile-optimized daily self-rating depression screening app: A preliminary study. by Kyungmi Chung, Min-Jeong Jeon, Jaesub Park, San Lee, Chang Oh Kim, Jin Young Park

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Differences in Characteristics of Peripartum Patients Who Did and Did Not Require an Upgrade to the Intensive Care Unit: A Propensity Score Matching Study by Jennifer A. Walker, Jerry M. Yang, Saad Pirzada, Manahel Zahid, Samantha Asuncion, Amanda Tuchler, Gillian Cooper, Allison Lankford, Emad Elsamadicy, Quincy K. Tran

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Evaluating visitor perception and spatial preferences of various museums based on machine learning from 2016 to 2024. by Yuandi Jiang, Kalyna Pashkevych, Shibo Bi

“…Kernel density and standard deviational ellipse methods revealed the spatio-temporal evolution of museum space preferences (2016-2024). TF-IDF and LDA algorithms identified key image perception themes. Visitor satisfaction was then evaluated with SnowNLP sentiment analysis to examine the dynamic correlation between the perception themes and satisfaction. …”
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Revolutionizing Nursing and Midwifery Informatics Curriculum Evaluation in Ghana: A Data-Driven Machine Learning Approach by Iven Aabaah, Japheth Kodua Wiredu, Bakaweri Emmanuel Batowise, Nelson Abuba Seidu

“…The study employed Random Forest, Gradient Boosting, Support Vector Machine, K-Nearest Neighbor, and Logistic Regression algorithms, evaluated using standard performance metrics, including accuracy, precision, and recall. …”
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Default Risk Prediction of Enterprises Based on Convolutional Neural Network in the Age of Big Data: Analysis from the Viewpoint of Different Balance Ratios by Zhe Li, Zhenhao Jiang, Xianyou Pan

“…To address these issues, this study conducts an analysis from the viewpoint of different balance ratios as well as the selection order of feature selection. …”
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Optimal Sizing and Deployment of Renewable Energy Generators in Practical Transmission Network Using Grid-Oriented Multiobjective Harmony Search Algorithm for Loss Reduction and Vo... by Pramod Kumar, Nagendra Kumar Swarnkar, Om Prakash Mahela, Baseem Khan, Divya Anand, Aman Singh, Juan Luis Vidal Mazon, Fahd S. Alharithi

“…Performance indexes such as active power loss minimization index (APMLI), the reactive power loss minimization index (RPMLI), and the total voltage deviation improvement index (TVDII) are introduced to evaluate the health of the test network with different load scenarios. …”
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The Forecasting Yield of Highland Barley and Wheat by Combining a Crop Model with Different Weather Fusion Methods in the Study of the Northeastern Tibetan Plateau by Peng Li, Liang He, Xuetong Wang, Mengfan Zhao, Fan Li, Ning Jin, Ning Yao, Chao Chen, Qi Tian, Bin Chen, Gang Zhao, Qiang Yu

“…This study examines the impact of different weather data forecasting methods on yield estimation. …”
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Assessment of suitable habitat of Semen Armeniacae Amarum. in China under different climatic conditions by Internal Transcribed Spacer 2 and Maxent model by Donglai Ma, Zikang Lu, Zhiqiang Xue, Zihan Yu, Xuhong Duan, Xian Gu, Yukun Yao, Le Cai, Kaiyan Zheng

“…The maximum entropy model was coupled with the stepwise regression algorithm to evaluate the potential impact of future climate on the quality of amygdalin. …”
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