Exploring machine learning classification for community based health insurance enrollment in Ethiopia by Seyifemickael Amare Yilema, Seyifemickael Amare Yilema, Yegnanew A. Shiferaw, Yikeber Abebaw Moyehodie, Setegn Muche Fenta, Denekew Bitew Belay, Denekew Bitew Belay, Haile Mekonnen Fenta, Haile Mekonnen Fenta, Teshager Zerihun Nigussie, Ding-Geng Chen, Ding-Geng Chen

“…Therefore, this study aimed to identify the ML algorithm with the best predictive accuracy for CBHI enrollment and to determine the most influential predictors among the dataset.MethodsThe 2019 Ethiopian Mini Demographic and Health Survey (EMDHS) data were used. …”
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The utilization of generative artificial intelligence in the professional development of teachers by Katia Cristian Puente Muniz, Caterine Fagundes Vila

“… This study focused on the integration of generative artificial intelligence, represented by ChatGPT, as an educational tool in teacher training courses in Brazil and Spain. …”
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Approximate Solution of Fuzzy Caputo's-Katugampola differential equation with order  0 by Ali Hadi Gabber

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A Coordinated Allocation Method for Right-Turn Strategy at Signalized Intersections with Optimal Pedestrian and Vehicle Delays by Yu Bai, Wanyan Luo

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Monte Carlo Simulation and Experimental Validation for Radiation Protection with Multiple Complex Source Terms and Deep Penetration for a Radioactive Liquid Waste Cementation Facil... by Wenqian Li, Xuegang Liu, Sheng Fang, Xueliang Fu, Kaiqiang Guo

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A Novel Crowdsourcing-Assisted 5G Wireless Signal Ranging Technique in MEC Architecture by Rui Lu, Lei Shi, Yinlong Liu, Zhongkai Dang

“…Experimental results demonstrate a mean positioning error of 5 m, with 95% of devices achieving errors within 10 m, as well as building and floor prediction error rates of 0.5% and 1%, respectively. …”
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Machine Learning-Based Classification and Statistical Analysis of Liver Cancer: A Comprehensive Study of Model Performance and Clinical Significance by Pratyush Kumar MAHARANA, Tapan Kumar BEHERA, Pradeep Kumar NAIK

“…Conclusion: After performing the complete process, we conclude that the extra tree classifier out of 17 models is the most suitable machine learning algorithm for liver cancer prediction. …”
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Mechanistic role of miR-375 in regulating PDPK1 to promote progression of small bowel neuroendocrine tumors: a silico analysis by Tao Ren, Lu Zhou, Zhenlong Li, Mingmei Pan, Xueqiong Han

“…Drug targeting prediction and immune environment evaluation were identified. …”
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Improvement of physics-based and data-driven model simulations based on multi-source soil moisture datasets by Xiao Liang, Haiting Gu, Yue-Ping Xu, Lu Wang, Yuxue Guo, Li Liu

“…Study focus: Accurate streamflow simulation is essential for effective water resource management in watersheds, necessitating the use of reliable models and precise data for the simulation and prediction of streamflow. This study integrates multi-source soil moisture datasets into both a process-based model and a data-driven model to explore the potential benefits of calibration and streamflow simulation within a mesoscale watershed in eastern China. …”
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Analysis of approaches to identification of trend in the structure of the time series by U. S. Mokhnatkina, D. V. Parfenov, D. A. Petrusevich

“…A combination of polynomial model for trend description and ARIMA for seasonally description and combination of ACD algorithm for trend and ETS for seasonal model obtained good forecasts in case of seasonal time series, while Fourier time series as a trend model also achieved close quality of prediction.Conclusions. …”
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Flood Detection and Susceptibility Mapping Using Sentinel-1 Time Series, Alternating Decision Trees, and Bag-ADTree Models by Ayub Mohammadi, Khalil Valizadeh Kamran, Sadra Karimzadeh, Himan Shahabi, Nadhir Al-Ansari

“…Based on AUC, success and prediction rates were 0.736 and 0.786 for bag-ADTree algorithm, in order, while these proportions were 0.714 and 0.784 for ADTree. …”
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Rock blasting evaluation - image recognition method based on deep learning by Haibao YI, Aixiang Wu, Xiliang Zhang

“…And a segmented function R-R block size distribution correction model was proposed, which can better characterize the characteristics of blasting block size distribution and serves as a guide for accurate prediction of block size distribution. Overall, image recognition technology can significantly improve the efficiency and accuracy of blasting evaluation, solve many drawbacks of traditional manual analysis methods, and holds great application prospects in blasting quality evaluation.…”
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HIDS-RPL: A Hybrid Deep Learning-Based Intrusion Detection System for RPL in Internet of Medical Things Network by Abdelwahed Berguiga, Ahlem Harchay, Ayman Massaoudi

“…The suggested model, designated HIDS-RPL, results from the hybridization of the Convolutional Neural Network (CNN) for feature extraction and the Long Short Term Memory neural network (LSTM), typically employed for sequence data prediction. We evaluate the proposed algorithm to detect intrusions using the benchmark CIC-DDoS2019 dataset. …”
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Object Detection in High-Resolution UAV Aerial Remote Sensing Images of Blueberry Canopy Fruits by Yun Zhao, Yang Li, Xing Xu

“…Blueberries, as one of the more economically rewarding fruits in the fruit industry, play a significant role in fruit detection during their growing season, which is crucial for orchard farmers’ later harvesting and yield prediction. Due to the small size and dense growth of blueberry fruits, manual detection is both time-consuming and labor-intensive. …”
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An object-based and Lagrangian view on an intense hailstorm day in Switzerland as represented in COSMO-1E ensemble hindcast simulations by K. P. Brennan, M. Sprenger, A. Walser, M. Arpagaus, H. Wernli

“…To this end, we investigate ensemble hindcast simulations using the COSMO-1E numerical weather prediction model that includes the HAILCAST hail growth parameterization. …”
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Synergistic Matching and Influencing Factors of Grain Production and Cropland Net Primary Productivity in the Black Soil Region of Northeast China by Quanxi Wang, Jun Ren, Maomao Zhang, Hongjun Sui, Xiaodan Li

“…This study analyzed the spatial–temporal mismatch characteristics of grain production and cropland net primary productivity (CNPP) using the gravity center model, spatial autocorrelation analysis, and spatial mismatch index (SMI), and identified the spatial heterogeneity and prediction–response relationships of influencing factors based on a geographically and temporally weighted regression (GTWR) model and boosted regression tree (BRT) machine learning algorithm. …”
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Aerodynamic Optimization of Morphing Airfoil by PCA and Optimization-Guided Data Augmentation by Ao Guo, Jing Wang, Miao Zhang, Han Wang

“…A Multi-Island Genetic Algorithm (MIGA) efficiently explores the reduced design space, while iterative retraining of the surrogate model enhances prediction accuracy, particularly in high-performance regions. …”
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A combined improved dung beetle optimization and extreme learning machine framework for precise SOC estimation by Kaihua Yao, Xinyu Yan, Xiling Mao, Mengwei Li, Xiao Li, Ziyu Lian, Yuxiang Han

“…This effectively resolves the problems of inconsistent performance and instability arising from randomly initialized hidden layer weights and biases in ELM, resulting in enhanced prediction accuracy. The proposed IDBO-ELM method is validated in the context of five parameters, namely, different ambient temperatures, operating conditions, battery materials, initial SOC values, and running time. …”
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THE TASK OF MINIMAX ADAPTIVE MANAGEMENT OF INNOVATIVE PROCESSES AT AN ENTERPRISE WITH RISK ASSESSMENT by Vitalina Babenko, Elena Alisejko, Zoya Kochuyeva

“…The results demonstrated in the work can be used for economic and mathematical modelling and solving other tasks of optimizing processes of data prediction and management under the lack of information and under risks as well as for developing corresponding software and hardware complexes to support efficient managerial decisions in practice.…”
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Uncovering Antibiotic Resistance Genes in Marmara Sea Mucilage via Shotgun Metagenome Sequencing by Gizem Karış, Herdem Aslan, Mehmet Hora, Aycan Gundogdu

“…The DNA data was analyzed using a de novo approach with IDBA-UD assembler, BWA-mem2, and Prodigal gene prediction algorithm. For ARG profiling, gene clusters were aligned to the CARD (The Comprehensive Antibiotic Resistance Database) using BlastX. …”
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