Predicting Students’ Performance Using a Hybrid Machine Learning Approach by Ropafadzo Duwati, Tawanda Mudawarima

“…Previous studies have employed individual ML algorithms for performance prediction; these models often suffer from limitations such as low accuracy and bias towards specific data characteristics. …”
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Experimental Study on the Influence Patterns of Buildings Displaced and Buried by Debris Flow by FENG Lei, SONG Dongri, CHEN Xiaoqing, LIU Jia, CHEN Qian, LIU Yunhui

“…ObjectiveThis study clearly determines the physical characteristic factors that govern the displacement and burial of buildings by debris flow, and clarifies the impact patterns of these physical characteristic factors on the deposition positions of buildings in debris flow. …”
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Model of Gait Control in Parkinson’s Disease and Prediction of Robotic Assistance by Clemence Vandamme, Virginie Otlet, Renaud Ronsse, Frederic Crevecoeur

“…Furthermore, we used this model to predict the potential benefit of an active orthosis on the gait pattern of patients. …”
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Aperture Field Anisotropy Control on Immiscible Displacement Patterns in Rough Fractures by Kun Xing, Xiaoqing Shi, Zhibing Yang, Xueyuan Kang, Siyuan Qiang, Jichun Wu

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Experimental Analysis of Rainfall-Induced Instability and Failure Patterns in Loess Fill Slopes by Jinlian Ma, Qian Wang, Xiumei Zhong, Ping Wang, Xiaohui Yang

“…These results offer valuable guidance for the design of support systems and drainage infrastructure in loess fill slopes, and provide practical insights for early-warning systems, hazard prediction, and disaster risk reduction strategies.…”
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Genome-wide DNA methylation patterns in Daphnia magna are not significantly associated with age by Ruoshui Liu, Marco Morselli, Lev Y. Yampolsky, Leonid Peshkin, Matteo Pellegrini

“…Our results showed no significant global differences in DNA methylation levels between young, mature, and old individuals, nor any age-related clustering in dimensionality reduction analyses. Attempts to construct an epigenetic clock using machine learning models did not yield accurate age predictions, likely due to the overall low DNA methylation levels and lack of robust age-associated methylation changes. …”
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Assessment and Prediction of Carbon Storage Based on Land Use/Land Cover Dynamics in the Gonghe Basin by Hong Jia, Siqi Yang, Lianyou Liu, Hang Li, Zeshi Li, Yixin Chen, Jifu Liu

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Psychometric Model of College Students Based on Time Series Analysis and Its Application in Educational Management by Lu Lu

“…This paper analyzes the psychometric behavior data, uses the time series analysis method for behavior prediction, deeply mines the relevant component information of the psychometric data, and solves the problems of weak correlation between the functions of the psychometric platform and low data accuracy of the psychometric model. …”
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Exploring and Predicting HIV Preexposure Prophylaxis Adherence Patterns Among Men Who Have Sex With Men: Randomized Controlled Longitudinal Study of an mHealth Intervention in West... by Bing Lin, Jiayan Li, Jiaxiu Liu, Wei He, Haiying Pan, Xiaoni Zhong

“…We included 8 variables that were significant in the univariate analysis in the decision tree prediction model. We found 4 factors and 8 prediction rules, and the results showed that HIV knowledge score, education attainment, mHealth intervention, and HIV testing were key nodes in the patterns of change in adherence. …”
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Challenges in developing reliable phosphorus predictive models: Unpredictable release under soil redox changes by Filippo Saiano, Riccardo Scalenghe

“…When an environmental or anthropogenic transformation induces anoxia, the P released does not follow a predictable pattern.…”
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Prediction of litchi flower induction in South China region based on the CMIP6 climate model by HOU Wei, ZHANG Liuhong, ZHANG Lei, LUAN Lan, ZHANG Mingjie, WANG Xiuzhen, ZHANG Hui

“…In recent years, the flowering rate of medium-late maturing litchi varieties in the low-latitude regions of South China has generally been low, resulting in a pronounced alternative-bearing years with high and low production. …”
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Behavioral engagement patterns and psychosocial outcomes in web-based interpretation bias training for anxiety. by Ángel Francisco Vela de la Garza Evia, Jeremy William Eberle, Sonia Baee, Emma Catherine Wolfe, Mehdi Boukhechba, Daniel Harold Funk, Bethany Ann Teachman, Laura Elizabeth Barnes

“…Digital mental health interventions (DMHIs) have the potential to expand treatment access for anxiety but often have low user engagement. The present study analyzed differences in psychosocial outcomes for different behavioral engagement patterns in a free web-based cognitive bias modification for interpretation (CBM-I) program. …”
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Artificial intelligence model in the cognitive and learning activities of university subjects by N. Abishev, R. Ramazanov, M. Abaideldanova, K. Chesnokova, A. Baizhumayeva

“…The authors design this model using algorithms–sets of rules that enable programs to make decisions, recognize patterns, and generate predictions based on input data relevant to the learning and cognitive processes of university subjects. …”
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Mind Over Waste: Decoding the Mental Models of Hard-to-Reach in Household Waste Practices by Bremane Inguna, Liberova Veronika, Bezrucko Alise Egija, Blumberga Dagnija, Blumberga Andra

“…The Mental Modeler tool is used to predict behavioural patterns of different consumer groups and simulate the impact of various scenarios on these behaviours. …”
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The effect of changing heat use patterns on residential energy efficiency in a Japanese smart community by Le Na Tran, Qian Wu, Huong Thanh Hoang

“…Given the lack of properly designated energy models for residential energy reduction, the primary objective of this study is to implement integrated energy prediction models and occupant-related parameters in proposing human-centered energy-saving and low-carbon building solutions. …”
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The potential habitat of Phlomoides rotata in Tibet was based on an optimized MaxEnt model by Jun-Wei Wang, Jun-Wei Wang, Min Xu, Norbu Ngawang, Yonghao Chen, Ngawang Bonjor, Xiaoyan Jia, Zhefei Zeng, Zhefei Zeng, La Qiong, La Qiong

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Predictors of Toxoplasma gondii IgG Seropositivity and Cranial Ultrasound Patterns among Children with Hydrocephalus by Sofia Ottaru, Mariam M. Mirambo, Rogatus Kabyemera, Benson R. Kidenya, Mwanaisha Seugendo, Delfina R. Msanga, Patrick Ngoya, Domenica Morona, Stephen E. Mshana

“…Despite the parasite being common in Tanzania, there is a paucity of information on the prevalence of T. gondii and cranial ultrasound patterns among children with hydrocephalus. Methods. …”
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Patterns of recurrence after curative D2 resection for gastric cancer: Implications for postoperative radiotherapy by Jing Xu, Li Shen, Yongjie Shui, Wei Yu, Qingqu Guo, Risheng Yu, Yulian Wu, Qichun Wei

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Predicting Cardiovascular Aging Risk Based on Clinical Data Through the Integration of Mathematical Modeling and Machine Learning by Kuat Abzaliyev, Madina Suleimenova, Siming Chen, Madina Mansurova, Symbat Abzaliyeva, Ainur Manapova, Almagul Kurmanova, Akbota Bugibayeva, Diana Sundetova, Raushan Bitemirova, Nazipa Baizhigitova, Merey Abdykassymova, Ulzhas Sagalbayeva

“…Objective: This study aimed to develop and externally validate a mathematical model for predicting cardiovascular aging in individuals aged 65 and older, based on general clinical and behavioral data. …”
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Interpretable Machine Learning Models for PISA Results in Mathematics by Ismael Gomez-Talal, Luis Bote-Curiel, Jose Luis Rojo-Alvarez

“…By preprocessing the PISA dataset, we categorized students into Low, Medium, and High proficiency levels and employed various binary classification models to discern predictive patterns. …”
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