Methodological bases for the design of flexible educational programs in a network format by Elena Mikhailovna Efimova, Denis Olegovich Efimov

“…The purpose of the research is determination of the methodology for constructing effective network educational programs, based on the formation of the student’s personality and his practical preparation for future professional activity through individual development. …”
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The Pedagogical Content Knowledge of the School of Education Pre-Service Teachers in Test Construction by Lorie Anne Socorro Moreno, Ronald Quileste

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Exploring perspectives of type 2 diabetes prevention program coaches and training delivery staff on e-learning training: a qualitative study by Kaela D. Cranston, Natalie J. Grieve, Mary E. Jung

“…E-learning training for diabetes prevention program coaches was designed and developed with input from end users. …”
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An interpretable machine learning model based on computed tomography radiomics for predicting programmed death ligand 1 expression status in gastric cancer by Lihuan Dai, Jinxue Yin, Xin Xin, Chun Yao, Yongfang Tang, Xiaohong Xia, Yuanlin Chen, Shuying Lai, Guoliang Lu, Jie Huang, Purong Zhang, Jiansheng Li, Xiangguang Chen, Xi Zhong

“…Abstract Background Programmed death ligand 1 (PD-L1) expression status, closely related to immunotherapy outcomes, is a reliable biomarker for screening patients who may benefit from immunotherapy. …”
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PENERAPAN TEORI KONSTRUKTIVISTIK PADA PEMBELAJARAN BAHASA ARAB DI KELOMPOK 28 PROGRAM INTENSIFIKASI BAHASA ARAB IAIN SYEKH NURJATI CIREBON by Hikmah Uswatun Ummi, Indrya Mulyaningsih

“…<p>Use appropriate teaching methods teachers' creativity. Learning foreign languages, especially Arabic Arabic Intensification Program IAIN Sheikh Nurjati Cirebon using various methods. …”
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THE APPLICATION OF AUTHENTIC ASSESSMENT WITH FEEDBACK TO IMPROVE THE COMPETENCE OF MTS 2 BANDUNG STUDENTS IN CONSTRUCTING A SCIENTIFIC REPORT OF MOTION MATERIAL IN SCIENCE LEARNING by A. Y. Nuryantini, T. Setiadi, K. Kurniawan, I. Farida

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Towards sustainable construction: estimating compressive strength of waste foundry sand-blended green concrete using a hybrid machine learning approach by Hoang Nhat-Duc, Nguyen Quoc-Lam

“…LightGBM is used to construct a functional mapping between the CS and its influencing factors. …”
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Determinants of WhatsApp and Telegram usage for learning support in Nigerian universities: a quantitative study by Chinyere Ori Elom, Hayford Mensah Ayerakwa, Sikiru Ibrahim-Olesin, Eric Worlanyo Deffor, Chidebe Chijioke Uwaleke, Robert Ugochukwu Onyeneke

“…The determinants of the use of WhatsApp and Telegram to enhance learning among students include age, gender, wealth status of parents/guardians, student’s faculty/program, location of school, and level of student in school. …”
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Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis by Xudong Shen, Xudong Shen, Xudong Shen, Guoxiang Li, Guoxiang Li, Guoxiang Li, Junfeng Yao, Junfeng Yao, Junfeng Yao, Junping Yang, Xiaobo Ding, Xiaobo Ding, Xiaobo Ding, Zongyao Hao, Zongyao Hao, Zongyao Hao, Yan Chen, Yang Chen, Yang Chen, Yang Chen

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Machine learning-driven multi-omics analysis identifies a prognostic gene signature associated with programmed cell death and metabolism in hepatocellular carcinoma by Xiang Li, Donghao Yin, Jiahao Geng, Yanyu Xu, Zijing Xu, Xuemeng Yang, Quanwei Li, Zimeng Shang, Zhiyun Yang, Zhong Xu, Jiabo Wang, Enxiang Zhang, Xinhua Song

“…The intersecting DEGs from both datasets were analyzed using univariate Cox regression, and a prognostic risk score model was constructed through machine learning algorithms. The model was subsequently evaluated in the context of the immune microenvironment and its relevance to immunotherapeutic responses. …”
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Pengembangan Media Pembelajaran Interaktif pada Mata Kuliah Teori dan Praktik Plambing di Program Studi S1 PVKB UNJ

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Combining realist evaluation and appreciative inquiry: A participatory, learning-focused methodology for tourism interventions by Jenny Suno Wu, Pete Barbrook-Johnson, Xavier Font, Anna Torres-Delgado

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Predictive biomarkers and molecular subtypes in DLBCL: insights from PCD gene expression and machine learning by Tiantian He, Jie Geng, Chuandong Hou, Hongyi Li, Hong Zhang, Peng Zhao, Peifeng He, Xuechun Lu

“…Additionally, 12 machine learning algorithms were employed to construct predictive models for DLBCL, with performance evaluated using AUC and F-score metrics. …”
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An Application Programming Interface (API) Sensitive Data Identification Method Based on the Federated Large Language Model by Jianping Wu, Lifeng Chen, Siyuan Fang, Chunming Wu

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Research discussion groups as a component of the development of practical skills of students in the field of training “Construction” by N. I. Taraseeva, O. V. Baulina, N. A. Dezhinova

“…The modern educational process, including theoretical and practical development of the basic educational program, provides that 40% of the basic information the student is receiving during the classes, the remaining 60% — for self-study. …”
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Effect of a Web-Based Educational Program on Prevention of Tobacco Smoking among Male Adolescents: An Application of Prototype Willingness Model by Alireza Heidarnia, Majid Barati, Shamsoddin Niknami, Hamid Allahverdipour, Saeed Bashirian

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Interpretable machine learning approaches to assess the compressive strength of metakaolin blended sustainable cement mortar by Naseer Muhammad Khan, Liqiang Ma, Waleed Bin Inqiad, Muhammad Saud Khan, Imtiaz Iqbal, Muhammad Zaka Emad, Saad S. Alarifi

“…Thus, this study was conducted to develop reliable empirical prediction models to assess CS of MK-based mortar from its mixture proportion using machine learning algorithms like gene expression programming (GEP), extreme gradient boosting (XGB), multi expression programming (MEP), bagging regressor (BR), and AdaBoost etc. …”
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RSS Tracking Control for AVs Under Bayesian-Network-Based Intelligent Learning Scheme by Kun Zhang, Kezhen Han, Nanbin Zhao

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Genetic programming-based algorithms application in modeling the compressive strength of steel fiber-reinforced concrete exposed to elevated temperatures by Mohsin Ali, Li Chen, Qadir Bux Alias Imran Latif Qureshi, Deema Mohammed Alsekait, Adil Khan, Kiran Arif, Muhammad Luqman, Diaa Salama Abd Elminaam, Amir Hamza, Majid Khan

“…However, extreme temperatures degrade concrete's material characteristics including stiffness and strength. The construction industry increasingly embraces machine learning (ML) to estimate concrete properties and optimize cost and time accurately. …”
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Programmed cell death signatures-driven microglial transformation in Alzheimer’s disease: single-cell transcriptomics and functional validation by Mi-Mi Li, Ying-Xia Yang, Ya-Li Huang, Shu-Juan Wu, Wan-Li Huang, Li-Chao Ye, Ying-Ying Xu

“…An integrated machine learning framework, combining 12 algorithms was used to construct a PCDS model. …”
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