Exploratory Survey on UUM Student’s Acceptance Towards the Founding of Waqf Institution For Education by Omar, Hydzulkifli Hashim, Abu Bakar, Azizi, Basary, Noor Faezah, Shuib, Mohd Sollehudin, Yusuff, Noraini

“…All the data are analysed using software of Statistical Package for Social Science (SPSS) by conducting statistical method namely, Independent Samples T-test, Analysis of Variance (ANOVA), Pearson Corellation and Multiple Linear Regression analysis to achieve the objectives of this research. …”
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Bridging the Health Divide: Achieving Equitable Healthcare Access in Kenya through Artificial Intelligence by Nyakiongora, Geoffrey Mosoti

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Macroeconomic and Firm-Specific Effects on Islamic Deposits Sustainability by Ab Rahman, Sazana, Ahmad, Nor Hayati, Che Arshad, Noraziah

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Adoption of ZakaTech in the Time of COVID-19: Cross-Country and Gender Differences by Nashwan, Saeed Awadh, Ismaiel, Abdelhamid Elsayed A., Muneeza, Aishath, Isa, Mohamad Yazid

“…Findings – By analyzing both Saudi and Egyptian samples, the authors found that all UTAUT constructs are statistically significant, except for effort expectancy in Egypt. …”
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Robust inference of memory structure for efficient quantum modeling of stochastic processes by Ho, Matthew, Gu, Mile, Elliott, Thomas J.

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Reduced cell and stack modeling of planar solid oxide fuel cells by He, Zhongjie

“…As a result of spatial smoothing with the developed correlation factors, the isothermal 3D single-cell model is reduced to a two-dimensional (2D) counterpart with effective physical parameters, which is solved with respect to directions along the cell length (streamwise direction, ex) and through the cell thickness (normal direction, ez). …”
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Enhancing construction site performance through technology and management practices as material waste mitigation in the Malaysian construction industry by Mohammed Abdullah Abkar, Mahdi, Yunus, Riduan, Gamil, Yaser, Albaom, Mohammed Abdo

“…Utilizing Partial Least Squares - Structural Equation Modeling (PLS-SEM) and Statistical Package for the Social Sciences (SPSS), the findings highlight the importance of technological integration, efficient material management, and competitive strategies in effective material waste mitigation. …”
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Challenges and Solution of Online Learning and Assessment Amidst the COVID-19 Pandemic: A Case Study in Universiti Utara Malaysia (S/O 14793) by Mohd Nordin, Nur Rasyidah, Omar, Wafa, Mohd Ridzuan, Iliya Nurul Iman

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Hidden markov model for decision making among heterogeneous systems in intelligent building by Abba, Babakura

“…HMM is chosen due to the characteristics it possesses such as probabilistic, statistical, machine learning as well as its robustness and scalability has been seen as an efficient and effective model to tackle the problem of interoperation in the intelligent building. …”
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A Study on Deploying Large Language Models as Agents by Cao, Jiannan

“…The study begins with an in-depth analysis of language models, tracing their evolution from pure statistical models to advanced neural network architectures like Transformers and their bidirectional variants. …”
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A data-driven method for automated data superposition with applications in soft matter science by Lennon, Kyle R., McKinley, Gareth H., Swan, James W.

“…This method enables a standardized, statistical treatment of self-similar data across many fields, producing interpretable data-driven models that may inform applications such as materials classification, design, and discovery.…”
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Reliability analysis and data driven modelling of railway component failure by Wang, Jinlong

“…Such statistical models are under some distribution assumptions which may not be fully satisfied in practice, but the models can be fitted with limited data samples and their interpretabilities are high. …”
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Modelling and development of carbon molecular sieve membrane for gas separation by Su, Jincai

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Integrated user-interface acceptance model for e-learning system by Ramadiani, -

“…Based on t-value, loading factors, and the relative suitability of each attribute, the User Interface Acceptance Model for e-learning can be accepted. Based on the Goodness of Fit statistical value in the first and the second model, the model of e-learning user interface has a highly significant correlation with e-learning acceptance. …”
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Deriving the intial abstraction ratio coefficient for runoff prediction in Peninsula Malaysia by Lloyd Ling

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Rainfall projection using CIMP6 models of extreme area in Johor by Hamid, H, Rahmat, S N, Kasmin, H, Tukimat, N N

“…The research employs statistical downscaling, using historical observed data (1988-2020) and GCM output data, with a bias correction through linear scaling. …”
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Two-stage Bayesian system identification using Gaussian discrepancy model by Zhang, Feng-Liang, Au, Siu-Kui, Ni, Yan-Chun

“…This opens up opportunities for explicitly accounting for modeling error in the structural model (Stage II) through the conditional distribution of modal parameters given structural model parameters. …”
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Leptospirosis modelling using hydrometeorological indices and random forest machine learning by Jayaramu, Veianthan, Zulkafli, Zed, De Stercke, Simon, Buytaert, Wouter, Rahmat, Fariq, Abdul Rahman, Ribhan Zafira, Ishak, Asnor Juraiza, Tahir, Wardah, Ab Rahman, Jamalludin, Mohd Fuzi, Nik Mohd Hafiz

“…An extreme model was the most sensitive while an average model was the most specific. …”

Modelling and characterization of membrane fouling in osmotically-driven membrane processes (ODMPs) by Lai, Li

“…In order to connect this experimentally inaccessible parameter with model, the parameter was extracted from optimization through series layers model and fed into a backpropagation neural networks with various experimentally-accessible real time parameters. …”
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A multi-omics strategy to understand PASC through the RECOVER cohorts: a paradigm for a systems biology approach to the study of chronic conditions by Sun, J, Aikawa, M, Ashktorab, H, Beckmann, ND, Enger, ML, Espinosa, JM, Gai, X, Horne, BD, Keim, P, Lasky-Su, J, Letts, R, Maier, CL, Mandal, M, Nichols, L, Roan, NR, Russell, MW, Rutter, J, Saade, GR, Sharma, K, Shiau, S, Thibodeau, SN, Yang, S, Miele, L, NIH Researching COVID to Enhance Recovery (RECOVER) Consortium

“…This approach will minimize lab-to-lab technical variability, maximize sample size for class discovery, and enable the incorporation of as many relevant variables as possible into statistical models. Many of our recommendations have already been considered by the NIH through the peer-review process, resulting in the creation of a systems biology panel that is currently designing the studies we proposed. …”