Modeling and forecasting customer demands by See, Tian Pau.

“…In this paper, I have made an attempt to seek what statistical models and forecasting techniques which are appropriate to support decision making in the operational level of supply chain while dealing with customer demands on short life cycle products to avoid undesired production condition. …”
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Uncertainty quantification framework for combined statistical spatial downscaling and temporal disaggregation for climate change impact studies on hydrology by Rajendran Queen Suraajini

“…The Statistical Downscaling Model (SDM) is the bridging model which is used to downscale the output from the General Circulation Model (GCM) for increasing the spatial resolution of future climate scenarios. …”
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A Non‐Intrusive Machine Learning Framework for Debiasing Long‐Time Coarse Resolution Climate Simulations and Quantifying Rare Events Statistics by Barthel Sorensen, B., Charalampopoulos, A., Zhang, S., Harrop, B. E., Leung, L. R., Sapsis, T. P.

“…Previous efforts have attempted to train such operators using loss functions that match statistics. However, this approach falls short with events that have longer return period than that of the training data, since the reference statistics have not converged. …”
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Bayes factors for logistic (mixed effect) models by Silvey, C, Dienes, Z, Wonnacott, E

“…We illustrate this using mainly the estimates from frequentist logistic mixed-effects models (because of their widespread adoption) but also using Bayesian model comparison with Bayesian hierarchical models (which have increased flexibility). …”

Bayesian neural network language modeling for speech recognition by Xue, Boyang, Hu, Shoukang, Xu, Junhao, Geng, Mengzhe, Liu, Xunying, Meng, Helen

“…State-of-the-art neural network language models (NNLMs) represented by long short term memory recurrent neural networks (LSTM-RNNs) and Transformers are becoming highly complex. …”
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Factors Influencing Students Intention to Choose Career of Halal Food Industry in Malaysia using Theory of Planned Behavior by Abu Bakar, Nashirah, Rosbi, Sofian, Haji Hashim, Hydzulkifli, Che Arshad, Noraziah

“…Next, the value of R-squared for model fit in this study is 0.675 that indicates a good model fit that explained 67.5% of variance in dependent variable. …”
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Topological data analysis for fake news detection by Deng, Ran

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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

“…A conceptual framework is built based on Theory Planned Behaviour (TPB) and Technology Acceptance Model (TAM)…”
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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

“…Therefore, this study aims to provide an integrated model that scrutinizes the determinants of acceptance and use of technology (UTAUT) of ZakaTech, combined with social cognitive theory (SCT), in the midst of the COVID-19 crisis where social distancing is the norm in conducting economic activities. …”
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On the weak convergence of stochastic integrals on Skorokhod space: From general theory to applications within the realm of continuous-time random walks by Wunderlich, F

“…We refine the classical theory, reveal new insights into convergence behaviours even in the classical J1 setting and address the sharpness of various key statements. …”

Efficient Bayesian estimation and use of cut posterior in semiparametric hidden Markov models by Moss, D, Rousseau, J

Differentially private deep learning for time series data by Dwitami, Inggriany

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Variability study of nanowire: a compact model application by Machavolu Kamakshi Srikanth

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Modeling human-like non-rationality in social agents by Kochanowicz, Jaroslaw Slawomir

“…To realize those postulates, Social Context Cognition Model (SCCM), inspired among others by the Dual Process Theory, is proposed. …”
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Modeling autobiographical memory in human-like autonomous agents by Wang, Di, Tan, Ah-Hwee, Miao, Chunyan

“…With the motivation of developing human-like intelligence, in this paper, we delineate our approach to enable an agent to maintain memories of its own and to wander in mind. Our model, named Autobiographical Memory-Adaptive Resonance Theory network (AM-ART), is designed to capture autobiographical memories, comprising pictorial snapshots of one's life experiences together with the associated context, namely time, location, people, activity, and emotion. …”
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Measuring dynamical uncertainty with Revealed Dynamics Markov Models by Bramson, Aaron, Baland, Adrien, Iriki, Atsushi

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Glass transition behaviour In a voronoi model of cell tissues by Loh, Leon Yeong Wei

“…This allows one to study the static and dynamical statistical properties in the temperature regime where mode-coupling theory is dominant. …”
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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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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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