ORCID Profile
0000-0001-5790-4682
Current Organisations
Nanyang Technological University
,
University of Wollongong
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Transport Engineering | Autonomous Vehicles | Mechanical Engineering | Computer-Human Interaction
Automotive Equipment | Road Safety | Application Tools and System Utilities |
Publisher: SAGE Publications
Date: 14-05-2023
DOI: 10.1177/00332941221087915
Abstract: The present study aimed to examine whether the level of strength-based parenting a student receives during remote learning affects their levels of academic motivation once returning to school. Additionally, the study sought to explore whether school belonging mediated the association between strength-based parenting and academic motivation and whether student strength use moderated this mediating relationship. The s le comprised of secondary school students who had recently returned back to c us, following a period of COVID-19 enforced remote learning ( n = 404 age range: 11 to 18 years M = 14.75, SD = 1.59 50.2% female, and 3% non-/other gendered or declined to answer). Strength-based parenting had a significant predictive effect on student academic motivation with school belonging mediating the association between strength-based parenting and academic motivation. The mediating effect of school belonging on the association between strength-based parenting and academic motivation was moderated by strength use during remote learning. The results of the study are discussed using a positive education lens with implications for improving skills and strategies to foster positive student functioning in times of remote learning and crisis.
Publisher: Elsevier BV
Date: 08-2023
Publisher: Elsevier BV
Date: 12-2021
Publisher: Informa UK Limited
Date: 18-05-2023
Publisher: SAGE Publications
Date: 07-2021
DOI: 10.1177/03611981211021550
Abstract: This paper studies the empty container repositioning (ECR) problem considering the exchange of slots and empty containers among liner shipping companies. It is common for an in idual shipping company to seek an optimal solution for ECR and cargo routing to maximize its own benefits. To achieve cooperation among shipping companies, a multi-stage solution strategy is proposed. With the inverse optimization technique, the guide leasing prices of slots and empty containers among shipping companies are derived considering the schedule of vessels and cargo routing. Based on the guide leasing price, a cooperative model is formulated to minimize the total cost, which includes the transportation cost for laden containers, the inventory holding cost, the container leasing cost, and the repositioning cost. All the involved shipping companies are expected to follow the best solution of ECR and cargo routing to achieve a cooperative and stable optimum. A real-world shipping network operated by three liner shipping companies is used as a case study with promising numerical results.
Publisher: Informa UK Limited
Date: 16-04-2021
Publisher: IEEE
Date: 08-2020
Publisher: Springer Science and Business Media LLC
Date: 03-10-2023
Publisher: Elsevier BV
Date: 03-2016
Publisher: Informa UK Limited
Date: 02-07-2023
Publisher: Elsevier BV
Date: 09-2019
Publisher: SAGE Publications
Date: 2013
DOI: 10.3141/2333-03
Abstract: The modeling of multimodal choice in a railway–highway system with single park-and-ride service on a linear travel corridor is studied. Commuters choose either auto or railway to travel directly from home to city center or drive to the park-and-ride facility and transfer to railway transit service. Both the traffic congestion on the highway and the crowding on rail transit are considered. The highway capacity is assumed to be stochastic to take into account travel time reliability for use of the auto mode. Commuters are assumed to be distributed uniformly along the corridor. A linear complementarity system to model commuters' mode choice along the corridor and to solve the spatial equilibrium travel pattern is proposed. The formulated linear complementarity system is transformed into a mixed integer linear program to be solved. The modeling approach and solution algorithm are implemented in a small numerical ex le.
Publisher: Elsevier BV
Date: 10-2022
Publisher: Elsevier BV
Date: 04-2022
Publisher: Springer Science and Business Media LLC
Date: 04-06-2021
Publisher: Elsevier BV
Date: 04-2022
Publisher: Elsevier BV
Date: 03-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2022
Publisher: Maximum Academic Press
Date: 2023
Publisher: Elsevier BV
Date: 05-2023
Publisher: MDPI AG
Date: 31-10-2022
DOI: 10.3390/EN15218124
Abstract: Forecasting return and profit is a primary challenge for financial practitioners and an even more critical issue when it comes to forecasting energy market returns. This research attempts to propose an effective method to predict the Brent Crude Oil return, which results in remarkable performance compared with the well-known models in the return prediction. The proposed hybrid model is based on long short-term memory (LSTM) and convolutional neural network (CNN) networks where the autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroscedasticity (GARCH) outputs are used as features, along with return lags, price, and macroeconomic variables to train the models, resulting in significant improvement in the model’s performance. According to the obtained results, our proposed model performs better than other models, including artificial neural network (ANN), principal component analysis (PCA)-ANN, LSTM, and CNN. We show the efficiency of our proposed model by testing it with a simple trading strategy, indicating that the cumulative profit obtained from trading with the prediction results of the proposed 2D CNN-LSTM model is higher than those of the other models presented in this research. In the second part of this study, we consider the spread of COVID-19 and its impact on the financial markets to present a precise LSTM model that can reflect the impact of this disease on the Brent Crude Oil return. This paper uses the significance test and correlation measures to show the similarity between the series of Brent Crude Oil during the SARS and the COVID-19 pandemics, after which the data during the SARS period are used along with the data during COVID-19 to train the LSTM. The results demonstrate that the proposed LSTM model, tuned by the SARS data, can better predict the Brent Crude Oil return during the COVID-19 pandemic.
Publisher: Informa UK Limited
Date: 07-07-2022
Publisher: Elsevier BV
Date: 07-2023
Publisher: Elsevier BV
Date: 08-2022
Publisher: Elsevier BV
Date: 04-2023
Publisher: IEEE
Date: 08-10-2022
Publisher: American Society of Civil Engineers (ASCE)
Date: 08-2018
Publisher: Informa UK Limited
Date: 24-03-2022
Publisher: IEEE
Date: 04-05-2022
Publisher: Elsevier BV
Date: 03-2023
Publisher: IEEE
Date: 08-10-2022
Publisher: Informa UK Limited
Date: 13-03-2022
Publisher: IEEE
Date: 08-10-2022
Publisher: SAGE Publications
Date: 2016
DOI: 10.3141/2567-05
Abstract: To satisfy growing travel demand and reduce traffic congestion, the continuous network design problem (CNDP) is often proposed to optimize road network performance by the expansion of road capacity. In the determination of the equilibrium travel flow pattern, equilibrium principles such as deterministic user equilibrium (DUE) and stochastic user equilibrium (SUE) may be applied to describe travelers’ route choice behavior. Because of the different mathematical formulation structures for the CNDP with DUE and SUE principles, most of the existing solution algorithms have been developed to solve the CNDP for either DUE or SUE. In this study, a more general solution method is proposed by applying the generalized geometric programming (GGP) approach to obtain the global optimal solution of the CNDP with both DUE and SUE principles. Specifically, the original CNDP problem is reformulated into a GGP form, and then a successive monomial approximation method is employed to transform the GGP formulation into a standard geometric programming form, which can be cast into an equivalent nonlinear but convex optimization problem whose global optimal solution can be guaranteed and solved by many existing solution algorithms. Numerical experiments are presented to demonstrate the validity and efficiency of the solution method.
Publisher: Maximum Academic Press
Date: 2023
Publisher: MDPI AG
Date: 03-12-2021
DOI: 10.3390/FUTURETRANSP1030042
Abstract: In many big cities, train delays are among the most complained-about events by the public. Although various models have been proposed for train delay prediction, prior studies on both primary and secondary train delay prediction are limited in number. Recent advances in deep learning approaches and increasing availability of various data sources has created new opportunities for more efficient and accurate train delay prediction. In this study, we propose a hybrid deep learning solution by integrating long short-term memory (LSTM) and Critical Point Search (CPS). LSTM deals with long-term prediction tasks of trains’ running time and dwell time, while CPS uses predicted values with a nominal timetable to identify primary and secondary delays based on the delay causes, run-time delay, and dwell time delay. To validate the model and analyse its performance, we compare the standard LSTM with the proposed hybrid model. The results demonstrate that new variants outperform the standard LSTM, based on predicting time steps of dwell time feature. The experiment results also showed many irregularities of historical trends, which draws attention for further research.
Publisher: IEEE
Date: 12-2019
Publisher: Elsevier BV
Date: 03-2023
Publisher: Elsevier BV
Date: 08-2022
Publisher: ACM
Date: 04-08-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2022
Publisher: Elsevier BV
Date: 11-2021
Publisher: American Society of Civil Engineers (ASCE)
Date: 11-2018
Publisher: SAGE Publications
Date: 30-09-2023
Publisher: Springer Science and Business Media LLC
Date: 17-04-2021
Publisher: Elsevier BV
Date: 02-2023
Publisher: IEEE
Date: 08-10-2022
Publisher: American Society of Civil Engineers (ASCE)
Date: 11-2023
Publisher: American Society of Civil Engineers (ASCE)
Date: 09-2020
Publisher: Elsevier BV
Date: 11-2014
Publisher: Elsevier BV
Date: 2023
Publisher: IEEE
Date: 08-10-2022
Publisher: IEEE
Date: 19-09-2021
Publisher: Informa UK Limited
Date: 27-05-2016
Publisher: IEEE
Date: 12-2021
Publisher: Elsevier BV
Date: 2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2022
Publisher: Wiley
Date: 06-10-2021
DOI: 10.1002/PITS.22600
Abstract: School belonging is an important component of adolescent well‐being, yet little is known about its relationship with adolescents' Information Communication Technology (ICT) use. This study aimed to examine the relationship between school belonging and various ICT use types in Australian adolescents. The s le was drawn from 14,530 Australian students in Grade 7 or higher, who completed the 2015 Organization for Economic Cooperation and Development's Program for International Student Assessment survey. A hierarchical regression analysis was conducted to investigate the relationship between self‐reported measures of school belonging and ICT use at home for schoolwork and ICT use at home for leisure, adjusting for covariates (age, gender, and economic, social, and cultural status). The regression model accounted for 3% of the variability of sense of school belonging, R 2 = 0.03, F (5, 10196) = 60.00, p .001. After adjusting for covariates, more frequent ICT use at home for schoolwork predicted a higher sense of school belonging. Conversely, more frequent ICT use at home for leisure predicted lower levels of sense of school belonging. The way adolescents engage with ICT is important for a student's sense of school belonging, and the present findings have implications for researchers and psychologists.
Publisher: Informa UK Limited
Date: 19-08-2021
Start Date: 11-2022
End Date: 06-2024
Amount: $548,940.00
Funder: Australian Research Council
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