A5063060613- Sustainable Supply Chain Management
- Healthcare Operations and Scheduling Optimization
- Supply Chain and Inventory Management
- Quality and Supply Management
- Transportation Planning and Optimization
- Supply Chain Resilience and Risk Management
- Transportation and Mobility Innovations
- Manufacturing Process and Optimization
- Advanced Manufacturing and Logistics Optimization
- Urban Transport and Accessibility
- Industrial Vision Systems and Defect Detection
- Business Process Modeling and Analysis
- Metaheuristic Optimization Algorithms Research
- Vehicle Routing Optimization Methods
- Scheduling and Optimization Algorithms
- Multi-Criteria Decision Making
- Healthcare Policy and Management
- COVID-19 Pandemic Impacts
- Product Development and Customization
- Maritime Ports and Logistics
- Remote Sensing and LiDAR Applications
- Environmental Sustainability in Business
- Automated Road and Building Extraction
- Remote-Sensing Image Classification
- Health Systems, Economic Evaluations, Quality of Life
Griffith University
2022-2025
University of Technology Sydney
2017-2022
University of Wollongong
2012-2017
University Ucinf
2017
University of Warwick
2008-2015
UNSW Sydney
2015
National Institute of Advanced Manufacturing Technology
2006-2008
Detecting COVID-19 early may help in devising an appropriate treatment plan and disease containment decisions. In this study, we demonstrate how transfer learning from deep models can be used to perform detection using images three most commonly medical imaging modes X-Ray, Ultrasound, CT scan. The aim is provide over-stressed professionals a second pair of eyes through intelligent image classification models. We identify suitable <italic xmlns:mml="http://www.w3.org/1998/Math/MathML"...
Supplier evaluation and selection (SES) problems have long been studied, leading to the development of a wide range individual hybrid models for solving them. However, lack widespread diffusion existing SES in industry points need simpler that can systematically evaluate both qualitative quantitative attributes potential suppliers while enhancing flexibility decision-makers account relevant situational factors. Furthermore, empirical validations few far between. With view addressing these...
Money laundering has been a global issue for decades, which is one of the major threat economy and society. Government, regulatory financial institutions are combating it together in their respective capacity, however still billions dollars fines by authorities make headlines news. High-speed internet services have enabled to deliver better customer experience through multi-channel engagements, led exponential growth transactions new avenues money fraudsters. Literature shows usage...
Detecting COVID-19 early may help in devising an appropriate treatment plan and disease containment decisions. In this study, we demonstrate how pre-trained deep learning models can be adopted to perform detection using X-Ray images. The aim is provide over-stressed medical professionals a second pair of eyes through intelligent image classification models. We highlight the challenges (including dataset size quality) utilising current publicly available datasets for developing useful propose...
Traffic emissions are considered one of the leading causes environmental impact in megacities and their dangerous effects on human health. This paper presents a hybrid model based data mining GIS models designed to predict vehicular Carbon Monoxide (CO) emitted from traffic New Klang Valley Expressway, Malaysia. The was developed integration optimized Artificial Neural Network algorithm that combined with Correlation Feature Selection (CFS) daily CO generate prediction maps at microscale...
The demand for food delivery services (FDSs) during the COVID-19 crisis has been fuelled by consumers who prefer to order meals online and have it delivered their door than wait at a restaurant. Since many restaurants moved joined FDSs such as Uber Eats, Menulog, Deliveroo, customer reviews on internet platforms become valuable source of information about company's performance. FDS organisations strive collect complaints effectively utilise identify improvements needed enhance satisfaction....
The COVID-19 pandemic exposed the vulnerabilities of global supply chains (SCs) and highlighted need for more resilient viable SCs. Panic-buying, in particular, has been a major challenge SCs as it can create sudden surges demand that are difficult to anticipate manage. However, literature lacks SC models strategies address panic-buying related challenges. As such, this research aims identify model recovery increase SC's agility, resilience, survivability reduce panic-buying's impact during...
Terrestrial features extraction, such as roads and buildings from aerial images using an automatic system, has many usages in extensive range of fields, including disaster management, change detection, land cover assessment, urban planning. This task is commonly tough because complex scenes, where road objects are surrounded by shadows, vehicles, trees, etc., which appear heterogeneous forms with lower inter-class higher intra-class contrasts. Moreover, extraction time-consuming expensive to...