Raymond Chiong

Raymond Chiong
The University of Newcastle, Australia · School of Electrical Engineering and Computing

About

218
Publications
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3,874
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Publications

Publications (218)
Article
Mechanisms promoting the evolution of cooperation in two players and two strategies (22) evolutionary games have been investigated in great detail over the past decades. Understanding the effects of repeated interactions in multiplayer spatial games, however, is a formidable challenge. In this paper, we present a multiplayer evolutionary game model...
Article
Full-text available
Trust and trustworthiness are of great importance in social and human systems, especially when considering managerial and economic decision-making. In this paper, we investigate the emergent dynamics of an evolutionary game-theoretic model – the N-player evolutionary trust game – consisting of three types of players: an investor, a trustee who is t...
Article
We study the impact of climate change induced migration on the evolution of cooperation using an N-player social dilemma game. Players in the population are divided into non-overlapped groups, and they can choose to either cooperate or defect within their group. At the same time, the players are mapped to the nodes of a scale-free network, enabling...
Article
Background and Objective: The term ‘obesity’ refers to excessive body fat, and it is a chronic disease associated with various complications. Although a range of techniques for body fat estimation have been developed to assess obesity, they are typically associated with high-cost tests requiring special equipment. Accurate prediction of the body fa...
Article
Machine on/off control is an effective way to achieve energy-efficient production scheduling. Turning off machines and restarting them frequently, however, would incur a considerable amount of additional energy and may even cause damage to the machines. In this paper, we propose a mathematical model based on the energy-efficient flexible job shop s...
Article
Full-text available
We present an evolutionary game model that integrates the concept of tags, trust and migration to study how trust in social and physical groups influence cooperation and migration decisions. All agents have a tag, and they gain or lose trust in other tags as they interact with other agents. This trust in different tags determines their trust in oth...
Article
Accurate identification of malicious web domains is crucial for protecting users from the risks of theft of private information, malware attack, and monetary loss. Various methods, including blacklist and machine learning-based models, have been proposed to identify malicious web domains effectively. However, maintaining an up-to-date blacklist is...
Article
While previous research established that culture plays an important role in technology adoption, there is only limited work on the role of cultural appropriateness in user interface design for users from a specific background. In this study, we focus on the case of avatar design as a user interface element for facilitating positive user experience....
Article
Mobile-based health (mHealth) systems are proving to be a popular alternative to the traditional visits to healthcare providers. They can also be useful and effective in fighting the spread of infectious diseases, such as the COVID-19 pandemic. Even though young adults are the most prevalent mHealth user group, the relevant literature has overlooke...
Article
Facial expression recognition (FER) is an active research area that has attracted much attention from both academics and practitioners of different fields. In this paper, we investigate an interesting and challenging issue in FER, where the training and testing samples are from a cross-domain dictionary. In this context, the data and feature distri...
Article
Full-text available
Obesity, associated with having excess body fat, is a critical public health problem that can cause serious diseases. Although a range of techniques for body fat estimation have been developed to assess obesity, these typically involve high-cost tests requiring special equipment. Thus, the accurate prediction of body fat percentage based on easily...
Chapter
While the elderly population is growing rapidly, acceptance and use of m-government services by them are far below expectation. Previous studies on acceptance and use of m-government services have predominantly focused on younger citizens with skills and experience of information technologies. Drawing upon the dual factor model, this study investig...
Article
Full-text available
Obesity is a critical public health problem associated with various complications and diseases. Accurate prediction of body fat is crucial for diagnosing obesity. Various measurement methods, including underwater weighing, dual energy X-ray absorptiometry, bioelectrical impedance analysis, magnetic resonance imaging, air displacement plethysmograph...
Article
Increasing energy shortages and environmental pollution have made energy efficiency an urgent concern in manufacturing plants. Most studies looking into sustainable production in general and energy-efficient production scheduling in particular, however, have not paid much attention to logistical factors (e.g., transport and setup). This study integ...
Conference Paper
Abstract—Predicting student performance and identifying under-performing students early is the first step towards helping students who might have difficulties in meeting learning outcomes of a course resulting in a failing grade. Early detection in this context allows educators to provide appropriate interventions sooner for students facing challen...
Conference Paper
Abstract—This paper presents a novel framework aimed at improving educational outcomes in tertiary-level courses. The framework integrates concepts from educational data mining, learning analytics and education research domains. The framework considers the entire life cycle of courses and includes processes and supporting technology artefacts. Well...
Article
In this paper, we propose a novel hybrid fuzzy–metaheuristic approach with the aim of overcoming premature convergence when solving multimodal single and multi-objective optimization problems. The metaheuristic algorithm used in our proposed approach is based on the imperialist competitive algorithm (ICA), a population-based method for optimization...
Article
Numerous studies on mental depression have found that tweets posted by users with major depressive disorder could be utilized for depression detection. The potential of sentiment analysis for detecting depression through an analysis of social media messages has brought increasing attention to this field. In this article, we propose 90 unique featur...
Article
Full-text available
The interior search algorithm (ISA) is an optimization algorithm inspired by esthetic techniques used for interior design and decoration. The algorithm has only one parameter, controlled by θ, and uses an evolutionary boundary constraint handling (BCH) strategy to keep itself within an admissible solution space while approaching the optimum. We app...
Article
This paper studies an important extension of energy-efficient production scheduling research, where machine on/off control and machine maintenance are considered simultaneously. The inspiration of this extension is that a machine must be turned off if it needs to be maintained, and an already-turned-off machine can be maintained without needing to...
Article
We present an evolutionary trust game to investigate the formation of trust in sharing economy situations, where participants have a fixed provider or consumer role, and can only choose between trustworthy or untrustworthy behaviour. There are a variety of sharing economy platforms catering for differing goods and services, the properties of which...
Chapter
Over 300 million people worldwide were suffering from depression in 2017. Australia alone invests more than $9.1 billion each year on mental health related services. Traditional intervention methods require patients to first present with symptoms before diagnosis, leading to a reactive approach. A more proactive approach to this problem is highly d...
Article
Malicious web domains represent a serious threat to online users’ privacy and security, causing monetary loss, theft of private information, and malware attacks, among others. In recent years, machine learning methods have been widely used as prediction models to identify malicious web domains. In this study, we propose a Fuzzy-Weighted Least Squar...
Article
Background Alzheimer’s disease (AD) is one of the deadliest diseases in developed countries. Treatments following early AD detection can significantly delay institutionalisation and extend patients’ independence. There has been a growing focus on early AD detection using artificial intelligence. Convolutional neural networks (CNNs) have proven revo...
Article
This paper presents an effective multi-objective Jaya (EMOJaya) algorithm to solve a multi-objective job-shop scheduling problem, aiming to simultaneously minimise the makespan, total flow time and mean tardiness. A strategy based on grey entropy parallel analysis (GEPA) is developed to assess and select solutions during the search process. To obta...
Article
This article presents a new model to handle the cast break problem caused by small daily disruptions in the processing time of the steelmaking and continuous casting (SCC) production process. In this model, the exact distribution of the uncertain parameters is unknown, and support set, mean, and covariance information is used to describe the uncert...
Article
This paper presents a computational evolutionary game model to study and understand fraud dynamics in the consumption tax system. Players are cooperators if they correctly declare their value added tax (VAT), and are defectors otherwise. Each player's payoff is influenced by the amount evaded and the subjective probability of being inspected by tax...
Article
Depression is one of the leading causes of suicide worldwide. However, a large percentage of cases of depression go undiagnosed and, thus, untreated. Previous studies have found that messages posted by individuals with major depressive disorder on social media platforms can be analysed to predict if they are suffering, or likely to suffer, from dep...
Article
Automatic human affect recognition is a key step towards more natural human-computer interaction. Recent trends include recognition in the wild using a fusion of audiovisual and physiological sensors, a challenging setting for conventional machine learning algorithms. Since 2010, novel deep learning algorithms have been applied increasingly in this...
Article
Full-text available
Fraudulent online sellers often collude with reviewers to garner fake reviews for their products. This act undermines the trust of buyers in product reviews, and potentially reduces the effectiveness of online markets. Being able to accurately detect fake reviews is, therefore, critical. In this study, we investigate several preprocessing and textu...
Article
New energy vehicles (NEVs) are welcomed by both policymakers and consumers because of their energy saving and low carbon properties. However, due to their high production cost and limited cruising range, the development of the NEV industry relies heavily on governments’ cash subsidy (CS) programs. At the same time, policymakers in several countries...
Article
The financial impact of positive reviews has prompted some fraudulent sellers to generate fake product reviews for either promoting their products or discrediting competing products. Many e-commerce portals have implemented measures to detect such fake reviews, and these measures require excellent detectors to be effective. In this work, we propose...
Article
Energy-efficient production scheduling research has received much attention because of the massive energy consumption of the manufacturing process. In this paper, we study an energy-efficient job-shop scheduling problem with sequence-dependent setup time (EJSP-SDST), aiming to minimize the makespan, total tardiness and total energy consumption simu...
Article
Full-text available
Recent large-scale migration flows from rural areas of the Mekong Delta (MKD) to larger cities in the South-East (SE) region of Vietnam have created the largest migration corridor in the country. This migration trend has further contributed to greater rural–urban disparities and widened the development gap between regions. In this study, our aim is...
Preprint
Full-text available
This paper presents a computational evolutionary game model to study and understand fraud dynamics in the consumption tax system. Players are cooperators if they correctly declare their value added tax (VAT), and are defectors otherwise. Each player's payoff is influenced by the amount evaded and the subjective probability of being inspected by tax...
Article
Online reviews are becoming increasingly important for decision-making. Consumers often refer to online reviews for opinions before making a purchase. Marketers also acknowledge the importance of online reviews and use them to improve product success. However, the massive amount of online review data, as well as its unstructured nature, is a challe...
Article
Full-text available
Ensemble learning is increasingly used in sentiment analysis. Determining the parameter settings of ensemble models, however, is not easy. Besides its own parameters, an ensemble model has base-predictors that have their individual parameters. Some ensemble models use a specific base-predictor and could be optimised using standard metaheuristics su...
Article
Purpose The aim of this study is to propose an efficient rule extraction and integration approach for identifying phishing websites. The proposed approach can elucidate patterns of phishing websites and identify them accurately. Design/methodology/approach Hyperlink indicators along with URL-based features are used to build the identification mode...
Article
Optimization techniques have drawn much attention for solving geotechnical engineering problems in recent years. Particle swarm optimization (PSO) is one of the most widely used population-based optimizers with a wide range of applications. In this paper, we first provide a detailed review of applications of PSO on different geotechnical problems....
Article
This paper presents a symbiotic organism search (SOS)-based support vector regression (SVR) ensemble for predicting the printed circuit board (PCB) cycle time of surface-mount-technology (SMT) production lines. Being able to predict the PCB cycle time accurately is essential for optimizing the SMT production schedule. Although a machine simulator c...
Article
External factors, such as increasing environmental awareness among consumers and introduction of environmental regulations by governments, have stimulated manufacturers to produce new green products. Cost factors, on the other hand, encourage the continuation of older generation products and hinder the launch of new green products. To study this di...
Article
While the elderly population is growing rapidly, acceptance and use of m-government services by them are far below expectation. Previous studies on acceptance and use of m-government services have predominantly focused on younger citizens with skills and experience of information technologies. Drawing upon the dual factor model, this study investig...
Article
Full-text available
The classical distributed production scheduling problem (DPSP) assumes that factories are identical, and each factory is composed of just some machines. Inspired by the fact that manufacturers these days typically work across different factories, and each of these factories normally has some workshops, we study an important extension of the DPSP wi...
Article
Conventional feature extraction methods generally focus on extracting global and local features from the original data or converting a high dimensional space to a lower dimensional one. However, they tend to overlook the discriminative information of pixel values hidden in the original data. Pixel values in some local parts of a face, such as the m...
Article
While avatars are frequently employed as a user interface (UI) element for improving user experience in human-computer interaction, the current design of avatars is primarily dominated by non-Arabian cultures. To the best of our knowledge, no previous research or guidelines (based on empirical evidence) can be found for avatar design in the context...
Article
Full-text available
Recent research has shown that the deep subspace learning (DSL) method can extract high-level features and better represent abstract semantics of data for facial expression recognition. While significant advances have been made in this area, traditional sparse representation classifiers or collaborative representation classifiers are still predomin...
Article
Concrete is one of the most commonly used construction materials in civil engineering. Being able to accurately predict concrete components based on concrete strength, slump and flow is crucial for saving manpower and financial resources. The reverse prediction nature of this task, however, makes it a very difficult problem to solve. Relative error...
Article
Fuzzy systems are widely used for solving complex and non-linear problems that cannot be addressed using precise mathematical models. Their performance, however, is critically affected by how they are constructed as well as their fuzzy rule base. Inspired by neural networks that apply a multi-layer structure to improve their performance, we propose...
Article
Full-text available
Dyeing is the most time and energy-consuming process in textile production. Motivated by a dyeing overdue problem in a lace textile factory, we study a parallel machine scheduling problem with different color families, sequence-dependent setup times, and machine eligibility restriction. An integer programming model is formulated to minimize the tot...
Article
Full-text available
Drought is a natural phenomenon that can have prolonged and widespread impacts on many communities and environments. The impact of climate change on drought is uncertain, which makes it challenging to quantify how future droughts will impact on society. This study uses downscaled rainfall data from four global climate models (GCMs) and two time win...
Article
This paper focuses on an energy-efficient job-shop scheduling problem within a machine speed scaling framework, where productivity is affected by deterioration. To alleviate the deterioration effect, necessary maintenance activities must be put in place during the scheduling process. In addition to sequencing operations on machines, the problem at...
Article
Due to severe congestion before the Three Gorges Dam, roll-on/roll-off and container carriers are encouraged to adopt water-land transshipment mode. Owing to high transit and road costs, however, carriers are reluctant to adopt this mode. In this paper, we study the spatial-temporal relationship between the transshipment mode and the transshipment...
Article
Full-text available
In this paper, we present an evolutionary trust game, taking punishment and protection into consideration, to investigate the formation of trust in the so-called sharing economy from a population perspective. This sharing economy trust model comprises four types of players: a trustworthy provider, an untrustworthy provider, a trustworthy consumer,...
Article
Purpose Despite the widespread use of mobile government (m-government) services in developed countries, the adoption and acceptance of m-government services among citizens in developing countries is relatively low. The purpose of this study is to explore the most critical determinants of acceptance and use of m-government services in a developing c...
Article
With the no-idle constraint, a machine has to process a job after finishing the previous one without any interruption. The start time of the first job on each machine must thus be delayed to meet this condition. In this paper, a new Iterated Greedy Algorithm (IGA) is presented for no-idle flowshop scheduling with the objective of minimizing the tot...
Article
Alzheimer's Disease (AD) is one of the leading causes of death in developed countries. From a research point of view, impressive results have been reported using computer-aided algorithms, but clinically no practical diagnostic method is available. In recent years, deep models have become popular, especially in dealing with images. Since 2013, deep...
Article
Computerised graphical representations of human users and computer agents, known as avatars and embodied agents, have been extensively explored and investigated in Information Systems (IS) research and practice. Such digital representations can be employed in either 2D or 3D. In order to facilitate research on user and agent representations and the...
Article
Predicting adsorption energies of reaction intermediates is critical for determining catalytic reaction mechanisms. Here, we present three combined representations for predicting adsorption energies of carbon reforming species on transition metal surfaces. Among the three combined representations, the Elemental Properties and Spectral London Axilro...
Article
The traditional flexible job shop scheduling problem (FJSP) considers machine flexibility but not worker flexibility. Given the influence and potential of human factors in improving production efficiency and decreasing the cost in practical production systems, we propose a mathematical model of an extended FJSP with worker flexibility (FJSPW). A hy...
Article
Remanufacturing has attracted much attention in recent years because of its potential to achieve sustainable production. Due to low consumer acceptance, however, the market size of remanufactured products remains small. There are different ways to promote remanufacturing, two of which being providing cash subsidy and imposing carbon regulation. Cas...
Article
The classical flexible flow shop scheduling problem (FFSP) only considers machine flexibility. Thus far, the relevant literature has not studied FFSPs with worker flexibility, which is widely seen in practical manufacturing systems. Worker flexibility may greatly affect production efficiency and productivity. Furthermore, with the increase of envir...
Article
This paper investigates the ability of a combined buy-back (BB) and revenue sharing (RS) contract to improve the efficiency of a supply chain involving a risk-neutral supplier and a risk-averse retailer facing stochastic demand. We show that the combined contract can coordinate the supply chain under mild conditions. Further, the effects of risk av...
Article
This paper presents an effective memetic algorithm (EMA) to solve the multi-objective job shop scheduling problem. A new hybrid crossover operator is designed to enhance the search ability of the proposed EMA and avoid premature convergence. In addition, a new effective local search approach is proposed and integrated into the EMA to improve the sp...
Article
Remanufacturing has been widely studied for its potential to achieve sustainable production in recent years. In the literature of remanufacturing research, process planning and scheduling are typically treated as two independent parts. However, these two parts are in fact interrelated and often interact with each other. Doing process planning witho...
Article
Full-text available
In this paper, we use agent-based modeling (ABM) to study different obstacles to the expansion of contract rice farming in the context of Mekong Delta (MKD)'s rice supply chain. ABM is a bottom-up approach for modeling the dynamics of interactions among individuals and complex combinations of various factors (e.g., economic, social or environmental...