Hua Wang

Hua Wang
Victoria University Melbourne | VU · Applied Informatics Research Centre

PhD

About

319
Publications
66,687
Reads
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6,117
Citations
Citations since 2016
161 Research Items
5128 Citations
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Introduction

Publications

Publications (319)
Article
Full-text available
Motor disability affects a person's ability to move and maintain balance. To remove this pain from the society, brain computer interface (BCI) system with the assistance of motor imagery (MI) tasks classification plays an important role. BCI translates human intension by brain activity into control signals to communicate with their external environ...
Preprint
Full-text available
There has been a significant increase in the adoption of technology in cricket recently. This trend has created the problem of duplicate work being done in similar computer vision-based research works. Our research tries to solve one of these problems by segmenting ball deliveries in a cricket broadcast using deep learning models, MobileNet and YOL...
Article
Full-text available
The diagnosis of neurological diseases is one of the biggest challenges in modern medicine, which is a major issue at the moment. Electroencephalography (EEG) recordings is usually used to identify various neurological diseases. EEG produces a large volume of multi-channel time-series data that neurologists visually analyze to identify and understa...
Chapter
Due to the expanding requirements for data publishing and growing concerns regarding data privacy, the privacy-preserving data publishing (PPDP) problem has received considerable attention from research communities, industries, and governments. However, it is challenging to tackle the trade-off between privacy preservation and data quality maintena...
Chapter
Mild Cognitive Impairment (MCI) and Alzheimer’s diseases (AD) are two common neurodegenerative disorders which belong to the dementia family mostly found in elders. There is evidence that MCI may lead to Alzheimer’s disease. Since there is no treatment for AD after it has been diagnosed, it is a significant public health problem in the twenty-first...
Article
The outsourced distributed database is frequently used to tackle the large amounts of data in various smart city scenarios. The data partition technique is a significant research topic in the outsourced distributed database because it can directly affect the database performance in data exchange and sharing. Multiple objectives, including communica...
Chapter
The future of neuro-science lies in Electroencephalography (EEG). EEG is the latest gold standard for diagnosing most neurological disorders like dementia, mild cognitive impairment (MCI), Alzheimer’s diseases, and so on. It is a cheap, portable and non-invasive option to discover neuro-disorders compared to the remaining expensive and time consumi...
Chapter
Mining large scale brain signal data using artificial intelligence offers an unparalleled chance to investigate the dynamics of the brain in neurological disorders diagnosis. Electroencephalography (EEG) produces a multi-channel time-series large scale brain signal data recorded from scalp and visually analyzed by expert clinicians for abnormality...
Chapter
The modern commercial industry is increasingly dependent on the analysis of vast data records. Analysing big electroencephalogram (EEG) signal data (called brain signal data) plays an important role in a wide variety of applications such as healthcare practices, brain computer interface (BCI) systems, innovative education, privacy and security, and...
Chapter
Full-text available
Data, as one of the most valuable assets for both individuals and companies in the digital age, is increasingly exposed to the threat of cyberattacks caused by software vulnerabilities. A major application in cybersecurity is software vulnerability assessment and management, which is the fundamental and systematic review process to identify the sev...
Article
Detecting mild cognitive impairment (MCI) from electroencephalography (EEG) data is a challenging problem as existing methods rely on machine learning based shallow architectures that are unable to successfully uncover relevant biomarkers from deep hidden layers of data. This study will design a deep learning-based framework including a Gated Recur...
Article
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Knowledge graph, as an extension of graph data structure, is being used in a wide range of areas as it can store interrelated data and reveal interlinked relationships between different objects within a large system. This paper proposes an algorithm to construct an access control knowledge graph from user and resource attributes. Furthermore, an on...
Article
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We offer a framework for automatically and accurately segmenting breast lesions from Dynamic Contrast Enhanced (DCE) MRI in this paper. The framework is built using max flow and min cut problems in the continuous domain over phase preserved denoised images. Three stages are required to complete the proposed approach. First, post-contrast and pre-co...
Article
Distributed differential evolution (DDE) is an efficient paradigm that adopts multiple populations for cooperatively solving complex optimization problems. However, how to allocate fitness evaluation (FE) budget resources among the distributed multiple populations can greatly influence the optimization ability of DDE. Therefore, this article propos...
Article
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Evolutionary multi-objective multi-task optimization is an emerging paradigm for solving multi-objective multi-task optimization problem (MO-MTOP) using evolutionary computation. However, most existing methods tend to directly treat the multiple multi-objective tasks as different problems and optimize them by different populations, which face the d...
Article
Full-text available
The COVID-19 epidemic has a catastrophic impact on global well-being and public health. More than 27 million confirmed cases have been reported worldwide until now. Due to the growing number of confirmed cases, and challenges to the variations of the COVID-19, timely and accurate classification of healthy and infected patients is essential to contr...
Article
Full-text available
Database fragmentation has been used as a protection mechanism of database’s privacy by allocating attributes with sensitive associations into separate data fragments. A typical relational database consists of multiple relations. Thus, fragmentation process is applied to each relation separately in a sequential manner. In other words, the existing...
Article
Full-text available
Exploitation time is an essential factor for vulnerability assessment in cybersecurity management. In this work, we propose an integrated consecutive batch learning framework to predict the probable exploitation time of vulnerabilities. To achieve a better performance, we combine features extracted from both vulnerability descriptions and the Commo...
Article
Mild cognitive impairment (MCI) is an irreparable progressive neuro-degenerative disorder, which seems to be a precursor to Alzheimer's disease (AD) that may lead to dementia in elderly people. It is a major public health challenge for healthcare in the 21st century. Because there is no curative or therapy to halt or reverse the course of MCI, earl...
Article
Co-exploitation behaviour, referring to multiple software vulnerabilities being exploited jointly by one or more exploits, brings enormous challenges to the prevention and remediation of cyber-attacks. Leveraging the latest advances in graph-driven intelligence, this paper formulates vulnerability co-exploitation behaviour discovery as a link predi...
Article
Full-text available
Diabetic eye disease (DED) is a cluster of eye problem that affects diabetic patients. Identifying DED is a crucial activity in retinal fundus images because early diagnosis and treatment can eventually minimize the risk of visual impairment. The retinal fundus image plays a significant role in early DED classification and identification. An accura...
Article
Full-text available
By breaking sensitive associations between attributes, database fragmentation can protect the privacy of outsourced data storage. Database fragmentation algorithms need prior knowledge of sensitive associations in the tackled database and set it as the optimization objective. Thus, the effectiveness of these algorithms is limited by prior knowledge...
Chapter
In this work, we propose a framework for the automatic and accurate segmentation of breast lesions from the Dynamic Contrast Enhanced (DCE) MRI. The framework is built using max flow and min cut problems in the continuous domain over phase preserved denoised images. The proposed method is achieved via three steps. First, post-contrast and pre-contr...
Article
Exploitability prediction has become increasingly important in cybersecurity, as the number of disclosed software vulnerabilities and exploits are soaring. Recently, machine learning and deep learning algorithms, including Support Vector Machine (SVM), Decision Tree, deep Neural Networks and their ensemble models, have achieved great success in vul...
Article
Automated classification of an epileptic seizure is very crucial for efficient diagnosis and treatment management in the health monitoring applications. Finding traces of epilepsy through the visual marking of long Electroencephalogram (EEG) recordings by human experts is a very tedious, time-consuming and high-cost task. It is always a challenging...
Article
Database fragmentation can protect the distributed database’s privacy by dividing attributes of sensitive associations into different fragments. Previous database fragmentation algorithms are designed for the initialization of the distributed database. However, the initial database fragmentation cannot maintain its effect during the distributed dat...
Article
Full-text available
Autism spectrum disorder (ASD) is a developmental disability characterized by persistent impairments in social interaction, speech and nonverbal communication, and restricted or repetitive behaviors. Currently Electroencephalography (EEG) is the most popular tool to inspect the existence of neurological disorders like autism biomarkers due to its l...
Article
Helpfulness prediction techniques have been widely incorporated into online decision support systems to identify high-quality reviews. Most current studies on helpfulness prediction assume that a review's helpfulness only relies on information from itself. In practice, however, consumers hardly process reviews independently because reviews are disp...
Article
Full-text available
A new class of link flooding attacks (LFA) can cut off internet connections of target links by employing legitimate flows to congest these without being detected. LFA is especially powerful in disrupting traffic in software-defined networks if the control channel is targeted. Most of the existing solutions work by conducting a deep packet-level ins...
Preprint
Full-text available
The COVID-19 epidemic appears to have a catastrophic impact on global well-being and public health. More than 10 million confirmed cases have been reported worldwide until now. Due to the growing number of confirmed cases, timely and accurate classification of healthy and infected patients is essential to control and treat COVID-19. To this end, in...
Article
Epilepsy is one of the most chronic brain disorder recorded from since 2000 BC. Almost one-third of epileptic patients experience seizures attack even with medicated treatment. The menace of SUDEP (Sudden unexpected death in epilepsy) in an adult epileptic patient is approximately 8-17% more and 34% in a children epileptic patient. The expert neuro...
Chapter
Analysis of brain signal data like Electroencephalography (EEG) plays an important role in efficient diagnosis of neurological disorders and treatment. EEG records electrical activity of the brain and contains huge volume of multi-channel time-series data that are visually analyzed by neurologists to identify abnormalities within the brain, which i...
Chapter
Access control is an effective way to prevent data exfiltration from insiders. Recently, machine learning algorithms have been widely used in access control decision-making. However, these algorithms usually fail to consider the dynamic class imbalance in access control problems and thus achieve poor performance on minority classes. In addition, co...
Chapter
Electroencephalography (EEG) contribute a leading role in brain studies, mental and brain diseases and disorders diagnosis, and treatments. Traditional Machine Learning (TML) approaches are employed in most of the recent efforts in identifying the anomalies from EEG data. But their shallowed architecture is one of the reasons why they fail to detec...
Article
Full-text available
Data privacy and utility are two essential requirements in outsourced data storage. Traditional techniques for sensitive data protection, such as data encryption, affect the efficiency of data query and evaluation. By splitting attributes of sensitive associations, database fragmentation techniques can help protect data privacy and improve data uti...
Article
Location-based social networks such as Swarm provide a rich source of information on human behaviour and urban functions. Our analysis of data created by users who voluntarily used check-ins with a mobile application can give insight into a user’s mobility and behaviour patterns. In this study, we used location-sharing data from Swarm to explore sp...
Chapter
The privacy of Electronic Health Records is facing a major issue while outsourcing data in the cloud or sharing the records among stakeholders which includes the leakage of private and sensitive information to unauthorized entities. This research mainly focuses on introducing an efficient referral mechanism employing advanced smart contracts for th...
Article
Full-text available
Epilepsy is a serious neurological condition which contemplates as top 5 reasons for avoidable mortality from ages 5–29 in the worldwide. The avoidable deaths due to epilepsy can be reduced by developing efficient automated epilepsy detection or prediction machines or software. To develop an automated epilepsy detection framework, it is essential t...
Article
Full-text available
Australian My Health Record (MyHR) is a significant development in empowering patients, allowing them to access their summarised health information themselves and to share the information with all health care providers involved in their care. Consequently, the MyHR system must enable efficient availability of meaningful, accurate, and complete data...
Article
Full-text available
Diabetic eye disease is a collection of ocular problems that affect patients with diabetes. Thus, timely screening enhances the chances of timely treatment and prevents permanent vision impairment. Retinal fundus images are a useful resource to diagnose retinal complications for ophthalmologists. However, manual detection can be laborious and time-...
Chapter
Recent works on open-domain question answering (QA) rely on retrieving related passages to answer questions. However, most of them can not escape from sub-optimal initial retrieval results because of lacking interaction with the retrieval system. This paper introduces a new framework MSReNet for open-domain question answering where the question ref...
Chapter
Exploitation analysis is vital in evaluating the severity of software vulnerabilities and thus prioritizing the order of patching. Although a few methods have been proposed to predict the exploitability of vulnerabilities, most of them treat this problem as an offline binary classification problem. To suit the real-world data stream applications an...
Chapter
Full-text available
Vertical fragmentation is a promising technique for outsourced data storage. It can protect data privacy while conserving original data without any transformation. Previous vertical fragmentation approaches need to predefine sensitive associations in data as the optimization objective, therefore unavailable for the data lacking related prior knowle...
Article
Most of the traditional alcoholism detection methods are developed based on machine learning based methods that cannot extract the deep concealed characteristics of Electroencephalogram (EEG) signals from different layers. Hence, this study aims to introduce a deep leaning-based method that can automatically identify alcoholic EEG signals. It also...
Article
Diagnosis of schizophrenia (SZ) is traditionally performed through patient’s interviews by a skilled psychiatrist. This process is time-consuming, burdensome, subject to error and bias. Hence the aim of this study is to develop an automatic SZ identification scheme using electroencephalogram (EEG) signals that can eradicate the aforementioned...
Article
Full-text available
Link Flooding Attacks (LFA) are a devastating type of stealthy denial of service attack that congests critical network links and can completely isolate the victim's network. In this work, we present a systematic survey of LFA patterns on all the layers of the Software Defined Network (SDN) ecosystem, along with a comparative analysis of mitigation...
Article
Full-text available
Cardiac arrhythmia has been identified as a type of cardiovascular diseases (CVDs) that causes approximately 12% of all deaths globally. The development of Internet-of-Things has spawned novel ways for heart monitoring but also presented new challenges for manual arrhythmia detection. An automated method is highly demanded to provide support for ph...
Article
Full-text available
Review helpfulness prediction aims to prioritize online reviews by quality. Existing methods largely combine review texts and star ratings for helpfulness prediction. However, star ratings are used in a way that has either little representation capacity or limited interaction with review texts. As a result, rating information has yet to be fully ex...
Article
Full-text available
Diabetes Mellitus, or Diabetes, is a disease in which a person’s body fails to respond to insulin released by their pancreas, or it does not produce sufficient insulin. People suffering from diabetes are at high risk of developing various eye diseases over time. As a result of advances in machine learning techniques, early detection of diabetic eye...
Article
Mild cognitive impairment (MCI) can be an indicator representing the early stage of Alzheimier's disease (AD). AD, which is the most common form of dementia, is a major public health problem worldwide. Efficient detection of MCI is essential to identify the risks of AD and dementia. Currently Electroencephalography (EEG) is the most popular tool to...
Preprint
Helpfulness prediction techniques have been widely used to identify and recommend high-quality online reviews to customers. Currently, the vast majority of studies assume that a review's helpfulness is self-contained. In practice, however, customers hardly process reviews independently given the sequential nature. The perceived helpfulness of a rev...
Chapter
Heart arrhythmia is a severe heart problem. Automated heartbeat classification provides a cost-effective screening for heart arrhythmia and allows at-risk patients to receive timely treatments, which is a highly demanded but challenging task. Recent works have brought visible improvements to this area, but to identify the problematic supraventricul...
Chapter
Diabetes is a life-threatening disease that affects various human body organs, including eye retina. Advanced Diabetic Eye disease (DED) leads to permanent vision loss, thus an early detection of DED symptoms is essential to prevent disease escalation and timely treatment. Up till now, research challenges in early DED detection can be summarised as...
Article
Full-text available
Due to the popularity of Web-based applications, various developers have provided an abundance of Web services with similar functionality. Such similarity makes it challenging for users to discover, select, and recommend appropriate Web services for the service-oriented systems. Quality of Service (QoS) has become a vital criterion for service disc...