
Dhiya Al-Jumeily Obe- Doctor of Philosophy
- Professor at Liverpool John Moores University
Dhiya Al-Jumeily Obe
- Doctor of Philosophy
- Professor at Liverpool John Moores University
About
377
Publications
137,677
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
5,625
Citations
Introduction
Al-Jumeily has extensive research interests covering a wide variety of interdisciplinary perspectives concerning the theory and practice of Applied Artificial Intelligence in medicine, human biology, environment, intelligent community and health care. He has published well over 300 peer reviewed scientific international publications, 12 books and 14 book chapters, in multidisciplinary research area
Skills and Expertise
Current institution
Publications
Publications (377)
Person de-identification has become a challenging problem that is receiving substantial attention because of the growing demand for privacy protection and related regulations. In this context, computer vision and Deep Learning (DL) algorithms offer automated solutions for Face de-identification (FDeID), commonly used to conceal personal identities...
Hallucinogenic new psychoactive substances have been rapidly emerging due to the increasing use of the Internet as a marketplace and source of information. This study explores hallucinogenic new psychoactive substances’ profile, effects and toxicity from the perspectives of e-psychonauts by conducting content analysis of online discussion forums. Q...
Accurate inflow forecasting is an essential non-engineering strategy to guarantee flood management and boost the effectiveness of the water supply. As inflow is the primary reservoir input, precise inflow forecasting may also offer appropriate reservoir design and management assistance. This study aims to generalize the machine learning model using...
Background
Commonly heard statements such as “Christmas comes around more quickly each year” suggest that the passage of time between annual events can become distorted, leading to the sensation of time passing more quickly than normal. At present however, it is unclear how prevalent such beliefs are and, what factors are predictive of it.
Aim
To...
The article outlines the personality of a student as the single channel through which knowledge flows within the cognitive theory of “learning”. This sustainable process is the means of mediating the thought activity of an individual in a higher school. The study estimates personal qualities of a student through the capacity for self-organization,...
Aims
To perform a systematic review of studies that sought to identify diagnostic biomarkers for the diagnosis of cardiovascular diseases (CVDs) and diabetes mellitus (DM), which could be used in low‐ and middle‐income countries (LMICs) where there is a lack of diagnostic equipment, treatments and training.
Materials and Methods
Papers were source...
Corporate bankruptcy is a global issue that has increased over the last few years. Due to lack of adequate historical data, current models have not been able to correctly predict cases of bankruptcy. This research proposed a composite procedure at four stages which includes pre-processing and data rebalancing methods to curate the data, perform fea...
E-commerce industry has become more popular over the last 20 years with the increased popularity of the Internet. Thus, the Internet facilitated retail for individuals who are able to order products online that get delivered to their own home. This made users’ experience crucial in e-commerce industry. In order to understand users’ experience and i...
Cardiovascular disease (CVDs) has been perceived as a ‘man’s disease’, and this impacted women’s referral to CVD diagnosis and treatment. This study systematically reviewed the evidence regarding gender bias in the diagnosis, prevention, and treatment of CVDs. Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines we...
The early diagnosis of Alzheimer’s disease (AD) presents a significant challenge due to the subtle biomarker changes often overlooked. Machine learning (ML) models offer a promising tool for identifying individuals at risk of AD. However, current research tends to prioritize ML accuracy while neglecting the crucial aspect of model explainability. T...
According to the World Health Organisation (WHO), stroke is the leading cause of death and the third cause of disability globally. Many factors play a role in stroke incidences that are related to the healthcare system, medicines, patients and lifestyle. Although these factors could be modifiable or not, modifiable risk factors are more prevalent e...
The Smart Grid is a modern power grid that relies on advanced technologies to provide reliable and sustainable electricity. However, its integration with various communication technologies and IoT devices makes it vulnerable to cyber-attacks. Such attacks can lead to significant damage, economic losses, and public safety hazards. To ensure the secu...
This study aimed to explore the role of artificial intelligence (AI) in predicting perinatal outcomes among women with COVID-19. Data was collected from hospitals in the Middle Euphrates and Southern regions of Iraq, with 152 pregnant patients included in the study. Patients were categorized into mild and severe infection groups, and their serum sa...
background: The COVID-19 pandemic has had a significant impact on global health, requiring a comprehensive understanding of its regional dynamics for effective management and response strategies. This study aimed to explore the demographics, risk factors, and post-COVID-19 syndrome among patients in the Middle Euphrates region of Iraq. Methods: A t...
Background: This study aimed to explore the correlation between Vitamin D3 levels and IFN-Gamma expression in children residing in the southern and central provinces of Iraq. Vitamin D3 plays a pivotal role in immune function, and IFN-Gamma is a crucial cytokine involved in antiviral defense. Investigating the connection between Vitamin D3 and IFN-...
The issue of complex sources, difficult to understand and share security threat intelligence, this paper realizes deep learning of threat intelligence features based on Restricted Boltzmann Machine, which graphs the original threat intelligence features from high dimensional space to low dimensional space layer by layer, and constructs the cyberspa...
BACKGROUND
Using microalgae for wastewater treatment offers an environmentally friendly method to produce microalgal biomass that can be used for many applications. However, the biochemical characteristics of microalgal biomass vary from species to species, from strain to strain, and between different growth stages within the same species/strain. T...
Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FT-IR) provides portable and rapid analysis of biomarkers and drugs within fingernails. Fingernails offer a suitable alternative to traditional biological matrices and provide advantages such as non-invasive collection and requiring small sample sizes. This work utilized ATR-...
Abstract: (129 Views)
The COVID-19 pandemic has led to the global distribution of vaccines, but there are concerns regarding potential side effects. Hair loss is one of the less commonly reported side effects. The purpose of this research is to examine whether or not vaccination against COVID-19 is linked to an increased risk of baldness in urban d...
Almost all signals existing in the universe experience varying degrees of noise interference. Specifically, audio signals necessitate efficient noise cancellation for most hearing devices to comfort the user. Various filtering techniques are employed in order to apply efficient noise cancellation, empowering the system to enhance the signal-to-nois...
Nowadays, robotic applications exist in various fields, including medical, industrial, and educational. The critical aspect of most of these applications is robot movement, where an efficient path-planning algorithm is required in order to guarantee a safe and cost-effective movement. The main goal of the path planning technique is to find the shor...
This retrospective study aimed to
investigate the epidemiological and
clinical characteristics of COVID-19
cases in the Middle Euphrates region
of Iraq. Principal Findings: A total of
853 patients were included in the
study, consisting of 340 males and
513 females, with ages ranging from
18 to 89 years old. The majority of
infected patient...
Fifth-generation (5G) networks have been deployed alongside fourth-generation networks in high-traffic areas. The most recent 5G mobile communication access technology includes mmWave and sub-6 GHz C-bands. However, 5G signals possibly interfere with existing radio systems because they are using adjacent and co-channel frequencies. Therefore, the m...
ABSTRACT
Counterfeit medicines represent a public health threat that results in
treatment failure and may even have lethal effects in the worst-case
scenario. Near-infrared Chemical Imaging (NIR-CI) offers an informative
and in-depth tool for several applications in the pharmaceutical industry,
particularly for medicine authentication. The current...
Sentiment analysis is an important study topic with diverse application domains including social network monitoring and automatic analysis of the body of natural language communication. Existing research on sentiment analysis has already utilised substantial domain knowledge available online comprising users’ opinion in various areas such as busine...
Gait datasets are often limited by a lack of diversity in terms of the participants, appearance, viewing angle, environments, annotations, and availability. We present a primary gait dataset comprising 1,560 annotated casual walks from 64 participants, in both indoor and outdoor real-world environments. We used two digital cameras and a wearable di...
Person identification is a problem that has received substantial attention, particularly in security domains. Gait recognition is one of the most convenient approaches enabling person identification at a distance without the need of high-quality images. There are several review studies addressing person identification such as the utilization of fac...
The increasing incidence of Alzheimer’s disease (AD) has been leading towards a significant growth in socioeconomic challenges. A reliable prediction of AD might be useful to mitigate or at-least slow down its progression for which, identification of the factors affecting the AD and its accurate diagnoses, are vital. In this study, we use Genome-Wi...
Animal-Vehicle Accidents have shown deep increase in the middle east regions over the last decades. These collisions resulting from camels fleeing the wildlife and crossing the roads and hence endangering drivers and camel's lives and leading to habitat degradation. Additionality, the size, strength, and the unpredictable behavior of camels play a...
Social media has become the primary source for the public for seeking news and updates in crisis such as disasters. However, the information sought from social media in disasters is usually in the form posts (images or texts) with unorganized content that often contains duplicate, feeds, inappropriate and irrelevant posts. Processing these posts an...
Autonomous Driving refers to self-driving vehicles without the need of intervention from the human driver. Safety enhancement, energy optimization, comfort, maintenance and cost are the key benefits of Autonomous Driving. Other benefits include - productivity, reduced congestion/traffic, prevention of car crashes, reducing carbon footprint and ease...
Supply chain is a cornerstone of the eCommerce industry and is a key component in its growth. Supply chain data analytics and risk management in the eCommerce space have picked up steam in recent times. With the availability of suitable & capable resources for big data and artificial intelligence, predictive analytics has become a significant area...
Text summarization has become very essential tool to record important points and has been used by several websites and applications to lessen length, difficulty, and to preserve the vital information of the original file. The requirement on well-organized and useful text summarization of the website content, news feed and other kinds of legal docum...
Suicide is turning out to be one of the most dangerous health hazards in today’s fast paced world and is one of the leading causes of deaths among general population. Unfortunately, it also happens to be one of the most ignored factors when we compare it against other causes of fatality like road accidents, terminal illness, crimes etc. It is well...
The online platform has evolved into an unparalleled storehouse of information. People use various social question-and-answer websites such as Quora, Form-spring, Stack-Overflow, Twitter, and Beepl to ask questions, clarify doubts, and share ideas and expertise with others. An increase in inappropriate and insincere comments by users without a genu...
Covid-19 pandemic created a global shift in the way how consumers purchase. Restrictions to movements of individuals and commodities created a big challenge on day today life. Due to isolation, social media usage has increased substantially, and these platforms created significant impact carrying news and sentiments instantaneously. These sentiment...
Background
Vaccine hesitancy poses a significant risk to global recovery from COVID-19. To date however, there is little research exploring the psychological factors associated with vaccine acceptability and hesitancy in Iraq.
Aim
To explore attitudes towards COVID-19 vaccination in Iraq. To establish the predictors of vaccine uptake and vaccine h...
Purpose: Numerous simulation software has been used to evaluate energy performance with 12% of the research focusing on long-term energy consumption prediction. This paper aims to utilize machine learning to predict the energy performance of building envelope wall materials over extended periods. Methodology: In our work, machine learning model lea...
Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. It is a subdiscipline of computer vision. In this paper, we describe some of Gesture recognition techniques such as Vision based gesture recognition and Graph based gesture recognition. Also, we explor...
Gesture recognition is a computing process that attempts to recognize and interpret human gestures through the use of mathematical algorithms. In this paper, we describe Point Based Gesture Recognition and Point Clouds nearest neighbors and sampling. Also, we explore these techniques with previous studies.
Alzheimer's disease (AD) is a type of brain disorder that is regarded as a degenerative disease because the corresponding symptoms aggravate with the time progression. Single nucleotide polymorphisms (SNPs) have been identified as relevant biomarkers for this condition. This study aims to identify SNPs biomarkers associated with the AD in order to...
Three-dimensional (3D) image and medical image processing, which are considered big data analysis, have attracted significant attention during the last few years. To this end, efficient 3D object recognition techniques could be beneficial to such image and medical image processing. However, to date, most of the proposed methods for 3D object recogn...
The world of the Internet and networking is exposed to many cyber-attacks and threats. Over the years, machine learning models have progressed to be integrated into many scenarios to detect anomalies accurately. This paper proposes a novel approach named cloud-based anomaly detection (CAD) to detect cloud-based anomalies. CAD consist of two key blo...
Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential...
In this study, we surveyed 635 participants to determine: (a) major causes of mental stress during the pandemic and its future impacts, and (b) diversity in public perception of the COVID-19 vaccination and its acceptance (specifically for children). Statistical results and intelligent clustering outcomes indicate significant associations between s...
Person identification is a key problem in the security domain and may be used to automatically identify criminals or missing persons. The traditional face matching approaches adopted by the police and security services across the world have recently been shown to produce a high rate of false positive identification. Alternatively, gait-based person...
Discrete Tchebichef polynomials (DTPs) and their moments are effectively utilized in different fields such as video and image coding, pattern recognition, and computer vision due to their remarkable performance. However, when the moments order becomes large (high), DTPs prone to exhibit numerical instabilities. In this article, a computationally ef...
In this study, we surveyed over 600 participants to determine: a) major causes to mental stress during the pandemic and its future impacts, and b) diversity in public perception and acceptance (specifically for children) of Covid-19 vaccination. Statistical results and intelligent clustering outcomes indicate significant relationships between socio...
Accent detection which is also known as dialect recognition represents an emerging topic in speech processing. The classification of spoken accents can provide details about people background and their demographic information which can help in several domains. In this research, convolution neural network is utilised for the detection of three accen...
Person identification is a challenging problem which has recently received significant interest mainly due to accelerated advances in sensor technologies and machine learning. It offers potential to support diverse applications that includes crime suspect identification, biometric authentication, and missing person identification. Many existing wor...
In this paper, a novel application of machine learning algorithms is presented for student levelling. In multicultural countries such as UAE, there are various education curriculums where the sector of private schools and quality assurance is supervising various private schools for many nationalities. As there are various education curriculums in U...
Person identification is a problem that has received substantial attention, particularly in security domains. Gait recognition is one of the
most convenient approaches enabling person identification at a distance without the need of high-quality images. There are several review
studies addressing person identification such as the utilization of f...
Machine learning algorithms have been used for detection (and possibly) prediction of Alzheimer’s disease using genotype information, with the potential to enhance the outcome prediction. However, detailed research about the analysis and the detection of Alzheimer’s disease using genetic data is still in its primitive stage. The aim of this paper w...
Air pollution is currently becoming a significant global environmental issue. The sources of air pollution in Malaysia are mobile or stationary. Motor vehicles are one of the mobile sources. Stationary sources originated from emissions caused by urban development, quarrying and power plants and petrochemical. The most noticeable contaminant in the...
Genome-wide association studies are aimed at identifying associations between commonly occurring variations in a group of individuals and a phonotype, in which the Deoxyribonucleic acid is genotyped in the form of single nucleotide polymorphisms. Despite the exsistence of various research studies for the prediction of chronic diseases using human g...
Dementia is a neurodegenerative disease which leads to the individual experiencing difficulties in their daily lives. Often these difficulties cause a large amount of stress, frustration and upset in the individual, however identifying when the difficulties are occurring or beginning can be difficult for caregivers, until the difficulty has caused...
Skin cancer is classified as one of the most dangerous cancer. Malignant melanoma is one of the deadliest types of skin cancer. Early detection of malignant melanoma is essential for treatment, hence saving lives and can significantly help to achieve full recovery. Current method heavily relies on clinical examination along with supportive methods...
The development of a wearable-based system for detecting difficulties in the daily lives of people with dementia would be highly useful in the day-to-day management of the disease. To develop such a system, it would be necessary to identify physiological indicators of the difficulties, which can be identified by analyzing physiological datasets fro...
Limited battery life and poor computational resources of mobile terminals are challenging problems for the present and future computation-intensive mobile applications. Wireless powered mobile edge computing is one of the solutions, in which wireless energy transfer technology and cloud server’s capabilities are brought to the edge of cellular netw...
This paper studies the cell-edge user’s performance of a secure multiple-input single-output non-orthogonal multiple-access (MISO-NOMA) system under the Rayleigh fading channel in the presence of an eavesdropper. We suppose a worst-case scenario that an eavesdropper has ideal user detection ability. In particular, we suggest an optimization-based b...