Dhiya Al-Jumeily Obe

Liverpool John Moores University | LJMU · Faculty of Engineering and Technology

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...

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...

Background: Iraq is among the countries affected by the COVID-19 pandemic. As of 2 August 2020, 129,151 COVID-19 cases were confirmed, including 91,949 recovered cases and 4,867 deaths. After the announcement of lockdown in early April 2020, situation in Iraq was getting steady until late May 2020, when daily COVID-19 infections have raised suddenl...

To improve the computational power and limited battery capacity of mobile devices (MDs), wireless powered mobile edge computing (MEC) systems are gaining much importance. In this paper, we consider a wireless powered MEC system composed of one MD and a hybrid access point (HAP) attached to MEC. Our objective is to achieve a joint time allocation an...

A primary dataset is presented comprising student grading records and educational diversity information. The dataset is collected from two international schools, a British curriculum, and an American Curriculum schools based in Abu Dhabi, UAE. Following the ethical approval from Liverpool John Moores University (19/CMS/001), the data is collected t...

Production of cement has been identified as a major source of carbon dioxide, particulates, and other gases, where it was reported that the production of one ton of OPC could produce one ton of CO 2 . These gases and particulates exert significant effects on human health and the environment. Therefore, the supplementary cementitious materials (SCMs...

When considering binding materials, cement mortar is thought to be one of the most conventional and effective materials. The cement mortar is mainly containing cement, sand (fine and rough), and water. In fact, there are many environmental and economical limitations to the usage of raw materials in mortar blends. For considering these limitations,...

A significant number of researches pointed to the serious environmental and health effects of the Ordinary Portland Cement (OPC), including the harmful emissions and alkaline wastewaters. Therefore, the development of eco-friendly alternatives for the OPC is one of the priorities of nowadays studies. However, the suggested eco-friendly alternatives...

This paper proposes a novel passenger car equivalent and capacity estimation methods that determine the effect of deceleration and acceleration performance of heavy goods vehicles on the traffic flow and estimate the capacity to facilitate rescheduling container carriers. The development of the new methods considers the driver’s perception of time...

The ‘riverine flooding’ is deemed a catastrophic phenomenon caused by extreme climate changes and other ecological factors (e.g., amount of sunlight), which are difficult to predict and monitor. However, the use of internet of things (IoT), various types of sensing including social sensing, 5G wireless communication and big data analysis have devis...

An amendment to this paper has been published and can be accessed via the original article.

Smartphones have changed the lives of many people all around the world with its technological evolution and computational capabilities. Moreover, with an increasing number of in-built sensors which can assist in efficient identification of user location, to detect the presence of nearby objects, to measure atmospheric pressure etc. The ability to d...

River flooding is a natural phenomenon that can have a devastating effect on human life and economic losses. There have been various approaches in studying river flooding; however, insufficient understanding and limited knowledge about flooding conditions hinder the development of prevention and control measures for this natural phenomenon. This pa...

The smart city concept has attracted high research attention in recent years within diverse application domains, such as crime suspect identification, border security, transportation, aerospace, and so on. Specific focus has been on increased automation using data driven approaches, while leveraging remote sensing and real-time streaming of heterog...

The proliferation of artificial intelligence and its continued development can be attributed to the pursuit of advanced machine learning techniques for handling big health data. Even though AI appears to be an independent system while considering algorithms and learning techniques, it, however, requires integration of different machine learning alg...

Fuel poverty has a negative impact on the wellbeing of individuals within a household; affecting not only comfort levels but also increased levels of seasonal mortality. Wellbeing solutions within this sector are moving towards identifying how the needs of people in vulnerable situations can be improved or monitored by means of existing supply netw...

In this study, artificial neural network (ANN) techniques are used in an attempt to predict the nonlinear hyperbolic soil stress–strain relationship parameters (k and Rf). Two ANN models are developed and trained to achieve the planned target, in an attempt at making the experimental test (unconsolidated undrained triaxial test) unnecessary. The fi...

Machine learning is as growing as fast as concepts such as Big data and the field of data science in general. The purpose of the systematic review was to analyze scholarly articles that were published between 2015 and 2018 addressing or implementing supervised and unsupervised machine learning techniques in different problem-solving paradigms. Usin...

This book constitutes the refereed proceedings of the First International Conference on Applied Computing to Support Industry: Innovation and Technology, ACRIT 2019, held in Ramadi, Iraq, in September 2019. The 38 revised full papers and 1 short paper were carefully reviewed and selected from 159 submissions. The papers of this volume are organiz...

Background: Machine learning is a branch of Artificial Intelligence that is concerned with the design and development of algorithms, and it enables today's computers to have the property of learning. Machine learning is gradually growing and becoming a critical approach in many domains such as health, education, and business. Methods: In this pa...

A new electrocoagulation reactor (EC), which utilises the concepts of baffle-plates, has been applied to remove Escherichia coli (E. coli) from wastewater. This new aluminium-based EC reactor utilises perforated baffle-plates electrodes to mix water, which reduces the need for mechanical or magnetic mixers that require extra power to work. This new...

The Great Al-Mussaib channel (GMC), in Babylon province, Iraq, has been selected as a case study to measure the concentration of nine heavy metals (Pb, Ni, Zn, Fe, Cd, Cr, Cu, Mn and Co) in both water and sediments of the GMC. The channel is used as a raw water source for two cities, which reveals the importance of the current study. Where any heav...

Epistasis is a progressive approach that complements the ‘common disease, common variant’ hypothesis that highlights the potential for connected networks of genetic variants collaborating to produce a phenotypic expression. Epistasis is commonly performed as a pairwise or limitless-arity capacity that considers variant networks as either variant vs...

With the emergence of big data and the continued growth in cloud computing applications, serious security and privacy concerns emerged. Consequently, several researchers and cybersecurity experts have embarked on a quest to extend data encryption to big data systems and cloud computing applications. As most cloud users turn to using public cloud se...

People at high-risk of cardiovascular disease are most likely vulnerable to chronic kidney diseases, and historical medical records can help avert complicated kidney problems. In this paper, 12 supervised machine learning algorithms were used to analyses a retrospective electronic medical data on chronic kidney disease. The study targeted 544 outpa...

The advent of eHealth and the need for real-time patient monitoring and assessment has prompted interest in understanding people behavior for improving care services. In this paper, the application of machine learning algorithms in clustering and predicting vital signs was pursued. In the context of big data and the debate surrounding vital signs d...

Of the many challenges that continue to make detection of cyber-attack detection elusive, lack of training data remains the biggest one. Even though organizations and business turn to known network monitoring tools such as Wireshark, millions of people are still vulnerable because of lack of information pertaining to website behaviors and features...

Smartphone applications (”apps”) have become ubiquitous with the advent of smartphones and tablets in recent years. Increasingly the utility of these apps is being explored in healthcare delivery. Hydrocephalus is a condition that is usually followed by a neurosurgeon for the patient’s life. We explore patient acceptability of a mobile app as an ad...

The problem of predicting nonlinear and nonstationary signals is complex since the physical law that controls them is unknown and it is complicated to be considered. In these cases, it is necessary to devise nonlinear models that imitate or learn the rules of behavior of the problem and can be developed based on historical data. For this reason, ne...

Smart meters are the next generation gas and electricity meters where the meter readings are presented digitally and accurately to the consumer via an In-Home Display unit. Access to the data sets generated by smart meters is becoming increasingly prevalent. As such, this paper presents an approach for detecting age groups from aggregated smart met...

This paper illustrates the utilise of various kind of machine learning approaches based on support vector machines for classifying Sickle Cell Disease data set. It has demonstrated that support vector machines generate an essential enhancement when applied for the pre-processing of clinical time-series data set. In this aspect, the objective of thi...

This paper aims to discuss specific immersive Virtual Reality Medical Training platforms developed as research projects in the use of Virtual Reality for Medical Training. It looks at the technology that is utilised by different applications and investigates the methodologies employed in the development of immersive applications. This paper identif...

The increase in data transmission volume and repository size have increased the need to secure and protecting a message such that it does not draw attention. in this paper, a new steganography algorithm in the transform domain of images based on orthogonal polynomials (OPs) is presented. The algorithms get benefits from the low energy moments, wher...

Different variants of LEACH algorithms are presented in the literature. A stable improved LEACH (SILEACH) algorithm, one of the LEACH variants, was proposed to overcome the problems of LEACH algorithm. Enhanced LEACH (ELEACH) and improved LEACH are other variants of LEACH algorithm which have the ability to increase the network lifetime. ELEACH uti...

We propose a methodology to aid clinicians in performing lumbar spinal stenosis detection through semantic segmentation and delineation of Magnetic Resonance Imaging (MRI) scans of lumbar spine using deep learning. Our dataset contains MRI studies of 515 patients with symptomatic back pains. Each study is annotated by expert radiologists with notes...

Modern time-domain astronomy is capable of collecting a staggeringly large amount of data on millions of objects in real time. Therefore, the production of methods and systems for the automated classification of time-domain astronomical objects is of great importance. The Liverpool Telescope has a number of wide-field image gathering instruments mo...

Detection of abnormalities in wireless capsule endoscopy (WCE) images is a challenging task. Typically, these images suffer from low contrast, complex background, variations in lesion shape and color, which affect the accuracy of their segmentation and subsequent classification. This research proposes an automated system for detection and classific...

Worldwide, the number of people living with self-limiting conditions, is increasing. The resulting strain on healthcare resources means that providing 24-h monitoring for patients is a challenge. As this problem escalates, caring for an ageing population will become more demanding over the next decade, and the need for new, innovative and cost effe...