SACM - Australia
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Item Restricted HOW DISSENTING JUDGMENTS HELP US UNDERSTAND THE ROLE OF FAIRNESS IN THE DEVELOPMENT OF THE COMMON LAW. IN LIGHT OF MABO (NO 2) V QLD (1992) 175 CLR 1 AND CARR V WA (2007) 232 CLR 138.(Saudi Digital Library, 2024-10-09) Almufarriji, Meshari Mohammed M; Bourke, JudyI argue that dissenting judgments have an immense role in developing the law through the lens of fairness and that it is because of how these judgments challenge the majority judgment by presenting the flaws that were not resolved and tested in accordance to legal principles such as fairness which is usually the main principle in dissenting judgments as they highlight the social implications of the majority judgment. The dissenting judgments develop the common law in the long term by making it responsive to social changes in future cases where it can be used as a starting point to create a new law compatible with the current social values, enhancing fairness as a legal principle while maintaining the coherence of the legal system. A great example of the role of fairness is the dissenting judgments in Mabo (No 2) v Qld (1992) 175 CLR 1 and Carr v WA (2007 232 CLR 138 which sets an example of how it can have a vital and crucial role in developing the common law and ensuring its dynamicity. Even though there are some critics about the role of dissent in developing the Common law, such as dissent might affect the certainty of the legal system and doctrine of precedent, which might lead to compromising the credibility before the public, the role of dissent can be balanced to avoid such critiques by ensuring these legal principles are not affected but align with the principle of fairness, and that can be done by accurately testing the precedents to see the ability to be applied before start dissenting.6 0Item Restricted The Impact of Process Mapping Techniques on Emergency Department Efficiency and Quality of Care: A Systematic Review(Saudi Digital Library, 2025-05-28) AL MANSOUR, TAREG MOHAMMED H; Than Win, KhinAbstract Background: Emergency departments worldwide face operational challenges that impact patient care quality and efficiency. Process mapping techniques have emerged as potential quality improvement strategies, yet comprehensive evidence of their effectiveness in emergency department settings remains limited. Objective: To systematically review the impact of process mapping techniques on emergency department efficiency and quality of care. Methods: Article search was conducted at five databases (PubMed, Web of Science, Scopus, MEDLINE, ACM) from August 2024 to January 2025, with no date restrictions. Studies were included if they explicitly applied process mapping techniques in emergency department settings and reported efficiency or quality outcomes. Two reviewers independently screened studies and extracted data. Study quality was assessed using the SQUIRE 2.0 checklist. Due to heterogeneity in study designs and outcome measures, a narrative synthesis was conducted. Results: Twenty-four studies met inclusion criteria, representing diverse settings across 12 countries. All studies reported positive efficiency outcomes, with process mapping techniques demonstrating median reductions of 20% in emergency department length of stay (range: 3-68%) and 54% in door-to-doctor wait times (range: 29-78%). Left without being seen (LWBS) rates decreased by an average of 46% in seven of eight studies, with one study reporting a slight, nonsignificant increase. Quality of care indicators showed improvements in patient satisfaction in all three studies measuring this outcome, with no studies reporting negative impacts on clinical safety measures. Value Stream Mapping, simulation-enhanced approaches, and comprehensive Lean methodologies demonstrated the most substantial improvements across multiple domains. Conclusions: Process mapping techniques consistently improve emergency department efficiency without compromising quality of care across diverse healthcare settings. The evidence strongly supports adopting these techniques as effective quality improvement strategies, particularly for departments facing operational challenges. Future research should focus on comparative effectiveness studies and long-term sustainability evaluations.31 0Item Restricted Improving Sleep Health with Deep Learning: Automated Classification of Sleep Stages and Detection of Sleep Disorders(Saudi Digital Library, 2024-07-07) Almutairi, Haifa; Datta, AmitavaSleep consumes roughly one-third of a person’s lifetime, and it is characterized by distinct stages within sleep cycle. The sequence of these stages at night provides insights into the quality of sleep. Poor sleep quality can have numerous consequences, including drowsiness, reduced concentration, and fatigue. Beyond sleep quality, an analysis of the sequence of sleep stages can uncover the presence of sleep disorders. This thesis aims to focus on three key research problems related to sleep. Firstly, it focuses on the classification of sleep stages using a combination of signals and deep learning models. Sleep stages are categorized into five distinct stages, namely Wake (W), non-rapid eye movement (NREM) stages comprising N1, N2, and N3, and rapid eye movement (REM) stage. Throughout the duration of sleep, individuals experience multiple cycles of sleep stages. Each cycle contains a standard allocation of each stage. An unbalanced distribution of the stages can indicate the presence of sleep disorders. Previous studies primarily classified sleep stages using a single channel of electroencephalography (EEG) signals. However, incorporating a combination of signals from electromyography (EMG) and electrooculogram (EOG) alongside EEG data provides additional features. These features extracted from muscle activity and eye movements during sleep, thereby enhancing classification accuracy. In this thesis, a robust model called SSNet is proposed to accurately classify sleep stages from a fusion of EEG, EMG, and EOG signals. This model combine convolutional neural networks (CNNs) and long short-term memory (LSTM) networks to extract the salient features from various physiological signals. The CNN architecture extracts spatial features from the input signals, while LSTM architecture captures the temporal features present in signals. This study has obtained encouraging outcomes in the classification of sleep stages through the fusion of physiological signals and deep learning techniques. Secondly, this thesis aim to detect obstructive sleep apnoea (OSA) from electrocardiography (ECG) signals using deep learning methods. Sleep disorder breathing (SDB) is categorized into three different types, which are OSA, central sleep apnoea, and mixed sleep apnoea. OSA is the most common form of SDB that is characterized by repeated interruptions in breathing during sleep, leading to fragmented sleep patterns and various health complications. Previous studies developed feature engineering methods and machine learning models for the detection of OSA. Feature engineering methods involve crafting relevant features to feed into machine learning models. However, feature engineering is time-consuming and requires domain expertise. In contrast, deep learning automatically extracts features from ECG signals for OSA detection, eliminating the need for manual feature engineering methods. In this thesis, three deep learning architectures are proposed, including standalone convolutional neural networks (CNN), CNN with long short-term memory (LSTM), and CNN with gated recurrent unit (GRU). Through rigorous experimentation and evaluation, the combination of CNN and LSTM architecture is the best-performing model for OSA detection. To further enhance the architecture’s performance, the hyperparameters of the CNN and LSTM models were tuned and tested over a large dataset to validate their effectiveness. The third research problem addressed in this thesis is detection of periodic leg movements (PLM) and SDB from NREM stage by using a combination of signals and deep learning models. PLM is characterized by involuntary leg movements during sleep. These movements can disrupt sleep and result in daytime sleepiness with reduced quality of life. Detecting PLM and SDB events during NREM stage allows for quantifying the severity of sleep disorders. Previous studies have focused on the development of signal-based models for detecting PLM or SDB. However, the models lacked the ability to distinguish these events within specific sleep stages. To address this problem, a novel deep learning architecture known as DeepSDBPLM is proposed. This architecture aims to detect PLM and SDB events during the NREM stage. This architecture incorporates novel input features called attention EMDRaw signals and utilizes a Residual Convolutional Neural Network (ResCNN) model. This thesis presents experimental results using publicly available datasets to evaluate the performance of the proposed deep learning models for classification of sleep stages, and detection of sleep disorders. The models were evaluated standard metrics. It includes accuracy, sensitivity, specificity, and F1 score. The empirical results establish the effectiveness of proposed approaches. The models can be a stepping stone towards more advanced techniques.10 0Item Restricted Exploring the High Energy Emission and Luminosity Mechanisms in Binary Black hole Systems Embedded in Active Galactic Nuclie(Saudi Digital Library, 2025) Mahnashi, Laila; Gendre, BruceIn this project, I implement a theoretical astrophysics study to investigate the potential electromagnetic (EM) signatures of binary black hole (BBH) systems embedded within the accretion discs of active galactic nuclei (AGNs). The primary objective is to model the spectral energy distribution (SED) of both the AGN and the BBH system, with the aim of identifying physical conditions under which the BBH-induced emission may become observationally distinguishable from the dominant disc background. To construct realistic SEDs, the model incorporates key radiative processes, including thermal blackbody emission from the AGN disc, synchrotron radiation from relativistic electrons, and inverse Compton scattering of seed photons. Systematic variations in viscosity, accretion rate, density, and optical depth are explored to assess their influence on the spectral properties. Special emphasis is also placed on transient flare events associated with BBH activity and on scenarios where the AGN disc is intrinsically dimmed. These conditions may enhance the visibility of BBH-driven high-energy emission, partic ularly in the hard X-ray and gamma-ray regimes. The results suggest that during low-luminosity phases of AGNs and BBH flaring episodes, the BBH emission can dominate at high photon energies, providing a promising opportunity for detection. This approach offers a complementary perspective to conventional methods, align ing with emerging observational efforts to connect gravitational-wave detections with electromagnetic counterparts. Although the model adopts several simplifying assumptions, it provides valuable theoretical insights into the EM observability of BBHsystems in AGN environments and contributes to the broader understanding of multimessenger astrophysics.6 0Item Restricted Exploring Female Preschool Teachers’ Perspectives on Conceptualising and Implementing Play and Play-Based Learning in the Kingdom of Saudi Arabia(Saudi Digital Library, 2024-09-12) Aljohani, Asma Hulayyil; Jo Bird, Associate; Sims, Margaret; Eliott, Sue; Zheng, HaoranThis study explored how Saudi female preschool teachers conceptualise and implement play and Play-Based Learning (PBL) within their unique cultural, social, and religious contexts. While Saudi Arabia’s early childhood curriculum has implmeneted Western models of PBL, the significant cultural differences challenge direct application. Through a qualitative, socially constructivist approach and indigenous methodology, the study involved 23 teachers from public, private, and charity-based preschools. Data were collected via interviews, lesson plans, and focus groups and analysed thematically. Findings revealed that teachers’ understanding of play is shaped by local values and religious practices. Three main types of play were identified:(Outdoor play)routines aligned with school, social, religious, and cultural contexts; (Interest area activities) as scripted play informed by the curriculum and society’s cultural norms and contexts; and (Refreshment play) for when children had a little spare time at the end of a group activity. Teachers also adopted varied pedagogical roles such as planner, co-player, facilitating leader, observer, and supporter based on their perspectives, understanding, curriculum goals, and children's needs. Challenges included societal expectations, gender norms, and administrative pressures. To bridge this gap, I have proposed a practical model to meld the Western and Saudi Arabia notions of play and PBL by creating a metaphorical model entitled, “Using a Date Palm Tree Metaphor for Play-Based Learning in the KSA”. ’The aim of this model and other recommendations arising from the study is to improve the cross-cultural transferability of the Western concept of PBL and to offer a suitable and consistent framework for supporting children’s learning and development in ways relevant and applicable to the Saudi educational setting.20 0Item Restricted IT Skills Required by Manufacturing Companies and the Effectiveness of University Educational Programs(Saudi Digital Library, 2024-10) Baqer, Baqer; Feng, YanmingThe focus of the research addresses the obvious gaps between the IT educational programs being offered against the market requirement in manufacturing companies, with the primary goal of identifying these gaps in both technical and interpersonal development aspects, these gaps were the subject of research on many articles investigating the abilities of IT graduates to perform in the workforce. A data-oriented approach was employed to gather deeper insights into the graduate’s abilities from several resources, manufacturing companies and the targeted demographics yielded positive responses for the survey from 38 professionals including HR, Managers, and IT employees. To support these prospects an analytical approach was done on the IT curriculum using the QUT University website as well. The results from the survey depicted the shortcomings in the educational abilities gained by the students and their applicability in practice covering a wide range of the gaps in their learning process and knowledge, awareness of different subjects that are required by the industrial complex such as cyber-security, cloud computing expertise, teamwork skills, and communication, and viewed the necessary needs of dealing with the newly emerging technologies augmented with artificial intelligence and machine learning. The paper views the requirements of training, how to further enhance the educational experiences, and the importance of revisiting and revising the educational program in the long term, as well as bridging these gaps with proposed methods of collaboration to improve the program outcomes and increase IT graduates job opportunities.46 0Item Restricted Sensorless Control and Large Signal Stability Analysis of Microgrids(Saudi Digital Library, 2025) Algarny, Khalil; Vilathgamuwa, Mahinda; Sera, DezsoMicrogrids in modern power networks have been gaining attention as a result of the global shift to sustainable energy systems. Microgrids, which are localised energy systems that can operate in either grid-connected or islanded modes, are essential for the development of renewable-powered solutions that are both flexible and reliable. But as these systems develop, they encounter major control, stability, and reliability challenges, especially when operating in dynamic environments and integrating more renewable energy sources. For microgrid technology to advance and remain viable over the long term, these challenges must be resolved. A comprehensive literature review of microgrids, sensorless control and large signal stability analysis is presented in chapter 2. The microgrid configurations, types of sources used, challenges of integrating renewable energy sources are discussed. In addition, the importance and types of voltage and current estimation techniques and the large signal stability analysis are studied to help understand the concept and current advancement in this research field. Additionally, the primary research gaps are highlighted after each subsection to ensure a clearer understanding of the specific challenges within each topic and helps accurately attribute the contributions made in addressing these gaps. Sensorless control of microgrids is presented in Chapter 3. The use of voltage and current estimators, typically used in conventional systems, to a master-slave distributed generator configuration is shown. The proposed method eliminates the need for expensive dc-side voltage and current sensors necessary for maximum power point tracking (MPPT) of the connected photovoltaic (PV) modules. Moreover, in medium and high-power applications, this method can provide a valuable substitute to one or more faulty current or voltage sensors which ensure system continuous operation while locating the faulty sensor(s). The introduced method doesn’t affect the PV normal operation even in the presence of partial shading, battery charging / discharging and fluctuating loads. The introduced method utilizes voltage and current estimators that rely on the ac-side measurements and a proposed switching function to isolate and calculate the voltage and current of each connected DG. The structure and the design details of these estimators are discussed in detail. The simulation and practical results conducted using series-connected converter configured by master (battery) – slave (PV) DG proved the validity of the proposed method in maintaining normal operation below 2% estimation error. In chapter 4 of the thesis, a new method to define the boundaries of large signal stability of a virtual-synchronous-generator-controlled converter is introduced. The new method estimates the region of attraction (ROA) around the converter’s stable equilibrium point (SEP) using vector perturbation and convex hull algorithm. It provides a mathematical representation of the converter’s stability boundaries, which can be used to evaluate its frequency and power angle stability under large disturbances. A case study, simulation results, and experimental results are provided to demonstrate the validity and the accuracy of the proposed method. Finally, conclusions and future work are presented. In final chapter of the thesis, the conclusion and the future work are discussed where it summarizes the main research gaps and contributions and draws on the potential future research directions driven from this thesis.10 0Item Restricted Best Practice Recommendations in non-Traumatic Knee Pain (NTKP) From Clinical Practice Guidelines: Systematic Review(Saudi Digital Library, 2024-10-25) Albhlal, Abdulaziz; Sin Man Chan; Gaute Herskedal; Khoi Pham; Waller, Robert - Kendell, Michelle - Sainsbury, DavidObjective: To identify and synthesise the best practice guidelines for the assessment and care of non-traumatic knee pain (NTKP) conditions in adults, with the aim of providing evidence- based recommendations for clinical practice. Design: Systematic review of clinical practice guidelines (CPGs) and expert consensus recommendations. Eligibility Criteria: Included CPGs provided recommendations on the diagnosis, assessment, and care of NTKP were written in English, published between 2016 and 2024, focused on adults, excluding knee osteoarthritis, injuries or post-surgical conditions. Data Sources: Searches were conducted in PubMed, MEDLINE, Embase, Cochrane, PEDro and CINAHL Library. Results: 5 records were identified, 2 CPGs, 2 consensus statements and 1 position statement. Numerous recommendations identified for NTKP care. Consistent recommendations include the use of outcome measures. Physical assessment should include a cluster of diagnostic criteria to provide a precise diagnosis. Care should include education, activity modification and exercise therapy. Conclusion: There is consistent consensus across guidelines that conservative management, primarily through exercise and education, should be the first-line treatment for PFP and PT. These recommendations aim to guide healthcare clinicians, for managing NTKP conditions. This review outlines directions for future research on NTKP.9 0Item Restricted Exploring Play-Based Learning in the Eastern Region of Saudi Arabia(Saudi Digital Library, 2024-12-03) Alajmi, Delail; Grieshaber, SusanThis study explores the implementation of play-based learning (PBL) within the self- learning curriculum (SLC) in kindergartens across the Eastern Region of the Kingdom of Saudi Arabia (KSA), targeting children aged four to six years. Through semi-structured interviews with 20 kindergarten teachers from diverse settings including cities, governorates, and villages, this research aimed to uncover how PBL is applied in the SLC, the roles teachers play during its application, and the challenges they encounter. The methodology also includes an analysis of photographs, such as classroom photographs and policy analysis related to the SLC, to gain deeper insights into the practical execution of the curriculum and its alignment with PBL principles. Findings reveal a spectrum of practices in implementing PBL, reflecting a combination of adherence to the SLC and Department of Education guidelines, and teachers' innovative strategies to foster an engaging learning environment. Teachers described their roles as facilitators, designers of learning experiences and observers, highlighting the importance of direct instruction in certain instances. Challenges identified include the outdated nature of the SLC, external interference from non-educators—DOE supervisors, kindergarten principals, and mothers of children who are not formally trained in ECE—, and high teacher-child ratios and inadequate environments.21 0Item Restricted Quality of life, disability, health behaviours and recovery among women living with mental illness in Saudi Arabia: A mixed methods study(Saudi Digital Library, 2025) Almalki, Ibtihal; Inder, Kerry; Alqudah, Muhammad; O'Brien, Tony; Inder, KerryBackground Research on women with mental illness in Saudi Arabia is limited with the voices of these women not heard. Quality of life, disability and recovery are critical concerns for these women. Healthy lifestyle behaviours and their life experiences are not known. Aim To explore the experiences of women hospitalised with mental illness and to examine the quality of life, level of disability, health behaviours and personal recovery of women living with mental illness in Saudi Arabia. Methods A convergent mixed methods research design was conducted in two Saudi government-funded mental health hospitals in the cities of Taif and Jeddah in the Kingdom of Saudi Arabia. Face-to-face in-depth semi-structured interviews were used to collect qualitative data. For quantitative data, a cross-sectional survey administered three standardised and validated instruments to measure quality of life, disability and recovery: the World Health Organization Quality of Life Brief Version questionnaire, the World Health Organization Disability Assessment Schedule 2.0, and a Questionnaire about the Process of Recovery. Demographic characteristics, clinical information and health behaviours were collected from medical records and by self-report. Data were collected simultaneously and analysed separately. Qualitative data were analysed thematically. Quantitative data were summarised descriptively, and linear and logistic regression techniques were used to determine factors associated with quality of life, disability and recovery. Results from both methods were integrated and discussed to gain a comprehensive understanding of the research phenomenon with researcher reflexivity. Findings and results Individual interviews were undertaken with 19 women hospitalised with mental illness. Four major themes emerged: lived experiences with mental illnesses, the voice of recovery, lifestyle and wellness, and knowledge and understanding. The cross-sectional survey was administered to 201 women. There was a higher proportion of married women and women who were housekeepers from Taif, while there was a high proportion of single women and more highly educated women from Jeddah. Health behaviour characteristics indicated that many women were either overweight or obese and did not engage in physical activity. Final adjusted regression models revealed several key findings. Recent diagnoses with mental illness and unemployment status resulted in lower quality of life scores. Lack of exercise resulted in lower physical health and psychological health. Being single resulted in lower social relationships and environment domains, while being married resulted in lower scores for physical and psychological health domains. Married or widowed women who were recently diagnosed with a mental illness, unemployed women, women with no formal education, or who never exercised were more likely to have higher disability levels. Recent diagnosis, being younger, married or widowed, unemployed, not engaging in activity and having poor sleep resulted in lower recovery levels. This integrated approach demonstrates that face-to-face interviews can reveal deeper, context-specific factors influencing the quality of life and recovery and underscores the necessity of a holistic approach to the mental health care of women with mental illness. The interviews revealed significant challenges related to stigma, social isolation and the impact of educational background on participants’ lives, which were less apparent in the quantitative component. The survey data provided a better understanding of potentially modifiable factors to impact quality of life, disability and recovery. Both data sources aligned with the Connectedness, Hope, Identity, Meaning and Empowerment framework revealing a shared emphasis on the five key aspects of personal recovery. Conclusion This thesis uniquely explores the experiences of women with mental illness in Saudi Arabia focusing on their quality of life, disability, health behaviours and recovery providing valuable insights and implications for enhancing support and care for women. This study provides new insights into their experiences and significantly advances the understanding of women’s challenges and perspectives. Delivering recovery-based practices and advocacy programs for community and mental health professionals is recommended. Incorporating counselling services into healthcare policies, enhancing community-based support, and improving nursing practices are critical. Advancing mental health education and addressing stigma through public awareness are crucial to building a more inclusive and supportive society. Future research should focus on understanding the mental health needs of women with mental illness, addressing socio-cultural barriers to help seeking, and reducing stigmatisation and discrimination. Including more women from this vulnerable group in research allows their voices to be heard.51 0