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Enhancing the Livability of Urban Pocket Parks through Human-Centered Design
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Abstract
Urbanization has intensified the need for high-quality public spaces that enhance
livability in dense cities. This study investigates the application of a human-centered design
(HCD) approach in the pocket park design and the subsequent effects on the residents'
urban livability. The study aims to investigate how human-centered design can enhance
urban livability by developing pocket parks. The key objectives of the study are to evaluate
the current situation of pocket parks and their impacts on urban livability, identify the
concepts of human design and livability relevant to developing pocket parks, and develop
design guidelines that achieve the livability of pocket parks through a human-design
approach to fulfill the users’ needs. Fieldwork consists of sampling an array of cases from
various locations, paying particular attention to community engagement, creativity in
design, sustainable practices, documented Accessibility, and reported outcomes. A case
study approach was used to obtain the data. The results showed that parks created with
detailed community involvement, adequate, sustainable features, and those that fostered
inclusiveness improved social interaction, mental health, and the environmental health of
the community. These results underscore the human-centered design principles of caring
for wellness when revitalizing small, neglected urban spaces into civic assets while offering
critical insights for planners, designers, and policymakers. The research is structured
around key elements, including the problem definition, objectives, methodology, scope,
limitations, and expected outcomes. It is recommended that urban planners, municipal
authorities, landscape designers, and cross-sector collaborators should integrate pocket
parks into dense urban areas using climate-conscious, inclusive, and culturally sensitive
design, while ensuring accessibility, ecological resilience, and community engagement.
These efforts should be supported by sustainable funding, participatory planning, and
ongoing evaluation to create vibrant spaces that promote health, equity, and well-being
The Influence of Social Media and Influencers on Fashion Trends and Consumer Behavior in the GCC
No full textPower Factor Improvement in Regional Distribution Feeders with Optimal Allocation of Distributed Generators and Shunt Capacitors
No full textThis paper critically assesses power factor (pf) compensation techniques for the regional distribution feeders, focusing on Distributed Generators (DGs) and shunt capacitors. Therefore, the research aims to identify the potential of distribution networks to maximize efficiency by combining the Backward Forward Sweep (BFS) with the Sea Horse Optimization (SHO) algorithm. Through extensive testing using Torrit software and the MATPOWER toolbox, the study primarily focuses on two scenarios: one type of the DGs known as type 2 DGs, which only injects the reactive power. One of the scenarios includes Q as a shunt capacitance, while the second model represents type 3 DGs that supply both active power (P) and reactive power (Q). The type 2 DG deployment reduces the reactive power loss in the network. On the other hand, the use of type 3 DGs leads to a significant enhancement of pf as well as enhancement of the voltage profile. Most notably, coordinating type 3 DGs with shunt capacitors reveals that they work well hand in hand, contributing to better network improvement. This study offers a specific analysis of DGs deployment for utility operators and presents a roadmap for aiding their decision-making process in efficiently analyzing power systems' optimization
The Nexus between Oil Rent and Economic Growth in Oil-Producing Countries
No full textThis study examines the intricate relationship between oil production and economic growth
among the Gulf Cooperation Council (GCC) countries, Saudi Arabia, United Arab Emirates,
Kuwait, Qatar, Bahrain, and Oman from 1975 to 2023. A mixed-methods approach was
employed, integrating quantitative econometric analysis with qualitative country-level insights to
capture the relationship's numerical and contextual dimensions. Data were collected from the
World Bank, BP Statistical Review of World Energy, and the International Energy Agency. The
key variables analyzed included oil production, oil rents (% of GDP), oil consumption, GDP
growth rates, and energy intensity. Descriptive statistics showed that Saudi Arabia contributed
approximately 42% of total GCC oil production over the study period, followed by the United
Arab Emirates at 20%, Kuwait at 16%, and Qatar at 10%. Bahrain and Oman together accounted
for the remaining 12%. Oil rents as a percentage of GDP ranged significantly across countries,
with Kuwait recording the highest average (42.7%), and Bahrain the lowest (7.5%). GDP growth
patterns fluctuated, with Qatar achieving the highest average annual GDP growth rate at 6.1%,
while Bahrain recorded a more modest 2.4%.
Correlation analysis indicated a strong positive relationship between oil consumption and GDP
growth (r = 0.71), suggesting domestic energy use drives economic activity in the GCC.
However, oil production itself showed a weaker and sometimes negative correlation with GDP
growth (r = -0.18), highlighting that mere volume of production without economic diversification
can limit long-term growth prospects. Regression analysis further revealed that a 1% increase in
oil consumption is associated with a 0.42% increase in GDP growth (p < 0.01), while a 1%
increase in oil rents contributes approximately 0.27% to GDP growth (p < 0.05).
Advanced econometric modeling using the autoregressive distributed lag (ARDL) technique
identified both short-run and long-run relationships. In the short run, fluctuations in oil prices
and production volumes had significant impacts on GDP growth, with oil price shocks causing a
0.6% immediate decrease in GDP growth on average. In the long run, however, the elasticity of
GDP growth concerning oil consumption remained positiv
Revolutionizing arabic learning: GNT and AI-enhanced Metaverse environments
No full textThe rapid evolution of artificial intelligence and extended reality technologies has opened new frontiers in language learning. Traditional methods often lack engagement, while modern approaches utilizing enhanced immersion [Augmented Reality (AR) and Virtual Reality (VR)] but remain constrained by static content. This research proposes an innovative framework integrating the Generalizable NeRF Transformer (GNT) with the Metaverse to facilitate Arabic language learning. By leveraging AI-driven dynamic 3D scene generation, the system allows learners to interact with virtual environments and engage in contextual conversations with intelligent avatars. The platform supports real-time speech-to-text conversion, AI-generated responses, and interactive 3D object generation corresponding to Arabic vocabulary, fostering a multisensory learning experience. This study outlines the architecture, algorithms, and implementation strategy, demonstrating how Metaverse-integrated GNT can revolutionize language acquisition through immersive, adaptive, and scalable methodologies
Adaptive Delta-Driven Sampling and Classification of the Smart Meter Data
No full textThis research work is financially supported by the Effat University under the grant number (UC#9/3June2024/7.1-22(4)5).The integration of solar photovoltaic (PV) systems and smart grids has enabled distributed energy trading, yet the development of regulatory frameworks for microgrid energy markets remains a challenge. Rising energy costs and greenhouse gas emissions necessitate innovative strategies to ensure affordable, sustainable, and reliable power for communities. This paper proposes a Community Energy Market (CEM) leveraging Linear Programming (LP) optimization to minimize energy costs and enhance renewable energy utilization. The results demonstrate that the CEM approach significantly increases energy self-sufficiency, reducing reliance on the grid. This method achieves Rs.38,830 cost saving. Furthermore, local energy trading within communities yields 68.75% % energy savings and reduces CO2 emissions by 88.01%. These findings highlight the effectiveness of the CEM model in fostering community collaboration, improving microgrid resilience, and promoting environmental sustainability. The proposed solution emphasizes the need for diversifying energy sources and adopting advanced energy market systems to deliver long-term, cost-effective, and eco-friendly energy solutions.Effat Universit
Relationship between parental perfectionism and child's disordered eating: mediating role of parental distress and validation of the arabic version of the eating disorders examination questionnaire-short-parent version (EDE-QS-P).
No full textEating disorders are an emerging global health crisis, with significant implications for both physical and psychological well-being. Disordered eating behaviors in childhood can serve as precursors to more severe eating disorders if left untreated. Previous literature evidences a strong association between perfectionism, as well as parental control and eating disorders, highlighting perfectionism as a significant factor in the development and maintenance of ED symptoms. Early intervention during this critical developmental period is essential to address these risks, prevent the progression to clinical eating disorders, and support healthier long-term outcomes for children. This study aimed to assess the mediating role of parental psychological distress in the association between perfectionism in parents and disordered eating in children. As a secondary objective, the study intended to validate the Arabic version of the Eating Disorders Examination Questionnaire-Short Parent Version (EDE-QS-P).A diverse sample of Lebanese parents of children aged 6-11 years (N = 502; mean age of 36.24 ± 8.29 years, 74.5% of mothers) were recruited from schools, community centers, and healthcare facilities into this cross-sectional study. One parent per child completed all the questionnaires, which assessed disordered eating in children, parental perfectionism, and psychological distress. The instruments used included the Eating Disorder Examination Questionnaire-Short Parent Version (EDE-QS-P) for disordered eating, the Big Three Perfectionism Scale - Short Form (BTPS-SF) for parental perfectionism, and the Depression, Anxiety, and Stress Scale-8 Items (DASS-8) for parental psychological distress. The SPSS software v.25 was used for statistical analysis. To examine the factor structure of the EDE-QS-P, we conducted a Confirmatory Factor Analysis (CFA) using SPSS AMOS v.28 software. The mediation analysis was conducted using PROCESS MACRO v.3.4 model 4.The Arabic EDE-QS-P showed a unidimensional factor structure, strong internal consistency reliability and high convergent validity. Higher child's disordered eating scores were reported by fathers compared to mothers (8.32 ± 9.12 vs. 5.62 ± 7.69, t (500) = 3.01, p = 0.003). Parental distress mediated the association between parental perfectionism and child's disordered eating (indirect effect: Beta = 0.14; Boot SE = 0.02; Boot CI 0.11; 0.18). More parental perfectionism was significantly associated with more parental distress, and higher parental distress was significantly associated with more child's disordered eating. Higher parental perfectionism was significantly and directly associated with more child's disordered eating.This study successfully validated the Arabic version of the EDE-QS-P in Lebanon, confirming its validity and reliability for assessing parental-reported disordered eating in children in Arab contexts. Elevated parental perfectionism correlates with increased child disordered eating, mediated by parental distress. This suggests that healthcare providers should be alert to signs of perfectionism and psychological distress in parents and provide appropriate interventions, such as cognitive-behavioral therapy or stress management techniques, to alleviate these issues and lower the risk of eating disorders in children
An AI-Driven Diabetes Prediction System Using Federated Learning Architecture
No full textDiabetes has become a significant global health concern, demanding innovative
solutions for early detection and effective management. Traditional machine learning
models typically rely on centralized data aggregation, raising substantial privacy issues and compliance risks. This project, Tayaqn: An AI-Driven Diabetes Prediction
System Using Federated Learning Architecture, introduces a novel framework that
employs Federated Learning (FL) to overcome these challenges. FL allows for secure,
decentralized model training, ensuring sensitive health data remains local while enabling collaborative learning across diverse datasets. The system integrates advanced
machine learning and deep learning techniques with robust privacy-preserving mechanisms, achieving high predictive accuracy while safeguarding data security. By
combining scalability, regulatory adherence, and user-friendly design, this project
provides a transformative solution for enhancing early diagnosis and personalized
diabetes management, equipping both patients and clinicians with actionable insights for better healthcare decision-making
Mohamed F. El-Amin Mohamed F. El-Amin Relative Permeability Modeling for Underground Hydrogen Storage: A Comparative Analysis of Hysteresis Effects
No full textThe transition towards a sustainable and low-carbon future introduces the necessity to develop efficient energy storage systems. H2, with its high energy density and environmental benignity, emerges as a pivotal element in this energy transition. Nevertheless, the efficient storage of H2 is impeded by substantial obstacles, which requires the development of innovative solutions. Underground H2 storage (UHS) in depleted hydrocarbon reservoirs is a promising solution for large-scale H2 energy management that is essential for the transition to an H2 economy. This paper investigates the mathematical modeling and curve fitting of experimental measured relative permeability hysteresis data for H2 and water during drainage, imbibition processes on reservoir-scale performance. This study evaluates the performance of several relative permeability models—Brooks-Corey (BC), Van Genuchten (VG), and Modified Brooks-Corey-variable Corey (BC-vC)—using experimental data for H2 and water during drainage and imbibition processes. Error metrics, including Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R2), are calculated to assess model accuracy. The results indicate that the VG model provides the best fit for H2 during drainage, while all models perform comparably for water drainage. The VG model is a more suitable option for H2 in terms of imbibition. The study underscores the importance of model selection in accurately describing multiphase flow in porous media
Orthopedic Surgery and Rehabilitation Hospital
No full textMusculoskeletal injuries caused by road accidents, aging, and sports trauma represent one of the
leading causes of disability in Saudi Arabia. In Jeddah, there is a shortage of specialized
hospitals that integrate orthopedic surgery with rehabilitation services, creating gaps in
continuous patient care.
This project proposes the design of a state-of-the-art Orthopedic Surgery and Rehabilitation
Hospital in Jeddah that combines surgical treatment, rehabilitation, and supportive facilities
under one roof. The project aligns with Saudi Vision 2030 by improving healthcare quality,
enhancing accessibility, and promoting social inclusion.
The research methodology included literature review, case studies of international rehabilitation
centers, and a community survey to identify user needs such as hydrotherapy, outdoor green
areas, and natural lighting.
The expected outcome is a holistic healthcare facility that addresses both physical and
psychological recovery, offering a sustainable, patient-centered, and culturally sensitive
environment that improves quality of life and sets a new standard for healthcare architecture in
Saudi Arabi