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Smart Living: Integrating AI, IoT, and VR for Inclusive Interior Design in the United Arab Emirates
No full textThis literature review examines how digital interior design tools—particularly systems combining data-driven intelligence, connected devices, and immersive visual platforms—can enhance home accessibility and adaptability. The discussion focuses on the development of an interactive consultation environment that incorporates personalized layout recommendations, real-time environmental input, and virtual visualization, all tailored to user needs. Emphasis is placed on the significance of inclusive design, especially for individuals with limited digital skills or physical impairments. Drawing from regional planning goals such as the UAE’s Vision 2031, the review highlights the growing demand for flexible and culturally responsive home solutions. Key studies are analyzed to understand current shortcomings in smart design platforms, including complexity, cost, and limited consideration of user diversity. The paper also explores how connected technologies can work together to support sustainable living, energy use monitoring, and improved user experience. Existing theoretical models like the Technology Acceptance Model (TAM) provide a framework for assessing user reception. The review ultimately identifies the importance of designing adaptable, easy-to-use environments that can evolve with household needs and expectations, especially within rapidly developing urban contexts
Practical Subject-Based Library Budget Allocation in a Bilingual International University
No full textFormula-based library budget allocation is a topic of much current interest, but most research to date has focused on the factors which affect or should affect budget allocation, rather than the functional units to which the budget is allocated. Typically, it is assumed that budget will be allocated amongst academic departments or programs, with factors such as use, demand, and program characteristics determining the proportion of budget that each department receives.
In this presentation, we propose and demonstrate a more granular, subject-focused model, where the monograph budget is allocated not amongst departments but amongst academic subjects as represented by course codes. This approach recognizes the interdependent nature of modern tertiary curricula where subject courses are shared between programs in complex ways.
During our session we will demonstrate how this practical, flexible approach was implemented at Zayed University, an English- and Arabic-medium university in the UAE, and show how interested participants can design and implement a similar approach at their own institutions. We will discuss the rationale for variables used in our formula, including subject enrolment, graduate and legacy program status, as well as a nonlinear measure of program age which facilitates rapid resourcing of new programs. Emphasis will be placed on how the choice of variables augments a subject-based allocation approach, making the model very robust to program and curriculum changes
Empowering women on screen: exploring the influence of female protagonists on contemporary culture and gendered enjoyment in film
Full text linkA prevalent notion in the film industry across the globe suggests that female-led films may underperform, leading producers to avoid casting women as leads. This fear of alienating male audiences perpetuates patriarchal ideologies, objectifies female bodies, reinforces gender stereotypes, and alters perceptions of femininity. Examining this perception, the present study investigated the impact of the gender of the protagonist on the audience preference, challenging the misconception that exists in the film industry globally that films starring females as protagonists are less commercially successful. The study conducted an online experiment of 434 participants who were assigned different movies starring male and female main characters and then completed the Bem Sex Role Inventory. They watched and read a summary of the movies and rated their expected pleasure of 24 randomly selected movie plots. Participants have also reported their previous exposure to the films. The study findings indicated that the anticipated pleasure of viewing female-dominant movies depended not on one’s sex but on gender identity. Interestingly, agentic (masculine-identified) participants were more likely to enjoy male-led films than feminine (communal-identified) participants were to enjoy female-led counterparts. The neutral participants noted no difference in their enjoyment. Additionally, increased familiarity with high-budget female-centered movies supplemented the significant correlation between female lead characters and expected enjoyment. In essence, The study challenges the stereotype that female-led films are less successful, suggesting that the industry should feature more diverse, empowered female characters for gender equality
Light dark matter constraints from SuperCDMS HVeV detectors operated underground with an anticoincidence event selection
No full textThis article presents constraints on dark-matter-electron interactions obtained from the first underground data-taking campaign with multiple SuperCDMS HVeV detectors operated in the same housing. An exposure of 7.63 g-days is used to set upper limits on the dark-matter-electron scattering cross section for dark matter masses between 0.5 and 1000 MeV/c2, as well as upper limits on dark photon kinetic mixing and axionlike particle axioelectric coupling for masses between 1.2 and 23.3 eV/c2. Compared to an earlier HVeV search, sensitivity was improved as a result of an increased overburden of 225 meters of water equivalent, an anticoincidence event selection, and better pile-up rejection. In the case of dark-matter-electron scattering via a heavy mediator, an improvement by up to a factor of 25 in cross section sensitivity was achieved
Status incongruence effects under conditions of task interdependence: Too close for comfort
Full text linkThere are five generations of employees in the workforce. Such a distribution of ages makes it more likely that employees will be in non-traditional situations where workers are not only older but have more work experience, organizational tenure, or education than their supervisors. These situations reflect status incongruence and defy traditional workplace norms. We find that status incongruence with one\u27s supervisor is negatively associated with job satisfaction. There is an indirect effect between status incongruence and organizational citizenship behavior (OCB) which is transmitted through job satisfaction. The relationship between status incongruence and job satisfaction is more negative when task interdependence with one\u27s supervisor is higher rather than lower. Similarly, the relationship between status incongruence and OCB is more negative when task interdependence with one\u27s supervisor is higher rather than lower. Results suggest that task interdependence may exacerbate employee responses to status incongruence
Understanding Trust In Educational Metaverse: The Role Of Social Cognitive Theory Constructs And Perceived Risks
No full textPurposeThis study investigates the impact of social cognitive theory (SCT) constructs and perceived risks on university students\u27 trusting intentions towards Metaverse-based educational platforms in the UAE. By examining factors such as self-efficacy, outcome expectations and vicarious learning (from SCT), alongside perceived risks like performance, time, social and security concerns, this research addresses critical gaps in understanding trust dynamics in educational technology.Design/methodology/approachA quantitative survey was conducted with 176 university students who experienced a Metaverse-based classroom prototype. Data were analyzed using structural equation modeling (SEM) to evaluate the relationships between SCT constructs, perceived risks and trusting intentions.FindingsThe results demonstrate that SCT constructs significantly enhance trust by fostering self-efficacy and providing positive learning experiences. Conversely, perceived risks reduce trust, emphasizing the need to mitigate security concerns and usability barriers to improve adoption. These insights underline the dual importance of managing risks and promoting psychological readiness among students.Practical implicationsThe findings offer actionable guidance for educators, policymakers and developers to design secure, user-friendly Metaverse platforms that align with educational objectives. The study emphasizes the importance of addressing perceived risks, enhancing student engagement and fostering trust to enable effective technology adoption in education.Originality/valueThis research provides a novel perspective on trust in Metaverse-based education by integrating SCT constructs with risk perceptions, offering a comprehensive framework to guide the successful implementation of immersive learning environments
AI Innovations in rPPG Systems for Driver Monitoring: Comprehensive Systematic Review and Future Prospects
Full text linkAdvanced technologies, notably camera-based systems using remote photoplethysmography (rPPG), are increasingly used in automotive safety to non-invasively monitor driver well-being and fatigue by measuring physiological metrics like heart and respiration rates. This review examines recent advancements in machine learning algorithms and signal processing for rPPG in driver monitoring. A literature search up to April 2, 2024, across major databases, identified 344 studies; 29 were analyzed in depth, focusing on: 1) rPPG signal extraction and heart rate estimation, where deep learning improved accuracy; 2) fatigue detection, showing benefits of multimodal data fusion; 3) mental state monitoring, with machine learning classifying cognitive load and distraction; and 4) emotional state monitoring and dataset development, indicating a trend toward holistic driver assessment. While deep learning has improved rPPG signal extraction, challenges remain in consistent physiological metric detection under dynamic conditions. There is also a lack of diverse population representation, especially female drivers, in datasets. The review underscores the potential of AI-enhanced camera systems to improve road safety, emphasizing the need for diverse, multimodal data integration for comprehensive monitoring
Prevalence, Phenotype, and Correlates of Avoidant/Restrictive Food Intake Disorder Symptoms in the Gulf Cooperation Council: An Underserved Region
Full text linkIntroduction: Prevalence estimates and correlates of ARFID in non-Western samples are lacking. This study aims to estimate the prevalence of ARFID symptoms, identify its phenotypes, and explore its correlates in a community sample from the Gulf Cooperation Council (GCC). Method: Participants were parents of children aged 4–13 years (n = 87) and individuals of ≥ 14 years old (n = 433). They completed the Pica, ARFID, and Rumination Disorder Interview-ARFID-Questionnaire (PARDI-AR-Q), the Nine Item ARFID Screen (NIAS) and the Eating Disorder Examination-Questionnaire (EDE-Q). Multiple regression analyses were performed with body mass index or its standard deviation score, comorbid psychopathology, EDE-Q global score, sex, and age as independent variables; the dependent variable was ARFID psychopathology. Results: Among individuals not reporting eating disorder symptoms driven by overvaluation of shape and weight, the PARDI-AR-Q diagnostic prediction suggested that approximately 23.4% of those aged ≥ 14 exhibited ARFID symptoms. Based on the NIAS, sensory-based food avoidance was the most reported phenotype expression, with approximately 29.4% of children (4–13 years) and 12.8% of adolescents/adults (≥ 14-years) reporting ARFID symptoms. In adolescents and adults, ARFID psychopathology was positively associated with eating disorder pathology driven by overvaluation of shape and weight, with female sex and negatively associated with age. Discussion: This study is the first to identify a subset of individuals in GCC countries with ARFID symptoms across sexes and a broad age range, with sensory sensitivity as the most common symptom
Chapter 3 Enabling digital transformation with IoT cloud applications and services
No full textThis chapter discusses the enabling factors for digital transformation and shows how the cloud-to-things continuum enhances this transformation. As digitalization paves the way for digital transformation, the increasing reliance on data and the imperative for real-time data processing to make fast business decisions promote a stronger connection between IoT and cloud-based services. This transformation journey is driven by the use of cloud-based AI models, which can handle and analyze large amounts of data, providing valuable directions for sustainable business initiatives. The chapter reveals the significance of establishing a scalable and adaptable technology infrastructure, coupled with suggested key performance indicators (KPIs) to gauge the ongoing transformation accurately. Then, the benefits of agile development and operations facilitated by the cloud-to-things continuum are discussed. The chapter concludes by illustrating enriched digital experiences that foster a successful digital transformation journey
Trace element removal from wastewater by agricultural biowastes: A data analysis on removal efficacy and optimized conditions
No full textValorization of agricultural biowastes to biosorbents provides an excellent opportunity to recycle these wastes into valuable products and filtration of contaminants, especially potentially toxic trace elements in aquatic ecosystems. Water contamination with potentially toxic trace elements is a widespread global issue. Various agricultural biosorbents have been tested to remove trace elements from wastewater. Despite abundant research, there are scarce studies regarding the critical data analysis on trace elements removal efficiency by agricultural biowastes under various conditions. This review critically delineates the data analysis of recent literature published from 2018 to 2024 for a critical comparison of different agricultural biosorbents and the applied conditions to remove trace elements from aqueous media. Data analysis (based on 1188 observations) revealed that the mean trace element removal by agricultural biowaste-derived biosorbents from contaminated water was 75 %, ranging from 2 to 100 %. The most frequently reported removal efficiencies of agricultural biosorbents were 90–100 %. Notably, few agricultural biosorbents such as banana peel demonstrated the highest removal efficiency of 97 %, followed by cassava peels at 92 %, emphasizing the significance of recycling these materials for sustainable trace element removal from wastewater. Data analysis revealed that the trend for trace element removal from wastewater follows a descending order, with zinc exhibiting the highest removal rate at 81 %, followed closely by lead at 80 %. This trend continues with arsenic at 75 %, nickel and cadmium both at 70 %, and so forth. Thus, agricultural biosorbents play a pivotal role in this process, showcasing their potential in waste valorization and environmental remediation. Hence, the present review article is expected to contribute towards the comparative efficiency of various agricultural biosorbents, and the selection of the best biosorbents, depending on applied conditions for trace element removal from targeted wastewater treatment facilities