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Smart Resturantordering System with AI-Powered Personliztion and secure Real-Time Management
No full textThis paper presents the design, implementation, and evaluation of a hybrid recommendation system aimed at enhancing personalized customer experiences within smart restaurant ordering environments. The proposed model integrates multiple recommendation strategies—collaborative filtering, content-based filtering, and popularity-based filtering—into a unified architecture using a top meta-learner hybrid approach. By combining these techniques, the system is able to capture both user-specific behavioral patterns and item-specific attributes, while also considering overall content popularity to boost recommendation relevance. Customer order histories and detailed item metadata (such as cuisine type, dietary tags, and taste profiles) were used to train and validate the system. The hybrid model dynamically learns how to weigh each recommendation strategy through a meta-learning framework, optimizing prediction accuracy based on contextual relevance and user preferences. The system’s performance was rigorously evaluated using standard metrics, including precision, recall, F1-score, and hit rate, across various top-N recommendation thresholds. Our analysis reveals that the hybrid approach significantly outperforms traditional single-method recommendation systems in aligning suggestions with actual customer behavior, particularly in scenarios requiring personalization and adaptability. Furthermore, the study explores how varying the number of recommended items impacts system performance, offering valuable insights into balancing breadth and relevance in recommendations. Limitations of the current model—such as scalability and cold-start challenges—are discussed, along with potential enhancements and directions for future research. This work contributes to the field of intelligent recommendation systems by demonstrating the effectiveness of a meta-learner-based hybrid framework in real-world applications and offering a scalable solution for personalized, context-aware suggestions in the food service industry
Behavioral Finance in modern Financial Decision Making
No full textBehavioral finance has emerged as a critical lens for understanding financial decision-making in an era characterized by market uncertainty, rapid technological advancements, and increasingly complex corporate structures. This dissertation investigates the multifaceted impact of behavioral finance across three key domains: corporate decision-making, investor behavior, and financial technology (FinTech). By analyzing how psychological biases—such as overconfidence, herding, and loss aversion—influence long-term financial strategies, risk management, market reactions, and digital financial interactions, this study highlights the limitations of traditional rational models. Utilizing a combination of literature review, content analysis, and case-based insights, the dissertation finds that behavioral tendencies play a substantial role in shaping capital structure decisions, investor responses during crises, and user interactions on FinTech platforms. These findings underline the importance of integrating behavioral insights into corporate governance, financial regulation, and technology design to promote more resilient and informed decision-making processes
Psychometric properties of the Arabic emotional and behavioral reaction to intrusions questionnaire among sample of Arabic speaking adults.
No full textBackground Intrusive "thoughts" represent undesirable cognitive activity that can cause distress, and occurs in individuals with and without psychological disorders. In order to deal with unwanted intrusive thoughts, individuals might consciously attempt to halt the flow of these cognitions through suppression or unconsciously avoid them automatically through repression. This study aimed to psychometrically evaluate and validate a translation of the Emotional and Behavioral Reaction to Intrusions Questionnaire (EBRIQ) in Arabic, for adults who speak the language. Methods The snowball sampling technique was used to recruit adults (n = 755) from five Arab countries (Lebanon, United Arab Emirates, Egypt, Jordan, and Kuwait), who completed the Arabic EBRIQ. A Confirmatory Factor Analysis (CFA) was conducted to examine the factor structure of the EBRIQ. Results A total of 755 participants completed the survey, with a mean age of 21.89 ± 4.18 years and 77.5% females. CFA indicated a modest fit for the one-factor model. Internal reliability was excellent (ω = 0.96; α = 0.96). No significant difference was found in terms of EBRIQ scores between males (M = 10.37, SD = 7.80) and females (M = 10.52, SD = 7.99) in the total sample, t(753) = - 0.22, p = .830. The highest EBRIQ scores were found in Jordanian participants (12.55 ± 6.94), followed by Emirati (12.23 ± 8.20), Lebanese (11.12 ± 7.69), Egyptian (8.96 ± 8.05) and Kuwaiti (8.20 ± 7.75) participants, F(4, 750) = 10.36, p < .001. Conclusion This study suggests that our Arabic translation of the EBRIQ is psychometrically proven to be reliable for use in Lebanon, United Arab Emirates, Egypt, Jordan, and Kuwait. This validated tool will allow researchers and practitioners to assess emotions and behaviors related to intrusive thoughts
Ensemble Learning and Event-Based Feature Mining for Li-Ion Battery State Prediction
No full textContemporary power solutions are revolutionizing the existing trend in residential and transportation services. Mobile realizations, in particular, are advancing based on innovative mobile power supply solutions. Batteries are essential to several key applications, such as electric vehicles (EVs), satellites, and mobile phones. Additionally, batteries are elementary parts of the energy storage for distributed renewable microgrids. The are just a few applications based on the batteries-based power supply. Li-ion batteries are frequently used because of their exceptional qualities, which include endurance, high power density, and compact size. Besides these notable benefits the Li-Ion batteries are expensive. To effectively compensate for this high initial cost, the "battery management systems" (BMSs) are used. These solutions are effective in maximizing the Li-Ion battery life and also guarantee a safer operation. Based on the advantages of modular design, the contemporary Li-Ion batteries can be comprised of thousands of individual cells. It results in complex and sophisticated BMSs and can render a notable overhead in terms of power consumption. The focus of this research is on enhancing the existing Li-Ion BMSs by incorporating novel event-based feature mining and machine/ensemble learning techniques. The event-based feature extractor mines pertinent information and promises significant real-time compression. In order to predict the capacity of Li-Ion cells, the produced feature set is then processed utilizing robust machine/ensemble learning algorithms, and the performance of considered regressors is compared. A real Li-Ion battery dataset is used to demonstrate the applicability. For the case of a bagging-based ensemble regressor, the method obtained a correlation coefficient of 0.9996
Academic Accreditation and Evaluation in Higher Education: Practices, Experiences, and Quality Assurance
No full textAcademic accreditation and evaluation in higher education ensures institutions meet established standards of quality and effectiveness. These practices serve to uphold educational excellence and foster transparency and accountability in academic programs. Through rigorous assessment methods, institutions evaluate their curricula, faculty qualifications, and student outcomes, improving and adapting to changing educational demands. The experiences of various institutions with accreditation processes can reveal valuable insights into best practices and the challenges faced in achieving and maintaining accreditation status. By examining these experiences, researchers may gain a deeper understanding of how quality assurance mechanisms shape the landscape of higher education and influence student success and institutional reputation.
Academic Accreditation and Evaluation in Higher Education: Practices, Experiences, and Quality Assurance delves into the crucial aspects of academic accreditation and evaluation in the context of higher education. It explores the best practices and experiences in the field, offering insights into quality assurance mechanisms that drive continuous improvement within educational institutions. This book covers topics such as higher education, quality assurance, and accreditation, and is a useful resource for education professionals, academicians, business owners, policymakers, scientists, and researchers.Academic accreditation and evaluation in higher education ensures institutions meet established standards of quality and effectiveness. These practices serve to uphold educational excellence and foster transparency and accountability in academic programs. Through rigorous assessment methods, institutions evaluate their curricula, faculty qualifications, and student outcomes, improving and adapting to changing educational demands. The experiences of various institutions with accreditation processes can reveal valuable insights into best practices and the challenges faced in achieving and maintaining accreditation status. By examining these experiences, researchers may gain a deeper understanding of how quality assurance mechanisms shape the landscape of higher education and influence student success and institutional reputation.
Academic Accreditation and Evaluation in Higher Education: Practices, Experiences, and Quality Assurance delves into the crucial aspects of academic accreditation and evaluation in the context of higher education. It explores the best practices and experiences in the field, offering insights into quality assurance mechanisms that drive continuous improvement within educational institutions. This book covers topics such as higher education, quality assurance, and accreditation, and is a useful resource for education professionals, academicians, business owners, policymakers, scientists, and researchers
The Effect of Modern Day Digital Luxury Marketing on Gen Z
No full textThe review discusses the complete overhaul that has been reaped by digital luxury marketing and how this affects Z traders: they who were born digital and have been formed with values entirely divergent from the previous centuries? In the past, digital luxury marketing represented the epitome of sophistication, exclusivity, and unattainability. Presently, however, it has invaded cyberspace and embedded itself in contemporary discourse on Instagram culture and instant gratification. Brands like Gucci, Loewe, and Jacquemus embody the new modality: creating emotional engagement and experiential narratives that speak to Gen Z consumers for whom authenticity, transparency, and purpose transcend aesthetics
Postpartum Retreats
No full textIncreasing maternal engagement with self-care during critical postpartum stages is important.
This retreat provides an environment where mothers are believed to have strong engagement
with themselves as they remain immersed in self-care and self-recovery practices. The postnatal
retreat seeks to combine the traditional practice with contemporary ones to create novel settings
that enable self-care and recovery for mothers. The relaxing environment created by such
attributes as mindfulness rooms, wellness rooms, and relaxation areas allows mothers to focus on
their health by taking care of themselves more effectively enhancing their health.
The postnatal retreat seeks comprehensive mother and infant wellness by developed personalized
care plans for each of them. The approach to mothers is based on science and compassion where
all possible evidence-based practices are employed to enhance mother care from day one. The
presence of these features dulls the senses using various soothing colors and simple designs that
help preserve tranquility.
This program seeks to change how postpartum care is perceived and carried out by providing a
different welcoming environment where women become stronger and appreciate their
motherhood pha
Corporate Governance and Financial Reporting Transparency: Evidence from an Emerging Market
No full textIn preventing reporting irregularities and ensuring proper financial transparency, corporate governance plays a key role. In this study, we examine the impact
of five key governance mechanisms—composite corporate governance score, board
independence, board size, institutional ownership, and family ownership, on financial reporting transparency in a developing market setting. Utilizing a balanced panel
of 215 non-financial companies listed on the Pakistan Stock Exchange covering the
years from 2012 to 2022, the analysis uses a panel logistic regression random effects
model to examine the determinants of reliability of financial disclosure. Results imply
that governance scores, board size, and institutional ownership adversely associate
with financial reporting transparency. In contrast, board independence and family
ownership have little explanatory power over the quality of financial disclosures.
One of the unique contributions of this study is the construction and implementation of a context-specific governance index that mirrors Pakistan’s updated corporate
governance code. This study enhances the growing body of literature on corporate
accountability in emerging markets through its combination of governance metrics
with financial reporting outcomes through the lens of the M-score framework as well
as provides practical implications for reforming regulation and protecting investors
Enhancing Quality of Life for Mothers of Children with Intellectual Disabilities in Saudi Arabia: A Pilot Psychoeducational Support Group Approach to Managing Parenting Stress
No full textAbstract
This study investigated the experiences of mothers of children with intellectual disabilities (ID) in Saudi Arabia and assessed preliminary evidence regarding their perception of the intervention's effectiveness incorporating Acceptance and Commitment Therapy (ACT) principles, in reducing stress and improving quality of life. A mixed-methods approach was employed. Seven volunteer mothers of children with ID in Saudi Arabia, recruited from the early intervention department of a specialized center in Jeddah. All seven mothers participated in the first session, where the Arabic version of the Parental Stress Scale (PSS) was administered to assess pre-intervention stress levels. The intervention consisted of two 90- minute psychoeducational support group sessions. Five mothers attended the second session, which incorporated art-based exercises. Both sessions focused on stress management techniques, emotional support, and sharing coping strategies. Data collection involved the pre- intervention PSS, post-intervention Likert-scale questionnaires, open-ended questions, and qualitative data from group discussions. Data analysis utilized SPSS for descriptive statistics on the PSS and post-intervention responses. Thematic analysis was applied to qualitative data from open-ended responses and group discussions. Results showed a moderate average pre-intervention PSS score (M = 38.00, SD = 6.74), indicating mild stress levels. Post-intervention, all participating mothers rated the support group as "Very Effective". Key themes included challenges of acceptance of the child's diagnosis, impact of family and religious beliefs, benefits of early intervention, family communication difficulties, and the impact of misinformation. The art-based session revealed that the intervention helped mothers better identify and utilize support systems. Mothers reported that the support group would improve their quality of life. Key recommendations include increasing availability and accessibility of psychoeducational support groups, integrating support group into early intervention services, providing training for healthcare professionals in sensitive communication, and raising public awareness.
Keywords: Parenting Stress, Quality of Life, Mothers of Children with Intellectual Disabilities, Saudi Arabia, Psychoeducational Support Group