Amman Arab University

• Energy Efficiency in Existing Buildings : The study addresses the critical issue of energy consumption in existing residential buildings, focusing on retrofitting to enhance energy efficiency. • Multi-objective Optimisation : Utilizes advanced multi-objective optimisation techniques to balance energy savings and upfront costs, providing a robust framework for decision-making. • Case Study in Gaziantep, Turkey : A detailed case study of a six-storey residential building in Gaziantep, Turkey, is used to explore various retrofit scenarios and their impact on energy performance and costs. • Significant Energy Savings : Optimal retrofit scenarios achieve up to 47% reduction in heating energy use and 32% reduction in cooling energy use compared to baseline scenarios. • Cost-effectiveness : Identifies refurbishment solutions that balance energy efficiency with upfront costs, emphasizing the importance of cost-effective retrofitting strategies. • Sustainable Development Goals (SDGs) : Aligns with the targets set under the 2030 global development plan, highlighting the role of retrofitting in achieving sustainable development goals. The rapid consumption of raw materials and non-recyclable energy sources in building production and operation has made energy efficiency a critical issue. This study addresses the challenge of improving energy efficiency in existing residential buildings through retrofitting, focusing on the optimisation of energy use and cost. The research is conducted within the framework of the United Nations' Sustainable Development Goals (SDGs), particularly Goal 11, which emphasizes the development of sustainable cities and communities. A comprehensive methodology is employed, involving a detailed literature review, the development of a Building Information Model (BIM) using Revit, and energy modelling with DesignBuilder. A case study of a six-storey residential building in Gaziantep, Turkey, is used to explore various retrofit scenarios. The study examines the impact of various materials and insulation strategies on energy performance and costs, employing a multi-objective optimization approach. The results highlight the significant potential of retrofitting to enhance energy efficiency, with optimal scenarios achieving up to 47% reduction in heating energy use and 32% reduction in cooling energy use compared to baseline scenarios. The study also emphasizes the importance of cost-effectiveness, identifying refurbishment solutions that balance energy savings with upfront costs. The findings highlight the crucial role of retrofitting in achieving sustainable development goals and offer valuable insights for decision-makers in the building sector.

Abstract This research examines file protection in cloud environments using the SHA-256 algorithm. It evaluates secure hash variants in file transfer systems, aiming to improve throughput while meeting security requirements. Data analysis involved gathering and cleaning datasets, measuring encryption times, and applying statistical and graphical methods. Results show SHA-256 as an effective base for encryption, with parallel processing increasing efficiency when real-time speed is essential. The study highlights the value of transformational techniques to boost performance and recommends hybrid systems that combine SHA-256 with other algorithms for stronger security. These outcomes support further work on cryptographic methods to strengthen the safety and reliability of cloud infrastructures.

Polymorphism is a cornerstone of object-oriented programming that promotes code reuse and interface consistency. While runtime polymorphism through virtual functions is well understood, compile-time polymorphism via function overloading deserves deeper study in the context of modern C++. This paper provides a detailed analysis of function overloading as a mechanism for compile-time polymorphism. It explores overload-resolution rules, evaluates performance differences between static and dynamic dispatch, and integrates these findings with features introduced up to C++20. The benchmarking experiments are grounded in a computational geometry case study that compares dispatch mechanisms through area calculations for geometric shapes. Experimental results show that static dispatch through overloading outperforms virtual function calls by a factor of 3.2 in micro-benchmarks. The study concludes that combining overloading with modern C++ features enables high-performance, type-safe, and expressive code.

The paper discusses how digital financial inclusion powered by financial technology and incorporation of environmental, social, and governance principles into finance can hasten the achievement of Sustainable Development Goal 7. We provide a systematic literature review, which relies on peer-reviewed literature in energy economics, sustainable finance, and development literature. Our search and screening strategy is informed by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The analysis shows that financial inclusion, which is promoted by FinTech (e.g. mobile banking, digital lending, and crowdfunding) has increased access to energy (e.g. pay-as-you-go solar, microfinance to clean cooking) especially by underserved communities in Asia, the Middle East and Africa. At the same time, the ESG consideration in financial decision-making is directing investments to renewable energy and energy efficiency initiatives. We discover that digital platforms and blockchain-based tools increase the levels of ESG data transparency and integrity, and strengthen the confidence of investors in green energy ventures. Nonetheless, it is also evidenced that financial inclusion should be accompanied with the introduction of clean energy to prevent the need to emit more carbon into the air through the consumption of additional energy. Our research gaps are household-level behavior, ESG adoption in developing markets and FinTech governance. Government and industry policies like subsidizing energy delivery through digital payments and requiring ESG reporting of FinTech companies will have the effect of making digital finance and sustainability agendas mutually reinforcing. All these points highlight the cross-cutting enabling nature of FinTech in sustainable energy shifts and the need to collaborate interdisciplinarily to utilize digital finance to achieve global clean energy targets.

ABSTRACT This study examines the financial consequences of ISO 1400 stices. Based on a large international dataset and advanced econometric methods, the analysis reveals that ISO 14001 adoption is positively linked to financial performance. The effect is amplified when firms demonstrate stronger ESG engagement, with environmental, social, and governance pillars each contributing to improved outcomes. Interaction results indicate that certification combined with ESG practices yields the most substantial gains, particularly for smaller firms and those operating in weaker institutional environments. These findings highlight the strategic importance of aligning environmental certification with ESG initiatives to enhance competitiveness, satisfy stakeholder expectations, and promote sustainable transitions. The study provides actionable implications for managers, policymakers, and investors seeking to integrate environmental management with responsible corporate governance.

Unmanned Aerial Vehicles (UAVs) are increasingly integrated into Internet of Things (IoT) ecosystems for applications such as surveillance, disaster response, environmental monitoring, and logistics. These missions demand reliable and secure communication between UAVs and cloud platforms for command, control, and data storage. However, UAV communication channels are highly vulnerable to eavesdropping, spoofing, and man-in-the-middle attacks due to their wireless and often long-range nature. Traditional cryptographic schemes either impose excessive computational overhead on resource-constrained UAVs or lack sufficient robustness for cloud-level security. To address this challenge, we propose a dual-layer encryption architecture that balances lightweight efficiency with strong cryptographic guarantees. Unlike prior dual-layer approaches, the proposed framework introduces a context-aware adaptive lightweight layer for UAV-to-gateway communication and a hybrid post-quantum layer for gateway-to-cloud security, enabling dynamic cipher selection, energy-aware key scheduling, and quantum-resilient key establishment. In the first layer, UAV-to-gateway communication employs a lightweight symmetric encryption scheme optimized for low latency and minimal energy consumption. In the second layer, gateway-to-cloud communication uses post-quantum asymmetric encryption to ensure resilience against emerging quantum threats. The architecture is further reinforced with optional multi-path hardening and blockchain-assisted key lifecycle management to enhance scalability and tamper-proof auditability. Experimental evaluation using a UAV testbed and cloud integration shows that the proposed framework achieves 99.85% confidentiality preservation, reduces computational overhead on UAVs by 42%, and improves end-to-end latency by 35% compared to conventional single-layer encryption schemes. These results confirm that the proposed adaptive and hybridized dual-layer design provides a scalable, secure, and resource-aware solution for UAV-to-cloud communication, offering both present-day practicality and future-proof cryptographic resilience.

This study investigates the attitudes of foreign students at Amman Arab University (AAU) in Jordan toward learning Arabic, shedding light on the teaching approaches of Arabic dialect, particularly Jordanian Arabic (JA), while exploring their perspective on Arabic diglossia. The study examines faculty member’s academic views specifically those of the English department and basic sciences, incorporating linguistics, translation scholars, and Arabic lecturers. The findings show that while students stigmatize the Jordanian dialect, recognizing its grammar inferiority to modern standard Arabic (MSA), they contradictorily express a keen interest in learning the dialect due to its cultural and practical relevance to Arabic-speaking societies. Contrarily and strikingly, faculty members, despite their tolerance of the vernacular in informal contexts, hold an opposing opinion that prevents the inclusion of an Arabic curriculum for non-native speakers. Moreover, the study affirms the divergence in perspectives which showcases the tension between the traditional view of H variety being the “proper” variety of the language and the practical demand of the dialect for effective communications in the Arab world. While emphasizing the significance of presenting these contradictions in Arabic language pedagogy, the study introduces the integration of dialect teaching alongside MSA to simply align with students’ linguistic needs.

The 5-Star Quality Rating System for nursing homes plays a central role in evaluating quality of care, although it has both strengths and limitations. This system relies heavily on the Minimum Data Set and derives several quality measures (QMs) from it. In this study, we validated the effectiveness of the 5-Star Quality Rating System for nursing homes and its underlying QMs in estimating quality of care. We constructed a panel dataset of US nursing homes (n=15,416) active from May 2020 to June 2023, retrieving data from three major sources: (1) COVID-19 nursing home data, (2) Payroll-Based Journal data, and (3) nursing home QM snapshots. The outcome variables included (1) resident infection, (2) staff infection, or (3) resident and staff deaths. The predictor variables were the 5-Star Quality Rating System for nursing homes and its underlying QMs classified as structure, process, or outcome (SPO) QMs. This study aims to evaluate the effectiveness of nursing home QMs by regressing nursing home COVID-19 outcomes on nursing home QMs, classified using the Donabedian SPO framework. We hypothesized that nursing homes with better structural quality (eg, greater staff availability, better skill mix, and so on), better process quality (eg, lower restraint use and higher vaccination rates), and better outcome quality (eg, lower number of residents with pressure ulcers and a lower number of resident falls) experienced better COVID-19 performance in terms of resident and staff infections and deaths. To examine the association between the COVID-19 outcomes and SPO QMs, we imputed missing values in the dataset using random forest. Subsequently, we modeled the imputed dataset using hurdled zero-inflated negative binomial mixed effects models. The zero inflation model included factors influencing initial susceptibility to COVID-19 or factors influencing the possibility of death after COVID-19 had been contracted. The model estimates were conditioned on zero inflation and random effects. Staffing measures (P<.001 for all variables in all models), health deficiency scores (P<.001 for all variables in at least 1 model), COVID-19 hospitalization rates (P<.001 for all variables in at least 2 models), and vaccinations (P<.001 for all variables in at least 2 models) exhibited meaningful relationships with the COVID-19 outcomes, while the 5-star components, Medicaid dependency, and ownership showed no clear relationships. Although widely used, the 5-Star Quality Rating System for nursing homes is an unreliable performance measure. Concerted efforts from lawmakers, policy makers, and lobbyists are needed to refine and enhance the measure, thereby ensuring its reliability and effectiveness.

This study aimed to identify the professional environment and its impact on life satisfaction among sanitation workers in Jordan. A qualitative approach was used on a sample of 15 sanitation workers. Additionally, two focus group discussions were held, each containing 10) workers. The sample was selected purposively. The results indicated the presence of challenges preventing the provision of a safe work environment, such as administrative and organizational obstacles represented by the absence of social protection in social security and health insurance, lack of access to official holidays and leaves, discrimination and randomness in the distribution of tasks, and poor organization of daily and overtime working hours. Among the most prominent economic challenges were the absence of financial rewards and incentives, and the lack of financial stability due to the nature of daily wage contracts (Miyawama) for sanitation workers. Social challenges also appeared, such as negative societal treatment and exposure to various forms of violence—economic, psychological, verbal, physical, and sexual—in the absence of complaint and reporting mechanisms. The results also showed deficiencies in the application of health and safety standards, such as conducting periodic medical examinations for workers, and the absence of necessary procedures to deal with accidents and injuries. Among the most important recommendations were enhancing societal respect for sanitation workers through media campaigns and social initiatives, and conducting further studies related to sanitation workers in Jordan.

This article examines the impact of data analytics, artificial intelligence (AI) technology, and cloud computing on HR efficiency of Jordanian organizations, with emphasis on the moderating effects of information quality. A quantitative approach was utilized, and structured surveys were distributed to HR experts and HR managers who work in different industrial sectors in Jordan. Data from 415 valid respondents were statistically analyzed rigorously using the statistical software SPSS and AMOS, and were able to identify direct effects and moderation pathways. The study proves that operational efficiency in HR advances substantially by using data analytical systems with AI and cloud-based platforms. The quality of the data obtained acts as the fundamental element connecting organizational success. Organizations can fully benefit from digital transformation with proper data governance and consistent human resource data, but the absence or incorrect management blocks their advantages. Organizations should adopt digital technology as it depends on producing quality HR information to maximize HR efficiency. Jordanian businesses should invest in AI ethics, data governance, and cloud security measures to obtain the full advantages of digital transformation in HRM. The study presents applicable guidance for HR professionals, management executives, and governmental policymakers.