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Big data transfer service architecture for cloud data centers: problems, methods, applications, and future trends
Get PDFData volume, velocity, and structure have significantly evolved over the years. The complex networking architectures of current infrastructures, and the development, and accessibility of cloud services to a diverse user base have introduced numerous challenges which have raised concerns regarding the quality-of-service performance in data processing for both service providers and customers. Key issues identified in the context of big data transfer services for cloud data centers include storage, big data transfer, service transfer architecture, data processing, bandwidth, and security, all of which demand extensive research. After thoroughly screening selected peer-reviewed articles, the primary open issues are: incorporating a data placement module in the data transfer service, providing end-to-end safeguards for packet delivery, improving data transfer time and speed, minimizing costs and implementation overhead, ensuring secure data transfer between servers in the cloud, demonstrating effective big data transfer architectures, considering topology-specific extensions to reduce the busty nature of data centers, and enhancing data transfer services using machine learning algorithms during upload and download operations. This article presents a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to understand current trends, methods/models, and research problems on big data transfer services for cloud data centers. Future work considers the security and privacy of big data transmission in cloud environments
A hybrid fog-edge computing architecture for real-time health monitoring in IoMT systems with optimized latency and threat resilience
Get PDFThe advancement of the Internet of Medical Things (IoMT) has transformed healthcare delivery by enabling real-time health monitoring. However, it introduces critical challenges related to latency and, more importantly, the secure handling of sensitive patient data. Traditional cloud-based architectures often struggle with latency and data protection, making them inefficient for real-time healthcare scenarios. To address these challenges, we propose a Hybrid Fog-Edge Computing Architecture tailored for effective real-time health monitoring in IoMT systems. Fog computing enables processing of time-critical data closer to the data source, reducing response time and relieving cloud system overload. Simultaneously, edge computing nodes handle data preprocessing and transmit only valuable information—defined as abnormal or high-risk health signals such as irregular heart rate or oxygen levels—using rule-based filtering, statistical thresholds, and lightweight machine learning models like Decision Trees and One-Class SVMs. This selective transmission optimizes bandwidth without compromising response quality. The architecture integrates robust security measures, including end-to-end encryption and distributed authentication, to counter rising data breaches and unauthorized access in IoMT networks. Real-life case scenarios and simulations are used to validate the model, evaluating latency reduction, data consolidation, and scalability. Results demonstrate that the proposed architecture significantly outperforms cloud-only models, with a 70% latency reduction, 30% improvement in energy efficiency, and 60% bandwidth savings. Additionally, the time required for threat detection was halved, ensuring faster response to security incidents. This framework offers a flexible, secure, and efficient solution ideal for time-sensitive healthcare applications such as remote patient monitoring and emergency response systems
Web-based systems in HR: a guide to digital transformation in organizations
No full textPurpose: This research examines how web-based technologies transform human resource management through digital systems. The study analyzes how these systems revolutionize organizational efficiency while identifying implementation challenges and ethical considerations in the digital age. Design/methodology/approach: A systematic review of literature published between 2000 and 2023 was conducted using JSTOR, ScienceDirect and Google Scholar. The methodological approach involved rigorous evaluation criteria and triangulation of qualitative and quantitative findings to ensure integral analysis. Findings: Digital HR systems significantly improve organizational efficiency through advanced recruitment processes, modernized payroll administration and improved employee engagement. However, implementation challenges include cybersecurity vulnerabilities, digital competency requirements and ethical considerations regarding data privacy. The effectiveness of these systems is influenced by organizational culture and change management approaches. Research limitations/implications: While this study provides an integral analysis of web-based HR systems, future research should explore emerging technologies including artificial intelligence applications and remote work technology integration in post-pandemic contexts. Practical implications: Organizations implementing web-based HR systems should develop complete security frameworks, establish ethical guidelines for data management and implement effective change management strategies to ensure successful digital transformation. Originality/value: This research addresses a significant gap in current literature by providing an integrated analysis of technical, organizational and ethical dimensions of web-based HR systems. Unlike previous studies that focused primarily on operational benefits, this research examines the interrelationship between technological capabilities and human factors in digital HR transformation
A Comprehensive Deep Learning System With MGRF Modeling for Predicting Breast Cancer Response to Neoadjuvant Chemotherapy
Get PDFAccurate prediction of breast cancer (BC) response to neoadjuvant chemotherapy (NAC) is critical for tailoring treatment strategies and improving patient outcomes. This study introduces a novel deep learning-based framework that integrates multi-parametric magnetic resonance imaging (MRI) (i.e., T1, T2, STIR, and DWI), along with clinical and molecular subtype markers, to classify tumor response into pathological complete response (pCR), partial response (PR), and stable disease (SD). First, tumor regions are delineated across MRI modalities and then modeled using a translation-invariant Markov-Gibbs random field (MGRF) with analytical parameter estimation to capture modality-specific spatial appearance patterns correlated with NAC response. Subsequently, diffusion-weighted MRI is processed to generate apparent diffusion coefficient (ADC) maps, offering quantitative assessment of intratumoral water diffusion and cellularity. Afterward, an adaptive rescaling module (ARM) is proposed to adjust spatial resolution and project volumetric inputs into 2D, enabling compatibility with pretrained convolutional networks. Finally, a customized SEResNet architecture, augmented with Squeeze-and-Excitation (SE) blocks, is introduced to extract modality-specific features which are then fused with clinical and molecular subtypes descriptors for final classification. Evaluated on a cohort of 109 BC patients using leave-one-subject-out (LOSO) cross-validation method, the system achieved an accuracy of 96.33%, a precision of 96.51%, a recall of 96.33%, an F1-score of 96.23%, and a Cohen’s kappa of 94.08%, outperforming its individual components, various pretrained deep learning models, and a state-of-the-art method. These results underscore the value of integrating the appearance model, functional (i.e., ADC) model, adaptive rescaling module, SE blocks, and clinical and molecular subtype markers for the precise prediction of NAC outcomes
City-Level Employee Education, Workplace Environment, And Audit Fees
No full textIn this study, we find that higher city-level employee education is associated with lower audit fees. This finding is robust to a battery of sensitivity tests, alternative model specifications, and endogeneity concerns. We find that this negative relationship is stronger for client firms that treat their employees better. Furthermore, we document that auditors are less likely to issue a going-concern opinion for client firms whose employees reside in cities with higher levels of education. Overall, our results show that city-level employee education and its interaction with the workplace environment play an important role in influencing audit fees
Asymmetric relationship between competition and innovation: Evidence from banks in the Eurozone
Get PDFThis study examines the asymmetric relationship between competition and innovation in Eurozone banking, using data from the original 11 Economic and Monetary Union member states. Employing the technology gap ratio for innovation and the Lerner index and Boone indicator for competition, we find an inverted-U pattern: innovation initially rises with competition but declines beyond a threshold. Granger causality tests confirm bidirectional causality on the upward slope but none on the downward, highlighting nonlinearity. These findings suggest that moderate competition fosters innovation, while excessive rivalry stifles it. Policymakers should balance competition to maximize innovation without undermining long-term technological progress
The effects of carbon disclosure and carbon performance on agency cost: International evidence
Get PDFThis study examines the relationships among carbon disclosure (CD), carbon performance (CP), and agency cost (AC) using a global sample across major industries. Employing Partial Least Squares Structural Equation Modelling (PLS-SEM) via WarpPLS, we find that increased carbon disclosure reduces agency cost, while improved carbon performance may increase it, likely due to the capital-intensive nature of environmental investments. Carbon disclosure is shown to mediate the relationship between carbon performance and agency cost. Firms in countries with emissions trading schemes and higher environmental performance indices tend to perform better in carbon management. Unlike previous studies focused solely on firm performance, this research contributes to the literature by examining how carbon-related practices influence agency costs, using comprehensive CDP-based measures and agency theory, stakeholder theory, and instrumental stakeholder perspectives
Cultural Interpretations: Exploring Beliefs and Perceptions Surrounding Supernatural Forces Versus Mental Illness: a Qualitative Study of Emirati Generational Differences
No full textBrief introduction: This study aims to explore how young and older Emirati adults perceive and distinguish mental illness symptoms (MIS) and supernatural forces symptoms (SFS), such as Jinn possession, the evil eye, and black magic. It explores the role of culture in influencing individuals\u27 understanding of mental health and how these beliefs impact the recognition and treatment of such symptoms in the United Arab Emirates (UAE). Method: The study employs a qualitative research design, utilising semistructured interviews with nine Emirati young adults (ages 18-30 years) and eight Emirati older adults (ages 60 years and above). A manual thematic analysis was conducted on the interview data to identify recurring patterns, themes, beliefs, and perceptions related to mental illness and supernatural phenomena. Results: The thematic analysis revealed four key themes shaping participants\u27 perceptions: mental health symptoms and psychological distress, spiritual interpretations and supernatural beliefs (such as Jinn possession, sorcery, and the evil eye), differentiating mental illness from supernatural causes, and generational differences in perceptions of mental illness. The study found that young Emirati participants, who tend to be more educated and exposed to contemporary medical systems, are more likely to attribute mental health problems like depression and anxiety to chemical imbalances or heredity, and prefer psychiatry as their primary treatment approach, contrasting with the more spiritual and culturally grounded views of older adults. Significant contributions: This study contributes to understanding the intersection of cultural beliefs and mental health. It emphasises the role of religious vi and supernatural frameworks in shaping mental health perceptions and beliefs. It highlights the need to integrate cultural sensitivity when addressing mental health issues in the UAE. Gap filled: The research fills a gap in the literature by examining mental illness through both Western psychological perspectives and local cultural beliefs
Toward Sustainable CO2 Reduction and Brine Utilizatio: Investigating Alkaline-Enhanced Solvay Processes
No full textThe pressing environmental challenge of carbon dioxide (CO2) emissions necessitates efficient CO2 sequestration methods, while managing concentrated brine from desalination plants remains critical. This study investigates the efficacy of modified Solvay processes for brine desalination management and CO2 capture, beginning with ammonia and subsequently replacing it with other alkaline materials including calcium hydroxide, potassium hydroxide, aluminum oxide, and carbide lime. Experimental analyses in a semi-batch reactor assessed the impact of different process parameters on CO2 capture efficiency and ion removal. Optimum conditions yielded peak sodium removal (25.0%) and CO2 capture efficiency (76.0%) using ammonia. Subsequently, calcium oxide replaced ammonia, achieving 33% sodium reduction and 86.2% CO2 capture efficiency. Additionally, potassium hydroxide and carbide lime demonstrated substantial brine desalination efficiencies of 44.1 and 47.1%, respectively, with carbide lime exhibiting superior CO2 capture efficiency (80%). Conversely, aluminum oxide showed low reactivity but effectively recovered 24.0% of magnesium ions from reject brine, indicating potential use as a coagulant. These findings underscore the potential of modified Solvay processes for addressing CO2 capture and brine management challenges while reducing environmental impacts of ammonia. Further research is warranted to optimize these processes for enhanced CO2 capture and sustainable brine desalination. This study contributes valuable insights into CO2 capture mechanisms and offers pathways toward more sustainable CO2 capture and brine desalination technologies
Psychological barriers to metaverse-based education: examining the impact of technophobia and digital fatigue
No full textPurpose This study aims to examine the psychological barriers to Metaverse-based education, focusing on the impact of technophobia and digital fatigue constructs. While the metaverse offers innovative educational experiences, these psychological factors may hinder its adoption, necessitating a deeper understanding of their influence. Design/methodology/approach This study adopted a quantitative research approach utilizing a survey methodology to examine how technophobia and digital fatigue shape students’ perceptions of metaverse-based education. Data were gathered from university students with prior experience with virtual learning platforms. Structural equation modeling (SEM) was conducted using SmartPLS 4.0 to evaluate the relationships among key variables, ensuring a robust analysis of the proposed model. Findings The findings reveal that technophobia impacts students’ perceptions of ease of use, while digital fatigue adversely affects their perceived usefulness. Furthermore, perceived ease of use improves perceived usefulness, and both factors play a crucial role in shaping students’ intention to adopt metaverse-based education. These results underscore the significant influence of psychological barriers on technology acceptance within digital learning environments. Originality/value This research expands the discussion on metaverse adoption in education by incorporating psychological factors into existing technology acceptance frameworks. Identifying critical psychological barriers offers valuable insights for educators, policymakers and platform developers to enhance accessibility, reduce digital fatigue and optimize the usability of metaverse-based learning environments