Search Results (93)

Background/Objectives: Continuous glucose monitoring (CGM) has transformed diabetes management by enabling high-resolution assessment of glucose dynamics, with well-established use in type 1 diabetes (T1D) and insulin-treated type 2 diabetes (T2D), and expanding applications across broader populations, including non-insulin-treated T2D and gestational diabetes. However, real-world implementation remains constrained by economic barriers, fragmented reimbursement, workflow challenges, and limited capacity for continuous data interpretation. This review examines key barriers to CGM implementation and synthesizes current evidence on pharmacist-integrated CGM care as an emerging model to support CGM adoption across clinical and community-based settings. Methods: A narrative literature review was conducted to synthesize evidence on pharmacist-integrated CGM services in diabetes care. Literature was identified through structured searches of PubMed, Embase, and the Cochrane Library, supplemented by Google Scholar and citation tracking, covering publications from January 2010 to December 2025. Studies were selected based on predefined criteria, including those reporting clinical outcomes, pharmacist involvement, or health system and implementation factors related to CGM use. Relevant survey-based and real-world studies were also considered to capture healthcare professionals’ perspectives and implementation experiences. Evidence was synthesized thematically across clinical, behavioral, and health system domains. Results: Available evidence suggests that pharmacist-integrated CGM care is associated with improvements in glycemic management, including increased time in range, reduced glycemic variability, and more timely pharmacotherapy optimization. Pharmacist involvement may also support patient education, self-management, and engagement with digital health technologies, and facilitate ongoing data interpretation and treatment adjustment between clinical encounters. However, evidence remains heterogeneous and geographically limited, with predominantly retrospective and pilot studies and few randomized trials, constraining the robustness and external validity of the findings. Further studies are needed to confirm its clinical effectiveness, comparative effectiveness, and economic value. Conclusions: Pharmacist-integrated CGM represents a promising and operationally feasible approach to supporting CGM use in routine diabetes care. While current evidence indicates potential benefits in glycemic management and care delivery processes, further research and implementation efforts are required to support its effective and sustainable adoption across diverse healthcare settings. Full article

The development and operation of cooperative digital library systems face management problems that do not always have a complete solution. These cooperative systems currently need to incorporate new artificial intelligence solutions to develop intelligent services for decision-making and recommendation mechanisms for which there is not an integral management solution. Indeed, the management of these intelligent services is outside the scope of traditional management systems for digital collections. This paper proposes using an intelligent management framework to address these issues. Basically, we use a top-down design approach based on six abstractions and four refinement techniques to design a management model that integrates suitable cooperative models, system behaviors, software architecture and processes to manage cooperative digital library systems that incorporate intelligent services. The work is novel since it concentrates on the major management problems found with concrete cooperative scenarios. And the intelligent management frameworks are reviewed and evolved to solve these management problems with digital library systems. Further, the approach is evaluated, designing an intelligent management framework for cooperative, intelligent digital library systems used in a government organization for current digital transformations. Finally, a qualitative analysis methodology is used with this case study, collecting relevant data with a questionnaire, and showing and discussing major results. These results demonstrate, for example, that our participants consider our approach a clear, feasible and useful solution for digital transformations. Further, they would strongly recommend our solution for other government organizations. Full article

Digital twin, a technology that offers an opportunity to access dynamic and real-time data for efficient decision-making, has witnessed minimal utilization in smart facilities management. Additionally, combining stakeholders’ views with a digital twin provides more efficient building management. Thus, this study aimed to combine digital twin technology and stakeholders’ views to develop a best practice framework for enhancing indoor conditions of a typical university building. It analyses feedback received from building stakeholders and results from a digital twin to develop the best practice framework. This study adopted a case study approach by using a university library at Western Sydney University, Australia. It used a multi-stage approach and a series of interviews with facility management experts for the development and validation of the framework, respectively. The key findings revealed that all the monitored parameters in the digital twin system were within acceptable thresholds. However, the building occupants expressed concerns regarding excessive solar heat gain, inadequate airflow, and direct glare. It was also revealed that heat was the most disturbing environmental parameter in the library, and built-in energy efficiency measures were also not adequately maintained, contributing to the building’s energy consumption. The proposed framework provides strategic measures for improving building occupants’ comfort and energy consumption. Furthermore, the best practice framework aids facility managers in holistically considering key aspects of building services management in managing such buildings. Full article

Software-Defined Networking (SDN) has emerged as a fundamental architecture for future Internet systems by enabling centralized control, programmability, and fine-grained traffic management. However, the logical centralization of the SDN control plane also introduces critical vulnerabilities, particularly to Distributed Denial-of-Service (DDoS) attacks that can severely disrupt network availability and performance. To address these challenges, machine-learning (ML) techniques have been increasingly adopted to enable intelligent, adaptive, and data-driven DDoS detection mechanisms within SDN environments. This study presents a PRISMA-guided systematic literature review of recent ML-based approaches for DDoS detection in SDN-based networks. A comprehensive search of IEEE Xplore, ACM Digital Library, ScienceDirect, and Google Scholar identified 38 primary studies published between 2021 and 2025. The selected studies were systematically analyzed to examine learning paradigms, experimental environments, evaluation metrics, datasets, and emerging architectural trends. The synthesis reveals that while single machine-learning classifiers remain dominant in the literature, hybrid and ensemble-based approaches are increasingly adopted to improve detection robustness under dynamic and high-volume traffic conditions. Experimental evaluations are predominantly conducted using SDN emulation platforms such as Mininet integrated with controllers, including Ryu and OpenDaylight, with performance commonly measured using accuracy, precision, recall, and F1 score, alongside emerging system-level metrics such as detection latency and controller resource utilization. Public datasets, including CICIDS2017, CICDDoS2019, and InSDN, are widely used, although a significant portion of studies rely on custom SDN-generated datasets to capture control-plane-specific behaviors. Despite notable advances in detection accuracy, several challenges persist, including limited generalization to low-rate and unknown attacks, dependency on synthetic traffic, and insufficient validation under real-time operational conditions. Based on the synthesized findings, this review highlights key research directions toward intelligent, scalable, and resilient DDoS defense mechanisms for future Internet architectures, emphasizing adaptive learning, lightweight deployment, and integration with programmable networking infrastructures. Full article

Quantum computing threatens widely deployed public-key cryptosystems, accelerating the adoption of Post-Quantum Cryptography (PQC) in practical systems. Beyond asymptotic security, the feasibility of PQC deployments depends on measured performance on real hardware and on implementation-level overheads. This paper presents an experimental evaluation of five post-quantum digital signature schemes (CRYSTALS-Dilithium, HAWK, SQISign, SNOVA, and SPHINCS+) and three key encapsulation mechanisms (Kyber, HQC, and BIKE) selected to cover multiple PQC design families and parameterizations used in practice. We implement a TCP client–server testbed in Python that invokes C implementations for each primitive—via standalone executables and, where provided, in-process dynamic libraries—and benchmarks key generation, encapsulation/decapsulation, and signature generation/verification on two Windows 11 commodity processors: an AMD Ryzen 7 4000 (8 cores, 16 threads, 1.8 GHz) and an Intel Core i5-1035G1 (4 cores, 8 threads, 1.0 GHz). Each operation is repeated ten times under a low-interference setup, and results are aggregated as mean (with 95% confidence intervals) timings over repeated runs. Across the evaluated configurations, lattice-based schemes (Kyber, Dilithium, HAWK) show the lowest computational cost, while code-based KEMs (HQC, BIKE), isogeny-based (SQISign), and multivariate (SNOVA) signatures incur higher overhead. Hash-based SPHINCS+ exhibits larger artifacts and higher signing latency depending on the parameterization. The AMD platform consistently outperforms the Intel platform, illustrating the impact of CPU characteristics on observed PQC overheads. These results provide comparative evidence to support primitive selection and capacity planning for quantum-resistant deployments, while motivating future end-to-end validation in protocol and web service settings. Full article

Edge–cloud computing has emerged as a key enabling paradigm for augmented and virtual reality (AR/VR) systems because of the stringent computational and ultra-low-latency requirements of AR/VR workloads. Designing efficient edge–cloud systems for such workloads involves multiple technical aspects, including communication technologies, service placement, task offloading and caching, service migration, and security and privacy. This paper provides a structured and technical analysis of these aspects from an AR/VR perspective. We adopt a two-stage literature analysis, in which Google Scholar is used to identify fundamental technical aspects and solution approaches, followed by a focused analysis of recent research trends and future directions using academic databases (e.g., IEEE Xplore, ACM Digital Library, and ScienceDirect). We present an organized classification of the core technical aspects and investigate existing solution approaches, including heuristic, metaheuristic, learning-based, and hybrid strategies. Rather than introducing application-specific designs, the analysis focuses on workload-driven challenges and trade-offs that arise in AR/VR systems. Based on this classification, we analyze recent research trends, identify underexplored technical areas, and highlight key research gaps that hinder the efficient deployment of AR/VR services over edge–cloud infrastructures. The findings of this study provide practical insights for researchers and system designers and help guide future research toward more responsive, scalable, and reliable edge–cloud AR/VR systems. Full article

Background/Objectives: Human papillomavirus (HPV) is a major cause of cervical, penile, anal, and oropharyngeal cancers. HPV vaccination is the most effective public health strategy for its prevention. Understanding the factors influencing vaccination intentions is critical for developing effective public health policies and improving population-level vaccine uptake. Therefore, in this scoping review, we aimed to examine HPV vaccination research conducted in Korea, identify common trends and gaps in study populations and influencing factors, and provide evidence-based recommendations for public health policies. Methods: We systematically searched four Korean databases—Research Information Sharing Service (RISS), DBpia, Korean Studies Information Service System (KISS), and National Digital Science Library (NDSL)—for studies published from their respective inception dates to January 2025, using “human papillomavirus,” “HPV,” “vaccination,” and “intention” as keywords. Thirty-six studies were ultimately included. Study characteristics, populations, theoretical frameworks, and key variables were extracted and analyzed using descriptive statistics and content analysis. Results: Of the included studies, 61.1% and 38.9% targeted vaccination-eligible individuals (adolescents and adults) and parents/guardians, respectively, with 50% focusing exclusively on women. The major factors influencing HPV vaccination intention were attitude (47.2%), subjective norms (38.9%), and perceived behavioral control (30.9%). Attitude and knowledge were critical for vaccination-eligible individuals (Direct group), whereas subjective norms were key for parents/guardians (Indirect group). Conclusions: Korean HPV vaccination intention research has predominantly focused on women and parents, with insufficient attention to adolescents and men. Public health strategies must employ multilevel interventions tailored to each group’s decision-making structures, including school-based programs for adolescents, gender-inclusive policies for men, and community-based approaches to address social norms among parents. These findings provide evidence for policy development aligned with the WHO cervical cancer elimination goals. Full article

Ensuring production safety and enabling rapid emergency response in complex industrial environments remains a critical challenge. Traditional inspection robots are often limited by perception delays when confronted with sudden dynamic threats. This paper presents a vision-driven dynamic digital twin system designed to enhance real-time monitoring and emergency management capabilities. The framework constructs high-fidelity 3D models using SolidWorks 2024, Scaniverse 5.0.0, and 3ds Max 2024, and integrates them into a unified digital twin environment via the Unity 3D engine. Its core contribution is a vision-driven dynamic mapping mechanism: robots operating on the Robot Operating System (ROS) and equipped with ZED stereo cameras and embedded YOLOv5m models perform real-time detection, such as personnel and fire sources. Recognized targets trigger the dynamic instantiation of corresponding virtual models from a pre-built library, enabling automated, real-time reconstruction within the digital twin. An integrated service platform further supports early warning, status monitoring, and maintenance functions. Experimental validation confirms that the system satisfies key performance metrics, including data collection completeness exceeding 99.99%, incident detection accuracy of 80%, and state synchronization latency below 90 milliseconds. The system improves the dynamic updating efficiency of digital twins and demonstrates strong potential for proactive safety assurance and efficient emergency response in dynamic industrial settings. Full article

Introduction: Rare diseases disperse expertise across institutions and borders, making structured second-opinion systems a pragmatic way to concentrate subspecialty knowledge and reduce diagnostic delays. This scoping review mapped the design, governance, adoption, and impacts of such services across implementation scales. Objectives: To describe how second-opinion services for rare diseases are organized and governed, to characterize technological and workflow models, to summarize benefits and barriers, and to identify priority evidence gaps for implementation. Methods: Using a population–concept–context approach, we included peer-reviewed studies describing implemented second-opinion systems for rare diseases and excluded isolated case reports, purely conceptual proposals, and work outside this focus. Searches in August 2025 covered PubMed/MEDLINE, Scopus, Web of Science Core Collection, Cochrane Library, IEEE Xplore, ACM Digital Library, and LILACS without date limits and were restricted to English, Portuguese, or Spanish. Two reviewers screened independently, and the data were charted with a standardized, piloted form. No formal critical appraisal was undertaken, and the synthesis was descriptive. Results: Initiatives were clustered by scale (European networks, national programs, regional systems, international collaborations) and favored hybrid models over asynchronous and synchronous ones. Across settings, services shared reproducible workflows and provided faster access to expertise, quicker decision-making, and more frequent clarification of care plans. These improvements were enabled by transparent governance and dedicated support but were constrained by platform complexity, the effort required to assemble panels, uneven incentives, interoperability gaps, and medico-legal uncertainty. Conclusions: Systematized second-opinion services for rare diseases are feasible and clinically relevant. Progress hinges on usability, aligned incentives, and pragmatic interoperability, advancing from registries toward bidirectional electronic health record connections, alongside prospective evaluations of outcomes, equity, experience, effectiveness, and costs. Full article

The integration of IT services is a critical challenge for public organizations that seek to modernize their operational ecosystems and strengthen mission-oriented processes. In the field of fiscal oversight, supreme audit institutions (SAIs) increasingly require systematized and interoperable service architectures to ensure transparency, accountability, and effective public resource control. However, existing literature reveals persistent gaps concerning how service integration models can be deployed and validated within complex government environments. This study describes an enterprise architecture-driven service integration model designed and evaluated within the Office of the General Comptroller of the Republic of Colombia (Contraloría General de la República, CGR). The study tests the hypothesis that an Enterprise Architecture-driven integration model provides the necessary structural coupling to align technical IT performance with the legal requirements of fiscal oversight, which is an alignment that typically does not appear in generic governance frameworks. The methodological approach followed in this study combines an IT service management maturity assessment, process analysis, architecture repository review, and iterative validation sessions with institutional stakeholders. The model integrates ITILv4 (Information Technology Infrastructure Library), TOGAF (The Open Group Architecture Framework), COBIT (Control Objectives for Information and Related Technologies), and ISO20000 into a coherent framework tailored to the operational and regulatory requirements of an SAI. Results show that the proposed model reduces service fragmentation, improves process standardization, strengthens information governance, and enables a unified service catalog aligned with fiscal oversight functions. The empirical validation demonstrates measurable improvements in service delivery, transparency, and organizational responsiveness. The study contributes to the field of applied system innovation by: (i) providing an integration model, which is scientifically grounded and evidence-based, (ii) demonstrating how hybrid governance and architecture frameworks can be adapted to complex public-sector environments, and (iii) offering a replicable approach for SAIs that seek to modernize their technological service ecosystems through enterprise architecture principles. Future research directions are also discussed to provide guidelines to advance integrated governance and digital transformation in oversight institutions. Full article

This paper presents an innovative approach to the design of intelligent software architecture for Digital Library Systems (DLSs) and the evaluation of this in the context of sustainable education. By leveraging Artificial Intelligence (AI) technologies, global cooperation and best practices in Software Engineering, we propose the design of a model that enhances the management, access and usability of digital libraries. Our framework introduces intelligent services for decision-making processes, research activities, and personalized learning experiences. Through global collaboration, our architecture aims to contribute significantly to achieving Sustainable Development Goal 4 (SDG4), ensuring inclusive and equitable education worldwide. Full article

Automatic vehicle detection and tracking are at the core of the latest smart city developments, enhancing mobility services across the globe. Nevertheless, research in this field often suffers from inconsistent results caused by heterogeneity in datasets, methodologies and evaluation metrics. These challenges highlight the need for this systematic review, which comprises the work of 29 peer-reviewed studies extracted from Scopus and ACM Digital Library published between 2020 and 2024, focusing on integrated vehicle detection–tracking systems using fixed top-down imagery. The selected works were critically examined according to their algorithms, methodological practices, dataset characteristics and performance metrics, culminating in a meta-analysis to quantify and fairly compare results. In parallel, the broader ecosystem surrounding vehicle detection and tracking was also explored to provide a complementary perspective, including evaluation standards and dataset diversity, helping to guide future works. The findings reveal that state-of-the-art research lacks standardization of metrics and reporting, heavily relies on datasets that are incompatible with tracking benchmarks and often limited in scenario diversity, and repeatedly exhibit methodological lenience compromising reproducibility and transparency. While the meta-analysis helps contextualize the best-reported implementations, the absence of standardized practices ultimately fragments the experiment. This review consolidates the current knowledge and suggests concrete directions to improve robustness, comparability and deployment of vehicle detection and tracking systems for future smart-cities infrastructures. Full article

Background: Preconception care (PCC) is a key element of preventive reproductive health, aiming to optimise maternal and child outcomes by addressing biomedical, behavioural, psychosocial, and genetic risks before conception. International frameworks provide clear guidance, yet implementation in many low- and middle-income countries remains inconsistent. Methods: A structured narrative review was conducted across PubMed, Web of Science, Cochrane Library, and Google Scholar, focusing on literature published between 2010 and 2025. Eligible sources included empirical studies, clinical guidelines, policy documents, and high-quality grey literature from health authorities. Quality, relevance, and applicability were assessed, with particular emphasis on European and Bulgarian contexts. Results: Evidence from diverse settings demonstrates that PCC interventions—such as chronic disease management, vaccination, lifestyle optimisation, and expanded carrier screening (ECS)—can reduce adverse pregnancy outcomes and prevent severe genetic disorders. Effective international models integrate PCC into primary care, leverage digital health tools, and ensure equitable access through public funding. In Bulgaria, PCC remains underdeveloped: genetic screening is not part of routine care, there are no national guidelines or surveillance systems, and only ~4% of women initiate folic acid supplementation before pregnancy. NGOs and EU-funded digital initiatives provide partial outreach but cannot replace state-supported services. Conclusions: Bulgaria urgently requires a coordinated national PCC strategy, incorporating standardised guidelines, provider training, digital platforms, and phased ECS introduction. Strengthening PCC delivery can reduce preventable maternal and neonatal morbidity, advance reproductive justice, and enhance the long-term sustainability of public health systems. These findings support the development of a publicly funded, guideline-driven national PCC strategy with phased introduction of expanded carrier screening under NHIF to improve equity and long-term system sustainability. Full article

Background: Modern rehabilitation approaches, encompassing physical, emotional, and social aspects, are gaining momentum in healthcare systems worldwide; however, their acceptance and effectiveness vary across different cultural contexts. Objective: This narrative review aims to produce a culturally informed overview of barriers and enablers, highlighting possible strategies to better align evidence-based rehabilitation with Saudi sociocultural realities. Methods: Drawing on literature from 2010 to 2024, this narrative review was conducted by searching the peer-reviewed literature from PubMed, Scopus, and the Saudi Digital Library using focused keywords. PICO framework was used to define inclusion and exclusion criteria. Relevant studies addressing cultural influences on rehabilitation adoption were included. Results: 1565 articles were initially identified from PubMed, Scopus, and the Saudi Digital Library. After careful screening, eight articles were included in the narrative review. We witnessed key factors relevant to the context of Saudi Arabia deriving health-seeking behaviors to be modesty, fatalism, family support, and religion. Factors possibly associated with the influence of physical therapy rehabilitation were gender, communication barriers, traditional healing practices, and culture and parental involvement. Conclusions: In Saudi Arabia, rehabilitation service utilization and practices may be prone to cultural factors. It is of utmost importance that healthcare providers step in and make sure that they sensitize themselves with cultural-specific awareness, knowledge, and competency to deliver optimal rehabilitation healthcare services that meet the standards and needs of the Saudi community. Full article

In the era of digital intelligence, information literacy (IL) competency has become a critical indicator for measuring the comprehensive quality and sustainable development potential of university’s education. Using Yancheng Institute of Technology as a case study, this study systematically elucidates the connotation and current development status of college students’ IL within the framework of sustainable development. An evaluation index system is constructed, comprising four dimensions: information awareness and attitude, information ethics, law and security, information knowledge and skills, and information integration and innovation. The study employs the Analytic Hierarchy Process (AHP) to determine the weights of indicators at various levels and integrates the Fuzzy Comprehensive Evaluation Method (FCEM) to establish a quantitative assessment model for IL competency. Empirical research demonstrates that the proposed model effectively enables a multidimensional and quantitative evaluation of students’ IL, with results that exhibit sound scientific validity and applicability. Based on the analysis, specific strategies are proposed to enhance students’ IL from the perspectives of curriculum design, teaching models, and library services, thereby providing theoretical references and practical pathways for advancing informatization and sustainable development in higher education. Full article