Search Results (170)

The increasing need for precise testing in battery and electronic component development has driven the demand for modular and scalable laboratory systems. This paper presents the design and initial implementation of a LabVIEW-based measurement system tailored for ISO/IEC 17025-compliant testing environments. The system’s software architecture is modular and built around a Hardware Abstraction Layer, enabling the integration of various remotely controlled instruments, such as programmable power supplies, electronic loads, and climate chambers. LabVIEW’s object-oriented programming and multi-threaded execution environment allows synchronized control and real-time data acquisition. Test procedures are defined using a JSON-based sequence structure, supporting repeatable testing. A graphical editor provides an intuitive interface for configuring test steps, ensuring ease of use. The system is designed to support future expansion, including high-speed measurement modules and parallel test execution. This solution lays the foundation for a reliable and extensible automated testing platform that aligns with modern industrial and regulatory standards. Full article

Quality Infrastructure (QI) underpins safe, sustainable, and competitive markets through metrology, standardization, accreditation, conformity assessment, and market surveillance. While mandatory schemes address immediate safety concerns, voluntary conformity assessments offer strategic advantages for emerging technologies by enabling market differentiation, regulatory anticipation, and gradual adaptation without compliance burdens. Focusing on Brazil’s National Institute of Metrology, Quality, and Technology (Inmetro), this study addresses operational gaps in implementing voluntary schemes under the modernized regulatory framework introduced by Inmetro’s Ordinance No. 30/2022. Using electric mobility to illustrate sustainability pathways, we show how voluntary assessments can operationalize and enable measurement of environmental and social co-benefits. Our five-stage qualitative methodology integrated documentary analysis of Brazilian regulations; comparative examination of approaches in the European Union, the United States, and South Korea; development of a 14-step methodological roadmap aligned with ISO/IEC standards; expert validation through a structured questionnaire with twelve specialists from government, industry, academia, and certification bodies; and systematic consolidation of feedback. The roadmap provides operational guidance on product definition, technical requirements, certification processes, and continuous improvement, with optional modules for advanced technologies and ESG criteria. Expert validation confirmed viability while identifying barriers (costs, laboratory capacity, cultural limitations) and enablers (fiscal incentives, procurement recognition). When applied to electric mobility, voluntary battery certification enhances safety and performance, charging infrastructure assessment improves reliability, and component schemes enable circular economy principles, directly supporting the Sustainable Development Goals. We conclude that strategically designed voluntary conformity schemes can accelerate regulatory convergence, strengthen competitiveness, and contribute to sustainability outcomes in modernizing economies. Full article

Digital Twin (DT) technology has rapidly matured from pilot projects to integral components of advanced asset management and process optimization in the oil and gas (O&G) industry. This review provides a structured synthesis of the current state of digital twin frameworks, with a focus on offshore and topside gas-processing systems, such as those found on Floating Production Storage and Offloading (FPSO). Emphasis is placed on high-fidelity process simulations and scalable architectures integrating real-time data with advanced analytics. Drawing on over 85 peer-reviewed sources and industrial frameworks, the paper outlines modular DT architectures, encompassing steady-state and dynamic process simulations (e.g., Aspen HYSYS), reduced-order and hybrid machine learning models, co-simulation environments, and advanced equation-of-state packages (e.g., GERG-2008). Special attention is given to compressor map integration, Equations of State (EOS) selection, ISO/IEC standard compliance, and digital thread continuity. Additionally, the review explores economic and sustainability-driven DT implementations, including flare and methane mitigation, ISO 50001-aligned energy optimization, and lifecycle/decommissioning strategies. It concludes with a technical and economic assessment of DT maturity for gas compression facilities, identifying research gaps in standardization, long-term validation, and cybersecurity integration. The insights provided are intended to support decision-makers, engineers, and researchers in deploying scalable, auditable, and high-impact DT solutions across the O&G value chain. Full article

Universities face continuous challenges in ensuring rapid and efficient communication during emergencies due to outdated, fragmented, and manual notification systems. This research presents the design, development, and implementation of a multiplatform mobile application to optimize emergency notifications at the Escuela Superior Politécnica de Chimborazo (ESPOCH). The application, developed using the Flutter framework, offers real-time alert dispatch, geolocation services, and seamless integration with ESPOCH’s Security Unit through Application Programming Interfaces (APIs). A descriptive and applied research methodology was adopted, analyzing existing notification workflows and evaluating agile development methodologies. MOBILE-D was selected for its rapid iteration capabilities and alignment with small development teams. The application’s architecture incorporates a Node.js backend, Firebase Realtime Database, Google Maps API, and the ESPOCH Digital ID API for robust and scalable performance. Efficiency metrics were evaluated using ISO/IEC 25010 standards, focusing on temporal behavior. The results demonstrated a 53.92% reduction in response times compared to traditional notification processes, enhancing operational readiness and safety across the campus. This study underscores the importance of leveraging mobile technologies to streamline emergency communication and provides a scalable model for educational institutions seeking to modernize their security protocols. Full article

Shore power systems, also known as cold ironing or shore-to-ship (STS) connections, are increasingly recognized as a viable solution to reduce emissions and noise from ships during berthing operations. This paper provides a comprehensive overview of shore power technology, with a focus on typical onboard energy consumption profiles across different types of ship, the main electrical architectures used in shore-side systems, and the compatibility challenges related to frequency, voltage, and control integration. The paper reviews international standards, particularly the ISO/IEC/IEEE 80005 series, that define technical requirements for interoperability and safety. A detailed analysis of recent patents highlights technological innovations in mobility, conversion topologies, and high-voltage integration. In addition, commercially available shore power solutions from major manufacturers are surveyed, with comparative data on power ratings, voltage levels, and converter topologies. Finally, the study discusses current limitations and outlines development directions for Onshore Power Supply systems, including regulatory developments, digital integration, and grid support functionalities. The insights presented aim to support the design, standardization, and deployment of efficient and scalable STS systems in line with global maritime decarbonization goals. Full article

With the growing intensity of global cybersecurity threats and the rapid advancement of attack techniques, strengthening enterprise information and communication technology (ICT) infrastructures and enhancing digital forensics have become critical imperatives. Cloud environments, in particular, present substantial challenges due to the limited availability of effective forensic tools and the pressing demand for impartial and legally admissible digital evidence. To address these challenges, we propose a proactive digital forensics mechanism (P-DFM) designed for emergency incident management in enterprise settings. This mechanism integrates a range of forensic tools to identify and preserve critical digital evidence. It also incorporates the MITRE ATT&CK framework with Security Information and Event Management (SIEM) and Managed Detection and Response (MDR) systems to enable comprehensive and timely threat detection and analysis. The principal contribution of this study is the formulation of a novel Proactive Digital Evidence Forensics Standard Operating Procedure (P-DEFSOP), which enhances the accuracy and efficiency of security threat detection and forensic analysis while ensuring that digital evidence remains legally admissible. This advancement significantly reinforces the cybersecurity posture of enterprise networks. Our approach is systematically grounded in the Digital Evidence Forensics Standard Operating Procedure (DEFSOP) framework and complies with internationally recognized digital forensic standards, including ISO/IEC 27035 and ISO/IEC 27037, to ensure the integrity, reliability, validity, and legal admissibility of digital evidence throughout the forensic process. Given the complexity of cloud computing infrastructures—such as Chunghwa Telecom HiCloud, Amazon Web Services (AWS), Google Cloud, and Microsoft Azure—we underscore the critical importance of impartial and standardized digital forensic services in cloud-based environments. Full article

The rapid adoption of electric vehicles (EVs) has intensified the demand for intelligent, scalable, and interoperable charging infrastructure. Traditional EV charging networks based on the Open Charge Point Protocol (OCPP) face challenges related to dynamic load management, cybersecurity, and efficient integration with renewable energy sources. This paper presents a novel AI-driven framework that integrates federated learning, predictive analytics, and real-time control within OCPP-compliant networks to enhance performance and sustainability. The proposed system utilizes edge AI modules at charging stations, supported by a central aggregator that employs federated learning to preserve data privacy while enabling network-wide optimization. A case study involving simulated smart charging stations demonstrates significant improvements, including an 18% reduction in peak load demand, a 29% increase in forecasting accuracy (MAPE of 8.5%), a 10% decrease in average charging wait times, and a 12% increase in on-site solar energy utilization. The framework’s compatibility with OCPP and related standards (e.g., IEC 61851, ISO 15118) ensures ease of deployment on existing infrastructure. These results indicate that the proposed AI-OCPP integration provides a scalable and intelligent foundation for next-generation EV charging networks that align with the goals of sustainable transportation and smart grid evolution. Full article

Serious games for children with Autism Spectrum Disorder (ASD) require rigorous evaluation frameworks that capture neurodivergent interaction patterns. This pilot study designed, developed, and evaluated a serious game for children with ASD, focusing on operability assessment aligned with ISO/IEC 25010:2023 standards. A repeated-measures design involved ten children with ASD from the Carlos Garbay Special Education Institute in Riobamba, Ecuador, across 25 gameplay sessions. A bespoke operability algorithm incorporating four weighted components (ease of learning, user control, interface familiarity, and message comprehension) was developed through expert consultation with certified ASD therapists. Statistical study used linear mixed-effects models with Kenward–Roger correction, supplemented by thorough validation including split-half reliability and partial correlations. The operability metric demonstrated excellent internal consistency (split-half reliability = 0.94, 95% CI [0.88, 0.97]) and construct validity through partial correlations controlling for performance (difficulty: r_partial = 0.42, p = 0.037). Eighty percent of sessions achieved moderate-to-high operability levels (M = 45.07, SD = 10.52). In contrast to requirements, operability consistently improved with increasing difficulty level (Easy: M = 37.04; Medium: M = 48.71; Hard: M = 53.87), indicating that individuals with enhanced capabilities advanced to harder levels. Mixed-effects modeling indicated substantial difficulty effects (H = 9.36, p = 0.009, ε² = 0.39). This pilot study establishes preliminary evidence for operability assessment in ASD serious games, requiring larger confirmatory validation studies (n ≥ 30) to establish broader generalizability and standardized instrument integration. The positive difficulty–operability association highlights the importance of adaptive game design in supporting skill progression. Full article

Comprehensive healthcare seeks to uphold the right to health by providing patient-centred care in both personal and work environments. However, the unequal distribution of healthcare services significantly restricts access in remote or underserved areas—a challenge that is particularly critical in mental health care within low-income countries. On average, there is only one psychiatrist for every 200,000 people, which severely limits early diagnosis and continuous monitoring in patients’ daily environments. In response to these challenges, this research explores the feasibility of implementing an information system that integrates cloud computing with an intelligent Facial Expression Recognition (FER) module to enable psychologists to remotely and periodically monitor patients’ emotional states. This approach enhances comprehensive clinical assessments, supporting early detection, ongoing management, and personalised treatment in mental health care. This applied research follows a descriptive and developmental approach, aiming to design, implement, and evaluate an intelligent cloud-based solution that enables remote monitoring of patients’ emotional states through Facial Expression Recognition (FER). The methodology integrates principles of user-centred design, software engineering best practices, and machine learning model development, ensuring a robust and scalable solution aligned with clinical and technological requirements. The development process followed the Software Development Life Cycle (SDLC) and included functional, performance, and integration testing. To assess overall system quality, we defined an evaluation framework based on ISO/IEC 25010 quality characteristics: functional suitability, performance efficiency, usability, and security. The intelligent FER model achieved strong validation results, with a loss of 0.1378 and an accuracy of 96%, as confirmed by the confusion matrix and associated performance metrics. Full article

This paper presents the design, development, and evaluation of the REDI Monitoring System, a web-based platform aimed at enhancing the management and monitoring of funded research projects at Romblon State University (RSU). The system provides streamlined functionalities for proposal creation, submission, collaborator management, and administrative oversight, tailored to the needs of both students and faculty members. The development process adhered to established software engineering standards to ensure robustness and usability. A comprehensive testing phase was conducted with 50 participants, including students and faculty, following the ISO/IEC/IEEE 29119 software testing framework. Results demonstrated high user satisfaction, with over 90% of participants finding the system user-friendly and reliable. Minor areas for improvement were identified in notification delivery and interface responsiveness for faculty users. The REDI Monitoring System presents an effective and efficient solution that supports RSU’s research administration processes, fostering greater collaboration and transparency in funded research activities. Full article

This research proposes a tailored Systems Engineering (SE) design process for the development of Attitude and Orbit Control Systems (AOCS) for small satellites operating in formation. These missions, known as Distributed Spacecraft Missions (DSMs), involve groups of satellites—commonly referred to as satellite constellations—whose primary objective is to maintain controlled relative positioning in three dimensions. In these configurations, each satellite may serve a specific role. For instance, one may act as a navigation reference, while another functions as a communication relay. These roles support synchronized control and ensure mission cohesion. To achieve precise relative positioning, the system must integrate specialized sensors and maintain continuous inter-satellite communication. This capability enables precise navigation across both the space and ground segments, while ensuring high control accuracy. As such, the development of AOCS must be approached as a complex systems challenge, involving the coordinated behavior of multiple autonomous elements working toward a shared mission objective. This study tailors the SE process using the ISO/IEC 15288 standard and incorporates a Model-Based Systems Engineering (MBSE) approach to enhance traceability, consistency, and architectural coherence throughout the system lifecycle. As a result, it proposes a customized SE process for AOCS development that begins in the mission’s conceptual phase and addresses the specific functional and operational demands of formation flying. A conceptual example illustrates the proposed process. It focuses on subsystem coordination, communication needs, and the architecture required to support an AOCS for autonomous satellite formations. Full article

Recent advancements in emerging technologies such as IoT and AI have driven digital innovation, while also accelerating the sophistication of cyberattacks and expanding the attack surface. In particular, inter-state cyber warfare, sophisticated ransomware threats, and insider-led personal data breaches have emerged as significant new security risks. In response, this study proposes a Privacy-Aware Integrated Log System model developed to mitigate diverse security threats. By analyzing logs generated from personal information processing systems and security systems, integrated scenarios were derived. These scenarios are designed to defend against various threats, including insider attempts to leak personal data and the evasion of security systems, enabling scenario-based contextual analysis that goes beyond simple event-driven detection. Furthermore, the Analytic Hierarchy Process (AHP) was applied to quantitatively assess the relative importance of each scenario, demonstrating the model’s practical applicability. This approach supports early identification and effective response to personal data breaches, particularly when time and resources are limited by focusing on the top-ranked scenarios based on relative importance. Therefore, this study is significant in that it goes beyond fragmented log analysis to establish a privacy-oriented integrated log system from a holistic perspective, and it further validates its operational efficiency in field applications by conducting an AHP-based relative importance evaluation. Full article

In an era of exponential data growth, ensuring high data quality has become essential for effective, evidence-based decision making. This study presents a structured and comparative review of the field by integrating data classifications, quality dimensions, assessment methodologies, and modern software tools. Unlike earlier reviews that focus narrowly on individual aspects, this work synthesizes foundational concepts with formal frameworks, including the Findable, Accessible, Interoperable, and Reusable (FAIR) principles and the ISO/IEC 25000 series on software and data quality. It further examines well-established assessment models, such as Total Data Quality Management (TDQM), Data Warehouse Quality (DWQ), and High-Quality Data Management (HDQM), and critically evaluates commercial platforms in terms of functionality, AI integration, and adaptability. A key contribution lies in the development of conceptual mappings that link data quality dimensions with FAIR indicators and maturity levels, offering a practical reference model. The findings also identify gaps in current tools and approaches, particularly around cost-awareness, explainability, and process adaptability. By bridging theory and practice, the study contributes to the academic literature while offering actionable insights for building scalable, standards-aligned, and context-sensitive data quality management strategies. Full article

With the emergence of Survey 4.0, the oil and gas (O & G) industry is now considering spatial digital twins during their field design to enhance visualization, efficiency, and safety. O & G companies have already initiated investments in the research and development of spatial digital twins to build digital mining models. Existing studies commonly adopt surveys and case studies as their evaluation approach to validate the feasibility of spatial digital twins and related technologies. However, this approach requires high costs and resources. To address this gap, this study explores the feasibility of the informed argument method within the design science framework. A land survey data model (LSDM)-based digital twin prototype for O & G field design, along with 3D spatial datasets located in Lot 2 on RP108045 at petroleum lease 229 under the Department of Resources, Queensland Government, Australia, was selected as a case for this study. The ISO/IEC 25010 model was adopted as a methodology for this study to evaluate the prototype and Digital Twin Victoria (DTV). It encompasses eight metrics, such as functional suitability, performance efficiency, compatibility, usability, security, reliability, maintainability, and portability. The results generated from this study indicate that the prototype encompasses a standard level of all parameters in the ISO/IEC 25010 model. The key significance of the study is its methodological contribution to evaluating the spatial digital twin models through cost-effective means, particularly under circumstances with strict regulatory requirements and low information accessibility. Full article

The increased occurrence and severity of cyber-attacks on critical infrastructure have underscored the need to embrace systematic and prospective approaches to resilience. The current research takes as its hypothesis that the InfraGuard Cybersecurity Framework—a capability model that measures the maturity of cyber resilience through three functional pillars, Cyber as a Shield, Cyber as a Space, and Cyber as a Sword—is an implementable and understandable means to proceed with. The model treats the significant aspects of situational awareness, active defense, risk management, and recovery from incidents and is measured using globally standardized maturity models like ISO/IEC 15504, NIST CSF, and COBIT. The contributions include multidimensional measurements of resilience, a scored scale of capability (0–5), and domain-based classification enabling organizations to assess and enhance their cybersecurity situation in a formalized manner. The framework’s applicability is illustrated in three exploratory settings of power grids, healthcare systems, and airports, each constituting various levels of maturity in resilience. This study provides down-to-earth recommendations to policymakers through the translation of the attributes of resilience into concrete assessment indicators, promoting policymaking, investment planning, and global cyber defense collaboration. Full article