• Quality Improvement in Health Care
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• v.29 no.2
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• pp.32-46
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• 2023

Purpose: Fire response education is critical for healthcare providers working in hospitals to ensure a safe environment for patients and staff. However, a comprehensive review that thoroughly examines the contents, methodologies, and outcomes of fire response education in hospitals is currently lacking. Methods: We conducted a scoping review by adhering to the framework proposed by Arksey and O'Malley. We searched five electronic databases for literature published after 1990, using the key categories of "hospitals," "fires," and "education." As a result, we identified 15 relevant articles that met our inclusion criteria for the review. Results: Of the 15 articles, 12 had adopted a quasi-experimental design and the remaining 3 had employed a true experimental design. The majority of these studies (11 out of 15) were conducted in the United States, with 4 studies forming committees or teams dedicated to education. Simulation methods were used in 13 studies, while 2 studies had employed a combination of methods. All studies focused on first-response procedures based on RACE (Rescue, Alarm, Contain, Extinguish/Evacuation). Outcome measures included the learners' overall experience, performance in the educational settings, and performance in the field, with all studies reporting positive results following the educational interventions. Conclusion: Our review highlights the importance of multi-professional and multi-departmental educational strategies based on institutional-level initiatives for healthcare providers to create a safe hospital environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.903-921
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• 2024

Industry 5.0 puts forward higher requirements for smart cities, including low-carbon, sustainable, and people-oriented, which pose challenges to the design of smart cities. In response to the above challenges, this study introduces the cyber-physical-social system (CPSS) and parallel system theory into the design of smart cities, and constructs a smart city framework based on parallel system theory. On this basis, in order to enhance the security of smart cities, a sustainable patrol subsystem for smart cities has been established. The intelligent patrol system uses a drone platform, and the trajectory planning of the drone is a key problem that needs to be solved. Therefore, a mathematical model was established that considers various objectives, including minimizing carbon emissions, minimizing noise impact, and maximizing coverage area, while also taking into account the flight performance constraints of drones. In addition, an improved metaheuristic algorithm based on ant colony optimization (ACO) algorithm was designed for trajectory planning of patrol drones. Finally, a digital environmental map was established based on real urban scenes and simulation experiments were conducted. The results show that compared with the other three metaheuristic algorithms, the algorithm designed in this study has the best performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.881-902
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• 2024

Fast decision support systems and accurate diagnosis have become significant in the rapidly growing healthcare sector. As the number of disparate medical IoT devices connected to the human body rises, fast and interrelated healthcare data retrieval gets harder and harder. One of the most important requirements for the Healthcare Internet of Things (HIoT) is semantic interoperability. The state-of-the-art HIoT systems have problems with bandwidth and latency. An extension of cloud computing called fog computing not only solves the latency problem but also provides other benefits including resource mobility and on-demand scalability. The recommended approach helps to lower latency and network bandwidth consumption in a system that provides semantic interoperability in healthcare organizations. To evaluate the system's language processing performance, we simulated it in three different contexts. 1. Polysemy resolution system 2. System for hyponymy-hypernymy resolution with polysemy 3. System for resolving polysemy, hypernymy, hyponymy, meronymy, and holonymy. In comparison to the other two systems, the third system has lower latency and network usage. The proposed framework can reduce the computation overhead of heterogeneous healthcare data. The simulation results show that fog computing can reduce delay, network usage, and energy consumption.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.644-654
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• 2024

After the Tohoku earthquake and tsunami (Japan, 2011), regulatory efforts to mitigate external hazards have increased both the safety requirements and the total capital cost of nuclear power plants (NPPs). In these circumstances, identifying not only disaster robustness but also cost-effective capacity setting of NPPs has become one of the most important tasks for the nuclear power industry. A few studies have been performed to relocate the seismic capacity of NPPs, yet the effects of multiple hazards have not been accounted for in NPP capacity optimization. The major challenges in extending this problem to the multihazard dimension are (1) the high computational costs for both multihazard risk quantification and system-level optimization and (2) the lack of capital cost databases of NPPs. To resolve these issues, this paper proposes an effective method that identifies the optimal multihazard capacity of NPPs using a multi-objective genetic algorithm and the two-stage direct quantification of fault trees using Monte Carlo simulation method, called the two-stage DQFM. Also, a capacity-based indirect capital cost measure is proposed. Such a proposed method enables NPP to achieve safety and cost-effectiveness against multi-hazard simultaneously within the computationally efficient platform. The proposed multihazard capacity optimization framework is demonstrated and tested with an earthquake-tsunami example.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.793-802
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• 2024

In the framework of the European project SAMOSAFER, this numerical study focuses on some thermal aspects of the Emergency Draining Tank (EDT) located underneath the core of a Molten Salt Reactor. In case of an emergency, this tank passively receives the liquid fuel salt and is designed to ensure a subcritical state. An important requirement is that the fuel does not overheat to maintain the EDT Hastelloy container integrity. The present EDT is based upon a group of hexagonal cooling assemblies arranged in a hexagonal grid and cooled down thanks to conduction through the inert salt layer up to an air flow in charge of removing the heat. This numerical thermal study relies on a conjugated heat transfer analysis coupling a Finite Element solid thermal code (SYRTHES) and two instances of a Finite Volume CFD codes (Code_Saturne). Calculations on an initial design suggest that a simple center airpipe flow is likely to not sufficiently cool the device. Alternative solutions have been evaluated. Introduction of fins to enhance the heat transfer do not bring a noticeable improvement regarding maximum temperature reached. However, a solution in which the central pipe air flow is replaced by several cooling channels located closer to the fuel is investigated and suggests a better cooling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1462-1477
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• 2024

With the evolving complexity of connected vehicle features, the volume and diversity of data generated during driving continue to escalate. Enabling data sharing among interconnected vehicles holds promise for improving users' driving experiences and alleviating traffic congestion. Yet, the unintentional disclosure of users' private information through data sharing poses a risk, potentially compromising the interests of vehicle users and, in certain cases, endangering driving safety. Federated learning (FL) is a newly emerged distributed machine learning paradigm, which is expected to play a prominent role for privacy-preserving learning in autonomous vehicles. While FL holds significant potential to enhance the architecture of the Internet of Vehicles (IoV), the dynamic mobility of vehicles poses a considerable challenge to integrating FL with vehicular networks. In this paper, a novel clustered FL framework is proposed which is efficient for reducing communication and protecting data privacy. By assessing the similarity among feature vectors, vehicles are categorized into distinct clusters. An optimal vehicle is elected as the cluster head, which enhances the efficiency of personalized data processing and model training while reducing communication overhead. Simultaneously, the Local Differential Privacy (LDP) mechanism is incorporated during local training to safeguard vehicle privacy. The simulation results obtained from the 20newsgroups dataset and the MNIST dataset validate the effectiveness of the proposed scheme, indicating that the proposed scheme can ensure data privacy effectively while reducing communication overhead.

• Steel and Composite Structures
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• v.51 no.5
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• pp.499-507
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• 2024

The paper delves into an emerging paradigm shift in architectural design, focusing on the development of a cutting-edge methodological framework for the artistic enhancement of nanocomposite brick facades in building construction. This innovative approach represents a fusion of art and science, harnessing the potential of advanced nanotechnology to redefine the aesthetic and functional properties of building exteriors. Central to this new methodology is the integration of state-of-the-art materials and fabrication techniques, aimed at not only elevating the visual appeal of architectural structures but also enhancing their structural robustness and environmental sustainability. By leveraging the unique characteristics of nanocomposite materials, the proposed method opens up new possibilities for pushing the boundaries of traditional brick facade design. Through a meticulous exploration of the intricacies involved in implementing this novel approach, the paper elucidates the transformative impact it can have on the architectural landscape. By marrying creativity with technical precision, the method environment for art design of nanocomposite brick facades promises to usher in a new era of sustainable, visually captivating, and structurally resilient building facades that are poised to redefine the very essence of architectural aesthetics.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.63-67
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• 2024

Recently, artificial intelligence (AI) workloads encompassing various industries such as smart logistics, FinTech, and entertainment are being executed on the cloud. In this paper, we address the scheduling issues of various AI workloads on a multi-tenant cloud system composed of heterogeneous GPU clusters. Traditional scheduling decreases GPU utilization in such environments, degrading system performance significantly. To resolve these issues, we present a new scheduling approach utilizing genetic algorithm-based optimization techniques, implemented within a process-based event simulation framework. Trace driven simulations with diverse AI workload traces collected from Alibaba's MLaaS cluster demonstrate that the proposed scheduling improves GPU utilization compared to conventional scheduling significantly.

• Smart Structures and Systems
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• v.33 no.3
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• pp.177-188
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• 2024

The fatigue-induced sequential failure of a structure having structural redundancy requires system-level analysis to account for stress redistribution. System reliability-based design optimization (SRBDO) for preventing fatigue-initiated structural failure is numerically costly owing to the inclusion of probabilistic constraints. This study incorporates the Branch-and-Bound method employing system reliability Bounds (termed the B³ method), a failure-path structural system reliability analysis approach, with a metaheuristic optimization algorithm, namely grey wolf optimization (GWO), to obtain the optimal design of structures under fatigue-induced system failure. To further improve the efficiency of this new optimization framework, an additional bounding rule is proposed in the context of SRBDO against fatigue using the B³ method. To demonstrate the proposed method, it is applied to complex problems, a multilayer Daniels system and a three-dimensional tripod jacket structure. The system failure probability of the optimal design is confirmed to be below the target threshold and verified using Monte Carlo simulation. At earlier stages of the optimization, a smaller number of limit-state function evaluation is required, which increases the efficiency. In addition, the proposed method can allocate limited materials throughout the structure optimally so that the optimally-designed structure has a relatively large number of failure paths with similar failure probability.

• Steel and Composite Structures
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• v.52 no.4
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• pp.461-473
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• 2024

This study focuses on the reliability of a transmission line under wind excitation and evaluates the failure probability using explicit data resources. The data-driven framework for calculating the failure probability of a transmission line subjected to wind loading is presented, and a probabilistic method for estimating the yearly extreme wind speeds in each wind direction is provided to compensate for the incompleteness of meteorological data. Meteorological data from the Xuwen National Weather Station are used to analyze the distribution characteristics of wind speed and wind direction, fitted with the generalized extreme value distribution. Then, the most vulnerable tower is identified to obtain the fragility curves in all wind directions based on uncertainty analysis. Finally, the failure probabilities are calculated based on the presented method. The simulation results reveal that the failure probability of the employed tower increases over time and that the joint probability distribution of the wind speed and wind direction must be considered to avoid overestimating the failure probability. Additionally, the mixed wind climates (synoptic wind and typhoon) have great influence on the estimation of structural failure probability and should be considered.