• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1141-1163
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• 2019

In an effort to minimize operational expenses and supply users with more scalable services, distributed applications are actually going towards the Cloud. These applications, sent out over multiple environments and machines, are composed by inter-connecting independently developed services and components. The implementation of such programs on the Cloud is difficult and generally carried out either by hand or perhaps by composing personalized scripts. This is extremely error prone plus it has been found that misconfiguration may be the root of huge mistakes. We introduce AutoBot, a flexible platform for modeling, installing and (re)configuring complex distributed cloud-based applications which evolve dynamically in time. AutoBot includes three modules: A simple and new model describing the configuration properties and interdependencies of components; a dynamic protocol for the deployment and configuration ensuring appropriate resolution of these interdependencies; a runtime system that guarantee the proper configuration of the program on many virtual machines and, if necessary, the reconfiguration of the deployed system. This reduces the manual application deployment process that is monotonous and prone to errors. Some validation experiments were conducted on AutoBot in order to ensure that the proposed system works as expected. We also discuss the opportunity of reusing the platform in the transition of applications from Cloud to Fog computing.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• Journal of Environmental Science International
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• v.29 no.12
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• pp.1153-1170
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• 2020

With global warming and the rapid increase in urbanization accompanied by a concentration of population, the urban heat island effects (UHI) have become an important environmental issue. In this study, rooftop greening and permeable asphalt pavement were selected as measures to reduce urban heat island and applied to a simple virtual urban environment to simulate temperature change using ENVI-met. A total of five measures were tested by dividing the partial and whole area application of each measure. The results showed that the temperature range of the base experiment is 33.11-37.11 ℃, with the UTCI comfort level described as strong heat and very strong heat stress. A case applied permeable asphalt has a greater temperature difference than a rooftop greening case, the larger the area where each condition was applied, the greater the temperature change was.

• Earthquakes and Structures
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• v.19 no.6
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• pp.459-469
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• 2020

An external prestressed steel-bar truss unit was developed as a new strengthening technology to enhance the seismic performance of an in-plane masonry wall structure while taking advantage of the benefits of a prestressed system. The presented method consists of six steel bars: two prestressed vertical bars to introduce a prestressing force on the masonry wall, two diagonal bars to resist shear deformation, and two horizontal bars to maintain the configuration. To evaluate the effects of this new technique, four full-scale specimens, including a control specimen, were tested under combined loadings that included constant-gravity axial loads and cyclic lateral loads. The experimental results were analyzed in terms of the shear strength, initial stiffness, dissipated energy, and strain history. The efficiency of the external prestressed steel-bar truss unit was validated. In particular, a retrofitted specimen with an axial load level of 0.024 exhibited a more stable post behavior and higher energy dissipation than a control specimen with an observed complete sliding failure. The four vertical bars of the adjacent retrofitting units created a virtual column, and their strain values did not change until they reached the peak shear strength. The shear capacity of the masonry wall structure with external prestressed steel-bar truss units could be predicted using the model suggested by Yang et al.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.3
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• pp.272-280
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• 2021

We research and develop a SW-based virtual testing product that can be commonly used in the design/development of non-communication EW systems before the production of physical test products. Through this study, we have developed M&S technology to improve the accuracy of EW weapon system analysis/design and to verify and predict the performance of EW equipment, and to develop proven engineering module models and model base systems. It proposes a technology to build an EW M&S framework that can flexibly link/integrate various engineering/engage-level EW heterogeneous M&S systems.

• Journal of Korea Game Society
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• v.21 no.1
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• pp.67-80
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• 2021

The purpose of this study were to develop VR-based cooking serious game(VR-Cook) for students with intellectual disabilities and to validate effectiveness. The VR-Cook was developed using the ASSURE model. Twenty students with intellectual disabilities were participated to verify effectiveness. Ten students were assigned to the experimental group and the others to the control group. The control group received traditional interventions, and the experimental group participated in the intervention combining traditional intervention with VR-Cook. Evaluations were made at three times, and evaluation data were analyzed with repeated two-way ANOVA. The experimental group has improved more than control group in cooking activities and class attitudes.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.1
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• pp.33-42
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• 2021

The design response spectrum presented in the seismic design standard reflects the characteristics of the tectonic environment at a site. However, since the design response spectrum does not represent the ground motion with a specific earthquake magnitude or distance, input ground motions for response history analysis need to be selected reasonably. It is appropriate to use observed ground motions recorded in Korea for the seismic design. However, recently recorded ground motions in the Gyeongju (2016) or Pohang (2017) earthquakes are not compatible with the design response spectrum. Therefore, it is necessary to convert the recorded ground motion in Korea to a model similar to the design response spectrum. In this study, several approaches to adjust the spectral acceleration level at each period range were tested. These are the intrinsic and scattering attenuation considering the earthquake environment, magnitude, distance change by the green function method, and a rupture propagation direction's directivity effect. Using these variables, the amplification ratio for the representative natural period was regressed. Finally, the optimum condition compatible with the design response spectrum was suggested, and the validation was performed by converting the recorded ground motion.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.1
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• pp.123-135
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• 2021

This study provides basic information for the convenient size selection of T-shirts in an online purchasing environment. The best preferred T-shirts fit was selected among five sizes of T-shirts according to body size group. The subjects were 103 students majoring in clothing. After setting a virtual model with her own body sizes, the subjects chose the best preferred fit among five sizes of T-shirts that included the one suitable to their bust circumference, two smaller T-shirts and two larger T-shirts. As a result, they preferred the fit of larger size T-shirts than body size, but they preferred a different fit by the body characteristic group such as waist height group and hip circumference group. T-shirt length was affected by waist height; in addition, shoulder ease was affected by hip circumference and bust circumference. Therefore waist height and hip circumference should be considerable sizes when consumers choose T-shirts sizes with a preferred fit.

• Journal of Information Technology Services
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• v.20 no.5
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• pp.189-207
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• 2021

Voice interaction combined with artificial intelligence is poised to revolutionize human-computer interactions with the advent of virtual assistants. This paper is analyzing interactive elements of AI-based voice recognition services such as sympathy, assurance, intimacy, and trust on intention to use. The questionnaire was carried out for 284 smartphone/smart TV users in Korea. The collected data was analyzed by structural equation model analysis and bootstrapping. The key results are as follows. First, AI-based voice recognition service characteristics such as sympathy, assurance, intimacy, and trust have positive effects on interactivity with the AI-based voice recognition service. Second, the interactivity with the AI-based voice recognition service has positive effects on intention to use. Third, AI-based voice recognition service characteristics such as interactional enjoyment and intimacy have directly positive effects on intention to use. Fourth, AI-based voice recognition service characteristics such as sympathy, assurance, intimacy and trust have indirectly positive effects on intention to use the AI-based voice recognition service by mediating the effect of the interactivity with the AI-based voice recognition service. It is meaningful to investigate factors affecting the interactivity and intention to use voice recognition assistants. It has practical and academic implications.

• Journal of Korean Academy of Nursing
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• v.51 no.6
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• pp.648-660
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• 2021

Purpose: This study aimed to develop an emerging infectious disease (COVID-19) simulation module for nursing students and verify its effectiveness. Methods: A one-group pretest-posttest quasi-experimental study was conducted with 78 under-graduate nursing students. A simulation module was developed based on the Jeffries simulation model. It consisted of pre-simulation lectures on disaster nursing including infectious disease pandemics, practice, and debriefings with serial tests. The scenarios contained pre-hospital settings, home visits, arrival to the emergency department, and follow-up home visits for rehabilitation. Results: Disaster preparedness showed a statistically significant improvement, as did competencies in disaster nursing. Confidence in disaster nursing increased, as did willingness to participate in disaster response. However, critical thinking did not show significant differences between time points, and neither did triage scores. Conclusion: The developed simulation program targeting an infectious disease disaster positively impacts disaster preparedness, disaster nursing competency, and confidence in disaster nursing, among nursing students. Further studies are required to develop a high-fidelity module for nursing students and medical personnel. Based on the current pandemic, we suggest developing more scenarios with virtual reality simulations, as disaster simulation nursing education is required now more than ever.