• Journal of The Korean Society For Urban Railway
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• v.6 no.4
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• pp.279-286
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• 2018

Recently, a safety control platform to monitor the safety of train operation in real time and prevent accidents and risks through control is under study. In the initial design, DDS communication method supporting distributed network is adopted for real-time processing of large amount of data according to the integration of existing distributed safety data. However, communication between server and console inside the safety control platform is applied to existing TCP socket communication. In the case of TCP socket communication, it is possible to process data for a small system of a safety control test bed by one-to-one communication. However, if the data is expanded all over the country in the future, it becomes difficult to cope with a case where communication traffic occurs due to vast amount of data. In this paper, we propose DDS communication method to support distributed network between server and console of security control platform, and demonstrate TCP socket and DDS method, and compare throughput and speed. As a result, we have found that the scalability and flexibility are improved in case of applying DDS communication to future systems.

• Safety and Health at Work
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• v.7 no.3
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• pp.185-193
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• 2016

Background: Management and workers in small and medium-sized enterprises (SMEs) often find it hard to comprehend the requirements related to controlling risks due to exposure to substances. An intervention study was set up in order to support 45 SMEs in improving the management of the risks of occupational exposure to chemicals, and in using the control banding tool and exposure model Stoffenmanager in this process. Methods: A 2-year intervention study was carried out, in which a mix of individual and collective training and support was offered, and baseline and effect measurements were carried out by means of structured interviews, in order to measure progress made. A seven-phase implementation evolutionary ladder was used for this purpose. Success and failure factors were identified by means of company visits and structured interviews. Results: Most companies clearly moved upwards on the implementation evolutionary ladder; 76% of the companies by at least one phase, and 62% by at least two phases. Success and failure factors were described. Conclusion: Active training and coaching helped the participating companies to improve their chemical risk management, and to avoid making mistakes when using and applying Stoffenmanager. The use of validated tools embedded in a community platform appears to support companies to organize and structure their chemical risk management in a business-wise manner, but much depends upon motivated occupational health and safety (OHS) professionals, management support, and willingness to invest time and means.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.181-189
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• 2021

The COVID-19 pandemic has impacted the tourism industry due to the resulting travel restrictions as well as a slump in demand among travelers. The tourism industry has been massively affected by the spread of coronavirus, as many countries have introduced travel restrictions in an attempt to contain its spread. In Vietnam, the government has largely been credited for the country's success in keeping COVID-19 transmission rates under control. Early awareness of the pandemic, appropriate, drastic, and people-centric measures, as well as public support, are the main factors behind the success of Vietnam. In that context, it is observed that people's travel demand has bounced back and this research will examine factors driving the public's travel intention in the post-crisis (pandemic) period. The survey was conducted on the Internet using questionnaires designed in the Google platform. Data was collected from April 16 to May 31, 2020, from 154 Vietnamese participants. Research findings demonstrate 4 direct and indirect determinants of travel intention. The strongest effects come from perceived behavioral control which is influenced by subjective well-being. Perceived risk negatively correlates with Self-efficacy and subjective well-being. Conducted in the context of post-COVID-19, the research implies that once the pandemic has been controlled, perceived risks, although still exist, insignificantly influence the public's travel intention.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.20-38
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• 2023

Recently, car sharing has shown the most remarkable growth among sharing economy services. In the process of analyzing the intention to reuse the car sharing service, this study tried to reflect the unique characteristics of the service, which consists of non-face-to-face self-service, such as reservation, approval, handover, inspection, and return of the vehicle. Specifically, in addition to the perceived benefits and the perceived risks, we considered 'information quality' as a platform characteristic and 'self-efficacy' as a personal characteristic. To collect data, an online survey was conducted on adults with experience in car sharing, and a total of 320 responses were used for analysis. As a result of analyzing the structural equation model, it was found that information quality and self-efficacy increased the perceived benefits of services, and the higher the information quality, the higher the self-efficacy. On the other hand, the role of information quality and self-efficacy in lowering perceived risks was insignificant, and the intention to reuse services was more affected by perceived benefits than perceived risks. As a result of further analysis using Process Macro, it was found that the effect of self-efficacy on reuse intention was mediated by perceived benefits. It was analyzed that the indirect effects of information quality on reuse intention through perceived benefits or self-efficacy were all significant. These results suggest that providing timely, sufficient, and easy-to-understand information required by users on the platform improves self-efficacy and increases service reuse intention. In order to increase the number of service users, it is important for service providers not only to provide promotional activities such as offering attractive prices, but also to provide high-quality information so that users can use it more easily.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.2977-2997
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• 2018

In big data era, fresh data grows rapidly every day. More than 30,000 gigabytes of data are created every second and the rate is accelerating. Many organizations rely heavily on real time streaming, while big data stream computing helps them spot opportunities and risks from real time big data. Storm, one of the most common online stream computing platforms, has been used for big data stream computing, with response time ranging from milliseconds to sub-seconds. The performance of Storm plays a crucial role in different application scenarios, however, few studies were conducted to evaluate the performance of Storm. In this paper, we investigate the performance of Storm under different application scenarios. Our experimental results show that throughput and latency of Storm are greatly affected by the number of instances of each vertex in task topology, and the number of available resources in data center. The fault-tolerant mechanism of Storm works well in most big data stream computing environments. As a result, it is suggested that a dynamic topology, an elastic scheduling framework, and a memory based fault-tolerant mechanism are necessary for providing high throughput and low latency services on Storm platform.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04b
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• pp.1203-1206
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• 2002

In maned airport, crews may have risks as they manage passenger control system in IPMS in damage situations such as fire in a airport. So the application of unmanned autonomous system can reduce the number of boarding crews and attribute to safe airplane tranportation. PBBC model can be used to obtain control strategy, and airplane and enhance oprators' skill by simulating the airport. The paper suggests an intelligent system of the pbbc control using microprocessor in integrated platform management system which can take measures against passenger situation of a airplane excluding unnecessary warnings with undamaged situations. The system here detected the passenger more accurately and adopted more appriate measures according to airplane status compared with conventional systems.

• Journal of Platform Technology
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• v.9 no.3
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• pp.18-23
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• 2021

As it develops into a hyper-connected society, the role of information and communication is greatly increasing. In the event of a communication disaster, it will cause a significant impact on social infrastructure, suspension of the national critical infrastructure services, and the lives of the people. In addition, the information communication sector needs systematic management to create an information communication environment that is safe from disasters because dependence on the information communication sector has increased rapidly as the industrial structure has advanced. In this paper, we analyzed the types and risks of disasters that may occur to the information communication infrastructure that play important roles in national critical infrastructure, such as information communications, finance, health and healthcare, for systematic management. In the event of a disaster in the information communication infrastructure, it is believed that it will have a significant impact on the national critical infrastructure service suspension and people's lives.

• The Journal of Information Systems
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• v.33 no.1
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• pp.159-182
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• 2024

Purpose This study aims to investigate the factors influencing social media users' sharing behaviors of COVID-19 health information. Specifically, we seek to examine the impact of three key antecedents-trust in information source, trust in information content, and trust in social media platform-on users' trust in information quality and determine whether their effects vary between South Korea and China. Design/methodology/approach To fulfill our research objectives, we conducted an online survey across two countries, collecting 408 valid responses (South Korea: N = 201; China: N = 207) for our analysis. We employed Partial Least Squared based Structural Equation Modeling (PLS-SEM) with SmartPLS 4 and performed Exploratory Factor Analysis (EFA) and independent t-tests with SPSS 27. Findings The study revealed that perceived risks significantly inhibit users from sharing health information, highlighting the critical role of trust in countering these effects. We also identified variances in the levels of trust in information content and trust in social media platform between the two countries, which offers fresh perspectives for designing culturally tailored public health communications and interventions.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.25-37
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• 2024

The objective of this study was to create intelligent rail robots that are optimized for facility management and implement digital twin systems for smart road tunnel management. An autonomous surveillance system is formed by combining the sensing platform consisting of railing robots, fixed cameras and environmental detection sensors with the digital twin data platform technology for tunnel monitoring and early fire suppression. In order to develop mobile rail robots for fire extinguishing, we also designed and manufactured robots for extinguishing & monitoring and fire extinguishing devices, and then we examined the optimization of all parts. Our next step was to build a digital twin for road tunnel management by developing continuous image display system and implementing 3D modeling. After constructing prototypes, we attempted simulations by configuring abnormal symptom scenarios, such as vehicles fires. This study's proposal proposes high-accuracy risk prediction services that will enable intelligent management of risks in the tunnel with early response at each stage, using the data collected from the intelligent rail robots and digital twin systems.

• Journal of Platform Technology
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• v.11 no.6
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• pp.13-20
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• 2023

Regularly inspecting vehicle tires' condition is imperative for driving safety and comfort. Poorly maintained tires can pose fatal risks, leading to accidents. Unfortunately, manual tire visual inspections are often considered no less laborious than employing an automatic tire inspection system. Nevertheless, an automated tire inspection method can significantly enhance driver compliance and awareness, encouraging routine checks. Therefore, there is an urgency for automated tire inspection solutions. Here, we focus on developing a deep learning (DL) model to predict cracked tires. The main idea of this study is to demonstrate the comparative analysis of DenseNet121, VGG-19 and EfficientNet Convolution Neural Network-based (CNN) Transfer Learning (TL) and suggest which model is more recommended for cracked tire classification tasks. To measure the model's effectiveness, we experimented using a publicly accessible dataset of 1028 images categorized into two classes. Our experimental results obtain good performance in terms of accuracy, with 0.9515. This shows that the model is reliable even though it works on a dataset of tire images which are characterized by homogeneous color intensity.