• Industry Promotion Research
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• v.9 no.2
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• pp.37-44
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• 2024

This study selected the worst-case scenario for fireball and vapor cloud explosion (VCE) of a styrene monomer storage tank installed in a petrochemical production plant and performed damage prediction and accident impact analysis. The range of influence of radiant heat and overpressure due to fireball and vapor VCE during the abnormal polymerization reaction of styrene monomer, the main component of the mixed residue oil storage tank, was quantitatively analyzed by applying the e-CA accident damage prediction program. The damage impact areas of radiant heat and explosion overpressure are analyzed to have a maximum radius of 1,150m and 626m, respectively. People within 1,150m of radiant heat of 4kW/m2 may have their skin swell when exposed to it for 20 seconds. In buildings within 626m, where an explosion overpressure of 21kPa is applied, steel structures may be damaged and separated from the foundation, and people may suffer physical injuries. In the event of a fire, explosion or leak, determine the risk standards such as the degree of risk and acceptability to workers in the work place, nearby residents, or surrounding facilities due to radiant heat or overpressure, identify the hazards and risks of the materials handled, and establish an emergency response system. It is expected that it will be helpful in establishing measures to minimize damage to workplaces through improvement and investment activities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.469-478
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• 2019

Car-sharing services have been settled on as a new type of public transportation owing to their enhanced convenience, expanded awareness of practical consumption patterns, the inspiration for environmental conscientiousness, and the diffusion of smart phones following the economic crisis. With development of the market, many people have started using such services. However, security is still an issue. Damage is expected since IDs and passwords are required for log-in when renting and controlling the vehicles. The protocol suggested in this study uses bio-information, providing an optimized service, and convenient (but strong) authentication with various service-provider clouds registering car big data about users through brokers. If using the techniques suggested here, it is feasible to reduce the exposure of the bio-information, and to receive service from multiple service-provider clouds through one particular broker. In addition, the proposed protocol reduces public key operations and session key storage by 20% on mobile devices, compared to existing car-sharing platforms, and because it provides convenient, but strong, authentication (and therefore constitutes a secure channel), it is possible to proceed with secure communications. It is anticipated that the techniques suggested in this study will enhance secure communications and user convenience in the future car-sharing-service cloud environment.

• The Korean Journal of Archival Studies
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• no.66
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• pp.5-35
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• 2020

In the digital age, the most basic unit of records management is a document file. Depending on whether each document file is produced in an open standard format or an exclusive proprietary format, there is a cost difference in the process of use and long-term preservation. As government agencies moved to cloud-based business management systems, web-based document editing software was newly adopted. They had the opportunity to select a new file format for web-based document editing software. This paper deals with strategies to maximize the advantages of open standard formats while considering the legacy public document production practices. It introduces ISO/IEC 26300:2006 ODF, ISO/IEC 29500:2008 OOXML, KS X 6101 OWPML, etc. as open standard formats, and looks at considerations when choosing a format and web-based document editing software. In addition, it proposes a strategy to maintain the format of document files shared in cloud storage as an open standard format.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.30-35
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• 2022

Rendering is widely used for visual effects in animations and movies. Although rendering is computing-intensive, we observe that it accompanies heavy I/O because of large input data. This becomes technical hurdles for multi-node rendering performed on public cloud nodes. To reduce the overhead of data transmission in multi-node rendering, this paper analyzes the characteristics of rendering workloads, and presents the cooperative caching scheme for multi-node rendering. Our caching scheme has the function of synchronization between original data in local storage and cached data in rendering nodes, and the cached data are shared between multiple rendering nodes. We perform measurement experiments in real system environments and show that the proposed cooperative caching scheme improves the conventional caching scheme used in the network file system by 27% on average.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.214-217
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• 2013

Advancements in automobile industries and the communication technologies caused VANET (Vehicular Ad Hoc NETwork) to evolve to VANET-based clouds before its deployment. It is more likely that VANET clouds will replace the traditional VANET in the deployment phase. It is to be noted that an abrupt deployment is out of question because it would require mass of resources and money to do so; instead incremental deployment is more ideal. In this paper, we aim at the incremental deployment phase of VANET clouds and focus on the well-established public transport networks. Data aggregation is one of the essential aspects in traditional VANET and has been researched for quite long time. However the previously proposed schemes are still controversial. Keeping in mind the time and space prediction of public buses, we leverage these buses as potential aggregators and MG (Mobile Gateways) in VANET clouds. Buses gather cooperative whereabouts information from neighbors, aggregate that information, disseminate it to the neighbor MGs and also send it to the cloud for storage and for services exchange. In our proposed scheme, we believe that the dissemination will be effective and cover most of the urban area since at any instant of time; buses cover most part of the urban areas. Besides, the effective transmission range is higher due to tall buses.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.669-678
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• 2018

This study developed information technology infrastructures for building a driving environment analysis platform using various big data, such as vehicle sensing data, public data, etc. First, a small platform server with a parallel structure for big data distribution processing was developed with H/W technology. Next, programs for big data collection/storage, processing/analysis, and information visualization were developed with S/W technology. The collection S/W was developed as a collection interface using Kafka, Flume, and Sqoop. The storage S/W was developed to be divided into a Hadoop distributed file system and Cassandra DB according to the utilization of data. Processing S/W was developed for spatial unit matching and time interval interpolation/aggregation of the collected data by applying the grid index method. An analysis S/W was developed as an analytical tool based on the Zeppelin notebook for the application and evaluation of a development algorithm. Finally, Information Visualization S/W was developed as a Web GIS engine program for providing various driving environment information and visualization. As a result of the performance evaluation, the number of executors, the optimal memory capacity, and number of cores for the development server were derived, and the computation performance was superior to that of the other cloud computing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1014-1035
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• 2013

With recent advances in wireless communication and low-power miniaturized biomedical sensor and semiconductor technologies, wireless body area networks (WBAN) has become an integral part of the disaster aid system. Wearable vital sign sensors can track patients' status and location, thus enhancing disaster rescue efficiency. In the past few years, most of the literatures in the area of disaster aid system based on WBAN have focused on issues concerning wireless sensor design, sensor miniaturization, energy efficiency and communication protocols. In this paper, we will give an overview of disaster aid, discuss about the types of network communication as well as outline related issues. We will emphasize on analyzing six key issues in employing the disaster aid system. Finally, we will also highlight some of the challenges that still need to be addressed in the future in order to help the disaster aid system be truly and widely accepted by the public.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5100-5119
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• 2018

Most of existing privacy-preserving multi-authorities attribute-based encryption schemes (PP-MA-ABE) only considers the privacy of the user identity (ID). However, in many occasions information leakage is caused by the disclosing of his/her some sensitive attributes. In this paper, we propose a collusion-resisting ciphertext-policy PP-MA-ABE (CRPP-MACP-ABE) scheme with hiding both user's ID and attributes in the cloud storage system. We present a method to depict anonymous users and introduce a managerial role denoted by IDM for the management of user's anonymous identity certificate ($AID_{Cred}$). The scheme uses $AID_{Cred}$ to realize privacy-preserving of the user, namely, by verifying which attribute authorities (AAs) obtain the blinded public attribute keys, pseudonyms involved in the $AID_{Cred}$ and then distributes corresponding private keys for the user. We use different pseudonyms of the user to resist the collusion attack launched by viciousAAs. In addition, we utilize IDM to cooperate with multiple authorities in producing consistent private key for the user to avoid the collusion attack launched by vicious users. The proposed CRPP-MACP-ABE scheme is proved secure. Some computation and communication costs in our scheme are finished in preparation phase (i.e. user registration). Compared with the existing schemes, our scheme is more efficient.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1277-1286
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• 2018

In this paper, we provide flexible scalability of computing resources in cloud environment and Apache Hadoop based cloud environment for analysis of public medical information big data. In fact, it includes the ability to quickly and flexibly extend storage, memory, and other resources in a situation where log data accumulates or grows over time. In addition, when real-time analysis of accumulated unstructured log data is required, the system adopts Hadoop-based analysis module to overcome the processing limit of existing analysis tools. Therefore, it provides a function to perform parallel distributed processing of a large amount of log data quickly and reliably. Perform frequency analysis and chi-square test for big data analysis. In addition, multivariate logistic regression analysis of significance level 0.05 and multivariate logistic regression analysis of meaningful variables (p<0.05) were performed. Multivariate logistic regression analysis was performed for each model 3.

• Journal of KIISE
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• v.41 no.9
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• pp.686-698
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• 2014

Recently, large-scale streaming sensor data have emerged due to explosive supply of smart phones, diffusion of IoT and Cloud computing technology, and generalization of IoT devices. Also, researches on combination of semantic web technology are being actively pushed forward by increasing of requirements for creating new value of data through data sharing and mash-up in large-scale environments. However, we are faced with big issues due to large-scale and streaming data in the inference field for creating a new knowledge. For this reason, we propose the RDFS rule based parallel reasoning scheme to service by processing large-scale streaming sensor data with the semantic web technology. In the proposed scheme, we run in parallel each job of Rete network algorithm, the existing rule inference algorithm and sharing data using the HBase, a hadoop database, as a public storage. To achieve this, we implement our system and evaluate performance through the AWS data of the weather center as large-scale streaming sensor data.