• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.8
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• pp.157-168
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• 2019

Modular Construction is regarded as having enhanced safety compared to traditional construction since most of modular manufacturing process in plants. Unlike general consideration for safety in modular construction, several industrial accident data and studies have pointed out that the accident rate of modular construction is not enough less as much as the practitioners have expected. It means that there is a clear need for improvement of safety management in modular construction. To enhance safety, it is necessary to identify the type and cause of accident through accident cases in order to prevent safety accident in advance. In this consideration, this study analyzed the types and causes of accidents through root cause analysis procedure with accident cases of U.S. OSHA. The classification was carried out in the order of process type, accident type and cause of accident. By following the classification criteria in this study, the causal factor was derived and the root cause map was created. Based on the analysis results, cross-analysis was conducted and it is shown that activity characteristics of modular construction are related to safety accidents. In addition, prevention methods to reduce safety accident by major activity are presented in terms of organizational, educational and technical aspects. This study contributes that the result can be used as the basic safety management in the manufacturing and construction process of modular construction.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.1
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• pp.29-36
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• 2021

The amount of data generated has been growing exponentially, and the complexity of data has been increasing owing to the advancement of information technology (IT). Big data analysts and engineers have therefore been actively conducting research to minimize the analysis targets for faster processing and analysis of big data. Hadoop, which is widely used as a big data platform, provides various processing and analysis functions, including minimization of analysis targets through Hive, which is a subproject of Hadoop. However, Hive uses a vast amount of memory for data deduplication because it is implemented without considering the complexity of data. Therefore, an efficient algorithm has been proposed for data deduplication of complex structures. The performance evaluation results demonstrated that the proposed algorithm reduces the memory usage and data deduplication time by approximately 79% and 0.677%, respectively, compared to Hive. In the future, performance evaluation based on a large number of data nodes is required for a realistic verification of the proposed algorithm.

• The Journal of Korean Institute of Information Technology
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• v.17 no.11
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• pp.17-26
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• 2019

RAID-5 technology is one of the choice for flash storage device to enhance its reliability. However, RAID-5 has inherent parity update overhead, especially, parity overhead for partial stripe write is one of the crucial issues for flash-based RAID-5 technologies. In this paper, we design efficient parity log architecture for RAID-5 to eliminate runtime partial parity overhead. During runtime, partial parity is retained in buffer memory until full stripe write completed, and the parity is written with full strip write. In addition, parity log is maintained in memory until whole the stripe group is used for data write. With this parity log, partial parity can be recovered from the power loss. In the experiments, the parity log method can eliminate partial parity writes overhead with a little parity log writes. Hence it can reduce write amplification at the same reliability.

• Genomics & Informatics
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• v.19 no.4
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• pp.49.1-49.11
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• 2021

Nowadays, Genomic data constitutes one of the fastest growing datasets in the world. As of 2025, it is supposed to become the fourth largest source of Big Data, and thus mandating adequate high-performance computing (HPC) platform for processing. With the latest unprecedented and unpredictable mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the research community is in crucial need for ICT tools to process SARS-CoV-2 RNA data, e.g., by classifying it (i.e., clustering) and thus assisting in tracking virus mutations and predict future ones. In this paper, we are presenting an HPC-based SARS-CoV-2 RNAs clustering tool. We are adopting a data science approach, from data collection, through analysis, to visualization. In the analysis step, we present how our clustering approach leverages on HPC and the longest common subsequence (LCS) algorithm. The approach uses the Hadoop MapReduce programming paradigm and adapts the LCS algorithm in order to efficiently compute the length of the LCS for each pair of SARS-CoV-2 RNA sequences. The latter are extracted from the U.S. National Center for Biotechnology Information (NCBI) Virus repository. The computed LCS lengths are used to measure the dissimilarities between RNA sequences in order to work out existing clusters. In addition to that, we present a comparative study of the LCS algorithm performance based on variable workloads and different numbers of Hadoop worker nodes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.77-82
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• 2022

The effect of indoor air pollution on the human body is greater and more dangerous than outdoor air pollution. In general, a person stays indoors for a long time, and in a closed room, pollutants are continuously accumulated and the polluted air is better delivered to the lungs. Especially in the case of young children, it is very sensitive to indoor air and it is fatal. In addition, methods to reduce indoor air pollution, which cannot be ventilated with more frequent indoor activities and continuously increasing external fine dust due to Covid 19, are becoming more important. In order to improve the problems of the existing autonomous driving air purifying robot, this paper divided the map and Upper Confidence bounds applied to Trees(UCT) based algorithm to solve the problem of the autonomous driving robot not sterilizing a specific area or staying in one space continuously, and the problem of children who are vulnerable to indoor air pollution. We propose a space-adaptive autonomous driving air purifying robot for a green smart school that can be improved.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.159-167
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• 2009

The vehicles play a significant role in modern people's life as economy grows. The development of car navigation system(CNS) provides various convenience because it shows the driver where they are and how to get to the destination from the point of source. However, the existing map-based CNS does not consider any environments such as traffic congestion. Given the same starting point and destination, the system always provides the same route and the required time. This paper proposes a path planning method with traffic prediction by applying historical driving information to the Fuzzy theory and Bayesian update. Fuzzy theory classifies the historical driving information into groups of leaving time and speed rate, and the traffic condition of each time zone is calculated by Bayesian update. An ellipse area including starting and destination points is restricted in order to reduce the calculation time. The accuracy and practicality of the proposed scheme are verified by several experiments and comparisons with real navigation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.260-262
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• 2021

In recent years, many studies are being conducted to reduce the damage to humans in the event of a fire. In case of fire in large cities, evacuation route guidance services are provided using Mobile GIS (geographic information system). However, among the algorithms used in the existing evacuation route system, Dijkstra Algorithm has a problem that when the cost is negative, it cannot obtain an infinite loop or an accurate result value, and does not help to select an appropriate shortest route by searching all routes. For this reason, in this paper, we propose the shortest route guidance system based on A^* Algorithm. In case of fire, the shortest route is searched and the shortest route is visualized and provided using a map service on a mobile device using mobile GIS.

• The Journal of the Acoustical Society of Korea
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• v.26 no.7
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• pp.353-360
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• 2007

Rapid urbanization and population increasing are making a high-rise residential building and high-density residential area. According to spacial concentration of population is occurred road traffic noise problem. Now we are popularly using almost only noise barrier installation, but it makes many disfunctions such as poor landscape, low noise barrier performance and crimes. The purpose of this research is to figure out which is best method one the traffic noise management. Alternative are composed to building layout type ($30^{\circ},\;90^{\circ},\;180^{\circ}$), separation between road and residential building, noise barrier types(noise barrier only, noise barrier and forests and etc). The noise barrier are shown to reduce barrier and building layout angle $30^{\circ}$ position is the best comparing with horizontal and vertical layouts. The gab distance is decreased approximately noise level 5dB(A). We figured out there are noise important method except noise barrier wall and it was analyzed how much decreased. This can be very useful before making a road planning and residential building design.

• Journal of the Korean Society of Radiology
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• v.82 no.3
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• pp.500-511
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• 2021

The prevalence of lower extremity disease is increasing with age. With recent technological advancements, endovascular treatment is being performed more frequently. The treatment goal of intermittent claudication is to improve walking and reduce claudication. To achieve these goals, anatomical durability and patency are important. In patients with critical limb ischemia, the lesions are diffuse and particularly severe in below-the-knee arteries. The treatment goal of critical limb ischemia is to promote wound healing and to prevent major amputation, which is evaluated by the limb salvage rate. Primary stenting using covered or bare metal stents is a widely accepted endovascular treatment. While drug-eluting technologies with or without atherectomy are widely used in the treatment of femoropopliteal disease, balloon angioplasty is the mainstay treatment for below-the-knee intervention. CT angiography provides a road map for planning endovascular treatment in patients without absolute contraindications.

• Investigative Magnetic Resonance Imaging
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• v.10 no.2
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• pp.108-116
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• 2006

Purpose : High-resolution spiral-scan imaging is performed at 3 Tesla MRI system. Since the gradient waveforms for the spiral-scan imaging have lower slopes than those for the Echo Planar Imaging (EPI), they can be implemented with the gradient systems having lower slew rates. The spiral-scan imaging also involves less eddy currents due to the smooth gradient waveforms. The spiral-scan imaging method does not suffer from high specific absorption rate (SAR), which is one of the main obstacles in high field imaging for rf echo-based fast imaging methods such as fast spin echo techniques. Thus, the spiral-scan imaging has a great potential for the high-speed imaging in high magnetic fields. In this paper, we presented various high-resolution images obtained by the spiral-scan methods at 3T MRI system for various applications. Materials and Methods : High-resolution spiral-scan imaging technique is implemented at 3T whole body MRI system. An efficient and fast higher-order shimming technique is developed to reduce the inhomogeneity, and the single-shot and interleaved spiral-scan imaging methods are developed. Spin-echo and gradient-echo based spiral-scan imaging methods are implemented, and image contrast and signal-tonoise ratio are controlled by the echo time, repetition time, and the rf flip angles. Results : Spiral-scan images having various resolutions are obtained at 3T MRI system. Since the absolute magnitude of the inhomogeneity is increasing in higher magnetic fields, higher order shimming to reduce the inhomogeneity becomes more important. A fast shimming technique in which axial, sagittal, and coronal sectional inhomogeneity maps are obtained in one scan is developed, and the shimming method based on the analysis of spherical harmonics of the inhomogeneity map is applied. For phantom and invivo head imaging, image matrix size of about $100{\times}100$ is obtained by a single-shot spiral-scan imaging, and a matrix size of $256{\times}256$ is obtained by the interleaved spiral-scan imaging with the number of interleaves of from 6 to 12. Conclusion : High field imaging becomes increasingly important due to the improved signal-to-noise ratio, larger spectral separation, and the higher BOLD-based contrast. The increasing SAR is, however, a limiting factor in high field imaging. Since the spiral-scan imaging has a very low SAR, and lower hardware requirements for the implementation of the technique compared to EPI, it is suitable for a rapid imaging in high fields. In this paper, the spiral-scan imaging with various resolutions from $100{\times}100$ to $256{\times}256$ by controlling the number of interleaves are developed for the high-speed imaging in high magnetic fields.