• 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.

• 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.

• 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.

• 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.

• Journal of Animal Environmental Science
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• v.11 no.3
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• pp.207-214
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• 2005

To reduce phosphorus and nitrogen from the swine wastewater, magnesium chloride $(MgCl_2)$ was used as a reaction material for both soluble phosphorus (SP) and ammonia-nitrogen (AN). The initial value of SP content were $471mg/\ell$ far aeration test and $515 mg/\ell$ for NaOH addition test, but treatment of $MgCl_2$ reduced SP value to $5mg/\ell$ and $4mg/\ell$. The removal efficiency of $MgCl_2$ for SP showed $99\%$ in both treatment, and the removal efficiency of $MgCl_2$ for AN showed $15\%$ with treatment of aeration and $18\%$ with NaOH. All the experiments were done in a low temperature of 6 to $8^{\circ}C$, suggesting that this methods are possibly able to apply to a cold weather conditions. Moreover, the struvite crystal structure was identified by electronic microscope, implying that $MgCl_2$ is an effective material for removal of SP from swine wastewater In addition to the increased removal rate of the AN in wastewater, both $MgCl_2$ and $KH_2PO_4$ were added. The SP value was reduced by $99\%$ with 2g addition of the phosphate. The SP removal rate by 4g addition of the phosphate was increased only as $15-19\%$, but the quantity of removed SP was higher than that of 2g addition test. The value of AN was not reduced as expected by adding $KH_2PO_4$. The AN removal rate were low as $18\%$ and $15\%$ like as the level of the former test with $MgCl_2$ alone. Therefore, it is needed to examine closely the reaction mechanism f3r reducing both SP and AN simultaneously.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.828-836
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• 2010

This study was conducted to evaluate soil erosion risk with a standard unit watershed in the upper Han river basin using the spatial soil erosion map according to the change of landuse. The study area is 14,577 $km^2$, which consists of 10 subbasins, 107 standard unit watersheds. Total annual soil loss and soil loss per area estimated were $895{\times}10^4\;Mg\;yr^{-1}$ and 6.1 Mg $ha^{-1}\;yr^{-1}$, respectively. A result of analysis with a subbasin as a unit showed that annual soil losses and soil loss per area in Namhan river basins was more than in Bukhan river ones. Predicted annual soil loss according to the landuse ranked as Forest & Grassland > Upland ${\gg}$ Urban & Fallow area > Paddy field > Orchard. Upland area covered 6.2% of the study area, but the contribution of total annul soil loss was 40.6% and that of Forest & Grassland was 44.2%. As a evaluation of soil erosion risk using the spatial soil erosion map, we could precisely conformed the potential hazardous region of soil erosion in each unit watersheds. The ratio of regions, graded as higher "Moderate" for annual soil loss, were respectively 8.7%, 7.9% and 7.8% in 1001, 1002 and 1003 subbasins in Namhan river basin. Most landuse of these area was upland, and these area is necessary to establish soil conservation practices to reduce soil erosion based on the field observation.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.