• Journal of the Institute of Convergence Signal Processing
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• v.10 no.2
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• pp.106-111
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• 2009

Real-time video stabilization technology is used in correction for the camera vibrations of the hand-held camera by hand or fixed camera by external condition. This paper is about the counterplan to cope with the vibration of the movie generated by the large external cause relatively. we use the movie stabilization parameters with the phase correlation method based the DFT to get the displacements of the current frame to the reference frame. we use the kalman filter for the efficient and stable searching works on the phase correlation map and present the proper conditions for the real-time processing through the experiments. We propose the measure to evaluate the capability of the video stabilizer which is the standard deviation of the brightness of the center block. and compare the capability for the video sequences randomly shifted and the jittered video sequences obtained from camera.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.1-17
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• 2009

In recent years, most of flood damage is associated with the levee failure. The objective of this study is to predict flow depths, flood area, flooding time and flood damage through flood inundation analysis considering the overflow of levee and the characteristics of levee failure. The hydrological parameters were extracted from GIS data such as DEM, land cover and soil map to estimate levee failure discharge. In addition, the characteristics of flood wave propagation could be accurately predicted as flood inundation analysis was accomplished considering the affection of structure within protected lowland and hourly prediction of flooded areas and estimation of flood strength will be utilized as basic data for the flood defence and establishment of measure to reduce flood damage.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.75-82
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• 2021

The number of traffic accidents is about 230,000, and due to non-recurring congestion and high driving speed, the number of deaths per traffic accident on freeways is more than twice compared to other roads. Currently, traffic information is provided based on nodes and links using the centerline of the road, but it does not provide detailed speed information. Recently, installing sensors for vehicles to monitor obstacles and measure location is becoming common not only for autonomous vehicles but also for ordinary vehicles as well. The analysis using large-capacity location-based data from such sensors enables real time service according to processing speed. This study presents an mapping method for individual vehicle data analysis based on space. The processing speed of large-capacity data was increased by using method which applied a quaternary notation basis partition method that splits into two directions of longitude and latitude respectively. As the space partition was processed, the average speed was similar, but the speed standard deviation gradually decreased, and decrease range became smaller after 9th partition.

• The Korean Journal of Pain
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• v.34 no.4
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• pp.405-416
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• 2021

Background: This study investigated the effect of intrathecal Sec-O-glucosylhamaudol (SOG) on the p38/c-Jun N-terminal kinase (JNK) signaling pathways, nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB)-related inflammatory responses, and autophagy in a spinal nerve ligation (SNL)-induced neuropathic pain model. Methods: The continuous administration of intrathecal SOG via an osmotic pump was performed on male Sprague-Dawley rats (n = 50) with SNL-induced neuropathic pain. Rats were randomized into four groups after the 7th day following SNL and treated for 2 weeks as follows (each n = 10): Group S, sham-operated; Group D, 70% dimethylsulfoxide; Group SOG96, SOG at 96 ㎍/day; and Group SOG192, SOG at 192 ㎍/day. The paw withdrawal threshold (PWT) test was performed to assess neuropathic pain. Western blotting of the spinal cord (L5) was performed to measure changes in the expression of signaling pathway components, cytokines, and autophagy. Additional studies with naloxone challenge (n = 10) and cells were carried out to evaluate the potential mechanisms underlying the effects of SOG. Results: Continuous intrathecal SOG administration increased the PWT with p38/JNK mitogen-activated protein kinase (MAPK) pathway and NF-κB signaling pathway inhibition, which induced a reduction in proinflammatory cytokines with the concomitant downregulation of autophagy. Conclusions: SOG alleviates mechanical allodynia, and its mechanism is thought to be related to the regulation of p38/JNK MAPK and NF-κB signaling pathways, associated with autophagy during neuroinflammatory processes after SNL.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.2
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• pp.347-354
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• 2021

In the equipment industry such as chemical plants, high temperature, high pressure, and toxic fluids move between various facilities through piping. The movement and damage of pipes due to changes in the surrounding environment such as temperature changes, vibrations, earthquakes, and ground subsidence often lead to major accidents involving personal injury. In order to prevent such an accident, various types of expansion joints are used to absorb and supplement various shocks applied to the pipe to prevent accidents in advance. Therefore, it is very important to measure the deformation of the used expansion joint and predict its lifespan to prevent a major accident. In this paper, the deformation of the expansion joint was understood as a kind of motion, and the change was measured using a Hall Effect Sensor and a 9-Axis Sensor. In addition, we studied a system that can predict the deformation of expansion joints by collecting and analyzing the measured data using a general-purpose microcomputer (Arduino Board) and C language.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1474-1480
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• 2018

When fires occur in high-rise buildings, it is difficult to determine whether each escape route is safe because of complex structure. Therefore, it is necessary to provide residents with escape routes quickly after determining their safety. We propose a method to measure the visibility of the escape route due to the smoke generated in the fire by analyzing the images. The visibility can be easily measured if the density of smoke detected in the input image is known. However, this approach is difficult to use because there are no suitable methods for measuring smoke density. In this paper, we use principal component analysis by extracting a background image from input images and making it training data. Background images and smoke images are extracted from images given as inputs, and then the learned principal component analysis is applied to map of as a new feature space, and the change is calculated and the visibility due to the smoke is measured.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.38.3-38.3
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• 2018

We present the results of high-resolution near-IR spectral mapping toward the Orion KL outflow. In this study, we used the Immersion Grating Infrared Spectrometer (IGRINS) on the 2.7 m Harlan J. Smith Telescope at McDonald Observatory. IGRINS's large wavelength coverage over the H & K bands and high spectral resolving power (R ~ 45,000) allowed us to detect over 35 shock-excited ro-vibrational H2 transitions and to measure directly the gas temperature and velocity of the dense outflows. In our previous study toward the H2 peak 1 region in the Orion KL outflow, we identified 31 outflow fingers from a datacube of the H2 1-0 S(1) $2.122{\mu}m$ line and constructed a three-dimensional map of the fingers. The internal extinction (${\Delta}AV$ > 10 mag) and overall angular spread of the flow argue for an ambient medium with a high density (105 cm-3). In this presentation, we show preliminary results of additional mapping toward a remarkable chain of bows (HH 205 - HH 207) farther from the ejection center, and obtain a more clear view of the shock physics of a single isolated bullet that improves on the knowledge gained from observations of the more complex peak 1 region in our earlier study.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.6
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• pp.29-41
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• 2020

Wild pollinators provide important pollination services for crops. However, their geographical ranges and impact on pollination services have not been fully explored within the scope of Korean agricultural land. This study aims to identify spatial supply-demand mismatches across orchard fields in the context of assessing pollination service risk. We first used National Ecosystem Survey data and a species distribution model (MaxEnt) to develop the geographic range of each of 32 wild pollinators belonging to three families (Diptera, Hymenoptera, and Lepidoptera). We then summed the modeled presence probability of each species to obtain a measure of spatially explicit pollinator richness. This modeled richness, defined as pollination supply, was compared with the summed area of orchard fields at the municipal boundary level to identify areas with supply-demand mismatches. The study found that Lepidoptera showed the highest species richness (8.3±1.5), followed by Hymenoptera (4.3±0.8) and Diptera (3.5±0.8) species. Median orchard area was 1.5 ㎢ (range of 0-176.7 ㎢) among 250 municipal regions in South Korea. The municipal regions were divided into three categories (tertiles) of low, middle, and high pollination supply and demand according to, respectivley, average polliator richness and orhard area. Finally, we found that 55 municipal regions (accounting for 49% of national orchard land) potentially faced high risk of pollination deficits, 81 regions (48% of national orchard land) faced intermediate risk, and 63 regions faced low risk (3% of national orchard land). In conclusion, this study revealed significant mismatch between pollination supply and demand and developed risk assessment map will guide our future efforts on pollinator habitat conservation and monitoring to conserve crop pollination services.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.646-653
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• 2021

The medical bed developed in this study consists of N keys and each is driven vertically by an actuator. Since M sensors are mounted on each keyboard to measure body pressure, the resolution of the body pressure map is determined by the MN. A sensor controller is mounted on each keyboard, and the body pressure values measured from M sensors are transmitted to the main controller through a serial communication network such as CAN (Car Area Network). Each keyboard is equipped with a servo driver that drives a motor, and it is connected to the main controller via CAN to control the height of the keyboard according to the displacement value indicated by the main controller. In addition, the maximum body pressure value and body pressure ratio applied to each part of the keyboard are calculated and used as the basic data for controlling bed comfort by artificial intelligence. As a result, the proposed system can be a foundation that can be used for the control of body comfort and pressure sore prevention by artificial intelligence to be developed in the future.

• 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.