• Journal of Environmental Science International
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• v.28 no.3
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• pp.341-356
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• 2019

In this study, the impacts of local meteorology caused by tidal changes in the West Sea on ozone distributions in the Seoul Metropolitan Area (SMA) were analyzed using a meteorological model (WRF) and an air quality (CMAQ) model. This study was carried out during the day (1200-1800 LST) between August 3 and 9, 2016. The total area of tidal flats along with the tidal changes was calculated to be approximately $912km^2$, based on data provided by the Environmental Geographic Information Service (EGIS) and the Ministry of Oceans and Fisheries (MOF). Modeling was carried out based on three experiments, and the land cover of the tidal flats for each experiment was designed using the coastal wetlands, water bodies (i.e., high tide), and the barren or sparsely vegetated areas (i.e., low tide). The land cover parameters of the coastal wetlands used in this study were improved in the herbaceous wetland of the WRF using updated albedo, roughness length, and soil heat capacity. The results showed that the land cover variation during high tide caused a decrease in temperature (maximum $4.5^{\circ}C$) and planetary boundary layer (PBL) height (maximum 1200 m), and an increase in humidity (maximum 25%) and wind speed (maximum $1.5ms^{-1}$). These meteorological changes increased the ozone concentration (about 5.0 ppb) in the coastal areas including the tidal flats. The increase in the ozone concentration during high tide may be caused by a weak diffusion to the upper layer due to a decrease in the PBL height. The changes in the meteorological variables and ozone concentration during low tide were lesser than those occurring during high tide. This study suggests that the meteorological variations caused by tidal changes have a meaningful effect on the ozone concentration in the SMA.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.430-439
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• 2019

In this study, a nonlinear impact analysis was performed to evaluate the safety and damage of an eco-pillar debris barrier with a hollow cross-section, which was proposed to improve constructability and economic efficiency. The construction of concrete eco-pillar debris barriers has increased recently. However, there are no design standards concerning debris barriers in Korea, and it is difficult to find a study on performance evaluations in extreme environments. Thus, an analysis of an eco-pillar debris barrier was done using the rock impact speed, which was estimated from the debris flow velocity. The diameters of rocks were determined by ETAG 27. The impact position, angles, and rock diameter were considered as variables. A concrete nonlinear material model was applied, and the estimation of damage was done by ABAQUS software. As a result, the damage ratio was found to be less than 1.0 at rock diameters of 0.3 m and 0.5 m, but it was 1.39 when the diameter was 0.7 m. This study could be used as basic data on impact force in the design of the cross section of an eco-pillar debris barrier.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.423-430
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• 2019

The convergence of the automotive industry and the ICT technology can be broadly divided into the commercial service sector and the Cooperative-ITS (C-ITS) service sector. The C-ITS service sector is using V2X communication technology as a field that aims to provide safer transportation, more green and efficient transportation, and more predictable and productive mobility. The recent convergence of self-driving cars and connected cars requires high data rates, low transmission delays, and low transmission error rates. Interest in comparison of performance between WAVE and C-V2X (LTE-V2X, 5G-V2X) has been amplified and application services by communication technology are being studied. In this paper, we design the application performance evaluation method of Hybrid V2X communication system and confirm that the decrease of packet error rate (PER) performance is caused by the increase of communication distance, not the vehicle speed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.887-895
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• 2018

This paper presents a braking model that can be used to design the safety distance of a train control system and a train braking system to increase the volume of traffic. For the braking model, a train set (electric multiple unit composed 6 cars) was tested. The factors that can affect the braking characteristics include the friction coefficient, braking pressure, and regenerative braking. The braking pressure was classified into service and emergency braking and reflected the characteristics of the vehicle. The external force acting on the running railway car was tested in accordance with KS R 9217, and the running resistance of the train is presented in the form of a polynomial. The dynamic behavior of the train running on a straight flat line was simulated using UM 8.3. The results were validated with experimental data, and the results were reasonable. With the validated model, a stopping distance was determined according to the initial braking speed and compared with the deceleration braking model. In addition, a safety distance for the train control system could be changed according to the frictional coefficient limits. These results are expected to be useful for analyzing the dynamic behavior of trains, and for analyzing various railway environments and improving the braking performance.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.64-74
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• 2019

Although a non-rigid registration has high demands in clinical practice, it has a high computational complexity and it is very difficult for ensuring the accuracy and robustness of registration. This study proposes a method of applying a non-rigid registration to 3D magnetic resonance images of brain in an unsupervised learning environment by using a deep-learning network. A feature vector between two images is produced through the network by receiving both images from two different patients as inputs and it transforms the target image to match the source image by creating a displacement vector field. The network is designed based on a U-Net shape so that feature vectors that consider all global and local differences between two images can be constructed when performing the registration. As a regularization term is added to a loss function, a transformation result similar to that of a real brain movement can be obtained after the application of trilinear interpolation. This method enables a non-rigid registration with a single-pass deformation by only receiving two arbitrary images as inputs through an unsupervised learning. Therefore, it can perform faster than other non-learning-based registration methods that require iterative optimization processes. Our experiment was performed with 3D magnetic resonance images of 50 human brains, and the measurement result of the dice similarity coefficient confirmed an approximately 16% similarity improvement by using our method after the registration. It also showed a similar performance compared with the non-learning-based method, with about 10,000 times speed increase. The proposed method can be used for non-rigid registration of various kinds of medical image data.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.73-80
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• 2021

In this paper, we propose a packet processing method capable of handling large-capacity traffic over 20Gbps using multi-core and huge page memory approaches. As ICT technology advances, the global average monthly traffic is expected to reach 396 exabytes by 2022. With the increase in network traffic, cyber threats are also increasing, increasing the importance of traffic analysis. Traffic analyzed as an existing high-cost foreign product simply stores statistical data and visually shows it. Network administrators introduce and analyze many traffic analysis systems to analyze traffic in various sections, but they cannot check the aggregated traffic of the entire network. In addition, since most of the existing equipment is of the 10Gbps class, it cannot handle the increasing traffic every year at a fast speed. In this paper, as a method of processing large-capacity traffic over 20Gbps, the process of processing raw packets without copying from single-core and basic SMA memory approaches to high-performance packet reception, packet detection, and statistics using multi-core and NUMA memory approaches suggest When using the proposed method, it was confirmed that more than 50% of the traffic was processed compared to the existing equipment.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.5
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• pp.195-200
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• 2021

Due to the development of video sharing platforms, the amount of video uploads is exploding. Such videos often include various types of music, among which cover songs are included. In order to protect the copyright of music, an algorithm to find the original song of the cover song is essential. However, it is not easy to find the original song because the cover song is a modification of the composition, speed and overall structure of the original song. So far, there is no known effective algorithm for searching the original song of the cover song. In this paper, we propose an algorithm for searching the original song of the cover song using the inflection points of the melody line. Inflection points represent the characteristic points of change in the melody sequence. The proposed algorithm compares the original song and the cover song using the sequence of inflection points for the representative phrase of the original song. Since the characteristics of the representative phrase are used, even if the cover song is a song made by modifying the overall composition of the song, the algorithm's search performance is excellent. Also, since the proposed algorithm uses only the features of the inflection point sequence, the memory usage is very low. The efficiency of the algorithm was verified through performance evaluation.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.4
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• pp.291-298
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• 2021

Purpose: The Pedisole is a newly developed shoe-mounted wearable assessment system for analyzing balance and gait. This study aimed to determine the reliability and validity of the parameters provided by the system for static balance and gait analysis of healthy adults. Methods: This study included 38 healthy adults (22.4±1.9 years) with no history of injury in the lower limbs. All participants were asked to perform balance and gait tasks for undertaking measurements. For analysis of balance, both the smart Pedisole and Pedoscan systems were concurrently used to analyze the path length of the center of pressure (COP) and the weight ratio of the left and right for 10 s. Gait was measured using the smart Pedisole and GaitRite walkway systems simultaneously. The participants walked at a self-selected preferred gait speed. The cadence, stance time, swing time, and step time were used to analyze gait characteristics. Using the paired t-test, the intra-class coefficient correlation (ICC) was calculated for reliability. The Spearman correlation was used to assess the validity of the measurements. In total, data for balance from 36 participants and the gait profiles of 37 participants were evaluated. Results: There were significant differences between the COP path lengths (p<.050) derived from the two systems, and a significant correlation was found for COP path length (r=.382~.523) for static balance. The ICC for COP path length and weight ratio was found to be greater than .687, indicating moderate agreement in balance parameters. The ICC of gait parameters was found to be greater than .697 except for stance time, and there was significant correlation (r=.678~.922) with the GaitRite system. Conclusion: The newly developed smart insole-type Pedisole system and the related application are useful, reliable, and valid tools for balance and gait analysis compared to the gold standard Pedoscan and the GaitRite systems in healthy individuals.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.141-148
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• 2021

In some intersections or busy traffic roads, there are more pedestrians in a specific period of time, and there are many traffic accidents caused by road congestion. Especially at the intersection where there are schools nearby, it is particularly important to protect the traffic safety of students in busy hours. In the past, when designing traffic lights, the safety of pedestrians was seldom taken into account, and the identification of motor vehicles and traffic optimization were mostly studied. How to keep the road smooth as far as possible under the premise of ensuring the safety of pedestrians, especially students, will be the key research direction of this paper. This paper will focus on person, motorcycle, bicycle, car and bus recognition research. Through investigation and comparison, this paper proposes to use YOLO v4 network to identify the location and quantity of objects. YOLO v4 has the characteristics of strong ability of small target recognition, high precision and fast processing speed, and sets the data acquisition object to train and test the image set. Using the statistics of the accuracy rate, error rate and omission rate of the target in the video, the network trained in this paper can accurately and effectively identify persons, motorcycles, bicycles, cars and buses in the moving images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.1-8
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• 2021

This study developed low-cost and high-efficiency pavement condition monitoring technology to produce the key information required for pavement management. A noise and artificial intelligence-based monitoring system was devised to compensate for the shortcomings of existing high-end equipment that relies on visual information and high-end sensors. From idea establishment to system development, functional definition, information flow, architecture design, and finally, on-site field evaluations were carried out. As a result, confidence in the high level of artificial intelligence evaluation was secured. In addition, hardware and software elements and well-organized guidelines on system utilization were developed. The on-site evaluation process confirmed that non-experts could easily and quickly investigate and visualized the data. The evaluation results could support the management works of road managers. Furthermore, it could improve the completeness of the technologies, such as prior discriminating techniques for external conditions that are not considered in AI learning, system simplification, and variable speed response techniques. This paper presents a new paradigm for pavement monitoring technology that has lasted since the 1960s.