• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.191-200
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• 2011

Levee failure cause the huge amount of damage to human and property. Overflow and erosion of levee are primary cause of a break in a levee but the analysis of breach pattern and impact is partially inadequate. The flow characteristics of meandering rivers are very important in field of river hydraulics that should be studied in practical viewpoints relating to river levee. In meandering the secondary flow that rotary direction is changed reciprocally occurs in three dimension is known. In this study flow characteristics of local river are considered and of meandering channels are analyzed using CCHE2D and FLOW3D. The stability and accuracy of models are examined comparing the measuring and analyzed data for the experimental channel and natural river(Namgang). Consequently, the flow characteristics in a meandering river are suggested precisely and it is essential that river levees having meandering river should be analyzed.

• Journal of Korean Physical Therapy Science
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• v.28 no.2
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• pp.46-56
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• 2021

Purpose: The purpose of this study is to examine whether the level of participation in physical activity affects the mental health of adolescents, that is, their subjective well-being. In addition, we would like to see if adolescents can improve their satisfaction with life away from the negative emotions they are currently feeling through physical activities such as hand-help and consolation activities and check if self-esteem has mediating effects in this process. Design: Survey. Methods: The survey was conducted by the surveyor, with a total of 9,041. Results: First, it shows that the higher frequency of adolescents' physical activity leads to higher self-esteem and subjective well-being. Second, it shows that the higher the self-esteem leads to higher subjective well-being felt by adolescents. Third, the level of youth physical activity itself contributes to subjective well-being while also affecting self-esteem, and the self-esteem also affects the subjective well-being that adolescents perceive. Conclusion: It will be necessary to provide programs to enhance subjective well-being for students with poor school life adaptation and satisfaction with life, as well as continuous attention such as organization and counseling of programs in schools to enhance self-esteem. In addition, it is considered that by encouraging and guiding teenagers with low satisfaction with life and low self-esteem to physical activities such as volunteer activities and leisure activities that suit their aptitude, and the adolescents will get away from the negative emotions they are currently feeling and increase their satisfaction with adaptation to school life and life.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.377-389
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• 2021

This paper presents a framework design of a digital twin system for a vertical smart farm. In this paper, a framework of digital twin systems establishes three factors: 1) Client 2) IoT gateway, and 3) Server. Especially, IoT gateway was developed using the Eclipse Ditto, which has been commonly used as the standard open hardware platform for digital twin. In particular, each factor is communicating with the client, IoT gateway, and server by defining the message sequence such as initialization and data transmission. In this paper, we describe the digital twin technology trend and major platform. The proposed design has been tested in a testbed of the lab-scale vertical smart-farm. The sensor data is received from 1 Jan to 31 Dec 2020. In this paper, a prototype digital twin system that collects environment and control data through a raspberry pi in a plant factory and visualizes it in a virtual environment was developed.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.84-94
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• 2021

Graph databases have been developed to efficiently store and query graph data composed of vertices and edges to express relationships between objects. Since the query types of graph database show very different characteristics from traditional NoSQL databases, benchmarking tools suitable for graph databases to verify the performance of the graph database are needed. In this paper, we propose an efficient graph database benchmarking system that supports diversity in graph inputs and queries. The proposed system utilizes OrientDB to conduct benchmarking for graph databases. In order to support the diversity of input graphs and query graphs, we use LDBC that is an existing graph data generation tool. We demonstrate the feasibility and effectiveness of the proposed scheme through analysis of benchmarking results. As a result of performance evaluation, it has been shown that the proposed system can generate customizable synthetic graph data, and benchmarking can be performed based on the generated graph data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.17-23
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• 2019

IaaS is well known as a very cost effective computing service which enables required infrastructures to be rented on demand without ownership of real hardwares. It is very suitable for price sensitive services due to pay-per-use style. Operators of such services would want to adjust utilization policy quickly by estimating costs for cloud infrastructures as soon as possible. However, swift response is not possible due to that cloud service providers provide a dozen or so hours delayed billing information. Our work proposes a realtime IaaS cost estimation model based on usages monitored by virtual machine instance. We operate PC laboratory service on a public cloud during full semester to validate our suggested model. From that experiment, an averaged disparity between estimation and actual cost is less than 5.2%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.822-828
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• 2019

An Augmented Reality(AR) provides virtual information with a real environment, and the processor needs to access the memory for the AR system. However, the processor has the heavy workload as the technology improvement leads to increase the size of data. We need a specific module to reduce the workload to overcome the limitation. In this paper, we propose a Direct Memory Access(DMA) controller displaying image instead of the processor. We implemented the proposed DMA controller on a Field Programmable Gate Array(FPGA) and demonstrated the functionality of the DMA controller based on an Avalon Memory Mapped(Avalon-MM) interface. Also, the DMA controller is fabricated by using Magnachip/Hynix 0.35um CMOS technology and verified the feasibility of the embedded system.

• Journal of the Korean Geosynthetics Society
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• v.18 no.2
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• pp.11-21
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• 2019

This paper describes the applicability of FEA(Finite Element Analysis) to the simulation of pile pullout behavior under various soil conditions (relative density and fines content), in order to evaluate reasonably the pullout resistance of pile. That is, the results of previous research (You et al., 2018) were analyzed by FEA under the same conditions. The FEA results showed that axisymmetric analysis using virtual ground was able to evaluate the skin friction of the pile. Also, axisymmetric analysis, which can apply the shear resistance characteristics of the pile-soil interface in various soil conditions, could be used as an analytical method that can simulate a reasonable pile pullout behavior. Therefore, the analytical model proposed in this study was able to simulate appropriately the pullout behavior based on the stress-strain relationship of the pile-soil interface.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.1
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• pp.12-22
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• 2019

This paper presents a method to perform a more efficient electromagnetic wave analysis inside a large building by external electromagnetic waves. Topological analysis and the PWB method are introduced for electromagnetic wave analysis. In addition, a Performance-Enhanced PWB method, which complements the performance of the PWB method is proposed. A large virtual structure was selected and an analysis environment was set up to perform the electromagnetic wave analysis inside a large building from external electromagnetic waves. A commercially available software, Wireless Insite, was used to verify the accuracy of the the Performance- Enhanced PWB method. As a result of comparing the two results in terms of accuracy, time, and memory, We conclude that the Performance-Enhanced PWB method proposed in this paper is a more efficient method in a large bulding.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.55-63
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• 2019

Recently, the GPU computing method has been utilized to improve the performance of the physics simulation field. In particular, in the case of a deformed object simulation requiring a large amount of computation, a GPU-based parallel processing algorithm is required to guarantee real-time performance. We have studied the parallel structure design method to improve the performance of the mass spring simulation method which is one of the methods of implementing the deformation object simulation. We used OpenGL's GLSL, a graphics library that allows direct access to the GPU, and implemented the GPGPU environment using an independent pipeline, the compute shader. In order to verify the effectiveness of the parallel structure design method, the mass - spring system was implemented based on CPU and GPU. Experimental results show that the proposed method improves computation speed by about 6,000% compared to the CPU Environment. It is expected that the lightweight simulation technology can be effectively applied to the augmented reality and the virtual reality field by using the design method proposed later in this research.

• Journal of the Korea Society of Computer and Information
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• v.26 no.9
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• pp.57-64
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• 2021

In this paper, we propose a device that can control the primary control surface of an aircraft by recognizing speech commands. The speech command consists of 19 commands, and a learning model is constructed based on a total of 2,500 datasets. The training model is composed of a CNN model using the Sequential library of the TensorFlow-based Keras model, and the speech file used for training uses the MFCC algorithm to extract features. The learning model consists of two convolution layers for feature recognition and Fully Connected Layer for classification consists of two dense layers. The accuracy of the validation dataset was 98.4%, and the performance evaluation of the test dataset showed an accuracy of 97.6%. In addition, it was confirmed that the operation was performed normally by designing and implementing a Raspberry Pi-based control device. In the future, it can be used as a virtual training environment in the field of voice recognition automatic flight and aviation maintenance.