• Journal of Korea Society of Industrial Information Systems
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• v.25 no.5
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• pp.31-39
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• 2020

According to lessons learned from an accident of Fukushima Daiichi nuclear power plant, it is advisable to make a comprehensive radiation survey by the accident phase for efficient response and risk management using diverse survey platforms. This study focuses on the technical status of environmental radiation monitoring using a UAV (Unmanned aerial vehicle) and the performance test of developed aerial survey system based on two detectors with an high energy resolution through the field application to contaminated areas. Finally, the performance of aerial survey at diverse flight heights was successfully achieved by introducing the correction factor to represent the results into ambient dose rate at 1m above the ground.

• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.4
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• pp.15-22
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• 2002

In the course of seismic probabilistic risk assessment(SPRA), seismic fragility analysis(SFA) is utilized as a tool to evaluate the actual seismic capacity of structures. This paper introduces a methodology of SFA and its evaluation procedures, especially focusing on the basic fragility variables. A new definition of the response spectrum shape factor as one of the most critical basic variables is suggested. The new factor is expressed as a term of linear algebraic sum using the modal contribution factor. The efficiency of new response spectrum shape factor is evaluated and validated to use in practice through the case study of the nuclear power plant structures. The case study results show that the proposed method can be effectively applicable to multi-mode structures with composite modal damping.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.4
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• pp.118-129
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• 2008

This paper describes an IEEE 802.15.4-based hierarchical sensor network model for a VAWS(Vehicle Approach Warning System) which provides the drivers of vehicles approaching a sharp turn with the information about vehicles approaching the same turn from the opposite end. In the proposed network model, a tree-structured topology, that can prolong the lifetime of network is formed in a self-organizing manner by a topology control protocol. A simple but efficient routing protocol, that creates and maintains routing tables based on the network topology organized by the topology control protocol, transports data packets generated from the sensor nodes to the base station which then forwards it to a display processor. These protocols are designed as a network layer extension to the IEEE 802.15.4 MAC. In the simulation, which models a scenario with a sharp turn, it is shown that the proposed network model achieves a high-level performance in terms of both energy efficiency and throughput simultaneously.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1173-1179
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• 2008

Since there are very strong clutter returns in airborne and ground weather radars used for the detection of low altitude weather hazards, the reliable weather data cannot be extracted from the weak Doppler weather signal without cancellation of these strong clutter returns. However, the clutter cancellation in Doppler frequency domain is not an easy task since even the fixed clutter returns not to mention the moving clutter can have Doppler shifts due to the antenna rotation and operational environment. Therefore, it was shown in this paper a simple array antenna system can be used for the efficient clutter cancellation in the spatial domain. The weather signal, various moving and fixed clutters were modelled and simulated to prove the performance of this adaptive array system. Also, the degree of accuracy in pulse-pair estimates of a weather radar was compared and analyzed from the simulated weather data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.3
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• pp.581-589
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• 2008

The goal of a simulator is to provide for the testing of new technologies and to facilitate the eventual transfer of these technologies to the applications. In the Development Step, Simulation can provide a cost effective alternative to expensive and hazardous field testing. In this paper, a 3D simulator is developed to test UUV navigation system bated on RVC model. The simulation system consists of a environment manager, objects and a 3D viewer. Objects are modeling all physical elements such as map, obstacle and UUV which reside in a underwater environment. Those objects are created and initialized by environment manager. The environment manager plays the role of intermediator which allows created objects to interact with each other, and transmits information on the objects to 3D viewer. The 3D viewer analyzes the received information and visualizes 3D graphic by using OpenGL primitives.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.17-24
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• 2017

As the fourth industrial revolution era, lots of new convergence products are being launched but most of them are disappearing due to intense competition. In particular, small and medium-sized businesses(SMBs) don't have a lot of management capabilities, so they focus on performance and quality rather than considering specific marketing strategies when planning a product. However, if the strategy isn't included when new convergence products are planned, it can be difficult to enter the initial market and mainstream market. In this paper, we examined the risk factors that may occur in the process of transition from the initial market to the mainstream market, from chasm marketing perspective. Through this analysis, to launch new convergence product and go beyond chasm at the same time, we have analyzed the chasm marketing and social network perspective, and then suggested four marketing strategies. When SMBs make new convergence product enter into mainstream market, these marketing strategies will be favorable to them which want to position at the dominant advantage of the market in the fierce competition.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.149-157
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• 2014

Diabetes is a chronic disease that requires continuous medical care and patient-self management education to prevent acute complications and reduce the risk of long-term complications. The worldwide prevalence and incidence of diabetes mellitus are reached epidemic proportions in most populations. Early detection of diabetes could help to prevent its onset by taking appropriate preventive measures and managing lifestyle. The major objective of this research is to develop an automated decision support system for detection of diabetes using mixture of experts model. The performance of the classification algorithms was compared on the Pima Indians diabetes dataset. The result of this study demonstrated that the mixture of expert model achieved diagnostic accuracies were higher than the other automated diagnostic systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.135-140
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• 2021

In this paper, we propose an on-line mechanism that simultaneously detects cracks and profiling pavement blocks to detect the displacement of ground surface adjacent to the excavation in the urban area. The proposed method utilizes a 2D laser to profile the information about pavement blocks including the depth and distance among them. In particular, it is designed to enable the detection of cracks and portholes at runtime. For the experiment, real data was collected through Gocator, and trainng was carried out using Faster R-CNN. The performance evaluation shows that our detection precision and recall are more than 90% and the pavement blocks are profiled at the same time. Our proposed mechanism can be used for monitoring management to quantitatively detect the level of excavation risk before a large-scale ground collapse occurs.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.5
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• pp.182-189
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• 2021

VPS(Void Plywood Slab System, VPS) has optimized the shape of the hollow material. In addition, it has a function to prevent the floating of the hollow material and the separation due to the working load. In this study, the punching shear capacity of flat plate was performed using Void Plywood Slab System with form work panel proposed in the previous study. As a result of the test, the strength of the VSPS specimen in which the hollow material was placed beyond 2.0 times the column width from the loading point was reduced by 9.4% compared to the reference specimen. However, the strength value was about 1.57 times higher than the design value suggested by KBC 2016. It was found that there was no change in stiffness compared to the reference specimen until shear failure occurred in the VSPS specimen in which the hollow material was placed. It can be seen that this experiment is being destroyed by shear as the flexural reinforcing bars are sufficiently reinforced.

• Journal of Biomedical Engineering Research
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• v.40 no.2
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• pp.62-67
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• 2019

The purpose of this study was to evaluate the performance of deep neural network model in order to determine whether there is a risk factor for coronary artery disease based on the cardiac variation parameter. The study used unidentifiable 297 data to evaluate the performance of the model. Input data consists of heart rate parameters, which are SDNN (standard deviation of the N-N intervals), PSI (physical stress index), TP (total power), VLF (very low frequency), LF (low frequency), HF (high frequency), RMSSD (root mean square of successive difference) APEN (approximate entropy) and SRD (successive R-R interval difference), the age group and sex. Output data are divided into normal and patient groups, and the patient group consists of those diagnosed with diabetes, high blood pressure, and hyperlipidemia among the various risk factors that can cause coronary artery disease. Based on this, a binary classification model was applied using Deep Neural Network of deep learning techniques to classify normal and patient groups efficiently. To evaluate the effectiveness of the model used in this study, Kernel SVM (support vector machine), one of the classification models in machine learning, was compared and evaluated using same data. The results showed that the accuracy of the proposed deep neural network was train set 91.79% and test set 85.56% and the specificity was 87.04% and the sensitivity was 83.33% from the point of diagnosis. These results suggest that deep learning is more efficient when classifying these medical data because the train set accuracy in the deep neural network was 7.73% higher than the comparative model Kernel SVM.