• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.985-992
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• 2020

Edge computing is a technology that can prepare for a new era of cloud computing. Edge computing is not a remote data center where data is processed and computed, but low-latency/high-speed computing is realized by adding computing power and data processing power to the edge side close to an access point such as a terminal device or a gateway. It is possible. The types of edge computing include mobile edge computing, fog computing, and cloudlet computing. In this article, we describes existing open source platforms for implementing edge computing nodes. By presenting and comparing the structure, features of open source edge platforms, it is possible to acquire knowledge required to select the best edge platform for industrial engineers who want to build an edge node using an actual open source edge computing platform.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.162-169
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• 2022

In a dynamically changing time-varying network environment, the optimal moving pattern of edge devices can be applied to distributing computing resources to edge cloud servers or deploying new edge servers in the FEC(Fog/Edge Computing) environment. In addition, this can be used to build an environment capable of efficient computation offloading to alleviate latency problems, which are disadvantages of cloud computing. This paper proposes an algorithm to extract the optimal moving pattern by analyzing the moving path of multiple edge devices requiring application services in an arbitrary spatio-temporal environment based on frequency. A comparative experiment with A^* and Dijkstra algorithms shows that the proposed algorithm uses a relatively fast execution time and less memory, and extracts a more accurate optimal path. Furthermore, it was deduced from the comparison result with the A^* algorithm that applying weights (preference, congestion, etc.) simultaneously with frequency can increase path extraction accuracy.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.399-406
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• 2023

Cloud computing has been evolved to support edge computing architecture that combines fog management layer with edge servers. The main reason why it is received much attention is low communication latency for real-time IoT applications. At the same time, various cloud task scheduling techniques based on artificial intelligence have been proposed. Artificial intelligence-based cloud task scheduling techniques show better performance in comparison to existing methods, but it has relatively high scheduling time. In this paper, we propose a deep learning-based dynamic scheduling with multi-agents supporting scalability in edge computing environments. The proposed method shows low scheduling time than previous artificial intelligence-based scheduling techniques. To show the effectiveness of the proposed method, we compare the performance between previous and proposed methods in a scalable experimental environment. The results show that our method supports real-time IoT applications with low scheduling time, and shows better performance in terms of the number of completed cloud tasks in a scalable experimental environment.

• Convergence Security Journal
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• v.23 no.2
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• pp.85-94
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• 2023

In the face of the serious security situation with the increasing threat from North Korea, Korean Army is pursuing a reduction in troops through the performance improvement project of the GOP science-based border security system, which utilizes advanced technology. In order for the GOP science-based border security system to be an effective alternative to the decrease in military resources due to the population decline, it must guarantee a high detection and identification rate and minimize troop intervention by dramatically improving the false detection rate. Recently introduced in Korean Army, the GOP science-based border security system is known to ensure a relatively high detection and identification rate in good weather conditions, but its performance in harsh weather conditions such as rain and fog is somewhat lacking. As an alternative to overcoming this, a radar-based border security system that can detect objects even in bad weather has been proposed. This paper proves the effectiveness of the AI-based scientific border security system based on radar that is being currently tested at the 00th Division through the 2021 Rapid Acquisition Program, and suggests the direction of development for the GOP scientific border security system.

• Journal of the Korean earth science society
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• v.36 no.6
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• pp.567-579
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• 2015

The accurate simulation of micro-scale weather phenomena such as fog using the mesoscale meteorological models is a very complex task. Especially, the uncertainty arisen from initial input data of the numerical models has a decisive effect on the accuracy of numerical models. The data assimilation is required to reduce the uncertainty of initial input data. In this study, the limitation of the mesoscale meteorological model was verified by WRF (Weather Research and Forecasting) model for a summer fog event around the Nakdong river in Korea. The sensitivity analyses of simulation accuracy from the numerical model were conducted using two different initial and boundary conditions: KLAPS (Korea Local Analysis and Prediction System) and LDAPS (Local Data Assimilation and Prediction System) data. In addition, the improvement of numerical model performance by FDDA (Four-Dimensional Data Assimilation) using the observational data from AWS (Automatic Weather System) was investigated. The result of sensitivity analysis showed that the accuracy of simulated air temperature, dew point temperature, and relative humidity with LDAPS data was higher than those of KLAPS, but the accuracy of the wind speed of LDAPS was lower than that of KLAPS. Significant difference was found in case of relative humidity where RMSE (Root Mean Square Error) for LDAPS and KLAPS was 15.7 and 35.6%, respectively. The RMSE for air temperature, wind speed, and relative humidity was improved by approximately $0.3^{\circ}C$, $0.2m\;s^{-1}$, and 2.2%, respectively after incorporating the FDDA.

• Journal of agriculture & life science
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• v.46 no.3
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• pp.119-127
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• 2012

For the promotion of the evaporative cooling efficiency of hot air in greenhouse in summer, a fog sprayer consisted of a high volume spraying two-fluid nozzle with turbo fan and a blowing fan was set up at 2.2 m height from bottom of small glass greenhouse and tested to estimate the possibility of the greenhouse cooling. The mean droplet size and the volume sprayed by one of fog sprayer were $29{\mu}m$ and $160m{\ell}/min$. All the droplets sprayed and blown by the fog sprayer were evaporated within 2 m radius. The result from the cooling test that two sprayers set up in glass greenhouse of plane area $228m^2$ was represented lower cooling effect that the temperature and relative humidity of inside air of greenhouse were $28.8^{\circ}C$ and 87.5% when those of outside air of greenhouse were $30.2^{\circ}C$ and 81.2%. Through investigation of literatures and results of the cooling test, it was estimated that the water spraying rate of evaporative cooling of single span greenhouse with 50% light curtain and with air change rate of 1 volume/min was $10m{\ell}/min/m^2$ so that the inside air temperature may cool down $2{\sim}3^{\circ}C$ on the basis of $35^{\circ}C$ atmospheric temperature in summer of south korean area.

• Proceedings of the KIEE Conference
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• 1999.07d
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• pp.1605-1607
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• 1999

Silicone rubber have presently been using in large number for a variety of outdoor HV applications. Silicone rubber have the properties of low surface energy and are able to retain its hydrophobicity or water repellency, thereby suppress the leakage current in the present of moisture and contamination. In this paper, we investigated the recovery characteristics of silicone rubber by measuring the leakage current under salt-fog.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.2
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• pp.190-196
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• 2004

ACR(All Clear Reflector), also widely referred to as FFR(Free Form Reflector), were designed in general and intelligent ways using a NUDBS surface for the mathematical modelling of the reflector shape and artificial intelligence as the optimum design algorithm. An ACR, which consists of a continuous surface reflector and clear outer lens, offers styling advantages and provides a high quality light performance. The clear outer lens of an ACR remains efficient even with a highly inclined shape, as in the design of a sports car, as well as the complete clearness of the reflector surface eliminates the nuisance of stray light caused by the steps between adjacent segments of multi-faced reflectors. The application of an ACR to low beam lamp was so sucessful to obtain the sharp cut-off with the lens-free single-surfaced-smooth reflector. The design technique of ACR was tested with all types of lamps, including low beams, high beams, and fog lamps.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.124-126
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• 1996

In this paper, the driving systems of the Fiber Optic Gyrocompass absolutely required a constant speed and a precise position control with fine step angle, are presented. One of the proposed systems is a stepping motor system with microstep driver, another one is a DC servo motor. Experimental results indicate that a low cost and simple FOG driving system using a stepping motor is capable of a satisfactory operation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.260-263
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• 2017

본 논문은 single image에서 측정한 빛 전달량 값과 local contrast 값을 사용하여 안개 량을 수치화하는 방법을 제안한다. 제안하는 방법은 빛 전달량 값을 사용하여 안개로 예측되는 지역을 추정하고, 추정된 안개 예측지역의 넓이와 해당 지역의 local contrast 크기의 범위를 사용하여 안개 정도를 수치화 한다. single image에서 측정 가능한 안개 의 물리적 특성들을 고려하였기 때문에 기존의 안개 검출 알고리즘들이 구분하지 못했던 영상들에서도 안개 량을 정확하게 측정하였다. 실제 빛의 산란 정도를 측정하는 감광 계수 측정계를 사용하여 측정한 안개 량과 제안하는 방법의 수치를 비교했을 때, 다양한 환경과 물체를 포함한 영상들에서 95%이상의 정확도로 안개 정도를 수치화 하였다. 또한 빛 전달량 추정 과정에서 local contrast 값을 추출하여 사용하기 때문에 기존의 빛 전달량을 측정하는 방법에서 복잡도를 거의 증가시키지 않는다.