• Journal of Biosystems Engineering
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• 제42권1호
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• pp.23-43
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• 2017

Purpose: As application-specific wireless sensor networks are gaining popularity, this paper discusses the development and field performance of the GHAN, a greenhouse area network system to monitor, control, and access greenhouse microenvironments. GHAN, which is an upgraded system, has many new functions. It is an intelligent wireless sensor and actuator network (WSAN) system for next-generation greenhouses, which enhances the state of the art of greenhouse automation systems and helps growers by providing them valuable information not available otherwise. Apart from providing online spatial and temporal monitoring of the greenhouse microclimate, GHAN has a modified vapor pressure deficit (VPD) fuzzy controller with an adaptive-selective mechanism that provides better control of the greenhouse crop VPD with energy optimization. Using the latest soil-matrix potential sensors, the GHAN system also ascertains when, where, and how much to irrigate and spatially manages the irrigation schedule within the greenhouse grids. Further, given the need to understand the microclimate control dynamics of a greenhouse during the crop season or a specific time, a statistical assessment tool to estimate the degree of optimality and spatial variability is proposed and implemented. Methods: Apart from the development work, the system was field-tested in a commercial greenhouse situated in the region of Punjab, India, under different outside weather conditions for a long period of time. Conclusions: Day results of the greenhouse microclimate control dynamics were recorded and analyzed, and they proved the successful operation of the system in keeping the greenhouse climate optimal and uniform most of the time, with high control performance.

• 한국안전학회지
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• 제36권5호
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• pp.79-85
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• 2021

A standard engineering model that reflects the current organization system and engineering operation process of domestic nuclear power plants was developed based on the Standard Nuclear Performance Model developed by the American Nuclear Energy Association. The level 0 screen, which is the main screen of the engineering model computer system, consisted of an object tree structure, which provided information that is phased down from a higher structure level to a lower structure level (i.e., level 3). The level 1 screen provided information related to the sub-process of the engineering operation, whereas the Level 2 screen provided information related to each engineering operation activity. In addition, the Level 2 screen provided additional functions, such as linking electronic procedures/guidelines, providing electronic performance forms, and connecting legacy computer systems (such as total equipment reliability monitoring system, configuration management systems, technical information systems, risk monitoring systems, regulatory information, and electronic drawing system). This screen level increased the convenience of user's engineering tasks by implementing them. The computerization of an engineering model that connects the entire engineering tasks of an establishment enables the easy understanding of information related to the engineering process before and after the operation, and builds a foundation for the enhancement of the work efficiency and employee capacity. In addition, KHNP developed an online training module, which operates as an e-learning process, on the overview and utilization of a standard engineering model to expand the understanding of standard engineering models by plant employees and to secure competitiveness.

• 한국인터넷방송통신학회논문지
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• 제14권3호
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• pp.69-74
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• 2014

범죄발생 예방 및 도로상 교통 상황파악 등 각종 요구로 인하여 각 기관 및 지자체 마다 CCTV설치가 이루어져 우리 주변의 많은 곳에서 CCTV를 살펴볼 수 있다. 이렇게 기존에 설치된 CCTV의 공간적 분포도만의 단면적 분석자료로는 향후 신규로 설치될 CCTV의 위치 선정이나 제한된 예산으로 이루어져야 할 시스템 구축에 명확한 기준을 줄 수 없다. 또한 각각의 기관마다 내부적으로 고유의 업무 기능 수행결과로 구축된 자료인 DataBas들이 많이 있지만 이를 다른 목적을 위해 통합적으로 분석하는 경우는 빈번하지 않다. 매시업(Mashup)은 별도로 존재하는 정보와 서비스를 융합하여 새로운 서비스, 데이터베이스 등을 만드는 것을 말한다. 이에 본 연구는 지역의 교통 환경, 기설치된 CCTV위치, 방범 등의 기관 내부 DB를 매쉬업기능을 통하여 안양시를 중심으로 하여 새로운 CCTV 설치 위치를 결정하는 방법을 제공한다.

• Journal of Electrical Engineering and Technology
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• 제3권4호
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• pp.484-490
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• 2008

In this paper, an integrated fault section detection and isolation strategy is proposed based on the application of the Distribution Automation System(DAS) utilizing advanced IT and communication technologies. The Feeder Remote Terminal Unit(FRTU) has been widely used to collect data in the Korean distribution system. The achieved data is adopted in this method for detecting multiple fault types. Especially in the case of single phase-to-ground fault, the fault section is detected by comparison of the zero-sequence current phase angle. The test results have verified the effectiveness of the proposed method in a radial distribution system through extensive simulations in Matlab/Simulink. Furthermore, a communication-based demo system identical to the simulation model has been developed, and it can be applied as an online monitoring and control program for fault section detection and isolation.

• Journal of Multimedia Information System
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• 제8권3호
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• pp.159-166
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• 2021

COVID-19 has dramatically changed people's daily life. Wearing masks is considered as a simple but effective way to defend the spread of the epidemic. Hence, a real-time and accurate mask wearing detection system is important. In this paper, a deep learning-based mask wearing detection system is developed to help people defend against the terrible epidemic. The system consists of three important functions, which are image detection, video detection and real-time detection. To keep a high detection rate, a deep learning-based method is adopted to detect masks. Unfortunately, according to the suddenness of the epidemic, the mask wearing dataset is scarce, so a mask wearing dataset is collected in this paper. Besides, to reduce the computational cost and runtime, a simple online and real-time tracking method is adopted to achieve video detection and monitoring. Furthermore, a function is implemented to call the camera to real-time achieve mask wearing detection. The sufficient results have shown that the developed system can perform well in the mask wearing detection task. The precision, recall, mAP and F1 can achieve 86.6%, 96.7%, 96.2% and 91.4%, respectively.

• Smart Structures and Systems
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• 제29권1호
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• pp.77-91
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• 2022

Various monitoring systems have been implemented in civil infrastructure to ensure structural safety and integrity. In long-term monitoring, these systems generate a large amount of data, where anomalies are not unusual and can pose unique challenges for structural health monitoring applications, such as system identification and damage detection. Therefore, developing efficient techniques is quite essential to recognize the anomalies in monitoring data. In this study, several machine learning techniques are explored and implemented to detect and classify various types of data anomalies. A field dataset, which consists of one month long acceleration data obtained from a long-span cable-stayed bridge in China, is employed to examine the machine learning techniques for automated data anomaly detection. These techniques include the statistic-based pattern recognition network, spectrogram-based convolutional neural network, image-based time history convolutional neural network, image-based time-frequency hybrid convolution neural network (GoogLeNet), and proposed ensemble neural network model. The ensemble model deliberately combines different machine learning models to enhance anomaly classification performance. The results show that all these techniques can successfully detect and classify six types of data anomalies (i.e., missing, minor, outlier, square, trend, drift). Moreover, both image-based time history convolutional neural network and GoogLeNet are further investigated for the capability of autonomous online anomaly classification and found to effectively classify anomalies with decent performance. As seen in comparison with accuracy, the proposed ensemble neural network model outperforms the other three machine learning techniques. This study also evaluates the proposed ensemble neural network model to a blind test dataset. As found in the results, this ensemble model is effective for data anomaly detection and applicable for the signal characteristics changing over time.

• 컴퓨터교육학회논문지
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• 제10권2호
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• pp.89-100
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• 2007

대규모 집단을 대상으로 시행하는 서답형 문항을 수기 채점 방식으로 채점하는 경우 채점 과정에서 발생하는 채점 오차를 줄이기 위해서는 많은 노력과 시간을 필요로 한다. 이러한 문제점을 해결하기 위해 세계 각국에서는 서답형 문항 채점 시스템을 개발하여 운용하고 있지만, 국내에서는 채점 시스템의 기초적인 연구도 미흡한 실정이다. 본 연구의 목적은 '서답형 문항의 인터넷 기반 채점 시스템' 설계의 기반을 마련하는데 있다. 시스템 설계의 기반 마련을 위한 시스템의 개요와 기본 설계도, 채점자 배정 방법, 채점자 신뢰도 추정에 의한 채점자 오류 검색 알고리즘을 제안하였다. 본 시스템은 실시간으로 채점 신뢰도를 추정하여 채점 오차를 보정할 수 있는 장점이 있다.

• 한국식품위생안전성학회지
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• 제38권6호
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• pp.496-507
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• 2023

본 연구는 대한민국 온라인 시장에서 판매되는 48개의 새우 제품의 종판별 및 제품 표시 사항 일치 여부를 조사하였다. 사용 원재료의 종 판별을 위해 cytochrome c oxidase subunit I 유전자의 염기서열을 분석하여 NCBI GenBank 및 BOLD system 데이터베이스에 등록된 생물종의 염기서열과 비교하였다. 또한 계통분석을 수행하여 동정된 새우종을 추가로 검증했다. 종판별 결과 총 16종[흰다리새우(Penaeus vannamei, Whiteleg shrimp or Pacific white shrimp), 북쪽분홍새우(Pandalus borealis, Alaskan pink shrimp), 그라비새우(Palaemon gravieri, Chinese ditch prawn), 돗대기새우(Leptochela gracilis, Lesser glass shrimp), 얼룩새우(Penaeus monodon, Giant tiger prawn), 아르헨티나붉은새우(Pleoticus muelleri, Argentine red shrimp), 산모양깔깔새우(Metapenaeopsis dalei, Kishi velvet shrimp), 태평양난바다곤쟁이(Euphausia pacifica, Isada krill), 가시배새우(Lebbeus groenlandicus, Spiny lebbeid), 꽃새우(Trachypenaeus curvirostris, Southern rough shrimp), 진흙새우(Argis lar, Kuro shrimp), 가시발새우(Metanephrops thomsoni, Red-banded lobster), 깔깔새우(Metapenaeopsis barbata, Whiskered velvet shrimp), 긴발딱총새우(Alpheus japonicus, Japanese snapping shrimp), 대하(Penaeus chinensis, Fleshy prawn), 긴뿔민새우(Mierspenaeopsis hardwickii, Spear shrimp)]이 확인되었으며, 흰다리새우(n=22, 45.8%)가 가장 큰 비중을 차지하였다. 일반명 '새우'를 포함하는 35개 제품(72.9%)에서 표시사항과 불일치를 나타내었으며, 일반명(n=30)을 제외할 경우 불일치율은 10.4%로 낮아졌다. 가공 정도별 불일치율은 다중 가공 제품(n=25, 89.3%)이 단순 가공 제품(n=10, 50%)보다 높은 비율을 보였다. 원산지별 분석 결과 특정 국가와 불일치율과의 상관성은 확인할 수 없었다. 본 연구 결과는 향후 새우 제품의 모니터링 수행 및 새우의 국명 표시 개선을 위한 기초자료로 쓰일 수 있을 것이다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.38-43
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• 1994

To provide more instructive and a safer ground control operation environments for satellite operators, and subsequently to implement a better look-and-feel user interface and a structural mechanism to enhance the efficiency of control and monitoring facilities, we have developed a prototype(laboratory model) ground control softwares targeting for the first generation KOREASAT scheduled to be launched in 1995. As far as the functionality is concerned, the developed system is covering almost all the mission phase operational functions except for some functions like antenna tracking control that are necessary for real operation environments. Most of the functions of the system is realized in softwares but some hardwares needed for TM/TC RF communications are also included in it. The system is now being integrated and under the system test. The performance and functionality is to be evaluated by the end of this year by using the satellite software simulator. Next year, this system could be configured to be used as a workbench for a online/off-line analysis of the operating KOREASAT satellites.

• 융합신호처리학회논문지
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• 제8권3호
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• pp.211-216
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• 2007

대형 정수장에서 개인수도꼭지까지 전체 급수 설비에서 수질은 반드시 먹는 물 수질기준을 만족해야 한다. 그러나 현재까지도 수돗물의 공급과정은 과학적으로 모니터링 되거나 관리되지 못하고 있다. 수돗물 특히 대부분의 작은 규모의 정수장은 항상 다양한 오염원 및 불순물 등에 노출되어 있다. 최근 일부 대형 정수장이나 배수지 등에 수질감시 시스템이 사용되고 있다. 특히 인터넷을 이용한 수질 모니터링 방법이 일부 지방자치단체에 도입되었으며 이 시스템은 해당 지역주민들이 언제 어디서나 수질을 확인할 수 있도록 되어있다. 그러나 이 시스템, 즉 대형 시스템에 사용되는 이 방법은 매우 높은 비용을 필요로 하고 이로 인해 아파트, 공공시설, 소규모의 지하저수조 및 고가(高架)저수조와 같은 소규모 급수설비에는 적용하기가 곤란하다. 따라서 본 연구에서는 저가의 개별 수질측정 센서모듈에 대한 통합시스템을 제안한다. 개발된 통합 시스템과 인터넷상에서 동작하는 모니터링 프로그램을 이용하여 저수조 시스템 관리자는 음용수에 대한 수질 특성치를 실시간으로 관리할 수 있다. 또한 제안된 시스템이 모듈화 되어있기 때문에 크고 작고의 규모에 관계없이 저비용으로 다양한 저수조나 정수장에 쉽게 설치할 수 있다.