• 해양환경안전학회지
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• 제29권7호
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• pp.887-892
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• 2023

해상교통관제센터에는 RADAR, AIS(Automatic Identification System), 기상센서, VHF(Very High Frequency) 등이 설치되어 운영되고 있으며, 해상교통관제사는 이를 활용하여 관제구역을 통항하는 선박의 동정을 관찰하고 정보를 제공하는 관제 업무를 수행한다. 이들 장비에서 생성되는 각종 관제 데이터는 해상교통 상황을 분석하기 위한 자료로 그 활용 가치가 매우 높지만, 시스템 제조사간 호환성 부족 또는 정책상의 문제로 인해 체계적으로 관리되지 않고 있는 실정이다. 이에 본 연구에서는 해상교통관제센터에서 수집되는 관제 데이터를 효율적으로 수집, 저장, 관리할 수 있는 관제 빅데이터 체계를 개발하였다. 개발된 관제 빅데이터 체계는 체계 개발의 중요한 이슈 중 하나였던 운영 안정성을 확보하기 위해 마이크로서비스 아키텍처를 적용하였으며, 효율적인 실시간 운항 정보의 탐색을 위해 저장소를 이원화하여 체계 성능을 향상시킬 수 있었다. 구현된 체계는 실해역 데이터를 적용한 시범 운영을 통해 성능을 확인하고 추가적인 개선 사항을 파악하였으며, 실제 관제 환경에서의 활용 가능성을 검토하였다.

• 정보교육학회논문지
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• 제11권2호
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• pp.139-146
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• 2007

현재 RFID(Radio Frequency Identification) 카드를 이용한 활용분야는 의료, 유통, 군사, 제조, 보안, 등 다양하게 확장되고 있다. RFID 기술은 식별 대상을 원거리에서 무선 주파수를 통해 한꺼번에 많은 정보를 인식할 수 있는 장점으로 인하여, 기존에 사용하던 바코드를 대체할 기술로서 주목받고 있다. 또한, 학교에서도 도서대출 관리 및 학생출석 관리 등의 RFID를 이용한 시스템에 대한 관심이 높아지고 있다. 본 논문은 RFID 카드를 이용한 출석관리 시스템을 개발하였으며, 교수들은 출석현황을 모바일로 확인할 수 있도록 하였고, 학생들은 웹을 통해서 언제든지 자신의 출석현황을 조회할 수 있도록 하였다. 그리고 학생들의 정보는 RFID 태그가 내장된 학생증을 소지하는 것만으로도 RFID 카드 판독기를 통해 정보가 수신된 후 DB에 저장되게 하였으며, 교수와 학생은 각각 관리자 프로그램과 웹 프로그램을 통해 출석부와 시간표를 관리하고 출력할 수 있다.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권7호
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• pp.313-318
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• 2006

An automatic sample centering system is underway at the protein crystallography beam line of the Pohang Light Source to improve the efficiency of the crystal screening process. A sample pin which contains a protein crystal is mounted on a goniometer head. Then the crystal should be moved to the center of X-ray beam by controlling the motorized goniometer to obtain diffraction data. Since the X-ray beam is located at the center of the image obtained from the CCD camera when the image of the sample pin is in focus, an auto-focusing algorithm is a very important part in the auto-sample-centering system. However the results of applying several well-known auto focusing algorithms directly to the images are not satisfactory owing to the following factors: misalignment of CCD camera, non-uniform cryo-stream in the background of the image and the supporter of the loop. The performance of an auto-focusing algorithm can be increased if the algorithm is applied to only the loop region identified. Non-uniform cryo-stream and a various illumination condition and a stain, which is shown in the image, are main obstacles to loop region identification. In this paper, a simple loop region identification algorithm, which can solve these problems, is proposed and the effective ness of the proposed scheme is shown by applying the auto-focusing algorithm to the loop region identified.

• 방사선산업학회지
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• 제17권1호
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• pp.11-17
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• 2023

Waste generated during the dismantling of nuclear power plants is not only diverse in types such as metal, concrete, soil, but also in a large amount, requiring systematic and efficient management. It is very important to quickly and accurately measure radioactive contamination of wastes generated simultaneously at the decommissioning site, classify them by level, and make decisions so that they can be disposed of in accordance with related laws and regulations. In this paper, for the technical and economic aspects of recycling of radioactive metal waste generated during the dismantling of nuclear power plants, we propose a management system that can measure the radioactive contamination by shape of metal waste at the decommissioning site and automatically classify it according to the presence or absence of contamination. Accordingly, a system for collecting information on metal samples such as weight measurement and shape acquisition of metal waste, measurement of radioactive contamination and identification of nuclides, and an automatic classification system according to radioactivity measurement results were described.

• 대한기계학회논문집A
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• 제21권6호
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• pp.988-994
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• 1997

The demands for robotic and automatic system are continually increasing in manufacturing fields. There have been many studies to monitor and predict the system, but they have mainly focused upon measuring cutting force, and current of motor spindle, and upon using acoustic sensor, etc. In this study, digital image of time series sequence was acquired by taking advantage of optical technique. Mean square error was obtained from it and was available for useful observation data. The parameter was estimated using PAA(parameter adaptation algorithm) from observation data. AR(auto regressive) model was selected for system model and fifth order was decided according to parameter estimation. Uncorrelation test was also carried out to verify convergence of parameter. Through the proceedings, it was found that there was a system stability.

• Journal of Multimedia Information System
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• 제4권4호
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• pp.233-238
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• 2017

Automatic identification of disease in plants from their leaves is one of the most challenging task to researchers. Diseases among plants degrade their performance and results into a huge reduction of agricultural products. Therefore, early and accurate diagnosis of such disease is of the utmost importance. The advancement in deep Convolutional Neural Network (CNN) has change the way of processing images as compared to traditional image processing techniques. Deep learning architectures are composed of multiple processing layers that learn the representations of data with multiple levels of abstraction. Therefore, proved highly effective in comparison to many state-of-the-art works. In this paper, we present a plant disease identification methodology from their leaves using deep CNNs. For this, we have adopted GoogLeNet that is considered a powerful architecture of deep learning to identify the disease types. Transfer learning has been used to fine tune the pre-trained model. An accuracy of 85.04% has been recorded in the identification of four disease class in Apple plant leaves. Finally, a comparison with other models has been performed to show the effectiveness of the approach.

• 한국통신학회논문지
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• 제32권4A호
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• pp.358-364
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• 2007

RFID(Radio Frequency IDentification) 기술은 라디오 주파수를 사용하는 비접촉 자동인식 기술이다. 이런 RFID 기술의 확산을 위해서는 리더(reader)가 다수의 태그(tag)를 짧은 시간 안에 인식하는 다중 태그 식별 문제를 해결 해야만 한다. 지금까지 이 문제를 해결하기 위한 충돌 방지(anti-collision) 알고리즘이 많이 개발되었고 이것들은 크게 알로하(ALOHA) 기반 알고리즘과 트리(tree) 기반 알고리즘으로 나뉜다. 본 논문에서는 이 두 가지 방법의 특징을 혼합한 새로운 충돌 방지 알고리즘 2가지를 제안한다. 그리고 대표적인 충돌 방지 알고리즘인 18000-6 Type A, Type B, Type C, query tree 알고리즘과 성능 비교 및 평가를 한다.

• 전기학회논문지
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• 제58권5호
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• pp.1025-1034
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• 2009

In steel making production line, steel slabs are given a unique identification number. This identification number, Slab management number(SMN), gives information about the use of the slab. Identification of SMN has been done by humans for several years, but this is expensive and not accurate and it has been a heavy burden on the workers. Consequently, to improve efficiency, automatic recognition system is desirable. Generally, a recognition system consists of text localization, text extraction, character segmentation, and character recognition. For exact SMN identification, all the stage of the recognition system must be successful. In particular, the text localization is great important stage and difficult to process. However, because of many text-like patterns in a complex background and high fuzziness between the slab and background, directly extracting text region is difficult to process. If the slab region including SMN can be detected precisely, text localization algorithm will be able to be developed on the more simple method and the processing time of the overall recognition system will be reduced. This paper describes about the slab region localization using SIFT(Scale Invariant Feature Transform) features in the image. First, SIFT algorithm is applied the captured background and slab image, then features of two images are matched by Nearest Neighbor(NN) algorithm. However, correct matching rate can be low when two images are matched. Thus, to remove incorrect match between the features of two images, geometric locations of the matched two feature points are used. Finally, search rectangle method is performed in correct matching features, and then the top boundary and side boundaries of the slab region are determined. For this processes, we can reduce search region for extraction of SMN from the slab image. Most cases, to extract text region, search region is heuristically fixed [1][2]. However, the proposed algorithm is more analytic than other algorithms, because the search region is not fixed and the slab region is searched in the whole image. Experimental results show that the proposed algorithm has a good performance.

• 한국지진공학회논문집
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• 제25권3호
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• pp.145-152
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• 2021

KAERI has planned to carry out a series of dynamic tests using a shaking table and time-history analyses for a channel-type concrete shear wall to investigate its seismic performance because of the recently frequent occurrence of earthquakes in the south-eastern parts of Korea. The overall size of a test specimen is b×l×h =2500 mm×3500 mm×4500 mm, and it consists of three stories having slabs and walls with thicknesses of 140 mm and 150 mm, respectively. The system identification, FE model updating, and time-history analysis results for a test shear wall are presented herein. By applying the advanced system identification, so-called pLSCF, the improved modal parameters are extracted in the lower modes. Using three FE in-house packages, such as FEMtools, Ruaumoko, and VecTor4, the eigenanalyses are made for an initial FE model, resulting in consistency in eigenvalues. However, they exhibit relatively stiffer behavior, as much as 30 to 50% compared with those extracted from the test in the 1st and 2nd modes. The FE model updating is carried out to consider the 6-dofs spring stiffnesses at the wall base as major parameters by adopting a Bayesian type automatic updating algorithm to minimize the residuals in modal parameters. The updating results indicate that the highest sensitivity is apparent in the vertical translational springs at few locations ranging from 300 to 500% in variation. However, their changes seem to have no physical meaning because of the numerical values. Finally, using the updated FE model, the time-history responses are predicted by Ruaumoko at each floor where accelerometers are located. The accelerograms between test and analysis show an acceptable match in terms of maximum and minimum values. However, the magnitudes and patterns of floor response spectra seem somewhat different because of the slightly different input accelerograms and damping ratios involved.

• 한국해양공학회지
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• 제24권2호
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• pp.10-17
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• 2010

Conventionally, because it is difficult to control a ship in shallow water and because attempting to do so creates unwanted environmental effects, maneuvering ships in the harbor area for berthing is usually done with the assistance of tugboats. In this paper, we propose a new method for berthing ships automatically by using bow and stern thrusters. Specifically, a steering motion model of a ship is considered, and parameters in the equation are evaluated by the system identification technique. An optimal controller based on observations was designed from the linearization of the non-linear ship motion in the horizontal plane. It is used to reduce the uncertainty about the ship's dynamics and reduce measurement requirements. The performance of the controller was also analyzed for its robustness relative to avoiding disturbing the environment due to winds, currents, and wave-drift forces. Experiments were conducted to estimate the potential for identifying result and the design of the controller. Specifically, in this paper, the system modeling and tracking control approach are discussed based on a two-degree-of-freedom (2DOF) servo-system design.