• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1098-1103
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• 1991

This paper discusses the training simulator designed to improve the skills of operators who handle the SCADA System of KEPCO. The system is composed of the simulation subsystem and database, and implemented on the 386 based P.C, It is linked to existing SCADA system (HARRIS computer and TADCOM) to work realistically for the situation of accidents and corresponding actions.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.204-204
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• 2000

This paper describes the development of training simulator for Hadong fossil Power Plant. The simulator was developed to train operator, test new control Logic and evaluate alternative operating procedure for expert engineer of control system. The most control logics such as Siemens TELEPERM ME and GE Mark V are translated directly from microprocessors. Those HMI are also directly emulated. The simulation was performed by ProTRAX modeling software. The paper discusses the configuration of simulator and the simulation results of 30%, 50%, 75% and 100% normal rate load test.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.522-524
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• 1993

This paper discusses the training simulator designed to improve the skills of operators who handle the SCADA System of KEPCO (Korea Electric Power Co. ). The system is composed of the simulation subsystem and database, and implemented on the 380-based P. C. It is 1 inked to existing SCADA system (HARRIS and TADCOM) to work realistically for the situation of accidents and corresponding actions.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.11a
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• pp.165-171
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• 2003

We have developed Virtual Reality Simulator MMI for operator training. MMI communicates with server model and client PC through OPCServer. We used Dataplant for Soft Panel and Simdiagram which shows more sophisticated and reality colors. We used vector method for MCR images instead of conventional bit-map method to protect images during zoom in and zoom out. VBScript and Components were used for real movements and images of instruments. VRMCR panel is consisted of 12 groups and designed to accommodate user's convenience.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.496-499
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• 1999

This paper describes a medular neural network(MNN) for a vision system which tracks a given object using a sequence of images from a camera unit. The MNN is used to precisely recognize the given robot endeffector and to minize the processing time. Since the robot endeffector can be viewed in many different shapes in 3-D space, a MNN structure, which contains a set of feedforwared neural networks, co be more attractive in recognizing the given object. Each single neural network learns the endeffector with a cluster of training patterns. The training patterns for a neural network share the similar charateristics so that they can be easily trained. The trained MNN is less sensitive to noise and it shows the better performance in recognizing the endeffector. The recognition rate of MNN is enhanced by 14% over the single neural network. A vision system with the MNN can precisely recognize the endeffector and place it at the center of a display for a remote operator.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.571-573
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• 2015

본 연구에서는 플랜트 운영 중 발생할 수 있는 다양한 인적에러를 최소화하고, 예측하기 힘든 사고 발생 시 운전자의 대응과 사고피해 확산을 방지할 수 있는 플랜트 안전훈련 시스템의 설계 방안과 이를 구현하는 플랫폼에 관한 연구를 소개한다. 제안하는 플랫폼은 기존에 활용 중인 플랜트 운영자 훈련 시스템(OTS : Operator Training System)과 비교하여, 관제실 운영자와 현장 조업자가 동시에 상호 유기적인 훈련을 가능케 하는 안전훈련 시스템 개발을 목표로 하며, 추후 서브 시스템의 구현과 통합과정을 통해 본 훈련 시스템 플랫폼의 실용성을 검증할 계획이다.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.124-131
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• 2024

Breast cancer classification using ultrasound, while widely employed, faces challenges due to its relatively low predictive value arising from significant overlap in characteristics between benign and malignant lesions, as well as operator-dependency. To alleviate these challenges and reduce dependency on radiologist interpretation, the implementation of automatic breast cancer classification in ultrasound image can be helpful. To deal with this problem, we propose a semi-supervised deep learning framework for breast cancer classification. In the proposed method, we could achieve reasonable performance utilizing less than 50% of the training data for supervised learning in comparison to when we utilized a 100% labeled dataset for training. Though it requires more modification, this methodology may be able to alleviate the time-consuming annotation burden on radiologists by reducing the number of annotation, contributing to a more efficient and effective breast cancer detection process in ultrasound images.

• Clinical Endoscopy
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• v.56 no.3
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• pp.290-297
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• 2023

Endoscopic retrograde cholangiopancreatography (ERCP) is an invasive endoscopic technique that has many diagnostic and therapeutic implications. It is a procedure with small but significant life-threatening complications. To ensure the best possible care, minimize complications, and improve the quality of health care, a constant review of the performance of the operator using ideal benchmark standards is needed. Hence, quality indicators are necessary. The American and European Societies of Gastrointestinal Endoscopy have provided guidelines on quality measures for ERCP, which describe the skills to be developed and training to be implemented in performing quality ERCP. These guidelines have divided the indicators into pre-procedure, intraprocedural, and post-procedure measures. The focus of this article was to review the quality indicators of ERCP.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.317-324
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• 2010

In recent years, many automatic classification approaches have been employed. An automatic classification method can be effective, time-saving and can produce objective results due to the exclusion of operator intervention. This paper proposes a classification method based on automated training for high resolution multispectral images using ancillary data. Generally, it is problematic to automatically classify high resolution images using ancillary data, because of the scale difference between the high resolution image and the ancillary data. In order to overcome this problem, the proposed method utilizes the classification results of a Landsat image as a medium for automatic classification. For the classification of a Landsat image, a maximum likelihood classification is applied to the image, and the attributes of ancillary data are entered as the training data. In the case of a high resolution image, a K-means clustering algorithm, an unsupervised classification, was conducted and the result was compared to the classification results of the Landsat image. Subsequently, the training data of the high resolution image was automatically extracted using regular rules based on a RELATIONAL matrix that shows the relation between the two results. Finally, a high resolution image was classified and updated using the extracted training data. The proposed method was applied to QuickBird and SPOT-5 images of non-accessible areas. The result showed good performance in accuracy assessments. Therefore, we expect that the method can be effectively used to automatically construct thematic maps for non-accessible areas and update areas that do not have any attributes in geographic information system.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.179-182
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• 1997

In a training simulator for power plant, operator's action in the MCR(Main Control Room) are given to plant process and computer system model as an inputs, and the same response as in real power plant is provided in real time. Inter-process communication and synchronization are especially important among various inputs. In the plant simulator, to simulate the digital control system such as FOXBORO SPEC-200 Micro control system, modification and adaptation of control card(CCC) and its continuous display station(CDS) is necessary. This paper describes the modeling and simulation of FOXBORO SPEC-200 Micro control system applied to Younggwang nuclear power plant unit #3 & 4, and its integration process to the full-scope replica type training simulator. In a simulator, display station like CDS of FOXBORO SPEC-200 Micro control system is classified as ITI(Intelligent Type Instrument), which has a micro processor inside to process information and the corresponding alphanumeric display, and the stimulation of ITI limits the important functions in a training simulator such as backtrack, replay, freeze and IC reset. Therefore, to achieve the better performance of the simulator, modification of CDS and special firmware is developed to simulate the FOXBORO SPEC-200 Micro control system. Each control function inside control card is modeled and simulated in generic approach to accept the plant data and control parameter conveniently, and debugging algorithms are applied for massive coding developed in short period.