• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.2
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• pp.320-326
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• 2008

In this paper, we propose a new algorithm emulating the DNA characteristics for noise-tolerant pattern matching problem on digital system. The digital pattern matching becomes core technology in various fields, such as, robot vision, remote sensing, character recognition, and medical diagnosis in particular. As the properties of natural DNA strands allow hybridization with a certain portion of incompatible base pairs, DNA-inspired data structure and computation technique can be adopted to bio-signal pattern classification problems which often contain imprecise data patterns. The key feature of noise-tolerance of DNA computing comes from control of reaction temperature. Our hardware system mimics such property to diagnose cardiovascular disease and results superior classification performance over existing supervised learning pattern matching algorithms. The hardware design employing parallel architecture is also very efficient in time and area.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.553-571
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• 2019

Geometric variation including welding distortion accumulates as many parts are joined together, ultimately affecting the final product. This variation is then subjected to correction, which requires considerable effort, time, and cost. This variation can be categorized as in-plane/out-of-plane variation. To date, studies on variation simulation have largely focused on the out-of-plane variation, however the variation generated in the in-plane direction requires more time and efforts to correct afterwards. This research aims to construct a variation simulation model considering both the in-plane and out-of-plane variations. A geometric analysis was performed to derive an equation that reflects the coupling effect of the out-of-plane variation on the in-plane variation. The proposed model is validated with case study analysis and the results shows that good fidelity in predicting and diagnosing the in-plane variation during the block assembly process considering welding distortion.

• Journal of Biomedical Engineering Research
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• v.42 no.5
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• pp.201-210
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• 2021

In Korean medicine, tongue diagnosis is one of the important diagnostic methods for diagnosing abnormalities in the body. Representative features that are used in the tongue diagnosis include color, shape, texture, cracks, and tooth marks. When diagnosing a patient through these features, the diagnosis criteria may be different for each oriental medical doctor, and even the same person may have different diagnosis results depending on time and work environment. In order to overcome this problem, recent studies to automate and standardize tongue diagnosis using machine learning are continuing and the basic process of such a machine learning-based tongue diagnosis system is tongue segmentation. In this paper, image data is augmented based on the main tongue features, and backbones of various famous deep learning architecture models are used for automatic tongue segmentation. The experimental results show that the proposed augmentation technique improves the accuracy of tongue segmentation, and that automatic tongue segmentation can be performed with a high accuracy of 99.12%.

• Journal of Mechanical Science and Technology
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• v.19 no.8
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• pp.1597-1610
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• 2005

The conventional computerized numerical controller (CNC) of machine tools has been increasingly replaced by a PC-based open architecture CNC (OAC) that is independent of a CNC vendor. The OAC and machine tools with an OAC have led to a convenient environment in which user-defined applications can be efficiently implemented within a CNC. This paper proposes a method of diagnosing the cause of operational faults. The method is based on the status of a programmable logic controller in machine tools with an OAC. An operational fault is defined as a disability that occurs during the normal operation of machine tools. Operational faults constitute more than 70 percent of all faults and are also unpredictable because most of them occur without any warning. To quickly and correctly diagnose the cause of an operational fault, two diagnostic models are proposed: the switching function and the step switching function. The cause of the fault is logically diagnosed through a fault diagnosis system using diagnostic models. A suitable interface environment between a CNC and developed application modules is constructed to implement the diagnostic functions in the CNC domain. The results of the diagnosis were displayed on a CNC monitor for machine operators and transmitted to a remote site through a Web browser. The proposed diagnostic method and its results were useful to unskilled machine operators and reduced the machine downtime.

• Journal of The Korea Institute of Healthcare Architecture
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• v.21 no.4
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• pp.49-58
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• 2015

Purpose: Musculoskeletal disorder is one of diseases with high medical demand over-65 populations. Considering complex, chronic property of diseases, it is important for patients to provide specialized medical service. The musculoskeletal center is one of the most essential facility type in order to give adequate care to the patient suffering from musculoskeletal diseases. Methods: Statistical analysis relating to the component ratio of patients for the demand for medical care. Literature analysis for characteristic of the musculoskeletal diseases. The Status Survey of health care facilities operating in the musculoskeletal center. Results: It is necessary for the musculoskeletal center to be composed of four major areas such as consultation, examination, diagnosis, intervention for continuity of care. For continuum of care, it is essential to build medical environment integrated with each level of care such as consultant, examination, diagnosis procedure. Implications: This study is a basic research for design of musculoskeletal center, and need to be followed by further study using various perspectives and methods.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2006.04a
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• pp.172-175
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• 2006

Recently, fire resistance of high performance concrete for explosive spatting was issued as high performance concrete was vulnerable to the explosive spatting in initial fire. Therefore, This study is willing to propose fundamental data for quick and accurate diagnosis of deteriorated concrete structure by fire damage with making variable concrete test specimen, exposing high temperature environment, observing the explosive spatting and examining engineering property.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.92-97
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• 2001

The major faults of CNC machine tool is operational error which is charge over 70%. This paper describes model of remote service and fault diagnosis for CNC machine tool with open architecture controller. For intelligent fault diagnosis, new model is proposed. In this paper, the three major operational faults, emergency stop error, cycle start disable and machine ready disable, are defined. Two diagnostic models based on the ladder diagram, switching function model, step switching function model, are proposed. For internet based remote service, suitable environment is proposed and implemented with web server and client.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.613-618
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• 2018

We are developing a shared remote control mobile robot for aerial work in nuclear power plants (NPPs); a robot consists of a mobile platform, a telescopic mast, and a dual-arm slave with a working tool. It is used at a high location operating the manual operation mechanism of a fuel changer of a heavy water NPP. The robot system can cut/weld a pipe remotely in the case of an emergency or during the dismantling of the NPP. Owing to the challenging control mission considering limited human operator cognitive capability, some remote tasks require a shared control scheme, which demands systematic software design and integration. Therefore, we designed the architecture of the software systematically.

• Journal of Mechanical Science and Technology
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• v.19 no.8
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• pp.1670-1681
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• 2005

In-situ diagnosis of chiller performance is an essential step for energy saving business. The main purpose of the in-situ diagnosis is to predict the performance of a target chiller. Many models based on thermodynamics have been proposed for the purpose. However, they have to be modified from chiller to chiller and require profound knowledge of thermodynamics and heat transfer. This study focuses on developing an easy-to-use diagnostic technique that is based on adaptive neuro-fuzzy inference system (ANFIS). The effect of sample data distribution on training the ANFIS is investigated. It is found that the data sampling over 10 days during summer results in a reliable ANFIS whose performance prediction error is within measurement errors. The reliable ANFIS makes it possible to prepare an energy audit and suggest an energy saving plan based on the diagnosed chilled water supply system.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.813-823
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• 2013

On-line monitoring system is important for high voltage vacuum circuit breakers (HVCBs) in operation condition assessment and fault diagnosis. A distributed multilayer system with client/server architecture is developed on rated voltage 10kV HVCB with spring operating mechanism. It can collect data when HVCB switches, calculate the necessary parameters, show the operation conditions and provide abundant information for fault diagnosis. Ensemble empirical mode decomposition (EEMD) is used to detect the singular point which is regarded as the contact moment. This method has been applied to on-line monitoring system successfully and its satisfactory effect has been proved through experiments. SVM and FCM are both effective methods for fault diagnosis. A combinative algorithm is designed to judge the faults of HVCB's operating mechanism. The system's precision and stability are confirmed by field tests.