• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.1
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• pp.120-127
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• 1991

The purpose of this study is to develop a fault detection and diagnosis scheme that can monitor process fault and instrument fault of a steam generator. The suggested scheme consists of a Kalman filter and two bias estimators. Method of detecting process and instrument fault in a steam generator uses the mean test on the residual sequence of Kalman filter, designed for the unfailed system, to make a fault decision. Once a fault is detected, two bias estimators are driven to estimate the fault and to discriminate process fault and instrument fault. In case of process fault, the fault diagnosis of outlet temperature, feed-water heater and main steam control value is considered. In instrument fault, the fault diagnosis of steam genrator's three instruments is considered. Computer simulation tests show that on-line prompt fault detection and diagnosis can be performed very successfully.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1197-1207
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• 2016

The purpose of this study was to develop an evidence-based Nursing Process System on Nursing Diagnosis, Nursing Outcomes, and Nursing Interventions Classification targeting nurse students. We use standard classification-focused research data on the basis of Nursing Diagnosis Classification established by NANDA (North American Nursing Diagnosis Association), NOC (Nursing Outcomes Classification) and NIC (Nursing Interventions Classification) mainly developed by Iowa Sate University. The existing research methods are difficult to be applied the consistent nursing process, since such methods need to repeatedly enter the same nursing process without systematic guidelines. But, this study was coded data of standardized nursing process in accordance with the 10 clinical condition in order to implement the nursing process macro, and developed a system that reflects the needs of nursing educators. Therefore, nurse students can improve clinical decision-making ability, and naturally learn the nursing process through a system developed.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1428-1431
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• 1997

This paper presents an efficient fault diagnosis methodology for lare chemical processes. The methodology is based on a two-tier strategy, When a falt occurs in a process, a top tier identifies the sector (process part or unit) that may contain the fault(s). Afterwards, a bottom tier or lower level evaluates the suspicious sector. The process modeling methodology based on functionality-behavior relations of process units, is proposed and utilized in the top-tier. This methodology models a target process as sequences of functions and variables and their relations. In the bottom tier, each sector has a dedicated diagostic module, which is tailored to the available information or models of the sector. For the sectors selected in the top-tier diagnosis, each diagnostic module is executed to identify the actual faults within the sector. Teh utility of the methodology is illustrated in the diagnosis of the CSTR with heat exchanger.

• Journal of the Korean Society of Safety
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• v.34 no.4
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• pp.59-67
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• 2019

Since it is really hard to construct process models based on prior process knowledges, various statistical approaches have been employed to build fault diagnosis models. However, the crucial drawback of these approaches is that the solutions may vary according to the fault magnitude, even if the same fault occurs. In this study, the parameter monitoring approach is suggested. When a fault occurs in a chemical process, this leads to trigger the change of a process model and the monitoring parameters of process models is able to provide the efficient fault diagnosis model. A few important variables are selected and their predictive models are constructed by partial least square (PLS) method. The Euclidean norms of parameters of PLS models are estimated and a fault diagnosis can be performed as comparing with parameters of PLS models based on normal operational conditions. To improve the monitoring performance, cumulative summation (CUSUM) control chart is employed and the changes of model parameters are recorded to identify the type of an unknown fault. To verify the efficacy of the proposed model, Tennessee Eastman (TE) process is tested and this model can be easily applied to other complex processes.

• Journal of Physiology & Pathology in Korean Medicine
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• v.30 no.3
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• pp.190-200
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• 2016

The aim of this study was to suggest the standard process in developing Questionnaire of Pattern Identification (QPI). The process in developing QPI was researched from validated and developed questionnaire and the standard process in developing QPI was suggested through review of the experts in research, statistics and clinics. Check list was also provided. The number of QPI reviewed in this research was 17(4 in disease in Korea Medicine, 5 in Pathological symptoms, 6 in Sasang constitutional Diagnosis, and 2 in etc), The standard process in developing QPI consisted of 11 phage and 33 check lists. 1) Composition of Research Member(3check lists), 2)Set up of the Aim(5), 3) Review for advanced research(3), 4) Finding an Important Index(3), 5) Review of item selection(4), 6) Developing the questions using items(5), 7) Developing Draft of Questionnaire(2), 8) 1^st Survey of Reliability and Validity(2), 9) Revision and Correction of Item(1), 10) 2^st Survey of Reliability and Validity(2), 11) Completion and Application(3). This study suggests the standard process in developing QPI for the first time in Korea. This following step may help A new QPI development.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.135-146
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• 1997

This paper describes fault diagnosis method in complex system with hierachical structure similar to human body structure. Complex system is divided into unit, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. Fault diagnosis system can forecast faults in a system and decide from current machine state signal information. Comparing with other diagnosis system for single fault, the developed system deals with multiple fault diagnosis comprising Hierarchical Neural Network(HNN). HNN consists of four level neural network, first level for item fault symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. UNIX IPC(Inter Process Communication) is used for implementing HNN wiht multitasking and message transfer between processes in SUN workstation with X-Windows(Motif). We tested HNN at four units, seven items per unit, seven components per item in a complex system. Each one neural newtork operate as a separate process in HNN. The message queue take charge of information exdhange and cooperation between each neural network.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.1
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• pp.171-184
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• 2015

The purpose of this study is to develop the self-diagnosis methodology based on process for improving the effectiveness in public institutions service and to suggest it. For this goal, we would like to select the management methodology which can be easily handled from the viewpoint of working personnel in the public institutions and make it as a process. First, the strategy for the public institutions and the strategic task for practicing it are acquired using BSC (Balanced Score Card) which is now under the active research. At this time, the relative degree of significance is derived using the AHP (Analytic Hierarchy Process) which is conducted for the professionals and management to get the degree of importance in the strategic tasks. The acquired relative degree of significance and the figures related to the performance of each strategic task derived from the subsequent questionnaire are used to get the final highly efficient strategic task through IPA (Importance Performance Analysis). In this study, this process based self diagnosis methodology will be explained in detail using the case of Project A in order to verify the effectiveness of the management science technique on the self diagnosis of the public institutions.

• Women's Health Nursing
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• v.19 no.1
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• pp.1-12
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• 2013

Purpose: This study was performed to propose an ontology methodology based on standardized nursing process as framework in obstetric and gynecologic nursing practice. Methods: The instrument used in this study was based on the nursing diagnosis classification established by North American Nursing Diagnosis Association (NANDA) (2009-2011), fifth edition of the Nursing Interventions Classification (NIC) (2008), forth edition of the Nursing Outcomes Classification (NOC) (2008) developed by Iowa State University and systematized nomenclature of medicine clinical terms (SNOMED CT). The nursing records data were collected from electronic medical records of one hospital from August to October 2010. Results: One hundred and forty-one nursing diagnosis statements used in obstetric and gynecologic nursing unit were linked standardized nursing classifications and constructed nursing diagnosis ontology including interoperability. Conclusion: Not only will this result be helpful to complete nurse's lack of knowledge and experience, it will also help to determine nursing diagnosis logically by using standardized nursing process. It will be utilized as the method to construct ontology including interoperability in other nursing units. It will be presented nursing interventions according to nursing diagnosis and thus will be easier to establish nursing planning. This can provide immediate feedback of the nursing process application.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.11
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• pp.443-450
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• 2018

Crohn's disease, which is recently increasing in Korea, may be seen throughout the gastrointestinal tract and cause various symptoms. In particular, Crohn's disease is especially difficult to diagnose with several symptoms similar to other ulcerative colonic diseases. Thus, some studies are underway to distinguish two or more similar diseases. However, the previous studies have not described the procedural diagnosis process of it, which may lead to over-examination in the process. Therefore, we propose a diagnosis process of Crohn's disease based on the analysis of redundancy, sequential linkage and decision point in the diagnosis of Crohn's disease, so that it enables to identify ulcerative colonic diseases with symptoms similar to Crohn's disease. Finally, we can distinguish the colon diseases that have symptoms similar to Crohn's disease and help diagnose Crohn's disease effectively by defining the proposed process-oriented association as an ontology. Applying the proposed ontology to 5 cases showed that more accurate diagnosis was possible and in one case it could be diagnosed even with fewer tests.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.538-543
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• 2016

For a good product quality and plant safety, it is necessary to implement the on-line monitoring and diagnosis schemes of industrial processes. Combined with monitoring systems, reliable diagnosis schemes seek to find assignable causes of the process variables responsible for faults or special events in processes. This study deals with the real-time diagnosis of complicated industrial processes from the intelligent use of multivariate statistical techniques. The presented diagnosis scheme consists of a classification-based diagnosis using nonlinear representation and filtering of process data. A case study based on the simulation data was conducted, and the diagnosis results were obtained using different diagnosis schemes. In addition, the choice of future estimation methods was evaluated. The results showed that the performance of the presented scheme outperformed the other schemes.