• 대한안전경영과학회지
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• 제12권2호
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• pp.65-73
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• 2010

In an automated industry PLC plays a central role to control the manufacturing system. Therefore, fault free operation of PLC controlled manufacturing system is essential in order to maximize a firm's productivity. On the contrary, distributed nature of manufacturing system and growing complexity of the PLC programs presented a challenging task of designing a rapid fault finding system for an uninterrupted process operation. Hence, designing an intelligent monitoring, and diagnosis system is needed for smooth functioning of the operation process. In this paper, we propose a method to continuously acquire a stream of PLC signal data from the normal operational PLC-based manufacturing system and to generate diagnosis model from the observed PLC signal data. Consequently, the generated diagnosis model is used for distinguish the possible abnormalities of manufacturing system. To verify the proposed method, we provided a suitable case study of an assembly line.

• 간호행정학회지
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• 제9권4호
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• pp.651-661
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• 2003

Purpose: This is the descriptive research project of which purpose is to acquire the practice, research, and educational data by establishing the database after confirming, classifying, and relating the nursing diagnosis, nursing intervention, and nursing outcome of Breast cancer patients by using the Yoo Hyung-sook's(2001) related 3N database model as the tool. Method : The Nursing Data occurring on Breast cancer patients nursing process was mapped to nursing diagnosis of NANDA, nursing interventions of NIC, nursing outcomes of NOC the 3N database linkage database which is related with the nursing process that was developed by using Yoo Hyung-sook's(2001). Result : 1. The nursing diagnosis were totally 505, and 26 articles of the nursing diagnosis were applied among 149 nursing diagnosis classification systems. 2. As for the nursing intervention, 250 articles(5l.4%) of nursing intervention were applied among 486 nursing intervention classification systems. 3. Regarding the nursing outcome, 28 articles(1l.2%l of the nursing outcome were applied among 250 nursing outcome classification systems. Conclusion: The result of this research in which the relating among the nursing diagnosis, nursing intervention, and nursing outcome of Breast cancer patients by using 3N nursing database was established is thought to be applied in the research and practice as well as to be utilized in the lecture or practice of the nursing process.

• 인터넷정보학회논문지
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• 제18권5호
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• pp.113-121
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• 2017

Company A's core competency is IT internet security services. The Web diagnosis team analyzes the vulnerability of customer's internet web servers and provides remedy reports. Traditionally, Company A management has utilized a simple table format report for resource planning. But these reports do not notify the timing of human resource commitment. So, upper management asked its team leader to organize a task team and design a visual dashboard for decision making with the help of outside professional. The Task team selected the web security diagnosis practice process as a pilot and designed a dashboard for performance evaluation. A structural design process was implemented during the heuristic working process. Some KPI (key performance indicators) for checking the productivity of internet web security vulnerability reporting are recommended with the calculation logics. This paper will contribute for security service management to plan and address KPI design policy, target process selection, and KPI calculation logics with actual sample data.

• 유공압시스템학회논문집
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• 제6권2호
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• pp.22-30
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• 2009

An in-process method of diagnosing the spool wear of hydraulic servovalves was explored. The diagnostic method discussed in this paper is for force-control hydraulic servo systems. The key principle used is that pressure sensitivity of a servovalve drops as the valve spool wears out so that it is possible to determine the spool condition by monitoring pressure sensitivity. A diagnostic algorithm was developed and evaluated through numerical simulation and experiments. Two major steps of diagnosis are the evaluation of null bias of the servovalve and the approximation of pressure sensitivity, both of which could be successfully done during normal operation of a servo system. The difference between a new servovalve and a worn valve could be clearly detected in-process, and the diagnostic test was found to be repeatable.

• 상하수도학회지
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• 제27권1호
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• pp.139-146
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• 2013

A process diagnosis method for membrane water treatment plant was developed using a constant flux membrane fouling model. This diagnosis method can be applied to a real-field membrane-based water treatment plant as an early alarming system for membrane fouling. The constant flux membrane fouling model was based on the simplest equation form to describe change in trans-membrane pressure (TMP) during the filtration cycle from a literature. The model was verified using a pilot-scale microfiltraton (MF) plant with two commercial MF membrane modules (72 m2 of membrane area). The predicted TMP data were produced using the model, where the modeling parameters were obtained by the least square method using the early plant data and modeling equations. The diagnosis was carried out by comparing the predicted TMP data (as baseline) and real plant data. As a result of the case study, the diagnsis method worked pretty well to predict the early points where fouling started to occur.

• 한국안전학회지
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• 제31권4호
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• pp.35-41
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• 2016

In order to guarantee the process safety and prevent accidents, the deviations from normal operating conditions should be monitored and their root causes have to be identified as soon as possible. The statistical theories-based method among various fault diagnosis methods has been gaining popularity, due to simplicity and quickness. However, according to fault magnitudes, the scalar value generated by statistical methods can be changed and this point can lead to produce wrong information. To solve this difficulty, this work employs PCA (Principal Component Analysis) based method with qualitative information. In the case study of our previous study, the number of assumed faults is much smaller than that of process variables. In the case study of this study, the number of predefined faults is 19, while that of process variables is 6. It means that a fault diagnosis becomes more difficult and it is really hard to isolate a single fault with a small number of variables. The PCA model is constructed under normal operation data in order to get a loading vector and the data set of assumed faulty conditions is applied with PCA model. The significant changes on PC (Principal Components) axes are monitored with CUSUM (Cumulative Sum Control Chart) and recorded to make the information, which can be used to identify the types of fault.

• 임상간호연구
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• 제14권3호
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• pp.141-151
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• 2008

Purpose: This study aimed at applying a standardized nursing process to adult surgery patients of post anesthetic care unit, and examining the validity of linkages in the measuring index of nursing outcome by which nursing outcome was applied. Method: The subjects were 184 surgery adult patients admitted at the post anesthetic care unit of Y university hospital. This study was used the measured tool developed by Choi et al.(2004) and by Lee (2004) who had already verified a validity based on Johnson and Bulechek's study(2001). Results: The nursing diagnosis of an acute pain, an urinary retention, a nausea, a decreased cardiac output, an ineffective airway clearance and an ineffective airway clearance were used in taking care for patients. The related factors according to the main nursing diagnosis were as the following: an injurious physical factor in an acute pain, reflex are inhibition in an urinary retention, post surgical anesthesia in a nausea, stroke volume change in a decreased cardiac output, secretory stasis in an ineffective airway clearance, pain in an ineffective breathing pattern. Conclusion: The study results could be facilitated in nursing process application for nurses at post anesthetic care unit. Also this study would provide basic data to develop a computerized program for the improvement of nursing process application.

• 중소기업융합학회논문지
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• 제6권4호
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• pp.79-84
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• 2016

본 논문에서는 스마트 헬스케어 서비스 시스템의 바이오 데이터 분석 과정을 프로세스로 해석하기 위하여, 온톨로지 기반 통계학적 개인 맞춤형 질병예측 기법인 PCADP(Personalized Computer Aided Diagnosis Probability)를 제안하였다. 또한 이러한 개인 맞춤형 질병예측 기법을 바탕으로 스마트 헬스케어 데이터 및 헬스케어 서비스 명세의 의미 있는 표현을 위하여 헬스케어 온톨로지 프레임워크를 시맨틱스형으로 모델링하였다. PCADP 기법은 스마트 헬스케어 환경에서 개인 맞춤형 판별 기법이 갖추어야 할 조건인 실시간 처리, 유연한 구조, 판별과정의 모니터링, 지속적인 개선 등에 부합하는 통계학적 질병예측 기법임을 확인하였다.

• 대한간호학회지
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• 제30권4호
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• pp.1078-1087
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• 2000

The purpose of this study was to develop and to evaluate the Computerized Nursing Diagnosis/ Intervention System for Nutritional and Eliminative Problems for clinical application. Each stage was processed based on the System Development Life Cycle. At the Strategy Planning Stage, valid nursing diagnoses and interventions were chosen. At the System Analysis Stage, a nursing diagnosis and intervention flowchart was drawn up. At the System Design Stage, a system was developed based on the flowchart and named the Nursing Diagnosis/Intervention System. The Nursing Diagnosis/Intervention System consisted of the Patient's Basic Information, Patient's Nursing Process, Nursing Process, and Code Registration. Each element in flowchart was coded and made into a database. The System was used and evaluated. A total of 30 cases were collected. After the application, the nurses evaluated the System using a 5 point Likert scale. Every item was scored at three points or more and 13 out of 17 items were scored at four points or more, thus the Nursing Diagnosis/Intervention System that was developed in this study was regarded as a useful one.

• 대한간호학회지
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• 제26권2호
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• pp.281-289
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• 1996

Neural networks have recently attracted considerable attention in the field of classification and other areas. The purpose of this study was to demonstrate an experiment using back-propagation neural network model applied to nursing diagnosis. The network's structure has three layers ; one input layer for representing signs and symptoms and one output layer for nursing diagnosis as well as one hidden layer. The first prototype of a nursing diagnosis system for patients with stomach cancer was developed with 254 nodes for the input layer and 20 nodes for the output layer of 20 nursing diagnoses, by utilizing learning data set collected from 118 patients with stomach cancer. It showed a hitting ratio of .93 when the model was developed with 20,000 times of learning, 6 nodes of hidden layer, 0.5 of momentum and 0.5 of learning coefficient. The system was primarily designed to be an aid in the clinical reasoning process. It was intended to simplify the use of nursing diagnoses for clinical practitioners. In order to validate the developed model, a set of test data from 20 patients with stomach cancer was applied to the diagnosis system. The data for 17 patients were concurrent with the result produced from the nursing diagnosis system which shows the hitting ratio of 85％. Future research is needed to develop a system with more nursing diagnoses and an evaluation process, and to expand the system to be applicable to other groups of patients.