• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.457-462
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• 1995

This paper describes diagnosis strategy of the Flexible Multiple Fault Diagnosis Module for forecasting faults in system and deciding current machine state form sensor information. Most studydeal with diagnosis control stategy about single fault in a system, this studies deal with multiple fault diagnosis. This strategy is consist of diagnosis control module such as backward tracking expert system shell, various neural network, numerical model to predict machine state and communication module for information exchange and cooperate between each model. This models are used to describe structure, function and behavior of subsystem, complex component and total system. Hierarchical structure is very efficient to represent structural, functional and behavioral knowledge. FT(Fault Tree). ST(Symptom Tree), FCD(Fault Consequence Diagrapy), SGM(State Graph Model) and FFM(Functional Flow Model) are used to represent hierachical structure. In this study, IA(Intelligent Agent) concept is introduced to match FT component and event symbol in diagnosed system and to transfer message between each event process. Proposed diagnosis control module is made of IPC(Inter Process Communication) method under UNIX operating system.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.2
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• pp.183-192
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• 2022

Function and performance degradation in tunnel structure can cause road's function loss, proactive maintenance is needed to prevent the initial damage from progressing to intensified damage. Inspection and diagnosis are implemented in accordance with regulations, but it does not fully reflect maintenance processes such as inspection and diagnosis, planning rehabilitation and carrying out. It was carried out for 5,540 cases inspection and diagnosis result in 1,728 tunnels was analyzed to suggest rational maintenance plan in this study.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.670-675
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• 1994

Yhis paper describes a fault diagnosis simulation of the Real-Time Multiple Fault Dignosis System (RTMFDS) for forcasting faults in a system and deciding current machine state from signal information. Comparing with other diagnosis system for single fault,the system developed deals with multiple fault diagnosis,comprising two main parts. One is a remotesignal generating and transimission terminal and the other is a host system for fault diagnosis. Signal generator generate the random fault signal and the image information, and send this information to host. Host consists of various modules and agents such as Signal Processing Module(SPM) for sinal preprocessing, Performence Monotoring Module(PMM) for subsystem performance monitoring, Trigger Module(TM) for multi-triggering subsystem fault diagnosis, Subsystem Fault Diagnosis Agent(SFDA) for receiving trigger signal, formulating subsystem fault D\ulcornerB and initiating diagnosis, Fault Diagnosis Module(FDM) for simulating component fault with Hierarchical Artificial Neural Network (HANN), numerical models and Hofield network,Result Agent(RA) for receiving simulation result and sending to Treatment solver and Graphic Agent(GA). Each agent represents a separate process in UNIX operating system, information exchange and cooperation between agents was doen by IPC(Inter Process Communication : message queue, semaphore, signal, pipe). Numerical models are used to deseribe structure, function and behavior of total system, subsystems and their components. Hierarchical data structure for diagnosing the fault system is implemented by HANN. Signal generation and transmittion was performed on PC. As a host, SUN workstation with X-Windows(Motif)is used for graphic representation.

• Convergence Security Journal
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• v.14 no.7
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• pp.45-51
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• 2014

The most important point in the QoS management system to ensure the quality of the IoT system design goal is quality measurement system and the quality evaluation system. This research study is a matrix model for the IoT based on key quality measures by diagnosis system structure and function. Developing for the quality metrics measured Internet of Things environment will provide the foundation for the Internet of Things quality measurement/analysis. IoT matrix system for quality evaluation is a method to describe the functional requirements and the quality requirements in a single unified table for quality estimation performed. Comprehensive functional requirements and quality requirements by assessing the association can improve the reliability and usability evaluation. When applying the proposed method IoT quality can be improved while reducing the QoS signaling, the processing, the basis for more efficient quality assurances as a whole.

• 모자간호학회지
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• v.4 no.1
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• pp.3-11
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• 1994

Presently there is an increasing demand for home health care services due to changes in the demographic structure as a result of an increasing elderly population, socio-economic improvements, and changes in the family structure, as well as the growing number of people with degenerative diseases. In addition to these reasons, rising medical costs and there a shortage of patient beds space in the hospital, particularly since introduction of national medical insurance. There has been an increasing demand for health care health care services. This study was done to identify the basic data for home health care management. It focused on developing client selection criteria, assessment tools, and recording methods. This was accomplished by the researchers visiting the patients in their homes. The research process included preparation investigation, tool development, training of the project researcher, and visiting the clients in their homes. The research tools are as follows : 1. Record development : a) The selection criteria tool for home health care of postpartum women was a structured tool and consisted of four parts. b) The structured assessment tool consisted of a general items, obstetric history, past medical history, methods of feeding, medications taken before admission, laboratory test results, discharge instructions, discharge medications, family tree, economic status, environmental status, a map, health assessment of postpartum women and their newborns. c) The visit note I consisted of the frequency of visits. Visit note II consisted of the date ; nursing problems ; nursing process including the initial assessment ; nursing goal ; visit plan ; postpartum women and their neonate health status, diagnosis, goal, implementation, evaluation, summary, next plan, for visit revision. d) Problem note consisted of the date, problem numbers, nursing diagnosis, problem appearance date problem resolution date. The research results are as follows : 1. Nursing problems : The nursing problems of the postpartum women and their neonates were evaluated by the number of nursing diagnoses and the change in the pattern of nursing diagnosis related to the number of visits. a) Nursing diagnosis The nursing diagnosis was classified according to physical function, psychosocial function, family system maintained function. b) The changes of nursing diagnosis related to the number of visits. As the type of nursing diagnosis changed related to the number of visits the number of nursing diagnoses decreased. 2. Contents of home health care : The content was categorized according to assessment, direct care, counseling, education, family care, reporting to with the attending doctor. The recommendations based on the research results are as follows : 1. Tool development Replication of this study is needed to test the validity of the assessment tools used. 2. Home visit a) Home health care nurses should be licensed and qualified. A referral form from the attending doctor is needed for legal protection of nurses. b) The first home visit need to be within 24 hours of discharge from the hospital to decrease the anxiety of frightened postpartum women. c) When the changes occur in the newborn's status, home health care nurses should consult a pediatrician. Communication within the home healthcare team is essential and needs to consistent and done smoothly. 3. Home health care A Study is required to develop protocols for education of staff and for operation of all aspects of this program.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.54-61
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• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. By using the FCM, authors have proposed FCM-based fault diagnostic algorithm. However, it can offer multiple interpretations for a single fault. In process engineering, as experience accumulated, some form of quantitative process knowledge is available. If this information can be integrated into the FCM-based fault diagnosis, the diagnostic resolution can be further improved. The purpose of this paper is to propose an enhanced FCM-based fault diagnostic scheme. Firstly, the membership function of fuzzy set theory is used to integrate quantitative knowledge into the FCM-based diagnostic scheme. Secondly, modified TAM recall procedure is proposed. Considering that the integration of quantitative knowledge into FCM-based diagnosis requires a great deal of engineering efforts, thirdly, an automated procedure for fusing the quantitative knowledge into FCM-based diagnosis is proposed by utilizing self-learning feature of neural network. Finally, the proposed diagnostic scheme has been tested by simulation on the two-tank system.

• Annals of Clinical Neurophysiology
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• v.10 no.1
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• pp.33-37
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• 2008

Diabetic polyneuropathy (DPN) is the most common form of diabetic neuropathy, and causes a significant morbidity with an impact on the quality of life in the patients with diabetes. Since DPN frequently induces foot deformity and ulceration, which finally leads to foot amputation, the early detection and treatment is very important for the prevention of a permanent structural change. In the early stage of DPN, the diagnostic methods which can evaluate the function or structure of small nerve fibers should be employed because small nerve fibers are first involved in the course of DPN. However, the nerve conduction study cannot reflect the function of the small nerve fibers, and thus, has a definite limitation in the early diagnosis of DPN. For the early detection of DPN, electrodiagnostic data should be interpreted on a clinical context, along with the careful evaluation of the small nerve fiber functions using the tests such as the analysis of intraepidermal nerve fiber density.

• Structural Engineering and Mechanics
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• v.16 no.5
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• pp.581-595
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• 2003

Since the conventional direct approaches are hard to be applied for damage diagnosis of complex large-scale structures, a two-step approach for diagnosing the joint damage of framed structures is presented in this paper by using artificial neural networks. The first step is to judge the damaged areas of a structure, which is divided into several sub-areas, using probabilistic neural networks with natural Frequencies Shift Ratio inputs. The next step is to diagnose the exact damage locations and extents by using the Radial Basis Function (RBF) neural network with the second Element End Strain Mode of the damaged sub-area input. The results of numerical simulation show that the proposed approach could diagnose the joint damage of framed structures induced by earthquake action effectively and has reliable anti-jamming abilities.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.544-544
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• 2000

From ancient times. the diagnosis method of the oriental medicine has been Performed by curing diseases by means of rectifying and adjusting the unbalance in the Physiological function of the five viscera and the six bowels of a human body. Diseases have been diagnosed by the condition of blood circulation that cycles a human body through blood vessels by dint of the vitality of the heart, Based on such a systematic pulse diagnosis method, the article presents parameters that will be beneficial to clinical application on the basis of its analysis of the filtering for eliminating noises from pulse signals inputted from sensor group the digital hardware dealing with signals necessary for recognition algorithm. and the structure of diagnosis algorithm and components of pulse waveform.

• Biotechnology and Bioprocess Engineering:BBE
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• v.7 no.3
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• pp.150-154
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• 2002

Monoclonal antibodies (Mabs) have been used as diagnostic and analytical reagents since hybridoma technology was invented in 1975. In recent years, antibodies have become increasingly accepted as therapeutics for human diseases, particularly for cancer, viral infection and autoimmune disorders. An indication of the emerging significance of antibody-based therapeutics is that over a third of the proteins currently undergoing clinical trials in the United States are antibodies. Until the late 1980's, antibody technology relied primarily on animal immunization and the expression of engineered antibodies. However, the development of methods for the expression of antibody fragments in bacteria and powerful techniques for screening combinatorial libraries, together with the accumulating structure-function data base of antibodies, have opened unlimited opportunities for the engineering of antibodies with tailor-made properties for specific applications. Antibodies of low immunogenicity, suitable for human therapy and in vivo diagnosis, can now be developed with relative ease. Here, antibody structure-function and antibody engineering technologies are described.