• Journal of Advanced Marine Engineering and Technology
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• v.31 no.1
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• pp.95-102
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• 2007

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signals onto frequency domain. The raw signals can not show the significant feature, therefore difference values between the signal of the health conditions and that of the fault conditions are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the fault type. This study describes the results of detecting fault using wavelet analysis.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.1
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• pp.48-55
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• 2003

Hidden Markov Model(HMM) has a doubly embedded stochastic process with an underlying stochastic process that can be observed through another set of stochastic processes. This structure of HMM is useful for modeling vector sequence that doesn't look like a stochastic process but has a hidden stochastic process. So, HMM approach has become popular in various areas in last decade. The increasing popularity of HMM is based on two facts : rich mathematical structure and proven accuracy on critical application. In this paper, we applied continuous HMM (CHMM) approach with AR coefficient to detect and predict the chatter of lathe bite and to diagnose the wear of oil Journal bearing using rotor shaft displacement. Our examples show that CHMM approach is very efficient method for machine health monitoring and prediction.

• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.6
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• pp.262-273
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• 1995

For rotating machinery with high speed and high efficiency, large labor and high expenses are required to conduct machine health monitoring. Therefore, it becomes necessary to develop new diagnosis technique which can detect abnormalities of the rotating machinery effectively. In this paper, it is identified that bispectrum analysis technique can be successfully applied to dectect the abnormalities of the roating machinery through computer simulation, and results of the bispectrum analysis are patterned in griding form. Further, pattern recognition technique using back propagation algorithm, which is one of neural network algorithm, being consisted of patterned input layer and output layer for abnormal status, is applied to detect the abnormalities of simulator which is able to make up various kinds of abnorml conditions(misalignment, unbalance, rubbing etc.) of the rotating machinery.

• Smart Structures and Systems
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• v.30 no.3
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• pp.263-271
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• 2022

In this paper we present an overview of damage diagnosis algorithms that have been developed over the past two decades using vibration signals obtained from structures. Then, the paper focuses primarily on algorithms that can be used following an extreme event such as a large earthquake to identify structural damage for responding in a timely manner. The algorithms presented in the paper use measurements obtained from accelerometers and gyroscope to identify the occurrence of damage and classify the damage. Example algorithms are presented include those based on autoregressive moving average (ARMA), wavelet energies from wavelet transform and rotation models. The algorithms are illustrated through application of data from test structures such as the ASCE Benchmark structure and laboratory tests of scaled bridge columns and steel frames. The paper concludes by identifying needs for research and development in order for such algorithms to become viable in practice.

• Journal of agricultural medicine and community health
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• v.31 no.2
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• pp.157-164
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• 2006

Objectives: Early diagnosis and treatment is the most important strategy to control malaria effectively. Microscopic examination of blood films is a traditional and standard method for diagnosing malaria, which takes a long time and needs expertise, Therefore, the alternative method, rapid diagnostic kit has been used for quick diagnosis in some counties, a highly infectious region by P. vivax. The purpose of this study was to evaluate the utility of malaria rapid diagnostic kit in Ganghwa county. Methods: The utility was evaluated by mean diagnosis time and sensitivity and specificity. For monitoring mean diagnosis time, 942 cases which were diagnosed for P. vivax were collected between 1998 and 2005, And for calculating sensitivity and specificity, 434 whole bloods in EDTA which were presented for P. vivax by microscopy and rapid diagnostic kit were collected between 2004 and 2005. Results: After malaria rapid diagnostic kit was used in 2003, mean diagnosis time has decreased to 3.36-3.14 day. The sensitivity and specificity of the rapid diagnostic kit was 98.2% and 98,5% and comparable to that of microscopic examination. Conclusions: The malaria rapid diagnostic kit is useful tool in a highly infectious region like Ganghwa county.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.839-845
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• 2003

This paper introduces multichannel blind source separation (BSS) and multichannel blind deconvolution (MBD) based on higher order statistics of signals from convolutive mixtures. In particular, we are concerned with the case that the number of inputs is the same as the number of outputs. Simulations for two input two output cases are carried out and their performances are assessed. One of the major applications of those sequential algorithms (BSS and MBD) is demonstrated through the fault signal detection from only a single measurement of rotating machine, which offers a certain degree of practicability in the engineering field such as machine health monitoring or condition monitoring.

• Proceedings of the KSR Conference
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• 2002.10b
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• pp.1074-1079
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• 2002

Long term measurement data on the bridge response caused by moving loads are fundamental ingredient to the development or improvement of the new bridge design. In addition, proper establishment of the systematic analysis and diagnosis together with the maintenance system become the essential procedure to the effective repair/reinforcement/retrofit of not only the high speed but also the conventional railway bridges. Therefore, the real time health monitoring system on the important railway bridges should be enhancing the proper maintenance of the structures. The main objective of this study is, therefore, to develop a monitoring device including Weigh-In-Motion (WIM) function and the emphasis is place on the easy and economic installation of the developed system in the field condition.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.6
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• pp.2935-2937
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• 2014

Studies of the causes of cancer, early detection, prevention or treatment need accurate, comprehensive, and timely cancer data. The clinical laboratory provides important cancer information needed for physicians which influence clinical decisions regarding treatment, diagnosis and patient monitoring. Poor communication between health care providers and clinical laboratory personnel can lead to medical errors and wrong decisions in providing cancer care. Because of the key impact of laboratory information on cancer diagnosis and treatment the quality of the tests, lab reports, and appropriate lab management are very important. A laboratory information management system (LIMS) can have an important role in diagnosis, fast and effective access to cancer data, decrease redundancy and costs, and facilitate the integration and collection of data from different types of instruments and systems. In spite of significant advantages LIMS is limited by factors such as problems in adaption to new instruments that may change existing work processes. Applications of intelligent software simultaneously with existing information systems, in addition to remove these restrictions, have important benefits including adding additional non-laboratory-generated information to the reports, facilitating decision making, and improving quality and productivity of cancer care services. Laboratory systems must have flexibility to change and have the capability to develop and benefit from intelligent devices. Intelligent laboratory information management systems need to benefit from informatics tools and latest technologies like open sources. The aim of this commentary is to survey application, opportunities and necessity of intelligent clinical laboratory as a tool to increase cancer care management productivity.

• Journal of Preventive Medicine and Public Health
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• v.47 no.4
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• pp.206-215
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• 2014

Objectives: The hospital standardized mortality ratio (HSMR) has been widely used because it allows for robust risk adjustment using administrative data and is important for improving the quality of patient care. Methods: All inpatients discharged from hospitals with more than 700 beds (66 hospitals) in 2008 were eligible for inclusion. Using the claims data, 29 most responsible diagnosis (MRDx), accounting for 80% of all inpatient deaths among these hospitals, were identified, and inpatients with those MRDx were selected. The final study population included 703 571 inpatients including 27 718 (3.9% of all inpatients) in-hospital deaths. Using logistic regression, risk-adjusted models for predicting in-hospital mortality were created for each MRDx. The HSMR of individual hospitals was calculated for each MRDx using the model coefficients. The models included age, gender, income level, urgency of admission, diagnosis codes, disease-specific risk factors, and comorbidities. The Elixhauser comorbidity index was used to adjust for comorbidities. Results: For 26 out of 29 MRDx, the c-statistics of these mortality prediction models were higher than 0.8 indicating excellent discriminative power. The HSMR greatly varied across hospitals and disease groups. The academic status of the hospital was the only factor significantly associated with the HSMR. Conclusions: We found a large variation in HSMR among hospitals; therefore, efforts to reduce these variations including continuous monitoring and regular disclosure of the HSMR are required.

• Biomedical Science Letters
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• v.15 no.2
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• pp.135-139
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• 2009

The CA(carbohydrate antigen)19-9 is complex protein that can be used as an important marker which aids the clinical diagnosis and prognosis of various pancreaticobiliary tumors. However, it was also reported that there were some CA19-9 positive patients with benign disease as using RIA method. The purpose of this study is to evaluate the clinical usefulness of serum level of CA19-9 with RIA(radioimmuno assay), CIA(chemiluminescence immuno assay), and conventional liver function tests. The correlation between CIA and RIA in CA19-9 of pancreatobiliary disease was 0.9833(P<0.01). Also, the correlations between CIA and RIA in CA19-9 of benign and malignant pancreaticobiliary tumor patients was 0.8714(P<0.01) and 0.9727(P<0.01) respectively. The correlation between CA19-9 and ALP was 0.5140(P<0.01) and CEA was 0.3385(P<0.05) as using CIA. The measurement of serum CA19-9 levels by CIA method may be useful in differentiating patients with malignant disease from those with benign disease in pancreaticobiliary tumors.