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Use of transrenal DNA for the diagnosis of Tuberculosis
김태윤,김대연,이정희,곽현경,김지연,옥철호,김제훈,김태윤,류성원 대한결핵 및 호흡기학회 2018 대한결핵 및 호흡기학회 추계학술대회 초록집 Vol.126 No.0
There have been attempts to use biological samples other than sputum for the diagnosis of TB. Urine is promising clinical specimen because of its availability, ease of access, processing and storage, and the low infection risk to healthcare workers during sample collection. In this study we evaluated the outcomes of urine diagnostics in hospitalized MDR, XDR pulmonary TB patients. In order to detect TB-specific transrenal DNA, 10 urine samples were collected during the study period, and quickly added to 1 ml of a stabilization buffer to a final concentration of 10 mM, in order to minimize degradation of soluble DNA by nucleases. DNA was extracted from 8ml of whole urine and eluted in 25ul with an automated system based on magnetic silica particle technology. We used droplet PCR, it might be an ideal alternative to conventional real-time PCR for microorganism detection. We aimed to assess the capacity of ddPCR for detecting low levels of circulating Mycobacterium tuberculosis DNA target (known as IS6110). ddPCR was found to provide results in good agreement with the other methods tested and to be highly reproducible.In this study, the results show that ddPCR could be used to measure low levels of MTB DNA, and it has the potential to be used to diagnose pulmonary TB based on clinical samples. The application of the Tr-DNA test could provide a significant advance in the diagnosis of TB. The availability of new method using urine that is more convenient and accessible may greatly usefulness for individual hospitalized patients for monitoring their treatment process.
3대째 우성유전된 Disseminated Superficial Actinic Porockratosis
김태윤,김정원,허원,김형옥,정은정 대한피부과학회 1981 大韓皮膚科學會誌 Vol.19 No.6
Disseminated superficial actinic porokeratosis (DSAP) has an autosomal dominant mode of inheritance with reduced penetration at young age, characterized by multiple superficial keratotic lesions surrounded by a slightly raised border. The aggrevation of the lesion by exposing UV light indicates that phenotypic expression of gene regluating DSAP is related to sun light. We observed a family of which 13 members had DSAP in 3 successive generations. They were grandrnother, two sons of her 3 offsprings, 2 grandsons and 8 granddaughters. Lesions of all cases were found on the sun exposed areas, especially, face, extremities and upper trunk but exceptionally one had a lesion on the unex posed area, abdomen below the iliac crest. The number of lesions of the individual patient were 12-116, and there appeared to be increasing number of lesions with age.
Review on Applications of Machine Learning in Coastal and Ocean Engineering
김태윤,이우동 한국해양공학회 2022 韓國海洋工學會誌 Vol.36 No.3
Recently, an analysis method using machine learning for solving problems in coastal and ocean engineering has been highlighted. Machine learning models are effective modeling tools for predicting specific parameters by learning complex relationships based on a specified dataset. In coastal and ocean engineering, various studies have been conducted to predict dependent variables such as wave parameters, tides, storm surges, design parameters, and shoreline fluctuations. Herein, we introduce and describe the application trend of machine learning models in coastal and ocean engineering. Based on the results of various studies, machine learning models are an effective alternative to approaches involving data requirements, time-consuming fluid dynamics, and numerical models. In addition, machine learning can be successfully applied for solving various problems in coastal and ocean engineering. However, to achieve accurate predictions, model development should be conducted in addition to data preprocessing and cost calculation. Furthermore, applicability to various systems and quantifiable evaluations of uncertainty should be considered.
김태윤,이재기,선광민,박병건,박해준,최득수,예성준 한국원자력학회 2022 Nuclear Engineering and Technology Vol.54 No.2
Non-destructive testing (NDT) technology is a widely used inspection method for agricultural products. Compared with the conventional inspection method, there is no extensive sample preparation for NDTtechnology, and the sample is not damaged. In particular, NDT technology is used to inspect the internalstructure of agricultural products infested by pests. The introduction and spread of pests during theimport and export process can cause significant damage to the agricultural environment. Until now, pestdetection in agricultural products and quarantine processes have been challenging because they usedexternal inspection methods. However, NDT technology is advantageous in these inspection situations. Inthis pilot study, we investigated the feasibility of X-ray computed tomography (X-ray CT) and magneticresonance imaging (MRI) to identify pest infestation in agricultural products. Three kinds of artificiallypest-infested fruits (mango, tangerine, and chestnut) were non-destructively inspected using X-ray CTand MRI. X-ray CT was able to identify all pest infestations in fruits, while MRI could not detect the pestinfested chestnut. In addition, X-ray CT was superior to the quarantine process than MRI based on thecontrast-to-noise ratio (CNR), image acquisition time, and cost. Therefore, X-ray CT is more appropriatefor the pest quarantine process of fruits than MR
Remarks on correlated error tests
김태윤,하정철 한국데이터정보과학회 2016 한국데이터정보과학회지 Vol.27 No.2
The Durbin-Watson (DW) test in regression model and the Ljung-Box (LB) test in ARMA (autoregressive moving average) model are typical examples of correlated error tests. The DW test is used for detecting autocorrelation of errors using the residuals from a regression analysis. The LB test is used for specifying the correct ARMA model using the first some sample autocorrelations based on the residuals of a fitted ARMA model. In this article, simulations with four data generating processes have been carried out to evaluate their performances as correlated error tests. Our simulations show that the DW test is severely dependent on the assumed AR(1) model but isn't sensitive enough to reject the misspecified model and that the LB test reports lackluster performance in general.