• Tuberculosis and Respiratory Diseases
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• v.49 no.5
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• pp.558-567
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• 2000

Background : Recently, serologic techniques for tuberculosis have been developed and some of them, which are focusing on detection of serum antibodies mainly directed against specific 38-kDa Mycobacterium tuberculosis, have already been introduced into the markel. In this study, diagnostic significance of a new serologic test(ELISA kit) for pulmonary tuberculosis was evaluated. Method : Serologic test with newly developed ELISA kit was performed upon 474 individuals, who include 333 active pulmonary tuberculosis patients, 80 healthy cases, and 61 tuberculosis contact cases. This serologic test was based on the ELISA technique and designed to detect antibodies to mixed complex antigens including 38-kDa, which were developed by Erume Biotech Co., Seoul. Active pulmonary tuberculosis was diagnosed by sputum AFB smear and culture methods. Results : The seropositivities using this ELISA kit were 82.1% and 73.6% in smear-positive and negative groups among active pulmonary tuberculosis, respectively. And, it also showed that seronegativities were 97.5% and 85.2% in healthy and contact groups, respectively. As a whole, the results of our study using the ELISA kit as a diagnostic method for pulmonary tuberculosis showed 80.0% sensitivity for active pulmonary tuberculosis, 97.5% specificity, 96.1% positive predictive value, and 65.0% negative predictive value when the prevalence of tuberuclosis in the samples was 60.1%. Conclusion : Our results reveal that the detection of antibody its reaction with 38-kDa antigen of M. tuberculosis is not sufficient to be accepted as single diagnostic method for pulmonary tuberculosis. However, they suggest that ELISA kit may be considered as an adjunctive test to standard diagnostic techniques of pulmonary tuberculosis.

• Journal of Conservation Science
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• v.32 no.2
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• pp.273-291
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• 2016

Some ceramic artifacts representing time-wise from comb pattern pottery in the Neolithic Age to white porcelain in Joseon Dynasty were selected from 7 sites in the north and south area of Charyeong Mountain Range in order to making techniques interpretation and development process of ancient ceramics through physicochemical and mineralogical quantitative analysis. Studied pottery samples in the Prehistoric times showed trace of ring piling in soft-type, and pottery in the Three Kingdoms Period had both soft and hard-type but kettle-ware and storage-ware were made with ring piling, but table-ware was made by wheel spinning. Different from pottery after the Three Kingdom Period when refinement of source clay was high, pottery in the Neolithic Age and in the Bronze Age exhibited highly mineral content in sandy source clay, which showed a lot of larger temper than source clay. Groundmass of celadon and white porcelain almost did not reveal primary minerals but had high content of minerals by high temperature firing. Ceramic samples showed some different in major and minor elements according to sites irrespective of times. Geochemical behaviors are very similar indicating similar basic characteristics of source clay. However, loss-on-ignition showed 0.01 to 12.59wt.% range with a large deviation but it rapidly decreased moving from the Prehistoric times to the Three Kingdom Period. They have correlation with the weight loss due to firings, according to burning degree of source clay and detection of high temperature minerals, estimated firing temperatures are classified into 5 groups. Pottery in the Neolithic Age and in the Bronze Age belongs from 750 to $850^{\circ}C$ group; pottery in the Three Kingdom Period are variously found in 750 to $1,100^{\circ}C$ range of firing temperature; and it is believed celadon and white porcelain were baked in high temperature of 1,150 to $1,250^{\circ}C$. It seems difference between refinement of source clay and firing temperature based on production times resulted from change in raw material supply and firing method pursuant to development of production skill. However, there was difference in production methods even at the same period and it is thought that they were utilized according to use purpose and needs instead of evolved development simply to one direction.

• Progress in Medical Physics
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• v.24 no.2
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• pp.99-107
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• 2013

The surgical resection was occurred mainly in liver metastasis before the development of radiation therapy techniques. Recently, Radiation therapy is increased gradually due to the development of radiation dose delivery techniques. 18F-FDG PET image showed better sensitivity and specificity in liver metastasis detection. This image modality is important in the radiation treatment with planning CT for tumor delineation. In this study, we applied automatic image segmentation methods on PET image of liver metastasis and examined the impact of image factors on these methods. We selected the patients who were received the radiation therapy and 18F-FDG PET/CT in Korea Cancer Center Hospital from 2009 to 2012. Then, three kinds of image segmentation methods had been applied; The relative threshold method, the Gradient method and the region growing method. Based on these results, we performed statistical analysis in two directions. 1. comparison of GTV and image segmentation results. 2. performance of regression analysis for relation between image factor affecting image segmentation techniques. The mean volume of GTV was $60.9{\pm}65.9$ cc and the $GTV_{40%}$ was $22.43{\pm}35.27$ cc, and the $GTV_{50%}$ was $10.11{\pm}17.92$ cc, the $GTV_{RG}$ was $32.89{\pm}36.8$4 cc, the $GTV_{GD}$ was $30.34{\pm}35.77$ cc, respectively. The most similar segmentation method with the GTV result was the region growing method. For the quantitative analysis of the image factors which influenced on the region growing method, we used the standardized coefficient ${\beta}$, factors affecting the region growing method show GTV, $TumorSUV_{MAX/MIN}$, $SUV_{max}$, TBR in order. The result of the region growing (automatic segmentation) method showed the most similar result with the CT based GTV and the region growing method was affected by image factors. If we define the tumor volume by the auto image segmentation method which reflect the PET image parameters, more accurate and consistent tumor contouring can be done. And we can irradiate the optimized radiation dose to the cancer, ultimately.

• Journal of radiological science and technology
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• v.32 no.3
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• pp.313-323
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• 2009

Diffusion-weighted imaging (DWI) has been demonstrated to be a practical method for the diagnosis of various brain diseases such as acute infarction, brain tumor, and white matter disease. In this study, we used two techniques to examine the average signal intensity (SI) and apparent diffusion coefficient (ADC) of the brains of patients who ranged in age from 10 to 60 years. Our results indicated that the average SI was the highest in amygdala (as derived from DWI), whereas that in the cerebrospinal fluid was the lowest. The average ADC was the highest in the cerebrospinal fluid, whereas the lowest measurement was derived from the pons. The average SI and ADC were higher in $T_2^*$-DW-EPI than in FLAIR-DW-EPI. The higher the b-value, the smaller the average difference in both imaging techniques; the lower the b-value, the greater the average difference. Also, comparative analysis of the brains of patients who had experienced cerebral infarction showed no distinct lesion in the general MR image over time. However, there was a high SI in apparent weighted images. Analysis of other brain diseases (e.g., bleeding, acute, subacute, chronic infarction) indicated SI variance in accordance with characteristics of the two techniques. The higher the SI, the lower the ADC. Taken together, the value of SI and ADC in accordance with frequently occurring areas and various brain disease varies based on the b-value and imaging technique. Because they provide additional useful information in the diagnosis and treatment of patients with various brain diseases through signal recognition, the proper imaging technique and b-value are important for the detection and interpretation of subacute stroke and other brain diseases.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.111-125
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• 2011

Clustering is a process of grouping similar or relevant documents into a cluster and assigning a meaningful concept to the cluster. By this process, clustering facilitates fast and correct search for the relevant documents by narrowing down the range of searching only to the collection of documents belonging to related clusters. For effective clustering, techniques are required for identifying similar documents and grouping them into a cluster, and discovering a concept that is most relevant to the cluster. One of the problems often appearing in this context is the detection of a complex concept that overlaps with several simple concepts at the same hierarchical level. Previous clustering methods were unable to identify and represent a complex concept that belongs to several different clusters at the same level in the concept hierarchy, and also could not validate the semantic hierarchical relationship between a complex concept and each of simple concepts. In order to solve these problems, this paper proposes a new clustering method that identifies and represents complex concepts efficiently. We developed the Hierarchical Overlapping Clustering (HOC) algorithm that modified the traditional Agglomerative Hierarchical Clustering algorithm to allow overlapped clusters at the same level in the concept hierarchy. The HOC algorithm represents the clustering result not by a tree but by a lattice to detect complex concepts. We developed a system that employs the HOC algorithm to carry out the goal of complex concept detection. This system operates in three phases; 1) the preprocessing of documents, 2) the clustering using the HOC algorithm, and 3) the validation of semantic hierarchical relationships among the concepts in the lattice obtained as a result of clustering. The preprocessing phase represents the documents as x-y coordinate values in a 2-dimensional space by considering the weights of terms appearing in the documents. First, it goes through some refinement process by applying stopwords removal and stemming to extract index terms. Then, each index term is assigned a TF-IDF weight value and the x-y coordinate value for each document is determined by combining the TF-IDF values of the terms in it. The clustering phase uses the HOC algorithm in which the similarity between the documents is calculated by applying the Euclidean distance method. Initially, a cluster is generated for each document by grouping those documents that are closest to it. Then, the distance between any two clusters is measured, grouping the closest clusters as a new cluster. This process is repeated until the root cluster is generated. In the validation phase, the feature selection method is applied to validate the appropriateness of the cluster concepts built by the HOC algorithm to see if they have meaningful hierarchical relationships. Feature selection is a method of extracting key features from a document by identifying and assigning weight values to important and representative terms in the document. In order to correctly select key features, a method is needed to determine how each term contributes to the class of the document. Among several methods achieving this goal, this paper adopted the $x^2$�� statistics, which measures the dependency degree of a term t to a class c, and represents the relationship between t and c by a numerical value. To demonstrate the effectiveness of the HOC algorithm, a series of performance evaluation is carried out by using a well-known Reuter-21578 news collection. The result of performance evaluation showed that the HOC algorithm greatly contributes to detecting and producing complex concepts by generating the concept hierarchy in a lattice structure.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.185-205
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• 2014

SAR ground moving target indicator (GMTI) has long been an important issue for SAR advanced applications. As spatial resolution of space-borne SAR system has been significantly improved recently, the GMTI becomes a very useful tool. Various GMTI techniques have been developed particularly using multi-channel SAR systems. It is, however, still problematic to detect ground moving targets within single channel SAR images while it is not practical to access high resolution multi-channel space-borne SAR systems. Once a ground moving target is detected, it is possible to retrieve twodimensional velocities of the target from single channel space-borne SAR with an accuracy of about 5 % if moving faster than 3 m/s. This paper presents a quick-and-dirty method for detecting ground moving targets from single channel SAR single-look complex (SLC) images by differentiation. Since the signal powers of derivatives present Doppler centroid and rate, it is very efficient and effective for detection of non-stationary targets. The derivatives correlate well with velocities retrieved by a precise method with a correlation coefficient $R^2$ of 0.62, which is well enough to detect the ground moving targets. While the approach is theoretically straightforward, it is necessary to remove the effects of residual Doppler rate before finalizing the ground moving target candidates. The confidence level of results largely depends on the efficiency and effectiveness of the residual Doppler rate removal method. Application results using TerraSAR-X and truck-mounted corner reflectors validated the efficiency of the method. While the derivatives of moving targets remain easily detectable, the signal energy of stationary corner reflectors was suppressed by about 18.5 dB. It results in an easy detection of ground targets moving faster than 8.8 km/h. The proposed method is applicable to any high resolution single channel SAR systems including KOMPSAT-5.

• Journal of Life Science
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• v.24 no.4
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• pp.361-369
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• 2014

Broad-range and specific 16S rRNA gene PCR is used for detection and identification of bacterial pathogens in clinical specimens from patients with a high suspicion for infection. We describe the development of a broad-range and specific PCR primer, based on bacterial 16S rRNA, for use in routine diagnostic clinical microbiology services. The primers were designed by using conservative regions of 16S rRNA sequences from 10 strains. Ninety-eight clinical strains were isolated from clinical patient specimens. A total of 98 strains of bacteria were identified by phenotypic methods; PCR with newly designed primers and universal primers. All purified PCR products were sequenced using both forward and reverse primers on an automated DNA analyzer. In this study, we evaluated the usefulness of the newly designed primers and the universal primers for the detection of bacteria, and both these techniques were compared with phenotypic methods for bacteria detection. When we also tested 98 strains of clinical isolates with newly designed primers, about 778 bp DNA fragments were amplified and identified from all strains. Of the 98 strains, 94 strains (95.9%) correspond in comparison with phenotypic methods. The newly designed primers showed that the identities of 98 (100%) strains were the same as those obtained by universal PCR primers. The overall agreement between the newly designed primers and universal primers was 100%. The primer set was designed for rapid, accurate, and cheap identification of bacterial pathogens. We think the newly designed primer set is useful for the identification of pathogenic bacteria.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1041-1053
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• 2018

In this study, a real-time storage level and capacity monitoring and forecasting system for Yongdam Dam watershed was developed using high resolution satellite image. The drought indices such as Standardized Precipitation Index (SPI) from satellite data were used for storage level monitoring in case of drought. Moreover, to predict storage volume we used a statistical method based on Principle Component Analysis (PCA) of Singular Spectrum Analysis (SSA). According to this study, correlation coefficient between storage level and SPI (3) was highly calculated with CC=0.78, and the monitoring and predictability of storage level was diagnosed using the drought index calculated from satellite data. As a result of analysis of principal component analysis by SSA, correlation between SPI (3) and each Reconstructed Components (RCs) data were highly correlated with CC=0.87 to 0.99. And also, the correlations of RC data with Normalized Water Surface Level (N-W.S.L.) were confirmed that has highly correlated with CC=0.83 to 0.97. In terms of high resolution satellite image we developed a water detection algorithm by applying an exponential method to monitor the change of storage level by using Multi-Spectral Instrument (MSI) sensor of Sentinel-2 satellite. The materials of satellite image for water surface area detection in Yongdam dam watershed was considered from 2016 to 2018, respectively. Based on this, we proposed the possibility of real-time drought monitoring system using high resolution water surface area detection by Sentinel-2 satellite image. The results of this study can be applied to estimate of the reservoir volume calculated from various satellite observations, which can be used for monitoring and estimating hydrological droughts in an unmeasured area.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• Journal of Microbiology and Biotechnology
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• v.17 no.12
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• pp.1955-1964
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• 2007

A recent report showed that analysis of CD154 expression in the presence of the secretion inhibitor Brefeldin A (Bref A) could be used to assess the entire repertoire of antigen-specific $CD4^+\;T$ helper cells. However, the capacity of intracellular CD154 expression to identify antigen-specific $CD8^+\;T$ cells has yet to be investigated. In this study, we compared the ability of intracellular CD154 expression to assess antigen-specific $CD8^+\;T$ cells with that of accepted standard assays, namely intracellular cytokine IFN-${\gamma}$ staining (ICS) and MHC class I tetramer staining. The detection of intracellular CD154 molecules in the presence of Bref A reflected the kinetic trend of antigen-specific $CD8^+\;T$ cell number, but unfortunately showed less sensitivity than ICS and tetramer staining. However, ICS levels peaked and saturated 8 h after antigenic stimulation in the presence of Bref A and then declined, whereas intracellular CD154 expression peaked by 8 h and maintained the saturated level up to 24 h post-stimulation. Moreover, intracellular CD154 expression in antigen-specific $CD8^+\;T$ cells developed in the absence of $CD4^+\;T$ cells changed little, whereas the number of IFN-${\gamma}$-producing $CD8^+\;T$ cells decreased abruptly. These results suggest that intracellular CD154 could aid the assessment of antigen-specific $CD8^+\;T$ cells, but does not have as much ability to identify heterogeneous $CD4^+\;T$ helper cells. Therefore, the combined analytical techniques of ICS and tetramer staining together with intracellular CD154 assays may be able to provide useful information on the accurate phenotype and functionality of antigen-specific $CD8^+\;T$ cells.