• Horticultural Science & Technology
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• v.31 no.3
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• pp.337-343
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• 2013

The aims of this study were to compare genetic distances among 14 Phalaenopsis varieties using simple sequence repeat (SSR) and sequence-related amplified polymorphism (SRAP) marker systems and to determine the discrimination using SSR. A total of 111 SSR primers and 30 SRAP combinations were initially screened. Twelve SSR primers and thirty SRAP combinations showed high polymorphism among the 14 Phalaenopsis varieties including domestic breeding varieties, conserved in National Institute of Horticultural & Herbal Science (NIHHS). The amplified DNA fragments were separated by denaturing acrylamide gels and detected by silver staining method. A total of 474 polymorphic bands, including 55 by SSRs and 419 by SRAPs, were identified and used for genetic diversity analysis. Polymorphic bands were scored for calculating a simple matching coefficient of genetic similarity and cluster analysis with multi-variate statistical package (MVSP) 3.1. Fourteen Phalaenopsis varieties were classified into three major groups at similarity coefficient value of 0.683 and 0.66 using SRAP and SSR, respectively. Also we could discriminate these domestic breeding Palaenopsis varieties using only SSR 20 and SSR 22. The results indicate that SSR analysis is effective for discrimination among Phalaenopsis varieties and SRAP is useful for genetic diversity when there is no sequence information. These studied SSR and SRAP markers will be useful tools for genotype identification, germplasm conservation and genetic relationship study in Phalaenopsis.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.289-307
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• 2010

The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model selection for the general case of arbitrary (random or deterministic) design matrices and arbitrary nonzero entries of the signal. In this regard, it generalizes the notion of incoherence in the existing literature on model selection and introduces two fundamental measures of coherence-termed as the worst-case coherence and the average coherence-among the columns of a design matrix. It utilizes these two measures of coherence to provide an in-depth analysis of a simple, model-order agnostic one-step thresholding (OST) algorithm for model selection and proves that OST is feasible for exact as well as partial model selection as long as the design matrix obeys an easily verifiable property, which is termed as the coherence property. One of the key insights offered by the ensuing analysis in this regard is that OST can successfully carry out model selection even when methods based on convex optimization such as the lasso fail due to the rank deficiency of the submatrices of the design matrix. In addition, the paper establishes that if the design matrix has reasonably small worst-case and average coherence then OST performs near-optimally when either (i) the energy of any nonzero entry of the signal is close to the average signal energy per nonzero entry or (ii) the signal-to-noise ratio in the measurement system is not too high. Finally, two other key contributions of the paper are that (i) it provides bounds on the average coherence of Gaussian matrices and Gabor frames, and (ii) it extends the results on model selection using OST to low-complexity, model-order agnostic recovery of sparse signals with arbitrary nonzero entries. In particular, this part of the analysis in the paper implies that an Alltop Gabor frame together with OST can successfully carry out model selection and recovery of sparse signals irrespective of the phases of the nonzero entries even if the number of nonzero entries scales almost linearly with the number of rows of the Alltop Gabor frame.

• Korean Journal of Construction Engineering and Management
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• v.14 no.1
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• pp.82-90
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• 2013

In the construction industry, there are so many qualitative factors affecting the performance of a project. So it is crucial to measure the factors in an effective way in order to analyze the interrelationship among the various factors. To improve the performance level of a project, it is also important to identify the most appropriate management practices which are inter-linked with the subject project. The purpose of this study is to develop a project performance management system (PPMS) to quantitatively analyze the variety of project performance data and identify the best management practice to increase the potential level of a particular performance area. Using a comparative statistical method, this study developed a quantification method and web-based computerized system to enhance the usage of the system. The system, however, is still under the validation stage because of the shortage of data set. In the future, when more and more completed project data are stored in the system, the system would play a crucial role in predicting the performance level and matching the best management practice for a subject project. In addition, the system can also be modified as a tool for a business- or industry-level system by incorporating the existing enterprise resource programs.

• Investigative Magnetic Resonance Imaging
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• v.18 no.1
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• pp.25-33
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• 2014

Purpose : To investigate whether quantitative parameters derived from Diffusion-weighted magnetic resonance imaging (DW-MRI) correlate with those of Dynamic contrast-enhanced MRI (DCE-MRI). Materials and Methods: Thirteen patients with pathologically or clinically proven bony metastasis who had undergone MRI prior to treatment were included. The voxel size was $1.367{\times}1.367{\times}5mm$. A dominant tumor was selected and the apparent diffusion coefficient (ADC) value and DCE-MRI parameters were obtained by matching voxels. DCE-MRI data were analyzed yielding estimates of $K^{trans}$ (volume transfer constant) and $v_e$. (extravascular extracellular volume fraction). Statistical analysis of ADC, $K^{trans}$, and $v_e$ value was conducted using Pearson correlation analyses. Results: Fifteen lesions in pelvic bones were evaluated. Of these, 11 showed a statistically significant correlation (P<0.05) between ADC and $K^{trans}$. The ADC and $K^{trans}$ were inversely related in 7 lesions and positively related in 4 lesions. This did not depend on the primary cancer or site of metastasis. The ADC and $v_e$ of 9 lesions correlated significantly. Of these, 4 lesions were inversely related and 5 lesions were positively related. Conclusion: Unlike our theoretic hypothesis, there was no consistent correlation between ADC values and $K^{trans}$ or between ADC values and $v_e$ in metastatic bone tumors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5A
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• pp.717-725
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• 2000

Within the last several years, there has been a large number of algorithms developed for face recognition. The majority of these algorithms have been view- and projection-based algorithms. Our definition of projection is not restricted to projecting the image onto an orthogonal basis the definition is expansive and includes a general class of linear transformation of the image pixel values. The class includes correlation, principal component analysis, clustering, gray scale projection, and matching pursuit filters. In this paper, we perform a detailed analysis of this class of algorithms by evaluating them on the FERET database of facial images. In our experiments, a projection-based algorithms consists of three steps. The first step is done off-line and determines the new basis for the images. The bases is either set by the algorithm designer or is learned from a training set. The last two steps are on-line and perform the recognition. The second step projects an image onto the new basis and the third step recognizes a face in an with a nearest neighbor classifier. The classification is performed in the projection space. Most evaluation methods report algorithm performance on a single gallery. This does not fully capture algorithm performance. In our study, we construct set of independent galleries. This allows us to see how individual algorithm performance varies over different galleries. In addition, we report on the relative performance of the algorithms over the different galleries.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.689-698
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• 2006

Pattern recognition is the study of how machines can observe the environment, learn to distinguish patterns of interest from their background, and make sound and reasonable decisions about the categories of the patterns. Color image consists of various color patterns. And most pattern recognition methods use the information of color which has been trained and extract the feature of the color. This thesis extracts adaptively specific color feature from images with several limited colors. Because the number of the color patterns is limited, the distribution of the color in the image is similar. But, when there are some noises and distortions in the image, its distribution can be various. Therefore we cannot extract specific color regions in the standard image that is well expressed in special color patterns to extract, and special color regions of the image to test. We suggest new method to reduce the error of recognition by extracting the specific color feature adaptively for images with the low distortion, and six test images with some degree of noises and distortion. We consequently found that proposed method shouws more accurate results than those of statistical pattern recognition.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.141-151
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• 2019

A network of graph data structure is used in many applications to represent interactions between entities. Recently, as the size of the network to be processed due to the development of the big data technology is getting larger, it becomes more difficult to handle it in one server, and thus the necessity of distributed processing is also increasing. In this paper, we propose a distributed processing system for efficiently performing subgraph and stores. To reduce unnecessary searches, we use statistical information of the data to determine the search order through probabilistic scoring. Since the relationship between the vertex and the degree of the graph network may show different characteristics depending on the type of data, the search order is determined by calculating a score to reduce unnecessary search through a different scoring method for a graph having various distribution characteristics. The graph is sequentially searched in the distributed servers according to the determined order. In order to demonstrate the superiority of the proposed method, performance comparison with the existing method was performed. As a result, the search time is improved by about 3 ~ 10% compared with the existing method.

• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.476-486
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• 2019

Objective : The functional information of $^{11}C$-methionine positron emission tomography (MET-PET) images can be applied for Gamma knife radiosurgery (GKR) and its image quality may affect defining the tumor. This study conducted the phantom-based evaluation for geometric accuracy and functional characteristic of diagnostic MET-PET image co-registered with stereotactic image in Leksell $GammaPlan^{(R)}$ (LGP) and also investigated clinical application of these images in metastatic brain tumors. Methods : Two types of cylindrical acrylic phantoms fabricated in-house were used for this study : the phantom with an array-shaped axial rod insert and the phantom with different sized tube indicators. The phantoms were mounted on the stereotactic frame and scanned using computed tomography (CT), magnetic resonance imaging (MRI), and PET system. Three-dimensional coordinate values on co-registered MET-PET images were compared with those on stereotactic CT image in LGP. MET uptake values of different sized indicators inside phantom were evaluated. We also evaluated the CT and MRI co-registered stereotactic MET-PET images with MR-enhancing volume and PET-metabolic tumor volume (MTV) in 14 metastatic brain tumors. Results : Imaging distortion of MET-PET was maintained stable at less than approximately 3% on mean value. There was no statistical difference in the geometric accuracy according to co-registered reference stereotactic images. In functional characteristic study for MET-PET image, the indicator on the lateral side of the phantom exhibited higher uptake than that on the medial side. This effect decreased as the size of the object increased. In 14 metastatic tumors, the median matching percentage between MR-enhancing volume and PET-MTV was 36.8% on PET/MR fusion images and 39.9% on PET/CT fusion images. Conclusion : The geometric accuracy of the diagnostic MET-PET co-registered with stereotactic MR in LGP is acceptable on phantom-based study. However, the MET-PET images could the limitations in providing exact stereotactic information in clinical study.

• Journal of the Korean School Mathematics Society
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• v.24 no.3
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• pp.283-308
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• 2021

This study aims to analyze statistical tasks in Korean and Singaporean textbooks with the mathematical modeling perspective and compare the learning contents and experiences of students from both countries. I analyzed mathematical modeling tasks in the textbooks based on five aspects: (1) the mathematical modeling process, (2) the data type, (3) the expression type, (4) the context, and (5) the mathematical activity. The results of this study show that Korean and Singaporean textbooks provide the highest percentage of the "working-with-mathematics" task, the highest percentage of the "matching task," and the highest percentage of the "picture" task. The real-world context and mathematical activities used in Korean and Singaporean textbooks differed in percentage. This study provides implications for the development of textbook tasks to support future mathematical modeling activities. This includes providing a balanced experience in mathematical modeling processes and presenting tasks in various forms of expression to raise students' cognitive level and expand the opportunity to experience meaningful mathematizing. In addition, it is necessary to present a contextually realistic task for students' interest in mathematical modeling activities or motivation for learning.

• Journal of Dental Rehabilitation and Applied Science
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• v.36 no.4
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• pp.242-253
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• 2020

Purpose: The aim of this study was to compare the accuracy of dies fabricated using 3D printing system to conventional method and to evaluate overall volumetric changes by arranging the superimposed surfaces. Materials and Methods: A mandibular right first molar from a dental model was prepared, scanned and fabricated with composites of polyetherketoneketone (PEKK). Master dies were classified into 4 groups. For the conventional method, the impression was taken with polyvinylsiloxane and the impression was poured with Type IV dental stone. For the 3D printing, the standard die was scanned and converted into models using three different 3D printers. Each of four methods was used to make 10 specimens. Scanned files were superimposed with the standard die by using 3D surface matching software. For statistical analysis, Kruskal-Wallis test and Mann-Whitney U test were done (P < 0.05). Results: Compared to the standard model, the volumetric changes of dies fabricated by each method were significantly different except the models fabricated by conventional method and 3D printer of Stereolithography (P < 0.05). The conventional dies showed the lowest volumetric change than 3D printed dies (P < 0.05). 3D printed dies fabricated by Stereolithography showed the lowest volumetric change among the different 3D printers (P < 0.05). Conclusion: The conventional dies were more accurate than 3D printed dies, though 3D printed dies were within clinically acceptable range. Thus, 3D printed dies can be used for fabricating restorations.