• Progress in Medical Physics
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• v.21 no.1
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• pp.113-119
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• 2010

Software for GafChromic EBT2 film dosimetry was developed in this study. The software provides film calibration functions based on color channels, which are categorized depending on the colors red, green, blue, and gray. Evaluations of the correction effects for light scattering of a flat-bed scanner and thickness differences of the active layer are available. Dosimetric results from EBT2 films can be compared with those from the treatment planning system ECLIPSE or the two-dimensional ionization chamber array MatriXX. Dose verification using EBT2 films is implemented by carrying out the following procedures: file import, noise filtering, background correction and active layer correction, dose calculation, and evaluation. The relative and absolute background corrections are selectively applied. The calibration results and fitting equation for the sensitometric curve are exported to files. After two different types of dose matrixes are aligned through the interpolation of spatial pixel spacing, interactive translation, and rotation, profiles and isodose curves are compared. In addition, the gamma index and gamma histogram are analyzed according to the determined criteria of distance-to-agreement and dose difference. The performance evaluations were achieved by dose verification in the $60^{\circ}$-enhanced dynamic wedged field and intensity-modulated (IM) beams for prostate cancer. All pass ratios for the two types of tests showed more than 99% in the evaluation, and a gamma histogram with 3 mm and 3% criteria was used. The software was developed for use in routine periodic quality assurance and complex IM beam verification. It can also be used as a dedicated radiochromic film software tool for analyzing dose distribution.

• Horticultural Science & Technology
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• v.33 no.1
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• pp.93-105
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• 2015

This study was performed to analyze genetic relationships of the four major cucurbitaceous crops including watermelon, melon, cucumber, and squash/pumpkin. Among 120 EST-SSR primer sets selected from the International Cucurbit Genomics Initiative (ICuGI) database, PCR was successful for 51 (49.17%) primer sets and 49 (40.8%) primer sets showed polymorphisms among eight Cucurbitaceae accessions. A total of 382 allele-specific PCR bands were produced by 49 EST-SSR primers from 24 Cucurbitaceae accessions and used for analysis of pairwise similarity and dendrogram construction. Assessment of the genetic relationships resulted in similarity indexes ranging from 0.01 to 0.85. In the dendrogram, 24 Cucurbitaceae accessions were classified into two major groups (Clade I and II) and 8 subgroups. Clade I comprised two subgroups, Clade I-1 for watermelon accessions [I-1a and I-1b-2: three wild-type watermelons (Citrullus lanatus var. citroides Mats. & Nakai), I-1b-1: six watermelon cultivars (Citrullus lanatus var. vulgaris S chrad.)] a nd C lade I -2 for melon and cucumber accessions [I-2a-1 : 4 melon cultivars(Cucumis melo var. cantalupensis Naudin.), I-2a-2: oriental melon cultivars (Cucumis melo var. conomon Makino.), and I-2b: five cucumber cultivars (Cucumis sativus L.)]. Squash and pumpkin accessions composed Clade II {II-1: two squash/ pumpkin cultivars [Cucurbita moschata (Duch. ex Lam.)/Duch. & Poir. and Cucurbita maxima Duch.] and II-2: two squash/pumpkin cultivars, Cucurbita pepo L./Cucurbita ficifolia Bouche.}. These results were in accordance with previously reported classification of Cucurbitaceae species, indicating that watermelon EST-SSRs show a high level of marker transferability and should be useful for genetic study in other cucurbit crops.

• Investigative Magnetic Resonance Imaging
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• v.15 no.2
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• pp.110-122
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• 2011

Purpose : The purpose of this study is to establish the method generating human brain anatomical connectivity from Korean children and evaluating the network topological properties using small-world network analysis. Materials and Methods : Using diffusion tensor images (DTI) and parcellation maps of structural MRIs acquired from twelve healthy Korean children, we generated a brain structural connectivity matrix for individual. We applied one sample t-test to the connectivity maps to derive a representative anatomical connectivity for the group. By spatially normalizing the white matter bundles of participants into a template standard space, we obtained the anatomical brain network model. Network properties including clustering coefficient, characteristic path length, and global/local efficiency were also calculated. Results : We found that the structural connectivity of Korean children group preserves the small-world properties. The anatomical connectivity map obtained in this study showed that children group had higher intra-hemispheric connectivity than inter-hemispheric connectivity. We also observed that the neural connectivity of the group is high between brain stem and motorsensory areas. Conclusion : We suggested a method to examine the anatomical brain network of Korean children group. The proposed method can be used to evaluate the efficiency of anatomical brain networks in people with disease.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.164-173
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• 2014

In underwater robotics, vision would be a key element for recognition in underwater environments. However, due to turbidity an underwater optical camera is rarely available. An underwater imaging sonar, as an alternative, delivers low quality sonar images which are not stable and accurate enough to find out natural objects by image processing. For this, artificial landmarks based on the characteristics of ultrasonic waves and their recognition method by a shape matrix transformation were proposed and were proven in Part 1. But, this is not working properly in undulating and dynamically noisy sea-bottom. To solve this, we propose a framework providing a selection phase of likelihood candidates, a selection phase for final candidates, recognition phase and tracking phase in sequence images, where a particle filter based selection mechanism to eliminate fake candidates and a mean shift based tracking algorithm are also proposed. All 4 steps are running in parallel and real-time processing. The proposed framework is flexible to add and to modify internal algorithms. A pool test and sea trial are carried out to prove the performance, and detail analysis of experimental results are done. Information is obtained from tracking phase such as relative distance, bearing will be expected to be used for control and navigation of underwater robots.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.62-71
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• 2013

The passive emitter location method using TDOA and FDOA measurements has higher accuracy comparing to the single TDOA or FDOA based method. Moreover, it is able to estimate the velocity vector of a moving platform. Recently, several non-iterative methods were suggested using the nuisance parameter but the common reference sensor is needed for each pair of sensors. They show also relatively low performance in the case of a long range between the sensor groups and the emitter. To solve this, we derive the estimation method of the position and velocity of a moving platform based on the Gauss-Newton method. In addition, to analyze the estimation performance of the position and velocity, respectively, we decompose the CRLB matrix into each subspace. Simulation results show the estimation performance of the derived method and the CEP planes according to the given geometry of the sensors.

• Journal of Forest and Environmental Science
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• v.15 no.1
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• pp.1-9
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• 1999

Noticing the intrinsic growing habit variations of hardwood species which is indigenous to the natural deciduous forest, eighteen tree species in overstory were selected for comparative evaluating tree form so as to develop the tree form index (TFI). Selected six tree form attributes were arbitrarily divided four assessment criteria and given appropriate scores. Eighteen tree species were undergone corresponding scores, converted to percentage base, and estimated TFI by the summation of the six scoring values. Cluster analysis was carried out to review which attribute would have been shared among species based on dissimilarity of scores for each pair of species in $18{\times}6$ data matrix. The result showed that Populus davidiana had the highest TFI value of 80.8 and Carpinus cordata had the lowest TFI va1ue of 46.3. The species which received more than 70 of TFI are Populus davidiana, Betula costata, Fraxinus mandshurica, and Ulmus davidiana var. japonica, characterized by the advantage of straight and longer bole, the narrower crown, and the thinner branch. On the contrary, such species as Sorbus alnifolia. Prunus sargentii, Acer mandshuricum, Juglans mandshurica, and Carpinus cordata received less than 60 of TFI, characterized by the disadvantage of the crooked or forked stem. the wider or deeper crown. and the thicker branch. In the dendrogram produced by cluster analysis, arbitrary value of Euclidean distance 10 divided eighteen species into four distinctive groups. and the typical characteristics of each group were discussed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.77-84
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• 2012

Face classification has wide applications in intelligent video surveillance, content retrieval, robot vision, and human-machine interface. Pose and expression changes, and arbitrary illumination are typical problems for face recognition. When the face is captured at a distance, the image quality is often degraded by blurring and noise corruption. This paper investigates the efficacy of multi-classifier decision level fusion for face classification based on the photon-counting linear discriminant analysis with two different cost functions: Euclidean distance and negative normalized correlation. Decision level fusion comprises three stages: cost normalization, cost validation, and fusion rules. First, the costs are normalized into the uniform range and then, candidate costs are selected during validation. Three fusion rules are employed: minimum, average, and majority-voting rules. In the experiments, unfocusing and motion blurs are rendered to simulate the effects of the long distance environments. It will be shown that the decision-level fusion scheme provides better results than the single classifier.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.685-695
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• 2008

This paper presents a method to segment the object of interest from a set of multi-view images with minimal user interaction. Specifically, after the user segments an initial image, we first estimate the transformations between foreground and background of the segmented image and the neighboring image, respectively. From these transformations, we obtain regions in the neighboring image that respectively correspond to the foreground and the background of the segmented image. We are then able to segment the neighboring image based on these regions, and iterate this process to segment the whole image set. Transformation of foregrounds are estimated by feature-based registration with free-form deformation, while transformation of backgrounds are estimated by homography constrained to affine transformation. Here, both are based on correspondence point pairs. Segmentation is done by estimating pixel color distributions and defining a shape prior based on the obtained foreground and background regions and applying them to a Markov random field (MRF) energy minimization framework for image segmentation. Experimental results demonstrate the effectiveness of the proposed method.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.163-176
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• 2006

The concept of 'spatial association' explains spatial distribution pattern of geographical phenomenon based on similarity with neighborhoods, as in the Tobler's Law of Geography: 'Everything is related to everything else, but near things are more related than distant things.' In this study, we develop a time-series exploratory analysis tool for discovering temporal patterns of spatial association by combining spatial statistics and geo-visualization, and thus present a possibility to support spatial decision-making process. As for the spatial proximity weight matrix indispensable to measuring global and local spatial association, we employ a variety of flexible weighting schemes using geometric characteristics of areal unit. In addition, we renovate the existing visualization methods for more effective understanding of the procedures and results of time-series analysis on spatial association: for instance, temporal parallel coordinate plot with box plot, animated map for spatial association, and 3D Moran scatterplot. The feasibility of our system is verified by time-series analysis experiments on the spatial association of land price fluctuation rate for all administrative units in Korea, $1995{\sim}2004$.

• The KIPS Transactions:PartA
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• v.15A no.2
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• pp.125-134
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• 2008

We implemented a system being able to suggest example sentences for multiple choice tests, considering the level of students. To build the system, we designed an automatic method for sentence generation, which made it possible to control the difficulty degree of questions. For the proper evaluation in the multiple choice tests, proper size of question pools is required. To satisfy this requirement, a system which can generate various and numerous questions and their example sentences in a fast way should be used. In this paper, we designed an automatic generation method using a linguistic resource called WordNet. For the automatic generation, firstly, we extracted keywords from the existing sentences with the morphological analysis and candidate terms with similar meaning to the keywords in Korean WordNet space are suggested. When suggesting candidate terms, we transformed the existing Korean WordNet scheme into a new scheme to construct the concept similarity matrix. The similarity degree between concepts can be ranged from 0, representing synonyms relationships, to 9, representing non-connected relationships. By using the degree, we can control the difficulty degree of newly generated questions. We used two methods for evaluating semantic similarity between two concepts. The first one is considering only the distance between two concepts and the second one additionally considers positions of two concepts in the Korean Wordnet space. With these methods, we can build a system which can help the instructors generate new questions and their example sentences with various contents and difficulty degree from existing sentences more easily.