• Investigative Magnetic Resonance Imaging
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• v.1 no.1
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• pp.103-107
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• 1997

Purpose: To investigate the localization and functional lateralization of the supplementary motor area (SMA) in motor activation tests in comparison to that of the primary motor area. Materials and Methods: Seven healthy volunteers obtained echoplanar imaging blood oxygen level dependent technique. This study was carried on 1.5T Siemens Magnetom Vision system with the standard head coil. Parameters of EPI were followed as; TR/TE : 1.0/66.0msec, flip angle: $90^{\circ}$, field of view: $22cm{\times}22cm,{\;}matrix:{\;}128{\times}128$, slice number/slice thickness/gap: 1O/4mm/0.8mm with fat suppression technique. Motor task as finger opposition in each hand consisted of 3 sets of alternative rest and activation periods. Postprocessing were done on Stimulate 5.0 by using cross-correlation statistics. To compare the functional lateralization of the SMA in the right and left hand tests, each examination was evaluated for the percent change of signal intensity and the number of activated voxels both in the SMA and in the pri¬mary motor area. Hemispheric asymmetry was defined as difference of summation of the activted voxels between each hemisphere. Results: Percent change of signal intensity in the SMA (2.49 -3.06%) is lower than that of primary motor area(4.4 -7.23%). Percent change of signal intensity including activated voxels were observed almost equally in the right and left SMA. As for summation of activated voxels, primary motor area had significant difference between each hemisphere but not did the SMA. Conclusion: Preferred contralateral dominant hemisphere and hemispheric asymmetry were detected in the primary motor area but not in the SMA.

• Information Systems Review
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• v.14 no.3
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• pp.25-51
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• 2012

The purpose of this study is to analyze the key factors affecting satisfaction of the visually impaired SNS users so that they may use SNS more effectively in the future. This study has used three factors such as the information factor, the relationship factor and the speed factor and the usability as independent variables. The social presence factor was used as a parameter and the SNS user satisfaction as a dependent variable. For the research, 195 visually impaired SNS users have participated in this survey. The major findings of this study are that the relationship factor has strong effects on the self-identification factor, the social presence factor and the SNS usage satisfaction among the factors affecting the visually impaired users to be satisfied with SNS. On the other hand, the information factor and usage factor have no effects on the self-identification factor and the social presence factor. However, they have effects on the SNS usage satisfaction. Additionally, the self-identification factor has no effect on the SNS usage satisfaction, but the social presence factor has effect. Based on the above study results, this paper proposed for the government to enhance the educational program on the use of SNS for the visually impaired and to increase its financial and political support on this subject. Additionally, technical supports on SNS service accessibility and usage by the government are vital for the visually impaired. Academically, this study provides a concrete groundwork for the research on the use of SNS by the visually impaired by providing a solid research direction for further study on this subject. Socially, this study helps the visually impaired use SNS more effectively by increasing the general public awareness of the importance of SNS usages by the visually impaired so that the information gap of the society may be diminished in the future.

• Journal of Magnetics
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• v.20 no.4
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• pp.381-386
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• 2015

The purpose of this study is to improve diagnostic efficiency of clinical study by setting up guidelines for more precise examination with a comparative analysis of signal intensity and image distortion depending on the location of X axial of object when performing magnetic resonance diffusion weighted imaging (MR DWI) examination. We arranged the self-produced phantom with a 45 mm of interval from the core of 44 regent bottles that have a 16 mm of external diameter and 55 mm of height, and were placed in 4 rows and 11 columns in an acrylic box. We also filled up water and margarine to portrait the fat. We used 3T Skyra and 18 Channel Body array coil. We also obtained the coronal image with the direction of RL (right to left) by using scan slice thinkness 3 mm, slice gap: 0mm, field of view (FOV): $450{\times}450mm^2$, repetition time (TR): 5000 ms, echo time (TE): 73/118 ms, Matrix: $126{\times}126$, slice number: 15, scan time: 9 min 45sec, number of excitations (NEX): 3, phase encoding as a diffusion-weighted imaging parameter. In order to scan, we set b-value to $0s/mm^2$, $400s/mm^2$, and $1,400s/mm^2$, and obtained T2 fat saturation image. Then we did a comparative analysis on the differences between image distortion and signal intensity depending on the location of X axial based on iso-center of patient's table. We used "Image J" as a comparative analysis programme, and used SPSS v18.0 as a statistic programme. There was not much difference between image distortion and signal intensity on fat and water from T2 fat saturation image. But, the average value depends on the location of X axial was statistically significant (p < 0.05). From DWI image, when b-value was 0 and 400, there was no significant difference up to $2^{nd}$ columns right to left from the core of patient's table, however, there was a decline in signal intensity and image distortion from the $3^{rd}$ columns and they started to decrease rapidly at the $4^{th}$ columns. When b-value was 1,400, there was not much difference between the $1^{st}$ row right to left from the core of patient's table, however, image distortion started to appear from the $2^{nd}$ columns with no change in signal intensity, the signal was getting decreased from the $3^{rd}$ columns, and both signal intensity and image distortion started to get decreased rapidly. At this moment, the reagent bottles from outside out of 11 reagent bottles were not verified from the image, and only 9 reagent bottles were verified. However, it was not possible to verify anything from the $5^{th}$ columns. But, the average value depends on the location of X axial was statistically significant. On T2 FS image, there was a significant decline in image distortion and signal intensity over 180mm from the core of patient's table. On diffusion-weighted image, there was a significant decline in image distortion and signal intensity over 90 mm, and they became unverifiable over 180 mm. Therefore, we should make an image that has a diagnostic value from examinations that are hard to locate patient's position.

• Journal of The Korean Astronomical Society
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• v.12 no.1
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• pp.41-70
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• 1979

From $B\ddot{o}hm$-Vitense's atmospheric model calculations, the relations, [$T_e$, (B-V)] and [B.C, (B-V)] with respect to heavy element abundance were obtained. Using these relations and evolutionary model calculations of Rood, and Sweigart and Gross, analytic expressions for some physical parameters relating to the C-M diagrams of globular clusters were derived, and they were applied to 21 globular clusters with observed transition periods of RR Lyrae variables. More than 20 different parameters were examined for each globular cluster. The derived ranges of some basic parameters are as follows; $Y=0.21{\sim}0.33,\;Z=1.5{\times}10^{-4}{\sim}4.5{\times}10^{-3},\;age,\;t=9.5{\sim}19{\times}10^9$ years, mass for red giants, $m_{RG}=0.74m_{\odot}{\sim}0.91m_{\odot}$, mass for RR Lyrae stars, $m_{RR}=0.59m_{\odot}{\sim}0.75m_{\odot}$, the visual magnitude difference between the turnoff point and the horizontal branch (HB), ${\Delta}V_{to}=3.1{\sim}3.4(<{\Delta}V_{to}>=3.32)$, the color of the blue edge of RR Lyrae gap, $(B-V)_{BE}=0.17{\sim}0.21=(<(B-V)_{BE}>=0.18),\;[\frac{m}{L}]_{RR}=-1.7{\sim}-1.9$, mass difference of $m_{RR}$ relative to $m_{RG},(m_{RG}-m_{RR})/m_{RG}=0.0{\sim}0.39$. It was found that the ranges of derived parameters agree reasonably well with the observed ones and those estimated by others. Some important results obtained herein can be summarized as follows; (i) There are considerable variations in the initial helium abundance and in age of globular clusters. (ii) The radial gradient of heavy element abundance does exist for globular clusters as shown by Janes for field stars and open clusters. (iii) The helium abundance seems to have been increased with age by massive star evolution after a considerable amount (Y>0.2) of helium had been attained by the Big-Bang nucleosynthesis, but there is not seen a radial gradient of helium abundance. (iv) A considerable amount of heavy elements ($Z{\sim}10{-3}$) might have been formed in the inner halo ($r_{GC}$<10 kpc) from the earliest galactic co1lapse, and then the heavy element abundance has been slowly enriched towards the galactic center and disk, establishing the radial gradient of heavy element abundance. (v) The final galactic disk formation might have taken much longer by about a half of the galactic age than the halo formation, supporting a slow, inhomogeneous co1lapse model of Larson. (vi) Of the three principal parameters controlling the morphology of C-M diagrams, it was found that the first parameter is heavy clement abundance, the second age and the third helium abundance. (vii) The globular clusters can be divided into three different groups, AI, BI and CII according to Z, Y an d age as well as Dickens' HB types. BI group clusters of HB types 4 and 5 like M 3 and NGC 7006 are the oldest and have the lowest helium abundance of the three groups. And also they appear in the inner halo. On the other hand, the youngest AI clusters have the highest Z and Y, and appear in the innermost halo region and in the disk. (viii) From the result of the clean separations of the clusters into three groups, a three dimensional classification with three parameters, Z, Y and age is prsented. (ix) The anomalous C-M diagrams can be expalined in terms of the three principal parameters. That is, the anomaly of NGC 362 and NGC 7006 is accounted for by the smaller age of the order of $1{\sim}2{\times}10^9$ years rather than by the helium abundance difference, compared with M 3. (x) The difference in two Oosterhoff types I and II can be explained in terms of the mean mass difference of RR Lyrae variables rather than in terms of the helium abundance difference as suggested by Stobie. The mean mass of the variables in Oosterhoff type I clusters is smaller by $0.074m_{\odot}$ which is exactly consistent with Rood's estimate. Since it was found that the mean mass of RR Lyrae stars increases with decreasing Z, the two Oosterhoff types can be explained substantially by the metal abundance difference; the type II has Z<$3.4{\times}10^{-4}$, and the type I has higher Z than the type II.

• Journal of Sensor Science and Technology
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• v.10 no.1
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• pp.62-70
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• 2001

The ZnSe sample grown by chemical bath deposition (CBD) method were annealed in Ar gas at $45^{\circ}C$. Using extrapolation method of X-ray diffraction pattern, it was found to have zinc blend structure whose lattice parameter $a_o$ was $5.6687\;{\AA}$. From Hall effect, the mobility was likely to be decreased by impurity scattering at temperature range from 10 K to 150 K and by lattice scattering at temperature range from 150 K to 293 K. The band gap given by the transmission edge changed from $2.700{\underline{5}}\;eV$ at 293 K to $2.873{\underline{9}}\;eV$ at 10 K. Comparing photocurrent peak position with transmission edge, we could find that photocurrent peaks due to excition electrons from valence band, ${\Gamma}_8$ and ${\Gamma}_7$ and to conduction band ${\Gamma}_6$ were observed at photocurrent spectrum. From the photocurrent spectra by illumination of polarized light on the ZnSe thin film, we have found that values of spin orbit coupling splitting ${\Delta}so$ is $0.098{\underline{1}}\;eV$. From the PL spectra at 10K, the peaks corresponding to free bound excitons and D-A pair and a broad emission band due to SA is identified. The binding energy of the free excitons are determined to be $0.061{\underline{2}}\;eV$ and the dissipation energy of the donor -bound exciton and acceptor-bound exciton to be $0.017{\underline{2}}\;eV$, $0.031{\underline{0}}\;eV$, respectively.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.665-679
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• 2019

Mesoscale soil moisture measurement from the promising Cosmic-Ray Neutron Probe (CRNP) is expected to bridge the gap between large scale microwave remote sensing and point-based in-situ soil moisture observations. Traditional calibration based on $N_0$ method is used to convert neutron intensity measured at the CRNP to field scale soil moisture. However, the static calibration parameter $N_0$ used in traditional technique is insufficient to quantify long term soil moisture variation and easily influenced by different time-variant factors, contributing to the high uncertainties in CRNP soil moisture product. Consequently, in this study, we proposed a modified traditional calibration method, so-called Dynamic-$N_0$ method, which take into account the temporal variation of $N_0$ to improve the CRNP based soil moisture estimation. In particular, a nonlinear regression method has been developed to directly estimate the time series of $N_0$ data from the corrected neutron intensity. The $N_0$ time series were then reapplied to generate the soil moisture. We evaluated the performance of Dynamic-$N_0$ method for soil moisture estimation compared with the traditional one by using a weighted in-situ soil moisture product. The results indicated that Dynamic-$N_0$ method outperformed the traditional calibration technique, where correlation coefficient increased from 0.70 to 0.72 and RMSE and bias reduced from 0.036 to 0.026 and -0.006 to $-0.001m^3m^{-3}$. Superior performance of the Dynamic-$N_0$ calibration method revealed that the temporal variability of $N_0$ was caused by hydrogen pools surrounding the CRNP. Although several uncertainty sources contributed to the variation of $N_0$ were not fully identified, this proposed calibration method gave a new insight to improve field scale soil moisture estimation from the CRNP.