• Journal of the Korean Magnetics Society
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• v.26 no.3
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• pp.92-98
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• 2016

To aim of this study was to assess the full scan and half scan of imaging with half scan factor. Patients without a cerebral vascular disease (n = 30) and were subject to the full scan half scan, and set a region of interest in the cerebral artery from the three regions (C1, C2, C3) in the range of 7 to 8 mm. MIP (maximum intensity projection) to reconstruct the images in signal strength SNR (signal to noise ration), PSNR (peak signal noise to ratio), RMSE (root mean square error), MAE (mean absolute error) and calculated by paired t-test for use by statistics were analyzed. Scan time was half scan (4 minutes 53 seconds), the full scan (6 minutes 04 seconds). The mean measurement range (7.21 mm) of all the ROI in the brain blood vessel, was the SNR of the first C1 is completely scanned (58.66 dB), half-scan (62.10 dB), a positive correlation ($r^2=0.503$), for the second C2 SNR is completely scanned (70.30 dB), half-scan (74.67 dB) the amount of correlation ($r^2=0.575$), third C3 of a complete scan SNR (70.33 dB), half scan SNR (74.64 dB) in the amount of correlation between the It was analyzed with ($r^2=0.523$). Comparative full scan with half of SNR ($4.75{\pm}0.26dB$), PSNR ($21.87{\pm}0.28dB$), RMSE ($48.88{\pm}1.61$), was calculated as MAE ($25.56{\pm}2.2$). SNR is also applied to examine the half-scans are not many differences in the quality of the two scan methods were not statistically significant in the scan (p-value > .05) image takes less time than a full scan was used.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.6
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• pp.148-160
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• 2012

The main purpose of this paper is to deliver a climate analysis and evaluation method based on GIS by using airborne LiDAR data and Biotop type map and to provide spatial information of climate analysis and evaluation based on Biotop type Map. At first stage, the area, slope, slope length, surface, wind corridor function and width, and obstacle factors were analyzed to obtain cold/fresh air production and wind corridor evaluation. In addition, climate evaluation was derived from those two results in the second stage. Airborne LiDAR data are useful in wind corridor analysis during the study. Correlation analysis results show that ColdAir_GRD grade was highly correlated with Surface_GRD (-0.967461139) and WindCorridor_ GRD was highly correlated with Function_GRD (-0.883883476) and Obstacle_GRD (-0.834057656). Climate Evaluation GRID was highly correlated with WindCorridor_GRD (0.927554516) than ColdAir_GRD (0.855051646). Visual validations of climate analysis and evaluation results were performed by using aerial ortho-photo image, which shows that the climate evaluation results were well related with in-situ condition. At the end, we applied climate analysis and evaluation by using Biotop map and airborne LiDAR data in Gwangmyung-Shiheung City, candidate for the Bogeumjari Housing District. The results show that the aerial percentile of the 1st Grade is 18.5%, 2nd Grade is 18.2%, 3rd Grade is 30.7%, 4th Grade is 25.2%, and 5th Grade is 7.4%. This study process provided both the spatial analysis and evaluation of climate information and statistics on behalf of each Biotop type.

• The Korean Journal of Nuclear Medicine
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• v.32 no.3
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• pp.225-237
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• 1998

Purpose: We investigated the statistical methods to compose the functional brain map of human working memory and the principal factors that have an effect on the methods for localization. Materials and Methods: Repeated PET scans with successive four tasks, which consist of one control and three different activation tasks, were performed on six right-handed normal volunteers for 2 minutes after bolus injections of 925 MBq $H_2^{15}O$ at the intervals of 30 minutes. Image data were analyzed using SPM96 (Statistical Parametric Mapping) implemented with Matlab (Mathworks Inc., U.S.A.). Images from the same subject were spatially registered and were normalized using linear and nonlinear transformation methods. Significant difference between control and each activation state was estimated at every voxel based on the general linear model. Differences of global counts were removed using analysis of covariance (ANCOVA) with global activity as covariate. Using the mean and variance for each condition which was adjusted using ANCOVA, t-statistics was performed on every voxel To interpret the results more easily, t-values were transformed to the standard Gaussian distribution (Z-score). Results: All the subjects carried out the activation and control tests successfully. Average rate of correct answers was 95%. The numbers of activated blobs were 4 for verbal memory I, 9 for verbal memory II, 9 for visual memory, and 6 for conjunctive activation of these three tasks. The verbal working memory activates predominantly left-sided structures, and the visual memory activates the right hemisphere. Conclusion: We conclude that rCBF PET imaging and statistical parametric mapping method were useful in the localization of the brain regions for verbal and visual working memory.

• The Journal of Korean Academy of Prosthodontics
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• v.50 no.4
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• pp.271-278
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• 2012

Purpose: Recently implant surgical guides were used for accurate and atraumatic operation. In this study, the accuracy of two different types of surgical guides, positioning device fabricated and stereolithography fabricated surgical guides, were evaluated in four different types of tooth loss models. Materials and methods: Surgical guides were fabricated with stereolithography and positioning device respectively. Implants were placed on 40 models using the two different types of surgical guides. The fitness of the surgical guides was evaluated by measuring the gap between the surgical guide and the model. The accuracy of surgical guide was evaluated on a pre- and post-surgical CT image fusion. Results: The gap between the surgical guide and the model was $1.4{\pm}0.3mm$ and $0.4{\pm}0.3mm$ for the stereolithography and positioning device surgical guide, respectively. The stereolithography showed mesiodistal angular deviation of $3.9{\pm}1.6^{\circ}$, buccolingual angular deviation of $2.7{\pm}1.5^{\circ}$ and vertical deviation of $1.9{\pm}0.9mm$, whereas the positioning device showed mesiodistal angular deviation of $0.7{\pm}0.3^{\circ}$, buccolingual angular deviation of $0.3{\pm}0.2^{\circ}$ and vertical deviation of $0.4{\pm}0.2mm$. The differences were statistically significant between the two groups (P<.05). Conclusion: The laboratory fabricated surgical guides using a positioning device allow implant placement more accurately than the stereolithography surgical guides in dental clinic.

• The korean journal of orthodontics
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• v.41 no.5
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• pp.312-323
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• 2011

Objective: This study compared the bone thickness of the palate between lateral cephalogram and 3D model measurements. Methods: The subjects consisted of 30 adults (15 men,15 women) with a normal skeletal pattern and occlusion. The CT images were transformed to a 3D model, and were compared with the cephalometric image. Descriptive statistics for each variable were calculated. Results: In the 3D CT model, the mid-palatal area was the thickest part. It became thinner as the palate tapered laterally. In the male group, the thinnest portion was positioned 6 mm away from the mid-palate, while in the female group the thinnest portion was 8mm away from the mid-palate. Correlation analysis between the lateral cephalometric and 3D CT model revealed a significant correlation except in the mid palatal area and the area 2 mm lateral to the mid-palate in men, whereas there was a significant relationship in every area in the women. In both men and women, the highest correlation appeared in the area 8 mm lateral to the mid palate. Conclusions: Using regression analysis, an actual prediction of the bone thickness between the measured bone thickness of the lateral cephalometric radiograph and 3D model was made. This will provide useful information for mini-implant length selection when inserting into the palate.

• Korean Journal of Acupuncture
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• v.17 no.1
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• pp.47-65
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• 2000

The meridian, the meridian point and the Acupuncture-Bu-Xie(鍼灸補瀉) of oriental medicine are very important in the Department of Acupuncture and Moxibustion. Until now it has been confused at the practical use, and it showed up many transformation to the ages and many scholars. And then, I made a study of effects on the thermal changes of Sangyang($LI_1$,商陽), Igan($LI_2$,二間), Samgan($LI_3$,三間), Hapkok($LI_4$,合谷), Yanggye($LI_5$,陽谿), Kokchi($LI_{11}$,曲池), Yonghyang($LI_{20}$,迎香) following acupuncture on the Hapkok with the Rotated Acupuncture-Bu-Xie(捻轉補瀉) stimulation. This study researched into clinical statistics for 140 men who are in good health, and they are studying oriental medicine at Woosuk university in Korea. This study was covered a period of 3 months form June, 1999 to August, 1999. The objective was divided into seven groups, those are the control group(CON, N=20), the acupuncture stimulation group with non-rotation on Hapkok of left hand(A-I, N=20), the acupuncture stimulation group with non-rotation on non-meridian point(NA) of left hand(A-II, N=20), the acupuncture stimulation group with Bu-rotation(捻轉補法) on Hapkok of left hand(B-I, N=20), the acupuncture stimulation group with Bu-rotation on non-meridian point(NA) of left hand(B-II, N=20), the acupuncture stimulation group with Xie-rotation(捻轉瀉法) on Hapkok of left hand(C-I, N=20), and the acupuncture stimulation group with Xie-rotation on non-meridian point of left hand(C-II, N=20). The first, I took a picture for 140 men with the Digital infrared thermal image(D.I.T.I.). After 10 minutes, I took a second picture for each group following experimental methods, those were followed acupuncture on the Hapkok and the non-meridian point with the retentive and Rotated Acupuncture-Bu-Xie stimulation. The results are summarized as follows : 1. The thermal changes of the area which is a meridian point in the Large Intestine Meridian of the acupuncture stimulation group on Hapkok different from the control groups with significantly change. 2.The thermal changes of the area which is a meridian point in the Large Intestine Meridian of acupuncture stimulation groups on non-meridian point was not significantly different from the control group. 3. The thermal changes of the area which is a meridian point in the Large Intestine Meridian of the acupuncture stimulation group with Bu-rotation on Hapkok different from the control group with significant increase. 4. The thermal changes of the area which is a meridian point in the Large Intestine Meridian of acupuncture stimulation group with Bu-rotation on non-meridian point was not significantly different from the control group. 5. The thermal changes of the area which is a meridian point in the Large Intestine Meridian of the acupuncture stimulation group with Xie-rotation on Hapkok different from the control group with significant decrease and increase following the decreasing or increasing temperature class, and the increasing temperature class of the acupuncture stimulation group with Xie-rotation on Hapkok significantly different from the acupuncture stimulation group with Bu-rotation on Hapkok. 6. The thermal changes of the area which is a meridian point in the Large Intestine Meridian of acupuncture stimulation group with Xie-rotation on non-meridian point was not significantly different from the control group. As a conclusion, I could think that the acupuncture stimulation with Bu-rotation or Xie-rotation on Hapkok affected the thermal change of the area which is a meridian point in the Large Intestine Meridian. And then I could relate these results with the existence of the meridian and meridian point, and with the Rotated Acupuncture-Bu-Xie theory of oriental medicine.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.531-548
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• 2015

Atmospheric Motion Vector (AMV) from satellite images have shown Slow Speed Bias (SSB) in comparison with rawinsonde. The causes of SSB are originated from tracking, selection, and height assignment error, which is known to be the leading error. However, recent works have shown that height assignment error cannot be fully explained the cause of SSB. This paper attempts a new approach to examine the possibility of SSB reduction of COMS AMV by using a new target tracking algorithm. Tracking error can be caused by averaging of various wind patterns within a target and changing of cloud shape in searching process over time. To overcome this problem, Gaussian Mixture Model (GMM) has been adopted to extract the coldest cluster as target since the shape of such target is less subject to transformation. Then, an image filtering scheme is applied to weigh more on the selected coldest pixels than the other, which makes it easy to track the target. When AMV derived from our algorithm with sum of squared distance method and current COMS are compared with rawindsonde, our products show noticeable improvement over COMS products in mean wind speed by an increase of $2.7ms^{-1}$ and SSB reduction by 29%. However, the statistics regarding the bias show negative impact for mid/low level with our algorithm, and the number of vectors are reduced by 40% relative to COMS. Therefore, further study is required to improve accuracy for mid/low level winds and increase the number of AMV vectors.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.43-62
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• 2019

At one time, the anomaly detection sector dominated the method of determining whether there was an abnormality based on the statistics derived from specific data. This methodology was possible because the dimension of the data was simple in the past, so the classical statistical method could work effectively. However, as the characteristics of data have changed complexly in the era of big data, it has become more difficult to accurately analyze and predict the data that occurs throughout the industry in the conventional way. Therefore, SVM and Decision Tree based supervised learning algorithms were used. However, there is peculiarity that supervised learning based model can only accurately predict the test data, when the number of classes is equal to the number of normal classes and most of the data generated in the industry has unbalanced data class. Therefore, the predicted results are not always valid when supervised learning model is applied. In order to overcome these drawbacks, many studies now use the unsupervised learning-based model that is not influenced by class distribution, such as autoencoder or generative adversarial networks. In this paper, we propose a method to detect anomalies using generative adversarial networks. AnoGAN, introduced in the study of Thomas et al (2017), is a classification model that performs abnormal detection of medical images. It was composed of a Convolution Neural Net and was used in the field of detection. On the other hand, sequencing data abnormality detection using generative adversarial network is a lack of research papers compared to image data. Of course, in Li et al (2018), a study by Li et al (LSTM), a type of recurrent neural network, has proposed a model to classify the abnormities of numerical sequence data, but it has not been used for categorical sequence data, as well as feature matching method applied by salans et al.(2016). So it suggests that there are a number of studies to be tried on in the ideal classification of sequence data through a generative adversarial Network. In order to learn the sequence data, the structure of the generative adversarial networks is composed of LSTM, and the 2 stacked-LSTM of the generator is composed of 32-dim hidden unit layers and 64-dim hidden unit layers. The LSTM of the discriminator consists of 64-dim hidden unit layer were used. In the process of deriving abnormal scores from existing paper of Anomaly Detection for Sequence data, entropy values of probability of actual data are used in the process of deriving abnormal scores. but in this paper, as mentioned earlier, abnormal scores have been derived by using feature matching techniques. In addition, the process of optimizing latent variables was designed with LSTM to improve model performance. The modified form of generative adversarial model was more accurate in all experiments than the autoencoder in terms of precision and was approximately 7% higher in accuracy. In terms of Robustness, Generative adversarial networks also performed better than autoencoder. Because generative adversarial networks can learn data distribution from real categorical sequence data, Unaffected by a single normal data. But autoencoder is not. Result of Robustness test showed that he accuracy of the autocoder was 92%, the accuracy of the hostile neural network was 96%, and in terms of sensitivity, the autocoder was 40% and the hostile neural network was 51%. In this paper, experiments have also been conducted to show how much performance changes due to differences in the optimization structure of potential variables. As a result, the level of 1% was improved in terms of sensitivity. These results suggest that it presented a new perspective on optimizing latent variable that were relatively insignificant.

• Journal of Nutrition and Health
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• v.53 no.6
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• pp.613-628
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• 2020

Purpose: The purpose of the study was to identify the health anxiety issues of middle-aged women, their health-promoting behavior, and quality of life as well as to examine the relationship between these variables. Methods: The participants were 334 women in Jeonbuk area. Demographic characteristics, the status of health anxiety, health-promoting behavior, and life quality was assessed using a self-administered questionnaire. The data were analyzed using a t-test, analysis of variance, Duncan test, and hierarchical regression analysis with SPSS ver. 24.0. Results: The score for health anxiety was 37.64 points out of a possible score of 60, and the score for health-promoting behavior was 79.18 points out of a possible score of 115. The score for the quality of life was 101.18 points out of a possible score of 150. The health anxiety scores showed significant differences, varying as per body mass index (BMI) (p < 0.05), income (p < 0.05), occupation (p < 0.05), disease (p < 0.05), satisfaction with weight (p < 0.05), and interest in weight control (p < 0.05). The health-promoting behavior showed significant differences according to age (p < 0.01), BMI (p < 0.01), income (p < 0.05), menses (p < 0.05), intake of dietary supplements (p < 0.05), perception of body image (p < 0.05), and satisfaction with weight (p < 0.05). The quality of life showed significant differences according to BMI (p < 0.05), income (p < 0.01), education level (p < 0.05), occupation (p < 0.05), disease (p < 0.05), and satisfaction with weight (p < 0.05). Regression analysis showed that health-promoting behavior was the most influential variable on the quality of life, followed by disease and health anxiety. Conclusion: Based on these results, we conclude that it is necessary to consider educational programs on improving the quality of life of middle-aged women according to the health anxiety levels and health-promoting behavior.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.258-266
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• 2023

This study analyzed methodologies for estimating carbon stocks of perennial woody crops and the research cases in overseas countries. As a result, we found that Australia, Bulgaria, Canada, and Japan are using the stock-difference method, while Austria, Denmark, and Germany are estimating the change in the carbon stock based on the gain-loss method. In some overseas countries, the researches were conducted on estimating the carbon stock change using image data as tier 3 phase beyond the research developing country-specific factors as tier 2 phase. In South Korea, convergence studies as the third stage were conducted in forestry field, but advanced research in the agricultural field is at the beginning stage. Based on these results, we suggest directions for the following four future researches: 1) securing national-specific factors related to emissions and removals in the agricultural field through the development of allometric equation and carbon conversion factors for perennial woody crops to improve the completeness of emission and removals statistics, 2) implementing policy studies on the cultivation area calculation refinement with fruit tree-biomass-based maturity, 3) developing a more advanced estimation technique for perennial woody crops in the agricultural sector using allometric equation and remote sensing techniques based on the agricultural and forestry satellite scheduled to be launched in 2025, and to establish a matrix and monitoring system for perennial woody crop cultivation areas in the agricultural sector, Lastly, 4) estimating soil carbon stocks change, which is currently estimated by treating all agricultural areas as one, by sub-land classification to implement a dynamic carbon cycle model. This study suggests a detailed guideline and advanced methods of carbon stock change calculation for perennial woody crops, which supports 2050 Carbon Neutral Strategy of Ministry of Agriculture, Food, and Rural Affairs and activate related research in agricultural sector.