• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.16 no.1
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• pp.1-32
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• 2003

Objectives: This study was carried out to analyze and understand the trends of research papers published In the Journal of Oriental Medical Surgery？phthalmology & Otolaryngology Society(JOMSOOS). Methods: We studied the 308 research papers that had been published in JOMSOOS from 1988 Vol. 1. No. 1. to 2002 Vol. 15. No. 2. Our study was developed through the four stages in order to analyze the papers; 1) we analyzed all the papers overall to classify them into three categories; original article. review article and case report. 2) we classified the original articles in terms of methodology. 3) we also analyzed the case reports according to the sort of disease each paper dealt with. 4) we had another statistical approach to each paper to figure out the distribution of diagnoses in detail. Results: We have got the following outcomes from our analysis of the papers in terms of the four stages. 1. Overall Analysis. 1) Classification of 308 research papers between 1988 and 2002: 137 original articles(44.48$\%$), 111 review articles(36.04$\%$), 56 case reports(18.18$\%$). 2) Used language: Korean(99.03$\%$). English(0.97$\%$). 3) The Number of Authors: 2 persons(42.86$\%$). 3 persons(29.87$\%$), 1 person(14.61$\%$). 2. Original Article Analysis 1) Classification of 137 original articles in terms of methodology: 90 experimental studies(65.69$\%$)46 descriptive studies(33.58$\%$), 1 analytic study(0.73$\%$). 2) Classification of the original articles according to the use of statistical methods: No statistical methods(36.42$\%$), Descriptive methods only(1.99$\%$), Not defined(23.18$\%$), t-test(24.50$\%$), ANOVA(3.97$\%$), Multiple comparison(2.65$\%$), Non-parametric test(2.65$\%$), Other methods(1.32$\%$). 3) Classification of 46 descriptive articles in terms of diseases: otorhinolaryngology(43.48$\%$), dermatology(23.91$\%$), ophthalmology(13.04$\%$), facial palsy(13.04$\%$). 4) Classification of descriptive articles in terms of the number of patients: the highest was 'more than 26 but less than 50 persons'(19 articles - 41.30$\%$). 5) Classification of descriptive articles in terms of the period for patients observation: the highest was the time 'more than 9 but less than 12 months(34.78$\%$)' Out of the 34.78$\%$, the number of articles with the patients observed for more than 12 months was 13(28.26$\%$). 3. Case Report Analysis 1) Classification of 56 case reports in terms of the sort of disease: dermatology(44.64$\%$), ophthalmology(19.64$\%$), otorhinolaryngology(14.29$\%$), facial palsy(8.93$\%$). 2) Classification in terms of the number of patients: 1 person(50$\%$), 3 persons(16.07$\%$), 2 persons(14.29$\%$). 4. Diagnosis Distribution of Each Disease. 1) Studies regarding ophthalmology : the percentage of 'strabismus' cases was the highest(33.33$\%$). 2) Studies regarding otorhinolaryngology : nasal inflammation(34.48$\%$), tinnitus(20.69$\%$). 3) Studies regarding dermatology: the percentage of 'allergic skin disease' was the highest(33.33$\%$). Conclusions: We analyzed the trends of research papers that have been published in JOMSOOS in detail. We came to understand the trends of the research through this study. However, we acknowledge that we only adopted the quantitative method out of various possible analysis methods. For further studies, we strongly urge to adopt the qualitative methods as well.

• (The) Korean Journal of Educational Psychology
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• v.23 no.3
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• pp.645-663
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• 2009

The purpose of this study is to develop and verify a Korean Diagnostic Scale of Multiple Intelligence(MI), which will be an alternative test to avoid problems with former Shearer's MI test and to adopt H. Gardner's suggestions to develop MI assessment. The test is developed 5 types; kindergartner, elementary lower grader, elementary upper grader, middle schooler, high schooler test. A form of test is diversified with 3 types; multiple-choice items for accomplishment, true or false items for ability, and self-reported items with likert scale for interest and ability. According to H. Gardner's suggestions, we have tried to reanalyze key component of MI, analyze an overlapping or hierarchical relationship between intelligences, develop intelligences-fair items, diversify form of item. We have developed a final standardized test through a primary, secondary preliminary-test analysis, and sampled 5,585 students by age, gender, and regional groups. As a result of this sampling test, we can get a norm score and compare individuals with other's score relatively. To verify this test, we analyzed behavior observation, mean, standard deviation, a percentage of correct answers, reliability of each test type, correlation between intelligence scales, Kruskal-Wallis test of mean rank of career choice by intelligences. As a result of correlation analysis between sub-intelligence scales, we can conclude that this MI test is satisfied with intelligence independent assumption. Besides, as non-parametric statistics test(Kruskal-Wallis) of career choice by intelligences, we can identify that MI is related with domain of career choice. This test is not a linguistic and logical-mathematical biased test but a intelligences-fair test. It makes us compare individual's potential with a norm score. Besides, it could be useful as a means of educational prescription or counsel in comparison with ability, interest, and accomplishment of individual. But this test is limited to do factor or correlation analysis between types of sub-test, because items are minimized for a time-constraint and a heavy burden of test receiver. But if it could be tested with increased items by two sessions, further research could be expected to get over this constraints and do a further validation analysis.

• Journal of the Korean Geotechnical Society
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• v.37 no.3
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• pp.19-30
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• 2021

The presence of the hydrate-bearing sediments in Ulleung Basin of South Korea has been confirmed from previous studies. Researches on gas production methods from the hydrate-bearing sediments have been conducted worldwide. As production mechanism is a complex phenomenon in which thermal, hydraulic, and mechanical phenomena occur simultaneously, it is difficult to accurately conduct the productivity and stability analysis of hydrate bearing sediments through lab-scale experiments. Thus, the importance of numerical analysis in evaluating gas productivity and stability of hydrate-bearing sediments has been emphasized. In this study, the numerical parametric analysis was conducted to investigate the effects of the bottom hole pressure and the depressurization rate on the gas productivity and stability of hydrate-bearing sediments during the depressurization method. The numerical analysis results confirmed that as the bottom hole pressure decreases, the productivity increases and the stability of sediments deteriorates. Meanwhile, it was shown that the depressurization rate did not largely affect the productivity and stability of the hydrate-bearing sediments. In addition, sensitivity analysis for gas productivity and stability of the sediments were conducted according to the depressurization rate in order to establish a production strategy that prevents sand production during gas production. As a result of the analysis, it was confirmed that controlling the depressurization rate from a low value to a high value is effective in securing the stability. Moreover, during gas production, the subsidence of sediments occurred near the production well, and ground heave occurred at the bottom of the production well due to the pressure gradient. From these results, it was concluded that both the productivity and stability analyses should be conducted in order to determine the bottom hole pressure when producing gas using the depressurization method. Additionally, the stress analysis of the production well, which is induced by the vertical displacements of sediments, should be evaluated.

• Journal of Dental Rehabilitation and Applied Science
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• v.38 no.1
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• pp.18-25
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• 2022

Purpose: This study aimed to evaluate the color stability and antibacterial properties of the surface of polyethyl methacrylate (PEMA) resin with zirconia nanoparticles added. Materials and Methods: The control group was pure PEMA resin, and the experiment group was PEMA resin 15 mm in diameter and 2.5 mm in thickness disk-shaped specimens with 2, 4 and 8 w/v% of zirconia nanoparticles added, which were respectively divided into Group Z2, Group Z4, and Group Z8. After analyzing the surface roughness and color stability of the specimens, their antibacterial properties were evaluated using Porphyromonas gingivalis (P. gingivalis). The Statistical analysis was performed using when normality was met in the Shapiro-Wilk test, one-way ANOVA was used to test parameters, and Tukey's test was used as a post hoc test. When normality was not met, the Kruskal-Wallis test, a non-parametric test was used (P < 0.05). Results: The surface roughness measurement found that there was no significant difference between the experimental and control groups. The color stability evaluation showed that the Z2, Z4, and Z8 groups were within the color range of natural teeth. The adhesion of P. gingivalis was evaluated to be significantly reduced in Group Z2 compared to the control group (P < 0.05). In the Z2 group, Z4 group, and Z8 group, dead cells bacteria than the control group were observed. Conclusion: In conclusion, PEMA resin with zirconia nanoparticles added was within the range of natural teeth in color and reduced the adhesion of P. gingivalis.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.209-223
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• 2023

This study was conducted to evaluate the effectiveness of a polar literacy education program for elementary and middle school students, and to derive implications for new education to respond to climate change. We developed modular education programs based on the seven principles of polar literacy established by the Polar-ICE team. We divided them into two courses, one emphasizing science concepts and another emphasizing humanities and sociological issues. We then selected and structured detailed programs suitable for the two courses. These two courses were applied to 26 elementary and middle school students for approximately 69 hours in a Saturday science class hosted by the Department of Science Education at a university in Seoul. The 26 students were divided into three groups. Two groups completed the science education program for polar literacy and a humanities and social studies education program for polar literacy, respectively. The third group, the control group, received general science education unrelated to polar literacy. Before and after running the programs, all three groups responded to a polar literacy test and questionnaires that used vocabulary and presented scenes associated with polar regions. The test results were expressed using Wilcoxon signed ranks, which is a non-parametric test method, and improvements made upon completion of the program were analyzed. From a cognitive aspect, all three groups showed improvement after completing the program in the knowledge area; however, the experimental groups showed a greater degree of improvement than the control group, and there was a clear difference in the contents or materials explicitly covered. From an affective aspect, the difference between before and after the program was minor, but the group that focused on humanities and social issues showed a statistically significant improvement. Regarding changes in polar imagery, the two experimental groups tended to diverge from monotonous images to more diverse images compared to the control group. Based on the above results, we suggested methods to increase the effectiveness of polar literacy education programs, the importance of polar literacy as appropriate material for scientific thinking and earth system education, measures to improve attitudes related to the polar region, and the need to link to school curriculums.

• The Korean Journal of Nuclear Medicine
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• v.39 no.6
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• pp.413-420
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• 2005

Purpose: Neuroreceptor PET studies require 60-120 minutes to complete and head motion of the subject during the PET scan increases the uncertainty in measured activity. In this study, we investigated the effects of the data-driven head mutton correction on the evaluation of endogenous dopamine release (DAR) in the striatum during the motor task which might have caused significant head motion artifact. Materials and Methods: $[^{11}C]raclopride$ PET scans on 4 normal volunteers acquired with bolus plus constant infusion protocol were retrospectively analyzed. Following the 50 min resting period, the participants played a video game with a monetary reward for 40 min. Dynamic frames acquired during the equilibrium condition (pre-task: 30-50 min, task: 70-90 min, post-task: 110-120 min) were realigned to the first frame in pre-task condition. Intra-condition registrations between the frames were performed, and average image for each condition was created and registered to the pre-task image (inter-condition registration). Pre-task PET image was then co-registered to own MRI of each participant and transformation parameters were reapplied to the others. Volumes of interest (VOI) for dorsal putamen (PU) and caudate (CA), ventral striatum (VS), and cerebellum were defined on the MRI. Binding potential (BP) was measured and DAR was calculated as the percent change of BP during and after the task. SPM analyses on the BP parametric images were also performed to explore the regional difference in the effects of head motion on BP and DAR estimation. Results: Changes in position and orientation of the striatum during the PET scans were observed before the head motion correction. BP values at pre-task condition were not changed significantly after the intra-condition registration. However, the BP values during and after the task and DAR were significantly changed after the correction. SPM analysis also showed that the extent and significance of the BP differences were significantly changed by the head motion correction and such changes were prominent in periphery of the striatum. Conclusion: The results suggest that misalignment of MRI-based VOI and the striatum in PET images and incorrect DAR estimation due to the head motion during the PET activation study were significant, but could be remedied by the data-driven head motion correction.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.1
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• pp.9-15
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• 2007

Purpose: Repetitive transcranial magnetic stimulation (rTMS) has recently been clinically applied in the treatment of drug resistant depressed patients. There are mixed findings about the efficacy of rTMS on depression. Furthermore, the influence of rTMS on the physiology of the brain is not clear. We prospectively evaluated changes of regional cerebral blood flow (rCBF) between pre- and post-rTMS treatment in patients with drug resistant depression. Materials and Methods: Twelve patients with drug-resistant depression (7 male, 5 female; age range: $19{\sim}52$ years; mean age: $29.3{\pm}9.3$ years) were given rTMS on right prefrontal lobe with low frequency (1 Hz) and on left prefrontal lobe with high frequency (20 Hz), with 20-minute-duration each day for 3 weeks. Tc-99m ECD brain perfusion SPECT was obtained before and after rTMS treatment. The changes of cerebral perfusion were analyzed using statistical parametric mapping (SPM; t=3.14, uncorrected p<0.01, voxel=100). Results: Following areas showed significant increase in rCBF after 3 weeks rTMS treatment: the cingulate gyrus, fusiform gyrus of right temporal lobe, precuneus, and left lateral globus pallidus. Significant decrement was noted in: the precental and middle frontal gyrus of right frontal lobe, and fusiform gyrus of left occipital lobe. Conclusion: Low-frequency rTMS on the right prefrontal cortex and high-frequency rTMS on the left prefrontal cortex for 3 weeks as an add-on regimen have increased and decreased rCBF in the specific brain regions in drug-resistant depressed patients. Further analyses correlating clinical characteristics and treatment paradigm with functional imaging data may be helpful in clarifying the pathophysiology of drug-resistant depressed patients.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.1
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• pp.32-36
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• 2016

Purpose In nuclear medicine examination, $^{131}I$ is widely used in nuclear medicine examination such as diagnosis, treatment, and others of thyroid cancer and other diseases. $^{131}I$ conducts examination and treatment through emission of ${\gamma}$ ray and ${\beta}^-$ ray. Since $^{131}I$ (364 keV) contains more energy compared to $^{99m}Tc$ (140 keV) although it displays high integrated rate and enables quick discharge through kidney, the objective of this study lies in comparing the difference in exposure dose of $^{131}I$ before and after wearing apron when handling $^{131}I$ with focus on 3 elements of external exposure protection that are distance, time, and shield in order to reduce the exposure to technicians in comparison with $^{99m}Tc$ during the handling and administration process. When wearing apron (in general, Pb 0.5 mm), $^{99m}Tc$ presents shield of over 90% but shielding effect of $^{131}I$ is relatively low as it is of high energy and there may be even more exposure due to influence of scattered ray (secondary) and bremsstrahlung in case of high dose. However, there is no special report or guideline for low dose (74 MBq) high energy thus quantitative analysis on exposure dose of technicians will be conducted based on apron wearing during the handling of $^{131}I$. Materials and Methods With patients who visited Department of Nuclear Medicine of our hospital for low dose $^{131}I$ administration for thyroid cancer and diagnosis for 7 months from Jun 2014 to Dec 2014 as its subject, total 6 pieces of TLD was attached to interior and exterior of apron placed on thyroid, chest, and testicle from preparation to administration. Then, radiation exposure dose from $^{131}I$ examination to administration was measured. Total procedure time was set as within 5 min per person including 3 min of explanation, 1 min of distribution, and 1 min of administration. In regards to TLD location selection, chest at which exposure dose is generally measured and thyroid and testicle with high sensitivity were selected. For preparation, 74 MBq of $^{131}I$ shall be distributed with the use of $2m{\ell}$ syringe and then it shall be distributed after making it into dose of $2m{\ell}$ though dilution with normal saline. When distributing $^{131}I$ and administering it to the patient, $100m{\ell}$ of water shall be put into a cup, distributed $^{131}I$ shall be diluted, and then oral administration to patients shall be conducted with the distance of 1m from the patient. The process of withdrawing $2m{\ell}$ syringe and cup used for oral administration was conducted while wearing apron and TLD. Apron and TLD were stored at storage room without influence of radiation exposure and the exposure dose was measured with request to Seoul Radiology Services. Results With the result of monthly accumulated exposure dose of TLD worn inside and outside of apron placed on thyroid, chest, and testicle during low dose $^{131}I$ examination during the research period divided by number of people, statistics processing was conducted with Wilcoxon Signed Rank Test using SPSS Version. 12.0K. As a result, it was revealed that there was no significant difference since all of thyroid (p = 0.345), chest (p = 0.686), and testicle (p = 0.715) were presented to be p > 0.05. Also, when converting the change in total exposure dose during research period into percentage, it was revealed to be -23.5%, -8.3%, and 19.0% for thyroid, chest, and testicle respectively. Conclusion As a result of conducting Wilcoxon Signed Rank Test, it was revealed that there is no statistically significant difference (p > 0.05). Also, in case of calculating shielding rate with accumulate exposure dose during 7 months, it was revealed that there is irregular change in exposure dose for inside and outside of apron. Although the degree of change seems to be high when it is expressed in percentage, it cannot be considered a big change since the unit of accumulated exposure dose is in decimal points. Therefore, regardless of wearing apron during high energy low dose $^{131}I$ administration, placing certain distance and terminating the administration as soon as possible would be of great assistance in reducing the exposure dose. Although this study restricted $^{131}I$ administration time to be within 5 min per person and distance for oral administration to be 1m, there was a shortcoming to acquire accurate result as there was insufficient number of N for statistics and it could be processed only through non-parametric method. Also, exposure dose per person during lose dose $^{131}I$ administration was measured with accumulated exposure dose using TLD rather than through direct-reading exposure dose thus more accurate result could be acquired when measurement is conducted using electronic dosimeter and pocket dosimeter.