• Journal of Korean Neurosurgical Society
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• v.63 no.3
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• pp.386-396
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• 2020

Objective : To generate synthetic spine magnetic resonance (MR) images from spine computed tomography (CT) using generative adversarial networks (GANs), as well as to determine the similarities between synthesized and real MR images. Methods : GANs were trained to transform spine CT image slices into spine magnetic resonance T2 weighted (MRT2) axial image slices by combining adversarial loss and voxel-wise loss. Experiments were performed using 280 pairs of lumbar spine CT scans and MRT2 images. The MRT2 images were then synthesized from 15 other spine CT scans. To evaluate whether the synthetic MR images were realistic, two radiologists, two spine surgeons, and two residents blindly classified the real and synthetic MRT2 images. Two experienced radiologists then evaluated the similarities between subdivisions of the real and synthetic MRT2 images. Quantitative analysis of the synthetic MRT2 images was performed using the mean absolute error (MAE) and peak signal-to-noise ratio (PSNR). Results : The mean overall similarity of the synthetic MRT2 images evaluated by radiologists was 80.2%. In the blind classification of the real MRT2 images, the failure rate ranged from 0% to 40%. The MAE value of each image ranged from 13.75 to 34.24 pixels (mean, 21.19 pixels), and the PSNR of each image ranged from 61.96 to 68.16 dB (mean, 64.92 dB). Conclusion : This was the first study to apply GANs to synthesize spine MR images from CT images. Despite the small dataset of 280 pairs, the synthetic MR images were relatively well implemented. Synthesis of medical images using GANs is a new paradigm of artificial intelligence application in medical imaging. We expect that synthesis of MR images from spine CT images using GANs will improve the diagnostic usefulness of CT. To better inform the clinical applications of this technique, further studies are needed involving a large dataset, a variety of pathologies, and other MR sequence of the lumbar spine.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.691-698
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• 2003

We extend the sue of the method of least square to develop a recursive algorithm for the design of adaptive transversal filters such that, given the least-square estimate of this vector of the filter at iteration n-l, we may compute the updated estimate of this vector at iteration n upon the arrival of new data. We begin the development of the RLS algorithm by reviewing some basic relations that pertain to the method of least squares. Then, by exploiting a relation in matrix algebra known as the matrix inversion lemma, we develop the RLS algorithm. An important feature of the RLS algorithm is that it utilizes information contained in the input data, extending back to the instant of time when the algorithm is initiated. In this paper, we propose new tap weight updated RLS algorithm in adaptive transversal filter with data-recycling buffer structure. We prove that convergence speed of learning curve of RLS algorithm with data-recycling buffer is faster than it of exiting RLS algorithm to mean square error versus iteration number. Also the resulting rate of convergence is typically an order of magnitude faster than the simple LMS algorithm. We show that the number of desired sample is portion to increase to converge the specified value from the three dimension simulation result of mean square error according to the degree of channel amplitude distortion and data-recycle buffer number. This improvement of convergence character in performance, is achieved at the B times of convergence speed of mean square error increase in data recycle buffer number with new proposed RLS algorithm.

• School Mathematics
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• v.15 no.2
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• pp.289-314
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• 2013

Achievement profile by attribute in Korean students' mathematics was analyzed by applying cognitive diagnostic model, which is the newest measurement theory, to 2011 NAEA(National Assessment of Educational Assessment) results. The results are as follows. As the level of school is higher from 6th grade, 9th grade to 11th grade, the percentage of students mastering cognitive attribute 9(expressions using picture, table, graph, formula, symbol, writing, etc) drastically declined from 78%, 35% to 26%. It is necessary to have learning strategies to reinforce their abilities of expressing table, graph, etc. that higher graders in mathematics are more vulnerable to. Next, the property of mastering cognitive attributes according to gender, multi-cultural family was analyzed. In terms of mathematics, the percentage of girls mastering most of the attribute generally is higher than that of boys from 6th grade to 9th grade, however, boys show higher mastery in almost attributes than girls in the 11th grade. Compared to boys, the part where girls have the most trouble is attribute 9 in mathematics(expressions using picture, table, graph, formula, symbol, writing, etc). As international marriage, influx of foreign workers, etc. increase, the number of students from Korea's multi-cultural families is expected to be higher, therefore, identifying the characteristics of their educational achievement is significant in reinforcing Korea's basic achievement. In mathematics, gap of mastery level of attributes between multi-cultural group and ordinary group is more severe in higher grade and the type of multi-cultural group that needs supports for improving achievement most urgently changed in 6th grade, 9th grade and 11th grade respectively. In the 6th and 11th grade, migrant students from North Korea show the lowest level of mastering attributes, however, in the 9th grade, the mastery rate of immigrant students is lowest. Therefore, there is an implication that supporting plans for improving achievement of students from multi-cultural family should establish other strategies based on the characteristics of school level.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.318-326
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• 2011

The purpose of this study is to investigate whether standardized patient(SP) can be used as a reliable examiner in Objective Structured Clinical Examination(OSCE). 4 SPs and 4 faculties who have more than 2 years experience of OSCE scoring were selected. For 1 assignment 2 members of faculty and 2 SPs were designated as raters. SPs were educated for assessing 2 technical skills, male Foley catheter insertion and wound dressing, for 8 hours (4 hours / day, each topic). The definition, method, cautions and complications for each of procedural skills were covered in the education. Theoretical lectures, video learning, faculty demonstration and practical training on mannequins were employed. The 8 raters were standardized for an hour with simulated OSCE scoring using previous videos on the day before the OSCE. Each assessment was composed of 14 checklists and 1 global rate. The allotted time for each assignment was 5minutes and for evaluation time 2 minutes per student. The evaluation from the faculty and SPs were compared and analyzed with the GENOVA program. The overall generalizability coefficient (G coefficient) was 0.839 from two cases of OASTS. The reliability of the raters was high, 0.946. The inter-rater agreement between faculty group and SP group was 0.949 for checklist and 0.908 for global rating. Therefore SPs can play a role of raters in OSCE for procedural skills, if they are given the appropriate training.

• Journal of KIISE:Software and Applications
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• v.35 no.3
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• pp.197-206
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• 2008

In the mobile Internet environment, frequent communications between a mobile device and a content server are required for searching or downloading learning materials. In this paper, we propose an efficient prefetching technique to reduce the network cost and to improve the communication efficiency in the mobile dictionary. Our prefetching-based approach can be explained as follows. First, we propose an overall framework for the prefetching-based mobile dictionary. Second, we present a systematic way of determining the amount of prefetching data for each of packet-based and flat-rate billing cases. Third, by focusing on the English-Korean mobile dictionary for middle or high school students, we propose an intuitive method of determining the words to be prefetched in advance. Fourth, based on these determination methods, we propose an efficient prefetching algorithm. Fifth, through experiments, we show the superiority of our prefetching-based method. From this approach, we can summarize major contributions as follows. First, to our best knowledge, this is the first attempt to exploit prefetching techniques in mobile applications. Second, we propose a systematic way of applying prefetching techniques to a mobile dictionary. Third, using prefetching techniques we improve the overall performance of a network-based mobile dictionary. Experimental results show that, compared with the traditional on-demand approach, our prefetching based approach improves the average performance by $9.8%{\sim}33.2%$. These results indicate that our framework can be widely used not only in the mobile dictionary but also in other mobile Internet applications that require the prefetching technique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.572-578
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• 2020

The stock market is affected by unexpected factors, such as politics, society, and natural disasters, as well as by corporate performance and economic conditions. In recent days, artificial intelligence has become popular, and many researchers have tried to conduct experiments with that. Our study proposes an experiment using not only stock-related data but also other various economic data. We acquired a year's worth of data on stock prices, the percentage of foreigners, interest rates, and exchange rates, and combined them in various ways. Thus, our input data became diversified, and we put the combined input data into a nonlinear autoregressive network with exogenous inputs (NARX) model. With the input data in the NARX model, we analyze and compare them to the original data. As a result, the model exhibits a root mean square error (RMSE) of 0.08 as being the most accurate when we set 10 neurons and two delays with a combination of stock prices and exchange rates from the U.S., China, Europe, and Japan. This study is meaningful in that the exchange rate has the greatest influence on stock prices, lowering the error from RMSE 0.589 when only closing data are used.

• The Journal of the Acoustical Society of Korea
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• v.14 no.2
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• pp.101-112
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• 1995

In order to construct a feature map-based phoneme classification system for speech recognition, two procedures are usually required. One is clustering and the other is labeling. In this paper, we present a phoneme classification system based on the Kohonen's Self-Organizing Feature Map (SOFM) for clusterer and labeler. It is known that the SOFM performs self-organizing process by which optimal local topographical mapping of the signal space and yields a reasonably high accuracy in recognition tasks. Consequently, SOFM can effectively be applied to the recognition of phonemes. Besides to improve the performance of the phoneme classification system, we propose the learning algorithm combined with the classical K-mans clustering algorithm in fine-tuning stage. In order to evaluate the performance of the proposed phoneme classification algorithm, we first use totaly 43 phonemes which construct six intra-class feature maps for six different phoneme classes. From the speaker-dependent phoneme classification tests using these six feature maps, we obtain recognition rate of $87.2\%$ and confirm that the proposed algorithm is an efficient method for improvement of recognition performance and convergence speed.

• Korea journal of population studies
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• v.23 no.2
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• pp.113-141
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• 2000

The aim of this paper is to project the state of the labor farce and employment in Korea from 2000 to 2005. The labor market in Korea is experiencing significant changes with the rapid development of Information and Telecommunication Technology (ICT) and the transition of the Korean economy into a knowledge-based economy. On the labor supply side, it is expected that the growth of the labor force will be sluggish; baby boomers will become the middle-aged, while the proportion of senior citizens, the highly educated and the female labor force will grow fast. These changes will alter the human resources management system in business sectors. Moreover, the permanent employment relationship, the hierarchy system and the seniority-based wage system are all expected to change. On the labor demand side, the employment share in highly skilled. knowledge-intensive industries will grow faster than the rest of the economy in tandem with the quickly growing output share of these industries. Especially, more jobs will be created in the ICT industries. The proportion of labor in highly skilled and professional occupations will also grow faster than in other occupations. At the same time, the employment share of female workers will grow more quickly than that of the male workers. These changes, however, may worsen income inequalities and/or increase the unemployment rate when workers do not have the suitable skills or knowledge required by the knowledge-based economy. To avoid this, it is necessary for the government to build up a lifetime learning system for workers.

• Journal of the Korean Society of School Health
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• v.12 no.2
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• pp.321-337
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• 1999

The purpose of this study was to obtain basic data for the prevention and control of adolescent back pain through analyzing connections between study environments and physical posture. The subjects were 960 male general high school students in the Chonju area and the data were collected by a self-reported questionnaire from Mar. 17 to Mar. 22, 1999. The collected data were analyzed by a frequency, chi-square and t-test using an SPSS program. The results are as follows; 1) The experience rate of back pain perceived by subjects was 67.5% and by each grade: 1st-27.5%, 2nd-35.4%, 3rd-37.1%. The relationship between grades and the experience of back pain didn't show any significant difference. 2) The causes of back pain perceived by subjects such as 'postures are not good' was 56.7%, 'sitting too much time in a chair' was 39.1%, and 'too severe exercise' was 32.4%. 27.8% had back pain first during the 3rd grade of middle school, and 23.9% had it first during the 1st grade of high school. 3) Intensity of subjects' back pain spread from 'moderate' at 49.6%, to 'severe' at 16.4%. Concerning the frequency of back pain, 58.6% said it was 'irregalar'. 4) Among interventions to deal with back pain: 'move by exercising my back or ask friends to beat my back' was 41.0%, 'just bear it' was 23.1%, and at home 'don't have 'any treatment' was ranked first, at 54.9%. 5) The relationship between subjects' general characteristics and back pain experiences: height (t=-1.99, P=.046), sitting/height (t=-2.61, P=.009), self-perceived condition of health (${\chi}^2=23.530$, P=.000), family history (${\chi}^2=43.903$, P=.000) showed significant difference, but the kinds of transportation, sleeping postures, sleeping method and smoking didn't show significant differences. 6) The relationship between subjects' learning environment and back pain experiences, the height of students' desk and chair showed significant difference (${\chi}^2=23.054$, P=.000), but the sitting time didn't show significant difference. 7) The relationship between the characteristics of subjects' physical postures and back pain experiences: standing postures (${\chi}^2=15.105$, P=.001), and sitting postures (${\chi}^2=20.264$X2, P=.001) showed significant difference, but lifting postures didn't show significant difference.

• Korean Journal of Social Welfare
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• v.68 no.1
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• pp.225-248
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• 2016

This study explores the effects on development of poor children by community-based orchestra educational activities and the orchestra educational activities factors for promoting the effects using longitudinal data are those collected for "The Evaluation of the Impact of Our Neighborhood Orchestra on Children's Learning" made by the Seoul Philharmonic Orchestra. For these purposes, this study employed a latent growth model analysis of the factors such as depression, aggressive behavior, communality and interpersonal relationship of development of poor children and evaluation, satisfaction, outsiders'attention and participation of facilitative factors. The result shows that they displayed significantly positive development in depression, aggressive behavior, and interpersonal relationship. It appears that the evaluation on music achievement had a positive impact on the rate of change in communality, while the evaluation on attitude had an impact in the initial value of depression, aggressive behavior, and communality, also the sense of satisfaction had a positive impact on the initial value of communality and interpersonal relationship in conditional models. And parents' attention and participation had a negative impact on the initial value of aggressive behavior, while the attention and participation of the community showed a positive impact on the initial value of depression and aggressive behavior. Based on these results, this study attempted to broaden the understanding of the development of poor children taking part in orchestra-based educational activities and provide a practical basis for social workers' direct invention, and look for new ways by shedding light on the merits of the cultural/art education of poor children that engage in the community-based orchestra educational activities.