• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.769-777
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• 1998

In this study, various time series are analyzed to check nonlinearities of the data. The nonlinearity of a system can be investigated by testing the randomness of the time series data. To test the randomness, four nonparametric test statistics and a new test statistic, called the BDS statistic are used and the results and the results are compared. The Brock, Dechert, and Scheinkman (BDS) statistic is originated from the statistical properties of the correlation integral which is used for searching for chaos and has been shown very effective in distinguishing nonlinear structures in dynamic systems from random structures. As a result of application to linear and nonlinear models which are well known, the BDS statistic is found to be more effective than nonparametric test statistics in identifying nonlinear structure in the time series. Hydrologic time series data are fitted to ARMA type models and the statistics are applied to the residuals. The results show that the BDS statistic can distinguish chaotic nonlinearity from randomness and that the BDS statistic can also be used for verifying the validity of the fitted model.

• Journal of Industrial Convergence
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• v.20 no.4
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• pp.47-55
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• 2022

The study was conducted to identify the effectiveness of nursing skills practice using VR(Virtual Reality) on competency and confidence in nursing skills, learning self-efficacy, and satisfaction of nursing students. This study used a randomized controlled trial design. The 35 patients in the experimental group took nursing skills practice using VR and The 35 patients in the control group took fundamental nursing skills practice. The data were conducted on confidence in nursing skills, learning self-efficacy, satisfaction, and nursing skills' competency. The collected data were analyzed using the SPSS WIN 23.0 program. As a result of the study, there were no significant differences between the experimental and control groups in competency and confidence in nursing skills, learning self-efficacy, and satisfaction. However, confidence in nursing skills and learning self-efficacy increased after practice in both groups. The results indicate that nursing skills practice using VR was effective in improving nursing skills.

• School Mathematics
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• v.19 no.4
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• pp.691-712
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• 2017

It is an important to develop teachers' statistical reasoning or thinking by teacher education. In this study, the "comparing two data sets" tasks is focused as a way to develop pre-service elementary teachers' reasoning about core ideas of statistics such as distribution, variability, center, and spread. 6 teams of each 4 pre-service elementary teachers participated on the tasks and their presentations are analyzed based on Pfannkuch's (2006) teachers' inference model in comparing two data sets. As a result, they paid attention to the distribution and variability in the statistical problem solving by the "comparing two data sets" tasks, and used their contextual knowledge to make a statistical decision. In addition, they used some statistics and graphs as the reference for statistical communication, which is expected to provide implications for improving statistical education. The finding implies that the "comparing two data sets" tasks can be used to develop statistical reasoning of pre-service elementary teachers. Some recommendations are suggested for teacher education by these tasks.

• Journal of Oral Medicine and Pain
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• v.32 no.4
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• pp.441-447
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• 2007

Internal derangement of the temporomandibular joint(TMJ) is defined as an abnormal relationship of the articular disc to the condyle. Mandibular manipulation is one of the conservative treatments to be considered first to manage the patients with anterior disc displacement without reduction. Mandibular manipulation is used to increase articular mobility and to restore the displaced disc into an anatomically normal position. While Farrar's technique has been popularly used, Minagi et al., Mongini and Suarez introduced the manipulation technique conducted by the patients themselves. But there is no study on the efficacy of self-manipulation technique, comparing with conventional one. The aim of this study was to investigate the efficacy of the conventional and self-manipulation technique, which was modified to complement the previously described technique by Minagi et al., in the treatment of patients with anterior disc displacement without reduction. TMD patients, who visited Department of Oral Medicine of Seoul National University Dental Hospital from December, 2002 to November, 2004 and were diagnosed as anterior disc displacement without reduction by TMJ magnetic resonance imaging (MRI) were enrolled. Conservative treatments including physical therapy, exercise, behavioral therapy, stabilization splint therapy, and manipulation therapy were done to every single patient until the symptomsimproved enough to discharge the patient. The charts were reviewed retrospectively according to the type of manipulation. In the results, patients whose maximum mouth opening was more than 40 mm was higher in the self-manipulation group(69.9%) than in the conventional manipulation group(42.9%). But difference between two groups was not significant. According to the fact that we decided to discharge the patients whentheir mouth opening increased to more than 40 mm and subjective symptoms such as pain and discomfort were improved as well, treatment period of discharged patients was significantly shorter in the self-manipulation group($29.2{\pm}12.3$ weeks) than in the conventional manipulation group ($61.0{\pm}38.0$ weeks) (p<0.01). In conclusion, in the treatment of TMD patients with anterior disc displacement without reduction, the self-manipulation technique which is performed by patients themselves is an effective treatment modality for increasing the range of mouth opening and shortening the total treatment period.

• Journal of Korean Society for Atmospheric Environment
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• v.7 no.3
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• pp.180-188
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• 1991

기후변화를 나타내는 연구 결과들은 기온이나 강수량을 대상으로 하여 두 기간 평균치의 비교, 5년 이동평균치의 圖示, 회귀분석 등의 방법들을 사용하여 발표되지만 대부분의 경우 밑바탕이 되는 모집단의 통계적 특성을 엄격히 검토하지 않는 정성적인 분석인 경우가 많다. 서울, 부산, 인천, 목포 등 4개 지점의 80년 동안의 연강수량과 연평균기온자료를 분석한 결과 기온은 정규분포를 나타내므로 전통적인 t-검정과 회귀분석을 적용할 수 있다. t-검정 결과 두 기간(1920 $sim$ 1949, 1961 ~ 1990)은 연평균기온에서 0.3$^{\circ}$C에서 $0.8^{\circ}$C의 의의있는 차이를 보였다. 최근 30년의 연평균기온자료를 회귀분석한 결과 1년에 $0.02^{\circ}$C의 증가경향을 나타내었다. 연강수량은 정적인 왜곡도를 보이므로 정규분포를 가정하는 母數的 통계분석을 적용해서는 안되며 비모수적 통계분석법을 적용해야 한다. 연강수량의 분석에는 t-검정에 상응하는 Mann-Whitney 검정을 적용해 본 결과 두 기간(1920 ~ 1949, 1961 ~ 1990)의 평균은 통계적으로 의의있는 차이가 없었다. 회귀분석에 상응하는 Mann's 검정과 이 연구에서 새로이 제안된 Median Slope Change Estimator를 적용해 본 결과 역시 통계적으로 의의있는 변화가 없었다. Median Slope Change Estimator는 비모수적 통계치로서 회귀분석의 기울기에 해당하는 연변화를 나타낼 수 있는데 분석하려는 자료의 정규분포성을 요구하지 않으며 異常點(outlier) 영향에 덜 민감하다는 장점이 있으므로 주목하여 연구할 만한 가치가 있다.^{\circ}$~40$^{\circ}$ 구간에서는 ${\sigma}_c$와 I$_{sa}$, 40$^{\circ}$~90$^{\circ}$ 구간에서는 ${\sigma}_c$와 I$_{sd}$가 각각 양호한 상관관계를 보여준다. 또한 상관비(K=${\sigma}_c$/I$_s$)는 약 13정도로서 일반적으로 적용되는 비, 24와 상당한 차이가 있다. 이러한 현상은 호상편마암의 구조적 및 역학적 이방성 특성으로 인한 결과라고 판단된다. 한편 맥암류에서 K가 약 23정도로서 일반적인 비 24에 상당히 접근한다. 따라서, 이방성 구조가 뚜렷한 암석에서 상관비 24는 항상 적용할 수는 없으며 일축압축강도시험과 병행 실시하여 적용하는 것이 바람직하다.다. 한편, 감작감염후 77일과 도전감염후 7일의 시점에 있어서 sRBC에 대한 면역능에 미치는 영향은 전자의 양상과 비슷하였는데 대조에 비하여 지연형 과민반응과 로제트 형성능이 현저하게 저하되었다. 이 시점에 있어서의 유충회수율은 대조가 10.5% 이었는데 비하여 8.3%이었다.e also compared for the cases of Kim et al, which again gives promising agreement.면적 306~453$\textrm{cm}^2$, 유색계의 경우 수당면적 340~453$\textrm{cm}^2$ 일 때 경제능력을 제대로 발휘할 수 있고 경제성이 있는 것으로 나타났다. 첨가구가 높은 경향이 있었다8.4%. 79.7% 그리고 80.2%였다.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.115-122
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• 2007

The aim of this study is to identify the effect that the blended learning has on the learning achievement of computer education in high school. To get the goal, 136 students were allocated into the experiment group(68 students) with the blended class and the control group(68 students) with the traditional face-to-face class. After identifying the homogeneity of two groups in learning achievement by analyzing the pre-test, the experiment was performed. The result of this research is as follows. Significant difference was found in the learning achievement of post-test between the experiment group and the control group (t=-3.16, p=.0019). This result underlies the potential of blended learning in computer education. It will be important for designing the class for computer education in high school.

• The Korean Journal of Financial Management
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• v.24 no.2
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• pp.1-40
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• 2007

We test a model of investment-cashflow-growth opportunities relationship in order to estimate the sensitivities to investments. In this study, we use a new proxy variable for the value of growth opportunities(hereafter "VGO"), which is based on the seminal papers of M&M(1958:1961:1963) and Lee(2006;2007). The empirical findings on the sensitivities of cashflow and growth opportunities are as follows. First, when the traditional proxy variables for the growth opportunities such as Tobin's Q, MBR and sales growth are included with the new proxy VGO in the estimation, their coefficients are turned out to be insignificant. Second, only the new proxy variable VGO shows a statistically significant positive sensitibity to investment, which can be regarded that the growth opportunities hold the positive influences to investments. Third, the Tobin's Q can be decomposed into three factors such as the value of growth opportunities(VGO), the value of asset-in-place and valuation errors. It turns out that only the VGO shows a statistically significant positive relationship with investment among others. This means that the new variable VGO is a good proxy variable for the growth opportunities in the investment-cashflow sensitivity analysis. In sum, thanks to the above findings in this study, we can say that it will not be proper to choose a proxy variable for the growth opportunities from the traditional set of proxies such as Tobin's Q, MBR, or sales growth rate.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.107-120
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• 2014

This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.

• Proceedings of the Korean Society of Community Living Science Conference
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• 2009.09a
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• pp.100-100
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• 2009

지명(地名)은 그 지역의 역사와 전설, 문화, 풍속은 물론 독특한 자연환경이나 생활 모습을 담고 있어 농업농촌의 지역적 특성을 나타낸다. 본 연구는 지명유래의 활용성 증진의 한 방편으로 브랜드 및 문화관광상품 개발을 위해 강릉시 지역의 자연마을 지명유래, 이미지, 관광자원 등을 조사하였다. 강릉시의 자연마을 유래 233건에 대한 자료는 국토지리정보원, 문화원자료집, 강릉시 홈페이지, 산, 강, 골, 고적, 못 등 그 외 지명자료는 한글학회 지명총람에서 1,147건을 수집하였다. 자연마을지명의 유래 233건을 8개 유형으로 구분하면 자연지리 60건, 인문지리 40건, 생태환경 37건, 산업경제 14건, 역사 14건, 유적유물 5건, 민속 49, 종교 14건이며, 지형(27건), 풍수(19건), 고사(19건)관련 유래가 많았다. 강릉시 지역브랜드 개발을 위한 요구도 조사는 지역민 162명과 방문객 154명 총 316명을 조사하여 SPSS WIN 12.0 프로그램을 이용 분석하였다. 응답자의 일반적인 특성은 남성이 50.6%, 대졸자가 54.1%, 연령은 40대(26.9%), 1500만원-3000만원 미만의 연소득자 32.3%가 가장 많았다. 강릉시의 형용사적 이미지를 기술통계량으로 살펴보면 지역민은 전통적인, 평화로운, 보수적인, 순수한, 따뜻한 순으로, 방문객은 순수한, 평화로운, 활기찬, 전통적인, 정감있는 순으로 평균값이 높게 나타났고, 요인분석에 의한 지역민과 방문객의 인지적 형용사 도출결과는 진취적, 평화적, 보수적인 3가지 요인이다. 또한 강릉의 대표적 상징자원은 지역민은 경포대(60.5%), 선교장(24.7%), 오죽헌(23.5%)순이며, 방문객은 경포대(74.7%), 정동진(22.7%), 오죽헌(18.8%) 순으로 높게 응답하였고, 지명 호감도는 지역민의 경우 송림(51.2%), 몽룡실(32.1%), 연화장터(18.5%)순이며, 방문객의 경우 송림(43.5%), 솔밭말(23.4%), 금단이(18.2%)순으로 높았다. 향후 본 연구에서 제시된 연구를 통하여 강릉시의 지명을 활용한 브랜드개성을 측정할 수 있어 마케팅 관점에서 강릉시의 브랜드를 도출하는데 기여할 수 있을 것이다.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.319-330
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• 2006

A signal in real world usually composes of multiple signals having different scales of frequencies. For example sun-spot data is fluctuated over 11 year and 85 year. Economic data is supposed to be compound of seasonal component, cyclic component and long-term trend. Decomposition of the signal is one of the main topics in time series analysis. However when the signal is subject to nonstationarity, traditional time series analysis such as spectral analysis is not suitable. Huang et. at(1998) proposed data-adaptive method called empirical mode decomposition (EMD) . Due to its robustness to nonstationarity, EMD has been applied to various fields. Huang et. at, however, have not considered denoising when data is contaminated by error. In this paper we propose efficient denoising method utilizing cross-validation.