• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.321-332
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• 2013

Because of the continuous low birthrates, the number of the elementary students will decrease by 17% in 2020 compared to 2011. The purpose of this study is to forecast the number of elementary school teachers until 2020. We used the data in education statistical year books from 1970 to 2010. We used the time-series regression model, time series grouped regression model and exponential smoothing model to predict the number of teachers for the next ten years. Consequently time-series grouped regression model is a better model for forecasting the number of elementary school teachers than other models.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.181-193
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• 2017

The paper introduces bottom-up and optimal combination methods that can analyze and forecast hierarchical time series. These methods allow forecasts at lower levels to be summed consistently to upper levels without any ad-hoc adjustment. They can also potentially improve forecast performance in comparison to independent forecasts. We forecast regional traffic accident counts as time series data in order to identify efficiency gains from hierarchical forecasting. We observe that bottom-up or optimal combination methods are superior to independent methods in terms of forecast accuracy.

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.695-708
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• 2022

Recently, several studies have been conducted using state space model. In this study, a dynamic linear model with state space model form is applied to stock data. The monthly returns for 135 Korean stocks are fitted to a dynamic linear model, to obtain an estimate of the time-varying 𝛽-coefficient time-series. The model formula used for the return is a capital asset pricing model formula explained in economics. In particular, the transition equation of the state space model form is appropriately modified to satisfy the assumptions of the error term. k-shape clustering is performed to classify the 135 estimated 𝛽 time-series into several groups. As a result of the clustering, four clusters are obtained, each consisting of approximately 30 stocks. It is found that the distribution is different for each group, so that it is well grouped to have its own characteristics. In addition, a common pattern is observed for each group, which could be interpreted appropriately.

• The korean journal of orthodontics
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• v.47 no.5
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• pp.298-305
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• 2017

Objective: This paper describes changes in the characteristics of patients seeking orthodontic treatment over the past decade and the treatment they received, to identify any seasonal variations or trends. Methods: This single-center retrospective cohort study included all patients who presented to Seoul National University Dental Hospital for orthodontic diagnosis and treatment between January 1, 2005 and December 31, 2015. The study analyzed a set of heterogeneous variables grouped into the following categories: demographic (age, gender, and address), clinical (Angle Classification, anomaly, mode of orthodontic treatment, removable appliances for Phase 1 treatment, fixed appliances for Phase 2 treatment, orthognathic surgery, extraction, mini-plate, mini-implant, and patient transfer) and time-related variables (date of first visit and orthodontic treatment time). Time series analysis was applied to each variable. Results: The sample included 14,510 patients with a median age of 19.5 years. The number of patients and their ages demonstrated a clear seasonal variation, which peaked in the summer and winter. Increasing trends were observed for the proportion of male patients, use of non-extraction treatment modality, use of ceramic brackets, patients from provinces outside the Seoul region at large, patients transferred from private practitioners, and patients who underwent orthognathic surgery performed by university surgeons. Decreasing trends included the use of metal brackets and orthodontic treatment time. Conclusions: Time series analysis revealed a seasonal variation in some characteristics, and several variables showed changing trends over the past decade.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2539-2554
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• 2017

Regression-based image super resolution (SR) methods have shown great advantage in time consumption while maintaining similar or improved quality performance compared to other learning-based methods. In this paper, we propose a novel single image SR method based on hierarchical regression to further improve the quality performance. As an improvement to other regression-based methods, we introduce a hierarchical scheme into the process of learning multiple regressors. First, training samples are grouped into different clusters according to their geometry similarity, which generates the structure layer. Then in each cluster, a compact dictionary can be learned by Sparse Coding (SC) method and the training samples can be further grouped by dictionary atoms to form the detail layer. Last, a series of projection matrixes, which anchored to dictionary atoms, can be learned by linear regression. Experiment results show that hierarchical scheme can lead to regression that is more precise. Our method achieves superior high quality results compared with several state-of-the-art methods.

• Journal of The Korean Society of Grassland and Forage Science
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• v.17 no.3
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• pp.305-314
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• 1997

Nineteen clones of Jerusalem Artichoke (JA) from several countries were collected through the series of experiments about JA started in 1979. Collected clones were screened for adaptibility in Korea and showed introduction path way. The results about an ecological response of collected clones including flowering, tuberization, biomass production, sugar contents and grouping of collected clones for use of genetic material were as follows; 1. Nineteen clones collected were ffom Korea(2), Japan(l), USA(Z), Canada(2), France(4), Germany(7), and USSR(1). 2. Through the characteristics of top collected clones were divided to the types of branch-non branch, short and long plant height, and early and late maturity. Tuber characteristics were mainly grouped to the types of white skin color-violet skin color, clusters-single unit, round-elongate, and knotty-smooth. 3. Total sugar yields 6-om top at flowering time were 490 - 630kgl10a and 6-om the tuber were 420 -490 kg/ IOa through the high yielding clones. The top-high yielding clones were Mammoth French White, Fuseau 60, Nahodka, and JA3. The higher tuber yields were got from the clones of D- 19, Colombia, Bianka and Mammoth French White. 4. Collected clones were grouped to three and first group was characterized to early maturity and short plant height and second group to medium and finally, third group to late maturity and high plant height. 5. High yielding of top was 6-om the I group of early maturity and short plant height and high yielding of tuber h m III group of late maturity and high plant height.

• Journal of Korea Technology Innovation Society
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• v.7 no.3
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• pp.681-709
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• 2004

The purpose of this study is to classify customers by e-mail responsiveness on time-series analysis and testify the effectiveness of grouping by ROI analysis. Response recency, response frequency and Activity(RFA) of e-mailing systems are adapted for Customer segmentations. ROI analysis are consisted of open, click-through, duration time, personalization, conversion rate and email loyalty index of email systems. Major findings are as follows: RFA analysis is used for customer segmentations that is fundamental process of e-CRM applications. Customers can be grouped into loyal customers, odds customers, dormant customers, secession customers, and observation customers by RFA grouping. Loyal customer group has high point in all ROI index compared to other groups. These results indicated that customer responsiveness of e-mail systems were appropriate methods to group the customer with demographic variables. Therefore, effective e-mail marketing strategy of e-Biz should have suitable active DB and Behavior targeting is best approach to enforce the target e-mail marketing.

• Journal of the korean society of oceanography
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• v.32 no.1
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• pp.38-45
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• 1997

To find out the changes in vertical distribution patterns over the 24-h period, a key and the first step to tackle the problem of adaptive significance of diel vertical migration (DVM), vertically stratified time series samplings with multiple opening/closing plankton samplers were done in the East Sea of Korea (Sea of Japan). Sampling was done almost every 4 h for one day period following the same water parcel in Nov. 1995 and May 1996, respectively. Resultant patterns of vertical distribution showed that some species such as most abundant taxa Metridia pacifica and Scolecithyicella minor, both Copepoda, performed DVM even in the study area of strong thermal stratification. Their patterns of DVM such as distance scales and timing of movements were not the same each other, and they were separated from other taxa in the dendrogram obtained by the cluster analyses, Most minor taxa grouped in one, however, seemed not to do DVM in the study area of strong thermal stratification. They usually preferred the warmer surface layer where the foods were probably more abundant.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.53 no.4
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• pp.386-395
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• 2017

For scientific research, a number of acoustic surveys using commercial echosounders equipped in fishing vessels were conducted throughout the world; however, few studies were performed in South Korea. Hence, this research is an preliminary study for presenting the application of a sounder from a fishing vessel. The fishing operations using a pair trawler (7 Cheonghae) was conducted in the Northwest-Western sea of Jeju Island from 20 to 23 April, 2016. Substantial impulse noises and attenuated signals were eliminated by the latest algorithms. Acoustic signals were grouped into the fish aggregations and long layer-like signals. The fish aggregations appeared between 30 and 60 m, and long layer-like signals showed the diurnal vertical migration. Energetic, morphological and positional properties of the fish aggregations and layer-like signals were described. The fish aggregations appeared mainly between sunrise and sunset; however layer-like signals tended to be presented regardless of time in consideration of the time series analysis. On the basis of the consignment sales, Scomberomorus niphonius, the target species of F/V 7 Cheonghae, was the highest catch with 4,280 kg (74.6%) and might have appeared in fish aggregations and layer forms.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.581-594
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• 2016

We introduce innovations state space exponential smoothing models (ISS-ESM) that can analyze time series with multiple seasonal patterns. Especially, in order to control complex structure existing in the multiple patterns, the model equations use a matrix consisting of seasonal updating parameters. It enables us to group the seasonal parameters according to their similarity. Because of the grouped parameters, we can accomplish the principle of parsimony. Further, the ISS-ESM can potentially accommodate any number of multiple seasonal patterns. The models are applied to predict electricity demand in Korea that is observed on hourly basis, and we compare their performance with that of the traditional exponential smoothing methods. It is observed that the ISS-ESM are superior to the traditional methods in terms of the prediction and the interpretability of seasonal patterns.