• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.412-421
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• 2013

Motion picture industry is one of the most representative fields in the cultural industry and has experienced constant growth both worldwide and within domestic markets. However, little research has been undertaken for diffusion patterns of motion pictures, whereas various issues such as demand forecasting and success factor analysis have been widely explored. To analyze diffusion patterns, we adopted extended Bass model to reflect the potential demand of movies. Four clusters of selected movies were derived by k-means clustering method with criteria of opening strength and profitability and then compared by their diffusion patterns. Results indicated that movies with high profitability and medium opening strength are most significantly influenced by word of mouth effect, while low profitability movies display nearly monotonic decreasing diffusion patterns with noticeable initial adoption rates and relatively early peak points in their runs.

• The Journal of Information Systems
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• v.3
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• pp.147-169
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• 1994

This paper present s a pattern generation scheme from financial charts. The patterns constitute knowledge which consists of patterns as the conditional part and the impact of the pattern as the conclusion part. The patterns in charts are represented in a syntactic approach. If the pattern elements and the impact of patterns are defined, the patterns are synthesized from simple to the more highly credible by evaluating each intermediate pattern from the instances. The overall process is divided into primitive discovery by Genetic Algorithms and pattern synthesis from the discovered primitives by the Syntactic Pattern-based Inductive Learning (SYNPLE) algorithm which we have developed. We have applied the scheme to a chart : the trend lines of stock price in daily base. The scheme can generate very credible patterns from training data sets.

• Spatial Information Research
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• v.19 no.2
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• pp.71-76
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• 2011

In this paper, for using emerging patterns to define and analyze the significant difference of safe and non-safe power load lines, and identify which line is potentially non-safe, we proposed an incremental TFP-tree algorithm for mining emerging patterns that can search efficiently within limitation of memory. Especially, the concept of pre-infrequent patterns pruning and use of two different minimum supports, made the algorithm possible to mine most emerging patterns and handle the problem of mining from incrementally increased, large size of data sets such as power consumption data.

• Journal of Nutrition and Health
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• v.37 no.7
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• pp.550-556
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• 2004

Dietary pattern analysis is important complementary approach for identifying associations between diet and chronic disease. A case-control study was conducted in order to examine dietary patterns and the risk of colon cancer in Korea. Data were collected from both 137 cases with either colorectal cancer or large bowl adenomatous polyps and 134 controls regarding social-demographic characteristics and food intake using a semi-quantitative food frequency questionnaire. We conducted factor analysis and identified 6 major dietary patterns: 'Well-being diet' characterized by higher intakes of potatoes, yogurt, soybean paste and vegetables, 'Meat & fish', 'Milk & juice', 'Pork & alcohol', 'Rice & kimchi', and 'Coffee & cake'. We calculated factor scores for each participant and examined the associations between dietary patterns and colon cancer risk. After adjusting for potential confounders, there was a relative risk for colon cancer of 0.16 (95% confidence interval, 0.07 - 0.34) when comparing the highest with the lowest tertile of the 'Well-being' pattern. Significant trends of decreasing risk of colon cancer also emerged with the 'Milk & juice' (OR = 0.40, 95% CI = 0.20 - 0.79). In contrast, inverse associations of the risk were found for 'Pork & alcohol' (OR = 1.92, 95% CI = 0.93 - 3.97), 'Coffee & cake' (OR = 2.18, 95% CI = 1.07 - 4.46). For the 'Meat & fish' pattern, the decreased risk of colon cancer was observed in the second tertile, but not in the highest tertile when comparing to the lowest. The 'Rice & kimchi' pattern had a nonsignificant association with the risk. These data suggest that major dietary patterns derived from the FFQ associated with the risk of colon cancer in Korea. Since foods are not consumed in isolation, dietary pattern research in natural eating behavior may be useful for understanding dietary causes of colon cancer.

• The korean journal of orthodontics
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• v.47 no.4
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• pp.248-255
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• 2017

Objective: The purpose of this study was to investigate whether the craniofacial patterns of Korean children with snoring and adenotonsillar hypertrophy (ATH) could be categorized into characteristic clusters according to age. Methods: We enrolled 236 children with snoring and ATH (age range, 5-12 years) in this study. They were subdivided into four age groups: 5-6, 7-8, 9-10, and 11-12 years. Based on cephalometric analysis, the sagittal and vertical skeletal patterns of each individual were divided into Class I, II, and III, as well as the normodivergent, hypodivergent, and hyperdivergent patterns, respectively. Cluster analysis was performed using cephalometric principal components in addition to the age factor. Results: Three heterogeneous clusters of craniofacial patterns were obtained in relation to age: cluster 1 (41.9%) included patients aged 5-8 years with a skeletal Class I or mild Class II and hyperdivergent pattern; cluster 2 (45.3%) included patients aged 9-12 years with a Class II and hyperdivergent pattern; and cluster 3 (12.8%) included patients aged 7-8 years with a Class III and hyperdivergent pattern. Conclusions: This study found that the craniofacial patterns of Korean children with snoring and ATH could be categorized into three characteristic clusters according to age groups. Although no significantly dominant sagittal skeletal discrepancy was observed, hyperdivergent vertical discrepancy was consistently evident in all clusters.

• Fashion & Textile Research Journal
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• v.8 no.6
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• pp.687-696
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• 2006

This study aims at analyzing the silhouette, dress patterns and detail of Empire Era(1789-1825), and making use of this results for the modern stage costume construction. The dresses of Empire era were divided into X and H style. The results revealed that the bust girth of X style group was bigger than that of H style group. Such patterns as high waistline, puff sleeve, train, etc. which appeared during the peak time of Empire style period were more remarkable for H style group. This obviously indicated that more epical characteristics were observed for H style group than for X style group. Similarly to silhouette analysis, based on the results from cluster analysis conducted to put similar groups together, two groups were formed - a visually differentiated and complex group and a simple group in the absence of detail. Most dress details from Empire period had simple embellishments. Comparison of the average size of the patterns between two groups indicated that waist front length of H style was shorter than that of X style. Front interscye was even greater than back width for both groups. Such trend was quite different from today's pattern in which back width is larger than front width based on body measurements. Preference for big breast during the period was reflected on dress patterns and the side length of front side goes across the back much further for bodice patterns. Two representatives were selected and reproduced using materials similar to those of real dresses of Empire style, following two times fit test.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.908-918
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• 2020

Objective: To categorize the radiological patterns of recurrence after bevacizumab treatment and to derive the pooled proportions of patients with recurrent malignant glioma showing the different radiological patterns. Materials and Methods: A systematic literature search in the Ovid-MEDLINE and EMBASE databases was performed to identify studies reporting radiological recurrence patterns in patients with recurrent malignant glioma after bevacizumab treatment failure until April 10, 2019. The pooled proportions according to radiological recurrence patterns (geographically local versus non-local recurrence) and predominant tumor portions (enhancing tumor versus non-enhancing tumor) after bevacizumab treatment were calculated. Subgroup and meta-regression analyses were also performed. Results: The systematic review and meta-analysis included 17 articles. The pooled proportions were 38.3% (95% confidence interval [CI], 30.6-46.1%) for a geographical radiologic pattern of non-local recurrence and 34.2% (95% CI, 27.3-41.5%) for a non-enhancing tumor-predominant recurrence pattern. In the subgroup analysis, the pooled proportion of non-local recurrence in the patients treated with bevacizumab only was slightly higher than that in patients treated with the combination with cytotoxic chemotherapy (34.9% [95% CI, 22.8-49.4%] versus 22.5% [95% CI, 9.5-44.6%]). Conclusion: A substantial proportion of high-grade glioma patients show non-local or non-enhancing radiologic patterns of recurrence after bevacizumab treatment, which may provide insight into surrogate endpoints for treatment failure in clinical trials of recurrent high-grade glioma.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.377-382
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• 2014

Analysis techniques of the data over time from the mobile environment and IoT, is mainly used for extracting patterns from the collected data, to find meaningful information. However, analytical methods existing, is based to be analyzed in a state where the data collection is complete, to reflect changes in time series data associated with the passage of time is difficult. In this paper, we introduce a method for analyzing multi-block streaming data(AM-MBSD: Analysis Method for Multi-Block Stream Data) for the analysis of the data stream with multiple properties, such as variability of pattern and large capacitive and continuity of data. The multi-block streaming data, define a plurality of blocks of data to be continuously generated, each block, by using the analysis method of the proposed method of analysis to extract meaningful patterns. The patterns that are extracted, generation time, frequency, were collected and consideration of such errors. Through analysis experiments using time series data.

• The Journal of Bigdata
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• v.2 no.2
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• pp.105-114
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• 2017

Today, many services are supported on the web sites. Analysis of usage patterns of web site visitors is very important to optimize the use and efficiency of the web sites. In this study, analysis of usage patterns and comparative analysis of user groups were conducted by analyzing web access log provided by BPI Challenge 2016. This data provides access logs to the web site in the IT system of a Dutch Employee Insurance Agency (UWV). The customer information, and the click data describing the customers' behavior when using the agency's web site. In this study, we use process mining techniques to analyze the usage patterns of customers and the characteristics of customer groups, and ultimately improve the service quality of customers using web services.

• Journal of Environmental Science International
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• v.18 no.2
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• pp.169-176
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• 2009

The present study observed temperature in order to identify factors affecting temperature by zoning and to measure the intensity of their impact on temperature. The empirical results of analyzing observed data are as follows. In order to make up for multicollinearity, a problem in multiple regression analysis, and to give more specific explanations, this study conducted factor analysis and obtained desirable data with adequacy and statistical significance. In the correlation matrix, factors decreasing temperature were planted areas, water surfaces and grasslands, and those increasing temperature were bare grounds, paved areas, and building area. According to land cover patterns, commercial areas had the highest temperature lowering effect. Through the rotated component matrix, we found that factors are grouped into those decreasing temperature, those increasing temperature, and those with low significance in increasing or decreasing temperature. In order to solve the problem of multicollinearity in multiple regression analysis, we performed factor analysis between the land use patterns and temperature and confirmed the usability of factor analysis as a new analysis method in urban heat island.