• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.1
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• pp.22-33
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• 1999

In this paper, we propose a new multi-way circuit partitioning system that partition large circuits to progrmmable circuit board which consist of FPGAs and interconnect components. Here the routing topology among the chips are predetermined and the number of available interconnections are fixed. Since the given constraints are difficult to be satisfied by the previous partition method, we suggest a new multi-way partition method by target restriction that considers all the constraints for the given board. To speed up, we construct a multi-level cluster tree for hierarchical partitioning. Experimental results for several benchmarks show that the our partition method partition them by satisfying all the given constraints and it used up to 10 % fewer interconnections among the chips than the previous K-way partition method.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5493-5498
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• 2015

Due to the lack of nationwide population-based cancer registration, the total cancer prevalence in Iran is unknown. Our previous work in which we used a basic network scale-up (NSU) method, failed to provide plausible estimates of total cancer prevalence in Kerman. The aim of the present study was to estimate total and partial prevalence of cancer in southeastern Iran using an adapted version of the generalized network scale-up method. A survey was conducted in 2014 using multi-stage cluster sampling. A total of 1995 face-to-face gender-matched interviews were performed based on an adapted version of the NSU questionnaire. Interviewees were asked about their family cancer history. Total and partial prevalence were estimated using a generalized NSU estimator. The Monte Carlo method was adopted for the estimation of upper/lower bounds of the uncertainty range of point estimates. One-yr, 2-3 yr, and 4-5 yr prevalence (per 100,000 people) was respectively estimated at 78 (95%CI, 66, 90), 128 (95%CI, 118, 147), and 59 (95%CI, 49, 70) for women, and 48 (95%CI, 38, 58), 78 (95%CI, 66, 91), and 42 (95%CI, 32, 52) for men. The 5-yr prevalence of all cancers was estimated at 0.18 percent for men, and 0.27 percent for women. This study showed that the generalized familial network scale-up method is capable of estimating cancer prevalence, with acceptable precision.

• Journal of the Korean Society of Clothing and Textiles
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• v.14 no.2
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• pp.129-136
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• 1990

The purpose of the study was to develope brand positioning map for ladies' ready-to-wear, to find out evaluative criteria in perception and preference to brands, and to persent the relationship between consumer's characteristics and brand preference. Subjects were selected for the housewives of middle and high socioeconomic classes living in Seoul area. A questionnaire including items of life style, self image, similarity between brands, preference degree to brands, and demographic variables was developed for the empirical study. The questionnaire was administrated to 137 housewives during fall in 1989. Data were analyzed by cluster analysis and multidimensional scaling method. The study had two research problems. The first research problem was to construct a brand perceptual map for ladies' ready-to-wear brands, selected for the study The perceptual map was constructed on the basis of brand similarity scores by multidimensional scaling method. As a result, brands were grouped into 4 clusters, and evaluative criteria for perceptual map were found to be fashionability (classic- fashionable) and familiarity (familiar-unfamiliar). The second problem was to construct a brand preference map for ladies' ready-to-wear brands, selected for the study. The preference map was constructed on the basis of brand preference scores by multidimensional scaling method. As a result, the brands were grouped into 4 clusters and evaluative critiera for preference map were found to be fashionability (unfashionable-fashionable) and image to age (mature-young directed). Also was shown the relationship among self image, age, socioeconomic class, and brand preference. The multidimensional scaling method was found to be useful as well as valid instrument for brand positioning research and the result can be utilized for establishing strategies for ladies' ready-to-wear brands.

• Journal of KIISE
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• v.43 no.4
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• pp.404-410
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• 2016

Automated road map generation poses significant research challenges since GPS-based navigation systems prevail in most general vehicles. This paper proposes an automated detecting method for intersection points using GPS vehicle trajectory data without any background digital map information. The proposed method exploits the fact that the trajectories are generally split into several branches at an intersection point. One problem in previous work on this intersection detecting is that those approaches require stopping points and direction changes for every testing vehicle. However our approach does not require such complex auxiliary information for intersection detecting. Our method is based on partial trajectory matching among trajectories since a set of incoming trajectories split other trajectory cluster branches at the intersection point. We tested our method on a real GPS data set with 1266 vehicles in Gangnam District, Seoul. Our experiment showed that the proposed method works well at some bigger intersection points in Gangnam. Our system scored 75% sensitivity and 78% specificity according to the test data. We believe that more GPS trajectory data would make our system more reliable and applicable in a practice.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.135-144
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• 2009

This study estimates the expected number of accidents in Kyungbuk Province to capitalize on experience gained from four years of accident history using the Empirical Bayes (EB) Method. The number of accidents of each site in Kyungbuk Province is recalculated using the Equivalent Property Damage Only (EPDO) method to reflect the severities of the accidents. A cluster analysis is performed to determine similar sites and a unique Safety Performance Function (SPF) is established for each site. The overdispersion parameter is built to correct the difference between the actual number of accidents and the underlying probability distribution. To adjust for varying traffic characteristics of each site, a relative weight is applied and eventually estimates the expected number of accidents. The results show that the highest accident sites are Kimcheon, Youngcheon, and Chilgok, but on the other hand the lowest is Gunwi.

• KIISE Transactions on Computing Practices
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• v.21 no.5
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• pp.387-392
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• 2015

MapReduce is a framework used to process large data sets in parallel on a large cluster. A group-by query is a query that partitions the input data into groups based on the values of the specified attributes, and then evaluates the value of the specified aggregate function for each group. In this paper, we propose an efficient method for processing multiple group-by queries using MapReduce. Instead of computing each group-by query independently, the proposed method computes multiple group-by queries in stages with one or more MapReduce jobs in order to reduce the total execution cost. We compared the performance of this method with the performance of a less sophisticated method that computes each group-by query independently. This comparison showed that the proposed method offers better performance in terms of execution time.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.10
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• pp.705-712
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• 2013

Active learning aims to improve the performance of a classification model by repeating the process to select the most helpful unlabeled data and include it to the training set through labelling by expert. In this paper, we propose a method for active learning based on hierarchical agglomerative clustering using Ward's linkage. The proposed method is able to construct a training set actively so as to include at least one sample from each cluster and also to reflect the total data distribution by expanding the existing training set. While most of existing active learning methods assume that an initial training set is given, the proposed method is applicable in both cases when an initial training data is given or not given. Experimental results show the superiority of the proposed method.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.331-348
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• 2019

Understanding the tumor heterogeneity due to differences in the growth pattern of metastatic tumors and rate of change is important for understanding the sensitivity of tumor cells to drugs and finding appropriate therapies. It is often possible to test for differences in population means using t-test or ANOVA when the group of N samples is distinct. However, these statistical methods can not be used unless the groups are distinguished as the data covered in this paper. Statistical methods have been studied to test heterogeneity between samples. The minimum combination t-test method is one of them. In this paper, we propose a maximum combinatorial t-test method that takes into account combinations that bisect data at different ratios. Also we propose a method based on the idea that examining the heterogeneity of a sample is equivalent to testing whether the number of optimal clusters is one in the cluster analysis. We verified that the proposed methods, maximum combination t-test method and gap statistic, have better type-I error and power than the previously proposed method based on simulation study and obtained the results through real data analysis.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.55-59
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• 2022

Recently, IoT technology has great attention and plays a key role in 4^th industrial revolution in order to design customized products and services. Additive Manufacturing (AM) is applied to fabricate IoT sensor directly or IoT sensor embedded structure. Also, design methods for AM are developing to consolidate various parts of IoT devices. Part consolidation leads to assembly time and cost reduction, reliability improvement, and lightweight. Therefore, a design method was proposed to guide designers to consolidate parts. The design method helps designers to define product architecture that consists of functions and function-part relations. The product architecture is converted to a network graph and then Girvan Newman algorithm is applied to cluster the graph network. Parts in clusters are candidates for part consolidation. To demonstrate the usefulness of the proposed design method, a case study was performed with e-bike fabricated by additive manufacturing.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.655-662
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• 2012

The aim of this study is to analyze tthe pattern of compacted area and the distribution characteristics in one-person household. Through ArcGis, we collect the basic data and classify the compact area in accordance with the pattern employing Ward method out of cluster analysis. The main results are found as follows; First, the station sphere type is located around Seomyun and Nampo-dong, which are the main CBD( Central Business District) This type must be essentially considered in residential plan for one-person household location. Second, the district oriented type is located around the subway and it has relatively better residential facilities and environments. Third, it is found that the younger worker including students resided in one room and villa in the type around university. Forth, the foreign workers and domestic workers in small and medium factory resided in the factory centered type which is far from the station sphere. Lastly, it is dormitory type which is isolated from the CBD, and insteadly amenable and well natural environment area, but students and workers in this area where there are lacking life-related facilities and aside from accessibilities feel uncomfortable.