• Journal of Korea Trade
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• v.23 no.4
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• pp.103-114
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• 2019

Purpose - This paper investigates the structure of exports across countries in terms of value added. Exports value added is examined under two categories, domestic and overseas. Using a statistical classification method by distance based on these two value added categories, this paper estimates the similarity of exports value added across countries including Korea. Design/methodology - The model of study is to employ a generalized distance function and then derive the Manhattan and Euclidean distances. The paper also performs cluster analysis using the Partitioning Around Medoids (PAM) and hierarchical methods to classify the 44 sample countries considered in this study. Findings - Our main findings are as follows. The 44 countries can be classified under 5 groups by their domestic and overseas value added in exports. Korea has a sandwich global value chains (GVCs) position between Japan, China, and Taiwan in the East Asian region. Originality/value - Existing papers point out the double counting problem of trade statistics as the intermediate goods trade across borders increases. This paper addresses the double counting problem by using the World Input-Output Table. The paper shows the need to explore the similarity of value added in exports structure across countries and investigate the GVCs position and role of each country.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.441-443
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• 2021

Sentence or text similarity is a measure of the degree of similarity between two sentences. Techniques for measuring text similarity include Jacquard similarity, cosine similarity, Euclidean similarity, and Manhattan similarity. Currently, the cosine similarity technique is most often used, but since this is an analysis according to the occurrence or frequency of a word in a sentence, the analysis on the semantic relationship is insufficient. Therefore, we try to improve the efficiency of analysis on the similarity of sentences by giving relations between words using ontology and including semantic similarity when extracting words that are commonly included in two sentences.

• Journal of the Korean Society of Food Culture
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• v.24 no.6
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• pp.655-665
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• 2009

Coupled with the international expansion of Korean culture in recent years, a number of restaurants from Korea have been trying to tap into the global market place. The purpose of this study was to identify the characteristics of non-Korean patrons in Korean Restaurants in New-york city. The survey was conducted at six popular Korean restaurants, all of which had been recognized in the Zagat Survey in recent years, located in prime business districts in Manhattan. The data collected from the six local Korean restaurants that participated in this study were qualitatively and quantitatively analyzed. After employing individual in-depth interviews with restaurant operators, a qualitative analysis identified demographic characteristics, Socioeconomic characteristics and segmentation of restaurant operation. Self-administrated survey questionnaires were used to acquire quantitative data. Primary data were collected from non-Korean patrons at the six participating Korean restaurants in New York City in 2008 (N=245). The patrons who answered the survey indicated that they were highly satisfied with the 'Food'; however, they were not satisfied with the 'Beverage' and 'Value'. In addition, older patrons (55<) were not as content with the 'Food' as the younger patrons. The most influential satisfaction variable that affected a patron's intention to revisit the Korean restaurant was 'Food' and 'Overall experience'. This study findings will help Korean restaurant operators and marketers better understand their patrons and formulate strategies to cater and target segments more effectively.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.273-273
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• 2022

The increasing number of Westernized eating patterns based on wheat flour in Korea has led to an increase in the rate of diseases such as obesity and diabetes, which has become a social problem. Wheat consumption is increasing due to changes in eating habits, but domestic wheat has low price competitiveness and has stagnated recently, so it is necessary to secure new resources to differentiate from imported wheat. Resistant starch, a newly created resource in domestic wheat, can act as a prebiotic similar to dietary fiber in the body, inducing microbial changes in the gut and having beneficial effects on metabolic syndrome. Wheat research on resistant starch was carried out based on the breeding of high amylose. A genome-wide association study (GWAS) was used to perform SNP identification and expression analysis related to wheat amylose through phenotype and genotype. 561 wheat core collection gene sources were investigated for amylose content in wheat, and related genes were extracted and analyzed. In the GWAS analysis, the model formulas BLIMK, FarmCPU, GLM, MLM, and MLMM were used to derive results such as QQ plots and Manhattan plots through phenotypic data. Among these models, BLAST was conducted to find the association between the SNPs identified using FarmCPU and genes related to starch, and 15 were found. Using the identified markers, it becomes easier to develop and browse related wheat cultivars according to their amylose content.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1171-1176
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• 2016

VANET are a special kind of MANET adapted to the communications between vehicles. In this work, we propose the models used for representing the communication among vehicles, vehicles mobility features, and VANET simulator using realistic vehicular mobility models. VANET requires that a traffic and network simulator should be used together to perform this test. But, simulator tool has been preferred over traffic simulation because it simple, easy and cheap. Goal of this paper is to create a simulation of Vehicular Ad-Hoc network for urban scenario which can be used for testing purposes. Such environment can be used while designing better MAC protocols in VANETs. We are evaluating the performance of two routing protocols namely AODV and DSDV. The comparison was based on the throughout, packet loss and end-to-end delay. We found that DSDV has less throughput performance and high routing overhead than AODV. On average end-to-end delay and packet loss, AODV performs better than DSDV.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.405-414
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• 2017

Spatial data processing often poses challenges due to the unique characteristics of spatial data and this becomes more complex in spatial big data processing. Some tools have been developed and provided to users; however, they are not common for a regular user. This paper presents a benchmark test between two notable tools of spatial big data processing: GIS Tools for Hadoop and SpatialHadoop. At the same time, a MapReduce application is introduced to be used as a baseline to evaluate the effectiveness of two tools and to derive the impact of number of maps/reduces on the performance. By using these tools and New York taxi trajectory data, we perform a spatial data processing related to filtering the drop-off locations within Manhattan area. Thereby, the performance of these tools is observed with respect to increasing of data size and changing number of worker nodes. The results of this study are as follows 1) GIS Tools for Hadoop automatically creates a Quadtree index in each spatial processing. Therefore, the performance is improved significantly. However, users should be familiar with Java to handle this tool conveniently. 2) SpatialHadoop does not automatically create a spatial index for the data. As a result, its performance is much lower than GIS Tool for Hadoop on a same spatial processing. However, SpatialHadoop achieved the best result in terms of performing a range query. 3) The performance of our MapReduce application has increased four times after changing the number of reduces from 1 to 12.

• Journal of The Korean Society of Grassland and Forage Science
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• v.11 no.2
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• pp.90-96
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• 1991

This experiment was carried out in order to estimate the recovery days of root and stubble to the days after cutting, and contribution of specific stubble weight on the regrowth was examined using the relationships between the dry weight of shoot and yield components, and regrowth parameters by the days after cutting. The varieties examined were Maprima, Manhattan, Tove, Peramo, Caliente, Tempo and P-2 grown under individual plant basis. The results are may be summarized as follows: 1. Dry weight of root and stubble were recovered up to 13.5 and 11 days after cutting, respectively. 2. Dry weight of shoot(regrowth parts+stubble) was affected significantly by the varieties, stages of regrowth and variety x stage of regrowth. 3. The variety with tiller weight type showed higher average productivity of shoot than those of the variety with tiller number type. 4. Absolute growth rate(AGR) of shoot was correlated significantly with regrowth parts, stubble, root and weight of a tiller at the early stage of regrowth(up to 12 days after cutting), and correlated with regrowth parts, stubble, weight of tiller and stubble area at the late stage of regrowth(up to 20 days after cutting). 5. Contribution of specific stubble weight to absolute growth rate of shoot was different between the stages of regrowth. Thus, regrowth parts per specific stubble weight(RP1SSbW) and weight of tiller per specific stubble weight(WT1SSbW) contributed to absolute growth rate of shoot at the early stage of regrowth, and efficiency of specific stubble weight(ESSbW), regrowth parts per specific stubble weight (RPISSbW) and weight of a tiller per specific stubble weight(WT1SSbW) contributed to absolute growth rate of shoot at the late stage of regrowth. 6. Regrowth utilization rate(RUR) was one of the useful regrowth parameter to indicate the regrowth potential of grasses.

• Journal of the Korean Wood Science and Technology
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• v.35 no.2
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• pp.39-50
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• 2007

The purpose of this study was to investigate the physico-mechanical properties and characteristics on reduction of formaldehyde and total volatile organic compound (TVOC) emission from particleboard (PB) with added volcanic pozzolan. Pozzolan was added as a scavenger at the level of 1, 3, 5, and 10 wt.% of urea formaldehyde (UF) resin for PB manufacture. The moisture content, density, thickness swelling, water absorption and physical properties of PBs were examined. Three-point bending strength and internal bond strength were determined using a universal testing machine. Formaldehyde and TVOC were determined by desiccator and 20L small chamber methods. With increasing pozzolan content the physical and mechanical properties of the PBs were not significantly changed, but formaldehyde and TVOC emissions were decreased. Because pozzolan has a rough and irregular surface with porous form, it can be used as a scavenger for PBs at a content up to 10 wt.% without any detrimental effect on the physical and mechanical properties.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.8-19
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• 2004

In this paper, we propose an efficient method for locating destination address block on both of machine-Printed and handwritten Korean mail piece images. The proposed method extracts connected components from the binary mail piece image, generates text lines by merging them, and then groups the text fines into nine clusters. The destination address block is determined by selecting some clusters. Considering the geometric characteristics of address information on Korean mail piece, we split a mail piece image into nine areas with an equal size. The nine clusters are initialized with the center coordinate of each area. A modified Manhattan distance function is used to compute the distance between text lines and clusters. We modified the distance function on which the aspect ratio of mail piece could be reflected. The experiment done with live Korean mail piece images has demonstrated the superiority of the Proposed method. The success rate for 1, 988 testing images was about 93.56%.

• Journal of Animal Science and Technology
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• v.54 no.6
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• pp.463-469
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• 2012

This study utilized a standardization and cluster analysis technique for the selection and classification of beneficial bacteria. A set of synthetic data consisting of 100 individual variables with three characteristics was created for analysis. The three characteristics assigned to each independent variable were designated to have different numeric scales, averages, and standard deviations. The variables were bacterial isolates at random, and the three characteristics were fermentation products, including cell yield, antioxidant activity of culture, and enzyme production. A standardization method utilizing a standard normal distribution equation to record fermentation yields of each isolate was employed to weight their different numeric scales and deviations. Following transformation, the data set was analyzed by cluster analysis. The Manhattan method for dissimilarity matrix construction along with complete linkage technique, an agglomerative method for hierarchical cluster analysis, was employed using statistical computing program R. A total of 100 isolates were classified into groups A, B, and C. In a comparison of the characteristics of each group, all characteristics in groups A and C were higher than those of group B. Isolates displaying higher cell yield were classified as group A, whereas those isolates showing high antioxidant activity and enzyme production were assigned to group C. The results of the cluster analysis can be useful for the classification of numerous isolates and the preparation of an isolation pool using numerical or statistical tools. The present study suggests that a simple technique can be applied to screen and select beneficial microbes using the freely downloadable statistical computing program R.