• Journal of the Korean Society of Clothing and Textiles
• /
• v.20 no.2
• /
• pp.282-297
• /
• 1996

The effective construction for ready-made clothes is one of the central concerns of both consumers and manufactuers in today's apparel industry. In order to reduce the burden of stocks and increase clothing fitness, systematic information on typical body sizes and somatotypes is essential. The purpose of this study i-: to provide basic data on young women's somatotypes for form designers and pattern makers. The subjects of the survey were 310 women of 18 to 26 years old. The study collected 84 anthropometric data for each Person. The data was analyzed by using of the multivariate method. The factor analysis was utilized in regard to the 65 items obtained from anthropometric measurement respectively. The principal component analysis was applied to the data with orthogonal rotation after extraction. The factor scores used in the factor analysis became the basis of determining the value of each variable of the cluster analysis. The cluster analysis was applied for identifying typical somatotypes. Ward's minimum variance method was applied for the purpose of extracting distance metrix by the standardized Euclidean distance. The element forming each cluster can be subdivided into several sets by crosstabulation which is obtained by the fastclus of the SAS. This research has demonstrated 3 distinctive types of silhouette contour of the trunk. Incidentally it also identified 4 of the lower body from the waistline to thigh contour respectively. The discriminant analysis showed that the most significant discriminant factor of the trunk classification were side neck point -1 scapular -1 waistiline length and waist girth. In Korea, the average somatotype of female college students tends to be tall, slim and straight. Reviewing the relationship between the classifications of three parts of body, they are related to each other to some extent but their distribution are not constant. Therefore, in view of clothing construction, a proper separation of the body surface is a necessity.

• Food Science of Animal Resources
• /
• v.36 no.6
• /
• pp.719-728
• /
• 2016

The aim of this study was to explore the volatile compounds of hind leg, foreleg, abdomen and Longissimus dorsi in both male and female Hyla rabbit meat by solid phase microextraction tandem with gas chromatography mass spectrometry, and to seek out the key odorants via calculating the odor activity value and principal component analysis. Cluster analysis is used to study the flavor pattern differences in four edible parts. Sixty three volatile compounds were detected, including 23 aldehydes, 4 alcohols, 5 ketones, 11 esters, 5 aromatics, 8 acids and 7 hydrocarbons. Among them, 6 aldehydes and 3 acids were identified as the potential key odorants according to the ratio of concentration and threshold. The contents of volatile compounds in male Hyla rabbit meat were significantly higher than those in female one (p<0.05). The results of principal component analysis showed that the first two principal component cumulative variance contributions reach 87.69%; Hexanal, octanal, 2-nonenal, 2-decenal and decanal were regard as the key odorants of Hyla rabbit meat by combining odor activity value and principal component analysis. Therefore volatile compounds of rabbit meat can be effectively characterized. Cluster analysis indicated that volatile chemical compounds of Longissimus dorsi were significantly different from other three parts, which provide reliable information for rabbit processing industry and for possible future sale.

• Journal of the Economic Geographical Society of Korea
• /
• v.11 no.3
• /
• pp.428-441
• /
• 2008

This article verifies the actual conditions of the Wonju area medical devices cluster for presentation of method for increasing promotion. It examines the general status of companies, reason for location, competitive power and supporting system with a questionnaire survey and in-depth research. The Wonju area has 79 medical device companies. It comprised 9% of total sales and 11% of export sales of korea medical devices in 2007. For enhancement of the Wonju area medical devices ability to accumulate and attract of medical device companies and front-line and back-line industries, the followings is needed, a supply of highly qualified man power, a support base for developing modem technology and information marketing, adequate infrastructure for housing and education system, methodologies for sustaining new business and innovation fund-raising programs and marketing, and provide the highest degree of education for CEO.

• Journal of KIISE:Computer Systems and Theory
• /
• v.31 no.11
• /
• pp.635-642
• /
• 2004

The traditional communication protocols such as TCP/IP are not suitable for PC cluster systems because of their high software processing overhead. To eliminate this overhead, industry leaders have defined the Virtual Interface Architecture (VIA). VIA provides two different data transfer mechanisms, a traditional Send/Receive model and the Remote Direct Memory Access (RDMA) model. RDMA is extremely efficient way to reduce software overhead because it can bypass the OS and use the network interface controller (NIC) directly for communication, also bypass the CPU on the remote host. In this paper, we have implemented VIA-based RDMA mechanism in hardware. Compared to the traditional Send/Receive model, the RDMA mechanism improves latency and bandwidth. Our RDMA mechanism can also communicate without using remote CPU cycles. Our experimental results show a minimum latency of 12.5${\mu}\textrm{s}$ and a maximum bandwidth of 95.5MB/s. As a result, our RDMA mechanism allows PC cluster systems to have a high performance communication method.

• Journal of the Korea Computer Industry Society
• /
• v.3 no.1
• /
• pp.77-84
• /
• 2002

An cluster system used consist of large number of running servers, one has the problem that does the low availability occured by the high chance of the server failures and it is difficult to provide occuring software aging. In this paper, running cluster web servers consists of n primary servers and k backup servers, based on the operational parameters such as number of running primary servers, number of backup severs, rejuvenation period, rejuvenation time, failure rate of sewers, repair rate of servers, unstable rate of servers. We calculate to evaluate the rejuvenation policy such steady-state probabilities, downtime, availability, and downtime cost. We validate the solutions of mathematical model by experiments based on various operation parameters and find that the software rejuvenation method can be adopted as prventive fault tolerant technique for stability of system. The failure rate and unstable rate of the servers are essential factors for decision making of the rejuvenation policies.

• Journal of the Economic Geographical Society of Korea
• /
• v.24 no.3
• /
• pp.232-242
• /
• 2021

The aim of this article is to examine the role of Gyeonggi Province in the industrial development in the Republic of Korea by taking a case study of the program of the national innovative cluster (NIC). In such program which has been for the purpose of the regional industrial development for non-Seoul metropolitan regions (N-SMRs) since 2018, the total firms' transactions were highly focused upon Gyeonggi Province and other Seoul metropolitan regions (SMRs). Especially, firms' transactions in 5 clusters of the total 14 clusters concentrated on Gyeonggi Province. Within this context, the future direction of this policy program for the regional industrial development and the national balanced development is more focused upon a win-win strategy between the SMR and N-SMRs rather than the dichotomy between them.

• Korean Journal of Organic Agriculture
• /
• v.28 no.4
• /
• pp.535-553
• /
• 2020

In this study, the characteristics of the waste sector CDM project were analyzed through cluster analysis of the waste sector CDM project and the analysis of the CDM investment cost in waste sector using CDM project data registered with UNFCCC since 2008 when EU ETS phase 2 began. As of September 2020, 772 cases of CDM projects in waste disposal and disposal are registered. Biogas technology is the largest, followed by livestock manure processing and biomass production technology. The results of the cluster analysis are summarized as follows: First, on average, projects utilizing AWMS technology are small in size and relatively low in investment costs. This is judged to be relatively low investment costs due to previously attracted foreign investment capital. Second, the average investment cost of CDM projects considered along with waste (No.13), the energy industry (No.1) and agriculture (No.15) was higher than those involving only waste. The analysis of the factors determining the investment cost of the waste sector CDM project showed that, as with cluster analysis, the AWMS technology, which is a livestock manure treatment technology, was lower in the investment cost than those that use other technologies. As a result of multiple regression analysis, the investment cost of the CDM project was analyzed lower in the order of biomass, AWMS, LFG and biogas. Also, the higher the investment cost for CDM projects linked to waste, energy and agriculture, and the better the investment environment, the higher the investment cost. Although no statistical feasibility was obtained, the larger the annual emission reduction, the lower the CDM investment cost.

• The Journal of Information Systems
• /
• v.30 no.2
• /
• pp.147-163
• /
• 2021

Purpose The study aims to predict real estate prices by utilizing regional characteristics. Since real estate has the characteristic of immobility, the characteristics of a region have a great influence on the price of real estate. In addition, real estate prices are closely related to economic development and are a major concern for policy makers and investors. Accurate house price forecasting is necessary to prepare for the impact of house price fluctuations. To improve the performance of our predictive models, we applied LSTM, a widely used deep learning technique for predicting time series data. Design/methodology/approach This study used time series data on real estate prices provided by the Ministry of Land, Infrastructure and Transport. For time series data preprocessing, HP filters were applied to decompose trends and SOM was used to cluster regions with similar price directions. To build a real estate price prediction model, SVR and LSTM were applied, and the prices of regions classified into similar clusters by SOM were used as input variables. Findings The clustering results showed that the region of the same cluster was geographically close, and it was possible to confirm the characteristics of being classified as the same cluster even if there was a price level and a similar industry group. As a result of predicting real estate prices in 1, 2, and 3 months, LSTM showed better predictive performance than SVR, and LSTM showed better predictive performance in long-term forecasting 3 months later than in 1-month short-term forecasting.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.219-221
• /
• 2022

Seoul Metropolitan City, the world's top 10 cities and Metro City, has traditional urban manufacturing industries such as printing, sewing, and mechanical metals. These manufacturing industries have developed in the form of mutual assistance by forming small business clusters according to detailed industries and processes. Due to the nature of the cluster, logistics between companies for each process in the cluster are being carried out quickly, but it is difficult for relatively small small business owners to prepare order processing services for consumers of finished products. Therefore, it is urgent to introduce an integrated order fulfillment service platform for collective business owners for smooth order and delivery processing. In this paper, we collect and analyze the existing Fulfillment Service data of small business owners in the printing industry among traditional urban industries, and design an artificial intelligence Fulfillment Service Platform system applying CRNN, k-NN, and ID3 Decision Tree algorithm. Through this study, it is expected to greatly contribute to the increase in sales and capacity of small business owners by enabling the use of individual orders and customized delivery services that can be used by any small business owner in the cluster.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.1
• /
• pp.91-98
• /
• 2023

Since risks occurring in construction projects can have a significant impact on schedules and costs, there have been many studies on this topic. However, risk analysis is often limited to only certain construction situations,and experience-dependent decision-making is therefore mainly performed. Data-based analyses have only been partially applied to safety and contract documents. Therefore, in this study, cluster analysis and a Word2Vec algorithm were applied to formal documents that contain important elements for contractors or clients. An initial classification of document content into six types was performed through cluster analysis, and 157 occurrence types were subdivided through application of the Word2Vec algorithm. The derived terms were re-classified into five categories and reviewed as to whether the terms could develop into potential construction risk factors. Identifying potential construction risk factors will be helpful as basic data for process management in the construction industry.