• KIISE Transactions on Computing Practices
• /
• v.23 no.8
• /
• pp.481-486
• /
• 2017

There are many scientists who want to perform experiments in a cloud environment, and pay-per-use services allow scientists to pay only for cloud services that they need. However, it is difficult for scientists to select a suitable set of resources since those resources are comprised of various characteristics. Therefore, classification is needed to support the effective utilization of cloud resources. Thus, a dynamic resource clustering method is needed to reflect the characteristics of the application that scientists want to execute. This paper proposes a resource clustering analysis method that takes into account the characteristics of an application in a hybrid cloud environment. The resource clustering analysis applies a Self-Organizing Map and K-means algorithm to dynamically cluster similar resources. The results of the experiment indicate that the proposed method can classify a similar resource cluster by reflecting the application characteristics.

• Spatial Information Research
• /
• v.20 no.6
• /
• pp.23-32
• /
• 2012

This study applied an exploratory analysis based on Self Organizing Map and GIS to cause specific age-standardized regional death rates data related to ten types of male cancers to find meaning patterns in the data. Then the patterns revealed from the exploratory analysis was evaluated to investigate possible relationship between these patterns and regional socio-economic status represented by regional educational attainment levels of head of household. The results from this analysis show that SI-GUN-GUs in Korea can be clustered to eighteen unique clusters in the stand point of male cancer death rates and these clusters are also spatially clustered. Also, the results reveal that regions with higher socio-economic status show lower level of the death rates compared with the regions with lower socio-economic status. However, for some cancer types, the regions with higher socio-economic status show relatively higher death rates. These patterns imply that the prevention, detection, and treatment of male cancers might be strongly affected by regional factors such as socio-economic status, environmental factors, and cultures and norms in Korea. Especially, one of the eighteen clusters, which includes Gangnam-Gu and Seocho-Gu, shows lower death rates in many of male cancer types. This implies that socio-economic status may be one of the most influential factors for regional cancer control.

• The Journal of the Korea Contents Association
• /
• v.10 no.2
• /
• pp.462-480
• /
• 2010

Patent analysis is the extracting knowledge which is needed for the company's research and development strategy through accumulated worldwide patent database. In order to set the future direction of corresponding technology which is scheduled to be developed, the technology trends and deployment processes are identified by analyzing results of present patent applications. The patent analysis provides the required results for analyzing present patent applications. In this paper, we will carry out technology classification for related patent analysis methods and systems. Moreover we will investigate and analyze related domestic patents, U.S. patents and IEEE papers. Due to the characteristics of technology sector, not only patents are applied but also research papers are released actively about patent analysis system. We will analyze patents according to the technology classification by using the final searching results which come from the selected search words in this study. To find necessary niche technology which is needed for patent analysis system, matrix analysis was performed to all of valid patents and papers. Identifying the technology development trends of registered patent analysis systems, and presenting the future direction of technology development which is related to patent analysis system. To figure out the technology which is developed relatively weak based on domestic patents, U.S patent and research papers by analyzing the valid patents and papers with statistical test and self-organizing map quantitatively. Then, presenting the necessity of this technology development.

• Atmosphere
• /
• v.28 no.3
• /
• pp.305-315
• /
• 2018

This study investigates the characteristic spatial patterns and dynamic processes associated with the summertime extreme temperature events in South Korea during the last 20 years (1995~2014) using Self-Organizing Map (SOM). The classified SOM patterns commonly have high temperature and anticyclonic circulation anomalies over South Korea. The two major teleconnection patterns are identified: one is from the subtropical western North Pacific (WNP) affecting to the north and the other is from the North Atlantic (NA) affecting downstream region. The meridional teleconnection pattern is related to the forcing of positive sea surface temperature (SST) anomaly over the WNP. The northward propagating Rossby wave generates the East Asia-Pacific (EAP) pattern to form an anticyclonic circulation anomaly over South Korea. On the other hand, NA SST anomalies generate an eastward Rossby wave train across the Eurasian continent, leading to the development of an anticyclonic circulation anomaly over South Korea. The EAP pattern occurs more frequently in July and August, whereas the midlatitude teleconnection pattern associated with NA SST anomalies develops more frequently in early summer (June).

• The Korean Journal of Applied Statistics
• /
• v.18 no.1
• /
• pp.83-98
• /
• 2005

Exploring distributional patterns of multivariate data is very essential in understanding the characteristics of given data set, as well as in building plausible models for the data. For that purpose, low-dimensional visualization methods have been developed by many researchers along various directions. As one of methods, Kohonen's SOM (Self-Organizing Map) is prominent. SOM compresses the volume of the data, yields abstraction from the data and offers visual display on low-dimensional grids. Although it is proven quite effective, it has one undesirable property: SOM's display is discrete. In this study, we propose two techniques for enhancing quality of SOM's display, so that SOM's display becomes continuous. The proposed methods are demonstrated in two numerical examples.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2009.05a
• /
• pp.1999-2003
• /
• 2009

우리나라는 기상학적으로 연중 총강수량의 약 2/3가 $6^{\sim}9$월에 편중해서 내리고 있고, 지형적으로 국토의 70% 이상이 산지로 구성되어 경사가 급해 수해를 입을 가능성이 매우 크다. 또한 산업화 및 도시화로 인해 불투수층의 증가로 강수량의 대부분이 직접유출로 기여해 강우초기에 노면상의 오염물질을 급속히 하천으로 이동시켜 오염을 가중시키고 있다. 강우-유출수 처리에 있어서 처리용량 산정 등에 이용될 수 있는 초기강우의 기준은 비점오염원 유출 연구에 있어서 대단히 중요한 요소이며, 지금까지 많은 연구자들에 많은 연구가 이루어져왔다. 그러나 유역을 구성하고 있는 토지피복에 따라 유출특성이 다르고 각각의 연구자들이 제안한 초기강우 기준이 명확하게 제시되지 못하고 있는 실정이다. 따라서 본 연구에서는 SOM(Self-Organizing Map)이론을 도입하여 본 연구의 시험유역에서 측정된 유출 및 수질자료에 대해 패턴분류를 수행하여 분할구역별 자료의 특성분석을 분석한다.

• Korean Journal of Environmental Biology
• /
• v.36 no.1
• /
• pp.21-32
• /
• 2018

This study was carried out to define the characteristics of the identified ground-dwelling invertebrate communities at Nari basin and Tonggumi area in Ulleungdo Island, designated as a nationally important agricultural heritage. The habitat types were divided into the following categories: crop land, forest, and ecotone, and the soil-dwelling invertebrates were collected according to habitat type. The ground-dwelling invertebrates were collected using a pitfall trap, and a self-organizing map (SOM) was applied to the invertebrates dataset to define the characteristics in invertebrates distribution. The SOM clearly classified the relevant information into four clusters, and extracted ecological information from the invertebrates dataset. The cluster II was composed of invertebrate communities which are collected in the Tonggumi area. The Tonggumi area is where mountainous areas were developed for agricultural purposes, which has geographical features commonly observed in Ulleungdo Island. It is noted that the cluster II has different characteristics as compared other clusters. The results of this study are expected to be used for the preservation of agricultural environment and maintenance of biodiversity by providing basic data, on the biotope of Ulleungdo Island designated as a nationally important agricultural heritage and information on the characteristics of the applicable ground-dwelling invertebrate communities.

• Journal of Korea Water Resources Association
• /
• v.41 no.10
• /
• pp.995-1007
• /
• 2008

Studies on modeling the rainfall-runoff relationship which shows nonlinear trend strongly use artificial neural networks theory not only for the prediction but also for the characteristics analysis of the data used by pattern classification. For the pattern classification, the results from Self-Organizing Map (SOM) mention that the map size and array for the SOM training have significantly influenced on the SOM performance. Since there is no deterministic method or theoretical equation to determine the number of rows and columns for the map size, hexagonal array is generally used for the map array. Therefore, this study present a determination of the optimized map structure for the rainfall-runoff analysis in Naju station considering the map size and array simultaneously which can represent the classified characterization of rainfall-runoff relationship. The result showed that the map size of 20$\times$16 hexagonal array with 8-clustered patterns was selected as an appropriate map structure for rainfall-runoff analysis in Naju station.

• Journal of Institute of Control, Robotics and Systems
• /
• v.2 no.2
• /
• pp.108-114
• /
• 1996

We present proofs of the stability and convergence of Self-organizing feature map (SOFM) neural network with time-invarient learning rate and binary reinforcement function. One of the major problems in Self-organizing feature map neural network concerns with learning rate-"Kalman Filter" gain in stochsatic control field which is monotone decreasing function and converges to 0 for satisfying minimum variance property. In this paper, we show that the stability and convergence of Self-organizing feature map neural network with time-invariant learning rate. The analysis of the proposed algorithm shows that the stability and convergence is guranteed with exponentially stable and weak convergence properties as well.s as well.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.1
• /
• pp.170-180
• /
• 2011

The purposes of this study are to find out the effectiveness of the tutoring program and the level of self-regulated learning ability in tutoring program attending students. This study has been performed for team-tutoring program attending students(n=183) who are in 15 department, D college in Daegu. Following results were drawn thought correlation analyses of variables obtained during the survey period. The results were as follows; There was statistically significant difference among perception controlling ability, purpose controlling ability, and action controlling ability. In over 20 ages, organization, meta-perception stratagem, arrangement, self-effectiveness, controlling learning time ability were higher than of lower 20 ages(p<0.05). In tutors, demonstration, organization, meta-perception stratagem, arrangement, checking, purpose intentions, self- effectiveness, achievement, controlling action, help requirement ability were higher than tutees(p<0.05). As results, the tutoring program was effective for both tutors and tutees in college students. Further studies in an education program for students in all years should be implemented to examine tutoring effects. Implementation of tutoring should address the frustrations and difficulties encountered by the students to facilitate better outcomes.