• Journal of applied mathematics & informatics
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• v.41 no.4
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• pp.861-868
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• 2023

Nonlinear network creates complex homotopy structural communication in wireless network medium because of complex distribution approach. Due to this multicast topological connection structure, the queuing probability was non regular principles to create routing structures. To resolve this problem, we propose a Co-cluster homotopy queuing model (Co-CHQT) for Nonlinear Algebraic Topological Structure (NLTS-) for improving poison distribution network communication. Initially this collects the routing propagation based on Nonlinear Distance Theory (NLDT) to estimate the nearest neighbor network nodes undernon linear at x_(a,b)→ax²+bx² = c. Then Quillen Network Decomposition Theorem (QNDT) was applied to sustain the non-regular routing propagation to create cluster path. Each cluster be form with co variance structure based on Two unicast 2(n+1)-Z2(n+1)-Z network. Based on the poison distribution theory X_(a,b) ≠ µ(C), at number of distribution routing strategies weights are estimated based on node response rate. Deriving shorte;'l/st path from behavioral of the node response, Hilbert -Krylov subspace clustering estimates the Cluster Head (CH) to the routing head. This solves the approximation routing strategy from the nonlinear communication depending on Max- equivalence theory (Max-T). This proposed system improves communication to construction topological cluster based on optimized level to produce better performance in distance theory, throughput latency in non-variation delay tolerant.

• Journal of the Korean association of regional geographers
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• v.22 no.2
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• pp.397-410
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• 2016

Although industrial complexes have played as an engine of the Korean economy for the last 40 years, the majority of industrial complexes shows limitations to the continuous growth such as a lack of innovation capabilities and social capital, conceived as a key to transforming into clusters of innovation. To overcome those problems, the Korean government embarked on the cluster policy from the mid 2000's, focusing on promoting the endogenous development capabilities of individual industrial complexes. Drawing upon the in-depth case study of the Gumi IT cluster, one of the representative large-scale industrial complexes in Korea, the authors conclude that the cluster policy has contributed to making the Gumi IT cluster enhance the capabilities of endogenous development through the facilitation of self-organizing learning communities within the cluster.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.514-537
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• 2020

Wireless sensor network (WSN) is a distributed network composed of many sensory nodes. It is precisely due to the clustering unevenness and cluster head election randomness that the energy consumption of WSN is excessive. Therefore, a many-objective optimization WSN energy balance model is proposed for the first time in the clustering stage of LEACH protocol. The four objective is considered that the cluster distance, the sink node distance, the overall energy consumption of the network and the network energy consumption balance to select the cluster head, which to better balance the energy consumption of the WSN network and extend the network lifetime. A many-objective optimization algorithm to optimize the model (LEACH-ABF) is designed, which combines adaptive balanced function strategy with penalty-based boundary selection intersection strategy to optimize the clustering method of LEACH. The experimental results show that LEACH-ABF can balance network energy consumption effectively and extend the network lifetime when compared with other algorithms.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.111-125
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• 2011

Clustering is a process of grouping similar or relevant documents into a cluster and assigning a meaningful concept to the cluster. By this process, clustering facilitates fast and correct search for the relevant documents by narrowing down the range of searching only to the collection of documents belonging to related clusters. For effective clustering, techniques are required for identifying similar documents and grouping them into a cluster, and discovering a concept that is most relevant to the cluster. One of the problems often appearing in this context is the detection of a complex concept that overlaps with several simple concepts at the same hierarchical level. Previous clustering methods were unable to identify and represent a complex concept that belongs to several different clusters at the same level in the concept hierarchy, and also could not validate the semantic hierarchical relationship between a complex concept and each of simple concepts. In order to solve these problems, this paper proposes a new clustering method that identifies and represents complex concepts efficiently. We developed the Hierarchical Overlapping Clustering (HOC) algorithm that modified the traditional Agglomerative Hierarchical Clustering algorithm to allow overlapped clusters at the same level in the concept hierarchy. The HOC algorithm represents the clustering result not by a tree but by a lattice to detect complex concepts. We developed a system that employs the HOC algorithm to carry out the goal of complex concept detection. This system operates in three phases; 1) the preprocessing of documents, 2) the clustering using the HOC algorithm, and 3) the validation of semantic hierarchical relationships among the concepts in the lattice obtained as a result of clustering. The preprocessing phase represents the documents as x-y coordinate values in a 2-dimensional space by considering the weights of terms appearing in the documents. First, it goes through some refinement process by applying stopwords removal and stemming to extract index terms. Then, each index term is assigned a TF-IDF weight value and the x-y coordinate value for each document is determined by combining the TF-IDF values of the terms in it. The clustering phase uses the HOC algorithm in which the similarity between the documents is calculated by applying the Euclidean distance method. Initially, a cluster is generated for each document by grouping those documents that are closest to it. Then, the distance between any two clusters is measured, grouping the closest clusters as a new cluster. This process is repeated until the root cluster is generated. In the validation phase, the feature selection method is applied to validate the appropriateness of the cluster concepts built by the HOC algorithm to see if they have meaningful hierarchical relationships. Feature selection is a method of extracting key features from a document by identifying and assigning weight values to important and representative terms in the document. In order to correctly select key features, a method is needed to determine how each term contributes to the class of the document. Among several methods achieving this goal, this paper adopted the $x^2$�� statistics, which measures the dependency degree of a term t to a class c, and represents the relationship between t and c by a numerical value. To demonstrate the effectiveness of the HOC algorithm, a series of performance evaluation is carried out by using a well-known Reuter-21578 news collection. The result of performance evaluation showed that the HOC algorithm greatly contributes to detecting and producing complex concepts by generating the concept hierarchy in a lattice structure.

• Journal of Technology Innovation
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• v.16 no.1
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• pp.165-190
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• 2008

The purpose of this study is to find problems of Geographical Cluster and to analyze relationships between problems of a Geographical Cluster and its performance. The problems of geographical cluster include those of technical fusion, increase of incidental expenses, conditions of settlement, and absence of industrial infrastructures, and performance factors are satisfaction with the cluster policy and within cluster firm's performance. According to the results of analyses based on the data collected from 75 firms located in the Gumi electronic industry cluster complex, first, problems of technical fusion, and absence of industrial infrastructures had a negative(-) effect on satisfaction with the cluster policy. Second, absence of industrial infrastructures had also a negative(-) effect on within cluster firm's performance. In the conclusion, further discussion, limitation of this study and future direction were suggested.

• The International Journal of Costume Culture
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• v.5 no.1
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• pp.58-66
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• 2002

The objectives of this study are to develope sensibility image scales for Korean traditional motifs by quantitatively measuring their images and preference and to classify them into clusters. Data were collected via a questionnaire from seven hundred twenty five Korean undergraduate students. Re experimental materials were forty eight stimuli of Korean traditional motifs with different categories, interpretation types, composition types, and application objects. The instruments consisted of 7-point polar semantic differential scales of twenty three bipolar adjectives including preference. Data were analyzed by correspondence analysis, cluster analysis, ANOVA and Duncan's multiple range test. Re major results are as follows; image scales for textile patterns and dress designs using Korean traditional motifs were constructed. The axes of sensibility image scales for both textile patterns and dress designs were defined by quality level and degree of simplicity. Second, four clusters on the scale of textile patterns and two clusters on the scale dress designs were identified. Third, in the case of textile Patterns, the preferred cluster had high-quality and classical images, while the cluster that was not preferred had a complex image. In the case of dress designs, the preferred cluster had simple and high-quality images, while the cluster that was not preferred had complex and low-quality images.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.237-246
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• 2011

Robots have been used in many fields due to its performance improvement and variety of its functionality, to the extent which robots can replace human tasks. Individual feature and better performance of robots are expected and required to be created. As their performances and functions have increased, systems have gotten more complicated. Multi mobile robots can perform complex tasks with simple robot system and algorithm. But multi mobile robots face much more complex driving problem than singular driving. To solve the problem, in this study, driving algorithm based on the energy method is applied to the individual robot in a group. This makes a cluster be in a formation automatically and suggests a cluster the automatic driving method so that they stably arrive at the target. The energy method mentioned above is applying attractive force and repulsive force to a special target, other robots or obstacles. This creates the potential energy, and the robot is controlled to drive in the direction of decreasing energy, which basically satisfies lyapunov function. Through this method, a cluster robot is able to create a formation and stably arrives at its target.

• International Journal of Contents
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• v.5 no.3
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• pp.57-64
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• 2009

Korea has relied on top down development method, in which companies, research and education institutions move into the industrial complexes established by the government. However, to improve local competitiveness, the paradigm is shifting from the government initiated industrial complex to the clusters based on the cooperative network of the region. Representative case is 'Samcheok-si Fire & Emergency industry cluster construction project' that begun in 2007. AHP technique analysis results on first-stage showed that priority was on policy and network elements, and the results of second-stage analysis show that priority was on Policy incentives to internationalize the cluster and strengthen link,. Cluster branding, Sharing of organizational culture to cope with changes in environment, Creation of group learning culture. The subject of this research is limited to Samcheok-si's the Fire and Emergency Industry cluster formation project. Therefore, the research area and standard should be expanded to increase generality in further researches.

• Journal of the Korean association of regional geographers
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• v.18 no.3
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• pp.283-297
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• 2012

This study aims to analyze an evolutionary path and the dynamics of the Seoul Digital Industrial Complex in Korea based on the analysis of cluster life cycles. From the mid 1960s to the late 1990s, the life cycles and their characteristics of the Seoul Digital Industrial Complex (Guro Industrial Park) are examined as emergence-growth-sustainment-decline focused on the number of firms and employees. After the late 1990s, the number of firms and employees increases rapidly and the active actors of the growth and restructuring are transformed to the technology-intensive SMEs and knowledge-based service firms. Knowledge industry centers (apartment-type factories) help evolve into the life cycle of transformation as knowledge-based clusters after the mid 2000s.

• Journal of Korean Society of Rural Planning
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• v.22 no.2
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• pp.153-164
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• 2016

Developed countries in agriculture like Netherlands, Belgium and England, have managed Green Care policy and project during the last decades. The needs in Green Care is also increasing as new growth power in rural area of Korea. This study investigated sites which are already operating as complex with Green Care theme. This study surveyed the operating conditions like type, scale, location pattern, purpose, customer and finance for cases of the complex. The period of the survey is from 2015. 8. 11 to 2015. 09. 10 for the 24 activated cases in aspect of operation and management. Among the 24 cases, 16 cases were classified as Green Care Complex which facilities are aggregated a place, and the other 8 cases as Green Care Cluster which are distributed at several places. The analysis result showed that there were apparent distinction among cases in total budget, costs of construction, capacity for guest, and the total number of annual visitors. Despite of the type and scale the accommodation cost, the number of workers, and amount of sales have small deviation in distribution of values, although the cases have various type of contents and scale of space. The result of this study can be used as data of bench marking to develop the Green Care Complex or Cluster in rural area.