• Journal of the Korean Home Economics Association
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• v.40 no.8
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• pp.123-135
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• 2002

The purpose of this study is to examine the relationship between shopping orientation and purchasing satisfaction of apparels. To achieve the purpose, this study was carried out by means of questionnaires with female consumers aged from 20s to 50s in Daegu. The data were analysed by the frequency analysis, percentage, reliability test, factor analysis, Pearson's correlation analysis, cluster analysis, one-way ANOVA and Duncan's multiple range analysis. The statistical package for social science 9.0 for Window was used for the statistical processing of the data. The result of this study is summarized as follows. 1. To examine factors which construct female consumers' shopping orientation for apparels, a factor analysis was done, therefore, which obtained 6 factors. Also A factor analysis was done to examine the motivative factors of satisfaction with purchased apparels, 6 factors were obtained. 2. Based on the average score of shopping-orientation factors for apparels, a cluster analysis was done and it was classified into 3 clusters. There were differences in purchasing satisfaction of purchased apparels between the 3 clusters. 3. The differences in variety, shopping convenience, dignity, brand & preference, and convenient selection between the clusters were entirely p<0.001 which were very significant. There were no differences in the quality and service factors between the brand-/practicality-oriented cluster and entertainment-oriented cluster. With other factors, entertainment-oriented cluster was most satisfied than brand-/ practicality oriented cluster. But, self-reliance-oriented cluster was lowest purchasing satisfaction of apparels.

• Korean Journal of Adult Nursing
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• v.23 no.5
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• pp.434-445
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• 2011

Purpose: This study was conducted to identify the impact of the symptom cluster of pain, fatigue, sleep disturbance, depression on the quality of life (QOL) among breast cancer patients receiving chemotherapy. Methods: One hundred and thirteen patients were recruited from five hospitals in Korea. The instruments used in this study were the fatigue, depression, sleep disturbance, pain and the quality of life scale for patients with breast cancer. The influence of the symptom cluster on patients' QOL was analyzed by using multiple regression. Results: Most patients reported a moderate level of pain, fatigue, sleep disturbance and depression. Eighty percent of patients reported three of the four symptoms. Among the four symptoms, there was no correlation between pain and sleep disturbance. Quality of life was negative correlated with the four symptoms in the cluster. Symptom cluster of pain, fatigue, and depression accounted for 51.2% of variance in QOL. Conclusion: The findings supported that there is a symptom cluster that negatively influences quality of life and needs to be addressed as we are caring for patients and are promoting quality of life.

• Journal of Korean Clinical Nursing Research
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• v.29 no.3
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• pp.337-347
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• 2023

Purpose: The objectives of this study were to categorize the conflict management types of preceptor nurses and determine the effects of these types on preceptors' role perception and core competencies. Methods: Data was collected from 192 preceptor nurses with at least two years experiences in general hospitals, from July 1 to July 31, 2022. Conflict management type, preceptor role perception, and core competency were investigated using structured instruments. The data was analyzed using K-means cluster analysis, Independent samples t-test, One-way ANOVA with Scheffé's test, and multiple regression analysis. Results: The conflict management types were categorized into four types; comprehensive type (cluster 1), integrating, obliging, compromising type (cluster 2), undifferentiated type (cluster 3) and obliging, avoiding type (cluster 4). The effect of conflict management types on preceptors' role recognition occurred in the following order of cluster 2 (integrating/obliging/compromising type), cluster 1 (comprehensive type), and cluster 4 (obliging/avoiding type). Next, cluster 1 (comprehensive type), cluster 2 (integrating/obliging/compromising type), and cluster 4 (obliging/avoiding type) were shown in the order of the impact on the core competencies of the preceptor. Conclusion: When preceptor nurses use a mixture of various attributes of conflict management evenly, they have been shown to demonstrate effective preceptor role recognition and core competencies. Therefore, it is proposed that future development of conflict management training programs for preceptor nurses should begin with identifying their conflict management type, followed by creating a program that addresses any deficiencies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5149-5173
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• 2016

Cooperative forwarding has shown a substantial network performance improvement compared to traditional routing in multi-hop wireless network. To further enhance the system throughput, especially in the presence of highly congested multiple cross traffic flows, a promising way is to incorporate the multi-radio multi-channel (MRMC) capability into cooperative forwarding. However, it requires to jointly address multiple issues. These include radio-channel assignment, routing metric computation, candidate relay set selection, candidate relay prioritization, data broadcasting over multi-radio multi-channel, and best relay selection using a coordination scheme. In this paper, we propose a simple and efficient cluster-based cooperative data forwarding (CCDF) which jointly addresses all these issues. We study the performance impact when the same candidate relay set is being used for multiple cross traffic flows in the network. The network simulation shows that the CCDF with MRMC not only retains the advantage of receiver diversity in cooperative forwarding but also minimizes the interference, which therefore further enhances the system throughput for the network with multiple cross traffic flows.

• Journal of Communications and Networks
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• v.12 no.3
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• pp.231-239
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• 2010

In cluster-based wireless sensor networks, the energy could be saved when the nodes that have data to transmit participate in cooperative multiple-input multiple-output (MIMO). In this paper, by making the idle nodes that have no data to transmit participate in the cooperative MIMO, it is found that much more energy could be saved. The number of the idle nodes that participate in the cooperative MIMO is optimized to minimize the total energy consumption. It is also found that the optimal number of all the nodes participating in cooperative communication does not vary with the number of nodes that have data to transmit. The proposition is proved mathematically. The influence of long-haul distance and modulation constellation size on the total energy consumption is investigated. A cooperative MIMO scheme with help-node participation is proposed and the simulation results show that the proposed scheme achieves significant energy saving.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.6
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• pp.648-653
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• 2011

In this paper, coordinated space division multiple access(SDMA) technology is proposed to mitigate inter-cell interference by using partial channel state information in cooperative wireless communications system with limited feedback. Each AT selects an optimal cluster transmission mode and sends it back to a cluster scheduler, and at the cluster scheduler, ATs are scheduled within a AT group with the identical cluster transmission mode, and the optimal transmission mode and the corresponding scheduled ATs are determined to maximize scheduling priority. Also, in order to enhance multiuser diversity gain, an extended transmission feedback method is proposed to feed back multiple preferred cluster transmission modes at each AT. It is shown that the proposed coordinated SDMA scheme outperforms existing non-coordinated SDMA schemes in terms of the average system throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1164-1183
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• 2019

The rapid development of cloud computing and high requirements of operators requires strong support from the underlying Data Center Networks. Therefore, the effectiveness of using resources in the data center networks becomes a point of concern for operators and material for research. In this paper, we discuss the online virtual-cluster provision problem for multiple tenants with an aim to decide when and where the virtual cluster should be placed in a data center network. Our objective is maximizing the total revenue for the data center networks under the constraints. In order to solve this problem, this paper divides it into two parts: online multi-tenancy scheduling and virtual cluster placement. The first part aims to determine the scheduling orders for the multiple tenants, and the second part aims to determine the locations of virtual machines. We first approach the problem by using the variational inequality model and discuss the existence of the optimal solution. After that, we prove that provisioning virtual clusters for a multi-tenant data center network that maximizes revenue is NP-hard. Due to the complexity of this problem, an efficient heuristic algorithm OMS (Online Multi-tenancy Scheduling) is proposed to solve the online multi-tenancy scheduling problem. We further explore the virtual cluster placement problem based on the OMS and propose a novel algorithm during the virtual machine placement. We evaluate our algorithms through a series of simulations, and the simulations results demonstrate that OMS can significantly increase the efficiency and total revenue for the data centers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10B
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• pp.964-972
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• 2009

Wireless mesh network (WMN) is emerging a future core technology to resolve many problems derived from exist wireless networks by employing multi-interface and multi-channel. Ability to utilize multiple channels in WMNs substantially increases the effective bandwidth available to wireless network nodes. However, minimum interference channel assignment algorithms are required to use the effective bandwidth in multi-channel environments. This paper proposes a cluster-based minimum interference channel assignment (MI-CA) algorithm to improve the performance of WMN. The MI-CA algorithm is consists of Inter-Cluster and Intra-Cluster Intrchannel assignment between clusters and in the internal clusters, respectively. The Inter-Cluster channel assignment assigns a barebone channel to cluster heads and border nodes based on minimum spanning tree (MST) and the Intra-Cluster channel assignment minimizes channel interference by reassigning ortasgonal channels between cluster mespann. Our simheation results show that MI-CA can improve the performance of WMNs by minimizing channel interference.

• Korean Journal of Child Studies
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• v.37 no.3
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• pp.135-146
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• 2016

Objective: This study explored the creative thinking styles of children according to cluster analyses and examined group differences in language ability, cognitive ability, and peer relationships. Methods: The study used the data from the 2012 Panel Study of Korean Children by the Korea Institute of Child Care and Education. The participants comprised 1,681 4-year-olds. Data were analyzed via cluster analyses, ${\chi}^2$ distributions, and ANOVA tests. Results and Conclusion: The results from the cluster analyses based on percentiles of the subfactors of K-FCTYC (Korean Figural Creativity Test for Young Children) indicated four clusters: "divergent creative with openness," "non-creative," "divergent creative," and "multiple creative." Additionally, the four clusters differed by gender, language ability, cognitive ability, and peer relationships.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.985-992
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• 2001

This paper proposes a self-organizing fuzzy modeling(SOFUM)which an create a new hyperplane shaped cluster and adjust parameters of the fuzzy model in repetition. The suggested algorithm SOFUM is composed of four steps: coarse tuning. fine tuning cluster creation and optimization of learning rates. In the coarse tuning fuzzy C-regression model(FCRM) clustering and weighted recursive least squared (WRLS) algorithm are used and in the fine tuning gradient descent algorithm is used to adjust parameters of the fuzzy model precisely. In the cluster creation, a new hyperplane shaped cluster is created by applying multiple regression to input/output data with relatively large fuzzy entropy based on parameter tunings of fuzzy model. And learning rates are optimized by utilizing meiosis-genetic algorithm in the optimization of learning rates To check the effectiveness of the suggested algorithm two examples are examined and the performance of the identified fuzzy model is demonstrated via computer simulation.