• Korean Parent-Child Health Journal
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• v.19 no.1
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• pp.25-32
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• 2016

Purpose: The purpose of this study was to use the social network analysis to verify the relationship between the interpersonal disposition and interactive characteristics of nursing college students. Five classes, a total of 117 nursing students were included in the study. Methods: The study interaction network centralization, density and in-degree & out-degree centrality were used as indicators for measuring students' study interaction. Also, the students' interpersonal disposition was measured using verified tool. Results: The results indicated that the ordinary type which gave and took the information generally showed the highest proportions in the study interaction network. Also, the empathic-acceptable tendency of social relation domain showed the highest proportions in the interpersonal disposition. Moreover, the students who play the isolate and the carrier role in the study interaction network had no relation with the expression tendency, and the transmitter role play students had no relation with the role tendency. Conclusion: Based on the results, the tutors should consider the students' interpersonal relationship disposition when implementing the instructional strategy in PBL curriculum.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.3
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• pp.163-172
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• 2016

Electric load forecasting is essential for effective power system planning and operation. Complex and nonlinear relationships exist between the electric loads and their exogenous factors. In addition, time-series load data has non-stationary characteristics, such as trend, seasonality and anomalous day effects, making it difficult to predict the future loads. This paper proposes a locally-weighted polynomial neural network (LWPNN), which is a combination of a polynomial neural network (PNN) and locally-weighted regression (LWR) for daily shortterm peak load forecasting. Model over-fitting problems can be prevented effectively because PNN has an automatic structure identification mechanism for nonlinear system modeling. LWR applied to optimize the regression coefficients of LWPNN only uses the locally-weighted learning data points located in the neighborhood of the current query point instead of using all data points. LWPNN is very effective and suitable for predicting an electric load series with nonlinear and non-stationary characteristics. To confirm the effectiveness, the proposed LWPNN, standard PNN, support vector regression and artificial neural network are applied to a real world daily peak load dataset in Korea. The proposed LWPNN shows significantly good prediction accuracy compared to the other methods.

• Journal of Korean Society of Rural Planning
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• v.24 no.3
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• pp.127-135
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• 2018

In countries and regions population plays an important role. Recently the importance of population migration increased as population growth slowed. Researches on population migration are mainly focused on the analysis of the population movement factors and the regional structure analysis using the network analysis method. Analysis of regional structure through population movement is not enough to explain the phenomenon of migration of small cities and rural regions. In this study, to overcome the limit of previous studies the characteristics of the population movement rate according to the size of the population were analyzed. Also network analysis using the population movement OD (Origin and Destination) and population movement rate OD were conducted and the results of them were compared. As the results of analysis by the regional population scale, the population movement by population size showed a big difference in the areas with more than 100 thousand people and less than 100 thousand people. Migration to the outside of the province was the most frequent in regions with 30,000~50,000 people. The population migration rate network analysis result showed that the new area with large population inflow capacity was identified, which could not be found in the population movement network analysis because population movement number is small. The population movement rate irate is expected to be used to identify the central regions of the province and to analyze the difference in resident attractiveness.

• Journal of the Korean Society of Safety
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• v.17 no.4
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• pp.196-201
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• 2002

Web-based predictive maintenance (PM) utilizes Virtual Device Network (VDN). VDN inevitably the implementation of Distributed Monitoring and Control Networks (DMCN). In general, one needs to integrate fieldbus protocol and TCP/IP to realize DMCN over IP network or internet, which can be viewed as Virtual Device Network (VDN). Interoperability between devices and equipments is essential to enhance the quality and the performance of predictive maintenance (PM). This paper investigates the transmission characteristics of VDN and suggests a basic framework for web-based PM using DMCN over IP network.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.2106-2119
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• 1997

NDAS(Network Data Access System) is a system that interconnects high speed network(B-ISDN) and Local Area Network(Ethernet, FDDI). Nowadays, the request of multimedia data increases rapidly, so NDAS system must accept and process that request efficiently. Comparing with normal data traffic characteristics, multimedia data traffic characteristics are much complex, so it is necessary to implement the system that can cover such factor. In this paper, we suggest a NDAS hardware system model and also we propose a proper buffer size of NDAS system through the simulation. For measuring the proper buffer size of NDAS, we assumed two different simulation models, one is the case of using only one buffer and the other is the case of using two different buffers for Ethernet and FDDI, respectively. After comparing and analyzing simulation results, we suggest the proper NDAS system buffer size.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.26-31
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• 2014

In this paper, we present performance analysis of video smoke detection based on BPN-Network that is using multi-smoke feature, and Neural Network. Conventional smoke detection method consist of simple or mixed functions using color, temporal, spatial characteristics. However, most of all, they don't consider the early fire conditions. In this paper, we analysis the smoke color and motion characteristics, and revised distinguish the candidate smoke region. Smoke diffusion, transparency and shape features are used for detection stage. Then it apply the BPN-Network (Back-Propagation Neural Network). The simulation results showed 91.31% accuracy and 2.62% of false detection rate.

• Journal of Distribution Science
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• v.22 no.3
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• pp.105-112
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• 2024

Purpose: This study analyzed the relationship between corporate capacity and management performance in the Korean distribution industry during the COVID-19 pandemic. Research design, data and methodology: The data for this study used the 2021 KOTRA GCL Test Data, and multiple regression analysis was performed using SPSS 26. As corporate competency, human capital and related capital of intellectual capital theory were utilized, and the global network level of social network theory was also utilized. As an additional analysis, corporate characteristics factors were used. Results: First, the level of global mindset of human capital acted as a positive factor in management performance, and the level of professional manpower did not achieve significant results. Second, related capital acted as a positive factor in corporate performance. Third, from the perspective of social network theory, the global network level of companies acted as a positive factor in management performance. Finally, the relationship between corporate characteristics and management performance was marginally significant. Conclusions: In order to improve the business performance of a company in a market shock such as the COVID-19 pandemic, it is required to strengthen the level of network construction with customers and increase the level of intellectual capital that a company has.

• The Korean Journal of Health Service Management
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• v.9 no.3
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• pp.233-246
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• 2015

Objectives : This study investigated the general characteristics, child rearing characteristics, and the level of self-differentiation of 120 custodial grandmothers. Methods : Data were collected with a self-administered questionnaire from 120 custodial grandmothers who registered Kinship Network in Busan City. Results : For the self-differentiation measure, the mean score of the sample was $2.52{\pm}0.51$. However, the level of the fusion with emotion $1.89{\pm}0.80$ was extremely low partly due to the influence of collectivist culture of Korean society. The levels of emotional reactivity and fusion with emotion were significantly low which were dependent on depression (F=4.387, p=0.015). Conclusions : The findings of this study show the need to improve the level of self-differentiation by increasing the score of emotional reactivity and fusion with the emotion among the kinship network grandmothers. Therefore, supportive programs for kinship network grandmothers need to develop self-differentiation.

• Journal of Information Technology Services
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• v.12 no.4
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• pp.145-164
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• 2013

With the rapidly expanding social network service, the distribution of information shows that social networks have evolved into platforms of communication and new information sharing among users. Previous studies are focused on the motivational factors of information sharing through social networking service. However, in this study, we focus on the factors that affect intention to share information in terms of both user's psychological motivation and functional characteristics of social network service. This study shows that factors such as enjoyfulness, image, identity and communication positively affect the attitude and intention of information sharing.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.284-287
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• 2017

This paper introduces liquid crystal (LC) alignment and its electro-optical properties in the LC cells with silver nanowire (AgNW) networks. The AgNW network was used as an electrode of LC cell as a substitute for an indium-tin-oxide (ITO) film. LC alignment characteristics in the LC cell using AgNW networks, which have two different sheet resistances of $60{\Omega}/m^2$ and $80{\Omega}/m^2$, were observed. The LC alignment characteristics including pretilt angle, LC alignment state, and thermal stability are similar irrespective of sheet resistance of AgNW network. However, twisted-nematic (TN)-LC cell normally operated when using AgNW network with sheet resistance of $80{\Omega}/m^2$. Electrooptical properties of TN-LC cell exhibited competitive performance compared to those of TN-LC cell based on conventional ITO electrode, which allow new approaches to replace conventional ITO electrode in display technology.