• Journal of the Korea Safety Management & Science
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• v.11 no.3
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• pp.63-71
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• 2009

Safety is totally established through not only legal regulations and system but the establishment of safety culture. As a foundation of safety culture, safety and health communication is the essential condition. Therefore, in the case of researching safety culture the communication network of a organization is a crucial factor. This study has analysed the structure of occupational safety and health communication between domestic and foreign corporations comparatively by the statistical analysis. The occupational safety and health communication is composed of four sub-dimensions: general communication in working site, using safety information communication, communication with the board of directors, and communication with labor union. The nationality of corporations influences the safety communication significantly except for communication with labor union. Consequently it is possible to infer that the nationality of corporations is a significant factor for safety communication network.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.8
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• pp.379-384
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• 2002

In the competitive electricity market, various pricing methods are developed and practiced in many countries. Among these pricing methods, marginal loss factor(MLF) can be applied to reflect the marginal cost of network losses. For the calculation of MLF, power flow method has been used to calculate system loss deviation. However, this power flow method shows some shortcomings such as necessity of regional reference node, and absence of an ability to consider network constraints like line congestion, voltage limit, and generation output limit. The former defect might affects adversely to the equity of market participants and the latter might generate an inappropriate price signals to customers and generators. To overcome these defects, the utilization of optimal power flow(OPF) is suggested to get the system loss deviation in this paper. 30-bus system is used for the case study to compare the MLF results by the power flow and the OPF method for 24-hour dispatching and pricing, Generator payment and customer charge are compared with these two methods also. The results show that MLF by OPF reflects the power system condition more faithfully than that of by the conventional power flow method

• Journal of Korean Society of Water and Wastewater
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• v.16 no.6
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• pp.686-699
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• 2002

The purpose of this study is to estimate deterioration factors and weighting factors in pipe network which each local self-governments takes rehabilitation and replacement work present time. Deterioration factors in pipe network are able to effected of specific province or location related with water supply. Most of water supply pipes are laid under the ground, it is hard to quantify deterioration degree of water system. Moreover, the timing and economic limitation and insufficient information on the spot survey gives a difficulty to look over how old water supply system is. Accordingly, this study collects and analyses five data as the laying environment, visual analysis, analysis of soil contents, analysis of pipe material, and questionary survey data in water pipe of A city. The deterioration factor estimates 14 factors with excavation and experimental analysis and 9 factors without excavation and experimental analysis. Also, the weighting factors are estimated by using the multiple linear regressions and the linear programming. The estimated deterioration factor and weighting results are compared the analysis result of visual, pipe material, and soil contents with the Probabilistic Neural Network Model. Consequently, the model results of estimated 9 factors in this study and 14 factors show the 1-2% difference. The result show that the proposed model could be used to decide the deterioration condition of pipe line with real excavation and experimental analysis.

• Knowledge Management Research
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• v.14 no.2
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• pp.71-88
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• 2013

The aim of this study was to investigate why people voluntarily contribute knowledge to others, primarily strangers, in the electronic network of practice for job examination expected potential competing. This paper is organized as follows. First, we introduce the electronic network of practice which is the knowledge sharing community for job examination, and discuss the key issues for understanding knowledge sharing in these networks on the basis of individual motivations, relational capital, sense of community, and sense of rivalry to develop a research model for this study. To test the proposed research model, we adopted the survey method for data collection, and examined our hypotheses by applying the multiple regression analysis method to the collected data. Our unit of analysis was the individual. The findings of this study show that the intention of knowledge sharing is influenced by the reputation and the enjoy helping as the factors of individual motivations, by the reciprocity as the factor of relational capital, and by a sense of rivalry as a psychological factor. Lastly, contributions of this study and future research opportunities are also discussed.

• Journal of Information Science Theory and Practice
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• v.9 no.2
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• pp.83-98
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• 2021

Research collaboration is an important strategy to improve research output, and virtual academic communities (VACs) have become an important platform to collaborate on. This paper reveals the influencing factors of researchers' collaboration intention in VACs from two attributes: individual, and inter-members. On the basis of the Social Cognitive Theory, Social Exchange Theory, social network theory, and Five-Factor Model, this paper constructed a model demonstrating the influencing factors of VACs researchers' collaboration intention. A self-administered questionnaire was employed on members of four VACs in China to collect data; subsequently, 558 usable responses were analyzed using structural equation modeling. The result showed that openness, conscientiousness, reciprocity, trust, and the social network characteristic had a significant influence on the collaboration intention of researchers in VACs, while self-efficacy, agreeableness, extroversion, neuroticism, and experience had no significant effects on the collaboration intention of researchers in VACs. This model plays a positive role in promoting the research collaboration intention of Chinese VACs researchers and in guiding the construction of VAC platforms.

• The Korea Journal of Herbology
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• v.34 no.6
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• pp.33-44
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• 2019

Objectives : This study aims to record and conserve oral traditional knowledge of medicinal animals from the indigenous people living in the local communities of Songnisan National Park, Korea. Methods : Data was collected by participatory observations and in-depth interviews with semi-structured questionnaires. Quantitative comparative analyses were accomplished through data received from the following three methods: informant consensus factor (ICF), fidelity level (FL), and network analysis. Results : The investigation reveals that the indigenous people have used 49 species of medicinal animals distributed within 45 genera, belonging to 39 families with 336 different usages. According to the distribution of recorded families, the most representative families were Scolpendridae and Phasianidae, which were utilized 36 times each (10.71 % each). The category with the highest degree of consensus from informants was disorders related to the nervous system (0.97). 16 species were classified with a fidelity level of 100 %. The network analysis revealed that a lack of vigor was related to 23 species, including Agkistrodon blomhoffii, Gallus domesticus, and Canis familiaris, among the total 49 species investigated. Conclusions : This documentation can help preserve the traditional knowledge and local health traditions of Korea that are disappearing due to rapid industrialization, urbanization, and death of the elderly with traditional knowledge. Additionally, the animals investigated in this study can be developed into medicinal food and drug for treating specific health conditions through further research.

• Smart Structures and Systems
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• v.29 no.4
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• pp.523-533
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• 2022

A novel metaheuristic search method, namely black widow optimization (BWO) is employed to increase the accuracy of slope stability analysis. The BWO is a recently-developed optimizer that supervises the training of an artificial neural network (ANN) for predicting the factor of safety (FOS) of a single-layer cohesive soil slope. The designed slope bears a loaded foundation in different distances from the crest. A sensitivity analysis is conducted based on the number of active individuals in the BWO algorithm, and it was shown that the best performance is acquired for the population size of 40. Evaluation of the results revealed that the capability of the ANN was significantly enhanced by applying the BWO. In this sense, the learning root mean square error fell down by 23.34%. Also, the correlation between the testing data rose from 0.9573 to 0.9737. Therefore, the postposed BWO-ANN can be promisingly used for the early prediction of FOS in real-world projects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3030-3049
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• 2023

With the development and wide application of hybrid network computing modes like cloud computing, edge computing and fog computing, the customer service requests and the collaborative optimization of various computing resources face huge challenges. Considering the characteristics of network environment resources, the optimized deployment of service resources is a feasible solution. So, in this paper, the optimal goals for deploying service resources are customer experience and service cost. The focus is on the system impact of deploying services on load, fault tolerance, service cost, and quality of service (QoS). Therefore, the alternate node filtering algorithm (ANF) and the adjustment factor of cost matrix are proposed in this paper to enhance the system service performance without changing the minimum total service cost, and corresponding theoretical proof has been provided. In addition, for improving the fault tolerance of system, the alternate node preference factor and algorithm (ANP) are presented, which can effectively reduce the probability of data copy loss, based on which an improved cost-efficient replica deployment strategy named ICERD is given. Finally, by simulating the random occurrence of cloud node failures in the experiments and comparing the ICERD strategy with representative strategies, it has been validated that the ICERD strategy proposed in this paper not only effectively reduces customer access latency, meets customers' QoS requests, and improves system service quality, but also maintains the load balancing of the entire system, reduces service cost, enhances system fault tolerance, which further confirm the effectiveness and reliability of the ICERD strategy.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.95-102
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• 2001

The design of automobile body assembly line is one of essential parts for improving the process performance. The major objective of this research is to develop a performance evaluation model for automobile assembly line using a closed queueing network(CQN) and simulation method. In this study we used a two-step approach to compute the performance of the assembly line : first, we used CQN model considering assembly line equipments and the line operating time under the assumption of no failure, and second we used a well-known simulator FACTOR/AIM. Finally we implemented this model on a K automobile company and we have shown the sample results of automobile body assembly line.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.8
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• pp.856-867
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• 1990

In this paper, the convergence and the learning accuracy of the back-propagation (BP) method in neural network are investigated by 1) analyzing the reason for decelerating the convergence of BP method and examining the rapid deceleration of the convergence when the learning is executed on the part of sigmoid activation function with the very small first derivative and 2) proposing the modified logistic activation function by defining, the convergence factor based on the analysis. Learning on the output patterns of binary as well as analog forms are tested by the proposed method. In binary output patter, the test results show that the convergence is accelerated and the learning accuracy is improved, and the weights and thresholds are converged so that the stability of neural network can be enhanced. In analog output patter, the results show that with extensive initial transient phenomena the learning error is decreased according to the convergence factor, subsequently the learning accuracy is enhanced.