• Proceedings of the Safety Management and Science Conference
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• 2000.11a
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• pp.131-134
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• 2000

Broadband networks are designed to support a wide variety of services with different traffic characteristics and demands for Quality of Services. Bandwidth allocation methods can be classified into two major categories: static and dynamic. In static allocation, bandwidth is allocated only at call setup time and the allocated bandwidth is maintained during a session. In dynamic allocation, the allocated bandwidth is negotiated during a session. The purpose of this paper is to develop policies for deciding and for adjusting the amount of bandwidth requested for a best effort connection over such as ATM networks. This method is to develop such policies that a good trade off between utilization and latency using cell delay variation to the forecast the incoming traffic in the next period. The performances of the different polices are compared by simulations.

• Journal of the Korea Safety Management & Science
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• v.7 no.1
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• pp.199-210
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• 2005

Customer segmentation prediction has attracted a lot of research interests in previous literature, and recent studies have shown that artificial neural networks (ANN) method achieved better performance than traditional statistical ones. However, ANN approaches have suffered from difficulties with generalization, producing models that can overfit the data. This paper employs a relatively new machine learning technique, support vector machines (SVM), to the customer segmentation prediction problem in an attempt to provide a model with better explanatory power. To evaluate the prediction accuracy of SVM, we compare its performance with logistic regression analysis and ANN. The experiment results with real data of insurance company show that SVM superiors to them.

• Journal of the Korean Society of Safety
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• v.16 no.4
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• pp.213-217
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• 2001

Requirements for Device Networks differ greatly from those of typical data networks. Specifically, any device network technology which employs a fieldbus protocol is different from IP network protocol TCP/IP. In general, one needs to integrate fieldbus protocol and TCP/IP to realize device network over IP network or internet. Interoperability between devices and equipments is essential to enhance the quality and the performance of predictive maintenance(PM). This paper suggests a basic framework for web-based predicted maintenance and a method to guarantee interoperability between devices and equipments.

• Journal of the Korea Safety Management & Science
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• v.14 no.1
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• pp.137-145
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• 2012

In the previous study, the construction guide line of IT infra-structure for a u-City was introduced. However, it is only concentrated on the components and construction procedure for provider-oriented and technology-oriented sensor networks. In this paper the architecture and building process of demander-oriented sensor networks for sustainable u-City service are proposed. In the paper it is described (1) the enhancement methods of the procedure that can be flexibly constructed according to the scale of the project, (2) the methods that can improve the structure from the wireless sensor network such as RFID/USN to the hybrid sensor network, and (3) the consideration factors for providing the sustainable u-City service.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.9 no.3
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• pp.102-106
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• 2010

Recently process industries from oil and gas procedures and mining companies to manufactures of chemicals, foods, and beverages has been exploring the USN (Ubiquitous Sensor Networks) technology to improve safety of production processes. However, to apply the USN technology in the large-scale plant industry, reliability and security issues are not fully addressed yet, and the absence of the industrial sensor networking standard causes a compatibility problem with legacy equipment and systems. Although this situation, process industry such as energy plants are looking for the secure wireless plant solution to provide detailed, accurate safety monitoring from previously hard-reach, unaccordable area. In this paper, SPSF (Smart Plant Safety Framework based on Reliable-Secure USN) is suggested to fulfill the requirements of high-risk industrial environments for highly secure, reliable data collection and plant monitoring that is resistant to interference. The SPSF consists of three main layers: 1) Smart Safety Sensing Layer, 2) Smart Safety Network Layers, 3) Plant Network System Layer.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.1
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• pp.162-171
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• 2016

The purpose of this study was to examine the mediation of ego-resilience in the relationship between social capital and safety awareness safety pursuit behavior of adult learners in order to provide a basis for planning safety education to improve the safety behaviors. The participants were 162 adult learners who participated in the "Go to find safety classroom of citizens" in Changwon city. Data were collected using self-report questionnaires and analyzed with the SPSS-WIN 20.0 program. As a results, first, the mean score for social capital was 3.36(social confidence 3.38, reciprocal norms 3.29, networks 3.22, democratic citizen awareness 3.56), ego-resilience 3.57. Second, social capital was significant correlation ego-resilience(r=.63, p<.001) and safety awareness safety pursuit behavior(r=.44, p<.001). Third, ego-resilience was significant correlation safety awareness safety pursuit behavior(r=.54, p<.001). Forth, ego-resilience had a partial mediating effect in the relationship between social capital and safety awareness safety pursuit behavior. Based on these findings of this study, safety education focusing on ego-resilience and social capital improvement are highly recommended to promote safety behavior in adult learners.

• Safety and Health at Work
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• v.10 no.4
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• pp.400-408
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• 2019

The "fourth industrial revolution" (FIR) is an age of advanced technology based on information and communication. FIR has a more powerful impact on the economy than in the past. However, the prospects for the labor environment are uncertain. The purpose of this study is to anticipate and prepare for occupational health and safety (OHS) issues. In FIR, nonstandard employment will be common. As a result, it is difficult to receive OHS services and compensation. Excessive trust in new technologies can lead to large-scale or new forms of accidents. Global business networks will cause destruction of workers' biorhythms, some cancers, overwork, and task complexity. The social disconnection because of an independent work will be a risk for worker's mental health. The union bonds will weaken, and it will be difficult to apply standardized OHS regulations to multinational enterprises. To cope with the new OHS issues, we need to establish new concepts of "decent work" and standardize regulations, which apply to enterprises in each country, develop public health as an OHS service, monitor emerging OHS events and networks among independent workers, and nurture experts who are responsible for new OHS issues.

• Proceedings of the Korean Nuclear Society Conference
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• 2003.05a
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• pp.91-91
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• 2003

• Proceedings of the Korean Nuclear Society Conference
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• 2005.05a
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• pp.791-792
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• 2005

• Geomechanics and Engineering
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• v.6 no.1
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• pp.1-15
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• 2014

In this study, artificial neural network (ANN) and multiple regression (MR) models were developed to predict the critical factor of safety ($F_s$) of the homogeneous finite slopes subjected to earthquake forces. To achieve this, the values of $F_s$ in 5184 nos. of homogeneous finite slopes having different slope, soil and earthquake parameters were calculated by using the Simplified Bishop method and the minimum (critical) $F_s$ for each of the case was determined and used in the development of the ANN and MR models. The results obtained from both the models were compared with those obtained from the calculations. It is found that the ANN model exhibits more reliable predictions than the MR model. Moreover, several performance indices such as the determination coefficient, variance account for, mean absolute error, root mean square error, and the scaled percent error were computed. Also, the receiver operating curves were drawn, and the areas under the curves (AUC) were calculated to assess the prediction capacity of the ANN and MR models developed. The performance level attained in the ANN model shows that the ANN model developed can be used for predicting the critical $F_s$ of the homogeneous finite slopes subjected to earthquake forces.