• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.2 no.1
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• pp.35-40
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• 2004

Final disposal of radioactive waste generated from Nuclear Power Plant (NPP) requires the detailed information about the characteristics and the quantities of radionuclides in waste package. Most of these radionuclides are difficult to measure and expensive to assay. Thus it is suggested to the indirect method by which the concentration of the Difficult-to-Measure (DTM) nuclide is estimated using the correlations of concentration - it is called the scaling factor - between Easy-to-Measure (Key) nuclides and DTM nuclides with the measured concentration of the Key nuclide. In general, the scaling factor is determined by the log mean average (LMA) method and the regression method. However, these methods are inadequate to apply to fission product nuclides and some activation product nuclides such as 14$^{C}$ and 90$^{Sr}$ . In this study, the artificial neural network (ANN) method is suggested to improve the conventional SF determination methods - the LMA method and the regression method. The root mean squared errors (RMSE) of the ANN models are compared with those of the conventional SF determination models for 14$^{C}$ and 90$^{Sr}$ in two parts divided by a training part and a validation part. The SF determination models are arranged in the order of RMSEs as the following order: ANN model

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.119-124
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• 2021

Today, both sides of modern culture are decisively invaded by digitalization. Authentication is considered to be one of the main components in keeping this process secure. Cyber criminals are working hard in penetrating through the existing network channels to encounter malicious attacks. When it comes to enterprises, the company's information is a major asset. Question here arises is how to protect the vital information. This takes into account various aspects of a society often termed as hyper connected society including online communication, purchases, regulation of access rights and many more. In this research paper, we will discuss about the concepts of MFA and KBA, i.e., Multi-Factor Authentication and Knowledge Based Authentication. The purpose of MFA and KBA its utilization for human.to.everything..interactions, offering easy to be used and secured validation mechanism while having access to the service. In the research, we will also explore the existing yet evolving factor providers (sensors) used for authenticating a user. This is an important tool to protect data from malicious insiders and outsiders. Access Management main goal is to provide authorized users the right to use a service also preventing access to illegal users. Multiple techniques can be implemented to ensure access management. In this paper, we will discuss various techniques to ensure access management suitable for enterprises, primarily focusing/restricting our discussion to multifactor authentication. We will also highlight the role of knowledge-based authentication in multi factor authentication and how it can make enterprises data more secure from Cyber Attack. Lastly, we will also discuss about the future of MFA and KBA.

• Structural Engineering and Mechanics
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• v.18 no.4
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• pp.441-459
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• 2004

This paper explores the potential use of neural networks (NNs) in the field of contact mechanics. A neural network model is developed for predicting, with sufficient approximation, the contact lengths between the elastic layer and two elastic circular punches. A backpropagation neural network of three layers is employed. First contact problem is solved according to the theory of elasticity with integral transformation technique, and then the results are used to train the neural network. The effectiveness of different neural network configurations is investigated. Effect of parameters such as load factor, elastic punch radii and flexibilities that influence the contact lengths is also explored. The results of the theoretical solution and the outputs generated from the neural network are compared. Results indicate that NN predicted the contact length with high accuracy. It is also demonstrated that NN is an excellent method that can reduce time consumed.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.5
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• pp.791-796
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• 2013

Advent of the brain wave health care system is considered as an important issues in the industrial and research area in these days. It is necessary to detect EEG signals in real-time in order to support the medical emergency service for the epileptic or brain infarct patients. Since the efficient network support is an essential factor for the system, several topologies using sensor node based wireless body area network is suggested and simulated in this paper. Finally the Opnet simulation result is evaluated for the efficient topology of the body area network.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.102-105
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• 2012

ONVIF is becoming a de factor standard specification for supporting interoperability among network video products, which also supports a specification for video analytics service. A smart IP network camera is an IP network supporting video analytics. In this paper, we present our efforts in integrating ONVIF Video Analytics Service into our currently developing smart IP network camera(SS IPNC; Soongsil Smart IP Network Camera). SSIPNC supports object detection, tracking, classification, and event detection with proprietary configuration protocol and meta data formats. SSIPNC is based on TI' IPNC ONVIF implementation which supports ONVI Core specification, and several ONVIF services such as device service, imaging service and media service, but not video analytics service.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1216-1222
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• 2002

In this study, we suggest structural plans for constructing local network economically and optimal broad local network coincided with regional characteristics in building broad local network - the most important factor in constructing broadband superspeed service digital network giving the consideration to broadband multimedia service unfolded in the future. For the purpose of constructing optimal superspeed local network, we made comparative study of the topology types of star and ring in various conditions from a economical point of view per node and with the transmission distance.

• Proceedings of the KIEE Conference
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• 2009.04a
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• pp.216-218
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• 2009

In this paper, a real time monitoring and management system being operated in the ubiquitous environment was developed to monitor leakage current, load current, and arc-fault, and an electrical safety network for reasonable management of electrical risk factor was proposed. For confirmation of usefulness and reliability of the proposed safety network and system, the developed intelligent panels were applied to 28 Korean traditional houses in Jeonjoo city, and the network including the panels was operated. If the National Electrical Safety Network is completely constructed in the houses of general electrical users, the network will have an effect on that a main manager transfers from general people to expert. As a result, the electrical fires caused by an over-load, an arc-fault, and an earth-fault will be prevented.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.4
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• pp.480-487
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• 1999

In this paper we propose a neural network precompensated PID(NNP PID) controller for load frequency control of 2-area power system. While proportional integral derivative(PID) controllers are used in power system they have many problems because of high nonlinearities of the power system So a neural network-based precompensation scheme is adopted into a conventional PID controller to obtain a robust control to the nonlinearities. The applied neural network precompen-sator uses an error back-propagation learning algorithm having error and change of error as inputand considers the changing component of forward term of weighting factor for reducing of learning time. Simulation results show that the proposed control technique is superior to a conventional PID controller and an optimal controller in dynamic responses about load disturbances. The pro-posed technique can be easily implemented by adding a neural network precompensator to an existing PID controller.

• Journal of The Korean Association For Science Education
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• v.12 no.1
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• pp.93-101
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• 1992

The purposes of this study were; 1) to apply the network analysis to evaluation of students' laboratory reports, 2) to test the applicability of the systematic network analysis. For this purposes, 7th grade 88 students from 22 middle schools in Inchon city of Korea were selected and their laboratory reports were evaluated by a evaluation criterion network developed in this study. The evaluation criterion consisted of 4 categories and 10 subcategories. The results of this study suggested that the network analysis approach was suitable one for the evaluation of students' laboratory reports. This was supported by total score distribution, means/weight, Cronbach's ${\alpha}$ coefficient(0.70), and the subcategories' reliabilities. The resluts of the factor analysis indicated that the evaluation criterion network of this study had two factors.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.1-12
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• 2017

The competition to acquire customers with repurchase intention is getting more and more intense in the saturated smartphone market. That is why the aim of this study is to investigate the difference in purchasing determinants between various age groups and gender. Furthermore we aimed to analyze which of the purchasing determinants influence repurchase intention. In order to gather information we conducted a survey on 252 respondents. We selected 5 purchasing determinants (A/S, H/W, switching cost, network effect and design) by conducting factor analysis and validity analysis. Then we analyzed how respondents of different age groups and gender perceived different purchasing determinants and analyzed the influence purchasing determinants have on repurchase intention. As for analyzing the difference of purchasing determinants throughout various age groups, the H/W, A/S, network effect showed a notable difference. The older respondents tended to consider H/W, A/S, network effect more importantly than younger respondents. When it came to comparing the results depending on the gender, male respondents tended to consider H/W factor more importantly compared to female respondents and the opposite was true for other factors such as A/S, switching cost, design, and network effect but there weren't any significant differences. Finally, out of various determinant factors, network effect and design turned out to have a considerable influence on repurchase intention. That is why it would be highly appropriate to say that if a company intends to boost repurchase intention, enhancing network effect and developing an effective design would be crucial. This study differs from other existing researches in that we analyzed respondents from different age groups and gender separately. Also unlike other researches we directly analyzed the influence purchasing determinants have on repurchase intention not customer satisfaction. This study is expected to serve as basic information that can be used to establish strategies both in an academic and practical level, allowing companies to boost the repurchase intention of the smartphone market.