• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.5
• /
• pp.817-826
• /
• 2023

In this paper, a fault determination methodology based on an artificial neural network was proposed to protect the system from faults on the lines in the smart grid distribution system. In the proposed methodology, first, it was designed to determine whether there is a low impedance line fault (LIF) based on the magnitude of the current RMS value, and if it is determined to be a normal current, it was designed to determine whether a high impedance ground fault (HIF) is present using Normal/HIF classifier based on artificial neural network. Among repetitive DSP module-based algorithm verification tests, the normal/HIF classifier recognized the current waveform as normal and did not show reclosing operation for the cases of normal state current waveform simulation test where the RMS value was smaller than the minimum operating current value. On the other hand, for the cases of LIF where RMS value is greater than the minimum operating current value, the validity of the proposed methodology could be confirmed by immediately recognizing it as a fault state and showing reclosing operation according to the prescribed procedure.

• Journal of Korea Technology Innovation Society
• /
• v.11 no.2
• /
• pp.145-170
• /
• 2008

The existence of network is indeed the single most important factor that brings about new business phenomena in the new digital economy, especially in the IT industry. Network effect refers to a phenomenon that the increase in size of the network leads to increased network value and user utility. It determines the competitive structure of an industry and the performances of industry competitors (Shapiro and Varian, 1999). The phenomenon of increasing returns and winner-take-all enjoyed by the early winner in the competition can be attributed to the existence of positive feedback which increases the value of network and induces more users into join the network (Arthur, 1996; Shapiro and Varian, 1999; Song and Lee, 2003). This research attempts to shed light on the topic of innovation and competitive strategy of network-based industries. We analyze the case of the Korean mobile communications industry, in which a shift in technological paradigm from 2G to 3G brought new changes to the competitive structure of the industry. The Korean mobile communications industry makes an ideal case for analysis since it is an industry whose value is inherently dependent upon its user network. It is characterized by the typical increasing returns, in which a monopolizing player is enjoying firstmover's network effects. Because of the existence of network in the mobile communications industry, latecomers' disruptive innovations could not outcompete the incumbent's sustaining innovations. The contribution of this research lies in laying a groundwork for future studies by introducing a numerical simulation model to analyze the complexity theory and network effect.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10b
• /
• pp.109-114
• /
• 1993

It is well known that neural networks can be used to diagnose multiple faults to some limited extent. In this work we present a Multiple Fault Diagnosis Method (MFDM) via neural network which can effectively diagnose multiple faults. To diagnose multiple fault, the proposed method finds the maximum value in the output nodes of the neural network and decreases the node value by changing the hidden node values. This method can find the other faults by computing again with the changed hidden node values. The effectiveness of this method is explored through a neural-network-based fault diagnosis case study of a fluidized catalytic cracking unit (FCCU).

• Convergence Security Journal
• /
• v.10 no.2
• /
• pp.51-57
• /
• 2010

This paper proposes extended trust evaluation mechanism which is able to become the standard of the node selection which provides a better service by using the basic transaction message which occurs from within the mobile Ad-hoc network and the additional transaction message and add confidence value. Furthermore, throughout the simulation shows the efficiency of the proposed trust evaluation mechanism.

• Proceedings of the KIEE Conference
• /
• 2006.10c
• /
• pp.154-156
• /
• 2006

These days wireless sensor networks receive much attention from industry and researchers on various fields. The challenge is that wireless sensor networks have limited resources. Nevertheless, the route discovery in ZigBee sensor networks is performed by simple flooding when the original racket is rebroadcasted at least once by every node in a network. Such uncontrolled flooding generates an excessive number of packets competing for the media and causes a high collision rate. In this article, we propose a suitable packet Time-To-Live value to solve problems of uncontrolled flooding in ZigBee networks. It is shown that more sufficient route discovery in a ZigBee network can save network resources and lengthen the life of a sensor network.

• Asia-Pacific Journal of Business
• /
• v.3 no.1
• /
• pp.29-38
• /
• 2012

This study aims at evaluating the impact of network formation variables and found to have positive impact on the economic performance and growth of the enterprises. The calucation of the weighted scores of networking statements brought some affirmative results to influence the performance of the enterprises. Through multiple regression and logistic regression models it is identified that network formation variables like service receiving status, consultation of the family, other business dummy and attendance in fair have some significant positive impact both on the growth and performance of the enterprises. In addition to above variables, from the set of enterprise characteristics natural logarithm of the market value of total assets and from the entrepreneurs' characteristics set of variables, schooling year and squared value of the experience have been found to have significant positive impact. Finally, it is concluded in the study that to enhance the performance and growth of the enterprises, government and policy rlated organizations need to consider important variables that have positive impact in supplying the entrepreneurial resources especially, developing the net-working relationship.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.12
• /
• pp.1055-1064
• /
• 2003

In many automated systems, such as manufacturing systems and process plants, a fieldbus is a very important component for the exchange of various and sometimes crucial information. Some of the information has a tendency to rapidly lose its value as time elapses after its creation. Such information or data is called real-time data that includes sensor values and control commands. In order to deliver these data in time, the fieldbus network should be tailored to have short delay with respect to the individual time limit of various data. Fine-tuning the network for a given traffic requires the knowledge on the relationship between the protocol parameters such as timer values and the performance measure such as network delay. This paper presents a mathematical performance model to calculate communication delays of the Profibus-FMS network when the timer value and the traffic characteristics are given.

• Proceedings of the KIEE Conference
• /
• 2004.05a
• /
• pp.105-107
• /
• 2004

In this work, we suggested the method which improves the efficiency of the face detection algorithm using Pulse-Coupled Neural Network. Face detection algorithm which uses the color information is independent on size, angle, and obstruction of a face. But the use of color information encounters some problems arising from skin-tone color in the background, intensity variation within faces, and presence of random noise, and so on. Depending on these conditions, we obtained the mean and variance of skin-tone colors by experiments. Then we introduce a preprocess that the pixel with a mean value of skin-tone colors has highest level value(255) and the other pixels in the skin-tone region have values between 0 and 255 according to a normal distribution with a variance. This preprocess leads to an easy decision of the linking parameters.

• Tunnel and Underground Space
• /
• v.6 no.1
• /
• pp.30-38
• /
• 1996

A two dimensional analysis program for groundwater flow in fractured network was developed to analyze the influence of discontinuity characteristics on groundwater flow. This program involves the generation of discontinuities and also connectivity analysis. The discontinuities were generated by the probabilistic density function(P.D.F.) reflecting the characteristics of discontinuities. And the fracture network model was completed through the connectivity analysis. This program also involves the analysis of groundwater flow through the discontinuity network. The result of numerical experiment shows that the equivalent hydraulic conductivity increased and became closer to isotropic as the density and trace length increased. And hydraulic head decreased along the fracture zone because of much water-flow. The grouting increased the groundwater head around cavern. An analysis of groundwater flow through discontinuity network was performed around underground oil storage cavern which is now under construction. The probabilistic density functions(P.D.F) were obtained from the investigation of the discontinuity trace map. When the anisotropic hydraulic conductivity is used, the flow rate into the cavern was below the acceptable value to maintain the hydraulic containment. But when the isotropic hydraulic conductivity is used, the flow rate was above the acceptable value.

• Journal of the Semiconductor & Display Technology
• /
• v.21 no.3
• /
• pp.130-134
• /
• 2022

An anti-reflective coating is used to improve the performance of the solar cell. The anti-reflective coating changes the value of the short-circuit current about the thickness. However, the current-voltage characteristics about the anti-reflective coating are difficult to calculate without simulation tool. In this paper, a modeling technique to determine the short-circuit current value and the current-voltage characteristics in accordance with the thickness is proposed. In addition, artificial neural network is used to predict the short-circuit current with the dependence of temperature and thickness. Simulation results incorporating the artificial neural network model are obtained using MATLAB/Simulink and show the current-voltage characteristic according to the thickness of the anti-reflective coating.