• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.780-791
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• 1996

A hybrid image processing system which automatically distinguished lean tissues in the image of a complex beef cut surface and generated the lean tissue contour has been developed. Because of the in homegeneous distribution and fuzzy pattern of fat and lean tissue on the beef cut, conventional image segmentation and contour generation algorithm suffer from a heavy computing requirement, algorithm complexity and poor robustness. The proposed system utilizes an artificial neural network enhance the robustness of processing. The system is composed of pre-network , network and post-network processing stages. At the pre-network stage, gray level images of beef cuts were segmented and resized to be adequate to the network input. Features such as fat and bone were enhanced and the enhanced input image was converted tot he grid pattern image, whose grid was formed as 4 X4 pixel size. at the network stage, the normalized gray value of each grid image was taken as the network input. Th pre-trained network generated the grid image output of the isolated lean tissue. A training scheme of the network and the separating performance were presented and analyzed. The developed hybrid system showed the feasibility of the human like robust object segmentation and contour generation for the complex , fuzzy and irregular image.

• Journal of Korea Trade
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• v.27 no.4
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• pp.61-76
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• 2023

Purpose - Along with emerging international entrepreneurship, there is a need for exploring the influencing mechanism of dual network embeddedness of the host country on international entrepreneurial performance. Drawing on network embeddedness theory and organizational improvisational theory, the present study constructs a theoretical model regarding the logic relationships between the dual network embeddedness of the host country, organizational improvisational capability, and international entrepreneurial performance. Design/methodology - Using a questionnaire survey, our study conducted data in two ways. The final research sample comprised 129 international new ventures. To test the hypotheses, a three-step mediation test method was conducted. Findings - Our empirical results suggested that both host-country social network embeddedness and industrial network embeddedness significantly affected the international entrepreneurial performance. Organizational improvisational capability significantly affected the international entrepreneurial performance. Third, organizational improvisational capability partially played mediating role in the relationship between the dual network embeddedness of the host country and international entrepreneurial performance. Originality/value - This study mainly concentrates on the two important types of host-country networks, host-country social network embeddedness and industrial network embeddedness, that may help international new ventures access the strategic resources necessary to support performance. Thus, it extends the existing network embeddedness theory and improvisational theory to encompass international entrepreneurship.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.53-62
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• 2023

Effects-Based Operations (EBO) refers to a process for achieving strategic goals by focusing on effects rather than attrition-based destruction. For a successful implementation of EBO, identifying key nodes in an adversary network is crucial in the process of EBO. In this study, we suggest a network-based approach that combines network centrality and optimization to select the most influential nodes. First, we analyze the adversary's network structure to identify the node influence using degree and betweenness centrality. Degree centrality refers to the extent of direct links of a node to other nodes, and betweenness centrality refers to the extent to which a node lies between the paths connecting other nodes of a network together. Based on the centrality results, we then suggest an optimization model in which we minimize the sum of the main effects of the adversary by identifying the most influential nodes under the dynamic nature of the adversary network structure. Our results show that key node identification based on our optimization model outperforms simple centrality-based node identification in terms of decreasing the entire network value. We expect that these results can provide insight not only to military field for selecting key targets, but also to other multidisciplinary areas in identifying key nodes when they are interacting to each other in a network.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.6
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• pp.38-46
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• 2012

In this paper, the necessity for the identification of the absolute phase value is introduced and analyzed for a particular conductor line of a 3-phase type distribution network and the recent methods are also introduced. For the determination of the exact phase value for a specific point in the line, as compared with the phase reference point, the measured phase value must be within a range of ${\pm}60[^{\circ}]$. However, the phase of a particular point can fluctuate depending on the line constant, transformer wiring method, line length, line amperage, etc. A theoretical formulation such as Simulink modeling and analysis for a distribution network are conducted for the identification of phase at a specific point in the line. In particular, through evaluating the effects of unbalanced current loads at the time of determination of the phase value, the limitations of the present method for the determination of phases is described.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1999-2005
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• 2005

Collaboration in wireless sensor networks must be fault-tolerant due to the harsh environmental conditions in which such networks can be deployed. This paper focuses on finding signal processing algorithms for collaborative target detection based on the generalized approach to signal processing in the presence of noise that are efficient in terms of communication cost, precision, accuracy, and number of faulty sensors tolerable in the wireless sensor network. Two algorithms, namely, value fusion and decision fusion constructed according to the generalized approach to signal processing in the presence of noise, are identified first. When comparing their performance and communication overhead, decision fusion is found to become superior to value fusion as the ratio of faulty sensors to fault free sensors increases. The use of the generalized approach to signal processing in the presence of noise under designing value and decision fusion algorithms in wireless sensor networks allows us to obtain the same performance, but at low values of signal energy, as under the employment of universally adopted signal processing algorithms widely used in practice.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.4
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• pp.381-387
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• 2002

In this paper, an efficient method to find shot boundaries in the MPEG video stream data is proposed. For this purpose, we first assume that the histogram difference value(HDV) and pixel difference value(PDV) as an one dimensional signal and apply the median filter to these signals. The output of the median filter is subtracted from the original signal to produce the median filtered difference(MFD). The MFD is a criterion of shot boundary. In addition a neural network is employed and trained to find exactly cut boundary. The proposed algorithm shows that the cut boundaries are well extracted, especially in a dynamic video.

• Journal of Power Electronics
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• v.15 no.4
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• pp.1139-1147
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• 2015

In this paper, an algorithm based on a model analysis of the online calculation of the root-mean-square (RMS) value of welding current for single-phase AC resistance spot welding (RSW) was developed. The current is highly nonlinear and typically non-sinusoidal, which makes the measuring and controlling actions difficult. Though some previous methods focused on this issue, they were so complex that they could not be effectively used in general cases. The electrical model of a single-phase AC RSW was analyzed, and then an algorithm for online calculation of the RMS value of the welding current was presented. The description includes two parts, a model-dependent part and a model-independent part. Using a previous work about online measurement of the power factor angle, the first part can be solved. For the second part, although the solution of the governing equation can be directly obtained, a lot of CPU time must be consumed due to the fact that it involves a lot of complex calculations. Therefore, a neural network was employed to simplify the calculations. Finally, experimental results and a corresponding analysis showed that the proposed algorithm can obtain the RMS values with a high precision while consuming less time when compared to directly solving the equations.

• ETRI Journal
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• v.43 no.4
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• pp.674-683
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• 2021

A trust-aware secure routing protocol (TSRP) for wireless sensor networks is proposed in this paper to defend against varieties of attacks. First, each node calculates the comprehensive trust values of its neighbors based on direct trust value, indirect trust value, volatilization factor, and residual energy to defend against black hole, selective forwarding, wormhole, hello flood, and sinkhole attacks. Second, any source node that needs to send data forwards a routing request packet to its neighbors in multi-path mode, and this continues until the sink at the end is reached. Finally, the sink finds the optimal path based on the path's comprehensive trust values, transmission distance, and hop count by analyzing the received packets. Simulation results show that TSRP has lower network latency, smaller packet loss rate, and lower average network energy consumption than ad hoc on-demand distance vector routing and trust based secure routing protocol.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1241-1248
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• 2004

A controller of wheeled mobile robot(WMR) based on Lyapunov theory is designed and a Fuzzy-Neural Network algorithm is applied to this system to adjust controller gain. In conventional controller of WMR that adopts fixed controller gain, controller can not pursuit trajectory perfectly when initial condition of system is changed. Moreover, acquisition of optimal value of controller gain due to variation of initial condition is not easy because it can be get through lots of try and error process. To solve such problem, a Fuzzy-Neural Network algorithm is proposed. The Fuzzy logic adjusts gains to act up to position error and position error rate. And, the Neural Network algorithm optimizes gains according to initial position and initial direction. Computer simulation shows that the proposed Fuzzy-Neural Network controller is effective.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.467-470
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• 1998

In this paper, we propose a matrix star graph which improves the network cost of the well-known star grah as an interconnection network. We analyze its characteristics in terms of the network parameters, such as degree, scalability, routing, and diameter. The proposed matrix star graph MS2,n has the half degrees of a star graph S2n with the same number of nodes and is an interconnection network with the properties of node symmetry, maximum fault tolerance, and recursive structure. In network cost, a matrix star graph MS2,n and a star graph S2n are about 3.5n2 and 6n2 respectively which means that the former has a better value by a certain constant than the latter has.