• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3706-3714
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• 2011

This study deals with the algorithm to finding the maximum capacity and their schedule of extra freight while honoring planned timetable of trains on railway network. Time-expanded network, a kind of space-time graph, can be shown both planned train timetable and dynamic features of given problem. Pre-processing procedure is a series of infeasible arcs removal from time-expanded network honoring planned timetable. In the result, this preprocessing transforms dynamic features of given problem into static maximal flow problem which can be easily solved.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.37
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• pp.211-220
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• 1996

We consider the problem of scheduling a maximal amount of additional, low priority transport through a large multiperiod network, given that we may not interfere with an existing schedule for high priority transport. The problem is transformed into the Time-Expanded network(TENET) without traverse time using TENET Generator (TENETGEN). We describe two specialized heuristic algorithms that guarantee the optimal solutions and show the effectiveness of them by comparing quite favorably with Dinic.

• Journal of Korean Society of Transportation
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• v.8 no.2
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• pp.67-75
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• 1990

This paper treats the problem to schedule for trains with how transit priority so as to maximizing the number that can be sent during given time periods without interfering with the fixed schedule for train with high transit priority in a track. We transform the this problem into Time Expanded Network without traverse time through application of Ford and Fulkerson Model and construct the Enumeration Algorithm for solutions using TENET Generator (TENETGEN). Finally, we compare our algorithm with Dinic's Maximal-Flow Algorithm and examine the avaliability of our procedures in personal computer.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.1
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• pp.37-44
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• 2015

In traditional social network analysis, the betweenness centrality measure has been heavily used to identify the relative importance of nodes. Since the time complexity to calculate the betweenness centrality is very high, however, it is difficult to get it of each node in large-scale social network where there are so many nodes and edges. In our past study, we defined a new type of network, called the expanded ego network, which is built only with each node's local information, i.e., neighbor information of the node's neighbor nodes, and also defined a new measure, called the expanded ego betweenness centrality. In this paper, We propose algorithm that quickly computes expanded ego betweenness centrality by exploiting structural properties of expanded ego network. Through the experiment with virtual network used Barab$\acute{a}$si-Albert network model to represent the generic social network and facebook network to represent actual social network, We show that the node's importance rank based on the expanded ego betweenness centrality has high similarity with that the node's importance rank based on the existing betweenness centrality. We also show that the proposed algorithm computes the expanded ego betweenness centrality quickly than existing algorithm.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.5
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• pp.209-216
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• 2013

In traditional social network analysis, the betweenness centrality measure has been heavily used to identify the relative importance of nodes in terms of message delivery. Since the time complexity to calculate the betweenness centrality is very high, however, it is difficult to get it of each node in large-scale social network where there are so many nodes and edges. In this paper, we define a new type of network, called the expanded ego network, which is built only with each node's local information, i.e., neighbor information of the node's neighbor nodes, and also define a new measure, called the expended ego betweenness centrality. Through the intensive experiment with Barab$\acute{a}$si-Albert network model to generate the scale-free networks which most social networks have as their embedded feature, we also show that the nodes' importance rank based on the expanded ego betweenness centrality has high similarity with that based on the traditional betweenness centrality.

• Journal of the Korea Safety Management & Science
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• v.12 no.1
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• pp.97-104
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• 2010

Expanded muti-source Weber problem (EWP), which introduced in this paper, is a reverse logistics network design problem to minimize the total transportation cost from customers thorough regional center to central center. Decision factor of EWP are the locations of regional centers and a central center. We introduce a GRASP heuristics for the EWP. In the suggested GRASP, an expanded iterative location allocation method (EILA) is introduced based on the Cooper's iterative location allocation method[3]. For the initial solution of GRASP, allocation first seed (AFSeed) and location first seed (LFSeed) are developed. The computational experiment for the objective value shows that the LFSeed is better than the AFSeed. Also the calculating time of the LFSeed is better than that of the AFSeed.

• IE interfaces
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• v.4 no.2
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• pp.25-34
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• 1991

The problem of scheduling the passage things with low transit priority to maximize the amonnt that can be sent during given time periods without interfering with the fixed schedule for passage things with high transit priority in a track, is treated in this paper. The problem is transformed into the Time Expanded Network without traverse time through the Ford and Fulkerson Model and the Enumeration Algorithm is developed for solutions using TENET GENerator(TENETGEN). Finally, the proposed algorithm is compared with Dinic's maximal-flow algorithm and examined for the availability of the procedures on the personal computer.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1113-1119
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• 2000

To operate a process plant safely and economically, process monitoring is very important. Process monitoring is the task to identify the state of the system from sensor data. Process monitoring includes data acquisition, regulatory control, data reconciliation, fault detection, etc. This research focuses on the data recon-ciliation using scale-space filtering and fault detection using functional-link associative neural networks. Scale-space filtering is a multi-resolution signal analysis method. Scale-space filtering can extract highest frequency factors(noise) effectively. But scale-space filtering has too large calculation costs and end effect problems. This research reduces the calculation cost of scale-space filtering by applying the minimum limit to the gaussian kernel. And the end-effect that occurs at the end of the signal of the scale-space filtering is overcome by using extrapolation related with the clustering change detection method. Nonlinear principal component analysis methods using neural network have been reviewed and the separately expanded functional-link associative neural network is proposed for chemical process monitoring. The separately expanded functional-link associative neural network has better learning capabilities, generalization abilities and short learning time than the exiting-neural networks. Separately expanded functional-link associative neural network can express a statistical model similar to real process by expanding the input data separately. Combining the proposed methods-modified scale-space filtering and fault detection method using the separately expanded functional-link associative neural network-a process monitoring system is proposed in this research. the usefulness of the proposed method is proven by its application a boiler water supply unit.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1999.11a
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• pp.256-261
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• 1999

Many control techniques have been proposed in order to improve the control performance of discrete-time domain control system. In the position control system using a DC servo motor as control system, the response-characteristic of system is controlled by the I-PD controller. In the I-PD longer if gains of I-PD controller are unsuitable. In this paper, therefore, a expanded I-PD control system is constructed by inserting a pre-compensator at out terminal of I-PD controller. It is implemented by neural network with two hidden layers. From the result of computer simulation in the proposed control algorithm, its usefulness is verified.

• Journal of Korea Game Society
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• v.18 no.5
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• pp.15-22
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• 2018

Currently, there are many augmented reality content, but little has been commercialized that two or more terminals communicate in real time and use at the same time. In this paper, we are going to study the possibility of network augmented reality contents using Bluetooth communication. Through this research, network augmented reality development and contents will be expanded further.