• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.38
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• pp.9-15
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• 1996

The purpose of this research is to develop a method for part-machine grouping subject to production and management constraints. In the proposed integer programming model, minimization of operating and material-handling costs are considered as an objective function. The model allows one to recognize the existing parts and machines into disaggregated cells. New constraints are introduced in the model to resolve unbalancing capacity and bottleneck problems. It is found that this approach could have a better flexibility on cell size design for mote alternatives than conventional methods. Experimental grouping and comparison studies with ROC algorithm are given for evaluation purposes.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.780-783
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• 2002

This paper proposes an approximate LCA methodology fur the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes Into impact driver (ID) index. The relationship Is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then an artificial neural network model is developed to predict an approximate LCA of grouping products in conceptual design stage. The training is generalized by using identified product attributes for an ID In a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give an approximate LCA results for design concepts.

• Journal of Internet Computing and Services
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• v.9 no.1
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• pp.79-90
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• 2008

In the ubiquitous environment sensor network technologies have advanced for collecting information of the environment. With the rapid growth of sensor network technology, it is necessary and important to share the collected sensor data with a large base of diverse users. In order to provide dissemination of sensor data, we design an information dissemination system using an independent disseminator between provider and consumer. This paper describes how we designed the information dissemination system using one of the possible dissemination patterns for sensor networks, and an efficient matching algorithm called CGIM (Classed Grouping Index Matching) which employs a dynamic re-grouping scheme.

• Journal of Broadcast Engineering
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• v.13 no.2
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• pp.236-244
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• 2008

We propose a new building detection and description algorithm for Lidar data and photogrammetric imagery using color segmentation, line segments matching, perceptual grouping. Our algorithm consists of two steps. In the first step, from the initial building regions extracted from Lidar data and the color segmentation results from the photogrammetric imagery, we extract coarse building boundaries based on the Lidar results with split and merge technique from aerial imagery. In the secondstep, we extract precise building boundaries based on coarse building boundaries and edges from aerial imagery using line segments matching and perceptual grouping. The contribution of this algorithm is that color information in photogrammetric imagery is used to complement collapsed building boundaries obtained by Lidar. Moreover, linearity of the edges and construction of closed roof form are used to reflect the characteristic of man-made object. Experimental results on multisensor data demonstrate that the proposed algorithm produces more accurate and reliable results than Lidar sensor.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.2
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• pp.1-11
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• 2009

This study presents HCWS algorithm for researcher grouping on a weighted researcher network. The weights represent intensity of connections among researchers based on the number of co-authors and the number of co-authored research papers. To confirm the validity of the proposed technique, this study conducted an experimentation on about 80 research papers. As a consequence, it is proved that HCWS algorithm is able to bring about more realistic clustering compared with HCS algorithm which presents semantic relations among researchers in simple connections. In addition, it is found that HCWS algorithm can address the problems of existing HCS algorithm; researchers are disconnected since their connections are classified as weak even though they are strong, and vise versa. The technique described in this research paper can be applied to efficiently establish social networks of researchers considering relations such as collaboration histories among researchers or to create communities of researchers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.787-790
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• 2015

Recently, M2M (Machine to Machine) communication is possible the development of MTC (Machine Type Communication) devices becomes active. MCT devices in the form of home appliances have a low power consumption, low cost, short-range wireless communication in wireless home network. For purpose, MTC devices based on IEEE 802.15.4/Zigbee are composed in the form of cluster-tree topology, which consists of one PAN (Personal Area Network), one or other router and end of nodes. It happens that transmission delay, packet drop, and lacking data resulted from collision originated by a competition for allocating channels among MTC devices that greatly increased. At last performance of entire network can be degradated. This paper proposes that the beacon frame-based grouping algorithm using multiple channels in a MTC devices in the presence of wireless home network interference. The proposed algorithm decreases the transmission delay, dropped packet and throughput is more increase, so the proposal algorithm is more efficient than the IEEE 802.15.4/ Zigbee standard.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.2
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• pp.58-69
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• 1995

In this paper GFI (Generalized Fuzzy Isodata) and FI (Fuzzy Isodata) algorithms are studied and applied to the tire tread pattern classification problem. GFI algorithm which repeatedly grouping the partitioned cluster depending on the fuzzy partition matrix is general form of GI algorithm. In the constructing the binary tree using GFI algorithm cluster validity, namely, whether partitioned cluster is feasible or not is checked and construction of the binary tree is obtained by FDH clustering algorithm. These algorithms show the good performance in selecting the prototypes of each patterns and classifying patterns. Directions of edge in the preprocessed image of tire tread pattern are selected as features of pattern. These features are thought to have useful information which well represents the characteristics of patterns.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.4
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• pp.285-293
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• 2004

In this study, a machine grouping problem for the formation of manufacturing cells is considered. We constructed the problem as minimizing manufacturing leadtime consisting of parts' processing, moving, and waiting time. Specifically, the main objective of the defined problem is established as minimizing inter-cell traffic in order to minimize the part's moving time. In addition, to reduce the waiting time of parts, the load balance among cells is implicitly included as constraints. Since this problem is well known as NP-complete and cannot be solved in polynomial time, a genetic algorithm is implemented to obtain solutions. Also, a local optimization algorithm is applied in order to improve the solution by the genetic algorithm. Several experiments show that the suggested algorithms guarantee near optimal solutions in a few seconds.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.219-224
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• 2017

This paper is to introduce an application of face recognition algorithm in parallel. We have experiments of 25 images with different motions and simulated the image recognitions; grouping of the image vectors, image normalization, calculating average image vectors, etc. We also discuss an analysis of the related eigen-image vectors and a parallel algorithm. To develop the parallel algorithm, we propose a new type of initial matrices for eigenvalue problem. If A is a symmetric matrix, initial matrices for eigen value problem are investigated: the "optimal" one, which minimize ${\parallel}C-A{\parallel}_F$ and the "super optimal", which minimize ${\parallel}I-C^{-1}A{\parallel}_F$. In this paper, we present a general new approach to the design of an initial matrices to solving eigenvalue problem based on the new optimal investigating C with preserving the characteristic of the given matrix A. Fast all resulting can be inverted via fast transform algorithms with O(N log N) operations.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.995-996
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• 2008

This paper proposes a algorithm that generate the intermediate scene from the stereo image. This system based on mesh representation method, and segmented objects which ar calculated from triangles the pro proposed algorithm is composed of two steps. One is triangle grouping using gestalt theory, and the other is disparity estimation using average disparity of segmented object. We make an experiment on the proposed algorithm with some stereo images and obtain good quality disparity map for intermediate scenes.