• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.57-65
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• 2022

DEA(data envelopment analysis) is a technique for evaluation of relative efficiency of decision making units (DMUs) that have multiple input and output. A DEA model measures the efficiency of a DMU by the relative position of the DMU's input and output in the production possibility set defined by the input and output of the DMUs being compared. In this paper, we proposed several DEA models measuring the multi-period efficiency of a DMU. First, we defined the input and output data that make a production possibility set as the spanning set. We proposed several spanning sets containing input and output of entire periods for measuring the multi-period efficiency of a DMU. We defined the production possibility sets with the proposed spanning sets and gave DEA models under the production possibility sets. Some models measure the efficiency score of each period of a DMU and others measure the integrated efficiency score of the DMU over the entire period. For the test, we applied the models to the sample data set from a long term university student training project. The results show that the suggested models may have the better discrimination power than CCR based results while the ranking of DMUs is not different.

• Journal of the Korean Mathematical Society
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• v.45 no.4
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• pp.1043-1056
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• 2008

The spanning column rank of an $m{\times}n$ matrix A over a semiring is the minimal number of columns that span all columns of A. We characterize linear operators that preserve the sets of matrix ordered pairs which satisfy multiplicative properties with respect to spanning column rank of matrices over semirings.

• Journal of the Korean Mathematical Society
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• v.45 no.2
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• pp.301-312
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• 2008

The spanning column rank of an $m{\times}n$ matrix A over a semiring is the minimal number of columns that span all columns of A. We characterize linear operators that preserve the sets of matrix pairs which satisfy additive properties with respect to spanning column rank of matrices over semirings.

• Bulletin of the Korean Mathematical Society
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• v.41 no.3
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• pp.427-434
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• 2004

The purpose of the paper is to correct erroneous proofs of two theorems of Walters ([1]) about the pressure of continuous transformations.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.146-146
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• 1996

Although knowledge discovery is increasingly important in databases, the discovered knowledge sets may not be effectively used for application domains. It is partly because knowledge discovery does not take user's interests into account, and too many knowledge sets are discovered to handle efficiently. We believe that user's interests are conveyed by a query and if a nested query is concerned it may include a user's thought process. This paper describes a novel concept for discovering knowledge sets based on query processing. Knowledge discovery process is performed by: extracting features from databases, spanning features to generate range features, and constituting a knowledge set. The contributions of this paper include the following: (1) not only simple queries but also nested queries are considered to discover knowledge sets regarding user's interests and user's thought process, (2) not only positive examples (answer to a query) but also negative examples are considered to discover knowledge sets regarding database abstraction and database exceptions, and (3) finally, the discovered knowledge sets are quantified.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.145-156
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• 1996

Although knowledge discovery is increasingly important in databases, the discovered knowledge sets may not be effectively used for application domains. It is partly because knowledge discovery does not take user's interests into account, and too many knowledge sets are discovered to handle efficiently. We believe that user's interests are conveyed by a query and if a nested query is concerned it may include a user's thought process. This paper describes a novel concept for discovering knowledge sets based on query processing. Knowledge discovery process is performed by: extracting features from databases, spanning features to generate range features, and constituting a knowledge set. The contributions of this paper include the following: (1) not only simple queries but also nested queries are considered to discover knowledge sets regarding user's interests and user's thought process, (2) not only positive examples (answer to a query) but also negative examples are considered to discover knowledge sets regarding database abstraction and database exceptions, and (3) finally, the discovered knowledge sets are quantified.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.472-478
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• 2017

In this paper, we deals with optimizing traffic signal timing in grid networks by using a network topology design method. Optimizing traffic signal timing includes minimizing delay time delay between departure and destination by interlocking straight traffic signal in the minimum spanning tree(MST). On the assumption that users of network abide by the paths provided in this paper, this paper shows optimizing traffic signal timing in grid networks. the paths provided in this paper is gathered by using Dijkstra algorithm used in computer networks. The results indicate minimizing delay time of passing through the grid network and interlocking traffic signal in the grid network.

• Tribology and Lubricants
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• v.36 no.6
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• pp.324-331
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• 2020

Wedging in a frictional elastic system is defined if the state of stick exists after the external loading on the system is removed. This paper presents a method to determine the critical coefficient of wedging for an elastic frictional system by considering the separation state. Wedging is always possible if the coefficient of friction exceeds a critical value known as the critical wedging coefficient. This method requires two concepts: a necessary and sufficient condition for wedging, which can be interpreted as positive spanning sets of constraint vectors existing in the wedged system, and the minimal positive basis that enables a minimum wedging coefficient. The algorithm based on the positive spanning concept is repeatedly executed after eliminating nodes from the contact stiffness matrix, for which the separation states are impending. The simulation results show that once a node enters the separation state, it never returns to the contact state again and the critical wedging coefficient reduces during repeated algorithm execution. The benefit of this method is that the computation time permits handling models with large numbers of contact nodes. The algorithm can also numerically find the critical wedging coefficient, thereby contributing to fastening and assembly performance improvements in mechanical systems.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.415-424
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• 2009

As one of the unsupervised learning neural network methods, self-organizing maps(SOM) are applied to various fields. It reduces the dimension of multidimensional data by representing observations on the low dimensional manifold. On the other hand, the minimal spanning tree(MST) of a graph that achieves the most economic subset of edges connecting all components by a single open loop. In this study, we apply the MST technique to SOM with subnodes. We propose SOM's with embedded MST and a distance measure for optimum choice of the size and shape of the map. We demonstrate the method with Fisher's Iris data and a real gene expression data. Simulated data sets are also analyzed to check the validity of the proposed method.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1367-1369
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• 2013

Applying Application-Level Multicast technology (ALM) to Distributed Interactive Applications (DIAs) becomes more and more popular. Especially for DIAs embedded priority that the sender forwards data to receivers due to their respective priorities. The priority-based directed minimum spanning tree (PST) algorithm was designed for these DIAs. However, the PST has no efficient priority selection and filtering mechanism. The system will consume a tremendous amount of resource for reconstructing distribution tree and becomes unstable and unscalable. In this paper, First, We propose a novel priority-based application level multicast algorithm: Predict-and-Quantize for Priority with directed minimum Spanning Tree (PQPST), which can efficiently predict efficient priorities for the receivers and quantize the predicted priorities to build the multicast distribution tree. Second, we propose Priority Discrepancy Heuristic Mechanism (PDHM), which sets different thresholds of priority discrepancy within the priority discrepancy interval to control the distribution tree construction can efficiently decrease the repeated distribution tree construction, and we get the best heuristic priority discrepancy interval by PQPST. According to the simulation results, the PQPST and PDHM can efficiently improve the performance of the PST algorithm.