• ETRI Journal
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• v.33 no.3
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• pp.344-354
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• 2011

In this paper, a model is introduced named double relation chains (DRC) based on ordered sets. It is proved that using DRC and special relationships among the members of an alphabet, vectors of this alphabet can be stored and searched in a tree. This idea is general; however, one special application of DRC is the longest prefix matching (LPM) problem in an IP network. Applying the idea of DRC to the LPM problem makes the prefixes comparable like numbers using a pair of w-bit vectors to store at least one and at most w prefixes, where w is the IP address length. This leads to good compression performance. Based on this, two recently introduced structures called coded prefix trees and scalar prefix trees are shown to be specific applications of DRC. They are implementable on balanced trees which cause the node access complexity for prefix search and update procedures to be O(log n) where n is the number of prefixes. As another advantage, the number of node accesses for these procedures does not depend on w. Additionally, they need fewer number of node accesses compared to recent range-based solutions. These structures are applicable on both IPv4 and IPv6, and can be implemented in software or hardware.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.153-162
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• 2008

We propose a novel image inpainting method composed of two parts: band matching and seamless cloning. In band matching, a band enclosing the boundary of a missing region is compared to those from the other parts of the image. The inner area of the minimum difference band is then copied to the missing region. Even though this band matching results in successful inpainting in many practical applications, brightness discontinuity (a seam) may appear between the filled missing region and its neighborhood. We apply seamless cloning to remove such discontinuity between the two regions. However, since this basic method using one patch may not deal with cases where there are abrupt changes of color or brightness along the boundary, we furthermore devise one more step: target sub-division. The target area is subdivided into small sub-areas, and the band matching and seamless cloning are applied to each of them. The multiple results from the sub-division are then ordered according to inpainting quality, which is measured based on the edge map or discontinuity map along the boundary band.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.829-846
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• 2017

Purpose: This paper compares the effectiveness of typical selective assembly criteria and suggests the most promising one. Based on the result of a computer simulation, the key issues of selective assembly are examined and the best criterion is recommended from the effectiveness perspective. Methods: Using JAVA program, production of ten thousand units for each pair of components are simulated for selective assembly of the two types. And the number of mismatching and the fraction nonconforming for each criterion are determined. Results: The best match criterion appeared to be most promising from the perspectives of both mismatching and nonconforming problems. Its effectiveness appears to be also good even when the precision of one component is different from that of the other. Conclusion: For designing an optimal method for selective assembly, the best match criterion is recommendable as the base criterion.

• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.81-97
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• 2024

This study examines the effects of adopting Information and Communication Technology (ICT) in livestock farm management on farm sales revenue. Using the 2020 Census of Agriculture, Forestry, and Fisheries, a nationally representative data set constructed by Statistics Korea, this study focuses on a sample of 9,020 livestock farms in South Korea. We employ Propensity Score Matching (PSM) methods to address the potential selection bias between 2,076 farms that used ICT for livestock farm management and 6,944 farms that did not. The findings consistently show that the use of ICT significantly increases farm revenue, taking into account the selection bias. The utilization of ICT in livestock farms leads to a higher increase in sales revenue, particularly for farms with greater sales.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2061-2074
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• 1998

In pattern recognition and image analysis upplications, a graph is a useful tool for complex obect representation and recognition. However it takes much time to pair proper nodes between the prototype graph and an input data graph. Futhermore it is difficult to decide whether the two graphs in a class are the same hecause real images are degradd in general by noise and other distortions. In this paper we propose a matching algorithm using a matrix. The matrix is suiable for simple and easily understood representation and enables the ordering and matching process to be convenient due to its predefined matrix manipulation. The nodes which constitute a gaph are ordered in the matrix by their geometrical positions and this makes it possible to save much comparison time for finding proper node pairs. for the classification, we defined a distance measure thatreflects the symbo's structural aspect that is the sum of the mode distance and the relation distance; the fornet is from the parameters describing the node shapes, the latter from the relations with othes node in the matrix. We also introduced a subdivision operation to compensate node merging which is mainly due t the prepreocessing error. The proposed method is applied to the recognition of musteal symbols and the result is given. The result shows that almost all, except heavily degraded symbols are recognized, and the recognition rate is approximately 95 percent.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.43-51
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• 2006

This paper proposes a metrics for example matching under the example-based machine translation for English-Korean machine translation. Our metrics served as similarity measure is based on edit-distance algorithm, and it is employed to retrieve the most similar example sentences to a given query. Basically it makes use of simple information such as lemma and part-of-speech information of typographically mismatched words. Edit-distance algorithm cannot fully reflect the context of matched word units. In other words, only if matched word units are ordered, it is considered that the contribution of full matching context to similarity is identical to that of partial matching context for the sequence of words in which mismatching word units are intervened. To overcome this drawback, we propose the context-weighting scheme that uses the contiguity information of matched word units to catch the full context. To change the edit-distance metrics representing dissimilarity to similarity metrics, to apply this context-weighted metrics to the example matching problem and also to rank by similarity, we normalize it. In addition, we generalize previous methods using some linguistic information to one representative system. In order to verify the correctness of the proposed context-weighted metrics, we carry out the experiment to compare it with generalized previous methods.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.5
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• pp.102-108
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• 1996

Adaptive resonance theory (ART2) characterized by its built-in mechanism of handling the stability-plasticity switching and by the adaptive learning without forgetting informations learned in the past, is based on an unsupervised template matching. We propose an improved tow-stage learning algorithm for aRT2: the original unsupervised learning followed by a new supervised learning. Each of the output nodes, after the unsupervised learning, is labeled according to the category informations to reinforce the template pattern associated with the target output node belonging to the same category some dominant classes from exhausting a finite number of template patterns in ART2 inefficiently. Experimental results on a set of 2545 FLIR images show that the ART2 trained by the two-stage learning algorithm yields better accuracy than the original ART2, regardless of th esize of the network and the methods of evaluating the accuracy. This improvement shows the effectiveness of the two-stage learning process.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.179-182
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• 2003

This study describes a new graphical method for assessing and characterizing effect modification by a matching covariate in matched case-control studies. This method to understand effect modification is based on a semiparametric model using a varying coefficient model. The method allows for nonparametric relationships between effect modification and other covariates, or can be useful in suggesting parametric models. This method can be applied to examining effect modification by any ordered categorical or continuous covariates for which cases have been matched with controls. The method applies to effect modification when causality might be reasonably assumed. An example from veterinary medicine is used to demonstrate our approach. The simulation results show that this method, when based on linear, quadratic and nonparametric effect modification, can be more powerful than both a parametric multiplicative model fit and a fully nonparametric generalized additive model fit.

• International Journal of Contents
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• v.8 no.3
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• pp.83-93
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• 2012

In this paper, we propose a novel method that automatically generates real character images to familiarize existing OCR systems with new fonts. At first, we generate synthetic character images using a simple degradation model. The synthetic data is used to train an OCR engine, and the trained OCR is used to recognize and label real character images that are segmented from ideal document images. Since the OCR engine is unable to recognize accurately all real character images, a substring matching method is employed to fix wrongly labeled characters by comparing two strings; one is the string grouped by recognized characters in an ideal document image, and the other is the ordered string of characters which we are considering to train and recognize. Based on our method, we build a system that automatically generates 2350 most common Korean and 117 alphanumeric characters from new fonts. The ideal document images used in the system are postal envelope images with characters printed in ascending order of their codes. The proposed system achieved a labeling accuracy of 99%. Therefore, we believe that our system is effective in facilitating the generation of numerous character samples to enhance the recognition rate of existing OCR systems for fonts that have never been trained.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.102-105
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• 2010

Traditional Pub/Sub(Publish/Subscribe) Systems search all subscriptions that match an incoming event by broker(i.e. it is not considering the accuracy of matching between an incoming event and subscriptions and only consider that an event either matches a subscription or not). However, subscriptions that match an event may have priority, therefore, we need priority Pub/Sub system. In this paper, we define what the accuracy means in order to prioritize among subscriptions and propose the Priority Retrieval Technique based on accuracy that able to search subscriptions. The Priority Retrieval Technique is based on IS-Lists. We can search the results ordered by accuracy.