• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.369-378
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• 2004

In partially free word order languages like Korean and Japanese, the rule-based method is effective for text chunking, and shows the performance as high as machine learning methods even with a few rules due to the well-developed overt Postpositions and endings. However, it has no ability to handle the exceptions of the rules. Exception handling is an important work in natural language processing, and the exceptions can be efficiently processed in memory-based teaming. In this paper, we propose a hybrid of rule-based method and memory-based learning for Korean text chunking. The proposed method is primarily based on the rules, and then the chunks estimated by the rules are verified by memory-based classifier. An evaluation of the proposed method on Korean STEP 2000 corpus yields the improvement in F-score over the rules or various machine teaming methods alone. The final F-score is 94.19, while those of the rules and SVMs, the best machine learning method for this task, are just 91.87 and 92.54 respectively.

• 한국데이터정보과학회:학술대회논문집
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• 2005.10a
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• pp.177-188
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• 2005

Association rule mining searches for interesting relationships among items in a given large data set. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary threshold measures in association rule; support and confidence and lift. In the case of appling real world to association rules, we have some difficulties in data interpretation because we obtain many rules. In this paper, we develop the model of association rules using latent variables for environmental survey data.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.149-160
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• 2006

Association rule mining searches for interesting relationships among items in a given large data set. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary threshold measures in association rule; support and confidence and lift. In the case of appling real world to association rules, we have some difficulties in data interpretation because we obtain many rules. In this paper, we develop the model of association rules using latent variables for environmental survey data.

• Management Science and Financial Engineering
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• v.17 no.1
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• pp.79-94
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• 2011

Team orienteering, an extension of single-competitor orienteering, is the problem of determining multiple paths from a starting node to a finishing node for a given allowed time or distance limit fixed for each of the paths with the objective of maximizing the total collected score. Each path is through a subset of nodes, each of which has an associated score. The team orienteering problem has many applications such as home fuel delivery, college football players recruiting, service technicians scheduling, military operations, etc. Unlike existing optimal and heuristic algorithms often leading to heavy computation, this paper suggests two types of priority rule based heuristics-serial and parallel ones-that are especially suitable for practically large-sized problems. In the proposed heuristics, all nodes are listed in an order using a priority rule and then the paths are constructed according to this order. To show the performances of the heuristics, computational experiments were done on the small-to-medium sized benchmark instances and randomly generated large sized test instances, and the results show that some of the heuristics give reasonable quality solutions within very short computation time.

• Progress in Medical Physics
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• v.35 no.1
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• pp.16-19
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• 2024

A new E_n score of the proficiency test (PT) is formulated; it is applicable when a correlation exists between the reference and participant's values. Based on the uncertainty propagation rule given in ISO/IEC Guide 98-3 (GUM:1995), the E_n score covering the correlation case is newly developed for the PT. The new E_n score will be applied in a future PT organized by the Korea Research Institute of Standards and Science (KRISS) dosimetry team. The new E_n score will enhance measurement traceability and contribute to improving the quality management system of participants in the KRISS PT by avoiding performance underestimation.

• Neonatal Medicine
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• v.24 no.1
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• pp.26-31
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• 2017

Purpose: To identify the factors associated with differential diagnosis of neonatal bacterial meningitis at the earliest opportunities possible and to evaluate the value of the bacterial meningitis score especially in neonates. Methods: We conducted a single-center, retrospective study of neonates diagnosed meningitis at our hospital between January 2000 and March 2014. We compared the general characteristics, clinical manifestations, laboratory findings, bacterial meningitis scores between the bacterial group and the aseptic group. Results: Bacterial meningitis differs significantly from aseptic meningitis in platelet count, the cerebrospinal fluid polymorphonuclear leukocyte count, and the serum protein including also the albumin (P<0.05). Except two infants, the bacterial meningitis score over 2 accurately predict bacterial meningitis in the other 11 infants. Conclusion: The bacterial meningitis score appears highly useful to identify neonatal infants with bacterial meningitis. However, its diagnostic and prognostic value is just 'adjunctive', because low score cannot rule out bacterial meningitis.

• Journal of the Korea Society for Simulation
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• v.9 no.3
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• pp.77-89
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• 2000

This paper suggests a multi-attribute dispatching rule for an automated guided vehicle(AGV). The attributes to be considered are the number of queues in outgoing buffers of workstations, distance between an idle AGV and a workstation with a job waiting for the service of vehicle, and the number of queues in input buffers of the destination workstation of a job. The suggested rule is based on the simple additive weighting method using a normalized score for each attribute. A neural network approach is applied to obtain an appropriate weight vector of attributes based on the current status of the manufacturing system. Backpropagation algorithm is used to train the neural network model. The proposed dispatching rules and some single attribute rules are compared and analyzed by simulation technique. A number of simulation runs are executed under different experimental conditions to compare the several performance measures of the suggested rules and some existing single attribute dispatching rules each other.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.41 no.1
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• pp.44-51
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• 2009

Proper test methods and instruments for evaluating score or creasing crack have not been provided, although score crack trouble occurs frequently in manufacturing corrugated containers. Because existing creasability tester has the limitation of the available thickness of test piece and folding rate, it cannot be used for corrugated fiberboards with high thickness. In this study, we developed the laboratory test instrument and the method to determine the score or creasing crack of corrugated fiberboard. This instrument can evaluate folding resistance of corrugated board without restriction on the folding rate and thickness of specimen. Corrugated fiberboard had the different folding behavior from linerboard when it was creased. By using this test machine, score crack can be objectively determined by folding test piece to the certain folding angle with constant folding rate.

• Journal of the Korean Solar Energy Society
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• v.36 no.5
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• pp.9-18
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• 2016

G-SEED(Green Standard for Energy and Environmental Design) is the certification system to evaluate environmental friendliness of buildings for the purpose of reducing environmental burden generated from the entire process of buildings, which is classified into 4 grades according to the evaluated score. Green building certification rule regulate to get over green 2nd grade for the public office buildings of $3000m^2$ or more. However, detailed measures on the applied level of each issue to obtain targeted certification grade have not been prepared yet. For each issue, the score distribution and the ratio of score in proportion to credit were analyzed by certification grade for office buildings which get the G-SEED certification. And applied level of issues were presented for each certification grade.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.2
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• pp.174-182
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• 2013

Most methods for fusion-based finger vein recognition were to fuse different features or matching scores from more than one trait to improve performance. To overcome the shortcomings of "the curse of dimensionality" and additional running time in feature extraction, in this paper, we propose a finger vein recognition technology based on matching score-level fusion of a single trait. To enhance the quality of finger vein image, the contrast-limited adaptive histogram equalization (CLAHE) method is utilized and it improves the local contrast of normalized image after ROI detection. Gabor features are then extracted from eight channels based on a bank of Gabor filters. Instead of using the features for the recognition directly, we analyze the contributions of Gabor feature from each channel and apply a weighted matching score-level fusion rule to get the final matching score, which will be used for the last recognition. Experimental results demonstrate the CLAHE method is effective to enhance the finger vein image quality and the proposed matching score-level fusion shows better recognition performance.