• Journal of KIISE:Computing Practices and Letters
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• v.8 no.4
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• pp.389-398
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• 2002

As XML has been proposed a standard format for organizing and exchanging data in the internet, many applications on managing XML data have been developed. Especially, there are many studies for storing XML documents. It is important to evaluate the performance for efficient storage techniques. In this work, we suggest an efficient technique for storing XML documents using an object-relational database model. We verify the efficiency of a new storage technique through the performance evaluation on XML storage techniques. The contributions of this paper is that we suggest an efficient storage technique using an existing data management model and evaluate the performance for storage techniques for XML documents including an new storage technique.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.4133-4145
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• 2017

Advances in science and technology are driving us to the better life but also forcing us to make more investment at the same time. Therefore, the government has provided the investment to carry on the promising futuristic technology successfully. Indeed, a lot of resources from the government have supported into the science and technology R&D projects for several decades. However, the performance of the public investments remains unclear in many ways, so thus it is required that planning and evaluation about the new investment should be on data driven decision with fact based evidence. In this regard, the government wanted to know the trend and issue of the science and technology with evidences, and has accumulated an amount of database about the science and technology such as research papers, patents, project reports, and R&D information. Nowadays, the database is supporting to various activities such as planning policy, budget allocation, and investment evaluation for the science and technology but the information quality is not reached to the expectation because of limitations of text mining to drill out the information from the unstructured data like the reports and papers. To solve the problem, this study proposes a practical text mining methodology for the science and technology trend analysis, in case of aerospace technology, and conduct text mining methods such as ontology development, topic analysis, network analysis and their visualization.

• Journal of Welding and Joining
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• v.31 no.5
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• pp.35-40
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• 2013

In this paper, we propose the Tangible Virtual Reality Representation Method to using haptic device and feature to morphology of created bead from Flux Cored Arc Welding. The virtual reality was started to rising for reduce to consumable materials and welding training risk. And, we will expected maximize virtual reality from virtual welding training. In this paper proposed method is get the database to changing the input factor such as work angle, travelling angle, speed, CTWD. And, it is visualization to bead from extract to optimal morphological feature information to using the Neural Network algorithm. The database was building without error to extract data from automatic robot welder. Also, the Neural Network algorithm was set a dataset of the highest accuracy from verification process in many times. The bead was created in virtual reality from extract to morphological feature information. We were implementation to final shape of bead and overlapped in process by time to using bead generation algorithm and calibration algorithm for generate to same bead shape to real database in process of generating bead. The best advantage of virtual welding training, it can be get the many data to training evaluation. In this paper, we were representation bead to similar shape from generated bead to Flux Cored Arc Welding. Therefore, we were reduce the gap to virtual welding training and real welding training. In addition, we were confirmed be able to maximize the performance of education from more effective evaluation system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.61-74
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• 2012

In this paper, we propose a illumination-robust face recognition system using MCS-LBP and 2D-PCA algorithm. A binary pattern transform which has been used in the field of the face recognition and facial expression, has a characteristic of robust to illumination. Thus, this paper propose MCS-LBP which is more robust to illumination than previous LBP, and face recognition system fusing 2D-PCA algorithm. The performance evaluation of proposed system was performed by using various binary pattern images and well-known face recognition features such as PCA, LDA, 2D-PCA and ULBP histogram of gabor images. In the process of performance evaluation, we used a YaleB face database, an extended YaleB face database, and a CMU-PIE face database that are constructed under varying lighting condition, and the proposed system which consists of MCS-LBP image and 2D-PCA feature show the best recognition accuracy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.4
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• pp.681-691
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• 2017

In this research, life cycle inventory database (LCI DB) was developed for elastomeric bearing employing life cycle assessment (LCA) methodology additionally the reliability improvement rate in the evaluation of the environmental load of the bridge was analyzed. As are result of impact assessment by 6 major impact categories, production of elastomeric bearing puts on environmental impact in the order of resource depletion, global warming, photochemical oxidant creation. and among a wide variety of input, steel plates contributes in most of the impact categories. As a result of applying the elastomeric bearing LCI database constructed in this study, the environmental loads increased by 0.53% on average, and the cut-off based on the cost of input materials increased by 11.36%. It is anticipated that it will be possible to improve the credibility and to provide data based on current production technology, such as estimating GHG emissions and evaluating environmental load, by constructing elastomeric bearing LCI DB.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.21-30
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• 2002

The active database system introduces the active rules detecting specified state. As the condition evaluation of the active rules is performed every time an event occurs, the performance of the system has a great influence, depending on the conditions processing method. In this paper, we propose the conditions processing system with the preprocessor which determines the delta tree structure, constructs the classification tree, and generates the aggregate function table. Due to the characteristics of the active database through which the active rules can be comprehended beforehand, the preprocessor can be introduced. In this paper, the delta tree which can effectively process the join, selection operations, and the aggregate function is suggested, and it can enhance the condition evaluation performance. And we propose the classification tree which effectively processes the join operation and the aggregate function table processing the aggregate function which demands high cost. In this paper, the conditions processing system can be expected to enhance the performance of conditions processing in the active rules as the number of conditions comparison decreases because of the structure which is made in the preprocessor.

• Journal of KIISE:Databases
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• v.32 no.2
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• pp.142-150
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• 2005

A shared disks (SD) cluster couples multiple computing nodes, and every node shares a common database at the disk level. A great deal of research indicates that the SD cluster is suitable to high performance transaction processing, but the aggregation of SD cluster with real-time processing has not been investigated at all. A real-time transaction has not only ACID properties of traditional transactions but also time constraints. By adopting cluster technology, the real-time services will be highly available and can exploit inter-node parallelism. In this paper, we first develop an experiment model of an SD-based real-time database system (SD-RTDBS). Then we investigate the feasibility of real-time transaction processing in the SD cluster using the experiment model. We also evaluate the cross effect of real-time transaction processing algorithms and SD cluster algorithms under a wide variety of database workloads.

• Journal of Nutrition and Health
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• v.47 no.5
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• pp.364-373
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• 2014

Purpose: The purpose of this study was to develop a mercury database for food commonly consumed by Koreans. Methods: Target foods for a mercury database were selected from dietary survey data of the 2007-2009 Korean National Health and Nutrition Examination Survey (KNHANES). Data for mercury contents of foods were collected through literature review. Among 702 food items reported by 24 hr dietary recall method, the contents of mercury for 300 food items were selected with systematic evaluation from the literature, which provided analytical values, and those of 56 food items were imputed by using a conversion factor. Results: The mercury database developed in this study covered 50.7% of all kinds of consumed foods and 95.1% of total amount of food intake reported by 2007-2009 KNHANES. In the database, the geometric mean of mercury contents in food items was the highest in the fishes and shellfishes group ($41.13{\mu}g/kg$, n = 101) followed by mushrooms ($18.93{\mu}g/kg$, n = 12) and seaweeds ($5.92{\mu}g/kg$, n = 14), and the lowest in the meats group ($0.15{\mu}g/kg$, n = 17). Conclusion: The developed mercury database can be used to estimate the dietary mercury exposure of Korean people, and the method for development of a mercury database would be helpful to researchers in development of a new database for other food borne hazardous substances.

• Journal of KIISE:Databases
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• v.36 no.5
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• pp.374-385
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• 2009

Flash memory becomes increasingly popular as data storage for various devices because of its versatile features such as non-volatility, light weight, low power consumption, and shock resistance. Flash memory, however, has some distinct characteristics that make today's disk-based database technology unsuitable, such as no in-place update and the asymmetric speed of read and write operations. As a result, most traditional disk-based database systems may not provide the best attainable performance on flash memory. To maximize the database performance on flash memory, some approaches have been proposed where only the changes made to the database, i.e., logs, are written to another empty place that has born erased in advance. In this paper, we propose an efficient log management scheme for flash-based database systems. Unlike the previous approaches, the proposed approach stores logs in specially allocated blocks, called log blocks. By evenly distributing logs across log blocks, the proposed approach can significantly reduce the number of write and erase operations. Our performance evaluation shows that the proposed approaches can improve the overall system performance by reducing the number of write and erase operation compared to the previous ones.

• Journal of Korean Library and Information Science Society
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• v.40 no.2
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• pp.223-242
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• 2009

This is an exploratory study targeting initial users to evaluate the usability of an aggregator-supplied full-text database and to analyze the differences in task performance and perceptions based on participant characteristics. The differences in completion time and perceptions on ease of use, terminology, subject categories and satisfaction were analyzed based on the participant characteristics such as Kolb learning style, gender and participation in user instruction on full-text databases. The results indicated that there was a statistically significant difference in completion time based on the Kolb learning style. Also a statistically significant difference was found in perceptions on ease of use and terminology based on gender. However no statistically significant difference was found in perceptions on the usability of the database based on the participation in user instruction.