• Journal of Information Technology Applications and Management
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• v.16 no.2
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• pp.135-150
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• 2009

Corporate databases are usually denormalized, due to the data modelers' impetuous belief that denormalization could improve system performance. By providing a logical insight into denormalization, this paper attempts to prevent every database modeler from falling into the denormalization pit. We indicate loopholes in the denormalization advocates' assertions, and then present four criteria to analyze the usefulness and validity of denormalization; 1) the level of concurrency among transactions, 2) the database independence of the application program, 3) the independence between the logical design and the physical one, and 4) the overhead cost to maintain database integrity under various query patterns. This paper also includes experimental results to evaluate performance of denormalized and fully normalized structures under various workloads.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.568-571
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• 2004

In this study, we propose an efficient expert system (ES) construction mechanism by using dynamic knowledge map (DKM) and database management systems (DBMS). Generally, traditional ES and ES developing tools has some limitations such as, 1) a lot of time to extend the knowledge base (KB), 2) too difficult to change the inference path, 3) inflexible use of inference functions and operators. First, to overcome these limitations, we use DKM in extracting the complex relationships and causal rules from human expert and other knowledge resources. Then, elation database (RDB) and its management systems will help to transform the relationships from diagram to relational table. Therefore, our mechanism can help the ES or KBS (Knowledge-Based Systems) developers in several ways efficiently. In the experiment section, we used medical data to show the efficiency of our mechanism. Experimental results with various disease show that the mechanism is superior in terms of extension ability and flexible inference.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.12a
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• pp.69-74
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• 2004

Selectivity estimation for spatial query is very important process in finding the most efficient execution plan. Many works have been performed to estimate accurately selectivity. Although they deal with some problems such as false-count, multi-count, they require a large amount of memory to retain accurate selectivity, so they can not get good results in little memory environments such as mobile-based small database. In order to solve this problem, we propose a new technique called MW histogram which is able to compress summary data and get reasonable results. It also has a flexible structure to react dynamic update. The experimental results showed that the MW histogram has lower relative error than MinSkew histogram and gets a good selectivity in little memory.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.766-768
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• 2003

Selectivity estimation for spatial query is curial in Spatial Database Management Systems(SDBMS). Many works have been performed to estimate accurate selectivity. Although they deal with some problems such as false-count, multi-count arising from properties of spatial dataset, they can not get such effects in little memory space.* Therefore, we need to compress spatial dataset into little memory. In this paper, we propose a new technique called MW Histogram which is able to compress summary data and get reasonable results. Our method is based on two techniques:(a)MinSkew partitioning algorithm which deal with skewed spatial datasets. efficiently (b) Wavelet transformation which compression effect is proven. We evaluate our method via real datasets. The experimental result shows that the MW Histogram has the ability of providing estimates with low relative error and retaining the similar estimates even if memory space is small.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.837-848
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• 2005

A multi-scale database is a set of spatial database, covering same geographic area with different scales and it can be derived from pre-existing databases. In the derivation processes of a new multi-scale spatial database, the geometries and topological relations on the source database can be transformed and the transformation can be the cause of the lack of integrity Therefore, it is necessary to assess the transformation whether it is consistent or not after the derivation process of a new multi-scale database. Thus, we propose assessment methods for the topological consistency between a source database and a derived multi-scale database in this paper. In particular, we focus on the case that 2-dimensional objects are collapsed to 1-dimensional ones in the derivation process of a multi-scale database. We also describe implementation of the assessment methods and show the results of the implementation with experimental data.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.66-72
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• 2003

Toxicogenomics is now emerging as one of the most important genomics application because the toxicity test based on gene expression profiles is expected more precise and efficient than current histopathological approach in pre-clinical phase. One of the challenging points in Toxicogenomics is the construction of intelligent database management system which can deal with very heterogeneous and complex data from many different experimental and information sources. Here we present a new Toxicogenomics database developed as a part of 'Toxicogenomics for Efficient Safety Test (TEST) project'. The TEST database is especially focused on the connectivity of heterogeneous data and intelligent query system which enables users to get inspiration from the complex data sets. The database deals with four kinds of information; compound information, histopathological information, gene expression information, and annotation information. Currently, TEST database has Toxicogenomics information fer 12 molecules with 4 efficacy classes; anti cancer, antibiotic, hypotension, and gastric ulcer. Users can easily access all kinds of detailed information about there compounds and simultaneously, users can also check the confidence of retrieved information by browsing the quality of experimental data and toxicity grade of gene generated from our toxicology annotation system. Intelligent query system is designed for multiple comparisons of experimental data because the comparison of experimental data according to histopathological toxicity, compounds, efficacy, and individual variation is crucial to find common genetic characteristics .Our presented system can be a good information source for the study of toxicology mechanism in the genome-wide level and also can be utilized fur the design of toxicity test chip.

• Structural Engineering and Mechanics
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• v.58 no.3
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• pp.475-514
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• 2016

Various models have been proposed by several researchers for predicting the exterior RC beam-column joint shear strength. Most of these models were calibrated and verified with some limited experimental database. From the models it has been identified that the joint shear strength majorly depends on ten governing parameters. In the present paper, detailed investigation of twelve analytical models for predicting shear strength of exterior beam-column joint has been carried out. The study shows the effect of each governing parameter on joint shear strength predicted by various models. It has been observed that the consensus on effect of few of the governing parameters amongst the considered analytical models has not been attained. Moreover, the predicted joint strength by different models varies significantly. Further, the prediction of joint shear strength by these analytical models has also been compared with a set of 200 experimental results from the literature. It has been observed that none of the twelve models are capable of predicting joint shear strength with sufficient accuracy for the complete range of experimental results. The research community has to reconsider the effect of each parameters based on larger set of test results and new improved analytical models should be proposed.

• 한국정보통신설비학회:학술대회논문집
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• 2002.08a
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• pp.199-207
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• 2002

A virtual laboratory for measurement and instrumentation must aim to realize an integrated environment. To achieve this goal, we designed and implemented a client/server distributed environment and developed a web-based virtual laboratory system for electronic circuits. Since our virtual laboratory system is implemented to describe the on-campus laboratory, the learners can obtain similar experimental data through it. The proposed virtual laboratory system is composed of four important components Principle Classroom, Virtual Experiment Classroom, Evaluation Classroom and Overall Management System. Through our virtual laboratory, the learners will be capable of teaming the concepts and theories related to electronic circuit experiments and how to operate the experimental equipments such as multimeters, function generators, digital oscilloscopes and DC power supplies. Also, every activity occurred in our virtual laboratory is recorded on database and Printed out on the preliminary report form. All of these can be achieved by the aid of the Management System. The database connectivity is made by PHP and the virtual laboratory environment is set up slightly differently for each learner. Finally, we have obtained several affirmative effects such as reducing the total experimental hours and the damage rate for experimental equipments and increasing Loaming efficiencies as well as faculty productivity.

• Computers and Concrete
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• v.27 no.3
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• pp.225-239
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• 2021

Carbon fiber reinforced polymer (CFRP) has extensive use in strengthening reinforced concrete structures due to its high strength and elastic modulus, low weight, fast and easy application, and excellent durability performance. Many studies have been carried out to determine the performance of the CFRP confined concrete cylinder. Although studies about the prediction of confined compressive strength using ANN are in the literature, the insufficiency of the studies to predict the strain of confined concrete cylinder using ANN, which is the most appropriate analysis method for nonlinear and complex problems, draws attention. Therefore, to predict both strengths and also strain values, two different ANNs were created using an extensive experimental database. The strength and strain networks were evaluated with the statistical parameters of correlation coefficients (R2), root mean square error (RMSE), and mean absolute error (MAE). The estimated values were found to be close to the experimental results. Mathematical equations to predict the strength and strain values were derived using networks prepared for convenience in engineering applications. The sensitivity analysis of mathematical models was performed by considering the inputs with the highest importance factors. Considering the limit values obtained from the sensitivity analysis of the parameters, the performances of the proposed models were evaluated by using the test data determined from the experimental database. Model performances were evaluated comparatively with other analytical models most commonly used in the literature, and it was found that the closest results to experimental data were obtained from the proposed strength and strain models.

• Steel and Composite Structures
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• v.29 no.4
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• pp.465-481
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• 2018

The use of external carbon-fiber-reinforced polymer (CFRP) laminates is one of the most effective techniques existing for the confinement of circular concrete specimens. Currently, several researches have been made to develop models for predicting the ultimate conditions of this type of confinement. As most of the major existing models were developed based on limited experimental database. This paper presents the development of new confinement ultimate conditions, strength and strain models, for concrete cylinders confined with CFRP composites based on a statistical analysis of a large existing experimental database of 310 cylindrical concrete specimens wrapped with CFRP. The database is used to evaluate the performance of the proposed and major existing strength and strain models. Based on the two different statistical indices, the coefficient of determination ($R^2$) and the Root Mean Square Error (RMSE), the two proposed confinement ultimate conditions presents a good performance compared to the major existing models except the models of Lam and Teng (2003) and Youssef et al. (2007) which have relatively similar performance to the proposed models.