• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.4
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• pp.429-438
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• 2017

Cranke-Nicolson scheme in native OpenFOAM source libraries was not able to provide 2nd order temporal accuracy of velocity and pressure since the volume flux of convective nonlinear terms was 1st accurate in time. In the present study the simplest way of getting the volume flux with 2nd order accuracy was proposed by using old fluxes. A possible numerical instability originated from an explicit estimation of volume fluxes could be handled by introducing a weighting factor which was determined by observing the ratio of the finally corrected volume flux to the intermediate volume flux at the previous step. The new calculation of volume fluxes was able to provide temporally accurate velocity and pressure with 2nd order. The improvement of temporal accuracy was validated by performing numerical simulations of 2D Taylor-Green vortex of which an exact solution was known and 2D vortex shedding from a circular cylinder.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.42-45
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• 2004

Electrochemical discharge machining (ECDM) has been found to be suitable for the micro-hole machining of nonconductive materials such as ceramics or glass compared with existing conventional and also non-conventional machining methods. However this machining process has some problems such as low geometric accuracy and low machining efficiency due to the random spark generation at the end of the electrode. This paper proposes the methods to improve the geometric accuracy of micro-hole using powder mixed ECDM process. The experimental results show the effects of powder producing improved geometric accuracy of machined hole and decreased concentration of spark energy.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.787-790
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• 2017

Data quality is the main issue in the classification problems; generally, the presence of noisy instances in the training dataset will not lead to robust classification performance. Such instances may cause the generated decision tree to suffer from over-fitting and its accuracy may decrease. Decision trees are useful, efficient, and commonly used for solving various real world classification problems in data mining. In this paper, we introduce a preprocessing technique to improve the classification accuracy rates of the C4.5 decision tree algorithm. In the proposed preprocessing method, we applied the naive Bayes classifier to remove the noisy instances from the training dataset. We applied our proposed method to a real e-commerce sales dataset to test the performance of the proposed algorithm against the existing C4.5 decision tree classifier. As the experimental results, the proposed method improved the classification accuracy by 8.5% and 14.32% using training dataset and 10-fold crossvalidation, respectively.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.61-67
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• 2017

The detection of oil spills using radar image has been studied extensively. However, most of the proposed techniques have been focused on improving detection accuracy through the advancement of algorithms. In this study, research has been conducted to improve the accuracy of oil spill detection by improving the quality of radar images, which are used as input data to detect oil spills. Thresholding algorithms were used to measure the image improvement both before and after processing. The overall accuracy increased by approximately 16%, the producer accuracy increased by 40%, and the user accuracy increased by 1.5%. The kappa coefficient also increased significantly, from 0.48 to 0.92.

• Journal of the Korea Safety Management & Science
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• v.12 no.1
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• pp.127-136
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• 2010

In this paper, the author proposed following two methods to improve the accuracy of the recommender system. First, in order to classify the users more accurately, the author used a EMC(Expanded Moving Center) heuristic algorithm which improved clustering accuracy. Second, the author proposed the Neighborhood-oriented preference prediction method that improved the conventional preference prediction methods, so the accuracy of the recommender system is improved. The test result of the recommender system which adapted the above two methods suggested in this paper was improved the accuracy than the conventional recommendation methods.

• English Language & Literature Teaching
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• v.17 no.4
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• pp.207-227
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• 2011

This paper investigates how two different modes of feedback (selective vs. comprehensive) affect selected students' writing development in terms of three different types of measurement (accuracy, fluency, and complexity). 139 university students participated in the study, and 278 writing samples were analyzed. The results of the study indicate that participants who received selective feedback wrote more accurately and fluently than their counterparts. However, in terms of complexity, both selective and comprehensive groups showed no sign of improvement in semester-based investigations. The results of this study support Skehan's (2009) theory of trade-off effects, suggesting that 'natural' tension exists between accuracy and complexity when resources are limited. Moreover, this finding contrasts with the theory of Cognition Hypothesis, which proposes that task complexity will be associated with increases in complexity and accuracy. In the study, selected participants (N=21) strongly nominated their error sources as unfamiliarity toward using key words, usage, transition, and sentence types. This study not only contributes to the accumulation of our current knowledge in the related area of theory, but offers educational implications for those who are dealing with intermediate-level students when deciding what particular teaching content should constitute a priority within a limited instructional period.

• Korean Journal of Geomatics
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• v.2 no.2
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• pp.99-105
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• 2002

The accuracy of the Digital Photologging System, designed for the construction of the road Facility Database, highly depends on the positions and attitudes of the cameras from GPS/INS integration. In this paper, the development of a loosely coupled GPS/INS is presented. The performance of the system is verified through a simulation as well as a real test data processing. Since the IMU used in this study shows large systematic errors, the possible accuracy of the positions and attitudes of this low-performance IMU when combined with precise GPS positions are assigned. Currently, the integrated system shows the positional accuracy better than 5cm in real data processing. Although the accuracy of attitude based on real test could not be assigned at this time, it is expected that better than 0.5 degrees and 1.8 degrees for horizontal and down component are achievable according to the simulation result.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2313-2319
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• 2020

The goal of this project is to achieve an accurate segmentation of the pulmonary tumors besides shortening the time and increasing the accuracy. Here, improved region growing (IRG) algorithm is introduced in order to segment the lung tumor with a sufficient accuracy in a shorter time compared to the other basics methods. This comprehensive algorithm was applied on 4 patients CT images and the results of the various steps on segmentation improvement shown 98% accuracy as compared to the basic algorithm. The combination of "multipoint growth start" produced a desirable outcome in accurately bounding the tumor. The proposed algorithm improved tumor identification by less than 13% along with a sufficient percentage of compliance accuracy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.366-369
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• 2005

Electrochemical discharge machining (ECDM) has been found to be potential fur the micro-machining of non-conductive materials such as ceramics or glass. However this machining process has its own inherent problem that the reproducibility is too low to get the available geometric accuracy fur micromachining applications. One main challenge in reaching this goal is the control of the hydrogen built around the tool-electrode in which happen the discharges. This paper proposes the methods to improve the geometric accuracy using powder-mixed ECDM process. The experimental results show the effects of powder producing improved geometric accuracy by averaging and decreasing the concentration of spark energy.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.139-142
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• 2020

NB-IoT(Narrow Band Internet of Things) is an emerging LPWAN(Low Power Wide Area Network) radio technology. NB-IoT has many advantages like low power, low cost, and high coverage. However low bandwidth and low sampling rates also lead to poor positioning accuracy. This paper proposed a solution to optimize positioning accuracy under the OTDOA(Observed Time Difference of Arrival) approach by utilizing MLR(Multiple Linear Regression) models. Through the MLR model to predict the influence degree of weather(temperature, humidity, light intensity and air pressure) on the arrival time of signal transmission to improve the measurement accuracy. The improvement of measurement accuracy can greatly improve IoT applications based on NB-IoT.