• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.11 no.2
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• pp.69-77
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• 1993

Investigation is given to the detailed procedure of a computer assisted automatic correction for scanning errors of the digital images of close-range photographs scanned by the CCD camera scanner. After determination of the exterior orientation parameters, photo coordinates of the all pixels were calculated using collinearity equation. For the generation of geometric corrected image from the photo coordinates of the all pixels, inverse-weighted-distance average method was used. And the accuracy of the resulting new image was checked comparing its image coordinates with there corresponding ground coordinates for the check points.

• Journal of KIISE
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• v.43 no.6
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• pp.636-644
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• 2016

Annotated Corpus is important to understand natural language using machine learning method. In this paper, we propose a new method to automate error reduction of annotated corpora. We use the Ripple-Down Rules(RDR) for reducing errors and Kernel to extend RDR for NLP. We applied our system to the Korean Wikipedia and blog corpus errors to find the annotated corpora error type. Experimental results with various views from the Korean Wikipedia and blog are reported to evaluate the effectiveness and efficiency of our proposed approach. The proposed approach can be used to reduce errors of large corpora.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.6
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• pp.535-544
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• 1988

In this paper, the hybrid ARQ scheme, which is incorporated the selective-repeat ARQ system with the finite receiver buffer and the single-error-correcting and double-error-detecting(63.56) cyclic Hamming code system, has been investigated. As a result of simulation, the proposed hybrid ARQ scheme shows that that throughput efficiencies are improved by one error correction, and that the reversed codewords due to retransmission are delivered to the user in order by means of detecting two errors. The hybrid ARQ scheme significantly outperforms the FEC or the ideal selective-repeat ARQ system in the respect of throughput and reliability, especially when the channel error rate is approximately in the range from $10^{-2}$~$10^{-3}$.

• Journal of Navigation and Port Research
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• v.30 no.5 s.111
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• pp.321-329
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• 2006

The ultimate target cf this study is to develop ship's Digital Compass that can substitute for conventional ship's Magnetic Compass. At first, a new Digital Compass system consisting of three-axis Flux-gate sensors and small sized step motor was developed Then, new deviation adjustment theory incorporating with Kalman filter method was proposed through which automatic deviation analysis and correction are obtainable without ship's swinging procedures. The effectiveness of developed Digital Compass and proposed deviation adjustment theory are verified throughout the performance evaluation tests on the training ship 'SAE-NU-RI'.

• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.31-39
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• 2010

The goal of automatic velocity analysis is to extract accurate velocity from voluminous seismic data with efficiency. In this study, we developed an efficient automatic velocity analysis algorithm by using bootstrapped differential semblance (BDS) and Monte Carlo inversion. To estimate more accurate results from automatic velocity analysis, the algorithm we have developed uses BDS, which provides a higher velocity resolution than conventional semblance, as a coherency estimator. In addition, our proposed automatic velocity analysis module is performed with a conditional initial velocity determination step that leads to enhanced efficiency in running time of the module. A new optional root mean square (RMS) velocity constraint, which prevents picking false peaks, is used. The developed automatic velocity analysis module was tested on a synthetic dataset and a marine field dataset from the East Sea, Korea. The stacked sections made using velocity results from our algorithm showed coherent events and improved the quality of the normal moveout-correction result. Moreover, since our algorithm finds interval velocity ($\nu_{int}$) first with interval velocity constraints and then calculates a RMS velocity function from the interval velocity, we can estimate geologically reasonable interval velocities. Boundaries of interval velocities also match well with reflection events in the common midpoint stacked sections.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.244-255
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• 2022

This study estimated and evaluated the high resolution (1km) gridded mountain meteorology data of daily mean, maximum and minimum temperature based on ASOS (Automated Surface Observing System), AWS (Automatic Weather Stations) and AMOS (Automatic Mountain Meteorology Observation System) in South Korea. The ASOS, AWS, and AMOS meteorology data which were located above 200m was classified as mountainous area. And the ASOS, AWS, and AMOS meteorology data which were located under 200m was classified as non-mountainous area. The bias-correction method was used for correct air temperature over complex mountainous area and the performance of enhanced daily coefficients based on the AMOS and mountainous area observing meteorology data was evaluated using the observed daily mean, maximum and minimum temperature. As a result, the evaluation results show that RMSE (Root Mean Square Error) of air temperature using the enhanced coefficients based on the mountainous area observed meteorology data is smaller as 30% (mean), 50% (minimum), and 37% (maximum) than that of using non-mountainous area observed meteorology data. It indicates that the enhanced weather coefficients based on the AMOS and mountain ASOS can estimate mean, maximum, and minimum temperature data reasonably and the temperature results can provide useful input data on several climatological and forest disaster prediction studies.

• Journal of Korean Dental Science
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• v.13 no.1
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• pp.28-34
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• 2020

Purpose: The purpose of this study was to investigate the influence of different implant computer software on the accuracy of image registration between radiographic and optical scan data. Materials and Methods: Cone-beam computed tomography and optical scan data of a partially edentulous jaw were collected and transferred to three different computer softwares: Blue Sky Plan (Blue Sky Bio), Implant Studio (3M Shape), and Geomagic DesignX (3D systems). In each software, the two image sets were aligned using a point-based automatic image registration algorithm. Image matching error was evaluated by measuring the linear discrepancies between the two images at the anterior and posterior area in the direction of the x-, y-, and z-axes. Kruskal-Wallis test and a post hoc Mann-Whitney U-test with Bonferroni correction were used for statistical analyses. The significance level was set at 0.05. Result: Overall discrepancy values ranged from 0.08 to 0.30 ㎛. The image registration accuracy among the software was significantly different in the x- and z-axes (P=0.009 and <0.001, respectively), but not different in the y-axis (P=0.064). Conclusion: The image registration accuracy performed by a point-based automatic image matching could be different depending on the computer software used.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.894-897
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• 2008

This paper analyzes the throughput performance of a selective repeat (SR)/automatic repeat request (ARQ) scheme to transmit packet data in burst home network channel. To combat the high degree of error caused by transmission of home network data a robust error control scheme is a necessity. Basically, error control schemes can be divided in two categories: ARQ schemes and forward error correction (FEC) schemes. ARQ schemes are often used for reliable data transmission. The performance of packet transmission using SR-ARQ schemes for bursty channels is analyzed and simple analytical expressions of its throughput are presented. Theoretic analysis and numerical results indicate that a small number of packet sizes can get good performance in bursty home network channel.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.03a
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• pp.695-702
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• 2002

Groundwater flow is primarily influenced by the presence of fractures, functioning as conduits. To block the flow, grouting operation is commonly used. Thereby the fractures are then expected to be sealed, which will add to enhance the shear strength in rock. This far, regarding the assessment of grouting efficiency, however, there's been a considerable uncertainty That is, several geophysical methods of high resolution such as tomography, S-wave logging have produced a significant amount of measurable response caused by grouting, but they can inevitably be used only for the qualitative assessment. Thus, this paper deals with an accurate quantitative assessment about the grouting result. In this, a new strategy is introduced, based mainly on evaluating the opening of fractures. For fracture-opening investigation purposes, borehole Televiewer has already proven to be an excellent logging technique that produces both amplitude image and traveltime image. As well known, the traveltime image can be converted to a high precision 3D caliper log with max. 288 arms, which allows to observe the opening of fractures. To evaluate the fracture opening from the traveltime image, an algorithm of practical use was developed, in which image correction due to the borehole deviation, feature discrimination of wall roughness from fractures, automatic evaluation procedure etc. were considered. Field examples are shown to confirm the efficiency of the suggested method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.8
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• pp.1424-1429
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• 2016

Segmentation is one of the first steps in most diagnosis systems for characterization of dental caries in an early stage. The purpose of automatic dental cavity detection system is helping dentist to make more precise diagnosis. We proposed the semi-automatic method for the segmentation of dental caries on digital x-ray images. Based on a manually and roughly selected ROI (Region of Interest), it calculated the contour for the dental cavity. A snake algorithm which is one of active contour models repetitively refined the initial contour and self-examination and correction on the segmentation result. Seven phantom tooth from incisor to molar were made for the evaluation of the developed algorithm. They contained a different form of cavities and each phantom tooth has two dental cavities. From 14 dental cavities, twelve cavities were accurately detected including small cavities. And two cavities were segmented partly. It demonstrates the practical feasibility of the dental lesion detection using Computer-aided Detection (CADe).