• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.6 no.2
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• pp.28-33
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• 1988

The objective of this work is to study the sue of precise triangulation nets by matrix analysis in adjusting coordinates. Results of this work show that matrix analysis has many advantages, namely in terms of accuracy and efficiency. In addition to this, comparison of adjusted vlues by two different methods, a Rigorous Method and an Approximate Method, show that differences in adjusted coordinates are 1-2 mm within the mean square error. This proves that the Approximate Method has sufficient accuracy in the practical application.

• Journal of electromagnetic engineering and science
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• v.12 no.4
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• pp.240-246
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• 2012

This paper presents a novel modeling technique for traces that cross a defected ground structure. A simple and accurate equivalent circuit model provides clear insight into the coupling mechanism between a microstrip line and a slot or split. The circuit models consist of a transformer as the coupling mechanism and LC resonators as the ground with a slot or split structure. Resistors, capacitors, and inductors are added to the model to increase accuracy and equivalence at high frequency. Simulated and measured S-parameters are presented for defected ground structures. The accuracy and validity of the proposed equivalent circuit model is verified by evaluation of the S-parameter characteristics of the defected ground structures and comparison with measured results.

• ETRI Journal
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• v.37 no.2
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• pp.251-261
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• 2015

We present a novel method for real-time automatic license plate detection in high-resolution videos. Although there have been extensive studies of license plate detection since the 1970s, the suggested approaches resulting from such studies have difficulties in processing high-resolution imagery in real-time. Herein, we propose a novel cascade structure, the fastest classifier available, by rejecting false positives most efficiently. Furthermore, we train the classifier using the core patterns of various types of license plates, improving both the computation load and the accuracy of license plate detection. To show its superiority, our approach is compared with other state-of-the-art approaches. In addition, we collected 20,000 images including license plates from real traffic scenes for comprehensive experiments. The results show that our proposed approach significantly reduces the computational load in comparison to the other state-of-the-art approaches, with comparable performance accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1307-1312
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• 2004

Word sense disambiguation is one of the most important problems in natural language processing research topics such as information retrieval and machine translation. Many approaches can be employed to resolve word ambiguity with a reasonable degree of accuracy. These strategies are: knowledge-based, corpus-based, and hybrid-based. This paper pays attention to the corpus-based strategy. The purpose of this paper is to compare three famous machine learning techniques, Snow, SVM and Naive Bayes in Word-Sense Disambiguation on Thai language. 10 ambiguous words are selected to test with word and POS features. The results show that SVM algorithm gives the best results in solving of Thai WSD and the accuracy rate is approximately 83-96%.

• Journal of Korea Multimedia Society
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• v.23 no.9
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• pp.1155-1163
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• 2020

Deep learning approach is emerging as a new way to improve the accuracy of tree species identification using bark image. However, the approach has not been studied enough because it is confronted with the problem of acquiring a large volume of bark image dataset. This study solved this problem by utilizing a pretrained off-the-shelf DCNN model. It compares the discrimination power of bark features extracted by each DCNN model. Then it extracts the features by using a selected DCNN model and feeds them to a multi-layer perceptron (MLP). We found out that the ResNet50 model is effective in extracting bark features and the MLP could be trained well with the features reduced by the principal component analysis. The proposed approach gives accuracy of 99.1% and 98.4% for BarkTex and Trunk12 datasets respectively.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.225-231
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• 2005

In this paper, to prediction of large deformation behavior of steel structures under loading, 3-Dimensional elastic-plastic FE analysis method is developed by using finite deformation theory and proposed cyclic plasticity model. The accuracy of developed analytical method was verified by comparison of experiment result and analysis results using infinitesimal deformation theory. The good agreement between analysis result by developed analytical method and experiment result is shown. Proposed 3-dimensional FE analysis using finite deformation theory and cyclic plasticity hysteresis model can be predict the large deformation of steel members under cyclic loading.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.109-128
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• 2016

This paper presents a new combined forecasting method that is guided by the soft set theory (CFBSS) to predict business failures with different sample sizes. The proposed method combines both qualitative analysis and quantitative analysis to improve forecasting performance. We considered an expert system (ES), logistic regression (LR), and support vector machine (SVM) as forecasting components whose weights are determined by the receiver operating characteristic (ROC) curve. The proposed procedure was applied to real data sets from Chinese listed firms. For performance comparison, single ES, LR, and SVM methods, the combined forecasting method based on equal weights (CFBEWs), the combined forecasting method based on neural networks (CFBNNs), and the combined forecasting method based on rough sets and the D-S theory (CFBRSDS) were also included in the empirical experiment. CFBSS obtains the highest forecasting accuracy and the second-best forecasting stability. The empirical results demonstrate the superior forecasting performance of our method in terms of accuracy and stability.

• Transactions of Materials Processing
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• v.26 no.2
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• pp.101-107
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• 2017

Aluminum alloys are widely used in automotive industry because of their high strength-to-density ratio and excellent corrosion resistance. However, conventional cold stamping of aluminum alloys leads to low formability and excessive spring-back. To overcome these problems, Hot Forming Quenching (HFQ) is applied to manufacture automotive part using aluminum alloy. The purpose of this study is to investigate effect of forming temperature on spring-back in HFQ of T6 heat treated AA6061 sheet. In this study, hat shape forming test was adopted to evaluate spring-back characteristics according to various forming temperatures. In additions, the test was also performed with warm forming conditions in comparison with dimensional accuracy of HFQed part. The experimental results showed that dimensional accuracy of HFQed part was superior to warm formed part and amount of spring-back was decreased as forming temperature rise.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.303-312
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• 2017

This paper indirectly created high density point cloud data using unmanned aerial vehicle image. Then, we tried to suggest new concept of classification technique where particular objects from point cloud data can be selectively classified. For this, we established the classification technique that can be used as search factor in classifying color information in point cloud data. Then, using suggested classification technique, we implemented object classification and analyzed classification accuracy by relative comparison with self-created proof resource. As a result, the possibility of point cloud data classification was observable using the image's information. Furthermore, it was possible to classify particular object's point cloud data in high classification accuracy.

• Journal of Korean Society for Geospatial Information Science
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• v.9 no.1 s.17
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• pp.59-66
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• 2001

Satellite visibility, Accuracy, and Availability were increased by the combined GPS/GLONASS. But, there are some problems such as differences in the time frame, differences in the coordinate datum, and the problem of solving carrier phase ambiguities in the combined carrier frequency solutions due to different GLONASS frequency. Therefore, the accuracy of single point positioning using the combined GPS/GLONASS will be assessed, and intend to study the characteristics of the combined GPS/GLONASS with considered the rate of data acquisition according to the visibility of satellite and elevation cutoff at the combined GPS/GLONASS.