• 한국측량학회지
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• 제23권2호
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• pp.137-145
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• 2005

이 논문에서는 선형 푸시브룸 방식으로 촬영한 위성영상에 대한 다양한 센서모델들의 정확도를 비교분석하고자 한다. 특히 이 논문에서는 센서모델의 정확도를 번들조정의 정확도와 외부표정요소추정의 정확도로 분리하여 고찰하려고 한다. 번들조정 정확도는 수립된 센서모델이 얼마나 기준점에 잘 부합하는 가를 알려주는 척도로 이제까지 대부분의 센서모델 정확도 분석에 사용되어온 기준이다. 이에 반하여 외부표정요소추정의 정확도는 센서모델이 얼마나 정확하게 촬영당시의 위성의 궤도 및 자세를 예측할 수 있는 지의 척도로서 매우 중요한 요소임에도 불구하고 기존의 연구에서 간과해온 부분이다. 이 논문에서는 여러 센서모델 중에서 사진측량분야에서 주로 사용하는 변형된 공선방정식기반 모델과 위성지상국 또는 자세제어분야에서 주로 사용하는 궤도좌표계 및 자세각에 기반한 모델의 정확도를 비교분석하고자 한다. 실험은 다목적실용위성 1호 EOC 영상과 GPS 수신기에서 취득한 기준점을 사용하였다. 실험결과 번들조정 정확도는 두 모델이 큰 차이를 보이지 않는 것으로 나타났으나 외부표정요소추정 정확도는 궤도좌표계 및 자세각에 기반한 모델이 더 나은 성능을 보였다.

• 한국항행학회논문지
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• 제27권6호
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• pp.841-848
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• 2023

위성 항법 장치 (GPS; global positioning system) 항법메시지에 포함된 Klobuchar 전리층모델은 L1 단주파수 사용자들에게 전리층 보정정보를 제공한다. 전리층모델 정확도는 항법해의 정확도에 큰영향을 끼치므로 이에 관한 분석이 필요하다. 본 연구에서는 1993년부터 2022년까지의 GPS 항법메시지를 조사하여 Klobuchar 모델의정확도 및 계수 존재 여부와 효용성 여부를 분석 하였다. 초기 GPS 항법메시지의 경우 전리층데이터를 포함하지 않는 경우가 많으며, 전리층모델을 포함되어 있더라도 정확도가 상당히 낮은 경우가 많이 존재하였다. 전리층모델의 정확도가 안정화된 2002년부터 2022년까지 전리층모델의 정확도 변화와 지자기 위도에 따른 정확도 차이를 IGS (International GNSS Service)에서 제공하는 전리층모델과 비교하는 방법으로 분석하였다.

• 한국자동차공학회논문집
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• 제21권1호
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• pp.30-35
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• 2013

The brake pedal is one of the most important parts for controlling the speed of the vehicle. Incorrect design of the brake pedal can place the driver in danger. CAE is being done for weight reduction to improve the safety of the driver and the vehicle performance and research is performed to improve the accuracy of analysis. The accuracy of the experimental and analysis values in regard to the stiffness of brake pedals, however, is still poor. Therefore, the aim of this study is to present appropriate analysis conditions based on the factors that influence the analysis in order to obtain accurate analysis results.

• Journal of information and communication convergence engineering
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• 제13권2호
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• pp.105-112
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• 2015

The estimation of missing sensor values is an important problem in sensor network applications, but the existing approaches have some limitations, such as the limitations of application scope and estimation accuracy. Therefore, in this paper, we propose a new estimation model based on a spatial-temporal correlation analysis (STCAM). STCAM can make full use of spatial and temporal correlations and can recognize whether the sensor parameters have a spatial correlation or a temporal correlation, and whether the missing sensor data are continuous. According to the recognition results, STCAM can choose one of the most suitable algorithms from among linear interpolation algorithm of temporal correlation analysis (TCA-LI), multiple regression algorithm of temporal correlation analysis (TCA-MR), spatial correlation analysis (SCA), spatial-temporal correlation analysis (STCA) to estimate the missing sensor data. STCAM was evaluated over Intel lab dataset and a traffic dataset, and the simulation experiment results show that STCAM has good estimation accuracy.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권4호
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• pp.362-369
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• 2017

Purpose: Recently, the government of China has established new safety regulations for towing devices. The new Chinese regulation has more unfavorable conditions than the conditions of other countries. So the various measures have been reviewed to satisfy this regulation. Methods: The regulation conditions were compared through analysis of strain energy, and a method for improving the accuracy of analysis is suggested. In addition, the test method considering the tolerance is presented through tolerance analysis. This paper also explained importance of confirming the quality of products through a case of poor quality of Chinese products such as poor heat treatment. Result: We could know how strong Chinese regulations are stronger than other national laws and investigated which member receives a lot of strain energy. In order to cope with these Chinese regulations, we suggested improvement of analysis accuracy, test method through tolerance analysis, and heat treatment quality. Conclusion: This paper contributed to general counterplan of the strengthened new Chinese regulations for towing device.

• ETRI Journal
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• 제46권1호
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• pp.137-153
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• 2024

This study introduces a new approach in Korean morphological analysis combining dictionary-based techniques with Transformer-based deep learning models. The key innovation is the use of a BERT-based reranking system, significantly enhancing the accuracy of traditional morphological analysis. The method generates multiple suboptimal paths, then employs BERT models for reranking, leveraging their advanced language comprehension. Results show remarkable performance improvements, with the first-stage reranking achieving over 20% improvement in error reduction rate compared with existing models. The second stage, using another BERT variant, further increases this improvement to over 30%. This indicates a significant leap in accuracy, validating the effectiveness of merging dictionary-based analysis with contemporary deep learning. The study suggests future exploration in refined integrations of dictionary and deep learning methods as well as using probabilistic models for enhanced morphological analysis. This hybrid approach sets a new benchmark in the field and offers insights for similar challenges in language processing applications.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.436-442
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• 2017

A novel method of Skin lesion segmentation based on the combination of Texture and Neural Network is proposed in this paper. This paper combines the textures of different pixels in the skin images in order to increase the performance of lesion segmentation. For segmenting skin lesions, a two-step process is done. First, automatic border detection is performed to separate the lesion from the background skin. This begins by identifying the features that represent the lesion border clearly by the process of Texture analysis. In the second step, the obtained features are given as input towards the Recurrent Echo state neural networks in order to obtain the segmented skin lesion region. The proposed algorithm is trained and tested for 862 skin lesion images in order to evaluate the accuracy of segmentation. Overall accuracy of the proposed method is compared with existing algorithms. An average accuracy of 98.8% for segmenting skin lesion images has been obtained.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.440-445
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• 1993

A two dimensional large scale laser digitizer with a cordless cursor was developed. The coordinate detecting scheme of this digitizer is fundamentally based on the triangulation method, in which two laser-rays are scanned by the rotating plane mirros, reflected backward by the cursor, reflected again by the rotating mirrors, and detected by optical sensors. From angles in which the cursor reflections are detected, we can determine the position of the cursor. But this method involves several problems about optical alignment and its calibration especially when it is applied to a large scale digitizer. In this paper, especially we propose simulation for error analysis with connection to angles measured at five control points which are needed to decide an appropriate model for calculating coordinates and optimal simulation for deciding the position of five control points to give the better coordinate accuracy. In this way, we realized the on-site calibration and on-site insurance of measurement accuracy with our appropriate model for calculating coordinates. The time required for on-site calibration is within 5 minutes and the average accuracy of 4m * 3m digitizer is about .+-.0.12mm.

• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.269-278
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• 2006

This paper presents the new hybrid data mining technique using error pattern, modeling of improving classification accuracy. The proposed method improves classification accuracy by combining two different supervised learning methods. The main algorithm generates error pattern modeling between the two supervised learning methods(ex: Neural Networks, Decision Tree, Logistic Regression and so on.) The Proposed modeling method has been applied to the simulation of 10,000 data sets generated by Normal and exponential random distribution. The simulation results show that the performance of proposed method is superior to the existing methods like Logistic regression and Discriminant analysis.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2006년도 춘계학술발표회 논문집
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• pp.255-258
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• 2006

With the increasing availability of high-resolution satellite imagery, the demand for ortho-rectified products will also be growing. High-resolution of the imagery (up to 1m) the desired accuracy of the ortho-rectification is more sensitive to a number of factors. including satellite position, velocity, internal sensor error (specifically, misalignment. lens distortion, etc.). sensor modeling, relief displacement and matching error, etc. The main objective of this study is to analysis the accuracy of high resolution satellite data using simulation data.