• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.2
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• pp.137-145
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• 2005

In this paper, we investigate the accuracy of various sensor models developed for linear pushbroom satellite images. We define the accuracy of a sensor model in two aspects: the accuracy of bundle adjustments and the accuracy of estimating exterior orientation parameters. The first accuracy has been analyzed and reported frequently whereas the second accuracy has somewhat been neglected. We argue that the second accuracy is as important as the first one. The second accuracy describes a model's ability to predict satellite orbit and attitude, which has many direct and indirect applications. Analysis was carried out on the traditional collinearity-based sensor models and orbit-based sensor models. Collinearity-based models were originally developed for aerial photos and modified for linear pushbroom-type satellite images. Orbit-based models have been used within satellite communities for satellite control and orbit determination. Models were tested with two Kompsat-1 EOC scenes and GPS-driven control points. Test results showed that orbit-based models produced better estimation of exterior orientation parameters while maintained comparable accuracy on bundle adjustments.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.841-848
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• 2023

The Klobuchar ionospheric model included in global positioning system (GPS) navigation messages provides ionospheric correction information to single-frequency users. This ionospheric model accuracy has a significant impact on the accuracy of navigation solutions. We examine the GPS navigation messages from 1993 to 2022 and analyze their accuracy, presence of coefficients and accuracy of the Klobuchar model. Early GPS navigation messages often did not include ionospheric data, and even when they did include ionospheric models, the accuracy was often quite low. From 2002, when the accuracy of the ionospheric model was stabilized, until 2022, the accuracy of the ionospheric model is analyzed by comparing it with the ionospheric model of the International GNSS Service (IGS). Changes in accuracy per day and per year and accuracy differences along geomagnetic latitude are analyzed.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.1
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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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• v.13 no.2
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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.

• Journal of Applied Reliability
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• v.17 no.4
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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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• v.46 no.1
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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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• v.12 no.1
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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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• 1993.10b
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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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• v.17 no.2
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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.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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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.