• Journal of Positioning, Navigation, and Timing
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• v.3 no.3
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• pp.117-122
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• 2014

In CDGPS, ambiguity resolution is determined by the performance of a floating solution, and thus, the performance needs to be improved. In the case of precise positioning at a stationary position, the batch method using multiple measurements is used for the accuracy improvement of a position. The position accuracy performance of a floating solution is outstanding, but it has a problem of high computation cost because all measurements are used. In this study, to improve the floating solution performance of the initial static user in CDGPS, a floating solution method using a recursive filter was implemented. A recursive filter estimates the position solution of the current epoch using the position solution of up to the previous epoch and the pseudorange measurement of the current epoch. The computation cost of the floating solution method using a recursive filter was found to be similar to that of the epoch-by-epoch method. Also, based on actual GPS signals, the floating solution performance was found to be similar to that of the batch method. The floating solution using a recursive filter could significantly improve the performance of the prompt initial position and ambiguity resolution of the initial static user.

• Journal of the Korea Society of Computer and Information
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• v.25 no.2
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• pp.123-131
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• 2020

The text ranking algorithm is a representative method for keyword extraction, and its importance is emphasized highly. In this paper, we compare the performance of recent research and experiments with TF-IDF, SMART, INQUERY and CCA algorithms, which are used in text ranking algorithm.. After explaining each algorithm, we compare the performance of each algorithm based on the data collected from news and Twitter. Experimental results show that all of four algorithms can extract specific words from news data equally. However, in the case of Twitter, CCA has the best performance to extract specific words, and INQUERY shows the worst performance. We also analyze the accuracy of the algorithm through six comparison metrics. The experimental results present that CCA shows the best accuracy in the news data. In case of Twitter, TF-IDF and CCA show similar performance and demonstrate good performance.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.125-132
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• 2018

The purpose of this study is to analyze the effect of managerial predictive accuracy on managerial performance-compensation. In this study, we compared managerial performance with managerial performance, And to analyze the relationship between manager compensation and manager compensation using managerial profit prediction accuracy. As a result of this study, there is a significant positive relationship between profit prediction accuracy and manager compensation, which can be interpreted as a result of manager's ability to compensate manager's ability to predict the future well. In this paper, we propose a new methodology that can be used to analyze the effects of managerial compensation on managerial compensation. This is because there is a difference in that it is proved to be a factor. Therefore, it is important to note that the prediction of the future of the company also identifies the additional determinants that affect manager compensation contracts with the key managerial capabilities.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.183-192
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• 2017

k-nearest neighbor (K-NN) is a well-known classification algorithm, being feature space-based on nearest-neighbor training examples in machine learning. However, K-NN, as we know, is a lazy learning method. Therefore, if a K-NN-based system very much depends on a huge amount of history data to achieve an accurate prediction result for a particular task, it gradually faces a processing-time performance-degradation problem. We have noticed that many researchers usually contemplate only classification accuracy. But estimation speed also plays an essential role in real-time prediction systems. To compensate for this weakness, this paper proposes correlation coefficient-based clustering (CCC) aimed at upgrading the performance of K-NN by leveraging processing-time speed and plurality rule-based density (PRD) to improve estimation accuracy. For experiments, we used real datasets (on breast cancer, breast tissue, heart, and the iris) from the University of California, Irvine (UCI) machine learning repository. Moreover, real traffic data collected from Ojana Junction, Route 58, Okinawa, Japan, was also utilized to lay bare the efficiency of this method. By using these datasets, we proved better processing-time performance with the new approach by comparing it with classical K-NN. Besides, via experiments on real-world datasets, we compared the prediction accuracy of our approach with density peaks clustering based on K-NN and principal component analysis (DPC-KNN-PCA).

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2017.11a
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• pp.199-200
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• 2017

In order to meet the international performance requirements for eLoran testbed operation, it is necessary to measure ASF (Additional Secondary Factor) of vessel's route as well as differential correction and the provision using differential Loran (dLoran) station operation. According to HEA (Harbor Entrance and Approach) performance of the IMO, the position accuracy should be within 10meters. Therefore this paper presents the possibility to meet the position accuracy of the IMO HEA through simulation results.

• Aerospace Engineering and Technology
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• v.11 no.2
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• pp.171-181
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• 2012

As a sub-system of an air traffic control system, SDP(Surveillance Data Processor) provides with the system tracks of aircraft using the surveillance sensor data from various air traffic surveillance sensors, such as radars. Therefore, the high accuracy of tracking results is a crucial requirement for safe flights, and verification of the required system performance of SDP is an essential step in development. Moreover, the quantitative evaluation of target tracking accuracy is important for newly developed SDP, since there are several tracking methods for Multi-Sensor Multi-Target Tracking, such as MRT(Multi Radar Tracking), inevitably required as the main function of SDP. In this study, definition of required system performances, establishment of test environment, and test results for MRT performance evaluation of SDP, which is being developed in KARI(Korea Airspace Research Institute) are presented.

• Computers and Concrete
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• v.19 no.3
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• pp.283-291
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• 2017

A large number of residential buildings in regions subjected to severe earthquakes do not have enough load carrying capacity. The most of them have been constructed without receiving any structural engineering attention. It is practically almost impossible to perform detailed experimental evaluation and analytical analysis for each building to determine their seismic vulnerability, because of time and cost constraints. This fact points to a need for a simple evaluation method that focuses on selection of buildings which do not have the life safety performance level by adopting the main requirements given in the seismic codes. This paper deals with seismic assessment of existing reinforced concrete residential buildings and contains an alternative simplified procedure for seismic evaluation of buildings. Accuracy of the proposed procedure is examined by taking into account existing 250 buildings. When the results of the proposed procedure are compared with those of the detailed analyses, it can be seen that the results are quite compatible. It is seen that the accuracy of the proposed procedure is about 80% according to the detailed analysis results of existing buildings. This accuracy percentage indicates that the proposed procedure in this paper can be easily applied to existing buildings to predict their seismic performance level as a first approach before implementing the detailed and complex analyses.

• Journal of Biosystems Engineering
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• v.32 no.6
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• pp.383-388
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• 2007

In precision farming, proper calibration and operation of a variable rate machine are critical to reduce input of agrochemicals and to ensure productivity and quality of agricultural products. As an effort to introduce precision farming to rice production in Korea, a pneumatic granular applicator was developed. This investigation intended to evaluate the application performance such as application accuracy, application uniformity and to suggest how to adjust the blow-heads to get uniform application pattern, and to suggest a practical way of adjustment of the blow-heads for uniform application. Tests to evaluate the application performance were conducted. The application uniformities (CV) in both transverse direction and longitudinal direction were less than 15% and application accuracy was greater than 81%. A simple method for adjusting the inserting length of blow-heads was suggested.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.252-256
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• 1998

Accurate mapping of satellite images is one of the most important Parts in many remote sensing applications. Since the position and the attitude of a satellite during image acquisition cannot be determined accurately enough, it is normal to have several hundred meters' ground-mapping errors in the systematically corrected images. The users which require a pixel-level or a sub-pixel level mapping accuracy for high-resolution satellite images must use a number of Ground Control Points (GCPs). In this paper, the performance of two geometric correction algorithms is tested and compared. One is the polynomial warping algorithm which is simple and popular enough to be implemented in most of the commercial satellite image processing software. The other is full camera modelling algorithm using Physical orbit-sensor-Earth geometry which is used in satellite image data receiving, pre-processing and distribution stations. Several criteria were considered for the performance analysis : ultimate correction accuracy, GCP representatibility, number of GCPs required, convergence speed, sensitiveness to inaccurate GCPs, usefulness of the correction results. This paper focuses on the usefulness of the precision correction algorithm for regular image pre-processing operations. This means that not only final correction accuracy but also the number of GCPs and their spatial distribution required for an image correction are important factors. Both correction algorithms were implemented and will be used for the precision correction of KITSAT-3 images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.6
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• pp.599-606
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• 2014

Since the accuracy of Global Positioning System (GPS)-based vehicle positioning system is significantly degraded or does not work appropriately in the urban canyon, the integration techniques of GPS with Inertial Navigation System (INS) have intensively been developed to improve the continuity and reliability of positioning. However, its accuracy is degraded as INS errors are not properly corrected due to the GPS signal blockage. Recently, the image-based positioning techniques have been started to apply for the vehicle positioning for the advanced in processing techniques as well as the increased the number of cars installing the camera. In this study, Single Photo Resection (SPR), which calculates the camera exterior orientation parameters using the Ground Control Points (GCPs,) has been integrated with the INS/GPS for continuous and stable positioning. The INS/GPS/SPR integration was implemented in both of a loosely and a tightly coupled modes, based on the Extended Kalman Filter (EKF). In order to analyze the performance of INS/SPR integration during the GPS outage, the simulation tests were conducted with a consideration of factors affecting SPR performance. The results demonstrate that the accuracy of INS/SPR integration is depended on magnitudes of the GCP errors and SPR processing intervals. Additionally, the simulation results suggest some required conditions to achieve accurate and continuous positioning, used the INS/SPR integration.