• Journal of Information Processing Systems
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• v.11 no.4
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• pp.556-572
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• 2015

This paper presents the applications of spatial interpolation and assimilation methods for satellite and ground meteorological data, including temperature, relative humidity, and precipitation in regions of Vietnam. In this work, Universal Kriging is used for spatially interpolating ground data and its interpolated results are assimilated with corresponding satellite data to anticipate better gridded data. The input meteorological data was collected from 98 ground weather stations located all over Vietnam; whereas, the satellite data consists of the MODIS Atmospheric Profiles product (MOD07), the ASTER Global Digital Elevation Map (ASTER DEM), and the Tropical Rainfall Measuring Mission (TRMM) in six years. The outputs are gridded fields of temperature, relative humidity, and precipitation. The empirical results were evaluated by using the Root mean square error (RMSE) and the mean percent error (MPE), which illustrate that Universal Kriging interpolation obtains higher accuracy than other forms of Kriging; whereas, the assimilation for precipitation gradually reduces RMSE and significantly MPE. It also reveals that the accuracy of temperature and humidity when employing assimilation that is not significantly improved because of low MODIS retrieval due to cloud contamination.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.1-10
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• 2024

The research on predicting the routes of ships, which constitute the majority of maritime transportation, can detect potential hazards at sea in advance and prevent accidents. Unlike roads, there is no distinct signal system at sea, and traffic management is challenging, making ship route prediction essential for maritime safety. However, the time intervals of the ship route datasets are irregular due to communication disruptions. This study presents a method to adjust the time intervals of data using appropriate interpolation techniques for ship route prediction. Additionally, a deep learning model for predicting ship routes has been developed. This model is an LSTM model that predicts the future GPS coordinates of ships by understanding their movement patterns through real-time route information contained in AIS data. This paper presents a data preprocessing method using linear interpolation and a suitable deep learning model for ship route prediction. The experimental results demonstrate the effectiveness of the proposed method with an MSE of 0.0131 and an Accuracy of 0.9467.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.108-116
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• 2008

In this paper, we propose an algorithm that can estimate the distance using disparity based on stereo vision system, even though the obstacle is located in long ranges as well as short ranges. We use sub-pixel interpolation to minimize quantization errors which deteriorate the distance accuracy when calculating the distance with integer disparity, and also we use enhanced adaptive fuzzy strong tracking Kalman filter(EAFSTKF) to improve the distance accuracy and track the path optimally. The proposed method can solve the divergence problem caused by nonlinear dynamics such as various vehicle movements in the conventional Kalman filter(CKF), and also enhance the distance accuracy and reliability. Our simulation results show that the performance of our method improves by about 13.5% compared to other methods in point of root mean square error rate(RMSER).

• Journal of Advanced Navigation Technology
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• v.24 no.5
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• pp.374-381
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• 2020

In order to improve the vertical position accuracy, the advantages of GPS and barometric altimeter are combined and used, but in order to fuse the two sensors, the geoid altitude must be compensated. In this paper, we proposed a technique that can calculate geoid altitude in real time even in low-cost embedded systems applied to drones or autonomous vehicles. Since the reference EGM08 is determined by a polynomial of the 2160th order, real-time calculation is impossible in the embedded system. Therefore, by introducing a linear interpolation technique, the amount of calculation was increased, and the storage space was saved by 75% by using the integer geoid height as a grid point. The accuracy of the proposed technique was evaluated through simulation, and it was confirmed that the accuracy of the maximum error is -1.215 m even in the region where the geoid change is rapid.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.478-485
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• 2021

An injection locking technology of a semiconductor laser is a promising technology to generate optical complex signals by adjusting optical injection parameters. The extraction of the precise injection parameters plays a key role in the generation of the optical complex signal. Rate equations of semiconductor lasers under optical injection are commonly used to map the injection parameters and the corresponding optical complex signal. The accuracy of the generated optical complex signal on the injection parameters is limited since the rate equations require a locking map-based interpolation method. We propose a novel analytic method, namely rate equation-based direct extraction method, to directly calculate the injection parameters without relying on the locking map-based interpolation method. We achieved 103-times improvement of the signal accuracy by using the proposed method compared to locking-map based interpolation method.

• Journal of Broadcast Engineering
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• v.16 no.5
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• pp.873-882
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• 2011

In this paper, we propose an efficient deinterlacing algorithm which interpolates the missing scan lines by weighted summing of the intra and the inter interpolation pixels according to the spatio-temporal variation. In the spatial interpolation, we adopt a new edge based spatial interpolation method which includes edge directional refinement. The conventional edge dependent interpolation algorithms are very sensitive to noise due to the failure of estimating edge direction. In order to exactly detect edge direction, our method first finds the edge directions around the pixel to be interpolated and then refines edge direction of the pixel using weighted maximun frequent filter. Futhermore, we improve the accuracy of motion detection by reducing the possibility of motion detection error using 3 tab median filter. In the final interpolation step, we adopt weighted sum of intra and inter interpolation pixels according to spatio-temporal variation ratio, thereby improving the quality in slow moving area. Simulation results show the efficacy of the proposed method with significant improvement over the previous methods in terms of the objective PSNR quality as well as the subjective image quality.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.29-41
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• 2010

In this study, the prediction errors of various spatial interpolation methods used to model values at unmeasured locations was compared and the accuracy of these predictions was evaluated. The root mean square (RMS) was calculated by processing different parameters associated with spatial interpolation by using techniques such as inverse distance weighting, kriging, local polynomial interpolation and radial basis function to known elevation data of the east coastal area under the same condition. As a result, a circular model of simple kriging reached the smallest RMS value. Prediction map using the multiquadric method of a radial basis function was coincident with the spatial distribution obtained by constructing a triangulated irregular network of the study area through the raster mathematics. In addition, better interpolation results can be obtained by setting the optimal power value provided under the selected condition.

• Journal of Industrial Technology
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• v.14
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• pp.127-140
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• 1994

This study is concerned with the accuracy and the patterns when different methods was used in interpolation task. Although 3 methods employed the same modality for input (visual) and for output (manual responding), they differed in central processing, which method 1 is relatively more tendency of verbal processing, method 2 is realtively more tendency of spatial processing and method 3 needed a number of switching code (verbal/spatial) performing task. Split-plot design was adopted, which whole plot consisted of methods (3), orientations (horizon, vertical), base-line sizes (300, 500, 700 pixels) and split plot consisted of target locations (1-99). The results showed the anchor effect and the range effect. Method 2, method 3 and method 1 that order was better accuracy. ANOVA showed that the accuracy was significantly influenced by the method, the location of target, and its interactions ($method{\times}location$, $size{\times}location$). Analysis of error data, response time and frequency of under, just, over estimate indicated that a systematic error pattern was made in task and methods changed not only the performance but also the pattern. The results provided support for the importance of the multiple resources theory in accounting for S-C-R compatibility and task performance. They are discussed in terms of multiple resources theory and guidelines for system design is suggested by the S-C-R compatibility.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.8 no.1
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• pp.41-50
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• 1990

The purpose of this thesis lies in proving the practicality of photogrammetry and in promoting photogrammetry in earthwork which plays a major role in civil engineering projects. Analysis of accuracy in the determination of ammount of earthework was done by applying interpolation methods in digital terrain model. As a result of analysis of the data acquisition method, in cross-section method produced acceptable accuracy from Simpson's three-eighths rule and prismoidal rule. In results DTM, we have obtained the fact that earthwork calculation accuracy was increased by applying two or more interpolation methods. Therefore, the method by digital terrain model using aerial photograph has proved to be more efficient.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.387-390
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• 2005

Parameter estimation for the probability model of wavelet coefficients is essential to the wavelet-domain interpolation. However, phase uncertainty, one well-known drawback of the orthogonal wavelet transforms, make it difficult to estimate parameters. In this paper, we exploit a phase shifting matrix in order to improve the accuracy of estimation. Nonlinear modeling to capture the interscale characteristics is also described. The experimental results show that the proposed method outperforms the previous wavelet-domain interpolation method as well as the conventional bicubic method.