• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.4
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• pp.467-474
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• 2019

Recently, optical phased array(OPA) based laser detection and ranging(LADAR) has gained great interest to replace the traditional mechanical light detection and ranging technique(LiDAR). In OPA-based LADAR, it is well known that phases of laser pulses traveling through each of channels should be the same to obtain a narrow free-space single beam without noise-like ripples in the far field. However, it is difficult to provide such ideal condition due to the fabrication errors. To tackle this problem, any algorithms should be necessary to compensate the initial random phases of each channel in OPA antenna. In this paper, we propose a hill-climbing based phase calibration algorithm and evaluate the performance of the proposed algorithm.

• Ocean and Polar Research
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• v.44 no.2
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• pp.179-190
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• 2022

Data missing in optical satellite images caused by natural variations have been a crucial barrier in observing the status of marine surfaces. Although there have been many attempts to fill the gaps of non-observation, there is little research to analyze the ratio of missing grids to overall sea grids and their seasonal patterns. This report introduces the method of quantifying the distribution of missing points and then shows how the missing points have spatial correlation and seasonal trends. Both temporal and spatial integration methods are compared to assess the effectiveness of reducing missing data. The temporal integration shows more outstanding performance than the spatial integration. Moran's I and K-function with statistical hypothesis testing show that missing grids are clustered and there is a non-random distribution from daily integration. The result of the seasonality test for Moran's I through a periodogram shows dependency on full-year, half-year, and quarter-year periods respectively. These analysis results can be used to deduce appropriate integration periods with permissible estimation errors.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.233-238
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• 2020

In the cloud environment, IoT devices using sensors and wearable devices are being applied in various environments, and technologies that accurately determine the information generated by IoT devices are being actively studied. However, due to limitations in the IoT environment such as power and security, information generated by IoT devices is very weak, so financial damage and human casualties are increasing. To accurately collect and analyze IoT information, this paper proposes a topographic information-based key management technique that considers IoT information errors. The proposed technique allows IoT layout errors and groups topographic information into groups of dogs in order to secure connectivity of IoT devices in the event of arbitrary deployment of IoT devices in the cloud environment. In particular, each grouped terrain information is assigned random selected keys from the entire key pool, and the key of the terrain information contained in the IoT information and the probability-high key values are secured with the connectivity of the IoT device. In particular, the proposed technique can reduce information errors about IoT devices because the key of IoT terrain information is extracted by seed using probabilistic deep learning.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.321-332
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• 2024

Understanding the status of surface cover in riparian zones is essential for river management and flood disaster prevention. Traditional survey methods rely on expert interpretation of vegetation through vegetation mapping or indices. However, these methods are limited by their ability to accurately reflect dynamically changing river environments. Against this backdrop, this study utilized satellite imagery to apply the Random Forest method to assess the distribution of vegetation in rivers over multiple years, focusing on the Naeseong Stream as a case study. Remote sensing data from Sentinel-2 imagery were combined with ground truth data from the Naeseong Stream surface cover in 2016. The Random Forest machine learning algorithm was used to extract and train 1,000 samples per surface cover from ten predetermined sampling areas, followed by validation. A sensitivity analysis, annual surface cover analysis, and accuracy assessment were conducted to evaluate their applicability. The results showed an accuracy of 85.1% based on the validation data. Sensitivity analysis indicated the highest efficiency in 30 trees, 800 samples, and the downstream river section. Surface cover analysis accurately reflects the actual river environment. The accuracy analysis identified 14.9% boundary and internal errors, with high accuracy observed in six categories, excluding scattered and herbaceous vegetation. Although this study focused on a single river, applying the surface cover classification method to multiple rivers is necessary to obtain more accurate and comprehensive data.

• Radiation Oncology Journal
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• v.19 no.3
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• pp.287-292
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• 2001

Prupose : We analyzed setup errors induced by using air-vacuum cushion as immobilization device in patients with rectal cancer. Materials and methods : We had treated the twenty patients with rectal cancer by 6 MV, 10 MV X-ray from Aug. 1998 to Aug. 1999 at Chungnam National University Hospital. All patients were treated at prone position. They were separated to two groups, control group, 10 patients using styrofoam, and test group, 10 patients using styrofoam and air-vacuum cushion. We measured errors of posterior field for x, y axis and lateral field for z, y axis with simulation film and EPID image using a matching technique. Results : In control group, the mean displacement values of pelvic bone landmark for x axis and y axis were 0.02 mm. 0.78 mm, respectively and the standard deviations of systematic error were 2.13 mm, 2.40 mm, respectively and the standard deviation of random error were 1.46 mm. 1.51 mm, respectively. In test group, the mean displacement values of x axis and y axis were -0.33 mm. 0.81 mm, respectively and the standard deviations of systematic error were 1.71 mm, 3.08 mm, respectively and the standard deviations of random errors were 1.40 mm. 1.88 mm, respectively. The mean displacement values of z axis and y axis were 2.98 mm. 0.74 mm, respectively and the standard deviations of systematic error were 4.75 mm, 2.65 mm, respectively and standard deviations of random error were 2.69 mm. 1.86 mm, respectively. The statistical difference of field size by using air vacuum cushion between two groups in posterior direction and lateral direction was not shown. Conclusion : We think that use of air-vacuum cushion may not be an advantage for improving setup accuracy in rectal cancer patients.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.543-559
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• 2019

Data often include missing values due to various reasons. If the missing data mechanism is not MCAR, analysis based on fully observed cases may an estimation cause bias and decrease the precision of the estimate since partially observed cases are excluded. Especially when data include many variables, missing values cause more serious problems. Many imputation techniques are suggested to overcome this difficulty. However, imputation methods using parametric models may not fit well with real data which do not satisfy model assumptions. In this study, we review imputation methods using nonlinear models such as kernel, resampling, and spline methods which are robust on model assumptions. In addition, we suggest utilizing imputation classes to improve imputation accuracy or adding random errors to correctly estimate the variance of the estimates in nonlinear imputation models. Performances of imputation methods using nonlinear models are compared under various simulated data settings. Simulation results indicate that the performances of imputation methods are different as data settings change. However, imputation based on the kernel regression or the penalized spline performs better in most situations. Utilizing imputation classes or adding random errors improves the performance of imputation methods using nonlinear models.

• Journal of The Korean Association of Information Education
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• v.1 no.1
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• pp.11-27
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• 1997

The purpose of this paper is to examine some effects of four menu types: icon menu, icontext menu, pulldown menu, and bar selection menu. Each have been mainly used with hypermedia instruction, learners' metacognition on their errors, menu search time, and scholastic achievements. A further purpose of this paper is suggest some strategies for enabling each learner to select menus more efficiently in order to enhance the learner's own learning effectiveness in hypermedia instruction. There were 100 college students selected as subjects for This study. They had never had experience in Hanoi hypermedia instruction. They were required to use four menu types at random in this experiement. The results of this study are as follows. The menu types had a significant effect on the low metacognition regulation group. Icontext menu types, especially, had a significant effect on achievements. In constrast to this, the menu types did not have any significant effect on the high metacognition regulation group.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1513-1525
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• 2016

Rapid and accurate phase synchronization is critical for the reliable control of grid-tied inverters. However, the commonly used software phase-locked loop methods do not always satisfy the need for high-speed and accurate phase synchronization under severe grid imbalance conditions. To address this problem, this study develops a novel open-loop phase locking scheme based on a synchronous reference frame. The proposed scheme is characterized by remarkable response speed, high accuracy, and easy implementation. It comprises three functional cascaded blocks: fast orthogonal signal generation block, fast fundamental-frequency positive sequence component construction block, and fast phase calculation block. The developed virtual orthogonal signal generation method in the first block, which is characterized by noise immunity and high accuracy, can effectively avoid approximation errors and noise amplification in a wide range of sampling frequencies. In the second block, which is the foundation for achieving fast phase synchronization within 3 ms, the fundamental-frequency positive sequence components of unsymmetrical grid voltages can be achieved with the developed orthogonal signal construction strategy and the symmetrical component method. The real-time grid phase can be consequently obtained in the third block, which is free from self-tuning closed-loop control and thus improves the dynamic performance of the proposed scheme. The proposed scheme is adaptive to severe unsymmetrical grid voltages with sudden changes in magnitude, phase, and/or frequency. Moreover, this scheme is able to eliminate phase errors induced by harmonics and random noise. The validity and utility of the proposed scheme are verified by the experimental results.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.91-98
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• 2009

This paper presents a solution to error avalanche of deciphering where radio noise brings random bit errors in encrypted image data under ubiquitous environment. The image capturing module is to be made comprising data compression and encryption features to reduce data traffic volume and to protect privacy. Block cipher algorithms may experience error avalanche: multiple pixel defects due to single bit error in an encrypted message. The new fault tolerant scheme addresses error avalanche effect exploiting a three-dimensional data shuffling process, which disperses error bits on many frames resulting in sparsely isolated errors. Averaging or majority voting with neighboring pixels can tolerate prominent pixel defects without increase in data volume due to error correction. This scheme has 33% lower data traffic load with respect to the conventional Hamming code based approach.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.5
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• pp.38-44
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• 2007

This paper presented a location and attitude estimation scheme of a capsule endoscope based on ultrasonic ranging. The scheme comprised eight on-capsule ultrasonic sensors to alleviate measurement errors due to irregularities in human body ultrasonic characteristics. It calculated the coordinate values and angles in a Cartesian coordinate system. The Matlab simulation reflecting random errors yielded the average deviations of 0.8mm in the location and $0.2^{\circ}$ in the attitude angle. These values are far smaller than normal intestine movement ranges inside human body, and will contribute accurate diagnosis of intestine.