Journal of the Korean Association of Geographic Information Studies
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v.22
no.3
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pp.82-98
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2019
The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.
The purpose of this study is to evaluate the effectiveness of virtual grid software (VGS). The purpose of this study is to evaluate the changes in energy and object thickness by dividing the use of VGS into two cases (Without-VGS) without using a movable grid. We attempted to determine the effectiveness of VGS by acquiring images using a chest phantom and a thigh phantom and analyzing SNR and CNR. In the chest phantom and femoral phantom, the tube flow was fixed at 2.5 mAs, and the tube voltage was changed by 10 kVp from 60 to 100 kVp to measure SNR and CNR, and SNR was about 1.09 to 8.86% higher in the chest phantom than in Without-VGS, and CNR was 4.18 to 14.56% higher in the VGS than in Without-VGS. And in the femoral phantom, SNR was about 9.78 to 18.05% higher in VGS than in Without-VGS, and CNR was 21.07 to 44.44% higher in VGS than in Without-VGS. The tube voltage was fixed at 70 kVp in the chest phantom and the femoral phantom, and the amount of tube current was changed at 2.5 to 16 mAs, respectively, and after X-ray irradiation, SNR and CNR were measured in the chest phantom, which was about 1.49 to 11.11% higher in VGS than in Without-VGS, and CNR was 4.76 to 13.40% higher in VGS than in Without-VGS. And in the femoral phantom, SNR was about 2.22 to 17.38% higher in VGS than in Without-VGS, and CNR was 13.85 to 40.46% higher in VGS than in Without-VGS. Therefore, if an inspection is required with a mobile X-ray imaging device, it is believed that good image quality can be obtained by using VGS in an environment where it is difficult to use a mobile grid, and it is believed that the use of mobile X-ray devices can be increased.
The only law related to airblast and ground vibration control in Korea is the Noise and Vibration Control Act enforced by the Ministry of Environment. But this law mainly deals with the annoyance aspects of noises and vibrations in ordinary human life. Hence, the law defines the safety criteria of ground vibration as the vibration level (VL) of dB(V) unit. The ground vibrations produced from blasting, however, have the unique characteristics that can be shown in shock vibrations, and the duration is also very short compared to the vibrations from machinery, tools or facilities. Hence, vibration regulations for blasting operations usually define the safety criterion as the peak particle velocity (PPV) considering the effect of ground vibrations to structural damage. Notwithstanding, there are several attempts that predict VL from PPV or estimate VL based on the scaled distances (SD; in unit of $m/kg^{1/2}$ or $m/kg^{1/3}$) without considering their frequency spectra. It appears that these attempts are conducted mainly for the purpose of satisfying the law in blasting contracts. But, in principle there could no correlation between peaks of velocity and acceleration over entire frequency spectrum. Therefore, such correlations or estimations should be conducted only for the waves with the same or very similar frequency spectra.
Journal of the Korean Association of Geographic Information Studies
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v.23
no.3
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pp.12-25
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2020
The purpose of this study was to obtain information about the type of drones suitable for the management of entrants and entrants of islands in the marine national park. The research sites were 25 islands in the Hallyeohaesang National Park. The target islands were divided into three zones, and were investigated with different types of drones. The survey period was from October to November, 2019. As a result of the operation of drone airframe, drone with fixed wings was found to be favorable for the management of marine parks in medium and long distances compared to other types, but stopping flights for broadcasting was found to be unsuitable. Drone with rotational wings was found to be suitable for image acquisition and broadcasting through close flight. However, it was deemed suitable for short and medium distance flights because of the fast battery consumption. In the case of helicopter rotorcraft drone, image acquisition and broadcasting were possible, but noise and vibration caused by propellers were disadvantageous. The number of entrants to the islands totaled 410 and the main act was fishing. The proportion of entrants to the islands in Area A was higher than that of other areas, and thus it was deemed more necessary to manage the area. Broadcasting was found to have had a positive effect on the management of fishers.
Park, Dae-Jin;Kwak, Sung-Ho;Kim, Chang-Min;Kim, Tag-Gon
Journal of the Institute of Electronics Engineers of Korea SP
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v.48
no.6
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pp.18-26
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2011
Debates concerning the competitive edge of leading 3DTV technology of the shutter glasses (SG) 3D and the film-type patterned retarder (FPR) are flaring up. Although SG technology enables Full-HD 3D vision, it requires complex systems including the sync transmitter (emitter), the sync processor chip, and the LCD lens in the active shutter glasses. In addition, the transferred sync-signal is easily affected by the external noise and a 3DTV viewer may feel flicker-effect caused by cross-talk of the left and right image. The operating current of the sync processor in the 3DTV active shutter glasses is gradually increasing to compensate the sync reconstruction error. The proposed chip is a low-power hardware sync processor based discrete-event SoC(system on a chip) designed specifically for the 3DTV active shutter glasses. This processor implements the newly designed power-saving techniques targeted for low-power operation in a noisy environment between 3DTV and the active shutter glasses. This design includes a hardware pre-processor based on a universal edge tracer and provides a perfect sync reconstruction based on a floating-point timer to advance the prior commercial 3DTV shutter glasses in terms of their power consumption. These two techniques enable an accurate sync reconstruction in the slow clock frequency of the synchronization timer and reduce the power consumption to less than about a maximum of 20% compared with other major commercial processors. This article describes the system's architecture and the details of the proposed techniques, also identifying the key concepts and functions.
Journal of the Institute of Electronics Engineers of Korea SP
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v.47
no.6
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pp.66-74
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2010
Recently distributed video coding (DVC) is spotlighted for the environment which has restriction in computing resource at encoder. Wyner-Ziv (WZ) coding is a representative scheme of DVC. The WZ encoder independently encodes key frame and WZ frame respectively by conventional intra coding and channel code. WZ decoder generates side information from reconstructed two key frames (t-1, t+1) based on temporal correlation. The side information is regarded as a noisy version of original WZ frame. Virtual channel noise can be removed by channel decoding process. So the performance of WZ coding greatly depends on the performance of channel code. Among existing channel codes, Turbo code and LDPC code have the most powerful error correction capability. These channel codes use stochastically iterative decoding process. However the iterative decoding process is quite time-consuming, so complexity of WZ decoder is considerably increased. Analysis of the complexity of LPDCA with real video data shows that the portion of complexity of LDPCA decoding is higher than 60% in total WZ decoding complexity. Using the HDA (Hard Decision Aided) method proposed in channel code area, channel decoding complexity can be much reduced. But considerable RD performance loss is possible according to different thresholds and its proper value is different for each sequence. In this paper, we propose an adaptive HDA method which sets up a proper threshold according to sequence. The proposed method shows about 62% and 32% of time saving, respectively in LDPCA and WZ decoding process, while RD performance is not that decreased.
Kong, Hae Jung;Kim, Seong Dae;Kim, Minju;Han, Seung Hoon
Journal of the Institute of Electronics and Information Engineers
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v.50
no.4
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pp.171-181
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2013
Recently, ground penetrating radar(GPR) has been widely used in detecting metallic and nonmetallic buried landmines and a number of related researches have been reported. A novel preprocessing method is proposed in this paper to flag potential locations of buried mine-like objects from GPR array measurements. GPR operates by measuring the reflection of an electromagnetic pulse from discontinuities in subsurface dielectric properties. As the GPR pulse propagates in the geologic medium, it suffers nonlinear attenuation as the result of absorption and dispersion, besides spherical divergence. In the proposed algorithm, a logarithmic transformed regression model which successfully represents the time-varying signal amplitude of the GPR data is estimated at first. Then, background signals may be densely distributed near the regression model and candidate signals of targets may be far away from the regression model in the time-amplitude space. Based on the observation, GPR signals are decomposed into candidate signals of targets and background signals using residuals computed from the estimated value by regression and the measurement of GPR. Candidate signals which may contain target signals and noise signals need to be refined. Finally, targets are detected through the refinement of candidate signals based on geometric signatures of mine-like objects. Our algorithm is evaluated using real GPR data obtained from indoor controlled environment and the experimental results demonstrate remarkable performance of our mine-like object detection method.
With the advent of high-speed railways, railways are one of the most frequently used means of transportation at home and abroad. In addition, in terms of environment, carbon dioxide emissions are lower and energy efficiency is higher than other transportation. As the interest in railways increases, the issue related to railway safety is one of the important concerns. Among them, visual abnormalities occur when various obstacles such as animals and people suddenly appear in front of the railroad. To prevent these accidents, detecting rail tracks is one of the areas that must basically be detected. Images can be collected through cameras installed on railways, and the method of detecting railway rails has a traditional method and a method using deep learning algorithm. The traditional method is difficult to detect accurately due to the various noise around the rail, and using the deep learning algorithm, it can detect accurately, and it combines the two algorithms to detect the exact rail. The proposed algorithm determines the accuracy of railway rail detection based on the data collected.
Journal of the Korean Institute of Landscape Architecture
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v.43
no.5
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pp.28-39
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2015
The purpose of this study is to analyze users' behavior and facility satisfaction and to suggest the practical solution plans for environmental improvement of trails in Suseong recreation park in Daegu. Therefore, satisfaction factor analysis on trails was carried out based on a field and questionnaire survey in Suseong recreation park. First, from users' behavior, 48% of users visited Suseong recreation park for walking. The greatest response to number of visits was once or twice a week, and average use time per visit was 80.4 minutes. In terms of trails, the greater responses to the number of visits were once(38.1%) or more than 5 times(23.8%), and average use time was 45.4 minutes. According to the results from the analysis of facility satisfaction, management condition, length, slope, and adjacent natural landscape of trails were evaluated at a satisfaction rate higher than 3.4 points. However, water pollution, and number of exits and parking lots were analyzed at a low rate of 2.75 and 2.78 points, respectively. In terms of analyzing determining factors of facility satisfaction for trails, use of facilities, walking convenience, surrounding landscapes, amenities, and noise had a significantly positive effect on satisfaction. In particular, walking convenience was the highest effect factor; its standardized coefficient was 0.533. The findings from this study can contribute to the improvement of the physical environment for trails of Suseong recreation park and provide basic data for plan and maintenance of similar waterside trails.
Kim, Yoo-Jun;Kim, Seon-Jeong;Kim, Geon-Tae;Choi, Byoung-Choel;Shim, Jae-Kwan;Kim, Byung-Gon
Korean Journal of Remote Sensing
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v.32
no.4
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pp.365-382
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2016
The results from the Global Positioning System (GPS) measurements of the Mobile Observation Vehicle (MOVE) on the eastern coast of Korea have been compared with REFerence (REF) values from the fixed GPS sites to assess the performance of Precipitable Water Vapor (PWV) retrievals in a kinematic environment. MOVE-PWV retrievals had comparatively similar trends and fairly good agreements with REF-PWV with a Root-Mean-Square Error (RMSE) of 7.4 mm and $R^2$ of 0.61, indicating statistical significance with a p-value of 0.01. PWV retrievals from the June cases showed better agreement than those of the other month cases, with a mean bias of 2.1 mm and RMSE of 3.8 mm. We further investigated the relationships of the determinant factors of GPS signals with the PWV retrievals for detailed error analysis. As a result, both MultiPath (MP) errors of L1 and L2 pseudo-range had the best indices for the June cases, 0.75-0.99 m. We also found that both Position Dilution Of Precision (PDOP) and Signal to Noise Ratio (SNR) values in the June cases were better than those in other cases. That is, the analytical results of the key factors such as MP errors, PDOP, and SNR that can affect GPS signals should be considered for obtaining more stable performance. The data of MOVE can be used to provide water vapor information with high spatial and temporal resolutions in the case of dramatic changes of severe weather such as those frequently occurring in the Korean Peninsula.
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