• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.35-45
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• 2018

Motion Estimation(ME) has been developed to reduce the redundant data in digital video signal. ME is an important part of video encoding system, However, it requires huge computational complexity of the encoder part, and fast motion search methods have been proposed to reduce huge complexity. Multi- view video is obtained by capturing on a three-dimensional scene with many cameras at different positions and its complexity increases in proportion to the number of cameras. In this paper, we proposed an efficient motion method which chooses a search pattern adaptively by using the temporal-spatial correlation of the block and the characteristics of the block. Experiment results show that the computational complexity reduction of the proposed method over TZ search method and FS method can be up to 70~75% and 99% respectively while keeping similar image quality and bit rates.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.75-85
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• 2017

A method to estimate hourly temperature profiles on calm and clear nights was developed based on temporal changes of inversion height and strength. A meteorological temperature profiler (Model MTP5H, Kipp and Zonen) was installed on the rooftop of the Highland Agriculture Research Institute, located in Daegwallyeong-myeon, Pyeongchang-gun, Gangwon-do. The hourly vertical distribution of air temperature was measured up to 600 m at intervals of 50 m from May 2007 to March 2008. Temperature and relative humidity data loggers (HOBO U23 Pro v2, Onset Computer Corporation, USA) were installed in the Jungdae-ri Valley, located between Gurye-gun, Jeollanam-do and Gwangyang-si, Jeollanam-do. These loggers were used to archive measurements of weather data 1.5 m above the surface from October 3, 2014, to November 23, 2015. The inversion strength was determined using the difference between the temperature at the inversion height, which is the highest temperature in the profile, and the temperature at 100 m from the surface. Empirical equations for the changes of inversion height and strength were derived to express the development of temperature inversion on calm and clear nights. To estimate air temperature near the ground on a slope exposed to crops, the equation's parameters were modified using temperature distribution of the mountain slope obtained from the data loggers. Estimated hourly temperatures using the method were compared with observed temperatures at 19 weather sites located within three watersheds in the southern Jiri-mountain in 2015. The mean error (ME) and root mean square error (RMSE) of the hourly temperatures were $-0.69^{\circ}C$ and $1.61^{\circ}C$, respectively. Hourly temperatures were often underestimated from 2000 to 0100 LST the next day. When temperatures were estimated at 0600 LST using the existing model, ME and RMSE were $-0.86^{\circ}C$ and $1.72^{\circ}C$, respectively. The method proposed in this study resulted in a smaller error, e.g., ME of $-0.12^{\circ}C$ and RMSE of $1.34^{\circ}C$. The method could be improved further taking into account various weather conditions, which could reduce the estimation error.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.15-15
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• 2015

기존 기후변화 영향평가 불확실성 연구들은 거의 대부분 GCM의 불확실성이 가장 크다고 결론내리고 있으나, ES 불확실성과의 정량적 비교는 하지 못했으며, 기존 접근방법은 민감도 분석 수준에 머무르고 있다. 이에 본 연구에서는 기후변화 영향평가 각 단계별 불확실성을 포괄적으로 정량화하고 수행단계별 불확실성의 전파정도를 추정할 수 있는 새로운 approach를 제안하였다. 첫째, 전체 불확실성, 각 단계별 불확실성 증가 정도, 각 단계별 불확실성의 비율을 제시할 수 있는 새로운 approach를 제안하였다. 또한 불확실성을 정량적으로 추정할 수 있는 방법으로 maximum entropy(이하 ME)를 선정하였으며, 이를 본 연구에서 제시한 approach에서 적용성을 살펴보았다. 둘째, 본 연구에서는 기후변화 영향평가 불확실성 단계별 정량화를 위해 2개 배출시나리오, 4개 GCM 시나리오, 2개 상세화기법, 2개 수문모형을 사용하여 기본적 기후변화 영향평가 단계를 모두 수행하였다. 기존 approach에서는 GCMs의 변화율(89.34)이 가장 커 GCMs의 불확실성이 가장 큰 것으로 나타났으나 제시한 approach에서는 배출시나리오의 불확실성이 전체 대비 58.66 %로 기후변화 영향평가에서 가장 큰 불확실성 발생 원인으로 파악되었다. 모형 불확실성에서는 GCMs의 불확실성(전체 대비 33.57 %)이 가장 높게 나타났다. 또한 배출시나리오의 ME는 3.32, GCMs의 ME는 5.22, 상세화기법의 ME는 5.57, 수문모형의 ME는 5.66으로 단계적으로 불확실성이 증가하였다. 다음으로 유량과 강수를 이용하여 불확실성 정량화를 수행하였으며, 강수를 이용한 불확실성 정량화에서는 유량을 이용한 결과와 다르게 배출시나리오 다음으로 상세화기법의 불확실성이 큰 것으로 나타나 어떤 수문변수에 초점을 두느냐에 따라 불확실성 정량화저감 노력 대상이 달라질 수 있음을 제시하였다. 마지막으로 자연변동성에 의한 불확실성이 기후변화 전체 불확실성의 45.47 % 정도로 나타났으며, 이는 미래 기후변화에 의해 발생하는 불확실성이 과거 자연변동보다 2배 이상으로서, 기후변화에 의한 미래전망의 불확실성이 매우 크게 증가한다는 매우 중요한 결과를 제시하였다.

• Journal of Fisheries and Marine Sciences Education
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• v.18 no.1
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• pp.19-30
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• 2006

For fishery stock assessment and optimum sustainable yield of anchovy in Korea, surplus production(SP) models and a maximum entropy(ME) model are employed in this paper. For determining appropriate models, five traditional SP models-Schaefer model, Schnute model, Walters and Hilborn model, Fox model, and Clarke, Yoshimoto and Pooley (CYP) model- are tested for effort and catch data of anchovy that occupies 7% in the total fisheries landings of Korea. Only CYP model of five SP models fits statistically significant at the 10% level. Estimated intrinsic growth rates are similar in both CYP and ME models, while environmental carrying capacity of the ME model is quite greater than that of the CYP model. In addition, the estimated maximum sustainable yield(MSY), 213,287 tons in the ME model is slightly higher than that of CYP model (198,364 tons). Biomass for MSY in the ME model, however, is calculated 651,000 tons which is considerably greater than that of the CYP model (322,881 tons). It is meaningful in that two models are compared for noting some implications about any significant difference of stock assessment and their potential strength and weakness.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.495-502
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• 2013

Motion estimation (ME) that limits the performance of image quality and encoding speed has been developed to reduce temporal redundancy in video sequences and plays an important role in digital video compression. But it is computational demanding part of the encoder. Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. ME for Multi-view video requires high computational complexity. To reduce computational complexity and maintain the image quality, a fast motion estimation method is proposed in this paper. The proposed method uses a hierarchical search strategy. This strategy method consists of modified diamond search patten, multi gird diamond search pattern, and raster search pattern. These search patterns place search points symmetrically and evenly that can cover the overall search area not to fall into the local minimum or exploits the characteristics of the distribution of motion vectors to place the search points. Experiment results show that the speedup improvement of the proposed method over TZ search method (JMVC) can be up to 1.2 ~3 times faster while maintaining similar video quality and bit rates.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.87-90
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• 2003

This paper presents a variable block size motion estimation (ME) algorithm and hardware architectures dedicated to H.264/AVC. Proposed ME architecture can achieve real-time processing for 720$\times$480@30Hz with search range of [-64, +63] in the horizontal and [-32, +31] in the vertical direction at integer-pel accuracy and upto 7 reference frames at the operating frequency of 54MHz.

• Journal of Astronomy and Space Sciences
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• v.18 no.2
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• pp.109-118
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• 2001

KITSAT-1, launched in 1992, passes through Inner Van Allen Radiation Belt in which high energy Protons cause single event upsets(SBUs) in the main memory of KITSAT-1 OBC(On-Board Computer) 186. The present paper compares SEU data from the OBC186 with the AP-8 model of NASA/NSSDC using the Chi-Square method to estimate the SEU threshold energy. Shielding effect by the satellite body has been taken into account to model the proton fluxes at the position of OBC186, and SEUs recorded during the high solar activities have been removed to avoid the spurious result. The result shows that the SEU threshold energy of the main memory of KITSAT-1 OBC186 is estimated to be about $110{pm}10MeV$.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.85-91
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• 2013

This paper proposes the data reusable search scan methods for full search and fast search to implement low power Motion Estimation (ME). The proposed Optimized Sub-region Partitioning (OSP) method which divide search region into several sub-region can reduce the number of the required Reconfigurable Register Array (RRA) by half compared to the existing smart snake scan method for the same data reusability. In addition, the proposed Center Biased Search Scan method (CBSS) for various fast search algorithms can improve the data reusability. The performance comparisons show that the proposed search scan methods can reduce the average redundant data loading about 26.9% and 16.1% compared with the existing rater scan and snake scan methods, respectively. Due to the reduction of memory accesses, the proposed search scan methods are quite suitable for low power and high performance ME implementation.

• Journal of Korea Water Resources Association
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• v.51 no.5
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• pp.439-449
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• 2018

Many potential sources of bias are used in several steps of the radar-rainfall estimation process because the hydrological and meteorological radars measure the rainfall amount indirectly. Previous studies on radar-rainfall uncertainties were performed to reduce the uncertainty of each step by using bias correction methods in the quantitative radar-rainfall estimation process. However, these studies do not provide comprehensive uncertainty for the entire process and the relative ratios of uncertainty between each step. Consequently, in this study, a suitable approach is proposed that can quantify the uncertainties at each step of the quantitative radar-rainfall estimation process and show the uncertainty propagation through the entire process. First, it is proposed that, in the suitable approach, the new concept can present the initial and final uncertainties, variation of the uncertainty as well as the relative ratio of uncertainty at each step. Second, the Maximum Entropy Method (MEM) and Uncertainty Delta Method (UDM) were applied to quantify the uncertainty and analyze the uncertainty propagation for the entire process. Third, for the uncertainty quantification of radar-rainfall estimation at each step, two quality control algorithms, two radar-rainfall estimation relations, and two bias correction methods as post-processing through the radar-rainfall estimation process in 18 rainfall cases in 2012. For the proposed approach, in the MEM results, the final uncertainty (from post-processing bias correction method step: ME = 3.81) was smaller than the initial uncertainty (from quality control step: ME = 4.28) and, in the UDM results, the initial uncertainty (UDM = 5.33) was greater than the final uncertainty (UDM = 4.75). However uncertainty of the radar-rainfall estimation step was greater because of the use of an unsuitable relation. Furthermore, it was also determined in this study that selecting the appropriate method for each stage would gradually reduce the uncertainty at each step. Therefore, the results indicate that this new approach can significantly quantify uncertainty in the radar-rainfall estimation process and contribute to more accurate estimates of radar rainfall.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.481-494
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• 2011

Investigation of the $CO_2$ exchange between biosphere and atmosphere at regional, continental, and global scales can be directed to combining remote sensing with carbon cycle process to estimate vegetation productivity. NASA Earth Observing System (EOS) currently produces a regular global estimate of gross primary productivity (GPP) and annual net primary productivity (NPP) of the entire terrestrial earth surface at 1 km spatial resolution. While the MODIS GPP algorithm uses meteorological data provided by the NASA Data Assimilation Office (DAO), the sub-pixel heterogeneity or complex terrain are generally reflected due to coarse spatial resolutions of the DAO data (a resolution of $1{\circ}\;{\times}\;1.25{\circ}$). In this study, we estimated inputs retrieved from MODIS products of the AQUA and TERRA satellites with 5 km spatial resolution for the purpose of finer GPP and/or NPP determinations. The derivatives included temperature, VPD, and solar radiation. Seven AmeriFlux data located in the Corn Belt region were obtained to use for evaluation of the input data from MODIS. MODIS-derived air temperature values showed a good agreement with ground-based observations. The mean error (ME) and coefficient of correlation (R) ranged from $-0.9^{\circ}C$ to $+5.2^{\circ}C$ and from 0.83 to 0.98, respectively. VPD somewhat coarsely agreed with tower observations (ME = -183.8 Pa ~ +382.1 Pa; R = 0.51 ~ 0.92). While MODIS-derived shortwave radiation showed a good correlation with observations, it was slightly overestimated (ME = -0.4 MJ $day^{-1}$ ~ +7.9 MJ $day^{-1}$; R = 0.67 ~ 0.97). Our results indicate that the use of inputs derived MODIS atmosphere and land products can provide a useful tool for estimating crop GPP.