• 기술혁신연구
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• 제14권3호
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• pp.93-116
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• 2006

This study provides a quantitative forecasting method to identify promising fusion technology and it also applies the method based on patent analysis to IT. This study defines fusion technology, promising technology, fusion index, promising index and promising fusion technology. From the analysis, this study found that the next generation computer network is the most promising in IT area. This result is consistent with the forecasts made by the interviews and discussion of experts.

• 대한원격탐사학회지
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• 제26권3호
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• pp.305-316
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• 2010

The MODerate Resolution Imaging Spectroradiometer (MODIS) sensor has 36 bands at 250m, 500m, 1km spatial resolution. However, 500m or 1km MODIS data exhibits a few limitations when low resolution data is applied at small areas that possess complex land cover types. In this study, we produce seven 250m spectral bands by fusing two MODIS 250m bands into five 500m bands. In order to recommend the best fusion method by which one acquires MODIS data, we compare seven fusion methods including the Brovey transform, principle components algorithm (PCA) fusion method, the Gram-Schmidt fusion method, the least mean and variance matching method, the least square fusion method, the discrete wavelet fusion method, and the wavelet-PCA fusion method. Results of the above fusion methods are compared using various evaluation indicators such as correlation, relative difference of mean, relative variation, deviation index, peak signal-to-noise ratio index and universal image quality index, as well as visual interpretation method. Among various fusion methods, the local mean and variance matching method provides the best fusion result for the visual interpretation and the evaluation indicators. The fusion algorithm of 250m MODIS data may be used to effectively improve the accuracy of various MODIS land products.

• 한국측량학회지
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• 제33권6호
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• pp.547-555
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• 2015

The vegetation index is a crucial parameter in many biophysical studies of vegetation, and is also a valuable content in ecological processes researching. The OVIs (Optical Vegetation Index) that of using multispectral and hyperspectral data have been widely investigated in the literature, while the RVI (Radar Vegetation Index) that of considering volume scattering measurement has been paid relatively little attention. Also, there was only some efforts have been put to fuse the OVI with the RVI as an integrated vegetation index. To address this issue, this paper presents a novel FVI (Fusion Vegetation Index) that uses multispectral and full-PolSAR (Polarimetric Synthetic Aperture Radar) data. By fusing a NDVI (Normalized Difference Vegetation Index) of RapidEye and an RVI of C-band Radarsat-2, we demonstrated that the proposed FVI has higher separability in different vegetation types than only with OVI and RVI. Also, the experimental results show that the proposed index not only has information on the vegetation greenness of the NDVI, but also has information on the canopy structure of the RVI. Based on this preliminary result, since the vegetation monitoring is more detailed, it could be possible in various application fields; this synergistic FVI will be further developed in the future.

• Journal of Periodontal and Implant Science
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• 제36권2호
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• pp.503-513
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• 2006

The purpose of this study was to determine the distribution, prevalence and relationship of the localized periodontitis of root fusion in maxillary and mandibular molars. One hundred patients who had eight maxillary and mandibular molars(third molars excluded) were consecutively selected for the study subjects. The subjects provided a total of 800 molars, i. e., 400 maxillary and 400 mandibular molars. A decision about root fusion was made on the radiographic examination. Probing depth, plaque index, gingival index and mobility were measured. The results were as follows. 1. 15.9% of the molars had a fused root. 22% of the maxillary molars and 9.8% of the mandibular molars had a fused molars. 2. In maxillary molars, the results of probing depth, plaque index, gingival index, mobility are more higher in test group than in control group, and there was a significantly difference except plaque index of maxillary first molars group(p<0.01). 3. In mandibular molars, the results of probing depth, plaque index, gingival index, mobility are more higher in test group than in control group, and there was a significantly difference(p<0.01). As a result of this study, it can be concluded that, in management of molars with a root fusion, we should detect the molars through the precise radiographic examination, early periodontal treatment and systematic treatment plan should be chosen. And postoperative continuing supportive periodontal therapy is needed.

• Journal of Korean Neurosurgical Society
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• 제56권4호
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• pp.315-322
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• 2014

Objective : Posterior accessed lumbar interbody fusion (PALIF) has a clear objective to restore disc height and spinal alignment but surgeons may occasionally face the converse situation and lose lumbar lordosis. We analyzed retrospective data for factors contributing to a postoperative flat back. Methods : A total of 105 patients who underwent PALIF for spondylolisthesis and stenosis were enrolled. The patients were divided according to surgical type [posterior lumbar inter body fusion (PLIF) vs. unilateral transforaminal lumbar interbody fusion (TLIF)], number of levels (single vs. multiple), and diagnosis (spondylolisthesis vs. stenosis). We measured perioperative index level lordosis, lumbar lordosis, pelvic tilt, sacral slope, pelvic incidence, and disc height in standing lateral radiographs. The change and variance in each parameter and comparative group were analyzed with the paired and Student t-test (p<0.05), correlation coefficient, and regression analysis. Results : A significant perioperative reduction was observed in index-level lordosis following TLIF at the single level and in patients with spondylolisthesis (p=0.002, p=0.005). Pelvic tilt and sacral slope were significantly restored following PLIF multilevel surgery (p=0.009, p=0.003). Sacral slope variance was highly sensitive to perioperative variance of index level lordosis in high sacral sloped pelvis. Perioperative variance of index level lordosis was positively correlated with disc height variance ($R^2=0.286$, p=0.0005). Conclusion : Unilateral TLIF has the potential to cause postoperative flat back. PLIF is more reliable than unilateral TLIF to restore spinopelvic parameters following multilevel surgery and spondylolisthesis. A high sacral sloped pelvis is more vulnerable to PALIF in terms of a postoperative flat back.

• 한국동물학회지
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• 제29권4호
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• pp.235-244
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• 1986

근세포가 분화하는 과정에 있어서 신경전달물질의 역할을 알아보기 위해서 배양중인 근원세포에 dopamine을 처리하고, 융합지수, creatine kinase 합성률 및 dopamine에 대한 차등감수성을 조사하였다. 배양후 34시간된 근원세포에 $3 \\times 10^{-5} M$의 dopamine을 처리하면 그후 전 시기에 걸쳐 융합지수가 크게 감소되며, 이와 더불어 creatine kinase의 합성률도 감소하는 사실로 미우러 이들 사이에 상관관계가 있음을 알 수 있었다. 또한 dopamine의 융합억제효과는 세포주기에 따라 감수성이 달라지는 차등감수성을 관찰할 수 있었는데, 이는 근세포막에 위치할 것으로 생각되는 dopamine receptor의 배치가 세포주기에 따라 달라지는 데 연유되는 것으로 추정되었다.

• 지능정보연구
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• 제18권3호
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• pp.79-96
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• 2012

기술의 발전과 융합이 빠르게 이루어지고 있는 오늘날 유망기술을 어떻게 파악하여, 다양한 후보군들 중에서 최적의 R&D 대상을 어떻게 선정할 것인가에 대한 문제는 주요한 경영의사결정문제 중 하나로 부상하고 있다. 본 연구에서는 이러한 R&D 기술 선정 의사결정을 지원할 수 있는 새로운 지능형 의사결정지원시스템을 제안한다. 본 연구의 의사결정지원시스템은 크게 3가지 모듈로 구성되는데, 우선 첫 번째 모듈인 '기술가치 평가' 모듈에서는 기업이 관심을 갖고 있는 분야의 특허들을 분석하여 유망기술 파악에 요구되는 다양한 차원의 기술가치 평가지수 값들을 산출하는 작업이 이루어진다. 이를 통해, 현재 시점에서의 각 기술의 가치가 다양한 차원에서 평가가 이루어지고 나면, 두 번째 모듈인 '미래기술가치 예측' 모듈에서 이들의 시간 흐름에 따른 변화를 학습한 인공지능 모형을 토대로 각 후보기술들이 미래 시점에 어떤 가치지수값을 갖게 될 것인지 예측값을 산출하게 된다. 마지막 세 번째 모듈인 '최적 R&D 대상기술 선정 지원' 모듈에서는 앞서 두 번째 모듈에서 산출된 각 차원별 예상 가치지수값들을 적절히 가중합하여 기술의 종합적인 미래가치 예측값을 산출하여 의사결정자에게 제공하는 기능을 수행한다. 이를 통해 의사결정자가 자사에 적합한 최적의 R&D 대상기술을 선정할 수 있도록 하였다. 본 연구에서는 제안된 시스템의 적용 가능성을 검증하기 위해, 10년치 특허데이터에 인공신경망 기법을 적용하여 실제 기술가치 예측모형을 구축해 보고, 그 효과를 살펴본다.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.927-935
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• 2007

Currently, Gyeongnam province is executing the social index survey every year to the provincials. But, this survey has the limit of the analysis as execution of the different survey per 3 year cycles. The solution of this problem is data fusion. Data fusion is the process of combining multiple data in order to provide information of tactical value to the user. But, data fusion doesn#t mean the ultimate result. Therefore, efficient analysis for the data fusion is also important. In this study, we present data fusion method of statistical survey data. Also, we suggest application methodology of association rule mining by clustering through data fusion of statistical survey data.

• 대한원격탐사학회지
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• 제36권5_1호
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• pp.807-821
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• 2020

이 연구에서는 작물 모니터링을 위한 시계열 고해상도 영상 구축을 위해 기존 중저해상도 위성영상의 융합을 위해 개발된 대표적인 시공간 융합 모델의 적용성을 평가하였다. 특히 시공간 융합 모델의 원리를 고려하여 입력 영상 pair의 특성 차이에 따른 모델의 예측 성능을 비교하였다. 농경지에서 획득된 시계열 Sentinel-2 영상과 RapidEye 영상의 시공간 융합 실험을 통해 시공간 융합 모델의 예측 성능을 평가하였다. 시공간 융합 모델로는 Spatial and Temporal Adaptive Reflectance Fusion Model(STARFM), SParse-representation-based SpatioTemporal reflectance Fusion Model(SPSTFM)과 Flexible Spatiotemporal DAta Fusion(FSDAF) 모델을 적용하였다. 실험 결과, 세 시공간 융합 모델은 예측 오차와 공간 유사도 측면에서 서로 다른 예측 결과를 생성하였다. 그러나 모델 종류와 관계없이, 예측 시기와 영상 pair가 획득된 시기 사이의 시간 차이보다는 예측 시기의 저해상도 영상과 영상 pair의 상관성이 예측 능력 향상에 더 중요한 것으로 나타났다. 또한 작물 모니터링을 위해서는 오차 전파 문제를 완화할 수 있는 식생지수를 시공간 융합의 입력 자료로 사용해야 함을 확인하였다. 이러한 실험 결과는 작물 모니터링을 위한 시공간 융합에서 최적의 영상 pair 및 입력 자료 유형의 선택과 개선된 모델 개발의 기초정보로 활용될 수 있을 것으로 기대된다.

• International Journal of Control, Automation, and Systems
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• 제4권2호
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• pp.165-171
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• 2006

This paper proposes a data fusion algorithm of nonlinear multi sensor dynamic systems of synchronous sampling based on filtering step by step. Firstly, the object state variable at the next time index can be predicted by the previous global information with the systems, then the predicted estimation can be updated in turn by use of the extended Kalman filter when all of the observations aiming at the target state variable arrive. Finally a fusion estimation of the object state variable is obtained based on the system global information. Synchronously, we formulate the new algorithm and compare its performances with those of the traditional nonlinear centralized and distributed data fusion algorithms by the indexes that include the computational complexity, data communicational burden, time delay and estimation accuracy, etc.. These compared results indicate that the performance from the new algorithm is superior to the performances from the two traditional nonlinear data fusion algorithms.