• Bulletin of the Korean Chemical Society
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• v.29 no.9
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• pp.1685-1688
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• 2008

• Bulletin of the Korean Chemical Society
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• v.29 no.8
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• pp.1449-1450
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• 2008

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1201-1208
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• 2006

Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. Currently, Gyeongnam province is executing the social survey every year with the provincials. But, they have the limit of the analysis as execute the different survey to 3 year cycles. In this paper, we study to data fusion of environmental survey data using sas macro. We can use data fusion outputs in environmental preservation and environmental improvement.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.279-287
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• 2007

Data fusion is the process of combining multiple data in order to produce information of tactical value to the user. Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. In this paper, we develop was macro program for statistical matching which is one of five branch types for data fusion. And then we apply data fusion and association rule techniques to environmental data.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.5
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• pp.676-686
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• 2012

This paper presents a sensor bias estimation method with serial fusion for asynchronous multisensory systems. Serial fusion processes the sensor measurements in a first-come-first-serve basis and it plays an essential role in asynchronous fusion in practice. The proposed algorithm generates the bias measurements using fusion estimates and sensor measurements for bias estimation, and compensates the sensor biases in fusion tracks. A simulation study indicates that the proposed algorithm has the superior performance in bias estimation and accurate tracking.

• Bulletin of the Korean Chemical Society
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• v.31 no.2
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• pp.503-506
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• 2010

• Korean Journal of Microbiology
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• v.31 no.3
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• pp.218-223
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• 1993

Conditions for the release and regeneration of protoplasts form Rhizopus oryzae and intergeneric protoplast fusion between Rhizopus oryzae and Aspergillus oryzae were studied. High yields of protoplast fusion between Rhizopus oryzae and Aspergillus oxyzae were studied. High yield of protoplasts from young germilings of R. oryzae were obtained by using lytic enzymes containing chitosanase (3 mg/ml), chitinase (3 mg/ml) and Novozym 234 (5 mg/ml). 0.5M glucose was used as the osmotic stabilizer and optimum pH of buffer was determined to be pH 7.5-8.0. Under these conditions, protoplasts were formed after about 3-4 hrs incubation. Approximately, 1.0%-4.9% of these protoplasts were formed after about 3-4 hrs incubation. Approximately, 1.0%-4.9% of these protoplasts regenerated on solid medium with a soft agar overlay. We have also carried out protoplasts fusion between R. oryzae and A. oryzae and have succeeded in obtaining three types of intergeneric fusants. In these experiments, 35% PEG-4000 and 10 mM CaCl$_{2}$ were used as fsogenic agents, and auxotrophic properties were used as a genetic marker to select fusants. Complementation frequency be protoplasts fusion of A. oxyzae and R. oryzae was 4.4% * 10$^{-5}$ . The fusant strains of the first type were prototrophs showing an Aspergillus type morphology with dark-yellow sporulation, those of the second type were also Apergillus type morphology but showed no sporulation. And the strains of the third type stopped growing when fusion products grown on regeneration minimal medium were transferred to fresh minimal medium. The formation of fusion products was observed by fluorescent vital stains for complementary labelling of protoplats from R. oryzae and A. oryzae. Rhodamine 6G and fluorescein diacetate wer useful complementary vital stains of Rhizopus and Aspergillus protoplasts for visualization of requency and type (dicell, multicell) of fusion.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.695-708
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• 2011

Image fusion is the process of combining multiple images of the same scene into a single fused image with application to many fields, such as remote sensing, computer vision, robotics, medical imaging and military affairs. The widely used image fusion rules that use wavelet transform have been based on a simple comparison with the activity measures of local windows such as mean and standard deviation. In this case, information features from the original images are excluded in the fusion image and distorted fusion images are obtained for noisy images. In this paper, we propose the use of a nonparametric squared ranks test on the quality of variance for two samples in order to overcome the influence of the noise and guarantee the homogeneity of the fused image. We evaluate the method both quantitatively and qualitatively for image fusion as well as compare it to some existing fusion methods. Experimental results indicate that the proposed method is effective and provides satisfactory fusion results.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.421-437
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• 2015

This paper aims to present a supervised classification algorithm based on data fusion for the segmentation of the textured images. The feature extraction method we used is based on discrete wavelet transform (DWT). In the segmentation stage, the estimated feature vector of each pixel is sent to the support vector machine (SVM) classifier for initial labeling. To obtain a more accurate segmentation result, two strategies based on information fusion were used. We first integrated decision-level fusion strategies by combining decisions made by the SVM classifier within a sliding window. In the second strategy, the fuzzy set theory and rules based on probability theory were used to combine the scores obtained by SVM over a sliding window. Finally, the performance of the proposed segmentation algorithm was demonstrated on a variety of synthetic and real images and showed that the proposed data fusion method improved the classification accuracy compared to applying a SVM classifier. The results revealed that the overall accuracies of SVM classification of textured images is 88%, while our fusion methodology obtained an accuracy of up to 96%, depending on the size of the data base.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.3
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• pp.34-42
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• 2007

It is very important for the combat system to process extensive data exactly at short time for the better situation awareness compared with the threats in these days. This paper suggests to add radial velocity on the decision factor of sensor data fusion in the existing algorithm for the accuracy enhancement of the sensor data fusion in the combat system.