• 한국전산유체공학회:학술대회논문집
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• 2006.05a
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• pp.311-314
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• 2006

The supersonic flow around tandem cavities was investigated by three- dimensional numerical simulations using the Reynolds-Averaged Navier-Stokes(RANS) equation with the $\kappa-\omega$ thrbulence model. The flow around a cavity is characterized as unsteady flow because of the formation and dissipation of vortices due to the interaction between the freestream shear layer and cavity internal flow, the generation of shock and expansion waves, and the acoustic effect transmitted from wake flow to upstream. The upwind TVD scheme based on the flux vector split using van Leer's limiter was used as the numerical method. Numerical calculations were performed by the parallel processing with time discretizations carried out by the 4th-order Runge-Kutta method. The aspect ratio of cavities are 3 for the first cavity and 1 for the second cavity. The ratio of cavity interval to depth is 1. The ratio of cavity width to depth is 1 in the case of three dimensional flow. The Mach number and the Reynolds number were 1.5 and $4.5{\times}10^5$, respectively. The characteristics of the dominant frequency between two-dimensional and three-dimensional flows were compared, and the characteristics of the second cavity flow due to the fire cavity flow cavity flow was analyzed. Both two dimensional and three dimensional flow oscillations were in the 'shear layer mode', which is based on the feedback mechanism of Rossiter's formula. However, three dimensional flow was much less turbulent than two dimensional flow, depending on whether it could inflow and outflow laterally. The dominant frequencies of the two dimensional flow and three dimensional flows coincided with Rossiter's 2nd mode frequency. The another dominant frequency of the three dimensional flow corresponded to Rossiter's 1st mode frequency.

• Journal of KIISE:Software and Applications
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• v.41 no.8
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• pp.586-597
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• 2014

The next generation mobile computing technology is recently attracting attention that smartphone and wearable device imbedded with various sensors are being deployed in the world. Existing activity and posture recognition research can be divided into two different ways considering feature of one's movement. While activity recognition focuses on catching distinct pattern according to continuous movement, posture recognition focuses on sudden change of posture and body orientation. There is a lack of research constructing a system mixing two separate patterns which could be applied in real world. In this paper, we propose a method to use both smartphone and wearable device to recognize activity and posture in the same time. To use smartphone and wearable sensor data together, we designed a pre-processing method and constructed recognition model mixing signal vector magnitude and orientation pattern features of vertical and horizontal. We considered cycling, fast/slow walking and running activities, and postures such as standing, sitting, and laying down. We confirmed the performance and validity by experiment, and proved the feasibility in real world.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1067-1076
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• 2020

In this paper, an unsupervised saliency guided change detection method using UAV and aerial imagery is proposed. Regions that are more different from other areas are salient, which make them more distinct. The existence of the substantial difference between two images makes saliency proper for guiding the change detection process. Change Vector Analysis (CVA), which has the capability of extracting of overall magnitude and direction of change from multi-spectral and temporal remote sensing data, is used for generating an initial difference image. Combined with an unsupervised CVA and the saliency, Principal Component Analysis(PCA), which is possible to implemented as the guide for change detection method, is proposed for UAV and aerial images. By implementing the saliency generation on the difference map extracted via the CVA, potentially changed areas obtained, and by thresholding the saliency map, most of the interest areas correctly extracted. Finally, the PCA method is implemented to extract features, and K-means clustering is applied to detect changed and unchanged map on the extracted areas. This proposed method is applied to the image sets over the flooded and typhoon-damaged area and is resulted in 95 percent better than the PCA approach compared with manually extracted ground truth for all the data sets. Finally, we compared our approach with the PCA K-means method to show the effectiveness of the method.

• Applied Biological Chemistry
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• v.40 no.3
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• pp.173-177
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• 1997

Bacillus licheniformis 9945a releases a natural ${\gamma}-poly(glutamic\;acid)({\gamma}-PGA)$ into fermentation broth and shows a mucoid phenotype on the solid agar medium. Transformation of mucoid cells of Bacillus species has not been simple and straightforward. The transpositional activity of Tn10 in B. licheniformis also has not been own either. Thus, a spontaneous non-mucoid derivative of the B. licheniformis was obtained first. Shuttle vector pHV1248 containing mini-Tn10 was introduced into the non-mucoid derivative by the method of protoplast transformation. The resulting transformant was reverted to the wild mucoid phenotype, and then mutated randomly with the mini-transposon by heat induction. Auxotrophs requiring arginine, lysine, or tryptophan were isolated by replica plating method. Southern blotting and DNA-DNA hybridzation analysis showed that these auxotrophs were generated by mini-Tn10 insertion into the chromosomal DNA. This method of transformation and mutation using pHV1248 would be useful for the generation of diverse mutants of B. licheniformis 9945a.(Received January 24,1997; accepted March 10, 1997)

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5385-5391
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• 2013

As on-line purchases is activated, customers' demand increases for the realistic and accurate digital information of a product design. In this paper, we propose a practical method that can generate a realistic 3D model of a real product using a 3D geometry obtained by a 3D scanner and its photographic images. In order to register images to the 3D geometry, the camera focal length, the CCD scanning aspect ratio and the transformation matrix between the camera coordinate and the 3D object coordinate must be determined. To perform this 2D-3D registration with consideration of computational complexity, a three-step method is applied, which consists of camera calibration, determination of a temporary optimum translation vector (TOTV) and nonlinear optimization for three rotational angles. A case study for a metallic coated industrial part, of which the colour appearance is hardly obtained by a 3D colour scanner has performed to demonstrate the effectiveness of the proposed method.

• Journal of Plant Biotechnology
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• v.31 no.2
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• pp.151-161
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• 2004

Transgenic plants have been studied as delivery system for edible vaccine against various diseases. Edible plant vaccines have several potential advantages as follows: an inexpensive source of antigen, easy administration, reduced need for medical personnel, economical to mass produce and easy transport, heat-stable vaccine without refrigerator, generation of systemic and mucosal immunity and safe antigen without fetal animal-virus contaminants. The amount of recombinant antigens in transgenic plants ranged from 0.002 to 0.8％ in total soluble protein, depending on promoters for the expression of interested genes and plants to be used for transformation. Throughout the last decade, edible plant vaccine made notable progresses that protect from challenges against virus or bacteria. However edible plant vaccines have still problems that could be solved. First, the strong promoter or inducible promoter or strategy of protein targeting could be solved to improve the low expression of antigens in transgenic plants. Second, the transformation technique of target plant should be developed to be able to eat uncooked. Third, marker-free vector could be constructed to be more safety. In this review we describe advances of edible plant vaccines, focusing on the yields depending on plants/promoters employed and the results of animal/clinical trials, and consider further research for the development of a new plant-derived vaccine.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.575-581
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• 2012

In general, various modeling and estimation techniques have been proposed to extract the tropospheric and ionospheric delays from the GPS CORS. In this study, Kalman filter approach is adopted to estimate the tropospheric and ionospheric delays and the proper modeling for the state vector and the variance-covariance matrix for the process noises are performed. The coordinates of reference stations and the zenith wet delays are estimated with the assumption of random walk stochastic process. Also, the first-order Gauss-Markov stochastic process is applied to compute the ionospheric effects. For the evaluation of the proposed modeling technique, Kalman filter algorithm is implemented and the numerical test is performed with the CORS data. The results show that the atmospheric effects can be estimated successfully and, as a consequence, can be used for the generation of VRS data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5785-5804
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• 2019

The information of localization is a fundamental requirement in wireless sensor network (WSN). The method of distance vector-hop (DV-Hop), a range-free localization algorithm, can locate the ordinary nodes by utilizing the connectivity and multi-hop transmission. However, the error of the estimated distance between the beacon nodes and ordinary nodes is too large. In order to enhance the positioning precision of DV-Hop, fast triangle flip bat algorithm, which is based on curve strategy and rank transformation (FTBA-TCR) is proposed. The rank is introduced to directly select individuals in the population of each generation, which arranges all individuals according to their merits and a threshold is set to get the better solution. To test the algorithm performance, the CEC2013 test suite is used to check out the algorithm's performance. Meanwhile, there are four other algorithms are compared with the proposed algorithm. The results show that our algorithm is greater than other algorithms. And this algorithm is used to enhance the performance of DV-Hop algorithm. The results show that the proposed algorithm receives the lower average localization error and the best performance by comparing with the other algorithms.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.1
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• pp.63-72
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• 2007

Recently, as recognizing the risk about the infection of an infectious wastes, the problems about the management and treatment of the infectious wastes stand out socially. In this paper, as being possible monitoring whole processing from the origin of the infectious waste to the processing plant, using the RFID which is the kernel technology of the next generation, we tried to solve the second infection problem by inefficient treatment of the infectious wastes. Through the research suggesting in this paper, as storing and monitoring the procedural business articles and the problem about miss-writing and input error being found in management system like documentary writing by the existing manager and computation input by the web application, we can understand the management state, immediately. And the Bio information for the personal authentication is carried out through storing the feature vector calculation by the PCA algorithm, into the tag. It suggested more systematic and safer management plan than previous thing, as giving attention about the wastes to manager.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.203-209
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• 2016

In this paper, we introduce a fuzzy inference systems for nonlinear inference using fuzzy cluster. Typically, the generation of fuzzy rules for nonlinear inference causes the problem that the number of fuzzy rules increases exponentially if the input vectors increase. To handle this problem, the fuzzy rules of fuzzy model are designed by dividing the input vector space in the scatter form using fuzzy clustering algorithm which expresses fuzzy cluster. From this method, complex nonlinear process can be modeled. The premise part of the fuzzy rules is determined by means of FCM clustering algorithm with fuzzy clusters. The consequence part of the fuzzy rules have four kinds of polynomial functions and the coefficient parameters of each rule are estimated by using the standard least-squares method. And we use the data widely used in nonlinear process for the performance and the nonlinear characteristics of the nonlinear process. Experimental results show that the non-linear inference is possible.