• The Journal of the Acoustical Society of Korea
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• v.20 no.4
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• pp.35-41
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• 2001

This paper describes Linear Discriminant Analysis and common vector extraction for speech recognition. Voice signal contains psychological and physiological properties of the speaker as well as dialect differences, acoustical environment effects, and phase differences. For these reasons, the same word spelled out by different speakers can be very different heard. This property of speech signal make it very difficult to extract common properties in the same speech class (word or phoneme). Linear algebra method like BT (Karhunen-Loeve Transformation) is generally used for common properties extraction In the speech signals, but common vector extraction which is suggested by M. Bilginer et at. is used in this paper. The method of M. Bilginer et al. extracts the optimized common vector from the speech signals used for training. And it has 100％ recognition accuracy in the trained data which is used for common vector extraction. In spite of these characteristics, the method has some drawback-we cannot use numbers of speech signal for training and the discriminant information among common vectors is not defined. This paper suggests advanced method which can reduce error rate by maximizing the discriminant information among common vectors. And novel method to normalize the size of common vector also added. The result shows improved performance of algorithm and better recognition accuracy of 2％ than conventional method.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.411-418
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• 2009

Vector quantization algorithm based on fuzzy clustering has been widely used in the field of data compression since the use of fuzzy clustering analysis in the early stages of a vector quantization process can make this process less sensitive to its initialization. However, the process of fuzzy clustering is computationally very intensive because of its complex framework for the quantitative formulation of the uncertainty involved in the training vector space. To overcome the computational burden of the process, this paper introduces an array architecture for the implementation of fuzzy vector quantization (FVQ). The arrayarchitecture, which consists of 4,096 processing elements (PEs), provides a computationally efficient solution by employing an effective vector assignment strategy during the clustering process. Experimental results indicatethat the proposed parallel implementation providessignificantly greater performance and efficiency than appropriately scaled alternative array systems. In addition, the proposed parallel implementation provides 1000x greater performance and 100x higher energy efficiency than other implementations using today's ARMand TI DSP processors in the same 130nm technology. These results demonstrate that the proposed parallel implementation shows the potential for improved performance and energy efficiency.

• Parasites, Hosts and Diseases
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• v.59 no.6
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• pp.615-623
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• 2021

Human sparganosis is a food-borne parasitic disease caused by the plerocercoids of Spirometra species. Clinical diagnosis of sparganosis is crucial for effective treatment, thus it is important to identify sensitive and specific antigens of plerocercoids. The aim of the current study was to identify and characterize the immunogenic proteins of Spirometra erinaceieuropaei plerocercoids that were recognized by patient sera. Crude soluble extract of the plerocercoids were separated using 2-dimensional gel electrophoresis coupled with immunoblot and mass spectrometry analysis. Based on immunoblotting patterns and mass spectrometry results, 8 antigenic proteins were identified from the plerocercoid. Among the proteins, cysteine protease protein might be developed as an antigen for diagnosis of sparganosis.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.216-221
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• 2008

Shape design optimization for linear elasticity problem is performed using isogeometric analysis method. In many design optimization problems for real engineering models, initial raw data usually comes from CAD modeler. Then designer should convert this CAD data into finite element mesh data because conventional design optimization tools are generally based on finite element analysis. During this conversion there is some numerical error due to a geometry approximation, which causes accuracy problems in not only response analysis but also design sensitivity analysis. As a remedy of this phenomenon, the isogeometric analysis method is one of the promising approaches of shape design optimization. The main idea of isogeometric analysis is that the basis functions used in analysis is exactly same as ones which represent the geometry, and this geometrically exact model can be used shape sensitivity analysis and design optimization as well. In shape design sensitivity point of view, precise shape sensitivity is very essential for gradient-based optimization. In conventional finite element based optimization, higher order information such as normal vector and curvature term is inaccurate or even missing due to the use of linear interpolation functions. On the other hands, B-spline basis functions have sufficient continuity and their derivatives are smooth enough. Therefore normal vector and curvature terms can be exactly evaluated, which eventually yields precise optimal shapes. In this article, isogeometric analysis method is utilized for the shape design optimization. By virtue of B-spline basis function, an exact geometry can be handled without finite element meshes. Moreover, initial CAD data are used throughout the optimization process, including response analysis, shape sensitivity analysis, design parameterization and shape optimization, without subsequent communication with CAD description.

• Journal of the Korean Institute of Landscape Architecture
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• v.20 no.3
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• pp.1-10
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• 1992

Land suitability method has become a standard part of planning analysis at many scales. GIS computer packages have been developed for this purpose. But those are still expensive and hard to learn, and also have limits to extend the results to a landscape design. For the relatively simple tasks and CAD-related works, an application of CAD software for the suitability analysis is very useful and easy to handle. For the purpose, this study develops a technique for suitability analysis, using vector based microcomputer CAD softwares.

• Journal of Life Science
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• v.27 no.8
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• pp.857-863
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• 2017

The FBJ murine osteosarcoma viral oncogene homolog B (FosB) gene is located at chromosome 19, and encodes 43 Kda protein. Functionally, the FosB gene is important for differentiation, development, and pathogenesis. Furthermore, the FosB gene is suggested as possible biomarker for tracing disease prognosis. In this study, we constructed plasmid containing a FosB promoter region and evaluate its promoter activity. We analyzed the putative promoter region in FosB genomic DNA using bioinformatics program, and we found important regulatory elements in 1 Kb upstream from transcription start site (TSS). Therefore, we performed polymerase chain reaction (PCR) amplification on region from-1,555 upstream to +73 of the FosB genomic DNA, and PCR product was inserted into TA vector to create the $TA-1^{st}FosBp$ plasmid. We then prepared the primer sets, which contain a restriction enzyme site for Kpn1 and Nhe1, in order to reinsert into the TA vector to prepare $TA-2^{nd}FosBp$ plasmid. It was finally subcloned into pGL3-luc vector after enzyme cutting. To evaluate whether the cloned plasmid is useful in cell based experiment, we performed luciferase assay with pGL3-FosBp-luctransfection. FosB promoter activity was increased compared to empty vector, and this activity was significantly increased by treatment of doxorubicin and taxol. We obtained consistent data on regulation of FosB gene expression after anticancer drug treatment using Western blot analysis. The results suggest that promoter cloning of the human FosB gene is very useful for studying gene expression and analyzing biomarkers.

• Korean Journal of Microbiology
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• v.52 no.4
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• pp.398-405
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• 2016

The Schizosaccharomyces pombe structural gene encoding bacterioferritin comigratory protein (BCP) was previously cloned using the shuttle vector pRS316 to generate the BCP-overexpressing plasmid pBCP10. The present work aimed to evaluate the thermoresistant properties of BCP against high temperature stress using the plasmid pBCP10. When the S. pombe cells were grown to the early exponential phase and shifted from $30^{\circ}C$ to $37^{\circ}C$ or $42^{\circ}C$, the S. pombe cells harboring pBCP10 grew significantly more at both $37^{\circ}C$ and $42^{\circ}C$ than the vector control cells. After 6 h of the shifting to higher incubation temperatures, they contained the lower reactive oxygen species (ROS) and nitrite content, an index of nitric oxide (NO), than the vector control cells. After the temperature shifts, total glutathione (GSH) content and total superoxide dismutase (SOD) activities were much higher in the S. pombe cells harboring pBCP10 than in the corresponding vector control cells. Taken together, the S. pombe BCP plays a thermoresistant role which might be based upon its ability both to down-regulate ROS and NO levels and to up-regulate antioxidant components, such as total GSH and SOD, and subsequently to maintain thermal stability.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.51-58
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• 2018

Recently, various satellite sensors have been developed and it is becoming more convenient to acquire multitemporal satellite images. Therefore, various researches are being actively carried out in the field of utilizing change detection techniques such as disaster and land monitoring using multitemporal satellite images. In particular, researches related to the development of unsupervised change detection techniques capable of extracting rapidly change regions have been conducted. However, there is a disadvantage that false detection occurs due to a spectral difference such as a seasonal change. In order to overcome the disadvantages, this study aimed to reduce the false alarm detection due to seasonal effects using the direction vector generated by applying the $S^2CVA$ (Sequential Spectral Change Vector Analysis) technique, which is one of the unsupervised change detection methods. $S^2CVA$ technique was applied to RapidEye images of the same and different seasons. We analyzed whether the change direction vector of $S^2CVA$ can remove false positives due to seasonal effects. For the quantitative evaluation, the ROC (Receiver Operating Characteristic) curve and the AUC (Area Under Curve) value were calculated for the change detection results and it was confirmed that the change detection performance was improved compared with the change detection method using only the change magnitude vector.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.67-69
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• 2021

Weather radar images can be used in a variety of ways because of their high visibility in terms of visuals. In other words it has the advantage of being able to grasp the flow of weather phenomena using not only the raw data of the weather radar, but also the change characteristics between consecutive images. In particular image processing techniques are gradually expanding in the field of meteorological research, and in the case of image data having high resolution such as weather radar images it is expected to produce useful information through a new approach called image processing techniques. In this study the weather phenomena flow was calculated as a vector from the change of the weather radar image according to time interval with the optical flow method, one of the image processing techniques. The characteristics of the weather phenomena to be analyzed were derived through vector analysis resolution suitable for the scale of weather, vector interpolation in regions where no radar echo exists, and the removal of relative flow vectors to distinguish the flow of specific weather and the entire atmosphere. Through this study, it is expected that not only the use of raw data of weather radar, but also the widening of the application area of weather radar, such as the use of unique characteristics of image data, and the active use of image processing techniques in the field of meteorology in the future.

• The Journal of Fisheries Business Administration
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• v.37 no.1 s.70
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• pp.95-110
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• 2006

Japan's frozen shrimp future market is the only fisheries future commodity market in the world. This empirical study examines the lead and lag relationship between Japan frozen shrimp spot and future markets using the daily prices from August 1, 2002 to December 31, 2005. Frozen shrimp future contract is listed on Japan Kansai Commodities Exchange. Japan imports approximately 250,000 tons of frozen shrimp annually, of which just under 70,000 tons, nearly 30%, are black tiger shrimp. Approximately 90% of black tiger shrimp are caught in Indonesia, India, Thailand and Vietnam, and the two largest consumers of these shrimp are Japan and the U.S.A. Kansai Commodities Exchange adopts the India black tiger shrimp as standard future commodity. We use unit root test, Johansen cointegration test, Granger causality test, Vector autoregressive analysis and Impulse response analysis. However, considering the long - term relationships between the level variables of frozen shrimp spot and futures, we introduced Vector Error Correction Model. We find that the price change of frozen shrimp futures with next 1, 2, 3, 4, 5 month maturity have a strong predictive power to the change of frozen shrimp spot and the change of frozen shrimp spot also have a predictive power to the change of frozen shrimp with next 1, 2, 3 month maturity. But, the explanatory power of the frozen shrimp futures is relatively greater than that of frozen shrimp spot.