• Journal of Fisheries and Marine Sciences Education
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• v.26 no.3
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• pp.485-491
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• 2014

The study of Web MGIS(Marine Geographic Information System) based on the SVG(Scalable Vector Graphics) is mainly performed on effective methodologies which transform real world data to computing world data. Web GUI system has its own target on reliable data service by acquisition of geometric information using HYCOM(HYbrid Coordinate Ocean Model), accurate measurement and graphical visualization. This type of raw data visualization can be built without software tools, yet is incredibly useful for interpreting and communicating data. Even simple visualizations can aid in the interpretation of complex hydrodynamic relationships that are frequently encountered in the marine environment. The Web MGIS provides an easy way for hydrodynamic geoscientists to construct complex visualizations that can be viewed with free software. This study proposes a Web GUI MGIS using FVCOM(Finite Volume Coastal Ocean Model). Finally, we design a Marine Web GUI system of Kosrae Coastal Waters integrating above data models. It must adds more ecological information and the various service item for approach more easily in order to user.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1540-1561
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• 2024

This research proposes a novel approach for Tamil Handwritten Character Recognition (THCR) that combines feature selection and ensemble learning techniques. The Tamil script is complex and highly variable, requiring a robust and accurate recognition system. Feature selection is used to reduce dimensionality while preserving discriminative features, improving classification performance and reducing computational complexity. Several feature selection methods are compared, and individual classifiers (support vector machines, neural networks, and decision trees) are evaluated through extensive experiments. Ensemble learning techniques such as bagging, and boosting are employed to leverage the strengths of multiple classifiers and enhance recognition accuracy. The proposed approach is evaluated on the HP Labs Dataset, achieving an impressive 95.56% accuracy using an ensemble learning framework based on support vector machines. The dataset consists of 82,928 samples with 247 distinct classes, contributed by 500 participants from Tamil Nadu. It includes 40,000 characters with 500 user variations. The results surpass or rival existing methods, demonstrating the effectiveness of the approach. The research also offers insights for developing advanced recognition systems for other complex scripts. Future investigations could explore the integration of deep learning techniques and the extension of the proposed approach to other Indic scripts and languages, advancing the field of handwritten character recognition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.444-447
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• 2018

Baculovirus expression systems have many known advantages including fast and cost-effective methods to generate large amounts of recombinant proteins in comparison to bacterial expression systems, particularly those requiring complex post-translational modifications. Especially, recombinant baculoviruses can transfer their vectors and express their recombinant proteins in a wide range of mammalian cell types. In this study, baculoviral vectors which were reconstructed from pcDNA3.1 vector, were recombined with cytomegalovirus (CMV) promoter,uroplakin II promoter, polyhedron promoter, vesicular stomatitis virus G (VSVG), enhanced green fluorescent protein (EGFP), and protein transduction domain (PTD). These recombinant vectors were infected with various cells and cell lines. The baculovirus vector thus developed was analyzed by comparing the metastasis and expression of the recombinant genes with conventional vectors. These results suggest that the baculovirus vector has higher efficiency in metastasis and expression than the control vector.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.165-170
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• 2003

This paper presents an integrated approach to unconstrained face recognition in arbitrary scenes. The front end of the system comprises of a scale and pose tolerant face detector. Scale normalization is achieved through novel combination of a skin color segmentation and log-polar mapping procedure. Principal component analysis is used with the multi-view approach proposed in[10] to handle the pose variations. For a given color input image, the detector encloses a face in a complex scene within a circular boundary and indicates the position of the nose. Next, for recognition, a radial grid mapping centered on the nose yields a feature vector within the circular boundary. As the width of the color segmented region provides an estimated size for the face, the extracted feature vector is scale normalized by the estimated size. The feature vector is input to a trained neural network classifier for face identification. The system was evaluated using a database of 20 person's faces with varying scale and pose obtained on different complex backgrounds. The performance of the face recognizer was also quite good except for sensitivity to small scale face images. The integrated system achieved average recognition rates of 87% to 92%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1661-1669
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• 2004

A rapid development of Internet is changing users' desire from existing static contents to dynamic and diverse ones. Thus the SVG provides more affluent and sophisticated graphic expressions than an existing method based on bitmap, it can faithfully display vector graphics without scarifying any functions or the problem of device compatibility. In addition, it allows indexing, searching, storing, and sharing by the description of the logical structure of graphics. Since there are, however, very few people who know the complex SVG syntax and make use it, an editing system, which enables users to utilize the SVG graphics easily, has been in need. Therefore, in this thesis, we do research on basic technology on the SVG, design and make an editing system for SVG documents. The system, therefore, provides uses with a user-friendly editing interface and enables them to write graphic objects easily, and generates complex SVG documents automatically.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1312-1317
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• 2003

This paper presents an integrated approach to unconstrained face recognition in arbitrary scenes. The front end of the system comprises of a scale and pose tolerant face detector. Scale normalization is achieved through novel combination of a skin color segmentation and log-polar mapping procedure. Principal component analysis is used with the multi-view approach proposed in[10] to handle the pose variations. For a given color input image, the detector encloses a face in a complex scene within a circular boundary and indicates the position of the nose. Next, for recognition, a radial grid mapping centered on the nose yields a feature vector within the circular boundary. As the width of the color segmented region provides an estimated size for the face, the extracted feature vector is scale normalized by the estimated size. The feature vector is input to a trained neural network classifier for face identification. The system was evaluated using a database of 20 person's faces with varying scale and pose obtained on different complex backgrounds. The performance of the face recognizer was also quite good except for sensitivity to small scale face images. The integrated system achieved average recognition rates of 87% to 92%.

• Kyungpook Mathematical Journal
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• v.56 no.4
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• pp.1207-1235
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• 2016

Let M be a real hypersurface with constant mean curvature in a complex space form $M_n(c),c{\neq}0$. In this paper, we prove that if the structure Jacobi operator $R_{\xi}= R({\cdot},{\xi}){\xi}$ with respect to the structure vector field ${\xi}$ is ${\phi}{\nabla}_{\xi}{\xi}$-parallel and $R_{\xi}$ commute with the structure tensor field ${\phi}$, then M is a homogeneous real hypersurface of Type A.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.97-102
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• 2015

In this paper, an extension of the standard common spatial pattern (CSP) algorithm using the strong uncorrelated transform (SUT) is used in order to extract the features for an accurate classification of the left- and right-hand motor imagery tasks. The algorithm is designed to analyze the complex data, which can preserve the additional information of the relationship between the two electroencephalogram (EEG) data from distant channels. This is based on the fact that distant regions of the brain are spatially distributed spatially and related, as in a network. The real-world left- and right-hand motor imagery EEG data was acquired through the Physionet database and the support vector machine (SVM) was used as a classifier to test the proposed method. The results showed that extracting the features of the pair-wise channel data using the strong uncorrelated transform complex common spatial pattern (SUTCCSP) provides a higher classification rate compared to the standard CSP algorithm.

• Kyungpook Mathematical Journal
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• v.56 no.2
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• pp.541-575
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• 2016

Let M be a real hypersurface of a complex space form with almost contact metric structure (${\phi}$, ${\xi}$, ${\eta}$, g). In this paper, we prove that if the structure Jacobi operator $R_{\xi}= R({\cdot},{\xi}){\xi}$ is ${\phi}{\nabla}_{\xi}{\xi}$-parallel and $R_{\xi}$ commute with the structure tensor ${\phi}$, then M is a homogeneous real hypersurface of Type A provided that $TrR_{\xi}$ is constant.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.10a
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• pp.190-195
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• 1997

Recently it is increased by degrees to construct complex or large lattice type structures such as bridges, towers, cranes, and structures that can be used for space technology. In general, in order to analyze, these structures we have used the finite element method(FEM). In this method, however, it is necessary to use a large amount of computer memory and computation time because the FEM requires many degrees of freedom for solving dynamic problems for these structures. For overcoming this problem, the authors have developed the transfer dynamic stiffness coefficient method(TDSCM). This method is based on the concepts of the transfer and the synthesis of the dynamic stiffness coefficient which is related to force and displacement vector at each node. In this paper, the authors formulate vibration analysis algorithm for a complex and large lattice type structure using the transfer of the dynamic stiffness coefficient. And the validity of TDSCM demonstrated through numerical computational and experimental results.