• 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.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.577-582
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• 2007

A variational formulation for plane elasticity problems is derived based on an isogeometric approach. The isogeometric analysis is an emerging methodology such that the basis functions in analysis domain arc generated directly from NURBS (Non-Uniform Rational B-Splines) geometry. Thus. the solution space can be represented in terms of the same functions to represent the geometry. The coefficients of basis functions or the control variables play the role of degrees-of-freedom. Furthermore, due to h-. p-, and k-refinement schemes, the high order geometric features can be described exactly and easily without tedious re-meshing process. The isogeometric sensitivity analysis method enables us to analyze arbitrarily shaped structures without re-meshing. Also, it provides a precise construction method of finite element model to exactly represent geometry using B-spline base functions in CAD geometric modeling. To obtain precise shape sensitivity, the normal and curvature of boundary should be taken into account in the shape sensitivity expressions. However, in conventional finite element methods, the normal information is inaccurate and the curvature is generally missing due to the use of linear interpolation functions. A continuum-based adjoint sensitivity analysis method using the isogeometric approach is derived for the plane elasticity problems. The conventional shape optimization using the finite element method has some difficulties in the parameterization of boundary. In isogeometric analysis, however, the geometric properties arc already embedded in the B-spline shape functions and control points. The perturbation of control points in isogeometric analysis automatically results in shape changes. Using the conventional finite clement method, the inter-element continuity of the design space is not guaranteed so that the normal vector and curvature arc not accurate enough. On tile other hand, in isogeometric analysis, these values arc continuous over the whole design space so that accurate shape sensitivity can be obtained. Through numerical examples, the developed isogeometric sensitivity analysis method is verified to show excellent agreement with finite difference sensitivity.

• Journal of Microbiology and Biotechnology
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• v.26 no.2
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• pp.356-363
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• 2016

Human papillomavirus (HPV), a non-enveloped, double-stranded DNA tumor virus, is a primary etiological agent of cervical cancer development. As a potential tool for prophylactic vaccination, the development of virus-like particles (VLPs) containing the HPV16 L1 capsid protein is highly desired. In this study, we developed a high-level expression system of the HPV16 L1 in Escherichia coli for the purpose of VLP development. The native gene of HPV16 L1 has many rare codons that cause the early termination of translation and result in the production of truncated forms. First, we optimized the codon of the HPV16 L1 gene to the preferable codons of E. coli, and we succeeded in producing the full-size HPV16 L1 protein without early termination. Next, to find the best host for the production of HPV16 L1, we examined a total of eight E. coli strains, and E. coli BL21(DE3) with the highest yield among the strains was selected. With the selected host-vector system, we did a fed-batch cultivation in a lab-scale bioreactor. Two different feeding solutions (complex and defined feeding solutions) were examined and, when the complex feeding solution was used, a 6-fold higher production yield (4.6 g/l) was obtained compared with that with the defined feeding solution.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.223-230
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• 2001

Since self-organizing map (SOM) preserves the topology of ordering in input spaces and trains itself by unsupervised algorithm, it is Llsed in many areas. However, SOM has a shortcoming: structure cannot be easily detcrmined without many trials-and-errors. Structure-adaptive self-orgnizing map (SASOM) which can adapt its structure as well as its weights overcome the shortcoming of self-organizing map: SASOM makes use of structure adaptation capability to place the nodes of prototype vectors into the pattern space accurately so as to make the decision boundmies as close to the class boundaries as possible. In this scheme, the initialization of weights of newly adapted nodes is important. This paper proposes a method which optimizes SASOM with genetic algorithm (GA) to determines the weight vector of newly split node. The leanling algorithm is a hybrid of unsupervised learning method and supervised learning method using LVQ algorithm. This proposed method not only shows higher performance than SASOM in terms of recognition rate and variation, but also preserves the topological order of input patterns well. Experiments with 2D pattern space data and handwritten digit database show that the proposed method is promising.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.3
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• pp.419-429
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• 1999

Identifying the boundary of the effective receiving power of waves is one of the most important factors for cell optimization. In this paper, we introduce a propagation loss prediction model which yields highly accurate prediction in very complex areas as Seoul where a mixture of many large buildings, small buildings, broad streets, narrow alleys, rivers and forests co-exist in an irregular arrangement. This prediction model is based on neural networks trained on field measurement data collected in the past. Using these data along with 3-D digital elevation maps and vector data for building structures, we extract the parameter values which mainly affect the amount of propagation loss. These parameter values are then used as the inputs to the neural network. Trained neural network becomes the approximated function of the propagation loss model which generalizes very well and can predict accurately in the regions not included in training the neural network. The experimental results show a superior performance over the other models in the cells operating in the city of Seoul.

• Journal of Korea Game Society
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• v.18 no.1
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• pp.125-134
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• 2018

This paper presents a practical method to efficiently extract the rotational part of a $3{\times}3$ matrix that changes continuously in time. This is the key technique in the corotational FEM and the shape matching deformation popular in physics-based dynamic deformation. Recently, in contrast to the traditional polar decomposition methods independent of time, an iterative method was proposed that formulates the rotation extraction in a physics-based way and exploits an incremental representation of rotation. We develop an optimization method that reduces the number of iterations under the assumption that the maximum magnitude of the incremental rotation vector is limited within ${\pi}/2$. Realistic simulation of dynamic deformation employs a sufficiently small time step, and thus this assumption is not problematic in practice. We demonstrate the efficiency and practicality of our method in various experiments.

• Mycobiology
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• v.49 no.5
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• pp.491-497
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• 2021

An endolichenic fungus Xylaria grammica EL000614 produces grammicin, a potent nematicidal pyrone derivative that can serve as a new control option for root-knot nematodes. We optimized an Agrobacterium tumefaciens-mediated transformation (ATMT) protocol for X. grammica to support genetic studies. Transformants were successfully generated after co-cultivation of homogenized young mycelia of X. grammica with A. tumefaciens strain AGL-1 carrying a binary vector that contains the bacterial hygromycin B phosphotransferase (hph) gene and the eGFP gene in T-DNA. The resulting transformants were mitotically stable, and PCR analysis showed the integratin of both genes in the genome of transformants. Expression of eGFP was confirmed via fluorescence microscopy. Southern analysis showed that 131 (78.9%) out of 166 transformants contained a single T-DNA insertion. Crucial factors for producing predominantly single T-DNA transformants include 48 h of co-cultivation, pretreatment of A. tumefaciens cells with acetosyringone before co-cultivation, and using freshly prepared mycelia. The established ATMT protocol offers an efficient tool for random insertional mutagenesis and gene transfer in studying the biology and ecology of X. grammica.

• Journal of Veterinary Science
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• v.22 no.6
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• pp.76.1-76.15
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• 2021

Background: The development of a vaccine for Jembrana disease is needed to prevent losses in Indonesia's Bali cattle industry. A DNA vaccine model (pEGFP-C1-tat) that requires a functional delivery system will be developed. Polylactic-co-glycolic acid (PLGA) may have potential as a delivery system for the vaccine model. Objectives: This study aims to evaluate the in vitro potential of PLGA as a delivery system for pEGFP-C1-tat. Methods: Consensus and codon optimization for the tat gene was completed using a bioinformatic method, and the product was inserted into a pEGFP-C1 vector. Cloning of the pEGFP-C1-tat was successfully performed, and polymerase chain reaction (PCR) and restriction analysis confirmed DNA isolation. PLGA-pEGFP-C1-tat solutions were prepared for encapsulated formulation testing, physicochemical characterization, stability testing with DNase I, and cytotoxicity testing. The PLGA-pEGFP-C1-tat solutions were transfected in HeLa cells, and gene expression was observed by fluorescent microscopy and real-time PCR. Results: The successful acquisition of transformant bacteria was confirmed by PCR. The PLGA:DNA:polyvinyl alcohol ratio formulation with optimal encapsulation was 4%:0.5%:2%, physicochemical characterization of PLGA revealed a polydispersity index value of 0.246, a particle size of 925 nm, and a zeta potential value of -2.31 mV. PLGA succeeded in protecting pEGFP-C1-tat from enzymatic degradation, and the percentage viability from the cytotoxicity test of PLGA-pEGFP-C1-tat was 98.03%. The PLGA-pEGFP-C1-tat demonstrated luminescence of the EGFP-tat fusion protein and mRNA transcription was detected. Conclusions: PLGA has good potential as a delivery system for pEGFP-C1-tat.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1765-1794
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• 2019

Genetic Programming (GP) is an intelligence technique whereby computer programs are encoded as a set of genes which are evolved utilizing a Genetic Algorithm (GA). In other words, the GP employs novel optimization techniques to modify computer programs; imitating the way humans develop programs by progressively re-writing them for solving problems automatically. Trial programs are frequently altered in the search for obtaining superior solutions due to the base is GA. These are evolutionary search techniques inspired by biological evolution such as mutation, reproduction, natural selection, recombination, and survival of the fittest. The power of GAs is being represented by an advancing range of applications; vector processing, quantum computing, VLSI circuit layout, and so on. But one of the most significant uses of GAs is the automatic generation of programs. Technically, the GP solves problems automatically without having to tell the computer specifically how to process it. To meet this requirement, the GP utilizes GAs to a "population" of trial programs, traditionally encoded in memory as tree-structures. Trial programs are estimated using a "fitness function" and the suited solutions picked for re-evaluation and modification such that this sequence is replicated until a "correct" program is generated. GP has represented its power by modifying a simple program for categorizing news stories, executing optical character recognition, medical signal filters, and for target identification, etc. This paper reviews existing literature regarding the GPs and their applications in different scientific fields and aims to provide an easy understanding of various types of GPs for beginners.

• Genomics & Informatics
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• v.20 no.1
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• pp.11.1-11.20
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• 2022

Vibrio harveyi belongs to the Vibrio genus that causes vibriosis in marine and aquatic fish species through double-stranded DNA virus replication. In humans, around 12 Vibrio species can cause gastroenteritis (gastrointestinal illness). A large amount of virus particles can be found in the cytoplasm of infected cells, which may cause death. Despite these devastating complications, there is still no cure or vaccine for the virus. As a result, we used an immunoinformatics approach to develop a multi-epitope vaccine against most pathogenic hemolysin gene of V. harveyi. The immunodominant T- and B-cell epitopes were identified using the hemolysin protein. We developed a vaccine employing three possible epitopes: cytotoxic T-lymphocytes, helper T-lymphocytes, and linear B-lymphocyte epitopes, after thorough testing. The vaccine was developed to be antigenic, immunogenic, and non-allergenic, as well as having a better solubility. Molecular dynamics simulation revealed significant structural stiffness and binding stability. In addition, the immunological simulation generated by computer revealed that the vaccination might elicit immune reactions in the actual life after injection. Finally, using Escherichia coli K12 as a model, codon optimization yielded ideal GC content and a higher codon adaptation index value, which was then included in the cloning vector pET2+ (a). Altogether, our experiment implies that the proposed peptide vaccine might be a good option for vibriosis prophylaxis.