• Journal of the Korean Society of Manufacturing Process Engineers
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• v.2 no.2
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• pp.52-59
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• 2003

Cam mechanism is a machine part frequently used in machinery. Specially, conjugate cam mechanism is very suitable for the high speed working and the heavy power translation. Then a conjugate cam mechanism need high precision for the relations between cam profiles and follower rollers. So, its design and manufacturing are very difficult. Thus, this study is a branch of exclusive CAM systems for design and NC machining of conjugate earn mechanism based on a master plate earn profile in order to exchange an old plate cam mechanism to a new conjugate earn mechanism. For the design of the other cam profile by using a master cam profile, some calculation processes were used by vector summation methods, from master cam profile data to the center data of master follower, from the center data of master follower to the center data of the other follower considered in link mechanism, and offsetting in the center direction of base circle of the other cam from the center data of the other follower. Finally, a sample conjugate cam was selected and machined m order to prove the contents of this study.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.735-740
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• 2012

In this paper, we introduce design methodologies of polynomial radial basis function neural network classifier with the aid of Principal Component Analysis(PCA) and Linear Discriminant Analysis(LDA). By minimizing the information loss of given data, Feature data is obtained through preprocessing of PCA and LDA and then this data is used as input data of RBFNNs. The hidden layer of RBFNNs is built up by Fuzzy C-Mean(FCM) clustering algorithm instead of receptive fields and linear polynomial function is used as connection weights between hidden and output layer. In order to design optimized classifier, the structural and parametric values such as the number of eigenvectors of PCA and LDA, and fuzzification coefficient of FCM algorithm are optimized by Artificial Bee Colony(ABC) optimization algorithm. The proposed classifier is applied to some machine learning datasets and its result is compared with some other classifiers.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.1
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• pp.41-47
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• 2024

This paper utilizes computational asymptotic analysis to compute the boundary layer solution for composite beams and validates the findings through a comparison with ANSYS results. The boundary layer solution, presented as a sum of the interior solution and pure boundary layer effects, necessitates a mathematically rigorous formalization for both interior and boundary layer aspects. Computational asymptotic analysis emerges as a robust technique for addressing such problems. However, the challenge lies in connecting the boundary layer and interior solutions. In this study, we systematically separate the principles of virtual work and the principles of Saint-Venant to tackle internal and boundary layer issues. The boundary layer solution is articulated by calculating the Papkovich-Fadle eigenfunctions, representing them as linear combinations of real and imaginary vectors. To address warping functions in the interior solutions, we employed a least squares method. The computed solutions exhibit excellent agreement with 2D finite element analysis results, both quantitatively and qualitatively. This validates the effectiveness and accuracy of the proposed approach in capturing the behavior of composite beams.

• Korean Journal of Cognitive Science
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• v.19 no.4
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• pp.477-497
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• 2008

Mood classification of blog text is an interesting problem, with a potential for a variety of services involving the Web. This paper introduces an approach to mood classification enhancements through the normalized negation n-grams which contain mood clues and corpus-specific term weighting(CSTW). We've done experiments on blog texts with two different classification methods: Enhanced Mood Flow Analysis(EMFA) and Support Vector Machine based Mood Classification(SVMMC). It proves that the normalized negation n-gram method is quite effective in dealing with negations and gave gradual improvements in mood classification with EMF A. From the selection of CSTW, we noticed that the appropriate weighting scheme is important for supporting adequate levels of mood classification performance because it outperforms the result of TF*IDF and TF.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.415-420
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• 2020

Crowd flows occur in metropolitan railway transit stations, terminals, multiple buildings, and stadiums and are important in ensuring the safety as well as smooth flow of pedestrians in these facilities. In this study, the author developed a new computational analysis method for crowd flow dynamics and applied it to models of transit connecting paths. Using the analysis method, the potential value of the exit was assigned the smallest value, and the potential value of the surrounding grids gradually increased to form the overall potential map. A pathline map was then constructed by determining the direction vector from the grid with large potential value to the grid and small potential. These pathlines indicate basic routes of passenger flow. In all models of the analysis object, the pedestrians did not move to the first predicted shortest path but instead moved using alternative paths that changed depending on the situation. Even in bottlenecks in which pedestrians in both directions encountered each other, walking became much smoother if the entry time difference was dispersed. The results of the analysis show that a method for reducing congestion could be developed through software analysis such as passenger flow analysis without requiring hardware improvement work at the railway station.

• Proceedings of the KSAR Conference
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• 2001.03a
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• pp.14-14
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• 2001

본 연구는 생명공학 관련 기술개발에 의하여 신소재 물질을 생산하고 사람에게 안전하고 생리활성이 높은 고가의 의료용 단백질 생산기술을 체계화하며 형질전환 가축을 이용한 유용물질 생산에 따른 산업화와 부가가치의 극대화에 그 목적이 있다. 유즙으로 사람의 빈혈치료제인 EPO(Erythropoietin)를 분비할 수 있는 형질전환돼지를 생산하기 위하여 WAP(Whey Acidic Protein) Promoter(2.6kb) 하류에 사람의 조혈촉진유전자(EPO: 2.6kb)를 연결시켜 미세주입용 재조합 벡터(WAP-EPO : 약 7.8kb)를 구축하였다. 구축된 재조합 벡터를 1세포기 수정란에 약 2ng/ul 농도로 미세주입한 다음 외과적 방법으로 이식하였다. 이식 후 분만 모돈으로부터 생산된 자돈의 꼬리조직을 이용 게놈DNA를 추출하고 PCR 검정을 한 결과, 유즙으로 사람의 빈혈치료제를 생산할 수 있는 유전자가 도입된 형질전환돼지 $\boxDr$새롬이$\boxUl$ (♂)를 확인하였다. 또한 이렇게 꼬리조직으로부터 확인된 새롬이의 혈액과 정액을 채취, 게놈 DNA를 추출하여 외래 유전자 삽입여부를 PCR 방법으로 검정한 결과 꼬리조직과 마찬가지로 혈액 및 정액에서도 외래유전자가 삽입되었음을 확인할 수 있었다. 이렇게 생산된 형질전환돼지 $\boxDr$새롬이$\boxUl$를 이용 계대번식을 통한 F$_1$ 산자의 생산과 유전자 전이율을 확인하기 위하여 $\boxDr$새롬이$\boxUl$정액을 이용한 인공수정을 실시하였다. 인공수정은 1999년 7월 1일부터 2000년 9월 8일 까지 총 78두의 모돈을 이용하였으며, 그 중 21두의 모돈이 분만하여 인공수정에 의한 분만율은 26.92%로 나타났다.(Table Omitted) Table 1에서와 같이 새롬이 정액을 이용한 인공수정에 의해 형질전환된 F$_1$ 자돈의 형질전환율은 17.98%로 나타났으며, 32두의 형질전환자돈 중 8두(암:4두, 수:4두)는 분만과 동시에 폐사하였거나 사육중 폐사하여 현재 24두(암:12두, 수:12두)가 생존하여 F$_1$ 간 교배계획에 의해 사육되고 있다. 이 중 암컷 4두는 현재 F$_2$ 자돈 생산과 함께 유즙내로 사람 빈혈치료제의 분비 유무를 검정중에 있으며, FISH 법에 의한 외래 유전자 삽입 검정을 확인 중에 있다.

• Journal of Korean Association for Spatial Structures
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• v.12 no.2
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• pp.81-88
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• 2012

Cable dome structures are composed of cables-masts and the cables should be in pre-tension since a structure without pre-tension is not stable. Under the pretension, self equilibrium stress state is the main characteristic of a cable dome structure. In this paper, a new method based on the basic principle of closed force polygon for equilibrium system is proposed for the determination of self-equilibrium mode of cable dome structure. The proposed method which is called geometric method has the unique characteristic of visualization of the force mode needed for maintenance of self-equilibrium. The basic theory for a self equilibrium of structure is that the summation of forces at each joint without any external load should be zero. The simplicity of the method which involves only drawing close polygon with the aid of suitable CAD software has been illustrated by means of a example. The results compared with mechanical calculation and existed method and shows good agreement.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.6
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• pp.307-317
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• 2002

In this paper we propose a new mesh reconstruction scheme that produces a displaced subdivision surface directly from unorganized points. The displaced subdivision surface is a new mesh representation that defines a detailed mesh with a displacement map over a smooth domain surface, but original displaced subdivision surface algorithm needs an explicit polygonal mesh since it is not a mesh reconstruction algorithm but a mesh conversion (remeshing) algorithm. The main idea of our approach is that we sample surface detail from unorganized points without any topological information. For this, we predict a virtual triangular face from unorganized points for each sampling ray from a parameteric domain surface. Direct displaced subdivision surface reconstruction from unorganized points has much importance since the output of this algorithm has several important properties: It has compact mesh representation since most vertices can be represented by only a scalar value. Underlying structure of it is piecewise regular so it ran be easily transformed into a multiresolution mesh. Smoothness after mesh deformation is automatically preserved. We avoid time-consuming global energy optimization by employing the input data dependant mesh smoothing, so we can get a good quality displaced subdivision surface quickly.

• Communications of Mathematical Education
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• v.37 no.1
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• pp.65-84
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• 2023

The method of Lagrange multipliers, one of the most fundamental algorithms for solving equality constrained optimization problems, has been widely used in basic mathematics for artificial intelligence (AI), linear algebra, optimization theory, and control theory. This method is an important tool that connects calculus and linear algebra. It is actively used in artificial intelligence algorithms including principal component analysis (PCA). Therefore, it is desired that instructors motivate students who first encounter this method in college calculus. In this paper, we provide an integrated perspective for instructors to teach the method of Lagrange multipliers effectively. First, we provide visualization materials and Python-based code, helping to understand the principle of this method. Second, we give a full explanation on the relation between Lagrange multiplier and eigenvalues of a matrix. Third, we give the proof of the first-order optimality condition, which is a fundamental of the method of Lagrange multipliers, and briefly introduce the generalized version of it in optimization. Finally, we give an example of PCA analysis on a real data. These materials can be utilized in class for teaching of the method of Lagrange multipliers.

• KSBB Journal
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• v.24 no.6
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• pp.591-597
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• 2009

B-type natriuretic peptide is a neurohormone secreted in the cardiac ventricles. BNP levels are elevated in patients with ventricular dysfunction. Therefore, the concentration of BNP is important factor to reflect diagnosis and prognosis for cardiovascular disease. In this respect, anti-BNP scFv is an urgent requirement for early diagnosis in the field of biosensor. Herein, the genetic codes of anti-BNP scFv were chemically synthesized and cloned into both pET22b (+) and pColdⅣ vector, respectively. The recombinant scFv was successfully expressed as a functional form in cytoplasm of E. coli and detected through Western blot and ELISA. The highest level of functional expression of anti-BNP scFv was achieved using pET22b (+) vector at $15^{\circ}C$ by addition of 0.1 mM IPTG. Additionally, being exposed to both BNP and ANP, anti-BNP scFv specifically captured only BNP. Therefore, anti-BNP scFv expressed in this study will be applied to measure the concentration of BNP as a diagnostic recognition molecule.