• 제목/요약/키워드: Functional optimization

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Global Optimization of Clusters in Gene Expression Data of DNA Microarrays by Deterministic Annealing

  • Lee, Kwon Moo;Chung, Tae Su;Kim, Ju Han
    • Genomics & Informatics
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    • v.1 no.1
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    • pp.20-24
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    • 2003
  • The analysis of DNA microarry data is one of the most important things for functional genomics research. The matrix representation of microarray data and its successive 'optimal' incisional hyperplanes is a useful platform for developing optimization algorithms to determine the optimal partitioning of pairwise proximity matrix representing completely connected and weighted graph. We developed Deterministic Annealing (DA) approach to determine the successive optimal binary partitioning. DA algorithm demonstrated good performance with the ability to find the 'globally optimal' binary partitions. In addition, the objects that have not been clustered at small non­zero temperature, are considered to be very sensitive to even small randomness, and can be used to estimate the reliability of the clustering.

Fairing B-spline Surfaces Using Optimization Technique (최적화 기법을 이용한 곡면페어링)

  • park, S.K.;Lee, K.W.
    • Transactions of the Korean Society of Automotive Engineers
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    • v.1 no.3
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    • pp.95-108
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    • 1993
  • The needs for smooth curves and surfaces are increasing in modeling cars, ships, airplanes, and other consumer products either for aesthetic or functional purpose. However, the curves and surfaces generated by conventional modeling methods usually exhibit an unwanted behavior due to digitizing errors or inadequate generation method, and thus much time and extra effort is spent afterwards to get the faired results. The objective of this work is to develop a fairing scheme by which well refined shape of a surface can be acquired with detecting and removing the shape imperfections of the given surface represented by NURBS. The fairing scheme is based on an optimization process in which the control points of the given surface are repositioned to minimize the integration of the jumps(perturbations) of the unit normal vectors at all surface points.

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A NEW CLASS OF NONLINEAR CONJUGATE GRADIENT METHOD FOR UNCONSTRAINED OPTIMIZATION MODELS AND ITS APPLICATION IN PORTFOLIO SELECTION

  • Malik, Maulana;Sulaiman, Ibrahim Mohammed;Mamat, Mustafa;Abas, Siti Sabariah;Sukono, Sukono
    • Nonlinear Functional Analysis and Applications
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    • v.26 no.4
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    • pp.811-837
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    • 2021
  • In this paper, we propose a new conjugate gradient method for solving unconstrained optimization models. By using exact and strong Wolfe line searches, the proposed method possesses the sufficient descent condition and global convergence properties. Numerical results show that the proposed method is efficient at small, medium, and large dimensions for the given test functions. In addition, the proposed method was applied to solve practical application problems in portfolio selection.

A Study on Application of Systems Approach for Laser Micro Machining Design Process (시스템적 접근을 통한 레이저 미세가공 설계 프로세스 개발에 관한 연구)

  • Moon, Seong-Wook;Park, Young-Won;Nam, Gi-Jung
    • Laser Solutions
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    • v.10 no.3
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    • pp.15-24
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    • 2007
  • In this paper laser micromachining system design process for commercialization is suggested. The constructed system design process is properly adjusted for laser micromachining area after tailoring engine process of system engineering process such as requirement analysis, functional analysis and allocation, system synthesis and system optimization process. In the current laser machining system design, system components and specifications are determined on the basis of experimental experience which a laser is being used in machining some materials as well as the current machining and research trend. In this paper, however, systematic process is suggested in addition to experimental experience, which the laser and system components and their specifications are decided in the process of definition of functional requirements and engine design variables of system to satisfy the customer's requirements.

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A hybrid inverse method for small scale parameter estimation of FG nanobeams

  • Darabi, A.;Vosoughi, Ali R.
    • Steel and Composite Structures
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    • v.20 no.5
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    • pp.1119-1131
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    • 2016
  • As a first attempt, an inverse hybrid numerical method for small scale parameter estimation of functionally graded (FG) nanobeams using measured frequencies is presented. The governing equations are obtained with the Eringen's nonlocal elasticity assumptions and the first-order shear deformation theory (FSDT). The equations are discretized by using the differential quadrature method (DQM). The discretized equations are transferred from temporal domain to frequency domain and frequencies of the nanobeam are obtained. By applying random error to these frequencies, measured frequencies are generated. The measured frequencies are considered as input data and inversely, the small scale parameter of the beam is obtained by minimizing a defined functional. The functional is defined as root mean square error between the measured frequencies and calculated frequencies by the DQM. Then, the conjugate gradient (CG) optimization method is employed to minimize the functional and the small scale parameter is obtained. Efficiency, convergence and accuracy of the presented hybrid method for small scale parameter estimation of the beams for different applied random error, boundary conditions, length-to-thickness ratio and volume fraction coefficients are demonstrated.

Optimization of the extraction of phytochemicals from black mulberry (Morus nigra L.) leaves

  • Nastic, Natasa;Borras-Linares, Isabel;Lozano-Sanchez, Jesus;Svarc-Gajic, Jaroslava;Segura-Carretero, Antonio
    • Journal of Industrial and Engineering Chemistry
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    • v.68
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    • pp.282-292
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    • 2018
  • This study aimed to compare the chemical composition of Morus nigra leaves extracts, obtained by maceration, accelerated solvent (ASE) and supercritical fluid extraction (SFE) under different extraction conditions. With regards to chemical composition, mainly phenolic acids and flavonoids were identified. HPLC-ESI-QTOF-MS allowed the identification of 13 new compounds reported in M. nigra leaves for the first time. ASE as a fast, green and innovative approach, seems to be the best choice for extracting compounds of different polarities within the shortest extraction time. The present study also highlights the potential application of M. nigra extracts as constituents of new added-value formulations.

Optimization of Conditions for High Concentration of Eleutheroside E and Chlorgenic Acid Components of Acanthopanax koreanum Stem Extract

  • Kim, Sung Gi;Yang, Byung Wook;Lee, Jae Bum;Kim, Sa Hyun;Ko, Sung Kwon
    • Biomedical Science Letters
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    • v.26 no.4
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    • pp.319-326
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    • 2020
  • This study was conducted to develop a new functional material by optimizing the conditions for high concentrations of chlorogenic acid and eleutheroside E in Acanthopanax koreanum stem. The total phenolic compound content was the highest in the 20 hours sonication Acanthopanax koreanum stem extract (UAK-20). In addition, eleutheroside E, a typical functional ingredient of Cortex Acanthopanacis, in the 20 hours treated Acanthopanax koreanum stem extract showed the highest content at 1.646%. However, another functional ingredient, chlorogenic acid, showed the highest content of 2.625% in 1 hour treated Acanthopanax koreanum stem extract. Therefore, it is considered that the optimal conditions for high concentrations of total phenolic compound and eleutheroside E are 20 hours sonication Acanthopanax koreanum stem extract.

APPROXIMATION OF FIXED POINTS AND THE SOLUTION OF A NONLINEAR INTEGRAL EQUATION

  • Ali, Faeem;Ali, Javid;Rodriguez-Lopez, Rosana
    • Nonlinear Functional Analysis and Applications
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    • v.26 no.5
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    • pp.869-885
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    • 2021
  • In this article, we define Picard's three-step iteration process for the approximation of fixed points of Zamfirescu operators in an arbitrary Banach space. We prove a convergence result for Zamfirescu operator using the proposed iteration process. Further, we prove that Picard's three-step iteration process is almost T-stable and converges faster than all the known and leading iteration processes. To support our results, we furnish an illustrative numerical example. Finally, we apply the proposed iteration process to approximate the solution of a mixed Volterra-Fredholm functional nonlinear integral equation.

Optimization of the Ingredient Mixing Ratio for Preparation of Kiwifruit (Actinidia deliciosa) Jam Prepared with added Barley Sproutling Powder (어린 보릿잎을 첨가한 키위잼 재료 혼합비율의 최적화)

  • Jang, Myung-Sook
    • Korean journal of food and cookery science
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    • v.25 no.2
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    • pp.234-242
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    • 2009
  • This study was performed to find the optimum ratio of ingredients for the manufacture of kiwifruit jam. The experiment was designed according to the D-optimal design of RSM (response surface methodology), which included 18 experimental points with 4 replicates for three independent variables (sugar $35{\sim}60%$, pectin $0.1{\sim}1.0.%$, kiwifruit paste $0.37{\sim}0.90%$). The compositional and functional properties of the prepared products were measured, and these values were applied to mathematical models. A canonical form and trace plot showed the influence of each variable on the quality attributes of the final product mixture. By use of the F-test, viscosity, color values (L, a, b), and sensory characteristics (color) were expressed by a linear model, while the L color value and select sensory characteristics (smell, taste, overall acceptance) were also expressed by a quadratic model. The optimum formulations by the numerical and graphical methods, were similar, and with the numerical method it presented as: sugar, pectin, and barley sproutling powder at 49.7%, 0.5%, and 0.6%, respectively. The above results demonstrate the feasibility of preparing kiwifruit jam added with barley sproutling powder, and therefore, the commercialization of a kiwifruit jam marketed as a functional food is deemed possible.

K-Means-Based Polynomial-Radial Basis Function Neural Network Using Space Search Algorithm: Design and Comparative Studies (공간 탐색 최적화 알고리즘을 이용한 K-Means 클러스터링 기반 다항식 방사형 기저 함수 신경회로망: 설계 및 비교 해석)

  • Kim, Wook-Dong;Oh, Sung-Kwun
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.8
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    • pp.731-738
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    • 2011
  • In this paper, we introduce an advanced architecture of K-Means clustering-based polynomial Radial Basis Function Neural Networks (p-RBFNNs) designed with the aid of SSOA (Space Search Optimization Algorithm) and develop a comprehensive design methodology supporting their construction. In order to design the optimized p-RBFNNs, a center value of each receptive field is determined by running the K-Means clustering algorithm and then the center value and the width of the corresponding receptive field are optimized through SSOA. The connections (weights) of the proposed p-RBFNNs are of functional character and are realized by considering three types of polynomials. In addition, a WLSE (Weighted Least Square Estimation) is used to estimate the coefficients of polynomials (serving as functional connections of the network) of each node from output node. Therefore, a local learning capability and an interpretability of the proposed model are improved. The proposed model is illustrated with the use of nonlinear function, NOx called Machine Learning dataset. A comparative analysis reveals that the proposed model exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.