• Title/Summary/Keyword: Mixed method approach

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Statistical Method of Ranking Candidate Genes for the Biomarker

  • Kim, Byung-Soo;Kim, In-Young;Lee, Sun-Ho;Rha, Sun-Young
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.169-182
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    • 2007
  • Receive operating characteristic (ROC) approach can be employed to rank candidate genes from a microarray experiment, in particular, for the biomarker development with the purpose of population screening of a cancer. In the cancer microarray experiment based on n patients the researcher often wants to compare the tumor tissue with the normal tissue within the same individual using a common reference RNA. Ideally, this experiment produces n pairs of microarray data. However, it is often the case that there are missing values either in the normal or tumor tissue data. Practically, we have $n_1$ pairs of complete observations, $n_2$ "normal only" and $n_3$ "tumor only" data for the microarray. We refer to this data set as a mixed data set. We develop a ROC approach on the mixed data set to rank candidate genes for the biomarker development for the colorectal cancer screening. It turns out that the correlation between two ranks in terms of ROC and t statistics based on the top 50 genes of ROC rank is less than 0.6. This result indicates that employing a right approach of ranking candidate genes for the biomarker development is important for the allocation of resources.

Daily Unit Commitment Scheduling of Power System with Energy Storage System (전력저장장치를 고려한 일간 최적 기동정지계획 수립연구)

  • Song, Ha-Na;Jang, Se-Hwan;Kim, Hyeong-Jung;Roh, Jae-Hyung;Park, Jong-Bae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.4
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    • pp.717-725
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    • 2011
  • In the power system with an electric storage system that can increase utilization rate of the source of such new renewable energy, this paper introduces the approach on the daily unit commitment scheduling that determines simultaneously optimum operational condition and output of thermal generators and electric storage device. The unit commitment is one of the most important issues in economic operation and security of short-term operational plan of the power system. It is to determine on/off status of generator to minimize operational cost during the given period. The committed generator should satisfy various operational limitation such as estimated demand by system, spinning reserve condition within minimum operational cost. In order to determine on/off or charge/discharge/idle condition and output level of units and electric storage system, the MILP(Mixed Integer Linear Programming) is suggested. The proposed approach is the mixed method between LP(Linear Programming) and IP(integer programming) which seeks the value of real number and integer that maximize or minimize function objective within given condition. The daily unit commitment problem with the electric storage system is applied to MILP algorithm through linearization and formulation process. The proposed approach is applied to the test system.

Evolutionary Approach for Traveling Salesperson Problem with Precedence Constraints

  • Moon, Chi-Ung;Yun, Young-Su
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.04a
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    • pp.305-308
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    • 2007
  • In this paper we suggest an efficient evolutionary approach based on topological sort techniques for precedence constrained TSPs. The determination of optimal sequence has much to offer to downstream project management and opens up new opportunities for supply chains and logistics. Experimental results show that the suggested approach is a good alternative to locate optimal solution for complicated precedence constrained sequencing as in optimization method for instance.

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An Interactive Multi-criteria Group Decision Making with the Minimum Distance Measure (최소 거리척도를 이용한 대화형 다기준 그룹 의사결정)

  • Cho, Namwoong;Kim, Jaehee;Kim, Sheung-Kown
    • Journal of Korean Institute of Industrial Engineers
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    • v.32 no.1
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    • pp.42-50
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    • 2006
  • The multi-criteria group decision making (MCGDM) problem is to determine the best compromise solution in a set of competing alternatives that are evaluated under conflicting criteria by decision maker (DM)s. In this paper, we propose a mixed-integer programming (MIP) model to solve MCGDM. The existing method based on minimizing a distance measure such as Median Approach can not guarantee the best compromise solution because the element of median point vector is defined with respect to each criteria separately. However, by considering all criteria simultaneously, we generate median point that is better for locating the best compromise solution. We also utilize the concept of spatial dispersion index (SDI) to produce a threshold value, which is used as a guideline to choose either the Utopian Approach or the Median Approach. And we suggest using CBITP (Convex hull of individual maxima Based Interactive Tchebycheff Procedure) to provide DMs with various Pareto-optimal solutions so that DMs have broad range of selection.

Probabilistic Performance Evaluation Technique for Mixed-criticality Scheduling with Task-level Criticality-mode (작업별 중요도 모드를 적용한 혼합 중요도 스케줄링에서 확률적 성능 평가 기법)

  • Lee, Jaewoo
    • The Journal of Society for e-Business Studies
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    • v.23 no.3
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    • pp.1-12
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    • 2018
  • Mixed-criticality systems consist of components with different criticality. Recently, components are categorized depending on criticality by ISO 26262 standard and DO-178B standard in automotive and avionic domain. Existing mixed-criticality system research achieved efficient and safe scheduling through system-level criticality mode. The drawback of these approaches is performance degradation of low-criticality tasks on high-criticality mode. Task-level criticality mode is one method to address the problem and improve the performance of low-critical tasks. In this paper, we propose probabilistic performance metric for the approach. In simulation results with probabilistic performance metric, we showed that our approach has better performance than the existing approaches.

Numerical nonlinear bending analysis of FG-GPLRC plates with arbitrary shape including cutout

  • Reza, Ansari;Ramtin, Hassani;Yousef, Gholami;Hessam, Rouhi
    • Structural Engineering and Mechanics
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    • v.85 no.2
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    • pp.147-161
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    • 2023
  • Based on the ideas of variational differential quadrature (VDQ) and finite element method (FEM), a numerical approach named as VDQFEM is applied herein to study the large deformations of plate-type structures under static loading with arbitrary shape hole made of functionally graded graphene platelet-reinforced composite (FG-GPLRC) in the context of higher-order shear deformation theory (HSDT). The material properties of composite are approximated based upon the modified Halpin-Tsai model and rule of mixture. Furthermore, various FG distribution patterns are considered along the thickness direction of plate for GPLs. Using novel vector/matrix relations, the governing equations are derived through a variational approach. The matricized formulation can be efficiently employed in the coding process of numerical methods. In VDQFEM, the space domain of structure is first transformed into a number of finite elements. Then, the VDQ discretization technique is implemented within each element. As the last step, the assemblage procedure is performed to derive the set of governing equations which is solved via the pseudo arc-length continuation algorithm. Also, since HSDT is used herein, the mixed formulation approach is proposed to accommodate the continuity of first-order derivatives on the common boundaries of elements. Rectangular and circular plates under various boundary conditions with circular/rectangular/elliptical cutout are selected to generate the numerical results. In the numerical examples, the effects of geometrical properties and reinforcement with GPL on the nonlinear maximum deflection-transverse load amplitude curve are studied.

Voter Perceptions and Behavior in East Asian Mixed Systems

  • Rich, Timothy S.
    • Journal of Contemporary Eastern Asia
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    • v.12 no.1
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    • pp.21-34
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    • 2013
  • How do mixed legislative systems shape voter behavior and public perceptions? Through an analysis of the electoral systems in Japan, South Korea, and Taiwan, this paper evaluates the extent to which the public in these three countries understand their mixed systems and whether claims of voter ignorance translate into irrational voting behavior based on the institutional effects of mixed systems. Through a multi-method approach including data from outside of East Asia, this analysis seeks to determine whether these three cases exhibit patterns consistent with other mixed systems. Empirical analysis affirms levels of strategic voting consistent with comprehension of electoral rules. Furthermore, this analysis suggests a disconnect between practical knowledge and electoral expectations.

SATURATION-VALUE TOTAL VARIATION BASED COLOR IMAGE DENOISING UNDER MIXED MULTIPLICATIVE AND GAUSSIAN NOISE

  • JUNG, MIYOUN
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.26 no.3
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    • pp.156-184
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    • 2022
  • In this article, we propose a novel variational model for restoring color images corrupted by mixed multiplicative Gamma noise and additive Gaussian noise. The model involves a data-fidelity term that characterizes the mixed noise as an infimal convolution of two noise distributions and the saturation-value total variation (SVTV) regularization. The data-fidelity term facilitates suitable separation of the multiplicative Gamma and Gaussian noise components, promoting simultaneous elimination of the mixed noise. Furthermore, the SVTV regularization enables adequate denoising of homogeneous regions, while maintaining edges and details and diminishing the color artifacts induced by noise. To solve the proposed nonconvex model, we exploit an alternating minimization approach, and then the alternating direction method of multipliers is adopted for solving subproblems. This contributes to an efficient iterative algorithm. The experimental results demonstrate the superior performance of the proposed model compared to other existing or related models, with regard to visual inspection and image quality measurements.

A New Model Approximation Using the ADP and MISE of Continuous-Time Systems (운송시간 제어계에 있어서 보조분모분수식과 MISE를 이용한 새로운모델 간략법)

  • 권오신;황형수;김성중
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.36 no.9
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    • pp.660-669
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    • 1987
  • Routh approximation method is the most computationally attractive. But this method may cause time-response error because this method does not match the time-response directly. In this paper a new mixed method for obtaining stable reduced-order models for high-order continuous-time systems is proposed. It makes use of the advantages of the Routh approximation method and the Minimization of Integral Squared Error(MISE) criterion approach. In this mixed method the characteristic polynomial of the reduced-order model is first obtained from that of original system by using the Auxiliary Denominator Polynomial(ADP). The numerator polynomial is then determined so as to minimize the intergral squared-error of unit step responses. The advantages of the propsed method are that the reduced models are always stable if the original system are stable and the frequency domain and time domain characteristic of the original system will be preserved in the reduced models.

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Bayesian mixed models for longitudinal genetic data: theory, concepts, and simulation studies

  • Chung, Wonil;Cho, Youngkwang
    • Genomics & Informatics
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    • v.20 no.1
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    • pp.8.1-8.14
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    • 2022
  • Despite the success of recent genome-wide association studies investigating longitudinal traits, a large fraction of overall heritability remains unexplained. This suggests that some of the missing heritability may be accounted for by gene-gene and gene-time/environment interactions. In this paper, we develop a Bayesian variable selection method for longitudinal genetic data based on mixed models. The method jointly models the main effects and interactions of all candidate genetic variants and non-genetic factors and has higher statistical power than previous approaches. To account for the within-subject dependence structure, we propose a grid-based approach that models only one fixed-dimensional covariance matrix, which is thus applicable to data where subjects have different numbers of time points. We provide the theoretical basis of our Bayesian method and then illustrate its performance using data from the 1000 Genome Project with various simulation settings. Several simulation studies show that our multivariate method increases the statistical power compared to the corresponding univariate method and can detect gene-time/ environment interactions well. We further evaluate our method with different numbers of individuals, variants, and causal variants, as well as different trait-heritability, and conclude that our method performs reasonably well with various simulation settings.