• Advances in aircraft and spacecraft science
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• 제7권6호
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• pp.517-536
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• 2020

The present study investigates axial vibration of a FG nanobeam using nonlocal elasticity theory under clamped-clamped and clamped-free boundary conditions. Power law, exponential law and sigmoid law are applied as grading laws to examine the effect of the material distribution on axial vibration of the FG nanobeam. A parametric study was done to examine the effect of length scale on the dynamic behavior of the structure and the results are presented. It was observed that consideration of the nonlocal length scale is essential when analyzing the free vibration of a FG nanobeam. The results of the present study can be used as benchmarks in future studies of FG nanostructures.

• International Journal of Control, Automation, and Systems
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• 제6권4호
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• pp.559-570
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• 2008

This paper proposes an improved particle swarm optimization named PSO with Controllable Random Exploration Velocity (PSO-CREV) behaving an additional exploration behavior. Different from other improvements on PSO, the updating principle of PSO-CREV is constructed in terms of stochastic approximation diagram. Hence a stochastic velocity independent on cognitive and social components of PSO can be added to the updating principle, so that particles have strong exploration ability than those of conventional PSO. The conditions and main behaviors of PSO-CREV are described. Two properties in terms of "divergence before convergence" and "controllable exploration behavior" are presented, which promote the performance of PSO-CREV. An experimental method based on a complex test function is proposed by which the proper parameters of PSO-CREV used in practice are figured out, which guarantees the high exploration ability, as well as the convergence rate is concerned. The benchmarks and applications on FCRNN training verify the improvements brought by PSO-CREV.

• Steel and Composite Structures
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• 제19권5호
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• pp.1237-1258
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• 2015

This paper proposes a simple inelastic analysis approach to efficiently map out the complete nonlinear post-collapse (strain-softening) response and the maximum load capacity of axially loaded concrete encased steel composite columns (stub and slender). The scheme simultaneously incorporates the influences of difficult instabilizing phenomena such as concrete confinement, initial geometric imperfection, geometric nonlinearity, buckling of reinforcement bars and local buckling of structural steel, on the overall behavior of the composite columns. The proposed numerical method adopts fiber element discretization and an iterative M${\ddot{u}}$ller's algorithm with an additional adaptive technique that robustly yields solution convergence. The accuracy of the proposed analysis scheme is validated through comparisons with various available experimental benchmarks. Finally, a parametric study of various key parameters on the overall behaviors of the composite columns is conducted.

• Coupled systems mechanics
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• 제4권1호
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• pp.1-18
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• 2015

The state-based peridynamics is considered a nonlocal method in which the equations of motion utilize integral form as opposed to the partial differential equations in the classical continuum mechanics. As a result, the enforcement of boundary conditions in solid mechanics analyses cannot follow the standard way as in a classical continuum theory. In this paper, a new approach for the boundary condition enforcement in the state-based peridynamic formulation is presented. The new method is first formulated based on a convex kernel approximation to restore the Kronecker-delta property on the boundary in 1-D case. The convex kernel approximation is further localized near the boundary to meet the condition that recovers the correct boundary particle forces. The new formulation is extended to the two-dimensional problem and is shown to reserve the conservation of linear momentum and angular momentum. Three numerical benchmarks are provided to demonstrate the effectiveness and accuracy of the proposed approach.

• Structural Engineering and Mechanics
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• 제38권6호
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• pp.767-802
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• 2011

Developers of new finite elements or nonlinear solution techniques rely on discriminative benchmark tests drawn from the literature to assess the advantages and drawbacks of new formulations. Buckling benchmark tests provide a rigorous evaluation of finite elements applied to thin structures, and a complete and detailed set of reference results would therefore prove very useful in carrying out such evaluations. Results are usually presented in the form of load-deflection curves that developers must reconstruct by extracting the points, a procedure which is often tedious and inaccurate. Moreover the curves are usually given without accompanying information such as the calculation time or number of iterations it took for the model to converge, even though this type of data is equally important in practice. This paper presents ten different limit-point buckling benchmark tests, and provides for each one the reference load-deflection curve, all the points necessary to recreate the curve in tabulated form, analysis data such as calculation time, number of iterations and increments, and all of the inputs used to obtain these results.

• Nuclear Engineering and Technology
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• 제42권5호
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• pp.520-545
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• 2010

This paper presents the neutronics modeling capabilities of the fast reactor simulation system SHARP, which ANL is developing as part of the U.S. DOE's NEAMS program. We discuss the three transport solvers (PN2ND, SN2ND, and MOCFE) implemented in the UNIC code along with the multigroup cross section generation code $MC^2$-3. We describe the solution methods and modeling capabilities, and discuss the improvement needs for each solver, focusing on massively parallel computation. We present the performance test results against various benchmark problems and ZPR-6 and ZPPR critical experiments. We also discuss weak and strong scalability results for the SN2ND solver on the ZPR-6 critical assembly benchmarks.

• 한국경영과학회지
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• 제28권2호
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• pp.105-127
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• 2003

In this paper, four different data mining techniques, two neural networks and two statistical modeling techniques, are compared in terms of prediction accuracy in the context of bankruptcy prediction. In business setting, how to accurately detect the condition of a firm has been an important event in the literature. In neural networks, Backpropagation (BP) network and the Kohonen self-organizing feature map, are selected and compared each other while in statistical modeling techniques, discriminant analysis and logistic regression are also performed to provide performance benchmarks for the neural network experiment. The findings suggest that the BP network is a better choice among the data mining tools compared. This paper also identified some distinctive characteristics of Kohonen self-organizing feature map.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (3)
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• pp.82-84
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• 2004

Java's performance is sometimes not acceptable due to interpretation overhead by the Java Virtual Machine (JVM). In this paper, we present a compiler structure of Java-to-C translator for high performance on resource limited environment like mobile devices. Our compiler framework translates Java into C codes to preserve Java's programming semantics such as inheritance, method overloading, virtual method invocation, and so on. Also our compiler fully supports Connected Limited Device Configuration (CLDC) 1.0 API's. We show that our compiler improves the speedup by up to eleven times more than JVM-only execution in measured benchmarks.

• Journal of Information Processing Systems
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• 제15권6호
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• pp.1489-1502
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• 2019

This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age of big data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance of UCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance of UCSS has been verified by the empirical experiments.

• 전자공학회논문지A
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• 제30A권11호
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• pp.132-139
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• 1993

This paper presents a new performance-driven multi-levelizer which transforms a two-level description into a boolean network of the multilevel structure satisfied with user's costraints, such as chip area, the number of wires and literals, maximum delay, function level, fanin, fanout, etc.. The performance of circuits is estimated by reference to the informations in cell library through the cell mapping phase, and multi-levelization of circuits is constructed by the decomposition using the kernel and factoring concepts. Here, the saving cost of a common subexpression is defined to the sum of area and delay saved, when it is substituted. The experiments with MCNC benchmarks show the efficiency of the proposed method.