• Asian Journal of Innovation and Policy
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• v.5 no.2
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• pp.146-184
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• 2016

This paper analyzes the major comparisons and contrasts in entrepreneurship among technology-based university alumni over multiple decades from Tsinghua University in China and the Massachusetts Institute of Technology in the United States. In doing so, we ask two related research questions: (1) Who enters entrepreneurship and with what types of ideas and founding teams? (2) How do the innovation and other firm performance outcomes compare? We find that the sources of venture ideas and the composition of founding teams differ as well as the initial capital levels and revenues. This research provides a step toward a better understanding of high-tech entrepreneurship in developing vs. developed institutional environments. Furthermore, while MIT and Tsinghua University are unique in the programs they offer and in their historical cultures of entrepreneurship, both Tsinghua University and MIT provide benchmarks by which other institutions can gauge their alumni entrepreneurs and the types of ventures that they create.

• Agribusiness and Information Management
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• v.1 no.2
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• pp.43-60
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• 2009

To improve the performance of wide-issue superscalar processors, it is essential to increase the width of instruction fetch and the issue rate. Removal of control hazard has been put forward as a significant new source of instruction-level parallelism for superscalar processors and the conditional branch prediction is an important technique for improving processor performance. Branch mispredictions, however, waste a large number of cycles, inhibit out-of-order execution, and waste electric power on mis-speculated instructions. Hence, the branch predictor with higher accuracy is necessary for good processor performance. In global-history-based predictors like gshare and GAg, many mispredictions come from commit update of the branch history. Some works on this subject have discussed the need for speculative update of the history and recovery mechanisms for branch mispredictions. In this paper, we present a new mechanism for recovering the branch history after a misprediction. The proposed mechanism adds an age_counter to the original predictor and doubles the size of the branch history register. The age_counter counts the number of outstanding branches and uses it to recover the branch history register. Simulation results on the SimpleScalar 3.0/PISA tool set and the SPECINT95 benchmarks show that gshare and GAg with the proposed recovery mechanism improved the average prediction accuracy by 2.14% and 9.21%, respectively and the average IPC by 8.75% and 18.08%, respectively over the original predictor.

• Journal of Korean Society for Quality Management
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• v.36 no.1
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• pp.20-30
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• 2008

Nowadays many countries in the world have been implementing TQM which is originated from Japanese management style. There are many research results that TQM has a positive influences on business results. But the levels of implementing TQM are different by countries. The domestic competitors and the customers, who have the great influences on business results are also quite different. Therefore the levels of TQM in some company and the influences of TQM factors on business results are supposed to be different by countries. The situations of the countries lying on the more developed stage will be a good benchmarks for the countries on following stages. There are few researches on this cross countries analysis. This paper do the empirical study on the effects of TQM factors on business results between Korean and Japanese small or medium sized manufacturing companies. First, the levels of TQM are compared between countries. Second, what key success factors among TQM ones are for business success is analyzed for each country and compared between two countries. This study will help to plan the road maps in TQM journey for the Korean companies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4510-4526
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• 2017

Most available methods of facial gender recognition work well under a constrained situation, but the performances of these methods have decreased significantly when they are implemented under unconstrained environments. In this paper, a method via low-rank and collaborative representation is proposed for facial gender recognition in the wild. Firstly, the low-rank decomposition is applied to the face image to minimize the negative effect caused by various corruptions and dynamical illuminations in an unconstrained environment. And, we employ the collaborative representation to be as the classifier, which using the much weaker $l_2-norm$ sparsity constraint to achieve similar classification results but with significantly lower complexity. The proposed method combines the low-rank and collaborative representation to an organic whole to solve the task of facial gender recognition under unconstrained environments. Extensive experiments on three benchmarks including AR, CAS-PERL and YouTube are conducted to show the effectiveness of the proposed method. Compared with several state-of-the-art algorithms, our method has overwhelming superiority in the aspects of accuracy and robustness.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.11
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• pp.836-852
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• 2006

This paper proposes an L1 cache prefetch scheme using an excessively aggressive hardware prefetcher and a hardware prefetch filter having a small direct-mapped filtering cache. A quantitative analysis method has been introduced and applied to analyze nonideal effects of aggressive cache prefetching. From those analysis results, the structure and algorithm of a prefetch filter has been derived and simulated, and the overall system performance has been measured using a cycle-by-cycle cache simulator. Experimental results show that the proposed scheme improves the overall system performance by 18% on the average over several benchmarks

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2607-2627
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• 2017

Nonnegative matrix factorization (NMF) has received considerable attention due to its effectiveness of reducing high dimensional data and importance of producing a parts-based image representation. Most of existing NMF variants attempt to address the assertion that the observed data distribute on a nonlinear low-dimensional manifold. However, recent research results showed that not only the observed data but also the features lie on the low-dimensional manifolds. In addition, a few hard priori label information is available and thus helps to uncover the intrinsic geometrical and discriminative structures of the data space. Motivated by the two aspects above mentioned, we propose a novel algorithm to enhance the effectiveness of image representation, called Dual graph-regularized Constrained Nonnegative Matrix Factorization (DCNMF). The underlying philosophy of the proposed method is that it not only considers the geometric structures of the data manifold and the feature manifold simultaneously, but also mines valuable information from a few known labeled examples. These schemes will improve the performance of image representation and thus enhance the effectiveness of image classification. Extensive experiments on common benchmarks demonstrated that DCNMF has its superiority in image classification compared with state-of-the-art methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4429-4447
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• 2018

Local binary descriptors are well-suited for many real-time and/or large-scale computer vision applications, while their low computational complexity is usually accompanied by the limitation of performance. In this paper, we propose a new optimization framework, RLDB (Robust-LDB), to improve a typical region-based binary descriptor LDB (local difference binary) and maintain its computational simplicity. RLDB extends the multi-feature strategy of LDB and applies a more complete region-comparing configuration. A cascade bit selection method is utilized to select the more representative patterns from massive comparison pairs and an online learning strategy further optimizes descriptor for each specific patch separately. They both incorporate LDP (linear discriminant projections) principle to jointly guarantee the robustness and distinctiveness of the features from various scales. Experimental results demonstrate that this integrated learning framework significantly enhances LDB. The improved descriptor achieves a performance comparable to floating-point descriptors on many benchmarks and retains a high computing speed similar to most binary descriptors, which better satisfies the demands of applications.

• Steel and Composite Structures
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• v.35 no.4
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• pp.555-566
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• 2020

This paper aims to present an analytical methodology to investigate influences of nanoscale and surface energy on buckling stability behavior of perforated nanobeam structural element, for the first time. The surface energy effect is exploited to consider the free energy on the surface of nanobeam by using Gurtin-Murdoch surface elasticity theory. Thin and thick beams are considered by using both classical beam of Euler and first order shear deformation of Timoshenko theories, respectively. Equivalent geometrical constant of regularly squared perforated beam are presented in simplified form. Problem formulation of nanostructure beam including surface energies is derived in detail. Explicit analytical solution for nanoscale beams are developed for both beam theories to evaluate the surface stress effects and size-dependent nanoscale on the critical buckling loads. The closed form solution is confirmed and proven by comparing the obtained results with previous works. Parametric studies are achieved to demonstrate impacts of beam filling ratio, the number of hole rows, surface material characteristics, beam slenderness ratio, boundary conditions as well as loading conditions on the non-classical buckling of perforated nanobeams in incidence of surface effects. It is found that, the surface residual stress has more significant effect on the critical buckling loads with the corresponding effect of the surface elasticity. The proposed model can be used as benchmarks in designing, analysis and manufacturing of perforated nanobeams.

• Structural Engineering and Mechanics
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• v.58 no.5
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• pp.799-823
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• 2016

A finite element model for the non-linear dynamic analysis of a reinforced concrete (RC) containment shell of a nuclear power plant subjected to extreme loads such as impact and earthquake is presented in this work. The impact is modeled by using an uncoupled approach in which a load function is applied at the impact zone. The earthquake load is modeled by prescribing ground accelerations at the base of the structure. The nuclear containment is discretized spatially by using 20-node brick finite elements. The concrete in compression is modeled by using a modified $Dr{\ddot{u}}cker$-Prager elasto-plastic constitutive law where strain rate effects are considered. Cracking of concrete is modeled by using a smeared cracking approach where the tension-stiffening effect is included via a strain-softening rule. A model based on fracture mechanics, using the concept of constant fracture energy release, is used to relate the strain softening effect to the element size in order to guaranty mesh independency in the numerical prediction. The reinforcing bars are represented by incorporated membrane elements with a von Mises elasto-plastic law. Two benchmarks are used to verify the numerical implementation of the present model. Results are presented graphically in terms of displacement histories and cracking patterns. Finally, the influence of the shear transfer model used for cracked concrete as well as the effect due to a base slab incorporation in the numerical modeling are analyzed.

• Nuclear Engineering and Technology
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• v.40 no.6
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• pp.477-488
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• 2008

The objective of the paper is to analyze the thermally induced density wave oscillations in water cooled boiling water reactors. A transient thermal hydraulic model is developed with a characteristics-based implicit finite-difference scheme to solve the nonlinear mass, momentum and energy conservation equations in a time-domain. A two-phase flow was simulated with a one-dimensional homogeneous equilibrium model. The model treats the boundary conditions naturally and takes into account the compressibility effect of the two-phase flow. The axial variation of the heat flux profile can also be handled with the model. Unlike the method of characteristics analysis, the present numerical model is computationally inexpensive in terms of time and works in a Eulerian coordinate system without the loss of accuracy. The model was validated against available benchmarks. The model was extended for the purpose of studying the flow-induced density wave oscillations in forced circulation and natural circulation boiling water reactors. Various parametric studies were undertaken to evaluate the model's performance under different operating conditions. Marginal stability boundaries were drawn for type-I and type-II instabilities in a dimensionless parameter space. The significance of adiabatic riser sections in different boiling reactors was analyzed in detail. The effect of the axial heat flux profile was also investigated for different boiling reactors.