The bending strip method for isogeometric analysis of Kirchhoff–Love shell structures comprised of multiple patches

In this paper we present an isogeometric formulation for rotation-free thin shell analysis of structures comprised of multiple patches. The structural patches are C¹- or higher-order continuous in the interior, and are joined with C⁰-continuity. The Kirchhoff–Love shell theory that relies on higher-order continuity of the basis functions is employed in the patch interior as presented in Kiendl et al. [36]. For the treatment of patch boundaries, a method is developed in which strips of fictitious material with unidirectional bending stiffness and zero membrane stiffness are added at patch interfaces. The direction of bending stiffness is chosen to be transverse to the patch interface. This choice leads to an approximate satisfaction of the appropriate kinematic constraints at patch interfaces without introducing additional stiffness to the shell structure. The attractive features of the method include simplicity of implementation and direct applicability to complex, multi-patch shell structures. The good performance of the bending strip method is demonstrated on a set of benchmark examples. Application to a wind turbine rotor subjected to realistic wind loads is also shown. Extension of the bending strip approach to the coupling of solids and shells is proposed and demonstrated numerically.     

Integrating independent component analysis and support vector machine for multivariate process monitoring

This study aims to develop an intelligent algorithm by integrating the independent component analysis (ICA) and support vector machine (SVM) for monitoring multivariate processes. For developing a successful SVM-based fault detector, the first step is feature extraction. In real industrial processes, process variables are rarely Gaussian distributed. Thus, this study proposes the application of ICA to extract the hidden information of a non-Gaussian process before conducting SVM. The proposed fault detector will be implemented via two simulated processes and a case study of the Tennessee Eastman process. Results demonstrate that the proposed method possesses superior fault detection when compared to conventional monitoring methods, including PCA, ICA, modified ICA, ICA–PCA and PCA–SVM.     

Improved results for scheduling batched parallel jobs by using a generalized analysis framework

We present two improved results for scheduling batched parallel jobs on multiprocessors with mean response time as the performance metric. These results are obtained by using a generalized analysis framework where the response time of the jobs is expressed in two contributing factors that directly impact a scheduler’s competitive ratio. Specifically, we show that the scheduler IGDEQ is 3-competitive against the optimal while AGDEQ is 5.24-competitive. These results improve the known competitive ratios of 4 and 10, obtained by Deng et al. and by He et al., respectively. For the common case where no fractional allotments are allowed, we show that slightly larger competitive ratios can be obtained by augmenting the schedulers with the round-robin strategy.     

Computational and mutagenesis studies of the streptavidin native dimer interface

Wt streptavidin forms a domain swapped tetramer consisting of two native dimers. The role of tetramerization has been studied previously and is known to contribute to biotin binding by allowing the exchange of W120 between adjacent subunits. However, the role of dimer formation in streptavidin folding and function has been largely overlooked to date, although native dimers are necessary for tetramer formation and thus for high affinity biotin binding. To understand how the side chain interactions at the dimer interface stabilize the subunit association, we studied the structural and functional consequences of introducing interfacial mutations by a combination of molecular dynamics (MD) simulation and biochemical characterization. In particular, we introduced rational mutations at the dimer interface to engineer new side chain interactions and measured the stability and function of the resulting mutants. We focused on two residues that form a "knob" and a "hole" pair, G74 and T76, since steric complementarity plays an important role at these positions. We introduced mutations that would change the polarity and side chain packing to test if the interface can be rationally redesigned. Both energy calculation and geometric parameterization were used to interpret the simulated structures and predict how the mutations affect the dimer stability. In this regard, obtaining precise energy estimates was difficult because the simulated structures have large stochastic variations and some mutants did not reach an equilibrium by the end of the simulation. In contrast, comparing the wt and mutants to one another and parameterizing the simulation using a geometric parameter, i.e. the degree of solvation of the buried interface, resulted in a testable prediction regarding which mutations would result in a stable dimer. We present experimental data (denaturation and binding measurements) to show that an intuitive parameter based on physical reasoning can be useful for characterizing simulations that are difficult to analyze quantitatively.     

MTPSO algorithm for solving planar graph coloring problem

In this paper, we proposed a modified turbulent particle swarm optimization (named MTPSO) model for solving planar graph coloring problem based on particle swarm optimization. The proposed model is consisting of the walking one strategy, assessment strategy and turbulent strategy. The proposed MTPSO model can solve the planar graph coloring problem using four-colors more efficiently and accurately. Compared to the results shown in Cui et al. (2008), not only the experimental results of the proposed model can get smaller average iterations but can get higher correction coloring rate when the number of nodes is greater than 30.     

A gradient-based adaptive error diffusion method with edge enhancement

This paper presents a gradient-based adaptive error diffusion method with edge enhancement effect while preserving the smoothness effect. The proposed method not only can modulate the threshold in halftoning dynamically but also can determine the weights of the error diffusion filter adaptively to diffuse the quantization error to neighboring pixels properly. Under six testing images, experimental results demonstrate that our proposed new error diffusion method has a good compromise between the edge enhancement effect in the halftone image and the image quality effect in the corresponding inverse halftone image when compared to the methods by Floyd–Steinberg, Eschbach and Knox, Hwang et al., Li, and Feng et al., but it has some execution-time degradation.     

A weighted segment-based caching algorithm for video streaming objects over heterogeneous networking environments

Traditional caching technology is not applicable to cache video streaming objects over heterogeneous networking environments. The popularity of mobile devices in the heterogeneous networking environments make the access of Internet content become a common phenomenon. To support different mobile devices in the heterogeneity networking environments, a transcoding proxy is used to transcode different versions of the streaming videos according to clients’ requests. In this paper, we propose a weighted caching replace strategy for video streaming objects over heterogeneous networking environments. A new caching algorithm with static weight transcoding graph and dynamic caching relation tree is introduced. The proposed algorithm is compared with LRU, LFU, CP and PF cache algorithms in three parts: hit ratio, byte hit ratio, and average transmission delay. Experimental results show that the proposed algorithm outperforms than traditional LRU, LFU, CP and PF cache algorithms.     

Using improved grey forecasting models to forecast the output of opto-electronics industry

Numerous forecasting models have been developed. Each has its own conditions of application. However, it has always been an important research objective to improve prediction accuracy with a small amount of data. In recent years, the grey forecasting model has achieved good prediction accuracy with limited data and has been widely used in various research fields. However, the grey forecasting models still have some potential problems that need to be improved. Therefore, this study proposed an improved transformed grey model based on a genetic algorithm (ITGM(1,1)), and used the output of the opto-electronics industry in Taiwan from 1990 to 2008 as an example for verification. Three grey forecasting models, GM(1,1), rolling GM(1,1), and the transformed GM(1,1), were chosen for the purpose of comparison with ITGM(1,1) by mean absolute percent error and root mean square percent error. The results show that ITGM(1,1) is more accurate than the other three models in both in-sample and out-of-sample forecasting performance, and can greatly improve the accuracy of short-term forecasts.     

Hybrid feature selection by combining filters and wrappers

Feature selection aims at finding the most relevant features of a problem domain. It is very helpful in improving computational speed and prediction accuracy. However, identification of useful features from hundreds or even thousands of related features is a nontrivial task. In this paper, we introduce a hybrid feature selection method which combines two feature selection methods – the filters and the wrappers. Candidate features are first selected from the original feature set via computationally-efficient filters. The candidate feature set is further refined by more accurate wrappers. This hybrid mechanism takes advantage of both the filters and the wrappers. The mechanism is examined by two bioinformatics problems, namely, protein disordered region prediction and gene selection in microarray cancer data. Experimental results show that equal or better prediction accuracy can be achieved with a smaller feature set. These feature subsets can be obtained in a reasonable time period.