Design complexity control in truss optimization

Truss optimization based on the ground structure approach often leads to designs that are too complex for practical purposes. In this paper we present an approach for design complexity control in truss optimization. The approach is based on design complexity measures related to the number of bars (similar to Asadpoure et al. Struct Multidisc Optim 51(2):385–396 2015) and a novel complexity measure related to the number of nodes of the structure. Both complexity measures are continuously differentiable and thus can be used together with gradient based optimization algorithms. The numerical examples show that the proposed approach is able to reduce design complexity, leading to solutions that are more fit for engineering practice. Besides, the examples also indicate that in some cases it is possible to significantly reduce design complexity with little impact on structural performance. Since the complexity measures are non convex, a global gradient based optimization algorithm is employed. Finally, a detailed comparison to a classical approach is presented.     

Application execution path analysis for the automatic parallelisation of binary codes in the Intel x86 platform

Traditionally, computer programs have been developed using the sequential programming paradigm. With the advent of parallel computing systems, such as multicore processors and distributed environments, the sequential paradigm became a barrier to the utilisation of the available resources, since the program is restricted to a single processing unit. To address this issue, we propose a transparent automatic parallelisation tool with a binary rewriter. The steps of our approach are: the disassembly of the Intel x86 application, its transformation into an intermediary language; the analysis of this intermediary representation to obtain the flow and dependency graphs; the partitioning of the application into parallel units, using the obtained graphs; and, finally, the reassembly of the application back into the original Intel x86 architecture. By transforming the compiled application software, we aim at obtaining a program which can better explore the parallel resources, with no extra effort required from users or developers.     

Note: a high transmission Faraday optical isolator in the 9.2 μm range

We have fabricated and characterized an n-doped InSb Faraday isolator in the mid-IR range (9.2 μm). A high isolation ratio (31(2) dB) and low insertion loss (1.9(3) dB) are obtained. Temperature dependance is analyzed. Further possible improvements are discussed, including the realization of a two-stage isolator. A similar design can be used to cover a wide wavelength range (λ ~ 7.5-30 μm).     

Discrete‐time output feedback for Markov jump systems with uncertain transition probabilities

This article addresses the output feedback control for discrete‐time Markov jump linear systems. With fully known transition probability, sufficient conditions for an internal model based controller design are obtained. For the case where the transition probabilities are uncertain and belong to a convex polytope with known vertices, we provide a sufficient LMI condition that guarantees the norm of the closed‐loop system is below a prescribed level. That condition can be improved through an iterative procedure. Additionally, we are able to deal with the case of cluster availability of the Markov mode, provided that some system matrices do not vary within a given cluster, an assumption that is suitable to deal with packet dropout models for networked control systems. A numerical example shows the applicability of the design and compares it with previous results. Copyright © 2012 John Wiley & Sons, Ltd.     

Image Compression and Video Segmentation Using Hierarchical Self-Organization

Both image compression based on color quantization and image segmentation are two typical tasks in the field of image processing. Several techniques based on splitting algorithms or cluster analyses have been proposed in the literature. Self-organizing maps have been also applied to these problems, although with some limitations due to the fixed network architecture and the lack of representation in hierarchical relations among data. In this paper, both problems are addressed using growing hierarchical self-organizing models. An advantage of these models is due to the hierarchical architecture, which is more flexible in the adaptation process to input data, reflecting inherent hierarchical relations among data. Comparative results are provided for image compression and image segmentation. Experimental results show that the proposed approach is promising for image processing, and the powerful of the hierarchical information provided by the proposed model.     

Young's modulus repeatability assessment using cycling compression loading on cancellous bone

For various applications, precision of the Young's modulus of cancellous bone specimens is needed. However, measurement variability is rarely given. The aim of this study was to assess the Young's modulus repeatability using a uniaxial cyclic compression protocol on embedded specimens of human cancellous bone. Twelve specimens from 12 human calcanei were considered. The specimens were first defatted and then 1 or 2 mm at the ends were embedded in an epoxy resin. The compression experiment consists in applying 20 compressive cycles between 0.2 per cent and 0.6 per cent strain with a 2 Hz loading frequency. The coefficient of variation of the current protocol was found to be 1.2 percent. This protocol showed variability similar to the end-cap technique (considered as a reference). It can be applied on porous specimen (especially human bone) and requires minimal bone length to limit end-artifact variability. The current method could be applied in association with noninvasive measurements (such as ultrasound) with full compatibility. This possibility opens the way for bone damage follow-up based on Young's modulus monitoring.     

Dual-color fluorescence lifetime correlation spectroscopy to quantify protein-protein interactions in live cell

Dual-color fluorescence correlation spectroscopy is an interesting method to quantify protein interaction in living cells. But, when performing these experiments, one must compensate for a known spectral bleed through artifact that corrupts cross-correlation data. In this article, problems with crosstalk were overcome with an approach based on fluorescence lifetime correlation spectroscopy (FLCS). We show that FLCS applied to dual-color EGFP and mCherry cross-correlation allows the determination of protein-protein interactions in living cells without the need of spectral bleed through calibration. The methodology was validated by using EGFP-mCherry tandem in comparison with coexpressed EGFP and mCherry in live cell. The dual-color FLCS experimental procedure where the different laser intensities do not have to be controlled during experiment is really very helpful to study quantitatively protein interactions in live sample.     

Variable Structure Control with chattering elimination and guaranteed stability for a generalized T-S model

In this paper, a fuzzy based Variable Structure Control (VSC) with guaranteed stability is presented. The main objective is to obtain an improved performance of highly non-linear unstable systems. The main contribution of this work is that, firstly, new functions for chattering reduction and error convergence without sacrificing invariant properties are proposed, which is considered the main drawback of the VSC control. Secondly, the global stability of the controlled system is guaranteed.The well known weighting parameters approach, is used in this paper to optimize local and global approximation and modeling capability of T-S fuzzy model.A one link robot is chosen as a nonlinear unstable system to evaluate the robustness, effectiveness and remarkable performance of optimization approach and the high accuracy obtained in approximating nonlinear systems in comparison with the original T-S model. Simulation results indicate the potential and generality of the algorithm. The application of the proposed FLC-VSC shows that both alleviation of chattering and robust performance are achieved with the proposed FLC-VSC controller. The effectiveness of the proposed controller is proven infront of disturbances and noise effects.     

A review on the combination of binary classifiers in multiclass problems

Several real problems involve the classification of data into categories or classes. Given a data set containing data whose classes are known, Machine Learning algorithms can be employed for the induction of a classifier able to predict the class of new data from the same domain, performing the desired discrimination. Some learning techniques are originally conceived for the solution of problems with only two classes, also named binary classification problems. However, many problems require the discrimination of examples into more than two categories or classes. This paper presents a survey on the main strategies for the generalization of binary classifiers to problems with more than two classes, known as multiclass classification problems. The focus is on strategies that decompose the original multiclass problem into multiple binary subtasks, whose outputs are combined to obtain the final prediction.