Robust linear quadratic regulator applied to an inverted pendulum

The natural instability of an inverted pendulum and its dynamics richness, in terms of nonlinearity, provide a nice apparatus to reproduce behaviors of analogous systems. In this way, it is useful to perform benchmark tests for new control approaches developed. In this paper, we address the main inverted pendulum problems: pendulum stabilization, tracking, and catching swing-up control. We show how robust recursive, control and filtering, techniques improve the system performance. They are developed to solve stochastic problems based on deterministic approaches, in order to decrease the worst influence of uncertainties. Experimental results of the proposed robust approach provide robust stability and performance despite parametric uncertainties, disturbances, and noise effects.     

Characterization of weld seam properties of extruded magnesium hollow profiles

Extrusions of hollow profiles with weld seams were conducted using the magnesium alloy ME21 applying various extrusion ratios. Subsequent analysis of the profiles’ microstructure was performed comparing weld free with weld seam containing material using (polarized) light optical microscopy (LOM). Additionally, the local texture and microstructure in the weld-free material as well as in the weld seam region has been examined with a scanning electron microscope coupled with electron backscatter diffraction technique (SEM-EBSD). The weld-free material and the weld seam are characterized by recrystallized microstructures, whereas few residual cast grains were identified. The local texture distinctively changes from the weld-free material to the weld seam. The texture of the weld-free material is comparable with the typical ME21 sheet texture. In the weld seam area, a pole density is found, which is distributed towards the transverse direction (TD) combined with a split and broadening of the pole density in the extrusion direction (ED). This texture influences the mechanical anisotropy due to the dependence of the activation of basal 〈a〉-slip and \( \{ 10\bar{1}2\} \;\langle 10\bar{1}1\rangle \)-extension twinning on the loading direction in favorably oriented grains.     

Cytosolic Calcium Concentration Changes in Neuronal Cells Under Clinorotation and in Parabolic Flight Missions

All life on earth has been established under conditions of stable gravity of 1g. Nevertheless, in numerous experiments the direct gravity dependence of biological processes has been shown on all levels of organization, from single molecules to humans. To study the effects especially of microgravity on biological systems, a variety of platforms are available, from drop towers to the ISS. Due to the costs of these platforms and their limited availability, as an alternative, numerous simulators have been developed for so called “simulated” microgravity. A classical systems is a clinostat, basically rotating a sample around one axis, and by integration of the gravity vector for 360° arguing that thus the effects of gravity are depleted. Indeed, a variety of studies has shown that taking out the direction of gravity from a biological system often results in consequences similar to the exposure of the system to real microgravity. Nevertheless, the opposite has been shown, too, and as a consequence the relevance of clinostats in microgravity research is still under discussion. To get some more insight into this problem we have constructed a small fluorescence clinostat and have studied the effects of clinorotation on the cytosolic calcium concentration of neuroglioma cells. The results have been compared to experiments with identical cells in real microgravity, utilizing parabolic flight missions. Our results show that in case of a cell suspension used in a small florescence clinostat within a tube diameter of 2mm, the effects of clinorotation are comparable to those under real microgravity, both showing a significant increase in intracellular calcium concentration.     

Controlled counter-flow motion of magnetic bead chains rolling along microchannels

We demonstrate controlled transport of superparamagnetic beads in the opposite direction of a laminar flow. A permanent magnet assembles 200 nm magnetic particles into about 200 μm long bead chains that are aligned in parallel to the magnetic field lines. Due to a magnetic field gradient, the bead chains are attracted towards the wall of a microfluidic channel. A rotation of the permanent magnet results in a rotation of the bead chains in the opposite direction to the magnet. Due to friction on the surface, the bead chains roll along the channel wall, even in counter-flow direction, up to at a maximum counter-flow velocity of 8 mm s⁻¹. Based on this approach, magnetic beads can be accurately manoeuvred within microfluidic channels. This counter-flow motion can be efficiently be used in Lab-on-a-Chip systems, e.g. for implementing washing steps in DNA purification.     

On regular temporal logics with past

The IEEE standardized Property Specification Language, PSL for short, extends the well-known linear-time temporal logic LTL with so-called semi-extended regular expressions. PSL and the closely related SystemVerilog Assertions, SVA for short, are increasingly used in many phases of the hardware design cycle, from specification to verification. In this article, we extend the common core of these specification languages with past operators. We name this extension PPSL. Although all ω-regular properties are expressible in PSL, SVA, and PPSL, past operators often allow one to specify properties more naturally and concisely. In fact, we show that PPSL is exponentially more succinct than the cores of PSL and SVA. On the star-free properties, PPSL is double exponentially more succinct than LTL. Furthermore, we present a translation of PPSL into language-equivalent nondeterministic Büchi automata, which is based on novel constructions for 2-way alternating automata. The upper bound on the size of the resulting nondeterministic Büchi automata obtained by our translation is almost the same as the upper bound for the nondeterministic Büchi automata obtained from existing translations for PSL and SVA. Consequently, the satisfiability problem and the model-checking problem for PPSL fall into the same complexity classes as the corresponding problems for PSL and SVA.     

Temporal kernel CCA and its application in multimodal neuronal data analysis

Data recorded from multiple sources sometimes exhibit non-instantaneous couplings. For simple data sets, cross-correlograms may reveal the coupling dynamics. But when dealing with high-dimensional multivariate data there is no such measure as the cross-correlogram. We propose a simple algorithm based on Kernel Canonical Correlation Analysis (kCCA) that computes a multivariate temporal filter which links one data modality to another one. The filters can be used to compute a multivariate extension of the cross-correlogram, the canonical correlogram, between data sources that have different dimensionalities and temporal resolutions. The canonical correlogram reflects the coupling dynamics between the two sources. The temporal filter reveals which features in the data give rise to these couplings and when they do so. We present results from simulations and neuroscientific experiments showing that tkCCA yields easily interpretable temporal filters and correlograms. In the experiments, we simultaneously performed electrode recordings and functional magnetic resonance imaging (fMRI) in primary visual cortex of the non-human primate. While electrode recordings reflect brain activity directly, fMRI provides only an indirect view of neural activity via the Blood Oxygen Level Dependent (BOLD) response. Thus it is crucial for our understanding and the interpretation of fMRI signals in general to relate them to direct measures of neural activity acquired with electrodes. The results computed by tkCCA confirm recent models of the hemodynamic response to neural activity and allow for a more detailed analysis of neurovascular coupling dynamics.     

A new linguistic MCDM method based on multiple-criterion data fusion

Multiple-criteria decision-making (MCDM) is concerned with the ranking of decision alternatives based on preference judgements made on decision alternatives over a number of criteria. First, taking advantage of data fusion technology to comprehensively consider each criterion data is a reasonable idea to solve the MCDM problem. Second, in order to efficiently handle uncertain information in the process of decision making, some well developed mathematical tools, such as fuzzy sets theory and Dempster Shafer theory of evidence, are used to deal with MCDM. Based on the two main reasons above, a new fuzzy evidential MCDM method under uncertain environments is proposed. The rating of the criteria and the importance weight of the criteria are given by experts’ judgments, represented by triangular fuzzy numbers. Then, the weights are transformed into discounting coefficients and the ratings are transformed into basic probability assignments. The final results can be obtained through the Dempster rule of combination in a simple and straight way. A numerical example to select plant location is used to illustrate the efficiency of the proposed method.     

Estimating m-regimes STAR-GARCH model using QMLE with parameter transformation

It is well known in the literature that obtaining the parameter estimates for the Smooth Transition Autoregressive-Generalized Autoregressive Conditional Heteroskedasticity (STAR-GARCH) can be problematic due to computational difficulties. Conventional optimization algorithms do not seem to perform well in locating the global optimum of the associated likelihood function. This makes Quasi-Maximum Likelihood Estimator (QMLE) difficult to obtain for STAR-GARCH models in practice. Curiously, there has been very little research investigating the cause of the numerical difficulties in obtaining the parameter estimates for STAR-GARCH using QMLE. The aim of the paper is to investigate the nature of the numerical difficulties using Monte Carlo Simulation. By examining the surface of the log-likelihood function based on simulated data, the results provide several insights into the difficulties in obtaining QMLE for STAR-GARCH models. Based on the findings, the paper also proposes a simple transformation on the parameters to alleviate these difficulties. Monte Carlo simulation results show promising signs for the proposed transform. The asymptotic and robust variance-covariance matrices of the original parameter estimates are derived as a function of the transformed parameter estimates, which greatly facilitates inferences on the original parameters.     

Convolutional Sparse Coding for High Dynamic Range Imaging

Current HDR acquisition techniques are based on either (i) fusing multibracketed, low dynamic range (LDR) images, (ii) modifying existing hardware and capturing different exposures simultaneously with multiple sensors, or (iii) reconstructing a single image with spatially‐varying pixel exposures. In this paper, we propose a novel algorithm to recover high‐quality HDRI images from a single, coded exposure. The proposed reconstruction method builds on recently‐introduced ideas of convolutional sparse coding (CSC); this paper demonstrates how to make CSC practical for HDR imaging. We demonstrate that the proposed algorithm achieves higher‐quality reconstructions than alternative methods, we evaluate optical coding schemes, analyze algorithmic parameters, and build a prototype coded HDR camera that demonstrates the utility of convolutional sparse HDRI coding with a custom hardware platform.     

Semantic-based authorization architecture for Grid

There are a few issues that still need to be covered regarding security in the Grid area. One of them is authorization where there exist good solutions to define, manage and enforce authorization policies in Grid scenarios. However, these solutions usually do not provide Grid administrators with semantic-aware components closer to the particular Grid domain and easing different administration tasks such as conflict detection or resolution. This paper defines a proposal based on Semantic Web to define, manage and enforce security policies in a Grid scenario. These policies are defined by means of semantic-aware rules which help the administrator to create higher-level definitions with more expressiveness. These rules also permit performing added-value tasks such as conflict detection and resolution, which can be of interest in medium and large scale scenarios where different administrators define the authorization rules that should be followed before accessing a resource in the Grid. The proposed solution has been also tested providing some reasonable response times in the authorization decision process.