Fundamental properties of reset control systems

Reset controllers are linear controllers that reset some of their states to zero when their input is zero. We are interested in their feedback connection with linear plants, and in this paper we establish fundamental closed-loop properties including stability and asymptotic tracking. This paper considers more general reset structures than previously considered, allowing for higher-order controllers and partial-state resetting. It gives a testable necessary and sufficient condition for quadratic stability and links it to both uniform bounded-input bounded-state stability and steady-state performance. Unlike previous related research, which includes the study of impulsive differential equations, our stability results require no assumptions on the evolution of reset times.     

Fast Decodable Turbo Codes

Decoding delay is an important consideration for the use of turbo codes in practical applications. We propose a new structure for turbo codes which is very suitable for parallel decoding. It is shown by union bound analysis and simulation results that the proposed system performance is comparable to that of the classical turbo codes     

Distribution of alpha 1A, alpha 1B and alpha 1E voltage-dependent calcium channel subunits in the human hippocampus and parahippocampal gyrus

The distribution of voltage-dependent calcium channel subunits in the central nervous system may provide information about the function of these channels. The present study examined the distribution of three alpha-1 subunits, alpha 1A, alpha 1B and alpha 1E, in the normal human hippocampal formation and parahippocampal gyrus using the techniques of in situ hybridization and immunocytochemistry. All three subunit mRNAs appeared to be similarly localized, with high levels of expression in the dentate granule and CA pyramidal layer. At the protein level, alpha 1A, alpha 1B and alpha 1E subunits were differentially localized. In general, alpha 1A-immunoreactivity was most intense in cell bodies and dendritic processes, including dentate granule cells, CA3 pyramidal cells and entorhinal cortex pre-alpha and pri-alpha cells. The alpha 1B antibody exhibited relatively weak staining of cell bodies but stronger staining of neuropil, especially in certain regions of high synaptic density such as the polymorphic layer of the dentate gyrus and the stratum lucidum and radiatum of the CA regions. The alpha 1E staining pattern shared features in common with both alpha 1A and alpha 1B, with strong immunoreactivity in dentate granule, CA3 pyramidal and entorhinal cortex pri-alpha cells, as well as staining of the CA3 stratum lucidum. These findings suggest regions in which particular subunits may be involved in synaptic communication. For example, comparison of alpha 1B and alpha 1E staining in the CA3 stratum lucidum with calbindin-immuno-reactivity suggested that these two calcium channels subunits may be localized presynaptically in mossy fibre terminals and therefore may be involved in neurotransmitter release from these terminals.     

Using genetic algorithm for the optimization of seismic behavior of steel planar frames with semi-rigid connections

Beam-column connections have a significant role in the results of the analysis and the design of steel frames. In this paper, a genetic algorithm has been used for the non-linear analysis and design of steel frames. For minimizing the weight of frames, while satisfying the applied constraints and restraints such as the limits of normal and combined stresses, criteria such as target displacement(s) and the number and locations of plastic hinges were used. To analyze and design the frame elements, I and box-shaped standard sections were used for beams and columns, respectively. Finally, some clues for finding optimizing semi-rigid connection stiffness values for beam-to-column connections have been obtained. The degrees of these rigidities are obtained by a genetic algorithm during the procedure of optimization in order to reach a frame with the minimum weight. SAP2000 structural analysis program was used to perform modal analysis and linear and non-linear static solutions as well as the design of the elements. A MATLAB program was written for the process of optimization. The procedure of optimization was based on a weight minimization carried out for 9 steel frames. Thus, the optimum connection stiffness could be obtained for minimizing the weight of the structure. The results show that the non-linear analysis gives less weight for short period frames with semi-rigid connections compared to those of linear ones. However, by increasing the periods of frames, much less weights are obtained in the case of non-linear analysis with semi-rigid connections.     

Release of salicylic acid through poly(vinyl alcohol)/poly(vinyl pyrrolidone) and poly(vinyl alcohol‐g‐N‐vinyl‐2‐pyrrolidone) membranes

A controlled release profile of salicylic acid (SA) for transdermal administration has been developed. Poly (vinyl alcohol) (PVA) and Poly(vinyl alcohol)/Poly(vinyl pyrrolidone) (PVP) blended preparations were used to prepare the membranes by solvent‐casting technique. The release of the drug from the membranes was evaluated at in vitro conditions. The effects of PVA/PVP (v/v) ratio, pH, SA concentration and temperature were investigated. 60/40 (v/v) PVA/PVP ratio was found to be the best ratio for the SA release. Increase in pH and temperature was observed to increase the transport of SA. Instead of blending PVA with PVP, N‐Vinyl‐2‐pyrrolidone (VP) was grafted onto the PVA and the delivery performance for SA was compared with that of the blended PVA/PVP membranes. Grafted membranes gave higher transport percentages than the blended membranes. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102:1244–1253, 2006     

An investigation of chloride-substituted Schiff bases as corrosion inhibitors for steel

Polarization and impedance measurements were performed on steel in deaerated 5% HCl solution with and without Schiff base additives within the concentration range 1 × 10⁻⁴–5 × 10⁻³ mol/dm³. The Schiff base compounds used were salicylaldimine, R, N-(2-chlorophenyl)salicyaldimine, 2Cl-R, N-(3-chlorophenyl)salicyaldimine, 3Cl-R, and N-(4-chlorophenyl)salicyaldimine, 4Cl-R. It was found that when the concentration of the inhibitors were increased the inhibitor efficiencies, η, also increased with increasing surface coverage. The results indicated that the ortho-substituted (2Cl-R) compound had the highest inhibition efficiency. All the Schiff base additives studied obeyed the Langmuir isotherm.     

Classification of brain hemorrhage computed tomography images using OzNet hybrid algorithm

Classification of brain hemorrhage computed tomography (CT) images provides a better diagnostic implementation for emergency patients. Attentively, each brain CT image must be examined by doctors. This situation is time-consuming, exhausting, and sometimes leads to making errors. Hence, we aim to find the best algorithm owing to a requirement for automatic classification of CT images to detect brain hemorrhage. In this study, we developed OzNet hybrid algorithm, which is a novel convolution neural networks (CNN) algorithm. Although OzNet achieves high classification performance, we combine it with Neighborhood Component Analysis (NCA) and many classifiers: Artificial neural networks (ANN), Adaboost, Bagging, Decision Tree, K-Nearest Neighbor (K-NN), Linear Discriminant Analysis (LDA), Naïve Bayes and Support Vector Machines (SVM). In addition, Oznet is utilized for feature extraction, where 4096 features are extracted from the fully connected layer. These features are reduced to have significant and informative features with minimum loss by NCA. Eventually, we use these classifiers to classify these significant features. Finally, experimental results display that OzNet-NCA-ANN excellent classifier model and achieves 100% accuracy with created Dataset 2 from Brain Hemorrhage CT images.     

Wavelet domain association rules for efficient texture classification

The wavelet domain association rules method is proposed for efficient texture characterization. The concept of association rules to capture the frequently occurring local intensity variation in textures. The frequency of occurrence of these local patterns within a region is used as texture features. Since texture is basically a multi-scale phenomenon, multi-resolution approaches such as wavelets, are expected to perform efficiently for texture analysis. Thus, this study proposes a new algorithm which uses the wavelet domain association rules for texture classification. Essentially, this work is an extension version of an early work of the Rushing et al. [10], [11], where the generation of intensity domain association rules generation was proposed for efficient texture characterization. The wavelet domain and the intensity domain (gray scale) association rules were generated for performance comparison purposes. As a result, Rushing et al. [10], [11] demonstrated that intensity domain association rules performs much more accurate results than those of the methods which were compared in the Rushing et al. work. Moreover, the performed experimental studies showed the effectiveness of the wavelet domain association rules than the intensity domain association rules for texture classification problem. The overall success rate is about 97%.