GCS of a class of chaotic dynamic systems with controller gain variations

In this paper, guaranteed cost synchronization (GCS) problem for chaotic dynamic systems with uncertainty in the controller is investigated. Based on the Lyapunov stability theory and LMI (linear matrix inequality) technique, two criteria for the existence of the nonfragile controller for GCS are obtained in terms of LMIs such that the closed-loop error system becomes asymptotically stable and suitable level of performance is guaranteed. Numerical simulation illustrates the feasibility of the proposed control scheme.     

Channel characterization of time reversal UWB communication systems

An ultra wideband (UWB) communications system that applies time reversal to transmit the desired signal is investigated. Exact expressions for the first- and second-order moments, cross-correlation, intersymbol interference metric, and correlation coefficient of time reversal (TR) UWB equivalent channel are derived in terms of the physical channel parameters such as delay spread and mean excess delay. These expressions are verified by simulated and experimental results. It is shown that TR-UWB excess delay is very smaller than UWB and its delay spread decreases as signaling bandwidth increases. Semi-analytical results show that the time reversal UWB delay spread is approximately the same as UWB. Furthermore, an ISI metric is derived for TR-UWB channel based on transmitted signal and UWB channel parameters. Moreover, correlation coefficient of two TR-UWB received signals with different power delay profile is computed analytically. Simulation and analytical results show that for τ?>?0.3T _w correlation coefficient is below 0.25 and for τ?>?T _w correlation coefficient is zero, where T _w is the transmitted pulse width. Finally, theoretical performance of a receiver with one tap matched filter is computed and compared with measured and simulated result.     

Experimental and Numerical Study of the Key Non-Dimensional Geometrical Parameters on the Noise Level of Dry-Type Cast Resin Transformers

Dry-Type Cast Resin Distribution Transformers (CRT) is the secondgeneration of air-cooled distribution transformers where oil is replaced by resin for electrical insulation. CRT transformers may installed indoor adjacent to or near residential areas since they are clean and safe comparing to the conventional transformers. But, as it is obvious, noise discrepancy is intrinsically accompanied with all types of transformers and is inevitable for CRT transformers too. Minimization of noise level caused by such these transformers has biological and ergonomic importance. As it is known the core of transformers is the main source of the noise generation. In this paper, experimental and numerical investigation is implemented for a large number of fabricated CRT transformers in IT Co (Iran Transfo Company) to evaluate the effective geometrical parameters of the core on the overall sound level of transformers. Noise Level of each sample is measured according to criteria of IEC60651 and is reported in units of Decibel (dB). Numerical simulation is done using noncommercial version of ANSYS Workbench software to extract first six natural frequencies and mode shapes of CRT cores which is reported in units of Hz. Three novel non-dimensional variables for geometry of the transformer core are introduced. Both experimental and numerical results show approximately similar response to these variables. Correlation between natural frequencies and noise level is evaluated statistically. Pearson factor shows that there is a robust conjunction between first two natural frequencies and noise level of CRTs. Results show that noise level decreases as the two first natural frequencies increases and vice versa, noise level increases as the two natural frequencies of the core decreases. Finally the noise level decomposed to two parts.     

Finite Order Batalin-Fradkin-Tyutin Method for Chiral Bosons in Non- Commutative Space

The recently improved finite order BFT Hamiltonian embedding method is applied to the two dimensional chiral bosons in non-commutative space. It is then systematically converted to a first class constraint model. Performing the momentum integrations, the corresponding fully gauge symmetry Lagrangian as well as its partition function in phase space are obtained.     

Diffusioosmotic flow in rectangular microchannels

The diffusioosmosis of an electrolyte solution inside a uniformly charged rectangular channel at steady locally developed conditions is the subject of this study. Utilizing a finite element based numerical procedure, we try to estimate the errors incurred by modeling the actual rectangular geometry of typical microchannels as a slit. We demonstrate that the flow pattern and direction are generally dependent upon the width‐to‐height ratio of the channel. Such a finding, besides showing the ineffectiveness of the slit geometry in representing a rectangular channel of small aspect ratio, informs us of another mechanism of controlling the diffusioosmotic flow. Inspections of the mean velocity reveal that, although it drastically grows by increasing the aspect ratio at smaller values of this parameter, no significant change is observed when the aspect ratio is 5 or higher. The same trend is observed when EDL is shrunk and is considered as a basis for the introduction of a slip‐like velocity, similar to the concept of the Helmholtz–Smoluchowski electroosmotic velocity, which will be of high practical importance when dealing with a micronsized channel. Because of its significance, an expression is presented for this slip velocity utilizing the curve fitting of the results, assuming a typical Peclet number.     

Synthesis of layered zinc hydroxide intercalated with dodecyl sulfate organic–inorganic hybrid nanocomposite as a fiber coating for the headspace solid‐phase microextraction of aromatic hydrocarbons from water

We describe the synthesis of a layered zinc hydroxide‐dodecyl sulfate organic–inorganic hybrid nanocomposite as a new solid‐phase microextraction fiber. The fiber coating can be prepared easily in a short time and the reaction is at room temperature; it is mechanically stable and exhibits relatively high thermal stability. The synthesized layered zinc hydroxide‐dodecyl sulfate nanocomposite was successfully prepared and immobilized on a stainless steel wire and evaluated for the extraction of aromatic compounds from aqueous sample solutions in combination with gas chromatography and mass spectrometry. The method yields good results for some validation parameters. Under optimum conditions (extraction time: 15 min, extraction temperature: 50°C, desorption time: 1 min, desorption temperature: 250°C, salt concentration: 0.5 g/mL), the limit of detection and dynamic linear range were 0.69–3.2 ng/L and 10–500 ng/L, respectively. The method was applied to the analyses of benzene, toluene, ethylbenzene, and o‐, p‐, and m‐xylenes in two real water samples collected from the Aji river and Mehran river, Tabriz, Iran. Under optimum conditions, the repeatability and reproducibility for one fiber (n = 3), expressed as the relative standard deviation, was 3.2–7.3% and 4.2–11.2% respectively. The fibers are thermally stable and yield better recoveries than conventional methods of analysis.     

Prediction of Rheological Properties of Multi-Component Dispersions by Using Artificial Neural Networks

This article shows the ability of artificial neural network (ANN) technology for predicting the correlation between rheological properties of multi-component food model systems and their chemical compositions. Multi-component food model systems were made of whey protein isolate (WPI) (2, 4 wt%), Iranian tragacanth gum (TG) (Astragalus gossypinus) (0.5, 1 wt%) and oleic acid (5, 10% v/v). The input parameters of the neural networks (NN) were these chemical compositions, namely WPI and TG concentrations, and oleic acid volume fractions. The output parameters of the NN models were rheological properties of multi-component food model systems (flow and consistency indices, viscosity, loss and storage moduli). Results showed that, ANN with training algorithm of back propagation (BP) was the best one for the creation of nonlinear mapping between input and output parameters. The best topology was 3-10-5. The ANN model predicted the rheological properties of multi-component food model systems with average RMSE 4.529 and average MAE 3.018. These results show that the ANN can potentially be used to estimate rheological parameters of multi-component food model systems from chemical composition. This development may have significant potential to improve product quality control and reduce time and costs by minimizing the rheological experiments.     

Existence and smoothness of continuous and discrete solutions of a two-dimensional shallow water problem over movable beds with nonlinear sediment transport relationship

A two-dimensional shallow water system over movable beds with nonlinear sediment transport relationship is considered in this paper. The existence of the solutions for the continuous system is proved here and their smoothness is investigated. A Galerkin method is employed to obtain a finite-dimensional problem. A Brouwer fixed point theorem is employed for this problem and it is shown that the model equations are satisfied by the limits of the resulting solution sequences.We also consider the discretized problem using a local discontinuous Galerkin scheme. We perform an error analysis and show that the method is convergent and the error is bounded according to a specific norm defined herein.     

LBAA: A novel load balancing mechanism in cloud environments using ant colony optimization and artificial bee colony algorithms

Recently, cloud computing has been recognized as an effective paradigm for offering an on-demand platform, software services, and an efficient infrastructure to cloud clients. Due to the exponential growth of cloud tasks and the rapidly increasing number of cloud users, scheduling and balancing these tasks among involved heterogeneous virtual machines becomes an Non-deterministic Polynomial hard (NP-hard) optimization problem considering significant constraints, such as high rate of resource usage, low scheduling time, and low implementation cost. Therefore, various meta-heuristic algorithms have been widely used to tackle the issue. The current paper proposes a novel load balancing mechanism using the ant colony optimization and artificial bee colony algorithms, called LBAA, which aims to balance the load division among systems in data centers. The simulation outcomes confirm that our algorithm outperforms previous works regarding response time, imbalance degree, makespan, and resource utilization up to 25%, 15%, 12%, and 10%, respectively.