A four-bias three-layer graphene-based THz absorber

Wave absorbers are considered to be fundamental building blocks for the manipulation of light. Almost all optical systems exploit absorbers to realize some functions. A highly tunable wide-band THz absorber is presented herein. Utilizing a dual-bias scheme with a single graphene layer leads to greater freedom to control the absorption response, while a conventional periodic array of graphene ribbons and a layer of graphene sheet are also exploited. Also, a circuit model representation for all the constituent parts of the proposed absorber is developed with an evolved design methodology. According to the simulation results, wide-band absorption from 3.5 to 6 THz is achieved.

     

Extracting Optimal Policies of Hydropower Multi-Reservoir Systems Utilizing Enhanced Differential Evolution Algorithm

Deriving the optimal policies of hydropower multi-reservoir systems is a nonlinear and high-dimensional problem which makes it difficult to achieve the global or near global optimal solution. In order to optimally solve the problem effectively, development of optimization methods with the purpose of optimizing reservoir operation is indispensable as well as inevitable. This paper introduces an enhanced differential evolution (EDE) algorithm to enhance the exploration and exploitation abilities of the original differential evolution (DE) algorithm. The EDE algorithm is first applied to minimize two benchmark functions (Ackley and Shifted Schwefel). In addition, a real world two-reservoir hydropower optimization problem and a large scale benchmark problem, namely ten-reservoir problem, were considered to indicate the effectiveness of the EDE. The performance of the EDE was compared with the original DE to solve the three optimization problems. The results demonstrate that the EDE would have a powerful global ability and faster convergence than the original DE to solve the two benchmark functions. In the 10-reservoir optimization problem, the EDE proved to be much more functional to reach optimal or near optimal solution and to be effective in terms of convergence rate, standard deviation, the best, average and worst values of objective function than the original DE. Also, In the case of two-reservoir system, the best values of the objective function obtained 93.86 and 101.09 for EDE and DE respectively. Based on the results, it can be stated that the most important reason to improve the performance of the EDE algorithm is the promotion of local and global search abilities of the DE algorithm using the number of novel operators. Also, the results of these three problems corroborated the superior performance, the high efficiency and robustness of the EDE to optimize complex and large scale multi-reservoir operation problems.     

On the stability issues of switched singular time‐delay systems with slow switching based on average dwell‐time

The issue of exponential stability analysis of continuous‐time switched singular systems consisting of a family of stable and unstable subsystems with time‐varying delay is investigated in this paper. It is very difficult to analyze the stability of such systems because of the existence of time‐delay and unstable subsystems. In this regard, on the basis of the free‐weighting matrix approach, by constructing the new Lyapunov‐like Krasovskii functional, and using the average dwell‐time approach, delay‐dependent sufficient conditions are derived and formulated in terms of LMIs to check the exponential stability of such systems. This paper also highlights the relationship between the average dwell‐time of the switched singular time‐delay system, its stability, exponential convergence rate of differential states, and algebraic states. Finally, a numerical example is given to confirm the analytical results and illustrate the effectiveness of the proposed strategy. Copyright © 2012 John Wiley & Sons, Ltd.     

Safe Autonomous Agent Formation Operations Via Obstacle Collision Avoidance

In this paper, we consider the problem of flocking and shape‐orientation control of multi‐agent systems with inter‐agent and obstacle collision avoidance. We first consider the problem of forcing a set of autonomous agents to form a desired formation shape and orientation while avoiding inter‐agent collision and collision with convex obstacles, and following a trajectory known to only one of the agents, namely the leader of the formation. Then we build upon the solution given to this problem and solve the problem of guaranteeing obstacle collision avoidance by changing the size and the orientation of the formation. Changing the size and the orientation of the formation is helpful when the agents want to go through a narrow passage while the existing size or orientation of the formation does not allow this. We also propose collision avoidance algorithms that temporarily change the shape of the formation to avoid collision with stationary or moving nonconvex obstacles. Simulation results are presented to show the performance of the proposed control laws.     

Short‐Time Linear Quadratic Form Technique for Estimating Fast‐Varying Parameters in Feedback Loops

The precision of a closed‐loop controller system designed for an uncertain plant depends strongly upon the maximum extent to which it is possible to track the trend of time‐varying parameters of the plant. The aim of this study is to describe a new parameter estimation algorithm that is able to follow fast‐varying parameters in closed‐loop systems. The short‐time linear quadratic form (STLQF) estimation algorithm introduced in this paper is a technique for tracking time‐varying parameters based on short‐time analysis of the regressing variables in order to minimize locally a linear quadratic form cost function. The established cost function produces a linear combination of errors with several delays. To meet this objective, mathematical development of the STLQF estimation algorithm is described. To implement the STLQF algorithm, the algorithm is applied to a planar mobile robot with fast‐varying parameters of inertia and viscous and coulomb frictions. Next, performance of the proposed algorithm is assessed against noise effects and variation in the type of parameters.     

A single-phase p-type ac–ac converter with reduced components count and high boost factor

This paper proposes a new single-phase direct step-up ac–ac converter by modifying the p-type impedance source. It provides a high boost factor as well as high efficiency, while only six parts are required to design it, involving just two bidirectional power switches. A safe commutation method has been applied to power switches to make the converter snubber-free and high efficient. Input and output harmonic filters are no longer required since input and output currents variate continuously with small ripple and low total harmonic distortion (THD). The proposed topology only modulates the output voltage amplitude, not the phase and frequency, so the output frequency is identical to the input frequency and constant. Thus, it can be utilized in step-up conversion applications, like inductive power transmission from low ac voltage sources. Input and output have the same ground, which is a good protective feature. In this paper, the operating principle of the converter is demonstrated. Experimental results have been represented to evaluate the performance of the converter. For this purpose, an experimental prototype has been fabricated. Results are investigated and compared with other previous step-up ac–ac converters. Results confirm the theory, operating principle, and performance of the converter.     

Evaluation of antifungal effect of iron‐oxide nanoparticles against different Candida species

Iron‐oxide nanoparticles (IONPs) have been widely favoured due to their biodegradable, low cytotoxic effects and having reactive surface which can be altered with biocompatible coatings. Considering various medical applications of IONPs, the authors were encouraged to study whether IONPs could be effective against fungal infections caused by Candida species. In this study, IONPs were characterised by scanning electron microscopy, X‐ray diffraction, Fourier transform infrared spectroscopy and vibrating sample magnetometer. The goal of this study was to evaluate the antifungal activity of IONPs against different Candida spp. compared with fluconazole (FLC). IONPs were spherical with the size of 30–40 nm. The minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) values of IONPs ranged from 62.5 to 500 µg/ml and 500 to 1000 μg/ml, respectively. The MIC and MFC of FLC were in range of 16–128 μg/ml and 64–512 μg/ml, respectively. The growth inhibition value indicated that Candida tropicalis, Candida albicans and Candida glabrata spp. were most susceptible to IONPs. The finding showed that the IONPs possessed antifungal potential against pathogenic Candida spp. and could inhibit the growth of all the tested Candida spp. Further studies, both in vitro and in vivo (including susceptibility, toxicity, Probability of kill (PK) and efficacy studies) are needed to determine whether IONPs are suitable for medicinal purposes.Inspec keywords: iron compounds, nanoparticles, nanomedicine, biomedical materials, microorganisms, cellular biophysics, toxicology, drugs, scanning electron microscopy, X‐ray diffraction, Fourier transform infrared spectraOther keywords: antifungal effect, iron‐oxide nanoparticles, Candida species, biodegradable effects, cytotoxic effects, reactive surface, biocompatible coatings, medical applications, IONP, fungal infections, Candidiasis, immunocompromised hosts, antifungal drugs, resistant organisms, antifungal properties, side effects, chemical drugs, scanning electron microscopy, X‐ray diffraction, Fourier transform infrared spectroscopy, vibrating sample magnetometer, antifungal activity, disc diffusion, broth microdilution, minimal inhibitory concentration, minimum fungicidal concentration, Candida tropicalis, Candida Albicans, Candida glabrata, antifungal potential, Fe₃ O₄      

Estimation of magnitude and time duration of temporary overvoltages using ANN in transmission lines during power system restoration

In most countries, the main step in the process of power system restoration, following a complete/partial blackout, is energization of primary restorative transmission lines. Artificial neural network (ANN) is employed for performing a nonlinear input–output mapping in this work, in order to estimate the temporary overvoltages (TOVs) due to transmission lines energization. In the proposed methodology, Levenberg–Marquardt second order method is used to train the multilayer perceptron. Proposed ANN is trained with equivalent circuit parameters of the network as input parameters, trained ANN has therefore satisfactory generalization capability. Both single and three-phase line energizations are analyzed. The simulated results for 39-bus New England test system, indicate that the proposed technique can estimate the peak values and duration of switching overvoltages with acceptable accuracy.     

Scatter search technique for exam timetabling

At universities where students enjoy flexibility in selecting courses, the Registrar’s office aims to generate an appropriate exam timetable for numerous courses and large number of students. An appropriate, real-world exam timetable should show fairness towards all students, respecting the following constraints: (a) eliminating or minimizing the number of simultaneous exams; (b) minimizing the number of consecutive exams; (c) minimizing the number of students with two or three exams per day (d) eliminating the possibility of more than three exams per day (e) exams should fit in rooms with predefined capacity; and (f) the number of exam periods is limited. These constraints are conflicting, which makes exam timetabling intractable. Hence, solving this problem in realistic time requires the use of heuristic approaches. In this work, we develop an evolutionary heuristic technique based on the scatter search approach for finding good suboptimal solutions for exam timetabling. This approach is based on maintaining and evolving a population of solutions. We evaluate our suggested technique on real-world university data and compare our results with the registrar’s manual timetable in addition to the timetables of other heuristic optimization algorithms. The experimental results show that our adapted scatter search technique generates better timetables than those produced by the registrar, manually, and by other meta-heuristics.