The synthesis of pixelated metamaterial cross polarizer using binary wind driven optimization algorithm

Microsystem Technologies - In this paper synthesis of two wideband Metamaterial Cross Polarizer (MCPs) is proposed. The synthesis of proposed MCPs is done by using Binary Wind Driven Optimization...     

Stability and electronic properties of armchair boron nitride/carbon nanotubes

In this work are studied the electronic and structural properties of armchair boron nitride/carbon nanotubes using first principles calculations. The density functional within the generalized gradient approximation (HSEh1PBE-GGA) is used. For each composition, different bonding schemes for the construction of the hybrid systems were employed. Among them, structural stability with neutral charge was determined for the following compositions: T1: B₄₀N₃₅C₇₅H₂₀, T2: B₃₅N₄₀C₇₅H₂₀, T3: B₃₇N₃₈C₇₅H₂₀, T4 : B₃₇N₃₇C₇₆H₂₀, and T7: B₃₅N₃₅C₈₀H₂₀. All these hybrid nanotubes have high polarity; the T3, T4 and T7 are semiconductors: whereas T1 and T2 are conductor in character. The formers also have magnetic behavior. These properties together with a low-chemical potential suggest applications as nano-vehicle for drug delivery. These mixed nanotubes also have potential applications in the electronic devices based on the small work function.     

Use of 3D printing for biofuel production: efficient catalyst for sustainable biodiesel production from wastes

This work deals with the sustainable biodiesel production from low-cost renewable feedstock (waste and non-edible oils) using a heterogeneous catalyst constituted by potassium loaded on an amorphous aluminum silicate naturally occurring as volcanic material (pumice). The main challenge to biodiesel production from low-quality oils (used oils and greases) is the high percentage of free fatty acids (FFAs) and water in the feedstock that causes undesirable side reactions. The catalytic materials studied were tested in the transesterification reaction when using low-quality oils containing a high proportion of free fatty acids (FFAs) and water. Results indicated that the amount of acid and basic sites on the catalytic surface increases upon increasing potassium loading in the catalyst, displaying better performance for biodiesel production. Indeed, the modification of the aluminum silicate substrate upon potassium incorporation results in a catalytic material containing both acidic and basic sites, which are responsible for both triglycerides transesterification and FFA esterification reactions. The studied catalyst not only showed good performance in the biodiesel production reaction but also good tolerance to FFA and water contained in the feedstock for biodiesel production. The catalytic material was microstructured by 3D printing in order to design a catalytic stirring system with high mechanical strength, efficient and reusable. The use of 3D printing in biofuel production is a novelty that brings good solutions for catalyst production.     

Veal colour assessment with three wavelengths

A method to derive reflectance spectra and colour coordinates of meat by measurement of reflectance at only three wavelengths, 480, 570 and 620 nm has been developed, by treating the spectra of a meat sample as a linear combination of the spectra of the three major myoglobin derivatives (reduced myoglobin, oxymyoglobin and metmyoglobin). Applied to 300 samples of Semitendinosus and Longissimus dorsi veal muscles at different times post mortem (24 h to 9 d), colour differences ΔE (?) between the derived spectra and the real ones were about 1.5 units. The total pigment content, with high correlation with the extraction method (P < 0.02), and the relative proportions of the derivatives can also be estimated.     

DEMORS: A hybrid multi-objective optimization algorithm using differential evolution and rough set theory for constrained problems

The aim of this paper is to show how the hybridization of a multi-objective evolutionary algorithm (MOEA) and a local search method based on the use of rough set theory is a viable alternative to obtain a robust algorithm able to solve difficult constrained multi-objective optimization problems at a moderate computational cost. This paper extends a previously published MOEA [Hernández-Díaz AG, Santana-Quintero LV, Coello Coello C, Caballero R, Molina J. A new proposal for multi-objective optimization using differential evolution and rough set theory. In: 2006 genetic and evolutionary computation conference (GECCO’2006). Seattle, Washington, USA: ACM Press; July 2006], which was limited to unconstrained multi-objective optimization problems. Here, the main idea is to use this sort of hybrid approach to approximate the Pareto front of a constrained multi-objective optimization problem while performing a relatively low number of fitness function evaluations. Since in real-world problems the cost of evaluating the objective functions is the most significant, our underlying assumption is that, by aiming to minimize the number of such evaluations, our MOEA can be considered efficient. As in its previous version, our hybrid approach operates in two stages: in the first one, a multi-objective version of differential evolution is used to generate an initial approximation of the Pareto front. Then, in the second stage, rough set theory is used to improve the spread and quality of this initial approximation. To assess the performance of our proposed approach, we adopt, on the one hand, a set of standard bi-objective constrained test problems and, on the other hand, a large real-world problem with eight objective functions and 160 decision variables. The first set of problems are solved performing 10,000 fitness function evaluations, which is a competitive value compared to the number of evaluations previously reported in the specialized literature for such problems. The real-world problem is solved performing 250,000 fitness function evaluations, mainly because of its high dimensionality. Our results are compared with respect to those generated by NSGA-II, which is a MOEA representative of the state-of-the-art in the area.     

Virtual wind tunnel: An alternative approach for the analysis of bridge behaviour under wind effects

The study of bridge responses under wind-induced loads is based upon full aeroelastic model testing or hybrid methods which use section model tests and subsequent computer analysis. Both methodologies present several strong points and some shortcomings, specially related with the visualization of the bridge dynamic behaviour. Nowadays, advances and improvements in computational power and computer aided design technologies make possible a new way towards the feasible design of long span bridges considering its aerodynamic and aeroelastic behaviour. The virtual wind tunnel (VWT) technique developed by the authors joins together accurate section model testing with computer aided design in order to obtain a detailed computer visualization of the complete bridge behaviour under wind flow. The results obtained for the Tacoma Narrows Bridge and the Messina Strait Bridge are presented.     

Scientometric Study of the Progress and Development of e-Government Research During the Period 2000–2012

Many countries have implemented changes in public-sector management models, based on the strategic and intensive use of new information and communication technologies. From a critical standpoint, this paper analyzes and characterizes the contributions made by research in the field of e-government, identifying future areas of interest and potentially valuable methodologies. In addition, it compares research efforts focused on developing countries with those concerning developed economies, in order to identify research gaps and possibilities for improvement in the context of e-government research in developing countries. Diverse scientometric approaches are employed in this analysis of papers published by international journals listed in the SSCI index in the fields of Public Administration and of Information Science & Library Science. Our findings reveal the existence of various research gaps and highlight areas that should be addressed in future research, especially in developing countries. Indeed, the research approach to e-government remains immature, focusing on particular cases or dimensions, while little has been done to produce theories or models to clarify and explain the political processes of e-government. In addition, significant differences are found between the impact of scientific output and patterns of scientific production as regards developing and developed countries.     

Two-space variability compensation technique for speaker verification in short length and reverberant environments

The performance of state-of-the-art speaker verification in uncontrolled environment is affected by different variabilities. Short duration variability is very common in these scenarios and causes the speaker verification performance to decrease quickly while the duration of verification utterances decreases. Linear discriminant analysis (LDA) is the most common session variability compensation algorithm, nevertheless it presents some shortcomings when trained with insufficient data. In this paper we introduce two methods for session variability compensation to deal with short-length utterances on i-vector space. The first method proposes to incorporate the short duration variability information in the within-class variance estimation process. The second proposes to compensate the session and short duration variabilities in two different spaces with LDA algorithms (2S-LDA). First, we analyzed the behavior of the within and between class scatters in the first proposed method. Then, both proposed methods are evaluated on telephone session from NIST SRE-08 for different duration of the evaluation utterances: full (average 2.5 min), 20, 15, 10 and 5 s. The 2S-LDA method obtains good results on different short-length utterances conditions in the evaluations, with a EER relative average improvement of 1.58%, compared to the best baseline (WCCN[LDA]). Finally, we applied the 2S-LDA method in speaker verification under reverberant environment, using different reverberant conditions from Reverb challenge 2013, obtaining an improvement of 8.96 and 23% under matched and mismatched reverberant conditions, respectively.     

Reliability and time‐to‐failure bounds for discrete‐time constrained Markov jump linear systems

This paper presents a methodology to obtain a guaranteed‐reliability controller for constrained linear systems, which switch between different modes according to a Markov chain (Markov jump linear systems). Inside the classical maximal robust controllable set, there is 100% guarantee of never violating constraints at future time. However, outside such set, some sequences might make hitting constraints unavoidable for some disturbance realisations. A guaranteed‐reliability controller based on a greedy heuristic approach was proposed in an earlier work for disturbance‐free, robustly stabilisable Markov jump linear systems. Here, extensions are presented by, first, considering bounded disturbances and, second, presenting an iterative algorithm based on dynamic programming. In non‐stabilisable systems, reliability is zero; therefore, prior results cannot be applied; in this case, optimisation of a mean‐time‐to‐failure bound is proposed, via minor algorithm modifications. Optimality can be proved in the disturbance‐free, finitely generated case. Copyright © 2016 John Wiley & Sons, Ltd.