Micro‐modeling of porous composite anodes for solid oxide fuel cells

A new anode micromodel for solid oxide fuel cells to predict the electrochemical performance of hydrocarbon‐fuelled porous composite anodes with various microstructures is developed. In this model, the random packing sphere method is used to estimate the anode microstructural properties, and the complex interdependency among the multicomponent mass transport, electron and ion transports, and electrochemical and chemical reactions is taken into account. As a case study, a porous Ni–YSZ composite anode operated with biogas fuel is simulated numerically and distributions of the current density, polarization, and mole fraction and rate of flux of the fuel components along the thickness of the anode are determined. The effect of the anode microstructural variables including the porosity, thickness, particle‐size ratio, and particle size and volume fraction of Ni particles on the anode electrochemical performance is also studied. © 2011 American Institute of Chemical Engineers AIChE J, 58: 1893–1906, 2012     

Investigating the effect of PGA on physical and mechanical properties of electrospun PCL/PGA blend nanofibers

In the field of tissue engineering there is always a need for new engineered polymeric biomaterials which have ideal properties and functional customization. Unfortunately the demands for many biomedical applications need a set of properties that no polymers can fulfill. One method to satisfy these demands and providing desirable new biomaterials is by mixing two or more polymers. In this work, random nanofibrous blends of poly (ε‐caprolactone) (PCL) and polyglycolic acid (PGA) with various PCL/PGA compositions (100/0, 80/20, 65/35, 50/50, and 0/100) were fabricated by electrospinning method and characterized for soft‐tissue engineering applications. Physical, chemical, thermal, and mechanical properties of PCL/PGA blend nanofibers were measured by scanning electron microscopy (SEM), porosimetry, contact angle measurement, water uptake, attenuated total reflectance Fourier transform‐infrared spectroscopy (ATR‐FT‐IR), X‐ray diffraction (XRD), differential scanning calorimetric (DSC), dynamic mechanical thermal analysis (DMTA), and tensile measurements. Morphological characterization showed that the addition of PGA to PCL results in an increase in the average diameter of the nanofibers. According to these results, when the amount of PGA in the blend solution increased, the hydrophilicity and water uptake of the nanofibrous scaffolds increased concurrently, approaching those of PGA nanofibers. Differential scanning calorimetric studies showed that the PCL and PGA were miscible in the nanofibrous structure and the mechanical characterization under dry conditions showed that increasing PGA content results in a tremendous increase in the mechanical properties. In conclusion, the random nanofibrous PCL/PGA scaffold used in this study constitutes a promising material for soft‐tissue engineering. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Preparation and characterization of polyurethane/silica aerogel nanocomposite materials

In this investigation, silica aerogel (SA)/Rigid Polyurethane (PUR) foam composites and silica aerogel/Polyurethane (PU) composites were prepared by dry mixing of granular and grinded silica aerogels with polyol part. They were then combined with diisocyanate part. Three different types of PUR foams and an elastomeric coating grade of PU were studied as well. Results show that thermal conductivity of foams did not decrease by adding silica aerogel. It even increased for some grades which is assumed to be due to the change in cell configuration of these foams. It was also found that sound insulation performance of these cellular composites did not improve significantly. Unlike foam composites, addition of silica aerogel into elastomeric PU improved its thermal and acoustic insulation properties. Because of the more promising properties of elastomeric PU composites, further examinations including measurements of compression strength and water contact angle of silica aerogel/PU composites were also taken. Final results showed a significant improvement in general properties of PU coatings by adding little amounts of silica aerogel (1–4 wt %). © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44521.     

Symmetric deformable image registration via optimization of information theoretic measures

The use of information theoretic measures (ITMs) has been steadily growing in image processing, bioinformatics, and pattern classification. Although the ITMs have been extensively used in rigid and affine registration of multi-modal images, their computation and accuracy are critical issues in deformable image registration. Three important aspects of using ITMs in multi-modal deformable image registration are considered in this paper: computation, inverse consistency, and accuracy; a symmetric formulation of the deformable image registration problem through the computation of derivatives and resampling on both source and target images, and sufficient criteria for inverse consistency are presented for the purpose of achieving more accurate registration. The techniques of estimating ITMs are examined and analytical derivatives are derived for carrying out the optimization in a computationally efficient manner. ITMs based on Shannon’s and Renyi’s definitions are considered and compared. The obtained evaluation results via registration functions, and controlled deformable registration of multi-modal digital brain phantom and in vivo magnetic resonance brain images show the improved accuracy and efficiency of the developed formulation. The results also indicate that despite the recent favorable studies towards the use of ITMs based on Renyi’s definitions, these measures are seen not to provide improvements in this type of deformable registration as compared to ITMs based on Shannon’s definitions.     

Coupled eagle strategy and differential evolution for unconstrained and constrained global optimization

The performance of an optimization tool is largely determined by the efficiency of the search algorithm used in the process. The fundamental nature of a search algorithm will essentially determine its search efficiency and thus the types of problems it can solve. Modern metaheuristic algorithms are generally more suitable for global optimization. This paper carries out extensive global optimization of unconstrained and constrained problems using the recently developed eagle strategy by Yang and Deb in combination with the efficient differential evolution. After a detailed formulation and explanation of its implementation, the proposed algorithm is first verified using twenty unconstrained optimization problems or benchmarks. For the validation against constrained problems, this algorithm is subsequently applied to thirteen classical benchmarks and three benchmark engineering problems reported in the engineering literature. The performance of the proposed algorithm is further compared with various, state-of-the-art algorithms in the area. The optimal solutions obtained in this study are better than the best solutions obtained by the existing methods. The unique search features used in the proposed algorithm are analyzed, and their implications for future research are also discussed in detail.     

Comparison of multiwavelet, wavelet, Haralick, and shape features for microcalcification classification in mammograms

We present an evaluation and comparison of the performance of four different texture and shape feature extraction methods for classification of benign and malignant microcalcifications in mammograms. For 103 regions containing microcalcification clusters, texture and shape features were extracted using four approaches: conventional shape quantifiers; co-occurrence-based method of Haralick; wavelet transformations; and multi-wavelet transformations. For each set of features, most discriminating features and their optimal weights were found using real-valued and binary genetic algorithms (GA) utilizing a k-nearest-neighbor classifier and a malignancy criterion for generating ROC curves for measuring the performance. The best set of features generated areas under the ROC curve ranging from 0.84 to 0.89 when using real-valued GA and from 0.83 to 0.88 when using binary GA. The multi-wavelet method outperformed the other three methods, and the conventional shape features were superior to the wavelet and Haralick features.     

Stealing PINs via mobile sensors: actual risk versus user perception

In this paper, we present the actual risks of stealing user PINs by using mobile sensors versus the perceived risks by users. First, we propose PINlogger.js which is a JavaScript-based side channel attack revealing user PINs on an Android mobile phone. In this attack, once the user visits a website controlled by an attacker, the JavaScript code embedded in the web page starts listening to the motion and orientation sensor streams without needing any permission from the user. By analysing these streams, it infers the user’s PIN using an artificial neural network. Based on a test set of fifty 4-digit PINs, PINlogger.js is able to correctly identify PINs in the first attempt with a success rate of 74% which increases to 86 and 94% in the second and third attempts, respectively. The high success rates of stealing user PINs on mobile devices via JavaScript indicate a serious threat to user security. With the technical understanding of the information leakage caused by mobile phone sensors, we then study users’ perception of the risks associated with these sensors. We design user studies to measure the general familiarity with different sensors and their functionality, and to investigate how concerned users are about their PIN being discovered by an app that has access to all these sensors. Our studies show that there is significant disparity between the actual and perceived levels of threat with regard to the compromise of the user PIN. We confirm our results by interviewing our participants using two different approaches, within-subject and between-subject, and compare the results. We discuss how this observation, along with other factors, renders many academic and industry solutions ineffective in preventing such side channel attacks.     

Chaotic imperialist competitive algorithm for optimum design of truss structures

The imperialist competitive algorithm is a new socio-politically motivated optimization algorithm which recently is applied for structural problems. This paper utilizes the idea of using chaotic systems instead of random processes in the imperialist competitive algorithm. The resulting method is called chaotic imperialist competitive algorithm (CICA) in which chaotic maps are utilized to improve the movement step of the algorithm. Some well-studied truss structures are chosen to evaluate the efficiency of the new algorithm.