Fuzzy reliability analysis of nanocomposite ZnO beams using hybrid analytical-intelligent method

A hybrid analytical-intelligent approach is proposed for fuzzy reliability analysis of the composite beams reinforced by zinc oxide (ZnO) nanoparticle. The fuzzy reliability index corresponding to buckling failure mode of nanocomposite beam under thickness-direction external voltage is computed based on three-levels: (1) fuzzy analysis, (2) reliability analysis and (3) analytical buckling analysis. In fuzzy analysis level, an improved gravitational search algorithm has been applied to determine uncertainty interval for membership levels of reliability index. The adaptive formulation with a dynamical self-adjusting process is used for reliability analysis level based on conjugate first-order reliability method (FORM). The self-adjusting term in conjugate sensitivity vector is used to satisfy the sufficient descent condition for controlling instability of FORM formula while the proposed conjugate scalar factor is computed less than the original conjugate FORM, thus it may be provided with the efficient results for the convex problem. The new and previous sensitivity vectors obtained by conjugate and steepest descent vectors dynamically adjusted the proposed conjugate factor. In the buckling analysis level, an exponential theory in conjunction with the method of energy is utilized. Fuzzy random variables including applied voltage, the volume fraction of ZnO, thickness of beam, spring constant and shear constant of the foundation are considered in studied nanocomposite beam. Survey results indicated that the proposed method can provide stable and acceptable fuzzy membership functions for parametric study. Moreover, the ratio of length to thickness and spring constant of foundation are the more sensitive parameters which affect fuzzy reliability index significantly.

     

Use of surface modified recycled rubber particles for toughening of epoxy polymers

The objective of this research is to investigate the feasibility of using surface treated recycled rubber particles for toughening of epoxy polymers. These particles are obtained through grinding of scrap tires followed by oxidizing the surface of the particles in a reactive gas atmosphere. Surface treated recycled rubber particles with a nominal particle size of approximately 75 μm and a commonly used reactive liquid elastomer, CTBN, have been incorporated in a DGEBA epoxy resin. It has been shown that the recycled rubber particles are not as effective as CTBN in toughening of the epoxy matrix. However, blending of the two modifiers results in a synergistic toughening. Microscopy reveals that, when used alone, recycled rubber particles simply act as large stress concentrators and modestly contribute to toughening via crack deflection and microcracking. In the presence of micron size CTBN particles, which cavitate and induce massive shear yielding in the matrix, however, the recycled particles “stretch” the plastic deformation to distances far from the crack tip. This mechanism causes plastic zone branching and provides an unexpectedly high fracture toughness value. This study, therefore, provides a practical approach for manufacturing engineering polymer blends utilizing the surface modified recycled rubber particles.     

Characterization of minocycline loaded chitosan/polyethylene glycol/glycerol blend films as antibacterial wound dressings

Wound care has been a challenging subject for medical teams and researchers. Bacterial infections are one of the most serious complications in injured skins that often affect healing process. Antibacterial wound dressings can be used to facilitate wound healing process. The purpose of this study is to fabricate chitosan (Chito)/polyethylene glycol (PEG) antibacterial wound dressing doped with minocycline, and to evaluate the influence of composition ratio on the blending properties of the films. To improve the mechanical properties of these films, we examined various amounts of glycerol as a plasticizer. Moreover, we investigated morphological and mechanical aspects, water uptake, degradation, water vapor transmission and wettability properties of the films prepared with various ratios of Chito/PEG/Gly. Assessment of mechanical properties revealed that film containing 80:20 ratio Chito/PEG with 40 PHR Gly content exhibits the highest ultimate tensile strength and elongation at break (9.74 MPa and 45.73% respectively). Furthermore, results demonstrated that upon increasing PEG and Gly contents, degradability and hydrophilicity of the films increased whereas water uptake decreased. Water vapor transmission rate of the films was close to the range of 530–1200 g/m²d, indicating that the as formed films are possible candidates for dressing low exudate wounds or burns. Minocycline loaded films exhibited a biphasic drug release profile and it was more effective on gram-positive bacteria than on gram-negative bacteria. The polymeric film with the highest amount of loaded drug (2%) exhibited insignificant cytotoxicity (88%) against normal fibroblast cell line.     

Symbiotic artificial immune system

Artificial Immune System algorithms use antibodies that fully specify the solution of an optimization, learning, or pattern recognition problem. By being restricted to fully specified antibodies, an AIS algorithm cannot make use of schemata or classes of partial solutions, while sub solutions can help a lot in faster emergence of a totally good solution in many problems. To exploit schemata in artificial immune systems, this paper presents a novel algorithm that combines traditional artificial immune systems and symbiotic combination operator. The algorithm starts searching with partially specified antibodies and gradually builds more and more specified solutions till it finds complete answers. The algorithm is compared with CLONALG algorithm on several multimodal function optimization and combinatorial optimization problems and it is shown that it is faster than CLONALG on most problems and can find solutions in problems that CLONALG totally fails.     

ConsilientSFL: using preferential voting system to generate combinatorial ranking metrics for spectrum-based fault localization

Spectrum-based fault localization (SFL) techniques have shown considerable effectiveness in localizing software faults. They leverage a ranking metric to automatically assign suspiciousness scores to certain entities in a given faulty program. However, for some programs, the current SFL ranking metrics lose effectiveness. In this paper, we introduce ConsilientSFL that is served to synthesize a new ranking metric for a given program, based on a customized combination of a set of given ranking metrics. ConsilientSFL can be significant since it demonstrates the usage of voting systems into a software engineering task. First, several mutated, faulty versions are generated for a program. Then, the mutated versions are executed with the test data. Next, the effectiveness of each existing ranking metric is computed for each mutated version. After that, for each mutated version, the computed existing metrics are ranked using a preferential voting system. Consequently, several top metrics are chosen based on their ranks across all mutated versions. Finally, the chosen ranking metrics are normalized and synthesized, yielding a new ranking metric. To evaluate ConsilientSFL, we have conducted experiments on 27 subject programs from Code4Bench and Siemens benchmarks. In the experiments, we found that ConsilientSFL outperformed every single ranking metric. In particular, for all programs on average, we have found performance measures recall, precision, f-measure, and percentage of code inspection, to be nearly 7, 9, 12, and 5 percentages larger than using single metrics, respectively. The impact of this work is twofold. First, it can mitigate the issue with the choice and usage of a proper ranking metric for the faulty program at hand. Second, it can help debuggers find more faults with less time and effort, yielding higher quality software.

     

UML-CI: A reference model for profiling critical infrastructure systems

The study of critical infrastructure systems organization and behavior has drawn great attention in the recent years. This is in part due to their great influence on the ordinary life of every citizen. In this paper, we study critical infrastructures’ characteristics and propose a reference model based on the Unified Modeling Language (UML). This reference model attempts to provide suitable means for the task of modeling an infrastructure system through offering five major metamodels. We introduce each of these metamodels and explain how it is possible to integrate them into a unique representation to characterize various aspects of an infrastructure system. Based on the metamodels of UML-CI, infrastructure system knowledge bases can be built to aid the process of infrastructure system modeling, profiling, and management.     

Multiresolution HVS and statistically based image coding scheme

In this paper a novel multiresolution human visual system and statistically based image coding scheme is presented. It decorrelates the input image into a number of subbands using a lifting based wavelet transform. The codec employs a novel statistical encoding algorithm to code the coefficients in the detail subbands. Perceptual weights are applied to regulate the threshold value of each detail subband that is required in the statistical encoding process. The baseband coefficients are losslessly coded. An extension of the codec to the progressive transmission of images is also developed. To evaluate the performance of the coding scheme, it was applied to a number of test images and its performance with and without perceptual weights is evaluated. The results indicate significant improvement in both subjective and objective quality of the reconstructed images when perceptual weights are employed. The performance of the proposed technique was also compared to JPEG and JPEG2000. The results show that the proposed coding scheme outperforms both coding standards at low compression ratios, while offering satisfactory performance at higher compression ratios.     

On the coupled dynamics of small spacecraft and elastic deployable appendages

A thorough investigation of the dynamics of finite-mass satellites with a deployable elastic arm is presented. This work is focused on the interaction between spacecraft rigid body motion and its flexible arm dynamics during the deployment process. The classical Newton–Euler formulation and the Lagrangian approach are applied to the study of the dynamics of spacecraft and its deploying arm. Utilizing a non-Newtonian floating frame to define the arm elastic deformation field, the interactions between the spacecraft and its moving arm have been simulated. Complete equations of motion show that the spacecraft motion induces dynamical stiffness on the arm; in addition, axial and lateral motions of the deploying elastic arm change the spacecraft mass-characteristics and thus influence the spacecraft’s rigid body motions. The overall dynamic behavior is highly dependent on spacecraft mass characteristics in addition to the “arm deployment time (ADT)”. The results of case studies clearly indicate that some assumptions previously applied in appendage dynamic analysis are not conservative and produce erroneous results. This study realistically investigates the dynamics of elastic deploying appendages by considering finite-mass characteristics for small and massy spacecraft. The results reveal that for massive spacecraft the arm’s flexible dynamics is mainly excited through deployment, while for small spacecraft the energy transfers to the arm base and the spacecraft rigid body motion is considerably stimulated. Moreover, this work has further highlighted the effects of ADT in the overall system response. The findings of this work show that the energy distribution between arm’s elastic dynamics and spacecraft rigid body motions is an important factor in the design of any control system to limit unwanted arm-tip motions.     

Preparation and study of a thermo-responsive membrane using binary liquid crystal mixtures of cholesteryl cetyl ether and cholesteryl oleyl carbonate

A facile method for the synthesis of thermotropic liquid crystalline cholesteryl cetyl ether (CCE) was carried out from cholesterol and cetyl alcohol using montmorillonite K-10 as an acid catalyst. The aim of this study was to investigate the use of liquid crystalline blends of CCE and cholesteryl oleyl carbonate (COC) with appropriate crystal to smectic phase temperature (T _c?Cs) just above body temperature as a temperature-modulated drug permeation system. Using 30/70?mol ratio of COC/CCE, a mixture of desirable phase transition temperature was obtained. The phase transition behavior of COC/CCE binary liquid crystalline mixture was established by differential scanning calorimetry and polarizing optical microsopy. The COC/CCE-embedded cellulose nitrate membrane was used by an in vitro drug penetration studies. Paracetamol and mesalazine were chosen as hydrophobic and hydrophilic drug models, respectively. Paracetamol permeability through the membrane was higher at temperatures above the phase transition of liquid crystal (LC) blends (39?°C) than its permeability below the phase transition temperature of liquid crystal blends (30?°C). The drug penetration through LC-embedded cellulose membrane was influenced by the pore size of the membrane and therefore the adsorbed amount of LC. There was no penetration of mesalazine through that membrane presumably, due to the differences in hydrophilicity of LC-embedded membrane and permeated drug.