Achieving dynamicity in security policies enforcement using aspects

The dynamic configuration and evolution of large-scale heterogeneous systems has made the enforcement of security requirements one of the most critical phases throughout the system development lifecycle. In this paper, we propose a framework architecture to associate the security policies with the specification and the execution phases of applications defined for these systems. Our proposed framework is based on an aspect-oriented programming approach and on the organization-based access control model to dynamically enforce and manage the access and the usage control. The deployment of the framework modules, proposed in this paper, takes into account the changes that may occur in the security policy during the application execution. We also present the implementation as well as the evaluation of our proposition.     

Fuzzy clustering complex-valued neural network to diagnose cirrhosis disease

In this study, fuzzy clustering complex-valued neural network (FCCVNN) was proposed to classify portal vein Doppler signals recorded from 54 patients with cirrhosis and 36 healthy subjects. This proposed neural network is a new model for biomedical pattern classification. The FCCVNN was composed of three phases: fuzzy clustering, calculation of FFT values and complex-valued neural network (CVNN). In first phase, fuzzy clustering was done to reduce the number of segments in training pattern. After that, FFT values of Doppler signals were calculated for pre-processing and then obtained values, which include real and imaginary components, were used as the inputs of the CVNN for classification of Doppler signals. Classification results of FCCVNN were evaluated by the different performance evaluation criterion in literature. It shows that Doppler signals were classified successfully with 100% correct classification rate using the proposed method. Moreover, the rates of sensitivity and specificity were calculated as 100% using FCCVNN method. These results were seen to be appropriate with the expected results that are derived from physician’s direct diagnosis. This method would be assisted the physician to make the final decision.     

Enhanced thermal conductivity of nanofluids: a state-of-the-art review

Adding small particles into a fluid in cooling and heating processes is one of the methods to increase the rate of heat transfer by convection between the fluid and the surface. In the past decade, a new class of fluids called nanofluids, in which particles of size 1–100 nm with high thermal conductivity are suspended in a conventional heat transfer base fluid, have been developed. It has been shown that nanofluids containing a small amount of metallic or nonmetallic particles, such as Al₂O₃, CuO, Cu, SiO₂, TiO₂, have increased thermal conductivity compared with the thermal conductivity of the base fluid. In this work, effective thermal conductivity models of nanofluids are reviewed and comparisons between experimental findings and theoretical predictions are made. The results show that there exist significant discrepancies among the experimental data available and between the experimental findings and the theoretical model predictions.     

Computational modeling of size effects in concrete specimens under uniaxial tension

The paper presents a follow-up study of numerical modeling of complicated interplay of size effects in concrete structures. The major motivation is to identify and study interplay of several scaling lengths stemming from the material, boundary conditions and geometry. Methods of stochastic nonlinear fracture mechanics are used to model the well published results of direct tensile tests of dog-bone specimens with rotating boundary conditions. Firstly, the specimens are modeled using microplane material and also fracture-plastic material laws to show that a portion of the dependence of nominal strength on structural size can be explained deterministically. However, it is clear that more sources of size effect play a part, and we consider two of them. Namely, we model local material strength using an autocorrelated random field attempting to capture a statistical part of the combined size effect, scatter inclusive. In addition, the strength drop noticeable with small specimens which was obtained in the experiments could be explained either by the presence of a weak surface layer of constant thickness (caused e.g. by drying, surface damage, aggregate size limitation at the boundary, or other irregularities) or three dimensional effects incorporated by out-of-plane flexure of specimens. The latter effect is examined by comparison of 2D and 3D models with the same material laws. All three named sources (deterministic-energetic, statistical size effects and the weak layer effect) are believed to be the sources most contributing to the observed strength size effect; the model combining all of them is capable of reproducing the measured data. The computational approach represents a marriage of advanced computational nonlinear fracture mechanics with simulation techniques for random fields representing spatially varying material properties. Using a numerical example, we document how different sources of size effects detrimental to strength can interact and result in relatively complicated quasibrittle failure processes. The presented study documents the well known fact that the experimental determination of material parameters (needed for the rational and safe design of structures) is very complicated for quasibrittle materials such as concrete.     

Exploring bioaugmentation strategies for azo dye CI Reactive Violet 5 decolourization using bacterial mixture: dye response surface methodology

The use of response surface methodology based on statistical design of experiments is becoming increasingly widespread in several sciences such as analytical and environmental chemistry. In the present study, the decolourization and the degradation efficiency of CI Reactive Violet 5 (CIRV5) was studied using a novel bacterial consortium. CIRV5 (1000 p.p.m.) biodegradation was investigated under shaking condition in mineral salt medium solution (MSM) at a 7.5 pH and a 25°C temperature. The degradation pathways were also predicted, using UV‐visible spectroscopy analysis. Under optimal conditions, the bacterial consortium was able to decolourize the dye completely (>99%) within 8 h. The colour and chemical oxygen demand (COD) removal were 99.29 and 94.93%, respectively. Polymerase chain reaction (PCR) technique was utilized to detect the adhesin genes ‘icaA’ and ‘icaD.’ Our results showed that Staphylococcus aureus had a high decolourization capacity. Phytotoxicity study using Triticum turgidum ssp durum showed the no toxicity of the produced products.     

Multiregion level-set partitioning of synthetic aperture radar images

The purpose of this study is to investigate synthetic aperture radar (SAR) image segmentation into a given but arbitrary number of gamma homogeneous regions via active contours and level sets. The segmentation of SAR images is a difficult problem due to the presence of speckle which can be modeled as strong, multiplicative noise. The proposed algorithm consists of evolving simple closed planar curves within an explicit correspondence between the interiors of curves and regions of segmentation to minimize a criterion containing a term of conformity of data to a speckle model of noise and a term of regularization. Results are shown on both synthetic and real images.     

FPA method for optimal production planning under availability/degradation machine and subcontracting constraint

This work treats an industrial problematic of a manufacturing system M₁ subject to random failure and that satisfies a random demand under required service level. To ensure the satisfaction of the demand, it calls up on a second manufacturing system M₂ that is a subcontractor and has a stochastic service level. This paper aims to determine an optimal production plan taking into account the degradation of the manufacturing system following its production rate and its availability. The unavailability of the machine M₁ is due to the non-negligible preventive and corrective maintenance actions duration. To consider a realistic case of the subcontractor, we consider that is not able to respond to the variation of the demand, and then it assumed that the manufacturer can order a minimum fixed quantity. We then derive an optimal production plan taking into account the degradation of the machine and simultaneously minimising: inventory, degradation and production cost. An algorithm based on finite perturbation analysis is proposed to determine the optimal production plan and the sensitivity study of the availability is presented.