Synthesis and characterization of novel polyacrylate-clay sol-gel materials

Organo-functional silanes which were able to form chemical bonds with kaolinite and could also have an affinity to the materials of concern here, were studied by the sol-gel process. Polymethacrylate with trialkoxy silyl functional groups were prepared, hydrolysed and co-condensed with kaolinite. The progress of the hydrolysis, which proceeded very slowly, was followed by Karl-Fischer titration. Thermal behavior was investigated by differential thermal analysis. The extent of the reaction leading to network formation was qualitatively followed by Fourier transform-infrared spectroscopy and X-ray diffraction. Free-radical polymerization was carried out ultrasonically in the presence of a catalyst. Trimethoxy silane end-capped silane was found to be covalently bonded to kaolinite. The copolymers, with various amounts of kaolinite, were then hydrolysed and co-condensed in the presence of a catalyst to yield sol-gel materials which have a controllable combination of properties of both the polymer and kaolinite.     

Exact solution of elasto-plastic stresses in a metal-matrix composite beam of arbitrary orientation subjected to transverse loads

An analytical elasto-plastic stress analysis is presented for a metal-matrix composite beam of arbitrary orientation subjected to a single transverse force applied to the free end of the beam and a uniformly distributed load. The material is assumed to be perfectly plastic in the elasto-plastic solution. A composite consisting of stainless-steel-reinforced aluminum was produced for this work. Sample problems are given for various orientation angles. Elastic, elastoplastic and residual normal and shear stresses are calculated. The location of the elasto-plastic boundary of the beam is obtained according to the x coordinates of the beam.     

General solution of one-dimensional,time dependent coupled heat flow systems

A new, powerful method of analysis, involving the combined use of finite integral transform and finite element techniques, is presented for the solution of time dependent heat flow systems composed of many one-dimensional elements connected through the nodes. This method leads to an eigenvalue problem which is not of the conventional Sturm-Liouville type. A procedure for the determination of the eigenvalues is described. The solution obtained is in the form of an infinite series and contains quasi-steady and transient terms. The general solution obtained can be applied in the mathematical modelling of many engineering applications such as the determination of the penetration of the daily temperature cycle into buildings, the analysis of heat transfer in array of extended surfaces in compact heat exchangers, and many others.     

Prediction of software vulnerability based deep symbiotic genetic algorithms: Phenotyping of dominant-features

The detection of software vulnerabilities is considered a vital problem in the software security area for a long time. Nowadays, it is challenging to manage software security due to its increased complexity and diversity. So, vulnerability detection applications play a significant part in software development and maintenance. The ability of the forecasting techniques in vulnerability detection is still weak. Thus, one of the efficient defining features methods that have been used to determine the software vulnerabilities is the metaheuristic optimization methods. This paper proposes a novel software vulnerability prediction model based on using a deep learning method and SYMbiotic Genetic algorithm. We are first to apply Diploid Genetic algorithms with deep learning networks on software vulnerability prediction to the best of our knowledge. In this proposed method, a deep SYMbiotic-based genetic algorithm model (DNN-SYMbiotic GAs) is used by learning the phenotyping of dominant-features for software vulnerability prediction problems. The proposed method aimed at increasing the detection abilities of vulnerability patterns with vulnerable components in the software. Comprehensive experiments are conducted on several benchmark datasets; these datasets are taken from Drupal, Moodle, and PHPMyAdmin projects. The obtained results revealed that the proposed method (DNN-SYMbiotic GAs) enhanced vulnerability prediction, which reflects improving software quality prediction.

     

Electrical properties of monoazacrown ether-substituted phthalocyanines

D.c. conductivities of polycrystalline monoazacrown ether-substituted phthalocyanines (M=2H, Ni, Zn, Pb, Cu) and diphthalocyanine (M=Lu) are measured as Au-MPc-Au sandwiches to be of the order 10^–10–10^–12 S m^–1. Chemical doping with oxidants (e.g. NOBF₄) and enhancing the stacking of planar phthalocyanine moieties through the formation of alkali metal adducts with sodium and potassium ions leads to increase in conductivity of the order 10¹–10². The low conductivity and the diamagneticity of the bis(phthalocyaninato)-lutetium can be ascribed to the lack of radical nature in LuH(Pc)₂. For the a.c. conductivities, lead and lutetium complexes form a group with higher conductivities and the rest show lower conductivity. The conduction activation energies calculated from Arrhenius plots exhibit the lowest value (0.40 eV) for the lutetium compound.Part of this work was presented at NATO-ASI on Semiconductor Materials and Processing Technologies, Erice, Sicily, 1–13 July 1991.     

Prediction of suspended sediment concentration from water quality variables

This study investigates use of water quality (WQ) variables, namely total chromium concentration, total iron concentration, and turbidity for predicting suspended sediment concentration (SSC). For this purpose, the artificial neural networks (ANNs) and regression analysis (RA) models are employed. Seven different RA models are constructed, considering the functional relation between measured WQ variables and SSC. The WQ and SSC data are fortnightly obtained from six monitoring stations, located on the stream Harsit, Eastern Black Sea Basin, Turkey. A total of 132 water samples are collected from April 2009 to February 2010. Model prediction results reveal that ANN is able to predict SSC from WQ data, with mean absolute error (MAE) of 10.30 mg/L and root mean square error (RMSE) of 13.06 mg/L. Among seven RA models, the best one, which has the form including all independent parameters, produces results comparable to those of ANN, with MAE = 14.28 mg/L and RMSE = 15.35 mg/L. The sensitivity analysis results reveal that the most effective parameter on the SSC is total chromium concentration. These results have time- and cost-saving implications.     

Spatio‐temporal geometry fusion for multiple hybrid cameras using moving least squares surfaces

Multi‐view reconstruction aims at computing the geometry of a scene observed by a set of cameras. Accurate 3D reconstruction of dynamic scenes is a key component for a large variety of applications, ranging from special effects to telepresence and medical imaging. In this paper we propose a method based on Moving Least Squares surfaces which robustly and efficiently reconstructs dynamic scenes captured by a calibrated set of hybrid color+depth cameras. Our reconstruction provides spatio‐temporal consistency and seamlessly fuses color and geometric information. We illustrate our approach on a variety of real sequences and demonstrate that it favorably compares to state‐of‐the‐art methods.     

Self-repair ability of evolved self-assembling systems in cellular automata

Self-repairing systems are those that are able to reconfigure themselves following disruptions to bring them back into a defined normal state. In this paper we explore the self-repair ability of some cellular automata-like systems, which differ from classical cellular automata by the introduction of a local diffusion process inspired by chemical signalling processes in biological development. The update rules in these systems are evolved using genetic programming to self-assemble towards a target pattern. In particular, we demonstrate that once the update rules have been evolved for self-assembly, many of those update rules also provide a self-repair ability without any additional evolutionary process aimed specifically at self-repair.     

Die Abtrennung von Ölsäuremonoglycerid aus einem Glyceridgemisch mit Hilfe eines überkritischen Extraktionsmittels

Separation of Glycerol-monooleate from a Mixture of Glycerides by Means of a Supercritical Extractant The continuous separation of pure monoglycerides out of a mixture of glycerides by means of supercritical fluid extraction was investigated. As supercritical extracting agent carbon dioxide containing propane as an entrainer was used. The phase equilibria concerning the process were measured and are discussed. In an extraction apparatus consisting of an extraction column and two separators the viability of the process was tested. At 40°C and 120 bar a product with 99.5 wt.% monoglycerides was manufactured out of a mixture of glycerides containing 59 wt.% monoglycerides.     

In situ esterification of rice bran oil with methanol and ethanol

In situ esterifications of high-acidity rice bran oil with methanol and ethanol and with sulfuric acid as catalyst were investigated. In the esterification with methanol, all free fatty acids (FFA) dissolved in methanol were interesterified within 15 min, and it was possible to obtain nearly pure methyl esters. The amount of methyl esters obtained from a given rice bran was dependent on the FFA content of the rice bran oil. In the esterification with ethanol, it was not possible to obtain pure esters as in methanol esterification, because the solubilities of oil components in ethanol were much higher than those in methanol.