Fuzzy inference system to modeling of crossflow milk ultrafiltration

Fuzzy inference systems (FISs) have been adopted as a powerful tool to adequately model and simulate the crossflow ultrafiltration of milk. It primary aim of this research was to predict the permeate flux, total hydraulic resistance and the milk components rejection as a function of different physicochemical properties. Dynamic modeling of ultrafiltration performance of colloidal systems (such as milk) is an important criterion in designing of a new process, due to the complex nature of milk in a dynamic manner. Such processes exhibit complex nonlinear behavior due to unknown interactions between compounds and colloidal system, thus the theoretical approaches were not being able do successfully model and simulate the processes. In addition, it has been attempted to test the FIS ability to predict new data that is not normally available. To obtain this objective, fuzzy output with a threshold of 1.2 was constructed in order to predict rejections from the limited number of accessible experimental data. The findings of this work also reveal that there exist an excellent agreement between the experimental data and predicted values. Furthermore, the experimental results shows that the total hydraulic resistance and solutes rejection (except for protein) increased significantly with time for every corresponding value of the hydrodynamic parameters. On the other hand, the permeate flux decreased sharply. However, the fat rejection does not change with time for every value of the pH.     

Transmitter antenna placement in indoor environments using particle swarm optimisation

The aim of this article is to suitably locate the minimum number of transmitter antennas in a given indoor environment to achieve good propagation coverage. To calculate the electromagnetic field in various points of the environment, we develop a software engine, named ray-tracing engine (RTE), in Matlab. To achieve realistic calculations, all parameters of geometry and material of building are considered. Particle swarm optimisation is employed to determine good location of transmitters. Simulation results show that a full coverage is obtained through suitably locating three transmitters.     

Temperature-dependent discrete layer-differential quadrature bending analysis of the multi-layered functionally graded annular plates rested on a two-parameter elastic foundation

A discrete layer approach coupled with the differential quadrature method (DQM) is employed to temperature dependent analyze the laminated functionally graded (FG) annular plates under mechanical loading in a thermal environment. The formulations are derived based on the elasticity theory, which includes the effects of the initial thermal stresses and two-parameter elastic foundation. The material properties are assumed to be temperature-dependent and graded in the thickness direction. In order to accurately evaluate the effect of the thermal environment, the initial thermal stresses are obtained by solving the thermoelastic equilibrium equation. Comparison studies with the available solutions in the literature for FG plates are performed. Then, as an application, three common types of FG sandwich plates, namely, the sandwich with homogeneous face sheets and FG core and the sandwich with FG face sheets and homogeneous metal (soft) and ceramic (hard) core are analyzed. The influences of temperature rise, temperature-dependence of material properties, layers lay-out, foundation stiffness parameters, material graded index, and geometrical parameters on the solution are carried out. The new results can be used as benchmark solutions for future researches.     

Parametric investigation of γ-alumina granule preparation via the oil-drop route

Taguchi M₃₂ experimental design was implemented to investigate the effect of operating variables on the structural and textural properties γ-alumina granules produced via the oil-drop route. Aluminum powder and hexamethylenetetramine (HMTA) were used as precursor and gelling agent, respectively. Nitric acid (HNO₃) was tested to dissolve aluminum powder as a novel digestive media. Response surface methodology (RSM) was employed to analyze the results of experimental design. The synthesized samples were characterized, by Thermo-gravimetric analysis (TGA/DTA), X-ray diffraction (XRD), nitrogen physisorption, energy dispersive X-ray (EDX), scanning electron microscopy (SEM), and transmitting electron microscopy (TEM). The output of RSM which is a multivariate linear regression model was examined to find out the effect of each factor on the response, namely the total surface area of γ-alumina granules to reach the optimum conditions. The optimized samples possess superior characteristics, e.g. highest surface area, magnificent sphericity, mesoporous structure, monotonous crystalline network, and broad pore size distribution. Based on the results, the surface area of γ-alumina granules relied too much on the temperature of aging solution, aging time and interactions between the factors. The role of heat treatment on the texture properties and morphology evolution of the samples were also precisely discussed.     

An intelligent strategy for the automatic detection of highlights in tennis video recordings

Professional sport is a vital part of many peoples’ lives and sport is a multi billion industry in its own right. Professional coaches, sporting professionals and sports journalists often use video recordings of sporting events as a tool in their daily work. With the rapid growth of sport video recordings, there is an emerging demand for a sophisticated sports content-based video indexing systems. Video recordings of sporting event broadcasts often last several hours including commercial breaks. It is therefore time-consuming and difficult to locate key segments containing highlights. This study proposes the use of computational intelligence strategies and information from both the audio and video domains to automatically locate sporting highlight on personal video playback devices. Tennis is chosen as the target domain but the strategy should generalize to other sports as well. Experimental results show that both the mean precision and recall rates are higher than 89%, hence, the proposed approach is capable of effectively detecting tennis highlights in sports broadcasts.     

Flank wear prediction in drilling using back propagation neural network and radial basis function network

In the present work, two different types of artificial neural network (ANN) architectures viz. back propagation neural network (BPNN) and radial basis function network (RBFN) have been used in an attempt to predict flank wear in drills. Flank wear in drill depends upon speed, feed rate, drill diameter and hence these parameters along with other derived parameters such as thrust force, torque and vibration have been used to predict flank wear using ANN. Effect of using increasing number of sensors in the efficacy of predicting drill wear by using ANN has been studied. It has been observed that inclusion of vibration signal along with thrust force and torque leads to better prediction of drill wear. The results obtained from the two different ANN architectures have been compared and some useful conclusions have been made.     

Metrizability on (semi)topological BL-algebras

In this paper we define the notion of quasifilter neighborhoods on (semi)topological BL-algebras and state and prove some of their properties. Finally, using the concept of quasifilter, we find some conditions under which a BL-algebra will become metrizable.     

Preparation of silica-decorated graphene oxide nanohybrid system as a highly efficient reinforcement for woven jute fabric reinforced epoxy composites

In the current work, silica-decorated graphene oxide (SiO₂@GONPs) nanohybrids were used to reinforce the jute fiber/epoxy (JF/EP) composite. Tetraethylorthosilicate (TEOS) was utilized to prepare the SiO₂@GONPs using a facial route. The results of Fourier-transform infrared spectroscopy (FTIR), atomic force microscopy, and elemental X-ray mapping confirmed the successful synthesis of SiO₂@GONPs nanohybrids. Herein, the effects of SiO₂@GONPs loading (0, 0.1, 0.3, and 0.5 wt%) on the mechanical behavior of the JF/EP composite were investigated with emphasis on the flexural and high-velocity impact properties. The results revealed that reinforcement of matrix with 0.3 wt% SiO₂@GONPs enhanced the flexural strength of the JF/EP composite by about 40%. The energy absorption capability and impact limit velocity of the 0.3 wt% SiO₂@GONPs-filled JF/EP composite were 61 and 28%, respectively, higher than those of the neat specimen. Compared to the untreated-GONPs, the SiO₂@GONPs nanohybrid demonstrated an evident superiority in improving the mechanical properties of the JF/EP composite at the same loading. Evaluation of the fracture surfaces of the multiscale composites revealed that the improved fiber-matrix interfacial bonding was the basic mechanism of fracture in these specimens.     

Cracking of C9 paraffins over xylene isomerization catalysts

The mechanism for cracking C₉ paraffins was studied in a series of experiments using feeds containing approximately 1.0% of one paraffin in a mixture of the three xylene isomers. Over a catalyst containing the medium pore molecular sieve AMS-1B, linear paraffins cracked more rapidly than branched paraffins. This difference was moderated somewhat by the addition of a hydrogenation metal to the catalyst. A similar effect is noted for catalysts containing the large pore zeolite Y where cracking of branched paraffins was favored in the absence of a hydrogenation metal. These shifts in cracking rates are shown to be consistent with a mechanism which involves an increase in the cracking rate due to the dehydrogenation activity of the metal and a decrease in cracking due to the hydrogenation activity of the metal. The distribution of cracked products indicates that the C₉ paraffins isomerize to an equilibrium distribution prior to cracking. The absence of isomerized C₉ paraffins in the product stream indicates that hydride abstraction is slow compared to either isomerization or cracking.