ZnO nanoparticles induced effects on nanomechanical behavior and cell viability of chitosan films

The aim of this paper is to develop novel chitosan–zinc oxide nanocomposite films for biomedical applications. The films were fabricated with 1, 5, 10 and 15% w/w of zinc oxide (ZnO) nanoparticles (NPs) incorporated with chitosan (CS) using a simple method. The prepared nanocomposite films were characterized using atomic force microscopy, Raman and X-ray diffraction studies. In addition, nano and micro mechanical properties were measured. It was found that the microhardness, nanohardness and its corresponding elastic modulus increased with the increase of ZnO NP percentage in the CS films. However, the ductility of films decreased as the percentage of ZnO NPs increased. Cell attachment and cytotoxicity of the prepared films at days two and five were evaluated in vitro using osteoblasts (OBs). It was observed that OB viability decreased in films with higher than 5% ZnO NPs. This result suggests that although ZnO NPs can improve the mechanical properties of pure CS films, only a low percentage of ZnO NPs can be applied for biomedical and bioengineering applications because of the cytotoxicity effects of these particles.     

Influence of the Thermal Barrier Coatings Design on the Oxidation Behavior

The properties of two different types of thermal barrier coatings(TBCs) were compared to improve the surface characteristics on high temperature components.These TBCs consisted of a duplex TBC and a five-layered functionally graded TBC.NiCrAlY bond coats were deposited on a number of Inconel-738LC specimens using high velocity oxy-fuel spraying(HVOF) technique.For duplex coating,a group of these specimens were coated with yttria stabilized zirconia(YSZ) using plasma spray technique.Functionally graded NiCrA...     

Uncertainty based distributed generation expansion planning in electricity markets

Decision making under uncertainty is a difficult task in most areas. The distributed generation expansion planning is certainly one of the problems where it is difficult to find an optimal solution for, due to the existence of various uncertain parameters that affect the optimal solution. This paper presents a distributed generation planning strategy based on the multi-objective decision making (MODM) approach under uncertainties. The proposed strategy achieves a Pareto set of locations, sizes, and typical types, for new DG installations in a case-study power network (as the result of a multi-objective optimization). The technical constraints of DG units are also considered in the MODM process. The effects of the uncertain parameters on choosing the best plan(s) are considered using robustness, flexibility, and risk exposure attributes. This aim is performed based on a composite index which is weighted sum of the three mentioned attributes. This paper considers four categories of uncertain parameters including the peak loading factor, electricity market price, and investment and operating costs for the DG long-term planning.     

Study on forcing schemes in the thermal lattice Boltzmann method for simulation of natural convection flow problems

The present study addresses the effect of various schemes for applying an external force term on the accuracy and performance of the thermal lattice Boltzmann method (LBM) for simulation of free convection problems. Herein, the forcing schemes of Luo, shifted velocity method, Guo, and exact difference method are applied by considering three velocity discrete models of D2Q4, D2Q5, and D2Q9. The accuracy and performance of these schemes are evaluated with the simulation of three natural convection problems, namely, free convection in a closed cavity, in a square enclosure with a hot obstacle inside, and the Rayleigh-Benard problem. The obtained results based on the present thermal LBM with different forcing schemes and velocity discrete models are compared with the existing experimental and numerical data in the literature. This comparison study indicates that imposing all employed forcing schemes leads to similar performance for the simulation of free convection problems studied at the middle range of Rayleigh numbers. It is found that the Luo forcing scheme is simple for implementation in comparison with the other three forcing schemes and provides the results with acceptable accuracy at moderate Rayleigh numbers. At higher Rayleigh numbers, however, the Guo scheme is not only numerically stable but a more precise forcing scheme in comparison with the other three methods. It is illustrated that employing the discrete velocity model of D2Q4 has more appropriate numerical stability along with less computational cost in comparison with two other discrete velocity models for simulation of natural convection heat transfer.     

A novel numerical modeling paradigm for bio particle tracing in non-inertial microfluidics devices

Microsystem Technologies - In this work, we report on the design and implementation of a new method for the two dimensional (2D) simulation of rigid spherical particles trajectory which are to be...     

GA-ANFIS modeling of higher heating value of wastes: Application to fuel upgrading

Combustion of wastes is a promising source for energy recovery because of having appropriate higher heating value (HHV) in order to use as fuel. The present study was aimed to estimate HHV value using a hybrid adaptive neuro-fuzzy inference system and genetic algorithm called GA-ANFIS. This model can predict HHV as a function of carbon (%C), hydrogen (%H), oxygen (%O), nitrogen (%N), and sulfur (%S) mass percentages. This suggested model has been also compared with other published correlations, and based on obtained results, great accuracy of our model was confirmed. The obtained values of Mean Squared Error (MSE) and R-squared were 0.236 and 0.9983, respectively. Consequently, this model can be very valuable to have accurate prediction of waste HHV value.     

Optimization of Split Keyboard Design for Touchscreen Devices

While many large touchscreen devices have a split keyboard option to enable two-thumb typing, there are significant differences in the design which affect users’ text entry rate. A mixed-integer programming model is developed to optimize key-to-thumb assignment with the objective of minimizing the expected time to type a character. Computer simulations are conducted to determine the optimal key dimension under different values of the Fitts’ law’s slope coefficient, typing error rate, and alternate-hand advantage phenomenon. The results show that text entry rate and the optimal key-to-thumb assignment depend on key dimensions, user’s speed-accuracy profile, and the level of alternate-hand advantage. The optimal keyboard is proposed. To validate the analytical findings, an empirical study is conducted with eighteen users and six different keyboards in terms of key dimensions and typing zone. Empirical results report between 7% and 18% improvement in the text entry rate over the other split keyboards tested.     

A DASH-based HEVC multi-view video streaming system

Recent advancement in cameras and image processing technology has generated a paradigm shift from traditional 2D and 3D video to multi-view video (MVV) technology, while at the same time improving video quality and compression through standards such as high efficiency video coding (HEVC). In multi-view, cameras are placed in predetermined positions to capture the video from various views. Delivering such views with high quality over the Internet is a challenging prospect, as MVV traffic is several times larger than traditional video, since it consists of multiple video sequences, each captured from a different angle, requiring more bandwidth than single-view video to transmit MVV. In addition, the Internet is known to be prone to packet loss, delay, and bandwidth variation, which adversely affect MVV transmission. Another challenge is that end users’ devices have different capabilities in terms of computing power, display, and access link capacity, requiring MVV to be adapted to each user’s context. In this paper, we propose an HEVC multi-view system using Dynamic Adaptive Streaming over HTTP to overcome the above-mentioned challenges. Our system uses an adaptive mechanism to adjust the video bit rate to the variations of bandwidth in best effort networks. We also propose a novel scalable way for the multi-view video and depth content for 3D video in terms of the number of transmitted views. Our objective measurements show that our method of transmitting MVV content can maximize the perceptual quality of virtual views after the rendering and hence increase the user’s quality of experience.     

Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir

Multiphase flow meters (MPFMs) are utilized to provide quick and accurate well test data in numerous numbers of oil production applications like those in remote or unmanned locations topside exploitations that minimize platform space and subsea applications. Flow rates of phases (oil, gas and water) are most important parameter which is detected by MPFMs. Conventional MPFM data collecting is done in long periods; because of radioactive sources usage as detector and unmanned location due to wells far distance. In this paper, based on a real case of MPFM, a new method for oil rate prediction of wells base on Fuzzy logic, Artificial Neural Networks (ANN) and Imperialist Competitive Algorithm is presented. Temperatures and pressures of lines have been set as input variable of network and oil flow rate as output. In this case a 1600 data set of 50 wells in one of the northern Persian Gulf oil fields of Iran were used to build a database. ICA-ANN can be used as a reliable alternative way without personal and environmental problems. The performance of the ICA-ANN model has also been compared with ANN model and Fuzzy model. The results prove the effectiveness, robustness and compatibility of the ICA-ANN model.