A novel noncooperative game competing model using generalized simple additive weighting method to perform network selection in heterogeneous wireless networks

Network selection mechanisms have a significant role in guaranteeing the QoS for users in a heterogeneous wireless networks environment. These mechanisms allow the selection of an optimal wireless network to satisfy the needs of users. Users are provided with the opportunity to select from multiple connectivity opportunities available all over various wireless networks. Furthermore, the network operators themselves can execute active selection strategies that facilitate proper decision making, in which user preferences are considered. This study proposes a new noncooperative competing game‐theoretic model and strategy space based on user preference. This model can solve network selection problems and capture the inter‐linkages of decisions taken by various networks. A generalized simple additive weighting method is incorporated into the framework of noncooperative game theory. In addition, the utility function is employed to assess the usefulness of the system. Simulation results and analysis illustrate the efficacy of the suggested model in attaining optimum network utility for heterogeneous wireless networks while optimizing user satisfaction. Copyright © 2014 John Wiley & Sons, Ltd.     

Evaluation of sericin/collagen membranes as prospective wound dressing biomaterial

Sericin, a silk protein, has high potential for use in biomedical applications. In this study, wound dressing membranes of Sericin (S) and Collagen (C) were prepared by glutaraldehyde cross-linking at S/C; 2:1, 1:1, 1:2, and 0:1 weight ratios. They were stable in water for 4 weeks. However, increasing the proportion of sericin had decreasing effect on the membrane stability. Water swelling property of membranes was enhanced with sericin. The highest water swelling was obtained in 1:1 group (9.06 g/g), but increasing collagen or sericin content in the membranes had a diminishing effect. Highest water vapor transmission rate was obtained with 1:2 group (1013.80 g/m²/day). Oxygen permeability results showed that 1:2 (7.67 mg/L) and 2:1 (7.85 mg/L) S/C groups were better than the other groups. While sericin decreased the tensile strength and elongation of membranes, it increased modulus. Sericin also increased brittleness of membranes, but their UTS range (24.93–44.92 MPa) was still suitable for a wound dressing. Membranes were not penetrable to microorganisms. Cytotoxicity studies showed that fibroblasts and keratinocytes attached and gained their characteristic morphologies. They also proliferated on membranes significantly. After 1 week of subcutaneous implantation, a fibrous capsule formed around all membranes with an acute inflammation. Sericin containing membranes showed signs of degradation (at 2nd week), while collagen only membranes remained largely intact. Eventually, sericin containing membranes degraded in 3 weeks with moderate inflammatory response. Overall results suggest that sericin/collagen membranes would be favorable as wound dressing material when sericin ratio is less than or equal to the collagen component.     

Study of Influence of Annealing Time on Some Physical Properties of ZnO:Cu Nanorods Grown by a Simple Chemical Bath Deposition Method

A simple chemical bath deposition method was used to prepare high density ZnO nanorods on ZnO seeded Si substrates. Upon the nanorods growth, Cu-doping was achieved by diffusion process at 500 ^°C for different times in vacuum ambient. The structural, optical, and magnetic properties of the obtained ZnO:Cu nanorods were then examined. XRD analysis showed that undoped and ZnO:Cu samples were highly c-axis oriented with a hexagonal wurtzite structure. SEM analysis indicated that ZnO:Cu nanorods had diameters of ～200 nm and lengths of ～1.5 μm. X-ray photoemission spectroscopy demonstrated that Cu was successfully doped into ZnO in a divalent state. Photoluminescence results showed that Cu-doping caused a decrease in the green band intensity of nanorods compared to undoped ZnO. Room temperature magnetic measurements showed that pure ZnO nanorods exhibited ferromagnetism that might be ascribed to defect-induced d⁰ ferromagnetism. All the ZnO:Cu nanorods also showed the room temperature ferromagnetism that was attributed to the bound magnetic polarons (BMPs).     

Experimental investigation of drying behaviour and conditions of pumpkin slices via a cyclone‐type dryer

This paper describes an experimental investigation of the drying behaviour and conditions of pumpkin slices via a convective cyclone‐type dryer. Drying experiments were conducted at air inlet temperatures of 60, 70 and 80 °C and air velocities of 1 and 1.5 m s^?1. Samples of 200 g of cylindrical pumpkin slices (thickness 5 mm × diameter 35 mm) were arranged in a single layer on each of two trays. The least squares method was applied to derive the drying curve equation of samples. During the experiments the following parameters were measured: weight loss, temperature, relative moisture and velocity. From these parameters, dimensionless mass loss, moisture content, mass shrinkage and drying rate of samples were calculated and are discussed in detail. Additionally, the transport of water during dehydration was described by the diffusion mechanism, and Fick's equation was used for evaluation of the experimental data. The linear sections of drying curves were analysed by linear regression to obtain the moisture diffusivities. It was found that pumpkin slices would dry perfectly within 340–720 min under these drying conditions. The convective cyclone dryer could also be used to dry other products. Thus it is expected that this new dryer will help farmers and producers to reduce the cost of drying. Copyright © 2003 Society of Chemical Industry     

Identification of Turkish extra virgin olive oils produced in different regions by using NMR (1H and 13C) and IRMS (13C/12C)

Isotope ratio mass spectroscopy (IRMS) and nuclear magnetic resonance (NMR) spectroscopy techniques are two of the analytical methods that are used to characterize food products. The aim of this study is to classify extra virgin olive oil (EVOO) samples collected from different regions of Turkey based on ¹H and ¹³C NMR spectra along with IRMS δ¹³C carbon isotope ratio data by using chemometrics multivariate data analysis methods. A total of 175 EVOO samples were analyzed in 2014/15 and 2015/16 harvest seasons. Multivariate classification and clustering models were used to identify geographical and botanical origins of the EVOOs. IRMS results showed that there was no significant difference in terms of δ¹³C values between the years in terms of harvest year (p > 0.05), only extraction phase and variety were statistically significant factors (p < 0.05). The interactions of the factors showed that the harvest year × variety interaction is important. The outcomes of this research clearly indicated that considering the partial least squares discriminant analysis result with NMR spectra, the percent success of the model in the South Marmara, North Aegean, and South Aegean region samples were 95%, 95.7%, and 96.4% in the model set, respectively. The results showed that by using classification and clustering models, geographic marking and labeling of these oils can be carried out regardless of differences in year and production systems (2 and 3 phase extraction system) according the NMR analysis.     

Performance characterization of a microwave transistor subject to the noise and matching requirements

In this paper, the gain G_T of a microwave transistor is expressed analytically in terms of the mismatchings (V_in ≥ 1, V_out ≥ 1) at the ports, noise figure F ≥ F_min and the [z]‐parameter and noise parameters. Firstly, because the input termination Z_S determines the noise F ≥ F_min, thus the input termination Z_S is pre‐determined to lie on the tangent constant noise and available gain circles so that the maximum power delivery is ensured for the given noise. Then, a design configuration is constructed in the input impedance Z_in‐ plane covering the gain and the required input and output mismatch circles within the Unconditionally Stable Working Area for the predetermined input termination Z_S. Finally, the compatible (F ≥ F_min, G_T, V_in ≥ 1, V_out ≥ 1) quadrates for either required or optimum (V_in ≥ 1, V_out ≥ 1) couples are obtained with their (Z_S, Z_L) couples from the analysis of the design configuration. Furthermore, a case study is also presented for the full flexible performance characterization of a selected microwave transistor. It can be concluded that the near future microwave transistor is expected to be identified by performance data base built by its compatible (F ≥ F_min, G_T, V_in ≥ 1, V_out ≥ 1) quadrates and the (Z_S, Z_L) terminations within the device operation domain to overview all the possible low‐noise amplifier designs using the full device capacity. Copyright © 2015 John Wiley & Sons, Ltd.     

Usage of class dependency based feature selection and fuzzy weighted pre-processing methods on classification of macular disease

In this paper, we propose a new feature selection method called class dependency based feature selection for dimensionality reduction of the macular disease dataset from pattern electroretinography (PERG) signals. In order to diagnosis of macular disease, we have used class dependency based feature selection as feature selection process, fuzzy weighted pre-processing as weighted process and decision tree classifier as decision making. The proposed system consists of three parts. First, we have reduced to 9 features number of features of macular disease dataset that has 63 features using class dependency based feature selection, which is first developed by ours. Second, the macular disease dataset that has 9 features is weighted by using fuzzy weighted pre-processing. And finally, decision tree classifier was applied to PERG signals to distinguish between healthy eye and diseased eye (macula diseases). The employed class dependency based feature selection, fuzzy weighted pre-processing and decision tree classifier have reached to 96.22%, 96.27% and 96.30% classification accuracies using 5–10–15-fold cross-validation, respectively. The results confirmed that the medical decision making system based on the class dependency based feature selection, fuzzy weighted pre-processing and decision tree classifier has potential in detecting the macular disease. The stated results show that the proposed method could point out the ability of design of a new intelligent assistance diagnosis system.     

Experimental study of gasoline-ethanol-hydrogen blends combustion in an SI engine

This study presents experimental results of engine performance, combustion and emissions in an SI engine fueled by gasoline-ethanol-hydrogen blends. In the experimental studies, engine performance and emission values were analyzed fueled by gasoline, gasoline-ethanol and gasoline-ethanol-hydrogen blends, respectively. When ethanol has been added volumetrically to gasoline 20% of ethanol (G80E20), engine performance and emissions have been worsened. However, the engine performance and emission values have been improved with the adding of hydrogen to blend. The results showed that the addition of hydrogen to the gasoline-ethanol blend improved the combustion process and improved the combustion efficiency, expanded the combustibility range of the gasoline-ethanol blend, reduced emissions. But, nitrogen oxide emission values increased with the adding of hydrogen.