Fuzzy logic-based performance improvement on MAC layer in wireless local area networks

There are many studies that have been done to improve the quality of service of wireless local area networks (WLANs). Institute of Electrical and Electronic Engineers (IEEE) WLAN are based on IEEE 802.11 protocol. The 802.11e medium access control (MAC) protocol is generally recommended for efficient quality of service in WLANs. There are many parameters in the MAC protocol that affect quality of services. Among these parameters, request to send threshold value (RSTV), fragmentation threshold value (FTV) and buffer size (BS) directly affect network performance. RSTV is used in the request to send/clear to send (RTS/CTS) mechanism in the carrier sense multiple access with collision avoidance (CSMA/CA) protocol for collision prevention. This parameter specifies the threshold used to activate the CSMA/CA protocol. FTV is another parameter that is used to send large-sized packets by dividing them into appropriate fragments during CSMA/CA transmission and reduces packet loss in WLAN. BS is another parameter that has a significant cost in the CSMA/CA model and also directly affects the performance. In this article, to improve the performance of WLANs, OPNET Modeler was used and ideal values were obtained for RSTV, FTV and BS by using fuzzy logic-based method. The values obtained by fuzzy logic were re-tested in OPNET Modeler, and the achieved improvement was as follows: for delay 36–38%, for load 2–10% and for throughput 25–44%, respectively. Thus, in WLANs, performance was improved by using fuzzy logic-based method.

     

On the polymer modified cement mortars with different lightweight aggregates in marine environment

Having a light weight is a design objective for offshore and coastal structures and in order to reach this aim, use of lightweight concrete consisting lightweight aggregates and polymers is a feasible solution. In this study, materials obtained from locally available crushed volcanic scoria as main aggregate and some additional lightweight aggregates with ceramic, perlite and andesite as well polymers were used in the mixtures with different proportions (totally 14 mixtures) to propose feasible alternatives for coastal structure designers. To evaluate the design performances of the mixtures, their properties such as density, cylinder compressive strength, capillarity, loss of mass under the effects of the agents in marine environment such as sodium sulphate and sodium chloride were obtained experimentally. It was found that mixtures with scoria aggregates showed more favourable results and additional aggregates gave flexibility to the designer to lower densities up to 40 % ‐ 60 % of normal‐weight mixtures. Polymer modification also improved the performance of the related materials.     

Cell-type based semantic segmentation of histopathological images using deep convolutional neural networks

Histopathological whole-slide image (WSI) analysis is still one of the most important ways to identify regions of cancer risk. For cancer in which early diagnosis is vital, pathologists are at the center of the decision-making process. Thanks to the widespread use of digital pathology and the development of artificial intelligence methods, automatic histopathological image analysis methods help pathologists in their decision-making process. In this process, rather than producing labels for whole-slide image patches, semantic segmentation is very useful, which facilitates the pathologists’ interpretation. In this study, automatic semantic segmentation based on cell type is proposed for the first time in the literature using novel deep convolutional networks structure (DCNN). We presents semantic information on four classes, including white areas in the whole-slide image, tissue without cells, tissue with normal cells and tissue with cancerous cells. This visual information presented to the pathologist is an easy-to-understand picture of the status of the cells and their implications for the spread of cancerous cells. A new DCNN architecture is created, inspired by the residual network and deconvolution network architecture. Our network is trained end-to-end manner with histopathological image patches for cell structures to be more discriminative. The proposed method not only produces more successful results than other state-of-art semantic segmentation algorithms with 9.2% training error and 88.89% F-score for test, but also has the most important advantage in that it has the ability to generate automatic information about the cancer and also provides information that pathologists can quickly interpret.     

Effect of fexofenadine on eosinophil-induced changes in epithelial permeability and cytokine release from nasal epithelial cells of patients with seasonal allergic rhinitis

Recent studies have suggested that antihistamines, widely used in the treatment of symptoms of patients with allergic rhinitis, may also possess antiinflammatory properties. The mechanisms underlying this property, however, are not clearly understood. We have cultured epithelial cells from nasal biopsy specimens from patients with seasonal allergic rhinitis outside the pollen season and studied the effect of 0 to 10(-3) mol/L fexofenadine, the main active metabolite of terfenadine, on eosinophil-induced changes in electrical resistance (measure of permeability) and release of proinflammatory mediators from these cells. Additionally, we have studied the effect of this drug on eosinophil chemotaxis and adherence to endothelial cells induced by conditioned medium from these human nasal epithelial cell (HNEC) cultures. Incubation of HNEC in the presence of eosinophils treated with opsonized latex beads significantly decreased the electrical resistance of these cultures, an effect that was abrogated by treatment of the cultures with 10(-9) to 10(-3) mol/L fexofenadine. Similarly, incubation of HNEC in the presence of eosinophils treated with latex beads also significantly increased the basal release of the chemokine "regulated upon activation, normal T cell expressed and secreted" (RANTES) (from 96.0 to 613.0 fg/microg cellular protein; p < 0.05), IL-8 (from 42.0 to 198.5 pg/microg cellular protein; p < 0.05), granulocyte-macrophage colony-stimulating factor (GM-CSF) (from 0.54 to 3.4 pg/microg cellular protein; p < 0.05), and soluble intercellular adhesion molecule-1 (sICAM-1) (from 7.8 to 18.4 pg/microg cellular protein; p < 0.05) from HNEC. The eosinophil-induced release of IL-8, GM-CSF, and sICAM-1 from the HNEC was significantly attenuated by treatment with fexofenadine. Analysis of the effects of conditioned medium from HNEC demonstrated that this significantly increased both eosinophil chemotaxis and adherence to endothelial cells. Addition of 10(-6) to 10(-3) mol/L fexofenadine to the conditioned medium significantly attenuated eosinophil chemotaxis and adherence to endothelial cells. These results suggest that fexofenadine may reduce nasal inflammation by modulating the release of proinflammatory mediators and adhesion molecules from HNEC.     

A Measurement and Structural Model for Usability Evaluation of Shared Workspace Groupware

This study presents the development process of a set of questionnaire items to establish a measurement model for the usability of shared workspace groupware systems, which is suggested as a usability scale called SWUS, the Shared Workspace Usability Scale. Manifest variables and latent variables are based on the various dimensions of teamwork collated through the literature. A structural model was built on the measurement model. Models were evaluated through PLS-SEM methods. Data acquired on candidate questionnaire items from 398 international respondents who are users of five different online collaborative word processors was used for the model analysis. Of 37 candidate manifest variables, 22 were retained, which were measuring seven latent constructs: “3C Mechanisms,” “Grounding,” “Team Integration,” “Communication,” “Shared Access,” “Awareness,” and “Usability.” The data provided empirical evidence for the structural model based on these latent variables. The responses of the participants were not sensitive to differences between users in terms of gender and native language but showed sensitivity to age, experience with the evaluated software, and different shared workspace groupware evaluated in the study. Our structural model attempts to integrate several frameworks and models of usability for CSCW environments and provides empirical evidence for its reliability and validity based on subjective responses from users of shared workspace groupware.     

Composition-Dependent Photoluminescence Properties and Anti-Counterfeiting Applications of A2AgX3 (A = Rb,Cs; X = Cl,Br, I)

Copper(I) halides are emerging as attractive alternatives to lead halide perovskites for optical and electronic applications. However, blue-emitting all-inorganic copper(I) halides suffer from poor stability and lack of tunability of their photoluminescence (PL) properties. Here, the preparation of silver(I) halides A₂AgX₃ (A = Rb, Cs; X = Cl, Br, I) through solid-state synthesis is reported. In contrast to the Cu(I) analogs, A₂AgX₃ are broad-band emitters sensitive to A and X site substitutions. First-principle calculations show that defect-bound excitons are responsible for the observed main PL peaks in Rb₂AgX₃ and that self-trapped excitons (STEs) contribute to a minor PL peak in Rb₂AgBr₃. This is in sharp contrast to Rb₂CuX₃, in which the PL is dominated by the emission by STEs. Moreover, the replacement of Cu(I) with Ag(I) in A₂AgX₃ significantly improves photostability and stability in the air under ambient conditions, which enables their consideration for practical applications. Thus, luminescent inks based on A₂AgX₃ are prepared and successfully used in anti-counterfeiting applications. The excellent light emission properties, significantly improved stability, simple preparation method, and tunable light emission properties demonstrated by A₂AgX₃ suggest that silver(I) halides may be attractive alternatives to toxic lead halide perovskites and unstable copper(I) halides for optical applications.     

Synthesis and characterization of epoxy based nanocomposites

Epoxy‐clay nanocomposites were synthesized to examine the effects of the content and type of different clays on the structure and mechanical properties of the nanocomposites. Diglycidyl ether of bisphenol‐A (epoxy) was reinforced by 0.5–11 wt % natural (Cloisite Na⁺) and organically modified (Cloisite 30B) types of montmorillonite. SEM results showed that as the clay content increased, larger agglomerates of clay were present. Nanocomposites with Cloisite 30B exhibited better dispersion and a lower degree of agglomeration than nanocomposites with Cloisite Na⁺. X‐ray results indicated that in nanocomposites with 3 wt % Cloisite 30B, d‐spacing expanded from 18.4 Å (the initial value of the pure clay) to 38.2 Å. The glass transition temperature increased from 73°C, in the unfilled epoxy resin, to 83.5°C in the nanocomposite with 9 wt % Cloisite 30B. The tensile strength exhibited a maximum at 1 wt % modified clay loading. Addition of 0.5 wt % organically modified clay improved the impact strength of the epoxy resin by 137%; in contrast, addition of 0.5 wt % unmodified clay improved the impact strength by 72%. Tensile modulus increased with increasing clay loading in both types of nanocomposites. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 1081–1086, 2005     

Preparation of compatible blends of poly(methyl methacrylate) used in dentistry with a reactive terpolymer containing maleic anhydride and their thermomechanical characterization

This study focuses on the preparation of compatible blends with the poly(methyl methacrylate) (PMMA) using a reactive terpolymer maleic anhydride–styrene–vinyl acetate (MA–St–VA). In the first series of experiments, binary blends of the PMMA and the MA–St–VA terpolymer have been prepared in tetrahydrofurane. The PMMA and the MA–St–VA terpolymer formed the compatible blends. The effects on thermomechanical properties of MA–St–VA terpolymer ratio in the blends were studied. The glass transition temperatures (T_g), thermal expansion coefficient (α), and other thermomechanical parameters for the blends have been established by TMA method and the compatibility of two polymers has been evaluated by these TMA parameters. The addition of MA–St–VA terpolymer to PMMA made a plasticizing effect on PMMA. This effect regularly changed with the increasing of the terpolymer in the blends. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 363–367, 2006     

Operation of a frequency-narrowed high-beam quality broad-area laser by a passively stabilized external cavity technique

The average spectral bandwidth of a 2 W broad-area diode laser was narrowed to 5 GHz with wavelength tunability of up to 12 nm at a center wavelength of 790 nm with the use of a Littman-Metcalf external cavity in a displaced configuration. The use of lens and combined lens-laser transformation systems allowed precise alignment of the beam shaping optics, which led to significant improvements of the beam quality and an enhanced suppression of the free-running laser modes. We characterize the spatial beam quality of our external cavity diode laser by measuring the M2 quality factor and relate this to our measured bandwidths. Our external cavity can be configured over a range of cavity lengths and is modular in design, enabling access to a broad frequency spectrum for a wide range of applications that require high-power, narrow bandwidth operation.     

Source apportionment of PM(10) and PM(2.5) using positive matrix factorization and chemical mass balance in Izmir, Turkey

Atmospheric particulate matter (PM) fractions (PM(10) and PM(2.5)) were sampled concurrently between June 2004 and May 2005 at two sites (urban and suburban) in Izmir, Turkey. The elemental composition of PM (Al, Ba, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Sr, V, and Zn) was determined using inductively coupled plasma-optical emission spectrometer. Elemental compositions of several PM sources were also characterized. Positive matrix factorization (PMF) and chemical mass balance modeling (CMB) were applied to determine the PM sources and their contributions to air concentrations. The major contributors to PM were fossil fuel burning, traffic emissions, mineral industries and marine salt according to the PMF results. However, undetermined parts were more than 40%. On the other hand, the contributions to PM could be determined completely by CMB, and the dominant contributor was traffic with >70% at the two sites. Fossil fuel burning, mineral industries, marine salt and natural gas-fired power plant were the minor contributors.