Active Queue Management for Fair Resource Allocation in Wireless Networks

This paper investigates the interaction between end-to-end flow control and medium access control (MAC)-layer scheduling on wireless links. We consider a wireless network with multiple users receiving information from a common access point; each user suffers fading and a scheduler allocates the channel based on channel quality but is subject to fairness and latency considerations. We show that the fairness property of the scheduler is compromised by the transport-layer flow control of transmission control protocol (TCP) New Reno. We provide a receiver-side control algorithm, CLAMP, that remedies this situation. CLAMP works at a receiver to control a TCP sender by setting the TCP receiver's advertised window limit, and this allows the scheduler to allocate bandwidth fairly between the users.     

Modelling and simulation of single- and triple-junction solar cells using MATLAB/SIMULINK

The main objective of this paper is to determine the single- and triple-junction solar cells’ I–V and P–V curves, define maximum voltage, current, and power. The paper demonstrates and analyses different environmental conditions that affect the solar cells, such as temperature and irradiance. The performance of single- and triple-junction solar cells is evaluated by analysing the fill factor. In this work, the analysis of single- and triple-junction solar cells is carried out through software simulation. Different conditions demonstrated to observe the results of this variation in both single- and triple-junction cells, such as observing the solar cell behaviour under variation of temperature between 15°C (288.315?K) and 45°C (318.15?K) for the single-junction cell and between 268.15?K (?5°C) and 348.15?K (75°C) for the triple-junction cell to observe the effect of temperature on open circuit voltage, the variation of different levels of irradiance to observe its effect on open circuit voltage and current density on both cell types, and cell performance evaluation using the fill factor concept. Practical results used in this paper are obtained from Clyde Space’s laboratories. Tests of Clyde Space were done using halide lamps to simulate the irradiation conditions with irradiance of half sun which is equivalent to 0.05?W?cm^?2. The operation was done under temperature of 40°C which is equivalent to 313.15?K.     

Neuro-fuzzy based constitutive modeling of undrained response of Leighton Buzzard Sand mixtures

This study aims to develop neuro-fuzzy (NF) based constitutive model for Leighton Buzzard Sand fraction B and Leighton Buzzard Sand fraction E mixtures using experimental data. The experimental database used for NF modeling is based on a laboratory study of saturated mixtures with various mix ratios under a 100 kPa effective stress. Emphasis was placed on assessing the role of fines content in mixture and strain level on the deviatoric stress and pore water pressure generation in a 100 mm diameter triaxial testing apparatus. The input variables in the developed rule based NF models are the Leighton Buzzard Sand fraction E content, and strain, and the outputs are deviatoric stress, pore water pressure generation and undrained Young’s modulus. Experimental results show that Leighton Buzzard Sand fraction B and Leighton Buzzard Sand fraction E mixtures exhibits clay-like behavior due to particle–particle effects with the increase in Leighton Buzzard Sand fraction E content. It is also shown that the performance of capacities of proposed NF models are quite satisfactory.     

A robust technique based on invariant moments – ANFIS for recognition of human parasite eggs in microscopic images

In this study, we propose a robust technique based on invariant moments – adaptive network based fuzzy inference system (IM-ANFIS). In this technique, some digital image processing methods such as noise reduction, contrast enhancement, segmentation, and morphological process are used for feature extraction stage of IM-ANFIS approach used in this study. Recently, the pattern recognition principles have come into prominence. The pattern recognition includes operation and design of systems that recognize patterns in data sets. Important application areas of pattern recognition techniques are character recognition, speech analysis, image segmentation, man and machine diagnostics and industrial inspection. The technique presented in this study enables to classify 16 different parasite eggs from their microscopic images. This proposed recognition method includes three stages. In first stage, a preprocessing subsystem is realized for obtaining unique features from the same group of patterns. In second stage, a feature extraction mechanism which is based on the invariant moments is used. In third stage, an adaptive network based fuzzy inference system (ANFIS) classifier is used for recognition process. We conduct computer simulations on MATLAB environment. The overall success rate is almost 95%.     

Constitutive modeling of Leighton Buzzard Sands using genetic programming

This paper investigates the results of laboratory experiments and numerical simulations conducted to examine the behavior of mixtures composed of coarse (i.e. Leighton Buzzard Sand fraction B) and fine (i.e. Leighton Buzzard Sand fraction E) sand particles. Emphasis was placed on assessing the role of fines content in mixture and strain level on the deviatoric stress and pore water pressure generation using experimental (i.e. Triaxial testing) and numerical approaches (i.e. genetic programming, GP). The experimental database used for GP modeling is based on a laboratory study of the properties of saturated coarse and fine sand mixtures with various mix ratios under a 100 kPa effective stresses in a 100 mm diameter conventional triaxial testing apparatus. Experimental results show that coarse–fine sand mixtures exhibit clay-like behavior due to particle–particle effects with the increase in fines content. It is shown that GP modeling of coarse–fine sand mixtures is observed to be quite satisfactory. The results have implications in the design of compressible particulate systems and in the development of prediction tools for the field performance coarse–fine sands.     

Photodynamic therapy results in induction of WAF1/CIP1/P21 leading to cell cycle arrest and apoptosis

Photodynamic therapy (PDT) is a promising new modality that utilizes a combination of a photosensitizing chemical and visible light for the management of a variety of solid malignancies. The mechanism of PDT-mediated cell killing is not well defined. We investigated the involvement of cell cycle regulatory events during silicon phthalocyanine (Pc4)-PDT-mediated apoptosis in human epidermoid carcinoma cells A431. PDT resulted in apoptosis, inhibition of cell growth, and G0-G1 phase arrest of the cell cycle, in a time-dependent fashion. Western blot analysis revealed that PDT results in an induction of the cyclin kinase inhibitor WAF1/CIP1/p21, and a down-regulation of cyclin D1 and cyclin E, and their catalytic subunits cyclin-dependent kinase (cdk) 2 and cdk6. The treatment also resulted in a decrease in kinase activities associated with all the cdks and cyclins examined. PDT also resulted in (i) an increase in the binding of cyclin D1 and cdk6 toward WAF1/CIP1/p21, and (ii) a decrease in the binding of cyclin D1 toward cdk2 and cdk6. The binding of cyclin E and cdk2 toward WAF1/CIP1/p21, and of cyclin E toward cdk2 did not change by the treatment. These data suggest that PDT-mediated induction of WAF1/CIP1/p21 results in an imposition of artificial checkpoint at G1 --> S transition thereby resulting in an arrest of cells in G0-G1 phase of the cell cycle through inhibition in the cdk2, cdk6, cyclin D1, and cyclin E. We suggest that this arrest is an irreversible process and the cells, unable to repair the damages, ultimately undergo apoptosis.     

Determining students’ level of page viewing in intelligent tutorial systems with artificial neural network

The concept of level of page viewing (LPV) refers to the extent to which a student actively revises the pages that he or she has to study in tutorial systems. In the present study, an artificial neural network (ANN) model, which is composed of 5 inputs, 20 and 30 neurons, 2 hidden layers, and 1 output, was designed to determine the students’ LPV. After this network was trained, it was integrated into a web-based prototype teaching system, which was developed by ASP.net C# programming language. Additionally, Decision Tree method is tried to determine students’ LPV. However, this method gave wrong results according to expected LPV values. In this system, the student first studies the pages uploaded by the teacher onto the system. After studying all the pages within the scope of a topic, the student can go to the test page for evaluation purposes. LPVs of a student who wants to navigate to the test page are calculated by an ANN module added to the system. On the condition that one or more of the LPV’s are not up to the desired level, the student is not allowed to take the test and is informed of the pages with missing LPV’s so that he can re-study these pages. This prototype system developed based on ANN to determine students’ LPV is essential for intelligent tutorial systems, geared to provide intelligent assistance and guidance. The system can track the pages which the students did not study sufficiently and thus direct them to relevant pages. How much activity the students perform on each page to study is observed before they actually take the test, and the areas which should be further revised are determined much in advance.     

Selective microwave absorption in Nd3+ substituted barium ferrite composites

Microwave(MW) frequency based wireless communications and electronic devices became prospective due to several ramifications.To meet this need,a series of neodymium ions(Nd3+) substituted barium ferrite composites with composition(20)BaO:(80-x)Fe_2 O_3:(x)Nd_2 O_3(0≤x≤3 mol%) was prepared at1100℃using solid-state reaction method.We evaluated the effect of various Nd3+ions contents on the surface morphology,structure,and magnetic properties of the as-synthesized barium ferrite composites.Meanwhile,microwave reflection loss,complex permittivity and permeability were determined using the transmission/reflection line method in the X-band(8—12 GHz).SEM image of the composites shows that the surface morphology consists of rough and porous microstructures.XRD patterns of the un-doped composites reveal the existence of BaFe_(12)O_(19)(hexagonal) and Fe_(21.333)O_(32)(tetragonal) crystalline phases.Furthermore,a new hexagonal crystalline phase of Ba_6 Nd_2 Fe_4 O_(15) with the crystallite sizes between 15 and 67 nm is observed due to Nd3+ions substitution in the composite.The saturation magnetization of the composite containing 2 mol% of Nd3+does not exhibit any significant alteration compared to the one devoid of Nd3+.The complex relative permitivity and permeability of the achieved composites enriched in Ba_6 Nd_2 Fe_4 O_(15) and BaFe_2 O_4 phases disclose significant MW frequency dependence.The composites also display selective MW absorption in the X-band which could be useful for diverse applications.     

Aluminium and cerium co-doped ZnO nanoparticles:Facile and inexpensive synthesis and visible light photocatalytic performances

Facile combustion route synthesized Al and Ce co-doped ZnO nanoparticles photocatalysts were characterized using XRD,SEM,BET,EDS,UV-visible DRS,PL,photocurrent and EIS techniques.XRD and SEM analyses identify that crystallite and particle size is reduced from 13.26 to 11.88 nm with introduction of Al and Ce into ZnO which assists inhibiting the recombination of photo generated charge carriers.UVvisible DRS spectra indicate that optical assimilation of ZnO is significantly increased to visible region(-406 nm)and band gap reduces from 3.18 to 3.06 eV with introduction of Al and Ce co-dopants.Electrochemical impedance spectroscopy analysis under visible light illumination confirms the enhancement in visible light activity of Al and Ce co-doped ZnO nanoparticles as photocatalysts.The enhanced activity of Al and Ce co-doped ZnO photocatalyst can be ascribed to enhanced light assimilation,high surface area and efficient charge transfer process.Our results reveal that by incorporating precise amount of Al(~2%)and Ce(~2%)into ZnO,a highly efficient catalyst can be synthesized that have degraded almost 95%methyl orange(MO)dye in just 45 min.Further,the influence of various operational parameters such as solution pH,catalyst dose,dye concentration,airflow rate and light intensity on photodecomposition of MO was evaluated.Furthe rmore,a possible mechanism for Al and Ce modified ZnO was proposed and designed photocatalysts demonstrates good stability in aqueous medium.     

A novel image segmentation approach based on neutrosophic c-means clustering and indeterminacy filtering

This paper presents a novel image segmentation algorithm based on neutrosophic c-means clustering and indeterminacy filtering method. Firstly, the image is transformed into neutrosophic set domain. Then, a new filter, indeterminacy filter is designed according to the indeterminacy value on the neutrosophic image, and the neighborhood information is utilized to remove the indeterminacy in the spatial neighborhood. Neutrosophic c-means clustering is then used to cluster the pixels into different groups, which has advantages to describe the indeterminacy in the intensity. The indeterminacy filter is employed again to remove the indeterminacy in the intensity. Finally, the segmentation results are obtained according to the refined membership in the clustering after indeterminacy filtering operation. A variety of experiments are performed to evaluate the performance of the proposed method, and a newly published method neutrosophic similarity clustering (NSC) segmentation algorithm is utilized to compare with the proposed method quantitatively. The experimental results show that the proposed algorithm has better performances in quantitatively and qualitatively.