A practical power allocation method for multi-user and multi-carrier networks

Wireless Networks - In the majority of studies on wireless networks, it is assumed that the receiver perfectly knows the channel. Since this is not the case for real life applications, the channel...     

The effect of the cutting parameters on performance of WEDM

In this study, variations of cutting performance with pulse time, open circuit voltage, wire speed and dielectric fluid pressure were experimentally investigated in Wire Electrical Discharge Machining (WEDM) process. Brass wire with 0.25 mm diameter and AISI 4140 steel with 10 mm thickness were used as tool and work materials in the experiments. The cutting performance outputs considered in this study were surface roughness and cutting speed. It is found experimentally that increasing pulse time, open circuit voltage, wire speed and dielectric fluid pressure increase the surface roughness and cutting speed. The variation of cutting speed and surface roughness with cutting parameters is modeled by using a regression analysis method. Then, for WEDM with multi-cutting performance outputs, an optimization work is performed using this mathematical models. In addition, the importance of the cutting parameters on the cutting performance outputs is determined by using the variance analysis (ANOVA).     

Expectation–maximization‐based joint data detection and channel estimation for a cellular multi‐carrier code division multiple access network using single‐hop relaying

This paper is concerned with channel estimation and data detection for a cellular multi‐carrier code division multiple access network using single‐hop relaying in the presence of frequency selective fading channels. The proposed expectation–maximization (EM) algorithm was used to jointly estimate both the coefficients of the channel between a relay and a base station and the data. EM algorithm is particularly suited to multi‐carrier code division multiple access systems because they have multi‐carrier signal format. The considered network uses single‐hop relaying technique to provide a higher quality transmission to the users with low quality channels. The base station (managing mechanism) gives them an opportunity to send their messages via the users with high quality channels in a time sharing mode. The performance of the proposed EM algorithm, with and without hopping and with cooperative communication technique, was analyzed by a computer simulation, and the results are presented. Copyright © 2011 John Wiley & Sons, Ltd.     

An Investigation of the Reaction of Epoxides with Wood

Abstract

The reaction of wood with two functionalised epoxides, allyl glycidyl ether (AGE) and glycidyl methacrylate (GMA), has been studied. For the reaction with whole wood samples of Scots Pine (Pinus sylvestris), maximum weight percent gains (WPG's) of 20% (GMA) and 7% (AGE) were obtained using pyridine as a solvent/catalyst. However, reaction of the epoxides with thermomechanically pulped Spruce fibre yielded WPG's of 15% (GMA) and 0% (AGE) under the same reaction conditions. In addition, the use of hydroquinone as an inhibitor of polymerisation yielded variable results. The observed WPG's obtained were found to be strongly influenced by the clean-up procedure used at the end of the reaction. The results suggest that, under the conditions used in this study, no reaction with the wood hydroxyl groups is occurring but that homopolymerisation of the epoxides is responsible for the observed data.     

Nanoclay assisted strengthening of the fiber/matrix interface in functionally filled polyamide 6 composites

This study describes the contribution of a nano-filler, i.e. an organically modified layered silicate, in respect of the fiber/matrix interfacial shear strength (IFSS) of a short glass fiber reinforced and functionally filled polyamide 6, given an exfoliated nanocomposite morphology. Apparent IFSS values are determined using a continuum micromechanical method. Polymer chains in the nanoconfined environment of an exfoliated clay nanocomposite are found to crystallize preferentially in the form of a specific crystalline phase with increased degree of crystallinity. Strong dependence of IFSS on polymer crystallinity is found which is related to enhanced shrinkage stresses associated with increased degree of crystallinity.     

Analytical characterisation and production of wool wax from Akkaraman and Morkaraman sheep's wool

The analytical characterisation and production of wool wax from Akkaraman and Morkaraman sheep in the East Anatolien region of Turkey have been investigated. It was shown that the analytical characteristics of Akkaraman and Morkaraman wool waxes differ only slightly from other wool waxes. Therefore, from a quality point of view, wool waxes obtained from this work can be used for the same purposes as wool waxes produced from different varieties of sheep.     

Correlation structure of training data and the fitting ability of back propagation networks: Some experimental results

White [6–8] has theoretically shown that learning procedures used in network training are inherently statistical in nature. This paper takes a small but pioneering experimental step towards learning about this statistical behaviour by showing that the results obtained are completely in line with White's theory. We show that, given two random vectorsX (input) andY (target), which follow a two-dimensional standard normal distribution, and fixed network complexity, the network's fitting ability definitely improves with increasing correlation coefficient r_XY (0r_XY1) betweenX andY. We also provide numerical examples which support that both increasing the network complexity and training for much longer do improve the network's performance. However, as we clearly demonstrate, these improvements are far from dramatic, except in the case r_XY=+ 1. This is mainly due to the existence of a theoretical lower bound to the inherent conditional variance, as we both analytically and numerically show. Finally, the fitting ability of the network for a test set is illustrated with an example.Nomenclature X Generalr-dimensional random vector. In this work it is a one-dimensional normal vector and represents the input vector - Y Generalp-dimensional random vector. In this work it is a one-dimensional normal vector and represents the target vector - Z Generalr+p dimensional random vector. In this work it is a two-dimensional normal vector - E Expectation operator (Lebesgue integral) - g(X)=E(Y¦X) Conditional expectation - Experimental random error (defined by Eq. (2.1)) - y Realized target value - o Output value - f Network's output function. It is formally expressed asf: R ^r×WR ^p, whereW is the appropriate weight space - Average (or expected) performance function. It is defined by Eq. (2.2) as (w)=E[(Yf(X,w)],w W - Network's performance - w ^* Weight vector for optimal solution. That is, the objective of network is such that (w ^*) is minimum - C ₁ Component one - C ₂ Component two - Z Matrix of realised values of the random vectorZ overn observations - Z _t Transformed matrix version ofZ in such a way thatX andY have values in [0,1] - X _t ,Y _t Transformed versions ofX andY and both are standard one-dimensional normal vectors - n _h Number of hidden nodes (neurons) - r _XY Correlation coefficient between eitherX andY orX _t andY _t - _s and _k in Eq. (3.1) and afterwards _s is average value of 100 differentZ _t matrices. _k is the error function ofkthZ _t , matrix. In Eq. (3.1), the summation is fromk=1 to 100, and in Eq. (3.2) fromi=1 ton. In Eq. (3.2)o _ki andy _ki are the output and target values for the kthZ _t matrix and ith observation, respectively - ^1/2(w ^*) and _k (w_n) k(w_n) is the sample analogue of ^1/2(w ^*) - _Y ² In Eq. (4.1) and afterwards, _Y ² is the variance ofY - _Y ² variance ofY _t . In Sect. 4.3 the transformation isY _t=a Y+b - Y _max,Y _min the maximum and minimum values ofY - R Correlation matrix ofX andY - Covariance matrix ofX andY - Membership symbol in set theory     

Augmented neural networks and problem structure-based heuristics for the bin-packing problem

In this article, we report on a research project where we applied augmented-neural-networks (AugNNs) approach for solving the classical bin-packing problem (BPP). AugNN is a metaheuristic that combines a priority rule heuristic with the iterative search approach of neural networks to generate good solutions fast. This is the first time this approach has been applied to the BPP. We also propose a decomposition approach for solving harder BPP, in which subproblems are solved using a combination of AugNN approach and heuristics that exploit the problem structure. We discuss the characteristics of problems on which such problem structure-based heuristics could be applied. We empirically show the effectiveness of the AugNN and the decomposition approach on many benchmark problems in the literature. For the 1210 benchmark problems tested, 917 problems were solved to optimality and the average gap between the obtained solution and the upper bound for all the problems was reduced to under 0.66% and computation time averaged below 33?s per problem. We also discuss the computational complexity of our approach.     

The false positive effect of residue of sulphur sources on dithiocarbamate analysis based on CS2 measurement

Turkey plays an important role in the international trade of apricots as it has the largest production rate in the world. Since the sulphurisation process is allowed to be used for different products, the effect of residual sulphur and its compounds (which can be found in products as pesticide residues or additive residues) on the positive detection of carbon disulphide (CS₂) still creates a big challenge in international trade. Therefore, the main objective of the present study was to investigate the effects of residues of sulphur or sulphur compounds on dithiocarbamate analysis methods based on CS₂ measurement. In this study, apricots were chosen since they contain sulphur residues as a result of the sulphurisation process. Sulphur dioxide and dithiocarbamate analyses were conducted on dried apricots prepared with the sulphurisation process (SA) and without the sulphurisation process (NSA); analysis was by two different accredited laboratories. No of pesticide was applied to either SA or NSA samples. Although some of the NSA samples had <LOQ values, approximately 70 ± 32 mg/kg SO₂ and 0.061 ± 0.021 mg/kg dithiocarbamate were detected for NSA samples. On the other hand, for the SA sample group, 927–2915 mg/kg of SO₂ and 0.265–0.825 mg/kg of dithiocarbamate were detected. Furthermore, a strong correlation between residual sulphur and dithiocarbamate values was observed. This study showed that the analysis method based on CS₂ measurement may lead to false positive results for dithiocarbamates when residues of sulphur or sulphur compounds are found in products as pesticide or additive residues. Therefore, residual sulphur compounds as a result of the sulphurisation process (which is not considered during the evaluation of products) must be taken into account during the evaluation of products for dithiocarbamates.