Dual segment rectangular dielectric resonator antenna with metamaterial for improvement of bandwidth and gain

The simulation and experimental studies of an aperture‐coupled wideband dual segment rectangular dielectric resonator antenna with metamaterial for C‐band applications are presented in this paper. The antenna consists of Alumina (Al₂O₃) ceramic as upper segment and Teflon as lower segment. The combination of circular‐shaped coplanar split‐ring resonator and conducting strip has been used as metamaterial superstrate. With the use of metamaterial superstrate, the bandwidth of the antenna is increased by 48% through simulation and 22% experimentally. The broadside radiation pattern of the antenna is converted into directive radiation pattern with reduced beamwidth when metamaterial superstrate is used. The peak gain of the antenna is also enhanced by 33% through simulation and 31% experimentally with the use of metamaterial superstrate. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:646–655, 2014.     

Mechanical,electrical, and thermal expansion properties of carbon nanotube-based silver and silver-palladium alloy composites

The mechanical, electrical, and thermal expansion properties of carbon nanotube（CNT）-based silver and silver–palladium（10：1, w/w） alloy nanocomposites are reported. To tailor the properties of silver, CNTs were incorporated into a silver matrix by a modified molecular level-mixing process. CNTs interact weakly with silver because of their non-reactive nature and lack of mutual solubility. Therefore, palladium was utilized as an alloying element to improve interfacial adhesion. Comparative microstructural characterizations and property evaluations of the nanocomposites were performed. The structural characterizations revealed that decorated type-CNTs were dispersed, embedded, and anchored into the silver matrix. The experimental results indicated that the modification of the silver and silver–palladium nanocomposite with CNT resulted in increases in the hardness and Young＇s modulus along with concomitant decreases in the electrical conductivity and the coefficient of thermal expansion（CTE）. The hardness and Young＇s modulus of the nanocomposites were increased by 30%？40% whereas the CTE was decreased to 50%-60% of the CTE of silver. The significantly improved CTE and the mechanical properties of the CNT-reinforced silver and silver–palladium nanocomposites are correlated with the intriguing properties of CNTs and with good interfacial adhesion between the CNTs and silver as a result of the fabrication process and the contact action of palladium as an alloying element.     

One pot synthesis of nano Ag in calcium alginate beads and its catalytic application in p‐Nitrophenol reduction with kinetic parameter estimation and model fitting

In this work, one step process of synthesis of silver nanoparticles (Agnp) embedded in insitu formed calcium alginate (CA) beads is stated. CA, formed from the reaction between sodium alginate and calcium hydroxide, acts as reducing and stabilizing agent as well as support for nanoparticles. The reaction mechanism for the formation and stabilization of Agnp is proposed where the vicinal dihydroxy groups of alginate are assumed to act as the reducing agent for Ag⁺ to Ag°. Transmission electron microscopy (TEM), x‐ray diffraction (XRD), UV‐vis spectroscopy, field emission scanning electron microscopy (FESEM), and atomic absorption spectroscopy (AAS) were used to characterize the Agnp. The formation of spherical nanoparticles with average size range of 4‐5 nm was confirmed by TEM. Catalytic activity of this nano silver‐calcium alginate (Agnp‐CA) composite was evaluated in the reduction of p‐nitrophenol. Concentrations of sodium alginate, calcium hydroxide, and AgNO₃ are found to be the parameters that critically affect the synthesis of Agnp. The efficacy of the catalyst is expressed on the basis of suitable reaction parameters. Both pseudo‐homogeneous and heterogeneous kinetic models are proposed for the reaction to find the best model and the Eley‐Riedel model is found to fit well with the experimental data. The novelty of this work is that the tandem process of CA bead formation, Agnp formation, and Agnp entrapment in CA have been transformed into a single‐step process. Moreover, elaborations of each step of the ionic mechanisms of Agnp formation and p‐NP reduction with Agnp and the establishment of a heterogeneous kinetic model for the reaction are reported for the first time here.     

Two‐echelon manufacturer–retailer supply chain strategies with price,quality, and promotional effort sensitive demand

This study deals with the two‐layer supply chain model of one manufacturer and one retailer for a single commodity where market demand is assumed to be dependent on selling price, quality of the products, and promotional effort of the retailer. We investigate the behavior of the supply chain under centralized, manufacturer Stackelberg, conditional manufacturer Stackelberg, retailer Stackelberg, conditional retailer Stackelberg, and vertical Nash model structure. The nature of the above models provides great insights to a firm's manager for achieving optimal strategy in a competitive marketing system. Quite often, not all items produced in a firm are of perfect quality; some are perfect (conforming) quality and others are imperfect (nonconforming) quality. The nonconforming products are sold in a secondary shop or by other retailers. The procurement cost of finished products depends on the quality of the products due to more investment in advanced technology, better raw materials, and skilled labor, etc. The warranty policy for the products is also imposed to attract the customers to buy more. Here, both members (manufacturer and retailer) jointly share the cost of the warranty policy. The objective of this paper is to determine the optimal selling price and promotional effort of the retailer, while the optimal wholesale price and quality of the products are determined by the manufacturer so that the above strategies are maximized. Finally, numerical examples with sensitivity analysis of the key parameters are illustrated to investigate the proposed model.     

Femtocell based green power consumption methods for mobile network

This paper presents the analytical models of power consumption in macrocell, microcell, picocell and femtocell based networks. Five case studies are presented in this paper where macrocells, microcells, picocells and femtocells are deployed based on the number of mobile subscribers present in a region, mobile user traffic in that region and the area of the region where cellular coverage has to be provided. A comparative study is performed between the power consumption by the base stations in each of these five cases and that of the only macrocell based network. The simulation results demonstrate that using each of these five strategies the power consumption by the base stations can be minimized than that of only macrocell based network. Based on the power consumption by the base stations in these five schemes, we have categorized the networks into five classes, A, B, C, D and E, each of which contains cells of different types to reduce power consumption to achieve green cellular network.     

Multi-objective optimization in wire-electro-discharge machining of TiC reinforced composite through Neuro-Genetic technique

This paper proposed a Neuro-Genetic technique to optimize the multi-response of wire electro-discharge machining (WEDM) process. The technique was developed through hybridization of a radial basis function network (RBFN) and non-dominated sorting genetic algorithm (NSGA-II). The machining was done on 5 vol% titanium carbide (TiC) reinforced austenitic manganese steel metal matrix composite (MMC). The proposed Neuro-Genetic technique was found to be potential in finding several optimal input machining conditions which can satisfy wide requirements of a process engineer and help in efficient utilization of WEDM in industry.     

Pseudo-bond graph modelling of temperature distribution in a through-process steel rolling

In a through-process hot steel rolling, the material moves from the reheat furnace to the rolling stands, and finally to the runout table. In this work, the pseudo-bond graph model has been developed to predict the temperature distribution in this process, which includes the study of essential temperature dynamics inside the material. For each section of the through-process rolling section, an individual pseudo-bond graph model has been developed, and finally those are connected to each other. By using this model one can predict the output temperature at the end of the runout table for a given set of input parameters at the entry of reheat furnace.     

An Architectural Framework for Accurate Characterization of Network Traffic

In networks carrying large volume of traffic, accurate traffic characterization is necessary for understanding the dynamics and patterns of network resource usage. Previous approaches to flow characterization are based on random sampling of the packets (e.g., Cisco's NetFlow) or inferring characteristics solely based on long lived flows (LLFs) or on lossy data structures (e.g., bloom filters, hash tables). However, none of these approaches takes into account the heavy-tailed nature of the Internet traffic and separates the estimation algorithm from the flow measurement architecture.In this paper, we propose an alternate approach to traffic characterization by closely linking the flow measurement architecture with the estimation algorithm. Our measurement framework stores complete information related to short lived flows (SLFs) while collecting partial information related to LLFs. For real-time separation of LLFs and SLFs, we propose a novel algorithm based on typical sequences from Information theory. The distribution (pdf) and sample space of the underlying traffic is estimated using the non-parametric Parzen window technique and likelihood function defined over the Coupon collector problem. We validate the accuracy and performance of our estimation technique using traffic traces from the internal LAN in our laboratory and from National Library for Applied Network Research (NLANR).     

An algorithm for recognizing palm polygons

A polygonP is said to be apalm polygon if there exists a pointxP such that the Euclidean shortest path fromx to any pointyP makes only left turns or only right turns. The set of all such pointsx is called thepalm kernel. In this paper we propose an O(E) time algorithm for recognizing a palm polygonP, whereE is the size of the visibility graph ofP. The algorithm recognizes the given polygonP as a palm polygon by computing the palm kernel ofP. If the palm kernel is not empty,P is a palm polygon.The extended abstract of this paper was reported at the Second Canadian Conference in Computational Geometry, pp. 246–251, 1990     

PsyCOP-a psychologically motivated connectionist system for objectperception

A connectionist system has been designed for learning and simultaneous recognition of flat industrial objects (based an the concepts of conventional and structured connectionist computing) by integrating the psychological hypotheses with the generalized Hough transform technique. The psychological facts include the evidence of separation of two regions for identification ("what it is") and pose estimation ("where it is"). The system uses the mechanism of selective attention for initial hypotheses generation. A special two-stage training paradigm has been developed for learning the structural relationships between the features and objects and the importance values of the features with respect to the objects. The performance of the system has been demonstrated on real-life data both for single and mixed (overlapped) instances of object categories. The robustness of the system with respect to noise and false alarming has been theoretically investigated.