New two-CFOA-based floating immittance simulators

This paper presents new topologies for emulating floating immittance functions using three to five passive elements and only two current-feedback operational-amplifiers (CFOAs). The feasibility of using only two CFOAs and two passive components is explored. The proposed topologies can emulate lossy positive and negative inductances and capacitance-, inductance-, resistance-multipliers, and frequency dependent negative and positive conductances. The functionality of the proposed circuits was experimentally verified using the commercially available AD844 CFOA. The experimental results are in excellent agreement with theoretical calculations.     

Effect of various surface preparation techniques on the delamination properties of vacuum infused Carbon fiber reinforced aluminum laminates (CARALL): Experimentation and numerical simulation

Carbon fiber reinforced aluminum laminates (CARALL) are one of the aluminum based Fiber metal laminates (FMLs) which, due to their high strength to weight ratio and good impact resistance are greatly replacing aluminum alloys in aircraft structures. In this research work, interlaminate shear strength of Vacuum assisted resin transfer molding (VARTM) manufactured CARALL has been investigated. Numerical simulation model incorporated with real time material data has been developed to predict the delamination behavior of CARALL laminates. Standard CARALL specimens with different surface morphologies were prepared by electric discharge machining, mechanical, chemical and electrochemical surface treatments. T-peel tests were carried out according to standard ASTM D1876-08 to find out inter laminate shear strength. FMLs made out of mechanically, chemically and electrochemically cleaned metal sheets depicted high interlaminate shear strength. SEM micrographs of failed surfaces verify the high adhesive strength of epoxy. Developed numerical simulation model accurately predicts the delamination behavior of CARALL as observed during experimentation.     

Job search website for illiterate users of Pakistan

Illiteracy is a major hurdle in socio-economic development of Pakistan. Research in the Information and Communication Technology (ICT) can help in tackling this issue by developing solutions tailored for illiterate population. The work presented within this paper proposes a job search website for illiterate population of KPK province of Pakistan. The designed website does not require any human assistance while searching a job. Moreover, the website uses culturally relevant graphical and audio content. The usability of the website is tested according to the ISO-9241-11 specification. Furthermore, we have studied the effect of the participants’ characteristics, i.e., their age, computer and mobile usage experience on the usability of the website. The results show that the participants found the website usable. Specifically, they could search suitable jobs with a minimal number of clicks and in less time as compared to the usual task completion rates reported throughout the literature. None of the participants’ characteristics were found to be affecting the usability of the website. These results suggest a promising potential of ICT solutions for providing services to illiterate population of Pakistan.     

A Distributed and Elastic Application Processing Model for Mobile Cloud Computing

The latest developments in mobile computing technology have increased the computing capabilities of smart mobile devices (SMDs). However, SMDs are still constrained by low bandwidth, processing potential, storage capacity, and battery lifetime. To overcome these problems, the rich resources and powerful computational cloud is tapped for enabling intensive applications on SMDs. In Mobile Cloud Computing (MCC), application processing services of computational clouds are leveraged for alleviating resource limitations in SMDs. The particular deficiency of distributed architecture and runtime partitioning of the elastic mobile application are the challenging aspects of current offloading models. To address these issues of traditional models for computational offloading in MCC, this paper proposes a novel distributed and elastic applications processing (DEAP) model for intensive applications in MCC. We present an analytical model to evaluate the proposed DEAP model, and test a prototype application in the real MCC environment to demonstrate the usefulness of DEAP model. Computational offloading using the DEAP model minimizes resources utilization on SMD in the distributed processing of intensive mobile applications. Evaluation indicates a reduction of 74.6% in the overhead of runtime application partitioning and a 66.6% reduction in the CPU utilization for the execution of the application on SMD.

     

Wide and multi-band reconfigurable Vivaldi antenna with slot-line feed

This paper presents a Vivaldi antenna. The antenna incorporates a slot-line feed, and is designed to operate in a wideband mode, along with four narrowband modes. The wideband mode extends from 1 to 3 GHz. A series of PIN diode switches is employed to reconfigure between the five different operating modes. Wideband-to-multiband reconfigurations are achieved by adjusting the antenna loading internally, and also by the incorporation of band-stop filters. To obtain the wideband mode, wideband matches load is used. On the other hand, to obtain the narrowband modes, two rectangular slits with narrowband matches load are used. The proposed Vivaldi antenna provides wideband operation. It is also supports operation within the LTE, GSM (L-band), GPS, and WiMAX bands.     

Scanning electron and light microscopy of foliar epidermal characters: A tool for plant taxonomists in the identification of grasses

SEM and light microscopy are of special interest for biologist to observe various features of the living bodies. In the current study we observed the foliar epidermal micro‐morphological characters of 44 grass species using SEM and Light microscopy to assess their taxonomic utility for taxonomists in the identification process. The aim of this study is to use the foliar epidermal structural variations in both upper and lower surfaces for identification of grasses. Significant diversity was observed in both qualitative and quantitative characters using SEM and Light microscopy. Variations were observed in stomatal number, size, guard cells shape, silica bodies, macro‐hairs, micro‐hairs, epidermal cell number, subsidiary cells, prickles, hooks, papillae, and short and long cells. A taxonomic key is prepared using these variations for the identification of grass species. Based on these findings, SEM and Light microscopy of foliar epidermal features can be of special interest for taxonomists in the identification of complex grass taxa.     

A churn prediction model for prepaid customers in telecom using fuzzy classifiers

The incredible growth of telecom data and fierce competition among telecommunication operators for customer retention demand continues improvements, both strategically and analytically, in the current customer relationship management (CRM) systems. One of the key objectives of a typical CRM system is to classify and predict a group of potential churners form a large set of customers to devise profitable and targeted retention campaigns for keeping a long-term relationship with valued customers. For achieving the aforementioned objective, several churn prediction models have been proposed in the past for the accurate identification of the customers who are prone to churn. However, these previously proposed models suffer from a number of limitations which place strong barriers towards the direct applicability of such models for accurate prediction. Firstly, the feature selection methods adopted in majority of the past work neglected the information rich variables present in call details record for model development. Secondly, selection of important features was done through statistical methods only. Although statistical methods have been applied successfully in diverse domains, however, these methods alone without the augmentation of domain knowledge have the tendency to yield erroneous results. Thirdly, the previous models have been validated mainly with benchmark datasets which do not provide a true representation of real world telecom data consisting of noise and large number of missing values. Fourthly, the evaluation measures used in the past neglected the True Positive (TP) rate, which actually highlights the ability of a model to correctly classify the percentage of churners as compared to non-churners. Finally, the classifiers used in the previous models completely neglected the use of fuzzy classification methods which perform reasonably well for data sets with noise. In this paper, a fuzzy based churn prediction model has been proposed and validated using a real data from a telecom company in South Asia. A number of predominant classifiers namely, Neural Network, Linear regression, C4.5, SVM, AdaBoost, Gradient Boosting and Random Forest have been compared with fuzzy classifiers to highlight the superiority of fuzzy classifiers in predicting the accurate set of churners.     

A computationally efficient selected mapping technique for reducing PAPR of OFDM

In orthogonal frequency division multiplexing (OFDM) system, high value of peak-to-average power ratio (PAPR) is an operational problem that may cause non-linear distortion resulting in high bit error rate. Selected mapping (SLM) is a well known technique that shows good PAPR reduction capability but inflicts added computational overhead. In this paper, using Riemann sequence based SLM method, we applied reverse searching technique to find out low PAPR yielding phase sequences with significant reduction in computational complexity. Additionally, we explored side-information free transmission that achieves higher throughput but sacrifices PAPR reduction. Finally, to overcome this loss in PAPR reduction, we proposed application of Square-rooting companding technique over the output OFDM transmitted signal. Simulation results show that the proposed method is able to compensate the sacrifice in PAPR and achieved PAPR reduction of 8.9 dB with very low computational overhead.     

Search me if you can: Multiple mix zones with location privacy protection for mapping services

The mobile vehicle is gaining popularity nowadays using map services like Google Maps and other mapping services. However, map services users have to expose sensitive information like geographic locations (GPS coordinates) or address to personal privacy concerns as users share their locations and queries to obtain desired services. Existing mix zones location privacy protection methods are most general purposed and theoretical value while not applicable when applied to provide location privacy for map service users. In this paper, we present new (multiple mix zones location privacy protection) MMLPP method specially designed for map services on mobile vehicles over the road network. This method enables mobile vehicle users to query a route between 2 endpoints on the map, without revealing any confidential location and queries information. The basic idea is to strategically endpoints to nearby ones, such that (1) the semantic meanings encoded in these endpoints (eg, their GPS coordinates) change much, ie, location privacy is protected; (2) the routes returned by map services little change, ie, services usability are maintained. Specifically, a mobile client first privately retrieves point of interest close to the original endpoints, and then selects 2 points of interest as the shifted endpoints satisfying the property of geoindistinguishability. We evaluate our MMLPP approach road network application for GTMobiSim on different scales of map services and conduct experiments with real traces. Results show that MMLPP strikes a good balance between location privacy and service usability.     

Tuning the interlaminar shear strength and thermo-mechanical properties of glass fiber composites by incorporation of (3-mercaptopropyl) trimethoxysilane-functionalized carbon black

The incorporation of functionalized nanoscale fillers into traditional glass fiber/unsaturated polyester (GF/UPE) composites provides a more robust mechanical attributes. The current study demonstrates the potential of 3-mercaptopropyl trimethoxysilane (MPTS)-functionalized carbon black (f-CB) for enhancing the thermo-mechanical properties of GF composites. The composites infused with 1, 3 and 5 wt% of pristine and MPTS-functionalized CB were fabricated by hand lay-up and hot press processing. Tensile testing, interlaminar shear strength (ILSS) testing and dynamic mechanical analysis were used to evaluate the performance of nanocomposites. Fourier transform infrared spectroscopy validated the MPTS functionalization of CB. Pristine CB-loaded nanocomposites exhibited marginal improvement in ultimate tensile strength (UTS), ILSS and thermo-mechanical properties. However, with the addition of f-CB, the improvement in all the studied properties was more substantial. The inclusion of 5 wt% f-CB increased the elastic modulus and UTS by 16 and 22%, respectively, whereas the ILSS was enhanced by 36%, in comparison to the neat GF composite. The scanning electron microscope analysis of fractured ILSS samples revealed better fiber-matrix adhesion and compatibility in f-CB-loaded nanocomposites. At the same filler weight percentage, the storage modulus at 25 °C was ~ 19% higher than that of neat composite. The f-CB inclusion resulted in increment of T _g by ~ 13 °C over the T _g of neat GF/UPE composite (~ 109 °C). These improvements were due to the chemical connection of f-CB to the UPE matrix and GF surface. With such improvements in thermal and mechanical properties, these nanocomposites can replace the conventional GF composites with prominent improvements in performance.