Filter-Bank Modulation Based Signal Design and Transmission Techniques for Intensity Modulated MIMO Visible Light Communication Systems

Wireless Personal Communications - Current research in wireless communication undoubtedly points towards the tremendous advantages of using visible light as a spectrum for significantly boosting...     

CDCSS: cluster-based distributed cooperative spectrum sensing model against primary user emulation (PUE) cyber attacks

In cognitive radio network, the secondary users (SUs) use the spectrum of primary users for communication which arises the security issues. The status of SUs as legitimate users is compulsory for the stability of the system. This paper addresses the issue of delay caused by a band-selection decision process that directly affects the security and performance. The model cluster-based distributed cooperative spectrum sensing is proposed. In this model, cluster heads (CHs) exchange control information with other CHs and ordinary nodes. This model significantly reduced the delay, sensing, convergence, routing, in band-selection process. This also reduces the energy consumption while sensing the spectrum which seriously leads to performance upgradation. The simulated results show the improved performance of cognitive radio networks in terms of delay, packet loss ratio and bandwidth usage as compared to cluster-based cooperative spectrum sensing model. The opportunity for primary user emulation attacker is minimized as the overall delay is reduced.     

Emulating Software Defined Network using Mininet-ns3-WIFI Integration for Wireless Networks

SDN enables a new networking paradigm probable to improve system efficiency where complex networks are easily managed and controlled. SDN allows network virtualization and advance programmability for customizing the behaviour of networking devices with user defined features even at run time. SDN separates network control and data planes. Intelligently controlled network management and operation, such that routing is eliminated from forwarding elements (switches) while shifting the routing logic in a centralized module named SDN Controller. Mininet is Linux based network emulator which is cost effective for implementing SDN having in built support of OpenFlow switches. This paper presents practical implementation of Mininet with ns-3 using Wi-Fi. Previous results reported in literature were limited upto 512 nodes in Mininet. Tests are conducted in Mininet by varying number of nodes in two distinct scenarios based on scalability and resource capabilities of the host system. We presented a low cost and reliable method allowing scalability with authenticity of results in real time environment. Simulation results show a marked improvement in time required for creating a topology designed for 3 nodes with powerful resources i.e. only 0.077 sec and 4.512 sec with limited resources, however with 2047 nodes required time is 1623.547 sec for powerful resources and 4615.115 sec with less capable resources respectively.

     

Novel Cost Efficient Resource Allocation Technique Based on Deadline and Budget Constraints for Edge Users

Wireless Personal Communications - The edge computing paradigm has experienced quick development in recent years. This paradigm is featured by pushing the storage and computational resources closer...     

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.     

Studies to analyse the relationship between IFNα2b gene dosage and its expression,using a Pichia pastoris‐based expression system

Human interferon α2b (hIFNα2b) is the most important member of the interferon family. Escherichia coli, yeasts, mammalian cell cultures and baculovirus‐infected insect cells have been used for expressing recombinant human interferon. Recently a Pichia pastoris‐based expression system has emerged as an attractive system for producing functional human recombinant IFNα2b. In this regard, gene dosage is considered an important factor in obtaining the optimum expression of recombinant protein, which may vary from one protein to another. In the present study we have shown the effect of IFNα2b gene dosage on extracellular expression of IFNα2b recombinant protein from P. pastoris. Constructs containing from one to five repeats of IFNα2b‐expressing cassettes were created via an in vitro multimerization approach. P. pastoris host strain X‐33 was transformed using these expression cassettes. Groups of P. pastoris clones transformed with different copies of the IFNα2b expression cassette were screened for intrachromosomal integration. The IFNα2b expression level of stable transformants was checked. The copy number of integrated IFNα2b was determined by performing qPCR of genomic DNA of recombinant P. patoris clones. It was observed that an increase in copy number generally had a positive effect on the expression level of IFNα2b protein. Regarding the performance of multicopy strains, those obtained from transformation of multicopy vectors showed relatively high expression, compared to those generated using transformation vector having only one copy of IFNα2b. It was also observed that an increase in drug resistance of a clone did not guarantee its high expression, as integration of a marker gene did not always correlate with integration of the gene of interest. Copyright © 2013 John Wiley & Sons, Ltd.     

Impact of hydrogen concentrations on the impedance spectroscopic behavior of Pd-sensitized ZnO nanorods

ZnO nanorods were synthesized using a low-cost sol-gel spin coating technique. The synthesized nanorods were consisted of hexagonal phase having c-axis orientation. SEM images reflected perpendicular ZnO nanorods forming bridging network in some areas. The impact of different hydrogen concentrations on the Pd-sensitized ZnO nanorods was investigated using an impedance spectroscopy (IS). The grain boundary resistance (R_gb) significantly contributed to the sensing properties of hydrogen gas. The boundary resistance was decreased from 11.95 to 3.765 kΩ when the hydrogen concentration was increased from 40 to 360 ppm. IS gain curve showed a gain of 6.5 for 360 ppm of hydrogen at room temperature. Nyquist plot showed reduction in real part of impedance at low frequencies on exposure to different concentrations of hydrogen. Circuit equivalency was investigated by placing capacitors and resistors to identify the conduction mechanism according to complex impedance Nyquist plot. Variations in nanorod resistance and capacitance in response to the introduction of various concentrations of hydrogen gas were obtained from the alternating current impedance spectra.     

Macrocell path loss prediction using artificial intelligence techniques

The prediction of propagation loss is a practical non-linear function approximation problem which linear regression or auto-regression models are limited in their ability to handle. However, some computational Intelligence techniques such as artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFISs) have been shown to have great ability to handle non-linear function approximation and prediction problems. In this study, the multiple layer perceptron neural network (MLP-NN), radial basis function neural network (RBF-NN) and an ANFIS network were trained using actual signal strength measurement taken at certain suburban areas of Bauchi metropolis, Nigeria. The trained networks were then used to predict propagation losses at the stated areas under differing conditions. The predictions were compared with the prediction accuracy of the popular Hata model. It was observed that ANFIS model gave a better fit in all cases having higher R² values in each case and on average is more robust than MLP and RBF models as it generalises better to a different data.