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Journal of Information and Data Management

ISSN 2166 - 6261 (Print)

ISSN 2166 - 6288 (Online)

Website: http://www.researchpub.org/journal/jidm/jidm.html

 
 

Volterra Kernel Identification by Wavelet Networks and its Applications to Nonlinear Nonstationary Time Series
Author(s) Minu.K.K. and Jessy John.C.


Abstract
Volterra series representation is the earliest method for the description of a nonlinear system. Volterra kernels completely characterize the Volterra series. Volterra series has been extended to incorporate the non stationarity. Even though Volterra series modeling was suggested much earlier, no canonical method for the identification of the Volterra kernel was available due to the exponential growth of parameters in the kernel with the order of expansion. Developments in the theories of Artificial Neural Networks and Wavelets gave rise to the concept of Wavelet Networks which are found to be effective in modeling the nonlinear nonstationary structures. In this paper a method for identifying the Volterra kernels is developed by applying Wavelet Network. Thereby the Volterra series is applied for the analysis of nonlinear nonstationary time series providing a powerful method in the analysis of nonlinear nonstationary time series, which appear quite often in various fields of study.


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Variability of Electrojet Strength along the Magnetic Equator Using MAGDAS/CPMN Data
Author(s) Abbas M., Joshua B. D. Bonde, Adimula I. A., A. B. Rabiu and O.R. Bello


Abstract
One year data of hourly values of H component of the earth magnetic field were used to study the magnetic strength of some selected stations along the 96O Magnetic Meridian (MM). The results revealed that the amplitude of dH has diurnal variation which peaks during the day at about local noon. This diurnal variation in H component is attributed to the enhancement dynamo action at this region. The diurnal variation along the 960 MM reveals a clear nocturnal minimum variation which could be attributed to distant current of non-ionospheric origin. The observed minimum variation could be as a result of a partial ring current. The electrojet strength at Addis Ababa with respect to Khartoum are 44.05 nT,60 nT and 12.88 nT for January, February and August around local noon, which is stronger than the electrojet strength observed with respect to Nairobi, 40.86 nT,42.41 nT and 19.12 nT .However, the pre-noon and post-noon minimum variation may be attributed to distant magnetospheric current.


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Analysis of a New Random Key Pre-distribution Scheme for WSN Based on Random Graph Theory and Kryptograph
Author(s) Seema Verma and Prachi


Abstract
Wireless Sensor Networks (WSNs) vast myriad of futuristic applications makes it matter of incessant research interest. Key management is crucial for WSN due to their high security requirements and resource constrained nature. Randomized key pre-distribution seems to be best suited solution for WSN due to scarceness of resources. However, most of the earlier proposed schemes are based on random graph theory model which is not that suitable for WSN. In this paper we present and implement a new randomized key pre-distribution scheme on TinyOS. Later on, we perform a rigorous mathematical analysis of our scheme under random graph theory on which most of the earlier proposed schemes are based and recently introduced kryptograph model. Our results prove that kryptograph model is more vital for secure WSNs.


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