Hierarchical Design Based Intrusion Detection System For Wireless Ad hoc Network

In recent years, wireless ad hoc sensor network becomes popular both in civil and military jobs. However, security is one of the significant challenges for sensor network because of their deployment in open and unprotected environment. As cryptographic mechanism is not enough to protect sensor network from external attacks, intrusion detection system needs to be introduced. Though intrusion prevention mechanism is one of the major and efficient methods against attacks, but there might be some attacks for which prevention method is not known. Besides preventing the system from some known attacks, intrusion detection system gather necessary information related to attack technique and help in the development of intrusion prevention system. In addition to reviewing the present attacks available in wireless sensor network this paper examines the current efforts to intrusion detection system against wireless sensor network. In this paper we propose a hierarchical architectural design based intrusion detection system that fits the current demands and restrictions of wireless ad hoc sensor network. In this proposed intrusion detection system architecture we followed clustering mechanism to build a four level hierarchical network which enhances network scalability to large geographical area and use both anomaly and misuse detection techniques for intrusion detection. We introduce policy based detection mechanism as well as intrusion response together with GSM cell concept for intrusion detection architecture.Comment: 16 pages, International Journal of Network Security & Its Applications (IJNSA), Vol.2, No.3, July 2010. arXiv admin note: text overlap with arXiv:1111.1933 by other author

Role of Mothers\u27 Nutritional Knowledge, Nutritional Factors on the School Performance

A cross sectional study was carried out to investigate the effects of mothers\u27 nutritional knowledge, health and nutritional factors and socio-economic parameters on school performance among class five students of University Laboratory School, Dhaka. All of the eighty students were selected for this study. This study found there is a strong relationship between mother\u27s knowledge score and school performance. It was found that mothers\u27 knowledge score was responsible for 91.1 percent change in school performance. The mean BMI of the mothers was 20.44. We found that the school performance measured by class roll number of the students is significantly related with mothers BMI. There was an imperfect negative association between socio-economic parameters and school performance. But the relationship between the school performances with socio-economic parameters was strongly significant. This study also observed the relationship between Individual Dietary Diversity Score (IDDS) of respondent and marks achieved in class 4 final exam. It is alarming that consumption percentage were low for eggs (30) and milk and milk products (37.5), but majority of the students who consumed milk and milk products (63.3%) and eggs (66.7%) got the highest marks

Algorithms to Compute the Lyndon Array

We first describe three algorithms for computing the Lyndon array that have been suggested in the literature, but for which no structured exposition has been given. Two of these algorithms execute in quadratic time in the worst case, the third achieves linear time, but at the expense of prior computation of both the suffix array and the inverse suffix array of x. We then go on to describe two variants of a new algorithm that avoids prior computation of global data structures and executes in worst-case n log n time. Experimental evidence suggests that all but one of these five algorithms require only linear execution time in practice, with the two new algorithms faster by a small factor. We conjecture that there exists a fast and worst-case linear-time algorithm to compute the Lyndon array that is also elementary (making no use of global data structures such as the suffix array)

Loss functions, utility functions and Bayesian sample size determination.

PhDThis thesis consists of two parts. The purpose of the first part of the research is to obtain Bayesian sample size determination (SSD) using loss or utility function with a linear cost function. A number of researchers have studied the Bayesian SSD problem. One group has considered utility (loss) functions and cost functions in the SSD problem and others not. Among the former most of the SSD problems are based on a symmetrical squared error (SE) loss function. On the other hand, in a situation when underestimation is more serious than overestimation or vice-versa, then an asymmetric loss function should be used. For such a loss function how many observations do we need to take to estimate the parameter under study? We consider different types of asymmetric loss functions and a linear cost function for sample size determination. For the purposes of comparison, firstly we discuss the SSD for a symmetric squared error loss function. Then we consider the SSD under different types of asymmetric loss functions found in the literature. We also introduce a new bounded asymmetric loss function and obtain SSD under this loss function. In addition, to estimate a parameter following a particular model, we present some theoretical results for the optimum SSD problem under a particular choice of loss function. We also develop computer programs to obtain the optimum SSD where the analytic results are not possible. In the two parameter exponential family it is difficult to estimate the parameters when both are unknown. The aim of the second part is to obtain an optimum decision for the two parameter exponential family under the two parameter conjugate utility function. In this case we discuss Lindley’s (1976) optimum decision for one 6 parameter exponential family under the conjugate utility function for the one parameter exponential family and then extend the results to the two parameter exponential family. We propose a two parameter conjugate utility function and then lay out the approximation procedure to make decisions on the two parameters. We also offer a few examples, normal distribution, trinomial distribution and inverse Gaussian distribution and provide the optimum decisions on both parameters of these distributions under the two parameter conjugate utility function

Structural, elastic, and electronic properties of newly discovered Li2PtSi3 superconductor: Effect of transition metals

First-principles calculations within the density functional theory (DFT) with GGA-PBE exchange-correlation scheme have been employed to predict the structural, the elastic and the electronic properties of newly discovered lithium silicide superconductor, Li2PtSi3, for the first time. All the theoretical results are compared with those calculated recently for isostructural Li2IrSi3. The present study sheds light on the effect of replacement of transition metal element Ir with Pt on different mechanical, electronic, and superconducting properties. The effect of spin-orbit coupling on electronic band structure was found to be insignificant for Li2PtSi3. The difference in superconducting transition temperatures of Li2PtSi3 and Li2IrSi3 arises primarily due to the difference in electronic energy density of states at the Fermi level. Somewhat reduced Debye temperature in Li2PtSi3 plays a minor role. We have discussed the implications of the theoretical results in details in this study.Comment: Submitted for publicatio