Previous Messages Provide the Key to Achieve Shannon Capacity in a Wiretap Channel

We consider a wiretap channel and use previously transmitted messages to generate a secret key which increases the secrecy capacity. This can be bootstrapped to increase the secrecy capacity to the Shannon capacity without using any feedback or extra channel while retaining the strong secrecy of the wiretap channel.Comment: Accepted for IEEE International Conference on Communications Workshop (ICC) 2013, Budapest, Hungary. arXiv admin note: text overlap with arXiv:1404.570

Resource Allocation in a MAC with and without security via Game Theoretic Learning

In this paper a $K$-user fading multiple access channel with and without security constraints is studied. First we consider a F-MAC without the security constraints. Under the assumption of individual CSI of users, we propose the problem of power allocation as a stochastic game when the receiver sends an ACK or a NACK depending on whether it was able to decode the message or not. We have used Multiplicative weight no-regret algorithm to obtain a Coarse Correlated Equilibrium (CCE). Then we consider the case when the users can decode ACK/NACK of each other. In this scenario we provide an algorithm to maximize the weighted sum-utility of all the users and obtain a Pareto optimal point. PP is socially optimal but may be unfair to individual users. Next we consider the case where the users can cooperate with each other so as to disagree with the policy which will be unfair to individual user. We then obtain a Nash bargaining solution, which in addition to being Pareto optimal, is also fair to each user. Next we study a $K$-user fading multiple access wiretap Channel with CSI of Eve available to the users. We use the previous algorithms to obtain a CCE, PP and a NBS. Next we consider the case where each user does not know the CSI of Eve but only its distribution. In that case we use secrecy outage as the criterion for the receiver to send an ACK or a NACK. Here also we use the previous algorithms to obtain a CCE, PP or a NBS. Finally we show that our algorithms can be extended to the case where a user can transmit at different rates. At the end we provide a few examples to compute different solutions and compare them under different CSI scenarios.Comment: 27 pages, 12 figures. Part of the paper was presented in 2016 IEEE Information theory and applicaitons (ITA) Workshop, San Diego, USA in Feb. 2016. Submitted to journa

Impact of Play on Early Childhood

In this essay, the concept of play is explored within the context of early childhood education, emphasizing its definition, functions, and developmental significance. This study examines many theoretical viewpoints and their consequences as it explores the multidimensional character of play, drawing on the insights of scholars and researchers. It also looks at specific types of play, such as play in the outdoors, play for children with special needs, and play's relationship to education. This investigation emphasizes the critical role that play plays in early childhood and development, emphasizing the value of play in promoting learning experiences and holistic growth

Enhancement of Map Function Image Processing System using DHRF Algorithm on Big Data in the Private Cloud Tool

Cloud computing is the concept of distributing a work and also processing the same work over the internet. Cloud computing is called as service on demand. It is always available on the internet in Pay and Use mode. Processing of the Big Data takes more time to compute MRI and DICOM data. The processing of hard tasks like this can be solved by using the concept of MapReduce. MapReduce function is a concept of Map and Reduce functions. Map is the process of splitting or dividing data. Reduce function is the process of integrating the output of the Map2019;s input to produce the result. The Map function does two various image processing techniques to process the input data. Java Advanced Imaging (JAI) is introduced in the map function in this proposed work. The processed intermediate data of the Map function is sent to the Reduce function for the further process. The Dynamic Handover Reduce Function (DHRF) algorithm is introduced in the reduce function in this work. This algorithm is implemented in the Reduce function to reduce the waiting time while processing the intermediate data. The DHRF algorithm gives the final output by processing the Reduce function. The enhanced MapReduce concept and proposed optimized algorithm is made to work on Euca2ool (a Cloud tool) to produce an effective and better output when compared with the previous work in the field of Cloud Computing and Big Data

Life Testing Analysis of Failure Censored Generalized Exponentiated Data

A generalized exponential distribution is considered for analyzing lifetime data; such statistical models are applicable when the observations are available in an ordered manner. This study examines failure censored data, which consist of testing n items and terminating the experiment when a pre-assigned number of items, for example r ( \u3c n), have failed. Due to scale and shape parameters, both have flexibility for analyzing different types of lifetime data. This distribution has increasing, decreasing and a constant hazard rate depending on the shape parameter. This study provides maximum likelihood estimation and uniformly minimum variance unbiased techniques for the estimation of reliability of a component. Numerical computation was conducted on a data set and a comparison of the performance of two different techniques is presented