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

Research options for controlling Zoonotic disease in India, 2010-2015

BACKGROUND: Zoonotic infections pose a significant public health challenge for low- and middle-income countries and have traditionally been a neglected area of research. The Roadmap to Combat Zoonoses in India (RCZI) initiative conducted an exercise to systematically identify and prioritize research options needed to control zoonoses in India. METHODS AND FINDINGS: Priority setting methods developed by the Child Health and Nutrition Research Initiative were adapted for the diversity of sectors, disciplines, diseases and populations relevant for zoonoses in India. A multidisciplinary group of experts identified priority zoonotic diseases and knowledge gaps and proposed research options to address key knowledge gaps within the next five years. Each option was scored using predefined criteria by another group of experts. The scores were weighted using relative ranks among the criteria based upon the feedback of a larger reference group. We categorized each research option by type of research, disease targeted, factorials, and level of collaboration required. We analysed the research options by tabulating them along these categories. Seventeen experts generated four universal research themes and 103 specific research options, the majority of which required a high to medium level of collaboration across sectors. Research options designated as pertaining to 'social, political and economic' factorials predominated and scored higher than options focussing on ecological, genetic and biological, or environmental factors. Research options related to 'health policy and systems' scored highest while those related to 'research for development of new interventions' scored the lowest. CONCLUSIONS: We methodically identified research themes and specific research options incorporating perspectives of a diverse group of stakeholders. These outputs reflect the diverse nature of challenges posed by zoonoses and should be acceptable across diseases, disciplines, and sectors. The identified research options capture the need for 'actionable research' for advancing the prevention and control of zoonoses in India

Parametric entropy based Cluster Centriod Initialization for k-means clustering of various Image datasets

One of the most employed yet simple algorithm for cluster analysis is the k-means algorithm. k-means has successfully witnessed its use in artificial intelligence, market segmentation, fraud detection, data mining, psychology, etc., only to name a few. The k-means algorithm, however, does not always yield the best quality results. Its performance heavily depends upon the number of clusters supplied and the proper initialization of the cluster centroids or seeds. In this paper, we conduct an analysis of the performance of k-means on image data by employing parametric entropies in an entropy based centroid initialization method and propose the best fitting entropy measures for general image datasets. We use several entropies like Taneja entropy, Kapur entropy, Aczel Daroczy entropy, Sharma Mittal entropy. We observe that for different datasets, different entropies provide better results than the conventional methods. We have applied our proposed algorithm on these datasets: Satellite, Toys, Fruits, Cars, Brain MRI, Covid X-Ray.Comment: 6 Pages, 2 tables, one algorithm. Accepted for publication in IEEE International Conference on Signal Processing and Computer Vision (SPCV-2023

Empirical Investigation of Debt-Maturity Structure: Evidence from Pakistan

We examine the empirical determinants of debt-maturity structure of 266 firms listed on the KSE over the period 2000 to 2004 using several variants of dynamic panel data models. We find mixed support for the agency cost hypothesis as our results show that debtmaturity increases with the size of the firm; however, growth options do not have any significant influence on debt-maturity structure. Our results lend unambiguous support to the maturity-matching hypothesis as debt-maturity varies inversely with operating activities and directly with the maturity of long-lived assets. Finally, we find evidence that supports the taxbased hypothesis but no evidence to support the signaling hypothesis. Moreover, the results demonstrate that there is a significant dynamic component in the determination of optimal debt-maturity structure of the sampled firms. JEL classification: G32 Keywords: Debt Maturity, Capital Structure, Panel Data, GMM, Pakistan

Bayesian Game Formulation of Power Allocation in Multiple Access Wiretap Channel with Incomplete CSI

In this paper, we address the problem of distributed power allocation in a $K$ user fading multiple access wiretap channel, where global channel state information is limited, i.e., each user has knowledge of their own channel state with respect to Bob and Eve but only knows the distribution of other users' channel states. We model this problem as a Bayesian game, where each user is assumed to selfishly maximize his average \emph{secrecy capacity} with partial channel state information. In this work, we first prove that there is a unique Bayesian equilibrium in the proposed game. Additionally, the price of anarchy is calculated to measure the efficiency of the equilibrium solution. We also propose a fast convergent iterative algorithm for power allocation. Finally, the results are validated using simulation results.Comment: 7 Pages, 2 Figures, submitted for possible publicatio