A Trustworthy and well-organized data disseminating scheme for ad-hoc wsns

Wireless Sensor Networks (WSNs) generate massive amount of live data and events sensed through dispersedly deployed tiny sensors. This generated data needed to be disseminate to the sink with slight consumption of network resources. One of the ways to efficiently transmit this bulk data is gossiping. An important consideration in gossip-based dissemination protocols is to keep routing table up to date. Considering the inherent resource constrained nature of adhoc wireless sensor networks, we propose a gossip based protocol that consumes little resources. Our proposed scheme aims to keep the routing table size R as low as possible yet it ensures that the diameter is small too. We learned the performance of our proposed protocol through simulations. Results show that our proposed protocol attains major improvement in network reachability and connectivity.Comment: 12 Pages, IJCNC 201

Eigenvalue Ratio Detection Based on Exact Moments of Smallest and Largest Eigenvalues

Detection based on eigenvalues of received signal covariance matrix is currently one of the most effective solution for spectrum sensing problem in cognitive radios. However, the results of these schemes always depend on asymptotic assumptions since the close-formed expression of exact eigenvalues ratio distribution is exceptionally complex to compute in practice. In this paper, non-asymptotic spectrum sensing approach to approximate the extreme eigenvalues is introduced. In this context, the Gaussian approximation approach based on exact analytical moments of extreme eigenvalues is presented. In this approach, the extreme eigenvalues are considered as dependent Gaussian random variables such that the joint probability density function (PDF) is approximated by bivariate Gaussian distribution function for any number of cooperating secondary users and received samples. In this context, the definition of Copula is cited to analyze the extent of the dependency between the extreme eigenvalues. Later, the decision threshold based on the ratio of dependent Gaussian extreme eigenvalues is derived. The performance analysis of our newly proposed approach is compared with the already published asymptotic Tracy-Widom approximation approach

Feature Matching in Iris Recognition System using MATLAB

Iris recognition system is a secure human authentication in biometric technology. Iris recognition system consists of five stages. They are Feature matching, Feature encoding, Iris Normalization, Iris Segmentation and Image acquisition. In Image acquisition, the eye Image is captured from the CASIA database, the Image must have good quality with high resolution to process next steps. In Iris Segmentation, the Iris part is detected by using Hough transform technique and Canny Edge detection technique. Iris from an eye Image segmented. In normalization, the Iris region is converted from the circular region into a rectangular region by using polar transform technique. In feature encoding, the normalized Iris can be encoded in the form of binary bit format by using Gabor filter techniques.  In feature matching, the encoded Iris template is compared with database eye Image of Iris template and generated the matching score by using Hamming distance technique and Euclidean distance technique. Based on the matching score, we get the result. This project is developed using Image processing toolbox of Matlab software

Role of Banks in Money Laundering through Fake Bank Accounts and Writing off Loan in Pakistan: An Analytical Study

Purpose: Recent media reports of money laundering through fake bank accounts implicate the involvement of banks in money laundering through "managed bank accounts". Further the waivers of loan of apparently sound institutions also give rise to specific questions and reservations on the role of banks. This paper attempts to explore the answer to those fundamental questions. Design/Methodology/Approach: The research follows qualitative content analysis methods to critically analyze the role of banks in money laundering and loan waiver policies. Findings: The research finds that despite of heavy banking regulations and laws the banking accounts are being used for money laundering. Further, the research concludes that the act of waiving off loans allegedly has provided a channel to misuse the public earned money, resulting in gross loss to the public exchequer. Implications/Originality/Value: The research concludes that the role of bank in maintaining the fake/idle accounts and the loan waiver policy and its malafide usage in the banking sector resulted in financial frauds and money laundering in Pakista

Role of Medicine Patent Pool (MPP) in Resolving Conflict between Patents and Access to Essential Medicines

This paper analyses the issue from both international intellectual property law and access to medicine with reference to contributions made by Medicine Patent Pool (MPP), an alternate model of resolving conflict between patent protection of medicines and access to medicine. Adoption of Trade-Related Aspects of Intellectual Property Rights (TRIPS) Agreement, under framework of World Trade Organisation (WTO), has significantly altered the enforcement standards of intellectual property rights, especially patent rights (Halewood, 1997).  Although, TRIPS Agreement introduces minimum standards of intellectual property rights protection but in case of pharmaceutical patents, they have impact on access to essential medicines because of strict standards (Kojo, 2018). This paper aims at analysing role of MPP towards solving conflict between patents on medicines and access to medicine

A multi-hop angular routing protocol for wireless sensor networks

In this article, we propose two new routing protocols for wireless sensor networks. First one is AM-DisCNT (angular multi-hop distance-based clustering network transmission) protocol which uses circular deployment of sensors (nodes) for uniform energy consumption in the network. The protocol operates in such a way that nodes with maximum residual energy are selected as cluster heads for each round. Second one is iAM-DisCNT (improved AM-DisCNT) protocol which exploits both mobile and static base stations for throughput maximization. Besides the proposition of routing protocols, iAM-DisCNT is provided with three mathematical models: two linear-programming-based models for information flow maximization and packet drop rate minimization and one model for calculating energy consumption of nodes. Graphical analysis for linear-programming-based mathematical formulation is also part of this work. Simulation results show that AM-DisCNT has 32% and iAM-DisCNT has 48% improved stability period as compared to LEACH (low-energy adaptive clustering hierarchy) and DEEC (distributed energy-efficient clustering) routing protocols. Similarly, throughput of AM-DisCNT and iAM-DisCNT is improved by 16% and 80%, respectively, in comparison with the counterpart schemes. © The Author(s) 2016

CONSTRUCTION OF COMPUTATIONAL 3D STRUCTURES OF PROTEIN DRUG TARGETS OF MYCOBACTERIUM TUBERCULOSIS

Objective: This study aims in constructing a three-dimensional modeled protein structure of potential drug targets in Mycobacterium tuberculosis bacteria. Methods: The protein models were constructed using SWISS-Model online tool. The constructed protein models were submitted in online database called Protein Model Database (PMDB) for public access to the structures. Results: A total of 100 protein sequences of M. tuberculosis were retrieved from UniProt database and were subjected for sequence similarity search and homology model construction. The constructed models were subjected for Ramachandran plot analysis to validate the quality of the structures. A total of 69 structures were considered to be of significant quality and were submitted to the online database PMDB. Conclusion: These predicted structures would help greatly in identification and drug design to various strains of M. tuberculosis that are sensitive and resistant to different antibiotics. This would greatly help in drug development and personalized drug treatment against different strains of the pathogen. This database would significantly support the structure-based computational drug design applications toward personalized medicine in regard to differences in the various strains of the pathogen

Measuring the impact of governance quality on stock market performance in developed countries

The aim of this article is to examine the relationship between stock market performance and country level governance indicators. A good quality of governance in a country ensures effective implementation of laws which can protect the investor and improve stock market performance and vice versa. Our study utilises annual stock returns and country level governance indicators for 25 developed countries from 1996 to 2018. The fixed effect estimation suggests that stock market performance and governance indicators share a positive relationship. Our findings suggest that high quality of governance is associated with higher returns on stock. Institutional quality is a preconditioned for financial developed that set the direction of change to reduce transaction costs and agency costs and make profitable projects available to firms that subsequently leads to higher demand for equity financing. These findings have significant implications for stock market policymakers and standard asset pricing models that only include market risk factors to predict future expected stock return

Lipohypertrophy due to HAART: a case series

A subset of HIV-1 infected patients undergoing Highly Active Antiretroviral Therapy (HAART) develops a lipodystrophy syndrome. It is characterised by loss of subcutaneous adipose tissue (face, limbs and buttocks) visceral fat accumulation and lipomatosis especially in dorsocervical area. In addition these patients show metabolic alteration implicative of metabolic syndrome particularly dyslipidaemia and insulin resistance. These alterations lead to enhanced cardiovascular risk and favour the development of diabetes in such patients. A complex combination of HIV infection, drug treatment related events and lipotoxicity appears to contribute to the development of lipodystrophy syndrome. Active lipolysis in subcutaneous fat combined with impaired storage capacity in subcutaneous depot leads to ectopic deposition of lipids either in visceral or in non-adipose sites. Lipotoxicity, a pathogenic factor in the lipodystrophy syndrome should be considered in the strategies for treating and /or preventing the morphological alterations and systemic metabolic disturbances associated with lipodystrophy