A Secure Authentication Scheme for RFID Systems

AbstractDay by day the importance of Radio Frequency Identification (RFID) systems is increasing for its powerful capabilities in automatic identification, localization and access control of the objects. However, the RFID techniques are plagued to security and privacy issues due to underlying wireless communication channel. In order to come up with a solution, we propose an efficient authentication scheme which uses pseudorandom number generators (PRNG) and some simple cryptographic operations. Moreover, as the current generation tags come with in-built pseudo random generators, the implementations of these operations are possible with low complexity. The secret information stored inside the tags is communicated in a more secure way ensuring confidentiality, integrity, and authentication. The security of our proposed scheme is analyzed against different attacks on RFID and with the performance of some existing protocols. Experimental results show a significant improvement in security with average cost, when compared with the existing techniques

EMPLOYEES PERCEPTION OF VIOLATION OF NORMS OF JUSTICE AND ITS RELATION WITH INTENTION TO LEAVE AND ORGANIZATIONAL CITIZENSHIP BEHAVIOUR

Purpose: The present research work was done to study the employees’ perception of Violation of Norms of Justice in Public and Private Organizations and also its relation to the outcome variables like Organizational Citizenship Behaviour (OCB) and Intention to Leave.Design/Methodology/Approach: The study was done on 250 employees of Public and Private Organizations (125 from each). By an interview done on some of the employees from both the sectors i.e. Public and Private, a scale for measuring perceived violation of norms of justice was developed. For measuring other variables, standard scales were used. Data were collected through questionnaire method. For analysis, correlational method and t-test were used.Findings: Results showed that Public and Private sector employees differed significantly in their perception of violation of norms of justice. Results also showed that the employees’ perception of violation of norms of justice is negatively related with the outcome variables like Organizational Citizenship Behaviour (OCB) and Intention to LeavePractical Implications: The study has implications for scholars of organizational behavior, to look into the organizational problems from the perspective of employees i.e. what do the employees think of existing social norms.Social Implications: This study shows that employees/humans are vital factors in the running/success of any organizations/society.Originality: The research is original in the sense that it tries to compare employees’ perception of Justice Norms in both Public and Private Organizations

MicroRNA-424/503 cluster involvement in regulation of bovine granulosa cell function and oocyte maturation

Several microRNA (miRNA) clusters are known to be differentially regulated during follicular development. Previously, it was reported that the miR-424/503 cluster was highly abundant in bovine granulosa cells (bGCs) of preovulatory dominant follicles compared to subordinate counterparts. However, the underlying mechanisms of this miRNA cluster in bGCs functions and oocyte maturation have not been investigated. Here, we aimed to investigate the role of miR-424/503 cluster in bGCs function and oocyte maturation. Target gene validation assay using luciferase reporter showed that SMAD7 and ACVR2A are the direct targets of the miR-424/503 cluster. In line with this, while overexpression of miR- 424/503 reduced, inhibition increased the expression of SMAD7 and ACVR2A genes. Furthermore, flow cytometric analysis indicated that overexpression of miR-424/503 cluster enhanced bGCs proliferation by promoting G1 to S phase cell cycle transition. Moreover, knockdown of the miR-424/503 cluster target gene using small interfering RNA also revealed similar phenotypic and molecular alterations when miR-424/503 cluster was overexpressed. Further, increased cell proliferation and downregulation of both miR-424/503 and its target gene with activin A treatment, indicated the presence of negative feedback loop between activin A and the miR-424/503 cluster. Moreover, expression of miR-424/503 was significantly higher at mature cumulus-oocyte complexes (COCs) (MII) compared to immature COCs (GV) in both cumulus and oocytes. Additionally, overexpression of miR-424 enhanced the expression of genes associated with cumulus cell expansion such as EGFR, PTGS2, PTX3 and MAPK1 and also increased the expression of KIT ligand gene associated with oocyte growth. In conclusion, the miR-424/503 cluster regulates bovine granulosa cell proliferation by targeting SMAD7 via activin signalling pathway and enhances the candidate gene expression involved in cumulus cell expansion and oocyte maturation.Die Beteiligung des microRNA-424/503-Clusters an der Regulation der Rinder- Granulosazellenfunktion und der Oozytenreifung Es ist bekannt, dass mehrere microRNA (miRNA) Cluster während der follikulären Entwicklung unterschiedlich reguliert sind. In vorherigen Studien wurde bereits berichtet, dass die Expression des miR-424/503-Clusters in Rinder-Granulosazellen (bGCs) von präovulatorischen dominanten Follikeln im Vergleich zu subordinanten Follikeln verstärkt auftritt. Die zugrunde liegenden Mechanismen dieses miRNA-Clusters in bGCs-Funktionen und Oozytenreifung wurden jedoch noch nicht betrachtet. Daher wollten wir in dieser Studie die Funktion des miR-424/503-Clusters in bGCs und der Eizellreifung untersuchen. Ein Target-Gen-Validierungsassay unter Verwendung des Luciferase-Reporter Systems zeigte, dass SMAD7 und ACVR2A die direkten Zielgene des miR-424/503-Clusters sind. In Übereinstimmung damit, während die Überexpression von miR-424/503 reduziert wurde, erhöhte die Inhibierung die Expression der Gene SMAD7 und ACVR2A. Darüber hinaus zeigte die Durchflusszytometrieanalyse, dass die Überexpression des miR-424/503-Clusters die bGCs-Proliferation durch die Stimulierung des G1-zu-S-Phasen-Zellzyklusübergangs verstärkt. Weiterhin ergab die Ausschaltung des miR-424/503-Clusters Zielgene mit siRNA ähnliche phänotypische und molekulare Veränderungen, wie während einer Überexpression des miR-424/503-Clusters. Eine erhöhte Zellproliferation und eine Herunterregulation sowohl von miR-424/503 als auch seiner Zielgene nach Activin A-Behandlung impliziert das Vorhandensein einer negativen Rückkopplungsschleife zwischen Activin A und dem miR- 424/503-Cluster. Darüber hinaus war die Expression von miR-424/503 in reifen Kumulus- Oozyten-Komplexen (COCs) (MII) signifikant höher als in unreifen COCs (GV) sowohl in den Kumuluszellen als auch in den Oozyten. Zusätzlich verstärkte die Überexpression von miR-424 die Expression von Genen, die mit der Kumulus-Expansion assoziiert sind, wie z.B. EGFR, PTGS2, PTX3 und MAPK1 und erhöhte auch die Expression des KIT-Ligandengens, das mit dem Oozytenwachstum assoziiert ist. Zusammenfassend lässt sich sagen, dass der miR-424/503-Cluster die Rinder-Granulosazellproliferation reguliert, indem er SMAD7 über den Activin-Signalweg aktiviert und die Expression von Kandidatengenen für die Kumuluszell-Expansion und Oozytenreifung erhöht

A Convex Reconstruction Model for X-ray Tomographic Imaging with Uncertain Flat-fields

Classical methods for X-ray computed tomography are based on the assumption that the X-ray source intensity is known, but in practice, the intensity is measured and hence uncertain. Under normal operating conditions, when the exposure time is sufficiently high, this kind of uncertainty typically has a negligible effect on the reconstruction quality. However, in time- or dose-limited applications such as dynamic CT, this uncertainty may cause severe and systematic artifacts known as ring artifacts. By carefully modeling the measurement process and by taking uncertainties into account, we derive a new convex model that leads to improved reconstructions despite poor quality measurements. We demonstrate the effectiveness of the methodology based on simulated and real data sets.Comment: Accepted at IEEE Transactions on Computational Imagin

Probabilistic game approaches for network cost allocation

In a restructured power market, the network cost is to be allocated between multiple players utilizing the system in varying capacities. Cooperative game approaches based on Shapley value and Nucleolus provide stable models for embedded cost allocation of power networks. Varying network usage necessitates the introduction of probabilistic approaches to cooperative games. This paper proposes a variety of probabilistic cooperative game approaches. These have variably been modeled based upon the probability of existence of players, the probability of existence of coalitions, and the probability of players joining a particular coalition along with their joining in a particular sequence. Application of these approaches to power networks reflects the system usage in a more justified way. Consistent and stable results qualify the application of probabilistic cooperative game approaches for cost allocation of power networks.Cooperative games, embedded cost allocation, probabilistic games, transmission pricing

Parameter Estimation of Unstable Aircraft using Extreme Learning Machine

The parameter estimation of unstable aircraft using extreme learning machine method is presented. In the past, conventional methods such as output error method, filter error method, equation error method and non-conventional method such as artificial neural-network based methods have been used for aircraft’s aerodynamic parameter estimation. Nowadays, a trend of finding an accurate nonlinear function approximation is required to represent the aircraft’s equations-of-motion. Such type of nonlinear function approximation is usually achieved using artificial neural-network which is trained with the aircraft input-output flight data using a training algorithm. The accuracy of estimated parameters, which is achieved using the trained network, is highly dependent on the generalisation capability of the network which can be improved using extreme learning machine based network in contrast to artificial neural-network. To estimate the unstable aircraft parameters from the simulated flight data, Gauss-Newton based optimisation method has been used with a predefined aerodynamic model using the trained network. Further, the confidence of the estimated parameters has been shown in comparison to that of the standard parameter estimation methods in terms of the Cramer-Rao bounds