Three Dimensional Quantum Gravity Coupled to Ising Matter

We establish the phase diagram of three--dimensional quantum gravity coupled to Ising matter. We find that in the negative curvature phase of the quantum gravity there is no disordered phase for ferromagnetic Ising matter because the coordination number of the sites diverges. In the positive curvature phase of the quantum gravity there is evidence for two spin phases with a first order transition between them.Comment: 12 page

GTRSSN: Gaussian trust and reputation system for sensor networks

This paper introduces a new Gaussian trust and reputation system for wireless sensor networks based on sensed continuous events to address security issues and to deal with malicious and unreliable nodes. It is representing a new approach of calculating trust between sensor nodes based on their sensed data and the reported data from surrounding nodes. It is addressing the trust issue from a continuous sensed data which is different from all other approaches which address the issue from communications and binary point of view. © Springer Science+Business Media B.V. 2008

Topology of event distribution as a generalized definition of phase transitions in finite systems

We propose a definition of phase transitions in finite systems based on topology anomalies of the event distribution in the space of observations. This generalizes all the definitions based on the curvature anomalies of thermodynamical potentials and provides a natural definition of order parameters. The proposed definition is directly operational from the experimental point of view. It allows to study phase transitions in Gibbs equilibria as well as in other ensembles such as the Tsallis ensemble.Comment: 4 pages, 3 figure

Theory of hydrogen pairing in yttrium

Journal ArticleThe energetics of hydrogen atoms interacting with yttrium have been investigated using the self-consistent cluster model and the local-density approximation. Our results provide a theoretical understanding of a range of novel phenomena observed recently in resistivity, neutron scattering, NMR, and channeling experiments. These include pairing of hydrogen at low temperatures and the pairs' structural origin, the anomalous fast diffusion of hydrogen along the pairing axis compared to the bulk rate, and the lack of long-range order between the pairs in the metal matrix

Bayesian fusion algorithm for inferring trust in wireless sensor networks

This paper introduces a new Bayesian fusion algorithm to combine more than one trust component (data trust and communication trust) to infer the overall trust between nodes. This research work proposes that one trust component is not enough when deciding on whether or not to trust a specific node in a wireless sensor network. This paper discusses and analyses the results from the communication trust component (binary) and the data trust component (continuous) and proves that either component by itself, can mislead the network and eventually cause a total breakdown of the network. As a result of this, new algorithms are needed to combine more than one trust component to infer the overall trust. The proposed algorithm is simple and generic as it allows trust components to be added and deleted easily. Simulation results demonstrate that a node is highly trustworthy provided that both trust components simultaneously confirm its trustworthiness and conversely, a node is highly untrustworthy if its untrustworthiness is asserted by both components. © 2010 ACADEMY PUBLISHER

Statistical Mechanics in the Extended Gaussian Ensemble

The extended gaussian ensemble (EGE) is introduced as a generalization of the canonical ensemble. The new ensemble is a further extension of the Gaussian ensemble introduced by J. H. Hetherington [J. Low Temp. Phys. {\bf 66}, 145 (1987)]. The statistical mechanical formalism is derived both from the analysis of the system attached to a finite reservoir and from the Maximum Statistical Entropy Principle. The probability of each microstate depends on two parameters $\beta$ and $\gamma$ which allow to fix, independently, the mean energy of the system and the energy fluctuations respectively. We establish the Legendre transform structure for the generalized thermodynamic potential and propose a stability criterion. We also compare the EGE probability distribution with the $q$-exponential distribution. As an example, an application to a system with few independent spins is presented.Comment: Revtex 4, 8 pages, 8 figure

Can we trust trusted nodes in wireless sensor networks?

In this paper we extend our previously designed trust model in wireless sensor networks to include both; communication trust and data trust. Trust management in wireless sensor networks is predominantly based on routing messages; whether the communication has happened or not (successful and unsuccessful transactions). The uniqueness of sensing data in wireless sensor networks introduces new challenges in calculating trust between nodes (data trust). If the overall trust is based on just the communication trust, it might mislead the network, that is; untrustworthy nodes in terms of sensed data can be classified as trusted nodes due to their communication capabilities. Hence we need to develop new trust models to address the issue of the actual sensed data. Here we are comparing the two trust models and proving that one model by itself is not enough to decide on the trustworthiness of a node, so new techniques are required to combine both data trust and communication trust. ©2008 IEEE

Accuracy Studies of a Magnetometer-Only Attitude-and-Rate-Determination System

A personal computer based system was recently prototyped that uses measurements from a three axis magnetometer (TAM) to estimate the attitude and rates of a spacecraft using no a priori knowledge of the spacecraft's state. Past studies using in-flight data from the Solar, Anomalous, and Magnetospheric Particles Explorer focused on the robustness of the system and demonstrated that attitude and rate estimates could be obtained accurately to 1.5 degrees (deg) and 0.01 deg per second (deg/sec), respectively, despite limitations in the data and in the accuracies of te truth models. This paper studies the accuracy of the Kalman filter in the system using several orbits of in-flight Earth Radiation Budget Satellite (ERBS) data and attitude and rate truth models obtained from high precision sensors to demonstrate the practical capabilities. This paper shows the following: Using telemetered TAM data, attitude accuracies of 0.2 to 0.4 deg and rate accuracies of 0.002 to 0.005 deg/sec (within ERBS attitude control requirements of 1 deg and 0.0005 deg/sec) can be obtained with minimal tuning of the filter; Replacing the TAM data in the telemetry with simulated TAM data yields corresponding accuracies of 0.1 to 0.2 deg and 0.002 to 0.005 deg/sec, thus demonstrating that the filter's accuracy can be significantly enhanced by further calibrating the TAM. Factors affecting the fillter's accuracy and techniques for tuning the system's Kalman filter are also presented

Modelling Trust In Wireless Sensor Networks from the Sensor Reliability Prospective

This paper surveys the state of the art trust-based systems in Wireless Sensor Networks (WSN); it highlights the difference between Mobile ad hoc networks (MANET) and WSN and based on this observed difference (monitoring events and reporting data) a new trust model is introduced, which takes sensor reliability as a component of trust. A new definition of trust is created based on the newly introduced component of trust (sensor data) and an extension of node misbehaviour classification is also presented based on this new component of trust

RBATMWSN: Recursive Bayesian approach to trust management in wireless sensor networks

This paper introduces a new trust model and a reputation system for wireless sensor networks based on a sensed continuous data. It establishes the continuous version of the beta reputation system introduced in [1] and applied to binary events and presents a new Gaussian Reputation System for Sensor Networks (GRSSN) . We introduce a theoretically sound Bayesian probabilistic approach for mixing second-hand information from neighbouring nodes with directly observed information. ©2007 IEEE