Distributed and Load-Adaptive Self Configuration in Sensor Networks

Proactive self-configuration is crucial for MANETs such as sensor networks, as these are often deployed in hostile environments and are ad hoc in nature. The dynamic architecture of the network is monitored by exchanging so-called Network State Beacons (NSBs) between key network nodes. The Beacon Exchange rate and the network state define both the time and nature of a proactive action to combat network performance degradation at a time of crisis. It is thus essential to optimize these parameters for the dynamic load profile of the network. This paper presents a novel distributed adaptive optimization Beacon Exchange selection model which considers distributed network load for energy efficient monitoring and proactive reconfiguration of the network. The results show an improvement of 70% in throughput, while maintaining a guaranteed quality-of- service for a small control-traffic overhead

Optimizing the beacon exchange rate for proactive autonomic configuration in ubiquitous MANETs

Proactive self-configuration is indispensable for MANETs like ubiquitous sensor networks (USNs), as component devices of the network are usually exposed to natural or man-made disasters due to the hostile deployment and ad hoc nature of the USNs. Network state beacons (NSBs) are exchanged among the key nodes of the network for crucial and effective monitoring of the network for steady state operation. The rate of beacon exchange (F/sub E/) and its contents, define the time and nature of the proactive action. Therefore it is very important to optimize these parameters to tune the functional response of the USN. This paper presents a comprehensive model for monitoring and proactively reconfiguring the network by optimizing the F/sub E/. The results confirm the improved throughput while maintaining QoS over longer periods of network operation

Simulation of continuous variable quantum games without entanglement

A simulation scheme of quantum version of Cournot's Duopoly is proposed, in which there is a new Nash equilibrium that may be also Pareto optimal without any entanglement involved. The unique property of this simulation scheme is decoherence-free against the symmetric photon loss. Furthermore, we analyze the effects of the asymmetric information on this simulation scheme and investigate the case of asymmetric game caused by asymmetric photon loss. A second-order phase transition-like behavior of the average profits of the firm 1 and firm 2 in Nash equilibrium can be observed with the change of the degree of asymmetry of the information or the degree of "virtual cooperation". It is also found that asymmetric photon loss in this simulation scheme plays a similar role with the asymmetric entangled states in the quantum game. PACS numbers: 02.50.Le, 03.67.-aComment: 7 pages, 4 figures, RevTex, some contents have been revise

Simplest Cubic Fields

Let $Q(\alpha)$ be the simplest cubic field, it is known that $Q(\alpha)$ can be generated by adjoining a root of the irreducible equation $x^{3}-kx^{2}+(k-3)x+1=0$, where $k$ belongs to $Q$. In this paper we have established a relationship between $\alpha$, $\alpha'$ and $k,k'$ where $\alpha$ is a root of the equation $x^{3}-kx^{2}+(k-3)x+1=0$ and $\alpha'$ is a root of the same equation with $k$ replaced by $k'$ and $Q(\alpha)=Q(\alpha')$

Laboratory Detection of Novel Corona Virus 2019 Using Polymerase Chain Reaction

Since mid-December 2019, several cases of a pneumonia like disease (with symptoms including fever, difficulty in breathing, cough and invasive lesions on both lungs) of unknown cause have emerged in the central Chinese city of Wuhan. Chinese authorities made a preliminary determination that the causative agent is a novel coronavirus(2019-nCoV). (1) Coronaviruses are enveloped RNA viruses belonging to Coronaviridae family and the order Nidovirales. This subfamily consists of four genera alphacoronavirus, betacoronavirus, gammacoronavirus and deltacoronavirus on the basis of their phylogenetic relationships and genomic structures. These subfamilies are broadly distributed for causing infections in humans and other mammals. (2) The alphacoronaviruses and betacoronaviruses infect only mammals. The gammacoronaviruses and deltacoronaviruses infect birds, but some of them can also infect mammals. The source of betacoronavirus 2019-nCoV is still unknown, although initial cases have been linked with south Huanan seafood market. (3) Viral infections already known to produce similar symptoms are influenza, parainfluenza, Middle East respiratory syndrome (MERS-CoV) and severe acute respiratory syndrome (SARS-CoV). (4) Laboratory investigations reported raised plasma levels of L2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα in patients

MONETARY EXCHANGE RATE MODEL REVISITED: COINTEGRATION AND FORECASTING IN HETEROGENEOUS PANEL DATA

ABSTRACT This study re-examines the exchange rate-monetary fundamentals link with in a panel data framework. Pure time series and pooled time series-based tests fail to find empirical support for monetary exchange rate models (Sarantis (1994) and Groen (2000)). Using recently developed Panel Data Techniques; we would test the exchange rates and monetary fundamentals in a quarterly panel of 19 countries mostly from developed region extending from 1973.1 to 1997.1. Present analysis would be centered on three issues. First, we test whether exchange rates cointegrated with long run determinants predicted by economic theory. For this purpose, we would be employed Pedroni (1997) and Larsson et al (2001) panel cointegration tests for empirical validation of the study. Second, we will also test the short run implications of exchange rate model. These short run implications will be tested; through adapting the panel VEC model the short run identification schemes of Johansen and Juselius (1994). The last issue is to examine the ability for monetary fundamentals to forecast future exchange rate returns. The present endeavor will follow Mark and Sul (2001) approach for forecasting in the case of Panel Data Testing.Panel cointegration; Prediction; Exchange rates.

The Refined Topological Vertex

We define a refined topological vertex which depends in addition on a parameter, which physically corresponds to extending the self-dual graviphoton field strength to a more general configuration. Using this refined topological vertex we compute, using geometric engineering, a two-parameter (equivariant) instanton expansion of gauge theories which reproduce the results of Nekrasov. The refined vertex is also expected to be related to Khovanov knot invariants.Comment: 70 Pages, 23 Figure