Neural network based modeling of round rotor synchronous generatorrotor body parameters from operating data

It is generally accepted that in order to account for the effect of eddy currents in the solid rotor-iron of a round-rotor synchronous machine, two or more fictitious rotor-circuits are to be used in each axis of the d- and q-axis equivalent circuit representations of the machine model. This paper presents a novel technique to estimate the parameters of these rotor-circuits (hereinafter referred to as rotor body parameters) from measurements collected online at several operating conditions. The effects of generator saturation, rotor position and loading are included in the estimation process. Tests conducted on a round-rotor synchronous generator reveal that certain rotor-body parameters are nonlinear functions of generator operating condition. A novel artificial neural network (ANN) based technique is used to map variables representative of generator operating condition to each parameter being modeled. The developed ANN models are validated with measurements not used in the modeling process     

Tuning radio resource in an overlay cognitive radio network for TCP: greed isn't good [Accepted from Open Call]

In this article we illustrate the performance of Transmission Control Protocol in an overlay cognitive radio network under dynamic spectrum access. We show that the performance of TCP in overlay CR networks that implement DSA to be quite different from its performance in conventional networks, which do not allow DSA. The key difference is that secondary users in an overlay CR network have to cope with a new type of loss called service interruption loss, due to the existence of primary users. We demonstrate on an NS2 simulation testbed the surprising result: Excessive radio resource usage leads to a decrease in aggregate TCP throughput. This behavior is in contrast to the behavior of TCP in conventional networks, where throughput increases monotonically with the available radio resource.     

Deletion of the putative effector region of Era, an essential GTP-binding protein in Escherichia coli, causes a dominant-negative phenotype

Gangliosides are highly immunosuppressive molecules but the mechanism(s) by which they act upon cells remains to be fully defined. Several metabolic products of exogenous gangliosides, including ceramide, have recently been suggested as second messengers in programmed cell death (PCD). Therefore, we have probed the role of gangliosides and ceramides in the induction of PCD and in the inhibition of in vitro lymphoproliferation. PCD was caused only by exogenous ceramides with short fatty acyl groups-d18:1-C2:0 (C2-ceramide, where d18:1 is sphingosine and C2:O is an acetyl group) and d18:1-C6:0 (C6-ceramide, where C6:O is a hexanoyl group). None of the gangliosides studied induced PCD, including naturally occurring GM3, synthetic d18:1-C18:0 GM3 (C18-Cer GM3, where C18:0 is a stearoyl group), or even d18:1-C2:0 GM3 (C2-Cer GM3), which itself contains a PCD-causing ceramide. However, these gangliosides were highly immunosuppressive, inhibiting antigen-induced lymphoproliferation at micromolar concentrations. We conclude that exogenous sphingolipids cause inhibition of lymphoproliferation and PCD by two separate and distinct mechanisms of action.     

Neural network based saturation model for round rotor synchronousgenerator

This paper presents an artificial neural network (ANN) based technique to model saturation for a round rotor synchronous generator. The effects of excitation level, rotor angle, and real power generation on generator saturation are included in the modeling process. To illustrate the technique, small excitation disturbance tests are conducted on a 7.5 kVA, 240 V, 60 Hz round rotor synchronous generator at various levels of excitation and loading. The small excitation disturbance responses are processed by a recursive maximum likelihood algorithm to yield estimates of mutual inductances L_ad and L _aq at each operating condition. By developing a suitable training pattern, variables representative of generator operating condition are mapped to mutual inductances L_ad and L_aq . The developed models are validated with measurements not used in the training process and with large disturbance responses     

A Price Based Decentralized Rate Selection in IEEE 802.11 Based WLANS

We consider the problem of decentralized rate selection in IEEE 802.11 wireless local area networks (WLANs). Owing to the decentralized nature of WLANs, we formulate the current problem of rate selection as a non-cooperative game where individual users (players) of a WLAN can pick their actions from a finite set of physical layer modulation rates. The utility of each user is the difference of throughput and a cost incurred due to the price imposed by the access point. We prove the resulting non-cooperative game to be supermodular, and hence has at least one pure strategy Nash equilibrium, that is contained in a set bounded by the smallest and largest Nash equilibria. We also prove the smallest and largest Nash equilibria to be non-decreasing functions of the price and the smallest Nash equilibrium to be Pareto-dominant. We present an algorithm to compute the best response of each user asynchronously, that converges almost surely to the smallest Nash equilibrium of the game. Next we extend our price based approach to the multi-channel case and prove the resulting game to be supermodular in the special case of two channels. Our simulation results demonstrate the improvement in overall network throughput with appropriate tuning of the price.     

Neural network observers for on-line tracking of synchronousgenerator parameters

This paper presents a methodology for implementing artificial neural network (ANN) observers in estimating and tracking synchronous generator parameters from time-domain online disturbance measurements. Data for training the neural network observers are obtained through offline simulations of a synchronous generator operating in a one-machine-infinite-bus environment. Nominal values of parameters are used in the machine model. After training, the ANN observer is tested with simulated online measurements to provide estimates of unmeasurable rotor body currents and in tracking simulated changes in machine parameters     

Localizing non‐line‐of‐sight nodes in Vehicluar Adhoc Networks using gray wolf methodology

Vehicular ad hoc networks (VANETs) evolved by adopting the principles of mobile ad hoc networks. This network has been designed to deploy safety related application in vehicular node in the less chaotic environment in road scenarios. Vehicles exchange emergency messages through direct communication. In a practical situation, a direct communication between the vehicles is not possible, and it is prohibited by either static or dynamic obstacles. These obstacles prevent the direct communication between the vehicles and can craft a situation like non‐line of sight (NLOS). This NLOS becomes a perennial problem to the researchers as it creates localization and integrity issues which are considered to be important for road safety applications. Handling the moving obstacles is found to be a challenging one in the VANET environment as obstacles like truck are found to have similar characteristics of the vehicular nodes. This paper utilizes the merits of the meta‐heuristic approach and makes use of the improved gray wolf optimization algorithm for improving the localization and integrity services of the VANET by overcoming the NLOS conditions. The proposed methodology is found to have improved neighborhood awareness, reduced latency, improved emergency message delivery rate, and reduced mean square error rate.     

Flow regimes in a turbulent bed contactor

Experiments were conducted in a turbulent bed contactor (TBC) with and without downcomer operating in Type I and Type II modes to obtain the flow regime maps. The variables include flow rate of the gas and liquid phases, size and density of the particles, bed height, free open area of the supporting grid, and diameter and weir height of the downcomer. Static, partially fluidized, completely fluidized, flooding and annular regimes are identified depending on geometric and operating conditions. The effect of these variables on flow maps is discussed and correlations are proposed for delineating the flow regimes.