15,428 research outputs found
An Overview on Application of Machine Learning Techniques in Optical Networks
Today's telecommunication networks have become sources of enormous amounts of
widely heterogeneous data. This information can be retrieved from network
traffic traces, network alarms, signal quality indicators, users' behavioral
data, etc. Advanced mathematical tools are required to extract meaningful
information from these data and take decisions pertaining to the proper
functioning of the networks from the network-generated data. Among these
mathematical tools, Machine Learning (ML) is regarded as one of the most
promising methodological approaches to perform network-data analysis and enable
automated network self-configuration and fault management. The adoption of ML
techniques in the field of optical communication networks is motivated by the
unprecedented growth of network complexity faced by optical networks in the
last few years. Such complexity increase is due to the introduction of a huge
number of adjustable and interdependent system parameters (e.g., routing
configurations, modulation format, symbol rate, coding schemes, etc.) that are
enabled by the usage of coherent transmission/reception technologies, advanced
digital signal processing and compensation of nonlinear effects in optical
fiber propagation. In this paper we provide an overview of the application of
ML to optical communications and networking. We classify and survey relevant
literature dealing with the topic, and we also provide an introductory tutorial
on ML for researchers and practitioners interested in this field. Although a
good number of research papers have recently appeared, the application of ML to
optical networks is still in its infancy: to stimulate further work in this
area, we conclude the paper proposing new possible research directions
A STATISTICAL EXAMINATION OF YIELD SWITCHING FRAUD IN THE FEDERAL CROP INSURANCE PROGRAM
An over-parameterized statistical yield-switching-fraud model is developed. Over-parameterized procedures are reviewed. Five percent of 206,952 producers (thirteen percent in one state) have suspicious yield patterns, elect higher coverage, and increase total multiple-unit indemnifications up to ten percent in some states and up to 30 percent at some coverage levels.Crop Production/Industries, Risk and Uncertainty,
Real-time flutter identification
The techniques and a FORTRAN 77 MOdal Parameter IDentification (MOPID) computer program developed for identification of the frequencies and damping ratios of multiple flutter modes in real time are documented. Physically meaningful model parameterization was combined with state of the art recursive identification techniques and applied to the problem of real time flutter mode monitoring. The performance of the algorithm in terms of convergence speed and parameter estimation error is demonstrated for several simulated data cases, and the results of actual flight data analysis from two different vehicles are presented. It is indicated that the algorithm is capable of real time monitoring of aircraft flutter characteristics with a high degree of reliability
System configuration and executive requirements specifications for reusable shuttle and space station/base
System configuration and executive requirements specifications for reusable shuttle and space station/bas
Nonlinear Compensation Empyoing Matrix Converter with DTC Controller
This paper describes a nonlinear harmful speed and torque controller for fourth order induction motor model. The investigation of optimality and cost function for that base on estimation of Hammerstein-Wiener model with the compensated mathematical model. The matrix converter with direct torque control combination is efficient way to get better performance specifications in the industry.The MC and the DTC advantages are combined together.The reduction of complexity and cost of DC link in the DTC since it has no capacitors in the circuit. However, the controlling torque is a big problem it in DTC because of high ripple torque production which results in vibrations response in the operation of the IM as it has no PID to control the torque directly. The combination of MC with DTC is applied to reduce the fluctuation in the output torque and minimize the steady state error. This paper presents the simulation analysis of induction machine drives using Maltlab/Simulink toolbox R2012a. Design of constant switching frequency MCDTC drive,stability investigation and fault protection as well as controllability and observability with minimum steady state error has been carried out which  proved the effectiveness of the proposed technique
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