An application of decision trees method for fault diagnosis of induction motors

Decision tree is one of the most effective and widely used methods for building classification model. Researchers from various disciplines such as statistics, machine learning, pattern recognition, and data mining have considered the decision tree method as an effective solution to their field problems. In this paper, an application of decision tree method to classify the faults of induction motors is proposed. The original data from experiment is dealt with feature calculation to get the useful information as attributes. These data are then assigned the classes which are based on our experience before becoming data inputs for decision tree. The total 9 classes are defined. An implementation of decision tree written in Matlab is used for these data

Medium Effects in rho-Meson Photoproduction

We compute dilepton invariant mass spectra from the decays of rho mesons produced by photon reactions off nuclei. Our calculations employ a realistic model for the rho photoproduction amplitude on the nucleon which provides fair agreement with measured cross sections. Medium effects are implemented via an earlier constructed rho propagator based on hadronic many-body theory. At incoming photon energies of 1.5 -3 GeV as used by the CLAS experiment at JLAB, the average density probed for iron targets is estimated at about half saturation density. At the pertinent rho-meson 3-momenta the predicted medium effects on the rho propagator are rather moderate. The resulting dilepton spectra approximately agree with recent CLAS data.Comment: One numerical error corrected, conclusions unchange

On the Design of Secure Full-Duplex Multiuser Systems under User Grouping Method

Consider a full-duplex (FD) multiuser system where an FD base station (BS) is designed to simultaneously serve both downlink users and uplink users in the presence of half-duplex eavesdroppers (Eves). Our problem is to maximize the minimum secrecy rate (SR) among all legitimate users by proposing a novel user grouping method, where information signals at the FD-BS are accompanied with artificial noise to degrade the Eves' channel. The SR problem has a highly nonconcave and nonsmooth objective, subject to nonconvex constraints due to coupling between the optimization variables. Nevertheless, we develop a path-following low-complexity algorithm, which invokes only a simple convex program of moderate dimensions at each iteration. We show that our path-following algorithm guarantees convergence at least to a local optima. The numerical results demonstrate the merit of our proposed approach compared to existing well-known ones, i.e., conventional FD and nonorthogonal multiple access.Comment: 6 pages, 3 figure

Stellar populations of seven early-type dwarf galaxies and their nuclei

Dwarf galaxies are the numerically dominating population in the dense regions of the universe. Although they seem to be simple systems at first view, the stellar populations of dwarf elliptical galaxies (dEs) might be fairly complex. Nucleated dEs are of particular interest, since a number of objects exhibit different stellar populations in their nuclei and host galaxy. We present stellar population parameters obtained from integrated optical spectra using a Lick index analysis of seven nucleated dwarf elliptical galaxies and their nuclei. After subtracting the scaled galaxy spectra from the nucleus spectra, we compared them with one another and explore their stellar populations. As a preliminary result, we find that the luminosity weighted ages of the nuclei slightly lower than those of galaxies, however, we do not see any significant difference in metallicity of the host galaxies and their nuclei.Comment: 3 pages, 3 figures, to be published in Astronomische Nachrichten (proceedings of Symposium 6 of the JENAM 2008, Vienna

Robust Beamforming for Secrecy Rate in Cooperative Cognitive Radio Multicast Communications

In this paper, we propose a cooperative approach to improve the security of both primary and secondary systems in cognitive radio multicast communications. During their access to the frequency spectrum licensed to the primary users, the secondary unlicensed users assist the primary system in fortifying security by sending a jamming noise to the eavesdroppers, while simultaneously protect themselves from eavesdropping. The main objective of this work is to maximize the secrecy rate of the secondary system, while adhering to all individual primary users' secrecy rate constraints. In the case of passive eavesdroppers and imperfect channel state information knowledge at the transceivers, the utility function of interest is nonconcave and involved constraints are nonconvex, and thus, the optimal solutions are troublesome. To address this problem, we propose an iterative algorithm to arrive at a local optimum of the considered problem. The proposed iterative algorithm is guaranteed to achieve a Karush-Kuhn-Tucker solution.Comment: 6 pages, 4 figures, IEEE ICC 201