Stochastically ordered subpopulations and optimal burn-in procedure

Burn-in is a widely used engineering method which is adopted to eliminate defective items before they are shipped to customers or put into the field operation. In the studies of burn-in, the assumption of bathtub shaped failure rate function is usually employed and optimal burn-in procedures are investigated. In this paper, however, we assume that the population is composed of two ordered subpopulations and optimal burn-in procedures are studied in this context. Two types of risks are defined and an optimal burn-in procedure, which minimizes the weighted risks is studied. The joint optimal solutions for the optimal burn-in procedure, which minimizes the mean number of repairs during the field operation, are also investigated.

UV-optical colors as probes of early-type galaxy evolution

We have studied ∼2100 early-type galaxies in the SDSS DR3 which have been detected by the GALEX Medium Imaging Survey (MIS), in the redshift range O <z <0.1.1. Combining GALEXUV photometry with corollary optical data from the SDSS, we find that, at a 95% confidence level, at least ∼30% of galaxies in this sample have UV to optical colors consistent with some recent star formation within the last Gyr. In particular, galaxies with an NUV - r color less than 5.5 are very likely to have experienced such recent star formation, taking into account the possibility of a contribution to NUV flux from the UV upturn phenomenon. We find quantitative agreement between the observations and the predictions of a semianalytical ACDM hierarchical merger model and deduce that early-type galaxies in the redshift range 0 <z <0.11 have ∼ 1 % -3 % of their stellar mass in stars less than 1 Gyr old. The average age of this recently formed population is ∼300-500 Myr. We also find that "monolithically" evolving galaxies, where recent star formation can be driven solely by recycled gas from stellar mass loss, cannot exhibit the blue colors (NUV - r <5.5) seen in a significant fraction (∼30%) of our observed sample.Peer reviewe

Analysis of ultra-sensitive fluorescence experiments

This work primarily investigates use of the neural network(NN) method to analyze spectral data collected in single molecule detection(SMD) and identification (SMI) ex-periments.. The 2-layer neural networks, with sigmoid as the activation function, are constructed and trained on a set of simulated data using back-propagation and the 6- learning rule. The trained networks are then used for identification of photon bursts in subsequent simulations. Results show that the NN method yields better identification of individual photon bursts than the traditional maximum likelihood estimation (MLE), particularly in cases where the fluorophores have disparate fluorescence quantum effi-ciencies, absorption cross-sections, or photodegradation efficiencies. In addition, this work reports several improvements over the prior version of the Monte Carlo simulation program. The improved version considers the fluorescence prob-ability as the convolution of the pure exponential decay function characterized by the fluorescence lifetime and the instrument impulse response function in the experiment. The setting of the time window is then implemented by monitoring the variation of signal and noise. A number of problems have been investigated by using the improved version. In particular, the effects of the number and widths of the bins within the time window on the precision of identification of molecules are studied. The results from the improved version of the simulation show that only a small number of bins (4-8) are required to achieve approximately 90% correct predictions with the NN method. Bin widths chosen in accordance with the intuitive algorithm, or equal bin widths, generally give better predictions. Experimental improvements are also reported in this work. In particular, the transit time of BODIBY-TR(D-6116) dye molecules in an SMD experiment was improved to less than 200 μ, and a circuit is implemented to accomplish fast and continuous data collection to be used in future single molecule identification experiments

Ultrasonic Doppler measurement of renal artery blood flow

An extensive evaluation of the practical and theoretical limitations encountered in the use of totally implantable CW Doppler flowmeters is provided. Theoretical analyses, computer models, in-vitro and in-vivo calibration studies describe the sources and magnitudes of potential errors in the measurement of blood flow through the renal artery, as well as larger vessels in the circulatory system. The evaluation of new flowmeter/transducer systems and their use in physiological investigations is reported

Sparse multiple relay selection for network beamforming with individual power constraints using semidefinite relaxation

This paper deals with the multiple relay selection problem in two-hop wireless cooperative networks with individual power constraints at the relays. In particular, it addresses the problem of selecting the best subset of K cooperative nodes and their corresponding beamforming weights so that the signal-to-noise ratio (SNR) is maximized at the destination. This problem is computationally demanding and requires an exhaustive search over all the possible combinations. In order to reduce the complexity, a new suboptimal method is proposed. This technique exhibits a near-optimal performance with a computational burden that is far less than the one needed in the combinatorial search. The proposed method is based on the use of the l1-norm squared and the Charnes-Cooper transformation and naturally leads to a semidefinite programming relaxation with an affordable computational cost. Contrary to other approaches in the literature, the technique exposed herein is based on the knowledge of the second-order statistics of the channels and the relays are not limited to cooperate with full power.Peer ReviewedPostprint (author's final draft

Young massive star clusters

Young massive clusters are dense aggregates of young stars that form the fundamental building blocks of galaxies. Several examples exist in the Milky Way Galaxy and the Local Group, but they are particularly abundant in starburst and interacting galaxies. The few young massive clusters that are close enough to resolve are of prime interest for studying the stellar mass function and the ecological interplay between stellar evolution and stellar dynamics. The distant unresolved clusters may be effectively used to study the star-cluster mass function, and they provide excellent constraints on the formation mechanisms of young cluster populations. Young massive clusters are expected to be the nurseries for many unusual objects, including a wide range of exotic stars and binaries. So far only a few such objects have been found in young massive clusters, although their older cousins, the globular clusters, are unusually rich in stellar exotica. In this review we focus on star clusters younger than $\sim100$ Myr, more than a few current crossing times old, and more massive than $\sim10^4$ \Msun, irrespective of cluster size or environment. We describe the global properties of the currently known young massive star clusters in the Local Group and beyond, and discuss the state of the art in observations and dynamical modeling of these systems. In order to make this review readable by observers, theorists, and computational astrophysicists, we also review the cross-disciplinary terminology.Comment: Only 88 pages. To be published in ARAA. Final version to be submitted on Friday 12 Februar

The Impact of Boreal Forest Fire on Climate Warming

We report measurements and analysis of a boreal forest fire, integrating the effects of greenhouse gases, aerosols, black carbon deposition on snow and sea ice, and postfire changes in surface albedo. The net effect of all agents was to increase radiative forcing during the first year (34 ± 31 Watts per square meter of burned area), but to decrease radiative forcing when averaged over an 80-year fire cycle (–2.3 ± 2.2 Watts per square meter) because multidecadal increases in surface albedo had a larger impact than fire-emitted greenhouse gases. This result implies that future increases in boreal fire may not accelerate climate warming

New Coding/Decoding Techniques for Wireless Communication Systems

Wireless communication encompasses cellular telephony systems (mobile communication), wireless sensor networks, satellite communication systems and many other applications. Studies relevant to wireless communication deal with maintaining reliable and efficient exchange of information between the transmitter and receiver over a wireless channel. The most practical approach to facilitate reliable communication is using channel coding. In this dissertation we propose novel coding and decoding approaches for practical wireless systems. These approaches include variable-rate convolutional encoder, modified turbo decoder for local content in Single-Frequency Networks, and blind encoder parameter estimation for turbo codes. On the other hand, energy efficiency is major performance issue in wireless sensor networks. In this dissertation, we propose a novel hexagonal-tessellation based clustering and cluster-head selection scheme to maximize the lifetime of a wireless sensor network. For each proposed approach, the system performance evaluation is also provided. In this dissertation the reliability performance is expressed in terms of bit-error-rate (BER), and the energy efficiency is expressed in terms of network lifetime