The effect of photon energy and temperature on the persistent tunneling photoconductivity effect in Al/δ(Si)-GaAs structures

The phenomenon of persistent tunneling photoconductivity was studied using the tunneling spectroscopy technique at liquid-helium temperature: the separation between the unoccupied levels in a δ-doped layer at the GaAs surface decreased after illumination. This decrease was due to an increase in the width of the quantum well of the δ-doped layer. For photon energies hv exceeding the GaAs band gap E _g , this increase in the width of the quantum well was related to the accumulation of positive charge in the depth of GaAs induced by the generation of the electron-hole pairs and photoionization of deep centers. For hv < E _g (including the case of CO₂ laser), only photoionization is important. The experimental data agree with the self-consistent calculations. The critical temperature for the effect has been determined (T _c = 45 K); at higher temperatures, the effect disappears.     

Finite sample size effect on minimum variance beamformers: optimum diagonal loading factor for large arrays

Minimum variance beamformers are usually complemented with diagonal loading techniques in order to provide robustness against several impairments such as imprecise knowledge of the steering vector or finite sample size effects. This paper concentrates on this last application of diagonal loading techniques, i.e., it is assumed that the steering vector is perfectly known and that diagonal loading is used to alleviate the finite sample size impairments. The analysis herein is asymptotic in the sense that it is assumed that both the number of antennas and the number of samples are high but have the same order of magnitude. Borrowing some results of random matrix theory, the authors first derive a deterministic expression that describes the asymptotic signal-to-noise-plus-interference ratio (SINR) at the output of the diagonally loaded beamformer. Then, making use of the statistical theory of large observations (also known as general statistical analysis or G-analysis), the authors derive an estimator of the optimum loading factor that is consistent when both the number of antennas and the sample size increase without bound at the same rate. Because of that, the estimator has an excellent performance even in situations where the quotient between the number of observations is low relative to the number of elements of the array.     

A tree partitioning dynamic policy for OVSF codes assignment in wideband CDMA

This paper proposes some novel techniques to accommodate users with different rate requirements in a wideband code-division multiple-access system employing orthogonal variable spreading factor codes. Two simple static code assignment strategies are first considered, and an improvement based on multicode assignment. Then the new idea of tree partitioning is introduced and used to devise a dynamic code reassignment algorithm. The behavior of these different techniques is experimentally investigated, in terms of call blocking probability and number of required reassignments. The tree partitioning method exhibits very good performances.     

A decision support system for interactive decision making - Part II: analysis and output interpretation

For pt.I see ibid., p.42-55 (2003). The development of a comprehensive decision support system, GMCR II, for the systematic study of real-world interactive decision problems is presented. The companion paper (Part I), discusses how GMCR II elicits, stores, and manages conflict models; here (Part II), the focus is on GMCR IIs analysis and output interpretation subsystems. Specifically, this paper describes the powerful and efficient analysis engine contained in GMCR II, its informative output presentation and interpretation facilities, and a number of follow-up analyses. Furthermore, an illustrative case study is used to demonstrate how GMCR II can be conveniently applied in practice.     

Control system design on a power-split CVT for high-power agricultural tractors

The problem considered in this paper is the design and tuning of the control system of a power-split continuously variable transmission (CVT) used in high-power tractors. Power-split CVTs are characterized by the combination of a traditional mechanical transmission and by a continuously-variable transmission. This guarantees, at the same time, smooth variations of the transmission-ratio and high efficiency of the overall transmission system. The control architecture of an hydrostatic power-split CVT is constituted by three main parts: 1) servo-controller on the current of the valve which drives the hydraulic transmission; 2) a servo-controller on the hydraulic transmission-ratio; and 3) a synchronizer which coordinates the hydraulic and the mechanical parts of the CVT. In this work, these three controllers are fully developed, including: design, implementation, and evaluation on an experimental system.     

On-demand learning for a wireless campus

The current Internet and wireless networks are harsh environments for transporting high-bandwidth multimedia data. We examine the technical issues involved, and describe an end-to-end solution to support a Web-based learn-on-demand system that operates in a wireless campus environment.     

Asymptotic performance of single parity-check product codes

This article investigates the asymptotic performance of single parity-check (SPC) product codes (PCs) from a decoding point of view. Specifically, the probability of bit error is bounded before and after the decoding of each dimension, similar to the analysis of "iterated codes" by Elias (1954). It is shown that the asymptotic probability of bit error can be driven to zero as the number of dimensions, and hence the block length, increases at signal-to-noise ratios (SNRs) within 2 dB of capacity over the additive white Gaussian noise (AWGN) channel.     

PNNI-based control plane for automatically switched optical networks

Much effort has been spent on the definition of control plane protocols for automatically switched optical networks (ASON). Most of the proposals brought into the standardization for an International Telecommunications Union-Telecommunication Sector, Internet Engineering Task Force, and Optical Internetworking Forum are based on Internet protocol concepts. One such proposal is the generalized multi-protocol label switching (GMPLS), an extension of the MPLS traffic engineering control plane model that includes nonpacket switched technologies (time, wavelength, and fiber switching). Recently, the potential use of private network-network interface (PNNI) in ASONs has been discussed as an alternative proposal by the standardization bodies. The goal of this paper is to appropriately adapt asynchronous transfer mode into an optical PNNI (O-PNNI) protocol that can be used as the control plane of ASONs. The paper also provides a critical viewpoint on the potential usage of either O-PNNI or GMPLS control plane and analyzes the pros and cons of each. The methodology adopted toward devising O-PNNI hinges on reviewing PNNI along with ASON recommendations in order to determine the set of PNNI features that require adaptation. Having identified these features we engineer and present appropriate solutions relating to routing, signaling and addressing aspects.     

Experimental real-time detector of GSM terminals

The authors present an experimental real-time GSM terminal detector, to be installed in a restricted area. The detector triggers terminal signaling, which can be captured.     

A fuzzy logic based-method for prognostic decision making in breast and prostate cancers

Accurate and reliable decision making in oncological prognosis can help in the planning of suitable surgery and therapy, and generally, improve patient management through the different stages of the disease. In recent years, several prognostic markers have been used as indicators of disease progression in oncology. However, the rapid increase in the discovery of novel prognostic markers resulting from the development in medical technology, has dictated the need for developing reliable methods for extracting clinically significant markers where complex and nonlinear interactions between these markers naturally exist. The aim of this paper is to investigate the fuzzy k-nearest neighbor (FK-NN) classifier as a fuzzy logic method that provides a certainty degree for prognostic decision and assessment of the markers, and to compare it with: 1) logistic regression as a statistical method and 2) multilayer feedforward backpropagation neural networks an artificial neural-network tool, the latter two techniques having been widely used for oncological prognosis. In order to achieve this aim, breast and prostate cancer data sets are considered as benchmarks for this analysis. The overall results obtained indicate that the FK-NN-based method yields the highest predictive accuracy, and that it has produced a more reliable prognostic marker model than both the statistical and artificial neural-network-based methods.