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.     

Practical OSPF traffic engineering

Open Shortest Path First (OSPF) traffic engineering (TE) is intended to bring long-awaited traffic management capabilities into IP networks, which still rely on today's prevailing routing protocols: OSPF or IS-IS. In OSPF, traffic is forwarded along, and split equally between, equal cost shortest paths. In this letter, we formulate the basic requirements placed on a practical TE architecture built on top of OSPF and present a theoretical framework meeting these requirements of practicality. The main contribution of our work comes from the recognition that coupled with an instance of the maximum throughput problem there exists a related inverse shortest-path problem yielding optimal OSPF link weights.     

Techniques for high-frequency integrated test and measurement

This paper describes techniques for the on-chip measurement of high-frequency and/or high-bandwidth electrical phenomena in ultra large-scale integration environments. The techniques rely on the integration of multiple compact and robust electronic test devices, or cores, at various locations within an integrated circuit. The cores consist primarily of signal generators that approximate the output of a sigma-delta modulator using finite repetitious bit patterns and a small set of highly robust analog components. They are capable of digitizing on-chip signals at gigahertz rates even using low-cost manufacturing processes. Simple communication between the multiple cores enables the migration of many "board-level" type measurements down to the chip level.     

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.     

High-efficiency LEDs of 1.6–2.4 µm spectral range for medical diagnostics and environment monitoring

High efficient LED structures covering the spectral range of 1.6–2.4 μm have been developed on the basis of GaSb and its solid solutions. The electroluminescent characteristics and their temperature and current dependences have been studied. The radiative and nonradiative recombination mechanisms and their effect on the quantum efficiency have been investigated. A quantum efficiency of 40–60% has been obtained in the quasi-steady mode at room temperature. A short-pulse optical power of 170 mW was reached. __________ Translated from Fizika i Tekhnika Poluprovodnikov, Vol. 37, No. 8, 2003, pp. 996–1009. Original Russian Text Copyright ? 2003 by Stoyanov, Zhurtanov, Astakhova, Imenkov, Yakovlev.     

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.     

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.