Optimal mean-square prediction of the mobile-radio fading envelope

Long-range prediction of the mobile-radio fading envelope is an enabling technology for many fading compensation approaches. Because the fading envelope is well modeled as a bandlimited process, it has special predictability properties. In this paper, we find a linear predictor that is optimal in the mean-square sense when the predictor impulse response is energy constrained. This solution may be used to determine the minimum mean squared error of a prediction based on past values that are corrupted with estimation errors.     

Optical intensity-modulated direct detection channels: signal space and lattice codes

Traditional approaches to constructing constellations for electrical channels cannot be applied directly to the optical intensity channel. This work presents a structured signal space model for optical intensity channels where the nonnegativity and average amplitude constraints are represented geometrically. Lattice codes satisfying channel constraints are defined and coding and shaping gain relative to a baseline are computed. An effective signal space dimension is defined to represent the precise impact of coding and shaping on bandwidth. Average optical power minimizing shaping regions are derived in some special cases. Example lattice codes are constructed and their performance on an idealized point-to-point wireless optical link is computed. Bandwidth-efficient schemes are shown to have promise for high data-rate applications, but require greater average optical power.     

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.     

Spontaneous and stimulated emission from CdxHg1−x Te semiconductor films

The experimental data on observation of spontaneous and stimulated emission from thin epitaxial Cd_xHg_1?x Te films optically pumped by Nd: YAG laser radiation are reported. A simple theoretical model is suggested to describe the initiation of population inversion under these conditions. The parameters realized under the experimental conditions are theoretically estimated.     

Exposed Die-Top Encapsulation Molding for an Improved High- Performance Flip Chip BGA Package

The recent advancement in high- performance semiconductor packages has been driven by the need for higher pin count and superior heat dissipation. A one-piece cavity lid flip chip ball grid array (BGA) package with high pin count and targeted reliability has emerged as a popular choice. The flip chip technology can accommodate an I/O count of more than five hundreds500, and the die junction temperature can be reduced to a minimum level by a metal heat spreader attachment. None the less, greater expectations on these high-performance packages arose such as better substrate real estate utilization for multiple chips, ease in handling for thinner core substrates, and improved board- level solder joint reliability. A new design of the flip chip BGA package has been looked into for meeting such requirements. By encapsulating the flip chip with molding compound leaving the die top exposed, a planar top surface can be formed. A, and a flat lid can then be mounted on the planar mold/die top surface. In this manner the direct interaction of the metal lid with the substrate can be removed. The new package is thus less rigid under thermal loading and solder joint reliability enhancement is expected. This paper discusses the process development of the new package and its advantages for improved solder joint fatigue life, and being a multichip package and thin core substrate options. Finite-element simulations have been employed for the study of its structural integrity, thermal, and electrical performances. Detailed package and board-level reliability test results will also be reported     

Sparse field level set method for non-convex Hamiltonians in 3D plasma etching profile simulations

Level set method [S. Osher, J. Sethian, J. Comput. Phys. 79 (1988) 12] is a highly robust and accurate computational technique for tracking moving interfaces in various application domains. It originates from the idea to view the moving front as a particular level set of a higher dimensional function, so the topological merging and breaking, sharp gradients and cusps can form naturally, and the effects of curvature can be easily incorporated. The resulting equations, describing interface surface evolution, are of Hamilton-Jacobi type and they are solved using techniques developed for hyperbolic equations. In this paper we describe an extension of the sparse field method for solving level set equations in the case of non-convex Hamiltonians, which are common in the simulations of the profile surface evolution during plasma etching and deposition processes. Sparse field method itself, developed by Whitaker [R. Whitaker, Internat. J. Comput. Vision 29 (3) (1998) 203] and broadly used in image processing community, is an alternative to the usual combination of narrow band and fast marching procedures for the computationally effective solving of level set equations. The developed procedure is applied to the simulations of 3D feature profile surface evolution during plasma etching process, that include the effects of ion enhanced chemical etching and physical sputtering, which are the primary causes of the Hamiltonian non-convexity.     

On the effect of spatial variances in historical rainfall time series to CSO performance evaluation.

Historical, high-resolution rain series are the backbone of modern combined sewer overflow (CSO) structure design. These rain series are the input to the computational estimation of the performance of the measures with respect to CSO pollution abatement. However, those historical precipitation measurements are available at only a few locations. Frequently rain series have to be used from gauging stations at a significant distance. In order to judge and to compensate for this influence an estimate between rain characteristics and combined sewer outflow (CSO) performance indicators would be useful. In this paper such correlations have been sought for a collection of 37 rain series covering large areas of Europe. It was found that the mean annual rain volume can explain most of the variances for the performance indicators Number of overflows and CSO volume. For explaining the spatial differences in the efficiency of the CSO structure another rain characteristic, i.e. the maximum event with a return period of one year, is to be used.     

Global stability of Internet congestion controllers with heterogeneous delays

In this paper, we study the problem of designing globally stable, scalable congestion control algorithms for the Internet. Prior work has primarily used linear stability as the criterion for such a design. Global stability has been studied only for single node, single source problems. Here, we obtain conditions for a general topology network accessed by sources with heterogeneous delays. We obtain a sufficient condition for global stability in terms of the increase/decrease parameters of the congestion control algorithm and the price functions used at the links.