Catalytic aminolysis of epoxide by alumina prepared from amine-protected Al precursor

The catalytic activities of alumina prepared from an Al alkoxide-amine adduct monomer for the reaction of cyclopentene oxide with piperidine was determined after various pretreatments, including calcination and exposure to moisture. They were compared with the activity of alumina prepared by the conventional hydrolysis method. It was found that the as-prepared sample from the alkoxide-amine monomer preparation was five times more active than a conventional preparation, suggesting that it has a higher density of surface Lewis acid sites. However, its activity was much more severely suppressed by exposure to moisture.     

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.     

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.     

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     

TEM Studies of High Temperature Corrosion Behaviour of TiAl Intermetallics with Surface Modifications

The oxidation/sulphidation behaviour of a Ti‐46.7Al‐1.9W‐0.5Si alloy with a TiAl₃ diffusion coating was studied in an environment of H₂/H₂S/H₂O at 850^oC. The kinetic results demonstrate that the TiAl₃ coating significantly increased the high temperature corrosion resistance of Ti‐46.7Al‐1.9W‐0.5Si. The SEM, EDX, XRD and TEM analysis reveals that the formation of an Al₂O₃ scale on the surface of the TiAl₃‐coated sample was responsible for the enhancement of the corroison resistance. The Ti‐46.7Al‐1.9W‐0.5Si alloy was also modified by Nb ion implantation. The Nb ion implanted and as received sampels were subjected to cyclic oxidation in an open air at 800^oC. The Nb ion implantation not only increased the oxidation resistance but also substantially improved the adhesion of scale to the substrate.     

Kinetic Characteristics of Amino Acid Salt Crystallization in Methanol‐Water System

Nucleation and growth mechanisms and kinetics of crystals of an amino acid salt were investigated in a methanol‐water system by measuring and evaluating the induction time as a function of the supersaturation ratio and temperature in batch salting out crystallization experiments. Discrimination between the possible crystallization mechanisms, and estimation of the kinetic parameters were carried out using nonlinear parameter identification. The results concerning the growth mechanism obtained were checked additionally by measuring the induction time as a function of number density of seed crystals.     

FIRE: fractal indexing with robust extensions for image databases

As already documented in the literature, fractal image encoding is a family of techniques that achieves a good compromise between compression and perceived quality by exploiting the self-similarities present in an image. Furthermore, because of its compactness and stability, the fractal approach can be used to produce a unique signature, thus obtaining a practical image indexing system. Since fractal-based indexing systems are able to deal with the images in compressed form, they are suitable for use with large databases. We propose a system called FIRE, which is then proven to be invariant under three classes of pixel intensity transformations and under geometrical isometries such as rotations by multiples of /spl pi//2 and reflections. This property makes the system robust with respect to a large class of image transformations that can happen in practical applications: the images can be retrieved even in the presence of illumination and/or color alterations. Additionally, the experimental results show the effectiveness of FIRE in terms of both compression and retrieval accuracy.