Structural, electrical, and optical analysis of ion implanted semi-insulating InP

Semi-insulating InP was implanted with MeV P, As, Ga, and In ions, and the resulting evolution of structural properties with increased annealing temperature was analyzed using double crystal x-ray diffractometry and cross sectional transmission electron microscopy. The types of damage identified are correlated with scanning spreading resistance and scanning capacitance measurements, as well as with previously measured Hall effect and time resolved photoluminescence results. We have identified multiple layers of conductivity in the samples which occur due to the nonuniform damage profile of a single implant. Our structural studies have shown that the amount and type of damage caused by implantation does not scale with implant ion atomic mass. (C) 2004 American Institute of Physics.

Using the EM Algorithm to Train Neural Networks: Misconceptions and a New Algorithm for Multiclass Classification

The expectation-maximization (EM) algorithm has been of considerable interest in recent years as the basis for various algorithms in application areas of neural networks such as pattern recognition. However, there exists some misconceptions concerning its application to neural networks. In this paper, we clarify these misconceptions and consider how the EM algorithm can be adopted to train multilayer perceptron (MLP) and mixture of experts (ME) networks in applications to multiclass classification. We identify some situations where the application of the EM algorithm to train MLP networks may be of limited value and discuss some ways of handling the difficulties. For ME networks, it is reported in the literature that networks trained by the EM algorithm using iteratively reweighted least squares (IRLS) algorithm in the inner loop of the M-step, often performed poorly in multiclass classification. However, we found that the convergence of the IRLS algorithm is stable and that the log likelihood is monotonic increasing when a learning rate smaller than one is adopted. Also, we propose the use of an expectation-conditional maximization (ECM) algorithm to train ME networks. Its performance is demonstrated to be superior to the IRLS algorithm on some simulated and real data sets.

Electromagnetic modeling of conformal wideband and multi-band patch antennas by bridging a solid-object modeler with MoM software

The advantages of antennas that can resemble the shape of the body to which they are attached are obvious. However, electromagnetic modeling of such unusually shaped antennas can be difficult. In this paper, the commercially available software SolidWorks(TM) is used for accurately drawing complex shapes in conjunction with the electromagnetic software FEKO(TM) to model the EM behavior of conformal antennas. The application of SolidWorks and custom-written software allows all the required information that forms the analyzed structure to be automatically inserted into FEKO, and gives the user complete control over the antenna being modeled. This approach is illustrated by a number of simulation examples of single, wideband, multi-band planar and curved patch antennas.

Effect of mutual coupling on the interference rejection capabilities of linear and circular arrays in CDMA systems

This paper is concerned with assessing the interference rejection capabilities of linear and circular array of dipoles that can be part of a base station of a code-division multiple-access cellular communication system. The performance criteria for signal-to-interference ratio (SIR) improvement employed in this paper is the spatial interference suppression coefficient. We first derive an expression for this figure of merit and then analyze and compare the SIR performance of the two types of arrays. For a linear array, we quantitatively assess the degradation in SIR performance, as we move from array broadside to array end-fire direction. In addition, the effect of mutual coupling is taken into account.

Novel target-field method for designing shielded biplanar shim and gradient coils

A new method is presented here for the systematic design of biplanar shielded shim and gradient coils, for use in magnetic resonance imaging (MRI) and other applications. The desired target field interior to the coil is specified in advance, and a winding pattern is then designed to produce a field that matches the target as closely as possible. Both gradient and shim coils can be designed by this approach, and the target region can be located asymmetrically within the coil. The interior target field may be matched at two or more interior locations, to improve accuracy. When shields are present, the winding patterns are designed so that the fields exterior to the biplanar coil are made as small as possible. The method is illustrated here by the design of some transverse gradient and shim coils.

Cognitive fit between conceptual schemas and internal problem representations: The case of geospatio-temporal conceptual schema comprehension

Geospatio-temporal conceptual models provide a mechanism to explicitly represent geospatial and temporal aspects of applications. Such models, which focus on both what and when/where, need to be more expressive than conventional conceptual models (e.g., the ER model), which primarily focus on what is important for a given application. In this study, we view conceptual schema comprehension of geospatio-temporal data semantics in terms of matching the external problem representation (that is, the conceptual schema) to the problem-solving task (that is, syntactic and semantic comprehension tasks), an argument based on the theory of cognitive fit. Our theory suggests that an external problem representation that matches the problem solver's internal task representation will enhance performance, for example, in comprehending such schemas. To assess performance on geospatio-temporal schema comprehension tasks, we conducted a laboratory experiment using two semantically identical conceptual schemas, one of which mapped closely to the internal task representation while the other did not. As expected, we found that the geospatio-temporal conceptual schema that corresponded to the internal representation of the task enhanced the accuracy of schema comprehension; comprehension time was equivalent for both. Cognitive fit between the internal representation of the task and conceptual schemas with geospatio-temporal annotations was, therefore, manifested in accuracy of schema comprehension and not in time for problem solution. Our findings suggest that the annotated schemas facilitate understanding of data semantics represented on the schema.