GaInP/GaAs HBTs for high-speed integrated circuit applications

The use of GaInP/GaAs heterojunction bipolar transistors (HBTs) for integrated circuit applications is demonstrated. The discrete devices fabricated showed excellent DC characteristics with low V_ce offset voltage and very low temperature sensitivity of the current gain. For a non-self-aligned device with a 3-μm×1.4-μm emitter area, f_T was extrapolated to 45 GHz and f_max was extrapolated to 70 GHz. The measured 1/f noise level was 20 dB better than that of AlGaAs HBTs and comparable to that of low-noise silicon bipolar junction transistors, and the noise bump (Lorentzian component) was not observed. The fabricated gain block circuits showed 8.5 dB gain with a 3-dB bandwidth of 12 GHz, and static frequency dividers (divide by 4) were operable up to 8 GHz     

Extraction of left-ventricular chamber from 3-D CT images of the heart

A semiautomatic method is described for extracting the volume and shape of the left ventricular (LV) chamber from a dynamic spatial reconstructor cardiac volume. For a given volume, the operator first performs some simple manual edits. Then, an automated stage, which incorporates concepts from 3-D mathematical morphology and technology, the maximum-homogeneity filter, and an adaptive 3-D thresholder, extracts the LV chamber. The method gives more consistent measurements and demands considerably less operator time than manual slice-editing.     

Training for an agricultural discrimination task

Skeleton weed, centaurea juncea, is a declared weed in Western Australia because it competes with grain crops for nutrients and moisture. When it is found during harvesting, mechanised teams search and eradicate it. In an earlier report of field trials (Hartley et al, 1989) it was reported that search teams' detection rate was poor and since search teams had usually never seen skeleton weeds, visual discrimination learning was to be expected and observed during searches. The present study investigated the nature of this discrimination learning in a laboratory by developing a training programme of colour photographic slides of weeds in stubble. Subjects receiving specific training with feedback on their performance compared with those receiving pseudo-training showed a significant improvement in detections. Subsequently the benefit of the programme was validated in a field trial.     

Real-time evaluation and visualization of learner performance in a mixed-reality environment for clinical breast examination

We investigate the efficacy of incorporating real-time feedback of user performance within mixed-reality environments (MREs) for training real-world tasks with tightly coupled cognitive and psychomotor components. This paper presents an approach to providing real-time evaluation and visual feedback of learner performance in an MRE for training clinical breast examination (CBE). In a user study of experienced and novice CBE practitioners (n = 69), novices receiving real-time feedback performed equivalently or better than more experienced practitioners in the completeness and correctness of the exam. A second user study (n = 8) followed novices through repeated practice of CBE in the MRE. Results indicate that skills improvement in the MRE transfers to the real-world task of CBE of human patients. This initial case study demonstrates the efficacy of MREs incorporating real-time feedback for training real-world cognitive-psychomotor tasks.     

Thermal modeling in cylindrical coordinates using effective conductivity

Predictive thermometry, utilizing minimally invasive sampling techniques, is an essential ingredient in the development of hyperthermia treatment planning capabilities. The authors demonstrate a powerful, but simple approach toward predicting temperature distributions in tissues, based on analytic solution, using in cylindrical symmetry, of the heat diffusion equation. Conduction and localized perfusion effects are combined as an effective conductivity term, readily measurable, and parametrized in a general exponential form. The proposed approach allows a first-order approximation to modeling three typical situations: hypoxic or necrotic tumor core with homogeneously perfused periphery; highly perfused periphery (in rapidly growing tumors); or perfused central cover with a less well-supplied periphery (such as for some invasive tumors). The utility and strength of this approach is that it provides a rapid, accurate model of directly observing the technical quality to be expected for different heating methods, making it possible to optimally configure source distributions in a treatment planning setting.     

The volume integral method of eddy-current modeling: Verification

The volume integral method of eddy-current modeling represents a flaw in metal as a set of electric dipoles located within volume elements or cells defining the flaw volume. Given this dipole distribution, impedance changes may be computed. The electric field of the dipole distribution is determined by an integral equation relating, by means of the electric field Green's tensor, the electric field due to the source to the total electric field in the flaw. The integral equation is solved by assuming that the total electric field is constant in each volume element, resulting in a matrix equation. The method has been programmed for use on a microcomputer. The method and computer program are verified using the analytical solution for a small spherical flaw and three sets of measured impedance data, measured by air-core coils along profiles overlying both surface-breaking and buried simulated flaws of known dimensions. Operating frequencies ranged between 900 and 4000 Hz. Generally agreement is good at lower frequencies ( 1000 Hz). At higher frequencies ( 4000 Hz), the agreement is not as good. This is thought to be due to the inability of the constant electric field approximation to model the steep electric field gradients present in the host metal at high frequency. The results are also sensitive to the method of computation of the electric field due to the source. Some improvements can and should be made to the method.     

Attenuation of second sound in bulk flowing He II

New measurements of second sound attenuation in bulk flowing He II are reported which extend to a region of higher Reynolds number. An expression for the attenuation explicitly containing the quantum vortex line density is developed which allows comparison with vortex line density data taken by other means. A bellows driven experimental apparatus is used to produce bulk flow velocities of 0 to 1 m/sec in a channel of 4.064 mm square internal cross section. Second sound pulses are produced by applying a square voltage pulse 200 s width and variable height to a strain gauge heater. The second sound pulses are detected with thin film sensors mounted 56 and 119 mm downstream. The velocity-dependent attenuation, measured as a function of bulk flow velocity at 1.5, 1.8, and 2.0 K, is compared with data from other researchers. The attenuation, and thus the vortex line density, appears to follow a gradual transition from laminar to turbulent behavior. Current theories do not account for the presence of quantized vortices in bulk flowing He II, where (v _n–v _s), and thus do not explain the observed second sound attentuation in this regime.     

Higher-Order and Modal Logic as a Framework for Explanation-Based Generalization

Certain tasks, such as formal program development and theorem proving, fundamentally rely upon the manipulation of higher-order objects such as functions and predicates. Computing tools intended to assist in performing these tasks are at present inadequate in both the amount of knowledge they contain (i.e., the level of support they provide) and in their ability to learn (i.e., their capacity to enhance that support over time). The application of a relevant machine learning technique—explanation-based generalization (EBG)—has thus far been limited to first-order problem representations. We extend EBG to generalize higher-order values, thereby enabling its application to higher-order problem encodings.Logic programming provides a uniform framework in which all aspects of explanation-based generalization and learning may be defined and carried out. First-order Horn logics (e.g., Prolog) are not, however, well suited to higher-order applications. Instead, we employ Prolog, a higher-order logic programming language, as our basic framework for realizing higher-order EBG. In order to capture the distinction between domain theory and training instance upon which EBG relies, we extend Prolog with the necessity operator of modal logic. We develop a meta-interpreter realizing EBG for the extended language, Prolog, and provide examples of higher-order EBG.     

A Universal Method of Scientific Inquiry

A paradigm of scientific discovery is defined within a first-order logical framework. Within this paradigm, the concept of successful scientific inquiry is formalized and investigated. Among other results, it is shown that a simple method of scientific inquiry is universal in the sense that it leads to success on every problem for which success is in principle possible.     

Surface mass transport of alumina

The kinetics of thermal grooving at the intersection of rhombohedral twin boundaries with the \((10\bar 10)\) plane in aluminium oxide were measured from 1773 to 2273 K. Analysis of the data using the model of Mullins showed that surface diffusion was the dominant mechanism for mass transport. The results were compared with other similar published work on alumina, and the following equation for surface diffusion was determined: $$D_s (cm^2 sec^{ - 1} ) = 4.05 x 10^5 exp - (452kJ mol^{ - 1} /RT).$$