Multi-emitter Si/GexSi1-x heterojunctionbipolar transistor with no base contact and enhanced logic functionality

We demonstrate multi-emitter Si/Ge_xSi_1-x n-p-n heterojunction bipolar transistors (HBT's) which require no base contact for transistor operation. The base current is supplied by the additional emitter contact under reverse bias due to the heavy doping of the emitter-base junction. Large-area HBT test structures exhibit good transistor characteristics, with current gain β≈400 regardless of whether the base current is supplied by a test base electrode or one of the emitter contacts. These devices have enhanced logic functionality because of emitter contact symmetry. Since device fabrication does not require base electrode formation, the number of processing steps can be reduced without significant penalty to HBT performance     

Multiple-Agent Perspectives in Reasoning About Situations for Context-Aware Pervasive Computing Systems

In open heterogeneous context-aware pervasive computing systems, suitable context models and reasoning approaches are necessary to enable collaboration and distributed reasoning among agents. This paper proposes, develops, and demonstrates the following: 1) a novel context model and reasoning approach developed with concepts from the state-space model, which describes context and situations as geometrical structures in a multidimensional space; and 2) a context algebra based on the model, which enables distributed reasoning by merging and partitioning context models that represent different perspectives of computing entities over the object of reasoning. We show how merging and reconciling different points of view over context enhances the outcomes of reasoning about the context. We develop and evaluate our proposed algebraic operators and reasoning approaches with cases using real sensors and with simulations. We embed agents and mobile agents with these modeling and reasoning capabilities, thus facilitating context-aware and adaptive mobile agents operating in open pervasive environments.     

Designing Nanoscale Logic Circuits Based on Markov Random Fields

As devices and operating voltages are scaled down, future circuits will be plagued by higher soft error rates, reduced noise margins and defective devices. A key challenge for the future is retaining high reliability in the presence of faulty devices and noise. Probabilistic computing offers one possible approach. In this paper we describe our approach for mapping circuits onto CMOS using principles of probabilistic computation. In particular, we demonstrate how Markov random field elements may be built in CMOS and used to design combinational circuits running at ultra low supply voltages. We show that with our new design strategy, circuits can operate in highly noisy conditions and provide superior noise immunity, at reduced power dissipation. If extended to more complex circuits, our approach could lead to a paradigm shift in computing architecture without abandoning the dominant silicon CMOS technology.     

Estimating computation times of data-intensive applications

We present a holistic approach to estimation that uses rough sets theory to determine a similarity template and then compute a runtime estimate using identified similar applications. We tested the technique in two real-life data-intensive applications: data mining and high-performance computing.     

Stabilization of oscillations by a nonnegative feedback control

The feedback stabilization of m-dimensional nonlinear systems is studied in this note. The Jacobian is assumed to possess 2q purely imaginary eigenvalues and m-2q eigenvalues with negative real parts. The feedback control law is assumed to be nonnegative and given by the square of a linear function. The direct and indirect control systems are investigated. In both cases stabilizability is proved and explicit formulas for the feedback functions are obtained. Lyapunov's direct method is employed     

Feedback stabilization of connected nonlinear oscillators with uncontrollable linearization

A nonlinear system with uncontrollable linearization is under investigation. The uncontrollable part of the linearization is assumed to have no eigenvalues in the right half-plane and have eigenvalues with zero real and nonzero imaginary part. A nonlinear feedback loop is assumed to carry out a connection between the controllable part of the system and the uncontrollable one. The control law of the controllable part is defined to be a linear function of the state variables. This linear feedback loop can maintain the stability of a whole control system provided its feedback law coefficients satisfy a system of algebraic inequalities. The consistence of this system of inequalities is proved.     

Assessment of an “Energy Tower” potential in Australia using a mathematical model and GIS

“Energy Tower” is a technology for producing renewable and clean electricity by means of cooling hot and dry air, which is continuously supplied to arid lands. We assess the potential of an Energy Tower by incorporating topographic and meteorological parameters into a computational model, providing evaluations for the net power production and the electricity production cost. We formulate a highly simplified model for the Energy Tower’s flow, setup and process a spatial dataset of topographic and Meteorological upper air parameters. The model was applied to the Australian continent. A model simulation of one annual cycle enabled the ranking and selection of promising sites. The highest potential for energy towers is in the Port Hedland region, where favorable meteorological and topographic conditions would result in high average net power (≈370 ± 160 MW), potentially providing the electricity needs of 0.5 million people, for an economically competitive costs (3.5 ¢kWh).