Experimental estimate of self-irradiation of building bricks due to incorporated radionuclides

A method is described for experimentally determining the dose rate created in building bricks by incorporated natural radionuclides. It was established using the thermoluminescence dosimetry method that the measured dose rate depends on the detector thickness, the mass of the ceramic product investigated, and the irradiation geometry. The contributions to the measured dose of weakly penetrating α and β radiation and hard ψ radiation are separated, the ratio between them depending on the experimental conditions. Translated from Izmeritel'naya Tekhnika, No. 7, pp. 62–66, July, 1996.     

Test Case Generation as an AI Planning Problem

While Artificial Intelligence techniques have been applied to a variety of software engineering applications, the area of automated software testing remains largely unexplored. Yet, test cases for certain types of systems (e.g., those with command language interfaces and transaction based systems) are similar to plans. We have exploited this similarity by constructing an automated test case generator with an AI planning system at its core. We compared the functionality and output of two systems, one based on Software Engineering techniques and the other on planning, for a real application: the StorageTek robot tape library command language. From this, we showed that AI planning is a viable technique for test case generation and that the two approaches are complementary in their capabilities.     

Development of a recurrent Sigma-Pi neural network rainfall forecasting system in Hong Kong

At the moment, weather forecasting is still an art — the experience and intuition of forecasters play a significant role in determining the quality of forecasting. This paper describes the development of a new approach to rainfall forecasting using neural networks. It deals with the extraction of information from radar images and an evaluation of past rain gauge records to provide shortterm rainfall forecasting. All of the meteorological data were provided by the Royal Observatory of Hong Kong (ROHK). Preprocessing procedures were essential for this neural network rainfall forecasting. The forecast of the rainfall was performed every half an hour so that a storm warning signal can be delivered to the public in advance. The network architecture is based on a recurrent Sigma-Pi network. The results are very promising, and this neural-based rainfall forecasting system is capable of providing a rain storm warning signal to the Hong Kong public one hour ahead.     

On a large-gain theorem

The aim of this paper is to give a general quantitative requirement which the loop gain must satisfy in order to stabilize a given unstable (possibly nonlinear and time-varying) plant, namely that the gain must exceed one.     

Finite element beam propagation method for three-dimensionaloptical waveguide structures

A beam propagation method (BPM) based on the finite element method (FEM) is described for longitudinally varying three-dimensional (3-D) optical waveguides. In order to avoid nonphysical reflections from the computational window edges, the transparent boundary condition is introduced. The present algorithm using the Pade approximation is, to our knowledge, the first wide-angle finite element beam propagation method for 3-D waveguide structures. To show the validity and usefulness of this approach, numerical results are shown for Gaussian-beam excitation of a straight rib waveguide and guided-mode propagation in a Y-branching rib waveguide     

Densification involved in the UV-based photosensitivity of silicaglasses and optical fibers

A comprehensive survey of photosensitivity in silica glasses and optical fiber is reviewed. Recent work on understanding the mechanisms contributing to germanium or aluminum doped fiber photosensitivity is discussed within the framework of photoelastic densification models     

A new lateral MOS-gated thyristor with controlling base-current

A new lateral MOS-gated thyristor, called the Base-Current-Controlled Thyristor, is described. This device is designed so that most holes at the on-stage reach the P base through the floating P⁺ region adjacent to the P base and the on-state MOSFET. At the turn-off stage, the interruption of the hole current to the P base due to switching off the above MOSFET occurs simultaneously with the conventional turn-off operation. The concept of this device is verified experimentally by using the fabricated lateral device with the external MOSFET. This device exhibits a better trade-off relation between the on-state voltage and the turn-off time compared uith the conventional MOS-gated thyristor     

Automatic tuning of decentralized PID controllers for MIMO processes

An automatic tuning algorithm for decentralized PID control in multiple-input multiple-output (MIMO) plants is presented. This algorithm generalizes the authors' recent auto-tuner for two-input two-output systems to any number of inputs and outputs. The algorithm consists of two stages. In the first, the desired critical point, which consists of the critical gains of all the loops and a critical frequency, is identified. The auto-tuner identifies the desired critical point with almost no a priori information about the process. During the identification phase all controllers are replaced by relays, thus generating limit cycles with the same period in all loops. It is shown that each limit cycle corresponds to a single critical point of the process. By varying the relays parameters different points can be determined. The auto-tuner contains a procedure which converges rapidly to the desired critical point while maintaining the amplitudes of the process variables as well as of the manipulated variables within prespecified ranges. In the second stage, the data of the desired critical point is used to tune the PID controllers by the Ziegler-Nichols rules or their modifications. This paper focuses on the first stage. The steady-state process gains, which are required for the appropriate choice of the desired critical point, are determined by the auto-tuner in closed-loop fashion simultaneously with the identification of the critical point. The identification of the process gains is achieved at no extra plant time. Based upon a large number of simulated cases, the proposed auto-tuner seems to be efficient and robust. The paper discusses the underlying principles of the auto-tuner and its properties and capabilities are demonstrated via examples.