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This work focuses on the implementation of high performance systems to the wastewater treatment of sugar factories. For this purpose, systems with immobilised bacteria were studied. For the hydrolysis of organic matter and denitrification, fluidized bed reactors were used. The nitrification was studied with an airlift reactor system. Both hydrolysis and nitrogen elimination were investigated on laboratory and pilot scales in sugar factories. Although with porous materials higher biomass concentrations are attainable for the hydrolysis (up to 55 kg/m3), for economical reasons sand was used (22.5 kg/m3) for the pilot scale-study. With a pilot-scale reactor (volume 1 m3) the maximum sucrose conversion rate achieved with sand in the first campaign was 52 kg/(m3 d). For the nitrogen elimination on the pilot scale, a system with denitrification and nitrification was combined. The highest performance for the nitrification (reactor volume: 0.68 m3) with pumice as support material was 1.2 kg NH4-N/(m3 d), limiting the whole system. The denitrification rate (reactor volume: 0.12 m3) was four times higher (3.5–5 kg NO3-N/(m3 d). Rules of the modelling of the system are discussed.

SUMMARY The purpose of this paper is to provide a quick overview of neural networks and to explain how they can be used in control systems. We introduce the multilayer perceptron neural network and describe how it can be used for function approximation. The backpropagation algorithm (including its variations) is the principal procedure for training multilayer perceptrons; it is briefly described here. Care must be taken, when training perceptron networks, to ensure that they do not overfit the training data and then fail to generalize well in new situations. Several techniques for improving generalization are discussed. The paper also presents three control architectures: model reference adaptive control, model predictive control, and feedback linearization control. These controllers demonstrate the variety of ways in which multilayer perceptron neural networks can be used as basic building blocks. We demonstrate the practical implementation of these controllers on three applications: a continuous stirred tank reactor, a robot arm, and a magnetic levitation system. Copyright # 2002 John Wiley & Sons, Ltd.

Dextransucrase catalyses the formation of dextran, but also of numerous oligosaccharides from sucrose and different acceptors, if appropriate conditions are chosen. Much experimental work has been carried out and a scheme of reactions and a mathematical model have been developed to describe the complex kinetic behaviour of the enzyme. A computer program was used to calculate the parameters of the model from a broad range of experimental data, investigating a large number of kinetic tests with the acceptors maltose and fructose. The results lead to design considerations for a continuous reactor system with immobilized dextransucrase to produce leucrose, a disaccharide of industrial interest.

Numerical image processing techniques are applied to the restoration of x‐ray pinhole photographs of solid targets irradiated by intense relativistic electron beams. The numerical and analytic bases for image restoration are briefly described. An experimentally determined point‐spread function for the pinhole camera is utilized to eliminate the effects of high‐energy x‐ray degradation of pinhole resolution. It is shown that penetration by hard x rays from filtered spectra through the pinhole edges can lead to apparent broadening of the electron‐beam pinch on high‐Z targets. Elimination of x‐ray shine‐through also permits determination of photon intensity from high‐Z target ablation products, and improves spatial resolution of the x‐ray source.

This paper presents an overall picture of the Kiwi-A reactor control systems. The techniques of analysis and design of the control systems, the reactor power and propellant flow rate control hardware, the control system performance during tests, and special measurements made on the control systems to check analytical predictions are discussed. Problems presented by future reactors and some new control systems for these reactors are described.

This short note describes two courses that dealt with microprocessors in an electrical engineering curriculum. The first course, taught at the junior level at Notre Dame, was in logic design. Training students in error-free microprocessor realization of logic circuits was a major course objective. The course was unique in that the first half was that of a "standard" logic curriculum, while the second half was devoted to microprocessor realization of combinational and sequential logic circuits. This second half included material on the Intel 8080 microprocessor, structured programming, a high level programming language (PL/M) and the application of skills in these areas to create microprocessor logic circuits. The course was self-paced. It achieved its primary objective and received an enthusiastic response from the students. The second course, taught at a senior/graduate level at the University of Tulsa, was titled "Advanced Microprocessor Systems Design." Its objectives were to introduce students to the 16 bit Intel 8086 microprocessor and associated integrated circuits, to develop student skills in both an assembly language (ASM-86) and a high level language (PL/M-86), and to teach the students the concepts of top-down structured design. Each student designed a small microcomputer based on the 8086 and its associated integrated circuits. In both courses, students learned new microprocessor and programming skills quickly and efficiently. As hoped, use of disciplined techniques such as careful problem statement and structured programming led students in both courses to error-free microprocessor logic circuits.