Abstract: Sanitation apparatus including: a treatment chamber having a chamber wall, an inlet penetrating the chamber wall for receiving liquid into the treatment chamber and an outlet penetrating the chamber wall remote from the liquid inlet for discharge of liquid from the treatment chamber; an expanded portion in the chamber wall adjacent the inlet; a cylindrical portion in the chamber wall intermediate the expanded portion and the outlet; a gas injector penetrating the chamber wall in the expanded portion for injecting gas into the chamber; and UV irradiation means mounted to the chamber wall and extending through the expanded portion and the cylindrical portion for irradiating at least part of the chamber.

Abstract: Sanitation apparatus including: a treatment chamber having a chamber wall, an inlet penetrating the chamber wall for receiving liquid into the treatment chamber and an outlet penetrating the chamber wall remote from the liquid inlet for discharge of liquid from the treatment chamber; an expanded portion in the chamber wall adjacent the inlet; a cylindrical portion in the chamber wall intermediate the expanded portion and the outlet; a gas injector penetrating the chamber wall in the expanded portion for injecting gas into the chamber; and UV irradiation means mounted to the chamber wall and extending through the expanded portion and the cylindrical portion for irradiating at least part of the chamber.

Abstract: A motorized valve including: a valve body having a housing wall and one or more inlet ports and a plurality of outlet ports penetrating the housing wall; each outlet port being arranged in spaced relationship from one another about a seat face, said seat face substantially conforming to an inner face of circular cylinder and each said outlet port having an orifice penetrating said seat face; a valve stopper having a stopper body formed with a sealing face conforming to an outer face of a circular cylinder commensurate with the dimensions of said seat face whereby said stopper body is rotatable within the valve body about a common axis shared by the valve body and the valve stopper, a valve stem extending axially from the stopper body, and a fluid communication passage formed into said stopper body for providing fluid communication between said one or more inlet ports penetrating said housing wall and a selected one or more of said outlet ports; and drive means operatively interposed between said valve stem an

Abstract: A signal transformation method that transforms an input signal obtained from a subject under a first value of a parameter to an output signal obtainable from said subject under a second value of said parameter is disclosed. The method creates a plurality of neural networks and subjects them to learn the mapping transformation. Genetic programming is used to evolve said plurality of neural networks by applying genetic operators to alter the configurations of said plurality of neural networks. The process of neural learning and genetic altering repeats until a predetermined number of generations is reach. The neural network that performs the mapping transformation best can be selected as the optimal neural network. This optimal neural network can be used subsequently to transform a second input signal to a second output signal for a pre-defined value of the parameter.

Abstract: The present invention is a computer system that analyses the factual and behavioural data of a group of subjects, extracts the common behavioural patterns from the collection, and is capable of forecasting the behaviour of a new subject when his or her factual data are inputted to the system. It does so by first taking a collection of both the factual data and behavioural data from a group of subjects. A clustering engine is employed to compute a set of exemplars that concisely represent the population. Afterwards, the factual data of a subject, and the corresponding behavioural exemplar that he or she belongs, are fed to a learning module so that it can learn the mapping between the subject's factual data and behavioural exemplar. After learning, the system is able to predict the behaviour patterns when factual data of a new subject is presented.