Artificial keys for botanical identification using a multilayer perceptron neural network (MLP)

In this paper, practical generation of identification keys for biological taxa using a multilayer perceptron neural network is described. Unlike conventional expert systems, this method does not require an expert for key generation, but is merely based on recordings of observed character states. Like a human taxonomist, its judgement is based on experience, and it is therefore capable of generalized identification of taxa. An initial study involving identification of three species of Iris with greater than 90% confidence is presented here. In addition, the horticulturally significant genus Lithops (Aizoaceae/Mesembryanthemaceae), popular with enthusiasts of succulent plants, is used as a more practical example, because of the difficulty of generation of a conventional key to species, and the existence of a relatively recent monograph. It is demonstrated that such an Artificial Neural Network Key (ANNKEY) can identify more than half (52.9%) of the species in this genus, after training with representative data, even though data for one character is completely missing.

Using self-organising feature maps for the control of artificial organisms

Variations on the standard Kohonen feature map can enable an ordering of the map state space by using only a limited subset of the complete input vector. Also it is possible to employ merely a local adaptation procedure to order the map, rather than having to rely on global variables and objectives. Such variations have been included as part of a hybrid learning system (HLS) which has arisen out of a genetic-based classifier system. In the paper a description of the modified feature map is given, which constitutes the HLSs long term memory, and results in the control of a simple maze running task are presented, thereby demonstrating the value of goal related feedback within the overall network.

Ventilation for air quality and energy efficiency

This article addresses the need for providing good standards of indoor air quality (IAQ) in buildings from the view point of health, well-being and productivity of building occupants. It briefly outlines the role of ventilation in achieving the required IAQ targets and discusses the performance of different types of ventilation systems in use. As a result of new energy efficiency directives and legislations in Europe and elsewhere, the ventilation energy component of HVAC systems has increased in relative terms and this article introduces a method for evaluating the performance air distribution systems that is based on ventilation and energy effectiveness. A range of ventilation systems are discussed, including mechanical and natural ventilation, and results for more recently developed mechanical air distribution systems are compared with conventional systems. The article provides an assessment and comparison of some of these systems with reference to ventilation performance and energy efficiency

Object detecting artificial retina

This paper describes the novel use of agent and cellular neural Hopfield network techniques in the design of a self-contained, object detecting retina. The agents, which are used to detect features within an image, are trained using the Hebbian method which has been modified for the cellular architecture. The success of each agent is communicated with adjacent agents in order to verify the detection of an object. Initial work used the method to process bipolar images. This has now been extended to handle grey scale images. Simulations have demonstrated the success of the method and further work is planned in which the device is to be implemented in hardware.

Evaluation of dichroic material for enhancing light pipe/natural ventilation and daylighting in an integrated system

Integration of natural ventilation and daylighting in a single installation would make both technologies more attractive. One method for the integration is the use of concentric light pipe and ventilation stack. By constructing the light pipe using dichroic materials, the infrared part of the solar radiation is allowed to be transmitted to the stack but the visible light is guided by the light pipe into a room. The heat gain to the interior can be reduced and the thermal stack effect strengthened. Work presented here involved the experimental and computational evaluation of dichroic materials for enhancing both natural stack ventilation and daylighting. The transmittance of a dichroic light pipe was found to be similar to that of a light pipe with a 95% specular reflectance. The infra-red radiation transmitted through the dichroic material into a passive stack was found to enhance the natural ventilation flow by up to 14%. The effect is greater in summer than in winter, which is highly desirable as there is often a lack of driving force for natural stack ventilation in summer.