The automatic identification of plant species is a great challenge because their patterns are complex and uncertain. In this paper, the fuzzy set theory was applied to ident@ weed species. A membership function was established. The experiment has shown, that the average rate of correct identifkation has improved from 67% to greater than 82%.They belong to fuzzy patterns. Therefore the fuzzy pattern recognition should be used to i d e n w plant species. Fuzzy sets are a mathematical concept proposed by Prof. L. A. Zadeh in 1965. Fuzzy set theory has been developed to include methodologies for applications such as modelling, evaluation, optimisation, decision making, control, diagnosis, and information[2]. In this paper an effective method based on the fuzzy set theory was developed to recognise weed species. The average rate of correct identification has reached over 82%.

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Accurate animation of the thermo-fluidic performance of the pressure-wave machine and its balanced material operation H. OberhemH.A. Nour Eldin Article information:To cite this document: H. OberhemH. A. Nour Eldin, (1995),"Accurate animation of the thermo-fluidic performance of the pressure-wave machine and its balanced material operation"If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. ABSTRACTModelling, computation and performance animation of turbomachinery systems has recently enjoyed remarkable attention in CAD research. This is also reflected its application to exhaust machine components such as turbo loaders and the exceptionally novel pressure wave machine (Comprex) in the automobile industry and gas turbines. The necessity for the thermo-fluidic performance animation of such pressure wave machines results from the fact that the machine geometry must be adapted to the technical and thermo-fluidic properties of the exhaust flow of the gas turbine or automobile engine. Experimental adaptation or adjustment is costly and should be validated for every application case. Thus the potential to apply accurate animation for such shock-tube like behaviour of compressible flow is now economically promising with a view to optimizing the design of the pressure wave machine. This paper presents briefly the problem oriented algorithms used and illustrates the performance animation of the pressure wave machine operating under constant speed drive. After introducing the pressure wave machine operation, the principles and summary of the algorithms used to compute the thermodynamic behaviour within the cell, the boundary models and the accuracy of computation. A Comprex cycle operating on an engine exhaust gas with T= 920°K, p = 2bar is illustrated through 3-dimensional representations for pressure, speed of flow and temperature. The particle path (gas and air) together with time representation of the state variables at different points of the Compex will be shown. The mass balance problem is discussed and the conditions for mass balanced flow for the gas as well as for the air side are given. The results achieved for such materially balanced pressure wave machines indicate a reduction in the costs for subsequent experimental validation and to ...

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Automatic identification of 10 weed species in digital images using Fourier descriptors and shape parameters Plant species discrimination in mixed plant communities has recently become possible using transforms and shape parameters to classify digital images. In the present study image analysis techniques were used to identify weeds commonly found in winter cereal fields. Those species included Veronica hedenfolia L., Thlaspi arvense Beauv., Alopecurus myosuroides L., Apera spica‐venti L., Poa annua L., Stellaria media L., Capsella bursa‐pastoris L., Lamium purpureum L., Matricaria chamomilla L. and Galium aparine L. Images of several growth stages of these weeds were photographed using a Still Videokamera, binarified, the shape extracted and then Fourier descriptors and shape parameter were calculated for each weed. Classified digital images of each species were stored on the computer. A separate set of photographic images of these 10 weeds were used to test the ability of the classified images for plant identification. The average rate of correct identification was 81.9 % ranging from 41.6 % to 100 %.