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The problem of the computer aided control of the temperature, humidity, and homogeneity of a glass batch and the degree of its compositional correspondence to a recipe using mathematical models based on artificial neural networks and a Siemens software tool system to improve the quality of flat glass has been solved.

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The article presents the architecture of a decision support system for a reasonable choice of the characteristics of autostereoscopic displays. Autostereoscopic displays are proposed as basic models developed by the corporate team, which are based on the original patented idea. It uses the combined reference images together with the appropriate optical systems. This allows to significantly reduce the requirements for the speed of data transmission channels, as well as to computers. The attention is paid to the main modules of the decision support system, which is a hybrid expert system. There is given the relationship in the form of adjacency matrix between characteristics that influence on the quality of the generated output volumetric image. The values of the coefficients of the influence of characteristics on the output image are described. A scheme has been developed for determining the user and design characteristics of autostereoscopic displays. There is given an example of determining the design characteristics of a given type of autostereoscopic displays using the proposed decision support system.

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