894 resultados para Computer-Aided Engineering (CAD, CAE) and design


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Cover title.

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The Community Development Block Grant (CDBG) Program was established by the federal Housing and Community Development Act of 1974 (Act). Administered nationally by the U.S. Department of Housing and Urban Development (HUD), the Act combined eight existing categorical programs into a single block grant program. In 1981, Congress amended the Act to allow states to directly administer the block grant for small cities. At the designation of the Governor, the Department of Commerce and Community Affairs assumed operation of the State of Illinois Community Development Block Grant -- Small Cities Program in the same year. The Illinois Block grant program is known as the Community Development Assistance Program (CDAP). Through this program, funds are available to assist Illinois communities meet their greatest economic and community development needs, with an emphasis upon helping persons of low-to-moderate income.

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The Community Development Block Grant (CDBG) Program was established by the federal Housing and Community Development Act of 1974 (Act). Administered nationally by the U.S. Department of Housing and Urban Development (HUD), the Act combined eight existing categorical programs into a single block grant program. In 1981, Congress amended the Act to allow states to directly administer the block grant for small cities. At the designation of the Governor, the Department of Commerce and Community Affairs assumed operation of the State of Illinois Community Development Block Grant -- Small Cities Program in the same year. The Illinois Block grant program is known as the Community Development Assistance Program (CDAP). Through this program, funds are available to assist Illinois communities meet their greatest economic and community development needs, with an emphasis upon helping persons of low-to-moderate income.

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Includes bibliographical references.

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Immunoinformatics is an emergent branch of informatics science that long ago pullulated from the tree of knowledge that is bioinformatics. It is a discipline which applies informatic techniques to problems of the immune system. To a great extent, immunoinformatics is typified by epitope prediction methods. It has found disappointingly limited use in the design and discovery of new vaccines, which is an area where proper computational support is generally lacking. Most extant vaccines are not based around isolated epitopes but rather correspond to chemically-treated or attenuated whole pathogens or correspond to individual proteins extract from whole pathogens or correspond to complex carbohydrate. In this chapter we attempt to review what progress there has been in an as-yet-underexplored area of immunoinformatics: the computational discovery of whole protein antigens. The effective development of antigen prediction methods would significantly reduce the laboratory resource required to identify pathogenic proteins as candidate subunit vaccines. We begin our review by placing antigen prediction firmly into context, exploring the role of reverse vaccinology in the design and discovery of vaccines. We also highlight several competing yet ultimately complementary methodological approaches: sub-cellular location prediction, identifying antigens using sequence similarity, and the use of sophisticated statistical approaches for predicting the probability of antigen characteristics. We end by exploring how a systems immunomics approach to the prediction of immunogenicity would prove helpful in the prediction of antigens.

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We present the prototype tool CADS* for the computer-aided development of an important class of self-* systems, namely systems whose components can be modelled as Markov chains. Given a Markov chain representation of the IT components to be included into a self-* system, CADS* automates or aids (a) the development of the artifacts necessary to build the self-* system; and (b) their integration into a fully-operational self-* solution. This is achieved through a combination of formal software development techniques including model transformation, model-driven code generation and dynamic software reconfiguration.