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The Development of an Artificial Organic Networks Toolkit for LabVIEW

机译:LabVIEW的人工有机网络工具包的开发

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Two of the most challenging problems that scientists and researchers face when they want to experiment with new cutting-edge algorithms are the time-consuming for encoding and the difficulties for linking them with other technologies and devices. In that sense, this article introduces the artificial organic networks toolkit for LabVIEW (AON-TL) from the implementation point of view. The toolkit is based on the framework provided by the artificial organic networks technique, giving it the potential to add new algorithms in the future based on this technique. Moreover, the toolkit inherits both the rapid prototyping and the easy-to-use characteristics of the LabVIEW software (e.g., graphical programming, transparent usage of other softwares and devices, built-in programming event-driven for user interfaces), to make it simple for the end-user. In fact, the article describes the global architecture of the toolkit, with particular emphasis in the software implementation of the so-called artificial hydrocarbon networks algorithm. Lastly, the article includes two case studies for engineering purposes (i.e., sensor characterization) and chemistry applications (i.e., blood-brain barrier partitioning data model) to show the usage of the toolkit and the potential scalability of the artificial organic networks technique. (c) 2015 Wiley Periodicals, Inc.
机译:科学家和研究人员在尝试使用新的尖端算法时面临的两个最具挑战性的问题是编码的耗时以及将它们与其他技术和设备链接的困难。从这种意义上讲,本文从实现的角度介绍了用于LabVIEW的人工有机网络工具包(AON-TL)。该工具包基于人工有机网络技术提供的框架,因此有可能在将来基于该技术添加新算法。而且,该工具包继承了LabVIEW软件的快速原型设计和易于使用的特性(例如,图形化编程,其他软件和设备的透明使用,内置的事件驱动的用户界面编程),以使其成为现实。对于最终用户来说很简单。实际上,本文描述了该工具包的全局体系结构,尤其着重于所谓的人工碳氢化合物网络算法的软件实现。最后,本文包括两个案例研究,分别用于工程目的(即传感器表征)和化学应用(即血脑屏障划分数据模型),以展示该工具包的用途以及人工有机网络技术的潜在可扩展性。 (c)2015年威利期刊有限公司

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