Ponce Hiram, Ponce Pedro, Molina Arturo
Graduate School of Engineering, Tecnologico de Monterrey, Campus Ciudad de Mexico, 14380, Mexico City, Mexico; Faculty of Engineering, Universidad Panamericana, 03920, Mexico City, Mexico.
J Comput Chem. 2015 Mar 15;36(7):478-92. doi: 10.1002/jcc.23818. Epub 2015 Jan 6.
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.
科学家和研究人员在尝试使用新的前沿算法进行实验时面临的两个最具挑战性的问题是编码耗时以及将它们与其他技术和设备进行连接存在困难。从这个意义上讲，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，使其未来有可能基于此技术添加新算法。此外，该工具包继承了LabVIEW™软件的快速原型制作和易于使用的特性（例如，图形化编程、其他软件和设备的透明使用、用于用户界面的内置编程事件驱动），从而使终端用户使用起来很简单。事实上，本文描述了该工具包的整体架构，特别强调了所谓的人工碳氢化合物网络算法的软件实现。最后，本文包括两个用于工程目的（即传感器表征）和化学应用（即血脑屏障分配数据模型）的案例研究，以展示该工具包的使用以及人工有机网络技术的潜在可扩展性。
