Department of Systems and Computer Science, Howard University, Washington, DC 20059, USA.
Comput Math Methods Med. 2012;2012:892098. doi: 10.1155/2012/892098. Epub 2012 Dec 9.
Biology data is increasing exponentially from biological laboratories. It is a complicated problem for further processing the data. Processing computational data and data from biological laboratories manually may lead to potential errors in further analysis. In this paper, we proposed an efficient data-driven framework to inspect laboratory equipment and reduce impending failures. Our method takes advantage of the 2D barcode technology which can be installed on the specimen as a trigger for the data-driven system. For this end, we proposed a series of algorithms to speed up the data processing. The results show that the proposed system increases the system's scalability and flexibility. Also, it demonstrates the ability of linking a physical object with digital information to reduce the manual work related to experimental specimen. The characteristics such as high capacity of storage and data management of the 2D barcode technology provide a solution to collect experimental laboratory data in a quick and accurate fashion.
生物实验室产生的数据呈指数级增长。这些数据的进一步处理是一个复杂的问题。手动处理计算数据和生物实验室数据可能会导致进一步分析中的潜在错误。在本文中，我们提出了一种高效的数据驱动框架来检查实验室设备并减少潜在故障。我们的方法利用了可以安装在标本上的二维条码技术，作为数据驱动系统的触发器。为此，我们提出了一系列算法来加速数据处理。结果表明，所提出的系统提高了系统的可扩展性和灵活性。此外，它还展示了将物理对象与数字信息联系起来的能力，从而减少了与实验标本相关的手动工作。二维条码技术的高存储容量和数据管理等特点为快速、准确地收集实验实验室数据提供了一种解决方案。
