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首页> 外文期刊>IAENG Internaitonal journal of computer science >A Solution for Problems in the Organization, Storage and Processing of Large Data Banks of Physiological Variables
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A Solution for Problems in the Organization, Storage and Processing of Large Data Banks of Physiological Variables

机译:大型生理变量数据库的组织,存储和处理中的问题的解决方案

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The proliferation and popularization of new instruments for measuring different types of electrophysiological variables have generated the need to store huge volumes of information, corresponding to the records obtained by applying this instruments on experimental subjects. Together with this must be added the data derived from the analysis and purification processes. Moreover, several stages involved in the processing of data is associated with one or more specific methods related to the area of research and to the treatment at which the base information (RAW) is subjected. As a result of this and with the passage of time, various problems occur, which are the most obvious consequence of that data and metadata derived from the treatment processes and analysis and can end up accumulating and requiring more storage space than the base data. In addition, the enormous amount of information, as it increases over time, can lead to the loss of the link between the processed data, the methods of treatment used, and the analysis performed so that eventually all becomes simply a huge repository of biometric data, devoid of meaning and sense. This paper presents an approach founded on a data model that can adequately handle different types of chronologies of physiological and emotional information, ensuring confidentiality of information according to the experimental protocols and relevant ethical requirements, linking the information with the methods of treatment used and the technical and scientific documents derived from the analysis. Consequently, the need to generate specific data model is justified by the fact that the tools currently associated with the storage of large volumes of information are not able to take care of the semantic elements that make up the metadata and information relating to the analysis of base records of physiological information. This work is an extension of our paper [25].
机译:用于测量不同类型的电生理变量的新仪器的激增和普及引起了对存储大量信息的需求,这与通过将该仪器应用于实验对象而获得的记录相对应。与此同时,必须添加从分析和纯化过程中获得的数据。此外,数据处理中涉及的几个阶段与一种或多种与研究领域和基础信息(RAW)所经受的处理有关的特定方法相关。结果,随着时间的流逝,出现了各种问题,这是从处理过程和分析中得出的数据和元数据的最明显后果,并且最终可能会积累起来并需要比基础数据更多的存储空间。此外,随着时间的推移,海量信息的增加会导致处理数据,所使用的处理方法以及所进行的分析之间的链接丢失,从而最终使所有信息变成一个巨大的生物统计数据存储库,没有意义和意义。本文提出了一种基于数据模型的方法,该方法可以充分处理不同类型的生理和情感信息的时间顺序,根据实验方案和相关的道德要求确保信息的机密性,并将信息与使用的治疗方法和技术联系起来分析得出的科学文献。因此,由于当前与大量信息的存储相关联的工具无法处理构成元数据和与基础分析有关的信息的语义元素,因此需要生成特定的数据模型是合理的。生理信息记录。这项工作是我们论文的扩展[25]。

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