Moon-Il Joo, Tae-Woong Kim, Youl-Ga Cho, Hee-Cheol Kim
{"title":"Design of AB Broker-Based Bio-Signal Analysis System to Secure Interoperability","authors":"Moon-Il Joo, Tae-Woong Kim, Youl-Ga Cho, Hee-Cheol Kim","doi":"10.1109/IS3C50286.2020.00016","DOIUrl":null,"url":null,"abstract":"With the recent development of artificial intelligence and data mining technology, various and intelligent bio-signal analysis technologies have been developed. Bio-signal analysis algorithms and technologies are primarily developed using MATLAB and open source technologies such as Python and R. The analysis algorithms developed with such programming languages can only be employed and run in their own respective development environments and hence are unfortunately not considered as platform independent. In that respect, the interoperability between development tools is needed to ensure efficiency in terms of development time and efforts and reusability between analysis technologies and algorithms developed in different languages. This paper presents the development of a bio-signal analysis system that ensures interoperability which leads to one common environment connecting different development platforms. To maintain the interoperability between MATLAB and R programming, we designed and implemented the Algorithm Block Broker (AB Broker). AB Broker is composed of AB Adapter and AB Broker. Here, the AB Broker uses AB Adapter to request execution of analysis algorithms developed in different languages such as MATLAB, R and Python. It also searches and runs the algorithm, helping implement the requested analysis technique. The AB Broker-based bio-signal analysis system enables the integrated management of analysis and data mining technologies developed in different languages. From developers' points of view, therefore, it is convenient and efficient to develop techniques using existing different programming technologies.","PeriodicalId":143430,"journal":{"name":"2020 International Symposium on Computer, Consumer and Control (IS3C)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Symposium on Computer, Consumer and Control (IS3C)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IS3C50286.2020.00016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the recent development of artificial intelligence and data mining technology, various and intelligent bio-signal analysis technologies have been developed. Bio-signal analysis algorithms and technologies are primarily developed using MATLAB and open source technologies such as Python and R. The analysis algorithms developed with such programming languages can only be employed and run in their own respective development environments and hence are unfortunately not considered as platform independent. In that respect, the interoperability between development tools is needed to ensure efficiency in terms of development time and efforts and reusability between analysis technologies and algorithms developed in different languages. This paper presents the development of a bio-signal analysis system that ensures interoperability which leads to one common environment connecting different development platforms. To maintain the interoperability between MATLAB and R programming, we designed and implemented the Algorithm Block Broker (AB Broker). AB Broker is composed of AB Adapter and AB Broker. Here, the AB Broker uses AB Adapter to request execution of analysis algorithms developed in different languages such as MATLAB, R and Python. It also searches and runs the algorithm, helping implement the requested analysis technique. The AB Broker-based bio-signal analysis system enables the integrated management of analysis and data mining technologies developed in different languages. From developers' points of view, therefore, it is convenient and efficient to develop techniques using existing different programming technologies.