• Journal of the Korean Society for information Management
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• v.40 no.1
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• pp.225-258
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• 2023

The purpose of this study is to investigate the current status and characteristics of research data sharing by domestic researchers by analyzing the data sharing mechanism and repository specified in DAS of papers authored by domestic researchers. To this end, in this study, papers of researchers belonging to domestic institutions published in PLOS ONE from 2014 to 2022 were selected as the subject of the study. First of all, the status of DAS's existence in the papers was identified, the types of data-sharing mechanisms were analyzed using precedent studies, and the trend of changes in each data-sharing mechanism over time was investigated. As a result, it was found that DAS was written in 99.6% of the target papers, and the types of data-sharing mechanisms were similar to international patterns, but preferred types were changing over time. Afterward, focusing on repositories among data sharing mechanisms, the number and ratio of repositories mentioned in DAS were identified, and the trend of changes in use of the five repositories mentioned a lot was analyzed in a time series. In addition, the presentation method, type, and validity of the data access point mentioned along with the repository were also investigated. It was confirmed that the top five frequently mentioned repositories account for 60% of all repository mentions, and the use of a repository dealing with data codes is increasing; in addition, it was found that most of the data access points presented with the repository were valid.

• Journal of Electrical Engineering and information Science
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• v.3 no.1
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• pp.1-7
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• 1998

High-Level synthesis of digital circuits calls for automatic translation of a behavioral description to a structural design entity represented in terms of components and connection. One of the critical steps in high-level synthesis is to determine a particular scheduling algorithm that will assign behavioral operations to control states. A new scheduling algorithm called Data Availability Scheduling (DAS) for high-level synthesis is presented. It can determine an appropriate scheduling algorithm and minimize the number of states required using data availability and dependency conditions extracted from the behavioral code, taking into account of states required using data availability and dependency conditions extracted from the behavioral code, taking into account resource constraint in each control state. The DAS algorithm is efficient because data availability conditions, and conditional and wait statements break the behavioral code into manageable pieces which are analyzed independently. The output is the number of states in a finite state machine and shows better results than those of previous algorithms.