An Interval Temporal Logic for Time Series Specification and Data Integration
The analysis of temporal series—in particular, analysis of multisensor data—is a complex problem. It depends on the application domain, the way the data have to be used, and sensors available, among other factors. Various models, algorithms, and technologies have been designed for this goal. Tempora...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/12/2236 |
| _version_ | 1797530966155067392 |
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| author | Piotr Kosiuczenko |
| author_facet | Piotr Kosiuczenko |
| author_sort | Piotr Kosiuczenko |
| collection | DOAJ |
| description | The analysis of temporal series—in particular, analysis of multisensor data—is a complex problem. It depends on the application domain, the way the data have to be used, and sensors available, among other factors. Various models, algorithms, and technologies have been designed for this goal. Temporal logics are used to describe temporal properties of systems. The properties may specify the occurrence and the order of events in time, recurring patterns, complex behaviors, and processes. In this paper, a new interval logic, called duration calculus for functions (DC4F), is proposed for the specification of temporal series corresponding to multisensor data. DC4F is a natural extension of the well-known duration calculus, an interval temporal logic for the specification of process duration. The adequacy of the proposed logic is analyzed in the case of multisensor data concerning volcanic eruption monitoring. It turns out that the relevant behavior concerns time intervals, not only accumulated history as it is described in other kinds of temporal logics. The examples analyzed demonstrate that a description language is required to specify time series of various kind relative to time intervals. The duration calculus cannot be successfully applied for this task. The proposed calculus allows one to specify temporal series and complex interval-dependent behaviors, and to evaluate the corresponding data within a unifying logical framework. It allows to formulate hypotheses concerning volcano eruption phenomena. However, the expressivity of DC4F comes at the cost of its decidability. |
| first_indexed | 2024-03-10T10:37:27Z |
| format | Article |
| id | doaj.art-c7b2fb5488f94f3b94676e71895624af |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T10:37:27Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-c7b2fb5488f94f3b94676e71895624af2023-11-21T23:13:50ZengMDPI AGRemote Sensing2072-42922021-06-011312223610.3390/rs13122236An Interval Temporal Logic for Time Series Specification and Data IntegrationPiotr Kosiuczenko0Institute of Information Systems, Military University of Technology, 00-908 Warsaw, PolandThe analysis of temporal series—in particular, analysis of multisensor data—is a complex problem. It depends on the application domain, the way the data have to be used, and sensors available, among other factors. Various models, algorithms, and technologies have been designed for this goal. Temporal logics are used to describe temporal properties of systems. The properties may specify the occurrence and the order of events in time, recurring patterns, complex behaviors, and processes. In this paper, a new interval logic, called duration calculus for functions (DC4F), is proposed for the specification of temporal series corresponding to multisensor data. DC4F is a natural extension of the well-known duration calculus, an interval temporal logic for the specification of process duration. The adequacy of the proposed logic is analyzed in the case of multisensor data concerning volcanic eruption monitoring. It turns out that the relevant behavior concerns time intervals, not only accumulated history as it is described in other kinds of temporal logics. The examples analyzed demonstrate that a description language is required to specify time series of various kind relative to time intervals. The duration calculus cannot be successfully applied for this task. The proposed calculus allows one to specify temporal series and complex interval-dependent behaviors, and to evaluate the corresponding data within a unifying logical framework. It allows to formulate hypotheses concerning volcano eruption phenomena. However, the expressivity of DC4F comes at the cost of its decidability.https://www.mdpi.com/2072-4292/13/12/2236duration calculusdata modelstemporal logictemporal seriesdata fusiondata evaluation |
| spellingShingle | Piotr Kosiuczenko An Interval Temporal Logic for Time Series Specification and Data Integration Remote Sensing duration calculus data models temporal logic temporal series data fusion data evaluation |
| title | An Interval Temporal Logic for Time Series Specification and Data Integration |
| title_full | An Interval Temporal Logic for Time Series Specification and Data Integration |
| title_fullStr | An Interval Temporal Logic for Time Series Specification and Data Integration |
| title_full_unstemmed | An Interval Temporal Logic for Time Series Specification and Data Integration |
| title_short | An Interval Temporal Logic for Time Series Specification and Data Integration |
| title_sort | interval temporal logic for time series specification and data integration |
| topic | duration calculus data models temporal logic temporal series data fusion data evaluation |
| url | https://www.mdpi.com/2072-4292/13/12/2236 |
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