Curtis Dyreson - Academia.edu (original) (raw)
Papers by Curtis Dyreson
Encyclopedia of Database Systems, 2018
Plug-and-play queries are portable, reliable, and easier to code. When a plug-and-play query is p... more Plug-and-play queries are portable, reliable, and easier to code. When a plug-and-play query is plugged into a data socket, the socket transforms the data to the shape needed by the query. If data is annotated with metadata, the semantics of the metadata potentially impacts the transformation. In this paper we describe how to account for the metadata in a transformation. We focus on temporal metadata and show how a transformation can preserve temporal semantics. We also show how the transformation can be driven by the metadata, for instance, the temporal metadata could be used to create data versions.
Encyclopedia of Database Systems, 2016
Encyclopedia of Database Systems, 2018
Encyclopedia of Database Systems, 2018
Temporal XML is a timestamped instance of an XML data model or, alternatively, an XML document wi... more Temporal XML is a timestamped instance of an XML data model or, alternatively, an XML document with specially interpreted timestamps which is parsed into a timestamped instance of an XML data model. An XML data model instance is a tree or graph in which each node corresponds to an element, attribute, or value, and each edge represents the lexical nesting of the child in the parent\u2019s content. In temporal XML, a timestamp is added to some nodes or edges in the instance. The timestamp represents the lifetime of the node or edge in one or more temporal dimensions, usually valid time or transaction time
Proceedings of the Second International Conference on Web Information Systems Engineering
Proceedings 12th Australasian Database Conference. ADC 2001
Proceedings of the 14th International Conference on Extending Database Technology, 2011
The TSQL2 Temporal Query Language, 1995
International Conference on Dublin Core and Metadata Applications, Oct 24, 2001
This paper presents the METAXPath data model and query language. METAXPath extends XPath with sup... more This paper presents the METAXPath data model and query language. METAXPath extends XPath with support for XML metadata. XPath is a specification language for locations in an XML document. It serves as the basis for XML query languages like XSLT and the XML Query Algebra. The METAXPath data model is a nested XPath tree. Each level of metadata induces a new level of nesting. The data model separates metadata and data into different dataspaces, supports meta-metadata, and enables sharing of metadata ...
Coronavirus Disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 ... more Coronavirus Disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2). The virus transmits rapidly; it has a basic reproductive number R of 2.2-2.7. In March 2020, the World Health Organization declared the COVID-19 outbreak a pandemic. COVID-19 is currently affecting more than 200 countries with 6M active cases. An effective testing strategy for COVID-19 is crucial to controlling the outbreak but the demand for testing surpasses the availability of test kits that use Reverse Transcription Polymerase Chain Reaction (RT-PCR). In this paper, we present a technique to screen for COVID-19 using artificial intelligence. Our technique takes only seconds to screen for the presence of the virus in a patient. We collected a dataset of chest X-ray images and trained several popular deep convolution neural network-based models (VGG, MobileNet, Xception, DenseNet, InceptionResNet) to classify the chest X-rays. Unsatisfied with these models, we then ...
Coronavirus Disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronaviru... more Coronavirus Disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2). The virus transmits rapidly, it has a basic reproductive number (R_0) of 2.2-2.7. In March, 2020 the World Health Organization declared the COVID-19 outbreak a pandemic. Effective testing for COVID-19 is crucial to controlling the outbreak since infected patients can be quarantined. But the demand for testing outstrips the availability of test kits that use Reverse Transcription Polymerase Chain Reaction (RT-PCR). In this paper, we present a technique to detect COVID-19 using Artificial Intelligence. Our technique takes only a few seconds to detect the presence of the virus in a patient. We collected a dataset of chest X-ray images and trained several popular deep convolution neural network-based models (VGG, MobileNet, Xception, DenseNet, InceptionResNet) to classify chest X-rays. Unsatisfied with these models we then designed and built a Residual Attention Netwo...
A now-centric collection of data is characterised by the property that as data in the collection ... more A now-centric collection of data is characterised by the property that as data in the collection ages, each datum individually becomes less relevant, but remains relevant in aggregate. Such data can be filtered by materialising an aggregate view on the data and then compressing, moving to backup, or deleting the data from which that view was materialised, yielding a smaller collection of data. This paper describes a tool to automatically filter data by building a statistical database from the now-centric collection of data. To build the statistical database, the user supplies a list of filters. Each filter consists of a filter unit and a filter measure. The filter unit specifies a pattern (a regular expression) to match as the now-centric data is filtered. The filter measure is the system of measurement in which occurrences of that pattern are counted. A key feature of the tool is that users may define their own units and measures. Queries on the filtered data are analysed to determ...
While "now " is expressed in SQL as CURRENT TIMESTAMP within queries, this value cannot... more While "now " is expressed in SQL as CURRENT TIMESTAMP within queries, this value cannot be stored in the database. However, this notion of an ever-increasing current-time value has been reflected in some temporal data models by inclusion of database-resident variables, such as "now," "until-changed," "1," "@" and "--." Time variables are very desirable, but their use also leads to a new type of database, consisting of tuples with variables, termed a variable database. This paper proposes a framework for defining the semantics of the variable databases of the relational and temporal relational data models. A framework is presented because several reasonable meanings may be given to databases that use some of the specific temporal variables that have appeared in the literature. Using the framework, the paper defines a useful semantics for such databases. Because situations occur where the existing time variables are inadequat...
Encyclopedia of Database Systems
We present the TreeScape system that, unlike any other system known to the authors, enables the r... more We present the TreeScape system that, unlike any other system known to the authors, enables the reuse of pre-computed aggregate query results for irregular dimension hierarchies, which occur frequently in practice. The system establishes a foundation for obtaining high query processing performance while pre-computing only limited aggregates. The paper shows how this reuse of aggregates is enabled through dimension transformations that occur transparently to the user.
Encyclopedia of Database Systems, 2018
Plug-and-play queries are portable, reliable, and easier to code. When a plug-and-play query is p... more Plug-and-play queries are portable, reliable, and easier to code. When a plug-and-play query is plugged into a data socket, the socket transforms the data to the shape needed by the query. If data is annotated with metadata, the semantics of the metadata potentially impacts the transformation. In this paper we describe how to account for the metadata in a transformation. We focus on temporal metadata and show how a transformation can preserve temporal semantics. We also show how the transformation can be driven by the metadata, for instance, the temporal metadata could be used to create data versions.
Encyclopedia of Database Systems, 2016
Encyclopedia of Database Systems, 2018
Encyclopedia of Database Systems, 2018
Temporal XML is a timestamped instance of an XML data model or, alternatively, an XML document wi... more Temporal XML is a timestamped instance of an XML data model or, alternatively, an XML document with specially interpreted timestamps which is parsed into a timestamped instance of an XML data model. An XML data model instance is a tree or graph in which each node corresponds to an element, attribute, or value, and each edge represents the lexical nesting of the child in the parent\u2019s content. In temporal XML, a timestamp is added to some nodes or edges in the instance. The timestamp represents the lifetime of the node or edge in one or more temporal dimensions, usually valid time or transaction time
Proceedings of the Second International Conference on Web Information Systems Engineering
Proceedings 12th Australasian Database Conference. ADC 2001
Proceedings of the 14th International Conference on Extending Database Technology, 2011
The TSQL2 Temporal Query Language, 1995
International Conference on Dublin Core and Metadata Applications, Oct 24, 2001
This paper presents the METAXPath data model and query language. METAXPath extends XPath with sup... more This paper presents the METAXPath data model and query language. METAXPath extends XPath with support for XML metadata. XPath is a specification language for locations in an XML document. It serves as the basis for XML query languages like XSLT and the XML Query Algebra. The METAXPath data model is a nested XPath tree. Each level of metadata induces a new level of nesting. The data model separates metadata and data into different dataspaces, supports meta-metadata, and enables sharing of metadata ...
Coronavirus Disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 ... more Coronavirus Disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2). The virus transmits rapidly; it has a basic reproductive number R of 2.2-2.7. In March 2020, the World Health Organization declared the COVID-19 outbreak a pandemic. COVID-19 is currently affecting more than 200 countries with 6M active cases. An effective testing strategy for COVID-19 is crucial to controlling the outbreak but the demand for testing surpasses the availability of test kits that use Reverse Transcription Polymerase Chain Reaction (RT-PCR). In this paper, we present a technique to screen for COVID-19 using artificial intelligence. Our technique takes only seconds to screen for the presence of the virus in a patient. We collected a dataset of chest X-ray images and trained several popular deep convolution neural network-based models (VGG, MobileNet, Xception, DenseNet, InceptionResNet) to classify the chest X-rays. Unsatisfied with these models, we then ...
Coronavirus Disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronaviru... more Coronavirus Disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2). The virus transmits rapidly, it has a basic reproductive number (R_0) of 2.2-2.7. In March, 2020 the World Health Organization declared the COVID-19 outbreak a pandemic. Effective testing for COVID-19 is crucial to controlling the outbreak since infected patients can be quarantined. But the demand for testing outstrips the availability of test kits that use Reverse Transcription Polymerase Chain Reaction (RT-PCR). In this paper, we present a technique to detect COVID-19 using Artificial Intelligence. Our technique takes only a few seconds to detect the presence of the virus in a patient. We collected a dataset of chest X-ray images and trained several popular deep convolution neural network-based models (VGG, MobileNet, Xception, DenseNet, InceptionResNet) to classify chest X-rays. Unsatisfied with these models we then designed and built a Residual Attention Netwo...
A now-centric collection of data is characterised by the property that as data in the collection ... more A now-centric collection of data is characterised by the property that as data in the collection ages, each datum individually becomes less relevant, but remains relevant in aggregate. Such data can be filtered by materialising an aggregate view on the data and then compressing, moving to backup, or deleting the data from which that view was materialised, yielding a smaller collection of data. This paper describes a tool to automatically filter data by building a statistical database from the now-centric collection of data. To build the statistical database, the user supplies a list of filters. Each filter consists of a filter unit and a filter measure. The filter unit specifies a pattern (a regular expression) to match as the now-centric data is filtered. The filter measure is the system of measurement in which occurrences of that pattern are counted. A key feature of the tool is that users may define their own units and measures. Queries on the filtered data are analysed to determ...
While "now " is expressed in SQL as CURRENT TIMESTAMP within queries, this value cannot... more While "now " is expressed in SQL as CURRENT TIMESTAMP within queries, this value cannot be stored in the database. However, this notion of an ever-increasing current-time value has been reflected in some temporal data models by inclusion of database-resident variables, such as "now," "until-changed," "1," "@" and "--." Time variables are very desirable, but their use also leads to a new type of database, consisting of tuples with variables, termed a variable database. This paper proposes a framework for defining the semantics of the variable databases of the relational and temporal relational data models. A framework is presented because several reasonable meanings may be given to databases that use some of the specific temporal variables that have appeared in the literature. Using the framework, the paper defines a useful semantics for such databases. Because situations occur where the existing time variables are inadequat...
Encyclopedia of Database Systems
We present the TreeScape system that, unlike any other system known to the authors, enables the r... more We present the TreeScape system that, unlike any other system known to the authors, enables the reuse of pre-computed aggregate query results for irregular dimension hierarchies, which occur frequently in practice. The system establishes a foundation for obtaining high query processing performance while pre-computing only limited aggregates. The paper shows how this reuse of aggregates is enabled through dimension transformations that occur transparently to the user.