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An Integrated Framework for Examining Innovation Alignment in Organizations
(World Scientific Publ Co Pte Ltd, 2018)
Innovation has been promoted as a panacea to solve the long-standing problem of how organizations deal with complexities associated with uncertainty and instability in ever changing environments. information systems (IS) ...
Semantic and syntactic interoperability for agricultural open-data platforms in the context of IoT using crop-specific trait ontologies
(MDPI AG, 2020)
In recent years, Internet-of-Things (IoT)-based applications have been used in various domains such as health, industry and agriculture. Considerable amounts of data in diverse formats are collected from wireless sensor ...
Analysis of the Patients and Physicians Connection Network on an online Health Information Platform
(IOS Press, 2014)
Social network applications have gained popularity in the health domain as they bring health information seekers (patients and alike) and medication advice providers (physicians and other relevant actors) together. By ...
A Hybrid Deep Learning Framework for Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data
(Mdpi, 2020)
Multivariate time-series data with a contextual spatial attribute have extensive use for finding anomalous patterns in a wide variety of application domains such as earth science, hurricane tracking, fraud, and disease ...
Adoption of Mobile Health Apps in Dietetic Practice: Case Study of Diyetkolik
(Jmır Publıcatıons, Inc, 130 Queens Quay E, 2020)
Background: Dietetics mobile health apps provide lifestyle tracking and support on demand. Mobile health has become a new trend for health service providers through which they have been shifting their services from clinical ...
An Integrated Framework for Examining Innovation Alignment in Organizations
(World Scientific Publ Co Pte Ltd, 2019)
Innovation has been promoted as a panacea to solve the long-standing problem of how organizations deal with complexities associated with uncertainty and instability in ever changing environments. information systems (IS) ...
A hybrid deep learning framework for unsupervised anomaly detection in multivariate spatio-temporal data
(MDPI AG, 2020)
Multivariate time-series data with a contextual spatial attribute have extensive use for finding anomalous patterns in a wide variety of application domains such as earth science, hurricane tracking, fraud, and disease ...
Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of COVID-19 Outbreak in Italy
(Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2020)
Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection. Most real-world time series data ...