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Now showing items 11-18 of 18
Impacts of Load and Generation Volatilities on the Voltage Profiles Improved by Distributed Energy Resources
(Institute of Electrical and Electronics Engineers Inc., 2020)
Weather-dependent distributed renewable energy sources such as photovoltaics (PVs) and wind turbines (WT) are increasingly being connected to distribution networks (DNs). Increased penetration of these intermittent sources ...
Voltage Profile Improving and Peak Shaving Using Multi-type Distributed Generators and Battery Energy Storage Systems in Distribution Networks
(Institute of Electrical and Electronics Engineers Inc., 2020)
Optimal sizing and siting of distributed generation (DG) units play an important role for improving voltage profile and reducing power losses. Moreover, battery energy storage system (BESS) units may help peak shaving. ...
Metadata Action Network Model for Cloud Based Development Environment
(Springer, 2020)
Cloud-based software development solutions (entitled as Platform-as-a-Service, Low-Code platforms) have been promoted as a game changing paradigm backed by model-driven architecture and supported by various cloud-based ...
A Sustainable Multi-Layered Open Data Processing Model For Agriculture: IoT Based Case Study Using Semantic Web For Hazelnut Fields
(ASTES Publishers, 2020)
In recent years, several projects which are supported by information and communications technologies (ICT) have been developed in the agricultural domain to promote more precise agricultural activities. These projects ...
Random CapsNet forest model for imbalanced malware type classification task
(Elsevier, 2021)
Behavior of malware varies depending the malware types, which affects the strategies of the system protection software. Many malware classification models, empowered by machine and/or deep learning, achieve superior ...
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 ...
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 ...