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Now showing items 31-36 of 36
Using Random Forest Tree Classification for Evaluating Vertical Cross-Sections in Epoxy Blocks to Get Unbiased Estimates for 3D Mineral Map
(Gazi University, 2021)
Areal mineral maps are constructed from the polished sections of particles that settle to the bottom of epoxy resin. However, heavy minerals can preferentially settle to the bottom, making the polished surface rich in heavy ...
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 ...
An inverse coefficient problem for a quasilinear parabolic equation with nonlocal boundary conditions
(Springer International Publishing Ag, 2013)
In this paper the inverse problem of finding the time-dependent coefficient of heat capacity together with the nonlocal boundary conditions is considered. Under some natural regularity and consistency conditions on the ...
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 ...