Results 11 to 20 of about 82,044 (253)
A New Extreme Detection Method for Remote Compound Extremes in Southeast China
The compound heat wave and extreme precipitation events are responsible for severe damages to the environment and human societies. Although major advances have been made in understanding the compound extremes (e.g., drought and heat wave), little is ...
Luqing Wang +6 more
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Effects of forest fragmentation on amazonian understory bird communities [PDF]
SUMMARYData form an intensive mist-netting mark-recapture program in the central Amazon demostrate significant changes in the undesrtory avian community in isolate patches of 1 and 10 ha of terra firme forest.
Richard O. Bierregaard Jr +1 more
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Efficient Driver Drunk Detection by Sensors: A Manifold Learning-Based Anomaly Detector
This study presents an effective data-driven anomaly detection scheme for drunk driving detection. Specifically, the proposed anomaly detection approach amalgamates the desirable features of the t-distributed stochastic neighbor embedding (t-SNE) as a ...
Abdelkader Dairi, Fouzi Harrou, Ying Sun
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Integration of Machine Learning Solutions in the Building Automation System
This publication presents a system for integrating machine learning and artificial intelligence solutions with building automation systems. The platform is based on cloud solutions and can integrate with one of the most popular virtual building ...
Bartlomiej Kawa, Piotr Borkowski
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Hyperspectral Anomaly Detection via Optimal Kernel and High-Order Moment Correlation Representation
Hyperspectral anomaly detection has been a hot topic in the field of remote sensing due to its potential application prospects. However, anomaly detection still has two typical problems to be solved.
Zhuang Li, Ye Zhang, Junping Zhang
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Intrusion Detection Based on Autoencoder and Isolation Forest in Fog Computing
Fog Computing has emerged as an extension to cloud computing by providing an efficient infrastructure to support IoT. Fog computing acting as a mediator provides local processing of the end-users' requests and reduced delays in communication between the ...
Kishwar Sadaf, Jabeen Sultana
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Anomaly Prediction in Electricity Consumption Using a Combination of Machine Learning Techniques
Electricity demand is increasing proportionally to the increase in power usage. Without a doubt, energy efficiency has gained significant importance and attention, with one of the primary concerns being the detection and forecasting of abnormal ...
Rawan ELhadad +2 more
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For the purpose of monitoring the behavior of complex infrastructures (e.g. aircrafts, transport or energy networks), high-rate sensors are deployed to capture multivariate data, generally unlabeled, in quasi continuous-time to detect quickly the occurrence of anomalies that may jeopardize the smooth operation of the system of interest. The statistical
Guillaume Staerman +3 more
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Magnetic Anomaly Detection Method Based on Feature Fusion and Isolation Forest Algorithm
In order to improve the weak magnetic detection ability under the background of Gaussian colored magnetic environment noise, a magnetic anomaly detection method based on feature fusion and isolation forest (IForest) algorithm is proposed in this paper ...
Ning Zhang +5 more
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