Results 11 to 20 of about 31,142 (265)
Simulation data as data streams [PDF]
ACM SIGMOD Record, 2004 Computational or scientific simulations are increasingly being applied to solve a variety of scientific problems. Domains such as astrophysics, engineering, chemistry, biology, and environmental studies are benefiting from this important capability. Simulations, however, produce enormous amounts of data that need to be analyzed and understood.
Abdulla, G., Arrighi, W., Critchlow, T.
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Real-Time UAV Trash Monitoring System
Applied Sciences, 2022 This study proposes a marine trash detection system based on unmanned aerial vehicles (UAVs) and aims to replace manpower with UAVs to detect marine trash efficiently and provide information to government agencies regarding real-time trash pollution ...
Yu-Hsien Liao, Jih-Gau Juang
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Complexity, 2020 In this paper, we investigate a class of nonautonomous fractional diffusion equations (NFDEs). Firstly, under the condition of weighted Hölder continuity, the existence and two estimates of classical solutions are obtained by virtue of the properties of ...
Jia Mu, Yang Liu, Huanhuan Zhang
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Incremental Entity Blocking over Heterogeneous Streaming Data
Information, 2022 Web systems have become a valuable source of semi-structured and streaming data. In this sense, Entity Resolution (ER) has become a key solution for integrating multiple data sources or identifying similarities between data items, namely entities.
Tiago Brasileiro Araújo +4 more
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Complexity, 2020 In this paper, a generalized Gronwall inequality is demonstrated, playing an important role in the study of fractional differential equations. In addition, with the fixed-point theorem and the properties of Mittag–Leffler functions, some results of the ...
Jia Mu, Jiecuo Nan, Yong Zhou
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Multi-View Data Analysis Techniques for Monitoring Smart Building Systems
Sensors, 2021 In smart buildings, many different systems work in coordination to accomplish their tasks. In this process, the sensors associated with these systems collect large amounts of data generated in a streaming fashion, which is prone to concept drift.
Vishnu Manasa Devagiri +4 more
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Correlation Clustering in Data Streams [PDF]
Algorithmica, 2021 AbstractClustering is a fundamental tool for analyzing large data sets. A rich body of work has been devoted to designing data-stream algorithms for the relevant optimization problems such as k-center, k-median, and k-means. Such algorithms need to be both time and and space efficient.
Ahn, KJ +4 more
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Parameterized streaming : maximal matching and vertex cover [PDF]
, 2014 As graphs continue to grow in size, we seek ways to effectively process such data at scale. The model of streaming graph processing, in which a compact summary is maintained as each edge insertion/deletion is observed, is an attractive one.
Chitnis, Rajesh; id_orcid +11 more
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A Fully Streaming Big Data Framework for Cyber Security Based on Optimized Deep Learning Algorithm
IEEE Access, 2023 Real-time deep learning faces the challenge of balancing accuracy and time, especially in cybersecurity where intrusion detection is crucial. Traditional deep learning techniques have been insufficient in identifying network anomalies and intrusions.
Noha Hussen +3 more
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2011 Data Compression Conference, 2011 We present a general-purpose, loss less compressor for streaming data. This compressor is based on the deplump probabilistic compressor for batch data. Approximations to the inference procedure used in the probabilistic model underpinning deplump are introduced that yield the computational asyptotics necessary for stream compression. We demonstrate the
Bartlett, N, Wood, F
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