Zobrazeno 1 - 10
of 28 940
pro vyhledávání: '"Data Stream"'
Autor:
Julian M. Bopp, Tim Schröder
Publikováno v:
SoftwareX, Vol 28, Iss , Pp 101964- (2024)
Experiments in science and particularly quantum physics grow complex requiring sophisticated control software. Such software must provide a rigorous abstraction between hardware and measurement modules. Furthermore, it should provide networking funct
Externí odkaz:
https://doaj.org/article/3f878b0f24514e1183cb6a606a093fc2
Autor:
Afnan M. Alhassan
Publikováno v:
Ain Shams Engineering Journal, Vol 15, Iss 10, Pp 102955- (2024)
Histopathology image analysis is paramount importance for accurate diagnosing diseases and gaining insight into tissue properties. The significant challenge of staining variability continues. This research work presents a new method that merges deep
Externí odkaz:
https://doaj.org/article/e277de9d49834dc1a5909ff213175a57
Publikováno v:
IEEE Access, Vol 12, Pp 13795-13808 (2024)
Many applications and fields produce a vast quantity of time-relevant or continuously changing data which may represent new phenomena. This data stream behavior is known as Concept Drift. The need to efficiently and accurately process online data str
Externí odkaz:
https://doaj.org/article/5e02aa854ada45aa94f705d6f2edee1d
Publikováno v:
Big Data Mining and Analytics, Vol 7, Iss 1, Pp 87-106 (2024)
With the enhancement of data collection capabilities, massive streaming data have been accumulated in numerous application scenarios. Specifically, the issue of classifying data streams based on mobile sensors can be formalized as a multi-task multi-
Externí odkaz:
https://doaj.org/article/5d5c3b20a35f4a30bed8ebb0e25d998c
Publikováno v:
Journal of Cloud Computing: Advances, Systems and Applications, Vol 13, Iss 1, Pp 1-19 (2024)
Abstract The detection of different types of concept drift has wide applications in the fields of cloud computing and security information detection. Concept drift detection can indeed assist in promptly identifying instances where model performance
Externí odkaz:
https://doaj.org/article/3861bf675e2642b49bc2910ac268d0c6
Autor:
Mudathir Ahmed Mohamud, Hamidah Ibrahim, Fatimah Sidi, Siti Nurulain Mohd Rum, Zarina Binti Dzolkhifli, Zhang Xiaowei
Publikováno v:
IEEE Access, Vol 12, Pp 120877-120898 (2024)
The proliferation of high-dimensional data in many advanced database applications is a result of today’s technological advancements. These data points that correspond to objects are often without a precise description, which make their representati
Externí odkaz:
https://doaj.org/article/82a014deb80f49bb89d14c0416eebcd5
Autor:
Shinichi Yamagiwa, Taiki Kato
Publikováno v:
IEEE Access, Vol 12, Pp 98768-98786 (2024)
Data stream is a major data type in modern information equipment such as sensory and video/sound devices, which is fast and continuously generated without any stall cycle. Due to artificial intelligence becoming a common tool to extend application do
Externí odkaz:
https://doaj.org/article/1e3008539fa54c89adfea487bc3a1c46
Publikováno v:
IEEE Access, Vol 12, Pp 21129-21146 (2024)
As machine learning models are increasingly applied to real-world scenarios, it is essential to consider the possibility of changes in the data distribution over time. Concept drift detection and adaptation refers to the process of identifying and tr
Externí odkaz:
https://doaj.org/article/33e86f4fd1d847d38392d9a09747badd
Akademický článek
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Publikováno v:
Energy Informatics, Vol 6, Iss S1, Pp 1-20 (2023)
Abstract Information and communication technology (ICT) is an increasing part of modern power systems, which are, therefore, recognised as cyber-physical energy system (CPESs). The increase of ICT affects the situational awareness in CPESs, which is
Externí odkaz:
https://doaj.org/article/2ddd7edf76e74fc78c3ccef0dc5f2445