Zobrazeno 1 - 10
of 2 869
pro vyhledávání: '"Log data"'
Autor:
ZHAO Haitao, LI Hongye
Publikováno v:
Zhihui kongzhi yu fangzhen, Vol 46, Iss 5, Pp 114-118 (2024)
In order to efficiently and correctly identify abnormal behaviors in Linux logs, this paper proposes a Linux log anomaly detection method based on the improved isolated forest algorithm. The method introduces an attention mechanism on the basis of th
Externí odkaz:
https://doaj.org/article/fc13f085d08c44539cf86e36e6361817
Publikováno v:
Frontiers in Education, Vol 9 (2024)
Assessing self-regulated learning (SRL)—the interplay between monitoring and control behavior—remains challenging, particularly in young learners. The unobtrusive assessment with log data to investigate SRL offers a promising method to deepen the
Externí odkaz:
https://doaj.org/article/2c80de87781043d499a3facc679457d5
Publikováno v:
Georesursy, Vol 25, Iss 4, Pp 176-191 (2024)
The article presents the results of studying four sections of the Bazhenov Formation and the overlying sediments in the central part of the Mansi syneclise, which are based on a comprehensive analysis of the results laboratory lithological and geoche
Externí odkaz:
https://doaj.org/article/cd03189452b54c27861f1942879752a3
Autor:
T. G. Isakova, A. S. Persidskaya, O. V. Khotylev, J. A. Kotochkova, A. D. Egorova, T. F. Dyakonova, A. S. Mozgovoy, V. V. Churkina, S. V. Kozakov, N. V. Kozhevnikova, R. Z. Livaev, V. S. Druchin, N. V. Belov, G. A. Kalmykov
Publikováno v:
Georesursy, Vol 24, Iss 2, Pp 172-185 (2024)
The article considers facies analysis and the application of its results for the typification of rocks of the Tyumen Formation. The aim of the article is to create algorithms for the differentiated interpretation of geophysical studies of well log da
Externí odkaz:
https://doaj.org/article/acc595cafb3b45db8467ca6e3827fe14
Autor:
Lotte Firet, Theodora Alberta Maria Teunissen, Rudolf Bertijn Kool, Reinier Peter Akkermans, Antoinette Leonarda Maria Lagro-Janssen, Huub van der Vaart, Willem Jan Jozef Assendelft
Publikováno v:
BMC Primary Care, Vol 25, Iss 1, Pp 1-13 (2024)
Abstract Background Stress urinary incontinence (SUI), though a prevalent condition among women, is undertreated in primary care. EHealth with pelvic floor muscle training is an evidence-based alternative to care-as-usual. It is unknown, however, how
Externí odkaz:
https://doaj.org/article/37e02de951cf43959950bb4c6c4d9869
Publikováno v:
Artificial Intelligence in Geosciences, Vol 5, Iss , Pp 100072- (2024)
Recently, machine learning (ML) has been considered a powerful technological element of different society areas. To transform the computer into a decision maker, several sophisticated methods and algorithms are constantly created and analyzed. In geo
Externí odkaz:
https://doaj.org/article/efb8a8bce86c4de586035e6b38cb52ae
Autor:
Áttila Leães Rodrigues, Fernanda Gontijo Fernandes Niquini, Sandro Pinzon, João Felipe Coimbra Leite Costa
Publikováno v:
REM: International Engineering Journal, Vol 77, Iss 3 (2024)
Abstract In the past decade, machine learning techniques were responsible for a revolution in classification and regression tasks, making it possible to automate some laborious activities, saving time and reducing errors. It is known that the geologi
Externí odkaz:
https://doaj.org/article/2573d668691f4b0e898fbd50058aaa0a
Publikováno v:
Frontiers in Veterinary Science, Vol 11 (2024)
IntroductionThis study investigates the log data and response behavior from invigilated in-person electronic timed exams at the University of Veterinary Medicine Hannover, Foundation, Germany. The primary focus is on understanding how various factors
Externí odkaz:
https://doaj.org/article/1e3e737aef544362997bfe3c9877f411
Publikováno v:
Smart Learning Environments, Vol 10, Iss 1, Pp 1-19 (2023)
Abstract In inclusive education, students with different needs learn in the same context. With the advancement of artificial intelligence (AI) technologies, it is expected that they will contribute further to an inclusive learning environment that me
Externí odkaz:
https://doaj.org/article/6fa3eff8ee8a4b25b3063f1802975ea4
Publikováno v:
BMC Digital Health, Vol 1, Iss 1, Pp 1-10 (2023)
Abstract Background Engagement with smartphone-based interventions stimulates adherence and improves the likelihood of gaining benefits from intervention content. Research often relies on system usage data to capture engagement. However, to what exte
Externí odkaz:
https://doaj.org/article/8f365029d77743f399766185205dbd2d