About the Journal

The Distributed Learning and Broad Applications in Scientific Research (DLBASR) is a peer-reviewed, open-access journal focused on disseminating original research articles, reviews, and short communications in the field of distributed learning and its diverse applications across scientific research. DLBASR encourages submissions from researchers worldwide, fostering a variety of perspectives and innovative methodologies.

Journal Snapshot

Journal Name: Distributed Learning and Broad Applications in Scientific Research (DLBASR)
ISSN: 2458-1234
Impact Factor: 5.2 (By ResearchBib)
Journal Initials: DLBASR
Research Scope: Distributed Learning, Machine Learning, Data Mining, Big Data Analytics, Computational Biology, Environmental Modeling, Scientific Simulations, AI Applications in Science
Publication Mode: Digital (On this Website)
Frequency: Annual (1 Volume a year)
Launch Year: 2015
Review Mode: Double Blind Peer Review
Plagiarism Allowed: 10% (as per Turnitin)
Coverage: Worldwide
Language: English

Current Issue

Vol. 10 (2024): Distributed Learning and Broad Applications in Scientific Research
View Vol. 10 (2024): Distributed Learning and Broad Applications in Scientific Research

In this issue of Distributed Learning and Broad Applications in Scientific Research, we present a collection of innovative studies showcasing the latest advancements in distributed learning technologies and their applications across various scientific fields. Featured themes include cutting-edge machine learning algorithms, deep learning frameworks, and artificial intelligence techniques applied to areas such as computational biology, environmental modeling, and materials science.

This volume also offers insightful reviews on current trends and future directions in distributed learning, along with case studies demonstrating real-world impacts. Contributions from global experts and emerging scholars highlight the journal's commitment to fostering interdisciplinary collaboration and driving innovation in scientific research.

Explore these groundbreaking developments and stay at the forefront of distributed learning's potential to revolutionize science.

Published: 01-01-2024

Articles

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