Journal Name: Distributed Learning and Broad Applications in Scientific Research (DLBASR)
ISSN: 2458-1232
Impact Factor: 7.2 (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
About the Journal
Distributed Learning and Broad Applications in Scientific Research is a premier journal dedicated to the dissemination of cutting-edge research and advancements in the field of distributed learning and its diverse applications across various scientific disciplines. This journal serves as a comprehensive platform for researchers, educators, and practitioners to explore the integration of distributed learning methodologies with scientific research, fostering innovation and collaboration.
The journal covers a wide range of topics, including but not limited to, machine learning, deep learning, artificial intelligence, and their implementation in fields such as biology, chemistry, physics, engineering, and environmental science. By publishing original research articles, review papers, and case studies, the journal aims to highlight the transformative impact of distributed learning technologies on scientific inquiry and problem-solving.
With contributions from leading experts and scholars worldwide, Distributed Learning and Broad Applications in Scientific Research strives to bridge the gap between theoretical developments and practical applications, promoting interdisciplinary approaches and novel solutions to complex scientific challenges. The journal is committed to advancing knowledge, supporting academic excellence, and driving progress in the ever-evolving landscape of scientific research.