UMT Artificial Intelligence Review (UMT-AIR) provides a wide variety of perspectives on the theory and practices of work in the realm of AI. We welcome research papers on foundational and applied work, as well as case studies.
This journal is a dedicated effort to endure the rapid proclamation of the innovative work in the following areas or in combination;
- Applied Machine Learning
- Cognition and Computation behind AI systems
- Learning and Problem-Solving models
- Knowledge acquisition, representation, and decision making aspects
- Big data analytics
- Intelligent and smart expert systems
- Social and behavioral aspects of AI
This journal is intended to record and reflect on new and effective techniques of AI demonstrations in a variety of ways.
UMT-AIR also invites studies on critical analytical studies on AI applications, which present an in-depth evaluation of the AI tools and methods being employed.
Aims and Scope
UMT-AIR is targeted for inspiring studies on approaches that involve machine learning in a wide variety of perspectives. The journal is aimed to publish articles reporting from the review of foundational approaches to Data Science and Machine Learning to advanced applications in Commercial, Applications, Cognitive Sciences, Medical Practices, HealthCare, RealEstate, Finance, Government, Robots, or Space sciences.
These studies can be influenced by simple classification, regression, learning, decision making, reasoning approaches to complex and hybrid approaches employed in Information retrieval, Natural Language Processing, Vision and speech recognition, and analysis field. Innovative ideas with Reinforcement learning, Connectionist approaches, augmented reality, Game playing; Industrial, Financial, and Scientific applications of all kinds are highly welcome.
Submitted paper generally describes studies on using existing methods or solving novel problems by using existing methods and issues on improving research methodology in the context of Machine Learning are highly welcome.
However, all such kind of papers must place their contribution clearly with supporting evidence.
In addition, papers that make novel claims about problem-solving or applied techniques should provide clear support of data and materials and clear justification with proof of the limitation of the study's approach.
- No charges for manuscript submission, processing, or publication
- OJS as Journal Management System
- DOI of your articles
- QR code of your articles
- Open access
- Double-blind peer-review from three or more experts
- Proofreading, reference checking and formatting services
- Acceptance letter
- Complementary hard copy
- International circulation
- Submission in online repositories