Aims and Scope
The journal's authorship is therefore not restricted to any discipline, but it is restricted in terms of quality and subject matter-articles are accepted based on merit, and their focus on the intersection of human activity (at whatever level of analysis) and social systems (at whatever level of analysis). The editors emphasize that cross-cultural, comparative, mixed-methods research is especially encouraged, and discourage submission of single-country case studies and/or studies that rely only on one method in isolation. Authors of single-country studies, if submitted, must demonstrate that they have situated their study in the broader context and have highlighted the significance of their study. In addition, studies that utilize primarily artificial intelligence methods and models focus on the data science side of its use and clearly meet the aims and scope of the journal.
MJAIAS welcomes papers on, but are not limited to the topics as below.
Artificial Intelligence and Machine Learning
- Machine Learning
- Deep Learning and Applications
- Natural language processing
- Decision support systems
- Pattern Recognition
- Knowledge discovery
- Intelligent agents
- Intelligent information systems
- Intelligent web-based business
- AI and evolutionary algorithms
- Neural networks and applications
- Integration of AI with other technologies
- Reinforcement learning
- Generative Models
- Computational Intelligence
- Distributed AI algorithms and techniques
- Constraint-based reasoning and constraint programming
Computer Vision and Image Processing
- Document Analysis
- Radar Signal Processing
- Audio/Speech Processing and Coding
- Biometrics and Pattern Recognition
- Cognitive and Biologically-Inspired Vision
- Content-based image retrieval
- Remote Sensing
- Point Cloud Data Processing
- Face and Gesture Recognition
- Medical Image Processing
- Image and Video Retrieval
- Motion and Tracking Stereo and Structure from Motion
- Object Detection, Recognition, and Categorization
- Image Restoration
- Statistic Learning and Pattern Recognition
- Speech, Audio, and Music Processing
Big Data and IoT
- Distributed Computing
- Cloud Computing
- Big Data Analysis
- Parallel and Distributed Computing
- Big Data Models and Algorithms
- Big Data Architectures and Management
- Big Data in Smart Cities
- Big Data Technologies, Services, and Applications
- 3D printing
- Architecture for secure and interactive IoT
- Future of IoT and Big Data
- Internet of Things
- Smart City Examples and Case Studies
- Technological focus for Smart Environments
- Vehicle-to-Vehicle
- Vehicle-to-Infrastructure