International conference
on
Artificial intElligence
&
Machine learning
(ICAIML)
Exploring the Impact, Advancement, Techniques and Applications
2020
04-05 September
Call for Papers
Authors are invited to submit their original, unpublished and quality research papers (full length manuscripts, not a review or survey paper) in the All subareas of AI and machine learning but not limited to:
- Modeling, Algorithms and Simulations
- Intelligent Electrical and Electronic Systems
- Problem Solving
- Scientific Computing
- Computational Sciences (Biology, Chemistry, mathematics, physics, forensics, etc.)
- High Performance Computing
- Network Analysis
- Computer Architecture
- Visualization and Virtual Reality as Applied to Computational Science
- Architectures and computation models, compiler, hardware and OS issues
- Large Scale Scientific Instruments
- Memory system, I/O, tools, programming environment and language supports
- Application-specific processors and devices
- Business Applications
- Component and binding models
- Embedded computing education
- Embedded hardware support
- Embedded software
- Embedded system architecture
- Hardware and software co-design
- Industrial practices and benchmark suites
- Integration with business logic
- Integration with SOA
- Middleware
- Networked Embedded Systems
- Policy-based management
- Programming abstractions
- Real-time systems
- Recent Trends
- Service-Oriented architectures
- Testing techniques
- Intelligent and Interactive Technologies in an Educational Context
- Data Mining and Machine Learning
- Semantic Web Technologies
- Multi-agent Architectures
- Tangible Interfaces, Wearables and Augmented Reality
- Modelling and Representation
- Ontological Modelling
- Modelling Motivation, Metacognition, and Affective Aspects of Learning
- Computational Thinking and Model-building
- Models of Teaching and Learning
- Design and formative studies of AIED system
- Intelligent Tutoring and Scaffolding
- Domain-specific Learning Applications
- Artificial Intelligence
- AI Algorithms
- Artificial Intelligence Tools & Applications
- Automatic Control
- Bioinformatics
- Natural Language Processing
- CAD Design & Testing
- Data Mining and Machine Learning Tools
- Fuzzy Logic
- Heuristic and AI Planning Strategies and Tools
- Computational Theories of Learning
- Hybrid Intelligent Systems
- Information Retrieval
- Intelligent System Architectures
- Knowledge Representation
- Knowledge-based Systems
- Mechatronics
- Multimedia & Cognitive Informatics
- Neural Networks
- Parallel Processing
- Pattern Recognition
- Pervasive Computing and Ambient Intelligence
- Programming Languages
- Reasoning and Evolution
- Recent Trends and Developments
- Robotics
- Soft Computing and Applications
- Fuzzy Systems
- Neural Networks
- Machine Learning
- Probabilistic Reasoning
- Evolutionary Computing
- Pattern Recognition
- Hybrid Intelligent Systems
- Software Agents
- Morphic Computing
- Image Processing
- E-commerce, E-medicine
- Rough Sets
- Symbolic Machine Learning
- Wavelet
- Signal or Image Processing
- Vision Recognition
- Biomedical Engineering
- Telecommunications
- Reactive Distributed AI
- Nano & Micro-systems
- Data Visualization
- Semantic Web Techniques and Technologies
- Soft Computing Theory and Applications
- Software & Hardware Architectures
- Web Intelligence Applications & Search
- Techniques & Methods
- Applications
Plagiarism Policy
The paper prior to submission should be checked for plagiarism from licensed plagiarism softwares like Turnitin/ iThenticate etc. The similarity content should not exceed 10% (in any case either self contents or others). Further, you have to strictly implement the following ethical guidelines for publication:
- Any form of self-plagiarism or plagiarism from others' work(s) should not be there in an article.
- If any model / concept / figure / table / data / conclusive comment by any previously published work is used in your article, you should properly cite a reference to the original work.
- Also language of explaining it should not be same as language of the work from which you have adopted it.
- If you are using any copyrighted material, you should acquire prior permission from the copyright holder.
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