COMPUTING AND INFORMATICS
Scope & Guideline
Innovating Through Open Access Research
Introduction
Aims and Scopes
- Artificial Intelligence and Machine Learning:
The journal emphasizes research in artificial intelligence (AI) and machine learning (ML), exploring their applications across diverse fields such as healthcare, agriculture, and robotics. It includes studies on predictive modeling, classification methods, and innovative algorithms. - Data Science and Big Data Analytics:
Research in data science, particularly in big data analytics, is a significant focus area. This includes methodologies for data processing, feature selection, and the application of statistical methods to extract insights from large datasets. - Computer Vision and Image Processing:
The journal covers advancements in computer vision and image processing, with studies on image classification, restoration, and analysis techniques, often leveraging deep learning methodologies. - Network and Security Technologies:
Research related to networking, cloud computing, and security is prominent, including studies on privacy, data fusion, and secure communications in various applications. - Robotics and Automation:
The journal includes research on robotics, particularly in navigation, path planning, and mobile robotics, contributing to advancements in autonomous systems. - Human-Computer Interaction and User Experience:
Explorations in user experience, particularly in educational or interactive systems, are also featured, focusing on enhancing user engagement through technology.
Trending and Emerging
- Deep Learning and Neural Networks:
There is a growing emphasis on deep learning techniques, particularly in applications related to image and signal processing, indicating a trend towards leveraging advanced neural network architectures for complex problem-solving. - AI in Healthcare:
Research exploring the application of AI in healthcare, such as disease prediction and medical imaging, is on the rise, reflecting the increasing integration of technology in health diagnostics and patient care. - Sustainable Computing and Green Technologies:
Emerging themes around sustainability in computing, including energy-efficient algorithms and eco-friendly technologies, are becoming increasingly relevant as the industry shifts towards addressing climate change. - Privacy and Security in Cloud Computing:
With the rise of cloud technologies, there is an emerging focus on privacy and security challenges, including innovative architectures and solutions aimed at safeguarding sensitive data in cloud environments. - Data-driven Decision Making:
The trend towards data-driven decision making is evident, with research focusing on predictive analytics and machine learning models that support strategic decision-making across various industries.
Declining or Waning
- Traditional Software Engineering Practices:
There has been a noticeable decrease in publications focused on traditional software engineering methodologies, such as formal methods and classic software development life cycle models, possibly due to the shift towards agile and DevOps practices. - Basic Network Protocols and Architectures:
Research on fundamental network protocols and architectures has diminished, as the field has evolved towards more complex networking solutions, such as software-defined networking and IoT frameworks. - Static Data Analysis:
Static analysis techniques for data have become less prevalent, likely overshadowed by the rise of dynamic and real-time data processing methodologies that cater to big data and streaming analytics. - Legacy System Integration:
There is a waning interest in the integration of legacy systems, as organizations increasingly focus on modernization and cloud migration strategies, leaving less room for traditional integration studies.
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