Submissions

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Author Guidelines

Authors are invited to make a submission to this journal. All submissions will be assessed by an editor to determine whether they meet the aims and scope of this journal. Those considered to be a good fit will be sent for peer review before determining whether they will be accepted or rejected.

Before making a submission, authors are responsible for obtaining permission to publish any material included with the submission, such as photos, documents and datasets. All authors identified on the submission must consent to be identified as an author. Where appropriate, research should be approved by an appropriate ethics committee in accordance with the legal requirements of the study's country.

An editor may desk reject a submission if it does not meet minimum standards of quality. Before submitting, please ensure that the study design and research argument are structured and articulated properly. The title should be concise and the abstract should be able to stand on its own. This will increase the likelihood of reviewers agreeing to review the paper. When you're satisfied that your submission meets this standard, please follow the checklist below to prepare your submission.

Submission Preparation Checklist

All submissions must meet the following requirements.

  • This submission meets the requirements outlined in the Author Guidelines.
  • This submission has not been previously published, nor is it before another journal for consideration.
  • All references have been checked for accuracy and completeness.
  • All tables and figures have been numbered and labeled.
  • Permission has been obtained to publish all photos, datasets and other material provided with this submission.

Research Articles

Research Articles are full-length, peer-reviewed manuscripts that present original, unpublished findings with significant contributions to the field of artificial intelligence and digital technologies. These articles must be based on sound theoretical frameworks, robust methodologies, and rigorous experimentation or modeling.

A strong research article clearly articulates its objectives, provides a comprehensive review of related work, explains the methodology in detail, and presents reproducible results supported by statistical or computational analysis. Authors must discuss how their work advances the current state of knowledge and its relevance to real-world applications or future research directions.

Examples: novel deep learning model, a new algorithm for anomaly detection, or an AI-based diagnostic system

Review Articles

Review Articles provide comprehensive, critical, and structured overviews of existing literature on specific topics within artificial intelligence, data science, and digital systems. These papers summarize recent developments, identify research gaps, discuss key challenges, and highlight emerging trends.

Review Articles should be written by authors with deep expertise in the subject matter and should offer a balanced, well-organized analysis that benefits both researchers and practitioners. These articles are especially valuable for early-stage researchers looking to understand a specific domain.

Examples: A review of explainable AI (XAI), survey on federated learning, comparative analysis of deep learning frameworks, etc.

Short Communications

Short Communications are concise research reports that present preliminary findings, innovative ideas, or rapid insights into current developments in AI and digital technology. These articles are shorter than full-length research papers but must still meet high academic standards and demonstrate scientific merit.

Ideal for pilot experiments, novel observations, prototype systems, or time-sensitive innovations, these contributions are reviewed quickly and are often used to share promising ideas with the community before complete validation.

Must include a brief introduction, methods, results, and a clear conclusion

Technical Notes

Technical Notes describe new technical methods, system architectures, algorithmic implementations, datasets, or software tools that can support research or application in AI, machine learning, and digital technologies. The focus is on clarity, reproducibility, and practical utility rather than experimental results.

These papers are ideal for reporting optimized code, unique system integrations, sensor configurations, software libraries, or detailed tutorials of frameworks used in computational intelligence.

These articles are often of interest to developers, engineers, and applied researchers.
May include code repositories, system diagrams, or configuration files.

Data Papers

Data Papers provide detailed descriptions of valuable datasets that have been collected, curated, and made available for use by the research community. These papers do not analyze the data directly but focus on describing its structure, acquisition process, quality assurance, and potential applications.

Each data paper must link to a permanent online repository (e.g., Zenodo, Kaggle, GitHub) where the dataset is freely accessible under an open license. Authors are encouraged to explain how the dataset can be reused, reproduced, or integrated into future AI applications.

A Data Paper must include metadata structure, formats, accessibility method, and example use cases.
Must include DOI or persistent identifier for the dataset.

Perspective

Perspective or Viewpoint Articles are scholarly essays that provide critical, forward-looking reflections on emerging trends, ethical challenges, theoretical debates, or the societal impact of artificial intelligence and digital technologies. These articles do not present original experimental results but rather offer expert commentary and conceptual insights.

Such articles are typically written by established researchers, policymakers, or industry leaders and are meant to stimulate discussion, propose new frameworks, or identify underexplored areas of research. They may take a reflective, speculative, or even provocative tone, as long as arguments are grounded in evidence or logic.

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