About the Journal

American Data Science Journal for Advanced Computations (ADSJAC)

ISSN: 3067-4166

What is ADSJAC?

The American Data Science Journal for Advanced Computations (ADSJAC) is a peer-reviewed, open-access scholarly journal dedicated to publishing high-quality research in data science, computational intelligence, and advanced computational methods. The journal provides a platform for researchers, practitioners, and academicians to share innovative findings, theoretical advancements, and real-world applications that contribute to the evolving landscape of data-driven science and high-performance computation.

ADSJAC is committed to advancing global research by ensuring free and permanent access to knowledge, fostering collaboration, and promoting excellence in scientific discovery across diverse computational fields.

Open Access & Publication Model

ADSJAC operates under a full open-access model. All published articles are freely available to the public without subscription or access restrictions.

To support sustainable publishing practices—including editorial management, peer review, production, and digital archiving—publication fees are collected only after a manuscript has been accepted following rigorous review.

The open-access approach ensures:

• Worldwide visibility and accessibility

• Greater readership and citation potential

• Rapid dissemination of scholarly work

Editorial & Peer-Review Ethics

ADSJAC upholds the highest editorial and ethical standards in scholarly publishing. Submitted manuscripts must:

• Be original and unpublished

• Not under consideration in another journal

• Follow ethical guidelines for research involving data, models, experiments, or human/AI-generated content

Peer-Review Process

1. Initial Editorial Screening
   Manuscripts are assessed for relevance, academic quality, originality, and compliance with journal requirements.

2. Double-Blind Peer Review
   Qualified reviewers evaluate submitted work without knowledge of author identities, ensuring fairness, impartiality, and scholarly rigor.

3. Final Decision
   Acceptance is based on scientific merit, methodological soundness, clarity, and contribution to the computational sciences.

ADSJAC follows strict policies for handling:

• Plagiarism

• Data manipulation or fabrication

• Ethical breaches

• Conflicts of interest

• Authorship disputes

Preservation & Archiving

ADSJAC maintains a long-term digital archiving policy to ensure the permanent preservation and accessibility of all published articles. This includes:

• Secure digital repositories

• Redundant backups

• Maintenance of accessible formats for future use

These measures ensure the integrity of the scientific record and uninterrupted access for researchers worldwide.

Retraction & Correction Policy

To uphold transparency and scholarly accuracy, ADSJAC may issue:

Corrections

Published when minor issues arise that do not compromise scientific validity.

Expressions of Concern

Issued when potential issues require further investigation.

Retractions

Applied in cases involving:

• Proven research misconduct

• Serious methodological flaws

• Ethical violations

• Duplicate or fraudulent data

All decisions follow internationally recognized publishing ethics standards.

Privacy & Data Handling Policy

ADSJAC respects the confidentiality of authors, reviewers, and users. Personal information collected during submission and peer-review processes is:

• Stored securely

• Used only for editorial and administrative purposes

• Accessible exclusively to authorized personnel

Authors may request updates or removal of their personal data at any time.

Contact Information

For submission support, editorial communication, or journal-related inquiries:

Email: editor@adsjac.com

The editorial office is available to assist authors and contributors throughout the submission and publication process.

Scope of ADSJAC

The American Data Science Journal for Advanced Computations (ADSJAC) publishes original research articles, review papers, short communications, technical reports, and case studies in the fields of data science, computational intelligence, and advanced computational systems.

Key Areas of Interest

Data Science & Analytics

• Data Mining

• Statistical Modeling

• Predictive and Prescriptive Analytics

• Big Data Algorithms

• Data Visualization and Interpretability

Machine Learning & Artificial Intelligence

• Deep Learning and Neural Networks

• Reinforcement Learning

• Natural Language Processing

• Computer Vision

• Explainable and Responsible AI

Advanced Computation & Algorithms

• High-Performance Computing

• Distributed and Cloud-Based Computation

• Optimization Algorithms

• Scientific and Numerical Computing

• Computational Mathematics

Emerging Computational Technologies

• Quantum Computing Methods

• Edge and Fog Computing

• Internet of Things (IoT) Intelligence

• Autonomous Intelligent Systems

Applications of Data Science & Computation

• Healthcare Data Analytics

• Financial and Business Intelligence

• Environmental and Climate Modeling

• Cybersecurity Analytics

• Smart Cities and Industrial Automation

ADSJAC encourages interdisciplinary research integrating data science with engineering, mathematics, computational biology, social sciences, and real-world applications that rely heavily on advanced computation and intelligent algorithms.