About the Journal
Focus and Scope
International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE) ISSN 2581-3242 is peer-reviewed, open access journal, registered with Crossref 10.30991/IJMLNCE. Each accepted manuscript shall be assigned a unique document object identifier. The abbreviated key title for our journal allocated by ISSN is Int. j. mach. learn. networked collab. eng. The journal appears in popular indexes like BASE (Bielefeld Academic Search Engine), CrossRef, CiteFactor, DRJI, Google Scholar, Index Copernicus, J-Gate, Portico, PKP-Index, ROAD, Scilit, Socolar.
International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE) ISSN 2581-3242 is a quarterly published, Open Access, peer-reviewed, international journal focuses on publishing authentic and unpublished quality research papers. This is a scientific journal which aims to promote quality and innovative research works, not limited to but focuses on the area of machine learning, collaborative engineering and allied areas. We publish original research articles, review articles and technical notes.
Authors are expected to ensure that their works are original and are required to declare that this work has not been published before in any conference, journal or Book Chapter. The submission should be only in Microsoft Word, Open Office or pdf Document format. Please click on the checkboxes provided in the Submission Requirement field for submitting a manuscript. The author can withdraw their paper dring getting a review-revision report or during review process.
Paper should be of comprise of minimum 250-300 words abstract along with 3500 words count minimum or 12-15 pages and submitted in standard journal template available here. Papers will be reviewed by the editorial board members on the basis of technical quality, originality, significance, clarity and scope of further research.
Papers should be submitted through online only. Decision about acceptance, revision or rejection of manuscript will be communicated to the corresponding authors’ e-mail only.
Accordingly, the journal welcomes contributions which investigate all aspects of machine learning’s and belongs to information technology and engineering domains from different disciplinary perspectives. Special focus is on new results in the following topics:
- Statistical Learning
- Neural Network Learning
- Learning Through Fuzzy Logic
- Learning Through Evolution (Evolutionary Algorithms)
- Reinforcement Learning
- Multi-Strategy Learning Cooperative Learning
- Planning And Learning
- Multi-Agent Learning
- Online And Incremental Learning
- Scalability Of Learning Algorithms
- Inductive Learning
- Inductive Logic Programming
- Bayesian Networks
- Support Vector Machines
- Case-Based Reasoning
- Machine Learning For Bioinformatics and Computational Biology
- Multi-Lingual Knowledge Acquisition And Representation
- Knowledge Acquisition And Learning
- Knowledge Discovery In Databases
- Knowledge Intensive Learning
- Knowledge Representation and Reasoning
- Machine Learning and Information Retrieval
- Machine Learning for Web Navigation And Mining
- Learning Through Mobile Data Mining
- Text and Multimedia Mining Through Machine Learning
- Distributed and Parallel Learning Algorithms and Applications
- Feature Extraction And Classification
- Theories and Models for Plausible Reasoning
- Computational Learning Theory
- Cognitive Modelling
- Hybrid Learning Algorithms
- Applications of Machine Learning In:
- Medicine, Health, Bioinformatics And Systems Biology
- Industrial and Engineering Applications
- Security Applications
- Smart Cities
- Game Playing and Problem Solving
- Intelligent Virtual Environments
Scientists and researchers are invited to submit papers in English that deal with research, development and design studies based on machine learning and artificial intelligence, experimental, theoretical or application-oriented in nature, as well as reviews relevant to the aforementioned topics.
Peer Review Process
International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE) ISSN 2581-3242 takes advantage of the efficiency and faster turnaround of the e-journal system, while maintaining the high standards of excellence that characterise traditional scientific journals. An integral part of this publication system is an unbiased, independent and critical peer review process.
After a submission has been uploaded, an editor of the journal examines whether a submission falls within the journal's subject area and complies with the formal guidelines of the journal.
First round of review
All original submissions that are suitable for inclusion undergo a rigorous single-blind peer review by two reviewers. External specialists or subject matter experts from the Editorial Board conduct peer review at the request of the assigned editor(s). Reviewers’ identities are concealed from the author.
Once a paper has entered the peer review process, the respective author is informed of the approximate date by which the managing editors will discuss and evaluate their manuscript as well as the date of possible publication. To facilitate timely publication, reviewers are asked to complete their reviews within one month.
Four types of reviewer recommendation are possible:
- Accept submission
- Likely accept, but minor revisions required
- Likely accept, but major revisions required
- Decline submission
Second round of review
In case a reviewer requests that an article be revised, the author has the opportunity to amend the article and resubmit it for a second review.
If minor revisions were required, the assigned editor(s) decides whether the amendments the author has made have taken into account all the points raised in the initial review.
If major revisions were needed, the revised version will be reevaluated by at least one of the reviewers. The review process, including possible resubmissions, may take up to three to four months.
Based on the reviewers' recommendations the assigned editor(s) finally approve or refuse contributions, and the author is informed of the decision and its reasons.
Reviewers for Technologies for Lightweight Structures must confirm:
- that all manuscripts are reviewed in fairness and honesty based on the intellectual content of the paper regardless of gender, race, ethnicity, religion, citizenry, political affiliation and values nor paradigmatic orientation of author(s);
- that any observed conflict of interest during the review process must be communicated to the managing editor. Such conflicts of interest can occur if the reviewer is asked to referee a paper written by a colleague of the same organization, former or current student, former advisor, frequent co-author, or closely-related person. If the conflict is severe, the reviewer should recuse himself/herself;
- that all information pertaining to the manuscript is treated as confidential, not to be disclosed to others prior to publication;
- that any information that may be the reason for the rejection of publication of a manuscript must be communicated to the managing editor.
- that deadlines agreed upon are met. Reviewers are kindly asked to complete their reviews within one month. If more time is needed, reviewers should contact the assigned editor(s) promptly.
Author fees: We are Un-Paid category journal, and do not charge any fee for article publication from the author.
Research misconduct case: Publishers and editors are very specific and serious to take reasonable steps to identify and prevent the publication of papers where research misconduct has occurred, including plagiarism, citation manipulation, and data falsification/fabrication, among others. We request authors and readers and researchers to communicate us in case they came to know any such information, so the corrective measures could be taken timely. It’s also plan to constitute at least 05 members team to take final decision about such case.
Conflicts of interest: Keeping in view of conflicts of interest, the manuscript assigned to the reviewers are blind in nature, also its keep in mind that the manuscript is communicated to at least two different countries reviewers, and also sometime in case they are not interested to review due to certain reasons, then its submitted to some other board members.
Access: The Journal is Open Access, and manuscripts are freely available through journal archive. Each articles are available to open access to readers and whether there are associated or not associated with us.
Archiving: A journal is working (under processing) for electronic backup and preservation of access to the journal content (for example, access to main articles via CLOCKSS in the event a journal is no longer published shall be clearly indicated.
International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE) ISSN 2581-3242 is published quarterly in the month of January, April, July, October.
Open Access Policy
Utilizing the potential of Open Access, the journal employs a system of rapid publication. To this end, each individual accepted article is made available in an “open issue” as soon as it is ready for publication, often weeks or months before the issue is complete. When all articles for that issue are published, the issue is closed and a new open issue is started. This guarantees that the visibility and impact of authors' contribution are accelerated.
Manuscript Copyright: Copyright and licensing information is clearly described on the journal’s Web site as well as it must be abide by author while uploading the manuscript.
International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE) ISSN 2581-3242 is an open-access journal. It provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. All content is published under a Creative Commons Licence “Attribution 4.0 International (CC BY 4.0)”.
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Call for Paper : for Vol 2, Issue No 04
Important Date : For Volume 2, No 4
Call for Paper last date : September 10, 2018
First Round Review : October 10, 2018
Second Round Review : November 25, 2018
Final Communication : December 10, 2018
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International Journal of Machine Learning and Networked Collaborative Engineering
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