Announcements

We are pleased to announce that the website of the MDPI Sustainability Foundation has been revamped! For the past couple of months, our UX UI team and front-end developers have been working hard to launch the website in time for the opening of the Sustainability Awards nominations.

The website is not the only thing that has had a remodeling. Indeed, the format of the Emerging Sustainability Leader Award (ESLA) has been updated. ESLA is now a competition open to individual researchers or start-ups founded by researchers under the age of 35. Nominee applications will go through 2 rounds of selection until the final 3 are decided. The finalists will then be invited to give pitch presentations during the Award Ceremony to win either first place (10,000 USD) or runner-up (2 x 5000 USD).

The World Sustainability Award, on the other hand, remains the same: a total prize money of 100,000 USD is up for grabs by senior individual researchers or groups of researchers from the international research community.

Nominations for both the World Sustainability Award and the Emerging Sustainability Leader award are now open! Check out our new website for more information on how to nominate.

1. “Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology”
by Stefan Studer, Thanh Binh Bui, Christian Drescher, Alexander Hanuschkin, Ludwig Winkler, Steven Peters and Klaus-Robert Müller
Mach. Learn. Knowl. Extr. 2021, 3(2), 392-413; https://doi.org/10.3390/make3020020
Available online: https://www.mdpi.com/2504-4990/3/2/392

2. “A Survey of Machine Learning-Based Solutions for Phishing Website Detection”
by Lizhen Tang and Qusay H. Mahmoud
Mach. Learn. Knowl. Extr. 2021, 3(3), 672-694; https://doi.org/10.3390/make3030034
Available online: https://www.mdpi.com/2504-4990/3/3/672

3. “Recent Advances in Deep Reinforcement Learning Applications for Solving Partially Observable Markov Decision Processes (POMDP) Problems: Part 1—Fundamentals and Applications in Games, Robotics and Natural Language Processing”
by Xuanchen Xiang and Simon Foo
Mach. Learn. Knowl. Extr. 2021, 3(3), 554-581; https://doi.org/10.3390/make3030029
Available online: https://www.mdpi.com/2504-4990/3/3/554

4. “Classification of Explainable Artificial Intelligence Methods through Their Output Formats”
by Giulia Vilone and Luca Longo
Mach. Learn. Knowl. Extr. 2021, 3(3), 615-661; https://doi.org/10.3390/make3030032
Available online: https://www.mdpi.com/2504-4990/3/3/615

5. “On the Scale Invariance in State of the Art CNNs Trained on ImageNet”
by Mara Graziani, Thomas Lompech, Henning Müller, Adrien Depeursinge and Vincent Andrearczyk
Mach. Learn. Knowl. Extr. 2021, 3(2), 374-391; https://doi.org/10.3390/make3020019
Available online: https://www.mdpi.com/2504-4990/3/2/374

6. “Privacy and Trust Redefined in Federated Machine Learning”
by Pavlos Papadopoulos, Will Abramson, Adam J. Hall, Nikolaos Pitropakis and William J. Buchanan
Mach. Learn. Knowl. Extr. 2021, 3(2), 333-356; https://doi.org/10.3390/make3020017
Available online: https://www.mdpi.com/2504-4990/3/2/333

7. “Deterministic Local Interpretable Model-Agnostic Explanations for Stable Explainability”
by Muhammad Rehman and Naimul Khan
Mach. Learn. Knowl. Extr. 2021, 3(3), 525-541; https://doi.org/10.3390/make3030027
Available online: https://www.mdpi.com/2504-4990/3/3/525

8. “Explainable Artificial Intelligence for Human Decision Support System in the Medical Domain”
by Samanta Knapič, Avleen Malhi, Rohit Saluja and Kary Främling
Mach. Learn. Knowl. Extr. 2021, 3(3), 740-770; https://doi.org/10.3390/make3030037
Available online: https://www.mdpi.com/2504-4990/3/3/740

9. “A Combined Short Time Fourier Transform and Image Classification Transformer Model for Rolling Element Bearings Fault Diagnosis in Electric Motors”
by Christos T. Alexakos, Yannis L. Karnavas, Maria Drakaki and Ioannis A. Tziafettas
Mach. Learn. Knowl. Extr. 2021, 3(1), 228-242; https://doi.org/10.3390/make3010011
Available online: https://www.mdpi.com/2504-4990/3/1/228

10. “Recent Advances in Deep Reinforcement Learning Applications for Solving Partially Observable Markov Decision Processes (POMDP) Problems Part 2—Applications in Transportation, Industries, Communications and Networking and More Topics”
by Xuanchen Xiang, Simon Foo and Huanyu Zang
Mach. Learn. Knowl. Extr. 2021, 3(4), 863-878; https://doi.org/10.3390/make3040043
Available online: https://www.mdpi.com/2504-4990/3/4/863

We are pleased to share that 28 Editorial Board Members from MDPI's journal Machine Learning and Knowledge Extraction (MAKE, ISSN: 2504-4990) were featured in the Stanford University’s list of the World’s Top 2% Scientists in 2022.

The latest Stanford rankings reflect the significant influence and research excellence of these scientists, who are committed to furthering their knowledge for the benefit of the world. The list was created by Prof. John P. A. Ioannidis from Stanford University and his research team. They have created a publicly available database of 100,000 top-cited scientists that provides standardized information on citations, h-index scores, co-authorship adjusted hm-index scores, citations to papers in different authorship positions, and a composite indicator (c-score). Scientists are classified into 22 scientific fields and 176 sub-fields.

We would like to congratulate our Editorial Board Members on their excellent achievement and thank them for their immense contribution to the scientific progression and development of Machine Learning and Knowledge Extraction.

Thank you for your continued support for the open access journal Machine Learning and Knowledge Extraction (MAKE, ISSN: 2504-4990). We are very pleased to announce that MAKE will receive an impact factor in June 2023. More information can be accessed at the following link: https://www.mdpi.com/about/announcements/4252.

Currently, MAKE’s Journal Citation Indicator (JCI) is 064, which corresponds to a ranking of 87/189 (Q2) in the “Computer Science, Artificial Intelligence” category, 77/157 (Q2) in the “Computer Science, Interdisciplinary Applications” category, and 153/344 (Q2) in the “Engineering, Electrical & Electronic” category.

We would like to extend our gratitude to the authors, editors, and reviewers whose efforts have helped us to achieve this milestone!

For more journal statistics, please visit the following link: https://www.mdpi.com/journal/make/stats.

Peer Review Week began 19 September 2022 under the theme of “Research Integrity: Creating and Supporting Trust in Research”. Through various blog articles, podcast, and webinar, we discussed this crucial subject throughout the week, celebrating the essential role peer review plays in maintaining research quality.

To begin, we held a Webinar on the topic. Professor Peter W. Choate and Dr. Emmanuel Obeng-Gyasi joined Dr. Ioana Craciun, one of MDPI’s scientific officers, for an in-depth discussion.

We invite you to view the event recording:

During the week, the MDPI Blog in a series articles highlighted how good Peer Review safeguards research integrity. The following topics were covered:

• Peer Review Week 2022
• Research Integrity
• What We’ve Learned About Peer Review Reports
• 4 Steps to the Perfect Peer Review Report
• How to Write the Perfect Peer Review Report: An Interview
• Inviting Great Peer Reviewers

In a new edition of Insight Faster, an MDPI podcast, we were delighted to talk to the co-chairs of the Peer Review Week committee, Jayashree Rajagopalan (Senior Manager of Global Community Engagement for CACTUS) and Danielle Padula (Head of Marketing and Community Development at Scholastica) to get their take on this year’s event and its related topics.

You can find the Podcast here.

We hope you enjoy the contents!

MDPI will be attending the Conference on Complex Systems (CCS2022) in Palma de Mallorca, Spain, which will take place from 17 to 21 October 2022. The CCS is the largest and most important annual meeting of the international complex systems community. It comes under the auspices of the Complex Systems Society. This edition, organized by IFISC, takes place after previous events held in Lyon, Singapore, Thessaloniki, and Cancun.

The following MDPI journals will be represented:

• Entropy;
• Fractal and Fractional;
• Symmetry;
• Mathematics;
• Dynamics;
• Algorithms;
• Systems;
• Informatics;
• MAKE;
• Information;
• Future Internet;
• Applied System Innovation;
• Data.

If you are attending this conference, please feel free to stop by our booth. Our delegates look forward to meeting you in person to answer any questions you may have. For more information about the conference, please visit the following link: https://www.ccs2022.org/.

We are pleased to announce that Prof. Dr. Simon Tjoa has been appointed Section Editor-in-Chief of the “Privacy” Section in Machine Learning and Knowledge Extraction (ISSN: 2504-4990).

Prof. Dr. Simon Tjoa is a professor and the head of the Computer Science and Security Department at St. Pölten University of Applied Sciences. He received his master’s and doctoral degrees in informatics from the University of Vienna. His research interests include critical infrastructure protection, digital forensics, business continuity management, and business process security. Furthermore, he is on the program committee and an organizing committee member of several security-related international workshops and conferences. He holds several professional security certifications, including AMBCI, CISA, CISM, and ISO 22301 Lead Auditor. Furthermore, he currently serves as the Chapter Secretary of the IEEE SMCS Austria Chapter.

The following is a short Q&A with Prof. Dr. Simon Tjoa, who shared his vision for the journal with us, as well as his views of the research area and open access publishing:

1. What appealed to you about the journal that made you want to take the role as its Section Editor-in-Chief?
MAKE is a fast-emerging journal with cutting-edge publications in the domain of machine learning. In this field it can be observed that there are also various challenges with regard to security and privacy, which match my research interests. It is therefore very inspiring to support the journal in this area.

2. What is your vision for the Section?
My vision is that the journal Section will shape the research field and developments in security as well as privacy in machine learning in the upcoming years.

3. What does the future of this field of research look like?
This field is challenging for various reasons, which makes it interesting for researchers. Firstly, we can observe that privacy holds importance for AI users and customers. Secondly, we can see that laws and regulations are increasingly addressing the security and privacy of AI systems. Thirdly, security and privacy play an essential role for all information technologies used in companies nowadays to deliver continuous and trusted services.

4. What do you think of the development of open access in the publishing field?
I think open access is the best way to share research results and promote collaboration among researchers. It can be observed that open access is becoming the preferred choice for publishing. I am therefore convinced that this area will also be greatly expanded in the future.

We warmly welcome Prof. Dr. Simon Tjoa in his role as Section Editor-in-Chief, and we look forward to him leading Machine Learning and Knowledge Extraction to achieve more milestones.

We are pleased to announce that Machine Learning and Knowledge Extraction (MAKE, ISSN: 2504-4990) has been selected for coverage in the Scopus indexing database in August 2022. We would like to extend our sincerest gratitude to all of the authors, reviewers, and editors who have contributed to this journal and helped accomplish this achievement.

At the same time, Machine Learning and Knowledge Extraction continues to be covered in ESCI (Web of Science), where its Journal Citation Indicator (JCI, 0.64) corresponds to a ranking of 87/189 (Q2) in the “Computer Science, Artificial Intelligence” category, 77/157 (Q2) in the “Computer Science, Interdisciplinary Applications” category, and 153/344 (Q2) in the “Engineering, Electrical & Electronic” category.

The journal provides an advanced forum for studies related to all areas of machine learning and knowledge extraction. It publishes reviews, regular research papers, communications, perspectives, and viewpoints, as well as Special Issues on particular subjects. Please see our video on YouTube explaining the MAKE journal concept.

To make the most of this opportunity, we would like to invite you to submit your research to the journal. If you have a paper concerning any topic within the scope of the journal, please feel free to submit it here.

We look forward to hearing from you.

1. “Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology”
by Stefan Studer et al.
Mach. Learn. Knowl. Extr. 2021, 3(2), 392-413; https://doi.org/10.3390/make3020020
Available online: https://www.mdpi.com/2504-4990/3/2/392

2. “Analysis of Explainers of Black Box Deep Neural Networks for Computer Vision: A Survey”
by Vanessa Buhrmester et al.
Mach. Learn. Knowl. Extr. 2021, 3(4), 966-989; https://doi.org/10.3390/make3040048
Available online: https://www.mdpi.com/2504-4990/3/4/48

3. “A Survey of Machine Learning-Based Solutions for Phishing Website Detection”
by Lizhen Tang et al.
Mach. Learn. Knowl. Extr. 2021, 3(3), 672-694; https://doi.org/10.3390/make3030034
Available online: https://www.mdpi.com/2504-4990/3/3/34

4. “Explainable AI Framework for Multivariate Hydrochemical Time Series”
by Michael C. Thrun et al.
Mach. Learn. Knowl. Extr. 2021, 3(1), 170-204; https://doi.org/10.3390/make3010009
Available online: https://www.mdpi.com/2504-4990/3/1/9

5. “Privacy and Trust Redefined in Federated Machine Learning”
by Pavlos Papadopoulos et al.
Mach. Learn. Knowl. Extr. 2021, 3(2), 333-356; https://doi.org/10.3390/make3020017
Available online: https://www.mdpi.com/2504-4990/3/2/17

6. “Voting in Transfer Learning System for Ground-Based Cloud Classification”
by Mario Manzo et al.
Mach. Learn. Knowl. Extr. 2021, 3(3), 542-553; https://doi.org/10.3390/make3030028
Available online: https://www.mdpi.com/2504-4990/3/3/28

7. “Benchmarking Studies Aimed at Clustering and Classification Tasks Using K-Means, Fuzzy C-Means and Evolutionary Neural Networks”
by Adam Pickens et al.
Mach. Learn. Knowl. Extr. 2021, 3(3), 695-719; https://doi.org/10.3390/make3030035
Available online: https://www.mdpi.com/2504-4990/3/3/35

8. “Explainable Artificial Intelligence for Human Decision Support System in the Medical Domain”
by Samanta Knapič et al.
Mach. Learn. Knowl. Extr. 2021, 3(3), 740-770; https://doi.org/10.3390/make3030037
Available online: https://www.mdpi.com/2504-4990/3/3/37

9. “A Combined Short Time Fourier Transform and Image Classification Transformer Model for Rolling Element Bearings Fault Diagnosis in Electric Motors”
by Christos T. Alexakos et al.
Mach. Learn. Knowl. Extr. 2021, 3(1), 228-242; https://doi.org/10.3390/make3010011
Available online: https://www.mdpi.com/2504-4990/3/1/11

10. “Orientation-Encoding CNN for Point Cloud Classification and Segmentation”
by Hongbin Lin et al.
Mach. Learn. Knowl. Extr. 2021, 3(3), 601-614; https://doi.org/10.3390/make3030031
Available online: https://www.mdpi.com/2504-4990/3/3/31

We are proud to recognize the winners of MDPI’s 2021 Travel Awards in the subject area of “Computer Science & Mathematics” for their outstanding presentations and to present them with the prize.

MDPI journals regularly offer travel awards to encourage talented junior scientists to present their latest research at academic conferences in specific fields, which helps to increase their influence.

The winners mentioned below were carefully selected by the journal editors based on an outline of their research and the work to be presented at an academic conference.

We would like to warmly congratulate the winners of Travel Awards for the year 2021 and wish them the greatest success with their future research endeavors.

MDPI will continue to enhance communication among scientists.

Computers:

• Umberto Michieli, University of Padova, Italy

Journal of Imaging:

• Cameron Kaye, University of Manitoba, Canada
• Alexandra Trujillo, Universidad Nacional del Sur, Argentina

Symmetry:

• José María, Autonomous University of Madrid, Spain
• Naser Ojaroudi Parchin, University of Bradford, UK