2018 New Year's Greetings from IEEE TNNLS

Dear all,

Happy New Year!

I would like to take this opportunity to sincerely thank you for your support to the IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS) in various capacities. With everyone’s great effort and support, the IEEE TNNLS has continued to grow in terms of quality, quantity, and impact:

* The latest impact factor of TNNLS is 6.108 according to the Journal Citation Reports (JCR), which marks a historical high impact factor for our journal and continue to place TNNLS as a premier journal in the field.

* The number of new submissions in 2017 reached the mark of 1400, another historical high in terms of manuscript submissions. This is another strong indicator of a healthy and continuous growth of the journal and the community.

We would not have achieved this level of success without your support and service! I deeply appreciate and acknowledge all the hard work you do for our community!

TNNLS is always taking proactive steps for innovation in the publication process. I am very excited to report to you that in 2017, TNNLS was one of the first 24 IEEE journals participated in the IEEE DataPort Trial initiative. "Data" is of essential importance to many articles published in TNNLS and also to our community in general, and this new DataPort feature at TNNLS will provide a great tool for our authors to publish, store, and share the data associated with their paper. With DataPort, you can enjoy more exposure to your data-based research, provide easy access to your data benchmarks, ensure long-term storage and accessibility, facilitate the participation of data challenges and competitions, and many more. With this new function, our authors can deposit their datasets up to 2TB in size into IEEE DataPort. You will receive a unique and persistent DOI (Digital Object Identifier) immediately upon loading the dataset, which can then be used in your manuscript file to refer readers to the related dataset. This will not only strengthen your article, but it can also support research reproducibility and broaden the impact of your research. The DataPort function has already been successfully implemented and tested at our TNNLS submission and review system, and I encourage you to try this new function when making a submittal to our journal and enjoy all the great advantages that DataPort bring to our community.

Please continue to submit your best research to IEEE TNNLS and also continue to help with timely and thorough reviews. As we kick-off the new year, we will work closely with the entire community to ensure the continued growth and success, including further reduce the backlog of accepted papers, reduce the turn-around time of the reviewing process, strengthen the quality of our accepted articles, and increase the journal's readership, outreach, and impact in and beyond the community.

We wish you and your loved ones all the best for the Holidays and a very happy, healthy, and prosperous New Year of 2018!

Sincerely,

Haibo He

Editor-in-Chief
IEEE Transactions on Neural Networks and Learning Systems