IEEE Transactions on Mobile Computing

IEEE Transactions on Mobile Computing (TMC) is a scholarly archival journal published monthly that focuses on the key technical issues related to Mobile Computing. It is the intent of TMC to publish mature works of research, typically those that have appeared in part in conferences. Furthermore, it is the intent of TMC to focus on issues at the link-layer and above in wireless communications, and to focus only on topics explicitly or plausibly related to mobile systems. Read the full scope of TMC.


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From the August 2018 issue

Autonomous Training of Activity Recognition Algorithms in Mobile Sensors: A Transfer Learning Approach in Context-Invariant Views

By Seyed Ali Rokni and Hassan Ghasemzadeh

featured article thumbnailWearable technologies play a central role in human-centered Internet-of-Things applications. Wearables leverage machine learning algorithms to detect events of interest such as physical activities and medical complications. A major obstacle in large-scale utilization of current wearables is that their computational algorithms need to be re-built from scratch upon any changes in the configuration. Retraining of these algorithms requires significant amount of labeled training data, a process that is labor-intensive and time-consuming. We propose an approach for automatic retraining of the machine learning algorithms in real-time without need for any labeled training data. We measure the inherent correlation between observations made by an old sensor view for which trained algorithms exist and the new sensor view for which an algorithm needs to be developed. Our multi-view learning approach can be used in both online and batch modes. By applying the autonomous multi-view learning in the batch mode, we achieve an accuracy of 83.7 percent in activity recognition which is an improvement of 9.3 percent due to the automatic labeling of the data in the new sensor node. In addition to gain the less computation advantage of incremental training, the online learning algorithm results in an accuracy of 82.2 percent in activity recognition.

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Editorials and Announcements

Announcements

  • We are pleased to announce that Eylem Ekici, Professor of Electrical and Computer Engineering at Ohio State University, has been named an Associate Editor-in-Chief of the IEEE Transactions on Mobile Computing starting April 2018.
  • TMC now offers authors access to Code Ocean. Code Ocean is a cloud-based executable research platform that allows authors to share their algorithms in an effort to make the world’s scientific code more open and reproducible. Learn more or sign up for free.
  • We are pleased to announce that Marwan Krunz, the Kenneth VonBehren Endowed Professor in the Department of Electrical and Computer Engineering at the University of Arizona, USA, has been named the new Editor-in-Chief of the IEEE Transactions on Mobile Computing starting in 2017.
  • We are pleased to announce that Kevin Almeroth, Professor of Computer Science at the University of California in Santa Barbara, has been named the new Associate Editor-in-Chief of the IEEE Transactions on Mobile Computing starting in 2017.
  • According to Thomson Reuters' 2016 Journal Citation Report, TMC has an impact factor of 3.822.

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TMC is a joint publication of the:

IEEE Computer SocietyIEEE Circuits and Systems Society IEEE Comunications Society IEEE Signal Processing Society

 

TMC is published in cooperation with: IEEE Electromagnetic Compatibility Society, IEEE Engineering in Medicine and Biology Society, IEEE Technology Management Council, IEEE Information Theory Society, IEEE Instrumentation and Measurement Society, IEEE Power & Energy Society, IEEE Robotics and Automation Society, and IEEE Systems, Man, and Cybernetics Society

TMC is indexed in ISI

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