ECE • Paper by ECE-NTUA Diploma Student K. Cheliotis, Postdoctoral Researcher V. Alimisis, Graduate A. Papathanasiou and O. Ntasiou and Prof. P. P. Sotiriadis received the Best PhD Symposium Paper Award in the Springer FAIEMA 2024 Conference

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width: 100"><h1>100 years of education and research on the cutting edge of technology</h1></div></a></div> <div class="pull-right promo"><a href="https://www.ece.ntua.gr/en/100years"><div style=" width: 166px; height: 60px; background: url('https://www.ece.ntua.gr/themes/ecetheme/assets/img/anniv_logo.png'); background-size: cover; background-repeat: no-repeat; "></div></a></div> </div> </div> <div id="content"> <div class="container"> <div class="text newstext"> <h3>Paper by ECE-NTUA Diploma Student K. Cheliotis, Postdoctoral Researcher V. Alimisis, Graduate A. Papathanasiou and O. Ntasiou and Prof. P. P. Sotiriadis received the Best PhD Symposium Paper Award in the Springer FAIEMA 2024 Conference</h3> <hr/> <p><img src="https://www.ece.ntua.gr/uploads/news/gT6su35X/Best_PhD_Track_Award_signedKS.png" alt="" /></p> <p>We are pleased to announce that the paper entitled "A Low-Power Analog Vector-Length Calculator Classifier for Fetal Health Classification" received the <strong>Best PhD Symposium Paper Award</strong> in the <strong>Springer 2nd International Conference on Frontiers of Artificial Intelligence, Ethics, and Multidisciplinary Applications</strong>; 1st-2nd October 2024, Athens, Greece.</p> <p>The Award-Winning paper was co-authored by <strong>Konstantinos Cheliotis</strong> (Diploma Student, ECE- NTUA and Researcher Archimedes/Athena RC), <strong>Vassilis Alimisis</strong> (Postdoctoral Researcher, ECE-NTUA and Researcher Archimedes/Athena RC), <strong>Andreas Papathanasiou</strong> (Graduate, ECE-NTUA), <strong>Ourania Ntasiou</strong> (Graduate, ECE-NTUA), and <strong>Paul P. Sotiriadis</strong> (Professor, ECE-NTUA; Lead Researcher, Archimedes/Athena RC; IEEE Fellow).</p> <p><strong>ABSTRACT</strong>: This research presents a novel, low-power, fully analog integrated circuit for classifying fetal health data. The circuit leverages a centroid-based approach, employing Vector Length calculations and current comparisons. Notably, it achieves high classification accuracy (93.8%) while consuming only 675nW. This design prioritizes energy efficiency by operating transistors in the sub-threshold region while maintaining robustness. To validate its effectiveness, the proposed circuit is compared against existing software and hardware-based classifiers. Python programming language was used to train the classification model and process the resulting data. The design and simulations were conducted within the Cadence IC Suite environment, utilizing the TSMC 90nm CMOS process technology.</p> </div> </div> </div> <div class="sticky-bottom"> <div id="bottom-bar" class="bg-dark white-links"> <div class="container"> <ul class="pull-left"> <li><a href="https://www.ece.ntua.gr/en/contact "><i class="fa fa-caret-right"></i> Contact</a></li> <li><a href="https://www.ece.ntua.gr/en/access"><i class="fa fa-caret-right"></i> Access</a></li> <li><a href="/admin"><i class="fa fa-caret-right"></i> Login</a></li> </ul> <ul class="social pull-right"> <li><a href="https://www.facebook.com/ece.school.ntua" rel="external" target="_BLANK"><i class="fa fa-facebook" aria-hidden="true"></i><span class="hide-text"> Facebook</span></a></li> <li><a href="https://twitter.com/ecentua" rel="external" target="_BLANK"><i class="fa fa-twitter" aria-hidden="true"></i><span class="hide-text"> Twitter</span></a></li> <li><a href="https://www.linkedin.com/company/school-of-electrical-and-computer-engineering-ntua/" rel="external" target="_BLANK"><i class="fa fa-linkedin" aria-hidden="true"></i><span class="hide-text"> LinkedIn</span></a></li> <li><a href="https://www.youtube.com/channel/UCesQBcFYw796R3O3pJO-4vQ" rel="external" target="_BLANK"><i class="fa fa-youtube" aria-hidden="true"></i><span class="hide-text"> YouTube</span></a></li> <li><a href="/en/rss" rel="external" target="_BLANK"> <i class="fa fa-rss" aria-hidden="true"></i><span class="hide-text"> RSS</span></a></li></li> </ul> </div> </div> <footer class="footer bg-medium"> <div class="container"> <ul class="copyright pull-left"> <li>Copyright © 2025 -</li> <li>School of Electrical and Computer Engineering,</li> <li><a href="https://www.ntua.gr/" rel="external" target="_BLANK">National Technical University of Athens</a></li> </ul> <ul class="credits pull-right"> <li><a href="mailto:webmaster@ece.ntua.gr">Webmaster</a></li> </ul> </div> </footer> </div> <script type="text/javascript" src="https://www.ece.ntua.gr/themes/ecetheme/assets/js/vendor.js"></script> <script type="text/javascript" src="https://www.ece.ntua.gr/themes/ecetheme/assets/js/back-to-top.js"></script> <script type="text/javascript" src="https://www.ece.ntua.gr/themes/ecetheme/assets/js/bootstrap-hover-dropdown.min.js"></script> <script type="text/javascript" src="https://www.ece.ntua.gr/themes/ecetheme/assets/js/isotope.pkgd.min.js"></script> <script type="text/javascript" src="https://www.ece.ntua.gr/themes/ecetheme/assets/js/velocity.js"></script> <script src="https://cdn.jsdelivr.net/gh/fancyapps/fancybox@3.5.2/dist/jquery.fancybox.min.js"></script> </body> </html>

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ECE • Paper by ECE-NTUA Diploma Student K. Cheliotis, Postdoctoral Researcher V. Alimisis, Graduate A. Papathanasiou and O. Ntasiou and Prof. P. P. Sotiriadis received the Best PhD Symposium Paper Award in the Springer FAIEMA 2024 Conference