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Department of Computer Science and Technology – Security Group: Past…
https://www.cl.cam.ac.uk/research/security/meetings/past-presentations.html17 Jun 2024: Jeff Yan: Collusion prevention and detection – a case study using online Bridge (20 min). ... 2006-03-31. Jeff Yan: Enhancing signature-based collaborative spam detection. 2006-04-21. JoonWoong Kim: Remark on HB protocol: RFID protocol using LPN. -
Completed work - S. Keshav
https://svr-sk818-web.cl.cam.ac.uk/keshav/wiki/index.php/Completed_work18 Mar 2024: IEEE ICBC, 2020. Using RFID-based sensors for determining soil moisture level. ... Spring 2019. Using IoT to reduce energy costs of lighting (with Yerbol Aussat). -
AWERB 3Rs Minutes 4th October 2024 Redacted
https://www.ubs.admin.cam.ac.uk/system/files/public/3rs_minutes_041023_redacted.pdf14 May 2024: The use of artificial intelligence in the future.• Home cage monitoring systems using Radio Frequency Identification (RFID) implants• University of Newcastle are developing a forum for the animal research community (ARC). -
Detecting Foot Strikes during Running with Earbuds
https://mobile-systems.cl.cam.ac.uk/papers/bodysys24-dong.pdf2 May 2024: hEARt [5] proposedmonitoring HR during running using an in-ear microphone,while RunBuddy [8] and ER-Rhythm [18] developed meth-ods for monitoring RR using smartphone IMUs and RFID,respectively. ... 1–11. [18] Yanni Yang, Jiannong Cao, and Xiulong Liu. -
The Digital Lab Manager: Automating Research Support
https://como.ceb.cam.ac.uk/media/preprints/c4e_318_sdr39_Digital_Laboratory_Manager.pdf25 Jan 2024: Preprint No. 318. Keywords: Laboratory Automation, Lab Management, LIMS, RFID, Asset tracking, Dynamic knowledgegraphs. ... a) Sample arrangements of the RFID components. (b) RFID labelling on a chemical container. -
FedConv: A Learning-on-Model Paradigm for Heterogeneous Federated…
https://www.cl.cam.ac.uk/~qy258/assets/files/paper/24-MobiSys-FedConv.pdf16 Jun 2024: We evaluatethe model using the server-side IID test data and non-IID client-sidetest data. ... Runtime performance: 1) Memory footprint: the real-time GPUmemory usage is monitored using the PyTorch CUDA Toolkit.
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