“Signal Processing in the AI era” was the tagline of this year’s IEEE International Conference on Acoustics, Speech and Signal Processing, taking place in Rhodes, Greece.
In this context, Brent de Weerdt, Xiangyu Yang, Boris Joukovsky, Alex Stergiou and Nikos Deligiannis presented ETRO’s research during poster sessions and oral presentations, with novel ways to process and understand graph, video, and audio data. Nikos Deligiannis chaired a session on Graph Deep Learning, attended the IEEE T-IP Editorial Board Meeting, and had the opportunity to meet with collaborators from the VUB-Duke-Ugent-UCL joint lab.
Featured articles:
- De Weerdt, B. et al., “Designing Transformer Networks for Sparse Recovery of Sequential Data Using Deep Unfolding” (https://ieeexplore.ieee.org/abstract/document/10094712)
- Yang X. et al., “Relevance Propagation through Deep Conditional Random Fields” (https://ieeexplore.ieee.org/abstract/document/10095075)
- Stergiou A. et al., “Play it back: Iterative attention for audio recognition” (https://ieeexplore.ieee.org/abstract/document/10096532, developed at the University of Bristol)
On November 15th 2024 at 10:00, Eden Teshome Hunde will defend their PhD entitled “CROSS-LAYER DESIGN, IMPLEMENTATION AND EVALUATION OF IPV6 MULTICAST FOR RADIO DUTY CYCLED WIRELESS SENSOR AND ACTUATOR NETWORKS”.
Everybody is invited to attend the presentation in room D.2.01 or online via this link.
Wireless sensor and actuator networks (WSANs), consist of small-sized constrained sensing and/or actuating devices which can run an Internet Protocol version 6 (IPv6) network stack. In such WSANs, there is often the need for sending the same message to several devices in the WSAN, such as for applications for controlling all the lights in a building or turning on/off all the air conditioners in the room etc. For doing so, IP multicast can be an efficient solution.
In this work, we study Bidirectional Multicast RPL Forwarding (BMRF) as this protocol relies on forwarding tables put in place by the well-known Routing Protocol for Low Power and Lossy Networks (RPL) and allows to combine the best ideas of existing multicast protocols. Through RPL, a routing tree towards the sink is installed for multihop routing from node to sink, and the nodes’ forwarding tables will also contain entries for reaching destinations in downward direction.
For downward forwarding IPv6 multicast packets, two methods exist. One is via link layer (LL), broadcasting a frame containing the IPv6 multicast packet. The other is to send several LL unicast frames containing that packet. BMRF allows a node to choose between these two methods. The best option will depend on the presence of a radio duty cycling (RDC) protocol. RDC is part of the medium access control (MAC) layer and puts the radio to sleep when no communication is needed. We investigate the influence of MAC/RDC protocols on BMRF’s performance.
We evaluate the performance of BMRF on non-synchronized WSANs that use Carrier Sense Multiple Access (CSMA) as MAC and ContikiMAC as RDC. We demonstrate that LL unicast outperforms LL broadcast in terms of packet delivery ratio (PDR), delay, and energy consumption in many settings.
We investigate the performance of BMRF on WSANs with synchronous MAC and RDC based on Time Slotted Channel hopping (TSCH). This is more challenging, as TSCH needs a schedule to tell which action must happen in each timeslot. The actions can be to send or to listen on a given channel or to be idle. Idleness allows the radio to switch OFF, providing RDC. The schedule is not part of the standard and must be proposed by the system designer. An elegant autonomous scheduling method called Orchestra is available to accommodate traffic in a RPL tree. We extend Orchestra with a novel scheduling rule for supporting LL downwards forwarding through LL broadcast. Comparing LL unicast with LL broadcast forwarding teaches us that LL unicast outperforms LL broadcast in terms of packet delivery ratio (PDR), but the latter can be beneficial to certain applications, especially those sensitive to delay.
Before conducting the two previous evaluation studies, we investigate the performance of simple convergecast traffic while considering ContikiMAC and TSCH with Orchestra under RPL on the real dual Zolertia Firefly Motes (one is observed and other one is observing mote). This study served two purposes; it reminds the reader of the characteristics of those protocols and allowed to fine-tune the dual motes.
We also contributed by adapting the Orchestra to bursty convergecast traffic. Simulation results demonstrate that the new scheduler slightly improves PDR and reduces delay compared to state-of-the-art solutions.
On September 17 2021 at 16.00 Jakub Ceranka will defend his PhD entitled “Advancements in Whole-Body Multi-Modal MRI: Towards Computer-Aided Diagnosis of Metastatic Bone Disease”.
Everybody is invited to attend the online presentation via  this teams link.
Cancer that begins in an organ, such as the lungs, breast or prostate, and then spreads to the bone or other organs, marks the beginning of metastatic disease. The confident detection of metastatic bone disease and the reliable assessment of the tumour load and treatment response is essential to improve patients’ quality of life and increase life expectancy. Magnetic resonance imaging (MRI) has been successfully used for monitoring of metastatic bone disease. Anatomical whole-body sequences offer excellent resolution and sensitivity for the detection of neoplastic cells within the bone marrow. In combination with spatially prealigned functional diffusion-weighted whole-body MRI and apparent diffusion coefficient maps, it allows for focused, efficient, multi-parametric and holistic evaluation of the total tumour volume, diffusion volume and treatment response assessment. One of the major challenges of radiological reading of whole-body MRI in the clinical routine comes from the large amount of data to be reviewed, making lesion detection and quantification demanding for a radiologist, but also prone to error. Additionally, whole-body MR images are often corrupted with multiple spatial and intensity artifacts, which degrade the performance of medical image processing algorithms.
This PhD thesis proposes number of contributions in the medical image processing domain aiming at improving the quality and extending the usability of whole-body multi-modal MRI in the clinical routine. These include spatial groupwise image registration (to align multiple MRI modalities), multi-atlas segmentation (to define the skeleton region of interest), image standardization (to map MRI intensities into comparable ranges) and a deep learning framework for detection and segmentation of metastatic bone disease, as it is pathology of choice for this work. Combined, proposed contributions provide building blocks for a fully automated computer-aided diagnosis (CAD) system for the detection and segmentation of metastatic bone disease using whole-body multi-modal MRI. Finally, an ablation study describing the impact of different CAD system components on detection and segmentation accuracy is provided.
AIOTI is organising a Web3 Hackathon on 21/22 September 2023 in Brussels and online.
Please feel free to register and share this information further within your communities.
About the Hackathon:
The WEB3 HACKATHON is a collaborative event with a mixed crowd of students, professionals and authorities, moderated by domain experts. The event is accessible for every individual, public or private organisations willing to enter the new digital era.
The Hackathon target is to solve a series of challenges, using WEB3 Technology:
- Industry – Challenge: Use WEB3 to TACKLE CLIMATE EMMERGENCY
- Authorities – Challenge: Use WEB3 to SOLVE A GOVERNANCE PROBLEM
- Media – Challenge: Use WEB3 to TACKLE FAKE NEWS
- Education – Challenge: Use WEB3 to INNOVATE EDUCATION
After two years of dedicated research and development under the leadership of ETRO-VUB, a breakthrough has been achieved within the INTOWALL project: a revolutionary radar technology for building inspection was developed, called the transient radar method (TRM). The initiative aimed to reduce the CO2 emissions of buildings and increase their energy efficiency.
The new technology enables the measurement of the density of glass wool in cavity walls with unprecedented precision, without the need for invasive methods. “This advancement not only promises to improve the accuracy of insulation assessments but also contributes to the ambition to achieve a CO2-neutral status by 2050,” says Professor Johan Stiens of ETRO.
Looking towards the future, the project team is focused on further refining the technology to map a wide range of insulation materials and building elements. This prospect of expansion and application on a larger scale highlights the endless possibilities. As part of the FTI Brussels Festival, the milestone of the INTOWALL project will be celebrated. A unique demonstration was held on March 18, 2024.
Additionally, the project team invites potential partners to contribute to and participate in this groundbreaking endeavour. Through collaboration, we can transform the construction sector into a more sustainable and efficient future.
For more information on InToWall press articles: https://press.vub.ac.be/wereldprimeur-in-radartechnologie and https://trends.knack.be/kanaal-z/z-nieuws/bekijk-radar-van-vub-ziet-isolatie-dwars-door-muren-heen/
FWO granted the project Exploiting plasma etching processes for micro/nanotexturing of metal surfaces to enable novel chemical, analytical, optical, and medical applications.
The plasma metal etcher will be installed in the core facility MICROLAB. The project execution will be coordinated by Prof. Wim de Malsche (CHIS) with two ETRO-promoters Prof. Johan Stiens and Prof. Peter Schelkens. Step by step the microfabrication facilities are growing, allowing to dive deeper again in microfabrication related projects.
Several new buildings on Campus Oefenplein become operational.