Application-Level QoS: Improving video conferencing quality through sending the best packet next

In a traditional network stack, data from an application is transmitted in the order that it is received. An algorithm is proposed where information about the priority of packets and expiry times is used by the transport layer to reorder or discard packets at the time of transmission to optimise the use of available bandwidth. This can be used for video conferencing to prioritise important data. This scheme is implemented and compared to unmodified datagram congestion control protocol (DCCP). This algorithm is implemented as an interface to DCCP and tested using traffic modelled on video conferencing software. The results show improvement can be made to video conferencing during periods of congestion - substantially more audio packets arrive on time with the algorithm, which leads to higher quality video conferencing. In many cases video packet arrival rate also increases and adopting the algorithm gives improvements to video conferencing that are better than using unmodified queuing for DCCP. The algorithm proposed is implemented on the server only, so benefits can be obtained on the client without changes being required to the client

ESTRO-ACROP guideline on surface guided radiation therapy

Surface guidance systems enable patient positioning and motion monitoring without using ionising radiation. Surface Guided Radiation Therapy (SGRT) has therefore been widely adopted in radiation therapy in recent years, but guidelines on workflows and specific quality assurance (QA) are lacking. This ESTRO-ACROP guideline aims to give recommendations concerning SGRT roles and responsibilities and highlights common challenges and potential errors. Comprehensive guidelines for procurement, acceptance, commissioning, and QA of SGRT systems installed on computed tomography (CT) simulators, C-arm linacs, closed-bore linacs, and particle therapy treatment systems are presented that will help move to a consensus among SGRT users and facilitate a safe and efficient implementation and clinical application of SGRT. Keywords: ACROP; ESTRO; Guideline; SGRT; Surface guided radiation therapy

Machine learning based iterative learning control for non-repetitive time-varying systems

The repetitive tracking task for time-varying systems (TVSs) with non-repetitive time-varying parameters, which is also called non-repetitive TVSs, is realized in this paper using iterative learning control (ILC). A machine learning (ML) based nominal model update mechanism, which utilizes the linear regression technique to update the nominal model at each ILC trial only using the current trial information, is proposed for non-repetitive TVSs in order to enhance the ILC performance. Given that the ML mechanism forces the model uncertainties to remain within the ILC robust tolerance, an ILC update law is proposed to deal with non-repetitive TVSs. How to tune parameters inside ML and ILC algorithms to achieve the desired aggregate performance is also provided. The robustness and reliability of the proposed method are verified by simulations. Comparison with current state-of-the-art demonstrates its superior control performance in terms of controlling precision. This paper broadens ILC applications from time-invariant systems to non-repetitive TVSs, adopts ML regression technique to estimate non-repetitive time-varying parameters between two ILC trials and proposes a detailed parameter tuning mechanism to achieve desired performance, which are the main contributions

Reduction of PTV margins for elective pelvic lymph nodes in online adaptive radiotherapy of prostate cancer patients

Background Cone beam CT (CBCT) based online adaptive radiotherapy (oART) is a new development in radiotherapy. With oART, the requirements for planning target volume (PTV) margins differ from standard therapy because motion occurs during a session. In this study, we aim to evaluate a margin reduction for locally advanced prostate patients treated with oART. Material and methods Intrafraction motion of the elective pelvic lymph nodes was evaluated by two radiation therapists (RTTs) for 150 fractions from 10 prostate patients treated with oART. PTV margins of 3, 4 and 5 mm where added to these lymph nodes for all patients. The seven first patients were treated with 5 mm PTV margin, while the last three patients were treated with 4 mm margin. After treatment, the RTTs reviewed the verification CBCTs and evaluated whether the various PTV margins would have covered the adapted clinical target volume, scoring each fraction as approved, inconclusive or rejected. Couch shifts corresponding to the rigid prostate match between the CBCTs were analyzed with respect to the RTT evaluation. Results The RTTs approved a 4 mm margin in 95% of the fractions, while 2% of the fractions were rejected. For a 3 mm margin, 57% of the fractions were approved, while 5% were rejected. The scoring from the two RTTs was consistent; e.g., for 3 mm, one RTT approved 58% of the fractions, while the other approved 55%. If the couch was moved less than 2 mm in any direction, 70% of the fractions were approved for a 3 mm margin, compared to 32% for shifts greater than 2 mm. Conclusion It is safe to reduce the PTV margin from 5 to 4 mm for the elective pelvic lymph nodes for prostate patients treated with oART. Further margin reductions can be motivated for patients presenting little intrafraction motion.publishedVersio

TCP-Based distributed offloading architecture for the future of untethered immersive experiences in wireless networks

IMX '22: ACM International Conference on Interactive Media Experiences, 22-24 June 2022, Aveiro, Portugal.Task offloading has become a key term in the field of immersive media technologies: it can enable lighter and cheaper devices while providing them higher remote computational capabilities. In this paper we present our TCP-based offloading architecture. The architecture, has been specifically designed for immersive media offloading tasks with a particular care in reducing any processing overhead which can degrade the network performance. We tested the architecture for different offloading scenarios and conditions on two different wireless networks: WiFi and 5G millimeter wave technologies. Besides, to test the network on alternative millimeter wave configurations, currently not available on the actual 5G millimeter rollouts, we used a 5G Radio Access Network (RAN) real-time emulator. This emulator was also used to test the offloading architecture for an simulated immersive user sharing network resources with other users. We provide insights of the importance of user prioritization techniques for successful immersive media offloading. The results show a great performance for the tested immersive media scenarios, highlighting the relevance of millimeter wave technology for the future of immersive media applications.This work has received funding from the European Union (EU) Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie ETN TeamUp5G, grant agreement No. 813391