30 research outputs found
Learning-Based Constraint Satisfaction With Sensing Restrictions
In this paper we consider graph-coloring problems, an important subset of
general constraint satisfaction problems that arise in wireless resource
allocation. We constructively establish the existence of fully decentralized
learning-based algorithms that are able to find a proper coloring even in the
presence of strong sensing restrictions, in particular sensing asymmetry of the
type encountered when hidden terminals are present. Our main analytic
contribution is to establish sufficient conditions on the sensing behaviour to
ensure that the solvers find satisfying assignments with probability one. These
conditions take the form of connectivity requirements on the induced sensing
graph. These requirements are mild, and we demonstrate that they are commonly
satisfied in wireless allocation tasks. We argue that our results are of
considerable practical importance in view of the prevalence of both
communication and sensing restrictions in wireless resource allocation
problems. The class of algorithms analysed here requires no message-passing
whatsoever between wireless devices, and we show that they continue to perform
well even when devices are only able to carry out constrained sensing of the
surrounding radio environment
Decentralised Algorithms for Wireless Networks.
Designing and managing wireless networks is challenging for many
reasons. Two of the most crucial in 802.11 wireless networks are:
(a) variable per-user channel quality and (b) unplanned, ad-hoc deployment
of the Access Points (APs). Regarding (a), a typical consequence
is the selection, for each user, of a different bit-rate, based on
the channel quality. This in turn causes the so-called performance
“anomaly”, where the users with lower bit-rate transmit for most of
the time, causing the higher bit-rate users to receive less time for
transmission (air time). Regarding (b), an important issue is managing
interference. This can be mitigated by selecting different channels
for neighbouring APs, but needs to be carried out in a decentralised
way because often APs belong to different administrative domains, or
communication between APs is unfeasible. Tools for managing unplanned
deployment are also becoming important for other small cell
networks, such as femtocell networks, where decentralised allocation
of scrambling codes is a key task
Can AI be used ethically to assist peer review?
As the rate and volume of academic publications has risen, so too has the pressure on journal editors to quickly find reviewers to assess the quality of academic work. In this context the potential of Artificial Intelligence (AI) to boost productivity and reduce workload has received significant attention. Drawing on evidence from an experiment utilising AI to learn and assess peer review outcomes, Alessandro Checco, Lorenzo Bracciale, Pierpaolo Loreti, Stephen Pinfield, and Giuseppe Bianchi, discuss the prospects for AI for assisting peer review and the potential ethical dilemmas its application might produce
Investigating User Perception of Gender Bias in Image Search
There is growing evidence that search engines produce results that are socially biased, reinforcing a view of the world that aligns with prevalent social stereotypes. One means to promote greater transparency of search algorithms - which are typically complex and proprietary - is to raise user awareness of biased result sets. However, to date, little is known concerning how users perceive bias in search results, and the degree to which their perceptions differ and/or might be predicted based on user attributes. One particular area of search that has recently gained attention, and forms the focus of this study, is image retrieval and gender bias. We conduct a controlled experiment via crowdsourcing using participants recruited from three countries to measure the extent to which workers perceive a given image results set to be subjective or objective. Demographic information about the workers, along with measures of sexism, are gathered and analysed to investigate whether (gender) biases in the image search results can be detected. Amongst other findings, the results confirm that sexist people are less likely to detect and report gender biases in image search results
ECMO for COVID-19 patients in Europe and Israel
Since March 15th, 2020, 177 centres from Europe and Israel have joined the study, routinely reporting on the ECMO support they provide to COVID-19 patients. The mean annual number of cases treated with ECMO in the participating centres before the pandemic (2019) was 55. The number of COVID-19 patients has increased rapidly each week reaching 1531 treated patients as of September 14th. The greatest number of cases has been reported from France (n = 385), UK (n = 193), Germany (n = 176), Spain (n = 166), and Italy (n = 136) .The mean age of treated patients was 52.6 years (range 16–80), 79% were male. The ECMO configuration used was VV in 91% of cases, VA in 5% and other in 4%. The mean PaO2 before ECMO implantation was 65 mmHg. The mean duration of ECMO support thus far has been 18 days and the mean ICU length of stay of these patients was 33 days. As of the 14th September, overall 841 patients have been weaned from ECMO
support, 601 died during ECMO support, 71 died after withdrawal of ECMO, 79 are still receiving ECMO support and for 10 patients status n.a. . Our preliminary data suggest that patients placed
on ECMO with severe refractory respiratory or cardiac failure secondary to COVID-19 have a reasonable (55%) chance of survival. Further extensive data analysis is expected to provide invaluable information on the demographics, severity of illness, indications and different ECMO management strategies in these patients
Decentralised Algorithms for Wireless Networks.
Designing and managing wireless networks is challenging for many
reasons. Two of the most crucial in 802.11 wireless networks are:
(a) variable per-user channel quality and (b) unplanned, ad-hoc deployment
of the Access Points (APs). Regarding (a), a typical consequence
is the selection, for each user, of a different bit-rate, based on
the channel quality. This in turn causes the so-called performance
“anomaly”, where the users with lower bit-rate transmit for most of
the time, causing the higher bit-rate users to receive less time for
transmission (air time). Regarding (b), an important issue is managing
interference. This can be mitigated by selecting different channels
for neighbouring APs, but needs to be carried out in a decentralised
way because often APs belong to different administrative domains, or
communication between APs is unfeasible. Tools for managing unplanned
deployment are also becoming important for other small cell
networks, such as femtocell networks, where decentralised allocation
of scrambling codes is a key task
Decentralised Algorithms for Wireless Networks.
Designing and managing wireless networks is challenging for many
reasons. Two of the most crucial in 802.11 wireless networks are:
(a) variable per-user channel quality and (b) unplanned, ad-hoc deployment
of the Access Points (APs). Regarding (a), a typical consequence
is the selection, for each user, of a different bit-rate, based on
the channel quality. This in turn causes the so-called performance
“anomaly”, where the users with lower bit-rate transmit for most of
the time, causing the higher bit-rate users to receive less time for
transmission (air time). Regarding (b), an important issue is managing
interference. This can be mitigated by selecting different channels
for neighbouring APs, but needs to be carried out in a decentralised
way because often APs belong to different administrative domains, or
communication between APs is unfeasible. Tools for managing unplanned
deployment are also becoming important for other small cell
networks, such as femtocell networks, where decentralised allocation
of scrambling codes is a key task