Polar Code decoder exploration framework

The increasing demand for fast wireless communications requires sophisticated baseband signal processing. One of the computational intense tasks here is advanced Forward Error Correction (FEC), especially the decoding. Finding efficient hardware implementations for sophisticated FEC decoding algorithms that fulfill throughput demands under strict implementation constraints is an active research topic due to increasing throughput, low latency, and high energy efficiency requirements.This paper focuses on the interesting class of Polar Codes that are currently a hot topic. We present a modular framework to automatically generate and evaluate a wide range of Polar Code decoders, with emphasis on design space exploration for efficient hardware architectures. To demonstrate the efficiency of our framework a very high throughput Soft Cancellation (SCAN) Polar Code decoder is shown that was automatically generated. This decoder is, to the best of our knowledge, the fastest SCAN Polar Code decoder published so far.</p

Citizens observatories for effective Earth observations: the WeSenseIt approach

The WeSenseIt project defines citizen observatories as “A method, an environment and an infrastructure supporting an information ecosystem for communities and citizens, as well as emergency operators and policymakers, for discussion, monitoring and intervention on situations, places and events” . A collaborative approach has been taken to develop solutions that involve an exchange of information and expertise from all participants and where the focus is on arriving at practical solutions with a clear vision and direction. This has created a shared ownership scheme, and shifts power to the process itself rather than remaining within authorities, developers or decision-makers. The project’s emphasis is on delivering highly innovative technologies to support citizens, communities and authorities in developing a real-time situation awareness while ensuring all stakeholders play their part. Implementation has been through a combination of crowdsourcing, custom applications and dedicated web portals designed to foster collaboration, and which has created a shared knowledge base that facilitates decision-making processes and engages with communities. Data is captured via innovative sensors that are used directly by citizens, crowdsourcing from social networks (or by collective intelligence)

Semi-natural grasslands in boreal Europe: a rise of a socioecological research agenda

Peer reviewe

The value of citizen science for flood risk reduction: cost–benefit analysis of a citizen observatory in the Brenta-Bacchiglione catchment

Citizen observatories are a relatively recent form of citizen science. As part of the flood risk management strategy of the Brenta-Bacchiglione catchment, a citizen observatory for flood risk management has been proposed and is currently being implemented. Citizens are involved through monitoring water levels and obstructions and providing other relevant information through mobile apps, where the data are assimilated with other sensor data in a hydrological–hydraulic model used in early warning. A cost–benefit analysis of the citizen observatory was undertaken to demonstrate the value of this approach in monetary terms. Although not yet fully operational, the citizen observatory is assumed to decrease the social vulnerability of the flood risk. By calculating the hazard, exposure and vulnerability of three flood scenarios (required for flood risk management planning by the EU Directive on Flood Risk Management) with and without the proposed citizen observatory, it is possible to evaluate the benefits in terms of the average annual avoided damage costs. Although currently a hypothetical exercise, the results showed a reduction in avoided damage of 45 % compared to a business as usual scenario. Thus, linking citizen science and citizen observatories with hydrological modelling to raise awareness of flood hazards and to facilitate two-way communication between citizens and local authorities has great potential in reducing future flood risk in the Brenta-Bacchiglione catchment. Moreover, such approaches are easily transferable to other catchments

The transprecision computing paradigm: Concept, design, and applications

Guaranteed numerical precision of each elementary step in a complex computation has been the mainstay of traditional computing systems for many years. This era, fueled by Moore’s law and the constant exponential improvement in computing efficiency, is at its twilight: from tiny nodes of the Internet-of-Things, to large HPC computing centers, subpicoJoule/operation energy efficiency is essential for practical realizations. To overcome the power wall, a shift from traditional computing paradigms is now mandatory. In this paper we present the driving motivations, roadmap, and expected impact of the European project OPRECOMP. OPRECOMP aims to (i) develop the first complete transprecision computing framework, (ii) apply it to a wide range of hardware platforms, from the sub-milliWatt up to the MegaWatt range, and (iii) demonstrate impact in a wide range of computational domains, spanning IoT, Big Data Analytics, Deep Learning, and HPC simulations. By combining together into a seamless design transprecision advances in devices, circuits, software tools, and algorithms, we expect to achieve major energy efficiency improvements, even when there is no freedom to relax end-to-end application quality of results. Indeed, OPRECOMP aims at demolishing the ultraconservative “precise” computing abstraction, replacing it with a more flexible and efficient one, namely transprecision computing

Mapping citizen science contributions to the UN Sustainable Development Goals

The UN Sustainable Development Goals (SDGs) are a vision for achieving a sustainable future. Reliable, timely, comprehensive, and consistent data are critical for measuring progress towards, and ultimately achieving, the SDGs. Data from citizen science represent one new source of data that could be used for SDG reporting and monitoring. However, information is still lacking regarding the current and potential contributions of citizen science to the SDG indicator framework. Through a systematic review of the metadata and work plans of the 244 SDG indicators, as well as the identification of past and ongoing citizen science initiatives that could directly or indirectly provide data for these indicators, this paper presents an overview of where citizen science is already contributing and could contribute data to the SDG indicator framework. The results demonstrate that citizen science is “already contributing” to the monitoring of 5 SDG indicators, and that citizen science “could contribute” to 76 indicators, which, together, equates to around 33%. Our analysis also shows that the greatest inputs from citizen science to the SDG framework relate to SDG 15 Life on Land, SDG 11 Sustainable Cities and Communities, SDG 3 Good Health and Wellbeing, and SDG 6 Clean Water and Sanitation. Realizing the full potential of citizen science requires demonstrating its value in the global data ecosystem, building partnerships around citizen science data to accelerate SDG progress, and leveraging investments to enhance its use and impact

Citizen science and the United Nations Sustainable Development Goals

Traditional data sources are not sufficient for measuring the United Nations Sustainable Development Goals. New and non-traditional sources of data are required. Citizen science is an emerging example of a non-traditional data source that is already making a contribution. In this Perspective, we present a roadmap that outlines how citizen science can be integrated into the formal Sustainable Development Goals reporting mechanisms. Success will require leadership from the United Nations, innovation from National Statistical Offices and focus from the citizen-science community to identify the indicators for which citizen science can make a real contribution

Transition Densities and Traces for Invariant Feller Processes on Compact Symmetric Spaces

We find necessary and sufficient conditions for a finite K–bi–invariant measure on a compact Gelfand pair (G, K) to have a square–integrable density. For convolution semigroups, this is equivalent to having a continuous density in positive time. When (G, K) is a compact Riemannian symmetric pair, we study the induced transition density for G–invariant Feller processes on the symmetric space X = G/K. These are obtained as projections of K–bi–invariant L´evy processes on G, whose laws form a convolution semigroup. We obtain a Fourier series expansion for the density, in terms of spherical functions, where the spectrum is described by Gangolli’s L´evy–Khintchine formula. The density of returns to any given point on X is given by the trace of the transition semigroup, and for subordinated Brownian motion, we can calculate the short time asymptotics of this quantity using recent work of Ba˜nuelos and Baudoin. In the case of the sphere, there is an interesting connection with the Funk–Hecke theorem