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Let Substr_k(X) denote the set of length-k substrings of a given string X for a given integer k > 0. We study the following basic string problem, called z-Shortest 𝒮_k-Equivalent Strings: Given a set 𝒮_k of n length-k strings and an integer z > 0, list z shortest distinct strings T₁,…,T_z such that Substr_k(T_i) = 𝒮_k, for all i ∈ [1,z]. The z-Shortest 𝒮_k-Equivalent Strings problem arises naturally as an encoding problem in many real-world applications; e.g., in data privacy, in data compression, and in bioinformatics. The 1-Shortest 𝒮_k-Equivalent Strings, referred to as Shortest 𝒮_k-Equivalent String, asks for a shortest string X such that Substr_k(X) = 𝒮_k. Our main contributions are summarized below: - Given a directed graph G(V,E), the Directed Chinese Postman (DCP) problem asks for a shortest closed walk that visits every edge of G at least once. DCP can be solved in 𝒪̃(|E||V|) time using an algorithm for min-cost flow. We show, via a non-trivial reduction, that if Shortest 𝒮_k-Equivalent String over a binary alphabet has a near-linear-time solution then so does DCP. - We show that the length of a shortest string output by Shortest 𝒮_k-Equivalent String is in 𝒪(k+n²). We generalize this bound by showing that the total length of z shortest strings is in 𝒪(zk+zn²+z²n). We derive these upper bounds by showing (asymptotically tight) bounds on the total length of z shortest Eulerian walks in general directed graphs. - We present an algorithm for solving z-Shortest 𝒮_k-Equivalent Strings in 𝒪(nk+n²log²n+zn²log n+|output|) time. If z = 1, the time becomes 𝒪(nk+n²log²n) by the fact that the size of the input is Θ(nk) and the size of the output is 𝒪(k+n²). LIPIcs, Vol. 223, 33rd Annual Symposium on Combinatorial Pattern Matching (CPM 2022), pages 16:1-16:17

This is the abstract volume of the Citizen Science SDG Conference titled "Knowledge for Change: A decade of Citizen Science (2020-2030) in support of the SDGs" that took place on 14.-15. October 2020 as a hybrid conference (in Berlin and online). This conference was an official event of Germany’s 2020 EU Council presidency. The conference took place as part of the CS-SDG project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101000014.

In early 2020, the EOSC Community took another crucial step on the road to the development and implementation of the European Open Science Cloud, as seven key EOSC-related Horizon 2020 projects signed a Collaboration Agreement in support of the EOSC Governance. The Agreement involves all the projects supported within the INFRAEOSC-05-2018-2019 call. The Agreement provides a useful framework for all parties to collaborate on a wide range of topics, in order to enhance synergies in all mutual activities related to the EOSC. The projects also agreed on a Joint Activity Plan, which will guide them towards the first iteration of EOSC. Overlaps and complementarities among projects were identified, as well as specific areas for potential cooperation, ultimately aimed at the development of a common strategy to synchronise activities with the EOSC Working Groups. Between April and May 2020, EOSCsecretariat.eu collected the position papers on EOSC compiled by the INFRAEOSC 5b projects, the subgroup that specifically includes the four regional projects covering all corners of Europe, as well as the thematic project ExPaNDS. We would like to thank the five Horizon 2020 projects which have contributed to the making of this compilation of EOSC position papers: EOSC-Nordic (GA No. 857652), EOSC-Pillar (GA No. 857650), EOSC-synergy (GA No. 857647), ExPaNDS (GA No. 857641), and NI4OS-Europe (GA No. 857645).

An article about the Powerskin+ project published in the European Energy Innovation Magazine.

Our third newsletter including information about our main achievements during the second 6 months project period.

This is the conference programme of the Citizen Science SDG Conference titled "Knowledge for Change: A decade of Citizen Science (2020-2030) in support of the SDGs" that took place on 14.-15. October 2020 as a hybrid conference (in Berlin and online). This conference was an official event of Germany’s 2020 EU Council presidency. The conference took place as part of the CS-SDG project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101000014.

An article about the Powerskin+ project in the Open Access Government publication.

In this article, we present Cellulo, a novel robotic platform that investigates the intersection of three ideas for robotics in education: designing the robots to be versatile and generic tools; blending robots into the classroom by designing them to be pervasive objects and by creating tight interactions with (already pervasive) paper; and finally considering the practical constraints of real classrooms at every stage of the design. Our platform results from these considerations and builds on a unique combination of technologies: groups of handheld haptic-enabled robots, tablets and activity sheets printed on regular paper. The robots feature holonomic motion, haptic feedback capability and high accuracy localization through a microdot pattern overlaid on top of the activity sheets, while remaining affordable (robots cost about EUR 125 at the prototype stage) and classroom-friendly. We present the platform and report on our first interaction studies, involving about 230 children.

Object recognition and classification as well as obstacle distance calculation are of the utmost importance in today’s autonomous driving systems. One such system designed to detect obstacle and track intrusion in railways is considered in this paper. The heart of this system is the decision support system (DSS), which is in charge of making complex decisions, important for a safe and efficient autonomous train drive based on the information obtained from various sensors. DSS determines the object class and its distance from a running train by analyzing sensor images using machine learning algorithms. For the quality training of these machine learning models, it is necessary to provide training sets with images of adequate quality, which is often not the case in real-world railway applications. Furthermore, the images of insufficient quality should not be processed at all in order to save computational time. One of the most common types of distortion which occurs in real-world conditions (train movement and vibrations, movement of other objects, bad weather conditions, and day and night image differences) is blur. This paper presents an improved edge-detection method for the automatic detection and rejection of images of inadequate quality regarding the blur level. The proposed method, with its improvements convenient for railway application, is compared with several other state-of-the-art methods for blur detection, and its superior overall performance is demonstrated.

High-energy cosmic rays, impinging on the atmosphere of the Earth initiate cascades of secondary particles, the extensive air showers. The electrons and positrons in the air shower emit electromagnetic radiation. This emission is detected with the LOFAR radio telescope in the frequency range from 30 to 240 MHz. The data are used to determine the properties of the incoming cosmic rays. The radio technique is now routinely used to measure the arrival direction, the energy, and the particle type (atomic mass) of cosmic rays in the energy range from 1017 to 1018 eV. This energy region is of particular astrophysical interest, since in this regime a transition from a Galactic to an extra-galactic origin of cosmic rays is expected. For illustration, the LOFAR results are used to set constraints on models to describe the origin of high-energy cosmic rays.