307 research outputs found

    The Level 0 Trigger Decision Unit for the LHCb experiment

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    The Level 0 Decision Unit (L0DU) is one of the main components of the first trigger level (named level 0) of the LHCb experiment. This 16 layers custom board receives data from the calorimeter, muon and pile-up sub-triggers and computes the level 0 decision, reducing the rate from 40MHz to 1MHz. The processing is implemented in FPGA using a 40MHz synchronous pipelined architecture. The L0DU algorithm is fully configured via the Experiment Control System without any firmware reprogramming. An overall L0DU latency of less than 450ns has been achieved. The board was installed in the experimental area in April 2007 and since then has played a major role in the commissioning of the experiment

    On the universality of small scale turbulence

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    The proposed universality of small scale turbulence is investigated for a set of measurements in a cryogenic free jet with a variation of the Reynolds number (Re) from 8500 to 10^6. The traditional analysis of the statistics of velocity increments by means of structure functions or probability density functions is replaced by a new method which is based on the theory of stochastic Markovian processes. It gives access to a more complete characterization by means of joint probabilities of finding velocity increments at several scales. Based on this more precise method our results call in question the concept of universality.Comment: 4 pages, 4 figure

    Level 0 trigger decision unit for the LHCb experiment

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    The Level-0 Decision Unit (L0DU) is the central part of the first trigger level of the LHCb detector. The L0DU receives information from the Calorimeter, Muon and Pile-Up sub-triggers, with fixed latencies, at 40 MHz via 24 high speed optical fiber links running at 1.6 Gb/s. The L0DU performs simple physics algorithm to compute the decision in order to reduce the data flow down to 1 MHz for the next trigger level and a L0Block is constructed. The processing is implemented in FPGA using a 40 MHz synchronous pipelined architecture. The algorithm can be easily configured with the Experiment Control System (ECS) without FPGA reprogramming. The L0DU is a 16 layer custom board

    Towards a Sustainable Governance of Information Systems: Devising a Maturity Assessment Tool of Eco-Responsibility Inspired by the Balanced Scorecard

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    Part 3: Section 2: Sustainable and Responsible InnovationInternational audienceThe assessment of the maturity of Information System (IS) regarding its contribution to corporate social responsibility policy is considered as a stake for organizations. However, few research efforts have been dedicated to this evaluation and even less to the elaboration of a management tool. This paper adopts an engineering perspective to develop a performance assessment approach in this field. Theoretically, this communication (1) mobilizes the methodology of engineering research to build a measurement system of the IS maturity in relation to the economic, social and environmental performance, (2) extends the researches about the sustainable balanced scorecard (SBSC) to the field of IS governance. Practically, this study provides organizations with a global approach to this complex phenomenon as well as a guide to assess it. The originality of this research lies in the application of the conceptual framework of the SBSC to a new research domain

    Towards an integrated crowdsourcing definition

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    Crowdsourcing is a relatively recent concept that encompasses many practices. This diversity leads to the blurring of the limits of crowdsourcing that may be identified virtually with any type of internet-based collaborative activity, such as co-creation or user innovation. Varying definitions of crowdsourcing exist, and therefore some authors present certain specific examples of crowdsourcing as paradigmatic, while others present the same examples as the opposite. In this article, existing definitions of crowdsourcing are analysed to extract common elements and to establish the basic characteristics of any crowdsourcing initiative. Based on these existing definitions, an exhaustive and consistent definition for crowdsourcing is presented and contrasted in 11 cases.Estelles Arolas, E.; González-Ladrón-De-Guevara, F. (2012). Towards an integrated crowdsourcing definition. Journal of Information Science. 32(2):189-200. doi:10.1177/0165551512437638S189200322Vukovic, M., & Bartolini, C. (2010). Towards a Research Agenda for Enterprise Crowdsourcing. Leveraging Applications of Formal Methods, Verification, and Validation, 425-434. doi:10.1007/978-3-642-16558-0_36Brabham, D. C. (2008). Crowdsourcing as a Model for Problem Solving. Convergence: The International Journal of Research into New Media Technologies, 14(1), 75-90. doi:10.1177/1354856507084420Vukovic, M. (2009). Crowdsourcing for Enterprises. 2009 Congress on Services - I. doi:10.1109/services-i.2009.56Doan, A., Ramakrishnan, R., & Halevy, A. Y. (2011). Crowdsourcing systems on the World-Wide Web. Communications of the ACM, 54(4), 86. doi:10.1145/1924421.1924442Brabham, D. C. (2008). Moving the crowd at iStockphoto: The composition of the crowd and motivations for participation in a crowdsourcing application. First Monday, 13(6). doi:10.5210/fm.v13i6.2159Huberman, B. A., Romero, D. M., & Wu, F. (2009). Crowdsourcing, attention and productivity. Journal of Information Science, 35(6), 758-765. doi:10.1177/0165551509346786Andriole, S. J. (2010). Business impact of Web 2.0 technologies. Communications of the ACM, 53(12), 67. doi:10.1145/1859204.1859225Denyer, D., Tranfield, D., & van Aken, J. E. (2008). Developing Design Propositions through Research Synthesis. Organization Studies, 29(3), 393-413. doi:10.1177/0170840607088020Egger, M., Smith, G. D., & Altman, D. G. (Eds.). (2001). Systematic Reviews in Health Care. doi:10.1002/9780470693926Tatarkiewicz, W. (1980). A History of Six Ideas. doi:10.1007/978-94-009-8805-7Cosma, G., & Joy, M. (2008). Towards a Definition of Source-Code Plagiarism. IEEE Transactions on Education, 51(2), 195-200. doi:10.1109/te.2007.906776Brabham, D. C. (2009). Crowdsourcing the Public Participation Process for Planning Projects. Planning Theory, 8(3), 242-262. doi:10.1177/1473095209104824Alonso, O., & Lease, M. (2011). Crowdsourcing 101. Proceedings of the fourth ACM international conference on Web search and data mining - WSDM ’11. doi:10.1145/1935826.1935831Bederson, B. B., & Quinn, A. J. (2011). Web workers unite! addressing challenges of online laborers. Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems - CHI EA ’11. doi:10.1145/1979742.1979606Grier, D. A. (2011). Not for All Markets. Computer, 44(5), 6-8. doi:10.1109/mc.2011.155Heer, J., & Bostock, M. (2010). Crowdsourcing graphical perception. Proceedings of the 28th international conference on Human factors in computing systems - CHI ’10. doi:10.1145/1753326.1753357Heymann, P., & Garcia-Molina, H. (2011). Turkalytics. Proceedings of the 20th international conference on World wide web - WWW ’11. doi:10.1145/1963405.1963473Kazai, G. (2011). In Search of Quality in Crowdsourcing for Search Engine Evaluation. Advances in Information Retrieval, 165-176. doi:10.1007/978-3-642-20161-5_17La Vecchia, G., & Cisternino, A. (2010). Collaborative Workforce, Business Process Crowdsourcing as an Alternative of BPO. Lecture Notes in Computer Science, 425-430. doi:10.1007/978-3-642-16985-4_40Liu, E., & Porter, T. (2010). Culture and KM in China. VINE, 40(3/4), 326-333. doi:10.1108/03055721011071449Oliveira, F., Ramos, I., & Santos, L. (2010). Definition of a Crowdsourcing Innovation Service for the European SMEs. Lecture Notes in Computer Science, 412-416. doi:10.1007/978-3-642-16985-4_37Porta, M., House, B., Buckley, L., & Blitz, A. (2008). Value 2.0: eight new rules for creating and capturing value from innovative technologies. Strategy & Leadership, 36(4), 10-18. doi:10.1108/10878570810888713Ribiere, V. M., & Tuggle, F. D. (Doug). (2010). Fostering innovation with KM 2.0. VINE, 40(1), 90-101. doi:10.1108/03055721011024955Sloane, P. (2011). The brave new world of open innovation. Strategic Direction, 27(5), 3-4. doi:10.1108/02580541111125725Wexler, M. N. (2011). Reconfiguring the sociology of the crowd: exploring crowdsourcing. International Journal of Sociology and Social Policy, 31(1/2), 6-20. doi:10.1108/01443331111104779Whitla, P. (2009). Crowdsourcing and Its Application in Marketing Activities. Contemporary Management Research, 5(1). doi:10.7903/cmr.1145Yang, J., Adamic, L. A., & Ackerman, M. S. (2008). Crowdsourcing and knowledge sharing. Proceedings of the 9th ACM conference on Electronic commerce - EC ’08. doi:10.1145/1386790.1386829Brabham, D. C. (2010). MOVING THE CROWD AT THREADLESS. Information, Communication & Society, 13(8), 1122-1145. doi:10.1080/13691181003624090Giudice, K. D. (2010). Crowdsourcing credibility: The impact of audience feedback on Web page credibility. Proceedings of the American Society for Information Science and Technology, 47(1), 1-9. doi:10.1002/meet.14504701099Stewart, O., Huerta, J. M., & Sader, M. (2009). Designing crowdsourcing community for the enterprise. 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    Évolution de la contribution française à l'upgrade de LHCb

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    Ce document décrit l'évolution de la contribution française à l'upgrade de LHCb. Il s'inscrit dans le prolongement de la Lettre d'Intention [1], du Framework TDR [2], du document soumis au Conseil scientifique de l'IN2P3 le 21 juin 2012 [3], et des Technical Design Reports soumis au LHCC en novembre 2013 [4, 5]. Ces derniers concernent le détecteur de vertex et les détecteurs utilisés dans l'identification des particules. La contribution française s'est cristallisée autour de quatre grands projets : l'électronique front-end des calorimètres et du trajectographe à fibres scintillantes, le système de déclenchement de premier niveau et la carte de lecture à 40MHz commune à l'ensemble des sous-systèmes. Dans ce document nous décrivons les contributions envisagées et les ressources nécessaires pour mener à bien ces projets
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