Strong Secrecy on a Class of Degraded Broadcast Channels Using Polar Codes

Different polar coding schemes are proposed for the memoryless degraded broadcast channel under different reliability and secrecy requirements: layered decoding and/or layered secrecy. In this setting, the transmitter wishes to send multiple messages to a set of legitimate receivers keeping them masked from a set of eavesdroppers. The layered decoding structure requires receivers with better channel quality to reliably decode more messages, while the layered secrecy structure requires eavesdroppers with worse channel quality to be kept ignorant of more messages. The implementation of the proposed polar coding schemes is discussed and their performance is evaluated by simulations for the symmetric degraded broadcast channel.Comment: 35 pages. Published in "MDPI Entropy". A short version of this paper had been accepted to the 3rd Workshop on Physical-Layer Methods for Wireless Security, IEEE CNS 201

Polar Coding for Common Message Only Wiretap Broadcast Channel

A polar coding scheme is proposed for the Wiretap Broadcast Channel with two legitimate receivers and one eavesdropper. We consider a model in which the transmitter wishes to send a private and a confidential message that must be reliably decoded by the receivers, and the confidential message must also be (strongly) secured from the eavesdropper. The coding scheme aims to use the optimal rate of randomness and does not make any assumption regarding the symmetry or degradedness of the channel. This paper extends previous work on polar codes for the wiretap channel by proposing a new chaining construction that allows to reliably and securely send the same confidential message to two different receivers. This construction introduces new dependencies between the random variables involved in the coding scheme that need to be considered in the secrecy analysis.Comment: A short version of this paper is submitted to ISIT1

Differences in kicking velocity and kicking deficit in young elite soccer players

El objetivo de este estudio fue examinar la evolución del rendimiento máximo de golpeo de balón a lo largo de la edad en futbolistas jóvenes de élite. Un total de 175 fueron divididos en 11 grupos edad (U-9 hasta U-19), además del equipo filial del club (U-23). Se registró la velocidad máxima de golpeo con la pierna dominante y no dominante mediante radar. El déficit de golpeo fue calculado para comparar el rendimiento entre ambas piernas. La velocidad máxima de golpeo aumenta progresivamente de forma significativa desde U-9 hasta U-16 con la pierna dominante y hasta U-18 con la no dominante, y sigue aumentando de forma no significativa hasta U-23. La etapa con mayor incremento de la velocidad de golpeo fue entre U-13 y U-16. Existe un déficit de golpeo con la pierna no dominante y sus valores permanecen estables (9.43%-18.18%) sin cambios significativos desde U-9 hasta U-23The purpose of this current study was to examine the age-related differences in kicking performance with both legs in 175 youth soccer players. Players from the development programme of a professional club were grouped according to their respective under-age team (U-9 to U-18), in addition to the club’s second team (U-23). Maximal kicking velocity with the preferred and non-preferred leg was recorded using a Doppler radar gun. Kicking deficit was calculated to compare side-to-side performance. Maximal kicking velocity improved progressively from the U-9 to U-16 age groups for the preferred leg and from U-16 to U-18 for the non-preferred leg, and continued to improve moderately but non-statistically significant until U-23. The stage of greatest kicking velocity development was between 13 and 16 years of age. There is a kicking deficit with the non-preferred leg and its values remain steady (9.43%-18.18%) without significant changes in players from U-9 to U-23 categorie

Quasars Clustering at z approx 3 on Scales less sim 10 h^{-1} Mpc

We test the hypothesis whether high redshift QSOs would preferentially appear in small groups or pairs, and if they are associated with massive, young clusters. We carried out a photometric search for \Ly emitters on scales $\lesssim 10 h^{-1}$ Mpc, in the fields of a sample of 47 $z\approx3$ known QSOs. Wide and narrow band filter color-magnitude diagrams were generated for each of the $6'.6\times6'.6$ fields. A total of 13 non resolved objects with a significant color excess were detected as QSO candidates at a redshift similar to that of the target. All the candidates are significantly fainter than the reference QSOs, with only 2 of them within 2 magnitudes of the central object. Follow-up spectroscopic observations have shown that 5, i.e., about 40% of the candidates, are QSOs at the same redshift of the target; 4 are QSOs at different z (two of them probably being a lensed pair at z = 1.47); 2 candidates are unresolved HII galaxies at z$\sim$0.3; one unclassified and one candidate turned out to be a CCD flaw. These data indicate that at least 10% of the QSOs at z$\sim$3 do have companions. We have also detected a number of resolved, rather bright \Ly Emitter Candidates. Most probably a large fraction of them might be bright galaxies with [OII] emission, at z$\approx$ 0.3. The fainter population of our candidates corresponds to the current expectations. Thus, there are no strong indication for the existence of an overdensity of \Ly galaxies brighter than m $\approx$ 25 around QSOs at $z\approx$ 3.Comment: 29 pages, 8 figures, tar gzip LaTex file, accepted to appear in Ap

Errors and Artefacts in Agent-Based Modelling

The objectives of this paper are to define and classify different types of errors and artefacts that can appear in the process of developing an agent-based model, and to propose activities aimed at avoiding them during the model construction and testing phases. To do this in a structured way, we review the main concepts of the process of developing such a model – establishing a general framework that summarises the process of designing, implementing, and using agent-based models. Within this framework we identify the various stages where different types of errors and artefacts may appear. Finally we propose activities that could be used to detect (and hence eliminate) each type of error or artefact.Verification, Replication, Artefact, Error, Agent-Based Modelling, Modelling Roles

Genetic algorithms for the scheduling in additive manufacturing

[EN] Genetic Algorithms (GAs) are introduced to tackle the packing problem. The scheduling in Additive Manufacturing (AM) is also dealt with to set up a managed market, called “Lonja3D”. This will enable to determine an alternative tool through the combinatorial auctions, wherein the customers will be able to purchase the products at the best prices from the manufacturers. Moreover, the manufacturers will be able to optimize the production capacity and to decrease the operating costs in each case.This research has been partially financed by the project: “Lonja de Impresión 3D para la Industria 4.0 y la Empresa Digital (LONJA3D)” funded by the Regional Government of Castile and Leon and the European Regional Development Fund (ERDF, FEDER) with grant VA049P17Castillo-Rivera, S.; De Antón, J.; Del Olmo, R.; Pajares, J.; López-Paredes, A. (2020). Genetic algorithms for the scheduling in additive manufacturing. International Journal of Production Management and Engineering. 8(2):59-63. https://doi.org/10.4995/ijpme.2020.12173OJS596382Ahsan, A., Habib, A., Khoda, B. (2015). Resource based process planning for additive manufacturing. Computer-Aided Design, 69, 112-125. https://doi.org/10.1016/j.cad.2015.03.006Araújo, L., Özcan, E., Atkin, J., Baumers, M., Tuck, C., Hague, R. (2015). Toward better build volume packing in additive manufacturing: classification of existing problems and benchmarks. 26th Annual International Solid Freeform Fabrication Symposium - an Additive Manufacturing Conference, 401-410.Berman, B. (2012). 3-D printing: The new industrial revolution. Business Horizons, 55: 155-162. https://doi.org/10.1016/j.bushor.2011.11.003Canellidis, V., Dedoussis, V., Mantzouratos, N., Sofianopoulou, S. (2006). Preprocessing methodology for optimizing stereolithography apparatus build performance. Computers in Industry, 57, 424-436. https://doi.org/10.1016/j.compind.2006.02.004Chergui, A., Hadj-Hamoub, K., Vignata, F. (2018). Production scheduling and nesting in additive manufacturing. Computers & Industrial Engineering, 126, 292-301. https://doi.org/10.1016/j.cie.2018.09.048Demirel, E., Özelkan, E.C., Lim, C. (2018). Aggregate planning with flexibility requirements profile. International Journal of Production Economics, 202, 45-58. https://doi.org/10.1016/j.ijpe.2018.05.001Fera, M., Fruggiero, F., Lambiase, A., Macchiaroli, R., Todisco, V. (2018). A modified genetic algorithm for time and cost optimization of an additive manufacturing single-machine scheduling. International Journal of Industrial Engineering Computations, 9, 423-438. https://doi.org/10.5267/j.ijiec.2018.1.001Hopper, E., Turton, B. (1997). Application of genetic algorithms to packing problems - A Review. Proceedings of the 2nd Online World Conference on Soft Computing in Engineering Design and Manufacturing, Springer Verlag, London, 279-288. https://doi.org/10.1007/978-1-4471-0427-8_30Ikonen, I., Biles, W.E., Kumar, A., Wissel, J.C., Ragade, R.K. (1997). A genetic algorithm for packing three-dimensional non-convex objects having cavities and holes. ICGA, 591-598.Kim, K.H., Egbelu, P.J. (1999). Scheduling in a production environment with multiple process plans per job. International Journal of Production Research, 37, 2725-2753. https://doi.org/10.1080/002075499190491Lawrynowicz, A. (2011). Genetic algorithms for solving scheduling problems in manufacturing systems. Foundations of Management, 3(2), 7-26. https://doi.org/10.2478/v10238-012-0039-2Li, Q., Kucukkoc, I., Zhang, D. (2017). Production planning in additive manufacturing and 3D printing. Computers and Operations Research, 83, 157-172. https://doi.org/10.1016/j.cor.2017.01.013Milošević, M., Lukić, D., Đurđev, M., Vukman, J., Antić, A. (2016). Genetic Algorithms in Integrated Process Planning and Scheduling-A State of The Art Review. Proceedings in Manufacturing Systems, 11(2), 83-88.Pour, M.A., Zanardini, M., Bacchetti, A., Zanoni, S. (2016). Additive manufacturing impacts on productions and logistics systems. IFAC, 49(12), 1679-1684. https://doi.org/10.1016/j.ifacol.2016.07.822Wilhelm, W.E., Shin, H.M. (1985). Effectiveness of Alternate Operations in a Flexible Manufacturing System. International Journal of Production Research, 23(1), 65-79. https://doi.org/10.1080/00207548508904691Xirouchakis, P., Kiritsis, D., Persson, J.G. (1998). A Petri net Technique for Process Planning Cost Estimation. Annals of the CIRP, 47(1), 427-430. https://doi.org/10.1016/S0007-8506(07)62867-4Zhang, Y., Bernard, A., Gupta, R.K., Harik, R. (2014). Evaluating the design for additive manufacturing: a process planning perspective. Procedia CIRP, 21, 144-150. https://doi.org/10.1016/j.procir.2014.03.17