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Cca-Secure Key Encapsulation Mechanism Based on Factoring Assumption


In this article a key encapsulation mechanism is presented which is based on squaring function, where the input element is from QR+ N, where QR+ N denotes the signed quadratic residue group, and N is a Blum integer. The article presents the soundness, the efficiency and the proof of CCA security of the proposed mechanism

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Preventing Potential Backdoors in Bike Algorithm

REFERENCES [1] ARAGON, N.—BARRETO, P.—BETTAIEB, S.—BIDOUX, L.—BLAZY, O. DENEU-VILLE, J.-C.—GABOR.IT, P.—GUERON, S.—GUNEYSU, T—MELCHOR, C. A. et al.: BIKE: Bit Flipping Key Encapsulation, (2017). [2] BARDET, M.—DRAGOI, V.—LUQUE, J.-G.—OTMANI, A.: MDPC public key encryption scheme. In: 8th International Conference on Cryptology in Africa, Fes, Moroco April 13–15, 2010. Progress in Cryptology—AFPICACPYPT 2016 (D. Pointcheval, A. Nitaj, T. Rachidi). Lecture Notes in Comput. Sci. Vol. 9646

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Efficiency and Agility for a Modern Solution of Deterministic Multiple Source Prioritization and Validation Tasks


This article focuses on a multiple source prioritization and validation service. We describe a modern rule-based, loosely coupled solution. We follow generalization, efficiency and agility principles in application design. We show benefits and stumbling blocks in micro-service architectural style and in rule-based solutions, where even the selection task is solved through selection rules, which encapsulate the calls to Entity Services, allowing access to input-sources. We allowing the rule-based service efficiency and further local and remote input data selection scenarios for the validation Statistical Service. In particular, data virtualization technologies enable architects to use remote sourcing and further increases agility in data selection issues. Through a wide number of experimental results, we show the necessary level of attention in process implementation, data architectures and resource usage. Agility and efficiency emerge as drivers which possibly sustain the Modernization flexibility impetus. In fact, flexible services may potentially serve multiple scenarios and domains.

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Cross-task code reuse in genetic programming applied to visual learning

representation for body-brain evolution, Artificial Life 8 (3): 223-246. Howard, D. (2003). Modularization by multi-run frequency driven subtree encapsulation, in R.L. Riolo and B. Worzel (Eds.), Genetic Programming Theory and Practice , Kluwer, New York, NY, Chapter 10, pp. 155-172. Howard, D., Roberts, S.C. and Ryan, C. (2006). Pragmatic genetic programming strategy for the problem of vehicle detection in airborne reconnaissance, Pattern Recognition Letters 27 (11): 1275-1288. Hsu, W.H., Harmon, S.J., Rodriguez, E. and

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Slime Mould Games Based on Rough Set Theory

a biological substrate, Parallel Processing Letters 17(04): 455-467. Adamatzky, A. (2007b). Physarum machines: Encapsulating reaction-diffusion to compute spanning tree, Die Naturwissenschaften 94(12): 975-980. Adamatzky, A. (2010). Physarum Machines: Computers from Slime Mould, World Scientific, Singapore. Baillot, P., Danos, V., Ehrhard, T. and Regnier, L. (1997). Believe it or not, AJM’s games is a model of classical linear logic, Proceedings of the 12th Symposium on Logic in Computer Science, Warsaw, Poland, pp

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Mathematical modelling of molecule evolution in protocells

.W. (2003). Experimental models of primitive cellular compartments: Encapsulation, growth, and division, Science 302 (5645): 618-622. Joyce, G.F. (2002). The antiquity of RNA-based evolution, Nature 418 (6894): 214-221. Joyce, G. and Orgel, L. (1999). Prospects for understanding the origin of the rna world, in R.F. Gesteland, T.R. Cech and J.F. Atkins (Eds.), The RNA World , 2nd Edn., Cold Spring Harbor Laboratory Press, New York, NY, Vol. 37, pp. 49-77. Kimmel, M. and Axelrod, D. (2002). Branching Processes in

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Comparative Study of Dark Beer Before and After Freeze Drying Rehydration Cycle

-89132013000600017 (last accessed 2 April 2018). Fang, Z., Bhandari, B. (2010). Encapsulation of polyphenols: Review. Trends Food Sci. Technol ., 21 , 510–523. Ghio, S., Barresi, A. A., Rovero, G. (2000). A comparison of evaporative and conventional freezing prior to freeze-drying of fruits and vegetables. Food Bioprod. Proc ., 4 , 187–192. Hammami, C., René, F. (1997). Determination of freeze-drying process variables for strawberries. J. Food Eng ., 32 (2), 133–154. Khalloufi, S., Ratti, C. (2003). Quality deterioration of freeze-dried foods as explained

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Pancreatic Islet Transplantation and Regeneration for Diabetes mellitus Treatment

-1176. Elliott, R.B., Escobar, L., Tan, P.L., Muzina, M., Zwain, S., Buchanan, C. (2007). Live encapsulated porcine islets from a type 1 diabetic patient 9.5 yr after xenotransplantation. Xenotransplantation , 14(2), 157-161. Farney, A.C., Najarian, J.S., Nakhleh, R.E., Lloveras, G., Field, M.J., Gores, P.F., Sutherland, D.E. (1991). Autotransplantation of dispersed pancreatic islet tissue combined with total or near-total pancreatectomy for treatment of chronic pancreatitis. Surgery , 110(2), 427-437. Finegood, D

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The Triaxiality Role in the Spin-Orbit Dynamics of a Rigid Body

_{\sigma_2}=c_{\sigma_2}(c_\iota;\tau_2) \end{array}$$ whose graph is studied in the Cartesian plane Oc ι c σ . Notice that the triaxiality of B 1 is encapsulated in the ratios τ 1 and τ 2 respecting some conditions as 0 < τ 1 < τ 2 < 1 and 1 < τ 1 + τ 2 . On figure 6 we distinguish curves of equilibria. A complete analysis of these curves is a work on progress in [ 6 ]. Fig. 6 (Left) triaxiality region with τ 1 = 0.35 and τ 2 = 0.9. (Right) Curves c σ 1 and c σ 2 restricted to interval [0, 1] for ζ = 0.7. A partial study of

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