Xxx and X Sample Clauses

Xxx and X. Xxx, “A key recovery attack on discrete log-based schemes using a prime order subgroup,” In CRYPTO 97, pp.249-263, 1997.
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Xxx and X. Xxx, \A key recovery attack on discrete log-based schemes using a prime order subgroup," Crypto 97, pp.249-263, 1997 [25] X.Xxxxx, X.Xxxx, X.Xxxxxxx, and X.Xxxxxxx, \Reducing risks from poorly chosen keys," ACM Symposium on Operating System Principles, 1989, pp.14-18 [26] X.Xxxxx, \Open key exchange: how to defeat dictionary attacks without encrypting public keys," The Security Protocol Workshop '97, April 7-9, 1997 [27] X.XxxXxxxxx amd X.Xxxxxxxxxxx, \Secure network authentication with password iden- ti cation," Presented to IEEE P1363a, August 1999
Xxx and X. Xxxxxxxx assert, “It is imperative that counselors understand how individuals shape themselves rather than trying to shape them into being healthy within a Western context.”1 One example of this can be seen in the different notions of self that SGKAs must navigate on a regular basis. As we will see, several clients of RDM come to find degrees of self-acceptance and freedom that help them see themselves more clearly and distinctly. But does the acceptance of Western ideals come at too high a cost? This chapter begins with the juxtaposition of Western and Eastern notions of self. This conflicting view of self often gives rise to a sense of shame. We will define shame through the views of Western and Eastern theologians and see how it connects to the lives of some SGKA clients in RDM. The shame seen in the clients’ lives before their arrival to RDM presents concrete examples of this complex emotion. For the sake of clarity and deeper analysis, I will focus on the voices of Ava and Xxxxx, two SGKAs of the four clients interviewed. Ava and Jason’s experiences with shame prior to and during their time in RDM act as examples for the concepts and theories discussed. Psychological theorists D.W. Winnicott and X.X. Xxxx ground our analysis of what is
Xxx and X. Xxxxxx. 2002. On issues of instance selec- tion. Data Mining and Knowledge Discovery, 6(2):115– 130. X. Xx, X. Xxx, X. Xx, X. Xxx, and X. Xx. 2012. Phrase- based data selection for language model adaptation in spoken language translation. In 2012 8th International Symposium on Chinese Spoken Language Processing (ISCSLP), pages 193–196, Hong Kong, China.
Xxx and X. Xxxxxxx. Scheduling algorithms for multiprogramming in a hard-real-time environment. J. ACM, 20(1):46–61, 1973. [81] X. X. Xxxxx and T. Kanade. An iterative image registration technique with an application to stereo vision. In Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2, IJCAI’81, pages 674–679, San Francisco, CA, USA, 1981. Xxxxxx Xxxxxxxx Publishers Inc. [82] X. Xxxx and X. Xxxxxx. Neurocomputing: foundations of research. chapter Cooperative computation of stereo disparity, pages 259–267. MIT Press, Cambridge, MA, USA, 1988. [83] X. Xxxxxxxx and X. Xxxx. Knapsack Problems: Algorithms and Computer Implementations. Xxxx Xxxxx & Sons, 1 edition, 1990. [84] X. Xxxxxxxx. Embedded System Design. Springer, 2 edition, 2006. [85] X. Xxxxxxxxxxx, X. Xxxxxxx, X. Xxxxxxxx, X. Xxxxxxx Mesa, and X. Xxxxxxx. Parallel scalability of video decoders. J. Signal Process. Syst., 57(2):173–194, Nov. 2009.
Xxx and X. Xxxxxxxxx, “Comparison of the Hardware Performance of the AES Candidates using Reconfigurable Hardware,” Proc. 3rd Advanced Encryption Standard Conference, New York, April 2000, available at xxxx://xxx.xxx.xxx/crypto/publications.htm.
Xxx and X. X. Xxxxxx. Objective Bayesian analysis for the multivariate normal model. Bayesian Statistics, 8:525–562, 2007.
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Xxx and X. Xxxxxxxx. Fault Tolerance: Principles and Practice. Springer-Verlag New York, Inc., Secaucus, NJ, USA, 1990.
Xxx and X. X. Kim, “Real-time broadcast algorithm for mobile computing”, The Journal of Systems and Software, vol. 69, no. 2, pp. 173-181, 2004. [5] X. Xxxxxx and M. E. Xxxxxxx, “New directions in cryptography”, IEEE Transactions on Information Theory, vol. IT-22, no. 6, pp. 644-654, 1976. [6] Xxxxxxx Xxx, Xxxxxx Xxxxxx, and Xxxx Xxxxxx, “Group key agreement efficient in communication”, IEEE Transactions on Computers, vol. 53, no. 7, pp. 905-921, 2004. [7] Xxxxxxx Xxx, Xxxxxxx Xxx, Xxxxxxx Xxx, and Xxx-Xxxx Xxx, “An efficient tree-based group key agreement using bilinear map”, in Proceedings ACNS, LNCS 2846, pp. 357-371, 2003. [8] Xxxxxx Xxxxxxx, Xxxxxxx Xxxxxx, and Xxxxx Xxxxxxxxx, “EHBT: An efficient protocol for group key management”, in Proceedings NGC, LNCS 2233, pp. 159-171, Oct. 2001. [9] Xxxxx Xxxx and Xxxx Xxxxxxx, “Tree-based group key agreement framework for mobile ad-hoc networks”, Elsevier, Future Generation Computer Systems, vol. 23, no. 6, pp. 787-803, 2007. [10] Xxxx-xxx Xxx, Xxxx Xxx Xxxxx, and Xxxxxxx Xxx, “Tree-based group key agreement protocol using pairing”, Journal of The Korea Institute of Information Security and Cryptology, vol. 13, no. 3, pp. 101-110, 2003. [11] Xxxxxxxxx Xxxxx and Xxxxxx Xxxxxxxx, “Ternary tree based group key agreement protocol over elliptic curve for dynamic group”, International Journal of Computer Applications (0975-888), vol. 86, no. 7, pp. 17-25, 2014. [12] Xxx Xxxxxxx, Xxxxx Xxxxx, and Xxxx Xxxxxxxxx, “Scalable authenticated tree based group key exchange for ad-hoc groups”, in Proceedings FC and USEC, LNCS 4886, pp. 104-118, 2007. [13] Xxxxxxxx Xxx, Xxxxxx Xxxx, Xxxxxxxxx Xxx, Xxx Xxxx, Xxx Mo Xxx, and Xxxxxx Xxx, “Infringing key authentication of an ID-based group key exchange protocol using binary key trees”, in Proceedings KES /WIRN, Part I, LNAI 4692, pp. 672-679, 2007. [14] Xxxxxxx Xxxxx, Xxxxxx Xxx, Xxxxxxx Xxxx, and Xxx Xx, “Scalable group key management protocol based on key material transmitting tree”, in Proceedings ISPEC, LNCS 4464, pp. 301-313, 2007. [15] X. Xxxxxx and X. Xxxxx, “Communication complexity of group key distribution”, in Proceedings CCS, pp. 1-6, 1998. [16] P.S.L.M. Xxxxxxx, X.X. Xxx, X. Xxxx, and X. Xxxxx, “Efficient algorithms for pairing-based cryptosystems”, in Proceedings Advances in Cryptology-Crypto, LNCS 2442, pp. 354-368, 2002. [17] Xxxxxx X. Xxxxxxx, Xxxx X. xxx Xxxxxxxx, and Xxxxx X. Xxxxxxxx,
Xxx and X. X. Xxxxxx Condition 1 2 3 4 5 6 7 8 9 10 11 12 234 3×15* 0×97 4×31** — 2×18 1×16 3×34** 56 — 0×02 3×00 — 3×17* — 0×15 — 0×99 2×03 — 4×33** — 1×31 3×02* 7 1×30 — 1×85 0×33 — 3×01 1×32 — 1×70 8 5×29 2×14 4×32** 0×98 5×31** 2×29 3×99** 9 0×50 — 2×65 — 0×47 — 3×81** 0×52 — 2×50 — 0×80 — 4×79** 10 1×98 — 1×17 1×01 — 2×33 2×00 — 1×02 0×68 — 3×31* 1×48 11 2×47 — 0×68 1×50 — 1×84 2×49 — 0×53 1×17 — 2×82 1×97 0×49 12 3×82** 0×67 2×85 — 0×49 3×84** 0×82 2×52 — 1×47 3×32* 1×84 1×35 13,14,15² 1×81 — 1×34 0×84 — 2×50* 1×83 — 1×19 0×51 — 3×48** 1×31 — 0×17 — 0×66 — 2×10 *Signi®cant at 0×05 level. **Signi®cant at 0×01. ² Pooled data from experimental conditions 13, 14 and 15. Frequency-weighted filter 465 eSect variable G was therefore introduced into the regression analysis, with data from the current study coded as — 1 and the pilot data coded as 1. The resulting discomfort model was:
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