Výsledky vyhledávání - acm: c.: computer system organizacia/c.4: performance of system/c.4.3: modeling techniques*

Upřesnit hledání
  1. 1
  2. 2
  3. 3

    Zdroj: Scientific Papers: Animal Science & Biotechnologies / Lucrari Stiintifice: Zootehnie si Biotehnologii. 2024, Vol. 57 Issue 1, p1-36. 36p.

    Plný text ve formátu PDF
  4. 4
  5. 5

    Autoři: Kratt, J. Spicker, M. Guayaquil, A. a další

    Zdroj: Computer Graphics Forum. May2015, Vol. 34 Issue 2, p361-372. 12p. 8 Color Photographs, 2 Black and White Photographs, 4 Diagrams, 3 Charts, 1 Graph.

  6. 6
  7. 7
  8. 8
  9. 9

    Thesis Advisors: Vieira, Flávio Henrique Teles, Carvalho, Cedric Luiz de, Brito, Leonardo da Cunha

    Zdroj: Biblioteca Digital de Teses e Dissertações da UFGUniversidade Federal de GoiásUFG.

    Popis souboru: application/pdf

    Relation: -5088589215393046129; 600; -7705723421721944646; -4730207349379833806; 2075167498588264571; AQUINO, V. A.; BARRIA, J. A. Multiresolution fir neural-network-based learning algorithm applied to network traffic prediction. IEEE Transactions on Systems, v. 36, n. 2, p. 208–220, 2006. Citado na p´agina 69. BEZDEK, J. Fuzzy models What are they, and why? Fuzzy Systems, IEEE Transactions on, v. 1, n. 1, p. 1–6, 1993. ISSN 1063-6706. Citado 2 vezes nas p´aginas 17 e 55. CHEN, B.; LIU, X.; TONG, S. Adaptive Fuzzy Output Tracking Control of MIMO Nonlinear Uncertain Systems. Fuzzy Systems, IEEE Transactions on, v. 15, n. 2, p. 287–300, April 2007. Citado na p´agina 78. CHEN, B.-S.; PENG, S.-C.; WANG, K.-C. Traffic modeling, prediction, and congestion control for high-speed networks: a fuzzy ar approach. Fuzzy Systems, IEEE Transactions on, v. 8, n. 5, p. 491–508, 2000. Citado na p´agina 55. CHEN, T. M.; LIU, S. S.; SAMALAM, V. K. The Available Bit Rate Service for Data in ATM Networks. Comm. Mag., v. 34, n. 5, p. 56–58, 63–71, maio 1996. Citado 3 vezes nas p´aginas 79, 80 e 89. CHUI, C. K. An Introduction to Wavelets. San Diego, CA, USA: Academic Press Professional, Inc., 1992. ISBN 0-12-174584-8. Citado na p´agina 22. DANG, T. D.; MOLNAR, S.; MARICZA, I. Capturing the complete characteristics of multifractal network traffic. GLOBECOM, Taipei, Taiwan, Novembro 2002. Citado 2 vezes nas p´aginas 21 e 83. DANG, T. D.; MOLNAR, S.; MARICZA, I. Capturing the Complete Multifractal Characteristics of Network Traffic. In: In Proc., GLOBECOM 2002. [S.l.: s.n.], 2002. Citado na p´agina 21. DANG, T. D.; MOLNAR, S.; MARICZA, I. Queuing performance estimation for general multifractal traffic. Int. J. Commun. Syst., v. 16, n. 2, p. 117–136, 2003. Citado 4 vezes nas p´aginas 19, 21, 22 e 28. DEC. Digital Equipament Corporation Traces. 1995. Dispon´ıvel em: . Citado 2 vezes nas p´aginas 57 e 127. DINIZ, P. S. R. Adaptive Filtering: Algorithms and Practical Implementation. [S.l.]: Springer, 2008. Citado 3 vezes nas p´aginas 45, 49 e 54. DITZE, M.; JAHNICH, I. Towards end-to-end QoS in service oriented architectures. In: Industrial Informatics, 2005. INDIN ’05. 2005 3rd IEEE International Conference on. [S.l.: s.n.], 2005. p. 92–97. Citado na p´agina 17. DURRESI, A.; SRIDHARAN, M.; JAIN, R. Congestion control using adaptive multilevel early congestion notification. International Journal of High performance and Networking, v. 4, n. 5, 2006. Citado na p´agina 78. EHLERS, R. S. [S.l.]: Departamento de Estat´ısticas UFPR, 2005. Citado na p´agina 31. FARHANG-BOROUJENY, B. Adaptive Filters: Theory and Applications. [S.l.]: John Wiley & Sons, 1999. Citado 2 vezes nas p´aginas 60 e 90. FELDMANN, A.; GILBERT, A. C.; WILLINGER, W. Data networks as cascades: investigating the multifractal nature of Internet WAN traffic. SIGCOMM Comput. Commun. Rev., ACM, New York, NY, USA, v. 28, n. 4, p. 42–55, 1998. Citado na p´agina 19. GILL, P. E.; MURRAY, W.; WRIGHT, M. H. Practical Optimization. [S.l.]: Emerald Group Publishing Limited, 1982. Citado na p´agina 48. GONCALVES, B. H. P.; VIEIRA, F. H. T.; COSTA, V. H. T. Modelagem Multifractal BMWM Adaptiva para Tr´afego de Redes de Computadores. In: X Encontro Anual de Computa¸c˜ao - EnAComp 2013. [S.l.: s.n.], 2013. p. 383–390. Citado 6 vezes nas p´aginas 24, 25, 82, 83, 85 e 86. GRIPENBERG, G.; NORROS, I. On the prediction of fractional brownian motion. Journal of Applied Probability, v. 33, p. 400–410, 1996. Citado na p´agina 56. GULER, O. Foundations of Optimization (Graduate Texts in Mathematics, Vol. 258). [S.l.]: Springer, 2010. Citado na p´agina 48. HABIB, I. W.; SAADAWI, T. N. Access flow control algorithms in broadband networks. Computer Communications, v. 15, n. 5, p. 326–332, 1992. Citado 2 vezes nas p´aginas 79 e 89. HATANO, T.; SHIGENO, H.; OKADA, K. TCP-friendly Congestion Control for HighSpeed Network. In: Applications and the Internet, 2007. SAINT 2007. International Symposium on. [S.l.: s.n.], 2007. p. 10–10. Citado na p´agina 17. HAYKIN, S. S. Modern filters. [S.l.]: Macmillan New York, 1989. Citado na p´agina 57. HIRCHOREN, G.; ARANTES, D. Predictors for the discrete time fractional gaussian processes. In: Telecommunications Symposium, 1998. ITS ’98 Proceedings. SBT/IEEE International. [S.l.: s.n.], 1998. p. 49–53 vol.1. Citado na p´agina 56. HU, Q.; PETR, D. A predictive self-tuning fuzzy-logic feedback rate controller. Networking, IEEE/ACM Transactions on, v. 8, n. 6, p. 697–709, Dec 2000. Citado na p´agina 78. INTEL. Intel Pentium Processor T4500. 2014. Dispon´ıvel em: . Citado na p´agina 58. JACOBSON, V. Congestion Avoidance and Control. SIGCOMM Comput. Commun. Rev., v. 25, n. 1, p. 157–187, jan. 1995. ISSN 0146-4833. Citado na p´agina 81. JANTZEN, J. Foundations of Fuzzy Control. [S.l.]: John Wiley & Sons, 2007. Citado na p´agina 38. JUSAK, J.; HARRIS, R. Study of UDP-based Internet traffic: Long-range dependence characteristics. In: Australasian Telecommunication Networks and Applications Conference (ATNAC), 2011. [S.l.: s.n.], 2011. p. 1–7. ISSN Pending. Citado na p´agina 17. KARNIK, A.; KUMAR, A. Performance of TCP Congestion Control with Explicit Rate Feedback. IEEE/ACM Trans. Netw., IEEE Press, v. 13, n. 1, p. 108–120, fev. 2005. ISSN 1063-6692. Citado 2 vezes nas p´aginas 79 e 89. KIM, E. et al. A new approach to fuzzy modeling. Fuzzy Systems, IEEE Transactions on, v. 5, n. 3, p. 328–337, Aug 1997. Citado na p´agina 55. KIM, S. et al. Dataset of BitTorrent traffic on Korea Telecom’s mobile WiMAX network. 2012. Dispon´ıvel em: . Citado 4 vezes nas p´aginas 22, 88, 129 e 131. KUO, S. M.; LEE, B. H.; TIAN, W. Real-Time Digital Signal Processing: Fundamentals, Implementations and Applications. [S.l.]: John Wiley & Sons, 2013. Citado na p´agina 50. LEE, I. W. C.; FAPOJUWO, A. O. Stochastic Processes for Computer Network Traffic Modeling. Comput. Commun., Elsevier Science Publishers B. V., v. 29, n. 1, p. 1–23, dez. 2005. ISSN 0140-3664. Citado na p´agina 78. LEE, K. Y. Complex fuzzy adaptive filter with LMS algorithm. Signal Processing, IEEE Transactions on, v. 44, n. 2, p. 424–427, 1996. ISSN 1053-587X. Citado na p´agina 57. LEE, T.-J.; VECIANA, G. de. Model and performance evaluation for multiservice network link supporting ABR and CBR services. Communications Letters, IEEE, v. 4, n. 11, p. 375–377, Nov 2000. Citado na p´agina 80. LI, H.; CHEN, C. P.; HUANG, H.-P. Fuzzy Neural Intelligent Systems: Mathematical Foundation and the Applications in Engineering. [S.l.]: CRC Press, 2000. Citado na p´agina 35. LILLY, J. H. Fuzzy control and identification. [S.l.]: John Wiley & Sons, 2010. Citado na p´agina 40. LIU, H.-H.; HSU, P.-L. Design and simulation of adaptive fuzzy control on the traffic network. In: SICE-ICASE, 2006. International Joint Conference. [S.l.: s.n.], 2006. p. 4961–4966. Citado na p´agina 55. MAMDANI, E.; ASSILIAN, S. An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, v. 7, n. 1, p. 1 – 13, 1975. Citado na p´agina 35. NORROS, I. A storage model with self-similar input. Queueing Systems. Citado na p´agina 32. OUYANG, C.-S.; LEE, W.-J.; LEE, S.-J. A TSK-type neurofuzzy network approach to system modeling problems. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, v. 35, n. 4, p. 751–767, Aug 2005. Citado na p´agina 78. OUYANG, Y. C.; YANG, C. W.; LIAN, W. S. Neural networks based variable bit rate traffic prediction for traffic control using multiple leaky bucket. Journal of High Speed Networks, v. 15, n. 2, p. 11–122, 2006. Citado na p´agina 69. PAPOULIS, A. Probability, Random Variables, and Stochastic Processes. [S.l.]: Mc-Graw Hill, 1984. Citado na p´agina 58. PARK, K.; WILLINGER, W. Self-similar Network Traffic and Performance Evaluation. New York: John Wiley and Sons, 2000. Citado 4 vezes nas p´aginas 19, 20, 31 e 55. PAVLOV, A. N.; ANISHCHENKO, V. S. Multifractal analysis of complex signals. Physics-Uspekhi, v. 50, n. 8, p. 819, 2007. Citado na p´agina 32. PAXSON, V.; FLOYD, S. Wide area traffic: the failure of poisson modeling. Networking, IEEE/ACM Transactions on, v. 3, n. 3, p. 226–244, Jun 1995. Citado na p´agina 57. RAMAKRISHNAN, K. K.; JAIN, R. A Binary Feedback Scheme for Congestion Avoidance in Computer Networks. ACM Trans. Comput. Syst., v. 8, n. 2, p. 158–181, maio 1990. ISSN 0734-2071. Citado na p´agina 89. RIBEIRO, V. J. et al. Multiscale queuing analysis of long-range-dependent network traffic. In: Proc. IEEE INFOCOM. [S.l.: s.n.], 2000. p. 1026–1035. Citado na p´agina 22. RIBEIRO, V. J. et al. Small-time scaling behavior of internet backbone traffic. Computer Networks: The International Journal of Computer and Telecommunications Networking, Elsevier North-Holland, Inc., v. 48, n. 3, p. 315–334, 2005. Citado na p´agina 31. RIEDI, R. H. et al. A multifractal wavelet model with application to network traffic. Information Theory, IEEE Transactions on, v. 45, n. 3, p. 992–1018, Apr 1999. Citado 5 vezes nas p´aginas 19, 22, 24, 31 e 83. ROCHA, F. G. C.; VIEIRA, F. H. T. Modelagem de tr´afego de v´ıdeo mpeg-4 utilizando cascata multifractal com distribuicao autorregressiva dos multiplicadores. In: The 8th International Information and Telecommunication Technologies Symposium. [S.l.: s.n.], 2009. Citado na p´agina 22. ROLLS, D. A.; MICHAILIDIS, G.; HERN´aNDEZ-CAMPOS, F. Queueing analysis of network traffic: Methodology and visualization tools. Comput. Netw., v. 48, n. 3, p. 447–473, jun. 2005. ISSN 1389-1286. Citado 2 vezes nas p´aginas 65 e 93. RONGCAI, Z.; SHUO, Z. Network traffic generation: A combination of stochastic and self-similar. In: Advanced Computer Control (ICACC), 2010 2nd International Conference on. [S.l.: s.n.], 2010. v. 2, p. 171–175. Citado na p´agina 17. ROSS, T. J. Fuzzy logic with engineering applications. [S.l.]: John Wiley & Sons, 2009. Citado 8 vezes nas p´aginas 6, 17, 35, 36, 40, 42, 43 e 55. SCHILLING, R.; HARRIS, S. Fundamentals of digital signal processing using MATLAB. [S.l.]: Cengage Learning, 2011. Citado na p´agina 45. SEURET, S.; GILBERT, A. Pointwise h¨older exponent estimation in data network traffic. ITC Specialist Semina, 2000. Citado na p´agina 31. SOUZA, B. V. L.; VIEIRA, F. H. T. Algoritmo de predi¸c˜ao de tr´afego de rede baseado na fun¸c˜ao autocorrela¸c˜ao de um modelo multifractal. In: XXXIV Congresso Nacional de Matem´atica Aplicada e Computacional. ´Aguas de Lid´oias, SP: [s.n.], 2012. Citado na p´agina 56. SUGENO, M.; YASUKAWA, T. A fuzzy-logic-based approach to qualitative modeling. Fuzzy Systems, IEEE Transactions on, v. 1, n. 1, p. 7–, Feb 1993. Citado na p´agina 55. TAKAGI, T.; SUGENO, M. Fuzzy identification of systems and its applications to modeling and control. Systems, Man and Cybernetics, IEEE Transactions on, SMC-15, n. 1, p. 116–132, Jan 1985. Citado na p´agina 55. TOREYIN, B. et al. Lms based adaptive prediction for scalable video coding. In: Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on. [S.l.: s.n.], 2006. v. 2, p. II–II. Citado na p´agina 57. TRAN, H. T.; ZIEGLER, T. Adaptive bandwidth provisioning with explicit respect to qos requirements. Computer Communications, v. 28, p. 1862–1876, 2005. Citado na p´agina 69. VIEIRA, F.; ROCHA, F. An adaptive fuzzy model using orthonormal basis functions based on multifractal characteristics applied to network traffic control. Neurocomputing, v. 74, n. 11, p. 1894–1907, 2011. Citado na p´agina 82. VIEIRA, F. H. T.; COSTA, V. H. T.; SOUZA, B. V. L. Neural network based approaches for network traffic prediction. Artificial Intelligence, Evolutionary Computing and Metaheuristics, v. 427, p. 657–684, 2013. Citado na p´agina 22. VIEIRA, F. H. T.; LING, L. L. Modelagem fuzzy utilizando fun¸c˜oes de base ortonormais aplicada `a predi¸c˜ao adaptativa de tr´afego de redes. Learning and Nonlinear Models. Rev. Socied. Brasileira de Redes Neurais (SBRN), v. 4, n. 2, p. 93–11, 2006. Citado 2 vezes nas p´aginas 19 e 26. VIEIRA, F. H. T.; LING, L. L. Performance bounds for a cascade based multifractal traffic model with generalized multiplier distributions. Journal of Communication and Information Systems, v. 21, p. 165–175, 2006. Citado na p´agina 20. VIEIRA, F. H. T.; LING, L. L. Modelagem de tr´afego de redes utilizando cascata multifractal generalizada. Revista de Inform´atica Te´orica e aplicada, v. 15, n. 2, 2008. Citado na p´agina 31. VIEIRA, F. H. T.; ROCHA, F. G. C.; LEMOS, R. P. An algorithm for adaptive prediction of local singularities of network traffic flows. 2010. Citado na p´agina 31. WANG, C. et al. LRED: A Robust and Responsive AQM Algorithm Using Packet Loss Ratio Measurement. Parallel and Distributed Systems, IEEE Transactions on, v. 18, n. 1, p. 29–43, Jan 2007. Citado 2 vezes nas p´aginas 78 e 79. WANG, L.-X. Adaptive Fuzzy Systems and Control: Design and Stability Analysis. Upper Saddle River, NJ, USA: Prentice-Hall, Inc., 1994. ISBN 0-13-099631-9. Citado 11 vezes nas p´aginas 6, 37, 39, 40, 41, 42, 44, 50, 57, 59 e 88. WANG, Z.-x. et al. Research on fuzzy neural network algorithms for nonlinear network traffic predicting. In: Optoelectronics Letters. [S.l.: s.n.], 2006. p. 373–375. ISSN Pending. Citado na p´agina 17. WITS. WITS: Waikato Internet Traffic Storage from University of Waikato. 2014. Dispon´ıvel em: . Citado 2 vezes nas p´aginas 57 e 88. YU, Y. et al. Traffic prediction in 3G mobile networks based on multifractal exploration. Tsinghua Science and Technology, v. 18, n. 4, p. 398–405, 2013. Citado na p´agina 17. ZHANG, R.; PHILLIS, Y. A.; KOUIKOGLOU, V. S. Fuzzy Control of Queuing Systems. [S.l.]: Springer, 2005. Citado na p´agina 17. ZOU, D.; ZHANG, X.; WANG, W. Multi-service traffic models of heterogeneous wireless communication networks. Proc. of the 7th World Congress on Intelligent Control and Automation, p. 495–498, 2008. Citado na p´agina 21.

  10. 10
  11. 11
  12. 12
  13. 13
  14. 14
  15. 15
  16. 16
  17. 17
  18. 18

    Zdroj: Kanev, Svilen, Gu-Yeon Wei, and Brooks, David. 2012. XIOSim: Power-performance Modeling of Mobile x86 Core. In Proceedings of the 2012 ACM/IEEE International Symposium on Low Power Electronics and Design, 267-272, Redondo Beach, California. doi:10.1145/2333660.2333722

    Popis souboru: application/pdf

    Relation: Proceedings of the 2012 ACM/IEEE international symposium on Low power electronics and design - ISLPED '12; ISLPED '12 Proceedings of the 2012 ACM/IEEE international symposium on Low power electronics and design

  19. 19

    Thesis Advisors: Ferreira, Deller James, Camilo Junior, Celso Gonçalves, Soares, Telma Woerle de Lima, Martinhon, Carlos Alberto de Jesus

    Zdroj: Biblioteca Digital de Teses e Dissertações da UFGUniversidade Federal de GoiásUFG.

    Popis souboru: application/pdf

    Relation: -3303550325223384799; 600; -7712266734633644768; 437660438475277419; [1] ABDOLLAH HOMAIFAR, C. X. Q.; LAI, S. H. Constrained optimization via genetic algorithms. SIMULATION, 62(4):242–254, 1994. [2] ABNAR, S.; OROOJI, F.; TAGHIYAREH, F. An evolutionary algorithm for forming mixed groups of learners in web based collaborative learning environments. In: Technology Enhanced Education (ICTEE), 2012 IEEE International Conference on, p. 1–6, 2012. [3] ADAMIDES, E. D.; KARACAPILIDIS, N. Information technology support for the knowledge and social processes of innovation management. Technovation, 26:50–59, 2006. [4] AGGARWAL, A. Functional diversity and its impact on distributed groups: An exploratory study. In: Proceedings of the 2012 45th Hawaii International Conference on System Sciences, HICSS ’12, p. 444–453, Washington, DC, USA, 2012. IEEE Computer Society. [5] AGGARWAL, A. K. Diversity in distributed decision making: An exploratory study. In: Proceedings of the 2010 43rd Hawaii International Conference on System Sciences, HICSS ’10, p. 1–11,Washington, DC, USA, 2010. IEEE Computer Society. [6] AGHA, S.; ALRUBAIEE, L.; JAMHOUR, M. Effect of core competence on competitive advantage and organizational performance. International Journal of Business and Management, 7(1):192–204, Janeiro 2012. [7] ANDERSON, W.; HILTZ, S. Culturally heterogeneous vs. culturally homogeneous grupos in distributed group support systems: effects on group process and consensus. In: 34th International Conference on Systems Sciences, 2001. [8] ANNE POWELL, GABRIELE PICCOLI, B. I. Virtual teams: A review of current literature and directions for future research. The data base for Advances in Information Systems, 35(1):6–36, 2004. [9] APPELBAUM, S. H.; GALLAGHER, J. The competitive advantage of organizational learning. Journal of Workplace Learning: Employee Counselling Today, 12(2):40–56, 2000. [10] ARAGON, C. R.; WILLIAMS, A. Collaborative creativity: a complex systems model with distributed affect. In: CHI ’11 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, p. 1875–1884, 2011. [11] ASOH, H.; MÜHLENBEIN, H. On the mean convergence time of evolutionary algorithms without selection and mutation. In: PARALLEL PROBLEM SOLVING FROM NATURE, LECTURE NOTES IN COMPUTER SCIENCE 866, p. 88–97. Springer-Verlag, 1994. [12] AVOLIO, B. Full Leadership Development: Building the Vital Forces in Organizations. Advanced Topics in Organizational Behavior series. SAGE Publications, 1999. [13] BANDURA, A. Social foundations of thought and action: a social cognitive theory. Prentice-Hall series in social learning theory. Prentice-Hall, 1986. [14] BANI-HANI, J. S.; FALEH, A. A. The impact of core competencies on competitive advantage: Strategic challenge. Journal of Business and Management, 4(2), 2011. [15] BARDIN, L. Análise de conteúdo. Edições 70, 2006. Título original: L’analyse de contenu, Presses Universitaires de France, 1977. [16] BARNATT, C. Virtual organizations in the small busciness sector: the case of cavendish management resources. International Small Business Journal, 15(4):36–47, 1997. [17] BASADUR, M.; HEAD, M. Team performance and satisfaction: A link to cognitive style within a process framework. Journal of Creative Behavior, 35:227–248, 2001. [18] BASS, B. Transformational Leadership: Industrial, Military, and Educational Impact. Lawrence Erlbaum Associates, Incorporated, 1998. [19] BASS, B.; AVOLIO, B. Improving Organizational Effectiveness Through Transformational Leadership. Thousands Oaks, California, 1994. [20] BATTITI, R.; BRUNATO, M.; MASCIA, F. Reactive search and intelligent optimization. Technical report, Università Degli Studi di Trento, Julho 2007. [21] BEKELE, R. Computer-Assisted Learner Group Formation Based on Personality Traits. PhD thesis, Universität Hamburg, 2005. [22] BELBIN, M. Team Roles at Work. Oxford: Butterworth Heinemann, 1993. [23] BELBIN, R. Management Teams: Why They Succeed Or Fail. Butterworth- Heinemann, 1981. [24] BELEW, R. K. Evolving networks: Using the genetic algorithm with connectionist learning. Technical report, University of California, La Jolla, CA 92093, Junho 1990. [25] BERGER, N. Pionnering experiences in distance learning: Lessons learned. Journal of Management Education, 23(6):684–690, 1999. [26] BERTTUCCI, A.; MELONI, C.; CONTE, S.; CARDELLINI, L. The role of personality gender and interaction in a cooperative and a computer supported collaborative learning task. Journal of Science Education, 6:32–36, 2005. [27] BRADLEY, J. H.; HEBERT, F. J. The effect of personality type on team performance. Journal of Management Development, 16:337–353, 1997. [28] BRANDON, D.; HOLLINGSHEAD, A. Collaborative learning and computer supported groups. Communication Education, 48(2):109–126, 1999. [29] BRASIL. Constituição da república federativa do brasil. Internet. http://www.planalto.gov.br/ccivil_03/Constituicao/Constituicao.htm, acesso em 14/07/2013. [30] BROPHY, D. Understanding, measuring, and enhancing collective creative problem-solving efforts. Creative Research Journal, 3:199–299, 1998. [31] BROWN, A.; CAMPIONE, J. Guided discovery in a community of learners. In: Press, C. M., editor, Classroom lessons: Integrating cognitive theory and classroom practice, p. 229–270. Classroom lessons: Integrating cognitive theory and classroom practice, 1994. [32] BROWN, S.; EISENHARDT, K. Product development: past research; present findings, and future directions. Academy of Management Review, 20:343–378, 1995. [33] BUNDERSON, J. S.; SUTCLIFFE, K. Comparing alternative conceptualizatios of funcional diversity and performance effects. Academy of Management Journal, 45 (5):875–893., 2002. [34] CAETANO, S. S.; FERREIRA, D. J.; CAMILO-JR, C. G. Multi-objective genetic algorithm for competency-based selection of auditing teams. Journal of Software & Systems Development, 2013(2013), 2013. [35] CANNON, D.; WHEELDON, D. ITIL Service Operation. TSO, May 2007. [36] CARSON, J. B.; TESLUK, P. E.; MARRONE, J. A. Shared leadership in teams: An investigation of antecedent conditions and performance. Academy of Management Journal, 50(5):1217–1234, 2007. [37] CARTE, T. A.; CHIDAMBARAM, L.; BECKER, A. Emergent leadership in selfmanaged virtual teams: A longitudinal study of concentrated and shared leadership behaviors. Group Decision and Negotiation, 15(4):323–343, 2006. [38] CAVANAUGH, R.; ELLIS, M.; LAYTON, R.; ARDIS, M. Automating the process of assigning students to cooperative-learning teams. In: in proc. 2004 ASEE Annual Conf, 2004. [39] CHAN, K. W. Issues of heterogeneous grouping for engaged learning. In: APERA Conference 2006, 2006. [40] CHIDAMBARAM, L.; CARTE, T. Diversity: Is there more than meets the eye. In: The 38th International Conference on System Science, 2005. [41] CHRISTODOULOPOULOS, C. E.; PAPANIKOLAOU, K. A. Investigation of group formation using low complexity algorithms. In: Proceedings of Workshop on Personalisation in E-Learning Environments at Individual and Group Level, p. 57– 60, 2007. 1th International Conference on User Modeling. [42] CONGER, J. A., K. R. A. Towards a behavioral theory of charismatic leadership in organizational settings. Academy of Management Review, 12:637–647, 1987. [43] COX, T. The multicultural organization. Academy of Management Executive, 5:34–47, 1991. [44] COX, T.; BLAKE, S. Managing cultural diversity: Implications for organizational competitiveness. Academy of Management Executive, 5:45–56, 1991. [45] DARWIN, C. On the Origin of the Species by Means of Natural Selection: Or, The Preservation of Favoured Races in the Struggle for Life. John Murray, 1859. [46] DAVIDSON, N.; KROLL, D. L. An overview of research on cooperative learning related to mathematic. Journal for Research in Mathematics Education, 22:362– 365, 1991. [47] DE GEUS, A. The living company. Harvard Business School Press, 1997. [48] DE PAIVA, I. A.; PERNAMBUCO, M. M. C. A. Educação e realidade: interdisciplinar. Universidade Federal do Rio Grande do Norte, 2005. [49] DEB, K. An efficient constraint handling method for genetic algorithms. In: Computer Methods in Applied Mechanics and Engineering, p. 311–338, 1998. [50] DILLENBOURG, P. Over-scripting cscl: The risks of blending collaborative learning with instructional design. http://hal.archivesouvertes. fr/docs/00/19/02/30/PDF/Dillenbourg-Pierre-2002.pdf, acesso em 14.05.2013. [51] DILLENBOURG, P. What do you mean by ’collaborative learning’? Collaborativelearning: Cognitive and Computational Approaches., 1999. [52] DOWLING, K.; CHIM, T. Reflectors as online extraverts. Educational Studies, 30(06):265–276, 2004. [53] DRUCKER, P. Post-Capitalism Society. Butterworth Heinemann, 1993. [54] EBRAHIM, N. A.; AHMED, S.; TAHA., Z. Virtual teams: a literature review. Australian Journal of Basic and Applied Sciences, 3(3):2653–2669, 2009. [55] EIBEN, A. E.; SMITH, J. E. Introduction to Evolutionary Computing. Natural Computing Series. Springer, 2003. [56] EIBEN, A.; RAUÉ, P.-E.; RUTTKAY, Z. Ga-easy and ga-hard constraint satisfaction problems, 1995. [57] EL-MIHOUB, T. A.; HOPGOOD, A. A.; NOLLE, L.; BATTERSBY, A. Hybrid genetic algorithms: A review. Engineering Letters, 13(2), 2006. [58] ENGELBRECHT, A. P. Computational intelligence : an introduction. John Wiley & Sons, John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England, 2nd edition edition, 2007. [59] FELDER, R. M.; SILVERMAN, L., K. Learning and teaching styles in engineering education. Engr. Education, 78:674–681, 1988. Disponível em http://www4.ncsu.edu/unity/lockers/users/f/felder/public/Papers/LS-1988.pdf, acesso em 28/12/2012. [60] FELDER, R. M. How students learn: Adapting teaching styles to learning styles. In: Frontiers In Education Conference Proceedings, p. 489–493, 1988. [61] FELIX, Z.; TEDESCO, P. Formação de grupos de aprendizagem em ambientes cscl ciente de contexto. II SEGeT – Simpósio de Excelência em Gestão e Tecnologia, 2006. [62] FILHO, J. A. B. L.; QUARTO, C. C.; FRANCA, R. M. Clustering algorithm for the socio-affective groups formation in aid of computer supported collaborative learning. Sistemas Colaborativos II, Simpósio Brasilerio de, 0:24–27, 2010. [63] FISCHER, G. A conceptual framework for computer-supported collaborative learning at work. In: Goggins, S. P.; Jahnke, I.; Wulf, V., editors, Computer- Supported Collaborative Learning at the Workplace, volume 14 de Computer- Supported Collaborative Learning Series, p. 23–42. Springer US, 2013. [64] FORSYTH, D. Group Dynamics. Psychology Series. Brooks/Cole, Wadsworth, 1999. [65] FREED, S. Pensar, dialogar e aprender. http://www.andrews.edu/ freed/ppdfs/4- 10InterdependenciaPositiva.pdf, acesso em 17.02.2013. [66] GOGGINS, S.; JAHNKE, I.; WULF, V. Cscl@work revisited - beyond cscl and cscw?: are there key design principles for computer supported collaborative learning at the workplace? In: Proceedings of the 17th ACM international conference on Supporting group work, GROUP ’12, p. 323–326, New York, NY, USA, 2012. ACM. [67] GOGGINS, S. P.; JAHNKE, I. Cscl@work: Making learning visible in unexpected online places across established boundaries. IJSKD, 4(3):17–37, 2012. [68] GOIÁS, E. Lei no 17.663, de 14 de junho de 2012. Internet, 06 2012. Dispõe sobre a reestruturação da Carreira dos Servidores do Poder Judiciário do Estado de Goiás e dá outras providências. [69] GRAF, S.; BEKELE, R. Forming heterogeneous groups for intelligent collaborative learning systems with ant colony optimization. In: Springer-Verlag Berlin, H., editor, ITS’06 Proceedings of the 8th international conference on Intelligent Tutoring Systems, p. 217–226, 2006. [70] GRANT, R. Toward a knoledge-based theory of firm. Strategic Management Journal, 17:109–122, 1996. [71] GRUAU, F.; WHITLEY, D. Adding learning to the cellular development of neural networks: Evolution and the baldwin effect. Evol. Comput., 1(3):213–233, Sept. 1993. [72] GRUDIN, J. Computer-supported cooperative work: history and focus. Computer, 27(5):19–26, 1994. [73] GRUNERT, K. G.; HILDEBRANDT, L. Success factors, competitive advantage and competence development. Journal of Business Research, 57(5):459 – 461, 2004. Success factors, competitive advantage and competence development . [74] GUIMERÀ, R.; UZZI2, B.; SPIRO, J.; AMARAL1, L. A. N. Team assembly mechanisms determine collaboration network structure and team performance. Science, 308(5722):697–702, April 2005. [75] GUZZO, R.; DICKSON, M. Teams in organizations: Recent research on performance and effectiveness. Annual Review of Psychology, 47:307–338, 1996. [76] HAKKINEN, P. What makes learning and understanding in virtual teams so difficult? CyberPsychology & Behavior, 7(2):201–206, 2004. [77] HARE, A. P. Types of roles in small groups : A bit of history and a current perspective. Small Group Research, 25:433–448, 1994. [78] HARRINGTON, D.; KEARNEY, A. The business school in transition: New opportunities in management development, knowledge transfer and knowledge creation. Journal of European Industrial Training, 35(2):116–134, 2011. [79] HARRISON, D.; PRICE, K.; GAVIN, J.; FLOREY, A. Time, teams and task performance: Changing effects of surface and deep-level diversity on group functioning. Academy of Management Journal, 45(5):1029–1045, 2002. [80] HART, W. E. Adaptive global optimization with local search. PhD thesis, La Jolla, CA, USA, 1994. UMI Order No. GAX94-32928. [81] HAUPT, R.; HAUPT, S. Practical Genetic Algorithms. Wiley, 2nd edition, 2004. [82] HENRY, S. M.; STEVENS, K. T. Using belbin’s leadership role to improve team effectiveness: an empirical investigation. J. Syst. Softw., 44(3):241–250, Jan. 1999. [83] HOADLEY, C. Roles, design, and the nature of cscl. Computers in Human Behavior, 26(4):551–555, Julho 2010. Elsevier Science Publishers B. V. Amsterdam, The Netherlands, The Netherlands. [84] HOLLAND, J. H. Adaptation in Natural and Artificial Systems. The University of Michigan Press, 1975. [85] HOUSE, R. J.; SHAMIR, B. Toward the integration of transformational, charismatic, and visionary theories. In: Press, U. A., editor, Leadership theory and research: Perspectives and directions, p. 81–107. M. M. Chemers and R. Ayman, San Diego, CA, 1993. [86] HOWELL, J.; AVOLIO, B. J. Transformational leadership, transactional leadership, locus of control and support for innovation: Key predictors of consolidated-business unit performance. Journal of Applied Psychology, 78:891–902, 1993. [87] HUBSCHER, R. Assigning students to groups using general and contextspecific criteria. IEEE Trans. Learn. Technol., 3(3):178–189, July 2010. [88] JANIS, I. Group Think. 1971. [89] JARKE, M. Experience-based knowledge management:a cooperative information systems perspective. Control Engineering Practice, 10:561–569, 2002. [90] JARVENPAA, S. L.; LEIDNER, D. E. Communication and trust in global virtual teams. Organization Science, 10(6):791–815, June 1999. [91] JIN, N.; TSANG, E.; LI, J. A constraint-guided method with evolutionary algorithms for economic problems. Appl. Soft Comput., 9(3):924–935, June 2009. [92] JOHNSON, D. W.; JOHNSON, R. Learning together and alone: Cooperation, competition and individualistic learning. Prentice Hall, 1987. [93] JOHNSON, D. W.; JOHNSON, R. T. Making cooperative learning work. Theory Into Practice, 38(2):67–73, 1999. [94] JOHNSON, D. W.; JOHNSON, R. T.; STANNE, M. B. Impact of group processing on achievement in cooperative groups. The journal of Social Psycology, 130(4):507– 516, 2001. [95] JOHNSON, D.; JOHNSON, R. Creative controversy: intellectual challenge in the classroom. Interaction Book Company, 1995. [96] JOHNSON, R. T.; JOHNSON, D. W. An overview of cooperative learning. http://teachers.henrico.k12.va.us/staffdev/mcdonald_j/downloads/21st/comm/BenefitsOfCL/OverviewOfCoopLrng_acesso em 27.12.2012. [97] JÄRVELÄ, S.; JÄRVENOJA, H.; VEERMANS, M. Understanding the dynamics of motivation in socially shared learning. International Journal of Educational Research, 47(2):122–135, 2008. [98] JUNG, D.; AVOLIO, B. Effects of leadership style and followers’ cultural values on performance under different task structure conditions. Academy of Management Journal, 42:208–218, 1999. [99] KANKANHALLI, A.; TAN, B.; WEI, K.-K. Conflict and performance in global virtual teams. J. Manage. Inf. Syst., 23(3):237–274, Jan. 2007. [100] KAPLAN, H., R.; NORTON, D. The Balanced Scorecard: Translating Strategy Into Action. Harvard Business School Press. Harvard Business School Publishing India Pvt. Limited, 1996. [101] KESSLER, E. H. Leveraging e-r&d processes: a knowledge-based view. Technovation, 23:905–915, 2003. [102] KIRSCHNER, P. A.; STRIJBOS, J.-W.; KREIJNS, K.; BEERS, P. Designing electronic collaborative learning environments. Educational Technology Research and Development, 52(3):47–66, 2004. [103] KOLB, D. A. The modern american college - Responding to the new realities of diverse students and a changing of society. Artur W. Chichering and associates, 1981. [104] KOLB D., A. Learning Style Inventory: Technical Manual. 1976. [105] KREBS, S., H. E.; BORDIA, P. Virtual teams and group member dissimiliarity. Small Group Research, 37(6):721–741, 2006. [106] KREIJNS, C.; P.A., K.; JOCHEMS, W. Identifying the pitfalls for social interaction in computer-supported collaborative learning environments: a review of the research. Computers in Human Behavior, 19:335–354, 2003. [107] KREIJNSA, K.; KIRSCHNERB, P. A.; JOCHEMSB, W. Identifying the pitfalls for social interaction in computer-supported collaborative learning environments: a review of the research. Computers in Human Behavior, 19:335–353, 2003. [108] KURTZBERG, T. R. Feeling creative, being creative: An empirical study of diversity and creativity in teams. Creativity Research Journal, 17 (1):51–65, 2005. [109] LAZERSON, M.; WAGENER, U. Teaching and learning the unfamiliar. Change: The Magazine of Higher Learning, 31:38–39, 1999. [110] LIANG, C.-J.; LIN, Y.-L.; HUANG, H.-F. Effect of core competence on organizational performance in an airport shopping center. Journal of Air Transport Management, 31(0):23 – 26, 2013. Notes . [111] LIN, Y.-T.; HUANG, Y.-M.; CHENG, S.-C. An automatic group composition system for composing collaborative learning groups using enhanced particle swarm optimization. Comput. Educ., 55(4):1483–1493, Dec. 2010. [112] LLOYD, V.; RUDD, C.; TAYLOR, S. ITIL - Service Design. TSO (The Stationery Office), 2007. [113] MACMASTER, M. D. The Intelligence Advantage: Organizing for Complexity. Butterworth-Heinemann Limited, 1996. [114] MAHFOUD, S. W. Boltzmann selection. In: Handbook of Evolutionary Computation, p. 231–234. IOP Publishing Ltd and Oxford University Press, 1997. Release 97/1. [115] MARGERISON, C.; MCCANN, D. Team Management: Practical New Approaches. Management Books 2000 Limited, 1995. [116] MARK, G. Conventions and commitments in distributed cscw groups. Comput. Supported Coop. Work, 11(3):349–387, Nov. 2002. [117] MARREIROS, A.; FONSECA, J.; CONBOY, J. O trabalho científico em ambiente de aprendizagem cooperativa. Revista da Educação, 10(2):99–112, 2001. [118] MARROTTA, S.; PETERS, B.; PALIOKAS, K. Teaching group dinamics: An interdisciplinary model. Journal of Specialists in Group Work, 25(1):16–28, 2000. [119] MARTÍN, E.; PAREDES, P. Using learning styles for dynamic group formation in adaptive collaborative hypermedia systems. Matera, M. & Comai, S. (Eds.) Engineering Advanced Web Applications. Proceedings of Workshops in Connection with 4th International Conference on Web Engineering, p. 188–197, 2004. [120] MICHALEWICZ, Z.; FOGEL, D. How to Solve It: Modern Heuristics. Springer, 2004. [121] MICHALEWICZ, Z. Genetic algorithms, numerical optimization, and constraints. p. 151–158. Morgan Kaufmann, 1995. [122] MICHALEWICZ, Z. A survey of constraint handling techniques in evolutionary computation methods. In: Proceedings of the 4th Annual Conference on Evolutionary Programming, p. 135–155. MIT Press, 1995. [123] MICHALEWICZ, Z. Genetic algorithms + data structures = evolution programs (3rd ed.). Springer-Verlag, London, UK, UK, 1996. [124] MISIOLEK, N. I.; HECKMAN, R. Patterns of emergent leadership in virtual teams. In: Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS’05) - Track 1 - Volume 01, HICSS ’05, p. 49.1–, Washington, DC, USA, 2005. IEEE Computer Society. [125] MITCHELL, M. An Introduction to Genetic Algorithms. MIT Press, Cambridge, MA, USA, 1998. [126] MORAES, R. Análise de conteúdo. Internet, 1999. http://cliente.argo.com.br/ mgos/analise_de_conteudo_moraes.html, acesso em 13.07.2013. [127] MORENO, J.; OVALLE, D. A.; VICARI, R. M. A genetic algorithm approach for group formation in collaborative learning considering multiple student characteristic. Computers & Education, 2011. [128] MUDRACK, P. E.; FARRELL, G. M. An examination of functional role behavior and its consequences for individuals in group settings. Small Group Research, 26(4):542–571, 1995. [129] MULDER, I.; SWAAK, J.; KESSELS, J. In search of reflective behavior and shared understanding in ad hoc expert teams. Cyberpsychol Behavior, 7(2):141–154, April 2004. [130] NASAJON, L. Gerenciamento da diversidade nas organizações. internet, May 2012. http://era.org.br/2012/05/gerenciamento-da-diversidade-nas-organizacoes, acesso em 09.06.2013. [131] NONAKA, I. An Inquiry into the Good, translated by M. Abe and C. Ive. Yale University Press, 1990. [132] NONAKA, I. A dynamic theory of organizational knowledge creation. Organization Science, 5 (1):14–37, 1994. [133] NONAKA, I.; UNIVERSITY, T. The Knowledge-Creating Company : How Japanese Companies Create the Dynamics of Innovation: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press, USA, 1995. [134] NONAKA, I. A empresa criadora do conhecimento. In: Bookman., editor, Gestão do Conhecimento, chapter 2, p. 39–53. Hirotaka Takeuchi and Ikujiro Nonaka, 2009. Tradução: Ana Thorell. [135] NONAKA, I.; TAKEUCHI, H. Teoria da criação do conhecimento organizacional. In: Bookman., editor, Gestão do Conhecimento, chapter 3, p. 54–91. Hirotaka Takeuchi and Ikujiro Nonaka, 2009. Tradução: Ana Thorell. [136] O’DONNELL, A. M.; DANSEREAU. Scripted cooperation in student dyads: A method for analyzing and enhancing academic learning and performance. In: Hertz-Lazarowitz.; Miller, N., editors, Interaction in cooperative groups: The theoretical anatomy of group learning, p. 120–144, New York, 1992. Cambridge University Press. [137] OLIVER, R.; OMARI, A. Using online technologies to support problem based learning: Learners’ responses and perceptions. Australian Journal of Education Technologies, 15(1):58–79, 1999. [138] ORAVEC, J. Virtual indivuals, virtuals groups. Cambridge University Press, 1996. [139] OUNNAS, A.; MILLARD, D. E.; DAVIS, H. C. A metrics framework for evaluating group formation. ACM, p. 221–224, 2007. [140] PAAVOLA, S. LIPPONEN, L. H. K. Epistemological foundations for cscl: A comparison of three models of innovative knowledge communities. In: CSCL 2002, p. 24–32, 2002. [141] PALMER, J. D.; FIELDS, N. A. Computer supported cooperative work. Washington Post., p. 15–17, 1994. [142] PANITZ, T. A definition of collaborative vs cooperative learning. Internet, 1996. http://www.londonmet.ac.uk/deliberations/collaborative-learning/panitzpaper. cfm, acesso em 24.06.2012. [143] PAREDES, P., A. O. A.; RODRIGUES, P. A method for supporting heterogeneousgroup formation through heuristics and visualization. Journal of Universal Computer Science, 16:2882–2901, 2010. [144] PAUL, S., S. P. S. I.; MYKYTYN, P. Impact of heterogeneity and collaborative conflict management style on the performance of synchronous global virtual teams. Information and Management, 41:303–321, 2004. [145] PEA, R. Seeing what we build together: Distributed multimedia learning environments for transformative communications. In: Koschmann, T., editor, CSCL:Theory and Practice of an emerging paradigm. Lawrence Erlbaum Associates, 1996. [146] PEREIRA, M. A. A.; FREIRE, J. E.; SEIXAS, J. A. Utilização da aprendizagem cooperativa no ensino de engenharia. In: XXII Encontro Nacional de Engenharia de Produção, 2002. [147] PODER JUDICIÁRIO, ESTADO DE GOIÁS, BRASIL. Regimento interno do tribunal de justiça do estado de goiás. Internet, Setembro 2000. [148] PODER JUDICIÁRIO, ESTADO DE GOIÁS, BRASIL. Resolução 44 de 10 de dezembro de 2001. Internet, 12 2001. Institui o Sistema de Controle Interno das atividades administrativas do Poder Judiciário do Estado de Goiás. [149] PODER JUDICIÁRIO, ESTADO DE GOIÁS, BRASIL. Decreto Judiciário 416/2010, chapter I, p. 1. Número 520. Poder Judiciário, 02 2010. Publicado em 12/02/2010. [150] PODER JUDICIÁRIO, ESTADO DE GOIÁS, BRASIL. Decreto Judiciário 288/2011, chapter I, p. 14. Número 914. Poder Judiciário, 09 2011. Publicado em 30/09/2011. [151] PODER JUDICIÁRIO, ESTADO DE GOIÁS, BRASIL. Provimento 11 de 25 de outubro de 2012. Internet, 10 2012. Dispõe sobre a nova sistemática de indenização aos oficiais de justiça avaliadores judiciários, das despesas de condução no cumprimento de mandado da Justiça Gratuita. [152] PODER JUDICIÁRIO, ESTADO DE GOIÁS, BRASIL. Portal da transparência. Internet, 2013. http://www.tjgo.jus.br/index.php/tribunal/tribunal-portaldatransparencia, acesso em 13.07.2013. [153] PORTER, M. Competitive Advantage: Creating and Sustaining Superior Performance. Free Press, 2008. [154] PRAHALAD, C.; HAMEL, G. The core competence of the corporation. Harvard Business Review, p. 1–15, May-June 1990. [155] QURESHI, S. Organisational change through collaborative learning in a network form. Group Decision and Negotiation, 9:129–147, 2000. [156] RAD, P.; LEVIN, G. Achieving project management success using virtual teams. J Ross Publishing Series. J ROSS PUB Incorporated, 2003. [157] REDMOND, M. A. A computer program to aid assignment of student project groups. ACM, p. 134–138, 2001. [158] RESTA, P.; LAFERRIÈRE, T. Technology in support of collaborative learning. Education and Psychology Review, 19:65–83, 2007. [159] ROBBINS, H.; FINLEY, M. Why teams don’t work. Texere, 2000. [160] ROBERT.JR., L. P. A multi-level analysis of the impact of shared leadership in diverse virtual teams. In: Proceedings of the 2013 conference on Computer supported cooperative work, p. 363–374. ACM, 2013. ISBN: 978-1-4503-1331-5. [161] ROBERTS, A. G. Team Role Balance: Investigating Knowledge-Building in CSCL Environment. PhD thesis, Queensland University of Technology, 2007. [162] RODDEN, T. A survey of CSCW systems in Interacting with Computers, volume 3. 1991. [163] RODRIGUES, P. B. Prática de ensino supervisionada em ensino do 1.o e do 2.o ciclo do ensino básico. Master’s thesis, Instituto Politécnico de Bragança - Escola Superior de Educação, 2012. [164] ROMNEY. The benefits of collaborative learning. Internet, december 1996. http://www.ucalgary.ca/pubs/Newsletters/Currents/Vol3.6/Benefits.html, acesso em24.03.2013. [165] ROTH, G.; ASSOR, A.; KANAT-MAYMON, Y.; KAPLAN, H. Autonomous motivation for teaching: How self-determined teaching may lead to self-determined learning. Journal of Educational Psychology, 99(4):761–774, 2007. [166] ROTHLAUF, F. Representations for Genetic and Evolutionary Algorithms. Springer-Verlag, 2006. [167] RUSSELL, S. J.; NORVIG, P.; CANDY, J. F.; MALIK, J. M.; EDWARDS, D. D. Artificial intelligence: a modern approach. Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 1996. [168] RYAN, R. M.; DECI, E. L. Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1):54–67, 2000. [169] SALMON, G. E-moderating: the key to teaching and learning online. 2000. [170] SARKER, S.; SARKER, S.; NICHOLSON, D.; JOSHI, K. Knowledge transfer in virtual systems development teams: an exploratory study of four key enablers. Professional Communication, IEEE Transactions on, 48(2):201–218, 2005. [171] SCHEDLER, A. Conceptualizing accountability. In: Schedler, A.; Diamond, L.; Plattner, M., editors, The Self-Restraining State: Power and Accountability in New Democracies, chapter I, p. 13–28. Lynne Rienner Publishers, 1999. [172] SHAH, A. Why fighting corruption remains a losing battle. In: Antho., editor, Governance, risk and compliance handbook : technology, finance, environmental and international guidance and best practices, chapter 10, p. 133–152. Jonh Wiley and Sons, 2008. [173] SHAMIR, B.; HOUSE, R. J.; ARTHUR, M. B. The motivational effects of charismatic leadership: A self-concept based theory. Organization Science November, 4(4):577–594, 1993. [174] SHAW, M.; ROBBIN, R.; BELSER, J. Group dynamics: the psychology of small group behavior. McGraw-Hill series in psychology. McGraw-Hill, 1981. [175] SIMON, D. Evolutionary Optimization Algorithms. Wiley, 2013. [176] SLAVIN, R. E. Cooperative learning. Review of Educational Research, 50(2):315– 342, 1980. [177] SLAVIN, R. E. Developmental and motivational perspectives on cooperative learning: A reconciliation. Child Development, 58:1161–1167, 1987. [178] SLAVIN, R. E. Research on cooperative learning and achievement: What we know, what we need to know. Contemporary Educational Psychology, 21(4):43–69, 1996. [179] SMITH, E. Applying knowledge enabling methods in the classroom and in the workplace. Journal of Workplace Learning, 12:236–244, 2000. [180] SPADA, H. Of scripts, roles, positions, and models. Computers in Human Behavior, 26:547–550, 2010. [181] STAHL, G.; KOSCHMANN, T.; SUTHERS, D. Computer-supported collaborative learning: An historical perspective. Cambridge handbook of the learning sciences, p. 409–426, 2006. [182] STRIJBOS, J.-W.; WEINBERGER, A. Emerging and scripted roles in computersupported collaborative learning. Computers in Human Behavior, 26(4):491 – 494, 2010. Emerging and Scripted Roles in Computer-supported Collaborative Learning . [183] TAKEUCHI, H.; NONAKA, I. Criação e dialética do conhecimento. In: Bookman., editor, Gestão do Conhecimento, chapter 1, p. 17–38. Hirotaka Takeuchi and Ikujiro Nonaka, 2009. Tradução: Ana Thorell. [184] TAMPOE, M. Exploiting the core competences of your organization. Long Range Planning, 27(4):66 – 77, 1994. [185] TARANTINO, A. Introduction. In: Tarantino, A., editor, Governance, risk and compliance handbook : technology, finance, environmental and international guidance and best practices. Jonh Wiley and Sons, 2008. [186] TEECE, D. J. Strategies for managing knowledge assets: the role of firm structure and industrial context. Long Range Planning, 33:35–54, 2000. [187] TERRACIANO, A.; ABDEL-KHALEK, A.; ADAM, N.AND ADAMOVOVA, L. A. C.; AHAN, H.; ET AL. National character does not reflect mean personality trait levels in 49 cultures. Science, 310(5745):96–100, 2005. [188] THIERENS, D.; GOLDBERG, D.; PEREIRA, A. Domino convergence, drift, and the temporal-salience structure of problems. In: Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on, p. 535–540, 1998. [189] TIDD, J.; BESSANT, J.; PAVITT, K. Managing Innovation: Integrating Technological, Market and Organizational Change. Wiley, 2011. [190] U.S. DEPT. OF ED. OFFICE OF RESEARCH, U. Cooperative learning. Internet, 1992. http://www2.ed.gov/pubs/OR/ConsumerGuides/cooplear.html, acesso em 24.06.2012. [191] VALCKE, M.; MARTENS, R. The problem arena of researching computer supported collaborative learning: Introduction to the special section. Computers & Education, 46(1):1 – 5, 2006. Methodological Issues in Researching CSCL . [192] VALLERAND, R. J.; PELLETIER, L. G.; BLAIS, M. R.; BRIÈRE, N. M.; SENÉCAL, C., V. E. F. The academic motivation scale: A measure of intrinsic, extrinsic, and a motivation in education. Educational and Psychological Measurement, 52:1003–1017, 1992. [193] VECCHIO, R. P. Leadership Understanding the Dynamics of Power and Influence in Organizations. University of Notre Dame Press, 2nd edition, 2007. [194] VONDERWELL, S. An examination of asynchronous communication experiences and perspectives of students in an online course: A case study. The Internet and Higher Education, 6(1):77–90, 2003. [195] WAKEFIELD, R.; LEIDNER, D.; GARRISON, G. A model of conflict, leadership and performance in virtual teams. Information Systems Research, 19(4):434–455, 2008. [196] WEBB, N. M. Testing a theoretical model of student interaction and learning in small groups. In: Hertz-Lazarowitz, R.; Miller, N., editors, Interaction in Cooperative Groups: The theoretical anatomy of group learning, p. 102–119+. Cambridge University Press, 1992. [197] WEBB, N. M. Predicting learning from student interaction: Defining the interaction variable. Educational Psychologist, 18:33–41, 1983. [198] WEINBERGER, A.; FISCHER, F. A framework to analyze argumentative knowledge construction in computer-supported collaborative learning. Computers & Education, 46(1):71 – 95, 2006. Methodological Issues in Researching CSCL . [199] WESSNER, M.; PFISTER, H. R. Group formation in computer-supported collaborative learning. ACM, 2001. [200] YAMAGUCHI, R.; BOS, N.; OLSON, J. Emergent leadership in small groups using computer-mediated communication. In: Proceedings of the Conference on Computer Support for Collaborative Learning: Foundations for a CSCL Community, CSCL ’02, p. 138–143. International Society of the Learning Sciences, 2002. [201] YANNIBELLI, V.; AMANDI, A. A deterministic crowding evolutionary algorithm to form learning teams in a collaborative learning context. Expert Systems with Applications, p. 8584–8592, 2012. [202] YUKL, G. Leadership in organizations. Prentice Hall, 2002. [203] ZACCARO, S.; BLAIR, V.; PETERSON, C.; ZAZANIS, M. Collective efficacy. In: Plenum Press, ., editor, Self-Efficacy, Adaptation, and Adjustment : Theory, Research, and Application (Plenum Series in Social/Clinical Psychology), chapter 11, p. 305–328. James E. Maddux, University of Michigan, May 1995. [204] ÖZGÜR YENIAY. Penalty function methods for constrained optimization with genetic algorithms. Mathematical and Computational Applications, 10(1):45–56, 2005. [205] ZHANG, M.; LADO, A. Information systems and competitive advantage: a competency based view. Technovation, 21:147–156, 2001. [206] ZIGURS, I. Leadership in virtual teams: Oxymoron or opportunity? Organizational Dynamics, 31(4):339–351, 2002.

  20. 20

    Thesis Advisors: Cardoso, Kleber Vieira, Ziviani, Artur

    Zdroj: Biblioteca Digital de Teses e Dissertações da UFGUniversidade Federal de GoiásUFG.

    Popis souboru: application/pdf

    Relation: -3303550325223384799; 600; -7712266734633644768; 3671711205811204509; 2075167498588264571; [1] Localização dos nós na Athens Wireless Metropolitan Network. http://wind.awmn.net/?page=gmap , July 2013. [2] Localização dos nós na Seattle Wireless. http://map.seattlewireless.net , July 2013. [3] AGUAYO, D.; BICKET, J.; BISWAS, S.; JUDD, G.; MORRIS, R. Link-level measurements from an 802.11b mesh network. SIGCOMM Computer Communication Review, 34(4):121–132, August 2004. [4] AIELLO, W.; CHUNG, F.; LU, L. A random graph model for massive graphs. In: Proceedings of the thirty-second annual ACM symposium on Theory of computing, STOC ’00, p. 171–180, 2000. [5] AIELLO, W.; CHUNG, F.; LU, L. Handbook of massive data sets. chapter Random evolution in massive graphs, p. 97–122. Kluwer Academic Publishers, 2002. [6] AKYILDIZ, I. F.; WANG, X.; WANG, W. Wireless mesh networks: a survey. Comput. Netw. ISDN Syst., 47(4):445–487, 2005. [7] ALBERT, R.; JEONG, H.; BARABASI, A. L. The diameter of the world wide web. Nature, 401:130–131, 1999. [8] ALMIRON, M. G.; RAMOS, H. S.; OLIVEIRA, E. M.; AO G. M. DE MENEZES, J.; GUIDONI, D. L.; STANCIOLI, P. O.; DA CUNHA, F. D.; DE AQUINO, A. L. L.; MINI, R. A. F.; FRERY, A. C.; LOUREIRO, A. A. F. Redes complexas na modelagem de redes de computadores. Minicurso SBRC, 2010. [9] AMARAL, L. A.; OTTINO, J. M. Complex networks. The European Physical Journal B-Condensed Matter and Complex Systems, 38(2):147–162, 2004. [10] ANTIQUEIRA, L.; NUNES, M. G. V.; JÚNIOR, O. N. O.; COSTA, L. F. Complex networks in the assessment of quality text. In Physics, 2005. [11] BARABÁSI, A.-L.; ALBERT, R. Emergence of scaling in random networks. Science, 286(5439):509–512, 1999. [12] BARABÁSI, A.-L.; ALBERT, R.; JEONG, H. Scale-free characteristics of random networks: the topology of the world-wide web. Physica A: Statistical Mechanics and its Applications, 281(1-4):69–77, 2000. [13] BARABASI, A.-L.; OLTVAI, Z. N. Network biology: understanding the cell’s functional organization. Nature Reviews Genetics, 5(2):101–113, 2004. [14] BENDER, E. A.; CANFIELD, E. R. The asymptotic number of labeled graphs with given degree sequences. Journal of Combinatorial Theory, Series A, 24(3):296– 307, May 1978. [15] BERMAN, K. A. Vulnerability of scheduled networks and a generalization of Menger’s Theorem. Networks, 28(3):125–134, 1996. [16] BHADRA, S.; FERREIRA, A. Complexity of connected components in evolving graphs and the computation of multicast trees in dynamic networks. In: Proc. 2nd Intl. Conference on Ad Hoc Networks and Wirelsss (AdHoc-Now), p. 259–270, 2003. [17] BIANCHI, G. Performance analysis of the IEEE 802.11 distributed coordination function. IEEE Journal on Selected Areas in Communications, 18(3):535–547, 2000. [18] BICKET, J.; AGUAYO, D.; BISWAS, S.; MORRIS, R. Architecture and evaluation of an unplanned 802.11b mesh network. In: International conference on Mobile computing and networking, p. 31–42, 2005. [19] BICKET, J. C. Bit-rate selection in wireless networks. Master’s thesis, Master of Science in Computer Science and Engineering at the Massachusetts Institute of Technology, 2005. [20] BISWAS, S.; MORRIS, R. Opportunistic routing in multi-hop wireless networks. SIGCOMM Computer Communication Review, 34(1):69–74, 2004. [21] BONACICH, P. Factoring and weighting approaches to status scores and clique identification. Journal of Mathematical Sociology, 2(1):113–120, 1972. [22] BONACICH, P. Power and centrality: a family of measures. American Journal of Sociology, 92(5):1170–1182, 1987. [23] BONACICH, P.; LLOYD, P. Eigenvector-like measures of centrality for asymmetric relations. Social Networks, 23(3):191–201, 2001. [24] BONDY, J. A.; MURTY, U. S. R. Graph theory. Springer, 2008. [25] BORGATTI, S. P. Centrality and network flow. Social Networks, 27(1):55–71, 2005. [26] BÖRNER, K.; SANYAL, S.; VESPIGNANI, A. Network science. Annual Review of Information Science and Technology, 41(1):537–607, 2007. [27] Bornholdt, S.; Schuster, H. G., editors. Handbook of graphs and networks: from the genome to the Internet. John Wiley & Sons, Inc., 2003. [28] BRANDES, U.; FLEISCHER, D. Centrality measures based on current flow. In: Conference on Theoretical Aspects of Computer Science (STACS), p. 533–544. Springer-Verlag, 2005. [29] BRIN, S.; PAGE, L. The anatomy of a large-scale hypertextual web search engine. Computer Networks and ISDN Systems, 30(1-7):107–117, 1998. [30] CALDEIRA, S. M. G. Lendo Bohr ao pé da letra: análise de elementos conceituais em escritos de Niels Bohr. Master’s thesis, Universidade Federal da Bahia, 2007. [31] Carrington, P. J.; Scott, J.; Wasserman, S., editors. Models and methods in social network analysis. Cambridge University Press, 2005. [32] CASTEIGTS, A.; FLOCCHINI, P.; QUATTROCIOCCHI, W.; SANTORO, N. Timevarying graphs and dynamic networks. International Journal of Parallel, Emergent and Distributed Systems, 2012. [33] CHAINTREAU, A.; MTIBAA, A.; MASSOULIE, L.; DIOT, C. The diameter of opportunistic mobile networks. In: Proceedings of the 2007 ACM CoNEXT conference, CoNEXT ’07, p. 1–12, 2007. [34] CHEN, Q.; HYUNSEOK, Q. C.; GOVINDAN, R.; JAMIN, S.; SHENKER, S. J.; WILLINGER, W. The origin of power laws in internet topologies revisited. In: In IEEE INFOCOM 2002, p. 608–617, 2002. [35] COHEN, J.; PIRES, K.; DUARTE JR., E. P. Medidas de conectividade baseadas em cortes de vértices para redes complexas. In: XXIX Simpósio Brasileiro de Redes e Sistemas Distribuídos (SBRC 2011), September 2012. [36] COSTA, L. D. F.; A., F.; TRAVIESO, G.; BOAS, V. P. R. Characterization of complex networks: A survey of measurements. Advances in Physics, 56(1):167– 242, 2006. [37] DIESTEL, R. Graph theory. Springer, 2006. [38] DUFFY, K.; LEITH, D. J.; LI, T.; MALONE, D. Improving fairness in multi-hop mesh networks using 802.11e. In: Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, 2006 4th International Symposium on, p. 1–8, 2006. [39] ELIANOS, F. A.; PLAKIA, G.; FRANGOUDIS, P. A.; POLYZOS, G. C. Structure and evolution of a large-scale wireless community network. In: IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks & Workshops (WoWMoM), p. 1–6, 2009. [40] ERD˝O S, P.; RÉNYI, A. On the evolution of random graphs. In: Publication of the Mathematical Institute of the Hungarian Academy of Sciences, p. 17–61, 1960. [41] ERD˝O S, P.; RÉNYI, A. On the strength of connectedness of a random graph. Acta Mathematica Hungarica, 12:261–267, 1961. [42] ERD˝O S, P.; RÉNYI, A. On random graphs. Publicationes Mathematicae Debrecen, 6:290–297, 1959. [43] EULER, L. Solutio problematis ad geometriam situs pertinentis. Commentarii academiae scientiarum Petropolitanae, 8:128–140, 1741. [44] EVERETTA, M.; BORGATTI, S. P. Ego network betweenness. Social Network, 27:31–38, 2005. [45] FALOUTSOS, M.; FALOUTSOS, P.; FALOUTSOS, C. On power-law relationships of the internet topology. SIGCOMM Computer Communication Review, 29(4):251– 262, 1999. [46] FLORY, P. J. Molecular size distribution in three dimensional polymers. III. Tetrafunctional branching units. Journal of the American Chemical Society, 63(11):3096–3100, 1941. [47] FOUNDATION, W. L. Wireless Leiden. http://www.wirelessleiden.nl , June 2012. [48] FOUNDATION, W. L. About Wireless Leiden. http://www.wirelessleiden.nl/en/about-wireless-leiden , May 2013. [49] FOUNDATION, W. L. Localização dos nós na Wireless Leiden. http://www.wirelessleiden.nl/en/coverage-map , July 2013. [50] FRANGOUDIS, P. A.; POLYZOS, G. C.; KEMERLIS, V. P. Wireless community networks: an alternative approach for nomadic broadband network access. IEEE Communications Magazine, 2011. [51] FREEMAN, L. Centrality in social networks conceptual clarification. Social Networks, 1(3):215–239, 1979. [52] FRIEDRICH, J.; FROHN, S.; GUBNER, S.; LINDEMANN, C. Understanding IEEE 802.11n multi-hop communication in wireless networks. In: International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), p. 321–326, May 2011. [53] GE, Y.; THAM, C.-K.; KONG, P.-Y.; ANG, Y.-H. Dynamic end-to-end capacity in IEEE 802.16 wireless mesh networks. Computer Network, 54:2147–2165, 2010. [54] GILBERT, E. Random graphs. The Annals of Mathematical Statistics, 30(4):1141– 1144, 1959. [55] GUEDES, D.; SILVA, E.; CARDOSO, K. Uma métrica para classificação dinâmica de nós em redes sem fio comunitárias. In: XXX Simpósio Brasileiro de Telecomunicações (SBrT 2012), September 2012. [56] GUEDES, D.; SILVA, E.; ZIVIANI, A.; CARDOSO, K. Dynamic labeling in wireless mesh networks. In: 4th IEEE Latin-American Conference on Communications (LATINCOM 2012), November 2012. [57] GUEDES, D.; ZIVIANI, A.; CARDOSO, K. Dynamic labeling in wireless mesh networks. IEEE Latin America Transactions, 11(3):948–954, 2013. [58] HODGMAN, T. C. A historical perspective on gene/protein functional assignment. Bioinformatics, 16(1):10–15, 2000. [59] HUBBELL, C. H. An input-output approach to clique identification. Sociometry, 28(4):377–399, 1965. [60] HWANG, W.; KIM, T.; RAMANATHAN, M.; ZHANG, A. Bridging centrality: graph mining from element level to group level. In: ACM international conference on Knowledge discovery and data mining (SIGKDD), p. 336–344, 2008. [61] JAMAKOVI´C, A. Characterization of complex networks – Application to robustness analysis. PhD thesis, Delft University of Technology, the Netherlands, 2008. [62] JÄRVELIN, K.; KEKÄLÄINEN, J. Cumulated gain-based evaluation of ir techniques. ACM Transactions on Information and System Security(TISSEC), 20(4):422– 446, 2002. [63] KATZ, L. A new status index derived from sociometric analysis. Psychometrika, 18(1):39–43, 1953. [64] KEMPE, D.; KLEINBERG, J.; KUMAR, A. Connectivity and inference problems for temporal networks. Journal of Computer and System Sciences, 64(4):820–842, 2002. [65] KENDALL, M. G. A new measure of rank correlation. Biometrika, 30(1-2):81–93, 1938. [66] KLEINBERG, J. The small-world phenomenon: an algorithmic perspective. In: Proceedings of the thirty-second annual ACM symposium on Theory of computing, STOC ’00, p. 163–170, 2000. [67] KRAMER, R.; LOPEZ, A.; KOONEN, A. Municipal broadband access networks in the Netherlands - three successful cases, and how New Europe may benefit. In: International conference on Access networks (AcessNets), p. 1–8, September 2006. [68] MALCZEWSKI, J.; OGRYC˙ZAK, W. An interactive approach to the central facility location problem: locating pediatric hospitals in Warsaw. Geographical Analysis, 22(3):244–258, 1990. [69] MALONE, D.; DUFFY, K.; LEITH, D. Modeling the 802.11 distributed coordination function in nonsaturated heterogeneous conditions. IEEE/ACM Transactions on Networking, 15(1):159–172, 2007. [70] MEIRELLES, A. L. S. Estratégias para aumentar a acurácia do sensoriamento de espectro baseado em sensor de energia. Master’s thesis, Universidade Federal de Goiás, 2012. [71] MELUCCI, M. Weighted rank correlation in information retrieval evaluation. In: Information Retrieval Technology, volume 5839, p. 75–86. Springer Berlin / Heidelberg, 2009. [72] MENDES, G. A. Estudo de sistemas complexos com interações de longo alcance: percolação, redes e tráfego. PhD thesis, Universidade Federal do Rio Grande do Norte, 2010. [73] MILGRAM, S. The small world problem. Psychology Today, 2:60–67, 1967. [74] MOLLOY, M.; REED, B. A critical point for random graphs with a given degree sequence. Random Structures and Algorithms, 6(2-3):161–180, 1995. [75] MONTGOMERY, D. C.; RUNGER, G. C. Applied statistics and probability for engineers, 4th Edition, and JustAsk! Set. John Wiley & Sons, 4 edition, May 2006. [76] NANDA, S.; KOTZ, D. Localized bridging centrality for distributed network analysis. In: International Conference on Computer Communications and Networks (ICCCN), p. 1–6, August 2008. [77] NANDA, S.; KOTZ, D. Social network analysis plugin (SNAP) for mesh networks. In: IEEE Wireless Communications and Networking Conference (WCNC), p. 725– 730, March 2011. [78] NETWORK SIMULATOR 3. Artigos validados no ns-3. http://www.nsnam.org/overview/publications/ , July 2013. [79] NETWORK SIMULATOR 3. Documentação do ns-3. http://www.nsnam.org/doxygen-release/index.html , July 2013. [80] NETWORK SIMULATOR 3. ns-3. http://www.nsnam.org/ , July 2013. [81] NEWMAN, M. E. J. The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences of the United States of America, 98(2):404–409, 2001. [82] NEWMAN, M. E. J. The structure and function of complex networks. SIAM REVIEW, 45:167–256, 2003. [83] NEWMAN, M. E. J.; GIRVAN, M. Finding and evaluating community structure in networks. Physical Review E, 69(2), 2003. [84] NEWMAN, M. E. J. A measure of betweenness centrality based on random walks. Social Networks, 27(1):39–54, 2005. [85] Newman, M. E. J.; Barabási, A. L.; Watts, D. J., editors. The structure and dynamics of networks. Princeton University Press, 2006. [86] NEWMAN, M.; WATTS, D. Scaling and percolation in the small-world network model. Phys. Rev. E, 60(6):7332–7342, 1999. [87] PALUMBO, M. C.; COLOSIMO, A.; GIULIANI, A.; FARINA, L. Functional essentiality from topology features in metabolic networks: a case study in yeast. FEBS Lett, 579(21):4642–4646, 2005. [88] PASTOR-SATORRAS, R.; VESPIGNANI, A. Evolution and structure of the Internet: a statistical physics approach. Cambridge University Press, 2004. [89] PINHEIRO, L.; SILVA, E. As redes cognitivas na ciência da informação brasileira: um estudo nos artigos científicos publicados nos periódicos da área. Ciência da Informação, 37(3), 2008. [90] RAPOPORT, A. Nets with distance bias. Bulletin of Mathematical Biophysics, 13:85–91, 1951. [91] RAPOPORT, A. Spread of information through a population with sociostructural bias: I. Assumption of transitivity. Bulletin of Mathematical Biology, 15(4):523–533, 1953. [92] RAPOPORT, A. Contribution to the theory of random and biased nets. Bulletin of Mathematical Biology, 19(4):257–277, December 1957. [93] REKA, A.; BARABÁSI. Statistical mechanics of complex networks. Reviews of Modern Physics, 74:47–97, 2002. [94] ROBINSON, J.; RANDHAWA, T. Saturation throughput analysis of ieee 802.11e enhanced distributed coordination function. Selected Areas in Communications, IEEE Journal on, 22(5):917–928, 2004. [95] SHIMBEL, A. Structural parameters of communication networks. Bulletin of Mathematical Biology, 15(4):501–507, 1953. [96] SHMOYS, D. B.; TARDOS, E.; AARDAL, K. Approximation algorithms for facility location problems (extended abstract). In: Proceedings of the twenty-ninth annual ACM symposium on Theory of computing, STOC ’97, p. 265–274, 1997. [97] SOLOMONOFF, R.; RAPOPORT, A. Connectivity of random nets. Bulletin of Mathematical Biology, 13(2):107–117, 1951. [98] TOREGAS, C.; SWAIN, R.; REVELLE, C.; BERGMAN, L. The location of emergency service facilities. Operations Research, 19:1363–1373, 1971. [99] VAN DRUNEN, R.; VAN GULIK, D.-W.; KOOLHAAS, J.; SCHUURMANS, H.; VIJN, M. Building a wireless community network in the netherlands. In: USENIX/Freenix Conference, p. 219–230, 2003. [100] WASSERMAN, S.; FAUST, K. Social network analysis: methods and applications. Cambridge University Press, 1994. [101] WATTS, D. J.; STROGATZ, S. H. Collective dynamics of small-world networks. Nature, 393(6684):409–10, 1998. [102] WATTS, D. J. Small worlds: The dynamics of networks between order and randomness. Princeton University Press, 1999. [103] WATTS, D. J. Six degrees: the science of a connected age (open market edition). W. W. Norton & Company, reprint edition, 2004. [104] WAXMAN, B. Routing of multipoint connections. IEEE Journal on Selected Areas in Communications, 6(1-2):1617 – 1622, 1988. [105] WEHMUTH, K.; ZIVIANI, A. Um novo algoritmo distribuído para avaliação e localização de centralidade de rede. In: Workshop em Desempenho de Sistemas Computacionais e de Comunicação (WPerformance), July 2011. [106] XUAN, B. B.; FERREIRA, A.; JARRY, A. Computing shortest, fastest, and foremost journeys in dynamic networks. International Journal of Foundations of Computer Science, 14(2):267–285, 2003. [107] YOU, L.; DONG, C.; CHEN, G.; DAI, Y.; ZHOU, W. Fhmesh: a flexible heterogeneous mesh networking platform. In: Sixth International Conference on Mobile Ad-hoc and Sensor Networks (MSN), 2010.