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REFERENCES 1. Abdul Waheed Khan, Abdul Hanan Abdullah, Mohammad Abdur Razzaque, and Javed Iqbal Bangash. VGDRA: A Virtual Grid-Based Dynamic Routes Adjustment Scheme for Mobile Sink-Based Wireless Sensor Networks , IEEE SENSORS JOURNAL, VOL. 15, NO. 1, JANUARY 2015 2. Ravinder Kaura, Kamal Preet Singhb. An Efficient Multipath Dynamic Routing Protocol for Mobile WSNs, International Conference on Information and Communication Technologies (ICICT 2014) , Procedia Computer Science 46 (2015) 1032–1040 3. Tapan Kumar Jain, Davinder Singh Saini, and Sunil Vidya

makes use of data related to scientific activities to help the development of the sciences, and for that purpose, we need a framework to represent relational data and to answer the questions that are potentially helpful to the development of other sciences. We claim that this framework is a network. Of course, we notice that many other scientometric studies have already looked into regularities or laws of various scientific activities aiming to help the development of other sciences and also scientometrics as a science, rather than directly working towards evaluation

References 1. Akinc, U., Khumawala, B.M. (1977) An Efficient Branch and Bound Algorithm for the CapacitatedWarehouse Location Problem. Management Science, Vol. 23, Issue 6, pp. 585-594 2. Altiparmak, F., Gen, M., Lin L., Paksoy, T. (2006) A genetic algorithm approach for multi-objective optimization of supply chain networks. Computers & Industrial Engineering, Vol. 51, pp. 196-215 3. Ambrosino, D., Scutella M.G. (2005) Distribution network design: New problems and related models. European Journal of Operational Research, Vol. 165, pp. 610-624 4. Anikin, B

1 Introduction Complex network theory has become an important paradigm to interpret problems in computer science, sociology, biology and many other areas. The research of complex network theory focused on aspects of the general features of network topology, topology generation mechanism, the network dynamics, and has achieved fruitful results. In recent years, peer to peer network (Peer-to-Peer, P2P) itself and its network environment both showed explosive complex growth, traditional ideas, techniques and methods for constructing P2P system are facing serious

, Artificial Intelligence 72(1-2): 329-365. Isham V. (1981). An introduction to spatial point processes and Markov random fields, International Statistical Review 49(1): 21-43. Jensen F. V. (2001). Bayesian Networks and Decision Graphs , Springer, New York, NY. Kuncheva L. (2000). Fuzzy Classifier Design , Physica-Verlag, Heidelberg. Lauritzen S. L. (1982). Lectures on Contingency Tables, 2nd Edn. , University of Aalborg Press, Aalborg. Moczulski W. (2004). Methods of acquisition of diagnostic knowledge, in J. Korbicz, J. Kościelny, Z. Kowalczuk and W. Cholewa (Eds

References 1. Ahern, K. R. (2012), “Bargaining Power and Industry Dependence in Mergers”, Journal of Financial Economics, Vol. 103, No.3, pp. 530–550. 2. Ahern, K. R., Harford, J. (2014), “The Importance of Industry Links in Merger Waves”, Journal of Finance, Vol. 69, No.2, pp. 527–576. 3. Ahuja, G. (2000), “Collaboration networks, structural holes, and innovation: a longitudinal study”, Administrative Science Quarterly, Vol. 45, pp. 425–455. 4. Aoibda, D., Caskey, J., Ozel, N. B. (2014), “Inter-Industry Network Structure and the Cross-Predictability of Earnings

References [1] Altrichter M., Horváth G. et. al.: Neurális hálózatok . Hungarian Edition Panem Könyvkiadó Kft., Budapest, 2006. [2] Krizhevsky A., Hinton G.: Learning multiple layers of features from tiny images .” Master’s Thesis. University of Toronto, Toronto, Canada, 2009. [3] Nair V., Hinton G. E.: Rectified linear units improve restricted boltzmann machines . In Proc. 27th International Conference on Machine Learning, 2010. [4] Krizhevsky, A. I. Sutskever, et. al.: ImageNet Classification with Deep Convolutional Neural Networks. Advances in Neural

-8281, DOI: 10.2478/jok. [3] Laskowski D., Łubkowski P.: Confidential transportation of data on the technical state of facilities, Advances in Intelligent Systems and Computing, Springer International Publishing AG, Switzerland, Volume 286, 2014, pp. 313-324, ISSN 2194-5357, ISBN 978-3-319-07012-4 (Print) 978-3-319-07013-1 (Online), DOI 10.1007/978-3-319-07013-1_31. [4] Łubkowski P., Laskowski D.: Test of the multimedia services implementation in in-formation and communication networks, Advances in Intelligent Systems and Computing, Springer International Publishing AG

References [1] D. Amic, D. Beslo, B. Lucic, S. Nikolic, N. Trinajsti ć , The vertex-connectivity index revisited, J. Chem. Inf. Comput. Sci. 38 (1998) 819-822 [2] L.F. Araghi, H. Khaloozade, M.R. Arvan, Ship identification using probabilistic neural networks. In: Proceedings of the international multiconference of engineers and computer scientists, 2(2009), 18-20 [3] M. Azari, A. Iranmanesh, Generalized Zagreb index of graphs, Studia Univ. Babes-Bolyai. 56 (3) (2011) 59-70 [4] M. Ba č a, J. Horv á thov á , M. Mokri š ov á , Andrea Semani č ov á -Fe ň ov č kov á

References Baarda, W. (1967). Statistical concepts in geodesy , volume 2 of Publication on Geodesy, New Series . Netherlands Geodetic Commision. Baarda, W. (1968). A testing procedure for use in geodetic networks , volume 2 of Publication on Geodesy, New Series . Netherlands Geodetic Commision. Grafarend, E. W. (1974). Optimization of geodetic networks. Bolletino di Geodesia a Science Affini , 33(4):351–406. Nowak, E. (2011). Reliability design of geodetic networks by quality harmonization of observations. Reports on Geodesy , 90(1):341–347. Prószyński, W