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Haocheng Shen, Jason Yosinski, Petar Kormushev, Darwin G. Caldwell and Hod Lipson

, J. C. Zagal, H. Lipson. Evolving Robot Gaits in Hardware: the Hyperneat Generative Encoding Vs. Parameter Optimization. - In: Proceedings of the 20th European Conference on Artificial Life, 2011. 13. Zykov, V., J. Bongard, H. Lipson. Evolving Dynamic Gaits on a Physical Robot. - In: Proceedings of Genetic and Evolutionary Computation Conference, Late Breaking Paper, GECCO, Vol. 4 , 2004.

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Zhang Hui and You Fei

Graphs for Testing Community Detection Algorithms. - Physical Review E, Vol. 78, 2008, No 4. 18. Zachary, W. W. An Information Flow Model for Confict and Fission in Small Groups. - J. Anthropol. Res., 1977, 452-473. 19. Lusseau, D., K. Schneider, O. J. Boisseau, P. Haase, E. Slooten, S. M. Dawson. The Bottlenose Dolphin Community of Doubtful Sound Features a Large Proportion of Long-Lasting Associations. - Behavioral Ecology and Sociobiology, Vol. 54, 2003, No 4, 396-405. 20. Newman, M. E. J. Finding Community Structure

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S. Cheresharov, H. Krushkov, S. Stoyanov and I. Popchev

. – Cybernetics and Information Technologies, Vol. 11 , 2011, No 2, pp. 46-64. 4. Stancheva, N., A. Stoyanova-Doycheva, S. Stoyanov, I. Popchev, V. Ivanova. A Model for Generation of Test Questions. – Compt. Rend. Acad. bulg. Sci., Vol. 70 , 2017, No 5, pp. 619-630. 5. Stancheva, N., A. Stoyanova-Doycheva, S. Stoyanov, I. Popchev, V. Ivanova. An Environment for Automatic Test Generation. – Cyberbetics and Information Technologies, Vol. 17 , 2017, No 2, pp. 183-196. 6. Stoyanov, S., I. Ganchev, I. Popchev, M. O’Droma. An Approach for the Development of

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Cunjiang Yu

-151. 4. Guibas, L. J. Tracking, Sensing and Reasoning with Relations. – IEEE Signal Processing Manazine, Vol. 19 , February 2002, pp. 73-85. 5. Rabaey, M. J., M. Ammer. Picoradio Supports Ad Hoc Ultra-Low Power Wireless Networking. –IEEE Computer Magazine, Vol. 33 , May 2000, pp. 42-48. 6. Warneke, B., M. Last. Communicating with a Cubic-Millimeter Computer. – IEEE Computer, Vol. 34 , May 2001, pp. 44-51. 7. Shih, E., C. Ickesn. Physical Layer Driven Protocol and Algorithm Design for Energy-Efficient Wireless Sensor Networks. – In: Proc. of ACM

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Wenju Wang, Zhang Xuan, Liujie Sun, Zhongmin Jiang and Jingjing Shang

References 1. Yu, Kanhua. Urban Planning Support System Based on Three Dimensional GIS. - IAES TELKOMNIKA Indonesian Journal of Electrical Engineering, Vol. 12, 2014, No 5, pp. 3928-3935. 2. Li, Chang, W. Shi, F. Li. The Scheme and the Preliminary Test of Object-Oriented Simultaneous 3D Geometric and Physical Change Detection Using GIS-Guided Knowledge. - Telkomnika - Indonesian Journal of Electrical Engineering, Vol. 11, 2013, No 12, pp. 7462-7469. 3. Toscano, E. S. A., V. Sorengo. 2Dand 3D GIS-Based Geological

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Xin-Hua Wang, Yu-Lin Jiao, Yong-Chao Niu and Jie Yang

/Shell Leakage Flow on Heat Transfer in Shell-and-Tube Heat Exchangers. – Experimental Thermal and Fluid Science, Vol. 8 , January 1994, Issue 1, pp. 10-20. 9. M. F. El-Amin, H. Kanayama. Boundary Layer Theory Approach to the Concentration Layer Adjacent to a Ceiling Wall at Impinging Region of a Hydrogen Leakage. – International Journal of Hydrogen Energy, Vol. 33 , November 2008, Issue 21, pp. 6393-6400. 10. Or, S. W., H. L. W. Chan, C. L. Choy. P(VDF-TrFE) Copolymer Acoustic Emission Sensors. – Sensors and Actuators A: Physical, Vol. 80 , 15 March 2000, Issue

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Wael Alosaimi, Michal Zak, Khalid Al-Begain, Roobaea Alroobaea and Mehedi Masud

3. Alosaimi, W., K. Al-Begain. A New Method to Mitigate the Impacts of Economical Denial of Sustainability Attacks Against the Cloud. - In: Proc. of 14th Annu. Post. Grad. Symp. Converg. Telecommun. Netw. Broadcating. Liverpool John Moores University, Liverpool, UK, 2013, pp. 116-121. 4. Aslan, T. Cloud Physical Security Considerations. IBM Cloud, 2012 [Cited 15 February 2017]. http://thoughtsoncloud.com/index.php/2012/02/cloud-physical-security-considerations/ 5. Beitollahi, H., G. Deconinc k. FOSe L: Filtering by Helping an

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Ivars Namatēvs, Ludmila Aleksejeva and Inese Poļaka

Entertainment Artist Using Clustering and Classification Approaches,” International Journal of Electronic Business Management, vol. 10, no. 4, 2012, pp. 274-285. [24] B. Ofoghi, J. Zeleznikowa, C. MacMahon and M. Raab, “Data Mining in Elite Sports: A review and a Framework,” Measurement in Physical Education and Exercise Science, vol. 17, 2013, pp. 171-186. Available: EBSCO. https://doi.org/10.1080/1091367X.2013.805137 [25] S. Provorovs and A. Borisov, “Use of Linear Genetic Programming and Artificial Neural Network Methods to Solve

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Anuj Kumar Singh and B. D. K. Patro

Intelligence and Informatics. Advances in Intelligent Systems and Computing, Springer, Singapore. Vol. 507 . 2016, pp. 221-230. 68. Wang, Q., T. Dunlap, Y. Cho, G. Qu. DoS Attacks and Countermeasures on Network Devices. – In: Proc. of 26th Wireless and Optical Communication Conference (WOCC’17), Newark, 2017, pp. 1-6. 69. Gassend, B., D. Clarke, M. V. Dijk, S. Devadas. Silicon Physical Random Functions. – In: Proc. of 9th ACM Conference on Computer and Communications Security. ACM, 2002, pp. 148-160. 70. Standaert, F. X. Introduction to Side

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Chunjuan Luan and Alan L. Porter

.000 0.568 8 Physics_Condensed_Matter 3.000 0.568 9 Chemistry_Physical 2.333 0.442 10 Materials_Science_Characterization_&_Testing 2.000 0.379 11 Biotechnology_&_Applied_Microbiology 1.500 0.284 12 Physics_Fluids_&_Plasmas 1.000 0.189 13 Biochemical_Research_Methods 1.000 0.189 14 Engineering_Manufacturing 0.333 0.063 It is notable that Material Science Multidisciplinary plays a very important role with a much higher nbetweenness value than the other WCs—except for