jist-202605192220260519222840CMV Verlagkhoffmann@cmv-verlag.comCMV VerlagJournal of Information Systems and Telecommunication (JIST) jist2322-14378272020830SaraErshadi-NasabShohrehKasaeiEsmaeilSanaeiErfanNouryHassanHafez-kolahi8272020718310.29252/jist.8.30.71http://jist.ir/en/Article/15333http://jist.ir/en/Article/Download/15333http://jist.ir/en/Article/Download/15333http://jist.ir/en/Article/Download/15333http://jist.ir/en/Article/Download/15333http://jist.ir/en/Article/Download/15333http://jist.ir/en/Article/Download/15333http://jist.ir/en/Article/Download/15333[1] E. Insafutdinov, L. Pishchulin, B. Andres, M. Andriluka, and B. Schiele, "Deepercut: A deeper, stronger, and faster multi-person pose estimation model," in European Conference on Computer Vision, 2016: Springer, pp. 34-50. [2] X. Chu, W. Yang, W. Ouyang, C. Ma, A. L. Yuille, and X. Wang, "Multi-context attention for human pose estimation," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 1831-1840. [3] A. Bulat and G. Tzimiropoulos, "Human pose estimation via convolutional part heatmap regression," in European Conference on Computer Vision, 2016: Springer, pp. 717-732. [4] S. Ershadi-Nasab, S. Kasaei, and E. Sanaei, "Regression-based convolutional 3D pose estimation from single image," Electronics Letters, vol. 54, no. 5, pp. 292-293, 2018. [5] S. E. Nasab, S. Kasaei, E. Sanaei, A. Ossia, and M. Mobini, "Multiview 3D reconstruction and human point cloud classification," in 2014 22nd Iranian Conference on Electrical Engineering (ICEE), 2014: IEEE, pp. 1119-1124. [6] L. Wang, J. Shi, G. Song, and I.-f. Shen, "Object detection combining recognition and segmentation," in Asian conference on computer vision, 2007: Springer, pp. 189-199. [7] L. Sigal, A. O. Balan, and M. J. Black, "Humaneva: Synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion," International journal of computer vision, vol. 87, no. 1-2, p. 4, 2010. [8] S. Johnson and M. Everingham, "Learning effective human pose estimation from inaccurate annotation," in CVPR 2011, 2011: IEEE, pp. 1465-1472. [9] V. Kazemi, M. Burenius, H. Azizpour, and J. Sullivan, "Multi-view body part recognition with random forests," in 2013 24th British Machine Vision Conference, BMVC 2013; Bristol; United Kingdom; 9 September 2013 through 13 September 2013, 2013: British Machine Vision Association. [10] F. Xia, J. Zhu, P. Wang, and A. L. Yuille, "Pose-guided human parsing by an and/or graph using pose-context features," in Thirtieth AAAI Conference on Artificial Intelligence, 2016. [11] P. Krähenbühl and V. Koltun, "Efficient inference in fully connected crfs with gaussian edge potentials," in Advances in neural information processing systems, 2011, pp. 109-117. [12] A. Adams, J. Baek, and M. A. Davis, "Fast high‐dimensional filtering using the permutohedral lattice," in Computer Graphics Forum, 2010, vol. 29, no. 2: Wiley Online Library, pp. 753-762. [13] N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," 2005. [14] V. Vineet, G. Sheasby, J. Warrell, and P. H. Torr, "Posefield: An efficient mean-field based method for joint estimation of human pose, segmentation, and depth," in International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, 2013: Springer, pp. 180-194. [15] M. Kiefel and P. V. Gehler, "Human pose estimation with fields of parts," in European Conference on Computer Vision, 2014: Springer, pp. 331-346. [16] S.-E. Wei, V. Ramakrishna, T. Kanade, and Y. Sheikh, "Convolutional pose machines," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 4724-4732. [17] Y. Bo and C. C. Fowlkes, "Shape-based pedestrian parsing," in CVPR 2011, 2011: IEEE, pp. 2265-2272. [18] I. Rauschert and R. T. Collins, "A generative model for simultaneous estimation of human body shape and pixel-level segmentation," in European Conference on Computer Vision, 2012: Springer, pp. 704-717. [19] P. Wang, X. Shen, Z. Lin, S. Cohen, B. Price, and A. L. Yuille, "Joint object and part segmentation using deep learned potentials," in Proceedings of the IEEE International Conference on Computer Vision, 2015, pp. 1573-1581. [20] P. Luo, X. Wang, and X. Tang, "Pedestrian parsing via deep decompositional network," in Proceedings of the IEEE international conference on computer vision, 2013, pp. 2648-2655. [21] L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille, "Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs," IEEE transactions on pattern analysis and machine intelligence, vol. 40, no. 4, pp. 834-848, 2017. [22] R. Alp Güler, N. Neverova, and I. Kokkinos, "Densepose: Dense human pose estimation in the wild," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 7297-7306. [23] Y. Chen, C. Shen, X.-S. Wei, L. Liu, and J. Yang, "Adversarial posenet: A structure-aware convolutional network for human pose estimation," in Proceedings of the IEEE International Conference on Computer Vision, 2017, pp. 1212-1221. [24] X. Peng, Z. Tang, F. Yang, R. S. Feris, and D. Metaxas, "Jointly optimize data augmentation and network training: Adversarial data augmentation in human pose estimation," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 2226-2234. [25] W. Yang, W. Ouyang, X. Wang, J. Ren, H. Li, and X. Wang, "3d human pose estimation in the wild by adversarial learning," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 5255-5264. [26] Y. Chen, Z. Wang, Y. Peng, Z. Zhang, G. Yu, and J. Sun, "Cascaded pyramid network for multi-person pose estimation," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 7103-7112. [27] M. Andriluka et al., "Posetrack: A benchmark for human pose estimation and tracking," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 5167-5176. [28] J. M. Mooij, "libDAI: A free and open source C++ library for discrete approximate inference in graphical models," Journal of Machine Learning Research, vol. 11, no. Aug, pp. 2169-2173, 2010. [29] A. Adams and J. Dolson, "ImageStack Library," https://github.com/abadams/ImageStack. [30] J. Baek, A. Adams, and J. Dolson, "Lattice-based high-dimensional gaussian filtering and the permutohedral lattice," Journal of mathematical imaging and vision, vol. 46, no. 2, pp. 211-237, 2013. [31] Y. Yang and D. Ramanan, "Articulated human detection with flexible mixtures of parts," IEEE transactions on pattern analysis and machine intelligence, vol. 35, no. 12, pp. 2878-2890, 2012. [32] V. Belagiannis, C. Amann, N. Navab, and S. Ilic, "Holistic human pose estimation with regression forests," in International Conference on Articulated Motion and Deformable Objects, 2014: Springer, pp. 20-30.NilufarTutunchiAfroozHaghbinBehradMahboobi827202011312010.29252/jist.8.30.113http://jist.ir/en/Article/15334http://jist.ir/en/Article/Download/15334http://jist.ir/en/Article/Download/15334http://jist.ir/en/Article/Download/15334http://jist.ir/en/Article/Download/15334http://jist.ir/en/Article/Download/15334http://jist.ir/en/Article/Download/15334http://jist.ir/en/Article/Download/15334[1] J. G. Andrews, S. Buzzi, W. Choi, S. V. Hanly, A. Lozano, A. C. Soong, et al., "What will 5G be?," IEEE Journal on selected areas in communications, vol. 32, pp. 1065-1082, 2014. [2] L. Dai, B. Wang, Y. Yuan, S. Han, I. Chih-Lin, and Z. Wang, "Non-orthogonal multiple access for 5G: solutions, challenges, opportunities, and future research trends," IEEE Communications Magazine, vol. 53, pp. 74-81, 2015. [3] Z. Ding, Z. Yang, P. Fan, and H. V. Poor, "On the performance of non-orthogonal multiple access in 5G systems with randomly deployed users," IEEE signal processing letters, vol. 21, pp. 1501-1505, 2014. [4] Q. Sun, S. Han, I. Chin-Lin, and Z. Pan, "On the ergodic capacity of MIMO NOMA systems," IEEE Wireless Communications Letters, vol. 4, pp. 405-408, 2015. [5] Z. Ding, F. Adachi, and H. V. Poor, "The application of MIMO to non-orthogonal multiple access," IEEE Transactions on Wireless Communications, vol. 15, pp. 537-552, 2015. [6] A. Benjebbour, K. Saito, A. Li, Y. Kishiyama, and T. Nakamura, "Non-orthogonal multiple access (NOMA): Concept and design," Signal Processing for 5G, 2016. [7] Z. Ding and H. V. Poor, "Design of massive-MIMO-NOMA with limited feedback," IEEE Signal Processing Letters, vol. 23, pp. 629-633, 2016. [8] X. Chen, A. Beiijebbour, A. Li, H. Jiang, and H. Kayama, "Consideration on successive interference canceller (SIC) receiver at cell-edge users for non-orthogonal multiple access (NOMA) with SU-MIMO," in 2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 2015, pp. 522-526. [9] J. Kim, J. Koh, J. Kang, K. Lee, and J. Kang, "Design of user clustering and precoding for downlink non-orthogonal multiple access (NOMA)," in MILCOM 2015-2015 IEEE Military Communications Conference, 2015, pp. 1170-1175. [10] S. Liu, C. Zhang, and G. Lyu, "User selection and power schedule for downlink non-orthogonal multiple access (NOMA) system," in 2015 IEEE International Conference on Communication Workshop (ICCW), 2015, pp. 2561-2565. [11] F. Rezaei, A. R. Heidarpour, C. Tellambura, and A. Tadaion, "Underlaid Spectrum Sharing for Cell-Free Massive MIMO-NOMA," IEEE Communications Letters, 2020. [12] O. Gustafsson, E. Bertilsson, J. Klasson, and C. Ingemarsson, "Approximate Neumann series or exact matrix inversion for massive MIMO?," in 2017 IEEE 24th Symposium on Computer Arithmetic (ARITH), 2017, pp. 62-63. [13] M. Wu, B. Yin, G. Wang, C. Dick, J. R. Cavallaro, and C. Studer, "Large-scale MIMO detection for 3GPP LTE: Algorithms and FPGA implementations," IEEE Journal of Selected Topics in Signal Processing, vol. 8, pp. 916-929, 2014. [14] C. H. Rycroft, "Iterative methods for linear systems," School of Engineering and Applied Sciences, Harvard University, Cambridge, 2007.LeenaChandrashekarA SreedeviAsundi82720209310410.29252/jist.8.30.93http://jist.ir/en/Article/15353http://jist.ir/en/Article/Download/15353http://jist.ir/en/Article/Download/15353http://jist.ir/en/Article/Download/15353http://jist.ir/en/Article/Download/15353http://jist.ir/en/Article/Download/15353http://jist.ir/en/Article/Download/15353http://jist.ir/en/Article/Download/15353[1] A.Prof Frank Gaillard et al. “Glioblastoma”. Article. https://radiopaedia.org/articles/glioblastoma. [2] Javier E Villanueva, Marc C Mabray, Soonmee Cha, “Current Clinical Brain Tumor Imaging”, Neurosurgery 81:397-415, 2017. [3] Olivier Keunen, Torfinn Taxt, et al., “Multimodal imaging of gliomas in context of evolving cellular and molecular therapies,” Adv. Drug Delivery Reviews, Vol.76, 2014, pp. 98-115. [4] Wolf-Dieter Heiss, Peter Raab, Heinrich Lanferman, “Multimodality Assessment of Brain Tumors and Tumor Recurrence”, J Nucl Med 2011, Vol.52, pp.1585-1600. [5] Maikel Verduin, Inge Compter, Danny Seijvers et al. “Noninvasive Glioblastoma Testing: Multimodal Approach to Monitoring and Predicting Treatment Response”. Hindawi, Disease Markers, Vol. 2018, Article ID 2908609. [6] Yin Fei, Gao Wei, Son Zongxi. “Medical Image Fusion Based on Feature Extraction and Sparse Representation”. Hindawi, International Journal of Biomedical Imaging, Vol. 2017. [7] Hui Huang, Xi’an Feng, Jionghul Jiang. “Medical Image Fusion Algorithm Based on Nonlinear Approximation of Contourlet Transform and Regional Features”. Hindwai Journal of Electrical and Computer Engineering, Vol. 2017. [8] Hiba Mzoughi, Ines Njeh, et al. “Histogram Equalization-Based Techniques for Contrast Enhancement of MRI Brain Glioma Tumor Images: Comparative Study,” in Proc. 4th. [9] International Conference on Advanced Technologies for Signal and Image Processing, ATSIP, March 21-24, 2018. [10] Bin Yang, Shutao Li, “Multifocus Image Fusion and Restoration with Sparse Restoration,” IEEE Transactions on Instrumentation and Measurement, Vol. 59, No.4, 2010. [11] Robert D Fiete. “Modelling the Imaging Chain of Digital Camera”, Image Enhancement Processing, Chap. 9, [Online], SPIE Digital Library. [12] Yakun Chang, Cheolkon Jung et al. “Automatic Contrast-Limited Adaptive Histogram Equalization with Dual Gamma Correction”, IEEE Access, Vol. 6, 2010. [13] Byong Seok Min, Dong Kyun Lim et al. “A Novel Method of Determining Parameters of CLAHE Based on Image Entropy”. International Journal of Software Engineering and Its Applications, Volume 7, No.5, pp. 113-120, 2013. [14] Monika Agarwal and Rashima Mahajan. “Medical Image Contrast Enhancement using Range Limited Weighted Histogram Equalization”, in Proc.6th International Conference on Smart Computing and Communication, ICSCC December 2017. [15] Monika Agarwal and Rashima Mahajan. “Medical Image Contrast Enhancement using Quad Weighted Histogram Equalization with Adaptive Gama Correction and Homomorphic Filtering”, in Proc. 7th International Conference on Advances in Computing & Communications, ICACC-2017. [16] Youlian Zhu, Cheng Huang. “An Adaptive Histogram Equalization Algorithm on the Image Gray Level Mapping”, in Proc. 2012 International Conference on Solid State Devices and Materials Science, Physics Procedia 25, pp.621-628. [17] K Zuiderveld. “Contrast Limited Adaptive Histogram Equalization”, in Graphics gems IV, pp474-485, San Diego, CA, USA, Academic Press Professional, Inc. [18] Hardeep Kaur, Jyothi Rani. “MRI brain image enhancement using Histogram equalization techniques”, in Proc. IEEE WISPNET, 2016. [19] Kitti Koonsanit, Saowapak Thongvigitmanee, et al. “Image Enhancement on Digital X-Ray Images using N-CLAHE”, in Proc. IEEE 10th Biomedical Engineering International Conference (BMEiCON), Aug 2017. [20] Shelda Mohan and T R Mahesh. “Particle Swarm Optimization Based Contrast Limited Enhancement for Mammogram Images”, in Proc. 7th International Conference on Intelligent Systems and Control, 2013. [21] Madhukar Bhat, Tarun Patil M S. “Adaptive Clip Limit for Contrast Limited Adaptive Histogram Equalization (CLAHE) of Medical Images using Least Mean Square Algorithm”, in Proc. International Conference on Advance Communication Control and Computing Technologies (ICACCCT), IEEE, 2014. [22] Luis G More, Macrcos A Brizuela et al. “Parameter Tuning of CLAHE-based on Multi-Objective Optimization to Achieve Different Contrast Levels in Medical Images”, in Proc. International Conference on Image Processing (ICIP), IEEE 2015. [23] Sheeba Jennifer, S Parasuraman, Amudha Kadirvelu. “Contrast Enhancement and Brightness preserving of digital mammograms using fuzzy clipped contrast-limited adaptive histogram equalization algorithm”, Applied Soft Computing Vol. 42, pp.167-177, May 2016. [24] Justin Joseph, J Sivaraman, R Periyasamy, V R Simi. “An Objective method to identify optimum clip-limit and histogram specification of contrast limited adaptive histogram equalization for MR Images,” Nalecz Institute of Biocybernetics and Biomedical Engineering 37, pp.489-497, 2017. [25] Gurshan Singh, Anand Kumar Mittal. “Controlled Bilateral Filter and CLAHE Based Approach for Image Enhancement,” International Journal of Engineering and Computer Science, Volume 3, Issue 11, Nov 2014. [26] Aziz Makandar, Bhagirathi Halalli. “Breast Cancer Image Enhancement using Median Filter and CLAHE,” in Proc. International Journal of Scientific & Engineering Research, Volume 6, Issue 4, 2015. [27] Mehemet Zeki, Sarp Erturk. “Enhancement of Ultrasound Images with Bilateral Filter and Rayleigh CLAHE”, in Proc. 23rd Signal Processing and Communications Applications Conference (SIU), Malatya, Turkey, 2015. [28] James Kennedy and Russell Eberhart. “Particle Swarm Optimization,” in Proc. International Conference on Neural Networks, 4, pp.1942-1948, IEEE 1995. [29] Malik Braik, Alaa Sheta, Aladdin Ayesh. “Image Enhancement Using Particle Swarm Optimization,” Proceedings of World Congress on Engineering, Vol. 1, London, UK, 2007. [30] Leena Chandrashekar, Sreedevi A. “Assessment of Non-Linear Filters for MRI Images,” in Proc. Second IEEE International Conference on Electrical, Computer and Communication Technologies, Feb 22-24, Coimbatore, India, 2017. [31] Leena Chandrashekar, Sreedevi A. “A Hybrid Multimodal Medical Image Fusion Technique for CT and MRI brain images,” IGI Global International Journal of Computer Vision and Image Processing (IJCVIP), Vol. 8, Issue 3, Sept 2018. [32] Leena Chandrashekar, Sreedevi A. “A Novel technique for fusing Multimodal and Multiresolution Brain Images,” in Proc. 7th International Conference on Advances in Computing and Communications, ICACC 2017, Aug 22-24, Cochin, India, 2017. [33] Leena Chandrashekar, Sreedevi A, “Leena Chandrashekar, A Sreedevi, “A Multi Objective Enhancement Technique for Poor Contrast Magnetic Resonance Images of Brain Glioma blastoma”, Third International Conference on Computing and Network Communication, CoCoNet 2019. MojtabaSharifianNedaAbdolvandSaeedehRajaee Harandi827202013013910.29252/jist.8.30.130http://jist.ir/en/Article/15407http://jist.ir/en/Article/Download/15407http://jist.ir/en/Article/Download/15407http://jist.ir/en/Article/Download/15407http://jist.ir/en/Article/Download/15407http://jist.ir/en/Article/Download/15407http://jist.ir/en/Article/Download/15407http://jist.ir/en/Article/Download/15407[1] T., Lappas, K., Liu, & E, Terzi. “A survey of algorithms and systems for expert location in social networks.” In Social Network Data Analytics (pp. 215-241). Springer, Boston, MA. 2011. [2] A., Kardan, A., Omidvar and F., Farahmandnia "Expert finding on social network with link analysis approach." In 2011 19th Iranian Conference on Electrical Engineering, pp. 1-6. IEEE, 2011. [3] A., El-Korany. “Integrated Expert Recommendation Model For Online Communities.” Arxiv preprint arxiv: 1311.3394.‏ 201. [4] A., Daud, M., Ahmad, M. S. I., Malik & D., Che. “Using machine learning techniques for rising star prediction in co-author network.” Scientometrics, Vol. 102, No. 2. 2015. pp. 1687-1711.‏ [5] L. A., Adamic, J., Zhang, E., Bakshy, & M. S., Ackerman. “Knowledge sharing and yahoo answers: everyone knows something.” In Proceedings of the 17th international conference on World Wide Web (pp. 665-674). ACM.‏ 2008, April. [6] H., Gui, Q., Zhu, L., Liu, A., Zhang, & J., Han. “Expert Finding in Heterogeneous Bibliographic Networks with Locally-trained Embeddings.” arXiv preprint arXiv: 1803.03370.‏ 2018. [7] M., Neshati, Z., Fallahnejad, & H., Beigy. “On dynamicity of expert finding in community question answering.” Information Processing & Management, Vol. 53, No. 5. 2017. pp. 1026-1042. [8] X., Ding, B., Liu & P. S., Yu “A holistic lexicon-based approach to opinion mining.” In Proceedings of the 2008 international conference on web search and data mining (pp. 231-240). ACM.‏ 200. [9] M., Karimzadehgan, R. W., White & M., Richardson. “Enhancing expert finding using organizational hierarchies.” In European Conference on Information Retrieval (pp. 177-188). Springer, Berlin, Heidelberg. 2009. [10] S. B., Sriramoju. “Heat Diffusion Based Search for Experts on World Wide Web.” International Journal of Science and Research (IJSR), https://www. Ijsr. Net/archive/v6i11/v6i11. Php, Vol. 6, No. 11. 2017. pp. 632-635.‏ [11] X., Liu, W. B., Croft & M., Koll. “Finding experts in community-based question-answering services.” In Proceedings of the 14th ACM international conference on Information and knowledge management (pp. 315-316). ACM. 2005, October. [12] S., Ravi, B., Pang, V., Rastogi & R., Kumar. “Great Question! Question Quality in Community Q&A.” ICWSM, Vol.14, No. 2014. pp. 426-435. [13] P., Brusilovsky, & E., Millán. “User models for adaptive hypermedia and adaptive educational systems.” In The adaptive web (pp. 3-53). Springer, Berlin, Heidelberg.‏ 2007. [14] K., Stephens-Martinez, M. A., Hearst & A., Fox. “Monitoring moocs: which information sources do instructors value?” In Proceedings of the first ACM conference on Learning@ scale conference, (pp. 79-88). ACM. 2014. [15] S., Yuan, Y., Zhang, J., Tang, W., Hall, & J. B., Cabotà. “Expert finding in community question answering: a review.” Artificial Intelligence Review, Vol. 53, No. 2, 2020, pp. 843-874. [16] M., Dadkhaha, M., Lagziana, F., Rahim-niaa, & K., Kimiafar. “The potential of business intelligence tools for expert finding.” Journal of Intelligence Studies in Business, Vol. 9, No. 2. 2019. pp. 82-95. [17] J., Zhang, J., Tang & J., Li. “Expert finding in a social network.” In International Conference on Database Systems for Advanced Applications, (pp. 1066-1069). Springer, Berlin, Heidelberg.‏ 2007. [18] Z., Zhao, L., Zhang, X., He & W., Ng. “Expert finding for question answering via graph regularized matrix completion.” IEEE Transactions on Knowledge and Data Engineering, Vol. 27, No. 4. 2015. pp. 993-1004. [19] P., Cifariello, P., Ferragina, & M., Ponza. “Wiser: A semantic approach for expert finding in academia based on entity linking.” Information Systems, Vol. 82 No.2019, 2019. pp. 1-16. [20] T. V., Rampisela, & E., Yulianti. “Academic Expert Finding in Indonesia using Word Embedding and Document Embedding: A Case Study of Fasilkom UI. In 2020 8th International Conference on Information and Communication Technology (ICoICT) pp. 1-6. IEEE. (2020, June). [21] A., Omidvar, M., Garakani, & H. R., Safarpour. “Context based user ranking in forums for expert finding using WordNet dictionary and social network analysis.” Information Technology and Management, Vol. 15, No. 1. 2014. pp. 51-63.‏ [22] F., Yupeng, R., Xiang, Y., Liu, M., Zhang, and Sh., Ma. "Finding experts using social network analysis." In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, pp. 77-80. IEEE Computer Society, 2007. [23] H., Ziaimatin, T., Groza, G., Bordea, P., Buitelaar, & J., Hunter. “Expertise Profiling in Evolving Knowledge curation Platforms.” GSTF Journal on Computing (JoC), Vol. 2, No. 3. 2018. pp. 118-127. [24] G., Zhou, S., Lai, K., Liu & J., Zhao. “Topic-sensitive probabilistic model for expert finding in question answer communities.” In Proceedings of the 21st ACM international conference on Information and knowledge management (pp. 1662-1666). ACM.‏ 2012. [25] M., Rafiei & A. A., Kardan. “A novel method for expert finding in online communities based on concept map and PageRank.” Human-centric computing and information sciences, Vol.5, No. 1. 2015. pp. 10-28. [26] H., Li, S., Jin & L. I., Shudong. “A hybrid model for experts finding in community question answering.” In Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2015 International Conference on (pp. 176-185). IEEE.‏ 2015. [27] G. A., Wang, J., Jiao, A. S., Abrahams, W., Fan & Z., Zhang. “Expert Rank: A topic-aware expert finding algorithm for online knowledge communities.” Decision Support Systems, Vol. 54, No. 3. 2013. pp. 1442-1451.‏ [28] Z., Dorrani, & M. S., Mahmoodi “Noisy images edge detection: Ant colony optimization algorithm.” Journal of AI and Data Mining, Vol 4, No 1. 2016. pp. 77-83. [29] M. B., Dowlatshahi & V., Derhami. “Winner Determination in Combinatorial Auctions using Hybrid Ant Colony Optimization and Multi-Neighborhood Local Search.” Journal of AI and Data Mining, Vol. 5, No 2. 2017. pp. 169-18. [30] G., Anuradha, G. L., Devi & M. P., Babu. “Antrank: An Ant Colony Algorithm for Ranking Web Pages.” International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Vol. 3, No. 2. 2014. pp. 208-212. [31] S., Setayesh, A., Harounabadi & A. M., Rahmani. “Presentation of an Extended Version of the PageRank Algorithm to Rank Web Pages Inspired by Ant Colony Algorithm.” International Journal of Computer Applications, Vol. 85, No. 17. 2014. pp. 7-10. [32] D. R., Liu, Y. H., Chen, W. C., Kao & H. W., Wang. “Integrating expert profile, reputation and link analysis for expert finding in question-answering websites.” Information processing & management, Vol. 49, No. 1. 2013. pp. 312-329.‏ [33] L., Silva, L., Goel & E., Mousavidin. “Exploring the dynamics of blog communities: the case of MetaFilter.” Information Systems Journal, Vol. 19, No.1. 2009. pp. 55-81.‏ [34] S. H., Hashemi, M., Neshati, & H., Beigy. “Expertise retrieval in bibliographic network: a topic dominance learning approach.” In Proceedings of the 22nd ACM international conference on Information & Knowledge Management (2013, October), pp. 1117-1126. [35] R., Navigli. “Word sense disambiguation: A survey.” ACM Computing Surveys (CSUR), Vol. 41, No.2. 2009. pp. 10-79. [36] M., Rowe. “Mining User Development Signals for Online Community Churner Detection.” ACM Transactions on Knowledge Discovery from Data (TKDD), Vol. 10, No. 3, 2016. pp. 1-29‏. [37] M., Neshati, D., Hiemstra, E., Asgari, & H., Beigy. „Integration of scientific and social networks.” World Wide Web, Vol. 17, No. 5, 2014. pp. 1051-1079.‏ [38] A. D., Well & J. L., Myers. Research design & statistical analysis. Psychology Press.‏ USA. 2003. [39] D., Petkova & W. B., Croft “Hierarchical language models for expert finding in enterprise corpora.” International Journal on Artificial Intelligence Tools, Vol. 17, No.1. 2008. pp. 5-18.‏AliHoseinmardySaeedehMomtazi8272020849210.29252/jist.8.30.84http://jist.ir/en/Article/15429http://jist.ir/en/Article/Download/15429http://jist.ir/en/Article/Download/15429http://jist.ir/en/Article/Download/15429http://jist.ir/en/Article/Download/15429http://jist.ir/en/Article/Download/15429http://jist.ir/en/Article/Download/15429http://jist.ir/en/Article/Download/15429[1] P. Bahar, C. Brix, H. Ney. “Towards Two-Dimensional Sequence to Sequence Model in Neural Machine Translation.” Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018, p. 3009–3015. [2] M. Bijankhan, J. Sheykhzadegan, M. Bahrani, M. Ghayoomi. “Lessons from building a Persian written corpus: Peykare”, Language Resources and Evaluation, Vol. 45, No. 2, 2011, pp. 143-164. [3] M.X. Chen, O. Firat., A. Bapna, M. Johnson, W. Macherey, G. Foster, L. Jones, N. Parmar, M. Schuster, Z. Chen, Y. Wu, M. Hughes. “The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation.” arXiv:1804.09849, 2018. [4] C.C. Chiu, T.N. Sainath, Y. Wu, R. Prabhavalkar, P. Nguyen, Z. Chen, A. Kannan, R.J. Weiss, K. Rao, E. Gonina, N. Jaitly, B. Li, J. Chorowski, M. Bacchiani, “State-of-the-Art Speech Recognition with Sequence-to-Sequence Models.”, In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018, pp. 4774-4778. [5] M. Ghayoomi, S. Momtazi, M. Bijankhan. “A study of corpus development for Persian.” International Journal on Asian Language Processing, 2010. [6] N. S. Kharusi and A. Salman, “The English Transliteration of Place Names in Oman”. Journal of Academic and Applied Studies Vol. 1, No. 3, 2011, pp. 1–27. [7] B. Li, "A Question Answering System Using Encoder-Decoder Sequence-to-Sequence Recurrent Neural Networks.", Master Thesis, The Faculty of the Department of Computer Science, San José’s State University, 2018. [8] M. Marcus, B. Santorini, M.A. Marcinkiewicz. “Building a Large Annotated Corpus of English: The Penn Treebank”, Journal of Computational Linguistics, Vo. 19, N. 2, 1993, pp. 313-330. [9] F.P. Miller, A.F. Vandome, and J. McBrewster, Levenshtein Distance: Information Theory, Computer Science, String (Computer Science), String Metric, Damerau?Levenshtein Distance, Spell Checker, Hamming Distance, 2009, Alpha Press. [10] M. Mo'in, Mo'in Encyclopedic Dictionary, Amirkabir Publisher, 1972. [11] A. Otsuka, K. Nishida, K. Bessho, H. Asano, and J. Tomita. “Query Expansion with Neural Question-to-Answer Translation for FAQ-based Question Answering”. In Proceedings of the Web Conference (WWW), 2018. pp. 1063-1068. [12] A. Rücklé, K. Swarnkar, I. Gurevych. “Improved Cross-Lingual Question Retrieval for Community Question Answering.”, In Proceedings of the Web Conference (WWW), 2019, pp. 3179-3186. [13] J. Schmidhuber, “Deep Learning in Neural Networks: An Overview”. Neural Networks. Vol. 61, 2015, 85–117. [14] L. Schubert and M. Tong. “Extracting and evaluating general world knowledge from the Brown corpus”. In Proceedings of the HLT-NAACL workshop on Text meaning, Association for Computational Linguistics, 2003, Vol. 9, pp. 7-13. [15] I. Sutskever, O.Vinyals, Q.V. Le. “Sequence to Sequence Learning with Neural Networks.” In Proceedings Neural Information Processing Systems (NIPS), 2014. [16] Terminology Department, "A collection of terms approved by the Academy of Persian Language and Literature". Vol. 6, 2009, Academy of Persian Language and Literature. Tehran. (ISBN 978-964-7531-85-6) [17] E.D. Vries, M. Schoonvelde, and G. Schumacher, “No Longer Lost in Translation: Evidence that Google Translate Works for Comparative Bag-of-Words Text Applications”. Political Analysis, Vol. 26, No. 4, 2018, pp. 417-430. [18] B. Wei, S. Lu, L. Mou, H. Zhou, P. Poupart, G. Li, Z. Jin, “Why Do Neural Dialog Systems Generate Short and Meaningless Replies? a Comparison between Dialog and Translation”, In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019. pp. 7290-7294. [19] M. Zhang, H. Li, A. Kumaran, M. Liu, “Report of NEWS 2011 Machine Transliteration Shared Task”. In Proceedings of the 5th international Joint Conference on Natural Language Processing (lJCNLP), 2011. Heshmatmorad haseliJalalHaghighatmonfared827202010511210.29252/jist.8.30.105http://jist.ir/en/Article/15459http://jist.ir/en/Article/Download/15459http://jist.ir/en/Article/Download/15459http://jist.ir/en/Article/Download/15459http://jist.ir/en/Article/Download/15459http://jist.ir/en/Article/Download/15459http://jist.ir/en/Article/Download/15459http://jist.ir/en/Article/Download/15459[1]. Constantinides, E and Fountain, S. Web 2: conceptual foundation and marketing issues. Journal of Direct, Data and Digital Marketing Practice. Vol. 9, No. 3, 2008, 231-244. [2]. Mohammed, Ph, Mohan, P. The design and implementation of an encultured web- based intelligent tutoring system for computer science education. The IEEE international Conference on advanced learning technology. 2011, 501-505. [3]. Mohammadi. Sh. designing the pattern of intelligent learning responding to Cultural diverse of students in Mehr University of alborz. Thesis of educational Management of Tehran University. 2017. [4]. Ahrens, A; Wen, M, L; Huang, Y; Zascerinska, J and Bassus, O. A comparative study of the relationship between social dimension of web 2.0 technologies and E- learning: students view in German and Taiwan. Paper presented at the 3rd International Conference on Innovation and Entrepreneurship and its implications in Engineering and Business Education, The La Consolacion College Manila, Manila, Philippines, 2010. 16 - 18 November. [5]. Trannsue, B, M. Connectivism and information literacy: moving from learning theory to pedagogical practice. Public Services Quarterly, 9:3, 2014, 185-195. [6]. Mercado, J, M; Rupp, M, A; Barbet, D & Procci, K. Intelligent Agent Transparency in Human–Agent Teaming for Multi-UxV Management. Vol. 58, No. 3, May 2016, pp. 401–415. [7]. Kumar, V; Dixit, A; Rajshekar, R & Javalgi, G. Research framework, strategies, and applications of intelligent agent technologies (IATs) in marketing. J. of the Acad. Mark. Sci. DOI 10.1007/s11747-015-0426-9. 2017. [8]. Rosenfeld, A; Agmon, N; Maksimov, O; Azaria, A & Kraus, S. Intelligent Agent Supporting Human-Multi-Robot Team Collaboration. Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015. [9]. Lemoine, P, M, P; Trentesaux, D; Rey, G, Z & Millot, P. Designing Intelligent Manufacturing Systems through Human-Machine Cooperation Principles: A Human-Centered Approach. Computers & Industrial Engineering, Volume 111, September 2017, Pages 581-595. [10]. Dermeval, D; Paiva, R; Borges, D; Bittencourt, I, I & Vassileva, J. Authoring Tools for Designing Intelligent Tutoring Systems: A Systematic Review of the Literature. International Journal of Artificial Intelligence in Education volume 28, pages336–384, 2018. [11]. Lin, Ch, F; Yeh, Y, Ch; Hung, Y, H and Chang, R, I. Developing an intelligent agent for managing web 2.0 services. International conference on future computer supported education. IEPRI, 2, 2012, 738-741. [12]. Alexander, S, Th, V. An affect-sensitive intelligent tutoring system with an animated pedagogical agent that adapts to student emotion like a human tutor. A thesis presented at Massey University, Albany, New Zealand. 2007. [13]. Anderson, T and Dron, J. Three generations of distance education pedagogy. International review of research in open and distance learning. 2011, Vol. 12.3. [14]. Blanchard, E and Frasson, C. Making intelligent tutoring systems culturally aware: the use of Hofstede’s cultural dimensions. HERON Laboratory, Computer Science Department. 2010. [15]. Brown, S. (2010). From VLEs to learning webs: the implications of Web 2.0 for learning and teaching. Interactive Learning Environments. Vol. 18, No. 1, 1–10. [16]. Hao. Y & Borich, G. A Practical Guide to Evaluate Quality of Online Courses. In Holim Song & Terry Kidd. Handbook of Research on Human Performance and Instructional Technology. New York: Information science reference. 2010. [17]. Hixon, E., Barczyk, C., Buckenmeyer, J., & Feldman, L. Mentoring university faculty to become high quality online educators: A program evaluation. Online Journal of Distance Learning Administration, 2011, 14 (5). [18]. Kaplan, A, M and Haenlein, M. Higher education and the digital revolution: About MOOCs, SPOCs, social media, and the Cookie Monster. Business horizon, 2016, 59, 441- 450. [19]. Kazemifard, M; Ghasem- Aghaee, N and Oren, T. Emotive and cognitive simulation by agents: roles of three levels of information processing. Cognitive systems research, 2011, 13, 24-38. [20]. Rocker, C; Janse, M; Portolm, N and Streitz, N. User requirements for intelligent home environments: A scenario-driven approach and empirical cross-cultural study. Published in: proceeding of the 2014 joint conference on intelligent objects and ambient intelligence, 2014, 111-116. [21]. Mazadi, Z; Ghasem Aghaee, N and Oren, T. Prelude to cultural software agents: cultural backgrounds in agent simulation. Conference: Proceedings of the Spring Simulation Multi conference. 2008, 135-142. [22]. Creswell J. w. Educational research: planning, conducting and evaluating quantitative and qualitative research. (Fourth edition). Pearson. Boston. 2012.Alireza shirmarzAliGhaffari827202012112910.29252/jist.8.30.121http://jist.ir/en/Article/15462http://jist.ir/en/Article/Download/15462http://jist.ir/en/Article/Download/15462http://jist.ir/en/Article/Download/15462http://jist.ir/en/Article/Download/15462http://jist.ir/en/Article/Download/15462http://jist.ir/en/Article/Download/15462http://jist.ir/en/Article/Download/15462[1] J. Pan, S. Paul, and R. Jain, “A survey of the research on future internet architectures,” Commun. Mag. IEEE, vol. 49, no. 7, pp. 26–36, 2011. [2] H. Qi and K. Li, Software Defined Networking Applications in Distributed Datacenters. Dalian, China: Engineering, SpringerBriefs in Electrical and Computer, 2016. [3] N. Feamster, J. Rexford, and E. Zegura, “The Road to SDN: An Intellectual History of Programmable Networks,” ACM Sigcomm Comput. Commun., vol. 44, no. 2, pp. 87–98, 2014. [4] R. Masoudi and A. Ghaffari, “Software defined networks: A survey,” J. Netw. Comput. Appl., vol. 67, no. May, pp. 1–25, 2016. [5] A. K. Singh, “A survey and classification of controller placement problem in SDN,” Int. J. Netw. Manag., no. December 2017. [6] S. Bera, S. Misra, and A. V. Vasilakos, “Software-Defined Networking for Internet of Things: A Survey,” IEEE Internet Things J., vol. 4662, pp. 1–1, 2017. [7] Y. E. Oktian, S. Lee, H. Lee, and J. Lam, “Distributed SDN Controller System: A Survey on Design Choice,” Comput. Networks, vol. 121, pp. 100–111, 2017. [8] A. Shirmarz and A. Ghaffari, “Performance issues and solutions in SDN-based data center: a survey,” J. Supercomput., 2020. [9] A. T. Oliveira, B. Jos, C. A. Martins, M. F. Moreno, and A. B. Vieira, “SDN-Based Architecture for Providing QoS to High-Performance Distributed Applications,” in IEEE Symposium on Computers and Communications (ISCC), 2018. [10] O. Aldhaibani, F. Bouhafs, M. Makay, and A. Raschellà, “An SDN-based Architecture for Smart Handover to Improve QoE in IEEE 802. 11 WLANs,” in 2018 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA), 2014, pp. 287–292. [11] I. Engineering, “Enhancing the performance of future wireless networks with software-defined networking ∗,” Front. Inf. Technol. Electron. Eng., vol. 17, no. 7, pp. 606–619, 2016. [12] T. Shozi, P. Mudali, and O. Matthew, “An SDN Solution for Performance Improvement in Dedicated Wide- Area Networks,” in 2019 Conference on Information Communications Technology and Society (ICTAS), pp. 1–6. [13] J. W. Kleinrouweler, S. Cabrero, and P. Cesar, “Delivering Stable High-Quality Video : An SDN Architecture with DASH Assisting Network Elements Categories and Subject Descriptors,” in Proceedings of the 7th International Conference on Multimedia Systems, 2016. [14] W. Wendong, Q. I. Qinglei, G. Xiangyang, H. U. Yannan, and Q. U. E. Xirong, “Autonomic QoS Management Mechanism in Software Defined Network,” China Commun., no. July, pp. 13–23, 2014. [15] G. Poulios, K. Tsagkaris, P. Demestichas, A. Tall, Z. Altman, and C. Destré, “Autonomics and SDN for self-organizing networks,” 11th Int. Symp. Wirel. Commun. Syst. ISWCS 2014 - Proc., pp. 830–835, 2014. [16] P. Neves et al., “The SELFNET Approach for Autonomic Management in an NFV/SDN Networking Paradigm,” Int. J. Distrib. Sens. Networks, vol. 2016, no. 4, 2016. [17] IBM, “Autonomic Computing White Paper: An Architectural Blueprint for Autonomic Computing,” IBM White Pap., no. June, p. 34, 2005. [18] V. W. Protocol, “OpenFlow Switch Specification,” 2012. [19] C. Zhang and X. Wang, “Deep learning-based network application classification for SDN,” Trans. Emerg. Telecommun. Technol. Wiley Online Libr. J., no. February 2018. [20] A. Shirmarz and A. Ghaffari, “An adaptive greedy flow routing algorithm for performance improvement in a software-defined network,” Int. Numer. Model. Electron. networks, Devices, Fields-Wiley online Libr., no. March, pp. 1–21, 2019. [21] T. Auld, A. W. Moore, and S. F. Gull, “Bayesian Neural Networks for Internet Traffic Classification,” IEEE Trans. Neural Networks, vol. 18, no. 1, pp. 223–239, 2007.