jist-202605192320260519232534CMV Verlagkhoffmann@cmv-verlag.comCMV VerlagJournal of Information Systems and Telecommunication (JIST) jist2322-14371122020726MortezaJaderyanHassanKhotanlou112202012013310.7508/jist.2019.02.004http://jist.ir/en/Article/15287http://jist.ir/en/Article/Download/15287http://jist.ir/en/Article/Download/15287http://jist.ir/en/Article/Download/15287http://jist.ir/en/Article/Download/15287http://jist.ir/en/Article/Download/15287http://jist.ir/en/Article/Download/15287http://jist.ir/en/Article/Download/15287[1] M. Fernández, I. Cantador, V. López, D. Vallet, Pablo Castells, E. Motta, “Semantically enhanced Information Retrieval: An ontology-based approach”, Web Semantics: Science, Services and Agents on the World Wide Web 9, 434–452, 2011. [2] M. R. Bouadjeneka, H. Hacidc, M. Bouzeghoubd, “Social networks and information retrieval, how are they converging? A survey, a taxonomyand an analysis of social information retrieval approaches and platforms”, Information Systems, Vol. 56, 1-18, 2016. [3] B. Steichen, H. Ashman, V. Wade, “A comparative survey of Personalized Information Retrieval and Adaptive Hypermedia techniques”, Information Processing and Management, Vol. 48, 698–724, 2012. [4] S. Kara, Ö. Alan, O. Sabuncu, S. Akpınar, N. K. Cicekli, F.N. Alpaslan, “An ontology-based retrieval system using semantic indexing”, Information Systems, Vol. 37, 294-305, 2012. [5] A. N. Jamgade, and J. K. Shivkumar, "Ontology based information retrieval system for Academic Library." International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), IEEE, 2015. [6] T. Roelleke, “Synthesis Lectures on Information Concepts, Retrieval, and Services”, Morgan & Claypool Publishers, 2013. [7] Z. Hengxiang, J. Lafferty, “A Study of Smoothing Methods for Language Models Applied to Ad Hoc Information Retrieval”, SIGIR Forum, Vol. 51, 268-276, 2017. [8] K.M. Kim, J.H. Hong, S.B. Cho, “A semantic Bayesian network approach to retrieving information with intelligent conversational agents”, Information Processing & Management,Vol.43,225–236, 2007. [9] Y. Bassil, P. Semaan, “Semantic-Sensitive Web Information Retrieval Model for HTML Documents”, European Journal of Scientific Research, Vol. 69, 1-11, 2012. [10] S.N. B. Bhushan, A. Danti, “Classification of text documents based on score level fusion approach”, Pattern Recognition Letters, Vol. 94, 118-126, 2017. [11] F. Ramli, S. A. Noah, T. B. Kurniawan, "Ontology-based information retrieval for historical documents", 2016 Third International Conference on Information Retrieval and Knowledge Management (CAMP), 2016. [12] M. Daoud, L. Tamine, M. Boughanem, “A personalized search using a semantic distance measure in a graph-based ranking model”, Journal of Information Science, Vol. 37, 614–636, 2011. [13] D. Laura, A. Kotov, and E. Meij, "Utilizing knowledge bases in text-centric information retrieval", In Proceedings of ACM International Conference on the Theory of Information Retrieval., 2016. [14] M. Banko, O. Etzioni, “The tradeoffs between open and traditional relation extraction”, in Proceedings of ACL-08: HLT, Association for Computational Linguistics, 2008. [15] B. Mitra, N. Craswel, “Neural Text Embeddings for Information Retrieval”, In Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, WSDM '17, 2017. [16] F. Gutierrez, D. Dejing, F. Stephen, W. Daya, Z. Hui. "A hybrid ontology-based information extraction system", Journal of Information Science, Vol. 42, 798-820, 2016. [17] Y. Gupta, A. Saini, A.K. Saxena, “A new fuzzy logic based ranking function for efficient Information Retrieval system”, Expert Systems with Applications, Vol. 42, 1223-1234, 2015. [18] M. Daoud, L. Tamine, M. Boughanem, “Towards a graph based user profile modeling for a session-based personalized search”, Knowledge and Information Systems Vol. 21, 365-398, 2009. [19] G-J. Hahm, J-H. Lee, H-W. Suh, “Semantic relation based personalized ranking approach for engineering document retrieval”, Advanced Engineering Informatics, Vol. 29, 366-379, 2015. [20] Z. Wu, H. Zhu, G. Li, Z. Cui, H. Huang, J. Li, E. Chen, G. Xu, “An efficient Wikipedia semantic matching approach to text document classification”, Information Sciences, Vol. 393, 15-28, 2017. [21] J. Yun, L. Jing, J. Yu, H. Huang, “A multi-layer text classification framework based on two-level representation model”, Expert Systems with Applications, Vol. 39, 2035-2046, 2012. [22] C. Jiang, F. Coenen, R. Sanderson, M. Zito, “Text classification using graph mining-based feature extraction”, Knowledge Based Systems, vol. 23, 302-308, 2010. [23] H. K. Kim, H. Kim, and S. Cho, “Bag-of-concepts: Comprehending document representation through clustering words in distributed representation.”, Neurocomputing, vol. 266, 336-352, 2017. [24] W. Jin, Z. wang, D. zhang, J. Yan, "Combining Knowledge with Deep Convolutional Neural Networks for Short Text Classification.", Proceedings of the 26th International Joint Conference on Artificial Intelligence. AAAI Press, 2017. [25] Y. Li, B. Wei, Y. Liu, L. Yao, H. Chen, J. Yu, W. Zhu, “Incorporating Knowledge into neural network for text representation”, Expert Systems With Applications, In Press - Accepted Manuscript, 2017. [26] <http://www.loa.istc.cnr.it/DOLCE.html#OntoWordNet>, “Laboratory for applied ontology - DOLCE”, last visited on 19 Feb 2013. [27] L. Meng, R. Huang, J. Gu, “A review of semantic similarity measures in wordnet,” International Journal of Hybrid Information Technology, vol. 6, 1-12, 2013. [28] P. Kolb, “DISCO: A Multilingual Database of Distribution-ally Similar Words”, In Proceedings of 9th Conference in Natural Language, 2008. [29] B. T. McInnes, T. Pedersen, “Evaluating measures of semantic similarity and relatedness to disambiguate terms in biomedical text”, Journal of Biomedical Informatics, Vol. 46, 1116-1124, 2013. [30] S. Pyysalo, “Part-of-Speech Tagging”, In: Dubitzky W., Wolkenhauer O., Cho KH., Yokota H. (eds) Encyclopedia of Systems Biology, Springer, 2013. [31] C. Manning, M. Surdeanu, J. Bauer, J. Finkel, S. Bethard, D. McClosky.,”The Stanford CoreNLP Natural Language Processing Toolkit”, In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, System Demonstrations, 2014. [32] J. Hakenberg, “Named Entity Recognition”, In: Dubitzky W., Wolkenhauer O., Cho KH., Yokota H. (eds) Encyclopedia of Systems Biology, Springer, 2013. [33] B. Mohit, “Named Entity Recognition. In: Zitouni I. (eds) Natural Language Processing of Semitic Languages”, Theory and Applications of Natural Language Processing, Springer, 2014. [34] J. Vilares, M. A. Alonso, M. Vilares, “Extraction of complex index terms in non-English IR: A shallow parsing based approach”, Information Processing & Management, Vol. 44, 1517-1537, 2008. [35] S.K. Saritha, R.K. Pateriya, “Rule-Based Shallow Parsing to Identify Comparative Sentences from Text Documents”, In: Shetty N., Prasad N., Nalini N. (eds) Emerging Research in Computing, Information, Communication and Applications, Springer, 2016. [36] M. Baziz, M. Boughanem, S. Traboulsi, “A Concept-based Approach for Indexing in IR”, in the proceedings of INFORSID05, 2005. [37] C. Biemann, S. P. Ponzetto, S. Faralli, A. Panchenko, and E. Ruppert, “Unsupervised Does Not Mean Uninterpretable: The Case for Word Sense Induction and Disambiguation.,” in EACL, 2017. [38] W. Cohen , P. Ravikumar, S. Fienberg, “A comparison of string distance metrics for name-matching tasks”, American Association for Artificial Intelligence, 73-78, 2003. [39] Lang, K. “The 20 Newsgroups data set, version 20news-18828”, [last update on Jan 14, 2017], [Online] Available: <http://www. qwone.com/~jason/20Newsgroups>. [40] N. Seco, T. Veale, J. Hayes., “An Intrinsic Information Content Metric for Semantic Similarity in WordNet”, In Proceedings of European Chapter of the Association for Computational Linguistics, 2004. [41] W. Zhang, X. Tang, T. Yoshida, “TESC: An approach to TExt classification using Semi-supervised Clustering”, Knowledge-Based Systems, Vol. 75, pp. 152-160, 2015. [42] S. Langer, J. Beel, “Apache Lucene as Content-Based-Filtering Recommender System: 3 Lessons Learned.”, 5th International Workshop on Bibliometric-enhanced Information Retrieval, 2017. [43] R. Song, S. Chen, B. Deng, and L. Li, “eXtreme Gradient Boosting for Identifying Individual Users Across Different Digital Devices”, In Proceedings of WAIM, Vol. 9658, pp. 43–54, 2016. [44] Q. Wu, Y. Ye, H. Zhang, M. Ng and S. Ho, “ ForesTexter: An efficient random forest algorithm for imbalanced text categorization”, Knowledge-Based Systems, Vol. 67, pp.105-116, 2014. [45] G. Rao, W. Huang, Z. Feng and Q. Cong, “LSTM with sentence representations for document-level sentiment classification”, Neurocomputing, Vol. 308, pp.49-57, 2018. [46] C . Olah, “Understanding LSTM Networks”, [last update on Aug 27, 2015], [Online] Available: <http://colah.github.io/posts/2015-08-Understanding-LSTMs/s>, [Retrieved on Nov 01, 2018]. [47] P. Srivastava, “Essentials of Deep Learning : Introduction to Long Short Term Memory”, [last update on Dec 10, 2017], [Online] Available: < https://www.analyticsvidhya.com/blog/2017/12/fundamentals-of-deep-learning-introduction-to-lstm/ >, [Retrieved on Nov 01, 2018.MaryamNajimi112202013414310.7508/jist.2019.02.005http://jist.ir/en/Article/15291http://jist.ir/en/Article/Download/15291http://jist.ir/en/Article/Download/15291http://jist.ir/en/Article/Download/15291http://jist.ir/en/Article/Download/15291http://jist.ir/en/Article/Download/15291http://jist.ir/en/Article/Download/15291http://jist.ir/en/Article/Download/15291[1] R. Zhang and Y.-C. Liang, "Investigation on multiuser diversity in spectrum sharing based cognitive radio networks", IEEE Commu. Lett., Vol. 14, No. 2, 2010,pp. 133–135. [2] R. Zhang, Y.-C. Liang, and S. Cui, "Dynamic resource allocation in cognitive radio networks", IEEE Sig. Proc. Mag., Vol. 27, No. 3,2010,pp. 102–114. [3] A. Attar, H.Tang, A.V. Vasilakos, F.R, Yu and V.C.M Leung, " A Survey of Security Challenges in Cognitive Radio Networks: Solutions and Future Research Directions", IEEE Proc., 2012, pp. 3172–3186. [4] J. Wang, J.Chen and D. Cabric, "Cramer-Rao Bounds for Joint RSS/DoA-Based Primary-User Localization in Cognitive Radio Networks", IEEE Trans. Wirel. Commun. Vol.12, 2013, pp.1363–1375. [5] F.Ye, Y.Li, R.Yang and Z. Sun, "The user requirement based competitive price model for spectrum sharing in cognitive radio networks", Int. J. Distrib. Sens. Netw, 2013, doi:10.1155/2013/724581. [6] J. Haupt, W. Bajwa, M. Rabbat, and R. Nowak, "Compressed sensing for networked data", IEEE Signal Processing Magazine, Vol. 25, No. 2, 2008,pp. 92-101. [7] Z. Tian and G. Giannakis, "Compressed sensing for wideband cognitive radios", IEEE International Conference on Acoustics, Speech and Signal Processing, 2007, Vol. 4, pp. 1357–1360. [8] F. Salahdine, N. Kaabouch and H.EI.Ghazi, " A survey on compressive sensing techniques for cognitive radio networks", Journal of Physical Commuincations, Vol.20, pp.61-73, 2016. [9] Th. Wimalajeewa, P. K. Varshney, "Application of compressive sensing techniques in distributed sensor networks:A survey",Electrical Engineering and Systems Science Journal, Last revised 19 Jan 2019. [10] Sh. Salim and S. Moh, "An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks", Sensors Journal, 2016 ,pp.1-20. [11] S.H.Hojjati, A.Ebrahimzadeh, S.M.H.Anadroli and M.Najimi, "Energy efficient cooperative spectrum sensing in wireless multi-antenna sensor networks", Springer Wireless Netw. Journal, 2017, pp. 567–578. [12] N. Radhi, K. Aziz MIET, S. Hamad 3,H.S.AL-Raweshidy, "Estimate primary user localization using cognitive radio networks", IEEE on International Conference on Innovations in Information Technology,2011,pp.381-385. [13] J. Werner, J. Wang, A.Hakkarainen, M. Valkama and D. Cabric, "Primary User Localization in Cognitive Radio Networks Using Sectorized Antennas", IEEE on 10th Annual Conference on Wireless On-demand Network Systems and Services (WONS),2013,pp.155-161. [14] X. Li, V. Chakravarthy, and Z. Wu, "Joint Spectrum Sensing and Primary User Localization for Cognitive Radio via Compressed Sensing", in Proc. of IEEE MILCOM, San Jose, California, 2010. [15] J. A. Bazerque and G. B. Giannakis, "Distributed spectrum sensing for cognitive radio networks by exploiting sparsity", IEEE Transations on Signal Processing, Vol. 58, No. 3, 2010, pp. 1847-1862. [16] W. Guibène and D.Slock, "Cooperative spectrum sensing and localization in cognitive radio systems using compressed sensing", Journal of Sensors, dx.doi.org/10.1155/2013/606413,2013. [17] X. Li , et al., "Spatio-temporal compressive sensing-based data gathering in wireless sensor networks", IEEE Wireless Commun. Lett.Vol.7,No. 2, pp.198-201,2018. [18] M.-H.Yang, et.al., "Fusion-based cooperative support identification for compressive networked sensing", published in ArXiv, DOI:10.1109/lwc.2019.2946552, 2019. [19] F. Ye, X. Zhang, Y. Li and H. Huang, "Primary User Localization Algorithm Based on Compressive Sensing in Cognitive Radio Networks", Algorithms Journal, Vo.9,No.12, 2016,pp.1-11. [20] Y. C. Liang, Y. Zeng, E. C. Peh, and A. T. Hoang, "Sensing-throughput trade off for cognitive radio networks", IEEE Trans.Wireless Commun.Vol.7, No.4, 2008, pp.1326-1337. [21] E. Peh and Y. Ch. Liang, "Optimization for cooperative sensing in cognitive radio networks", IEEE Commun. Society, WCNC, 2007, pp.27-32. [22] B. Zhang, "Sparse target counting and localization in sensor networks based on compressive sensing", IEEE Globecom, 2009. [23] S. Maleki, A. Pandharipande, and G. Leus, "Energy-efficient distributed spectrum sensing for cognitive sensor networks", in Proc. 35th Annu. Conf. IEEE Ind. Electron. Soc., 2009, pp. 2642–2646. [24] M. J. Osborne and A. Rubinstein, A Course in Game Theory. Cambridge, MA, USA: MIT Press, 1994. [25] Quan Z., Cui S., Sayed A.H. "linear cooperation for spectrum sensing in cognitive radio networks", IEEE Journal of Selected Topics in Signal Processing,,Vol.2,No.1,2008, pp.28–39. [26] M.Najimi, A. Ebrahimzadeh, S.M.Hosseni Andargoli, A. Fallahi, "A novel sensing nodes and decision node selection method for energy efficiency of cooperative spectrum sensing in cognitive sensor networks", IEEE Sensors Journal, Vol.13,No.5, 2013, pp.1610-1621.RaziehTorkamaniRamezan AliSadeghzadeh1122020879510.7508/jist.2019.02.001 http://jist.ir/en/Article/15301http://jist.ir/en/Article/Download/15301http://jist.ir/en/Article/Download/15301http://jist.ir/en/Article/Download/15301http://jist.ir/en/Article/Download/15301http://jist.ir/en/Article/Download/15301http://jist.ir/en/Article/Download/15301http://jist.ir/en/Article/Download/15301[1] M. Fornasier and H. Rauhut, “Compressive Sensing”, 2010. [2] E. J. Candès and M. B. Wakin, “An Introduction to Compressive Sampling”, IEEE Signal Process. Magazine, 2008, pp. 21-30. [3] R.G. Baraniuk, “Compressive Sensing”, IEEE Signal Process. Mag., 2007, pp. 118-124. [4] M. F. Duarte, S. Sarvotham, D. Baron, M. B. Wakin and R. G. Baraniuk, “Distributed Compressed Sensing of Jointly Sparse Signals”, in Proc. Asilomar Conf. Signals, Syst., Comput., 2005, pp. 1537–1541. [5] M. Duarte, M. Wakin, D. Baron, S. Sarvotham and R. Baraniuk, “Measurement Bounds for Sparse Signal Ensembles via Graphical Models”, IEEE Trans. Inf. Theory, Vol. 59, No. 7, 2013, pp. 4280-4289. [6] D. P. Wipf and B. D. Rao, “An Empirical Bayesian Strategy for Solving the Simultaneous Sparse Approximation Problem”, IEEE Trans. Signal Process., Vol. 55, No. 7, 2007, pp. 3704–3716. [7] D. Baron, M. Wakin, M. Duarte, S. Sarvotham and R. Baraniuk, “Distributed Compressed Sensing”, Technical Report ECE-0612, Electrical and Computer Engineering Department, Rice University, 2009. [8] S. F. Cotter, B. D. Rao, K. Engan and K. Kreutz-Delgado, “Sparse Solutions to Linear Inverse Problems with Multiple Measurement Vectors”, IEEE Trans. Signal Process., Vol. 53, No. 7, 2005, pp. 2477–2488. [9] T. Wimalajeewa and P. Varshney, “Cooperative Sparsity Pattern Recovery in Distributed Networks via Distributed OMP”, in Proc. ICASSP, 2013, pp. 5288–5292. [10] G. Li, T. Wimalajeewa and P. Varshney, “Decentralized Subspace Pursuit for Joint Sparsity Pattern Recovery”, in Proc. ICASSP, 2014, pp. 3365–3369. [11] W. Chen and I. J. Wassell, “A Decentralized Bayesian Algorithm for Distributed Compressive Sensing in Networked Sensing Systems”, IEEE Trans. Wireless Commun., Vol. 15, No. 2, 2016, pp. 1282–1292. [12] J. Hua and Ch. Li, “Distributed Variational Bayesian Algorithms Over Sensor Networks”, IEEE Trans. Sig. Process., Vol. 64, No. 3, 2016, pp. 783-798. [13] H. Yang, L. Huang, H. Xu, and A. Liu, “Distributed Compressed Sensing in Wireless Local Area Networks”, International Journal of Communication Systems, Vol. 27, No. 11, 2013, pp. 2723-2743. [14] N. Youness, and Kh. Hassan, “Energy Preservation in Large-Scale Wireless Sensor Network Utilizing Distributed Compressive Sensing”, IEEE 10th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2014. [15] H. Dai, Y. Zhang, and J. Liu, “Structured Variational Methods for Distributed Inference in Networked Systems: Design and Analysis”, IEEE Trans. Sig. Process., Vol. 61, No. 15, 2013, pp. 3827-3839. [16] K. M. León-López, L. V. G. Carreño, and H. A. Fuentes, “Temporal Colored Coded Aperture Design in Compressive Spectral Video Sensing”, IEEE Trans. Image Process., Vol. 28, No. 1, 2019, pp. 253-264. [17] C. Chen, F. Ding, and D. Zhang, “Perceptual Hash Algorithm-Based Adaptive GOP Selection Algorithm for Distributed Compressive Video Sensing”, IET Image Process., Vol. 12, No. 2, 2018, pp. 210-217. [18] L. W. Kang, and C. S. Lu, “Distributed Compressive Video Sensing. In: Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing. 2009, pp. 1169–1172. [19] N. Yu, T. Qiu, F. Bi, and A. Wang, “Image Features Extraction and Fusion based on Joint Sparse Representation” IEEE Journal of Selected Topics in Signal Processing, Vol. 5, No. 5, 2011, pp. 1074–1082. [20] J. Wei, L. Wang, P. Liu, X. Chen, W. Li, and A. Y. Zomaya, “Spatiotemporal Fusion of MODIS and Landsat-7 Reflectance Images via Compressed Sensing”, IEEE Trans. Geosc. Remote Sens., Vol. 55, No. 12, 2017, pp. 7126-7139. [21] F. Li, Sh. Hong, and L. Wang, “A New Satellite Image Fusion Method Based on Distributed Compressed Sensing”, 25th IEEE International Conference on Image Processing (ICIP), 2018. [22] Y. Lin, B. Zhang, H. Jiang, W. Hong, and Y. Wu, “Multi-Channel SAR Imaging based on Distributed Compressive Sensing”, Sci. China Inf. Sci., Vol. 55, No. 2, 2012, pp. 245- 259. https://doi.org/10.1007/s11432-011-4452-z . [23] W. Kong, H. Li, and W. Zhang, “Compressed Sensing-Based Sparsity Adaptive Doubly Selective Channel Estimation for Massive MIMO Systems”, Wireless Comm. and Mobile Computing, Vol. 2019, Article ID 6071672, 10 pages, 2019. https://doi.org/10.1155/2019/6071672. [24] D. Wu, W. P. Zhu, and M. Swamy, “Compressive Sensing-Based Speech Enhancement in Non-Sparse Noisy Environments”, IET Sig. Process., Vol. 7, No. 5, 2013, pp. 450–457. [25] D. Liu, Q. Wang, Y. Zhang, X. Liu, J. Lu, and J. Sun, “FPGA-based Real-Time Compressed Sensing of Multichannel EEG Signals for Wireless Body Area Networks” Biomedical Sig. Process. and Control, Vol. 49, 2019, pp. 221-230. [26] A. N. Uwaechia, and N. M. Mahyuddin, “Spectrum-Efficient Distributed Compressed Sensing Based Channel Estimation for OFDM Systems Over Doubly Selective Channels”, IEEE Access, Vol. 7, 2019, pp. 35072-35088. [27] L. Prunte, “Application of Distributed Compressed Sensing for GMTU Purposes”, IET International Conference on Radar Systems, 2012. [28] L. He and L. Carin, “Exploiting Structure in Wavelet-Based Bayesian Compressive Sensing”, IEEE Trans. Signal Proccess., Vol. 57, No. 9, 2009, pp. 3488–3497. [29] R. Torkamani¬ and R. A. Sadeghzadeh, “Bayesian Compressive Sensing using Wavelet Based Markov Random Fields”, Signal Processing: Image Communication, Vol. 58, 2017, pp. 65-72. [30] S. Mallat, A Wavelet Tour of Signal Processing, 2nd ed. New York: Academic, 1998. [31] M. F. Duarte, M. B. Wakin and R. G. Baraniuk, “Wavelet-Domain Compressive Signal Reconstruction using a Hidden Markov Tree Model”, in Proc. IEEE Int. Conf. Acoust., Speech Signal Process. (ICASSP), 2008, pp. 5137–5140. [32] M. S. Crouse, R. D. Nowak and R. G. Baraniuk, “Wavelet-Based Statistical Signal Processing using Hidden Markov Model”, IEEE Trans. Signal Process., Vol. 46, 1998, pp. 886–902. [33] Sh. Ji, Y. Xue and L. Carin, “Bayesian compressive sensing”, IEEE Trans. Signal Process., Vol. 56, No. 6, 2008, pp. 2346-2356. [34] M. Beal, “Variational Algorithms for Approximate Bayesian Inference,” Ph.D. thesis, Univ. College of London, London, U.K., May 2003. [35] W. Chen, M. Rodrigues and I. Wassell, “A Fréchet Mean Approach for Compressive Sensing Date Acquisition and Reconstruction in Wireless Sensor Networks”, IEEE Trans. Wireless Comm., Vol. 11, No. 10, 2012, pp. 3598 –3606. [36] X. Chen, Y. Zhang, and R. Qi, “Block Sparse Signals Recovery Algorithm for Distributed Compressed Sensing Reconstruction”, Journal of Inf. Process. Systems, Vol. 15, No. 2, 2019, pp. 410-421. [37] P. Bodik, W. Hong, C. Guestrin, S. Madden, M. Paskin and R. Thibaux. (2004) Intel lab data. [Online]. Available: http://db.csail.mit.edu/labdata/labdata.html. [38] http://www.sandia.gov/radar/sar-data.html. [39] Z. Wong, A.C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image Quality Assessment: From Error Visibility to Structural Similarity”, IEEE Trans. Image Process., Vol. 13, No. 4, 2004, pp. 600-612. [40] E. Aguilera, M. Nannini and A Reigber, “Multisignal Compressed Sensing for Polarimetric SAR Tomography”, IEEE Geoscience and Remote Sensing Letters, Vol. 9, No. 5, 2012, pp.871-875.ZahraNajafabadi SamaniMohammad Reza Khayyam Bashi 11220209610910.7508/jist.2019.02.002http://jist.ir/en/Article/15307http://jist.ir/en/Article/Download/15307http://jist.ir/en/Article/Download/15307http://jist.ir/en/Article/Download/15307http://jist.ir/en/Article/Download/15307http://jist.ir/en/Article/Download/15307http://jist.ir/en/Article/Download/15307http://jist.ir/en/Article/Download/15307[1] N. Fernando, S. W. Loke, and W. Rahayu, “Mobile cloud computing: A survey,” Future Generation Computer Systems, vol. 29, no. 1, pp. 84-106, 2013. [2] M.Othman, S. A. Madani, and S. U. Khan, “A survey of mobile cloud computing application models,” IEEE Communications Surveys & Tutorials, vol. 16, no. 11, pp. 393-413, 2014. [3] G. F. Huerta Cánepa, “A context-aware application offloading scheme for a mobile peer to peer environment,” Ph.D. dissertation, Department of Information and Communication Engineering, KAIST, South Korea, 2012. [4] M. Conti, et al. “Looking ahead in pervasive computing: Challenges and opportunities in the era of cyber–physical convergence,” Pervasive and Mobile Computing, vol. 8, no. 1, pp. 2-21, 2012. [5] V. Cardellini, V. De NitoPersoné, V. Di Valerio, F. Facchinei, V. Grassi, F. Lo Presti and V. Piccialli, “A game-theoretic approach to computation offloading in mobile cloud computing,” Technical Report, 2013. [6] S. G. Falavarjani, M. Nematbakhsh, and B. S. Ghahfarokhi, "Context-aware multi-objective resource allocation in mobile cloud," Computers & Electrical Engineering,¬vol. 44, pp. 218-240, 2015. [7] C.Shi, et al. “Serendipity: enabling remote computing among intermittently connected mobile devices,” In Proceedings of the thirteenth ACM international symposium on Mobile Ad Hoc Networking and Computing. ACM, 2012, pp. 145-154. [8] B. Zhou, A. V. Dastjerdi, R. N. Calheiros, S. N. Srirama, and R. Buyya, “A context sensitive offloading scheme for mobile cloud computing service,” In Proceedings of IEEE of 8th International Conference on In Cloud Computing (CLOUD), 2015, pp.869-876. [9] D. N. Raju, and V. Saritha. "Architecture for fault tolerance in mobile cloud computing using disease resistance approach." International Journal of Communication Networks and Information Security, vol. 8, no. 2, 2016. [10] B. Zhou and R. Buyya, "A Group based Fault Tolerant Mechanism for Heterogeneous Mobile Clouds," In Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, Nov 2017. [11] J. Park, H. Yu, H. Kim, and E. Lee, “Dynamic group‐based fault tolerance technique for reliable resource management in mobile cloud computing,” Concurrency and Computation: Practice and Experience, John Wiley & Sons, vol. 26, no. 17, Jan. 2014. [12] J. Park, H. Yu, E. Lee, “Resource allocation techniques based on availability and movement reliability for mobile cloud computing,” Distributed Computing and Internet Technology, Springer Berlin Heidelberg, 2012,pp. 263–264. [13] J. S. Park and E. Y. Lee, “Entropy-based grouping techniques for resource management in mobile cloud computing,” Ubiquitous Information Technologies and Applications, Springer Netherlands, 2013, pp. 773-780. [14] P. Stahl, et al, "Dynamic Fault-Tolerance and Mobility Provisioning for Services on Mobile Cloud Platforms." In Proceedings of the 2017 5th International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud), IEEE, 2017, pp. 131-138. [15] S. Choi, K. Chung, and H. Yu, “Fault tolerance and QoS scheduling using CAN in mobile social cloud computing”, Cluster Computing, vol.17, no.3, pp. 911-926, 2014. [16] E. E. Marinelli, Hyrax: cloud computing on mobile devices using MapReduce. No. CMU-CS-09-164. Carnegie-mellon univ Pittsburgh PA school of computer science, 2009. [17] C-A. Chen, et al., “Energy-efficient fault-tolerant data storage and processing in mobile cloud,” IEEE Transactions on cloud computing, vol. 3, no. 1, pp. 28-41, 2015. [18] J. Park, H. Yu, K. Chung, and E. Lee, “Markov Chain based Monitoring Service for Fault Tolerance in Mobile Cloud Computing,” In Proceedings of IEEE Workshops of International Conference on Advanced Information Networking and Applications, 2011, pp.520-525. [19] P. Patel and V. Prakash, “FTAB: Fault Tolerance Approach by Using HMM with BAUM-WELCH Algorithm in MCC,” In Proceedings of Tenth international conference on Wireless and Optical Communication Network (WOCN), 2013, pp.1-4. [20] L. Ling, W. Zhulin and Y. Xiuhua, “Mobile Resource Reliability-Based Task Allocation for Mobile Cloud”, In Proceedings of the 2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC), IEEE, 2015, pp.1746-1750. [21] J.Park, et al, “Two‐phase grouping‐based resource management for big data processing in mobile cloud computing,” International Journal of Communication Systems, vol. 27, no. 6, pp. 839-851, 2014. [22] L. McNamara, C. Mascolo, L. Capra, “Media sharing based on colocation prediction in urban transport,” In Proceedings of the 14th ACM international conference on mobile computing and networking, ACM, 2008. pp. 58–69. [23] P. A, Lee, and T. Anderson, “Dependable computing and fault tolerant systems,” Fault Tolerance: Principles and Practice, Springer Verlag, NewYork, vol. 3, 1990. [24] Ch. Song, et al. “Limits of predictability in human mobility,” Science 327.5968 , 2010, pp.1018-1021. [25] J. Nicholson and B. D. Noble. “Breadcrumbs: forecasting mobile connectivity,” In Proceedings of the 14th ACM international conference on Mobile computing and networking. ACM, 2008, pp. 46-57. [26] Huang, Wei, et al. “Predicting human mobility with activity changes,” International Journal of Geographical Information Science, vol. 29, no. 9, pp. 1569-1587, 2015. [27] S. Ch. Shah, “Energy efficient and robust allocation of interdependent tasks on mobile ad hoc computational grid,” Concurrency and Computation: Practice and Experience, vol. 27, no. 5, pp. 1226-1254, 2015. [28] M.Sepahkar and M. R. Khayyambashi, “A novel collaborative approach for location prediction in mobile networks,” Wireless Networks, pp. 1-12, DOI 10.1007/s11276-016-1304-1, 2016. [29] J. A. Gubner, Probability and random processes for electrical and computer engineers, Cambridge University Press, 2006. [30] M. Wiesmann, et al. “Understanding replication in databases and distributed systems”, In Proceedings of the 20th International Conference on IEEE, Distributed Computing Systems, 2000, pp. 464-474. [31] R. Tuli and P. Kumar, “Analysis of recent checkpointing techniques for mobile computing systems,” International Journal of Computer Science & Engineering Survey, vol. 2, no. 3, 2011. [32] E. Cuervo, et al. “MAUI: making smartphones last longer with code offload,” In: Proceedings of the 8th international conference on mobile systems, applications, and services, MobiSys’10, 2010, pp. 49–62. [33] M.D. Kristensen, “Scavenger: transparent development of efficient cyber foraging applications,” In: Proceedings of the IEEE international conference on pervasive computing and communications (PerCom); 2010. p. 217–26. [34] C. L. Hwang, and K. Yoon. Multiple attribute decision making: methods and applications a state-of-the-art survey, Springer Science & Business Media, Vol. 186, 2012. [35] C. E. Shannon, “A mathematical theory of communication,” ACM SIGMOBILE Mobile Computing and Communications Review, vol. 5, no. 1, pp. 3-55, 2001. [36] FaceDetector, http://developer.android.com/reference/android/media/FaceDetector.html Avalaible Online @ September 2016. [37] L. Zhang, et al. “Accurate online power estimation and automatic battery behavior based power model generation for smartphones,” In Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis. ACM, 2010, pp. 105.HamidrezaNaseriAliShahidinejadMostafaGhobaei-Arani112202014415410.7508/jist.2019.02.006http://jist.ir/en/Article/15318http://jist.ir/en/Article/Download/15318http://jist.ir/en/Article/Download/15318http://jist.ir/en/Article/Download/15318http://jist.ir/en/Article/Download/15318http://jist.ir/en/Article/Download/15318http://jist.ir/en/Article/Download/15318http://jist.ir/en/Article/Download/15318[1]"ISO 14224, Petroleum, petrochemical and natural gas industries -- Collection and exchange of reliability and maintenance data for equipment." https://www.iso.org/standard/64076.html. [2] P. Agarwal, M. Sahai, V. Mishra, M. Bag, and V. Singh, "A review of multi-criteria decision making techniques for supplier evaluation and selection," International journal of industrial engineering computations, vol. 2, no. 4, pp. 801-810, 2011. [3] A. Garg and S. Deshmxukh, "Maintenance management: literature review and directions," Journal of quality in maintenance engineering, vol. 12, no. 3, pp. 205-238, 2006. [4] M. Jain and K. Pathak, "Applications of artificial neural network in construction engineering and management-a review," International Journal of Engineering Technology, Management and Applied Sciences, vol. 2, no. 3, pp. 134-142, 2014. [5] C. Friedrich, A. Lechler, and A. Verl, "Autonomous Systems for Maintenance Tasks–Requirements and Design of a Control Architecture," Procedia Technology, vol. 15, pp. 595-604, 2014. [6] D. Goyal and B. Pabla, "Condition based maintenance of machine tools—A review," CIRP Journal of Manufacturing Science and Technology, vol. 10, pp. 24-35, 2015. [7]A. Mérigaud and J. V. Ringwood, "Condition-based maintenance methods for marine renewable energy," Renewable and Sustainable Energy Reviews, vol. 66, pp. 53-78, 2016. [8] M. C. O. Keizer, S. D. P. Flapper, and R. H. Teunter, "Condition-based maintenance policies for systems with multiple dependent components: A review," European Journal of Operational Research, vol. 261, no. 2, pp. 405-420, 2017. [9] R. Ahmad and S. Kamaruddin, "An overview of time-based and condition-based maintenance in industrial application," Computers & Industrial Engineering, vol. 63, no. 1, pp. 135-149, 2012. [10] M. C. Carnero, "Condition Based Maintenance in small industries," IFAC Proceedings Volumes, vol. 45, no. 31, pp. 199-204, 2012. [11] Q. Zhu, H. Peng, B. Timmermans, and G.-J. van Houtum, "A condition-based maintenance model for a single component in a system with scheduled and unscheduled downs," International Journal of Production Economics, vol. 193, pp. 365-380, 2017. [12] M. C. O. Keizer, R. H. Teunter, J. Veldman, and M. Z. Babai, "Condition-based maintenance for systems with economic dependence and load sharing," International Journal of Production Economics, vol. 195, pp. 319-327, 2018. [13] P. Do, A. Voisin, E. Levrat, and B. Iung, "A proactive condition-based maintenance strategy with both perfect and imperfect maintenance actions," Reliability Engineering & System Safety, vol. 133, pp. 22-32, 2015. [14] B. Liu, S. Wu, M. Xie, and W. Kuo, "A condition-based maintenance policy for degrading systems with age-and state-dependent operating cost," European Journal of Operational Research, vol. 263, no. 3, pp. 879-887, 2017. [15] J. Poppe, R. N. Boute, and M. R. Lambrecht, "A hybrid condition-based maintenance policy for continuously monitored components with two degradation thresholds," European Journal of Operational Research, vol. 268, no. 2, pp. 515-532, 2018. [16] P. Guariente, I. Antoniolli, L. P. Ferreira, T. Pereira, and F. Silva, "Implementing autonomous maintenance in an automotive components manufacturer," Procedia Manufacturing, vol. 13, pp. 1128-1134, 2017. [17] M. Lewandowski and S. Oelker, "Towards autonomous control in maintenance and spare part logistics–challenges and opportunities for preacting maintenance concepts," Procedia Technology, vol. 15, pp. 333-340, 2014. [18] G. Walter and S. D. Flapper, "Condition-based maintenance for complex systems based on current component status and Bayesian updating of component reliability," Reliability Engineering & System Safety, vol. 168, pp. 227-239, 2017. [19] R. Kothamasu and S. H. Huang, "Adaptive Mamdani fuzzy model for condition-based maintenance," Fuzzy Sets and Systems, vol. 158, no. 24, pp. 2715-2733, 2007. [20] M. Engeler, D. Treyer, D. Zogg, K. Wegener, and A. Kunz, "Condition-based Maintenance: Model vs. Statistics a Performance Comparison," Procedia CIRP, vol. 57, pp. 253-258, 2016. [21] M. Ghobaei-Arani, R. Khorsand and M. Ramezanpour, "An autonomous resource provisioning framework for massively multiplayer online games in cloud environment", Journal of Network and Computer Applications, Volume 142, pp. 76-97, 2019. [22] M. Aslanpour, S. Dashti, M. Ghobaei-Arani and A. Rahmanian, "Resource provisioning for cloud applications: a 3-D, provident and flexible approach", The Journal of Supercomputing, vol. 74, no. 12, pp. 6470-6501, 2018. [23] M. Ghobaei-Arani, A. Rahmanian, M. Shamsi and A. Rasouli-Kenari, "A learning-based approach for virtual machine placement in cloud data centers", International Journal of Communication Systems, vol. 31, no. 8, p. e3537, 2018. [24] A. Sharifi, A. Vosolipour, M. A. Sh, and M. Teshnehlab, "Hierarchical Takagi-Sugeno type fuzzy system for diabetes mellitus forecasting," in Machine Learning and Cybernetics, 2008 International Conference on, 2008, vol. 3: IEEE, pp. 1265-1270. [25] N. Walia, H. Singh, and A. Sharma, "ANFIS: Adaptive neuro-fuzzy inference system-a survey," International Journal of Computer Applications, vol. 123, no. 13, 2015.HekmatAdelnia NajafabadiAhmadrezaShekarchizadehAkbarNabiollahiNaserKhaniHamidRastegari112202015516410.7508/jist.2019.02.007http://jist.ir/en/Article/15326http://jist.ir/en/Article/Download/15326http://jist.ir/en/Article/Download/15326http://jist.ir/en/Article/Download/15326http://jist.ir/en/Article/Download/15326http://jist.ir/en/Article/Download/15326http://jist.ir/en/Article/Download/15326http://jist.ir/en/Article/Download/15326[1] K Holt, Product innovation Management. London: The University Press, 1998. [2] Shahriyar Azizi, "Pricing in Electronic Markets," Tadbir, no. 186, p. [In Persion], 2008. [3] V. H Spingies and A. S. A du Toit, "Pricing of information products: three scenarios," Library Management, vol. 18, no. 5, pp. 301-304, 1997. [4] D Shipley and D Jobber, "Integrative Pricing Via The Pricing Wheel," Industrial Marketing Management, vol. 3, no. 30, pp. 301-314, 2001. [5] A Hinterhuber and S.M Liozu, "Is Innovation in Pricing Your Next Source of Competitive Advantage?," Business Horizons, vol. 57, no. 3, pp. 413-423, 2014. [6] K. L Wang, "Pricing strategies for information products: A review," in In IEEE International conference on e-commerce technology for dynamic E-business, 2004. [7] L Kai and Y.K. C Patrick, "Classifying digital products," Communications of the ACM, vol. 45, no. 6, pp. 73-79, 2002. [8] R Steele. (2003) Software business models. [Online]. http://www.corp21.com/download/SWBusinessModels.pdf. [9] T Dixit, G Whipple, E Zinkhan, and A Gailey, "A Taxonomy of Information Technology-Enhanced Pricing Strategies," Journal of Business Research, vol. 61, no. 4, pp. 275-283, 2008. [10] Dhruv Grewal et al., "Innovations in Retail Pricing and Promotions," Journal of Retailing, pp. 43-52, 2011. [11] Amir Baghtaee and Shadi Golchinfar, Tadbir, 2008. [12] F Pascual-Miguel and et all, "Influences of gender and product type on online purchasing," Journal of Business Research, vol. 68, pp. 1550-1556, 2015. [13] C Antoun, "Who Are the Internet Users, Mobile Internet Users, and Mobile-Mostly Internet Users?: Demographic Differences across Internet-Use Subgroups in the U.S," in Mobile Research Methods: Opportunities and Challenges of Mobile Research Methodologies, D Toninelli, B Pinter, and P Pedraza, Eds. London: Ubiquity Press, 2015, pp. 99-117. [14] K Shampanier, N Mazar, and D Ariely, "Zero as a special price: The true value of free products," Marketing Science, vol. 26, no. 6, pp. 742-757, 2007. [15] A Onetti and S Verma, "Open source licensing and business models," Journal of Knowledge Management, no. 7, pp. 68-94, 2009. [16] R Mohammed, R. J Fisher, and B. J Jaworski, Internet Marketing: Building Advantage in the Networked Economy.: McGraw – Hill press, 2002. [17] S Lehmann and P Buxmann, "Pricing Strategies of Software Vendors," Business & Information Systems Engineering, vol. 6, no. 1, pp. 452–462, 2009. [18] B. R Larson, "Psychology Pricing Principle for Organization with Market Power," Journal of Applied Business, 2014. [19] L. W McKnight and J Boroumand, "Pricing Internet services: Approaches and challenges," Computer, vol. 32, no. 2, pp. 128-129, 2000. [20] A Morin, J Urban, and P Sliz, "A quick guide to software licensing for the scientist programmer," PLoS Comput Biol, vol. 8, no. 1, pp. 1-7, 2012. [21] Shivashis Nayak, "Pricing and licensing of software products and services: A study on industry trend," System Design and Management Program, MSc 2006. [22] M Massoud and M Abo-Rizka, "A Conceptual Model of Personalized Pricing Recommender System Based on Customer Online Behavior," IJCSNS International Journal of Computer Science and Network Security, vol. 12, no. 6, 2012. [23] J. R Carlson and M Kukar-Kinney, "Investigating discounting of discounts in an online context: The mediating effect of discount credibility and moderating effect of online daily deal promotions," Journal of Retailing and Consumer Services, no. 41, pp. 153-160, 2018. [24] C Shapiro and H. R Varian, "Versioning: The smart way to sell information," Harvard Business Review, pp. 106-114, 1988. [25] Kang Bae Lee, Sung-Yeol Yun, and Seong Jun Kim, "Analysis of pricing strategies for e-business companies providing information goods and services," Computers & Industrial Engineering, vol. 1, no. 51, pp. 72-78, 2006. [26] F Linde, "Pricing information goods," Journal of Product & Brand Management, vol. 18, no. 5, pp. 379-384, 2009. [27] W Hui, B Yoo, V Choudhary, and K. Y Tam, "Sell by bundle or unit?: Pure bundling versus mixed bundling of information goods," Decision Support Systems, vol. 53, no. 3, pp. 517-525, 2012. [28] J Rowley, A Baregheh, and S Sambrook, "Toward an innovation type mapping tool," Journal of management decision, pp. 73-86, 2011. [29] S Liozu and K Ecker, "The organizational design of the pricing function in firms," in Innovation in Pricing: Contemporary Theories and Best Practices. New York: Routledge, 2013, pp. 27-46. [30] P. M Senge, "The art and practice of the learning organization," The new paradigm in business: Emerging strategies for leadership and organizational change, pp. 126-138, 1990. [31] A Jerome, Colletti, and B Lawrence, "Change Management Initiatives: Moving Sales Organizations from Obsolescence to High Performance," Journal of Personal Selling & Sales Management, vol. 17, no. 2, pp. 1-30, 1997. [32] G Laatikainen and A Ojala, "Pricing of digital goods and services," in Information Systems Research Conference in Scandinavia, 2018. [33] S Liozu and A Hinterhuber, "CEO championing of pricing, pricing capabilities, and firm performance in industrial firms," Industrial Marketing Management, vol. 42, no. 4, p. 633—643, 2013. [34] Haris Ahmed, Tahseen Ahmed Jilani, Waleej Haider, and Mohammad Asad Abbasi, "Establishing Standard Rules for Choosing Best KPIs for an E-Commerce Business based on Google Analytics and Machine Learning Technique," International Journal of Advanced Computer Science and Applications, vol. 8, no. 5, pp. 12-24, 2017. [35] C Aydede and T Turkoglu, "How to utilize a value-based pricing strategy in service contracts: A descriptive case study of how a Swedish pricing consultancy company optimizes pricing of services for its customers," Master thesis 2017. [36] Sarah Wikner, "The Next Generation CRM Tools: Bridging the Gaps between Sales Needs and CRM Tools Architecture," in Organizing Marketing and Sales., 2018, pp. 195-205. [37] Gartner Group. (2018) Gartner IT Glossary - Customer Relationship Management (CRM). [Online]. https://www.gartner.com/it-glossary/customer-relationship-management-crm/. [38] Hamed Tohidi and Mohammad Mehdi Jabbari, "CRM as a Marketing Attitude Based on Customer’s Information," Procedia Technology, vol. 1, pp. 565-569, 2012. [39] Philip T Kotler, Marketing Management, 14th ed.: Pearson, 2011. [40] T Fiig, O Goyons, R Adelving, and B Smith, "Dynamic pricing – The next revolution in RM?," Journal of Revenue and Pricing Management, vol. 15, no. 5, pp. 360–379, 2016. [41] Alessandro Capocchi, Economic Value and Revenue Management Systems.: Palgrave Macmillan, 2019. [42] H R Varian, "Pricing Information Goods," Research Libraries Group Symposium on Scholarship in the New Information Environment, 1995. [43] Roy Jones and Haim Mendelson, "Information Goods vs. Industrial Goods: Cost Structure and Competition," Management Science, vol. 57, no. 1, pp. 164-176, 2011. [44] Alper Şen, "A comparison of fixed and dynamic pricing policies in revenue management," Omega, vol. 41, no. 3, pp. 586-597, 2013. [45] E. T Anderson and D. I Simester, "Effects of $9 price endings on retail sales: Evidence from field experiments," Quantitative Marketing and Economics, vol. 1, no. 1, pp. 93-110, 2003. [46] T O’Keeffe, "Organizational Learning: a new perspective," Journal of European Industrial Training, vol. 26, no. 2, pp. 130-141, 2002. [47] P Rikhardsson and O Yigitbasioglu, "Business intelligence & analytics in management accounting research: Status and future focus," International Journal of Accounting Information Systems, pp. 37-58, 2018. [48] Dong-Qing Yao, Ziping Wang, Samar K Mukhopadhyay, and Yu Cong, "Dynamic pricing strategy for subscription-based information goods," Journal of Revenue and Pricing Management, vol. 11, no. 2, pp. 210-224, 2012. [49] William G. Morrison, "Product bundling and shared information goods: A pricing exercise," The Journal of Economic Education, vol. 47, no. 1, 2016. [50] N Biehn and C Zawada, "Innovations in Determining Willingness-to-Pay for B2B Companies," in Innovation in Pricing: Contemporary Theories and Best Practices. New York: Routledge, 2013, pp. 288-297.EhsanPoodinehFarhadGhorbaniRezaAsadiHadiAliakbarian112202011011910.7508/jist.2019.02.003http://jist.ir/en/Article/15380http://jist.ir/en/Article/Download/15380http://jist.ir/en/Article/Download/15380http://jist.ir/en/Article/Download/15380http://jist.ir/en/Article/Download/15380http://jist.ir/en/Article/Download/15380http://jist.ir/en/Article/Download/15380http://jist.ir/en/Article/Download/15380[1].Leach, R. and M.B. Alexander, Electronic systems failures and anomalies attributed to electromagnetic interference. , is presented at the space programs and Technologies conference,alabam1995. [2].Stephenson, J.H., D. Weitsman, and N.S. Zawodny, Effects of flow recirculation on unmanned aircraft system (UAS) acoustic measurements in closed anechoic chambers. The Journal of the Acoustical Society of America, 2019. 145(3): p. 1153-1155. [3].Smith, K.M., A homogeneous RF-shielded magnet for low-field magnetic resonance studies," MASTER OF SCIENCE, Department of Physics and Astronomy, in Winnipeg, Manitoba. 2019, The University of Manitob: canada. [4].J. W. Hansen, E.M.S., J. D. Cleveland, S. M. Asif, B. Brooks, B. D. Braaten, A Systematic Review of In-vitro and in Vivo Radio Frequency Exposure Methods. IEEE reviews in biomedical engineering, 2019. [5].Vinci, J.J., Sparse Aperture Measurement in a Non-Ideal Semi-Anechoic Chamber., University of Dayton United States,2019. [6].Dubey, S.K. and V. Ojha, Numerical Analysis and Measurement of Electric field Strength inside GTEM Cell at GSM Frequencies. Defence Science Journal, 2019. 69(5): p. 423. [7].A.Sahraei, H.A., On the Design and Fabrication of a Large GTEM Cell and its Challenges. to be published in IEEE EMC Magazine, 2020. [8].A. K. Fall, P.B., C. Lemoine, M. Zhadobov, and R. Sauleau, Design and experimental validation of a mode-stirred reverberation chamber at millimeter waves. EEE Transactions on Electromagnetic Compatibility, 2014. vol. 57: p. pp. 12-21. [9].States, U., A document that establishes uniform engineering and technical requirements for military-unique osubstantially modified commercial processes, procedures, practices, and methods. 1999. p. pp. 707-710. [10].Compatibility, E., Part 4-21: Testing and measurement techniques—reverberation chamber test methods. IEC Standard, 2003: p. 61000-4. [11].Pfennig, S., A general method for determining the independent stirrer positions in reverberation chambers: Adjusting the Correlation Threshold. IEEE Transactions on Electromagnetic Compatibility, 2016. vol. 58: p. pp. 1252-1258. [12].Q. Xu, Y.H., L. Xing, Z. Tian, C. Song, and M. Stanley, The limit of the total scattering cross section of electrically large stirrers in a reverberation chamber. IEEE Transactions on Electromagnetic Compatibility, 2016. vol. 58: p. pp. 623-626. [13].L. Bastianelli, V.M.P., and F. Moglie, Stirrer efficiency as a function of its axis orientation. IEEE Transactions on Electromagnetic Compatibility, 2015. vol. 57: p. pp. 1732-1735. [14].Bruns, C.a.R.V., A closer look at reverberation chambers-3-D simulation and experimental verification. IEEE Transactions on Electromagnetic Compatibility. IEEE Transactions on Electromagnetic Compatibility, 2005. vol. 47: p. p. 612-626. [15].Hill, D.A., Electromagnetic fields in cavities: deterministic and statistical theories vol, J.W. Sons, Editor. 2009. [16].B. Urul, I.B.B., T. Göksu, and S. Helhel, CST simulation of reverberation chamber for improved field uniformity, in International Conference on Electrical and Electronics Engineering (ELECO). 2017. p. pp. 1070-1074. [17].Yamanaka, K.H.a.Y., FDTD analysis on the effect of stirrers in a reverberation chamber,. International Symposium on Electromagnetic Compatibility, 1999: p. pp. 260-263.