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Shared Subscribe Hyper Simulation Optimization (SUBHSO) Algorithm for Clustering Big Data – Using Big Databases of Iran Electricity Market

.1023/A:1024016609528 [21] C. Domeniconi, D. Gunopulos, S. Ma, B. Yan, M. Al-Razgan, and D. Papadopoulos, “Locally adaptive metrics for clustering high dimensional data,” Data Mining and Knowledge Discovery , vol. 14, no. 1, 2007, pp. 63–97. https://doi.org/10.1007/s10618-006-0060-8 [22] Y. Zhu, K. M. Ting, and M. J. Carman, “Grouping points by shared subspaces for effective subspace clustering,” Pattern Recognition , vol. 83, 2018, pp. 230–244. https://doi.org/10.1016/j.patcog.2018.05.027 [23] H. Chen, W. Wang, and X. Feng, “Structured sparse

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Integrated Cloud-Based Services for Medical Workflow Systems

executing workflows of Web Services on the desktop, web or in the cloud,” Nucleic acids research , vol. 41, issue W1, pp. W557–W561, July 2013. https://doi.org/10.1093/nar/gkt328 [10] J. Wang, P. Korambath, I. Altintas, J. Davis and D. Crawl, “Workflow as a service in the cloud: architecture and scheduling algorithms,” Procedia Computer Science , vol. 29, pp. 546–556, 2014. https://doi.org/10.1016/j.procs.2014.05.049 [11] P. Korambath, J. Wang, A. Kumar et al., “Deploying Kepler workflows as services on a cloud infrastructure for smart manufacturing

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Testing and Traceability Aspects in the Context of the Model Driven Architecture (MDA)

. Shaham-Gafni, "Model traceability," IBM Systems Journal , vol. 45, no. 3, 2006. "MDA guide version 1.0.1", Object Management Group. [Online]. Available: http://www.omg.org/cgi-bin/doc?omg/03-06-01.pdf "Revised submission for MOF 2.0 Query/View/Transformations RFP (ad/2002-04-10)," QVT-Merge Group, Version 2.1, OMG Document ad/05-07-01, Object Management Group, Inc., August 2005. "MOF model to text transformation language RFP," OMG Document ad/2004-04-07, Object Management Group, Inc

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Appropriateness of Dropout Layers and Allocation of Their 0.5 Rates across Convolutional Neural Networks for CIFAR-10, EEACL26, and NORB Datasets

://doi.org/10.1016/j.neunet.2015.07.007 [4] A. Iosifidis, A. Tefas, and I. Pitas, “DropELM: Fast Neural Network Regularization with Dropout and DropConnect,” Neurocomputing , vol. 162, pp. 57–66, Aug. 2015. https://doi.org/10.1016/j.neucom.2015.04.006 [5] M. Elleuch, R. Maalej, and M. Kherallah, “A New Design Based-SVM of the CNN Classifier Architecture with Dropout for Offline Arabic Handwritten Recognition,” Procedia Computer Science , vol. 80, pp. 1712–1723, 2016. https://doi.org/10.1016/j.procs.2016.05.512 [6] W. Sun and F. Su, “A Novel Companion

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An Improvement of the VDSR Network for Single Image Super-Resolution by Truncation and Adjustment of the Learning Rate Parameters

, and K. M. Lee, “Accurate image super-resolution using very deep convolutional networks,” 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , pp. 1646–1654, 2016. https://doi.org/10.1109/CVPR.2016.182 [10] W. Xie, Y. Li, and X. Jia, “Deep convolutional networks with residual learning for accurate spectral-spatial denoising,” Neurocomputing , vol. 312, pp. 372–381, 2018. https://doi.org/10.1016/j.neucom.2018.05.115 [11] R. Kress, “Interpolation,” in: Numerical Analysis , Kress R. (ed.). Springer, 1998, pp. 151–188. https

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An Efficient Technique for Size Reduction of Convolutional Neural Networks after Transfer Learning for Scene Recognition Tasks

,” Neurocomputing , vol. 225, pp. 188–197, 2017. https://doi.org/10.1016/j.neucom.2016.11.023 [15] A. Krizhevsky, I. Sutskever, and G. E. Hinton, “ImageNet classification with deep convolutional neural networks,” Communications of the ACM , vol. 60, no. 2, pp. 84–90, 2017. https://doi.org/10.1145/3065386 [16] C. Wang, J. Yu, and D. Tao, “High-level attributes modeling for indoor scenes classification,” Neurocomputing , vol. 121, pp. 337–343, 2013. https://doi.org/10.1016/j.neucom.2013.05.032 [17] S. Bai, “Growing random forest on deep convolutional neural

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Definition of the Criteria for Layout of the UML Use Case Diagrams

.1145/774833.774860 [20] D. Sun, and K. Wong, “On evaluating the layout of UML class diagrams for program comprehension” 13th International Workshop on Program Comprehension (IWPC’05), 2005, pp. 1–10. [21] G. Bist, N. MacKinnon, and S. Murphy, “Sequence diagram presentation in technical documentation”, SIGDOC’04: Proceedings of the 22nd Annual International Conference on Design of Communication , New York, NY, USA, 2004, pp. 128–133. https://doi.org/10.1145/1026533.1026566 [22] T. Poranen, E. Makinen, and J. Nummenmaa, “How to draw a sequence diagram”, Proceedings of

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Alternative Development for Data Migration Using Dynamic Query Generation

, VLDB '05, pp. 1251–1254, 2005. [4] V. Ebai, What Is Sql?: Fundamentals of Sql, T-Sql, Pl/Sql and Datawarehousing , 2012, pp XI. [5] K. Loudon, Mastering Algorithms with C, O Reilly Media, Inc. 2009, p. 206. [6] A. D. Munoz, Metaheuristics . Ed. Dykinson, 2007, p. 12. [7] B. R. Ullrey. Implementing a Data Warehouse: A Methodology that Worked . AuthorHouse, 2007, pp. 93–94. [8] Z. Bellahsene, A. Bonifati, E. Rahm, Schema Matching and Mapping . Springer Science & Business Media. 2011, pp. 152, 153. [9] A. D. Ionita, Migrating

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The Perspective on Data and Control Flow Analysis in Topological Functioning Models by Petri Nets

, no. 16 (November 2012), pp. 12636-12649. http://dx.doi.org/10.1016/j.eswa.2012.05.019 [30] Zh. Xiao, and M. Zhong, “A method of workflow scheduling based on colored Petri nets,” in Data & Knowledge Engineering vol. 70, no. 2 (February 2011), pp. 230-247. http://dx.doi.org/10.1016/j.datak.2010.11.005 [31] Y. Yi, “An Extended Stochastic Petri Nets Modeling Method for Collaborative Workflow Process,” in Physics Procedia vol. 33, 2012, pp. 1547-1552. http://dx.doi.org/10.1016/j.phpro.2012.05.251 [32] V. Valentín, H. Macià

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State Synchronization Approaches in Web-based Applications

Consortium, (2010, November) Web SQL Database [Online] Available: http://dev.w3.org/html5/webdatabase/ [9] C. Cao, J. Luo, Z. Qiu, “Technology of Application System Integration Based on RIA” in International Conference CSIE 2011, Zhengzhou, China, May 21-22, 2011. Proceedings, Part I: Springer Berlin Heidelberg, 2011, pp. 55-60. [10] M. Ayenson, et al., (2011, July) Flash Cookies and Privacy II: Now with HTML5 and ETag Respawning. [Online] Available: http://ssrn.com/abstract=1898390 [11] D. Maciej, W. Zabierowski. “Web

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