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Application of the Layered Model Management System in an Interactive Map of the University Campus

on (Vol. 2, pp. 120-125). IEEE [4] Crickard III, P. (2014). Leaflet. js Essentials . Packt Publishing Ltd [5] Derrough, J. (2013). Instant Interactive Map Designs with Leaflet JavaScript Library How-to . Packt Publishing Ltd [6] Graser, A., Mearns, B., Mandel, A., Olaya Ferrero, V., Bruy A. (2010). QGIS: Becoming a GIS Power User , O’Reilly Media [7] Murray, S. (2017). Interactive Data Visualization for the Web: An Introduction to Designing with . O’Reilly Media, Inc. [8] Nawrocki, W. (2016). Measurement systems and sensors

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Analysis of application of distributed multi-node, multi-GPU heterogeneous system for acceleration of image reconstruction in Electrical Capacitance Tomography

Measurement Data Visualization: Developments Towards 3D, proc of 5th World Congress on Industrial Process Tomography, Bergen, Norway, 2006 [15] P. Russek, K.Wiatr, Dedicated architecture for double precision matrix multiplication in supercomputing environment, Proceedings of the 2007 IEEE Workshop on Design and diagnostics of Electronic Circuits and Systems, DDECS, pp. 321-324, 2007 [16] M. Soleimani, Three-dimensional electrical capacitance tomography imaging, Insight, Non- Destructive Testing and Condition Monitoring, vol. 48, no. 10, pp

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Data Analytics in CRM Processes: A Literature Review

.02.021 [6] N. R. Mabroukeh and C. I. Ezeife, “A Taxonomy of Sequential Pattern Mining Algorithms,” ACM Computing Surveys, vol. 43, no. 1, pp. 1-41, Nov. 2010. https://doi.org/10.1145/1824795.1824798 [7] M. Friendly, Milestones in the history of thematic cartography, statistical graphics, and data visualization, 2009 [Online]. Available: http://www.math.yorku.ca/SCS/Gallery/milestone/milestone.pdf [8] M. Aparicio and C. J. Costa, “Data visualization,” Communication Design Quarterly Review, vol. 3, no. 1, pp. 7-11, Jan. 2015. https

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Cloud Service for Numerical Calculations and Visualizations of Photonic Dissipative Systems

of Light via Photon Blockade in Optical Nanocavities. - Phys. Rev., Vol. A81, 2010, 033838. 25. Abhijit, J. Data Visualization with the D3. JS JavaScript library. - Journal of Computing Sciences in Colleges, Vol. 30, 2014, No 2, pp. 139-141. 26. Scott, W. Adding Visualization with JSON. Pro j Query in Oracle Application Express. Apress, 2015, pp. 133-147.

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Analysis of Application of Distributed Multi-Node, Multi-GPU Heterogeneous System for Acceleration of Image Reconstruction in Electrical Capacitance Tomography

. (2006). Hopper flow measurement data visualization: Developments towards 3D. In Proc. of 5th World Congress on Industrial Process Tomography [17] Russek, P., Wiatr, K. (2007). Dedicated architecture for double precision matrix multiplication in supercomputing environment. In Design and Diagnostics of Electronic Circuits and Systems, 2007. DDECS’07. IEEE (pp. 1-4). IEEE. [18] Soleimani, M. (2006). Three-dimensional electrical capacitance tomography imaging. Insight-Non-Destructive Testing and Condition Monitoring , 48(10), 613-617 [19] Soleimani

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Empirical Study of Job Scheduling Algorithms in Hadoop MapReduce

References 1. Bardhan, S., D. A. Menascé. The Anatomy of Mapreduce Jobs, Scheduling, and Performance Challenges. - In: Proc. of 2013 Conference of the Computer Measurement Group, 2013. 2. Apache Hadoop. Last accessed on 15 April 2016. http://hadoop.apache.org 3. Shilpa, M. K. Big Data Visualization Tool with Advancement of Challenges. - International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 4, 2014, No 3, pp. 665-668. 4. Davis, R. I., A. Burns. A Survey of

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Optimization of Distributed Multi-Node, Multi-GPU, Heterogeneous System for 3D Image Reconstruction in Electrical Capacitance Tomography

-118 [15] Majchrowicz, M., Kapusta, P., Jackowska-Strumiłło, L., Sankowski, D. (2015). Analysis of application of distributed multi-node, multi-GPU heterogeneous system for acceleration of image reconstruction in Electrical Capacitance Tomography. Image Processing & Communications , 20(3), 5-14 [16] Romanowski, A., Grudzien, K., Banasiak, R., Williams, R. A., Sankowski, D. (2006). Hopper flow measurement data visualization: Developments towards 3D. In Proc. of 5th World Congress on Industrial Process Tomography [17] Russek, P., Wiatr, K. (2007, April

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A Review of Feature Selection and Its Methods

, Vol. 5 , July 1994, No 4, pp. 537-550. 44. Yang, H. H., J. Moody. Data Visualization and Feature Selection: New Algorithms for Nongaussian Data. – In: In Advances in Neural Information Processing Systems, 1999, pp. 687-693. 45. Meyer, P. E., G. Bontempi. On the Use of Variable Complementarity for Feature Selection in Cancer Classification. – In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3907 . LNCS, Springer, Berlin, Heidelberg, 2006, pp. 91-102. 46

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Topographic surface modelling using raster grid datasets by GMT: example of the Kuril–Kamchatka Trench, Pacific Ocean

1 Introduction Current paper introduces the use of Generic Mapping Tools (GMT) for the cartographic workflow aimed at the geological data visualization. Among the wide range of GIS software used for mapping and geospatial data modelling, GMT stands apart from the traditional tools such as ArcGIS ( ESRI Team, 2010 ), QGIS ( QGIS, 2019 ) and MapINFO. The particularity of the GMT comparing to the standard GIS consists in its fundamentally different approach towards geodata processing. The GMT, originally developed by Wessel and Smith (1998) is not a classic

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Introduction of the Inaugural Issue of the Journal of Data and Information Science

multidimensional approach of examining raw data with the purpose of discovering meaningful patterns, analyzing and communicating the obtained information to specific target groups. Data analytics relies on the simultaneous application of mathematics, statistics, computer programming, and operations research. It makes use of techniques for explanatory research, seeks to identify underlying factors, and performs conceptual modeling, often leading to data visualization to communicate insights. As a consequence we hope that this journal will play an important role in the scholarly

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