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immigration processes with catastrophes, Journal of Statistical Theory & Practice 1(1): 39-48. Gross, D., Shortle, J.F., Thompson, J.M. and Harris, C.M. (2008). Fundamentals of Queueing Theory, 4th Edn., Wiley, Hoboken, NJ. Haviv, M. (2013). A Course in Queueing Theory, Springer, New York, NY. Jiang, T. and Liu, L. (2017). Analysis of a GI/M/1 in a multi-phase service environment with disasters, RAIROOperations Research 51(1): 79-100. Jiang, T., Liu, L. and Li, J. (2015). Analysis of the M/G/1 queue in multi-phase random environment with disasters, Journal of Mathematical

] and next for the pulse magnetron sputtering deposition (PMS) (e.g. [8 – 11] ); we named the “gas” modified PMS as the GIMS (Gas Injection Magnetron Sputtering) [7 , 12] . The use of gas mode for deposition of TiN coatings on non-heated cutting tools by the modified IPD method enabled 16-fold increase of the tools lifetime in comparison to the uncoated tools [1] . This is a substantial improvement compared with 2 to 4 times extending of the coated tools Service life that was previously reported in literature for tools coated in industrial scale production with


The positioning accuracy of single frequency precise point positioning (SFPPP) attributes mainly to the ionosphere error, which strongly affects GNSS signals. When GNSS signals pass through the various ionosphere layers, they will be bent and their speed will be changed due to dispersive nature of ionosphere. To correct the ionosphere error, it is common to use Klobuchar ionosphere model or Global Ionosphere Maps (GIM). However, Klobuchar can deal with only about 50% of the Ionosphere effect and global Ionosphere maps are often inadequate to describe detailed features of local ionosphere because of limited precision and resolution. In this paper, an enhanced local ionosphere model was developed relying on modeling of measurements from a dense Egyptian permanent tracking GNSS network in order to achieve high precision ionosphere delay correction. The performance of the developed enhanced Egyptian ionosphere model (EIM) was verified through multi-constellations SFPPP accuracy for static and kinematic modes. For static mode, 24 hours multi-constellations datasets collected at three selected stations, Alexandria, Cairo, and Aswan, in Egypt on February 27, 2017, to investigate the performance of the developed local ionospheric model in comparison with the Klobuchar, GIM and ionosphere free models. After session time of half an hour, the results show that the performance of static SFPPP based on the developed Egyptian ionospheric map (EIM) achieved a comparable accuracy WRT using ionosphere free model. While using EIM, achieved an improvements of (38%, 28%, and 42%) and (32%, 10%, and 37%) for accuracy of latitude, longitude, and altitude in comparison with using Klobuchar and GIM models, respectively For kinematic mode, datasets of 2 hours of observations with 1 second sampling rate were logged during vehicular test; the test was carried out on the ring road of the city of Cairo, Egypt, on September 16, 2017. After half an hour of kinematic SFPPP data-processing, the performance of using Egyptian ionospheric map (EIM) for ionosphere delay correction, achieved an improvements of three dimension coordinates of (83%, 47%, and 62%) and (57%, 65%, and 21%) with respect to using Klobuchar model and GIM model, respectively.


In 2011, we proposed a novel magnetron sputtering method. It involved the use of pulsed injection of working gas for the initiation and control of gas discharge during reactive sputtering of an AlN layer (Gas Injection Magnetron Sputtering — GIMS). Unfortunately, the presence of Al-Al bonds was found in XPS spectra of the AlN layers deposited by GIMS onto Si substrate. Our studies reported in this paper proved that the synchronization of time duration of the pulses of both gas injection and applied voltage, resulted in the elimination of Al-Al bonds in the AlN layer material, which was confirmed by the XPS studies. In our opinion the most probable reason of Al-Al bonds in the AlN layers deposited by the GIMS was the self-sputtering of the Al target in the final stage of the pulsed discharge.

References [1] Krapivin, V.F., Shutko, A.M. Information technol-ogies for remote monitoring of the environment. Springer/Praxis, Chichester U.K., 2012, 498 pp. [2] Nitu, C., Krapivin, V.F., Soldatov, V.Yu. Information-modeling technology for environmental investigations. Matrix Rom, Bucharest, Romania, 2013. 621 pp. [3] Mkrtchyan, F.A., Krapivin V.F. GIMS - technology in the water quality monitoring. Proceedings of the International Conference on GeoInformatics for Spatial-Infrastructure Development in Earth & Allied Sciences (GIS-IDEAS 2016). 12-15 November

Kempa, W. M. (2013). Genetic cost optimization of the GI/M/1/N finite-buffer queue with a single vacation policy, in L. Rutkowski, M. Korytkowski, R. Scherer, R. Tadeusiewicz, L.A. Zadeh and J.M. Zurada (Eds.), 12th International Conference, ICAISC 2013, Zakopane, Poland, June 9-13, 2013, Proceedings, Part II, Lecture Notes in Artificial Intelligence, Vol. 7895, Springer-Verlag, Berlin/Heidelberg, pp. 12-23. Gabryel, M. and Rutkowski, L. (2010). Evolutionary designing of logic-type fuzzy systems, in L. Rutkowski, R. Scherer, R. Tadeusiewicz, L.A. Zadeh and J.M. Zurada

REFERENCES Dodson, A. H. (1988). The Effects of Atmospheric Refraction on GPS Measurements. Seminar on the Global Positioning System , Nottingham University. Farah, A. (2008). Comparison of GPS/Galileo Single Frequency Ionospheric Models with Vertical Tec Maps. Artificial Satellites, Journal of Planetary Geodesy, Vol. 43, No. 2, 2008. IGS (2018a). The ionospheric coefficients for GPS ionospheric model and BeiDou ionospheric model. ( (Accessed 1/9/2018). IGS (2018b). IGS-GIMs (International GNSS Service

, Terrestrial & Planetary Science 25 (4), 307-310. ICTP (2017). The Abdus Salam International Centre for Theoretical Physics (ICTP) ( Accessed (15/3/2017). IGS (2018a). (2003-2004) IGS Annual Report. ( (Accessed 15/1/2018). IGS (2018b). IGS-GIMs (International GNSS Service-Global Ionospheric Maps (IONEX format)) ( (Accessed 15/1/2018). ITU (2003). (International Telecommunication Union) Ionospheric propagation data and prediction methods

., Aragón-Àngel À., García-Rigo A., Salazar D., Escudero M. (2011). The ionosphere: effects, GPS modeling and the benefits for space geodetic techniques. J. Geod. 85 (12): 887–907. Hofmann-Wellenhof B., Lichtenegger H., Wasle E. (2008). GNSS—global navigation satellite systems — GPS, GLONASS, Galileo, and more. Springer, Vienna. doi:10.1007/978-3-211-73017-1. IGS (2019a). The ionospheric coefficients for GPS, BeiDou and Galileo ionospheric models. ( (Accessed 1/9/2019). IGS (2019b). IGS-GIMs (International GNSS

. Wiley-Blackwell. Shahrour I (2018) Use of GIS in Smart City Projects. Managing and Visualising Geospatial Data in a User-friendly Environment. Available from: < > Rajabifard A (2014) 3D Cadastres and Beyond. 4th International FIG 3D Cadastre Workshop, Dubai. Rajabifard A, Ho S (2015) Towards smart future cities: 3D cadastres as a fundamental enabler. Coordinates. Available from: < > Toschi I