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Vertical Handover Decision Algorithm for Heterogeneous Cellular-WLAN Networks

Abstract

Multi-access and heterogeneous wireless communications are considered to be one of the solutions for providing generalized mobility, high system efficiency and improved user experience, which are important characteristics of the Next Generation Networks. This paper proposes a Vertical Handover (VHO) decision algorithm for heterogeneous network architectures which integrate both cellular networks and Wireless Local Area Networks (WLANs). The cellular-WLAN and WLAN-WLAN VHO decisions are taken based on parameters which characterize both the coverage and the traffic load of the WLANs. Computer simulations performed in complex scenarios show that the proposed algorithm ensures better performance compared to “classical” VHO decision algorithms.

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Low Complexity H.265/HEVC Coding Unit Size Decision for a Videoconferencing System

, Electric Engineering and Computer (MEC), Shenyang, China, December 2013, pp. 1096-1099. 9. Ahn, S., B. Lee, M. Kim. A Novel Fast CU Encoding Scheme Based on Spatiotemporal Encoding Parameters for HEVC Inter Coding. – IEEE Transactions on Circuits and Systems for Video Technology, Vol. 25 , 2015, No 3, pp. 422-435. 10. Lee, J., S. Kim, K. Lim, S. Lee. A Fast CU Size Decision Algorithm for HEVC. – IEEE Transactions on Circuits and Systems for Video Technology, Vol. 25 , 2015, No 3, pp. 411-421. 11. Zhang, Y., H. Wang, Z. Li. Fast Coding Unit Depth

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Modelowanie położenia jednostek kompleksów rolniczej przydatności gleb na podstawie przetwarzania ograniczonych informacji fizjograficznych i Glebowych ze zdigitalizowanych materiałów kartograficznych / Modeling the Position of Agricultural Suitability Units of Soils on the Basis of the Limited Physiographic Information Processing with Digitized Cartographic Materials

Abstract

The aim of the study was to test the ability to model soil capability units diversity of on the basis of limited information about particle size and morphology of the terrain data. The data obtained from digitization of maps of agricultural soil and topography of the region of the Upper Silesian Industrial District. Rule extraction tools and build models were algorithms in the field of computational intelligence: different versions of decision trees, neural networks and deep learning algorithms. The best algorithms allow for correct classification to 90% of the elements of the validation set. The design ensemble of specialized classifier algorithm increased the efficiency of decision-making algorithm to identify a set of validation to about 94%. Proper selection decision algorithm allows the estimation of the likelihood vector belonging to a complex object. Computational intelligence algorithms can be considered as a tool for extracting classification rules from the collection of data on soils on the local or regional level.

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Investigation of the high frequency band of heart rate variability: identification of preeclamptic pregnancy from normal pregnancy in Oman

, physiological interpretation, and clinical use. Eur Heart J. 1996; 17:354-81. 7. Hossen A, Heute U. Fully adaptive evaluation of SB-DFT, proceedings of IEEE Int. Symposium on Circuits and Systems, Chicago, Illinois, 1993. 8. Hossen A. Power spectral density estimation via wavelet decomposition. Electronics Letters. 2004; 40:1055-6. 9. Hossen A, Al--Ghunaimi B, Hassan MO. Subband decomposition soft decision algorithm for heart rate variability analysis in patients with OSA and normal controls. Signal Processing. 2005; 85

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Genetic algorithm method for solving the optimal allocation of response resources problem on the example of polish zone of the Baltic Sea / Metoda algorytmów genetycznych do rozwiązywania problemów optymalnej alokacji środków do zwalczania rozlewów olejowych na przykładzie polskiej strefy Morza Bałtyckiego

. Materiały dydaktyczne dla studentów matemetyki. [5] Michalewicz, Z., 1996. Agorytmy genetyczne+struktury danych=programy ewolucyjne. Wydawnictwa Naukowo-Techniczne, Warszawa. [6] Przywarty, M., 2012. Stochastyczny Model Oceny Bezpieczeństwa Nawigacyjnego na Akwenach Otwartych. Szczecin. [7] Psaraftis, H.N., Ziogas, B.O., 1985. Tactical decision Algorithm for the optimal dispatching of oil spill cleanup equipment. Manag. Sci. 31. [8] Rabbani, M., Yousefnejad, H., 2013. A novel approach for solving a

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Enumeration and Automatic Sequences

://www.fedoa.unina.it/3457/. [14] A. de Luca and S. Varricchio, Some combinatorial properties of the Thue-Morse sequence and a problem in semigroups, Theoret. Comput. Sci., 63 (1989) 333-348. [15] C. F. Du, H. Mousavi, L. Schaeffer and J. Shallit, Decision Algorithms for Fibonacci-Automatic Words, with Applications to Pattern Avoidance, preprint, 2014, available at http://arxiv.org/abs/1406.0670. [16] D. Goč, D. Henshall and J. Shallit, Automatic theorem-proving in combinatorics on words, Internat. J. Found. Comp. Sci., 24 (2013) 781

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Can interestingness measures be usefully visualized?

. (2003). Data mining, in J. Blazewicz,W. Kubiak, T.Morzy and M.E. Rusinkiewicz (Eds.), Handbook on Data Management Information Systems, Springer, Heidelberg, pp. 487-565. Nozick, R. (1981). Philosophical Explanations, Clarendon Press, Oxford. Pawlak, Z. (2002). Rough sets, decision algorithms and Bayes’ theorem, European Journal of Operational Research 136(1): 181-189. Pawlak, Z. (2004). Some issues on rough sets, Transactions on Rough Sets I, Elsevier Science Publishers, New York, NY, pp. 1-58. Shaikh, M

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On classification with missing data using rough-neuro-fuzzy systems

-360. Patel, A. V. and Mohan, B. M. (2002). Some numerical aspects of center of area defuzzification method, Fuzzy Sets and Systems   132 (3): 401-409. Pawlak, Z. (1982). Rough sets, International Journal of Information and Computer Science   11 (341): 341-356. Pawlak, Z. (1991). Rough Sets: Theoretical Aspects of Reasoning About Data , Kluwer, Dordrecht. Pawlak, Z. (2002). Rough sets, decision algorithms and Bayes' theorem, European Journal of Operational Research   136 (1): 181

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The biomarkers for acute kidney injury: A clear road ahead?

decision making for the initiation of renal replacement therapy (RRT) in patients with AKI. Selected studies demonstrated that NGAL, cystatin-C, NAG, KIM-1, and a1-microglobulin had the potential to distinguish patients in whom RRT will be needed. This would imply that these biomarkers may be integrated into clinical decision algorithms, and could synergistically improve current ability to initiate RRT early.[ 16 , 17 ] However, published studies have many recognized limitations, which preclude the ability to adapt their findings into clinical practice today. While the

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