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Jayesh Ruikar, Ashoke Sinha and Saurabh Chaudhury

R eferences [1] Z. Wang and A. C. Bovik, “A universal image quality index,” Signal Processing Letters, IEEE , vol. 9, no. 3. pp. 81–84, 2002. [2] J. D. Ruikar, A. K. Sinha, and S. Chaudhury, “Review of Image Enhancement Techniques,” in International Conference on Information Technology in Signal and Image Processing - itSIP , p. 2013. [3] Q. Huynh-Thu and M. Ghanbari, “Scope of validity of PSNR in image/video quality assessment,” Electronics Letters , vol. 44, no. 13. pp. 800–801, 2008. [4] Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P

Open access

Michal Mardiak and Jaroslav Polec

References A. B. Watson, J. Hu, and J. F. McGowan, "Dvq: A digital video quality metric based on human vision," Electronic Imaging , 2001. ITU-R, "Methodology for the subjective assessment of the quality of television pictures," International Telecommunication Union - Radio-communication Sector, Tech. Rep. BT.500-11, 2002. J. L. Martnez, P. Cuenca, F. Delicado, and F. Quiles, "Objective video quality metrics: A performance analysis," Sep. 2006. Z. Wang, A

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Filip Lewandowski, Mateusz Paluszkiewicz, Tomasz Grajek and Krzysztof Wegner

References [1] C. Fehn, “Depth-image-based rendering (DIBR), Compression and Transmission for a New Approach on 3D-TV,” Proceedings of SPIE , vol. 5291, pp. 93-104, January 2004, CA, U.S.A. [2] J. W. Shade, S. J. Gortler, L.-W. He, and R. Szeliski, “Layered depth images,” Computer Graphics , vol. 32, pp. 231-242, July 1998, Annual Conference Series. [3] ITU-R Rec. BT.500-11, “Methodology for the Subjective Assessment of the Quality of Television Pictures,” 2002. [4] Z. Wang, A. C. Bovik

Open access

Dariusz Strzęciwilk

References [1] L. D. Ghein, MPLS Fundamentals. Indianapolis, USA: Cisco Press, 2007. [2] J. Postel (ed.), Internet protocol - DARPA Internet Program Protocol Specification, USC/Information Science Institute RFC 791, September 1981. [3] A. Grenville, Quality of Service in IP Networks. Pearson Higher Education, 2000. [4] D. Hucaby, CCNP BCMSN exam certification guide: CCNP self-study. Indianapolis, USA: Cisco Press, 2006. [5] K. Ahlin, Quality of Service Over IP Networks. Linköping

Open access

Mirolyub Mladenov

References 1. Andrés, S., I. Murray, E. A. Navajas, A. V. Fisher, N. R. Lambe, L. Buenger. Prediction of Sensory Characteristics of Lamb Meat Samples by Near Infrared Reflectance Spectroscopy. - Meat Science, 76, 2007, No. 3, 509-516. 2. Chmiel, M., M. Slowinski, K. Dasiewicz. Lightness of the Color Measured by Computer Image Analysis as a Factor for Assessing the Quality of Pork Meat. - Meat Science, 88, 2011, Issue 3, 566-570. 3. Da-Wen Sun. Computer Vision Technology in the Food and Beverage Industries

Open access

Elisaveta Trichkova

References 1. Bari, M. and R. Djouab. The Current Situation of e-learning.Preparation, 2014. 2. Chua, B. B. & L. E. Dyson. Applying the ISO9126 Model to the Evaluation of an e-learning System. R. Atkinson, C. McBeath, D. Jonas-Dwyer & R. Phillips (Eds), Beyond the Comfort Zone: Proceedings of the 21st ASCILITE Conference, Perth, 5-8 December 2004, 184-190. 3. Padayachee, I., P. Kotze and A. van der Merwe. ISO 9126, External Systems Quality Characteristics, SubCharacteristics and Domain Specific Criteria for

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Zenon Chaczko and Anup Kale

. M. Mozina, D. Tomjevic, F. Pernus, and B. Likar, "Real Time Image Segmentation of Pharmaceutical Tablets," Machine Vision and Applications , August 2009. E. Deutschl and A. Linnhofer, "Tablet Quality Assurance in Real Time," 14th International Conference on Pattern Recognition , vol. 2, 1998. J. R. Koza, Genetic Programming . Masschusetts, USA: MIT Press, 1992. T. Centeno, H. Lopes, M. Felisberto, and L. Arruda, "Object Detection Using Robust Genetic Algorithm, Evo Workshops," LNCS

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Krzysztof Stachowiak and Piotr Zwierzykowski

References [1] R. K. Ahuja, T. L. Magnanti, and J. B. Orlin, Network flows: theory, algorithms, and applications. Upper Saddle River, NJ, USA: Prentice- Hall, Inc., 1993. [2] S. Chen and K. Nahrstedt, “An overview of quality of service routing for next-generation high-speed networks: problems and solutions,” IEEE Network, vol. 12, pp. 64-79, 1998, DOI: 10.1109/65.752646. [3] T. Korkmaz and M. Krunz, “Multi-Constrained Optimal Path Selection,” in Proceedings of IEEE International Conference on Computer

Open access

V. C. Prasad


Two new problems are posed and solved concerning minimal sets of prime implicants of Boolean functions. It is well known that the prime implicant set of a Boolean function should be minimal and have as few literals as possible. But it is not well known that min term repetitions should also be as few as possible to reduce power consumption. Determination of minimal sets of prime implicants is a well known problem. But nothing is known on the least number of (i) prime implicants (ii) literals and (iii) min term repetitions , any minimal set of prime implicants will have. These measures are useful to assess the quality of a minimal set. They are then extended to determine least number of prime implicants / implicates required to design a static hazard free circuit. The new technique tends to give smallest set of prime implicants for various objectives.

Open access

International Journal of Electronics and Telecommunications

The Journal of Committee of Electronics and Telecommunications of Polish Academy of Sciences