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Low-carbon Building Innovation Trends and Policy Pespectives in Hungary between 2020 and 2030

. , ’Assessment Model for Energy Consumption and Greenhouse Gas Emissions during Building Construction. ’ J. Manage. Eng. , 30 Volume 2 (2014), pp. 226–235. DOI: 10.1061/(ASCE)ME.1943-5479.0000199 [21] F ogarassy , C s ., B akosne , B., M., R ashad , S., M., Z sarnoczai , J., M. Low-carbon principles and sustainability relations of the Rubik’s cube layer by layer solution method. Journal of Central European Green Innovation, Volume 2 Issue 4 (2014), pp. 29-52. URL: http://real.mtak.hu/23444/1/Fogarassy_et_al_3_u.pdf

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Decision-Making Enhancement in a Big Data Environment: Application of the K-Means Algorithm to Mixed Data

. [11] Gal Engelberg, Oded Koren, and Nir Perel. Big data performance evaluation analysis using apache pig. International Journal of Software Engineering and Its Applications, 10(11):429–440, 2016. [12] Johann Füller, Katja Hutter, Julia Hautz, and Kurt Matzler. User roles and contributions in innovation-contest communities. Journal of Management Information Systems, 31(1):273–308, 2014. [13] Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung. The google file system. In Proceedings of the 19th ACM Symposium on Operating Systems Principles, pages 20

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Detecting Driver’s Fatigue, Distraction and Activity Using a Non-Intrusive Ai-Based Monitoring System

Processing, May 2012, pp. 1–5. [44] W. Zhang, B. Cheng, and Y. Lin, Driver drowsiness recognition based on computer vision technology, Tsinghua Science and Technology, vol. 17, no. 3, pp. 354–362, June 2012. [45] IEE. Hands Off Detection - IEE - a sense for innovation. (2018, Oct. 17). [Online]. Available: https://www.iee.lu/en/products/automotive/hands-off-detection [46] M. Miyaji, H. Kawanaka, and K. Oguri, Driver’s cognitive distraction detection using physiological features by the adaboost, in 2009 12th International IEEE Conference on Intelligent

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Long-term Green Innovation Opportunities Within the Hungarian District Heating Sector Towards 2030

Európai Unió energiapolitikájában, Politikatudományi Szemle 4. (2004), p.192-198. [8] Camp R. C. “Learning from the Best Leads to Superior Performance”, Journal of Business Strategy, Volume 13 (1992), Issue 3, pp. 3 - 6 DOI: 10.1108/eb039486 [9] Fogarassy Cs., Horvath B. Low-carbon building innovation trends and policy perspectives in Hungary between 2020 and 2030 YBL Journal Of Built Environment Volume 3 (2015), No. 2 pp. 17-23. DOI: 10.1515/jbe-2015-0005 [10] Pigou A.C. The Economics of Welfare, MacMillan, Part II. (1920

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Contactless Impedance Cardiography Using Embedded Sensors

Impedance cardiography is a technique developed with the intent of monitoring cardiac output. By inspecting a few properties of the obtained signal (impedance cardiogram (ICG), the left ventricular ejection time can be derived with certainty, and an estimate of cardiac output is available. This signal is nowadays used in non-invasive monitoring, requiring the placement of electrodes over the subject’s skin, either ECG-type or in the form of encircling bands. The work here reported describes the implementation steps and the results obtained when embedding the ICG circuitry in a wheelchair’s backrest. The subject is seated normally, is normally dressed, and is completely unaware that monitoring is taking place. That means that the variation of tenths of ohm produced due to the cardiac cycle has to be detected with electrodes having substantial coupling impedance. Contactless ICG with embedded sensors was developed and tested on fourteen healthy subjects. The signal was always acquired, although respiratory activity is also important, constituting a noteworthy innovation in the area.

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Measurement, Information Channels, and Discretization: Exploring the Links

Measurement, Information Channels, and Discretization: Exploring the Links

The goal of this paper is to present a unified algebraic-analytic framework for (static and dynamic) deterministic measurement theory, which we find to be fully adequate in engineering and natural science applications. The starting point of this paradigm is the notion of a quantity algebra of a measured system and that of a measuring instrument, underlying the causal linkages in classical ‘system + instrument’ interactions. This approach is then further enriched by providing a superimposed data lattice of measurement outcomes, intended to handle the information flow from the measured system to its measurand's designated instrument.

We argue that the language of Banach and von Neumann algebras is ideally suited for the treatment of quantities, encountered in theoretical and experimental science. These algebras and convex spaces of expectation functionals thereon together with information (co)channels between them provide a comprehensive information-theoretic framework for measurement theory. Concrete examples and applications to length and position measurements are also discussed and rigorously framed within the proposed quantity algebra and associated information channel paradigms.

In modeling physical systems, investigators routinely rely on the assumption that state spaces and time domains form a continuum (locally homeomorphic to the real line or its Cartesian powers). But in sharp contrast, measurement and prediction outcomes pertaining to physical systems under consideration tend to be presented in terms of small discrete sets of rational numbers. We investigate this conceptual gap between theoretical and finitary data models from the perspectives of temporal, spatial and algebraic discretization schemes.

The principal innovation in our approach to classical measurement theory is the representation of interactive instrument-based measurement processes in terms of channel-cochannel pairs constructed between dynamical quantity algebras of a target system and its measurand's measuring instrument.

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Numerical Analysis of Isotropy Electromagnetic Sensor Measurement Error

analysis - a closed form calculation in cartesian coordinates. Journal of Electrical Engineering, 64 (5), 327-330. [4] Balanis, C.A. (1997) Antenna Theory: Analysis and Design, 2nd edition. John Wiley & Sons. [5] Slížik, J., Harťanský, R. (2013) Metrology of electromagnetic intensity measurement in near field.Quality Innovation Prosperity, 17 (1), 57-66. [6] Bittera, M., Kováč, K., Hallon, J. (2007) Measurement of semi-anechoic chamber using modified VSWR method above 1GHz. Measurement Science Review, 7 (3), 42

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New Discrete Fibonacci Charge Pump Design, Evaluation and Measurement

computer systems. In IEEE International Symposium on Circuits and Systems , 11-14 June 1991. IEEE, 1065-1068. [5] Tanzawa, T. (2016). Innovation of switched-capacitor voltage multiplier: Part 1: A brief history. IEEE Solid-State Circuits Magazine , 8 (1), 51-59. [6] Allasasmeh, Y., Gregori, S. (2009). A performance comparison of dickson and fibonacci charge pumps. In European Conference on Circuit Theory and Design , 23-27 August 2009. IEEE, 599-602. [7] Matousek, D., Hospodka, J., Subrt, O. (2016). Efficiency of innovative charge pump versus clock

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Measurement of the Operating Parameters and Numerical Analysis of the Mechanical Subsystem

). Numerical impedance analysis of thin wire dipoles. In Mechatronika 2010 : 13th International Conference on Mechatronics, 2-4 June 2010. IEEE, 51-53. [4] Gruttner, E., Pinninghoff, M.A., Tudela, A., Diaz, H. (2002). Recorridos optimos de lineas de transporte publico usando algoritmos geneticos. In Jornadas Chilenas de Computación (JCC’2002), November 2002, Copiapo, Chile. [5] Sližik, J., Harťansky, R. (2013). Metrology of electromagnetic intensity measurement in near field. Quality Innovation Prosperity, 17 (1), 57-66. [6

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Sensor Interaction as a Source of the Electromagnetic Field Measurement Error

References [1] Vavra, Š., Turán, J. (1989). Antény a šírenie elektromagnetických vĺn . Bratislava: Alfa. [2] Balanis, A.C. (1997) Antenna Theory Analysis and Design, 3th edition . John Wiley & Sons. [3] Slížik, J., Harťanský, R. (2013). Metrology of electromagnetic intensity measurement in near field metrology of electromagnetic intensity measurement in near field. Quality Innovation Prosperity, 17 (1), 57-66. [4] Harťanský, R., Slížik, J., Maršálka, L. (2013). Dipole near field analysis – a closed form calculation in cartesian coordinates

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