TY  - CHAP
AU  - Sütő, József
AU  - Oniga, István
AU  - Hegyesi, Gyula
ED  - Szakál, A
TI  - A simple fast Fourier transformation algorithm to microcontrollers and mini computers
T2  - IEEE 18th International Conference on Intelligent Engineering Systems
PB  - Institute of Electrical and Electronics Engineers (IEEE)
CY  - Piscataway (NJ)
SN  - 147994615X
PY  - 2014
SP  - 61
EP  - 65
PG  - 5
DO  - 10.1109/INES.2014.6909342
UR  - https://m2.mtmt.hu/api/publication/2744063
ID  - 2744063
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - C, Lung
AU  - Oniga, István
AU  - Buchman, Attila
AU  - A, Tisan
TI  - Wireless data acquisition system for IoT applications
JF  - CARPATHIAN JOURNAL OF ELECTRONIC AND COMPUTER ENGINEERING
J2  - CARPATH J ELECTRONIC COMPUTER ENGINEERING
VL  - 6
PY  - 2013
IS  - 1
SP  - 64
EP  - 67
PG  - 4
SN  - 1844-9689
UR  - https://m2.mtmt.hu/api/publication/2454257
ID  - 2454257
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Sütő, József
AU  - Oniga, István
AU  - I, Orha
ED  - Illyefalvi-Vitéz, Zsolt
TI  - Microcontroller based health monitoring system
T2  - 2013 IEEE 19th International Symposium for Design and Technology in Electronic Packaging (SIITME)
PB  - IEEE
CY  - Piscataway (NJ)
SN  - 1479915548
PY  - 2013
SP  - 227
EP  - 230
PG  - 4
DO  - 10.1109/SIITME.2013.6743679
UR  - https://m2.mtmt.hu/api/publication/2454215
ID  - 2454215
N1  - Faculty of Informatics, University of Debrecen, Debrecen, Hungary            
            Electronic, Electronic and Computer Engineering, North University Center Baia Mare, Baia Mare, Romania            
            Cited By :6            
            Export Date: 27 December 2018
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Sütő, József
AU  - Oniga, István
TI  - Testing artificial neural network for hand gesture recognition
JF  - CREATIVE MATHEMATICS AND INFORMATICS
J2  - CREAT MATH INFORM
VL  - 22
PY  - 2013
IS  - 2
SP  - 223
EP  - 228
PG  - 6
SN  - 1584-286X
UR  - https://m2.mtmt.hu/api/publication/2531428
ID  - 2531428
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Terdik, György
AU  - Gál, Zoltán
TI  - Advances and practice in Internet of Things
T2  - 4th IEEE International Conference on Cognitive Infocommunications
PB  - IEEE
CY  - New York, New York
CY  - Piscataway (NJ)
SN  - 9781479915460
PY  - 2013
SP  - 435
EP  - 440
PG  - 6
DO  - 10.1109/CogInfoCom.2013.6719286
UR  - https://m2.mtmt.hu/api/publication/2720926
ID  - 2720926
AB  - Internet of Things (IoT) services and technologies become more and more predominant in the current and future era of the Internet. Lot of devices and applications are developed and connected to the classical IP networks. As for any new network services testing and evaluation is made in the intranet environment in these days. Neither the efficiency measurement methods of the energy usage nor communication nor sustainability aspects of these services have been determined exactly. Well defined solutions based on statistical analysis are needed to gather practical knowledge about the sensor based network nodes. The errors of the collected data arise in different levels of the process. There are errors during the measurement of a given signal by the sensor, another type of errors is generated during the transmission of collected data through the sensor access network, finally the store process of the received data influenced by errors as well. Evaluation of the hardware and software resource usage by the services and applications are very dissimilar tasks from the classical wired or wireless data network situations in case of IoT. Because of the data streams coming from quite a number of sensors, the statistical analysis of several dozens or hundreds of time series become a complex processing problem. The time series affected by errors generate a pre-processing challenge, which depends on several simultaneous aspects like the measured signal, the applied IoT communication technology and the data storing mechanism. The statistical analysis methods of the time series originated from the preliminary processing differ from the classical data network performance evaluation methods since in the IoT streams are grouped in epoch time periods, for instance. Having huge number of several variables distributed in time and physical space which describes special aspects of the measured and/or controlled system implies complex event processing. This paper presents a case study for the complex data set which has been captured from 18 TFLOPS capacity supercomputer system with 1.5 thousand CPU cores. © 2013 IEEE.
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Bérczes, Tamás
AU  - Sztrik, János
AU  - Orosz, Péter
AU  - Pascal, Moyal
AU  - N., Limnios
AU  - S., Georgiadis
TI  - Tool supported modeling of sensor communication networks by using finite-source priority retrial queues
JF  - CARPATHIAN JOURNAL OF ELECTRONIC AND COMPUTER ENGINEERING
J2  - CARPATH J ELECTRONIC COMPUTER ENGINEERING
VL  - 5
PY  - 2012
SP  - 13
EP  - 18
PG  - 6
SN  - 1844-9689
UR  - https://m2.mtmt.hu/api/publication/2166892
ID  - 2166892
LA  - English
DB  - MTMT
ER  -