University of Rijeka

About: University of Rijeka is a education organization based out in Rijeka, Croatia. It is known for research contribution in the topics: Population & Tourism. The organization has 3471 authors who have published 7993 publications receiving 110386 citations. The organization is also known as: Rijeka University & Sveučilište u Rijeci.

MAGIC observations and multifrequency properties of the Flat Spectrum Radio Quasar 3C 279 in 2011

Abstract: We study the multifrequency emission and spectral properties of the quasar 3C 279. We observed 3C 279 in very high energy (VHE, E>100GeV) gamma rays, with the MAGIC telescopes during 2011, for the first time in stereoscopic mode. We combine these measurements with observations at other energy bands: in high energy (HE, E>100MeV) gamma rays from Fermi-LAT, in X-rays from RXTE, in the optical from the KVA telescope and in the radio at 43GHz, 37GHz and 15GHz from the VLBA, Mets\"ahovi and OVRO radio telescopes and optical polarisation measurements from the KVA and Liverpool telescopes. During the MAGIC observations (February to April 2011) 3C 279 was in a low state in optical, X-ray and gamma rays. The MAGIC observations did not yield a significant detection. These upper limits are in agreement with the extrapolation of the HE gamma-ray spectrum, corrected for extragalactic background light absorption, from Fermi-LAT. The second part of the MAGIC observations in 2011 was triggered by a high activity state in the optical and gamma-ray bands. During the optical outburst the optical electric vector position angle rotatated of about 180 degrees. There was no simultaneous rotation of the 43GHz radio polarisation angle. No VHE gamma rays were detected by MAGIC, and the derived upper limits suggest the presence of a spectral break or curvature between the Fermi-LAT and MAGIC bands. The combined upper limits are the strongest derived to date for the source at VHE and below the level of the previously detected flux by a factor 2. Radiation models that include synchrotron and inverse Compton emissions match the optical to gamma-ray data, assuming an emission component inside the broad line region (BLR) responsible for the high-energy emission and one outside the BLR and the infrared torus causing optical and low-energy emission. We interpreted the optical polarisation with a bent trajectory model.

Modelling International Tourism Demand Using Seasonal ARIMA Models

Abstract: Purpose – The purpose of this study is to establish a seasonal autoregressive integrated moving average model able to capture and explain the patterns and the determinants of German tourism demand in Croatia.Design – The present study is based on the Box-Jenkins approach in building a seasonal autoregressive integrated moving average model intend to describe the behaviour of the German tourists’ flows to Croatia.Approach – The proposed model is a seasonal ARIMA(0,0,0)(1,1,3)4 model.Findings – The diagnostic checking and the performed tests showed that the estimated seasonal ARIMA(0,0,0)(1,1,3)4 model is adequate in modelling and analysing the number of German tourists’ arrivals to Croatia.Originality of the Paper – This study provides a seasonal ARIMA model helpful to analyse, understand and forecast German tourists’ flows to Croatia. Such, more detailed and systematic studies should be considered as starting points of future macroeconomic development strategies, pricing strategies and tourism sector routing strategies in Croatia, as a predominantly tourism oriented country.

Kinetic Energy Harvesting for Wearable Medical Sensors.

Abstract: The process of collecting low-level kinetic energy, which is present in all moving systems, by using energy harvesting principles, is of particular interest in wearable technology, especially in ultra-low power devices for medical applications. In fact, the replacement of batteries with innovative piezoelectric energy harvesting devices can result in mass and size reduction, favoring the miniaturization of wearable devices, as well as drastically increasing their autonomy. The aim of this work is to assess the power requirements of wearable sensors for medical applications, and address the intrinsic problem of piezoelectric kinetic energy harvesting devices that can be used to power them; namely, the narrow area of optimal operation around the eigenfrequencies of a specific device. This is achieved by using complex numerical models comprising modal, harmonic and transient analyses. In order to overcome the random nature of excitations generated by human motion, novel excitation modalities are investigated with the goal of increasing the specific power outputs. A solution embracing an optimized harvester geometry and relying on an excitation mechanism suitable for wearable medical sensors is hence proposed. The electrical circuitry required for efficient energy management is considered as well.