273 SummaryThe objective of this study was to determine the possibility of soil contamination with propagative stages of intestinal endoparasites at different public places (public parks, playgrounds, sandpits, sidewalks, road sides). In a oneyear-study, totally 578 dog's faecal samples from 8 towns (Košice, Trebišov, Veľké Kapušany, Prešov, Snina, Levoča, Zvolen and Trenčín) and 3 villages (Dlhé Stráže, Dravce, Valaliky) were examined for the presence of parasitic germs. 29.9 % of faecal samples were positive. Eight different species of intestinal parasites with following incidence were detected: Toxocara canis (11.9 %), Trichuris vulpis (8.5 %), Ancylostomatidae (8.1 %), Taenia spp. varied between the urban and rural environments. The highest number of Toxocara spp. was found in village Valaliky (33.3 %) whereas cities showed lesser prevalence (Prešov -10 %, Košice -7.4 %, Trenčín -5.6 %, Zvolen -5.3 %, Veľké Kapušany -4.2 %). The epidemiological aspects and health risk factors are also discussed.

A new routing algorithm for mobile ad hoc networks is proposed in this paper: an Enhanced Hybrid Social Based Routing (HSBR) algorithm for MANET-DTN as optimal solution for well-connected multihop mobile networks (MANET) and/or worse connected MANET with small density of the nodes and/or due to mobility fragmented MANET into two or more subnetworks or islands. This proposed HSBR algorithm is fully decentralized combining main features of both Dynamic Source Routing (DSR) and Social Based Opportunistic Routing (SBOR) algorithms. The proposed scheme is simulated and evaluated by replaying real life traces which exhibit this highly dynamic topology. Evaluation of new proposed HSBR algorithm was made by comparison with DSR and SBOR. All methods were simulated with different levels of velocity. The results show that HSBR has the highest success of packet delivery, but with higher delay in comparison with DSR, and much lower in comparison with SBOR. Simulation results indicate that HSBR approach can be applicable in networks, where MANET or DTN solutions are separately useless or ineffective. This method provides delivery of the message in every possible situation in areas without infrastructure and can be used as backup method for disaster situation when infrastructure is destroyed.

In the real world, wireless mobile devices are carried by humans. For this reason, it is useful if mobility models as simulation tools used to test routing protocols and other MANET-DTN features follow the behaviour of humans. In this paper, we propose a new social based mobility model called Students Social Based Mobility Model (SSBMM). This mobility model is inspired by the daily routine of student's life. Since many current social based mobility models give nodes freedom in terms of movement according to social feeling and attractivity to other nodes or places, we focus more on the mandatory part of our life, such as going to work and school. In the case of students, this mandatory part of their life is studying in university according to their schedule. In their free time, they move and behave according to attractivity to other nodes or places of their origin. Finally, proposed SSBMM was tested and verified by Tools for Evaluation of Social Relation in Mobility Models and compared with random based mobility models. At the end, SSBMM was simulated to examine the impact of social relations on routing protocols.

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This study deals with the problem of fiber-free optical communication systems—known as free space optics—using received signal strength identifier (RSSI) prediction analysis for hard switching of optical fiber-free link to base radio-frequency (RF) link and back. Adverse influences affecting the atmospheric transmission channel significantly impair optical communications, therefore attention was paid to the practical design, as well as to the implementation of the monitoring device that is used to record and process weather information along a transmission path. The article contains an analysis and methodology of the solution of the high availability of the optical link. Attention was paid to the technique of hard free space optics (FSO)/RF-switching with regard to the amount of received optical power detected and its relation to the quantities influencing the optical communication line. For this purpose, selected methods of machine learning were used, which serve to predict the received optical power. The process of analysis of prediction of received optical power is realized by regression models. The study presents the design of the optimal data input matrix model, which forms the basis for the training of the prediction models for estimating the received optical power.