Wastewater and wastewater treatment plants serve as urban reservoirs of pathogenic microorganisms. Wastewaters frequently contain bacteria, antibiotic-resistant bacteria, and developmental stages of parasites with significant zoonotic potential. Five wastewater treatment plants in the central part of Slovakia were investigated to determine the effect of treatment on bacterial community, antibiotic-resistant bacteria, and the occurrence of helminth eggs. Although all monitored chemical factors (chemical oxygen demand, biochemical oxygen demand, N-NH4, total nitrogen, and total phosphorus) in the effluent were in line with the legislative standards for discharge into public waterways, the results of minimal inhibitory concentrations show that reclaimed water harbors E. coli resistant to several commonly used antibiotics (ampicillin, piperacillin, and tazobactam, combine ampicillin and sulbactam, cefotaxime, tetracycline). The presence of endoparasite developmental stages in wastewater and sludge (Ascaris spp., Hymenolepis nana, eggs from the Ancylostomatidae family, Giardia duodenalis) indicates potential health risks for humans and workers at these sites. Treatment such as composting before applying sludge to land is necessary to reduce human pathogens.

This paper deals with a plaintext-related image encryption algorithm that modifies the parameter values used by the logistic map according to plain image pixel intensities. The parameter values are altered in a row-wise manner, which enables the usage of the same procedure also during the decryption. Furthermore, the parameter modification technique takes into account knowledge about the logistic map, its fixed points and possible periodic cycles. Since the resulting interval of parameter values achieves high positive values of Lyapunov exponents, the chaotic behavior of the logistic map should be most pronounced. These assumptions are verified by a set of experiments and the obtained numerical values are compared with those reported in relevant papers. It is found that the proposed design that uses a simpler, but well-studied, chaotic map with mitigated issues obtains results comparable with algorithms that use more complex chaotic systems. Moreover, the proposed solution is much faster than other approaches with a similar purpose.

The 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 one-year-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. (4.0 %), Toxascaris leonina (3.1 %), Capillaria spp. (1.0 %), Dipylidium caninum (0.2 %) and Coccidia oocysts (0.2 %). Additionally 285 sandpits were examined. Sand samples were collected from Košice (136), Zvolen (38), Trenčín (36), Prešov (30), Veľké Kapušany (24), Snina (15), and village Valaliky (6). The parasitic eggs occurence in the sandpits was as follows: Toxocara spp. (11.8 %), Ancylostomatidae (1.1 %), Taenia type (0.7 %) and Trichuris spp. (0.4 %). The occurrence of Toxocara 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.

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.

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. 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.

Resilient of routing processes is one of the biggest challenges for data transmission in mobile networks without infrastructure. Communication under current routing protocols is through a communication path that, although the shortest, may not perform satisfactorily in terms of resilient. Routing and communication within such a path may take place using nodes that are malicious or inappropriate in the communication process due to malicious or poor technical state. This paper presents a new algorithm for various uses of mobile ad hoc networks not only in edge networks with infrastructure but also with the possibility of being used in the cloud solutions. We have modified decentralized blockchain technology and artificial intelligence using deep learning methods that have been implemented in routing processes. The objective of this algorithm was to select the most resilient communication path from the source to the destination node. Such a communication path selection consisted of selecting the nodes that were most suitable in terms of resilience, where the selection nodes was provided through a network and technical parameters. The key quality of service metrics, throughput, total delay, number of delivered signaling and data packets and the ratio between them were used to evaluate the proposed resilient routing algorithm. Modified resilient routing protocols achieved improvement in all the analyzed parameters compared to the original routing protocols. The improvement in these parameters led to an increase in the resilience of the routing process based on the actual data obtained from each node in the network and previous communications.