Utilization of Unmanned Aerial Vehicle (UAV) for observing landscape is rapidly increasing because it is fast a fast way which provides data on demand with an appropriate resolution. Data are suitable for next processing and analyses and the whole procedure is reasonably cheap. It is necessary to propose and describe a suitable process for data collection and processing to repeatedly obtain correct results. Thus, the paper proposes the whole procedure of UAV data collection, preprocessing, classification and indices calculation. The selected aspects of the process are described in a graphical form of various process diagrams (process map, data flow diagram and indicators matrix). The paper describes a case study which is focused on an identification of a small water body (pond Pohranov near Pardubice city in the Czech Republic) shoreline to demonstrate the whole process. The provided graphical description allows standardise the whole process, choose suitable data and an appropriate way of their analysis (e.g. indicators matrix). Main advantage of the proposed procedure is applicability on various data sources and areas of interest.

Mobile ad-hoc network (MANET) has attracted the attention of networking industries owning to their desirable characteristics such as multi-hop routing, self-configuration, self-healing, self-managing, reliability, and scalability. Routing over wireless mobile networks is a critical problem due to the dynamic nature of the link qualities, even when nodes are static. A key challenge in MANETs is the need for an efficient routing protocol that establishes a route according to certain performance metrics related to the link quality. The routing issue in MANETs is generally concerned with finding a good path between the source and the destination pairs. Based on that, there is a demand for the development of a high throughput routing protocol. The impact of a single-path routing protocol and a multi path routing protocol on the performance of MANETs is required to be investigated. In this work, a performance comparison in terms of throughput, packet delivery, routing overhead, and end to end delay of well-known routing protocols such as AODV, AOMDV, and OLSR using network simulator version 2 (NS-2) has been introduced. The simulation results of this work show that the single-path AODV protocol out performance the multi path OLSR and AOMDV protocols in terms of throughput and packet delivery ratio. In addition to that, the single-path routing protocol presents less routing overhead in comparison to the AOMDV and OLSR. While the OLSR and AOMDV demonstrate a relatively better end to end delay in comparison to the AODV protocol.

The amount of available educational data is growing and the educational institutions try to organize and understand large complex datasets. Since these big data are an emerging field of study, there is no simple solution to process or analyze them. This paper aims to provide a model approach to process big educational data from the Moodle system in the cloud using the Apache Hadoop cluster. An experimental implementation of the proposed model approach is included to validate this solution. The results then suggest that the proposed model approach has a potential to be widely used for the processing of big educational data, especially with user interaction data.