No abstract

The research is focused on the relationship between aviation systems and extreme terrorist events, the impacts of such events, and the solutions to manage the associated risks on medium and long term. The development of predictive models for extremeasymmetric events in aviation (EAEA) still represents an emerging direction of interdisciplinary research because not all mechanisms and interactions are understood. The testing of models is difficult due to lack of data and interpretation frameworks and includes a major human component specific to social sciences. The proposed risk assessment model is based on a simulation algorithm, and relies on a spreadsheet program that models the risk in conjunction with input data: threat, vulnerability and consequences. The main advantage of the model is that it provides a fast and intuitive image of the phenomenon, using unsophisticated databases. In addition, the case study developed by the authors of the article and focused on modeling and simulating terrorist risk in a Romanian international airport answers decision makers' current requirement to operate a flexible, adaptable and scalable platform efficiently and rapidly.

In the field of UAV, information processing centers most often materialize through ground control stations (GCS) that are used in various variants from simple commercial products in the form of tablets or radio control stations for controlling the vector within the visual range at low altitudes and autonomies, or portable, fixed or self-propelled technologies for missions beyond the visual range at high altitudes and autonomies. The article wants an overview of the theoretical bases on the construction and operation of GCS and aspects of flight mission debriefing using freeware tools.

The objective of this contribution is to explore innovative ways to increase the efficiency of large scale photovoltaic systems (LSPVS) in the medium term through effective management of operating, monitoring and maintenance (OMM) costs based on aerial surveillance with small multi-rotor flight robot (s-MRFR). An effective solution of OMM cost assessment must capture the dynamic interaction between energy market developments, technological progress and investor tolerance to the risk posed by climate changes. The valuation method for OMM cost-risk analysis is based on generalized Wiener process with stochastic jumps. The interest is to increase the value of the investment by using innovative but efficient procedures of PV systems inspection based on aerial infrared thermography. The results are encouraging because the total costs of s-MRFR monitoring are very low compared to the benefits.

This scientific approach has been initiated in the context of the rapid and unpredictable developments of climatic factors that generate a major challenge for military critical infrastructure protection systems. The proposed methodology integrates on a specially designed decision-making platform the two approaches specific to risk management: adaptive-preventive (risk assessments at the local area based on the connection between climate change vectors-the asset of infrastructure-the potential impact on medium and long term) and adaptive-reactive (real-time event monitoring using emerging technologies: integration of sensors on a robotic aerial platform). The architecture of the research model was designed to meet both user requirements (modular, flexible, scalable) and the needs to overlap the stages of the risk management process. Model testing on simulated scenarios under laboratory conditions demonstrated the functionality and highlighted the expected performance.