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This article is a continuation of the authors’ study on the ways to ensure safety in the Air Traffic Management (ATM) system. It directly refers to the processes of risk management involving,in particular,risk management in (air) transport. The main aim of this paperis to present and indicate the hazard identification and risk assessment tools that can be used in air transport and toapply one of them for a risk analysis of a specific ATM originating case. Thisis why,after a short introduction, describing the background of the research as well as literature review, the risk management process as such is characterized. It is shown ina schematic way and its main components are identified. At the same time,from the entire management process,the risk assessment procedure is highlightedas its most crucial part. Then, general hazards identification techniques, risk analysis and assessment tools are described, with an indication that they can also be implemented in air transport, if compatible with ICAO Standards and Recommended Practices (SARPs). In the following part,the process of risk assessmentin air transport, based onthe SafetyManagement Manual, using a safety risk tolerability matrix, is characterized. Finally, in this article,an exemplary risk analysis is carried out, focusing ona selected case arising from the ATM field. For the analysed case,safety risk hazards and theirpossible effects are identified and then assigned to the Intolerable, Tolerable and Acceptable regions.The entire paperis summarized and conclusions are drawn in relation to the publication’s main goal. Attention is also paid to the potential causes of appearance of hazards including,first of all,lack of adequate verification procedures, as well as people’scompetence and last but not the least humanerrors, being the reason for 70-80%of unwanted transport accidents.

Today’s technological developments make it possible to use machines to perform specific tasks instead of humans. However, the challenge for such autonomous devices is to precisely move and navigate in constantly changing external environments. In this paper, the influence of varying weather conditions (air temperature, humidity, wind speed, atmospheric pressure, type of satellite systems used/satellites visible, and solar activity) on the accuracy of position determination was analyzed. To reach the receiver, a satellite signal must travel a great distance and pass through all layers of the Earth’s atmosphere, the variability of which causes errors and delays. Moreover, the weather conditions for receiving data from satellites are not always favorable. In order to investigate the impact of delays and errors on position determination, the measurements of the satellite signal were conducted, the motion trajectories were determined, and the standard deviations of these trajectories were compared. The results obtained show that it is possible to achieve high precision in determining the position, but varying conditions, such as solar flares or satellites’ visibility, meant that not all measurements are able to achieve the required accuracy. The use of the absolute method of satellite signal measurements contributed to this to a large extent. To increase the accuracy of positioning by GNSS systems, it is first of all proposed to use a dual-frequency receiver that eliminates ionospheric refractions.

This paper refers to a machine learning method for solving NP-hard discrete optimization problems, especially planning and scheduling. The method utilizes a special multistage decision process modeling paradigm referred to as the Algebraic Logical Metamodel based learning methods of Multistage Decision Processes (ALMM). Hence, the name of the presented method is the ALMM Based Learning method. This learning method utilizes a specifically built local multicriterion optimization problem that is solved by means of scalarization. This paper describes both the development of such local optimization problems and the concept of the learning process with the fractional derivative mechanism itself. It includes proofs of theorems showing that the ALMM Based Learning method can be defined for a much broader problem class than initially assumed. This significantly extends the range of the prime learning method applications. New generalizations for the prime ALMM Based Learning method, as well as some essential comments on a comparison of Reinforcement Learning with the ALMM Based Learning, are also presented.

Aviation has been one of the key engines of the globalization process and, at the same, time one of the industries most affected by the COVID-19 pandemic and the parallel economic crisis. As safety seems to be the key issue at aerodromes, the aim of this article is to analyze what kind of safety hazards have the coronavirus slowdown created and which of them pose the greatest risk for aerodrome safety in the long run. What is more, the goal of the paper is to direct managers’ attention to proper crisis management in line with sustainability. The main findings are that all classified hazards cause, according to an expert’s assessment, similar safety risk at aerodromes, though limited workforce training and development are perceived as posing the greatest risk. The recommended solution to minimize the occurrence of the hazard is proactive risk management, which means that managers try to anticipate possible hazards in advance and act accordingly, which requires continual controlling combined with internal and external environment analysis and a consistent learning process. That should be accompanied by constant staff development. All these seem to effectively minimize most risks and make ground for a sustainable and safe transport system.

The increase in the role of companion robots in everyday life is inevitable, and their safe communication with the infrastructure is one of the fundamental challenges faced by designers. There are many challenges in the robot’s communication with the environment, widely described in the literature on the subject. The threats that scientists believe have the most significant impact on the robot’s communication include denial-of-service (DoS) attacks, satellite signal spoofing, external eavesdropping, spamming, broadcast tampering, and man-in-the-middle attacks. In this article, the authors attempted to identify communication threats in the new robot-to-infrastructure (R2I) model based on available solutions used in transport, e.g., vehicle-to-infrastructure (V2I), taking into account the threats already known affecting the robot’s sensory systems. For this purpose, all threats that may occur in the robot’s communication with the environment were analyzed. Then the risk analysis was carried out, determining, in turn, the likelihood of potential threats occurrence, their consequence, and ability of detection. Finally, specific methods of responding to the occurring threats are proposed, taking into account cybersecurity aspects. A critical new approach is the proposal to use communication and protocols so far dedicated to transport (IEEE 802.11p WAVE, dedicated short-range communications (DSRC)). Then, the companion’s robot should be treated as a pedestrian and some of its sensors as an active smartphone.

There is a noticeable number of studies carried out on both the operational parameters of Global Navigation Satellite System (GNSS) and the satellite signal itself. Researchers look for, inter alia, proven sources of errors affecting the integrity of the satellite signal because this parameter determines the approval of the system’s operational use. It also seems of key importance that the atmospheric conditions, in any area of satellite signal usage, should not be underestimated due to their extensive impact. As the ionospheric refraction seriously limits the operational use of the satellite navigation signal, in this article, the authors attempted to quantify the effect of solar activity (expressed by sunspots) on the signal integrity using fuzzy logic. Fuzzy reasoning is used when information is inaccurate or incomplete and necessitates making decisions under conditions of uncertainty. Thanks to fuzzy sets, there are no obstacles to characterize the degree of intensity of a given phenomenon. In order to look at the problem more broadly, attention was also paid to the tropospheric conditions, and it was verified whether, against the background of cloudiness, precipitation, humidity, pressure and temperature, solar activity affects the integrity to the greatest extent. The integrity measurements from the EGNOS system (PRN120 and PRN126) collected at the monitoring station in Warsaw, Poland in 2014 were used.

The issue addressed in this publication concerns new Air Traffic Management (ATM) functionality, identified in the Commission Implementing Regulation (EU) No 716/2014, known as Flexible Airspace Management and Free Route (FRA). The authors pose a question—does free route implementation influence air transport safety? What can be done to maintain the current level of safety and still implement modern solutions? To achieve the aim of this paper a developed concept of Risk Priority Number (RPN) calculation, with determination of main RPN components rating scales, in order to carry out the FMEA (Failure Mode and Effects Analysis) risk analysis of FRA implementation was done. The results allow lining up of the identified potential incompatibilities according to their criticality to the system. In effect it can be said that each modification in a management system, related to safety, influence the safety itself. Nevertheless, this influence does not always lead to negative impact.

This study describes a rare case of a giant phyllodes tumor in a 13-year-old girl. The authors have conducted an analysis of the diagnostic process and have shown the results of operative treatment of the tumor. Moreover, organisational aspects of the diagnostics concerning breast diseases in patients from smaller towns in Poland have been discussed. It has been indicated that the availability of suitable diagnostics and treatment of breast diseases in children and teenagers from rural areas and smaller towns is limited.