## 2 State of the Art  
The world literature [3] indicates that the activities carried out by security control operators are priority activities to meet civil aviation security standards. However, the articles that deal with the security control process at airports mainly deal with the problems related to the efficiency of this process rather than its effectiveness. A comprehensive review of the literature on the management of the performance of passenger service processes at the airport terminal is presented in ref. [4]. It also includes all the work that deals with the problems of the efficiency of the security control process at airports. Scientific works aimed at ensuring an adequate level of security are a significant minority. In their case, two different areas of application can be distinguished. The first area relates to research that seeks automated support for detecting prohibited items. The deep convolutional neural network YOLO (You Only Look Once) was instantiated by [PERSON] et al. [5] to classify X-ray baggage images and identify hazardous materials. Convolutional neural networks have been used to detect specific dangerous objects such as knives [6], sharp objects [6; 7], and weapons hidden in luggage [8; 9]. An analogous method was also used in [5; 10; 11; 12; 13]. The general conclusion of such work, however, is that the current development in this area does not provide a basis for abandoning the human element in the security control process. [PERSON] et al. [14], in a study on the automation of explosive detection systems for cabin baggage screening (EDSCB), verified that a human-machine system with automatic decision-making showed better performance than automation as a diagnostic aid. The proposed systems have also a computational performance problem, making them unsuitable for real-world deployment [15]. The second area of work is directly focused on the human factor. Few scientific works have addressed aspects related to ensuring an appropriate level of security. These works confirm that the human factor is the most important and directly affects the reliability of the detection of prohibited items in security control at airports [2]. Based on experimental data from a real system, various factors influencing the level of safety were evaluated. In the work [16], it was proven that the level of training of security control operators needs to be improved. Operators do not meet the required indicators on the real system after training that is not conducted on a replica of the workstation. Security control operators gain experience only after more than half a year of work experience. Analogous conclusions were drawn in ref. [17]. An essential factor in correctly assessing the image is the time it takes for the security control operator to decide on the contents of the baggage [18]. The correct detection of prohibited articles depends on how the prohibited article is placed in the baggage, the degree to which the baggage is full, and the extent to which other items in the baggage cover the prohibited article [19]. Work aimed at increasing the level of safety has yet to be dedicated to trying to directly influence the human factor by directly eliminating the causes of misjudgment. Systemic attempts have been made by increasing the number of barriers (e.g., two-stage screening) [9]. However, such solutions are not used in practice due to the throughput limitation of such a system. Studies have also been conducted using different detection methods [20]. However, the reconfiguration of the systems is associated with high costs without eliminating the human factor [21,22]. The work to date has focused on an attempt to assess the current state and increase the security and efficiency of the process. All the work mentioned above has yet to be dedicated to increasing the precision of assessing security control operators. However, this factor is crucial to know the operators' weaknesses and train them better.