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The most common cause of incidents and accidents in aviation is linked to the category “Loss of Control Inflight” [1]. Remarkably in consequence this means that aircraft without any technical defect or such with manageable defects according to certification requirements are involved. The research project “Virtual Instructor for General Aviation” (VIGA) was aimed to validate an idea that addresses this problem by an entirely different approach. The idea can be best described by looking at the way a flight instructor takes decisions to intervene. A human pilot has an expectation of the maneuvers and the corresponding trajectories that can be flown in the future based on the present flight conditions. Decision making is based on the analysis of the consequences of the expectations. This approach is one of the key principles of the project, and is completely different to any known AFCS system.
Yet technical implementation requires considerable effort. Essentially it comprises a faster than real time simulation with an adequately accurate aerodynamic model of the particular aircraft in combination with a module to evaluate the results of the simulated exit trajectories. In consequence this idea requires an autopilot module capable of tracking the calculated three-dimensional trajectories which then resulted in the need to design and develop a completely new type of autopilot algorithm.
The objective of this project was to test and demonstrate principle functionality thereby also finding pathways determining future developments as well as to analyze system behavior. Therefore, the project was deliberately designed to help the pilot by depicting the solutions on the PFD. Direct intervention of the system with aircraft flight controls did not take place. This also raised the question of how to design an effective visual human interface.
Fortunately, all results proved to be very satisfying. The underlying idea could be validated and was demonstrated both in a simulation environment and in flight test. The path tracking algorithm was developed in a parallel project and also showed very satisfactory results, meeting all requirements.
The research on the new generation mobile networks is currently in the phase of defining the key technologies to make 6G successful. Hereby, the research project 6G NeXt is aiming to provide a tight integration between the communication network, consisting of the radio access as well as backbone network, and processing facilities. By the concept of split computing, the processing facilities are distributed over the entire backbone network, from centralised cloud to the edge cloud at a base station. Based on two demanding use cases, Smart Drones and Hologradic Communication, we investigate a joint communication and compute architecture that will make the application of tomorrow become reality.
The aim was to implement uncertainty calculation for detecting the negative effects of smoking on the bone density of the paranasal sinus. Materials and Methods: A total of 100 male participants aged 20 to 44 were included in the study and divided into two groups. The first group comprised individuals with minimal harmful habits, while the second group consisted of individuals who had been smoking for at least 10 years, consuming 1 to 2 packs of cigarettes per day. Results Bone density has a negative impact on the bone tissue of the upper wall of the maxillary sinus. The findings suggest that individuals with a pronounced decrease in minimum density, as well as those with a marked difference between minimum and maximum density values, may require heightened medical attention due to potential associations with undiagnosed diseases or specific structural characteristics in the skull. Conclusions. The uncertainty calculation was implemented for the detection of negative effect of smoking on the bone density of paranasal sinuses. The calculated difference between maximum and minimum density during the research suggests significant medical implications, especially considering the heterogeneity of the trabecular bone structure in the skull. Individuals with a marked difference may require heightened medical attention, potentially associated with undiagnosed diseases or specific structural characteristics in the skull.
The Peculiarities of Measuring Bone Density in Males and Females Using Uncertainty Calculation
(2023)
The article discusses the approach to solving the problem of reducing time spent on the preparation of medical images for teaching neural networks, by reducing the time of creating masks for images. The task is considered on the example of processing images of the mucous membrane of the paranasal sinus. The specifics of the task did not allow effectively using existing software solutions. During the study, a software solution was proposed, which made it possible to radically reduce the time of creating masks for images. The article also analyzes the shortcomings of the automated creation of masks, as well as the directions of their solution. The loss of time due to the adjustment of the color palette can be reduced even more to 1-2 minutes, the average deviation is 7.61%.
The article discusses the approach to solving the problem of reducing time spent on the preparation of medical images for teaching neural networks, by reducing the time of creating masks for images. The task is considered on the example of processing images of the mucous membrane of the paranasal sinus. The specifics of the task did not allow effectively using existing software solutions. During the study, a software solution was proposed, which made it possible to radically reduce the time of creating masks for images. The article also analyzes the shortcomings of the automated creation of masks, as well as the directions of their solution. The loss of time due to the adjustment of the color palette can be reduced even more to 1-2 minutes, the average deviation is 7.61%.
Evaluation of medical images is of key importance in the work of medical staff today. Especially this problem pays important role in otolaryngology.
The aim of our work was to develop an automatic complex method for assessing the state of the human paranasal sinuses.
Our research included 10 people of different sex and age, who were divided into groups, taking into account the recommendations of the WHO for 2019-2021. The structure of the mucous membrane of the maxillary sinus were calculated and compared.
In the course of our research, an algorithm was developed for the automatic assessment of the state of the mucous membrane of the maxillary sinus and its bone walls according to the data of the spiral computed tomography. The difference between obtained data in the manual and automatic mode is minimal.
Solutions to the 3D Model Problem of Pressure Measurement in the Area of Maxillary Sinus Anastomosis
(2020)
The ostiomeatal complex (OMC) is a key area that determines the occurrence of inflammatory processes in the paranasal sinuses (PNSs). The aim of our work was to develop a procedure for studying the OMC components in the preoperative period that allows for identification the impact of anatomical peculiarities on change of physiological pressure in the maxillary sinus. Materials and methods: The study was carried out on the basis of the otorhinolaryngological department of Kharkiv Regional Clinical Hospital in 2019-2020. It involved 100 patients of both sexes aged 20-59 years with chronic non-polyposis maxillary sinusitis. Results: The sizes of the uncinate process, the middle turbinate and the natural anastomosis were determined using the calculation of uncertainty. Basing on the data obtained, all the patients were divided into three groups. Conclusions: Changes in the size of the natural anastomosis (both an increase and its narrowing) lead to changes in pressure in the area of the anastomosis, and a decrease in ventilation in the paranasal sinuses. SCT study with subsequent 3D modeling is an informative, accurate and effective method for assessment of OMC and PNSs condition. It allows surgeons to presume the method and volume of surgery as early as at the preoperative stage, without resorting to invasive research methods.
The new coronavirus COVID-19 has been spreading worldwide for almost three years. The global community has developed effective measures to contain and control the pandemic. However, new factors are emerging that are driving the dynamics of COVID-19. One of these factors was the escalation of Russia's war in Ukraine. This study aims to test the hypothesis of the influence of migration flows caused by the Russian war in Ukraine on the dynamics of the epidemic process in Germany. For this, a model of the COVID-19 epidemic process was built based on the polynomial regression method. The model's adequacy was tested 30 days before the start of the escalation of the Russian war in Ukraine. To assess the impact of the war on the dynamics of COVID-19, the model was used to calculate the forecast of cumulative new and fatal cases of COVID-19 in Germany in the first 30 days after the start of the escalation of the Russian war in Ukraine. Modeling showed that migration flows from Ukraine are not a critical factor in the growth of the dynamics of the incidence of COVID-19 in Germany, but they influenced the number of cases. The next stage of the study is the development of more complex models for a detailed analysis of population dynamics, identifying factors influencing the epidemic process in the context of the Russian war in Ukraine, and assessing their information content.
Model based Configuration of Platforms for Managing Cross- Organizational (Business) Processes
(2022)
In this contribution interoperability is considered from the perspective of platforms, which have to manage cross-organisational business processes. A model-based approach for configuring a cloud platform for managing complex processes and their dependencies across different organisations is provided. The approach is applied on using FIWARE, which provides a framework of open source software platform components. The core concept is to extend the open source core data model of FIWARE by using the artefacts of an Enterprise model, describing the dependencies of processes, roles, object data and application interfaces. Based on a given use case the principal configuration was applied and validated.
The aim of our study was to investigate the impact of insulin resistance on the bone density of the upper wall of the maxillary sinus. Materials and Methods: The study included 100 female participants aged 18 to 44 years, divided into two groups. The first group consisted of individuals with insulin resistance, while the control group comprised individuals without signs of insulin resistance. In each group, we conducted an investigation of the radiological density of the upper wall of the maxillary sinus using uncertainty calculations. Results of the study suggest a potential influence of insulin resistance on the density of bone tissue around the nasal sinuses, specifically the upper wall of the maxillary sinus in our case. This parameter was found to be minimal in the group of individuals with insulin resistance. It is particularly noteworthy that both minimum and maximum bone density decreased in this group. Conclusions. The research focused on how insulin resistance affects the density of the upper wall of the maxillary sinus. By employing uncertainty calculations, the study revealed that insulin resistance is associated with a decrease in the minimum density of the upper wall of the maxillary sinus. This tendency may act as a catalyst for the emergence of significant inflammatory alterations in the nasal sinuses, serving as a foundation for the initiation of complications.