The prediction of landslides and other events associated with slope movement is a very serious issue in many national parks around the world. This article deals with the territory of the Malá Studená Dolina (Little Cold Valley, High Tatras National Park-Slovakia), where there are extensive talus cones, through which seasonally heavy hiking trails lead. In the last few years particularly, there have been frequent falls and landslides in the mountainous environment, which also caused several fatal injuries in 2018. For the above reasons, efforts are being made to develop a methodology for monitoring the changes of the talus cones in this specific alpine area, to determine the size, speed, and character of the morphological changes of the soil. Non-contact methods of mass data collection (laser scanning with Leica P40 and aerial photogrammetry with unmanned aerial system (UAS) DJI Phantom 4 Pro) have been used. The results of these measurements were compared and the overall suitability of both methods for measurement in such terrain evaluated. The standard deviation of the difference of surface determination (represented by the point cloud) is about 0.03 m. As such accuracy is sufficient for the purpose of monitoring talus cones and the use of UAS is easier and associated with lower risk of damage of expensive equipment, we conclude that this method is more suitable for mapping and for repeated monitoring of such terrain. The properties of the outputs of the individual measurement methods, the degree of measurement difficulty and specific measurement conditions in the mountainous terrain, as well as the economy of the individual methods, are discussed in detail.
Environmental risks, in particular climate change and environmental pollution, are among the key challenges faced by modern governments nowadays. Environmental risks are associated with specific costs and expenditures necessary to mitigate their negative effects. In this context, the financial system plays a significant role, particularly the public financial system, which allocates and redistributes public resources and has an impact on market participants by imposing environmental taxes. This study assessed the interdependence between environmental degradation and public expenditure, financial sector development, environmental taxes, and related socioeconomic policies. The aim was to diagnose and define the relationship between environmental degradation and sustainable fiscal instruments used in the financial system. The original research approach adopted in the study is the inclusion of variables representing a sustainable approach to assessment of the financial system. Two groups of European Union countries were analyzed for the period 2008–2017, namely, converging economies from Central and Eastern Europe and the largest developed economies of Western Europe. The authors found a strong relationship between greenhouse gas emissions and fiscal instruments, especially expenditure on research and development, and the development of the financial sector. In the case of environmental taxes, their impact differed depending on the country, being predominantly beneficial in countries with higher greenhouse gas emissions but unfavorable in countries with lower emissions levels.
The purpose of this paper is to develop a fuzzy model of the risk assessment for environmental start-up projects in the air transport sector at the stage of business expansion. The model developed for the following software will be a useful tool for the risk decision support system of investment funds in financing environmental start-up projects at the stage of market conquest. Developing a quantitative risk assessment for environmental start-up projects for the air transport sector will increase the resilience of making risk decisions about their financing by the investors. In this paper, a set of 21 criteria for assessing the risk of launching environmental start-up projects in the air transport sector were formulated for the first time by presenting inputs in the form of a linguistic risk assessment and the number of credible expert considerations. The fuzzy risk assessment model, based on expert knowledge, uses linguistic variables, reveals the uncertainty of the input data, and displays a risk assessment with linguistic interpretation. The result of the paper is a fuzzy model that is embedded in a generalized algorithm and tested in an example risk assessment of environmental start-up projects in the air transport sector.
The purpose of this paper is to develop an applied fuzzy model of information technology to obtain quantitative estimates of environmental start-up projects in air transport. The developed model will become a useful tool for venture funds, business angels, or crowdfunding platforms for the development of innovative air transport businesses. Obtaining a quantitative estimate of the environmental start-up projects will increase the sustainability of the decision making on the security of financing of such projects by investors. This article develops a fuzzy evaluation model of project start-ups in air transport as an application of our neuro-fuzzy model in a specific air transport environment. The applied model provides output ranking of start-up project teams in air transport based on a four-layer neuro-fuzzy network. The presented model declares the possibilities of the application to solve these economic problems and offers the space for subsequent research focused on its usability in several areas of start-up development, in sectors and processes differentiated. The benefits are also visible for several types of policies, with an emphasis on decision-making processes in regulatory mechanisms to support the state funding in Slovakia, the EU etc.
The information technology models improving security functioning of crowdfunding platforms and advice on a new type of business were developed. The article solves the problem of safety of crowdfunding platform functioning based on developed models: rating assignment system of unified assessment crowdfunding platforms; startup projects assessment; startup projects risk assessment concerning their financing safety level and criminal law protection of investors against the financial fraud. The models are based on the correct usage of fuzzy logic and fuzzy set device to reveal the uncertainty of experts’ consideration that insures authenticity of scientific results.
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