NoSQL database for air quality prediction

    Industry 4.0, Vol. 7 (2022), Issue 5, pg(s) 191-194

    The increasing application of NoSQL database technology and the neural networks raises the question of how compatible and applicable are the NoSQL databases to the neural network prediction models. This paper examines the applicability of a traditional relational database for storing air quality data and compares it to a NoSQL database performing the same functions. The possibility of the NoSQL database to feed a neural network model for predicting the atmospheric air quality is evaluated. The tendencies in the data are studied, and some solutions for improving the air quality are proposed. An analysis and a comparison of the performance of both relational SQL and NoSQL database systems by using real-world data for the Air Quality Index in the city of London is assessed and their performance is compared. Bivariate analysis on the data in order to assess the quality of the neural network forecast is performed.


    Application of artificial neural networks for prediction of business indicators

    Mathematical Modeling, Vol. 5 (2021), Issue 4, pg(s) 141-144

    This paper examines the applicability of the neural networks in developing predictive models. A predictive model based on artificial neural networks has been proposed and training has been simulated by applying the Long Short-Term Memory Neural Network module and the time series method. Python programming language to simulate the neural network was used. The model uses the stochastic gradient descent and optimizes the mean square error. Business indicators for forecasting the results of the activity and the risk of bankruptcy of a company are forecasted and a comparison of the obtained forecast values with the actual ones is performed in order to assess the accuracy of the forecast of the developed model. As a result, it can be noted that business indicators can be successfully predicted through the Long Short-Term Memory Neural Network and the forecasted values are close to the actual ones.


    Web application with Python and security of the information system

    Security & Future, Vol. 4 (2020), Issue 3, pg(s) 103-106

    The aim of the research is to develop a database management system for collecting, processing, storing and using information for the teaching of PhD students at a university using the high-level Python language.
    Studied and researched in the process of development are the main characteristics of the most widely used database management systems. The practical aspects of the design, creation and use of databases were analysed. Has been formulated the requirements to the functional capabilities of the developed database. For the development of the web-application was used Python programming language. The database model, the user interface and a set of reports were developed. A physical data model, oriented towards the design and the development of a database management system using the Python programming language was proposed. The main risks and threats to the security of information in the web-application are characterized. Guidelines for infrastructure protection are proposed.



    Security & Future, Vol. 3 (2019), Issue 4, pg(s) 163-166

    This report focuses on vulnerabilities on web-applications and web-sites from Cross-Site Scripting attacks (XSS). The different types of XSS attacks are examined: DOM-based, active and passive attacks. The spread of XSS attacks across platforms – government and financial institutions, transportation companies, hospitality and entertainment has been analyzed. Research and analysis of the security of corporate websites and their resistance to XSS attacks have been carried out. The basic guidelines for preventing valuable data theft and unauthorized access to websites and applications from XSS attacks are reviewed and systematized.