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Vol. 3 No. 1 (2013): JITA - APEIRON

Luisa Sturiale, Alessandro Scuderi

The innovation ICT strategy in agri-food sector

Original scientific paper

DOI: https://doi.org/10.7251/JIT1301043S

Abstract

The achievement of Information Communication Technology (ICT) as a new ground for economic competition is deeply affecting the trade organization in many merchant sectors. For Italian agri-food products it is of absolute importance for Internet marketing to be undertaken and to foresee the consequent scenarios. The aim of this research is to exactly assess the opportunities and problems of the distribution circuit based on the virtual scenario, with a methodological and empirical approach, working on the analysis of experiences already begun by agri-food companies established in Italy and engaged in “business to consumer” and “business to business”. The ICT is configured as a phenomenon in a continuous and rapid evolution, which makes it necessary for companies to continually adapt to it and to the habits of web-consumers. This means that it is necessary to effectively enter the network of agri-food firms, and to strategically revise marketing methods focusing on the market place.

Keywords: web marketing, e-business, agri-food , web site.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.