An increasing number of services and facilities that are of interest to users is based on video streaming. Technical characteristics of video have a strong impact on the quality of a video streaming service and its perception by users. The most important measure of quality, which focuses on the user, is the Quality of Experience (QoE). Given that video advertising is a typical video streaming application, it is necessary to analyze the effect of the change of video characteristics on the QoE. This paper examines the impact of resolution and frame rate change on the QoE level by using objective and subjective QoE metrics. It also looks at the possibility of mapping the objective QoE metrics into subjective ones, if the QoE in Internet video advertising is analyzed. It was demonstrated that the values obtained by the objective assessment of quality can be mapped to the results obtained by subjective assessment of quality when the quality of experience of linear in- stream video ads is analyzed. The results indicate that temporal aspects of video quality assessment, e.g. influence of resolution and frame rate change to the level of the QoE, can be achieved by implementation of objective methods. Therefore, quality of experience can be improved by the proper selection of video characteristics values.
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.
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.
