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Using Multivariate Statistics

The measurement of meaning

A wide variety of media can be used in learning, including distance learning, such as print, lectures, conference sections, tutors, pictures, video, sound, and computers. Any one instance of distance learning will make choices among these media, perhaps using several.

Multimedia in Learning

An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

With digital equipment becoming increasingly networked, either on wired or wireless networks, for personal and professional use alike, distributed software systems have become a crucial element in information and communications technologies. The study of these systems forms the core of the ARLES' work, which is specifically concerned with defining new system software architectures, based on the use of emerging networking technologies. In this context, we concentrate on the study of distributed systems which bring to life the vision of ubiquitous computing systems, also known as ambient intelligence.

반도체 공정 overview

Most research on Quality of Experience treats QoE as a static event. As a result, QoE is measured for stimuli of delimited length, and the QoE which is associated with the stimulus is considered to be stable along its duration. However, this rarely happens in reality where usage episodes extend over several seconds and minutes (e.g. a phone call), hours (e.g. a video film), or regularly over periods of weeks or months (when considering QoE of a subscribed service). In this chapter, we will discuss the cognitive processes involved when QoE is integrated over usage episodes, and describe corresponding assessment methods. We will also review models for estimating episodic and multi-episodic QoE from momentary QoE judgments or their predictions.

Temporal Development of Quality of Experience

The gaming industry is one of the largest digital markets for decades and is steady developing as evident by new emerging gaming services such as gaming video streaming, online gaming, and cloud gaming. While the market is rapidly growing, the quality of these services depends strongly on network characteristics as well as resource management. With the advancement of encoding technologies such as hardware accelerated engines, fast encoding is possible for delay sensitive applications such as cloud gaming. Therefore, already existing video quality models do not offer a good performance for cloud gaming applications. Thus, in this paper, we provide a gaming video quality dataset that considers hardware accelerated engines for video compression using the H.264 standard. In addition, we investigate the performance of signal-based and parametric video quality models on the new gaming video dataset. Finally, we build two novel parametric-based models, a planning and a monitoring model, for gaming quality estimation. Both models are based on perceptual video quality dimensions and can be used to optimize the resource allocation of gaming video streaming services.

Quality estimation models for gaming video streaming services using perceptual video quality dimensions

Telephone speech quality prediction: towards network planning and monitoring models for modern network scenarios

The subjective evaluation of video quality mostly relies on opinion tests in which test participants judge perceived quality on rating scales. However, these methods provide limited insight how the quality judgments are being formed in the brain. In past studies we showed the general feasibility to complement opinion tests with physiological measures, as the electroencephalography (EEG), for pure video and audio experiments. To establish EEG as a reliable complement measurement method in standard quality rating tests, the next step is to validate the method in the audiovisual domain. For this purpose we conducted an experiment using audiovisual stimuli and degraded these in both modalities. We show that the more degraded a video is the earlier and higher the P300 amplitude is rising. In addition, the peak amplitudes are highly correlated with the audiovisual Mean Opinion Score (MOS).

Perception of low-quality videos analyzed by means of electroencephalography

As multimedia services become more widespread, there is a need for standardized methods for assessment of the quality perceived by the end user. ITU-T SG12 has been at the forefront in defining and validating subjective and objective quality assessment methods for many years and has issued many recommendations in this area. Subjective assessment remains the definitive methodology but objective methods are now becoming mature enough to provide very accurate results, especially for voice, and much more convenient to implement. However, currently available objective quality estimation methods can require a lot of computational resources, which makes them difficult, or even impossible, to be deployed operationally in a large network. Attention in SG12 is now heavily focused on lightweight models based on parametric or bit stream input, which enable large-scale real-time QoE assessment in a network. These models have a potential to simultaneously monitor many, or even all, of the audiovisual sessions in a network.

Sebastian Möller

Papers

Temporal Development of Quality of Experience

Quality estimation models for gaming video streaming services using perceptual video quality dimensions

Telephone speech quality prediction: towards network planning and monitoring models for modern network scenarios

Perception of low-quality videos analyzed by means of electroencephalography

Multimedia Quality Assessment Standards in ITU-T SG12