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Sociopaths as Antiheroes of Streaming Media

100%

Zdunkiewicz L.

2019

nr 57

89-101

Unlike their traditional counterparts, contemporary TV antiheroes are becoming increasingly non-empathetic. Despite their dislikable qualities, they succeed in attracting audiences. I consider two factors that may be influencing their popularity. The first involves viewers’ increasing familiarity with storytelling techniques and their resulting gravitation towards narratives capable of challenging their story schemas. The second aspect concerns the entertainment industry’s transformations. Aware of their well-watched audiences’ expectations, studios are turning to novelists to pursue more defamiliarizing forms. I discuss The Assassination of Gianni Versace (2018) as an example of a series that experiments with viewers’ affective responses towards its sociopathic protagonist. I argue that the writer’s choices extricate Versace from the formulaic justice-is-served narrative, thus appealing to those consumers additionally motivated by, what researchers call, eudaemonic concerns.

Efektywność mediów strumieniowych

84%

Sulej W. , Ziółkowska M.

tom R. 17, nr 30

89-109

W artykule przedstawiono problem efektywności mediów strumieniowych. Przede wszystkim problem ten został określony i zdefiniowany. Ponadto w artykule przedstawiono co może wpływać i w jaki sposób na efektywność mediów strumieniowych. Na podstawie zebranych danych będzie można opracować skuteczne metody pomiaru efektywności mediów strumieniowych.

The paper presents the problem of the efficiency of streaming media. First of all, this concept has been identified and defined. Moreover, the paper presents what may influence and how on the efficiency of streaming media. On the basis of the collected data effective methods of measuring the efficiency of streaming media can be developed.

Dual-Path Image Reconstruction: Bridging Vision Transformer and Perceptual Compressive Sensing Networks

67%

Bairi Z. , Bey K. B. , Ben-Ahmed O. , Amamra A. , Bradai A.

Annals of Computer Science and Information Systems

2023

tom Vol. 35

347--354

Over the past few years, notable advancements have been made through the adoption of self-attention mechanisms and perceptual optimization, which have proven to be successful techniques in enhancing the overall quality of image reconstruction. Self-attention mechanisms in Vision Transformers have been widely used in neural networks to capture long-range dependencies in image data, while perceptual optimization has been shown to enhance the perceptual quality of reconstructed images. In this paper, we present a novel approach to image reconstruction by bridging the capabilities of Vision Transformer and Perceptual Compressive Sensing Networks. Specifically, we use a self-attention mechanism to capture the global context of the image and guide the sampling process, while optimizing the perceptual quality of the sampled image using a pre-trained perceptual loss function. Our experiments demonstrate that our proposed approach outperforms existing state-of-the-art methods in terms of reconstruction quality and achieves visually pleasing results. Overall, our work contributes to the development of efficient and effective techniques for image sampling and reconstruction, which have potential applications in a wide range of domains, including medical imaging and video processing.