Broken Theory is a jettisoned collection of fragmentary writing, collected and collaged by new media artist, writer, musician, and theorist Alan Sondheim. Folding theoretical musings, text ...experiments, and personal confessions into a single textual flow, it examines the somatic foundations of philosophical theory and theorizing, discussing their relationships to the writer and body, and to the phenomenology of failure and fragility of philosophy’s production. Writing remains writing, undercuts and corrects itself, is always superseded, always produced within an untoward and bespoke silo – not as an inconceivable last word, but instead a broken contribution to philosophical thinking. The book is based on fragmentation and collapse, displacing annihilation and wandering towards a form of “roiling” within which the text teeters on the verge of disintegration. In other words, the writing develops momentary scaffoldings – writing shored up by the very mechanisms that threaten its disappearance. Broken Theory is prefaced by a text from Maria Damon and followed by an extensive interview with art historian Ryan Whyte.
This paper addresses the issue of monitoring and tracking people and vehicles within smart cities. The actors in this work jointly cooperate in sensing, sensible data processing, anonymized data ...delivery, and data processing, with the final goal of providing real-time mapping of vehicular and pedestrian concentration conditions. The classification of conditions can bring out critical situations that can be communicated in real-time to citizens. Tests were conducted in the city of Cagliari, Italy.
Screens are ubiquitous today. Yet contemporary screen media eliminate the presence of the screen and diminish the visibility of its boundaries. As the image becomes indistinguishable from the ...viewer’s surroundings, this unsettling prompts re.examination of how screen boundaries demarcate. Through readings of three media forms – Virtual Reality; holograms; and light projections – this book develops new theories of the surfaces on and spaces in which images are displayed. Interrogating contemporary contestations of reality against illusion, it argues that the disappearance of difference reflects shifted conditions of actuality and virtuality in understanding the human condition. These shifts further connect to the current state of politics by way of their distorted truth values, corrupted terms of information, and internalizations of difference. The Post.Screen Through Virtual Reality, Holograms and Light Projections thus thinks anew the image’s borders and delineations, evoking the screen boundary as an instrumentation of today’s intense virtualizations which do not tell the truth. In the process, a new imagination for images emerges for a gluttony of the virtual; for new conceptualizations of object and representation, materiality and energies, media and histories, real and unreal; for new understandings of appearances, dis-appearances, replacement and re.placement – the post-screen.
Multimedia pedagogical agents are on-screen characters that allow users to navigate or learn in multimedia environments. Several agents’ characteristics may moderate their instructional ...effectiveness, including appearance, gender, nonverbal communication, motion, and voice. Here, we conducted a meta-analysis to test hypotheses from diverse theories predicting the effects of these agents’ characteristics. We tested predictions of cognitive load theory, cognitive theory of multimedia learning, computers are social actors, social agency theory, uncanny valley, and the action observation network. Our meta-analysis of 32 effect sizes (
N
= 2104) revealed a small overall effect (
g
+ = 0.20), showing that learning with multimedia pedagogical agents was more effective than learning without these agents. As predicted by the redundancy effect of cognitive load theory and the coherence principle of cognitive theory of multimedia learning, 2D agents (
g
+ = 0.38) tended to be more effective than 3D agents (
g
+ = 0.11). As predicted by the computers are social actors hypothesis, most of the agents’ characteristics, including nonverbal communication, motion, and voice, appeared not to moderate their effectiveness. We conclude that multimedia pedagogical agents help learning through multimedia, and that students may be able to learn similarly from different types of agents.
The focus of High Performance Multimedia is on the ever expanding European e-content industry. Production, aggregation and distribution of that content are the starting points to any future ...development towards a flourishing industry sector of the third millennium. Nevertheless, in addition to the diffusion of knowledge throughout the industry, digitalisation has completely changed the structure of the content business through the dissociation of content and media channel. This movement creates problems in the process of the business. Highest technological demands in time and money are limiting the size of e-content enterprises today. In contrast, its distribution is still being dominated by broadcasters and telecom providers that skim the biggest part of the profits. However, possibilities do arise when analyzing the industry of e-content. The European e-content market will be able to play a major role in the future by including all relevant players and their abilities. The challenge during the next years will be to stop the concentration on high-end technology and to create new adequate e-content services providing added value to everyone in Europe.
A review on extreme learning machine Wang, Jian; Lu, Siyuan; Wang, Shui-Hua ...
Multimedia tools and applications,
12/2022, Letnik:
81, Številka:
29
Journal Article
Recenzirano
Odprti dostop
Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward neural network (SLFN), which converges much faster than traditional methods and yields promising ...performance. In this paper, we hope to present a comprehensive review on ELM. Firstly, we will focus on the theoretical analysis including universal approximation theory and generalization. Then, the various improvements are listed, which help ELM works better in terms of stability, efficiency, and accuracy. Because of its outstanding performance, ELM has been successfully applied in many real-time learning tasks for classification, clustering, and regression. Besides, we report the applications of ELM in medical imaging: MRI, CT, and mammogram. The controversies of ELM were also discussed in this paper. We aim to report these advances and find some future perspectives.
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