Causal Mechanisms as Temporal Bridges in a Connectionist Model of Causal Attribuion

We use a connectionist model which relies on the encoding of lempnjral relationships a m o n g events to investigate the role of causal mechanisms in causal attribution. Mechanisms are encoded as intervening events with temporal extent that occur between the offset of a causal event and the onset of an effect. In one set of simulations, the presence of intervening events facilitated acquisition of a relationship between cause and effect via the mechanism. In a second set of simulations, prior experience with mechanisms enhanced development of a cause-effect relationship during later training absent the mechanism. The results provide evidence that causal mechanisms can facilitate causal attribution via H u m e a n cues-to-causality

Lucy Duff-Gordon

Lucy, Lady Duff-Gordon, professionally known as “Lucile,” was a couturière to wealthy European and American women as well as actresses in London, Paris, and New York when she began to design costumes for film stars. As early as 1913, she dressed Alice Joyce in Kalem’s The American Princess (1913). In addition, Lucile’s New York and London salons provided the setting for several motion pictures in which fashion show scenes were filmed. These included: The American Princess (Kalem, 1913), The Whirl of Life (Cort Film, 1915), The Spendthrift (George Kleine, 1915), The Amateur Wife (Famous Players-Lasky, 1920), and Walls of Prejudice (Gaumont, 1920)

LE PIVOT INTELLIGENT SURVEILLE ET OPTIMISE LES BESOINS DES CULTURES

Les réseaux de capteurs sans fil, l'Internet des objets et l'intelligence artificielle apportent conjointement un appui non négligeable dans la gestion quotidienne des infrastructures agricoles et contribuent à relever les défis de demain liés à la raréfaction des ressources, l'augmentation de la population ainsi que les changements climatiques

A New Edge Computing Architecture for IoT and Multimedia Data Management

The Internet of Things and multimedia devices generate a tremendous amount of data. The transfer of this data to the cloud is a challenging problem because of the congestion at the network level, and therefore processing time could be too long when we use a pure cloud computing strategy. On the other hand, new applications requiring the processing of large amounts of data in real time have gradually emerged, such as virtual reality and augmented reality. These new applications have gradually won over users and developed a demand for near real-time interaction of their applications, which has completely called into question the way we process and store data. To address these two problems of congestion and computing time, edge architecture has emerged with the goal of processing data as close as possible to users, and to ensure privacy protection and responsiveness in real-time. With the continuous increase in computing power, amounts of memory and data storage at the level of smartphone and connected objects, it is now possible to process data as close as possible to sensors or directly on users devices. The coupling of these two types of processing as close as possible to the data and to the user opens up new perspectives in terms of services. In this paper, we present a new distributed edge architecture aiming to process and store Internet of Things and multimedia data close to the data producer, offering fast response time (closer to real time) in order to meet the demands of modern applications. To do this, the processing at the level of the producers of data collaborate with the processing ready for the users, establishing a new paradigm of short supply circuit for data transmission inspired of short supply chains in agriculture. The removing of unnecessary intermediaries between the producer and the consumer of the data improves efficiency. We named this new paradigm the Short Supply Circuit Internet of Things (SSCIoT)