2,958 research outputs found
La messa di San Michele ovvero la corona e l'aureola
No full textÉcole thématiqueAnalisi iconografica di un affresco del XIV secolo già sulle pareti della chiesa di San Michele a Monza ed ora al Museo del Duomo. Il nucleo centrale del dipinto riguarda la santità auspicata di Teodolinda, la regina monzese che si fece docile strumento nelle mani di papa Gregorio Magno nell'opera di conversione al Cristianesimo del popolo Longobardo; santità promossa dal clero locale a capo del quale era, al tempo dell'affresco, Lombardo della Torre
La messa di San Michele ovvero la corona e l'aureola
No full textÉcole thématiqueAnalisi iconografica di un affresco del XIV secolo già sulle pareti della chiesa di San Michele a Monza ed ora al Museo del Duomo. Il nucleo centrale del dipinto riguarda la santità auspicata di Teodolinda, la regina monzese che si fece docile strumento nelle mani di papa Gregorio Magno nell'opera di conversione al Cristianesimo del popolo Longobardo; santità promossa dal clero locale a capo del quale era, al tempo dell'affresco, Lombardo della Torre
The Use of Visual Imagery in Asperger Syndrome
No full textAbstract
Date Presented 3/30/2017
This poster presents a pilot study that showed that visual imagery increased activity of daily living skills in participants with Asperger syndrome. To date, there has been no such documented research. Limitations will be outlined with a quantitative study in mind.
Primary Author and Speaker: Pat Precin
Contributing Authors: Michele Floria, Simi Thomas, January Magno, Diana Chang, Charles Jean-Paul</jats:p
An ultra low power high sensitivity wake-up radio receiver with addressing capability
No full textIn power-limited wireless devices such as wireless sensor networks, wearable components, and Internet of Things devices energy efficiency is a critical concern. These devices are usually battery operated and have a radio transceiver that is typically their most power-hungry block. Wake-up radio schemes can be used to achieve a reasonable balance among energy consumption, range, data receiving capabilities and response time. In this paper, a high-sensitivity low power wake-up radio receiver (WUR) for wireless sensor networks is presented. The wake-up radio is comprised of a fully passive differential RF-to-DC converter that rectifies the incident RF signal, a low-power comparator and an ultra low power microcontroller to detects the envelope of the on-off keying (OOK) wake-up data used as address. We designed and implemented a novel low power tunable wake up radio with addressing capability, a minimal power consumption of only 196nW and a maximum sensitivity of -55dBm and minimal wake up time of 130μs without addressing and around 1,6ms with 2byte addressing at 10Kbit/s data rate. The flexibility of the solution makes the wake up radio suitable for both power constrained low range application (such as Body Area Network) or applications with long range needs. The wake up radio can work also at different frequencies and the addressing capability directly on board helps reduce false positives. Experimental on field results demonstrate the low power of the solution, the high sensitivity and the functionality
Energy harvesting for smart city applications
No full textThe 'smart cities' concept is now becoming a reality: cities are increasingly connected and intelligent, with rapid advances in diverse areas including transportation, utilities, and municipal services. These can allow services to be delivered more efficiently and reliably, enriching residents' and visitors' experiences, and the data generated can be used for innovative new applications. While many sensors enabling these applications can be grid-powered, there is an increasing need for autonomous distributed or wearable sensing devices, which may also perform edge analytics. While these systems are typically powered by batteries so that they can be deployed quickly and cheaply, this comes with the cost of periodic battery replacement. This paper surveys the state-of-the-art in smart city sensing applications and considers their future directions, focusing on the power demands of sensors, and considerations for using energy harvesting.</p
Ponge dans le paysage poétique italien de l'extrême contemporain
No full textCet article revient sur la présence de Francis Ponge dans le paysage littéraire italien contemporain. Après avoir été traduit, de façon éparse, par un certain nombre de poètes dans les années 1960-1970, Ponge suscite à nouveau l'intérêt de plusieurs écrivains en ce début de XXI siècle (Michele Zaffarano, Andrea Inglese, Mario Corticelli, etc.). Ce sont les formes et les enjeux de cette résurgence, spécifiques au contexte italien, qui sont ici étudiés
Poster Abstract: An Ultra-Low Power Wake up Radio with Addressing and Retransmission Capabilities for Advanced Energy Efficient MAC Protocols
No full textWireless sensor networks (WSNs) are today widely employed in real world applications. However, their lifetime is still challenging and the most critical limitation for the success of this technology. In fact, wireless sensors nodes, which are the backbone of the network, are typically powered by limited energy storage devices (i.e. small batteries or supercaps) and their short lifetime is a critical issue. To overcome this limitation a major research effort focuses on reducing power consumption, especially of communication, as the radio transceiver is one of the highest power consumers. A critical energy-efficiency issue in WSN transceivers is idle listening. Wake-up radio receivers are very effective in minimizing idle listening. This fact has resulted in a significant number of wake-up radio receiver architectures proposed in last decade. In this work we present an advanced design and implementation of an advanced wake-up radio that is capable of both processing the received data (i.e. for addressing) and retransmitting data or wake up messages to the neighbours when necessary. With these features it can be possible to further enhance the energy efficiency of the communication and allowing ultra-low power multi-hop communication. Experimental results demonstrate the functionality as well as the power and range of the proposed design which is ready for future energy efficient and pure-asynchronous MAC protocols
Combining microbial fuel cell and ultra-low power event-driven audio detector for zero-power sensing in underwater monitoring
No full textAchieving zero-power always-on sensing is an attractive challenge for academic and industrial researchers. Long-term and perpetual monitoring are particularly important for battery-operated systems, such as wearable and IoT devices and necessary in a wide range of applications. Zero-power sensing is crucial for devices that are supposed to collect data and important events in inaccessible places, such as under the water, where the replacement of batteries is almost impossible or inconvenient. In this paper, we present a novel ultra-low power always-on event-driven acoustic sensor able to feature pattern recognition with up to eight simultaneous time-frequency features exploiting mixed-signal low power design. Moreover, this paper achieves a zero-power acoustic smart sensor combining the event-driven acoustic detector with a microbial fuel cell, aiming long-term monitoring in underwater applications. Experimental results show that our solution is able to recognize a specific audio pattern in less than 1 seconds with 50μW to 55μW power consumption for single and multi-frequency detection respectively. Finally, we achieve a zero-power smart sensor able to work perpetually when powered with microbial fuel cells providing only 0.4mW of continuous power
Accelerating real-time embedded scene labeling with convolutional networks
Get PDFToday there is a clear trend towards deploying advanced computer vision (CV) systems in a growing number of application scenarios with strong real-time and power constraints. Brain-inspired algorithms capable of achieving record-breaking results combined with embedded vision systems are the best candidate for the future of CV and video systems due to their flexibility and high accuracy in the area of image understanding. In this paper, we present an optimized convolutional network implementation suitable for real-time scene labeling on embedded platforms. We show that our algorithm can achieve up to 96GOp/s, running on the Nvidia Tegra K1 embedded SoC. We present experimental results, compare them to the state-of-the-art, and demonstrate that for scene labeling our approach achieves a 1.5x improvement in throughput when compared to a modern desktop CPU at a power budget of only 11 W
- …
