FPGA power efficient inverse lifting wavelet IP Grangetto, M.; Martina, M.; Masera, G. ...
Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256),
2001, Letnik:
2
Conference Proceeding
In this paper a power efficient lifting-based wavelet transform IP, well suited for mobile and tetherless applications, is proposed. Recently, reconfigurable architectures, driven by new ...communication technology challenges and by mobile market explosion have moved developers' interest towards novel IP design strategies. Despite the increasing importance gathered by easily retargetable blocks, a lack of power conscious cores is felt by the developer's community. This IP is intended to be employed as the source coding kernel in many multimedia emerging algorithms. From post-place and route simulation a power dissipation of 36.6 mW has been obtained on a Xilinx XCV200E.
Cycling as an active mode of transport is increasing across all Europe 1. Multiple benefits are coming from cycling both for the single user and the society as a whole. With increasing cycling, we ...expect more conflicts to happen between cyclists and vehicles, as it is also shown by the increasing cyclists' share of fatalities, contrary to the passenger cars' share 2. Understanding cyclists' behavioral patterns can help automated vehicles (AVs) to predict cyclist's behavior, and then behave safely and comfortably when they encounter them. As a result, developing reliable predictive models of cyclist behavior will help AVs to interact safely with cyclists.
In Europe, the use of electric bicycles is rapidly increasing. This trend raises important safety concerns: Is their use compatible with existing infrastructure and regulations? Do they present novel ...safety issues? How do they impact other traffic? This study sought to address these concerns, using instrumented electric bicycles to monitor e-cyclists’ behavior in a naturalistic fashion. Data was collected from 12 bicyclists, each of whom rode an instrumented bicycle for two weeks. In total, 1500 km worth of data were collected, including 88 critical events (crashes and near-crashes). Analysis of these critical events identified pedestrians, light vehicles and other bicycles as main threats to a safe ride. Other factors also contributed to crash causation, such as being in proximity to a crossing or encountering a vehicle parked in the bicycle lane. A comparison between electric and traditional bicycles was enabled by the availability of data from a previous study a year earlier, which collected naturalistic cycling data from traditional bicycles using the same instrumentation as in this study. Electric bicycles were found to be ridden faster, on average, than traditional bicycles, in addition to interacting differently with other road users. The results presented in this study also suggest that countermeasures to bicycle crashes should be different for electric and traditional bicycles. Finally, increasing electric bicycle conspicuity appears to be the easiest, most obvious way to increase their safety.
