Geometric Hamiltonian formulation of a variational problem depending on the covariant acceleration

We consider a second-order variational problem depending on the covariant acceleration, which is related to the notion of Riemannian cubic polynomials. This problem and the corresponding optimal control problem are described in the context of higher order tangent bundles using geometric tools. The main tool, a presymplectic variant of Pontryagin’s maximum principle, allows us to study the dynamics of the control problem.

Variable stability research aircraft. Submitted to the Panel on Acceleration Stress of the Armed Forces, National Research Council Committee on Bio-Astronautics, Woods Hole Conference, 16-24 July, 1959.

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A Mapping-Scheduling Algorithm for Hardware Acceleration on Reconfigurable Platforms

Reconfigurable platforms are a promising technology that offers an interesting trade-off between flexibility and performance, which many recent embedded system applications demand, especially in fields such as multimedia processing. These applications typically involve multiple ad-hoc tasks for hardware acceleration, which are usually represented using formalisms such as Data Flow Diagrams (DFDs), Data Flow Graphs (DFGs), Control and Data Flow Graphs (CDFGs) or Petri Nets. However, none of these models is able to capture at the same time the pipeline behavior between tasks (that therefore can coexist in order to minimize the application execution time), their communication patterns, and their data dependencies. This paper proves that the knowledge of all this information can be effectively exploited to reduce the resource requirements and the timing performance of modern reconfigurable systems, where a set of hardware accelerators is used to support the computation. For this purpose, this paper proposes a novel task representation model, named Temporal Constrained Data Flow Diagram (TCDFD), which includes all this information. This paper also presents a mapping-scheduling algorithm that is able to take advantage of the new TCDFD model. It aims at minimizing the dynamic reconfiguration overhead while meeting the communication requirements among the tasks. Experimental results show that the presented approach achieves up to 75% of resources saving and up to 89% of reconfiguration overhead reduction with respect to other state-of-the-art techniques for reconfigurable platforms.

Individual differences in activity and habitat selection of juvenile queen conch evaluated using acceleration biologgers

Fine-scale differences in behaviour and habitat use have important ecological implications, but have rarely been examined in marine gastropods. We used tri-axial accelerometer loggers to estimate activity levels and movement patterns of the juvenile queen conch Lobatus gigas (n = 11) in 2 habitat types in Eleuthera, The Bahamas. In 2 manipulations in nearshore areas, queen conchs were equipped with accelerometers and released in adjacent coral rubble or seagrass habitats. Queen conchs were located approximately every 6 h during daylight by snorkeling, to measure individual differences in linear distance moved, and after 24 h they were relocated to an alternate habitat (24 h in each habitat). We found significant inter-individual variability in activity levels, but more consistent levels of activity between the 2 habitat types within individual queen conchs. Four (36%) of the individuals placed in seagrass moved back to the adjacent coral rubble habitat, suggesting selectivity for coral rubble. Individuals showed variable behavioural responses when relocated to the less preferable seagrass habitat, which may be related to differing stress-coping styles. Our results suggest that behavioural variability between individuals may be an important factor driving movement and habitat use in queen conch and, potentially, their susceptibility to human stressors. This study provides evidence of diverse behavioural (activity) patterns and habitat selectivity in a marine gastropod and highlights the utility of accelero meter biologgers for continuously monitoring animal behaviour in the wild.

Validity of a wearable accelerometer device to measure average acceleration values during high speed running

The aim of this study was to determine the validity of an accelerometer to measure average acceleration values during high speed running. Thirteen subjects performed three sprint efforts over a 40 m distance (n = 39). Acceleration was measured using a 100 Hz tri-axial accelerometer integrated within a wearable tracking device (SPI-HPU, GPSports, Canberra). To provide a concurrent measure of acceleration, timing gates were positioned at 10 m intervals (0 m - 40 m). Accelerometer data collected during 0 m - 10 m and 10 m - 20 m provided a measure of average acceleration values. Accelerometer data was recorded as the raw output and filtered by applying a 3 point moving average and a 10 point moving average. The accelerometer could not measure average acceleration values during high speed running. The accelerometer significantly overestimated average acceleration values during both 0 m - 10 m and 10 m - 20 m, regardless of the data filtering technique (p < 0.001). Body mass significantly affected all accelerometer variables (p < 0.10, partial η = 0.091 - 0.219). Body mass and the absence of a gravity compensation formula affect the accuracy and practicality of accelerometers. Until GPSports integrated accelerometers incorporate a gravity compensation formula the usefulness of any accelerometer derived algorithms is questionable.

System-on-a-Chip (SoC) based Hardware Acceleration in Register Transfer Level (RTL) Design

Today, modern System-on-a-Chip (SoC) systems have grown rapidly due to the increased processing power, while maintaining the size of the hardware circuit. The number of transistors on a chip continues to increase, but current SoC designs may not be able to exploit the potential performance, especially with energy consumption and chip area becoming two major concerns. Traditional SoC designs usually separate software and hardware. Thus, the process of improving the system performance is a complicated task for both software and hardware designers. The aim of this research is to develop hardware acceleration workflow for software applications. Thus, system performance can be improved with constraints of energy consumption and on-chip resource costs. The characteristics of software applications can be identified by using profiling tools. Hardware acceleration can have significant performance improvement for highly mathematical calculations or repeated functions. The performance of SoC systems can then be improved, if the hardware acceleration method is used to accelerate the element that incurs performance overheads. The concepts mentioned in this study can be easily applied to a variety of sophisticated software applications. The contributions of SoC-based hardware acceleration in the hardware-software co-design platform include the following: (1) Software profiling methods are applied to H.264 Coder-Decoder (CODEC) core. The hotspot function of aimed application is identified by using critical attributes such as cycles per loop, loop rounds, etc. (2) Hardware acceleration method based on Field-Programmable Gate Array (FPGA) is used to resolve system bottlenecks and improve system performance. The identified hotspot function is then converted to a hardware accelerator and mapped onto the hardware platform. Two types of hardware acceleration methods – central bus design and co-processor design, are implemented for comparison in the proposed architecture. (3) System specifications, such as performance, energy consumption, and resource costs, are measured and analyzed. The trade-off of these three factors is compared and balanced. Different hardware accelerators are implemented and evaluated based on system requirements. 4) The system verification platform is designed based on Integrated Circuit (IC) workflow. Hardware optimization techniques are used for higher performance and less resource costs. Experimental results show that the proposed hardware acceleration workflow for software applications is an efficient technique. The system can reach 2.8X performance improvements and save 31.84% energy consumption by applying the Bus-IP design. The Co-processor design can have 7.9X performance and save 75.85% energy consumption.

Head and eye movements and lane keeping in drivers with hemianopia and quadrantanopia compared to controls

Purpose: To compare the eye and head movements and lane-keeping of drivers with hemianopia and quadrantanopia with that of age-matched controls when driving under real world conditions. Methods: Participants included 22 hemianopes and 8 quadrantanopes (M age 53 yrs) and 30 persons with normal visual fields (M age 52 yrs) who were ≥ 6 months from the brain injury date and either a current driver or aiming to resume driving. All participants drove an instrumented dual-brake vehicle along a 14-mile route in traffic that included non-interstate city driving and interstate driving. Driving performance was scored using a standardised assessment system by two “backseat” raters and the Vigil Vanguard system which provides objective measures of speed, braking and acceleration, cornering, and video-based footage from which eye and head movements and lane-keeping can be derived. Results: As compared to drivers with normal visual fields, drivers with hemianopia or quadrantanopia on average were significantly more likely to drive slower, to exhibit less excessive cornering forces or acceleration, and to execute more shoulder movements off the seat. Those hemianopic and quadrantanopic drivers rated as safe to drive by the backseat evaluator made significantly more excursive eye movements, exhibited more stable lane positioning, less sudden braking events and drove at higher speeds than those rated as unsafe, while there was no difference between safe and unsafe drivers in head movements. Conclusions: Persons with hemianopic and quadrantanopic field defects rated as safe to drive have different driving characteristics compared to those rated as unsafe when assessed using objective measures of driving performance.

Influence of all-out and fast start of 5-min cycling time trial performance

Purpose: To examine the influence of two different fast-start pacing strategies on performance and oxygen consumption (V˙O2) during cycle ergometer time trials lasting ∼5 min. Methods: Eight trained male cyclists performed four cycle ergometer time trials whereby the total work completed (113 ± 11.5 kJ; mean ± SD) was identical to the better of two 5-min self-paced familiarization trials. During the performance trials, initial power output was manipulated to induce either an all-out or a fast start. Power output during the first 60 s of the fast-start trial was maintained at 471.0 ± 48.0 W, whereas the all-out start approximated a maximal starting effort for the first 15 s (mean power: 753.6 ± 76.5 W) followed by 45 s at a constant power output (376.8 ± 38.5 W). Irrespective of starting strategy, power output was controlled so that participants would complete the first quarter of the trial (28.3 ± 2.9 kJ) in 60 s. Participants performed two trials using each condition, with their fastest time trial compared. Results: Performance time was significantly faster when cyclists adopted the all-out start (4 min 48 s ± 8 s) compared with the fast start (4 min 51 s ± 8 s; P < 0.05). The first-quarter V˙O2 during the all-out start trial (3.4 ± 0.4 L·min-1) was significantly higher than during the fast-start trial (3.1 ± 0.4 L·min-1; P < 0.05). After removal of an outlier, the percentage increase in first-quarter V˙O2 was significantly correlated (r = -0.86, P < 0.05) with the relative difference in finishing time. Conclusions: An all-out start produces superior middle distance cycling performance when compared with a fast start. The improvement in performance may be due to a faster V˙O2 response rather than time saved due to a rapid acceleration.

Comprehensive evaluation of driver gaze pattern using fuzzy rules for driver training

The over representation of novice drivers in crashes is alarming. Research indicates that one in five drivers’ crashes within their first year of driving. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the drive. This paper presents a system that evaluates the data stream acquired from multiple in-vehicle sensors (acquired from Driver Vehicle Environment-DVE) using fuzzy rules and classifies the driving manoeuvres (i.e. overtake, lane change and turn) as low risk or high risk. The fuzzy rules use parameters such as following distance, frequency of mirror checks, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvre to assess risk. The fuzzy rules to estimate risk are designed after analysing the selected driving manoeuvres performed by driver trainers. This paper focuses mainly on the difference in gaze pattern for experienced and novice drivers during the selected manoeuvres. Using this system, trainers of novice drivers would be able to empirically evaluate and give feedback to the novice drivers regarding their driving behaviour.

Experimental evaluation of position control methods for hydraulic systems

Presents a unified and systematic assessment of ten position control strategies for a hydraulic servo system with single-ended cylinder driven by a proportional directional control valve. We aim at identifying those methods that achieve better tracking, have a low sensitivity to system uncertainties, and offer a good balance between development effort and end results. A formal approach for solving this problem relies on several practical metrics, which is introduced herein. Their choice is important, as the comparison results between controllers can vary significantly, depending on the selected criterion. Apart from the quantitative assessment, we also raise aspects which are difficult to quantify, but which must stay in attention when considering the position control problem for this class of hydraulic servo systems.

Large area noise evaluation

A software tool (DRONE) has been developed to evaluate road traffic noise in a large area with the consideration of network dynamic traffic flow and the buildings. For more precise estimation of noise in urban network where vehicles are mainly in stop and go running conditions, vehicle sound power level (for acceleration/deceleration cruising and ideal vehicle) is incorporated in DRONE. The calculation performance of DRONE is increased by evaluating the noise in two steps of first estimating the unit noise database and then integrating it with traffic simulation. Details of the process from traffic simulation to contour maps are discussed in the paper and the implementation of DRONE on Tsukuba city is presented