A convolutional neural network for automatic analysis of aerial imagery

This paper introduces a new method to automate the detection of marine species in aerial imagery using a Machine Learning approach. Our proposed system has at its core, a convolutional neural network. We compare this trainable classifier to a handcrafted classifier based on color features, entropy and shape analysis. Experiments demonstrate that the convolutional neural network outperforms the handcrafted solution. We also introduce a negative training example-selection method for situations where the original training set consists of a collection of labeled images in which the objects of interest (positive examples) have been marked by a bounding box. We show that picking random rectangles from the background is not necessarily the best way to generate useful negative examples with respect to learning.

Assessment of robust autonomy for unmanned systems : progress and challenges

The growing number of potential applications of Unmanned Aircraft Systems (UAS) in civilian operations and national security is putting pressure of National Airworthiness Authorities to provide a path for certification and allow UAS integration into the national airspace. The success of this integration depends not only on developments in improved UAS reliability and safety, but also on regulations for certification, and methodologies for operational performance and safety assessment. This paper focuses on the latter and describes progress in relation to a previously proposed framework for evaluating robust autonomy of UAS. The paper draws parallels between the proposed evaluation framework and the evaluation of pilots during the licensing process. It discusses how the data from the proposed evaluation can be used as an aid for decision making in certification and UAS designs. Finally, it discusses challenges associated with the evaluation.

The impact of a congestion pricing exemption on the demand for new energy efficient vehicles in Stockholm

As governments seek to transition to more efficient vehicle fleets, one strategy has been to incentivize ‘green’ vehicle choice by exempting some of these vehicles from road user charges. As an example, to stimulate sales of Energy-Efficient Vehicles (EEVs) in Sweden, some of these automobiles were exempted from Stockholm’s congestion tax. In this paper the effect this policy had on the demand for new, privately-owned, exempt EEVs is assessed by first estimating a model of vehicle choice and then by applying this model to simulate vehicle alternative market shares under different policy scenarios. The database used to calibrate the model includes owner-specific demographics merged with vehicle registry data for all new private vehicles registered in Stockholm County during 2008. Characteristics of individuals with a higher propensity to purchase an exempt EEV were identified. The most significant factors included intra-cordon residency (positive), distance from home to the CBD (negative), and commuting across the cordon (positive). By calculating vehicle shares from the vehicle choice model and then comparing these estimates to a simulated scenario where the congestion tax exemption was inactive, the exemption was estimated to have substantially increased the share of newly purchased, private, exempt EEVs in Stockholm by 1.8% (+/- 0.3%; 95% C.I.) to a total share of 18.8%. This amounts to an estimated 10.7% increase in private, exempt EEV purchases during 2008 i.e. 519 privately owned, exempt EEVs.

Echolocation call production during aerial and terrestrial locomotion by New Zealand's enigmatic lesser short-tailed bat, Mystacina tuberculata

Linkage of echolocation call production with contraction of flight muscles has been suggested to reduce the energetic cost of flight with echolocation, such that the overall cost is approximately equal to that of flight alone. However, the pattern of call production with limb movement in terrestrially agile bats has never been investigated. We used synchronised high-speed video and audio recordings to determine patterns of association between echolocation call production and limb motion by Mystacina tuberculata Gray 1843 as individuals walked and flew, respectively. Results showed that there was no apparent linkage between call production and limb motion when bats walked. When in flight, two calls were produced per wingbeat, late in the downstroke and early in the upstroke. When bats walked, calls were produced at a higher rate, but at a slightly lower intensity, compared with bats in flight. These results suggest that M. tuberculata do not attempt to reduce the cost of terrestrial locomotion and call production through biomechanical linkage. They also suggest that the pattern of linkage seen when bats are in flight is not universal and that energetic savings cannot necessarily be explained by contraction of muscles associated with the downstroke alone.

Echolocation call intensity in the aerial hawking bat Eptesicus bottae (Vespertilionidae) studied using stereo videogrammetry

Aerial hawking bats use intense echolocation calls to search for insect prey. Their calls have evolved into the most intense airborne animal vocalisations. Yet our knowledge about call intensities in the field is restricted to a small number of species. We describe a novel stereo videogrammetry method used to study flight and echolocation behaviour, and to measure call source levels of the aerial hawking bat Eptesicus bottae (Vespertilionidae). Bats flew close to their predicted minimum power speed. Source level increased with call duration; the loudest call of E. bottae was at 133 dB peSPL. The calculated maximum detection distance for large flying objects (e.g. large prey, conspecifics) was up to 21 m. The corresponding maximum echo delay is almost exactly the duration of one wing beat in E. bottae and this also is its preferred pulse interval. These results, obtained by using videogrammetry to track bats in the field, corroborate earlier findings from other species from acoustic tracking methods.

Wireless Power Transfer (WPT) for electric vehicles (EVs) - present and future trends

100 year old gasoline engine technology vehicles have now become one of the major contributors of greenhouse gases. Plug-in Electric Vehicles (PEVs) have been proposed to achieve environmental friendly transportation. Even though the PEV usage is currently increasing, a technology breakthrough would be required to overcome battery related drawbacks. Although battery technology is evolving, drawbacks inherited with batteries such as; cost, size, weight, slower charging characteristic and low energy density would still be dominating constrains for development of EVs. Furthermore, PEVs have not been accepted as preferred choice by many consumers due to charging related issues. To address battery related limitations, the concept of dynamic Wireless Power Transfer (WPT) enabled EVs have been proposed in which EV is being charged while it is in motion. WPT enabled infrastructure has to be employed to achieve dynamic EV charging concept. The weight of the battery pack can be reduced as the required energy storage is lower if the vehicle can be powered wirelessly while driving. Stationary WPT charging where EV is charged wirelessly when it is stopped, is simpler than dynamic WPT in terms of design complexity. However, stationary WPT does not increase vehicle range compared to wired-PEVs. State-of-art WPT technology for future transportation is discussed in this chapter. Analysis of the WPT system and its performance indices are introduced. Modelling the WPT system using different methods such as equivalent circuit theory, two port network theory and coupled mode theory is described illustrating their own merits in Sect. 2.3. Both stationary and dynamic WPT for EV applications are illustrated in Sect. 2.4. Design challenges and optimization directions are analysed in Sect. 2.5. Adaptive tuning techniques such as adaptive impedance matching and frequency tuning are also discussed. A case study for optimizing resonator design is presented in Sect. 2.6. Achievements by the research community is introduced highlighting directions for future research.

Bio-inspired plume tracking algorithm for UAVS

There is an increased interest on the use of UAVs for environmental research and to track bush fire plumes, volcanic plumes or pollutant sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A memory based and gradient based approach, were developed and compared. A method for generating sparse plumes was also developed. Results indicate the ability of the algorithms to track plumes in 2D and 3D.

IMU aided 3D visual odometry for car-like vehicles

We present a method for calculating odome- try in three-dimensions for car-like ground ve- hicles with an Ackerman-like steering model. In our approach we use the information from a single camera to derive the odometry in the plane and fuse it with roll and pitch informa- tion derived from an on-board IMU to extend to three-dimensions, thus providing odometric altitude as well as traditional x and y transla- tion. We have mounted the odometry module on a standard Toyota Prado SUV and present results from a car-park environment as well as from an off-road track.

Managing moose harvests by the seat of your pants

Moose populations are managed for sustainable yield balanced against costs caused by damage to forestry or agriculture and collisions with vehicles. Optimal harvests can be calculated based on a structured population model driven by data on abundance and the composition of bulls, cows, and calves obtained by aerial-survey monitoring during winter. Quotas are established by the respective government agency and licenses are issued to hunters to harvest an animal of specified age or sex during the following autumn. Because the cost of aerial monitoring is high, we use a Management Strategy Evaluation to evaluate the costs and benefits of periodic aerial surveys in the context of moose management. Our on-the-fly "seat of your pants" alternative to independent monitoring is management based solely on the kill of moose by hunters, which is usually sufficient to alert the manager to declines in moose abundance that warrant adjustments to harvest strategies. Harvests are relatively cheap to monitor; therefore, data can be obtained each year facilitating annual adjustments to quotas. Other sources of "cheap" monitoring data such as records of the number of moose seen by hunters while hunting also might be obtained, and may provide further useful insight into population abundance, structure and health. Because conservation dollars are usually limited, the high cost of aerial surveys is difficult to justify when alternative methods exist. © 2012 Elsevier Inc.

Double star chopper cell converter for battery electric vehicles with inter-module SoC balancing and fault tolerant control

A modularized battery system with Double Star Chopper Cell (DSCC) based modular multilevel converter is proposed for a battery operated electric vehicle (EV). A design concept for the modularized battery micro-packs for DSCC is described. Multidimensional pulse width modulation (MD-PWM) with integrated inter-module SoC balancing and fault tolerant control is proposed and explained. The DSCC can be operated either as an inverter to drive the EV motor or as a synchronous rectifier connected to external three phase power supply equipment for charging the battery micro-packs. The methods of operation as inverter and synchronous rectifier with integrated inter-module SoC balancing and fault tolerant control are discussed. The proposed system operation as inverter and synchronous rectifier are verified through simulations and the results are presented.