615 resultados para Bucket Seats.


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A pneumatic vehicle is provided with a first and second sub-assembly. The first sub-assembly has a chassis supporting an air tank. The second sub-assembly has part of the vehicle body and is bonded to the first-sub-assembly using a structural adhesive. Another pneumatic vehicle is provided with a first and second sub-assembly. The first sub-assembly has a chassis, air tank, part of the vehicle body, a pair of B-pillars, and a pair of rear rails. The second sub-assembly has a part of the vehicle body, a pair of A-pillars, and a pair of roof rails. A vehicle seat is provided with a seat base and upright seat back providing a seating area. A bladder located in the central region of the seating area inflates to provide two bucket seats, and deflates to provide a bench seat. The vehicle seat also has inflatable inserts to provide cushioning.

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A pneumatic vehicle is provided with a first and second sub-assembly. The first sub-assembly has a chassis supporting an air tank. The second sub-assembly has part of the vehicle body and is bonded to the first-sub-assembly using a structural adhesive. Another pneumatic vehicle is provided with a first and second sub-assembly. The first sub-assembly has a chassis, air tank, part of the vehicle body, a pair of B-pillars, and a pair of rear rails. The second sub-assembly has a part of the vehicle body, a pair of A-pillars, and a pair of roof rails. A vehicle seat is provided with a seat base and upright seat back providing a seating area. A bladder located in the central region of the seating area inflates to provide two bucket seats, and deflates to provide a bench seat. The vehicle seat also has inflatable inserts to provide cushioning.

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National Highway Traffic Safety Administration, Washington, D.C.

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This paper presents a method for calculating the in-bucket payload volume on a dragline for the purpose of estimating the material’s bulk density in real-time. Knowledge of the bulk density can provide instant feedback to mine planning and scheduling to improve blasting and in turn provide a more uniform bulk density across the excavation site. Furthermore costs and emissions in dragline operation, maintenance and downstream material processing can be reduced. The main challenge is to determine an accurate position and orientation of the bucket with the constraint of real-time performance. The proposed solution uses a range bearing and tilt sensor to locate and scan the bucket between the lift and dump stages of the dragline cycle. Various scanning strategies are investigated for their benefits in this real-time application. The bucket is segmented from the scene using cluster analysis while the pose of the bucket is calculated using the iterative closest point (ICP) algorithm. Payload points are segmented from the bucket by a fixed distance neighbour clustering method to preserve boundary points and exclude low density clusters introduced by overhead chains and the spreader bar. A height grid is then used to represent the payload from which the volume can be calculated by summing over the grid cells. We show volume calculated on a scaled system with an accuracy of greater than 95 per cent.

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Australia’s Future Tax System Review, headed by the then head of the Australian Treasury, and the Productivity Commission’s Research Report on the not for profit sector, both examined the state of tax concessions to Australia’s not for profit sector in the light of the High Court’s decision in Commissioner of Taxation v Word Investments Ltd. Despite being unable to quantify with any certainty the pre- or post-Word Investments cost of the tax concessions, both Reports indicated their support for continuation of the income tax exemption. However, the government acted in the 2011 Budget to target the not for profit income tax concessions more precisely, mainly on competitive neutrality grounds. This article examines the income tax exemption by applying the five taxation design principles, proposed in the Australia’s Future Tax System Review, for assessing tax expenditure. The conclusion is that the exemptions can be justified and, further, that a rationale for the exemption can be consistent with the reasoning in the Word Investments case.

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Numeric set watermarking is a way to provide ownership proof for numerical data. Numerical data can be considered to be primitives for multimedia types such as images and videos since they are organized forms of numeric information. Thereby, the capability to watermark numerical data directly implies the capability to watermark multimedia objects and discourage information theft on social networking sites and the Internet in general. Unfortunately, there has been very limited research done in the field of numeric set watermarking due to underlying limitations in terms of number of items in the set and LSBs in each item available for watermarking. In 2009, Gupta et al. proposed a numeric set watermarking model that embeds watermark bits in the items of the set based on a hash value of the items’ most significant bits (MSBs). If an item is chosen for watermarking, a watermark bit is embedded in the least significant bits, and the replaced bit is inserted in the fractional value to provide reversibility. The authors show their scheme to be resilient against the traditional subset addition, deletion, and modification attacks as well as secondary watermarking attacks. In this paper, we present a bucket attack on this watermarking model. The attack consists of creating buckets of items with the same MSBs and determine if the items of the bucket carry watermark bits. Experimental results show that the bucket attack is very strong and destroys the entire watermark with close to 100% success rate. We examine the inherent weaknesses in the watermarking model of Gupta et al. that leave it vulnerable to the bucket attack and propose potential safeguards that can provide resilience against this attack.

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This paper details the implementation and trialling of a prototype in-bucket bulk density monitor on a production dragline. Bulk density information can provide feedback to mine planning and scheduling to improve blasting and consequently facilitating optimal bucket sizing. The bulk density measurement builds upon outcomes presented in the AMTC2009 paper titled ‘Automatic In-Bucket Volume Estimation for Dragline Operations’ and utilises payload information from a commercial dragline monitor. While the previous paper explains the algorithms and theoretical basis for the system design and scaled model testing this paper will focus on the full scale implementation and the challenges involved.

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Digital image

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Digital image

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Digital image