28 resultados para driver verification

em University of Queensland eSpace - Australia


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This paper summarises test results that were used to validate a model and scale-up procedure of the high pressure grinding roll (HPGR) which was developed at the JKMRC by Morrell et al. [Morrell, Lim, Tondo, David,1996. Modelling the high pressure grinding rolls. In: Mining Technology Conference, pp. 169-176.]. Verification of the model is based on results from four data sets that describe the performance of three industrial scale units fitted with both studded and smooth roll surfaces. The industrial units are currently in operation within the diamond mining industry and are represented by De Beers, BHP Billiton and Rio Tinto. Ore samples from the De Beers and BHP Billiton operations were sent to the JKMRC for ore characterisation and HPGR laboratory-scale tests. Rio Tinto contributed an historical data set of tests completed during a previous research project. The results conclude that the modelling of the HPGR process has matured to a point where the model may be used to evaluate new and to optimise existing comminution circuits. The model prediction of product size distribution is good and has been found to be strongly dependent of the characteristics of the material being tested. The prediction of throughput and corresponding power draw (based on throughput) is sensitive to inconsistent gap/diameter ratios observed between laboratory-scale tests and full-scale operations. (C) 2004 Elsevier Ltd. All rights reserved.

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Automatic signature verification is a well-established and an active area of research with numerous applications such as bank check verification, ATM access, etc. This paper proposes a novel approach to the problem of automatic off-line signature verification and forgery detection. The proposed approach is based on fuzzy modeling that employs the Takagi-Sugeno (TS) model. Signature verification and forgery detection are carried out using angle features extracted from box approach. Each feature corresponds to a fuzzy set. The features are fuzzified by an exponential membership function involved in the TS model, which is modified to include structural parameters. The structural parameters are devised to take account of possible variations due to handwriting styles and to reflect moods. The membership functions constitute weights in the TS model. The optimization of the output of the TS model with respect to the structural parameters yields the solution for the parameters. We have also derived two TS models by considering a rule for each input feature in the first formulation (Multiple rules) and by considering a single rule for all input features in the second formulation. In this work, we have found that TS model with multiple rules is better than TS model with single rule for detecting three types of forgeries; random, skilled and unskilled from a large database of sample signatures in addition to verifying genuine signatures. We have also devised three approaches, viz., an innovative approach and two intuitive approaches using the TS model with multiple rules for improved performance. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

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Proof reuse, or analogical reasoning, involves reusing the proof of a source theorem in the proof of a target conjecture. We have developed a method for proof reuse that is based on the generalisation replay paradigm described in the literature, in which a generalisation of the source proof is replayed to construct the target proof. In this paper, we describe the novel aspects of our method, which include a technique for producing more accurate source proof generalisations (using knowledge of the target goal), as well as a flexible replay strategy that allows the user to set various parameters to control the size and the shape of the search space. Finally, we report on the results of applying this method to a case study from the realm of software verification.

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It is not surprising that students are unconvinced about the benefits of formal methods if we do not show them how these methods can be integrated with other activities in the software lifecycle. In this paper, we describe an approach to integrating formal specification with more traditional verification and validation techniques in a course that teaches formal specification and specification-based testing. This is accomplished through a series of assignments on a single software component that involves specifying the component in Object-Z, validating that specification using inspection and a specification animation tool, and then testing an implementation of the specification using test cases derived from the formal specification.

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Despite decades of research, the takeup of formal methods for developing provably correct software in industry remains slow. One reason for this is the high cost of proof construction, an activity that, due to the complexity of the required proofs, is typically carried out using interactive theorem provers. In this paper we propose an agent-oriented architecture for interactive theorem proving with the aim of reducing the user interactions (and thus the cost) of constructing software verification proofs. We describe a prototype implementation of our architecture and discuss its application to a small, but non-trivial case study.

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Research in verification and validation (V&V) for concurrent programs can be guided by practitioner information. A survey was therefore run to gain state-of-practice information in this context. The survey presented in this paper collected state-of-practice information on V&V technology in concurrency from 35 respondents. The results of the survey can help refine existing V&V technology by providing a better understanding of the context of V&V technology usage. Responses to questions regarding the motivation for selecting V&V technologies can help refine a systematic approach to V&V technology selection.

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This paper reports on a current research project in which virtual reality simulators are being investigated as a means of simulating hazardous Rail work conditions in order to allow train drivers to practice decision-making under stress. When working under high stress conditions train drivers need to move beyond procedural responses into a response activated through their own problem-solving and decision-making skills. This study focuses on the use of stress inoculation training which aims to build driver’s confidence in the use of new decision-making skills by being repeatedly required to respond to hazardous driving conditions. In particular, the study makes use of a train cab driving simulator to reproduce potentially stress inducing real-world scenarios. Initial pilot research has been undertaken in which drivers have experienced the training simulation and subsequently completed surveys on the level of immersion experienced. Concurrently drivers have also participated in a velocity perception experiment designed to objectively measure the fidelity of the virtual training environment. Baseline data, against which decision-making skills post training will be measured, is being gathered via cognitive task analysis designed to identify primary decision requirements for specific rail events. While considerable efforts have been invested in improving Virtual Reality technology, little is known about how to best use this technology for training personnel to respond to workplace conditions in the Rail Industry. To enable the best use of simulators for training in the Rail context the project aims to identify those factors within virtual reality that support required learning outcomes and use this information to design training simulations that reliably and safely train staff in required workplace accident response skills.