246 resultados para intelligent manufacturing systems


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Road surface macrotexture is identified as one of the factors contributing to the surface's skid resistance. Existing methods of quantifying the surface macrotexture, such as the sand patch test and the laser profilometer test, are either expensive or intrusive, requiring traffic control. High-resolution cameras have made it possible to acquire good quality images from roads for the automated analysis of texture depth. In this paper, a granulometric method based on image processing is proposed to estimate road surface texture coarseness distribution from their edge profiles. More than 1300 images were acquired from two different sites, extending to a total of 2.96 km. The images were acquired using camera orientations of 60 and 90 degrees. The road surface is modeled as a texture of particles, and the size distribution of these particles is obtained from chord lengths across edge boundaries. The mean size from each distribution is compared with the sensor measured texture depth obtained using a laser profilometer. By tuning the edge detector parameters, a coefficient of determination of up to R2 = 0.94 between the proposed method and the laser profilometer method was obtained. The high correlation is also confirmed by robust calibration parameters that enable the method to be used for unseen data after the method has been calibrated over road surface data with similar surface characteristics and under similar imaging conditions.

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Variable Speed Limits (VSL) is an Intelligent Transportation Systems (ITS) control tool which can enhance traffic safety and which has the potential to contribute to traffic efficiency. Queensland's motorways experience a large volume of commuter traffic in peak periods, leading to heavy recurrent congestion and a high frequency of incidents. Consequently, Queensland's Department of Transport and Main Roads have considered deploying VSL to improve safety and efficiency. This paper identifies three types of VSL and three applicable conditions for activating VSL on for Queensland motorways: high flow, queuing and adverse weather. The design objectives and methodology for each condition are analysed, and micro-simulation results are presented to demonstrate the effectiveness of VSL.

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Railway timetabling is an important process in train service provision as it matches the transportation demand with the infrastructure capacity while customer satisfaction is also considered. It is a multi-objective optimisation problem, in which a feasible solution, rather than the optimal one, is usually taken in practice because of the time constraint. The quality of services may suffer as a result. In a railway open market, timetabling usually involves rounds of negotiations among a number of self-interested and independent stakeholders and hence additional objectives and constraints are imposed on the timetabling problem. While the requirements of all stakeholders are taken into consideration simultaneously, the computation demand is inevitably immense. Intelligent solution-searching techniques provide a possible solution. This paper attempts to employ a particle swarm optimisation (PSO) approach to devise a railway timetable in an open market. The suitability and performance of PSO are studied on a multi-agent-based railway open-market negotiation simulation platform.

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Increasing global competitiveness worldwide has forced manufacturing organizations to produce high-quality products more quickly and at a competitive cost. In order to reach these goals, they need good quality components from suppliers at optimum price and lead time. This actually forced all the companies to adapt different improvement practices such as lean manufacturing, Just in Time (JIT) and effective supply chain management. Applying new improvement techniques and tools cause higher establishment costs and more Information Delay (ID). On the contrary, these new techniques may reduce the risk of stock outs and affect supply chain flexibility to give a better overall performance. But industry people are unable to measure the overall affects of those improvement techniques with a standard evaluation model .So an effective overall supply chain performance evaluation model is essential for suppliers as well as manufacturers to assess their companies under different supply chain strategies. However, literature on lean supply chain performance evaluation is comparatively limited. Moreover, most of the models assumed random values for performance variables. The purpose of this paper is to propose an effective supply chain performance evaluation model using triangular linguistic fuzzy numbers and to recommend optimum ranges for performance variables for lean implementation. The model initially considers all the supply chain performance criteria (input, output and flexibility), converts the values to triangular linguistic fuzzy numbers and evaluates overall supply chain performance under different situations. Results show that with the proposed performance measurement model, improvement area for each variable can be accurately identified.

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This paper provides fundamental understanding for the use of cumulative plots for travel time estimation on signalized urban networks. Analytical modeling is performed to generate cumulative plots based on the availability of data: a) Case-D, for detector data only; b) Case-DS, for detector data and signal timings; and c) Case-DSS, for detector data, signal timings and saturation flow rate. The empirical study and sensitivity analysis based on simulation experiments have observed the consistency in performance for Case-DS and Case-DSS, whereas, for Case-D the performance is inconsistent. Case-D is sensitive to detection interval and signal timings within the interval. When detection interval is integral multiple of signal cycle then it has low accuracy and low reliability. Whereas, for detection interval around 1.5 times signal cycle both accuracy and reliability are high.

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Evaluating the safety of different traffic facilities is a complex and crucial task. Microscopic simulation models have been widely used for traffic management but have been largely neglected in traffic safety studies. Micro simulation to study safety is more ethical and accessible than the traditional safety studies, which only assess historical crash data. However, current microscopic models are unable to mimic unsafe driver behavior, as they are based on presumptions of safe driver behavior. This highlights the need for a critical examination of the current microscopic models to determine which components and parameters have an effect on safety indicator reproduction. The question then arises whether these safety indicators are valid indicators of traffic safety. The safety indicators were therefore selected and tested for straight motorway segments in Brisbane, Australia. This test examined the capability of a micro-simulation model and presents a better understanding of micro-simulation models and how such models, in particular car following models can be enriched to present more accurate safety indicators.

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Pedestrians’ use of mp3 players or mobile phones can pose the risk of being hit by motor vehicles. We present an approach for detecting a crash risk level using the computing power and the microphone of mobile devices that can be used to alert the user in advance of an approaching vehicle so as to avoid a crash. A single feature extractor classifier is not usually able to deal with the diversity of risky acoustic scenarios. In this paper, we address the problem of detection of vehicles approaching a pedestrian by a novel, simple, non resource intensive acoustic method. The method uses a set of existing statistical tools to mine signal features. Audio features are adaptively thresholded for relevance and classified with a three component heuristic. The resulting Acoustic Hazard Detection (AHD) system has a very low false positive detection rate. The results of this study could help mobile device manufacturers to embed the presented features into future potable devices and contribute to road safety.

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This chapter discusses a range of issues associated with supporting inquiry and deep reasoning while utilising information and communications technology (ICT). The role of questioning in critical thinking and reflection is considered in the context of scaffolding and new opportunities for ICT-enabled scaffolding identified. In particular, why-questioning provides a key point of focus and is presented as an important consideration in the design of systems that not only require cognitive engagement but aim to nurture it. Advances in automated question generation within intelligent tutoring systems are shown to hold promise for both teaching and learning in a range of other applications. While shortening attention spans appear to be a hazard of engaging with digital media cognitive engagement is presented as something with broader scope than attention span and is best conceived of as a crucible within which a rich mix of cognitive activities take place and from which new knowledge is created.

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The lack of satisfactory consensus for characterizing the system intelligence and structured analytical decision models has inhibited the developers and practitioners to understand and configure optimum intelligent building systems in a fully informed manner. So far, little research has been conducted in this aspect. This research is designed to identify the key intelligent indicators, and develop analytical models for computing the system intelligence score of smart building system in the intelligent building. The integrated building management system (IBMS) was used as an illustrative example to present a framework. The models presented in this study applied the system intelligence theory, and the conceptual analytical framework. A total of 16 key intelligent indicators were first identified from a general survey. Then, two multi-criteria decision making (MCDM) approaches, the analytic hierarchy process (AHP) and analytic network process (ANP), were employed to develop the system intelligence analytical models. Top intelligence indicators of IBMS include: self-diagnostic of operation deviations; adaptive limiting control algorithm; and, year-round time schedule performance. The developed conceptual framework was then transformed to the practical model. The effectiveness of the practical model was evaluated by means of expert validation. The main contribution of this research is to promote understanding of the intelligent indicators, and to set the foundation for a systemic framework that provide developers and building stakeholders a consolidated inclusive tool for the system intelligence evaluation of the proposed components design configurations.

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This paper presents the benefits and issues related to travel time prediction on urban network. Travel time information quantifies congestion and is perhaps the most important network performance measure. Travel time prediction has been an active area of research for the last five decades. The activities related to ITS have increased the attention of researchers for better and accurate real-time prediction of travel time. Majority of the literature on travel time prediction is applicable to freeways where, under non-incident conditions, traffic flow is not affected by external factors such as traffic control signals and opposing traffic flows. On urban environment the problem is more complicated due to conflicting areas (intersections), mid-link sources and sinks etc. and needs to be addressed.

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The return of emotions to debates about crime and criminal justice has been a striking development of recent decades across many jurisdictions. This has been registered in the return of shame to justice procedures, a heightened focus on victims and their emotional needs, fear of crime as a major preoccupation of citizens and politicians, and highly emotionalised public discourses on crime and justice. But how can we best make sense of these developments? Do we need to create "emotionally intelligent" justice systems, or are we messing recklessly with the rational foundations of liberal criminal justice? This volume brings together leading criminologists and sociologists from across the world in a much needed conversation about how to re-calibrate reason and emotion in crime and justice today. The contributions range from the micro-analysis of emotions in violent encounters to the paradoxes and tensions that arise from the emotionalisation of criminal justice in the public sphere. They explore the emotional labour of workers in police and penal institutions, the justice experiences of victims and offenders, and the role of vengeance, forgiveness and regret in the aftermath of violence and conflict resolution. The result is a set of original essays which offer a fresh and timely perspective on problems of crime and justice in contemporary liberal democracies.

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With the development of enterprise informatisation, Product Lifecycle Management (PLM) systems have been widely deployed and applied in enterprises. This paper analyzes the requirement that conducting version operations on business objects as specified in process models should be compliant with the versioning policies imposed by product lifecycles. This leads to the introduction of the concept of versioning compliance, and the approach of compliance checking that we proposed in our earlier work, which comprises both syntactical compatibility and behavioural compatibility checking. The paper then focuses on the tool implementation for providing automated support to the versioning compliance checking. An empirical evaluation of the tool was also performed with industrial partners using the well-known questionnaire-based method. The evaluation and feedback from practitioners further evidence the practical significance of this research question in the PLM field and demonstrate that the proposed solution with its automated tool support possesses a high application potential.