99 resultados para fault handling


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In the form of an installation, this panel will question the problems of combining the fleshiness of our bodies and the technologies of (re-)presentation in the production of knowledge that is contemporary teaching in a material environment. Do the aesthetics and methods of the performing arts open up new, dynamic approaches towards teaching practices? Conversely, how do traditional approaches to classroom management and learning undermine the performativity of our disciplinary concerns? We wish to challenge in the strongest possible terms the appropriateness of the traditional format for academic conferences with their monologic presentation of research outcomes. We crave new and unimagined formats for conferences that rely upon the very theatrical devices that we study, master, enact, and live through. This installation will express each participant's response to these provocations and will provide an interactive environment with many dialogic elements. Participants will use video images, live performers, and other theatrical devices to create an installation that deconstructs the experience of teaching. Signalling though the flames, should our teaching be any less?

The installation will be available for perusal as five simultaneous events occur in over-lapping space. This will last approximately 45 minutes and will be followed by a round-table discussion for the remainder of our time.

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The development of fault-tolerant computing systems is a very difficult task. Two reasons contributed to this difficulty can be described as follows. The First is that, in normal practice, fault-tolerant computing policies and mechanisms are deeply embedded into most application programs, so that these application programs cannot cope with changes in environments, policies and mechanisms. These factors may change frequently in a distributed environment, especially in a heterogeneous environment. Therefore, in order to develop better fault-tolerant systems that can cope with constant changes in environments and user requirements, it is essential to separate the fault tolerant computing policies and mechanisms in application programs. The second is, on the other hand, a number of techniques have been proposed for the construction of reliable and fault-tolerant computing systems. Many computer systems are being developed to tolerant various hardware and software failures. However, most of these systems are to be used in specific application areas, since it is extremely difficult to develop systems that can be used in general-purpose fault-tolerant computing. The motivation of this thesis is based on these two aspects. The focus of the thesis is on developing a model based on the reactive system concepts for building better fault-tolerant computing applications. The reactive system concepts are an attractive paradigm for system design, development and maintenance because it separates policies from mechanisms. The stress of the model is to provide flexible system architecture for the general-purpose fault-tolerant application development, and the model can be applied in many specific applications. With this reactive system model, we can separate fault-tolerant computing polices and mechanisms in the applications, so that the development and maintenance of fault-tolerant computing systems can be made easier.

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This study contributes to work in baggage handling system (BHS) control, specifically dynamic bag routing. Although studies in BHS agent-based control have examined the need for intelligent control, but there has not been an effort to explore the dynamic routing problem. As such, this study provides additional insight into how agents can learn to route in a BHS. This study describes a BHS status-based routing algorithm that applies learning methods to select criteria based on routing decisions. Although numerous studies have identified the need for dynamic routing, little analytic attention has been paid to intelligent agents for learning routing tables rather than manual creation of routing rules. We address this issue by demonstrating the ability of agents to learn how to route based on bag status, a robust method that is able to function in a variety of different BHS designs.

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Scheduling check-in station operations are a challenging problem within airport systems. Prior to determining check-in resource schedules, an important step is to estimate the Baggage Handling System (BHS) operating capacity under non-stationary conditions. This ensures that check-in stations are not overloaded with bags, which would adversely affect the system and cause cascade stops and blockages. Cascading blockages can potentially lead to a poor level of service and in worst scenario a customer may depart without their bags. This paper presents an empirical study of a multiobjective problem within a BHS system. The goal is to estimate near optimal input operating conditions, such that no blockages occurs at check-in stations, while minimising the baggage travel time and maximising the throughput performance measures. We provide a practical hybrid simulation and binary search technique to determine a near optimal input throughput operating condition. The algorithm generates capacity constraint information that may be used by a scheduler to plan check-in operations based on flight arrival schedules.

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The provision of fault tolerance is an important aspect to the success of distributed and cluster computing. Through this research , a transparent, autonomic and efficient fault tolerant facility was designed and implemented; thereby relieving the burden of a user having to handle and react to the failure of an application.

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The topic of systems of systems has been one of the most challenging areas in science and engineering due to its multidisciplinary scope and inherent complexity. Despite all attempts carried out so far in both academia and industry, real world applications are far remote. The purpose of this paper is to modify and adopt a recently developed modeling paradigm for system of systems and then employ it to model a generic baggage handling system of an airport complex. In a top-down design approach, we start modeling process by definition of some modeling goals that guide us in selection of some high level attributes. Then functional attributes are defined which act as ties between high level attributes (the first level of abstraction) and low level metrics/measurements. Since the most challenging issues in developing models for system of systems are identification and representation of dependencies amongst constituent entities, a machine learning technique is adopted for addressing these issues.

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In this study, we develop some deterministic metamodels to quickly and precisely predict the future of a technically complex system. The underlying system is essentially a stochastic, discrete event simulation model of a big baggage handling system. The highly detailed simulation model of this is used for conducting some experiments and logging data which are then used for training artificial neural network metamodels. Demonstrated results show that the developed metamodels are well able to predict different performance measures related to the travel time of bags within this system. In contrast to the simulation models which are computationally expensive and expertise extensive to be developed, run, and maintained, the artificial neural network metamodels could serve as real time decision aiding tools which are considerably fast, precise, simple to use, and reliable.

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System monitoring and fault diagnosis capabilities are the most important aspects in improving safety and reliability of automatic control systems. This research proposed new methodologies on fault diagnosis and estimation for complex uncertain systems. As a result of this research, complex industrial plants can now be more effectively controlled.

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Fault tolerance of robotic manipulators is determined based on the fault tolerance measures. In this study a Jacobian of a 7DOF optimal fault tolerant manipulator is designed based on optimality of worse case relative manipulability and worse case dexterity from geometric perspective instead of numerical solution of constrained optimisation problem or construction of optimal Jacobean through a desired null space. The proposed Jacobean matrix is optimal and equally fault tolerant for a single joint failure within any joint of the manipulators.

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Fault tolerant manipulators maintain their trajectory even if their joint/s fails. Assuming that the manipulator is fault tolerant on its trajectory, fault tolerant compliance manipulators provide required force at their end-effector even when a joint fails. To achieve this, the contributions of the faulty joints for the force of the end-effector are required to be mapped into the proper compensating joint torques of the healthy joints to maintain the force. This paper addresses the optimal mapping to minimize the force jump due to a fault, which is the maximum effort to maintain the force when a fault occurs. The paper studies the locked joint fault/s of the redundant manipulators and it relates the force jump at the end-effector to the faults within the joints. Adding on a previous study to maintain the trajectory, in here the objective is to providing fault tolerant force at the end-effector of the redundant manipulators. This optimal mapping with minimum force jump is presented using matrix perturbation model. And the force jump is calculated through this model for single and multiple joints fault. The proposed optimal mapping is used in different fault scenarios for a 5-DOF manipulator; also it is deployed to compensate the force at the end-effector for the 5-DOF manipulator through simulation study and the results are presented.