612 resultados para fault tolerant control


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The detection and correction of defects remains among the most time consuming and expensive aspects of software development. Extensive automated testing and code inspections may mitigate their effect, but some code fragments are necessarily more likely to be faulty than others, and automated identification of fault prone modules helps to focus testing and inspections, thus limiting wasted effort and potentially improving detection rates. However, software metrics data is often extremely noisy, with enormous imbalances in the size of the positive and negative classes. In this work, we present a new approach to predictive modelling of fault proneness in software modules, introducing a new feature representation to overcome some of these issues. This rank sum representation offers improved or at worst comparable performance to earlier approaches for standard data sets, and readily allows the user to choose an appropriate trade-off between precision and recall to optimise inspection effort to suit different testing environments. The method is evaluated using the NASA Metrics Data Program (MDP) data sets, and performance is compared with existing studies based on the Support Vector Machine (SVM) and Naïve Bayes (NB) Classifiers, and with our own comprehensive evaluation of these methods.

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Background: Health policy, guidelines, and standards advocate giving patients comprehensive information and facilitating their involvement in health-related decision-making. Routine assessment of patient reports of these processes is needed. Our objective was to examine decision-making processes, specifically information provision and consumer involvement in decision-making, for nine pregnancy, labour, and birth procedures, as reported by maternity care consumers in Queensland, Australia. Methods: Participants were women who had a live birth in Queensland in a specified time period and were not found to have had a baby that died since birth, who completed the extended Having a Baby in Queensland Survey, 2010 about their maternity care experiences, and who reported at least one of the nine procedures of interest. For each procedure, women answered two questions that measured perceived (i) receipt of information about the benefits and risks of the procedure and (ii) role in decision-making about the procedure. Results: In all, 3,542 eligible women (34.2%) completed the survey. Between 4% (for pre-labour caesarean section) and 60% (for vaginal examination) of women reported not being informed of the benefits and risks of the procedure they experienced. Between 2% (epidural) and 34% (episiotomy) of women reported being unconsulted in decision-making. Over one quarter (26%) of the women who experienced episiotomy reported being neither informed nor consulted. Conclusions: There is an urgent need for interventions that facilitate information provision and consumer involvement in decision-making about several perinatal procedures, especially those performed within the time-limited intrapartum care episode.

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In this paper, a model-predictive control (MPC) method is detailed for the control of nonlinear systems with stability considerations. It will be assumed that the plant is described by a local input/output ARX-type model, with the control potentially included in the premise variables, which enables the control of systems that are nonlinear in both the state and control input. Additionally, for the case of set point regulation, a suboptimal controller is derived which has the dual purpose of ensuring stability and enabling finite-iteration termination of the iterative procedure used to solve the nonlinear optimization problem that is used to determine the control signal.

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This paper proposes an approach to achieve resilient navigation for indoor mobile robots. Resilient navigation seeks to mitigate the impact of control, localisation, or map errors on the safety of the platform while enforcing the robot’s ability to achieve its goal. We show that resilience to unpredictable errors can be achieved by combining the benefits of independent and complementary algorithmic approaches to navigation, or modalities, each tuned to a particular type of environment or situation. In this paper, the modalities comprise a path planning method and a reactive motion strategy. While the robot navigates, a Hidden Markov Model continually estimates the most appropriate modality based on two types of information: context (information known a priori) and monitoring (evaluating unpredictable aspects of the current situation). The robot then uses the recommended modality, switching between one and another dynamically. Experimental validation with a SegwayRMP- based platform in an office environment shows that our approach enables failure mitigation while maintaining the safety of the platform. The robot is shown to reach its goal in the presence of: 1) unpredicted control errors, 2) unexpected map errors and 3) a large injected localisation fault.

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Considering the wide spectrum of situations that it may encounter, a robot navigating autonomously in outdoor environments needs to be endowed with several operating modes, for robustness and efficiency reasons. Indeed, the terrain it has to traverse may be composed of flat or rough areas, low cohesive soils such as sand dunes, concrete road etc. . .Traversing these various kinds of environment calls for different navigation and/or locomotion functionalities, especially if the robot is endowed with different locomotion abilities, such as the robots WorkPartner, Hylos [4], Nomad or the Marsokhod rovers. Numerous rover navigation techniques have been proposed, each of them being suited to a particular environment context (e.g. path following, obstacle avoidance in more or less cluttered environments, rough terrain traverses...). However, seldom contributions in the literature tackle the problem of selecting autonomously the most suited mode [3]. Most of the existing work is indeed devoted to the passive analysis of a single navigation mode, as in [2]. Fault detection is of course essential: one can imagine that a proper monitoring of the Mars Exploration Rover Opportunity could have avoided the rover to be stuck during several weeks in a dune, by detecting non-nominal behavior of some parameters. But the ability to recover the anticipated problem by switching to a better suited navigation mode would bring higher autonomy abilities, and therefore a better overall efficiency. We propose here a probabilistic framework to achieve this, which fuses environment related and robot related information in order to actively control the rover operations.

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Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This model is used to construct a control policy for navigation to a goal region in a terrain map built using an on-board RGB-D camera. The terrain includes flat ground, small rocks, and non-traversable rocks. We report the results of 200 simulated and 35 experimental trials that validate the approach and demonstrate the value of considering control uncertainty in maintaining platform safety.

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This article presents an approach to improve and monitor the behavior of a skid-steering rover on rough terrains. An adaptive locomotion control generates speeds references to avoid slipping situations. An enhanced odometry provides a better estimation of the distance travelled. A probabilistic classification procedure provides an evaluation of the locomotion efficiency on-line, with a detection of locomotion faults. Results obtained with a Marsokhod rover are presented throughout the paper

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Purpose Patient-reported symptoms and health-related quality of life (QoL) benefits were investigated in a randomized, phase III trial of afatinib or cisplatin/pemetrexed. Patients and Methods Three hundred forty-five patients with advanced epidermal growth factor receptor (EGFR) mutation-positive lung adenocarcinoma were randomly assigned 2:1 to afatinib 40 mg per day or up to six cycles of cisplatin/pemetrexed. Lung cancer symptoms and health-related QoL were assessed every 21 days until progression using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 and Lung Cancer-13 questionnaires. Analyses of cough, dyspnea, and pain were preplanned, including percentage of patients who improved on therapy, time to deterioration of symptoms, and change in symptoms over time. Results Questionnaire compliance was high. Compared with chemotherapy, afatinib significantly delayed the time to deterioration for cough (hazard ratio [HR], 0.60; 95% CI, 0.41 to 0.87; P = .007) and dyspnea (HR, 0.68; 95% CI, 0.50 to 0.93; P = .015), but not pain (HR, 0.83; 95% CI, 0.62 to 1.10; P = .19). More patients on afatinib (64%) versus chemotherapy (50%) experienced improvements in dyspnea scores (P lt; .010). Differences in mean scores over time significantly favored afatinib over chemotherapy for cough (P lt; .001) and dyspnea (P = .001). Afatinib showed significantly better mean scores over time in global health status/QoL (P = .015) and physical (P = .001), role (P = .004), and cognitive (P lt; .007) functioning compared with chemotherapy. Fatigue and nausea were worse with chemotherapy, whereas diarrhea, dysphagia, and sore mouth were worse with afatinib (all P = .01). Conclusion In patients with lung adenocarcinoma with EGFR mutations, first-line afatinib was associated with better control of cough and dyspnea compared with chemotherapy, although diarrhea, dysphagia, and sore mouth were worse. Global health status/QoL was also improved over time with afatinib compared with chemotherapy.

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Wireless networked control systems (WNCSs) have been increasingly deployed in industrial applications. As they require timely data packet transmissions, it is difficult to make efficient use of the limited channel resources, particularly in contention based wireless networks in the layered network architecture. Aiming to maintain the WNCSs under critical real-time traffic condition at which the WNCSs marginally meet the real-time requirements, a cross-layer design (CLD) approach is presented in this paper to adaptively adjust the control period to achieve improved channel utilization while still maintaining effective and timely packet transmissions. The effectiveness of the proposed approach is demonstrated through simulation studies.

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Mosquito-borne diseases pose some of the greatest challenges in public health, especially in tropical and sub-tropical regions of theworld. Efforts to control these diseases have been underpinned by a theoretical framework developed for malaria by Ross and Macdonald, including models, metrics for measuring transmission, and theory of control that identifies key vulnerabilities in the transmission cycle. That framework, especially Macdonald’s formula for R0 and its entomological derivative, vectorial capacity, are nowused to study dynamics and design interventions for many mosquito-borne diseases. A systematic review of 388 models published between 1970 and 2010 found that the vast majority adopted the Ross–Macdonald assumption of homogeneous transmission in a well-mixed population. Studies comparing models and data question these assumptions and point to the capacity to model heterogeneous, focal transmission as the most important but relatively unexplored component in current theory. Fine-scale heterogeneity causes transmission dynamics to be nonlinear, and poses problems for modeling, epidemiology and measurement. Novel mathematical approaches show how heterogeneity arises from the biology and the landscape on which the processes of mosquito biting and pathogen transmission unfold. Emerging theory focuses attention on the ecological and social context formosquito blood feeding, themovement of both hosts and mosquitoes, and the relevant spatial scales for measuring transmission and for modeling dynamics and control.

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Aim To test the efficacy of Medilixir [cream] against the standard treatment of aqueous cream in the provision of relief from the symptoms of postburn itch. Design RCT with two parallel arms. Setting Professor Stuart Pegg Adult Burns Centre, Royal Brisbane and Women's Hospital, Brisbane, Australia. Participants Fifty-two patients aged between 18 and 80 years, admitted directly to the burns centre between 10 March and 22 July 2008, were able to provide informed consent, and had shown no allergic reaction to a patch test with the study medication, were randomised. Patients admitted from intensive care or high dependency were excluded. Main results Effect estimates and confidence intervals were not reported for any of the outcomes; only group means/proportions and P-values from hypothesis testing were provided. More patients in the intervention group reported itch reduction compared to comparison treatment (91 vs. 82%, P=0.001). Itch recurrence after cream application occurred later in the intervention group compared to the control group (P<0.001). Use of antipruritic medication was significantly greater in the control group (P=0.023). There was no difference in sleep disturbance between groups (not quantified). On average, Medilixir took longer to apply than aqueous cream (157s for Medilixir vs. 139s for aqueous cream; mean difference 17s), but authors noted that the groups did not differ significantly (CI for mean difference and P-values were not reported).

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A microgrid may contain a large number of distributed generators (DGs). These DGs can be either inertial or non-inertial, either dispatchable or non-dispatchable. Moreover, the DGs may operate in plug and play fashion. The combination of these various types of operation makes the microgrid control a challenging task, especially when the microgrid operates in an autonomous mode. In this paper, a new control algorithm for converter interfaced (dispatchable) DG is proposed which facilitates smooth operation in a hybrid microgrid containing inertial and non-inertial DGs. The control algorithm works satisfactorily even when some of the DGs operate in plug and play mode. The proposed strategy is validated through PSCAD simulation studies.

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This paper presents a distributed communication based active power curtailment (APC) control scheme for grid connected photovoltaic (PV) systems to address voltage rise. A simple distribution feeder model is presented and simulated using MATLAB. The resource sharing based control scheme proposed is shown to be effective at reducing voltage rise during times of peak generation and low load. Simulations also show the even distribution of APC using simple communications. Simulations demonstrate the versatility of the proposed control method under major communication failure conditions. Further research may lead to possible applications in coordinated electric vehicle (EV) charging.

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Public engagement is a defining feature of collaborative approaches to environmental management (Petts 2006, Whelan and Oliver 2005). Public engagement in this context is focused on incorporating residents and communities of interest in activities like ecological restoration, catchment management, and environmental conservation in a wide range of situations (Nelson and Pettit 2004, Petts 2007). Some authors consider public engagement to be a sign of healthy democratic functioning in society (Skocpol and Fiorina 1999). Others draw attention to overcoming widely noted practical limitations of top-down mechanisms, emphasising that public engagement results in programs being implemented more effectively (Broderick 2005, Leach et al. 1999).

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This paper proposes a new method for stabilizing disturbed power systems using wide area measurement and FACTS devices. The approach focuses on both first swing and damping stability of power systems following large disturbances. A two step control algorithm based on Lyapunov Theorem is proposed to be applied on the controllers to improve the power systems stability. The proposed approach is simulated on two test systems and the results show significant improvement in the first swing and damping stability of the test systems.