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Design of an Intermediate Layer to Enhance Operator Awareness and Safety in Telesurgical Systems

This paper presents a novel control architecture for enhanced operator awareness and improved safety in telesurgical systems. We introduce an intermediate layer between the master and slave sides which allows us to modify the slave motion for safety and the force feedback for operator awareness. The intermediate layer is then designed with a performance objective for the specific task at hand. The

Evaluation of 11 terrestrial carbon-nitrogen cycle models against observations from two temperate Free-Air CO2 Enrichment studies

We analysed the responses of 11 ecosystem models to elevated atmospheric [CO2] (eCO(2)) at two temperate forest ecosystems (Duke and Oak Ridge National Laboratory (ORNL) Free-Air CO2 Enrichment (FACE) experiments) to test alternative representations of carbon (C)-nitrogen (N) cycle processes. We decomposed the model responses into component processes affecting the response to eCO(2) and confronted

Parameter Selection for Real-Time Controllers in Resource-Constrained Systems

Inresource-constrained systems, the interference generated by the concurrent execution of multiple controller tasks leads to extra delay and jitter, which degrade control performance and may even jeopardize the stability of the controlled system. This work presents a general methodology that integrates control issues and real-time schedulability analysis to improve the control performance in embed

Continuous-Tme Interval Model Identification of Blood Glucose Dynamics for Type 1 Diabetes

While good physiological models of the glucose metabolism in type 1 diabetic patients are well known, their parameterisation is difficult. The high intra-patient variability observed is a further major obstacle. This holds for data-based models too, so that no good patient-specific models are available. Against this background, this paper proposes the use of interval models to cover the different

Rao-Blackwellized Particle Filters with Out-of-Sequence Measurement Processing

This paper addresses the out-of-sequence measurement (OOSM) problem for mixed linear/nonlinear state-space models, which is a class of nonlinear models with a tractable, conditionally linear substructure. We develop two novel algorithms that utilize the linear substructure. The first algorithm effectively employs the Rao-Blackwellized particle filtering framework for updating with the OOSMs, and i

Comparison of Decision Making Strategies for Self-Optimization in Autonomic Computing Systems

Autonomic computing systems are capable of adapting their behavior and resources thousands of times a second to automatically decide the best way to accomplish a given goal despite changing environmental conditions and demands. Different decision mechanisms are considered in the literature, but in the vast majority of the cases a single technique is applied to a given instance of the problem. This

Trend analysis for rainfall in Delhi and Mumbai, India

Urbanisation has burdened cities with many problems associated with growth and the physical environment. Some of the urban locations in India are becoming increasingly vulnerable to natural hazards related to precipitation and flooding. Thus it becomes increasingly important to study the characteristics of these events and their physical explanation. This work studies rainfall trends in Delhi and

Multiple access channel with various degrees of asymmetric state Information

We consider the problem of reliable communication over multiple-access channels (MAC) where the channel is driven by an independent and identically distributed state process and the encoders and the decoder are provided with various degrees of asymmetric (noisy or partial) channel state information (CSI). Namely, we provide a single letter characterization for the capacity region when the encoders

Modeling undertow due to random waves

A numerical model of undertow due to random waves is developed. The model includes three sub-models: (i) a model for multi-directional and multi-frequency random wave transformation, (ii) a surface roller evolution model, and (iii) a model for calculating the vertical distribution and the mean value of the undertow velocity. The calculation of wave trough level is performed based on a theory for t

Estimation-based ILC applied to a parallel kinematic robot

Estimation-based iterative learning control (ILC) is applied to a parallel kinematic manipulator known as the Gantry-Tau parallel robot. The system represents a control problem where measurements of the controlled variables are not available. The main idea is to use estimates of the controlled variables in the ILC algorithm, and in the paper this approach is evaluated experimentally on the Gantry-

Theory of Time-Dependent Freezing. Part I: Description of Scheme for Wet Growth of Hail

At subzero temperatures, cloud particles can contain both ice and liquid water fractions. Wet growth of precipitation particles occurs when supercooled cloud liquid is accreted faster than it can freeze on impact. With a flexible framework, the theory of wet growth of hail is extended to the case of the inhomogeneities of surface temperature and of liquid coverage over the surface of the particle.

Optimal Priority Assignment to Control Tasks

In embedded real-time systems, task priorities are often assigned to meet deadlines. However, in control tasks, a late completion of a task has no catastrophic consequence. Rather, it has a quantifiable impact in the control performance achieved by the task. In this paper, we address the problem of determining the optimal assignment of priorities and periods of sampled-data control tasks that run

Weight assignment in regional climate models

An important new development within the European ENSEMBLES project has been to explore performance-based weighting of regional climate models (RCMs). Until now, although no weighting has been applied in multi-RCM analyses, one could claim that an assumption of ‘equal weight’ was implicitly adopted. At the same time, different RCMs generate different results, e.g. for various types of extremes, and

Conjugate Gradient Bundle Adjustment

Bundle adjustment for multi-view reconstruction is traditionally done using the Levenberg-Marquardt algorithm with a direct linear solver, which is computationally very expensive. An alternative to this approach is to apply the conjugate gradients algorithm in the inner loop. Tins is appealing since the main computational step of the CG algorithm involves only a simple matrix-vector multiplication

Derivative backoff: The other saturation problem for PID controllers

tThe PID controller is by far the most common controller, and to ensure good behavior under all circumstances, a PID implementation must consider many practical aspects such as integrator windup,derivative kick, and bumpless parameter and mode changes. In this paper, an entirely new issue for the derivative part is introduced and has been named derivative backoff. It occurs when the process value

Seasonal streamflow forecast: a GCM multi-model downscaling approach

This work investigates the predictability of seasonal to inter-annual streamflow over several river basins in Norway through the use of multi-model ensembles. As general circulation models (GCMs) do not explicitly simulate streamflow, a statistical link is made between GCM-forecast fields generated in December and average streamflow in the melting season May-June. By using the Climate Predictabili

A mathematical model of spit growth and barrier elongation: Application to Fire Island Inlet (USA) and Badreveln Spit (Sweden)

A mathematical model of spit growth and barrier elongation adjacent to an inlet (of arbitrary width), supplied by sediment coming from longshore sediment transport, was developed based on the spit growth model proposed by Kraus (1999). The fundamental governing equation is the conservation equation for sand, where the width of the spit is assumed constant during growth. The portion of the longshor

Force Controlled Robotic Assembly without a Force Sensor

The traditional way of controlling an industrial robot is to program it to follow desired trajectories. This approach is sufficient as long as the accuracy of the robot and the calibration of the workcell is good enough. In robotic assembly these conditions are usually not fulfilled, because of uncertainties, e.g., variability in involved parts and objects not gripped accurately. Using force contr