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The terrestrial biosphere is a key regulator of atmospheric chemistry and climate. During past periods of climate change, vegetation cover and interactions between the terrestrial biosphere and atmosphere changed within decades. Modern observations show a similar responsiveness of terrestrial biogeochemistry to anthropogenically forced climate change and air pollution. Although interactions betwee
A new parameterization of sticking efficiency for aggregation of ice crystals onto snow and graupel is presented. This parameter plays a crucial role for the formation of ice precipitation and for electrification processes. The parameterization is intended to be used in atmospheric models simulating the aggregation of ice particles in glaciated clouds. It should improve the ability to forecast sno
Resource reservation is a technique that allows isolating applications from interfering among each other. In the most classic setting, this method requires the periodic allocation of a given budget of resource over time. However, in reality, the actual budget allocation may deviate from its ideal value. Examples of causes of this deviation are: the presence of a system tick, the usage of shared re
Accurate modelling of long-term changes in plant stomatal functioning is vital to global climate change studies because changes in evapotranspiration influence temperature via physiological forcing of the climate. Various stomatal models are included in land surface schemes, but their robustness over longer timescales is difficult to validate. We compare the performance of three stomatal models, v
In this theoretical paper we consider the problem of accurately triangulating a scene plane. Rather than first triangulating a set of points and then fitting a plane to these points, we try to minimize the back-projection errors as functions of the plane parameters directly. As this is both geometrically and statistically meaningful our method performs better than the standard two step procedure.
Stochastic optimal power flow can provide the system operator with adequate strategies for controlling the power flow to maintain secure operation under stochastic parameter variations. One limitation of stochastic optimal power flow has been that only steady-state variable limits have been used as security constraints. In many systems voltage stability and small-signal stability also play an impo
Precision agriculture requires detailed crop status information at high spatial and temporal resolutions. Remote sensing can provide such information, but single sensor observations are often incapable of meeting all data requirements. Spectral-temporal response surfaces (STRSs) provide continuous reflectance spectra at high temporal intervals. This is the first study to combine multispectral sate
The rate of constitutive isoprenoid emissions from plants is driven by plant emission capacity under specified environmental conditions (E-S, the emission factor) and by responsiveness of the emissions to instantaneous variations in environment. In models of isoprenoid emission, E-S has been often considered as intrinsic species-specific constant invariable in time and space. Here we analyze the v
Nowadays, the same piece of code should run on different architectures, providing performance guarantees in a variety of environments and situations. To this end, designers often integrate existing systems with ad-hoc adaptive strategies able to tune specific parameters that impact performance or energy—for example, frequency scaling. However, these strategies interfere with one another and unpred
This work presents an event-based control structure using the generalized predictive control (GPC) algorithm with actuator deadband. The main objective of this work is to limit the number of controlled system updates. In this approach, the controlled process is sampled with a constant sampling time and is updated in an asynchronous way that depends on the obtained control signal value. To achieve
Gradient orientations are a common feature used in many computer vision algorithms. It is a good feature when the gradient magnitudes are high, but can be very noisy when the magnitudes are low. This means that some gradient orientations are matched with more confidence than others. By estimating this uncertainty, more weight can be put on the confident matches than those with higher uncertainty.
We analyze reinforcement learning under so-called "dynamic reinforcement." In reinforcement learning, each agent repeatedly interacts with an unknown environment (i.e., other agents), receives a reward, and updates the probabilities of its next action based on its own previous actions and received rewards. Unlike standard reinforcement learning, dynamic reinforcement uses a combination of long-ter
One of the most challenging problems in paleoclimate research is how orbital cyclicities forced Earth’s climate variations during the late Quaternary. To address this issue, we investigated the differences in silicate weathering, a sensitive climate indicator, at different latitudes on orbital timescales by examining geochemical and clay mineral data from the mid-latitude Sea of Okhotsk and integr
In this paper, we present a framework to identify discrete-time, single-input/single-output, switched linear systems (SISO-SLSs) from input–output data measurements. Continuous state is not assumed to be measured. The key step is a deadbeat observer-based transformation of the SLS model to a switched auto-regressive with exogenous input (SARX) model. Discrete states are estimated by a three-stage
In embedded systems, the computing resources are often scarce and several control tasks may have to share the same computer. In this brief, we assume that a set of feedback controllers should be implemented on a single-CPU platform. We study the problem of optimal sampling period assignment, where the goal is to assign sampling rates to the controllers so that the overall control performance is ma
The cluster power is an important parameter for cluster-based wireless channel models. This paper addresses modeling and estimation of the cluster power for wireless channels. A novel way of estimating the cluster decay and cluster fading, where the effects of the noise floor is taken into account, is presented. Due to the noise floor present in the measurement, only a limited number of clusters a
Recent papers have proposed to design scheduling algorithms entirely as discrete-time controllers, i.e., to refrain from preserving the already installed scheduler, and replace it completely. At the cost of some system re-design impact, this new approach has been proved to yield significant advantages in terms of code size and simplicity, and above all to open the way to a system-theoretical analy
Mobile robots and robotic manipulators have traditionally been used separately performing different types of tasks. For example, industrial robots have typically been programmed to follow trajectories using position sensors. If combining the two types of robots and adding sensors new possibilities emerge. This enables new applications, but it also raises the question of how to combine the sensors
Execution trace graph analysis of dataflow programs has been demonstrated to be an effective way for exploring and optimizing the design space of many core applications. In this work a novel transformation from the execution trace graph to an event driven linear system is proposed. It is also illustrated how the trace space of can be effectively reduced and well known system control techniques can
