132 resultados para Partial feedback linearisation


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We have obtained H$\alpha$ high spatial and time resolution observations of the upper solar chromosphere and supplemented these with multi-wavelength observations from the Solar Dynamic Observatory (SDO) and the {\it Hinode} ExtremeUltraviolet Imaging Spectrometer (EIS). The H$\alpha$ observations were conducted on 11 February 2012 with the Hydrogen-Alpha Rapid Dynamics Camera (HARDcam) instrument at the National Solar Observatory's Dunn Solar Telescope. Our H$\alpha$ observations found large downflows of chromospheric material returning from coronal heights following a failed prominence eruption. We have detected several large condensations ("blobs") returning to the solar surface at velocities of $\approx$200 km s$^{-1}$ in both H$\alpha$ and several SDO AIA band passes. The average derived size of these "blobs" in H$\alpha$ is 500 by 3000 km$^2$ in the directions perpendicular and parallel to the direction of travel, respectively. A comparison of our "blob" widths to those found from coronal rain, indicate there are additional smaller, unresolved "blobs" in agreement with previous studies and recent numerical simulations. Our observed velocities and decelerations of the "blobs" in both H$\alpha$ and SDO bands are less than those expected for gravitational free-fall and imply additional magnetic or gas pressure impeding the flow. We derived a kinetic energy $\approx$2 orders of magnitude lower for the main eruption than a typical CME, which may explain its partial nature.

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Belief revision performs belief change on an agent’s beliefs when new evidence (either of the form of a propositional formula or of the form of a total pre-order on a set of interpretations) is received. Jeffrey’s rule is commonly used for revising probabilistic epistemic states when new information is probabilistically uncertain. In this paper, we propose a general epistemic revision framework where new evidence is of the form of a partial epistemic state. Our framework extends Jeffrey’s rule with uncertain inputs and covers well-known existing frameworks such as ordinal conditional function (OCF) or possibility theory. We then define a set of postulates that such revision operators shall satisfy and establish representation theorems to characterize those postulates. We show that these postulates reveal common characteristics of various existing revision strategies and are satisfied by OCF conditionalization, Jeffrey’s rule of conditioning and possibility conditionalization. Furthermore, when reducing to the belief revision situation, our postulates can induce Darwiche and Pearl’s postulates C1 and C2.

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Belief revision studies strategies about how agents revise their belief states when receiving new evidence. Both in classical belief revision and in epistemic revision, a new input is either in the form of a (weighted) propositional formula or a total
pre-order (where the total pre-order is considered as a whole).
However, in some real-world applications, a new input can be a partial pre-order where each unit that constitutes the partial pre-order is important and should be considered individually. To address this issue, in this paper, we study how a partial preorder representing the prior epistemic state can be revised by another partial pre-order (the new input) from a different perspective, where the revision is conducted recursively on the individual units of partial pre-orders. We propose different revision operators (rules), dubbed the extension, match, inner and outer revision operators, from different revision points of view. We also analyze several properties for these operators.

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Belief revision is the process that incorporates, in a consistent way,
a new piece of information, called input, into a belief base. When both belief
bases and inputs are propositional formulas, a set of natural and rational properties, known as AGM postulates, have been proposed to define genuine revision operations. This paper addresses the following important issue : How to revise a partially pre-ordered information (representing initial beliefs) with a new partially pre-ordered information (representing inputs) while preserving AGM postulates? We first provide a particular representation of partial pre-orders (called units) using the concept of closed sets of units. Then we restate AGM postulates in this framework by defining counterparts of the notions of logical entailment and logical consistency. In the second part of the paper, we provide some examples of revision operations that respect our set of postulates. We also prove that our revision methods extend well-known lexicographic revision and natural revision for both cases where the input is either a single propositional formula or a total pre-order.

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Differential equations are often directly solvable by analytical means only in their one dimensional version. Partial differential equations are generally not solvable by analytical means in two and three dimensions, with the exception of few special cases. In all other cases, numerical approximation methods need to be utilized. One of the most popular methods is the finite element method. The main areas of focus, here, are the Poisson heat equation and the plate bending equation. The purpose of this paper is to provide a quick walkthrough of the various approaches that the authors followed in pursuit of creating optimal solvers, accelerated with the use of graphical processing units, and comparing them in terms of accuracy and time efficiency with existing or self-made non-accelerated solvers.

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In this paper, we investigate an amplify-and-forward (AF) multiple-input multiple-output - spatial division multiplexing (MIMO-SDM) cooperative wireless networks, where each network node is equipped with multiple antennas. In order to deal with the problems of signal combining at the destination and cooperative relay selection, we propose an improved minimum mean square error (MMSE) signal combining scheme for signal recovery at the destination. Additionally, we propose two distributed relay selection algorithms based on the minimum mean squared error (MSE) of the signal estimation for the cases where channel state information (CSI) from the source to the destination is available and unavailable at the candidate nodes. Simulation results demonstrate that the proposed combiner together with the proposed relay selection algorithms achieve higher diversity gain than previous approaches in both flat and frequency-selective fading channels.

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Timely and individualized feedback on coursework is desirable from a student perspective as it facilitates formative development and encourages reflective learning practice. Faculty however are faced with a significant and potentially time consuming challenge when teaching larger cohorts if they are to provide feedback which is timely, individualized and detailed. Additionally, for subjects which assess non-traditional submissions, such as Computer-Aided-Design (CAD), the methods for assessment and feedback tend not to be so well developed or optimized. Issues can also arise over the consistency of the feedback provided. Evaluations of Computer-Assisted feedback in other disciplines (Denton et al, 2008), (Croft et al, 2001) have shown students prefer this method of feedback to traditional “red pen” marking and also that such methods can be more time efficient for faculty.
Herein, approaches are described which make use of technology and additional software tools to speed up, simplify and automate assessment and the provision of feedback for large cohorts of first and second year engineering students studying modules where CAD files are submitted electronically. A range of automated methods are described and compared with more “manual” approaches. Specifically one method uses an application programming interface (API) to interrogate SolidWorks models and extract information into an Excel spreadsheet, which is then used to automatically send feedback emails. Another method describes the use of audio recordings made during model interrogation which reduces the amount of time while increasing the level of detail provided as feedback.
Limitations found with these methods and problems encountered are discussed along with a quantified assessment of time saving efficiencies made.

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Necessary and sufficient conditions for choice functions to be rational have been intensively studied in the past. However, in these attempts, a choice function is completely specified. That is, given any subset of options, called an issue, the best option over that issue is always known, whilst in real-world scenarios, it is very often that only a few choices are known instead of all. In this paper, we study partial choice functions and investigate necessary and sufficient rationality conditions for situations where only a few choices are known. We prove that our necessary and sufficient condition for partial choice functions boils down to the necessary and sufficient conditions for complete choice functions proposed in the literature. Choice functions have been instrumental in belief revision theory. That is, in most approaches to belief revision, the problem studied can simply be described as the choice of possible worlds compatible with the input information, given an agent’s prior belief state. The main effort has been to devise strategies in order to infer the agents revised belief state. Our study considers the converse problem: given a collection of input information items and their corresponding revision results (as provided by an agent), does there exist a rational revision operation used by the agent and a consistent belief state that may explain the observed results?

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In recent years, sonification of movement has emerged as a viable method for the provision of feedback in motor learning. Despite some experimental validation of its utility, controlled trials to test the usefulness of sonification in a motor learning context are still rare. As such, there are no accepted conventions for dealing with its implementation. This article addresses the question of how continuous movement information should be best presented as sound to be fed back to the learner. It is proposed that to establish effective approaches to using sonification in this context, consideration must be given to the processes that underlie motor learning, in particular the nature of the perceptual information available to the learner for performing the task at hand. Although sonification has much potential in movement performance enhancement, this potential is largely unrealised as of yet, in part due to the lack of a clear framework for sonification mapping: the relationship between movement and sound. By grounding mapping decisions in a firmer understanding of how perceptual information guides learning, and an embodied cognition stance in general, it is hoped that greater advances in use of sonification to enhance motor learning can be achieved.

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We present the Pan-STARRS1 discovery of the long-lived and blue transient PS1-11af, which was also detected by Galaxy Evolution Explorer with coordinated observations in the near-ultraviolet (NUV) band. PS1-11af is associated with the nucleus of an early type galaxy at redshift z = 0.4046 that exhibits no evidence for star formation or active galactic nucleus activity. Four epochs of spectroscopy reveal a pair of transient broad absorption features in the UV on otherwise featureless spectra. Despite the superficial similarity of these features to P-Cygni absorptions of supernovae (SNe), we conclude that PS1-11af is not consistent with the properties of known types of SNe. Blackbody fits to the spectral energy distribution are inconsistent with the cooling, expanding ejecta of a SN, and the velocities of the absorption features are too high to represent material in homologous expansion near a SN photosphere. However, the constant blue colors and slow evolution of the luminosity are similar to previous optically selected tidal disruption events (TDEs). The shape of the optical light curve is consistent with models for TDEs, but the minimum accreted mass necessary to power the observed luminosity is only 0.002 M, which points to a partial disruption model. A full disruption model predicts higher bolometric luminosities, which would require most of the radiation to be emitted in a separate component at high energies where we lack observations. In addition, the observed temperature is lower than that predicted by pure accretion disk models for TDEs and requires reprocessing to a constant, lower temperature. Three deep non-detections in the radio with the Very Large Array over the first two years after the event set strict limits on the production of any relativistic outflow comparable to Swift J1644+57, even if off-axis.