977 resultados para Kahler metrics


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The introduction of metrics, league tables, performance targets, research assessment exercises and a range of other pressures placed by society, funding bodies and employers on scholars, teachers and students have resulted in diminished value being placed on the essential ethical criterion of truth. The impact of reduced valuation for truth has a huge impact on the standing of science and not least horticultural science in the eyes of the general public at a time when this should be a primary concern. This contribution discusses examples of the impact of diminished valuation of truth, the causes of this phenomenon, the results that come from this situation and remedies that are needed.

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Graphical tracking is a technique for crop scheduling where the actual plant state is plotted against an ideal target curve which encapsulates all crop and environmental characteristics. Management decisions are made on the basis of the position of the actual crop against the ideal position. Due to the simplicity of the approach it is possible for graphical tracks to be developed on site without the requirement for controlled experimentation. Growth models and graphical tracks are discussed, and an implementation of the Richards curve for graphical tracking described. In many cases, the more intuitively desirable growth models perform sub-optimally due to problems with the specification of starting conditions, environmental factors outside the scope of the original model and the introduction of new cultivars. Accurate specification for a biological model requires detailed and usually costly study, and as such is not adaptable to a changing cultivar range and changing cultivation techniques. Fitting of a new graphical track for a new cultivar can be conducted on site and improved over subsequent seasons. Graphical tracking emphasises the current position relative to the objective, and as such does not require the time consuming or system specific input of an environmental history, although it does require detailed crop measurement. The approach is flexible and could be applied to a variety of specification metrics, with digital imaging providing a route for added value. For decision making regarding crop manipulation from the observed current state, there is a role for simple predictive modelling over the short term to indicate the short term consequences of crop manipulation.

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One of the most common decisions we make is the one about where to move our eyes next. Here we examine the impact that processing the evidence supporting competing options has on saccade programming. Participants were asked to saccade to one of two possible visual targets indicated by a cloud of moving dots. We varied the evidence which supported saccade target choice by manipulating the proportion of dots moving towards one target or the other. The task was found to become easier as the evidence supporting target choice increased. This was reflected in an increase in percent correct and a decrease in saccade latency. The trajectory and landing position of saccades were found to deviate away from the non-selected target reflecting the choice of the target and the inhibition of the non-target. The extent of the deviation was found to increase with amount of sensory evidence supporting target choice. This shows that decision-making processes involved in saccade target choice have an impact on the spatial control of a saccade. This would seem to extend the notion of the processes involved in the control of saccade metrics beyond a competition between visual stimuli to one also reflecting a competition between options.

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Inhibition is intimately involved in the ability to select a target for a goal-directed movement. The effect of distracters on the deviation of oculomotor trajectories and landing positions provides evidence of such inhibition. individual saccade trajectories and landing positions may deviate initially either towards, or away from, a competing distracter-the direction and extent of this deviation depends upon saccade latency and the target to distracter separation. However, the underlying commonality of the sources of oculomotor inhibition has not been investigated. Here we report the relationship between distracter-related deviation of saccade trajectory, landing position and saccade latency. Observers saccaded to a target which could be accompanied by a distracter shown at various distances from very close (10 angular degrees) to far away (120 angular degrees). A fixation-gap paradigm was used to manipulate latency independently of the influence of competing distracters. When distracters were close to the target, saccade trajectory and landing position deviated toward the distracter position, while at greater separations landing position was always accurate but trajectories deviated away from the distracters. Different spatial patterns of deviations across latency were found. This pattern of results is consistent with the metrics of the saccade reflecting coarse pooling of the ongoing activity at the distracter location: saccade trajectory reflects activity at saccade initiation while landing position reveals activity at saccade end. (C) 2009 Elsevier B.V. All rights reserved.

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Saccadic eye movements and fixations are the behavioral means by which we visually sample text during reading. Human oculomotor control is governed by a complex neurophysiological system involving the brain stem, superior colliculus, and several cortical areas [1, 2]. A very widely held belief among researchers investigating primate vision is that the oculomotor system serves to orient the visual axes of both eyes to fixate the same target point in space. It is argued that such precise positioning of the eyes is necessary to place images on corresponding retinal locations, such that on each fixation a single, nondiplopic, visual representation is perceived [3]. Vision works actively through a continual sampling process involving saccades and fixations [4]. Here we report that during normal reading, the eyes do not always fixate the same letter within a word. We also demonstrate that saccadic targeting is yoked and based on a unified cyclopean percept of a whole word since it is unaffected if different word parts are delivered exclusively to each eye via a dichoptic presentation technique. These two findings together suggest that the visual signal from each eye is fused at a very early stage in the visual pathway, even when the fixation disparity is greater than one character (0.29 deg), and that saccade metrics for each eye are computed on the basis of that fused signal.

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Frequency recognition is an important task in many engineering fields such as audio signal processing and telecommunications engineering, for example in applications like Dual-Tone Multi-Frequency (DTMF) detection or the recognition of the carrier frequency of a Global Positioning, System (GPS) signal. This paper will present results of investigations on several common Fourier Transform-based frequency recognition algorithms implemented in real time on a Texas Instruments (TI) TMS320C6713 Digital Signal Processor (DSP) core. In addition, suitable metrics are going to be evaluated in order to ascertain which of these selected algorithms is appropriate for audio signal processing(1).

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Single point interaction haptic devices do not provide the natural grasp and manipulations found in the real world, as afforded by multi-fingered haptics. The present study investigates a two-fingered grasp manipulation involving rotation with and without force feedback. There were three visual cue conditions: monocular, binocular and projective lighting. Performance metrics of time and positional accuracy were assessed. The results indicate that adding haptics to an object manipulation task increases the positional accuracy but slightly increases the overall time taken.

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This paper presents a novel two-pass algorithm constituted by Linear Hashtable Motion Estimation Algorithm (LHMEA) and Hexagonal Search (HEXBS). compensation. for block base motion On the basis of research from previous algorithms, especially an on-the-edge motion estimation algorithm called hexagonal search (HEXBS), we propose the LHMEA and the Two-Pass Algorithm (TPA). We introduce hashtable into video compression. In this paper we employ LHMEA for the first-pass search in all the Macroblocks (MB) in the picture. Motion Vectors (MV) are then generated from the first-pass and are used as predictors for second-pass HEXBS motion estimation, which only searches a small number of MBs. The evaluation of the algorithm considers the three important metrics being time, compression rate and PSNR. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms. Experimental results show that the proposed algorithm can offer the same compression rate as the Full Search. LHMEA with TPA has significant improvement on HEXBS and shows a direction for improving other fast motion estimation algorithms, for example Diamond Search.

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This paper presents an improved Two-Pass Hexagonal (TPA) algorithm constituted by Linear Hashtable Motion Estimation Algorithm (LHMEA) and Hexagonal Search (HEXBS) for motion estimation. In the TPA, Motion Vectors (MV) are generated from the first-pass LHMEA and are used as predictors for second-pass HEXBS motion estimation, which only searches a small number of Macroblocks (MBs). The hashtable structure of LHMEA is improved compared to the original TPA and LHMEA. The evaluation of the algorithm considers the three important metrics being processing time, compression rate and PSNR. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms.

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This paper discusses the problems inherent within traditional supply chain management's forecast and inventory management processes arising when tackling demand driven supply chain. A demand driven supply chain management architecture developed by Orchestr8 Ltd., U.K. is described to demonstrate its advantages over traditional supply chain management. Within this architecture, a metrics reporting system is designed by adopting business intelligence technology that supports users for decision making and planning supply activities over supply chain health.

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This paper presents the results of the crowd image analysis challenge, as part of the PETS 2009 workshop. The evaluation is carried out using a selection of the metrics available in the Video Analysis and Content Extraction (VACE) program and the CLassification of Events, Activities, and Relationships (CLEAR) consortium. The evaluation highlights the strengths of the authors’ systems in areas such as precision, accuracy and robustness.

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This work compares classification results of lactose, mandelic acid and dl-mandelic acid, obtained on the basis of their respective THz transients. The performance of three different pre-processing algorithms applied to the time-domain signatures obtained using a THz-transient spectrometer are contrasted by evaluating the classifier performance. A range of amplitudes of zero-mean white Gaussian noise are used to artificially degrade the signal-to-noise ratio of the time-domain signatures to generate the data sets that are presented to the classifier for both learning and validation purposes. This gradual degradation of interferograms by increasing the noise level is equivalent to performing measurements assuming a reduced integration time. Three signal processing algorithms were adopted for the evaluation of the complex insertion loss function of the samples under study; a) standard evaluation by ratioing the sample with the background spectra, b) a subspace identification algorithm and c) a novel wavelet-packet identification procedure. Within class and between class dispersion metrics are adopted for the three data sets. A discrimination metric evaluates how well the three classes can be distinguished within the frequency range 0. 1 - 1.0 THz using the above algorithms.

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Many kernel classifier construction algorithms adopt classification accuracy as performance metrics in model evaluation. Moreover, equal weighting is often applied to each data sample in parameter estimation. These modeling practices often become problematic if the data sets are imbalanced. We present a kernel classifier construction algorithm using orthogonal forward selection (OFS) in order to optimize the model generalization for imbalanced two-class data sets. This kernel classifier identification algorithm is based on a new regularized orthogonal weighted least squares (ROWLS) estimator and the model selection criterion of maximal leave-one-out area under curve (LOO-AUC) of the receiver operating characteristics (ROCs). It is shown that, owing to the orthogonalization procedure, the LOO-AUC can be calculated via an analytic formula based on the new regularized orthogonal weighted least squares parameter estimator, without actually splitting the estimation data set. The proposed algorithm can achieve minimal computational expense via a set of forward recursive updating formula in searching model terms with maximal incremental LOO-AUC value. Numerical examples are used to demonstrate the efficacy of the algorithm.

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A novel Linear Hashtable Method Predicted Hexagonal Search (LHMPHS) method for block based motion compensation is proposed. Fast block matching algorithms use the origin as the initial search center, which often does not track motion very well. To improve the accuracy of the fast BMA's, we employ a predicted starting search point, which reflects the motion trend of the current block. The predicted search centre is found closer to the global minimum. Thus the center-biased BMA's can be used to find the motion vector more efficiently. The performance of the algorithm is evaluated by using standard video sequences, considers the three important metrics: The results show that the proposed algorithm enhances the accuracy of current hexagonal algorithms and is better than Full Search, Logarithmic Search etc.