999 resultados para event log


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In the picture-word interference task, naming responses are facilitated when a distractor word is orthographically and phonologically related to the depicted object as compared to an unrelated word. We used event-related functional magnetic resonance imaging (fMRI) to investigate the cerebral hemodynamic responses associated with this priming effect. Serial (or independent-stage) and interactive models of word production that explicitly account for picture-word interference effects assume that the locus of the effect is at the level of retrieving phonological codes, a role attributed recently to the left posterior superior temporal cortex (Wernicke's area). This assumption was tested by randomly presenting participants with trials from orthographically related and unrelated distractor conditions and acquiring image volumes coincident with the estimated peak hemodynamic response for each trial. Overt naming responses occurred in the absence of scanner noise, allowing reaction time data to be recorded. Analysis of this data confirmed the priming effect. Analysis of the fMRI data revealed blood oxygen level-dependent signal decreases in Wernicke's area and the right anterior temporal cortex, whereas signal increases were observed in the anterior cingulate, the right orbitomedial prefrontal, somatosensory, and inferior parietal cortices, and the occipital lobe. The results are interpreted as supporting the locus for the facilitation effect as assumed by both classes of theoretical model of word production. In addition, our results raise the possibilities that, counterintuitively, picture-word interference might be increased by the presentation of orthographically related distractors, due to competition introduced by activation of phonologically related word forms, and that this competition requires inhibitory processes to be resolved. The priming effect is therefore viewed as being sufficient to offset the increased interference. We conclude that information from functional imaging studies might be useful for constraining theoretical models of word production.

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We used event-related functional magnetic resonance imaging (fMRI) to investigate neural responses associated with the semantic interference (SI) effect in the picture-word task. Independent stage models of word production assume that the locus of the SI effect is at the conceptual processing level (Levelt et al. [1999]: Behav Brain Sci 22:1-75), whereas interactive models postulate that it occurs at phonological retrieval (Starreveld and La Heij [1996]: J Exp Psychol Learn Mem Cogn 22:896-918). In both types of model resolution of the SI effect occurs as a result of competitive, spreading activation without the involvement of inhibitory links. These assumptions were tested by randomly presenting participants with trials from semantically-related and lexical control distractor conditions and acquiring image volumes coincident with the estimated peak hemodynamic response for each trial. Overt vocalization of picture names occurred in the absence of scanner noise, allowing reaction time (RT) data to be collected. Analysis of the RT data confirmed the SI effect. Regions showing differential hemodynamic responses during the SI effect included the left mid section of the middle temporal gyrus, left posterior superior temporal gyrus, left anterior cingulate cortex, and bilateral orbitomedial prefrontal cortex. Additional responses were observed in the frontal eye fields, left inferior parietal lobule, and right anterior temporal and occipital cortex. The results are interpreted as indirectly supporting interactive models that allow spreading activation between both conceptual processing and phonological retrieval levels of word production. In addition, the data confirm that selective attention/response suppression has a role in resolving the SI effect similar to the way in which Stroop interference is resolved. We conclude that neuroimaging studies can provide information about the neuroanatomical organization of the lexical system that may prove useful for constraining theoretical models of word production.

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This paper addresses the problem of predicting the outcome of an ongoing case of a business process based on event logs. In this setting, the outcome of a case may refer for example to the achievement of a performance objective or the fulfillment of a compliance rule upon completion of the case. Given a log consisting of traces of completed cases, given a trace of an ongoing case, and given two or more possible out- comes (e.g., a positive and a negative outcome), the paper addresses the problem of determining the most likely outcome for the case in question. Previous approaches to this problem are largely based on simple symbolic sequence classification, meaning that they extract features from traces seen as sequences of event labels, and use these features to construct a classifier for runtime prediction. In doing so, these approaches ignore the data payload associated to each event. This paper approaches the problem from a different angle by treating traces as complex symbolic sequences, that is, sequences of events each carrying a data payload. In this context, the paper outlines different feature encodings of complex symbolic sequences and compares their predictive accuracy on real-life business process event logs.

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Even though crashes between trains and road users are rare events at railway level crossings, they are one of the major safety concerns for the Australian railway industry. Nearmiss events at level crossings occur more frequently, and can provide more information about factors leading to level crossing incidents. In this paper we introduce a video analytic approach for automatically detecting and localizing vehicles from cameras mounted on trains for detecting near-miss events. To detect and localize vehicles at level crossings we extract patches from an image and classify each patch for detecting vehicles. We developed a region proposals algorithm for generating patches, and we use a Convolutional Neural Network (CNN) for classifying each patch. To localize vehicles in images we combine the patches that are classified as vehicles according to their CNN scores and positions. We compared our system with the Deformable Part Models (DPM) and Regions with CNN features (R-CNN) object detectors. Experimental results on a railway dataset show that the recall rate of our proposed system is 29% higher than what can be achieved with DPM or R-CNN detectors.

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Permissions are special case of deontic effects and play important role compliance. Essentially they are used to determine the obligations or prohibitions to contrary. A formal language e.g., temporal logic, event-calculus et., not able to represent permissions is doomed to be unable to represent most of the real-life legal norms. In this paper we address this issue and extend deontic-event-calculus (DEC) with new predicates for modelling permissions enabling it to elegantly capture the intuition of real-life cases of permissions.

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The standard curve-fitting methods, Casagrande's log t method and Taylor's root t method, for the determination of the coefficient of consolidation use the later part of the consolidation curve and are influenced by secondary compression effects. Literature shows that secondary compression is concurrent with primary consolidation and that its effect is to decrease the value of the coefficient of consolidation. If the early part of the time-compression data is used, the values obtained will be less influenced by secondary compression effects. A method that uses the early part of the log t plot is proposed in this technical note. As the influence of secondary compression is reduced, the value obtained by this method is greater than that yielded by both the standard methods. The permeability values computed from C-v (obtained from the proposed method) rue more in agreement with the measured values than the standard methods showing that the effects of secondary compression are minimized. Time-compression data for a shorter duration is sufficient for the determination of C-v if the coefficient of secondary compression is not required.

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Critical, loud, highly discursive and polarised; the #auspol hashtag represents a space, an event and a network for politically involved individuals to engage in and with Australian politics and speak to, at and about a variety of involved stakeholders. Contributors declare, debate and often berate each other’s opinions about current Australian politics. The hashtag itself is an important material object and engagement event involved within this performance of political participation. As a long-standing institution in the Twittersphere, and one studied by the authors and their colleagues since its early beginnings (Bruns and Burgess, 2011; Bruns and Stieglitz, 2012; 2013), the #auspol hashtag provides a potent case study through which to explore the discursive and affective dimensions of a hashtag public. This chapter that engages both empirically and theoretically with the use of this particular hashtag on Twitter to provide a qualitatively illustrated case in point for thinking about the long-term use of political hashtags as engagement events.

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In this paper we tackle the problem of efficient video event detection. We argue that linear detection functions should be preferred in this regard due to their scalability and efficiency during estimation and evaluation. A popular approach in this regard is to represent a sequence using a bag of words (BOW) representation due to its: (i) fixed dimensionality irrespective of the sequence length, and (ii) its ability to compactly model the statistics in the sequence. A drawback to the BOW representation, however, is the intrinsic destruction of the temporal ordering information. In this paper we propose a new representation that leverages the uncertainty in relative temporal alignments between pairs of sequences while not destroying temporal ordering. Our representation, like BOW, is of a fixed dimensionality making it easily integrated with a linear detection function. Extensive experiments on CK+, 6DMG, and UvA-NEMO databases show significant performance improvements across both isolated and continuous event detection tasks.

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It has been suggested that semantic information processing is modularized according to the input form (e.g., visual, verbal, non-verbal sound). A great deal of research has concentrated on detecting a separate verbal module. Also, it has traditionally been assumed in linguistics that the meaning of a single clause is computed before integration to a wider context. Recent research has called these views into question. The present study explored whether it is reasonable to assume separate verbal and nonverbal semantic systems in the light of the evidence from event-related potentials (ERPs). The study also provided information on whether the context influences processing of a single clause before the local meaning is computed. The focus was on an ERP called N400. Its amplitude is assumed to reflect the effort required to integrate an item to the preceding context. For instance, if a word is anomalous in its context, it will elicit a larger N400. N400 has been observed in experiments using both verbal and nonverbal stimuli. Contents of a single sentence were not hypothesized to influence the N400 amplitude. Only the combined contents of the sentence and the picture were hypothesized to influence the N400. The subjects (n = 17) viewed pictures on a computer screen while hearing sentences through headphones. Their task was to judge the congruency of the picture and the sentence. There were four conditions: 1) the picture and the sentence were congruent and sensible, 2) the sentence and the picture were congruent, but the sentence ended anomalously, 3) the picture and the sentence were incongruent but sensible, 4) the picture and the sentence were incongruent and anomalous. Stimuli from the four conditions were presented in a semi-randomized sequence. Their electroencephalography was simultaneously recorded. ERPs were computed for the four conditions. The amplitude of the N400 effect was largest in the incongruent sentence-picture -pairs. The anomalously ending sentences did not elicit a larger N400 than the sensible sentences. The results suggest that there is no separate verbal semantic system, and that the meaning of a single clause is not processed independent of the context.

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An event sequence recorder is a specialized piece of equipment that accepts inputs from switches and contactors, and prints the sequence in which they operate. This paper describes an event sequence recorder based on an Intel 8085 microprocessor. It scans the inputs every millisecond and prints in a compact form the channel number, type of event (normal or abnormal) and time of occurrence. It also communicates these events over an RS232C link to a remote computer. A realtime calendar/clock is included. The system described has been designed for continuous operation in process plants, power stations etc. The system has been tested and found to be working satisfactorily.

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Sawing studies of mixed species and age plantation hardwoods representing potential early resource flows available to plantation sawlog processing industry. Provide information needed to underpin a business case to invest in small log sawing infrastucture.