941 resultados para Textual information processing
Resumo:
Effective techniques for organizing and visualizing large image collections are in growing demand as visual search gets increasingly popular. iMap is a treemap representation for visualizing and navigating image search and clustering results based on the evaluation of image similarity using both visual and textual information. iMap not only makes effective use of available display area to arrange images but also maintains stable update when images are inserted or removed during the query. A key challenge of using iMap lies in the difficult to follow and track the changes when updating the image arrangement as the query image changes. For many information visualization applications, showing the transition when interacting with the data is critically important as it can help users better perceive the changes and understand the underlying data. This work investigates the effectiveness of animated transition in a tiled image layout where the spiral arrangement of the images is based on their similarity. Three aspects of animated transition are considered, including animation steps, animation actions, and flying paths. Exploring and weighting the advantages and disadvantages of different methods for each aspect and in conjunction with the characteristics of the spiral image layout, we present an integrated solution, called AniMap, for animating the transition from an old layout to a new layout when a different image is selected as the query image. To smooth the animation and reduce the overlap among images during the transition, we explore different factors that might have an impact on the animation and propose our solution accordingly. We show the effectiveness of our animated transition solution by demonstrating experimental results and conducting a comparative user study.
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Decision-making and memory are fundamental processes for successful human behaviour. For eye movements, the frontal eye fields (FEF), the supplementary eye fields (SEF), the dorsolateral prefrontal cortex (DLPFC), the ventrolateral frontal cortex and the anterior cingulum are important for these cognitive processes. The online approach of transcranial magnetic stimulation (TMS), i.e., the application of magnetic pulses during planning and performance of saccades, allows interfering specifically with information processing of the stimulated region at a very specific time interval (chronometry of cortical processing). The paper presents studies, which showed the different roles of the FEF and DLPFC in antisaccade control. The critical time interval of DLPFC control seems to be before target onset since TMS significantly increased the percentage of antisaccade errors at that time interval. The FEF seems to be important for the triggering of correct antisaccades. Bilateral stimulation of the DLPFC could demonstrate parallel information-processing transfer in spatial working memory during memory-guided saccades.
Resumo:
BACKGROUND: Patients with apparent complete recovery from thrombotic thrombocytopenic purpura (TTP) often complain of problems with memory, concentration, and fatigue. STUDY DESIGN AND METHODS: Twenty-four patients who were enrolled in the Oklahoma TTP-HUS Registry for their initial episode of TTP, 1995-2006, and who had ADAMTS13 activity of less than 10 percent were evaluated for a broad range of cognitive functions 0.1 to 10.6 years (median, 4.0 years) after their most recent episode. At the time of their evaluation, they had normal physical and Mini-Mental State Examinations and no evidence of TTP. RESULTS: The patients, as a group, performed significantly worse on 4 of the 11 cognitive domains tested than standardized US data from neurologically normal individuals adjusted for age, sex, and education (p < 0.05). These four domains measured complex attention and concentration skills, information processing speed, rapid language generation, and rote memorization. Twenty-one (88%) patients performed below expectations on at least 1 of the 11 domains. No clear patterns were observed between cognitive test results and patients' characteristics or features of the preceding TTP, including age, occurrence of severe neurologic abnormalities, multiple episodes, and interval from an acute episode. CONCLUSION: Patients who have recovered from TTP may have persistent cognitive abnormalities. The abnormalities observed in these patients are characteristic of disorders associated with diffuse subcortical microvascular disease. Studies of larger patient groups will be required to confirm these preliminary observations and to determine patient characteristics that may contribute to persistent cognitive abnormalities.
Resumo:
Phase locking or synchronization of brain areas is a key concept of information processing in the brain. Synchronous oscillations have been observed and investigated extensively in EEG during the past decades. EEG oscillations occur over a wide frequency range. In EEG, a prominent type of oscillations is alpha-band activity, present typically when a subject is awake, but at rest with closed eyes. The spectral power of alpha rhythms has recently been investigated in simultaneous EEG/fMRI recordings, establishing a wide-range cortico-thalamic network. However, spectral power and synchronization are different measures and little is known about the correlations between BOLD effects and EEG synchronization. Interestingly, the fMRI BOLD signal also displays synchronous oscillations across different brain regions. These oscillations delineate so-called resting state networks (RSNs) that resemble the correlation patterns of simultaneous EEG/fMRI recordings. However, the nature of these BOLD oscillations and their relations to EEG activity is still poorly understood. One hypothesis is that the subunits constituting a specific RSN may be coordinated by different EEG rhythms. In this study we report on evidence for this hypothesis. The BOLD correlates of global EEG synchronization (GFS) in the alpha frequency band are located in brain areas involved in specific RSNs, e.g. the 'default mode network'. Furthermore, our results confirm the hypothesis that specific RSNs are organized by long-range synchronization at least in the alpha frequency band. Finally, we could localize specific areas where the GFS BOLD correlates and the associated RSN overlap. Thus, we claim that not only the spectral dynamics of EEG are important, but also their spatio-temporal organization.
Resumo:
Behavioral reflection is crucial to support for example functional upgrades, on-the-fly debugging, or monitoring critical applications. However the use of reflective features can lead to severe problems due to infinite metacall recursion even in simple cases. This is especially a problem when reflecting on core language features since there is a high chance that such features are used to implement the reflective behavior itself. In this paper we analyze the problem of infinite meta-object call recursion and solve it by providing a first class representation of meta-level execution: at any point in the execution of a system it can be determined if we are operating on a meta-level or base level so that we can prevent infinite recursion. We present how meta-level execution can be represented by a meta-context and how reflection becomes context-aware. Our solution makes it possible to freely apply behavioral reflection even on system classes: the meta-context brings stability to behavioral reflection. We validate the concept with a robust implementation and we present benchmarks.
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To quickly localize defects, we want our attention to be focussed on relevant failing tests. We propose to improve defect localization by exploiting dependencies between tests, using a JUnit extension called JExample. In a case study, a monolithic white-box test suite for a complex algorithm is refactored into two traditional JUnit style tests and to JExample. Of the three refactorings, JExample reports five times fewer defect locations and slightly better performance (-8-12\%), while having similar maintenance characteristics. Compared to the original implementation, JExample greatly improves maintainability due the improved factorization following the accepted test quality guidelines. As such, JExample combines the benefits of test chains with test quality aspects of JUnit style testing.
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Artificial neural networks are based on computational units that resemble basic information processing properties of biological neurons in an abstract and simplified manner. Generally, these formal neurons model an input-output behaviour as it is also often used to characterize biological neurons. The neuron is treated as a black box; spatial extension and temporal dynamics present in biological neurons are most often neglected. Even though artificial neurons are simplified, they can show a variety of input-output relations, depending on the transfer functions they apply. This unit on transfer functions provides an overview of different transfer functions and offers a simulation that visualizes the input-output behaviour of an artificial neuron depending on the specific combination of transfer functions.
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This paper investigates the relationship between annual report disclosure, market liquidity, and capital cost for firms registered on the Deutsche Börse. Disclosure is comprehensively measured using the innovative Artificial Intelligence Measurement of Disclosure (AIMD). Results show that annual report disclosure enhances market liquidity by changing investors’ expectations and inducing portfolio adjustments. Trading frictions are negatively associated with disclosure. The study provides evidence for a capital-costreduction effect of disclosure based on the analysis of investors’ return requirements and market values. Altogether, no evidence is found that the information processing at the German capital market is structurally different from other markets.
Resumo:
Die voranschreitende Entwicklung von Konzepten und Systemen zur Nutzung digitaler Informationen im industriellen Umfeld eröffnet verschiedenste Möglichkeiten zur Optimierung der Informationsverarbeitung und damit der Prozesseffektivität und -effizienz. Werden die relevanten Daten zu Produkten oder Prozessen jedoch lediglich in digitaler Form zur Verfügung gestellt, fällt ein Eingriff des Menschen in die virtuelle Welt immer schwerer. Auf Grundlage dessen wird am Beispiel der RFIDTechnologie dargestellt, inwiefern digitale Informationen durch die Verwendung von in den Arbeitsablauf integrierten Systemen für den Menschen nutzbar werden. Durch die Entwicklung eines Systems zur papierlosen Produktion und Logistik werden exemplarisch Einsatzszenarien zur Unterstützung des Mitarbeiters in Montageprozessen sowie zur Vermeidung von Fehlern in der Kommissionierung aufgezeigt. Dazu findet neben einer am Kopf getragenen Datenbrille zur Visualisierung der Informationen ein mobiles RFID-Lesegerät Anwendung, mit Hilfe dessen die digitalen Transponderdaten ohne zusätzlichen Aufwand für den Anwender genutzt werden können.
Resumo:
Reports on left-lateralized abnormalities of component P300 of event-related brain potentials (ERP) in schizophrenics typically did not vary task difficulties. We collected 16-channel ERP in 13 chronic, medicated schizophrenics (25±4.9 years) and 13 matched controls in a visual P300 paradigm with targets defined by one or two stimulus dimensions (C1: color; C2: color and tilt); subjects key-pressed to targets. The mean target-ERP map landscapes were assessed numerically by the locations of the positive and negative map-area centroids. The centroids' time-space trajectories were searched for the P300 microstate landscape defined by the positive centroid posterior of the negative centroid. At P300 microstate centre latencies in C1, patients' maps tended to a right shift of the positive centroid (p<0.10); in C2 the anterior centroid was more posterior (p<0.07) and the posterior (positive) centroid more anterior (p<0.03), but without leftright difference. Duration of P300 microstate in C2 was shorter in patients (232 vs 347 ms;p<0.03) and the latency of maximal strength of P300 microstate increased significantly in patients (C1: 459 vs 376 ms; C2: 585 vs 525 ms). In summary only the one-dimensional task C1 supported left-sided abnormalities; the two-dimensional task C2 produced abnormal P300 microstate map landscapes in schizophrenics, but no abnormal lateralization. Thus, information processing involved clearly aberrant neural populations in schizophrenics, different when processing one and two stimulus dimensions. The lack of lateralization in the two-dimensional task supported the view that left-temporal abnormality in schizophrenics is only one of several task-dependent aberrations.
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The present study shows that different neural activity during mental imagery and abstract mentation can be assigned to well-defined steps of the brain's information-processing. During randomized visual presentation of single, imagery-type and abstract-type words, 27 channel event-related potential (ERP) field maps were obtained from 25 subjects (sequence-divided into a first and second group for statistics). The brain field map series showed a sequence of typical map configurations that were quasi-stable for brief time periods (microstates). The microstates were concatenated by rapid map changes. As different map configurations must result from different spatial patterns of neural activity, each microstate represents different active neural networks. Accordingly, microstates are assumed to correspond to discrete steps of information-processing. Comparing microstate topographies (using centroids) between imagery- and abstract-type words, significantly different microstates were found in both subject groups at 286–354 ms where imagery-type words were more right-lateralized than abstract-type words, and at 550–606 ms and 606–666 ms where anterior-posterior differences occurred. We conclude that language-processing consists of several, well-defined steps and that the brain-states incorporating those steps are altered by the stimuli's capacities to generate mental imagery or abstract mentation in a state-dependent manner.
Resumo:
Brain processing of grammatical word class was studied analyzing event-related potential (ERP) brain fields. Normal subjects observed a randomized sequence of single German nouns and verbs on a computer screen, while 20-channel ERP field map series were recorded separately for both word classes. Spatial microstate analysis was applied, based on the observation that series of ERP maps consist of epochs of quasi-stable map landscapes and based on the rationale that different map landscapes must have been generated by different neural generators and thus suggest different brain functions. Space-oriented segmentation of the mean map series identified nine successive, different functional microstates, i.e., steps of brain information processing characterized by quasi-stable map landscapes. In the microstate from 116 to 172 msec, noun-related maps differed significantly from verb-related maps along the left–right axis. The results indicate that different neural populations represent different grammatical word classes in language processing, in agreement with clinical observations. This word class differentiation as revealed by the spatial–temporal organization of neural activity occurred at a time after word input compatible with speed of reading.
Resumo:
The influence of the immediate prestimulus EEG microstate (sub-second epoch of stable topography/map landscape) on the map landscape of visually evoked 47-channel event-related potential (ERP) microstates was examined using the frequent, non-target stimuli of a cognitive paradigm (12 volunteers). For the two most frequent prestimulus microstate classes (oriented left anterior-right posterior and right anterior-left posterior), ERP map series were selectively averaged. The post-stimulus ERP grand average map series was segmented into microstates; 10 were found. The centroid locations of positive and negative map areas were extracted as landscape descriptors. Significant differences (MANOVAs and t-tests) between the two prestimulus classes were found in four of the ten ERP microstates. The relative orientation of the two ERP microstate classes was the same as prestimulus in some ERP microstates, but reversed in others. — Thus, brain electric microstates at stimulus arrival influence the landscapes of the post-stimulus ERP maps and therefore, information processing; prestimulus microstate effects differed for different post-stimulus ERP microstates.
Resumo:
In young, first-episode, productive, medication-naive patients with schizophrenia, EEG microstates (building blocks of mentation) tend to be shortened. Koenig et al. [Koenig, T., Lehmann, D., Merlo, M., Kochi, K., Hell, D., Koukkou, M., 1999. A deviant EEG brain microstate in acute, neuroleptic-naïve schizophrenics at rest. European Archives of Psychiatry and Clinical Neuroscience 249, 205–211] suggested that shortening concerned specific microstate classes. Sequence rules (microstate concatenations, syntax) conceivably might also be affected. In 27 patients of the above type and 27 controls, from three centers, multichannel resting EEG was analyzed into microstates using k-means clustering of momentary potential topographies into four microstate classes (A–D). In patients, microstates were shortened in classes B and D (from 80 to 70 ms and from 94 to 82 ms, respectively), occurred more frequently in classes A and C, and covered more time in A and less in B. Topography differed only in class B where LORETA tomography predominantly showed stronger left and anterior activity in patients. Microstate concatenation (syntax) generally were disturbed in patients; specifically, the class sequence A→C→D→A predominated in controls, but was reversed in patients (A→D→C→A). In schizophrenia, information processing in certain classes of mental operations might deviate because of precocious termination. The intermittent occurrence might account for Bleuler's “double bookkeeping.” The disturbed microstate syntax opens a novel physiological comparison of mental operations between patients and controls.