The Atmospheric Remote-sensing Infrared Exoplanet Large-survey (ARIEL) is the latest addition as the M4 mission in the ESA Cosmic Vision programme. This mission will study the chemical composition of exoplanetary atmo...
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ISBN:
(纸本)9781510636927
The Atmospheric Remote-sensing Infrared Exoplanet Large-survey (ARIEL) is the latest addition as the M4 mission in the ESA Cosmic Vision programme. This mission will study the chemical composition of exoplanetary atmospheres via high resolution, multi-wavelength spectroscopy with high photometric precision. These tasks demand highly stable pointing during operation, which is provided by a dedicated Fine Guiding Sensor (FGS) instrument. The FGS uses two Mercury Cadmium Telluride (MCT) detectors operating in the 0.5-1.95 mu m range. The centroid measurements are provided to the spacecraft forming a closed loop in the guiding. In addition, the FGS detectors are also used for science including photometric and spectral windows. The instrument contains a Data Processing Unit (DPU) with a dual core LEON-based computer running the Instrument Application Software (IASW). The software implements a large number of ECSS services to fulfill the various operating needs. The mission-specific modes cover target acquisition and tracking tasks, processing of the photometric and spectral windows as well as various calibration modes. The science data need to be compressed in a lossless manner using algorithms previously developed for the ESA missions HERSCHEL and CHEOPS. While the science data processing has only soft real-timing needs, the centroiding is critical to run and provide results as fast as possible. We present the architectural design of the software particularly highlighting the low-level software adaptations needed to support the high demands from the centroid timing. The presented overview of the design is complemented with the expected performance of the algorithms.
Reinforcement Learning holds the potential to enable many systems with rapid, intelligent automated decision-making. However, reinforcement learning on embodied systems is a much greater challenge than the simulated e...
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ISBN:
(数字)9781510636286
ISBN:
(纸本)9781510636286
Reinforcement Learning holds the potential to enable many systems with rapid, intelligent automated decision-making. However, reinforcement learning on embodied systems is a much greater challenge than the simulated environments and tasks which have been solved to date. A learner in an embodied system cannot run millions of trials or easily tolerate fatal trajectories. Therefore, the ability to train agents in simulated environments and effectively transfer their knowledge to real-world environments will be crucial, and likely an integral part of constructing future robotic systems. We perform experiments in an original transfer reinforcement learning task we constructed using the game "Sonic 3 & Knuckles", evaluating two transfer learning techniques from the literature.
Real-time behaviour analysis is of paramount importance to ensure the safety of passengers in border-crossing areas. It allows to recognize the security threats on time. Moreover, it can accelerate the security check ...
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ISBN:
(纸本)9781510638983
Real-time behaviour analysis is of paramount importance to ensure the safety of passengers in border-crossing areas. It allows to recognize the security threats on time. Moreover, it can accelerate the security check since the security personnel only consider severe checks for passengers with suspicious behaviour. In this work, we consider the following suspicious patterns: (a) mindless turn, (b) peculiar interest to the security units, and (c) avoiding the security units. We propose an algorithm to compute an abnormal behaviour score in real-time. This score can help the security personnel to assess passenger movement patterns. We show the performance of our scoring algorithm via different synthetic examples.
Modern sensors produce increasingly high volume of data that requires efficient and reliable statistical methods for information processing. We consider frequent problems of information processing which can be cast in...
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ISBN:
(纸本)9781510638624;9781510638617
Modern sensors produce increasingly high volume of data that requires efficient and reliable statistical methods for information processing. We consider frequent problems of information processing which can be cast into the framework of parameter estimation and multihypothesis testing. We propose a unified approach for statistical inference of information processing by introducing the inclusion principle, confidence process, unimodal likelihood estimator, and time-uniform concentration inequalities. Our methods attempt to make decision based on observing data in an adaptive and sequential way so that the decision can be made as quick as possible, while the probability of committing mistakes is acceptably small.
The color rendering of whole-slide images (WSIs) depends on factors involving the sample, such as tissue type, preparation methods, staining type and staining protocol, as well as equipment, such as the WSI scanner, W...
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ISBN:
(纸本)9781510634077
The color rendering of whole-slide images (WSIs) depends on factors involving the sample, such as tissue type, preparation methods, staining type and staining protocol, as well as equipment, such as the WSI scanner, WSI viewer, and WSI display. Variations in any of these steps may change the color rendering and therefore affect the performance of pathologists in the interpretation of WSIs and the robustness of artificial intelligence algorithms. In the literature, color normalization techniques have been proposed to reduce the color variations. The purpose of this work is to develop an objective approach to characterizing color normalization methods used in digital pathology. We employed color normalization methods to normalize the color rendered by a WSI scanner and then compared the normalized color with the actual scan by that scanner. The normalization errors were evaluated on the pixel level using the CIE color difference ∆E metric that have been shown to correlate with visually perceived differences in human vision. A selected set of 310 patch images of breast tissues scanned by two scanners from the ICPR 2014 MITOS & ATYPIA contest was used. Images from one scanner were color normalized to match the color rendering of the other scanner. Four color normalization methods were compared - Macenko, Reinhard, Vahadane, and StainGAN. Experimental results show that average color differences between two scanners in terms of ∆E were reduced from 16.2 before normalization to the range of [13.7,16.9] after normalization for the Macenko, Reinhard, Vahadane methods, and to 8.3 for the StainGAN method. Apparently the StainGAN method is significantly superior to the other three methods in terms of the ∆E metric. As such, we demonstrated a quantitative method for objectively evaluating color normalization techniques. Future work is needed to explore the relationship of the color fidelity measure and the impact of color normalization on pathologist and AI performance in clinic
There are gaps in understanding in and between those who design systems of AI/ ML, those who critique them, and those positioned between these discourses. This gap can be defined in multiple ways - e.g. methodological...
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ISBN:
(纸本)9781450369367
There are gaps in understanding in and between those who design systems of AI/ ML, those who critique them, and those positioned between these discourses. This gap can be defined in multiple ways - e.g. methodological, epistemological, linguistic, or cultural. To bridge this gap requires a set of translations: the generation of a collaborative space and a new set of shared sensibilities that traverse disciplinary boundaries. This workshop aims to explore translations across multiple fields, and translations between theory and practice, as well as how interdisciplinary work could generate new operationalizable *** define 'knowledge' as a social product (L. Code) which requires fair and broad epistemic cooperation in its generation, development, and dissemination. As a "marker for truth" (B. Williams) and therefore a basis for action, knowledge circulation sustains the systems of power which produce it in the first place (M. Foucault). Enabled by epistemic credence, authority or knowledge, epistemic power can be an important driver of, but also result from, other (e.g. economic, political) *** produce reliable output, our standards and methods should serve us all and exclude no-one. Critical theorists have long revealed failings of epistemic practices, resulting in the marginalization and exclusion of some types of knowledge. How can we cultivate more reflexive epistemic practices in the interdisciplinary research setting of FAT*?We frame this ideal as 'epistemic justice' (M. Geuskens), the positive of 'epistemic injustice', defined by M. Fricker as injustice that exists when people are wronged as a knower or as an epistemic subject. Epistemic justice is the proper use and allocation of epistemic power; the inclusion and balancing of all epistemic *** S. Jasanoff reminds us, any authoritative way of seeing must be legitimized in discourse and practice, showing that practices can be developed to value and engage with other viewpoints and possibly
Introduction Tremor is a disabling symptom of Multiple Sclerosis (MS). The development of objective methods of tremor characterisation to assess intervention efficacy and disease progression is therefore important. Th...
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Introduction Tremor is a disabling symptom of Multiple Sclerosis (MS). The development of objective methods of tremor characterisation to assess intervention efficacy and disease progression is therefore important. The possibility of using a Fast Fourier Transform (FFT) method for tremor detection was explored. Methods Acceleration from a wrist-worn device was analysed using FFTs to identify and characterise tremor magnitude and frequency. Processing parameters were explored to provide insight into the optimal algorithm. Participants wore a wrist tri-axial accelerometer during 9 tasks. The FAHN clinical assessment of tremor was used as the reference standard. Results Five people with MS and tremor (57.6 +/- 15.3 years, 3 F/2M) and ten disease-free controls (42.4 +/- 10.9 years, 5 M/5F) took part. Using specific algorithm settings tremor identification was possible (peak frequency 3-15Hz;magnitude greater than 0.06 g;2 s windows with 50% overlap;using 2 of 3 axes of acceleration), giving sensitivity 0.974 and specificity 0.971 (38 tremor occurrences out of 108 tasks, 1 false positive, 2 false negatives). Tremor had frequency 3.5-13.0 Hz and amplitude 0.07-2.60g. Conclusions Upper limb tremor in people with MS can be detected using a FFT approach based on acceleration recorded at the wrist, demonstrating the possibility of using this minimally encumbering technique within clinical practice.
We develop a new algorithm, the simplified urban-extent (SUE) algorithm, to estimate the surface urban heat island (UHI) intensity at a global scale. We implement the SUE algorithm on the Google Earth Engine platform ...
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We develop a new algorithm, the simplified urban-extent (SUE) algorithm, to estimate the surface urban heat island (UHI) intensity at a global scale. We implement the SUE algorithm on the Google Earth Engine platform using Moderate Resolution Imaging Spectroradiometer (MODIS) images to calculate the UHI intensity for over 9500 urban clusters using over 15 years of data, making this one of the most comprehensive characterizations of the surface UHI to date. The results from this algorithm are validated against previous multi-city studies to demonstrate the suitability of the method. The dataset created is then filtered for elevation differentials and percentage of urban area and used to estimate the diurnal, monthly, and long-term variability in the surface UHI in different climate zones. The global mean surface UHI intensity is 0.85 degrees C during daytime and 0.55 degrees C at night. Cities in arid climate show distinct diurnal and seasonal patterns, with higher surface UHI during nighttime (compared to daytime) and two peaks throughout the year. The diurnal variability in surface UHI is highest for equatorial climate zone (0.88 degrees C) and lowest for arid zone (0.53 degrees C). The seasonality is highest in the snow climate zone and lowest for equatorial climate zone. While investigating the change in the surface UHI over a decade and a half, we find a consistent increase in the daytime surface UHI in the urban clusters of the warm temperate climate zone (0.04 degrees C/decade) and snow climate zone (0.05 degrees C/decade). Only arid climate zones show a statistically significant increase in the nighttime surface UHI intensity (0.03 degrees C/decade). Globally, the change is mainly seen during the daytime (0.03 degrees C/decade). Finally, the importance of vegetation differential between urban and rural areas on the spatiotemporal variability is examined. Vegetation has a strong control on the seasonal variability of the surface UHI and may also partly control
Determining stream networks automatically from digital elevation models is an issue that is actively being studied. The quality of elevation models has increased over time, but many hydrologically critical features, s...
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Determining stream networks automatically from digital elevation models is an issue that is actively being studied. The quality of elevation models has increased over time, but many hydrologically critical features, such as culverts, are often missing from the elevation data. To analyze the surficial water flow, one must either prepare a special elevation model or post-process an already-existing model. This study builds on the traditional, well-established method of determining the stream network from digital elevation models. We have extended the traditional method by locating culverts automatically, using road network data as an input. We show, by comparison to the reference data, that the culverts being most relevant for the stream network can be found with good accuracy. We demonstrate that by including the automatically located culverts in the automatic stream network determination, the quality of the generated network can be noticeably improved.
Both equivalent radar reflectivity factor (Z_e) and specific attenuation (k) in several snow events are measured using a dual Ka-band radar system. Different k-Z_e relations are obtained depending on surface air tempe...
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ISBN:
(纸本)9781479911127
Both equivalent radar reflectivity factor (Z_e) and specific attenuation (k) in several snow events are measured using a dual Ka-band radar system. Different k-Z_e relations are obtained depending on surface air temperature. When surface air temperature is just above 0 ℃, k-Z_e relations scatter and larger k values than those of rain appear. On the other hand, when surface air temperature is below 0 ℃, both k and Z_e are small and a slight positive trend appears in the k-Z_e relations. The difference of k-Z_e relations can be attributed to the difference of the backscattering and attenuation characteristics between wet and dry snow. To confirm wet/dry snow existences, 2D-video-disdrometer data are analyzed. Velocity-size distributions of wet snow events are different from those of dry snow events. Graupels also show different velocity-size distributions from wet and dry snow particles with different k-Z_e relations.
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