Non close loop manufacturing process, typically in the hard disk media industries rely from its inspection machine to generate production yield temporal data that can be used for future analysis. In order for an engin...
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Future planetary exploration of the outer satellites of the Solar System will require higher levels of onboard automation, including autonomous determination of sites where the probability of significant scientific fi...
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ISBN:
(纸本)9780819471512
Future planetary exploration of the outer satellites of the Solar System will require higher levels of onboard automation, including autonomous determination of sites where the probability of significant scientific findings is highest. Generally, the level of needed automation is heavily influenced by the distance between Earth and the robotic explorer(s) (e.g. spacecraft(s), rover(s), and balloon(s)). Therefore, planning missions to the outer satellites mandates the analysis, design and integration within the mission architecture of semi-and/or completely autonomous intelligence systems. Such systems should (1) include software packages that enable fully automated and comprehensive identification, characterization, and quantification of feature information within an operational region with subsequent target prioritization and selection for close-up reexamination;and (2) integrate existing information with acquired, "in transit" spatial and temporal sensor data to automatically perform intelligent planetary reconnaissance, which includes identification of sites with the highest potential to yield significant geological and astrobiological information. In this paper we review and compare some of the available Artificial Intelligence (AI) schemes and their adaptation to the problem of designing expert systems for onboard-based, autonomous science to be performed in the course of outer satellites exploration. More specifically, the fuzzy-logic framework proposed is analyzed in some details to show the effectiveness of such a scheme when applied to the problem of designing expert systems capable of identifying and further exploring regions on Titan and/or Enceladus that have the highest potential to yield evidence for past or present life. Based on available information (e.g., Cassini data), the current knowledge and understanding of Titan and Enceladus environments is evaluated to define a path for the design of a fuzzy-based system capable of reasoning over collected
The purpose of this study was to identify the quality indicators of visual-based learning material in technology education for grades 7-12. A three-round modified Delphi method was used to answer the following researc...
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作者:
Assiri, A.Alsaleh, A.Mousa, H.
P.O. Box 6086 Riyadh 11442 Saudi Arabia
Geosciences Department P.O. Box 2445 Riyadh 11451 Saudi Arabia
This study aims at exploiting multi-spectral data, acquired from ASTER, satellite to explore areas of hydrothermal alteration and Gossan including massive Sulphide deposits. Auger sulphide is a good source of raw mate...
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ISBN:
(纸本)9781615676156
This study aims at exploiting multi-spectral data, acquired from ASTER, satellite to explore areas of hydrothermal alteration and Gossan including massive Sulphide deposits. Auger sulphide is a good source of raw materials such as economic copper, silver, gold and zinc. Major steps involved in the analysis of ASTER satellite data have been discussed using ERDAS Imagine Software. The extent of interdependence among spectral regions, hydrothermal alteration and Gossan has been studied through digital image analysis and classification. The visual interpretation techniques have been employed to identify and earmark hydrothermal alteration and Gossan zones on the satellite image for carrying out subsequent supervised image classification. Imagery analysis was supported by the color composite, developed by exposing bands 4, 6 & 9 with Red, Green and Blue radiations respectively, to make iron-rich cap or Gossan and hydrothermal alteration zones prominent. The Gossan-laden regions appeared in Red color while the hydrothermal alteration zones took color range from reddish green to light green. Image enhancement has also been achieved through the application of image ratioing techniques and an improved color composite was developed by exposing results of band ratios of band 5 & band 7, band 5 & band 4, and band 2 & band 1 with Red, Green and Blue radiations respectively. Resultantly, the combination of visual interpretation, previous knowledge of the landcover and digital image processing techniques applied on the ASTER Satellite imagery in multi-spectral mode, has proved beneficial in studying hydrothermal alteration zones and Gossan in the Nuqrah area.
The proceedings contain 12 papers. The topics discussed include: genomic spring-synteny visualization with IMAS;visualizing the ene ontology-annotated clusters of co-expressed genes: a two-design study;from microarray...
ISBN:
(纸本)9780769532844
The proceedings contain 12 papers. The topics discussed include: genomic spring-synteny visualization with IMAS;visualizing the ene ontology-annotated clusters of co-expressed genes: a two-design study;from microarrays to promoters: the visual story of Stat3;visualization of clinical and non-clinical characteristics of patients with behavioral and psychological symptoms of Dementia;interactive exploration of medical data sets;visualizing domain interaction network and the impact of alternative spicing events;3D multiscale visualization for medical datasets;3D visualization of the radiological features of type ii collagenopathies associated with Skeletal Dysplasias;using Web services for distributed medical visualization;and medical image segmentation using new hybrid level-set method.
Reflectance spectrophotometry (RS), laser Doppler flowmetry (LDF) and transepidermal water loss (TEWL) techniques were simultaneously used to non-invasively monitor skin colour (SC), skin blood flow (SBF) and barrier ...
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ISBN:
(纸本)9780819470393
Reflectance spectrophotometry (RS), laser Doppler flowmetry (LDF) and transepidermal water loss (TEWL) techniques were simultaneously used to non-invasively monitor skin colour (SC), skin blood flow (SBF) and barrier function damage (BFD) in routinely patch-tested Japanese patients in dermatology clinic. The analytical quality, reliability and reproducibility of each technique were compared and analyzed in correlated to visual scoring patch test (PT) reactions as negative (), doubtful (+?), weak (+) and strong (++/+++) at 48- and 72-hour monitoring. An attempt was made to quantify predominant in the clinic "+?"- and "+"-PT-reactions. The relationship between 48 h and 72 h measurements in different reaction groups was poor for TEWL, LDF showed a tendency to decrease at 72 h, but good for RS. A correlation between visual scorings and instrumental mean values was poor for TEWL, good for LDF and excellent for RS. So, measurements by RS were the most statistically significant to non-invasively monitor and quantify doubtful, weak and strong PT reactions, accordingly providing continuous data grading of reaction intensity suitable in the clinic. Moreover, monitoring of SC changes was the most reliable parameter for the quantitative distinguishing of doubtful and weak reactions in pigmented skin.
Multi-label classification assigns a data item to one or several classes. This problem of multiple labels arises in fields like acoustic and visual scene analysis, news reports and medical diagnosis. In a generative f...
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ISBN:
(纸本)9783540874805
Multi-label classification assigns a data item to one or several classes. This problem of multiple labels arises in fields like acoustic and visual scene analysis, news reports and medical diagnosis. In a generative framework, data with multiple labels can be interpreted as additive mixtures of emissions of the individual sources. We propose a deconvolution approach to estimate the individual contributions of each source to a given data item. Similarly, the distributions of multi-label data are computed based on the source distributions. In experiments with synthetic data, the novel approach is compared to existing models and yields more accurate parameter estimates, higher classification accuracy and ameliorated generalization to previously unseen label sets. These improvements are most pronounced on small training data sets. Also on real world acoustic data, the algorithm outperforms other generative models, in particular on small training data sets.
Three-dimension(3D) modeling and visualization of stratum plays important role in seismic active fault detection,of course in GeoInformation science. Well-logging data of strata is taken as time series. Similarity mea...
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ISBN:
(纸本)9780769533056
Three-dimension(3D) modeling and visualization of stratum plays important role in seismic active fault detection,of course in GeoInformation science. Well-logging data of strata is taken as time series. Similarity measure of subsequence search is proposed based on dynamic time warping (DTW), Realizing time series match in different length of time series. The frequent pattern mining experiment is carried on to survey data of strata by multivariable combination analysis, We supply the stratum geophysics attribute by the depth (time) records sequence in the non-drill hole survey data's places using these frequent patterns, combining structure frame and mathematics geology interpolation technology, establish 3D geology model of the target area,and develop the underground geologic body 3D visualization software depending on visual studio. net and OpenGL graph packages, realize 3D visualization system.
In this paper, we present the strategy for evaluating the performance of a variety of configurations of an architecture template for a computer vision system (CVS). For this study a generic model of an architecture is...
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Cogent confabulation is a computation model that mimics the Hebbian learning, information storage, inter-relation of symbolic concepts, and the recall operations of the brain. The model has been applied to cognitive p...
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ISBN:
(纸本)9781424418206
Cogent confabulation is a computation model that mimics the Hebbian learning, information storage, inter-relation of symbolic concepts, and the recall operations of the brain. The model has been applied to cognitive processing of language, audio and visual signals. In this project, we focus on how to accelerate the computation which underlie confabulation based sentence completion through software and hardware optimization. On the software implementation side, appropriate data structures can improve the performance of the software by more than 5,000X. On the hardware implementation side, the cogent confabulation algorithm is an ideal candidate for parallel processing and its performance can be significantly improved with the help of application specific, massively parallel computing platforms. However, as the complexity and parallelism of the hardware increases, cost also increases. Architectures with different performance-cost tradeoffs are analyzed and compared. Our analysis shows that although increasing the number of processors or the size of memories per processor can increase performance, the hardware cost and performance improvements do not always exhibit a linear relation. Hardware configuration options must be carefully evaluated in order to achieve good cost performance tradeoffs.
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