983 resultados para automated knowledge visualization
Resumo:
With the purpose of at lowering costs and reendering the demanded information available to users with no access to the internet, service companies have adopted automated interaction technologies in their call centers, which may or may not meet the expectations of users. Based on different areas of knowledge (man-machine interaction, consumer behavior and use of IT) 13 propositions are raised and a research is carried out in three parts: focus group, field study with users and interviews with experts. Eleven automated service characteristics which support the explanation for user satisfaction are listed, a preferences model is proposed and evidence in favor or against each of the 13 propositions is brought in. With balance scorecard concepts, a managerial assessment model is proposed for the use of automated call center technology. In future works, the propositions may become verifiable hypotheses through conclusive empirical research.
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We describe a novel approach to explore DNA nucleotide sequence data, aiming to produce high-level categorical and structural information about the underlying chromosomes, genomes and species. The article starts by analyzing chromosomal data through histograms using fixed length DNA sequences. After creating the DNA-related histograms, a correlation between pairs of histograms is computed, producing a global correlation matrix. These data are then used as input to several data processing methods for information extraction and tabular/graphical output generation. A set of 18 species is processed and the extensive results reveal that the proposed method is able to generate significant and diversified outputs, in good accordance with current scientific knowledge in domains such as genomics and phylogenetics.
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With the advent of wearable sensing and mobile technologies, biosignals have seen an increasingly growing number of application areas, leading to the collection of large volumes of data. One of the difficulties in dealing with these data sets, and in the development of automated machine learning systems which use them as input, is the lack of reliable ground truth information. In this paper we present a new web-based platform for visualization, retrieval and annotation of biosignals by non-technical users, aimed at improving the process of ground truth collection for biomedical applications. Moreover, a novel extendable and scalable data representation model and persistency framework is presented. The results of the experimental evaluation with possible users has further confirmed the potential of the presented framework.
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Wireless Sensor Networks(WSN) are networks of devices used to sense and act that applies wireless radios to communicate. To achieve a successful implementation of a wireless device it is necessary to take in consideration the existence of a wide variety of radios available, a large number of communication parameters (payload, duty cycle, etc.) and environmental conditions that may affect the device’s behaviour. However, to evaluate a specific radio towards a unique application it might be necessary to conduct trial experiments, with such a vast amount of devices, communication parameters and environmental conditions to take into consideration the number of trial cases generated can be surprisingly high. Thus, making trial experiments to achieve manual validation of wireless communication technologies becomes unsuitable due to the existence of a high number of trial cases on the field. To overcome this technological issue an automated test methodology was introduced, presenting the possibility to acquire data regarding the device’s behaviour when testing several technologies and parameters that care for a specific analysis. Therefore, this method advances the validation and analysis process of the wireless radios and allows the validation to be done without the need of specific and in depth knowledge about wireless devices.
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After the incorporation of automated external defibrilators by other airlines and the support of the Brazilian Society of cardiology, Varig Airlines Began the onboard defibrilation program with the initial purpose of equiping wide-body aircrafts frequently used in international flights and that airplanes use in the Rio - São Paulo route. With all fight attendants trained, the automated. External defibrilation devides were incorporated to 34 airplanes of a total pleet of 80 aircrats. The devices were intalled in the bagage compartments secured with velero straps and 2 pairs of electrods, one or which pre-conected to the device to minimize application time. Later, a portable monitor was addres to the ressocitation kit in the long flights. The expansion of the knowledge of the basic life support fundamentors and the correted implantation of the survival chain and of the automated external defibrilators will increase the extense of recovery of cardiorespiratory arrest victins in aircrafts.
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Many classifiers achieve high levels of accuracy but have limited applicability in real world situations because they do not lead to a greater understanding or insight into the^way features influence the classification. In areas such as health informatics a classifier that clearly identifies the influences on classification can be used to direct research and formulate interventions. This research investigates the practical applications of Automated Weighted Sum, (AWSum), a classifier that provides accuracy comparable to other techniques whilst providing insight into the data. This is achieved by calculating a weight for each feature value that represents its influence on the class value. The merits of this approach in classification and insight are evaluated on a Cystic Fibrosis and Diabetes datasets with positive results.
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The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.
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TCRep 3D is an automated systematic approach for TCR-peptide-MHC class I structure prediction, based on homology and ab initio modeling. It has been considerably generalized from former studies to be applicable to large repertoires of TCR. First, the location of the complementary determining regions of the target sequences are automatically identified by a sequence alignment strategy against a database of TCR Vα and Vβ chains. A structure-based alignment ensures automated identification of CDR3 loops. The CDR are then modeled in the environment of the complex, in an ab initio approach based on a simulated annealing protocol. During this step, dihedral restraints are applied to drive the CDR1 and CDR2 loops towards their canonical conformations, described by Al-Lazikani et. al. We developed a new automated algorithm that determines additional restraints to iteratively converge towards TCR conformations making frequent hydrogen bonds with the pMHC. We demonstrated that our approach outperforms popular scoring methods (Anolea, Dope and Modeller) in predicting relevant CDR conformations. Finally, this modeling approach has been successfully applied to experimentally determined sequences of TCR that recognize the NY-ESO-1 cancer testis antigen. This analysis revealed a mechanism of selection of TCR through the presence of a single conserved amino acid in all CDR3β sequences. The important structural modifications predicted in silico and the associated dramatic loss of experimental binding affinity upon mutation of this amino acid show the good correspondence between the predicted structures and their biological activities. To our knowledge, this is the first systematic approach that was developed for large TCR repertoire structural modeling.
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Introduction. Development of the fetal brain surfacewith concomitant gyrification is one of the majormaturational processes of the human brain. Firstdelineated by postmortem studies or by ultrasound, MRIhas recently become a powerful tool for studying in vivothe structural correlates of brain maturation. However,the quantitative measurement of fetal brain developmentis a major challenge because of the movement of the fetusinside the amniotic cavity, the poor spatial resolution,the partial volume effect and the changing appearance ofthe developing brain. Today extensive efforts are made todeal with the âeurooepost-acquisitionâeuro reconstruction ofhigh-resolution 3D fetal volumes based on severalacquisitions with lower resolution (Rousseau, F., 2006;Jiang, S., 2007). We here propose a framework devoted tothe segmentation of the basal ganglia, the gray-whitetissue segmentation, and in turn the 3D corticalreconstruction of the fetal brain. Method. Prenatal MRimaging was performed with a 1-T system (GE MedicalSystems, Milwaukee) using single shot fast spin echo(ssFSE) sequences in fetuses aged from 29 to 32gestational weeks (slice thickness 5.4mm, in planespatial resolution 1.09mm). For each fetus, 6 axialvolumes shifted by 1 mm were acquired (about 1 min pervolume). First, each volume is manually segmented toextract fetal brain from surrounding fetal and maternaltissues. Inhomogeneity intensity correction and linearintensity normalization are then performed. A highspatial resolution image of isotropic voxel size of 1.09mm is created for each fetus as previously published byothers (Rousseau, F., 2006). B-splines are used for thescattered data interpolation (Lee, 1997). Then, basalganglia segmentation is performed on this superreconstructed volume using active contour framework witha Level Set implementation (Bach Cuadra, M., 2010). Oncebasal ganglia are removed from the image, brain tissuesegmentation is performed (Bach Cuadra, M., 2009). Theresulting white matter image is then binarized andfurther given as an input in the Freesurfer software(http://surfer.nmr.mgh.harvard.edu/) to provide accuratethree-dimensional reconstructions of the fetal brain.Results. High-resolution images of the cerebral fetalbrain, as obtained from the low-resolution acquired MRI,are presented for 4 subjects of age ranging from 29 to 32GA. An example is depicted in Figure 1. Accuracy in theautomated basal ganglia segmentation is compared withmanual segmentation using measurement of Dice similarity(DSI), with values above 0.7 considering to be a verygood agreement. In our sample we observed DSI valuesbetween 0.785 and 0.856. We further show the results ofgray-white matter segmentation overlaid on thehigh-resolution gray-scale images. The results arevisually checked for accuracy using the same principlesas commonly accepted in adult neuroimaging. Preliminary3D cortical reconstructions of the fetal brain are shownin Figure 2. Conclusion. We hereby present a completepipeline for the automated extraction of accuratethree-dimensional cortical surface of the fetal brain.These results are preliminary but promising, with theultimate goal to provide âeurooemovieâeuro of the normal gyraldevelopment. In turn, a precise knowledge of the normalfetal brain development will allow the quantification ofsubtle and early but clinically relevant deviations.Moreover, a precise understanding of the gyraldevelopment process may help to build hypotheses tounderstand the pathogenesis of several neurodevelopmentalconditions in which gyrification have been shown to bealtered (e.g. schizophrenia, autismâeuro¦). References.Rousseau, F. (2006), 'Registration-Based Approach forReconstruction of High-Resolution In Utero Fetal MR Brainimages', IEEE Transactions on Medical Imaging, vol. 13,no. 9, pp. 1072-1081. Jiang, S. (2007), 'MRI of MovingSubjects Using Multislice Snapshot Images With VolumeReconstruction (SVR): Application to Fetal, Neonatal, andAdult Brain Studies', IEEE Transactions on MedicalImaging, vol. 26, no. 7, pp. 967-980. Lee, S. (1997),'Scattered data interpolation with multilevel B-splines',IEEE Transactions on Visualization and Computer Graphics,vol. 3, no. 3, pp. 228-244. Bach Cuadra, M. (2010),'Central and Cortical Gray Mater Segmentation of MagneticResonance Images of the Fetal Brain', ISMRM Conference.Bach Cuadra, M. (2009), 'Brain tissue segmentation offetal MR images', MICCAI.
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A large percentage of bridges in the state of Iowa are classified as structurally or fiinctionally deficient. These bridges annually compete for a share of Iowa's limited transportation budget. To avoid an increase in the number of deficient bridges, the state of Iowa decided to implement a comprehensive Bridge Management System (BMS) and selected the Pontis BMS software as a bridge management tool. This program will be used to provide a selection of maintenance, repair, and replacement strategies for the bridge networks to achieve an efficient and possibly optimal allocation of resources. The Pontis BMS software uses a new rating system to evaluate extensive and detailed inspection data gathered for all bridge elements. To manually collect these data would be a highly time-consuming job. The objective of this work was to develop an automated-computerized methodology for an integrated data base that includes the rating conditions as defined in the Pontis program. Several of the available techniques that can be used to capture inspection data were reviewed, and the most suitable method was selected. To accomplish the objectives of this work, two userfriendly programs were developed. One program is used in the field to collect inspection data following a step-by-step procedure without the need to refer to the Pontis user's manuals. The other program is used in the office to read the inspection data and prepare input files for the Pontis BMS software. These two programs require users to have very limited knowledge of computers. On-line help screens as well as options for preparing, viewing, and printing inspection reports are also available. The developed data collection software will improve and expedite the process of conducting bridge inspections and preparing the required input files for the Pontis program. In addition, it will eliminate the need for large storage areas and will simplify retrieval of inspection data. Furthermore, the approach developed herein will facilitate transferring these captured data electronically between offices within the Iowa DOT and across the state.
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We have developed a digital holographic microscope (DHM), in a transmission mode, especially dedicated to the quantitative visualization of phase objects such as living cells. The method is based on an original numerical algorithm presented in detail elsewhere [Cuche et al., Appl. Opt. 38, 6994 (1999)]. DHM images of living cells in culture are shown for what is to our knowledge the first time. They represent the distribution of the optical path length over the cell, which has been measured with subwavelength accuracy. These DHM images are compared with those obtained by use of the widely used phase contrast and Nomarski differential interference contrast techniques.
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This report documents work undertaken in the demonstration of a low-cost Automatic Weight and Classification System (AWACS). An AWACS procurement specification and details of the results of the project are also included. The intent of the project is to support and encourage transferring research knowledge to state and local agencies and manufacturers through field demonstrations. Presently available, Weigh-in-Motion and Classification Systems are typically too expensive to permit the wide deployment necessary to obtain representative vehicle data. Piezo electric technology has been used in the United Kingdom and Europe and is believed to be the basic element in a low-cost AWACS. Low-cost systems have been installed at two sites, one in Portland Cement Concrete (PCC) pavement in Iowa and the other in Asphaltic Cement Concrete (ACC) pavement in Minnesota to provide experience with both types of pavement. The systems provide axle weights, gross vehicle weight, axle spacing, vehicle classification, vehicle speed, vehicle count, and time of arrival. In addition, system self-calibration and a method to predict contact tire pressure is included in the system design. The study has shown that in the PCC pavement, the AWACS is capable of meeting the needs of state and federal highway agencies, producing accuracies comparable to many current commercial WIM devices. This is being achieved at a procurement cost of substantially less than currently available equipment. In the ACC pavement the accuracies were less than those observed in the PCC pavement which is concluded to result from a low pavement rigidity at this site. Further work is needed to assess the AWACS performance at a range of sites in ACC pavements.
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Although severe patient-ventilator asynchrony is frequent during invasive and non-invasive mechanical ventilation, diagnosing such asynchronies usually requires the presence at the bedside of an experienced clinician to assess the tracings displayed on the ventilator screen, thus explaining why evaluating patient-ventilator interaction remains a challenge in daily clinical practice. In the previous issue of Critical Care, Sinderby and colleagues present a new automated method to detect, quantify, and display patient-ventilator interaction. In this validation study, the automatic method is as efficient as experts in mechanical ventilation. This promising system could help clinicians extend their knowledge about patient-ventilator interaction and further improve assisted mechanical ventilation.
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An important aspect of immune monitoring for vaccine development, clinical trials, and research is the detection, measurement, and comparison of antigen-specific T-cells from subject samples under different conditions. Antigen-specific T-cells compose a very small fraction of total T-cells. Developments in cytometry technology over the past five years have enabled the measurement of single-cells in a multivariate and high-throughput manner. This growth in both dimensionality and quantity of data continues to pose a challenge for effective identification and visualization of rare cell subsets, such as antigen-specific T-cells. Dimension reduction and feature extraction play pivotal role in both identifying and visualizing cell populations of interest in large, multi-dimensional cytometry datasets. However, the automated identification and visualization of rare, high-dimensional cell subsets remains challenging. Here we demonstrate how a systematic and integrated approach combining targeted feature extraction with dimension reduction can be used to identify and visualize biological differences in rare, antigen-specific cell populations. By using OpenCyto to perform semi-automated gating and features extraction of flow cytometry data, followed by dimensionality reduction with t-SNE we are able to identify polyfunctional subpopulations of antigen-specific T-cells and visualize treatment-specific differences between them.
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L’Escola Politècnica Superior de la Universitat de Vic disposa d’una cèl·lula de fabricació flexible del fabricant Festo, que simula un procés d’emmagatzematge automàtic, aquesta cèl·lula esta composta per quatre estacions de muntatge diferenciades i independents, l’estació palets, l’estació plaques, l’estació magatzem intermedi i l’estació transport. Cada una d’aquestes estacions està formada per sensors i actuadors elèctrics i pneumàtics del fabricant Festo que van connectats a un PLC SIEMENS S7-300.Els quatre PLC’s (un per cada estació) estan connectats entre ells mitjançant el bus de comunicacions industrials Profibus. L’objectiu d’aquest treball consisteix en l’adaptació de la programació dels PLC’s i la realització d’un SCADA per tal de controlar el funcionament del conjunt de la cèl·lula de fabricació a través del software Vijeo Citect, d’aquesta manera es coneixerà el funcionament de la cèl·lula i permetrà treure’n rendiment per la docència. Aquest projecte ha estat realitzat en quatre fases principals. 1. Estudi i coneixement de les estacions, en aquesta fase s’han estudiat els manuals de funcionament de les estacions i s’han interpretat els codis de programació dels seus PLCs, amb l’objectiu de conèixer bé el programa per tal de interaccionar-hi més endavant amb el sistema SCADA 2. Disseny i programació del sistema SCADA, en aquesta fase s’ha realitzat tot el disseny gràfic de les pantalles de la interfície SCADA així com la programació dels objectes, la connexió amb els PLCs i la base de dades. 3. Posada en marxa del sistema complert, quan es coneixia abastament el funcionament de les estacions i el sistema SCADA estava completat s’ha fet la posada en marxa del conjunt i s’ha comprovat el correcte funcionament i interacció dels sistemes. 4. Realització de la memòria del projecte, en aquesta ultima fase s’ha realitzat la memòria del projecte on s’expliquen les característiques i funcionament de totes les estacions i del sistema SCADA. La conclusió més rellevant obtinguda en aquest treball, és la clara visualització de la potència i simplicitat que han aportat els sistemes SCADA al món de l’automatització, anys enrere per la supervisió de l’estat d’un sistema automatitzat era necessari disposar d’un gran espai amb grans panells de control formats per una gran quantitat de pilots lluminosos, potenciòmetres, interruptors, polsadors, displays i sobretot un voluminós i complexa cablejat, gràcies als sistemes SCADA avui en dia tot això pot quedar reduït a un PC o terminal tàctil, amb pantalles gràfiques clares i una gran quantitat d’opcions de supervisió control i configuració del sistema automatitzat.