Search results for "Data mining"
showing 10 items of 907 documents
Distributed Clustering Algorithm for Spatial Field Reconstruction in Wireless Sensor Networks
2015
En este trabajo, consideramos el problema de la estimación espacial distribuida para la reconstrucción del campo radio en redes de sensores inalámbricos. Para estimar el campo, se utiliza una técnica geoestadística llamada kriging. La estimación espacial centralizada con un gran número de sensores conllevan un elevado coste computacional y gasto de energía. Presentamos un novedoso algoritmo de clustering distribuido para estimar mapas de interferencia espacial, que son esenciales para las operaciones y la gestión de las futuras redes inalámbricas. En este algoritmo, los clústeres de sensores se forman de forma adaptativa mediante la minimización de la varianza de kriging. El cálculo del sem…
Visual Data Mining : Real Applications and New Approaches
2014
En los últimos años, la visualización de datos se ha convertido en un área muy activa y vital de la investigación. Es una manera eficaz de analizar grandes cantidades de datos para identificar correlaciones, tendencias, valores extremos, patrones, entre otra mucha información. Los datos sin procesar a menudo carecen de sentido, pero representar dichos datos visualmente ofrece al público un contexto importante para entender la información contenida en ellos. Debido a la importancia de esta área de investigación, y a su novedad, esta tesis se centra en esta temática y pretende descubrir nuevos hallazgos, extraer conclusiones y legar contribuciones relevantes a la comunidad científica en dicho…
A Digital Twin for Lift Planning With Offshore Heave Compensated Cranes
2020
Abstract This paper presents a state-of-the-art digital twin of a hydraulic actuated winch that is used for heave compensation in offshore applications. The digital twin is used as part of a larger simulation model that involves all necessary components to perform lift planning and, subsequently, determine the corresponding weather window. The winch simulation model is described and verified by means of full-scale measurements. In addition, a set of acceptance criteria are presented that should be used whenever verifying digital twins of heave compensating winches that are to be used for lift planning.
Scientific Merits and Analytical Challenges of Tree‐Ring Densitometry
2019
X-ray microdensitometry on annually resolved tree-ring samples has gained an exceptional position in last-millennium paleoclimatology through the maximum latewood density (MXD) parameter, but also increasingly through other density parameters. For 50 years, X-ray based measurement techniques have been the de facto standard. However, studies report offsets in the mean levels for MXD measurements derived from different laboratories, indicating challenges of accuracy and precision. Moreover, reflected visible light-based techniques are becoming increasingly popular, and wood anatomical techniques are emerging as a potentially powerful pathway to extract density information at the highest resol…
Accurate estimation of retinal vessel width using bagged decision trees and an extended multiresolution Hermite model.
2012
We present an algorithm estimating the width of retinal vessels in fundus camera images. The algorithm uses a novel parametric surface model of the cross-sectional intensities of vessels, and ensembles of bagged decision trees to estimate the local width from the parameters of the best-fit surface. We report comparative tests with REVIEW, currently the public database of reference for retinal width estimation, containing 16 images with 193 annotated vessel segments and 5066 profile points annotated manually by three independent experts. Comparative tests are reported also with our own set of 378 vessel widths selected sparsely in 38 images from the Tayside Scotland diabetic retinopathy scre…
Active learning strategies for the deduplication of electronic patient data using classification trees.
2012
Graphical abstractDisplay Omitted Highlights? Active learning for medical record linkage is used on a large data set. ? We compare a simple active learning strategy with a more sophisticated variant. ? The active learning method of Sarawagi and Bhamidipaty (2002) 6] is extended. ? We deliver insights into the variations of the results due to random sampling in the active learning strategies. IntroductionSupervised record linkage methods often require a clerical review to gain informative training data. Active learning means to actively prompt the user to label data with special characteristics in order to minimise the review costs. We conducted an empirical evaluation to investigate whether…
A context-aware approach for long-term behavioural change detection and abnormality prediction in ambient assisted living
2015
This research aims to describe pattern recognition models for detecting behavioural and health-related changes in a patient who is monitored continuously in an assisted living environment. The early anticipation of anomalies can improve the rate of disease prevention. Here we present different learning techniques for predicting abnormalities and behavioural trends in various user contexts. In this paper we described a Hidden Markov Model based approach for detecting abnormalities in daily activities, a process of identifying irregularity in routine behaviours from statistical histories and an exponential smoothing technique to predict future changes in various vital signs. The outcomes of t…
Prediction of stock index futures prices based on fuzzy sets and multivariate fuzzy time series
2015
Abstract This paper makes a prediction of Chinese stock index (CSI) future prices using fuzzy sets and multivariate fuzzy time series method. We select Chinese CSI 300 index futures as the research object. The fuzzy time series model combines the fuzzy theory and the time series theory, thus this model can solve the fuzzy data in stock index futures prices. This paper establishes a multivariate model and improves the accuracy of computation. By combing traditional fuzzy time series models and rough set method, we use fuzzy c-mean algorithm to make the data into discrete. Further more, we deal with the rules in mature modules of the rough set and then refine the rules using data mining algor…
Visualizing Time Series State Changes with Prototype Based Clustering
2009
Modern process and condition monitoring systems produce a huge amount of data which is hard to analyze manually. Previous analyzing techniques disregard time information and concentrate only for the indentification of normal and abnormal operational states. We present a new method for visualizing operational states and overall order of the transitions between them. This method is implemented to a visualization tool which helps the user to see the overall development of operational states allowing to find causes for abnormal behaviour. In the end visualization tool is tested in practice with real time series data collected from gear unit.
Maxillary sinus lift performed using ultrasound. Evaluation of 21 patients.
2008
Purpose: The aim of the present study was to evaluate the sinus membrane perforations that occurred during a sinus lift procedure using the ultrasound technique, and to evaluate the bone gain obtained. Materials and methods: In 21 patients, 26 sinus lifts were performed using ultrasound and filled with bone graft material. The bone height and the bone gain obtained were observed in postoperative orthopantomographs, correcting for previous distortion. Results: Of the 26 maxillary sinus lifts, 4 Schneiderian membrane perforations were observed. The average bone height prior to the intervention was 3.5 mm (scale 0.6- 8.7 mm ) and the average postsurgical bone height was 10.8 mm (scale 7.5- 15.…