Search results for "Bay"
showing 10 items of 1187 documents
Inferring intentions through state representations in cooperative human-robot environments
2014
Humans and robots working safely and seamlessly together in a cooperative environment is one of the future goals of the robotics community. When humans and robots can work together in the same space, a whole class of tasks becomes amenable to automation, ranging from collaborative assembly to parts and material handling to delivery. Proposed standards exist for collaborative human-robot safety, but they focus on limiting the approach distances and contact forces between the human and the robot. These standards focus on reactive processes based only on current sensor readings. They do not consider future states or task-relevant information. A key enabler for human-robot safety in cooperative…
Thorium-234 derived information on particle residence times and sediment deposition in shallow waters of the south-western Baltic Sea
2009
Abstract Activities of the naturally occurring, short-lived and highly particle-reactive radionuclide tracer 234 Th in the dissolved and particulate phase were measured at three shallow-water stations (maximum water depths: 15.6, 22.7 and 30.1 m) in Mecklenburg Bay (south-western Baltic Sea) to constrain the time scales of the dynamics and the depositional fate of particulate matter. Activities of particle-associated (> 0.4 μm) and total (particulate + dissolved) 234 Th were in the range of 0.08–0.11 dpm L − 1 and 0.11–0.20 dpm L − 1 , respectively. The activity ratio of total 234 Th and its long-lived and conservative parent nuclide 238 U was well below unity (range: 0.09–0.19) indicating …
Bayesian approach for uncertainty quantification in water quality modelling: The influence of prior distribution
2010
Summary Mathematical models are of common use in urban drainage, and they are increasingly being applied to support decisions about design and alternative management strategies. In this context, uncertainty analysis is of undoubted necessity in urban drainage modelling. However, despite the crucial role played by uncertainty quantification, several methodological aspects need to be clarified and deserve further investigation, especially in water quality modelling. One of them is related to the “a priori” hypotheses involved in the uncertainty analysis. Such hypotheses are usually condensed in “a priori” distributions assessing the most likely values for model parameters. This paper explores…
Mapping Sediment Accumulation Rate by using Volume magnetic Susceptibility Core Correlation in a contaminated Bay (Lake Geneva, Switzerland)
2003
The Bay of Vidy is the most contaminated area of Lake Geneva: contamination is caused by the effluent of the sewage treatment plant (STP) of the City of Lausanne. The implementation of a chemical stage in the treatment plant to remove phosphorus using FeC13 in 1971 is indirectly recorded in the lake sediments by a strong and sharp increase in the volume magnetic susceptibility (VMS) signal. A total of 43 sediment cores have been retrieved and measured for VMS. The synchronism of the VMS signal increase and its relation to the implementation of the P-removal stage in the STP has been shown in seven 137Cs-dated sediment cores. The VMS signal has been used to date by stratigraphie correlation …
Apparent discrepancy in contamination history of a sub-tropical estuary evaluated through 210Pb profile and chronostratigraphical markers.
2005
Abstract Zn and Cd concentrations, stable lead isotopes and 210 Pb-derived chronology were determined in a sediment core sampled at Sepetiba Bay (South-eastern Brazil). During the last decades, the bay’s watershed has been modified by the increase of industrial activities and human interventions. In particular, Zn and Cd ore treatment plants were built near the coast in 1960 and 1970, respectively, and water has been diverted from the adjacent Paraiba do Sul River watershed since 1950. The core collected at shallow depth near the industrial area exhibits four successive events: (i) at 50 cm depth, a change in the 206 Pb/ 207 Pb ratio from about 1.162 to more than 1.18 might be the result of…
Passive millimeter wave image classification with large scale Gaussian processes
2017
Passive Millimeter Wave Images (PMMWIs) are being increasingly used to identify and localize objects concealed under clothing. Taking into account the quality of these images and the unknown position, shape, and size of the hidden objects, large data sets are required to build successful classification/detection systems. Kernel methods, in particular Gaussian Processes (GPs), are sound, flexible, and popular techniques to address supervised learning problems. Unfortunately, their computational cost is known to be prohibitive for large scale applications. In this work, we present a novel approach to PMMWI classification based on the use of Gaussian Processes for large data sets. The proposed…
Geographical variation in pharmacological prescription
2009
Promoting rational drug administration in treatments is one of the most important issues in Public Health. Bayesian hierarchical models are a very useful tool for incorporating geographical information into the analysis of pharmacological prescription data. They allow the mapping of spatial components which express the trend of geographical variation. In addition, these models are able to deal with uncertainty in a sequential way through prior distributions on parameters and hyperparameters. Bayes' theorem combines all types of information and provides the posterior distribution which is computed through Markov Chain Monte Carlo (MCMC) simulation methods. Simulated data for pharmacological …
A Novel System for Multi-level Crohn’s Disease Classification and Grading Based on a Multiclass Support Vector Machine
2020
Crohn’s disease (CD) is a chronic inflammatory condition of the gastrointestinal tract that can highly alter patient’s quality of life. Diagnostic imaging, such as Enterography Magnetic Resonance Imaging (E-MRI), provides crucial information for CD activity assessment. Automatic learning methods play a fundamental role in the classification of CD and allow to avoid the long and expensive manual classification process by radiologists. This paper presents a novel classification method that uses a multiclass Support Vector Machine (SVM) based on a Radial Basis Function (RBF) kernel for the grading of CD inflammatory activity. To validate the system, we have used a dataset composed of 800 E-MRI…
Temperamentos afectivos y edad de inicio en pacientes bipolares tipo II
2016
Actualmente es imperante contar con indicadores que posibiliten realizar una detección temprana y correcta del trastorno bipolar en general, y del tipo II, en particular. Los temperamentos afectivos constituyen estilos de reactividad emocional temporalmente estables a lo largo del ciclo vital, con una importante base biológica. Dada la escasez de investigaciones al respecto, se exploraron posibles asociaciones entre la edad de inicio de 32 pacientes eutímicos con diagnóstico de trastorno bipolar tipo II y los temperamentos afectivos ciclotímico, depresivo, irritable, ansioso e hipertímico. Los participantes presentaron una edad media de 51,5 años (rango intercuartil 8) y el 65,6% de la mues…
Using Bayesian networks to describe hydrologic processes
2014
Masteroppgave i Informasjons- og kommunikasjonsteknologi IKT590 Universitetet i Agder 2014 The goal for this Masters thesis is to explore the use of dynamic Bayesian networks for describinghydrologic processes. The main intent is to try and provide better descriptions of the uncertainties thatare tied to dealing with such complex and partially unknown processes, while also trying to reducethese uncertainties. For this purpose I have translated part of a well known and widely useddeterministic model, the snow module of the HBV model, into a dynamic Bayesian network.