Regional-scale integration of multi-scale hydrological and geophysical data using a two-step Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale for the purpose of improving predictions of groundwater flow and solute transport. However, extending corresponding approaches to the regional scale still represents one of the major challenges in the domain of hydrogeophysics. To address this problem, we have developed a regional-scale data integration methodology based on a two-step Bayesian sequential simulation approach. Our objective is to generate high-resolution stochastic realizations of the regional-scale hydraulic conductivity field in the common case where there exist spatially exhaustive but poorly resolved measurements of a related geophysical parameter, as well as highly resolved but spatially sparse collocated measurements of this geophysical parameter and the hydraulic conductivity. To integrate this multi-scale, multi-parameter database, we first link the low- and high-resolution geophysical data via a stochastic downscaling procedure. This is followed by relating the downscaled geophysical data to the high-resolution hydraulic conductivity distribution. After outlining the general methodology of the approach, we demonstrate its application to a realistic synthetic example where we consider as data high-resolution measurements of the hydraulic and electrical conductivities at a small number of borehole locations, as well as spatially exhaustive, low-resolution estimates of the electrical conductivity obtained from surface-based electrical resistivity tomography. The different stochastic realizations of the hydraulic conductivity field obtained using our procedure are validated by comparing their solute transport behaviour with that of the underlying ?true? hydraulic conductivity field. We find that, even in the presence of strong subsurface heterogeneity, our proposed procedure allows for the generation of faithful representations of the regional-scale hydraulic conductivity structure and reliable predictions of solute transport over long, regional-scale distances.

Management of a post-operative multi-resistant infectious spondylitis associated with a kyphotic deformity.

Anterior spinal infection (prevertebral abscess and/or discitis) after posterior instrumentation for vertebral fractures is a challenging complication, since a new implant may become necessary anteriorly, in a septic environment. Generally accepted management guidelines are yet to be established. The authors present a case of posterior instrumentation for fractures of T12 and L1, complicated after 9 months with an anterior infection (prevertebral abscess and discitis) with extended-spectrum beta-lactamase (ESBL) producing Escherichia coli (E. coli). This case is unique in that the multi-resistant organism was isolated only after the second stage of infection treatment, which consisted of anterior débridement and anterior implantation of titanium cages and rods. In this particular case, infection was controlled despite implantation of multiple cages, screws and rods, and fusion was achieved, by means of intravenous antibiotic treatment for 12 months. At the latest follow-up, 24 months post surgery, there was no evidence of infection. This problem case may be helpful for surgeons confronted with spinal deformities secondary to infections with multi-resistant organisms.

BCN-Routing : càlcul web de rutes amb pgRouting, OpenStreetMaps i OpenLayers

Es presenta un sistema acurat de càlcul web d'itineraris mínims (per a vianants i per a vehicles) entre dos punts de la ciutat de Barcelona, un dels quals es triat per l'usuari directament a sobre un mapa i l'altre, alternativament, a sobre el mateix mapa o bé a sobre una llista de selecció de les principals atraccions turístiques de Barcelona.El sistema es troba implementat per medi de MapServer (1) com a servidor, OpenLayers (2) per a la interfície d'usuari, una base de dades PostrgreSQL (3)/PostGIS (4) que recull dades d'OpenStreetMaps (5) per a la navegació i dades introduïdes manualment, per a la llista de selecció d'atraccions turístiques. Per al càlcul d'itineraris es fa servir, pgRouting (6) alhora que s'accedeix a la cartografia de CartoCiudad (7) per a mostrar un mapa de base i opcionalment els noms dels carrers i punts d'interès a partir de les capes FondoUrbano, Vial i Topónimo del servidor WMS de CartoCiudad.Tot el sistema corre a sobre Windows 7 Home Premium (8).Així mateix es presenten quatre noves funcions i un tipus definit per l'usuari de PostgreSQL per al càlcul acurat d'itineraris mínims i l'estudi teòric que justifica la seva bondat.

An approach to vision-based station keeping for an unmanned underwater vehicle

This paper presents an automatic vision-based system for UUV station keeping. The vehicle is equipped with a down-looking camera, which provides images of the sea-floor. The station keeping system is based on a feature-based motion detection algorithm, which exploits standard correlation and explicit textural analysis to solve the correspondence problem. A visual map of the area surveyed by the vehicle is constructed to increase the flexibility of the system, allowing the vehicle to position itself when it has lost the reference image. The testing platform is the URIS underwater vehicle. Experimental results demonstrating the behavior of the system on a real environment are presented

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

A review of sensor fusion techniques for underwater vehicle navigation

This work provides a general description of the multi sensor data fusion concept, along with a new classification of currently used sensor fusion techniques for unmanned underwater vehicles (UUV). Unlike previous proposals that focus the classification on the sensors involved in the fusion, we propose a synthetic approach that is focused on the techniques involved in the fusion and their applications in UUV navigation. We believe that our approach is better oriented towards the development of sensor fusion systems, since a sensor fusion architecture should be first of all focused on its goals and then on the fused sensors

Enhanced multi-layer protection in multi-service GMPLS networks

This paper focuses on QoS routing with protection in an MPLS network over an optical layer. In this multi-layer scenario each layer deploys its own fault management methods. A partially protected optical layer is proposed and the rest of the network is protected at the MPLS layer. New protection schemes that avoid protection duplications are proposed. Moreover, this paper also introduces a new traffic classification based on the level of reliability. The failure impact is evaluated in terms of recovery time depending on the traffic class. The proposed schemes also include a novel variation of minimum interference routing and shared segment backup computation. A complete set of experiments proves that the proposed schemes are more efficient as compared to the previous ones, in terms of resources used to protect the network, failure impact and the request rejection ratio

Profitability, uncertainty and multi-product firm product proliferation: The Spanish car industry

This article studies how product introduction decisions relate to profitability and uncertainty in the context of multi-product firms and product differentiation. These two features, common to many modern industries, have not received much attention in the literature as compared to the classical problem of firm entry, even if the determinants of firm and product entry are quite different. The theoretical predictions about the sign of the impact of uncertainty on product entry are not conclusive. Therefore, an econometric model relating firms’ product introduction decisions with profitability and profit uncertainty is proposed. Firm’s estimated profits are obtained from a structural model of product demand and supply, and uncertainty is proxied by profits’ variance. The empirical analysis is carried out using data on the Spanish car industry for the period 1990-2000. The results show a positive relationship between product introduction and profitability, and a negative one with respect to profit variability. Interestingly, the degree of uncertainty appears to be a driving force of entry stronger than profitability, suggesting that the product proliferation process in the Spanish car market may have been mainly a consequence of lower uncertainty rather than the result of having a more profitable market

A simulation-based algorithm for solving the resource-assignment problem in satellite telecommunication networks

This paper proposes an heuristic for the scheduling of capacity requests and the periodic assignment of radio resources in geostationary (GEO) satellite networks with star topology, using the Demand Assigned Multiple Access (DAMA) protocol in the link layer, and Multi-Frequency Time Division Multiple Access (MF-TDMA) and Adaptive Coding and Modulation (ACM) in the physical layer.

Integración de Google Maps y TSP Solvers para la definición y resolución del TSP

Este trabajo final de carrera presenta la arquitectura e implementación de un entorno web para la descripción y visualización de instancias reales del TSP (Travelling Salesman Problem), a través de Google Maps, y su posterior resoluación mediante tècnicas de optimización combinatoria.

Multi-scale label interaction to improve object detection and segmentation

The project aims at advancing the state of the art in the use of context information for classification of image and video data. The use of context in the classification of images has been showed of great importance to improve the performance of actual object recognition systems. In our project we proposed the concept of Multi-scale Feature Labels as a general and compact method to exploit the local and global context. The feature extraction from the discriminative probability or classification confidence label field is of great novelty. Moreover the use of a multi-scale representation of the feature labels lead to a compact and efficient description of the context. The goal of the project has been also to provide a general-purpose method and prove its suitability in different image/video analysis problem. The two-year project generated 5 journal publications (plus 2 under submission), 10 conference publications (plus 2 under submission) and one patent (plus 1 pending). Of these publications, a relevant number make use of the main result of this project to improve the results in detection and/or segmentation of objects.

Feasibility of replacing multiple ADSL connections with Multi-Dwelling Access

This final project was made for the Broadband/Implementation department of TeliaSonera Finland. The question to be examined is if the operator should replace multiple ADSL connections implemented over a leased line with Multi-Dwelling access based on an Ethernet/Optical Fibre access network. The project starts with describing the technology related to these access network solu-tions and presents the technology that is used in TeliaSonera Finland's access network. It continues from the technology to describe the problem with some of the ADSL implemen-tations of TeliaSonera. The problem is the implementations done over a leased line that can cost TeliaSonera over years as much as a possible investment to extend network when there is several lines leased to the same building. The project proposes a Multi-Dwelling access as a solution to this problem and defines the circumstances when to use it. After a satisfactory solution has found the project takes a view how implementation of the solution might alter the network and a new problem is found. When used commonly to replace need of ADSL implementation Multi-Dwelling access would significantly increase optical cable congestion near operators POP. As a final deed this project also proposes a technical change to existing way to implement multi-dwelling access with EPON technology.

Driver scheduling problem modelling

The Drivers Scheduling Problem (DSP) consists of selecting a set of duties for vehicle drivers, for example buses, trains, plane or boat drivers or pilots, for the transportation of passengers or goods. This is a complex problem because it involves several constraints related to labour and company rules and can also present different evaluation criteria and objectives. Being able to develop an adequate model for this problem that can represent the real problem as close as possible is an important research area.The main objective of this research work is to present new mathematical models to the DSP problem that represent all the complexity of the drivers scheduling problem, and also demonstrate that the solutions of these models can be easily implemented in real situations. This issue has been recognized by several authors and as important problem in Public Transportation. The most well-known and general formulation for the DSP is a Set Partition/Set Covering Model (SPP/SCP). However, to a large extend these models simplify some of the specific business aspects and issues of real problems. This makes it difficult to use these models as automatic planning systems because the schedules obtained must be modified manually to be implemented in real situations. Based on extensive passenger transportation experience in bus companies in Portugal, we propose new alternative models to formulate the DSP problem. These models are also based on Set Partitioning/Covering Models; however, they take into account the bus operator issues and the perspective opinions and environment of the user.We follow the steps of the Operations Research Methodology which consist of: Identify the Problem; Understand the System; Formulate a Mathematical Model; Verify the Model; Select the Best Alternative; Present the Results of theAnalysis and Implement and Evaluate. All the processes are done with close participation and involvement of the final users from different transportation companies. The planner s opinion and main criticisms are used to improve the proposed model in a continuous enrichment process. The final objective is to have a model that can be incorporated into an information system to be used as an automatic tool to produce driver schedules. Therefore, the criteria for evaluating the models is the capacity to generate real and useful schedules that can be implemented without many manual adjustments or modifications. We have considered the following as measures of the quality of the model: simplicity, solution quality and applicability. We tested the alternative models with a set of real data obtained from several different transportation companies and analyzed the optimal schedules obtained with respect to the applicability of the solution to the real situation. To do this, the schedules were analyzed by the planners to determine their quality and applicability. The main result of this work is the proposition of new mathematical models for the DSP that better represent the realities of the passenger transportation operators and lead to better schedules that can be implemented directly in real situations.

Optimization of multiclass queueing networks with changeover times via the achievable region method: Part II, the multi-station case

We address the problem of scheduling a multi-station multiclassqueueing network (MQNET) with server changeover times to minimizesteady-state mean job holding costs. We present new lower boundson the best achievable cost that emerge as the values ofmathematical programming problems (linear, semidefinite, andconvex) over relaxed formulations of the system's achievableperformance region. The constraints on achievable performancedefining these formulations are obtained by formulatingsystem's equilibrium relations. Our contributions include: (1) aflow conservation interpretation and closed formulae for theconstraints previously derived by the potential function method;(2) new work decomposition laws for MQNETs; (3) new constraints(linear, convex, and semidefinite) on the performance region offirst and second moments of queue lengths for MQNETs; (4) a fastbound for a MQNET with N customer classes computed in N steps; (5)two heuristic scheduling policies: a priority-index policy, anda policy extracted from the solution of a linear programmingrelaxation.

Multi-modal assessment of long-term erythropoietin treatment after neonatal hypoxic-ischemic injury in rat brain.

Erythropoietin (EPO) has been recognized as a neuroprotective agent. In animal models of neonatal brain injury, exogenous EPO has been shown to reduce lesion size, improve structure and function. Experimental studies have focused on short course treatment after injury. Timing, dose and length of treatment in preterm brain damage remain to be defined. We have evaluated the effects of high dose and long-term EPO treatment in hypoxic-ischemic (HI) injury in 3 days old (P3) rat pups using histopathology, magnetic resonance imaging (MRI) and spectroscopy (MRS) as well as functional assessment with somatosensory-evoked potentials (SEP). After HI, rat pups were assessed by MRI for initial damage and were randomized to receive EPO or vehicle. At the end of treatment period (P25) the size of resulting cortical damage and white matter (WM) microstructure integrity were assessed by MRI and cortical metabolism by MRS. Whisker elicited SEP were recorded to evaluate somatosensory function. Brains were collected for neuropathological assessment. The EPO treated animals did not show significant decrease of the HI induced cortical loss at P25. WM microstructure measured by diffusion tensor imaging was improved and SEP response in the injured cortex was recovered in the EPO treated animals compared to vehicle treated animals. In addition, the metabolic profile was less altered in the EPO group. Long-term treatment with high dose EPO after HI injury in the very immature rat brain induced recovery of WM microstructure and connectivity as well as somatosensory cortical function despite no effects on volume of cortical damage. This indicates that long-term high-dose EPO induces recovery of structural and functional connectivity despite persisting gross anatomical cortical alteration resulting from HI.