Road environment modeling using robust perspective analysis and recursive Bayesian segmentation

Recently, vision-based advanced driver-assistance systems (ADAS) have received a new increased interest to enhance driving safety. In particular, due to its high performance–cost ratio, mono-camera systems are arising as the main focus of this field of work. In this paper we present a novel on-board road modeling and vehicle detection system, which is a part of the result of the European I-WAY project. The system relies on a robust estimation of the perspective of the scene, which adapts to the dynamics of the vehicle and generates a stabilized rectified image of the road plane. This rectified plane is used by a recursive Bayesian classi- fier, which classifies pixels as belonging to different classes corresponding to the elements of interest of the scenario. This stage works as an intermediate layer that isolates subsequent modules since it absorbs the inherent variability of the scene. The system has been tested on-road, in different scenarios, including varied illumination and adverse weather conditions, and the results have been proved to be remarkable even for such complex scenarios.

Biogenic opal estimation of deep-sea sediment cores from the Scotia Sea

We present biogenic opal flux records from two deep-sea sites in the Scotia Sea (MD07-3133 and MD07-3134) at decadal-scale resolution, covering the last glacial cycle. Besides conventional and time-consuming biogenic opal measuring methods, we introduce new biogenic opal estimation methods derived from sediment colour b*, wet bulk density, Si/Ti-count ratio, and Fourier transform infrared spectroscopy (FTIRS). All methods capture the biogenic opal amplitude, however, FTIRS - a novel method for marine sediment - yields the most reliable results. 230Th normalization data show strong differences in sediment focusing with intensified sediment focusing during glacial times. At MD07-3134 230Th normalized biogenic opal fluxes vary between 0.2 and 2.5 g/cm2/kyr. Our biogenic opal flux records indicate bioproductivity changes in the Southern Ocean, strongly influenced by sea ice distribution and also summer sea surface temperature changes. South of the Antarctic Polar Front, lowest bioproductivity occurred during the Last Glacial Maximum when upwelling of mid-depth water was reduced and sea ice cover intensified. Around 17 ka, bioproductivity increased abruptly, corresponding to rising atmospheric CO2 contents and decreasing seasonal sea ice coverage.

A földrajzi távolság, a kulturális hasonlóság és a szabadkereskedelem hatása a borkereskedelemre = Effects on the global wine trade of geographical distance, cultural and linguistic similarity, and free trade

A globalizálódó világgazdaságban a vezető bortermelő országok egyre jelentősebb borkereskedelmet bonyolítanak le egymás között. Míg Európában a fogyasztók egyre kevesebb bort vásárolnak, addig Amerikában és Ázsiában a bor iránti kereslet folyamatosan bővül: a borkereskedelem földrajzi átrendeződése zajlik. A kulturális hasonlóság és a földrajzi távolság kereskedelemre gyakorolt hatását gyakran a kereskedelemelméletek gravitációs modelljével elemzik. E tanulmány azt vizsgálja, hogy a fő borexportáló országok közötti földrajzi távolság, kulturális hasonlóság és szabadkereskedelem milyen hatással van a nemzetközi borkereskedelemre, annak költségeire. A regressziós becslés eredményei alátámasztják, hogy a borkereskedelem költségei alacsonyabbak, ha a kereskedelmi partnerek kulturálisan hasonlók, földrajzilag közel helyezkednek el egymáshoz, vagy van tengeri kikötőjük, tagjai a WTO-nak, illetve ha kötöttek egymással regionális kereskedelmi megállapodást. Ezenkívül megállapítható, hogy az angolszász, a latin-amerikai és az európai kulturális klaszterek elsősorban egymással kereskednek. A kutatás számos kulturális változó alkalmazásával és több ökonometriai modell, illetve becslési eljárás nagymintás tesztelésével gazdagítja a szakirodalmat. ____ In a globalizing world, major wine-producing countries export considerable quantities to the global wine market and turn over a notable trade, but in what happens European wine regions differ markedly from the New World. Here major wine producers suffered a remarkable fall in domestic wine consumption in recent decades, while New World wine producers increased their production potential and generated new foreign demand. The changes have been joined by geographical relocation of wine consumption and exports. The gravity equation can be derived from demand-side or supply-side theory-consistent estimation methods that suggest relationships between the size of the economies, geographical distances, cultural similarities, and size of their trade. The paper analyses the effects of cultural and geographical proximity, free trade, and linguistic similarity on bilateral trade in the main wine-producing countries, using a cross-section gravity model for 2012. The results suggest that larger countries export more wine, while transport costs rise in line with geographical distance and are higher for landlocked trading partners. Wine export costs are lower if trading partners are culturally similar, share a dominant religion, or are both WTO members with regional trade agreements. Anglo-Saxon, Germanic, Latin American and Latin European countries mainly trade wines within their groups. The paper looks to extend the number of trading partners, investigate the effect of language clusters, and confirm that the results are robust by different econometric methodologies.

Freeway travel time estimation and prediction using dynamic neural networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. ^ This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.^

Freeway Travel Time Estimation and Prediction Using Dynamic Neural Networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.

Estimate of the (R)USLE rainfall erosivity factor from monthly precipitation data in mainland Spain

The need for continuous recording rain gauges makes it difficult to determine the rainfall erosivity factor (R-factor) of the (R)USLE model in areas without good temporal data coverage. In mainland Spain, the Nature Conservation Institute (ICONA) determined the R-factor at few selected pluviographs, so simple estimates of the R-factor are definitely of great interest. The objectives of this study were: (1) to identify a readily available estimate of the R-factor for mainland Spain; (2) to discuss the applicability of a single (global) estimate based on analysis of regional results; (3) to evaluate the effect of record length on estimate precision and accuracy; and (4) to validate an available regression model developed by ICONA. Four estimators based on monthly precipitation were computed at 74 rainfall stations throughout mainland Spain. The regression analysis conducted at a global level clearly showed that modified Fournier index (MFI) ranked first among all assessed indexes. Applicability of this preliminary global model across mainland Spain was evaluated by analyzing regression results obtained at a regional level. It was found that three contiguous regions of eastern Spain (Catalonia, Valencian Community and Murcia) could have a different rainfall erosivity pattern, so a new regression analysis was conducted by dividing mainland Spain into two areas: Eastern Spain and plateau-lowland area. A comparative analysis concluded that the bi-areal regression model based on MFI for a 10-year record length provided a simple, precise and accurate estimate of the R-factor in mainland Spain. Finally, validation of the regression model proposed by ICONA showed that R-ICONA index overpredicted the R-factor by approximately 19%.

Exploring the joint compositional variability of major components and trace elements in the Tellus soil geochemistry survey (Northern Ireland)

The complexity of modern geochemical data sets is increasing in several aspects (number of available samples, number of elements measured, number of matrices analysed, geological-environmental variability covered, etc), hence it is becoming increasingly necessary to apply statistical methods to elucidate their structure. This paper presents an exploratory analysis of one such complex data set, the Tellus geochemical soil survey of Northern Ireland (NI). This exploratory analysis is based on one of the most fundamental exploratory tools, principal component analysis (PCA) and its graphical representation as a biplot, albeit in several variations: the set of elements included (only major oxides vs. all observed elements), the prior transformation applied to the data (none, a standardization or a logratio transformation) and the way the covariance matrix between components is estimated (classical estimation vs. robust estimation). Results show that a log-ratio PCA (robust or classical) of all available elements is the most powerful exploratory setting, providing the following insights: the first two processes controlling the whole geochemical variation in NI soils are peat coverage and a contrast between “mafic” and “felsic” background lithologies; peat covered areas are detected as outliers by a robust analysis, and can be then filtered out if required for further modelling; and peat coverage intensity can be quantified with the %Br in the subcomposition (Br, Rb, Ni).

Development of error correction techniques for nitrate-N load estimation models

Excess nutrient loads carried by streams and rivers are a great concern for environmental resource managers. In agricultural regions, excess loads are transported downstream to receiving water bodies, potentially causing algal blooms, which could lead to numerous ecological problems. To better understand nutrient load transport, and to develop appropriate water management plans, it is important to have accurate estimates of annual nutrient loads. This study used a Monte Carlo sub-sampling method and error-corrected statistical models to estimate annual nitrate-N loads from two watersheds in central Illinois. The performance of three load estimation methods (the seven-parameter log-linear model, the ratio estimator, and the flow-weighted averaging estimator) applied at one-, two-, four-, six-, and eight-week sampling frequencies were compared. Five error correction techniques; the existing composite method, and four new error correction techniques developed in this study; were applied to each combination of sampling frequency and load estimation method. On average, the most accurate error reduction technique, (proportional rectangular) resulted in 15% and 30% more accurate load estimates when compared to the most accurate uncorrected load estimation method (ratio estimator) for the two watersheds. Using error correction methods, it is possible to design more cost-effective monitoring plans by achieving the same load estimation accuracy with fewer observations. Finally, the optimum combinations of monitoring threshold and sampling frequency that minimizes the number of samples required to achieve specified levels of accuracy in load estimation were determined. For one- to three-weeks sampling frequencies, combined threshold/fixed-interval monitoring approaches produced the best outcomes, while fixed-interval-only approaches produced the most accurate results for four- to eight-weeks sampling frequencies.

Cardiac T2-mapping using a fast gradient echo spin echo sequence - first in vitro and in vivo experience

Background: The aim of this study was the evaluation of a fast Gradient Spin Echo Technique (GraSE) for cardiac T2-mapping, combining a robust estimation of T2 relaxation times with short acquisition times. The sequence was compared against two previously introduced T2-mapping techniques in a phantom and in vivo. Methods: Phantom experiments were performed at 1.5 T using a commercially available cylindrical gel phantom. Three different T2-mapping techniques were compared: a Multi Echo Spin Echo (MESE; serving as a reference), a T2-prepared balanced Steady State Free Precession (T2prep) and a Gradient Spin Echo sequence. For the subsequent in vivo study, 12 healthy volunteers were examined on a clinical 1.5 T scanner. The three T2-mapping sequences were performed at three short-axis slices. Global myocardial T2 relaxation times were calculated and statistical analysis was performed. For assessment of pixel-by-pixel homogeneity, the number of segments showing an inhomogeneous T2 value distribution, as defined by a pixel SD exceeding 20 % of the corresponding observed T2 time, was counted. Results: Phantom experiments showed a greater difference of measured T2 values between T2prep and MESE than between GraSE and MESE, especially for species with low T1 values. Both, GraSE and T2prep resulted in an overestimation of T2 times compared to MESE. In vivo, significant differences between mean T2 times were observed. In general, T2prep resulted in lowest (52.4 +/- 2.8 ms) and GraSE in highest T2 estimates (59.3 +/- 4.0 ms). Analysis of pixel-by-pixel homogeneity revealed the least number of segments with inhomogeneous T2 distribution for GraSE-derived T2 maps. Conclusions: The GraSE sequence is a fast and robust sequence, combining advantages of both MESE and T2prep techniques, which promises to enable improved clinical applicability of T2-mapping in the future. Our study revealed significant differences of derived mean T2 values when applying different sequence designs. Therefore, a systematic comparison of different cardiac T2-mapping sequences and the establishment of dedicated reference values should be the goal of future studies.

Robust Adaptive Control with Applications to Multi-Agent Systems and Mobile Robotics

This thesis deals with robust adaptive control and its applications, and it is divided into three main parts. The first part is about the design of robust estimation algorithms based on recursive least squares. First, we present an estimator for the frequencies of biased multi-harmonic signals, and then an algorithm for distributed estimation of an unknown parameter over a network of adaptive agents. In the second part of this thesis, we consider a cooperative control problem over uncertain networks of linear systems and Kuramoto systems, in which the agents have to track the reference generated by a leader exosystem. Since the reference signal is not available to each network node, novel distributed observers are designed so as to reconstruct the reference signal locally for each agent, and therefore decentralizing the problem. In the third and final part of this thesis, we consider robust estimation tasks for mobile robotics applications. In particular, we first consider the problem of slip estimation for agricultural tracked vehicles. Then, we consider a search and rescue application in which we need to drive an unmanned aerial vehicle as close as possible to the unknown (and to be estimated) position of a victim, who is buried under the snow after an avalanche event. In this thesis, robustness is intended as an input-to-state stability property of the proposed identifiers (sometimes referred to as adaptive laws), with respect to additive disturbances, and relative to a steady-state trajectory that is associated with a correct estimation of the unknown parameter to be found.

Crystallization and preliminary X-ray diffraction analysis of human IL-22 bound to its soluble decoy receptor IL-22BP

Interleukin-22 (IL-22) is a pleiotropic cytokine that is involved in inflammatory responses. Human IL-22 was incubated with its soluble decoy receptor IL-22BP (IL-22 binding protein) and the IL-22 -IL-22BP complex was crystallized in hanging drops using the vapour-diffusion method. Suitable crystals were obtained from polyethylene glycol solutions and diffraction data were collected to 2.75 angstrom resolution. The crystal belonged to the tetragonal space group P41, with unit-cell parameters a = b = 67.9, c = 172.5 angstrom, and contained two IL-22-IL- 22BP complexes per asymmetric unit.

Dissociation of deprotonated microcystin variants by collision-induced dissociation following electrospray ionization

Microcystins (MC) are a family of hepatotoxic cyclic heptapeptides produced by a number of different cyanobacterial species. Considering the recent advances in the characterization of deprotonated peptides by mass spectrometry, the fragmentation behavior of four structurally related microcystin compounds was investigated using collision-induced dissociation (CID) experiments on an orbitrap mass spectrometer. It is demonstrated in this study that significant structural information can be obtained from the CID spectra of deprotonated microcystins. A predominant ring-opening reaction at the isoMeAsp residue, as well as two major complementary fragmentation pathways, was observed, reducing the complexity of the product ion spectra in comparison with spectra observed from protonated species. This proposed fragmentation behavior was applied to characterize [Leu(1)]MC-LR from a cyanobacterial cell extract. In conclusion, CID spectra of microcystins in the negative ion mode provide rich structurally informative mass spectra which greatly enhance confidence in structural assignments, in particular when combined with complementary positive ion CID spectra. Copyright (C) 2011 John Wiley & Sons, Ltd.

Evaluating the efficiency of fractional integration parameter estimators

This article deals with the efficiency of fractional integration parameter estimators. This study was based on Monte Carlo experiments involving simulated stochastic processes with integration orders in the range]-1,1[. The evaluated estimation methods were classified into two groups: heuristics and semiparametric/maximum likelihood (ML). The study revealed that the comparative efficiency of the estimators, measured by the lesser mean squared error, depends on the stationary/non-stationary and persistency/anti-persistency conditions of the series. The ML estimator was shown to be superior for stationary persistent processes; the wavelet spectrum-based estimators were better for non-stationary mean reversible and invertible anti-persistent processes; the weighted periodogram-based estimator was shown to be superior for non-invertible anti-persistent processes.

Trade relationships between the Gulf Cooperation Council and the European Union

This paper examines the trade relationship between the Gulf Cooperation Council (GCC) and the European Union (EU). A simultaneous equation regression model is developed and estimated to assist with the analysis. The regression results, using both the two stage least squares (2SLS) and ordinary least squares (OLS) estimation methods, reveal the existence of feedback effects between the two economic integrations. The results also show that during times of slack in oil prices, the GCC income from its investments overseas helped to finance its imports from the EU.

Métodos de estimativa de descarga sólida em rios : análise comparativa

Transporte de sedimentos em bacias hidrográficas está relacionado com geomorfologia, ecologia fluvial, estabilidade das estruturas de engenharia e condições de navegação, dentre outros aspectos importantes para o planejamento e o controle de recursos hídricos. Existência de inúmeras variáveis envolvidas na mecânica de transporte de sedimentos e complexidade nas interações de processos físicos tornam difícil o estabelecimento de metodologias indiretas para estimativa de transporte de sedimentos em rios. Desta forma, não existe ainda metodologia universalmente aceita. O principal objetivo do presente trabalho é a análise comparativa de diferentes métodos empíricos disponíveis na literatura para estimativa de descargas sólidas em rios, considerando suas características específicas e resultados de aplicações às bacias dos rios Santa Joana e Santa Maria do Doce e microbacias Sossego e Santa Júlia, inseridas na porção da bacia do rio Doce localizada no Espírito Santo. Foram aplicados os métodos de estimativa indireta de descarga sólida: Einstein Modificado por Colby e Hembree (1955); Colby Simplificado (1957); Engelund & Hansen (1967); Ackers & White (1973); Yang (1973), Karim (1998) e Cheng (2002). Considerando as médias das estimativas de descarga sólida de material de leito (Qsml) relativas às campanhas realizadas em período chuvoso para a seção transversal do rio Doce, de maior porte, o método de Karim (1998), seguido pelo método de Ackers & White (1973), apresentou o maior valor, enquanto que o método de Yang (1973) apresentou o menor. Para os rios Santa Maria do Doce e Santa Joana e os córregos Santa Júlia e Sossego, verificou-se que o método de Ackers & White (1973), seguido de Karim (1998) e Yang (1973) apresentaram as maiores médias, enquanto que os métodos de Cheng (2002) e Engelund & Hansen (1967) apresentaram as menores. O método Simplificado de Colby apresentou as maiores estimativas de descargas sólidas totais (Qst) para todas as seções transversais de todos os cursos d'água monitorados. Concluiu-se que os diferentes métodos indiretos podem resultar em grandes diferenças em estimativas de transporte de sedimento em rios e que, desta forma, resultados de aplicação destes métodos devem ser considerados com muita cautela. Os resultados mostraram a grande importância de realização de campanhas de medição sedimentométricas para avaliação do transporte de sedimentos e definição dos melhores métodos indiretos de estimativa para cursos d'água específicos.