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See detailEarly Career Researchers in Digital Medieval Studies: A Round Table Discussion
Busch, Hannah; Dubuisson, Bastien UL; Davies, Helen et al

Presentation (2021, July 06)

As a relatively young and constantly emerging field, the Digital Humanities (DH) encompasses a large group of early career researchers with different backgrounds and diverse career paths. Digital Medieval ... [more ▼]

As a relatively young and constantly emerging field, the Digital Humanities (DH) encompasses a large group of early career researchers with different backgrounds and diverse career paths. Digital Medieval Studies as a subfield of DH is characterised by various disciplines as well as a high number of international collaborations and is populated by scholars with different educational backgrounds: from scholars trained as medievalists who implemented digital components only during their postgrad studies to scholars who approached medieval studies through their technical skills. This round table discussion brings together early career scholars from this domain on the border between traditional humanities research and DH to discuss the challenges and opportunities of their diverse career paths. [less ▲]

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See detailEARLY FLOWERING4 Recruitment of EARLY FLOWERING3 in the Nucleus Sustains the Arabidopsis Circadian Clock
Herrero, Eva; Kolmos, Elsebeth; Bujdoso, Nora et al

in Plant Cell (2012), 24(2), 428-443

The plant circadian clock is proposed to be a network of several interconnected feedback loops, and loss of any component leads to changes in oscillator speed. We previously reported that Arabidopsis ... [more ▼]

The plant circadian clock is proposed to be a network of several interconnected feedback loops, and loss of any component leads to changes in oscillator speed. We previously reported that Arabidopsis thaliana EARLY FLOWERING4 (ELF4) is required to sustain this oscillator and that the elf4 mutant is arrhythmic. This phenotype is shared with both elf3 and lux. Here, we show that overexpression of either ELF3 or LUX ARRHYTHMO (LUX) complements the elf4 mutant phenotype. Furthermore, ELF4 causes ELF3 to form foci in the nucleus. We used expression data to direct a mathematical position of ELF3 in the clock network. This revealed direct effects on the morning clock gene PRR9, and we determined association of ELF3 to a conserved region of the PRR9 promoter. A cis-element in this region was suggestive of ELF3 recruitment by the transcription factor LUX, consistent with both ELF3 and LUX acting genetically downstream of ELF4. Taken together, using integrated approaches, we identified ELF4/ELF3 together with LUX to be pivotal for sustenance of plant circadian rhythms. [less ▲]

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See detaileCoBus: Smart and sustainable public transport in Luxembourg
Viti, Francesco UL

Scientific Conference (2020, November)

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See detailEcological Advanced Driver Assistance System for Optimal Energy Management in Electric Vehicles
Sajadi Alamdari, Seyed Amin UL; Voos, Holger UL; Darouach, Mohamed

in IEEE Intelligent Transportation Systems Magazine (2018)

Battery Electric Vehicles have a high potential in modern transportation, however, they are facing limited cruising range. The driving style, the road geometries including slopes, curves, the static and ... [more ▼]

Battery Electric Vehicles have a high potential in modern transportation, however, they are facing limited cruising range. The driving style, the road geometries including slopes, curves, the static and dynamic traffic conditions such as speed limits and preceding vehicles have their share of energy consumption in the host electric vehicle. Optimal energy management based on a semi-autonomous ecological advanced driver assistance system can improve the longitudinal velocity regulation in a safe and energy-efficient driving strategy. The main contribution of this paper is the design of a real-time risk-sensitive nonlinear model predictive controller to plan the online cost-effective cruising velocity in a stochastic traffic environment. The basic idea is to measure the relevant states of the electric vehicle at runtime, and account for the road slopes, the upcoming curves, and the speed limit zones, as well as uncertainty in the preceding vehicle behavior to determine the energy-efficient velocity profile. Closed-loop Entropic Value-at-Risk as a coherent risk measure is introduced to quantify the risk involved in the system constraints violation. The obtained simulation and field experimental results demonstrate the effectiveness of the proposed method for a semi-autonomous electric vehicle in terms of safe and energy-efficient states regulation and constraints satisfaction. [less ▲]

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See detailEconomies of scale in recoverable robust maintenance location routing for rolling stock
Arts, Joachim UL; Tönissen, Denise

in Transportation Research. Part B, Methodological (2018), 117

We consider the problem of locating maintenance facilities in a railway setting. Different facility sizes can be chosen for each candidate location and for each size there is an associated annual facility ... [more ▼]

We consider the problem of locating maintenance facilities in a railway setting. Different facility sizes can be chosen for each candidate location and for each size there is an associated annual facility costs that can capture economies of scale in facility size. Because of the strategic nature of facility location, the opened facilities should be able to handle the current maintenance demand, but also the demand for any of the scenarios that can occur in the future. These scenarios capture changes such as changes to the line plan and the introduction of new rolling stock types. We allow recovery in the form of opening additional facilities, closing facilities, and increasing the facility size for each scenario. We provide a two-stage robust programming formulation. In the first-stage, we decide where to open what size of facility. In the second-stage, we solve a NP-hard maintenance location routing problem. We reformulate the problem as a mixed integer program that can be used to make an efficient column-and-constraint generation algorithm. To show that our algorithm works on practical sized instances, and to gain managerial insights, we perform a case study with instances from the Netherlands Railways. A counter intuitive insight is that economies of scale only play a limited role and that it is more important to reduce the transportation cost by building many small facilities, rather than a few large ones to profit from economies of scale. [less ▲]

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See detailThe effect of dataset confounding on predictions of deep neural networks for medical imaging
Garcia Santa Cruz, Beatriz UL; Husch, Andreas UL; Hertel, Frank UL

in Vol. 3 (2022): Proceedings of the Northern Lights Deep Learning Workshop 2022 (2022, April 18)

The use of Convolutional Neural Networks (CNN) in medical imaging has often outperformed previous solutions and even specialists, becoming a promising technology for Computer-aided-Diagnosis (CAD) systems ... [more ▼]

The use of Convolutional Neural Networks (CNN) in medical imaging has often outperformed previous solutions and even specialists, becoming a promising technology for Computer-aided-Diagnosis (CAD) systems. However, recent works suggested that CNN may have poor generalisation on new data, for instance, generated in different hospitals. Uncontrolled confounders have been proposed as a common reason. In this paper, we experimentally demonstrate the impact of confounding data in unknown scenarios. We assessed the effect of four confounding configurations: total, strong, light and balanced. We found the confounding effect is especially prominent in total confounder scenarios, while the effect on light and strong confounding scenarios may depend on the dataset robustness. Our findings indicate that the confounding effect is independent of the architecture employed. These findings might explain why models can report good metrics during the development stage but fail to translate to real-world settings. We highlight the need for thorough consideration of these commonly unattended aspects, to develop safer CNN-based CAD systems. [less ▲]

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See detailEffect of Red Blood Cell Aging In Vivo on Their Aggregation Properties In Vitro: Measurements with Laser Tweezers
Ermolinskiy, Petr; Lugovtsov, Andrei; Yaya, Francois et al

in Applied Sciences (2020), 10(21), 7581-10

Red blood cell (RBC) aggregation highly influences hemorheology and blood microcirculation in the human body. The aggregation properties of RBCs can vary due to numerous factors, including RBC age. The ... [more ▼]

Red blood cell (RBC) aggregation highly influences hemorheology and blood microcirculation in the human body. The aggregation properties of RBCs can vary due to numerous factors, including RBC age. The aim of this work was to estimate in vitro the differences in the RBC aggregation properties of different RBC age populations in single-cell experiments using laser tweezers. RBCs from five healthy volunteers were separated into four subpopulations by Percoll density gradient centrifugation. Each subpopulation of the RBC was separately resuspended in autologous plasma or dextran 70 kDa (50 mg/mL). The aggregation force between the single cells was measured with holographic laser tweezers. The obtained data demonstrated an enhancement of RBC aggregation force in doublets with age: the older the cells, the higher the aggregation force. The obtained data revealed the differences between the aggregation and aggregability of RBC in dependence of the RBC in vivo age. [less ▲]

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See detailEffect of vagus nerve stimulation on EEG oscillations and connectivity
Vespa, Simone; Agram, Youssef; Lucchetti, Federico UL et al

in Effect of vagus nerve stimulation on EEG oscillations and connectivity (2020)

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See detailThe effect of workplace relocation on individuals’ activity travel behavior
Sprumont, Francois; Viti, Francesco UL

in Journal of Transport and Land Use (2018), 11(1),

On working days, homes and workplaces can be seen as anchor locations at the heart of daily mobility patterns, as well as being central to an employee’s activity pattern. In this study, we investigate how ... [more ▼]

On working days, homes and workplaces can be seen as anchor locations at the heart of daily mobility patterns, as well as being central to an employee’s activity pattern. In this study, we investigate how workplace relocation affects the entire daily activity-travel chain. While past research has shown that workplace decentralization is often associated with higher car use for the commuting trip, little is known about the effect on the whole activity travel pattern. Two waves of a two-week travel diary were completed by 43 employees of the University of Luxembourg: one before and one after the relocation of their office. Using descriptive statistics as well as standard deviational ellipses (SDE) theory combined with the results of a clustering analysis showed that workers’ activity spaces (represented by the standard deviational ellipses) were significantly modified due to the relocation of a single anchor activity location, i.e., their workplace. [less ▲]

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See detailThe effect of workplace relocation on individuals’ activity travel behaviour
Sprumont, François UL; Viti, Francesco UL

Scientific Conference (2017, July 04)

During working days, home and workplace are anchor locations shaping the daily mobility as well as the employee’s activity pattern. While past research has shown that workplace decentralization is often ... [more ▼]

During working days, home and workplace are anchor locations shaping the daily mobility as well as the employee’s activity pattern. While past research has shown that workplace decentralization is often associated with higher car use for the commuting trip, little is known concerning the effect on activity-travel patterns as whole. The objective of this paper is to assess how workplace decentralization is affecting individuals’ daily activity space. A two-weeks travel diary has been filled by 43 employees of the University of Luxembourg, both before and after the relocation of their workplace. Using descriptive statistics, as well as Standard Deviational Ellipses (SDE) combined with a cluster analysis, results of this paper show that workers’ activity spaces, represented by the Standard Deviational Ellipses, have been importantly modified due to a relocation of a single anchor activity location, i.e. their workplace [less ▲]

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See detailEffectiveness of the Two-Step Dynamic Demand Estimation model on large networks
Cantelmo, Guido UL; Viti, Francesco UL; Derrmann, Thierry UL

in Proceedings of 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) (2017, June 28)

In this paper, the authors present a Two-Step approach that sequentially adjusts generation and distribution values of the (dynamic) OD matrix. While the proposed methodology already provided excellent ... [more ▼]

In this paper, the authors present a Two-Step approach that sequentially adjusts generation and distribution values of the (dynamic) OD matrix. While the proposed methodology already provided excellent results for updating demand flows on a motorway, the aim of this paper is to validate this conclusion on a real network: Luxembourg City. This network represents the typical middle-sized European city in terms of network dimension. Moreover, Luxembourg City has the typical structure of a metropolitan area, composed of a city centre, ring, and suburb areas. An innovative element of this paper is to use mobile network data to create a time-dependent profile of the generated demand inside and outside the ring. To support the claim that the model is ready for practical implementation, it is interfaced with PTV Visum, one of the most widely adopted software tools for traffic analysis. Results of these experiments provide a solid empirical ground in order to further develop this model and to understand if its assumptions hold for urban scenarios. [less ▲]

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See detailThe Effects of Natural Sounds and Proxemic Distances on the Perception of a Noisy Domestic Flying Robot
Wang, Ziming UL; Hu, Ziyi; Rohles, Björn UL et al

in ACM Transactions on Human - Robot Interaction (in press)

When flying robots are used in close-range interaction with humans, the noise they generate, also called consequential sound, is a critical parameter for user acceptance. We conjecture that there is a ... [more ▼]

When flying robots are used in close-range interaction with humans, the noise they generate, also called consequential sound, is a critical parameter for user acceptance. We conjecture that there is a benefit in adding natural sounds to noisy domestic drones. To test our hypothesis experimentally, we carried out a mixed-methods research study (N=56) on reported user perception of a sonified domestic flying robot with three sound conditions at three distances. The natural sounds studied were respectively added to the robot’s inherent noises during flying; namely a birdsong and a rain sound, plus a control condition of no added sound. The distances studied were set according to proxemics; namely near, middle, and far. Our results show that adding birdsong or rain sound affects the participants’ perceptions, and the proxemic distances play a nonnegligible role. For instance, we found that participants liked the bird condition the most when the drone was at far, while they disliked the same sound the most when at near. We also found that participants’ perceptions strongly depended on their associations and interpretations deriving from previous experience. We derived six concrete design recommendations. [less ▲]

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See detailEffects of periurban structure on air pollution: coupling CA models to understand the link between urban structure and air pollution
Schindler, Mirjam UL; Caruso, Geoffrey UL

in Pinto N, Dourado J (Ed.) Proceedings of the Symposium on Cellular Automata Models of Urban and Spatial Systems (2012)

Air quality is a major concern in urban areas worldwide not only because of its severe health impacts but also due to its influence on living quality and residential behaviour. The subsequent increasing ... [more ▼]

Air quality is a major concern in urban areas worldwide not only because of its severe health impacts but also due to its influence on living quality and residential behaviour. The subsequent increasing demand for residential areas in the greener fringes of urban agglomerations fuels the discussion about sustainability in future cities. As traffic emissions are acknowledged to be the major source of pollutants in an urban environment this residential trend has triggered research to further understand the influence of urban structure on air quality. In order to meet sustainable growth, many researchers argue that in a global perspective a compact city is the desirable urban form due to less traffic distance, just in contrast to the trend towards urban sprawl. However, quantifying the link between urban structure and air pollution has only been the aim of few research studies so far. Thus, our objective is to deepen the understanding of this link by coupling a micro-economic CA urban growth model with a traffic emission model and a CA air pollution model while focussing on the impact on residential population. [less ▲]

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See detailAn efficient deep learning approach for ground point filtering in aerial laser scanning point clouds
Nurunnabi, Abdul Awal Md UL

in Nurunnabi, Abdul Awal Md; Teferle, Felix Norman; Li, Jonathan (Eds.) et al An efficient deep learning approach for ground point filtering in aerial laser scanning point clouds (2021, July 02)

Ground surface extraction is one of the classic tasks in airborne laser scanning (ALS) point cloud processing that is used for three-dimensional (3D) city modelling, infrastructure health monitoring, and ... [more ▼]

Ground surface extraction is one of the classic tasks in airborne laser scanning (ALS) point cloud processing that is used for three-dimensional (3D) city modelling, infrastructure health monitoring, and disaster management. Many methods have been developed over the last three decades. Recently, Deep Learning (DL) has become the most dominant technique for 3D point cloud classification. DL methods used for classification can be categorized into end-to-end and non end-to-end approaches. One of the main challenges of using supervised DL approaches is getting a sufficient amount of training data. The main advantage of using a supervised non end-to-end approach is that it requires less training data. This paper introduces a novel local feature-based non end-to-end DL algorithm that generates a binary classifier for ground point filtering. It studies feature relevance, and investigates three models that are different combinations of features. This method is free from the limitations of point clouds’ irregular data structure and varying data density, which is the biggest challenge for using the elegant convolutional neural network. The new algorithm does not require transforming data into regular 3D voxel grids or any rasterization. The performance of the new method has been demonstrated through two ALS datasets covering urban environments. The method successfully labels ground and non-ground points in the presence of steep slopes and height discontinuity in the terrain. Experiments in this paper show that the algorithm achieves around 97% in both F1-score and model accuracy for ground point labelling. [less ▲]

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See detailAn efficient goal-oriented sampling strategy using reduced basis method for parametrized elastodynamic problems
Hoang, Khac Chi; Kerfriden, Pierre; Bordas, Stéphane UL et al

in Numerical Methods for Partial Differential Equations (2014)

In this paper, we study the class of linear elastodynamic problems with a ne parameter dependence using a goal-oriented approach by finite element (FE) and reduced basis (RB) methods. The main ... [more ▼]

In this paper, we study the class of linear elastodynamic problems with a ne parameter dependence using a goal-oriented approach by finite element (FE) and reduced basis (RB) methods. The main contribution of this paper is the "goal-oriented" proper orthogonal decomposition (POD)-Greedy sampling strategy within the RB approximation context. The proposed sampling strategy looks for the parameter points such that the output error approximation will be minimized by Greedy iterations. In estimating such output error approximation, the standard POD-Greedy algorithm is invoked to provide enriched RB approximations for the FE outputs. We propose a so-called "cross-validation" process to choose adaptively the dimension of the enriched RB space corresponding with the dimension of the RB space under consideration. Numerical results show that the new goal-oriented POD-Greedy sampling procedure with the cross-validation process improves signi ficantly the space-time output computations in comparison with the ones computed by the standard POD-Greedy algorithm. The method is thus ideally suited for repeated, rapid and reliable evaluations of input-output relationships in the space-time setting. [less ▲]

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See detailEfficient modeling of random heterogeneous materials with an uniform probability density function
Paladim, Daniel; Kerfriden, Pierre; Bordas, Stéphane UL

Scientific Conference (2014, July)

Homogenised constitutive laws are largely used to predict the behaviour of composite structures. Assessing the validity of such homogenised models can be done by making use of the concept of ``modelling ... [more ▼]

Homogenised constitutive laws are largely used to predict the behaviour of composite structures. Assessing the validity of such homogenised models can be done by making use of the concept of ``modelling error''. First, a microscopic ``faithful'' -and potentially intractable- model of the structure is defined. Then, one tries to quantify the effect of the homogenisation procedure on a result that would be obtained by directly using the ``faithful'' model. Such an approach requires (a) the ``faithful'' model to be more representative of the physical phenomena of interest than the homogenised model and (b) a reliable approximation of the result obtained using the "faithful" and intractable model to be available at cheap costs. We focus here on point (b), and more precisely on the extension of the techniques developed in [3][2] to estimate the error due to the homogenisation of linear, spatially random composite materials. Particularly, we will approximate the unknown probability density function by bounding its first moment. In this paper, we will present this idea in more detail, displaying the numerical efficiencies and computational costs related to the error estimation. The fact that the probability density function is uniform is exploited to greatly reduce the computational cost. We will also show some first attempts to correct the homogenised model using non-conforming, weakly intrusive microscopic patches. [less ▲]

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See detailEfficient modeling of random heterogeneous materials with an uniform probability density function (slides)
Paladim, Daniel; Kerfriden, Pierre; Moitinho de Almeida, José et al

Scientific Conference (2014)

Homogenised constitutive laws are largely used to predict the behaviour of composite structures. Assessing the validity of such homogenised models can be done by making use of the concept of “modelling ... [more ▼]

Homogenised constitutive laws are largely used to predict the behaviour of composite structures. Assessing the validity of such homogenised models can be done by making use of the concept of “modelling error”. First, a microscopic “faithful” -and potentially intractable- model of the structure is defined. Then, one tries to quantify the effect of the homogenisation procedure on a result that would be obtained by directly using the “faithful” model. Such an approach requires (a) the “faithful” model to be more representative of the physical phenomena of interest than the homogenised model and (b) a reliable approximation of the result obtained using the ”faithful” and intractable model to be available at cheap costs. We focus here on point (b), and more precisely on the extension of the techniques devel- oped in [3] [2] to estimate the error due to the homogenisation of linear, spatially random composite materials. Particularly, we will approximate the unknown probability density function by bounding its first moment. In this paper, we will present this idea in more detail, displaying the numerical efficiencies and computational costs related to the error estimation. The fact that the probability density function is uniform is exploited to greatly reduce the computational cost. We will also show some first attempts to correct the homogenised model using non-conforming, weakly intrusive microscopic patches. [less ▲]

Detailed reference viewed: 292 (1 UL)