Lernstörung oder Sprachbarriere? – Entwicklung eines für Luxemburg angepassten Wortschatztests

Poster (2023, February 24)

The Ugly Truth of Realistic Perception in Vehicular Simulations

Poster (2023, January 08)

Automated vehicles use sensors to perceive the environment, and studies have shown the limitations of these sensors. The onboard sensors may not detect objects when other participants occlude the Field of ... [more ▼]

Automated vehicles use sensors to perceive the environment, and studies have shown the limitations of these sensors. The onboard sensors may not detect objects when other participants occlude the Field of View (FoV). Thus, sensor efficiency must be tested to ensure its reliability. Simulation is an excellent test option due to the complexity associated with practical experiments. However, emerging simulation frameworks still have various limitations, especially when it comes to large-scale evaluation. This work investigates realistic perception simulation options for autonomous vehicles. We report the perception accuracy for different traffic scenarios. [less ▲]

Do your magic, Harry Potter! popular fiction books and their impact on students’ reading performances

Poster (2022, November 10)

Previous surveys on the reading habits of Luxembourgish secondary school students (conducted within the framework of the national school monitoring programme Épreuves Standardisées (ÉpStan) in 2016 and ... [more ▼]

Previous surveys on the reading habits of Luxembourgish secondary school students (conducted within the framework of the national school monitoring programme Épreuves Standardisées (ÉpStan) in 2016 and 2019) revealed better reading comprehension results in French and German for those students who frequently read printed narrative texts in their leisure time. However, these studies only focused on different reading modes and text types. They did not investigate which digital and/or printed books students actually read for pleasure, nor which text features determine the positive impact narrative texts have on their reading performances: Is it, for example, the language quality, the richness and complexity of content, or simply the amount of written language they need to process? Therefore, we conducted an explorative follow-up survey within the framework of ÉpStan 2020 and asked secondary school students (Grade 7: n=3055; Grade 9: n=5781) to indicate up to three book titles – printed and e-books respectively – they had read in their leisure time. Despite the omnipresence of digital media, preliminary findings show that both age groups prefer paper-based reading activities when reading longer texts (or books) for pleasure. Nevertheless, the most popular text types and book titles are the same for printed books and e-books: Among them, we find the novel series “Harry Potter”, the rather comic-like book series “Gregs Tagebuch”, and the mangas from the “Naruto”/“Boruto” series. The linkage between students’ leisure time reading activities and their ÉpStan reading performances will be drawn, and some first linguistic text analyses of extracts from the most popular book titles will be conducted in order to reveal some of the text features that foster reading comprehension skills. [less ▲]

Early Childhood Education and Care in Luxembourg - Is attendance influenced by immigration background and socioeconomic status?

Poster (2022, November 10)

For decades, researchers have been raising awareness of the issue of educational inequalities in the multilingual Luxemburgish school system. Especially children from families with a migration background ... [more ▼]

For decades, researchers have been raising awareness of the issue of educational inequalities in the multilingual Luxemburgish school system. Especially children from families with a migration background or a lower socio-economic status show large deficits in their language and mathematics competences in comparison to their peers. The same applies to children who do not speak Luxemburgish or German as their first language (Hornung et al., 2021; Sonnleitner et al., 2021). One way to reduce such educational inequalities might be an early and extensive participation in early childhood education and care (ECEC). Indeed, participation in ECEC was found to be positively connected to language and cognitive development in other countries, especially for children from disadvantaged families (Bennett, 2012). However, these children attend ECEC less often (Vandenbroeck & Lazzari, 2014). There are indications that lower parental costs might go hand in hand with a greater attendance of ECEC in general (for a Luxembourgish study, see Bousselin, 2019) and in particular by disadvantaged families (Busse & Gathmann, 2020). The aim of this study is to spotlight the attendance of ECEC in Luxembourg during the implementation of the ECEC reform after 2017 which increased free ECEC hours for all families from 3 to 20 hours a week. We draw on a large dataset of about 35.000 children from the Épreuves Standardisées (ÉpStan, the Luxemburg school monitoring programme) from 2015 to 2021 and investigate which children attend any kind of regulated ECEC service (public, private or family daycare) in which intensity, taking socio-economic and cultural family factors into account. The findings might help to understand in which contexts ECEC attendance should be further encouraged. Implications for future policy decisions are discussed with the goal of further promoting equal educational opportunities for all children. [less ▲]

Demand aware Resource Management Techniques for Flexible Broadband Satellite Communication Systems

Poster (2022, November 08)

Improving Machine Learning-based Prediction of Frailty in Elderly People with Digital Wearables : Data from the Berlin Aging Study II (BASE-II)

Poster (2022, October 26)

Frailty is a geriatric medical condition that is highly associated with age and age-related diseases. The multidimensional consequences of frailty are heavily impacting the quality of life, and will ... [more ▼]

Frailty is a geriatric medical condition that is highly associated with age and age-related diseases. The multidimensional consequences of frailty are heavily impacting the quality of life, and will inevitably increase the burden on healthcare systems in the future. Most importantly, the lack of a universal standard to describe, diagnose, or let alone treat frailty, is further complicating the situation in the long-term. Nowadays, more and more frailty assessment tools are being developed on a regional and institutional basis, which is continuing to drive the heterogeneity in the characterization of frailty further apart. Gaining better insights into the underlying causes and pathophysiology of frailty, and how it is developing in patients is, therefore, required to establish strong and accurately tailored response schemes for frail patients, where currently only symptoms are treated. Thus, in this study, we deployed machine learning-based classification and optimization techniques to predict frailty in elderly people aged 65 or above from the Berlin Aging Study II (BASE-II, n=1512, frail=484) and revealed some of the most informative biomedical information to characterize frailty, including new potential biomarkers. Frailty in BASE-II was measured by the Fried et al. 5-item frailty index, composed of the clinical variables grip strength, weight loss, exhaustion, physical activity, and gait. The level of frailty in BASE-II was adapted for binary classification purposes by merging the pre-frail and frail levels as frail. A configurable in-house pipeline was developed for pre-processing the clinical data and predicting the target disease by deploying Support Vector Machines Classification. The most informative and essential subgroup of clinical measurements with regards to frailty was investigated by re-optimizing an initially full data-driven model by sequentially leaving out one subgroup. The best prediction power was yielded with resampling and dimensionality reduction techniques using the F-beta-2 score, and was further improved by adding one item of the Fried et al. frailty index. Furthermore, differences between the gender in the data set led to the investigation of gender-specific model configurations, followed by re-optimizations. As a result, we were able to specifically increase the predictive power in gender-specific groups, and will simultaneously emphasize on the differences between the most informative clinical biomarkers as well as the most essential subgroups for mixed and gender-specific BASE-II. The results herein suggest that a combination of the detected easy-to-obtain biomedical information on frailty risk factors together with one Fried et al. phenotype information provided by i.e., smart wearable devices (gait, grip strength, …) could significantly improve the frailty prediction power in mixed and gender-specific clinical cohort data. [less ▲]

Machine learning-based prediction of frailty in elderly people : Data from the Berlin Aging Study II (BASE-II)

Poster (2022, October 09)

Frailty is a geriatric medical condition that is highly associated with age and age-related diseases. The multidimensional consequences of frailty are heavily impacting the quality of life, and will ... [more ▼]

Frailty is a geriatric medical condition that is highly associated with age and age-related diseases. The multidimensional consequences of frailty are heavily impacting the quality of life, and will inevitably increase the burden on healthcare systems in the future. Most importantly, the lack of a universal standard to describe, diagnose, or let alone treat frailty, is further complicating the situation in the long-term. Nowadays, more and more frailty assessment tools are being developed on a regional and institutional basis, which is continuing to drive the heterogeneity in the characterization of frailty further apart. Gaining better insights into the underlying causes and pathophysiology of frailty, and how it is developing in patients is, therefore, required to establish strong and accurately tailored response schemes for frail patients, where currently only symptoms are treated. Thus, in this study, we deployed machine learning-based classification and optimization techniques to predict frailty in the Berlin Aging Study II (BASE-II, N=1512, frail=484) and revealed some of the most informative biomedical information to characterize frailty, including new potential biomarkers. Frailty in BASE-II was measured by the Fried et al. 5-item frailty index, composed of the clinical variables grip strength, weight loss, exhaustion, physical activity, and gait. The level of frailty in BASE-II was adapted for binary classification purposes by merging the pre-frail and frail levels as frail. A configurable in-house pipeline was developed for pre-processing the clinical data, predicting the target disease, and determining the most informative subgroup of clinical measurements with regards to frailty. The best prediction power was yielded with resampling and dimensionality reduction techniques using the F-beta-2 score, and was further increased by adding one item of the Fried et al. frailty index. We suggest that a combination of the easy-to-obtain biomedical information on frailty risk factors together with one Fried et al. phenotype information provided by i.e. smart wearable devices (gait, grip strength, . . . ) could significantly improve the frailty prediction power. [less ▲]

Machine learning applied to higher order functional representations of omics data reveals biological pathways associated with Parkinson‘s Disease

Poster (2022, September 18)

Background: Despite the increasing prevalence of Parkinson’s Disease (PD) and research efforts to understand its underlying molecular pathogenesis, early diagnosis of PD remains a challenge. Machine ... [more ▼]

Background: Despite the increasing prevalence of Parkinson’s Disease (PD) and research efforts to understand its underlying molecular pathogenesis, early diagnosis of PD remains a challenge. Machine learning analysis of blood-based omics data is a promising non-invasive approach to finding molecular fingerprints associated with PD that may enable an early and accurate diagnosis. Description: We applied several machine learning classification methods to public omics data from PD case/control studies. We used aggregation statistics and Pathifier’s pathway deregulation scores to generate higher order functional representations of the data such as pathway-level features. The models’ performance and most relevant predictive features were compared with individual feature level predictors. The resulting diagnostic models from individual features and Pathifier’s pathway deregulation scores achieve significant Area Under the Curve (AUC, a receiver operating characteristic curve) scores for both cross-validation and external testing. Furthermore, we identify plausible biological pathways associated with PD diagnosis. Conclusions: We have successfully built machine learning models at pathway-level and single-feature level to study blood-based omics data for PD diagnosis. Plausible biological pathway associations were identified. Furthermore, we show that pathway deregulation scores can serve as robust and biologically interpretable predictors for PD. [less ▲]

PRELIMINARY RESULTS ON THE COGNITIVE PROFILE IN PRODROMAL PARKINSON’S DISEASE – A PROSPECTIVE STUDY 

Poster (2022, September)

Retrograde procedural memory in Parkinson's Disease and in REM-Sleep Behavior Disorder

Poster (2022, August)

Hybrid Active-Passive Reconfigurable Intelligent Surface-Assisted Multi-User MISO Systems

Poster (2022, July 04)

We consider a multi-user multiple-input single- output (MISO) communications system which is assisted by a hybrid active-passive reconfigurable intelligent surface (RIS). Unlike conventional passive RISs ... [more ▼]

We consider a multi-user multiple-input single- output (MISO) communications system which is assisted by a hybrid active-passive reconfigurable intelligent surface (RIS). Unlike conventional passive RISs, hybrid RIS is equipped with a few active elements with the ability to reflect and amplify incident signals to significantly improve the system performance. Towards a fairness design, we maximize the minimum rate among all users through jointly optimizing the transmit beamforming vectors and RIS reflecting/amplifying coefficients. Combining tools from block coordinate ascend and successive convex approximation, the challenging nonconvex problem is efficiently solved by a low- complexity iterative algorithm. The numerical results show that a hybrid RIS with 4 active elements out of a total of 50 elements with a power budget of −1 dBm offers an improvement of up to 80% to the considered system, while that achieved by a fully passive RIS is only 27% [less ▲]

A comparative study of automatic classifiers to recognize speakers based on fricatives

Poster (2022, July)

Speakers’ voices are highly individual and for this reason speakers can be identified based on their voice. Nevertheless, voices are often more variable within the same speaker than they are between ... [more ▼]

Speakers’ voices are highly individual and for this reason speakers can be identified based on their voice. Nevertheless, voices are often more variable within the same speaker than they are between speakers, which makes it difficult for humans and machines to differentiate between speakers (Hansen, J. H., & Hasan, T., 2015). To date, various machine learning methods have been developed to recognize speakers based on the acoustic characteristics of their speech; however, not all of them have proven equally effective in speaker identification, and depending on the obtained techniques, the system achieves a different result. Here, different machine learning classifiers have been applied to identify the best classification model (i.e., Naïve Bayes (NB), support vector machines (SVM), random forests (RF), & k-nearest neighbors (KNN)) for categorizing 4 speaking styles based on the segment types (voiceless fricatives) considering acoustic features of center of gravity, standard deviation, and skewness. We used a dataset consisting of speech samples from 7 native Persian subjects speaking in 4 different speaking styles: read, spontaneous, clear, and child-directed speech. The results revealed that the best performing model to predict the speakers based on the segment type was RF model with an accuracy of 81,3%, followed by SVM (76.3%), NB (75.4%), and KNN (74%) (Table 1). Our results showed that the RF performed the best for voiceless fricatives /f/, /s/, and / ʃ / which may indicate that these segments are much more speaker-specific than others (Gordon et al., 2002), and the model performance was low for the voiceless fricatives of /h/ and /x/. Performance can be seen in the confusion matrix (Figure 1), which produced high precision and recall values (above 80%) for /f/, /s/ and / ʃ / (Table 2). We found that the model performance improved when the data related to clear speaking style; the information in individual speakers (i.e., voiceless fricatives) are more distinguishable in clear style than other styles (Table 1). [less ▲]

Real-Time Large Deformation Simulations Using Probabilistic Deep Learning Framework

Poster (2022, June 28)

Personalized neurofeedback: a systematic comparison of self- and externally-paced training in healthy adults

Poster (2022, June 16)

MATERIAL MODELLING AND FINITE ELEMENT ANALYSIS IN METAL ADDITIVE MANUFACTURING

Poster (2022, May 31)

The additive manufacturing (AM) is competent method for the manufacturing of complex metal parts with wider process flexibility. During manufacturing, the metal part repetitively undergoes heating and ... [more ▼]

The additive manufacturing (AM) is competent method for the manufacturing of complex metal parts with wider process flexibility. During manufacturing, the metal part repetitively undergoes heating and cooling under the influence of laser passes and ambient conditions respectively. In turn, the material experiences the thermal strain and residual stress. The aim of the work is to predict them using certain material model. Where the solidified metal part from melt-pool is considered in current analysis. For numerical simulation, Finite Element Method (FEM) is chosen. The heat equation is first solved for thermal profile of AM Process. Afterwards, the structural analysis is performed with such thermal load. The non linear constitutive material model is utilised. For concerned material model, the temperature dependence upon the material properties is also implemented. The resulting Finite Element Analysis (FEA) platform offers the macro-scale thermal solution and the prediction of resulting plastic distortion in material. This prediction however has become more accurate when the variable material property, depending upon the temperature of analysis zone, is introduced. [less ▲]

A CLOSER LOOK AT AUTOENCODERS FOR UNSUPERVISED ANOMALY DETECTION

Poster (2022, May 22)

The Best Space Resource is the One You Can Catch and Reuse

Poster (2022, May 03)

From the beginning of space exploration more than 60 years ago, only a few in-orbit objects have been removed or reused. In fact, the Kessler Syndrome states that the number of space debris is growing ... [more ▼]

From the beginning of space exploration more than 60 years ago, only a few in-orbit objects have been removed or reused. In fact, the Kessler Syndrome states that the number of space debris is growing exponentially [1], leaving unused uncooperative objects orbiting at high velocities at several altitudes, especially in Low-Earth Orbit (LEO). In other words, the situation brings up two main critical issues: not only a non-sustainable space environment for satellite missions, with orbit saturation, but also the creation of an unsafe place for future human-related space exploration missions. Active Debris Removal is a possible solution for tackling the problem of space debris. Despite being extremely challenging, catching autonomously and harmlessly an uncooperative object tumbling at high velocity demands reliability, compliance and robustness. The fruitful collaboration between industry and academia (Spacety Luxembourg - SnT-SpaceR research group at the University of Luxembourg), is leading to the cutting-edge concept of a two-step capturing mechanism. A first ‘soft capture’ ensures that the debris is received softly while dampening any vibrations generated during the contact. Then, a ‘hard capture’ secures the debris so that it would be deorbited or safely shipped for other orbits or space stations for reuse. Capturing debris and decommissioned in-orbit objects for recycling or reusing can be the anchor of new opportunities in space and beyond. Most of the objects in orbit can have aluminum parts, besides other beneficial materials among their subsystems, such as solar panels, antennas or electronics which can be reused. To maximize space resources reusability, it is important to not harm the target. Capturing solutions such as harpoons or rigid interfaces can cause damage to the targets, resulting in hardly exploitable resources, and even more smaller debris tumbling in orbit [2]. An application of the proposed capturing technology would be to collect defunct satellites and debris, thus contributing to a more sustainable environment in space, gathering those on a possible recycling orbit or to any future Space Station for recycling. References [1] Drmola J. and Hubik T., Kessler Syndrome: System Dynamics Model (2018), In-Space Policy, 44–45, 29–39 [2] Zhao P., Liu J. and Wu C., Survey on Research and Development of On-Orbit Active Debris Removal Methods (2020), Sci China Tech Sci, 63: 2188–2210 [less ▲]

A Collaborative System of Flying and Ground Robots with Universal Physical Coupling Interface (PCI), and the Potential Interactive Applications

Poster (2022, April 28)

Flying and ground robots complement each other in terms of their advantages and disadvantages. We propose a collaborative system combining flying and ground robots, using a universal physical coupling ... [more ▼]

Flying and ground robots complement each other in terms of their advantages and disadvantages. We propose a collaborative system combining flying and ground robots, using a universal physical coupling interface (PCI) that allows for momentary connections and disconnections between multiple robots/devices. The proposed system may better utilize the complementary advantages of both flying and ground robots. We also describe various potential scenarios where such a system could be of benefit to interact with humans - namely, remote field works and rescue missions, transportation, healthcare, and education. Finally, we discuss the opportunities and challenges of such systems and consider deeper questions which should be studied in future work. [less ▲]

Individual factors and beliefs determining COVID-19 vaccination willingness

Poster (2022, April)

Background: High vaccination coverage rates are necessary to reduce infections and transmissions of the SARS-CoV-2 virus causing COVID-19 and to allow successful mitigation of the current pandemic. To ... [more ▼]

Background: High vaccination coverage rates are necessary to reduce infections and transmissions of the SARS-CoV-2 virus causing COVID-19 and to allow successful mitigation of the current pandemic. To date, we are still lacking information to explain the hesitancy in Luxembourg towards uptake of the available COVID-19 vaccines. The present study explored motivations for and against vaccination in a population-representative sample of residents across Luxembourg to identify hesitant groups and develop strategies to increase population immunity against SARS-CoV-2. Methods: In the framework of the nationwide, representative longitudinal CON-VINCE study, a sample of 1589 respondents (49.6% women, 84.3% Luxembourg nationality) ranging from 18-84 years, participated in the survey in spring 2021. The protocol of the CON-VINCE study has been described in detail elsewhere (Snoeck et al. 2020). Results: 52% of the respondents had at least partial vaccination at time of assessment between April to June 2021. The most common reasons for vaccination of those willing to be vaccinated (81.2%) were altruistic motivations. Prevalent reasons against vaccination for those undecided (8.7%) or reluctant (10.2%) to be vaccinated were that the vaccine had not been tested sufficiently and the fear of long-term vaccine side effects. Only very few of the vaccination-hesitant or -reluctant respondents reported that they did not believe in vaccination in general. Conclusion: The present study identified motivations for and against COVID-19 vaccination and determined demographic and socio-economic factors associated with vaccination willingness. To increase vaccination rates, public health communication needs to target those unsure or unwilling to be vaccinated. We will continue to study the vaccination uptake in the Luxembourg population, as CON-VINCE is now part of the H2020-funded international ORCHESTRA project (https://orchestra-cohort.eu), research into comparing these results on a Pan-European level. [less ▲]

Waveform Design for Joint Radar-Communications with Low Complexity Analog Components

Poster (2022, March)

In this paper, we aim to design an efficient and low hardware complexity based dual-function multiple-input multiple-output (MIMO) joint radar-communication (JRC) system. It is implemented via a low ... [more ▼]

In this paper, we aim to design an efficient and low hardware complexity based dual-function multiple-input multiple-output (MIMO) joint radar-communication (JRC) system. It is implemented via a low complexity analog architecture, constituted by a phase shifting network and variable gain amplifier. The proposed system exploits the multiple antenna transmitter for the simultaneous communication with multiple downlink users and radar target detection. The transmit waveform of the proposed JRC system is designed to minimize the downlink multi-user interference such that the desired radar beampattern is achieved and the architecture specific constraints are satisfied. The resulting optimization problem is non-convex and in general difficult to solve. We propose an efficient algorithmic solution based on the primal-dual framework. The numerical results show the effectiveness of the proposed approach. [less ▲]

A Deep Learning Based Acceleration of Complex Satellite Resource Management Problem

Poster (2022)

CONVERGENCE TIME ANALYSIS OF ASYNCHRONOUS DISTRIBUTED ARTIFICIAL NEURAL NETWORKS

Poster (2022)

How to catch a space debris

Poster (2021, November 18)

The partnership between SpaceR and Spacety Luxembourg aims to develop cutting edge active space debris removal solutions that can be implemented into small cube sats The solution will take the advantage ... [more ▼]

The partnership between SpaceR and Spacety Luxembourg aims to develop cutting edge active space debris removal solutions that can be implemented into small cube sats The solution will take the advantage of latest advancements in many tech domains, such as gecko like sticky adhesives and energy efficient shape memory alloy materials. [less ▲]

Poster: A Methodology for Semi-Automated CAN Bus Reverse Engineering

Poster (2021, November)

Semi-automated Controller Area Network (CAN) reverse engineering has been shown to provide decoding accuracy comparable to the manual approach, while reducing the time required to decode signals. However ... [more ▼]

Semi-automated Controller Area Network (CAN) reverse engineering has been shown to provide decoding accuracy comparable to the manual approach, while reducing the time required to decode signals. However, current approaches are invasive, as they make use of diagnostic messages injected through the On-Board Diagnostics (OBD-II) port and often require a high amount of non-CAN external data. In this work, we present a non-invasive universal methodology for semi-automated CAN bus reverse engineering, which is based on the taxonomy of CAN signals. The data collection is simplified and its time reduced from the current standard of up to an hour to few minutes. A mean recall of around 80 % is obtained. [less ▲]

The retrograde procedural memory in people with Parkinson’s disease with or without freezing of gait – a cross-sectional study

Poster (2021, September 17)

Objective: To investigate the retrograde procedural memory in people with typical Parkinson’s disease (PwP) with or without freezing of gait (FOG). We hypothesized that the retrograde procedural memory is ... [more ▼]

Objective: To investigate the retrograde procedural memory in people with typical Parkinson’s disease (PwP) with or without freezing of gait (FOG). We hypothesized that the retrograde procedural memory is more strongly impaired in patients with FOG (FOG+) than in patients without FOG (FOG-). Background: Given that cognitive functions, like executive control and automaticity, are crucial for mobility, it is of great importance to get a deeper knowledge of the cognitive impairment that may interfere with walking and causing gait disturbances in PwP, i.e. FOG. The integrity of retrograde procedural memory, the ability to execute skills that have been learned in earlier life stages, is essential for a person’s ability to complete routine, procedural activities like walking. As FOG is characterized as a de-automatization disorder, we hypothesized an impairment of the retrograde procedural memory in patients with FOG. Methods: A total of 194 patients from the Luxembourg Parkinson’s study were included into the cross-sectional study. All patients were assigned to the FOG+ / FOG- groups based on a semi-structured interview conducted by a study physician. The extended evaluation system of the cube copying test was applied to evaluate both the cube-drawing procedure, representing the retrograde procedural memory, and the final result, representing the visuo-constructive abilities (Pauly et al., 2020, MDS abstract). We compared the cube copying performance of n=97 FOG+ with n=97 age-, gender- and education-matched FOG-. Results: FOG+ scored lower on the cube copying procedure compared to the FOG- (p=0.027), which is suggestive of an impaired retrograde procedural memory in FOG+. No significant differences in the visuo-constructional abilities were detected (p=0.945). Conclusion: In line with FOG being considered a de-automatization of walking, a skill acquired in earlier life stages, the present results suggest that PwP with FOG have an impaired retrograde procedural memory in comparison to PwP without FOG. The results lend support to the ability of the extended evaluation system of the cube copying test to assess impaired retrograde procedural memory and help improve our understanding of behavioral symptoms in PwP. [less ▲]

Massive MIMO Downlink Transmission for LEO Satellite Communications

Poster (2021, September)

We investigate the downlink (DL) transmit strategy for massive multiple-input multiple-output (MIMO) low-earthorbit (LEO) satellite communication (SATCOM) systems, in which only the slow-varying ... [more ▼]

We investigate the downlink (DL) transmit strategy for massive multiple-input multiple-output (MIMO) low-earthorbit (LEO) satellite communication (SATCOM) systems, in which only the slow-varying statistical channel state information is known at the transmitter side. First, we establish the massive MIMO LEO satellite channel model, in which the uniform planar arrays are deployed at both the satellite and user terminals (UTs). Building on the rank-one property of satellite channel matrices, we show that transmitting a single data stream to each UT is optimal for the ergodic sum rate maximization. This result is of great importance for massive MIMO LEO SATCOM systems, since the sophisticated design of transmit covariance matrices is turned into that of precoding vectors, with no loss of optimality at all. Furthermore, we conceive an algorithm to compute the precoding vectors. Simulation results show the significant performance gains of the proposed approaches over the previous schemes. [less ▲]

Developing multiliteracies in early years education in Luxembourg

Poster (2021, August 17)

Relationship between Critical Consciousness and Multiculturalism? A comparison across four countries

Poster (2021, July 29)

Multiculturalism Ideology (MCI) describes the “appreciation of the value of cultural diversity for a society, and a need for mutual acceptance and accommodation that promotes equitable participation” ... [more ▼]

Multiculturalism Ideology (MCI) describes the “appreciation of the value of cultural diversity for a society, and a need for mutual acceptance and accommodation that promotes equitable participation” (Berry, 2016, p. 416f). The aim of the present study was to explore if and how diversity-related attitudes and the perception of less privileged members of society are linked and thus contribute to the growing body of research on social inequity awareness. Whilst some studies have focused on MCI and minority rights, awareness of structural discrimination and lowering prejudice, few have focused specifically on Critical Consciousness (CC), the reflection about inequalities in society and action taken to address them. Components of CC include Critical Reflection (Perceived Inequality and Egalitarianism), Political Efficacy (Internal and External), and Critical Action (Sociopolitical Participation). The present study draws on a quantitative design. An online questionnaire was launched in four countries, France, Luxembourg, Hong Kong, and Malaysia, which differ in their approaches in dealing with diversity. Measures included the Critical Consciousness Scale, the Political Efficacy Short Scale with the subscales regarding internal and external political efficacy and the Multicultural Ideology Scale (MCI). The questionnaire was made available in English, French and German. The total sample comprised 120 participants (68.2% female, Mage = 26.40, SDage = 9.71). Results indicate that MCI was highly positively correlated with Perceived Inequality and Egalitarianism and negatively with External Political Efficacy. Mean scores for CC components and MCI did not statistically differ across the four countries, while the correlation patterns between CC components and MCI were different. This finding suggests that CC may develop quite independently of cultural influences, as perception of unequal treatment and status differences between groups is an issue prevalent in all societies. More detailed results and implications as well as limitations of the present study will be discussed. [less ▲]

A Cubesat-ready Phase Synchronization Digital Payload for Coherent Distributed Remote Sensing Missions

Poster (2021, July 15)

Distributed antenna arrays, fractionated payloads and cooperative platforms can provide unprecedented performance in the next generation of spaceborne communications and remote sensing systems. Remote ... [more ▼]

Distributed antenna arrays, fractionated payloads and cooperative platforms can provide unprecedented performance in the next generation of spaceborne communications and remote sensing systems. Remote phase synchronization of physically separated oscillators is the first step towards a coherent operation of distributed systems. This work shows the preliminary results of a TDD remote phase synchronization algorithm with a master-follower architecture. Herein, we describe the implementation and validation of the proposed algorithm. The implementation has been conducted in a Cubesat-ready software defined radio and validated at the end-to-end satellite communications testbed available at the University of Luxembourg. [less ▲]

𝑘-Pareto Optimality for Many-Objective Genetic Optimization

Poster (2021, July)

Investigating the associations of trajectories of depressive symptoms and self-perceived health and incident dementia : an unsupervised machine learning approach.

Poster (2021, July)

Background: Risk factors for dementia show inter-individually varying trajectories over the lifespan. However, risk factors have been mainly investigated with one time-point assessments. New research ... [more ▼]

Background: Risk factors for dementia show inter-individually varying trajectories over the lifespan. However, risk factors have been mainly investigated with one time-point assessments. New research suggests that certain risk factor trajectories are associated with increased risk of adverse cognitive outcomes (Demnitz et al., 2020 [https://doi.org/10.1101/2020.05.20.20106963]; Singh-Manoux et al., 2018 [https://doi.org/10.1016/j.jalz.2017.06.2637]). However, it remains unclear how sequential and simultaneous changes of risk factors alter the individual risk for developing dementia. Testing the joint contribution of trajectories of depressive symptoms and self-perceived health on incidence of dementia, we hypothesized that consistently poor as well as deteriorating trajectories increase the risk for incident dementia, and explored possible interactions of the trajectories. Method: A total of 5,326 respondents to the SHARE survey, mean age 73.9 years, and 6 complete follow-ups spanning ~13 years, answered the EURO-D depression scale, self-perceived health (SPH) (t1-t5), and self-reported dementia diagnosis at last follow-up (t6). To investigate the predictive ability of distinct longitudinal trajectories, we applied unsupervised statistical learning methods (K-means cluster modelling). Clusters indicated distinct risk factor trajectories, which were used as exposures in stepwise logistic regressions to predict incident dementia, controlling for age, gender, education, and country. Result: Cluster analysis revealed five distinct trajectories each for SPH and EURO-D, with varying dementia incidence. In stepwise logistic regressions, respondents with trajectories “consistently poor health” and “consistently high depression” showed elevated risk of dementia (OR = 4.02 [1.39, 14.75] and OR = 2.26 [1.03, 4.95], respectively) compared to the combined baseline risk for “consistently low depression” and “consistently good health”. Interactions were not significant. However, respondents with the combination of “consistently high depression” and “consistently poor health” showed increased risk (N = 246; 6.1% dementia). Conclusion: Applying unsupervised machine learning is helpful to incorporate longitudinal information on depressive symptoms and self-perceived health and model these risk factors longitudinally to test their contribution to explain incidence of dementia. The predictive ability of the trajectories of depressive symptoms and self-perceived health for dementia indicates the potential for improving the identification of people at risk for developing dementia in late life by exploiting trajectory information readily accessible through regular medical check-ups in old age. [less ▲]

Energy Efficiency Optimization Technique for SWIPT-enabled Multi-Group Multicasting Systems with Heterogeneous Users

Poster (2021, June)

We consider a multi-group (MG) multicasting (MC) system wherein a multi-antenna transmitter serves heterogeneous users capable of either information decoding (ID) or energy harvesting (EH), or both. In ... [more ▼]

We consider a multi-group (MG) multicasting (MC) system wherein a multi-antenna transmitter serves heterogeneous users capable of either information decoding (ID) or energy harvesting (EH), or both. In this context, we investigate a precoder design framework to explicitly serve the ID and EH users categorized within certain MC and EH groups. Specifically, the ID users are categorized within multiple MC groups while the EH users are a part of single (last) group. We formulate a problem to optimize the energy efficiency in the considered scenario under a quality-of-service (QoS) constraint. An algorithm based on Dinkelback method, slack-variable replacement, and second-order conic programming (SOCP)/semi-definite relaxation (SDR) is proposed to obtain a suitable solution for the above-mentioned fractional-objective dependent non-convex problem. Simulation results illustrate the benefits of proposed algorithm under several operating conditions and parameter values, while drawing a comparison between the two proposed methods. [less ▲]

Does Physical Activity Moderate The Influence Of Sedentary Behavior On Health In Young People?

Poster (2021, June)

Assessing the clinical utility of the DSM-5 internet gaming disorder criteria by using supervised machine learning

Poster (2021, May 21)

DATA-INTEGRATED MULTISCALE MODELLING OF FIBROUS EXTRACELLULAR MATRIX

Poster (2021, May 21)

Transferability of the Tkatchenko-Scheffler and the Many-body Dispersion Method Between Quantum Chemical Codes

Poster (2021, May 21)

Predicting Vulnerability to Poverty with Machine Learning

Poster (2021, May 21)

Science Inequalities

Poster (2021, May 21)

A data-driven computational framework to provide deformable solids with the sense of touch

Poster (2021, May 21)

A data-driven, probabilistic, computational framework will be developed that provides a deformable solid with the sense of 'touch', so that it can detect the shape and mechanical behaviour of its ... [more ▼]

A data-driven, probabilistic, computational framework will be developed that provides a deformable solid with the sense of 'touch', so that it can detect the shape and mechanical behaviour of its environment. The framework will rely on three modules: a mechanical model to simulate the contact between the deformable solid and its environment, a machine learning module to rapidly emulate the mechanical simulations, and a probabilistic framework to identify the shape and mechanical behaviour of the solid’s environment. [less ▲]

Poster Presentation: Talking Borders. From Local Expertise to Global Exchange - Das Potential von Citizen Science für die Grenzforschung

Poster (2021, May 06)

Privacy-Preserving PayString Service

Poster (2021, May)

PayString is an initiative to make payment identifiers global and human-readable, facilitating the exchange of payment information. However, the reference implementation lacks privacy and security ... [more ▼]

PayString is an initiative to make payment identifiers global and human-readable, facilitating the exchange of payment information. However, the reference implementation lacks privacy and security features, making it possible for anyone to access the payment information as long as the PayString identifier is known. Also, this paper presents the first performance evaluation of PayString. Via a large-scale testbed, our experimental results show an overhead which, given the privacy and security advantages offered, is acceptable in practice, thus making the proposed solution feasible. [less ▲]

Lunar Surface Images Enhancement for Space Resources Localization and Extraction

Poster (2021, April 19)

Bridging the space systems performance-reliability gap for future deep space resources exploration and exploitation.

Poster (2021, April)

In building equipment for space exploitation, one has to trade system robustness for the high processing capabilities and low energy consumption. The high performance, low robustness approach, is ... [more ▼]

In building equipment for space exploitation, one has to trade system robustness for the high processing capabilities and low energy consumption. The high performance, low robustness approach, is acceptable, especially in Earths’ vicinity. However, in more demanding (especially high-radiation) environments, attempts had disappointing outcomes. The processing-reliability gap, between highly reliable and highly performant systems, spans 2-3 orders of magnitude. This gap brings hope, that some of this excess processing power can be utilized, in building a combination of hardware and software mechanisms that is capable of increasing robustness and resilience of otherwise susceptible semiconductor devices, while allowing to harness the remaining processing power to build affordable space systems with large degrees of autonomy, rich functionality and high bandwidth. At the CritiX research group, we aim to bridge this performance-reliability gap, by researching the enabling building blocks for constructing more reliable and more secure System-on-Chips. [less ▲]

Quantification of removal mechanisms in vertical flow constructed wetlands as nature based solutions for treatment of wastewater effluent

Poster (2021, March 18)

Principles for setting single or multiline control based on network characteristics

Poster (2021, January)

Defining the Pre-Examination Experience of MRI patients through Affective Interaction.

Poster (2021)

For many patients, Magnetic Resonance Imaging (MRI) experiences are uncomfortable and associated with high levels of anxiety and stress. Such negative experiences may interfere with image quality and ... [more ▼]

For many patients, Magnetic Resonance Imaging (MRI) experiences are uncomfortable and associated with high levels of anxiety and stress. Such negative experiences may interfere with image quality and increase examination time. It is therefore necessary to understand the mental states of the patients prior to the examination in order to provide stress-relieving measures. Studies exploring MRI-related anxiety and interventions to alleviate it have typically relied on self-reported data (e.g. STAI-6 questionnaire) or psychophysiological measures [1], usually in the waiting room. One could however benefit from an alternative measurement approach to overcome the limitations of current methods. The purpose of our study is to develop a tool for measuring mental states in the context of MRI experiences and explore the suitability of various sensors to detect anxiety. [less ▲]

Categorization alters perception: Assessing potential predictors of pain categorization biases

Poster (2021)

Intelligent Reflecting Surface-assisted MU-MISO Systems with Imperfect Hardware: Channel Estimation and Beamforming Design

Poster (2021)

Intelligent reflecting surface (IRS), consisting of lowcost passive elements, is a promising technology for improving the spectral and energy efficiency of the fifth-generation (5G) and beyond networks ... [more ▼]

Intelligent reflecting surface (IRS), consisting of lowcost passive elements, is a promising technology for improving the spectral and energy efficiency of the fifth-generation (5G) and beyond networks. It is also noteworthy that an IRS can shape the reflected signal propagation. Most works in IRSassisted systems have ignored the impact of the inevitable residual hardware impairments (HWIs) at both the transceiver hardware and the IRS while any relevant works have addressed only simple scenarios, e.g., with single-antenna network nodes and/or without taking the randomness of phase noise at the IRS into account. In this work, we aim at filling up this gap by considering a general IRS-assisted multi-user (MU) multiple-input single-output (MISO) system with imperfect channel state information (CSI) and correlated Rayleigh fading. In parallel, we present a general computationally efficient methodology for IRS reflect beamforming (RB) optimization. Specifically, we introduce an advantageous channel estimation (CE) method for such systems accounting for the HWIs. Moreover, we derive the uplink achievable spectral efficiency (SE) with maximal-ratio combining (MRC) receiver, displaying three significant advantages being: 1) its closed-form expression, 2) its dependence only on large-scale statistics, and 3) its low training overhead. Notably, by exploiting the first two benefits, we achieve to perform optimization with respect to the that can take place only at every several coherence intervals, and thus, reduces significantly the computational cost compared to other methods which require frequent phase optimization. Among the insightful observations, we highlight that uncorrelated Rayleigh fading does not allow optimization of the SE, which makes the application of an IRS ineffective. Also, in the case that the phase drifts, describing the distortion of the phases in the RBM, are uniformly distributed, the presence of an IRS provides no advantage. The analytical results outperform previous works and are verified by Monte-Carlo (MC) simulations. [less ▲]

Ongoing sound changes in the Luxembourgish vowel system

Poster (2021)

Cross-Evaluation of Surface Meteorological Data and GNSS-derived Water Vapor with Re-analysis Information for South Georgia Island, South Atlantic Ocean

Poster (2020, December 11)

As one of the most important components of the global hydrologic cycle, atmospheric water vapor shows significant variability in both space and time over a large range of scales. This variability results ... [more ▼]

As one of the most important components of the global hydrologic cycle, atmospheric water vapor shows significant variability in both space and time over a large range of scales. This variability results from the interactions of many different factors, including topography and the presence of specific atmospheric processes. One of the key regions for affecting global climatic variations lies in the sub-Antarctic zone over the Southern Ocean with its Antarctic Circumpolar Current and the associated Antarctic Convergence. There, in this cold and maritime region, lies South Georgia Island with its weather and climate being largely affected by both the dominating ocean currents and the strong east ward blowing winds in this zone. While the island forms an important outpost for various surface observations in this largely under-sampled and extremely remote region, it also forms a barrier for these winds due to its high topography, which, in turn, leads to various local meteorological phenomena, such as foehn winds. Surface meteorological data have been available for several stations near King Edward Point (KEP) on South Georgia for much of the 20th century. Since 2013 and 2014, Global Navigation Satellite System (GNSS) data have been available at five locations around the periphery of the island and during a few months in 2016 also radiosonde data have been collected at KEP. This study aims at investigating the consistency between the different surface meteorological data sets such as temperature, pressure and wind direction/speed that have been collected at KEP and a nearby GNSS station on Brown Mountain (BMT) for which we also compare the precipitable water vapor estimates. A cross-evaluation of these data sets with model values from the ERA-Interim re-analyses is carried out to further investigate the performance of both instruments and models. Overall, our preliminary results show high consistency between the surface meteorological observations and the re-analysis model values. It was our main objective to investigate the homogeneity and accuracy of the BMT observation time series through cross-evaluation with the series of the official WMO station at KEP. Air temperature and pressure at both sites from observation and model data are strongly correlated at hourly intervals, reaching correlation coefficients in the range of 0.966 - 0.968 for the former data set. The difference temperature time series shows seasonal variations but no obvious steps. The difference pressure time series is flat, also indicating no discontinuities. A cross-evaluation of the wind observations shows the distinct directional feature at KEP for a station in a valley where the winds are funneled through the valley. For BMT the wind observations confirm the main directions of winds but also show the openness of the station from all directions. The observations of temperature, pressure, humidity and GNSS-derived PWV clearly show the signatures of the frequent foehn events. [less ▲]