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See detailComparing old maps with cartometric methods
Solchenbach, Karl UL

in e-Perimetron (2021)

The planimetric accuracy of old maps can be calculated using cartometric methods like Helmert transformations. As the choice of control points for these transformations is somewhat arbitrary, this may ... [more ▼]

The planimetric accuracy of old maps can be calculated using cartometric methods like Helmert transformations. As the choice of control points for these transformations is somewhat arbitrary, this may cause stochastic variations in the results. This paper addresses these stochastic variations and proposes to apply Bayesian data analysis methods to quantify the uncertainty of the cartometric calculations. The paper shows that the Bayesian data analysis is consistent with the deterministic calculations, and it provides safe statistical bounds for the results. [less ▲]

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See detailDistributed Prediction of Unsafe Reconfiguration Scenarios of Modular Robotic Programmable Matter
Piranda, Benoit; Chodkiewicz, Paweł; Holobut, Paweł et al

in IEEE Transactions on Robotics (2021), 37(6), 2226-2233

We present a distributed framework for predicting whether a planned reconfiguration step of a modular robot will mechanically overload the structure, causing it to break or lose stability under its own ... [more ▼]

We present a distributed framework for predicting whether a planned reconfiguration step of a modular robot will mechanically overload the structure, causing it to break or lose stability under its own weight. The algorithm is executed by the modular robot itself and based on a distributed iterative solution of mechanical equilibrium equations derived from a simplified model of the robot. The model treats intermodular connections as beams and assumes no-sliding contact between the modules and the ground. We also provide a procedure for simplified instability detection. The algorithm is verified in the Programmable Matter simulator VisibleSim, and in real-life experiments on the modular robotic system Blinky Blocks. © 2004-2012 IEEE. [less ▲]

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See detailTransfer learning for credit card fraud detection : A journey from research to production.
Siblini, Wissam; Coter, Guillaume; Fabry, Remy et al

in The Proceedings of the Data Science and Advanced Analytics (DSAA 2021) IEEE conference (2021)

The dark face of digital commerce generalization is the increase of fraud attempts. To prevent any type of attacks, state-of-the-art fraud detection systems are now embedding Machine Learning (ML) modules ... [more ▼]

The dark face of digital commerce generalization is the increase of fraud attempts. To prevent any type of attacks, state-of-the-art fraud detection systems are now embedding Machine Learning (ML) modules. The conception of such modules is only communicated at the level of research and papers mostly focus on results for isolated benchmark datasets and metrics. But research is only a part of the journey, preceded by the right formulation of the business problem and collection of data, and followed by a practical integration. In this paper, we give a wider vision of the process, on a case study of transfer learning for fraud detection, from business to research, and back to business. [less ▲]

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See detailIncremental learning strategies for credit cards fraud detection.
Lebichot, Bertrand UL; Gian-Marco, Paldino; Wissam, Siblini et al

in nternational Journal of Data Science and Analytics (2021)

very second, thousands of credit or debit card transactions are processed in financial institutions. This extensive amount of data and its sequential nature make the problem of fraud detection ... [more ▼]

very second, thousands of credit or debit card transactions are processed in financial institutions. This extensive amount of data and its sequential nature make the problem of fraud detection particularly challenging. Most analytical strategies used in production are still based on batch learning, which is inadequate for two reasons: Models quickly become outdated and require sensitive data storage. The evolving nature of bank fraud enshrines the importance of having up-to-date models, and sensitive data retention makes companies vulnerable to infringements of the European General Data Protection Regulation. For these reasons, evaluating incremental learning strategies is recommended. This paper designs and evaluates incremental learning solutions for real-world fraud detection systems. The aim is to demonstrate the competitiveness of incremental learning over conventional batch approaches and, consequently, improve its accuracy employing ensemble learning, diversity and transfer learning. An experimental analysis is conducted on a full-scale case study including five months of e-commerce transactions and made available by our industry partner, Worldline. [less ▲]

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See detailPatterning enhanced tetragonality in BiFeO3 thin films with effective negative pressure by helium implantation
Toulouse, Constance UL; Fischer, Johanna; Farokhipoor, Saeedeh et al

in Physical Review Materials (2021), 5(2), 024404

Helium implantation in epitaxial thin films is a way to control the out-of-plane deformation independently from the in-plane strain controlled by epitaxy. In particular, implantation by means of a helium ... [more ▼]

Helium implantation in epitaxial thin films is a way to control the out-of-plane deformation independently from the in-plane strain controlled by epitaxy. In particular, implantation by means of a helium microscope allows for local implantation and patterning down to the nanometer resolution, which is of interest for device applications. We present here a study of bismuth ferrite (BiFeO3) films where strain was patterned locally by helium implantation. Our combined Raman, x-ray diffraction, and transmission electron microscopy (TEM) study shows that the implantation causes an elongation of the BiFeO3 unit cell and ultimately a transition towards the so-called supertetragonal polymorph via states with mixed phases. In addition, TEM reveals the onset of amorphization at a threshold dose that does not seem to impede the overall increase in tetragonality. The phase transition from the R-like to T-like BiFeO3 appears as first-order in character, with regions of phase coexistence and abrupt changes in lattice parameters. [less ▲]

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See detailTransfer Learning Strategies for Credit Card Fraud Detection.
Lebichot, Bertrand UL; Verheslt, Théo; Le Borgne, Yann-aël et al

in IEEE Access (2021)

Credit card fraud jeopardizes the trust of customers in e-commerce transactions. This led in recent years to major advances in the design of automatic Fraud Detection Systems (FDS) able to detect ... [more ▼]

Credit card fraud jeopardizes the trust of customers in e-commerce transactions. This led in recent years to major advances in the design of automatic Fraud Detection Systems (FDS) able to detect fraudulent transactions with short reaction time and high precision. Nevertheless, the heterogeneous nature of the fraud behavior makes it difficult to tailor existing systems to different contexts (e.g. new payment systems, different countries and/or population segments). Given the high cost (research, prototype development, and implementation in production) of designing data-driven FDSs, it is crucial for transactional companies to define procedures able to adapt existing pipelines to new challenges. From an AI/machine learning perspective, this is known as the problem of transfer learning. This paper discusses the design and implementation of transfer learning approaches for e-commerce credit card fraud detection and their assessment in a real setting. The case study, based on a six-month dataset (more than 200 million e-commerce transactions) provided by the industrial partner, relates to the transfer of detection models developed for a European country to another country. In particular, we present and discuss 15 transfer learning techniques (ranging from naive baselines to state-of-the-art and new approaches), making a critical and quantitative comparison in terms of precision for different transfer scenarios. Our contributions are twofold: (i) we show that the accuracy of many transfer methods is strongly dependent on the number of labeled samples in the target domain and (ii) we propose an ensemble solution to this problem based on self-supervised and semi-supervised domain adaptation classifiers. The thorough experimental assessment shows that this solution is both highly accurate and hardly sensitive to the number of labeled samples. [less ▲]

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See detailL'architecture d'un sol commun
Hertweck, Florian UL

in FACES Journal d'architecture (2021), 79

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See detailUplink Power Control in Massive MIMO with Double Scattering Channels
Trinh, van Chien UL; Ngo, Quoc Hien; Chatzinotas, Symeon UL et al

in IEEE Transactions on Wireless Communications (2021)

Massive multiple-input multiple-output (MIMO) is a key technology for improving the spectral and energy efficiency in 5G-and-beyond wireless networks. For a tractable analysis, most of the previous works ... [more ▼]

Massive multiple-input multiple-output (MIMO) is a key technology for improving the spectral and energy efficiency in 5G-and-beyond wireless networks. For a tractable analysis, most of the previous works on Massive MIMO have been focused on the system performance with complex Gaussian channel impulse responses under rich-scattering environments. In contrast, this paper investigates the uplink ergodic spectral efficiency (SE) of each user under the double scattering channel model. We derive a closed-form expression of the uplink ergodic SE by exploiting the maximum ratio (MR) combining technique based on imperfect channel state information. We further study the asymptotic SE behaviors as a function of the number of antennas at each base station (BS) and the number of scatterers available at each radio channel. We then formulate and solve a total energy optimization problem for the uplink data transmission that aims at simultaneously satisfying the required SEs from all the users with limited data power resource. Notably, our proposed algorithms can cope with the congestion issue appearing when at least one user is served by lower SE than requested. Numerical results illustrate the effectiveness of the closed-form ergodic SE over Monte-Carlo simulations. Besides, the system can still provide the required SEs to many users even under congestion. [less ▲]

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See detailAdverse Life Trajectories Are a Risk Factor for SARS-CoV-2 IgA Seropositivity.
Holuka, Cyrielle; Snoeck, Chantal J.; Mériaux, Sophie B. et al

in Journal of clinical medicine (2021), 10(10),

Asymptomatic individuals, called "silent spreaders" spread SARS-CoV-2 efficiently and have complicated control of the ongoing COVID-19 pandemic. As seen in previous influenza pandemics, socioeconomic and ... [more ▼]

Asymptomatic individuals, called "silent spreaders" spread SARS-CoV-2 efficiently and have complicated control of the ongoing COVID-19 pandemic. As seen in previous influenza pandemics, socioeconomic and life-trajectory factors are important in disease progression and outcome. The demographics of the asymptomatic SARS-CoV-2 carriers are unknown. We used the CON-VINCE cohort of healthy, asymptomatic, and oligosymptomatic individuals that is statistically representative of the overall population of Luxembourg for age, gender, and residency to characterise this population. Gender (male), not smoking, and exposure to early-life or adult traumatic experiences increased the risk of IgA seropositivity, and the risk associated with early-life exposure was a dose-dependent metric, while some other known comorbidities of active COVID-19 do not impact it. As prior exposure to adversity is associated with negative psychobiological reactions to external stressors, we recorded psychological wellbeing during the study period. Exposure to traumatic events or concurrent autoimmune or rheumatic disease were associated with a worse evolution of anxiety and depressive symptoms throughout the lockdown period. The unique demographic profile of the "silent spreaders" highlights the role that the early-life period plays in determining our lifelong health trajectory and provides evidence that the developmental origins of health and disease is applicable to infectious diseases. [less ▲]

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See detailA Trusted Hybrid Learning Approach to Secure Edge Computing
Sedjelmaci, Hichem; Senouci, Sidi Mohammed; Ansari, Nirwan et al

in IEEE Consumer Electronics Magazine (2021)

Securing edge computing has drawn much attention due to the vital role of edge computing in Fifth Generation (5G) wireless networks. Artificial Intelligence (AI) has been adopted to protect networks ... [more ▼]

Securing edge computing has drawn much attention due to the vital role of edge computing in Fifth Generation (5G) wireless networks. Artificial Intelligence (AI) has been adopted to protect networks against attackers targeting the connected edge devices or the wireless channel. However, the proposed detection mechanisms could generate a high false detection rate, especially against unknown attacks defined as zero-day threats. Thereby, we propose and conceive a new hybrid learning security framework that combines the expertise of security experts and the strength of machine learning to protect the edge computing network from known and unknown attacks, while minimizing the false detection rate. Moreover, to further decrease the number of false detections, a cyber security mechanism based on a Stackelberg game is used by the hybrid learning security engine (activated at each edge server) to assess the detection decisions provided by the neighboring security engines. [less ▲]

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See detailResponsible Vulnerability Disclosure under the NIS 2.0 Proposal
Schmitz, Sandra UL; Schiffner, Stefan UL

in Journal of Intellectual Property, Information Technology and E-Commerce Law (2021), 12(5),

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See detailSchloss Malberg - Das Barockjuwel in der Südeifel
Solchenbach, Karl UL

Book published by Förderverein Schloss Malberg (2021)

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See detailHow photoluminescence can predict the efficiency of solar cells
Siebentritt, Susanne UL; Weiss, Thomas UL; Sood, Mohit UL et al

in JPhys Materials (2021)

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See detailSimilarities and Differences in How Supervisors at Canadian and UK Institutions Understand Doctoral Supervision.
Kreber, Carolin; Wealer, Cyril UL; Heather, Kanuka

in International Journal of Doctoral Studies (2021), (16), 657-688

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See detailGDAP1 loss of function inhibits the mitochondrial pyruvate dehydrogenase complex by altering the actin cytoskeleton 2021.03.04.433895
Wolf, Christina; Pouya, Alireza; Bitar, Sara et al

E-print/Working paper (2021)

Charcot-Marie-Tooth (CMT) disease 4A is an autosomal-recessive polyneuropathy caused by mutations of ganglioside-induced differentiation-associated protein 1 (GDAP1), a putative glutathione transferase ... [more ▼]

Charcot-Marie-Tooth (CMT) disease 4A is an autosomal-recessive polyneuropathy caused by mutations of ganglioside-induced differentiation-associated protein 1 (GDAP1), a putative glutathione transferase, which affects mitochondrial shape and alters cellular Ca2+ homeostasis. Here, we identify the underlying mechanism. We found that patient-derived motoneurons and GDAP1 knockdown SH-SY5Y cells display two phenotypes: more tubular mitochondria and a metabolism characterized by glutamine dependence and fewer cytosolic lipid droplets. GDAP1 interacts with the actin-depolymerizing protein Cofilin-1 in a redoxdependent manner, suggesting a role for actin signaling. Consistently, GDAP1 loss causes less F-actin close to mitochondria, which restricts mitochondrial localization of the fission factor dynamin-related protein 1, instigating tubularity. Changes in the actin cytoskeleton also disrupt mitochondria-ER contact sites. This results in lower mitochondrial Ca2+ levels and inhibition of the pyruvate dehydrogenase complex, explaining the metabolic changes upon GDAP1 loss of function. Together, these findings reconcile GDAP1-associated phenotypes and implicate disrupted actin signaling in CMT4A pathophysiology. [less ▲]

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See detailGesundheit als Metapher. Über die ästhetischen Dimensionen eines nicht nur medizinischen Begriffs
Bendheim, Amelie UL; Jennifer, Pavlik

in Bendheim, Amelie; Pavlik, Jennifer (Eds.) Gesundheit als Metapher (2021)

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See detailThe Cost of No Reform: Assessing the Impact of Different Electricity Pricing Regimes on Indonesia\textquoterights Energy Trilemma
Heffron, Raphael; Körner, Marc Fabian; Sumarno, Theresia et al

E-print/Working paper (2021)

Many countries have a clear policy objective of increasing their share of renewable energy sources (RESs). However, a major impediment to higher RES penetration often lies in the historically grown ... [more ▼]

Many countries have a clear policy objective of increasing their share of renewable energy sources (RESs). However, a major impediment to higher RES penetration often lies in the historically grown structures of a country\textquoterights electricity sector. In Indonesia, policy makers have relied on cheap fossil fuels and state control to provide the population with access to both reliable and affordable electricity. However, this focus on only two of the three horns of the energy trilemma, namely energy security and energy equity (and not sustainability), may put Indonesia at risk of missing its ambitious RES targets. In this context, a number of small-scale reform attempts to promote RES integration in recent years have proved to be relatively unsuccessful. Like many other countries, Indonesia needs clear policy directions to avoid an unsustainable lock-in into a fossil fuel future. In the last decades, several other countries have successfully restructured their electricity sectors, for example by introducing a wholesale market for electricity under different electricity pricing systems, including nodal, zonal, or uniform pricing. These countries may hold valuable experiences of overcoming the historically grown barriers to successful RES integration through a greater role for market mechanisms. We develop three generic models that allow policy makers to analyze the impact of introducing either a nodal, a zonal, or a uniform pricing system on the three horns of the energy trilemma in their country. We evaluate our model using a simplified network representation of the Indonesian electricity sector. Our results indicate that each of the pricing systems is able to foster specific horns of the energy trilemma. Considering that any major reform intended to improve energy sustainability in Indonesia will only be a success if it also addresses energy security and energy equity, we also discuss our results from the perspective of energy justice and the need to balance the country\textquoterights energy trilemma. Ultimately, we illustrate a transformation pathway for a more sustainable and just transition to a low-carbon economy in Indonesia. [less ▲]

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See detailPreface - Journal of Applied Logics
Gabbay, Dov M. UL; Giacomin, Massimiliano; Simari, Guillermo Ricardo et al

in IfCoLog Journal of Logics and Their Applications (2021), 8(6), 1335-1338

Detailed reference viewed: 27 (0 UL)