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Peer Reviewed
See detailScalable Viewing. Digitale Methoden und die Digital Humanities
Pause, Johannes UL; Walkowski, Niels-Oliver UL

E-print/Working paper (2019)

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See detailMOBILITY ANALYSIS AND PROFILING FOR SMART MOBILITY SERVICES: A BIG DATA DRIVEN APPROACH. An Integration of Data Science and Travel Behaviour Analytics
Toader, Bogdan UL

Doctoral thesis (2019)

Smart mobility proved to be an important but challenging component of the smart cities paradigm. The increased urbanization and the advent of sharing economy require a complete digitalisation of the way ... [more ▼]

Smart mobility proved to be an important but challenging component of the smart cities paradigm. The increased urbanization and the advent of sharing economy require a complete digitalisation of the way travellers interact with the mobility services. New sharing mobility services and smart transportation models are emerging as partial solutions for solving some tra c problems, improve the resource e ciency and reduce the environmental impact. The high connectivity between travellers and the sharing services generates enormous quantity of data which can reveal valuable knowledge and help understanding complex travel behaviour. Advances in data science, embedded computing, sensing systems, and arti cial intelligence technologies make the development of a new generation of intelligent recommendation systems possible. These systems have the potential to act as intelligent transportation advisors that can o er recommendations for an e cient usage of the sharing services and in uence the travel behaviour towards a more sustainable mobility. However, their methodological and technological requirements will far exceed the capabilities of today's smart mobility systems. This dissertation presents a new data-driven approach for mobility analysis and travel behaviour pro ling for smart mobility services. The main objective of this thesis is to investigate how the latest technologies from data science can contribute to the development of the next generation of mobility recommendation systems. Therefore, the main contribution of this thesis is the development of new methodologies and tools for mobility analysis that aim at combining the domain of transportation engineering with the domain of data science. The addressed challenges are derived from speci c open issues and problems in the current state of the art from the smart mobility domain. First, an intelligent recommendation system for sharing services needs a general metric which can assess if a group of users are compatible for speci c sharing solutions. For this problem, this thesis presents a data driven indicator for collaborative mobility that can give an indication whether it is economically bene cial for a group of users to share the ride, a vehicle or a parking space. Secondly, the complex sharing mobility scenarios involve a high number of users and big data that must be handled by capable modelling frameworks and data analytic platforms. To tackle this problem, a suitable meta model for the transportation domain is created, using the state of the art multi-dimensional graph data models, technologies and analytic frameworks. Thirdly, the sharing mobility paradigm needs an user-centric approach for dynamic extraction of travel habits and mobility patterns. To address this challenge, this dissertation proposes a method capable of dynamically pro ling users and the visited locations in order to extract knowledge (mobility patterns and habits) from raw data that can be used for the implementation of shared mobility solutions. Fourthly, the entire process of data collection and extraction of the knowledge should be done with near no interaction from user side. To tackle this issue, this thesis presents practical applications such as classi cation of visited locations and learning of users' travel habits and mobility patterns using historical and external contextual data. [less ▲]

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See detailDeformation quantization of Kähler manifolds
La Fuente-Gravy, Laurent UL

Presentation (2019, March 11)

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See detailLes premières élections sociales en 1903: une rupture historique
Scuto, Denis UL

Article for general public (2019)

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Peer Reviewed
See detailCRAFT: Lightweight Tweakable Block Cipher with Efficient Protection Against DFA Attacks
Beierle, Christof UL; Leander, Gregor; Moradi, Amir et al

in IACR Transactions on Symmetric Cryptology (2019), 2019(1), 5-45

Traditionally, countermeasures against physical attacks are integrated into the implementation of cryptographic primitives after the algorithms have been designed for achieving a certain level of ... [more ▼]

Traditionally, countermeasures against physical attacks are integrated into the implementation of cryptographic primitives after the algorithms have been designed for achieving a certain level of cryptanalytic security. This picture has been changed by the introduction of PICARO, ZORRO, and FIDES, where efficient protection against Side-Channel Analysis (SCA) attacks has been considered in their design. In this work we present the tweakable block cipher CRAFT: the efficient protection of its implementations against Differential Fault Analysis (DFA) attacks has been one of the main design criteria, while we provide strong bounds for its security in the related-tweak model. Considering the area footprint of round-based hardware implementations, CRAFT outperforms the other lightweight ciphers with the same state and key size. This holds not only for unprotected implementations but also when fault-detection facilities, side-channel protection, and their combination are integrated into the implementation. In addition to supporting a 64-bit tweak, CRAFT has the additional property that the circuit realizing the encryption can support the decryption functionality as well with very little area overhead. [less ▲]

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See detailLower plasma insulin levels during overnight closed loop in schoolchildren with type 1 diabetes: potential advantage?
Schierloh, Ulrike; Wilinska, M.; Pit-Ten Cate, Ineke UL et al

in PLoS ONE (2019), 14(3: e0212013), 1-11

Background Studies have shown that overnight closed-loop insulin delivery can improve glucose control and reduce the risk of hypoglycemia and hence may improve metabolic outcomes and reduce burden for ... [more ▼]

Background Studies have shown that overnight closed-loop insulin delivery can improve glucose control and reduce the risk of hypoglycemia and hence may improve metabolic outcomes and reduce burden for children with type 1 diabetes and their families. However, research so far has not reported insulin levels while comparing closed-loop to open-loop insulin delivery in children. Therefore, in this study we obtained glucose levels as well plasma insulin levels in children with type 1 diabetes to evaluate the efficacy of a model - based closed-loop algorithm compared to an open-loop administration. Methods Fifteen children with type 1 diabetes, 6-12 years, participated in this open-label single center study. We used a randomized cross over design in which we compared overnight closed-loop insulin delivery with sensor augmented pump therapy for two nights in both the hospital and at home (i.e., 1 night in-patient stay and at home per treatment condition). Only during the in-patient stay, hourly plasma insulin and blood glucose levels were assessed and are reported in this paper. Results Results of paired sample t-tests revealed that although plasma insulin levels were significantly lower during the closed-loop than in the open-loop (Mean difference 36.51 pmol/l; t(13)=2.13, p=.03, effect size d= 0.57), blood glucose levels did not vary between conditions (mean difference 0.76 mmol/l; t(13)=1.24, p=.12, d=0.37). The administered dose of insulin was significantly lower during the closed-loop compared with the open-loop (mean difference 0.10 UI; t(12)=2.45, p=.02, d=0.68). Conclusions Lower insulin doses were delivered in the closed-loop, resulting in lower plasma insulin levels , whereby glucose levels were not affected negatively. This suggests that the closed-loop administration is better targeted and hence could be more effective. [less ▲]

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See detailDu papier aux données
Schafer, Valerie UL

Conference given outside the academic context (2019)

Ce discours proposait un parcours historique au cœur de 50 ans d’invention et de ré-invention de l’Office des publications de l'Union Européenne, et ce à la croisée de l’histoire européenne et de ... [more ▼]

Ce discours proposait un parcours historique au cœur de 50 ans d’invention et de ré-invention de l’Office des publications de l'Union Européenne, et ce à la croisée de l’histoire européenne et de l’histoire des réseaux et technologies numériques. L’Office est en effet un point d’observation privilégié de ces évolutions, qui bien sûr ne sont pas linéaires et connaissent des temps de doutes comme d’accélération. [less ▲]

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See detailSequence Organisation: What is the interactional work done? Insights from Conversation Analysis!
Arend, Béatrice UL; Sunnen, Patrick UL

Presentation (2019, March 07)

Conversation Analysis is concerned with how people achieve current actions mainly through talk. CA investigates how and why we understand (or misunderstand) each other. Talk-in-interaction is sequentially ... [more ▼]

Conversation Analysis is concerned with how people achieve current actions mainly through talk. CA investigates how and why we understand (or misunderstand) each other. Talk-in-interaction is sequentially organised action! “There is order at all points” (Harvey Sacks). Thus, one primary issue of applied conversation analysis is to visualise this order as well as the ‘work done’ by the interlocutors during conversation. Turn-construction, pauses, overlaps are not anodyne but relevant accounts of meaning making and understanding. [less ▲]

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See detailRegulation in Digital Financial Services (DFS)
Dewi, Tsany Ratna UL

Presentation (2019, March 07)

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See detailDeep neural networks outperform human expert's capacity in characterizing bioleaching bacterial biofilm composition
Buetti-Dinh, Antoine; Galli, Vanni; Bellenberg, Sören et al

in Biotechnology Reports (2019)

Background Deep neural networks have been successfully applied to diverse fields of computer vision. However, they only outperform human capacities in a few cases. Methods The ability of deep neural ... [more ▼]

Background Deep neural networks have been successfully applied to diverse fields of computer vision. However, they only outperform human capacities in a few cases. Methods The ability of deep neural networks versus human experts to classify microscopy images was tested on biofilm colonization patterns formed on sulfide minerals composed of up to three different bioleaching bacterial species attached to chalcopyrite sample particles. Results A low number of microscopy images per category (<600) was sufficient for highly efficient computational analysis of the biofilm's bacterial composition. The use of deep neural networks reached an accuracy of classification of ∼90% compared to ∼50% for human experts. Conclusions Deep neural networks outperform human experts’ capacity in characterizing bacterial biofilm composition involved in the degradation of chalcopyrite. This approach provides an alternative to standard, time-consuming biochemical methods. [less ▲]

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See detailCorporate Governance of Financial Institutions
Dewi, Tsany Ratna UL

Presentation (2019, March 06)

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See detailA unified polygonal locking-free thin/thick smoothed plate element
Katili, Irwan; Maknun, Imam Jauhari; Katili, Andi Makarim et al

in Composite Structures (2019), 219

A novel cell-based smoothed finite element method is proposed for thin and thick plates based on Reissner-Mindlin plate theory and assumed shear strain fields. The domain is discretized with arbitrary ... [more ▼]

A novel cell-based smoothed finite element method is proposed for thin and thick plates based on Reissner-Mindlin plate theory and assumed shear strain fields. The domain is discretized with arbitrary polygons and on each side of the polygonal element, discrete shear constraints are considered to relate the kinematical and the independent shear strains. The plate is made of functionally graded material with effective properties computed using the rule of mixtures. The influence of various parameters, viz., the plate aspect ratio and the material gradient index on the static bending response and the first fundamental frequency is numerically studied. It is seen that the proposed element: (a) has proper rank; (b) does not require derivatives of shape functions and hence no isoparametric mapping required; (c) independent of shape and size of elements and (d) is free from shear locking. [less ▲]

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See detailCultures of memory and practices of forgetting in the digital age
Fickers, Andreas UL

Presentation (2019, March 05)

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See detailCombining Deep Gaussian Process and Rule-Based Method for Decision-Making in Self-Driving Simulation with Small Data
Fang, W.; Li, H.; Dang, S. et al

in 2019 15th International Conference on Computational Intelligence and Security (CIS) (2019, March 05)

Self-driving vehicle is a popular and promising field in artificial intelligence. Conventional architecture consists of multiple sensors, which work collaboratively to sense the units on road to yield a ... [more ▼]

Self-driving vehicle is a popular and promising field in artificial intelligence. Conventional architecture consists of multiple sensors, which work collaboratively to sense the units on road to yield a precise and safe driving strategy. Besides the precision and safety, the quickness of decision is also a major concern. In order to react quickly, the vehicle need to predict its next possible action, such as acceleration, brake and steering angle, according to its latest few actions and status. In this paper, we treat this decision-making problem as a regression problem and use deep gaussian process to predict its next action. The regression model is trained using simulation data sets and accurately captures the most significant features. Combined with rule-based method, it can be used in Torcs simulation engine to realize successful loop trip on virtual roads. The proposed method outperforms the existing reinforcement learning methods on the performance indicators of time consumption and the size of data volume. It may be useful for real road tests in the future. [less ▲]

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See detailQuality of life predicts outcome of deep brain stimulation in early Parkinson disease
Krüger, Rejko UL; EARLYSTIM study group; Schuepbach, Michael et al

in Neurology (2019)

Objective Toinvestigatepredictorsforimprovementofdisease-specificqualityoflife(QOL)afterdeepbrainstimulation (DBS) of the subthalamic nucleus (STN) for Parkinson disease (PD) with early motor complications ... [more ▼]

Objective Toinvestigatepredictorsforimprovementofdisease-specificqualityoflife(QOL)afterdeepbrainstimulation (DBS) of the subthalamic nucleus (STN) for Parkinson disease (PD) with early motor complications. Methods We performed a secondary analysis of data from the previously published EARLYSTIM study, a prospective randomizedtrialcomparingSTN-DBS(n= 124)tobestmedicaltreatment(n= 127)after2yearsfollow-up with disease-specific QOL (39-item Parkinson ’s Disease Questionnaire summary index [PDQ-39-SI]) as the primary endpoint. Linear regression analyses of the baseline characteristics age, disease duration, duration of motor complications, and disease severity measured at baseline with the Unified Parkinson’s Disease Rating Scale(UPDRS)(UPDRS-III“off”and“on”medications,UPDRS-IV)wereconductedtodeterminepredictors of change in PDQ-39-SI. Results PDQ-39-SIatbaselinewascorrelatedtothechangeinPDQ-39-SIafter24monthsinbothtreatmentgroups (p<0.05).Thehigherthebaselinescore(worseQOL)thelargertheimprovementinQOLafter24months. No correlation was found for any of the other baseline characteristics analyzed in either treatment group. Conclusion Impaired QOL as subjectively evaluated by the patient is the most important predictor of benefit in patients with PD and early motor complications, fulfilling objective gold standard inclusion criteria for STN-DBS. Our results prompt systematically including evaluation of disease-specific QOL when selecting patients with PD for STN-DBS. [less ▲]

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See detailIon-Hydroxyl Interactions: From High-Level Quantum Benchmarks to Transferable Polarizable Force Fields
Wineman-Fisher, Vered; Al-Hamdani, Yasmine; Addou, Iqbal et al

in Journal of Chemical Theory and Computation (2019), 154

Ion descriptors in molecular mechanics models are calibrated against reference data on ion–water interactions. It is then typically assumed that these descriptors will also satisfactorily describe ... [more ▼]

Ion descriptors in molecular mechanics models are calibrated against reference data on ion–water interactions. It is then typically assumed that these descriptors will also satisfactorily describe interactions of ions with other functional groups, such as those present in biomolecules. However, several studies now demonstrate that this transferability assumption produces, in many different cases, large errors. Here we address this issue in a representative polarizable model and focus on transferability of cationic interactions from water to a series of alcohols. Both water and alcohols use hydroxyls for ion-coordination, and, therefore, this set of molecules constitutes the simplest possible case of transferability. We obtain gas phase reference data systematically from “gold-standard” quantum Monte Carlo and CCSD(T) methods, followed by benchmarked vdW-corrected DFT. We learn that the original polarizable model yields large gas phase water → alcohol transferability errors – the RMS and maximum errors are 2.3 and 5.1 kcal/mol, respectively. These errors are, nevertheless, systematic in that ion-alcohol interactions are overstabilized, and systematic errors typically imply that some essential physics is either missing or misrepresented. A comprehensive analysis shows that when both low- and high-field responses of ligand dipole polarization are described accurately, then transferability improves significantly – the RMS and maximum errors in the gas phase reduce, respectively, to 0.9 and 2.5 kcal/mol. Additionally, predictions of condensed phase transfer free energies also improve. Nevertheless, within the limits of the extrathermodynamic assumptions necessary to separate experimental estimates of salt dissolution into constituent cationic and anionic contributions, we note that the error in the condensed phase is systematic, which we attribute, at least, partially to the parametrization in long-range electrostatics. Overall, this work demonstrates a rational approach to boosting transferability of ionic interactions that will be applicable broadly to improving other polarizable and nonpolarizable models. [less ▲]

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See detailCharacterizations and classifications of quasitrivial semigroups
Devillet, Jimmy UL; Marichal, Jean-Luc UL; Teheux, Bruno UL

Scientific Conference (2019, March 03)

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