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See detailRevisiting Deniability in Quantum Key Exchange via Covert Communication and Entanglement Distillation
Atashpendar, Arash UL; Policharla, Guru Vamsi; Roenne, Peter UL et al

in Secure IT Systems, 23rd Nordic Conference, NordSec 2018 (in press)

We revisit the notion of deniability in quantum key exchange (QKE), a topic that remains largely unexplored. In the only work on this subject by Donald Beaver, it is argued that QKE is not necessarily ... [more ▼]

We revisit the notion of deniability in quantum key exchange (QKE), a topic that remains largely unexplored. In the only work on this subject by Donald Beaver, it is argued that QKE is not necessarily deniable due to an eavesdropping attack that limits key equivocation. We provide more insight into the nature of this attack and how it extends to other constructions such as QKE obtained from uncloneable encryption. We then adopt the framework for quantum authenticated key exchange, developed by Mosca et al., and extend it to introduce the notion of coercer-deniable QKE, formalized in terms of the indistinguishability of real and fake coercer views. Next, we apply results from a recent work by Arrazola and Scarani on covert quantum communication to establish a connection between covert QKE and deniability. We propose DC-QKE, a simple deniable covert QKE protocol, and prove its deniability via a reduction to the security of covert QKE. Finally, we consider how entanglement distillation can be used to enable information-theoretically deniable protocols for QKE and tasks beyond key exchange. [less ▲]

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See detailHomotopical algebraic context over differential operators
Di Brino, Gennaro; Pistalo, Damjan UL; Poncin, Norbert UL

in Journal of Homotopy and Related Structures (in press)

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See detailRevisiting Gaussian Mixture Models for Driver Identification
Jafarnejad, Sasan UL; Castignani, German UL; Engel, Thomas UL

in Proceedings of IEEE International Conference on Vehicular Electronics and Safety (ICVES) (ICVES 2018) (in press)

The increasing penetration of connected vehicles nowadays has enabled driving data collection at a very large scale. Many telematics applications have been also enabled from the analysis of those datasets ... [more ▼]

The increasing penetration of connected vehicles nowadays has enabled driving data collection at a very large scale. Many telematics applications have been also enabled from the analysis of those datasets and the usage of Machine Learning techniques, including driving behavior analysis predictive maintenance of vehicles, modeling of vehicle health and vehicle component usage, among others. In particular, being able to identify the individual behind the steering wheel has many application fields. In the insurance or car-rental market, the fact that more than one driver make use of the vehicle generally triggers extra fees for the contract holder. Moreover being able to identify different drivers enables the automation of comfort settings or personalization of advanced driver assistance (ADAS) technologies. In this paper, we propose a driver identification algorithm based on Gaussian Mixture Models (GMM). We show that only using features extracted from the gas pedal position and steering wheel angle signals we are able to achieve near 100 accuracy in scenarios with up to 67 drivers. In comparison to the state-of-the-art, our proposed methodology has lower complexity, superior accuracy and offers scalability to a larger number of drivers. [less ▲]

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See detailAn Empirical Evaluation of Evolutionary Algorithms for Unit Test Suite Generation
Campos, Jose; Ge, Yan; Albunian, Nasser et al

in Information and Software Technology (in press)

Context: Evolutionary algorithms have been shown to be e ective at generating unit test suites optimised for code coverage. While many speci c aspects of these algorithms have been evaluated in detail (e ... [more ▼]

Context: Evolutionary algorithms have been shown to be e ective at generating unit test suites optimised for code coverage. While many speci c aspects of these algorithms have been evaluated in detail (e.g., test length and di erent kinds of techniques aimed at improving performance, like seeding), the in uence of the choice of evolutionary algorithm has to date seen less attention in the literature. Objective: Since it is theoretically impossible to design an algorithm that is the best on all possible problems, a common approach in software engineering problems is to rst try the most common algorithm, a Genetic Algorithm, and only afterwards try to re ne it or compare it with other algorithms to see if any of them is more suited for the addressed problem. The objective of this paper is to perform this analysis, in order to shed light on the in uence of the search algorithm applied for unit test generation. Method: We empirically evaluate thirteen di erent evolutionary algorithms and two random approaches on a selection of non-trivial open source classes. All algorithms are implemented in the EvoSuite test generation tool, which includes recent optimisations such as the use of an archive during the search and optimisation for multiple coverage criteria. Results: Our study shows that the use of a test archive makes evolutionary algorithms clearly better than random testing, and it con rms that the DynaMOSA many-objective search algorithm is the most e ective algorithm for unit test generation. Conclusions: Our results show that the choice of algorithm can have a substantial in uence on the performance of whole test suite optimisation. Although we can make a recommendation on which algorithm to use in practice, no algorithm is clearly superior in all cases, suggesting future work on improved search algorithms for unit test generation [less ▲]

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See detailIdentifying elastoplastic parameters with Bayes' theorem considering double error sources and model uncertainty
Rappel, Hussein UL; Beex, Lars UL; Noels, Ludovic et al

in Probabilistic Engineering Mechanics (in press)

We discuss Bayesian inference for the identi cation of elastoplastic material parameters. In addition to errors in the stress measurements, which are commonly considered, we furthermore consider errors in ... [more ▼]

We discuss Bayesian inference for the identi cation of elastoplastic material parameters. In addition to errors in the stress measurements, which are commonly considered, we furthermore consider errors in the strain measurements. Since a difference between the model and the experimental data may still be present if the data is not contaminated by noise, we also incorporate the possible error of the model itself. The three formulations to describe model uncertainty in this contribution are: (1) a random variable which is taken from a normal distribution with constant parameters, (2) a random variable which is taken from a normal distribution with an input-dependent mean, and (3) a Gaussian random process with a stationary covariance function. Our results show that incorporating model uncertainty often, but not always, improves the results. If the error in the strain is considered as well, the results improve even more. [less ▲]

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See detailTeacher expectations concerning students with immigrant background or special educational needs
Pit-Ten Cate, Ineke UL; Glock, Sabine UL

in Journal of Educational Research and Evaluation (in press)

Male students with immigrant backgrounds are disproportionally referred for special educational support outside regular classrooms or schools, which may reflect differential teachers´ expectations ... [more ▼]

Male students with immigrant backgrounds are disproportionally referred for special educational support outside regular classrooms or schools, which may reflect differential teachers´ expectations concerning the academic achievement of students based on socio-demographic characteristics. Although research has indicated differential teachers´ expectations for students based on immigrant background or special educational needs (SEN), less is known about a possible double vulnerability associated with combined stereotypes. Therefore, in the current study both SEN and immigrant background were systematically varied and teachers were asked to rate the students´ academic achievement. Results show that teachers´ expectations of students with SEN and immigrant background was lower than for students without immigrant background, especially in regards to language proficiency. These results may help to explain the overrepresentation of students with immigrant background in special educational programs. The educational and theoretical implications of these findings are discussed. [less ▲]

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See detailMaintenance location routing for rolling stock under line and fleet planning uncertainty
Arts, Joachim UL; Tönissen, Denise; Shen, Zuo-Jun

in Transportation Science (in press)

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See detailNew synthetic opioids: Part of a new addiction landscape.
Karila, Laurent; Marillier, Maude; Chaumette, Boris et al

in Neuroscience and biobehavioral reviews (in press)

Synthetic opioids (SO) are a major risk for public health across the world. These drugs can be divided into 2 categories, pharmaceutical and non-pharmaceutical fentanyls. A new generation of SO has ... [more ▼]

Synthetic opioids (SO) are a major risk for public health across the world. These drugs can be divided into 2 categories, pharmaceutical and non-pharmaceutical fentanyls. A new generation of SO has emerged on the drug market since 2010. North America is currently facing an opioid epidemic of morbi-mortality, caused by over-prescription of opioids, illegally diverted prescribed medicines, the increasing use of heroin, is and the emergence of SO. Furthermore, this opioid crisis is also seen in Europe. SO are new psychoactive substances characterized by different feature such as easy availability on the Internet, low price, purity, legality, and lack of detection in laboratory tests. They have not been approved or are not recommended for human use. Opioid misuse is associated with somatic and psychiatric complications. For many substances, limited pharmacological information is available, increasing the risk of harmful adverse events. Health actors and the general population need to be clearly informed of the potential risks and consequences of the diffusion and use of SO. [less ▲]

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See detailSelfitis and behavioural addiction: A plea for terminological and conceptual rigour.
Starcevic, Vladan; Billieux, Joël UL; Schimmenti, Adriano

in The Australian and New Zealand journal of psychiatry (in press)

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See detailA Pedagogical Note on Risk Sharing Versus Instability in International Financial Integration: When Obstfeld Meets Stiglitz
Boucekkine, Raouf; Zou, Benteng UL

in Open Economies Review (2019)

The pure risk sharing mechanism implies that financial liberalization is growth enhancing for all countries as the world portfolio shifts from safe low-yield capital to riskier high-yield capital. This ... [more ▼]

The pure risk sharing mechanism implies that financial liberalization is growth enhancing for all countries as the world portfolio shifts from safe low-yield capital to riskier high-yield capital. This result is typically obtained under the assumption that the volatilities for risky assets prevailing under autarky are not altered after liberalization. We relax this assumption within a simple two-country model of intertemporal portfolio choices. By doing so, we put together the risk sharing effect and a well defined instability effect. We identify the conditions under which liberalization may cause a drop in growth. These conditions combine the typical threshold conditions outlined in the literature, which concern the deep characteristics of the economies, and size conditions on the instability effect induced by liberalization. [less ▲]

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See detailClimate politics: how public persuasion affects the trade-off between environmental and economic performance
Prieur, Fabien; Zou, Benteng UL

in Mathematical Social Sciences (2019)

This paper aims at studying the impact of public persuasion, through information dissemination, on environmental and economic performance. A differential game in which opposite interest groups compete for ... [more ▼]

This paper aims at studying the impact of public persuasion, through information dissemination, on environmental and economic performance. A differential game in which opposite interest groups compete for bringing the majority’s environmental concern closer to their views is developed. The results show a strong asymmetry in the impact of public persuasion. It may bring the median voter economy closer to the social optimum in the long run, thereby reducing environmental and economic distorsions. But this only occurs when the environmental group exhibits a radical ideology and people are initially closer to the industrialists’ views. By contrast, economies where industrial groups are powerful and strongly opposed to environmental protection never benefit from the outcome of the game of persuasion. This may explain why the US have failed to take action on global warming up to now. [less ▲]

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See detailTo MigrateWith orWithout Ones’ Children in China - That is the Question
Chen, Yiwen UL; Fromentin, Vincent; Zou, Benteng UL

in Annals of Eceonomcis and statistics (2019)

Where should Chinese internal migrant parents locate their school-aged children: migrate with them or leave them behind? And should they invest in private education of their children? We investigate ... [more ▼]

Where should Chinese internal migrant parents locate their school-aged children: migrate with them or leave them behind? And should they invest in private education of their children? We investigate whether migrant parents can afford to take their children to migrate and thus provide theoretical optimum that maximizes migrant parents’ utility which includes the children’s educational performance. Depending on the educational investment parents make and the relocation cost of children, we provide necessary and sufficient conditions under which migrant parents should take their children to migrate and conditions under which migrant parents should provide their children with private education. [less ▲]

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See detailPower and Load Optimization in Interference-Coupled Non-Orthogonal Multiple Access Networks
Lei, Lei UL; You, Lei; Yang, Yang UL et al

in IEEE Global Communications Conference (GLOBECOM) 2018 (2018, December)

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See detailThe Price of Privacy in Collaborative Learning
Pejo, Balazs UL; Tang, Qiang UL; Gergely, Biczok

Poster (2018, October)

Machine learning algorithms have reached mainstream status and are widely deployed in many applications. The accuracy of such algorithms depends significantly on the size of the underlying training ... [more ▼]

Machine learning algorithms have reached mainstream status and are widely deployed in many applications. The accuracy of such algorithms depends significantly on the size of the underlying training dataset; in reality a small or medium sized organization often does not have enough data to train a reasonably accurate model. For such organizations, a realistic solution is to train machine learning models based on a joint dataset (which is a union of the individual ones). Unfortunately, privacy concerns prevent them from straightforwardly doing so. While a number of privacy-preserving solutions exist for collaborating organizations to securely aggregate the parameters in the process of training the models, we are not aware of any work that provides a rational framework for the participants to precisely balance the privacy loss and accuracy gain in their collaboration. In this paper, we model the collaborative training process as a two-player game where each player aims to achieve higher accuracy while preserving the privacy of its own dataset. We introduce the notion of Price of Privacy, a novel approach for measuring the impact of privacy protection on the accuracy in the proposed framework. Furthermore, we develop a game-theoretical model for different player types, and then either find or prove the existence of a Nash Equilibrium with regard to the strength of privacy protection for each player. [less ▲]

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See detailReport: The European Commission's e-Evidence Proposals
Robinson, Gavin UL

in European Data Protection Law Review (2018), (3),

In April 2018, the European Commission presented a legislative package intended to enable, foster and formalise cross-border access by national judicial authorities to electronic evidence controlled by ... [more ▼]

In April 2018, the European Commission presented a legislative package intended to enable, foster and formalise cross-border access by national judicial authorities to electronic evidence controlled by private service providers.1 In particular the public-private character of the ‘cooperation’ envisaged in the proposed set-up raises several questions at the interface of criminal procedure and data protection law. This report provides a brief overview of the proposed EUlegislation and an introduction to themost salient attendant legal and policy-related issues. [less ▲]

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See detailShared Access Satellite-Terrestrial Reconfigurable Backhaul Network Enabled by Smart Antennas at MmWave Band
Artiga, Xavier; Pérez-Neira; Baranda et al

in IEEE Network (2018)

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See detailForum Choice and Cybercrime
Robinson, Gavin UL

in Ligeti, Katalin; Robinson, Gavin; European Law Institute (Eds.) Preventing and Resolving Conflicts of Jurisdiction in EU Criminal Law (2018)

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See detailKnowledge Graph-based Teacher Support for Learning Material Authoring
Grevisse, Christian UL; Manrique, Rubén; Mariño, Olga et al

in Advances in Computing - CCC 2018 (2018, September 26)

Preparing high-quality learning material is a time-intensive, yet crucial task for teachers of all educational levels. In this paper, we present SoLeMiO, a tool to recommend and integrate learning ... [more ▼]

Preparing high-quality learning material is a time-intensive, yet crucial task for teachers of all educational levels. In this paper, we present SoLeMiO, a tool to recommend and integrate learning material in popular authoring software. As teachers create their learning material, SoLeMiO identifies the concepts they want to address. In order to identify relevant concepts in a reliable, automatic and unambiguous way, we employ state of the art concept recognition and entity linking tools. From the recognized concepts, we build a semantic representation by exploiting additional information from Open Knowledge Graphs through expansion and filtering strategies. These concepts and the semantic representation of the learning material support the authoring process in two ways. First, teachers will be recommended related, heterogeneous resources from an open corpus, including digital libraries, domain-specific knowledge bases, and MOOC platforms. Second, concepts are proposed for semi-automatic tagging of the newly authored learning resource, fostering its reuse in different e-learning contexts. Our approach currently supports resources in English, French, and Spanish. An evaluation of concept identification in lecture video transcripts and a user study based on the quality of tag and resource recommendations yielded promising results concerning the feasibility of our technique. [less ▲]

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See detailTeacher Attitudes towards Ethnic Minority Students: Effects of Schools´ Cultural Diversity
Glock, Sabine UL; Kovacs, Carrie UL; Pit-Ten Cate, Ineke UL

in British Journal of Educational Psychology (2018), online first

Background: Research exploring mechanisms driving inequalities in school systems, has found that biased teacher judgments contribute to observed disadvantages for ethnic minority students. Teacher ... [more ▼]

Background: Research exploring mechanisms driving inequalities in school systems, has found that biased teacher judgments contribute to observed disadvantages for ethnic minority students. Teacher judgments may be driven by explicit and implicit attitudes. Aims: The current research explored the effect of cultural diversity at schools (actual or imagined) on teachers’ attitudes toward ethnic minority students. Samples: One hundred and-five preservice teachers (90 female) with a mean age 26.20 of years (teaching experience: 57.55 weeks) participated in Study 1. Two hundred and thirty-one teachers (159 female) with a mean age of 41.00 years (teaching experience: 12.92 years) participated Study 2. Method: Cultural diversity was operationalized via a fictive description of a school (Study 1) or via the actual proportion of ethnic minority students at the school (Study 2). An Implicit Association Test assessed implicit attitudes toward ethnic minority students. Explicit attitudes were assessed via questionnaire. Results: Preservice teachers imagining a more culturally diverse school held more negative implicit attitudes toward ethnic minority students than those imagining a less diverse school. In contrast, in-service teachers actually working in more diverse schools held less negative implicit attitudes toward minority students. Preservice teachers associated teaching in culturally diverse schools with increased effort, whereas in-service teachers actually working in culturally diverse schools reported more enthusiasm toward teaching ethnic minority students. Conclusions: This research shows the challenge and the negative stereotypes preservice teachers associate with culturally diverse schools, while inservice teachers’ negative associations may be buffered by the actual experience of working with ethnic minority students. [less ▲]

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