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Higher legal standards with regards to the data protection of individu-als such as the General Data Protection Regulation (GDPR) are increasing the pressure on developers of IT artifacts. Typically, when developing systems, we subsequently evaluate them with users to elaborate aspects such as user experi-ence perceptions. However, nowadays, other evaluation aspects such as legality and data policy issues are also important criteria for system development. For this purpose, we introduce LEGIT (legal design science evaluation), which pro-vides developers with guidance when considering legal requirements. We use the case of the GDPR to illustrate the feasibility, applicability, and benefit to the de-velopment process. With this novel method adapted from law research, we are able to derive actionable guidance for developers to evaluate developer efforts in increasing legal compatibility. To illustrate our methodological approach, in this paper, we describe the key steps of the method with respect to the evaluation of a learning assistant. We develop an AI-based learning assistant for university stu-dents to demonstrate the application of the novel evaluation method. We briefly discuss how this procedure can serve as the foundation for a new evaluation method of legally compatible systems in design science research.

One in four consumers is insufficiently physically active, resulting in substantial health risks. Conventional activity tracking apps motivate consumers but can promote motivational crowding-out. Gamification can help overcome these challenges. This paper presents two case studies and introduces a new motivational framework for gamification.

The goal of this paper is to offer a model to quantify the level of complexity of the linguistic content of a corpus in Italian extracted from OpenWHO, WHO’s health emergency learning platform (Rohloff et al. 2018; Zhao et al. 2019). The nature of the computational ranking costs of a typology of relativization strategies is investigated. To reach this goal, the results of the corpus are compared with other three syntactic annotated corpora from Italian belonging to different genres (news, social media, encyclopedic entries, legal). The results show that online learning contents in public health reduce complex structures in syntactic terms. The case study presented here provides a methodology to quantify syntactic and computational complexity in corpus studies.

The success of innovative teaching/learning approaches aiming to foster problem solving in management education depends on useful and easy-to-use IT components in the learning process. However, the complexity of problem solving in self-regulated learning approaches may overwhelm the learner and can lead to unsatisfying learning outcomes. Research suggests the implementation of technology-enhanced scaffolds as a mechanism to guide the learners in their individual problem-solving process to enhance their learning outcomes. We present a theoretical model based on adaptive structuration theory and cognitive load theory that explains how technology-enhanced scaffolding contributes to learning outcomes. We test the model with a fully randomized between-subject experiment in a flipped classroom for management education focusing on individual problem solving. Our results show that technology-enhanced scaffolding contributes significantly to the management of cognitive load as well as to learning process satisfaction and problem-solving learning outcomes. Thereby, our paper provides new conceptual and empirically tested insights for a better understanding of technology-enhanced scaffolds and their design to assist problem solving and its respective effects in flipped classrooms for management education.

The present study focuses on serially occurring narrations of ‘everyday’ life, more specifically on birthing as narrated by mothers on online forums; the underlying idea being that these narrations happen against the background of cultural narratives.The present paper uses word embedding models to detect typical topics and actors in these narrations. The calculation of word embeddings automatically constructs semantic spaces, where semantic relations (synonymy in particular) can be modeled. This method offers a way to think of synonymy as ‘functional equivalence in discourse’.The present study relies on previous work with n-grams (Bubenhofer, 2018). N-grams are sequences of words that often appear together; their sequential order in different narrations gives insight in narrative patterns. A further step in the analysis is the construction of ‘narrative topoi’, which is achieved through clustering neighboring vectors. The emerging clusters can in turn be grouped into five narrative elements of ‘telling a birth story’: 1) disruption of daily life, 2) personnel, 3) body, 4) fear, 5) joy. While it seems obvious that certain themes ‘belong’ into the narration of a delivery, it is less obvious with what vocabulary these themes are expressed.The presented method of clustering word-embedding-profiles adds tremendously to the modelling of a narrative. Its advantages lie in its potential to show lexical variation, as it also includes rare, non-conformative orthographical variants. Furthermore, it allows for a discourse-specific (and usage-based) view on semantic relations. The same applies to relations between semantic clusters. Seen from a discourse linguistics or cultural analysis perspective, word embeddings renew our understanding of semantics. This shows particularly fruitful if used to analyze (discourse dependent) derivations between semantic spaces.

The dynamics of software – and thus also of its development – is an inherent part of the story of how mobilities are made and work. Building on this argument, this ethnographic study explains how navigation software development is caught in a constant culture of acceleration through commercial competition and shifting transport conditions, on the one hand, and a logic of routing and navigation based on creating the fastest route possible for its users, on the other hand. Behind this overall process of technological acceleration lies a multiplicity of forces – sometimes accelerating, but at other times slowing down, stuttering, moving in reverse, or completely coming to a halt in breakdown, shifting the pace of such technological progress. Bringing software development practice into the picture of how mobility systems work (or don’t work) allows us to understand the multiple temporal orders of speeding up and slowing down that push and pull at the fabric of our mobile infrastructures. Doing so will help us counter the popular discourse that our networked, seamless digital technologies are invincible. Based on an ethnography at ‘BerlinTech’, a large commercial navigation software company, this paper provides a multilayered understanding about the temporal forces fuelling our software driven mobility infrastructures.

The globally increasing prevalence and incident rates of mental diseases is one of the most serious public health challenges according to the World Health Organization. Today, treatment is based on professional therapies which require a high amount of financial resources and personnel effort, however IT-supported interventions in ubiquitous devices promise help and a new leverage beyond traditional therapies. We identify the car as a space for new treatments since drivers often have time and the environment in the automobile is highly controlled. In-vehicle information systems can reach people in their daily routine and could introduce innovative prevention measures. In this research in progress paper, we address the open question how the car can improve a driver’s affective state while driving. First, we thoroughly describe the design of a study we conducted to motivate other researchers for this topic. Second, we analyse 631 completed interventions collected in a 2-month field study with 10 drivers. First analyses indicate that we can positively influence the short-term affective state of drivers with at least one of ourintervention types. We provide first practical examples of how to reach the masses of everyday drivers.

The noun phrase (NP), one of the key elements of a sentence, can reveal the characteristics of a learner’s linguistic competence. The present study focuses on actual decomposition of NP in the predicate construction. This is when the attribute elements of a noun phrase are included in the predicate construct as factor-actualized determinants. In this position, the copula verb is merely a grammatical means of allowing the attribute to become a predicate (Gaulmyn, Basset 1991: 177).The aim of the study being a more thorough investigation of the criteria and peculiarities of producing this type of predicate constructs in learner language, the present research is based on the empirical material from the Lithuanian learner corpus. The paper briefly discusses the concept of the predicate construction and describes the process of compiling the learner corpus as well as the principles of data selection. The analysis of the NP in a predicate construction is then presented, and the characteristic cases from the corpus data are examined. The main limitation of the present study is related to the scope of the learner corpus. Having summarized the results of the quantitative and qualitative research, the following conclusions were formulated. The learner language is dominated by NP predicate constructions with an adjective more often than a noun. As to the verb conjunction, the typical attribute verb être ‘to be’ was the only one widely used in the corpus under investigation. The analysis of the corpus data also revealed a number of specific errors that are typical of the learners’ written language. In general, the predictive constructions in the learners’ language are characterized by the omission of redundancy tags in the grammatical categories of gender and number. The analysis of the learner corpus provided a broader look at the NP in a predicate construction, highlighting the simplicity, conciseness and repetition of this construct. The results of the study are important for a more comprehensive description of the learners’ language, for solving problems in foreign language analysis, and for contributing to the quality of teaching and learning the French language.

Although the ODD (One Document Does it all) language is normally used to create TEI customizations or extensions, it is also a highly effective tool for editors working in other XML markup languages. This paper will discuss the use of ODD to define a highly constrained schema for HTML5 that will enforce stylistic rules and encoding practices, define custom attributes and value lists, and enable easier editing and validation of project content in the Oxygen XML Editor environment. I will provide a brief history of the project, whose first incarnation, created with the Dreamweaver HTML editor, was somewhat chaotically coded, and show how the implementation of an ODD-based schema provides huge advantages for authors, editors, and encoders, as well as substantially simplifying the code itself.

Illness management among married adults is mainly shared with their spouses and it involves social support. Social support among couples has been shown to affect emotional well-being positively or negatively and result in healthier habits among diabetes patients. Hence, through automatic emotion recognition, we could have an assessment of the emotional well-being of couples which could inform the development and triggering of interventions to help couples better manage chronic diseases. We are developing an emotion recognition system to recognize the emotions of real couples in everyday life and in this paper, we describe our approach to collecting sensor and self-report emotion data among Swiss-based German-speaking couples in everyday life. We also discuss various aspects of the study such as our novel approach of triggering data collection based on detecting that the partners are close and speaking, the self-reports and multimodal data as well as privacy concerns with our method.

Couples’ relationships affect partners’ mental and physical well-being. Automatic recognition of couples’ emotions will not only help to better understand the interplay of emotions, intimate relationships, and health and well-being, but also provide crucial clinical insights into protective and risk factors of relationships, and can ultimately guide interventions. However, several works developing emotion recognition algorithms use data from actors in artificial dyadic interactions and the algorithms are likely not to perform well on real couples. We are developing emotion recognition methods using data from real couples and, in this paper, we describe two studies we ran in which we collected emotion data from real couples — Dutch-speaking couples in Belgium and German-speaking couples in Switzerland. We discuss our approach to eliciting and capturing emotions and make five recommendations based on their relevance for developing well-performing emotion recognition systems for couples.

In the realm of smart services, smart personal assistants (SPAs) have become a popular medium for value co-creation between service providers and users. The market success of SPAs is largely based on their innovative material properties, such as natural language user interfaces, machine learning-powered request handling and service provision, and anthropomorphism. In different combinations, these properties offer users entirely new ways to intuitively and interactively achieve their goals and thus co-create value with service providers. But how does the nature of the SPA shape value co-creation processes? In this paper, we look through a functional affordances lens to theorize about the effects of different types of SPAs (i.e., with different combinations of material properties) on users’ value co-creation processes. Specifically, we collected SPAs from research and practice by reviewing scientific literature and web resources, developed a taxonomy of SPAs’ material properties, and performed a cluster analysis to group SPAs of a similar nature. We then derived 2 general and 11 cluster-specific propositions on how different material properties of SPAs can yield different affordances for value co-creation. With our work, we point out that smart services require researchers and practitioners to fundamentally rethink value co-creation as well as revise affordances theory to address the dynamic nature of smart technology as a service counterpart.

Crowdfunding is now established as a valid alternative to conventional methods of financing for startups. Unfortunately, to date, research has not investigated how backers can be encouraged to support entrepreneurs beyond funding. The aim of this study is to design and evaluate certain design elements for reward-based crowdfunding platforms that can engage backers in co-creational activities for product development. The study uses a design science research (DSR) approach and the theoretical concept of psychological ownership to inform a new design and then experimentally test that design. The results suggest that the derived artifacts positively influence co-creational activities in crowdfunding and that feelings of psychological ownership play an important mediating role. The contribution of this research is threefold. First, this paper extends crowdfunding’s application potential from merely a method of financing to a method of value creation with customers for product development. Second, the study advances DSR by applying a new DSR approach that shows whether a design performs as hypothesized by theory. Third, this research allows the exploration of backers’ individual behavior as opposed to their collective behavior.

Depression is an affective disorder characterised by psychomotor retardation; in speech, this shows up in reduction of pitch (variation, range), loudness, and tempo, and in voice qualities different from those of typical modal speech. A similar reduction can be observed in sleepy speech (relaxation). In this paper, we employ a small group of acoustic features modelling prosody and spectrum that have been proven successful in the modelling of sleepy speech, enriched with voice quality features, for the modelling of depressed speech within a regression approach. This knowledge-based approach is complemented by and compared with brute-forcing and automatic feature selection. We further discuss gender differences and the contributions of (groups of) features both for the modelling of depression and across depression and sleepiness.

Um den Fachkräftemangel im MINT-Bereich zu bekämpfen, bemühen sich Bund und Kantone, auf allen Bildungsstufen Interesse an Mathematik, Informatik, Naturwissenschaften und Technik zu wecken. Unter anderem soll dabei geschlechtsspezifischen Unterschieden hinsichtlich der Lehrstellen- bzw. Fächerwahl entgegengewirkt werden. Der vorliegende Beitrag setzt hier an und analysiert anhand der Daten der "ÜGK 2016", wie viele Jugendliche am Ende der obligatorischen Schulzeit denken, dass sie im Alter von 30 Jahren einen Beruf im Bereich der MINT-Fachkräfte ausüben werden. Dabei wird deutlich, dass bei jungen Frauen die Unterschätzung ihrer mathematischen Kompetenzen dazu beiträgt, dass sie sich seltener eine berufliche Zukunft im MINT-Bereich vorstellen können als junge Männer. (DIPF/Orig.), Pour lutter contre la pénurie de main-d’oeuvre qualifiée dans le secteur des STIM (sciences, technologies, ingénierie et mathématiques), la Confédération et les cantons s’efforcent de susciter l’intérêt pour les STIM à tous les niveaux de l’enseignement. Cette mesure vise notamment à contrecarrer les différences entre les sexes lors du choix des apprentissages et des matières. Dans ce contexte, nous utilisons les données "ÜGK 2016" pour analyser la part de jeunes en fin de scolarité obligatoire qui pensent avoir un emploi dans le secteur des STIM à l’âge de 30 ans. Les résultats montrent clairement qu’en raison d’une sous-estimation de leurs propres compétences en mathématiques, les jeunes femmes sont moins susceptibles que les jeunes hommes d’imaginer une carrière dans le domaine des STIM. (DIPF/Orig.)

Der Beitrag erörtert die Entwicklung des Video-Streaming-Marktes und die Bedeutung für Öffentliche und wissenschaftliche Bibliotheken. Dabei geht er auch auf die Spezialisierung bestimmter Anbieter ein. Zusammenfassend ist festzuhalten, dass Streaming von AV-Medien vor allem für Öffentliche Bibliotheken ein wertvolles Zusatzangebot für Nutzende darstellt, für wissenschaftliche Bibliotheken hinsichtlich der Dauerhaftigkeit, Zitierfähigkeit und Nachnutzbarkeit von Ressourcen noch wesentliche Fragen ungelöst bleiben. The paper discusses the development of the video streaming market and its importance for public and academic libraries. It also deals with the specialization of certain providers. In summary, it can be said that streaming of AV media is a valuable additional service for users, especially for public libraries, but for academic libraries essential questions regarding the persistence, citation and subsequent use of resources remain unsolved.

This paper discusses a learner-friendly and student-centred approach to introducing Shakespeare for less advanced English language learners in the university-level EFL classroom. Shakespeare becomes welcome material when the input is comprehensible and enjoyable. In this light, the teaching should first start with the story rather than the language. After hooking students by recounting stories from Shakespeare, the teacher needs to familiarise them with the authentic language through activities carefully designed to initiate them into the language. In approaching the content of Shakespeare’s plays, the students are asked to relate themselves to the world of Shakespeare through active methods advanced by the RSC and the world that students already know. Raising language awareness in learners rather than being taught the language, the students become less frustrated while learning to appreciate Shakespeare.

Intelligent systems (IS) have become more popular in the last years resulting into an ethical debate whether Artificial Intelligence (AI) is entirely beneficial or should be seen as a threat. This paper focuses on the antecedent drivers of perceived responsibility suchlike sense of ownership and a marketing manager`s involvement when engaging with IS for their decisions. It lays out the impact and degree of responsibility along with the attribution of blame by comparing the outcome made by a human or a machine. The research is divided in two studies: The first study explores the potential of AI and derives four propositions from technology experts and managers. The second examines whether the recommendation for an action (machine or human) has implications on the perceived responsibility and attribution of blame for a negative decision outcome. The results propose theoretical and practical implications which lead to assumptions to improve the acceptance of AI.

Higher legal standards with regards to data protection of individuals such as EU-GDPR are increasing the pressure on developers of IT artifacts. This is especially prevalent when considering conversational speech agents (CSA) that are collecting data in new ways, and thus, are oftentimes producing conflicts with existing law regulations. For this purpose, we introduce the law simulation method which is a well-known evaluation method among law researchers for capturing legal compatibility of IT artifacts such as CSA. With this rigorous method, we are able to derive actionable guidance for CSA developers to evaluate developer efforts for increasing legal compatibility. To illustrate our methodological approach, we describe in this workshop paper key steps of the method with respect to the evaluation of CSA. We discuss how this can serve as the foundation for a new evaluation method of legally compatible systems in information systems.

Ziel dieses Beitrages ist es, Einsicht in Verarbeitungsprozesse, die bei der Verwendung von kollokationalen Verbindungen in der fremdsprachigen Textproduktion aktiviert werden, zu erhalten. Da Untersuchungen der produktiven Kollokationskompetenz auf der Ebene des Sprachenpaares Kroatisch als L1 und Deutsch als Fremdsprache als L2 bisher nicht systematisch durchgeführt wurden, steht die empirische Analyse des Gebrauchs von Kollokationen in 210 Aufsätzen kroatischer DaF-Lernenden im Mittelpunkt unter Bezugnahme folgender Aspekte: Transfer aus L1 und L2 und Zahl der Kollokationsfehler, Art der Transferfehler und semantische Transparenz der Kollokationen, der sog. Kongruenzeffekt, das Sprachniveau der Lernenden, die Vorkommenshäufigkeit der Kollokationen und ihrer Bestandteile sowie die Wortfeldzugehörigkeit der Kollokationen. Diese möglichen Einflussfaktoren wurden in die Analyse einbezogen, um einen komplexeren Einblick in diese Art exikalischer Kompetenz zu gewinnen, was zu einem besseren Verständnis dieser Problematik führt und somit die Grundlage für praktische Implikationen bietet. Wie die Untersuchungsergebnisse zeigen, überwiegt im analysierten Korpus der normgerechte Gebrauch von denjenigen Kollokationen, die in L1 und L2 übereinstimmen und semantisch transparent sind, während Abweichungen bei divergenten Strukturen zu vermerken sind. Ebenfalls ergeht aus den Ergebnissen, dass mit dem Steigen der Fremdsprachenkompetenz zwar ein wesentlicher Unterschied in der Zahl, nicht jedoch in der Fehlerqoute der verwendeten Kollokationen zu vermerken ist. Dies bestätigt die Notwendigkeit der Förderung der Kollokationskompetenz als integrativem Teil der lexikalischen Kompetenz, wobei der gezielten Schulung von divergierenden Strukturen auf der Ebene eines bestimmten Sprachenpaares im Fremdsprachenunterricht mehr Aufmerksamkeit geschenkt werden sollte., The aim of this paper is to gain insight into the mechanisms activated in L2 produc-tion, with a special focus on the use of collocations in written text production in L2 German. In order to achieve this aim, an empirical analysis of the use of collocations was carried out on a corpus of 210 compositions written by Croatian learners of Ger-man, with respect to the following aspects: L1 to L2 transfer and the number of errors in collocational concordance, the type of transfer and semantic transparency of collo-cations, the so called congruency effect, the level of proficiency in German, the frequency of occurrence of a certain collocation and its constituents, and the semantic field of a certain collocation. The inclusion of these aspects into the analysis enables us to gain a more detailed insight into collocational competence as an integrative part of lexical competence, which in turn contributes to a better understanding of collocatio-nal issues and creates a basis for practical implications. The results of the research show that in the analysed corpus the use of collocations which follow the rules of the standard German language prevails in those collocations that are congruent in L1 and L2 and, at the same time, semantically transparent; the deviations from the standard are seen in incongruent structures. The results also show that with increased profici-ency in L2 the use of collocations increases, but the number of errors, that is, deviations from the standard, does not decrease. This points to the need for develo-ping collocational competence in foreign language teaching, where special attention needs to be given to the acquisition of structures incongruent at the level of L1 and L2.

Short range inductive data transfer has become very popular in the last years with the increased interest in technologies like RFID and NFC. Additionally, wireless power transfer has been a field of intensive research and product development. In industrial applications, a combination of both is often needed to replace mechanical contacts, mainly for safety and reliability reasons, especially regarding spark prevention and maintenance reduction. In this paper, we present a compact inductive structure that can be implemented in an existing wireless energy transfer system. The structure is developed by field considerations, leading to a single structure comprising two signal ports that are decoupled from each other, but can be used to transfer a signal to a second structure of that kind with very small interference. An optimisation to achieve comparable channel characteristics is conducted by using 3-D field simulations. Subsequent measurements are conducted to verify the achieved performance.

Nowadays there are a few tools on the market which support the development of soft competences and build users’ motivation to self-development. One of the newly created tools, which is described in this paper is the Internet application called Integrated Development Assistant (ZAR), which can be accessed at the Internet address: www.zar.edu.pl. The ZAR system differs from the existent solutions because it combines online practices with the face-to-face ones (diagnostic and educational games). It also allows to follow in a flexible way and shape the educational path of an adult, therefore in some areas, it is an innovative tool, offering functions which have not been used in other applications so far and the one integrating various solutions applied in competitive tools. ZAR provides its users with the possibility to use educational contents, development materials, etc. The assumptions of ZAR are based on the concept of real/ideal me by E. T. Higgins.

The paper deals with the impact of the controlling system adjustment on the level of the dynamic loads operating on the hoisting machine parts during the period of the non-steady motion. The impact of the operating regime of the hoisting machine generalized mechanism on the consistency of operation and the variation of the parameters of the mechanism controlling system with the electric drive and frequency converter is experimentally shown. The procedure of the experiment is described; there are given the comparative results of the variation of the mechanism performance when it works using the controlling system with the frequency converter and brake resistor, and without it, when working on the natural parameters. There are conclusions about adequacy of the normative method for the dynamic coefficient option, determining the loading of the hoisting machine metalware, and in case of occurrence of adjustment errors in the frequency converter controlling system.

The paper concerns the analysis of the building of Cricoteka in terms of theatricality, which is the role of architecture in the performance of city life. It discusses such aspects as the transfer of the idea of theatre onto architectural form, the dialogue with the viewer, the place of the building in the city and the influence of the object on the environment by generating tension between individual elements of composition solids. Theatrical dimension of architecture might be understood as a spectacle, invented and robust physiognomy, but also intriguing visual appeal. Through the versatile architectural costumes the architecture puts on, especially contemporary architecture, which stands out from the other buildings, tends to be incomprehensible to its recipients. Aiding the comprehension of the message, as well as its conscious shaping by the authors, is key to mutual understanding and establishing the dialogue. The detailed analysis of the building’s interior, which is the key aim of a project of Cricoteka, remains out of scope of this work.

The global Digital Elevation Model (DEM) resulting from the TanDEM-X mission provides information about the world topography with outstanding precision. In fact, performance analysis carried out with the already available data have shown that the global product is well within the requirements of 10 m absolute vertical accuracy and 2 m relative vertical accuracy for flat to moderate terrain. The mission's science phase took place from October 2014 to December 2015. During this phase, bistatic acquisitions with across-track separation between the two satellites up to 3.6 km at the equator were commanded. Since the relative vertical accuracy of InSAR derived elevation models is, in principle, inversely proportional to the system baseline, the TanDEM-X science phase opened the doors for the generation of elevation models with improved quality with respect to the standard product. However, the interferometric processing of the large-baseline data is troublesome due to the increased volume decorrelation and very high frequency of the phase variations. Hence, in order to fully profit from the increased baseline, sophisticated algorithms for the interferometric processing, and, in particular, for the phase unwrapping have to be considered. This paper proposes a novel dual-baseline region-growing framework for the phase unwrapping of the large-baseline interferograms. Results from two experiments with data from the TanDEM-X science phase are discussed, corroborating the expected increased level of detail of the large-baseline DEMs.

This paper presents a comparison of technology delivery bulk cargo. The subject of study is the structure of the tech-nology delivery bulk cargo. The aim of the study is to improve the technological scheme of delivery of cargo in the supply chain. Methods based on the analysis and synthesis of existing methods of collecting baseline information, methods of processing it in a substantiation of the choice of the most efficient transportation technologies.

In this paper the mathematical models of the main types of turning hydraulic engines, which at the present time widely used in the construction of handling systems of domestic and foreign mobile transport-technological machines wide functionality. They allow to take into consideration the most significant from the viewpoint of ensuring high technical-economic indicators of hydraulic efficiency criteria – minimum mass (weight), their volume and losses of power. On the basis of these mathematical models the problem of multicriterial constrained optimization of the constructive sizes of turning hydraulic engines are subject to complex constructive, strength and deformation limits. It allows you to develop the hydraulic engines in an optimized design which is required for the purpose of designing a comprehensive measure takes into account efficiency criteria. The multicriterial optimization problem is universal in nature, so when designing a turning hydraulic engines allows for one-, two - and three-criteria optimization without making any changes in the solution algorithm. This is a significant advantage for the development of universal software for the automation of design of mobile transport-technological machines.

Although Swiss dialects of German are widely used in everyday communication, automatic processing of Swiss German is still a considerable challenge due to the fact that it is mostly a spoken variety and that it is subject to considerable regional variation. This paper presents the ArchiMob corpus, a freely available general-purpose corpus of transcribed spoken Swiss German based on oral history interviews. The corpus is a result of a long design process, intensive manual work and specially adapted computational processing. We first present the modalities of access of the corpus for dialectological, historical and computational research. We then describe how the documents were transcribed, segmented and aligned with the sound source, and summarise a series of experiments that have led to automatically annotated normalisation and part-of-speech tagging layers. Finally, we present several case studies to stimulate the use of the corpus for dialectological research.

Big data is a field of investigation rich in promises but still complex in renewing spatial mobility analysis. In fact, thinking about mobility through the prism of digital footprints raises many questions regarding the data nature, the accessibility procedures and the methods and techniques of treatment. This paper aims to explore the potential of digital footprints in the analysis of mobility through the example of data from the Carpooling platform BlaBlaCar. By analyzing (temporal and spatial) trips to and from city of Rennes over the course of 5 months, the goal is both to draw a portrait of Carpooling in the capital of Britanny and to give an overview of advantages and limitations of these data in understanding this new form of mobility.Key-words : exploratory data analysis (eda), spatial analysis, data, mobility, GIS

This paper aims to analyse the intermodal practices of mobility in the bus-metro network of Rennes metropole. Intermodality being strongly linked to the use of urban public transport networks, the Rennes Metropole bus and metro network data provided by Keolis-Rennes provides a very significant part of daily intermodality. To compensate for the lack of information on destinations and correspondances in the ticketing data a reconstruction of trips was made on the basis of hypotheses provided by the literature. The research carried out in the "Mobilletic" project considerably deepened the understanding of the temporal and spatial dimensions of intermodal mobility within Rennes Metropole’s urban public transport network.daily mobility, public transport, data science, data analysis, intermodal transportation

The aim of this paper is to present a pilot study which applies the framework of Corpus Pattern Analysis (CPA, Hanks 2004) to analyse some Lithuanian verbs which form part of the basic vocabulary. CPA draws on the insights of the corpus-driven language analysis and contextual and functional theory of meaning: a meaning of a word is associated with a specific lexical and grammatical environment, e.g. corpus patterns which represent an interconnection of lexical and grammatical elements. The CPA procedure is one of the several corpus-driven methods differing from the pattern grammar (Hunston, Francis 2000) in the way that CPA not only uses typical grammatical categories (e.g. word classes) but also introduces semantic values (e.g. semantic types) to distinguish different senses of a word. Semantic types are often the main separator of meanings, especially when two verb senses are associated with the same grammatical pattern. Concerning learners’ dictionaries, CPA could provide learners with more detailed usage data, and this could lead to a better understanding of meaning differences, important both for language reception and language production. After introducing the CPA methodology, we present the CPA analysis of two Lithuanian verbs, namely, the inductive procedure followed to observe and define meaning-related patterning. We also discuss the problematic issues related to the application of CPA as identified in this study and mentioned by other CPA practitioners. First, observing and defining corpus patterns is a challenging task for lexicographers, especially because of the pattern / meaning division and generalizations related to semantic types. The second problematic aspect is automatization in the process of pattern recognition. The third issue relates to foreign language learners as a target group: meaning-related patterning observed in the data has to be presented in a learner dictionary in a user-friendly way.

Despite efforts to reduce them, traffic accidents continue to increase and bypass reduction targets. The costs of traffic accidents are enormous, killing 1.35 million people every year and costing 3% of most countries’ GDP. Recent research aims to target interventions at high-accident-density locations, called accident hotspots. New methods and technologies can systematically identify hotspots, but it remains unclear whether hotspots contribute to accident costs as well as volume. This paper investigates the monetary and human costs of accident hotspots. We analyze a dataset of all accidents from 2011 - 2017 in Switzerland. We identify hotspots, then analyze their contributions to traffic accident costs. We find that hotspot accidents are not different in monetary costliness or injury rates from non-hotspot accidents, so hotspots drive costs along with accident volume. However, hotspot accidents are less fatal, so hotspot targeting might not be best for fatalities. If hotspots are reduced to normal road conditions, total monetary costs can be reduced by up to 5% per year as a theoretical upper bound. Targeting the top 10% most frequent, costly, injurious, or deadly hotspots yeilds different results for different cost types, with accident number and monetary cost targets creating the highest reductions overall.

Requirements Engineering (RE) has been aiding software-intensive development projects for quite some time now. However, today’s projects growingly demand for agile and human-centered approaches to discover and meet the often fuzzy needs of the various stakeholders involved. In that regard, Design Thinking (DT) has become one of the most promising methods to address complex problems and define innovative solutions. We see potential to combine both, the strongly human-oriented working mode of DT with the more formal, technology-driven world of RE, to develop human-centered solutions more effectively. Yet, little is known how such an integration could be realized and which concrete benefits and challenges to expect. To better understand this endeavor, we conduct a longitudinal case study to identify how DT and RE can work together in an agile development setting from the very beginning of idea conceptualization to market-ready implementation. In this paper, we summarize our research protocol and present first findings how Design Thinking can complement current RE practices through meeting known challenges encountered by the RE community of practitioners. We provide a better understanding of the multi-faceted potential of DT for RE for both, scholars and practitioners, and describe open issues and planned future steps in our study.

Character animation tools are based on a keyframing metaphor where artists pose characters at selected keyframes and the software automatically interpolates the frames inbetween. Although the quality of the interpolation is critical for achieving a fluid and engaging animation, the tools available to adjust the result of the automatic inbetweening are rudimentary and typically require manual editing of spline parameters. As a result, artists spend a tremendous amount of time posing and setting more keyframes. In this pose-centric workflow, animators use combinations of forward and inverse kinematics. While forward kinematics leads to intuitive interpolations, it does not naturally support positional constraints such as fixed contact points. Inverse kinematics can be used to fix certain points in space at keyframes, but can lead to inferior interpolations, is slow to compute, and does not allow for positional contraints at non-keyframe frames. In this paper, we address these problems by formulating the control of interpolations with positional constraints over time as a space-time optimization problem in the tangent space of the animation curves driving the controls. Our method has the key properties that it (1) allows the manipulation of positions and orientations over time, extending inverse kinematics, (2) does not add new keyframes that might conflict with an artist's preferred keyframe style, and (3) works in the space of artist editable animation curves and hence integrates seamlessly with current pipelines. We demonstrate the utility of the technique in practice via various examples and use cases.

The fusion of complementary information from co-registered multi-modal image data enables a more detailed and more robust understanding of an image scene or specific objects, and is important for several applications in the field of remote sensing. In this paper, the benefits of combining RGB, near infrared (NIR) and thermal infrared (TIR) aerial images for the task of semantic vehicle segmentation through deep neural networks are investigated. Therefore, RGB, NIR and TIR image triplets acquired by the Modular Aerial Camera System (MACS) are precisely co-registered through the application of a virtual camera system and subsequently used for the training of different neural network architectures. Various experiments were conducted to investigate the influence of the different sensor characteristics and an early or late fusion within the network on the quality of the segmentation results.

Model-Based Systems Engineering (MBSE) is gaining popularity in organizations creating complex systems where it is crucial to collaborate in a multi-disciplinary environment. SysML, being one of the key MBSE components, has a good foundation for capturing requirements, architecture, constraints, views and viewpoints. However, SysML does not provide the necessary constructs to capture safety and reliability information in the system model. A group of industry experts at the OMG has been working since 2016 to define a new specification providing the necessary capabilities. This paper provides an update on the progress of this work. It discusses the proposed specification’s use of generic concepts to allow information interchange amongst diverse analyses, its use of existing SysML constructs to provide automation of safety and reliability work in existing modelling tools, and describes several of the supported analysis methods.

The automatic matching of corresponding regions in remote sensing imagery acquired by synthetic aperture radar (SAR) and optical sensors is a crucial pre-requesite for many data fusion endeavours such as target recognition, image registration, or 3D-reconstruction by stereogrammetry. Driven by the success of deep learning in conventional optical image matching, we have carried out extensive research with regard to deep matching for SAR-optical multi-sensor image pairs in the recent past. In this paper, we summarize the achieved findings, including different concepts based on (pseudo-)siamese convolutional neural network architectures, hard negative mining, alternative formulations of the underlying loss function, and creation of artificial images by generative adversarial networks. Based on data from state-of-the-art remote sensing missions such as TerraSAR-X, Prism, Worldview-2, and Sentinel-1/2, we show what is already possible today, while highlighting challenges to be tackled by future research endeavors.

This paper presents a motion intention estimation algorithm that is based on the recordings of joint torques, joint positions, electromyography, eye tracking and contextual information. It is intended to be used to support a virtual-reality-based robotic arm rehabilitation training. The algorithm first detects the onset of a reachingmotion using joint torques and electromyography. It thenpredicts the motion target using a combination of eyetracking and context, and activates robotic assistance to-ward the target. The algorithm was first validated offlinewith 12 healthy subjects, then in a real-time robot controlsetting with 3 healthy subjects. In offline crossvalidation,onset was detected using torques and electromyography116msprior to detectable changes in joint positions. Fur-thermore, it was possible to successfully predict a majorityof motion targets, with the accuracy increasing over thecourse of the motion. Results were slightly worse in onlinevalidation, but nonetheless show great potential for real-time use with stroke patients., at - Automatisierungstechnik, 63 (4), ISSN:0178-2312, ISSN:2196-677X

Building semantic segmentation is a crucial task for building information modeling (BIM). Current research generally exploits terrestrial image data, which provides only limited view of a building. By contrast, oblique imagery acquired by unmanned aerial vehicle (UAV) can provide richer information of both the building and its surroundings at a larger scale. In this paper, we present a novel pipeline for building semantic segmentation from oblique UAV images using a fully convolutional neural network (FCN). To cope with the lack of UAV image annotations at facade level, we leverage existing ground-view facades databases to simulate various aerial-view images based on estimated homography, yielding abundant synthetic aerial image annotations as training data. The FCN is trained end-to-end and tested on full-tile UAV images. Experiments demonstrate that the incorporation of simulated views can significantly boost the prediction accuracy of the network on UAV images and achieve reasonable segmentation performance.

The design of future low-noise aircraft will require an account of noise shielding as a fundamental design parameter. This aspect was already recognized in the 70s, where early experimental work set the ground on possible solutions to the conventional, short and reduced take-off and landing noise problem. The current low-noise aircraft design concepts of the hybrid-wing-body type require establishing a new knowledge base to allow an assessment of their potential noise benefit. Experimental work done in the course of the last 15 years slowly moved in this direction with the establishment of new testing methodologies. Currently available databases render an estimation of the turbomachinery noise shielding benefit of specific design choices on aircraft of the hybrid-wing-body type possible. Still, research in this domain would strongly benefit from the development of reliable and flexible numerical prediction methods. Recent experimental results obtained using a broadband non-intrusive laser-based sound source are presented. The methodology is used to conduct experiments on a wide range of configurations, providing an extensive high-quality validation database. The paper presents an overview of available datasets of dedicated experimental investigations, ranging from simple generic test cases to full 3D aircraft configurations, as well as comparisons with numerical results.

When using digital technologies, various data traces are left behind for collection, storage and analysis. Innovative solutions for information systems are needed that mitigate privacy risks and foster information privacy. One mechanism to achieve this are privacy nudges. Nudges are a concept from behavioural economics to influence individual’s decisions. This paper focusses on building an integrative understanding of privacy nudging. Specifically, we conceptualize the constituting characteristics of privacy nudges by conducting a systematic literature review to cover the current state of knowledge in the interdisciplinary privacy nudge literature stream. We structure the intrapersonal factors that determine effectiveness for each privacy nudge in a morphological box and conceptualize on this basis current research coverage as well as demand for future research. Finally, we develop theoretical propositions contributing to the discussion of how to study and design effective privacy nudges that can pave the way for more privacy sensitive IT systems.

Collaboration Engineering (CE) is an approach for the design and deployment of repeatable collaborative work practices that can be executed by practitioners themselves without the ongoing support of external collaboration professionals. A key design activity in CE concerns modeling current and future collaborative work practices. CE researchers and practitioners have used the Facilitation Process Model (FPM) technique. However, this modeling technique suffers from a number of shortcomings to model contemporary collaborative work practices. We use a design science approach to identify the main challenges with the original FPM technique, derive requirements and design a revised modeling technique that is based on the current technique enriched by BPMN 2.0 elements. This paper contributes to the CE literature by offering a revised FPM technique that assists CE-designers to capture new forms of collaborative work practices.

The use of active inceptor systems allows for control of the aircraft even during mechanical failures within the control inceptor. For the specific case of isometric failure, whereby the inceptor ‘freezes’ in position, a virtual force-displacement model is used to continue to provide control input. Experimental flight tests using the German Aerospace Center’s (DLR) research helicopter (ACT/FHS) has shown the potential to encounter pilot-induced oscillation (PIO) tendencies when flying using this mode. This paper presents results from a simulation campaign undertaken to confirm whether PIOs may be exposed through this use of control and/or the resultant severity. The results show that the isometric failure mode caused severe PIOs. Unacceptable failure characteristics were reported by all four pilots. The use of offline prediction tools showed the incipience of PIO. It is recommended that specific PIO investigations are undertaken during > the evaluation of active inceptor failure modes.

The digital age has yielded systems that increasingly reduce the complexity of our everyday lives. As such, smart personal assistants such as Amazon’s Alexa or Apple’s Siri combine the comfort of intuitive natural language interaction with the utility of personalized and situation-dependent information and service provision. However, research on SPAs is becoming increasingly complex and opaque. To reduce complexity, this paper introduces a classification system for SPAs. Based on a systematic literature review, a cluster analysis reveals five SPA archetypes: Adaptive Voice (Vision) Assistants, Chatbot Assistants, Embodied Virtual Assistants, Passive Pervasive Assistants, and Natural Conversation Assistants.

Low complexity decoding algorithms are necessary to meet data rate requirements in excess of 1 Tbps. In this paper, we study one and two bit message passing algorithms for belief propagation decoding of low-density parity-check (LDPC) codes and analyze them by density evolution. The variable nodes (VNs) exploit soft information from the channel output. To decrease the data flow, the messages exchanged between check nodes (CNs) and VNs are represented by one or two bits. The newly proposed quaternary message passing (QMP) algorithm is compared asymptotically and in finite length simulations to binary message passing (BMP) and ternary message passing (TMP) for spectrally efficient communication with higher-order modulation and probabilistic amplitude shaping (PAS). To showcase the potential for high throughput forward error correction, spatially coupled LDPC codes and a target spectral efficiency (SE) of 3 bits/QAM symbol are considered. Gains of about 0.7 dB and 0.1 dB are observed compared to BMP and TMP, respectively. The gap to unquantized belief propagation (BP) decoding is reduced to about 0.75 dB. For smaller code rates, the gain of QMP compared to TMP is more pronounced and amounts to 0.24 dB in the considered example., Accepted for IEEE/OSA Journal on Lightwave Technology

This paper presents a system calibration method for a trifocal sensor, which is sensitive to different spectral bands. The trifocal camera system consists of a stereo camera, operating in the visual (VIS) spectrum and a thermal imaging camera, operating in the Long-Wave- Infrared (LWIR) spectrum. Intrinsic parameters and spatial alignment are determined simultaneously. As calibration target a passive aluminium chessboard is used. Corner detection and subsequent bundle adjustment is done on all synchronized image triplets. The remaining reprojection errors are in the sub-pixel range and enable the system to generate metric point clouds, colored with thermal intensities in real-time.

This paper sheds light on the possibilities and perspectives of linking digital editions of Medieval German texts to each other and to other digital resources. Furthermore, it discusses some of the internal and technical conditions necessary to render this linkage meaningful, like lemmatisation, part-of-speech-tagging, and using standardised mark-up languages. Finally, the sustainability and reusability of digital editions are considered. While in the past, editions of medieval texts were conceived as rather isolated scholarly works of individual editors, nowadays the collaboration and cooperation of greater working groups is essential in editing projects. Due to the complexity of editions consisting of multiple textual layers, e. g. apparatus entries, annotations, or facsimiles, the requirements for future digital editions have risen. The first approach to respond to these demands is to link the various textual layers to each other, enabling the users to navigate between these layers in a sensible way. The second step is to link the edited text to other resources, such as online dictionaries or other editions, allowing complex research networks to be created. These goals are achieved by lemmatising and other tagging methods, ensuring the information being mapped to a normalised and idealised frame of reference. Common standards like Unicode or the TEI guidelines are of great importance for such purposes, as they assure the interchange and re-use of scientific data, as well as their sustainability.