@article{34822, abstract = {{The role of domain-specific content knowledge is discussed controversially for the early childhood context. Therefore, this review aims at untangling the research on domain-specific content knowledge for early childhood educators by systematically reviewing the conceptual and operational definition of and results on early childhood educators' content knowledge in different domains. Using the scientific databases ERIC, PsycInfo and Web of Sciences, we identified 36 studies on early childhood educators' domain-specific content knowledge. By comparing these studies, we found that conceptualizations of early childhood educators' content knowledge move on a continuum between a scientific related perspective and a practice related perspective. The scientific related perspective defines content knowledge as the knowledge of key concepts, facts and rules of the domain integrating knowledge taught in primary, secondary or upper secondary school. The practice related perspective includes knowledge of key concepts, facts and rules of the domain limited to the knowledge explicitly relevant for teaching in early childhood education as well as selected domain-specific knowledge of children and teaching. Our review shows that the results and implications drawn by the study authors depend on how these authors conceptualize early childhood educators' content knowledge on this continuum. Further research, therefore, needs to consider carefully how early childhood educators' content knowledge is conceptualized. The paper further discusses gaps in this research field, such as validating methods for measuring early childhood educators' content knowledge or implementing more rigorous experimental designs to examine effects of early childhood educators' content knowledge.}}, author = {{Bruns, Julia and Gasteiger, Hedwig and Strahl, Carolin}}, issn = {{2049-6613}}, journal = {{Review of Education}}, keywords = {{content knowledge, domain-specific learning, early childhood education, teacher knowledge}}, number = {{2}}, pages = {{500--538}}, publisher = {{Wiley}}, title = {{{Conceptualising and measuring domain-specific content knowledge of early childhood educators: A systematic review}}}, doi = {{10.1002/rev3.3255}}, volume = {{9}}, year = {{2021}}, } @inproceedings{27491, abstract = {{ Students often have a lack of understanding and awareness of where, how, and why personal data about them is collected and processed. Especially, when interacting with data-driven digital artifacts, an appropriate perception of the data collection and processing is necessary for self-determination. This dissertation deals with the development and evaluation of a concept called data awareness which aims to foster students’ self-determination interacting with data-driven digital artifacts.}}, author = {{Höper, Lukas}}, booktitle = {{21st Koli Calling International Conference on Computing Education Research}}, isbn = {{9781450384889}}, keywords = {{data awareness, machine learning, data science education, data-driven digital artifacts, artificial intelligence}}, publisher = {{Association for Computing Machinery}}, title = {{{Developing and Evaluating the Concept Data Awareness for K12 Computing Education}}}, doi = {{10.1145/3488042.3490509}}, year = {{2021}}, } @inbook{22930, abstract = {{Self-piercing riveting is an established technique for joining multi-material structures in car body manufacturing. Rivets for self-piercing riveting differ in their geometry, the material used, the condition of the material and their surface condition. To shorten the manufacturing process by omitting the heat treatment and the coating process, the authors have elaborated a concept for the use of stainless steel with high strain hardening as a rivet material. The focus of the present investigation is on the evaluation of the influences of the rivet’s geometry and material on its deformation behaviour. Conventional rivets of types P and HD2, a rivet with an improved geometry made of treatable steel 38B2, and rivets made of the stainless steels 1.3815 and 1.4541 are examined. The analysis is conducted by means of multi-step joining tests for two material combinations comprising high-strength steel HCT70X and aluminium EN AW-5083. The joints are cut to provide a cross-section and the deformation behaviour of the different rivets is analysed on the basis of the measured changes in geometry and hardness. In parallel, an examination of the force-stroke curves provides further insights. It can be demonstrated that, besides the geometry, the material strength, in particular, has a significant influence on the deformation behaviour of the rivet. The strength of steel 1.4541 is seen to be too low for the joining task, while the strength of steel 1.3815 is sufficient, and hence the investigation confirms the capability of rivets made of 1.3815 for joining even challenging material combinations.}}, author = {{Uhe, Benedikt and Kuball, Clara-Maria and Merklein, Marion and Meschut, Gerson}}, booktitle = {{Forming the Future - Proceedings of the 13th International Conference on the Technology of Plasticity. The Minerals, Metals & Materials Series.}}, editor = {{Daehn, Glenn and Cao, Jian and Kinsey, Brad and Tekkaya, Erman and Vivek, Anupam and Yoshida, Yoshinori}}, keywords = {{Self-piercing riveting, Lightweight design, Deformation behaviour, Stainless steel, High nitrogen steel}}, pages = {{1495--1506}}, publisher = {{Springer}}, title = {{{Self-Piercing Riveting Using Rivets Made of Stainless Steel with High Strain Hardening}}}, doi = {{10.1007/978-3-030-75381-8_124}}, year = {{2021}}, } @inproceedings{22274, abstract = {{The use of high-strength steel and aluminium is rising due to the intensified efforts being made in lightweight design, and self-piercing riveting is becoming increasingly important. Conventional rivets for self-piercing riveting differ in their geometry, the material used, the condition of the material and the coating. To shorten the manufacturing process, the use of stainless steel with high strain hardening as the rivet material represents a promising approach. This allows the coating of the rivets to be omitted due to the corrosion resistance of the material and, since the strength of the stainless steel is achieved by cold forming, heat treatment is no longer required. In addition, it is possible to adjust the local strength within the rivet. Because of that, the authors have elaborated a concept for using high nitrogen steel 1.3815 as the rivet material. The present investigation focusses on the joint strength in order to evaluate the capability of rivets in high nitrogen steel by comparison to conventional rivets made of treatable steel. Due to certain challenges in the forming process of the high nitrogen steel rivets, deviations result from the targeted rivet geometry. Mainly these deviations cause a lower joint strength with these rivets, which is, however, adequate. All in all, the capability of the new rivet is proven by the results of this investigation. }}, author = {{Uhe, Benedikt and Kuball, Clara-Maria and Merklein, Marion and Meschut, Gerson}}, keywords = {{Self-piercing Riveting, Joining Technology, Rivet Geometry, Rivet Material, High Nitrogen Steel, Joint Strength}}, location = {{Liège, Belgien}}, title = {{{Strength of self-piercing riveted Joints with conventional Rivets and Rivets made of High Nitrogen Steel}}}, doi = {{10.25518/esaform21.1911}}, year = {{2021}}, } @inbook{57884, abstract = {{Although music apps are becoming increasingly popular, there has been little research on informal music practices with apps. This article presents findings of an ongoing study on learning processes and aesthetic experiences with informal appmusic practices. In particular, it discusses the aesthetic practices (Reckwitz, 2008b) of using specific places for making music. In our grounded theory study (Charmaz, 2014) we collected data using interviews, participant observation and videography. As exemplary cases, this article presents two analyses of the use of ‘inspiring places’ and ‘safe places’. The results suggest that perceiving the atmosphere is a fundamental prerequisite for both places. Additionally, the results shed light on aesthetic aspects of mobile music making. (DIPF/Orig.)}}, author = {{Eusterbrock, Linus and Godau, Marc and Haenisch, Matthias and Krebs, Matthias and Rolle, Christian}}, booktitle = {{Musikpädagogik im Spannungsfeld von Reflexion und Intervention}}, editor = {{Hasselhorn, Johannes and Kautny, Oliver and Platz, Friedrich}}, keywords = {{Education, Ästhetik, Schul- und Bildungswesen, Informal learning, Informelles Lernen, Musical education, Musikpädagogik, Anwendung, Ästhetische Erfahrung, Grounded Theory, Längsschnittuntersuchung, Learning process, Lernprozess, Longitudinal analysis, Longitudinal study, Mobiles Gerät, Music reading, Musizieren, Erziehung}}, pages = {{155–172}}, publisher = {{Waxmann}}, title = {{{Von ’inspirierenden Orten’ und ’Safe Places’. Die ästhetische Nutzung von Orten in der Appmusikpraxis}}}, volume = {{41}}, year = {{2021}}, } @article{32558, abstract = {{With the rapid progress of technological development, self-efficacy in reference to digital devices (i.e., information and computer technology [ICT] self-efficacy) is an important driver that helps students to deal with technological problems and support their lifelong learning processes. Schools, peers, and home learning environments are important sources for the development of positive self-efficacy. Expanding on previous research, we investigated the associations between different aspects of the digital home learning environment and students’ ICT self-efficacy. The moderation effects of gender were also tested. A total of 651 children answered a questionnaire about different digital home learning environment dimensions and estimated their ICT self-efficacy using an adapted scale—Schwarzer and Jerusalem’s (1999) general self-efficacy scale. Using the structural equation modeling technique, a digital home learning environment containing six different qualities of parental support was investigated. Families’ cultural capital, parents’ attitudes toward the Internet, and shared Internet activities at home contributed positively to ICT self-efficacy. We observed small gender differences, with the moderation effect being nonsignificant. The results help researchers and practitioners to understand how different dimensions of the digital home learning environment support ICT self-efficacy. We will discuss how parents can enhance the home learning environment and how teachers can integrate this knowledge into formal education.}}, author = {{Bonanati, Sabrina and Buhl, Heike M.}}, issn = {{1387-1579}}, journal = {{Learning Environments Research}}, keywords = {{Digital media use, Gender, Home learning environment, ICT self-efcacy, Motivation, Parental involvement}}, number = {{2}}, pages = {{485--505}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{The digital home learning environment and its relation to children’s ICT self-efficacy}}}, doi = {{10.1007/s10984-021-09377-8}}, volume = {{25}}, year = {{2021}}, } @inproceedings{19609, abstract = {{Modern services comprise interconnected components, e.g., microservices in a service mesh, that can scale and run on multiple nodes across the network on demand. To process incoming traffic, service components have to be instantiated and traffic assigned to these instances, taking capacities and changing demands into account. This challenge is usually solved with custom approaches designed by experts. While this typically works well for the considered scenario, the models often rely on unrealistic assumptions or on knowledge that is not available in practice (e.g., a priori knowledge). We propose a novel deep reinforcement learning approach that learns how to best coordinate services and is geared towards realistic assumptions. It interacts with the network and relies on available, possibly delayed monitoring information. Rather than defining a complex model or an algorithm how to achieve an objective, our model-free approach adapts to various objectives and traffic patterns. An agent is trained offline without expert knowledge and then applied online with minimal overhead. Compared to a state-of-the-art heuristic, it significantly improves flow throughput and overall network utility on real-world network topologies and traffic traces. It also learns to optimize different objectives, generalizes to scenarios with unseen, stochastic traffic patterns, and scales to large real-world networks.}}, author = {{Schneider, Stefan Balthasar and Manzoor, Adnan and Qarawlus, Haydar and Schellenberg, Rafael and Karl, Holger and Khalili, Ramin and Hecker, Artur}}, booktitle = {{IEEE International Conference on Network and Service Management (CNSM)}}, keywords = {{self-driving networks, self-learning, network coordination, service coordination, reinforcement learning, deep learning, nfv}}, publisher = {{IEEE}}, title = {{{Self-Driving Network and Service Coordination Using Deep Reinforcement Learning}}}, year = {{2020}}, } @inproceedings{18686, author = {{Kersting, Joschka and Bäumer, Frederik Simon}}, booktitle = {{PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020}}, keywords = {{Software Requirements, Natural Language Processing, Transfer Learning, On-The-Fly Computing}}, location = {{Lisbon, Portugal}}, pages = {{119----123}}, publisher = {{IADIS}}, title = {{{SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH}}}, year = {{2020}}, } @inproceedings{15580, abstract = {{This paper deals with aspect phrase extraction and classification in sentiment analysis. We summarize current approaches and datasets from the domain of aspect-based sentiment analysis. This domain detects sentiments expressed for individual aspects in unstructured text data. So far, mainly commercial user reviews for products or services such as restaurants were investigated. We here present our dataset consisting of German physician reviews, a sensitive and linguistically complex field. Furthermore, we describe the annotation process of a dataset for supervised learning with neural networks. Moreover, we introduce our model for extracting and classifying aspect phrases in one step, which obtains an F1-score of 80%. By applying it to a more complex domain, our approach and results outperform previous approaches.}}, author = {{Kersting, Joschka and Geierhos, Michaela}}, booktitle = {{Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) -- Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020)}}, keywords = {{Deep Learning, Natural Language Processing, Aspect-based Sentiment Analysis}}, location = {{Valetta, Malta}}, pages = {{391----400}}, publisher = {{SCITEPRESS}}, title = {{{Aspect Phrase Extraction in Sentiment Analysis with Deep Learning}}}, year = {{2020}}, } @article{20143, author = {{Otroshi, Mortaza and Rossel, Moritz and Meschut, Gerson}}, journal = {{Journal of Advanced Joining Processes}}, keywords = {{Self-pierce riveting, Ductile fracture, Damage modeling, GISSMO damage model}}, publisher = {{Elsevier}}, title = {{{Stress state dependent damage modeling of self-pierce riveting process simulation using GISSMO damage model}}}, doi = {{10.1016/j.jajp.2020.100015}}, volume = {{1}}, year = {{2020}}, } @article{35313, abstract = {{The article discusses the explanatory power of conceptual change for research on workplace learning in digitalized workplaces. Interestingly, research on conceptual change is well-established within the area of science education but widely neglected within the broad area of workplace learning research. Digitalization of work establishes new quality of tasks and tools by integrating workers and machines into digital networks. Hence, conceptual change can be considered a core concept for identifying workers’ successful adaption to digital transformation. Therefore, conceptual change research in the area of workplace learning in digitalized workplaces is highly relevant. The article reflects upon reasons, explores the potential of conceptual change for understanding workplace learning in digitalized workplaces, and illustrates the argumentation by exemplarily referring to digitalized farming. Finally, the article provides suggestions for future research.}}, author = {{Harteis, Christian and Goller, Michael and Caruso, Carina}}, journal = {{Frontiers in Education}}, keywords = {{conceptual change, digitalization, workplace learning, professional development, agriculture}}, number = {{1}}, title = {{{Conceptual Change in the Face of Digitalization}}}, doi = {{10.3389/feduc.2020.00001}}, volume = {{5}}, year = {{2020}}, } @article{35298, abstract = {{Im Artikel werden drei verschiedene Lernzugänge (kom-petenzorientiertes, ästhetisches und biographisches Lernen) vorgestellt und aus theoretischer Perspektive deren motivierender Gehalt für selbstreguliertes Lernen in Praxisphasen des Lehramtsstudiumsherausgearbeitet. Als theoretische Grund-lage dient die Selbstbestimmungstheorie als zentrale motivationale Theorie zur Erklärung selbstbestimmten Handelns.}}, author = {{Caruso, Carina and Adammek, Christine and Bonanati, Sabrina and Wiescholek, Sybille}}, issn = {{2625-0675}}, journal = {{Herausforderung Lehrer*innenbildung - Zeitschrift Zur Konzeption, Gestaltung Und Diskussion}}, keywords = {{ästhetische Forschung, Biographiearbeit, Praxissemester, Professionalisierung, selbstreguliertes Lernen, Motivation / aesthetic research, biographical work, long-term internship, profes-sionalization, self-regulated learning, motivation}}, number = {{1}}, pages = {{18--33}}, title = {{{Motivierende Lernzugänge als Ausgangspunkt der Professionalisierung angehender Lehrer_innen}}}, doi = {{10.4119/hlz-2540}}, volume = {{3}}, year = {{2020}}, } @article{33299, abstract = {{The aim of this study was to find out whether teaching how to search for literature would be more beneficial to students and teachers if done online through short videos rather than in person during course time. To find out whether online videos are more beneficial, two courses were asked to fill in questionnaires, one at the beginning and one at the end of the semester. One of the courses received the input online via videos and were given an exercise to put the newly learned skills to use, the other course served as a control group and learned how to search for literature during the course. The results show that while the difference between the two groups is not significant, the videos can still be regarded as being more beneficial than teaching the necessary skills during course time.}}, author = {{Hahn, Charlotte Anna}}, issn = {{ISSN 2199-8825}}, journal = {{die hochschullehre}}, keywords = {{E-Learning, information competence, literature, library, research}}, number = {{6}}, title = {{{Informationskompetenz durch E-Learning? Durch Lernvideos nach Literatur suchen}}}, year = {{2020}}, } @inproceedings{48897, abstract = {{In this work we focus on the well-known Euclidean Traveling Salesperson Problem (TSP) and two highly competitive inexact heuristic TSP solvers, EAX and LKH, in the context of per-instance algorithm selection (AS). We evolve instances with nodes where the solvers show strongly different performance profiles. These instances serve as a basis for an exploratory study on the identification of well-discriminating problem characteristics (features). Our results in a nutshell: we show that even though (1) promising features exist, (2) these are in line with previous results from the literature, and (3) models trained with these features are more accurate than models adopting sophisticated feature selection methods, the advantage is not close to the virtual best solver in terms of penalized average runtime and so is the performance gain over the single best solver. However, we show that a feature-free deep neural network based approach solely based on visual representation of the instances already matches classical AS model results and thus shows huge potential for future studies.}}, author = {{Seiler, Moritz and Pohl, Janina and Bossek, Jakob and Kerschke, Pascal and Trautmann, Heike}}, booktitle = {{Parallel Problem Solving from {Nature} (PPSN XVI)}}, isbn = {{978-3-030-58111-4}}, keywords = {{Automated algorithm selection, Deep learning, Feature-based approaches, Traveling Salesperson Problem}}, pages = {{48–64}}, publisher = {{Springer-Verlag}}, title = {{{Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem}}}, doi = {{10.1007/978-3-030-58112-1_4}}, year = {{2020}}, } @proceedings{19976, abstract = {{The aim to reduce pollutant emission has led to a trend towards lightweight construction in car body development during the last years. As a consequence of the resulting need for multi-material design, mechanical joining technologies become increasingly important. Mechanical joining allows for the combination of dissimilar materials, while thermic joining techniques reach their limits. Self-piercing riveting enables the joining of dissimilar materials by using semi-tubular rivets as mechanical fasteners. The rivet production, however, is costly and time-consuming, as the rivets generally have to be hardened, tempered and coated after forming, in order to achieve an adequate strength and corrosion resistance. A promising approach to improve the efficiency of the rivet manufacturing is the use of high-strength high nitrogen steel as rivet material because these additional process steps would not be necessary anymore. As a result of the comparatively high nitrogen content, such steels have various beneficial properties like higher strength, good ductility and improved corrosion resistance. By cold bulk forming of high nitrogen steels high-strength parts can be manufactured due to the strengthening which is caused by the high strain hardening. However, high tool loads thereby have to be expected and are a major challenge during the production process. Consequently, there is a need for appropriate forming strategies. This paper presents key aspects concerning the process design for the manufacturing of semi-tubular self-piercing rivets made of high-strength steel. The aim is to produce the rivets in several forming stages without intermediate heat treatment between the single stages. Due to the high strain hardening of the material, a two stage forming concept will be investigated. Cup-backward extrusion is chosen as the first process step in order to form the rivet shank without forming the rivet foot. Thus, the strain hardening effects in the area of the rivet foot are minimized and the tool loads during the following process step can be reduced. During the second and final forming stage the detailed geometry of the rivet foot and the rivet head is formed. In this context, the effect of different variations, for example concerning the final geometry of the rivet foot, on the tool load is investigated using multistage numerical analysis. Furthermore, the influence of the process temperature on occurring stresses is analysed. Based on the results of the investigations, an adequate forming strategy and a tool concept for the manufacturing of semi-tubular self-piercing rivets made of high-strength steel are presented.}}, editor = {{Kuball, Clara-Maria and Uhe, Benedikt and Meschut, Gerson and Merklein, Marion}}, keywords = {{high nitrogen steel, self-piercing riveting, joining by forming, bulk forming, tool design}}, pages = {{280--285}}, title = {{{Process design for the forming of semi-tubular self-piercing rivets made of high nitrogen steel}}}, doi = {{10.1016/j.promfg.2020.08.052}}, volume = {{50}}, year = {{2020}}, } @article{19973, abstract = {{As a result of lightweight design, increased use is being made of high-strength steel and aluminium in car bodies. Self-piercing riveting is an established technique for joining these materials. The dissimilar properties of the two materials have led to a number of different rivet geometries in the past. Each rivet geometry fulfils the requirements of the materials within a limited range. In the present investigation, an improved rivet geometry is developed, which permits the reliable joining of two material combinations that could only be joined by two different rivet geometries up until now. Material combination 1 consists of high-strength steel on both sides, while material combination 2 comprises aluminium on the punch side and high-strength steel on the die side. The material flow and the stress and strain conditions prevailing during the joining process are analysed by means of numerical simulation. The rivet geometry is then improved step-by-step on the basis of this analysis. Finally, the improved rivet geometry is manufactured and the findings of the investigation are verified in experimental joining tests.}}, author = {{Uhe, Benedikt and Kuball, Clara-Maria and Merklein, Marion and Meschut, Gerson}}, journal = {{Production Engineering}}, keywords = {{Self-piercing riveting, Joining technology, Rivet geometry, Multi-material design, High-strength steel, Aluminium}}, pages = {{417--423}}, title = {{{Improvement of a rivet geometry for the self-piercing riveting of high-strength steel and multi-material joints}}}, doi = {{10.1007/s11740-020-00973-w}}, volume = {{14}}, year = {{2020}}, } @proceedings{19974, abstract = {{Due to the trend towards lightweight design in car body development mechanical joining technologies become increasingly important. These techniques allow for the joining of dissimilar materials and thus enable multi-material design, while thermic joining methods reach their limits. Semi-tubular self-piercing riveting is an important mechanical joining technology. The rivet production, however, is costly and time-consuming, as the process consists of several process steps including the heat treatment and coating of the rivets in order to achieve an adequate strength and corrosion resistance. The use of high nitrogen steel as rivet material leads to the possibility of reducing process steps and hence increasing the efficiency of the process. However, the high tool loads being expected due to the high strain hardening of the material are a major challenge during the rivet production. Thus, there is a need for appropriate forming strategies, such as the manufacturing of the rivets at elevated temperatures. Prior investigations led to the conclusion that forming already at 200 °C results in a distinct reduction of the yield strength. To create a deeper understanding of the forming behaviour of high nitrogen steel at elevated temperatures, compression tests were conducted in a temperature range between room temperature and 200 °C. The determined true stress – true strain curves are the basis for the further process and tool design of the rivet production. Another key factor for the rivet manufacturing at elevated temperatures is the influence of the process temperature on the tribological conditions. For this reason, ring compression tests at room temperature and 200 °C are carried out. The friction factors are determined on the basis of calibration curves resulting from the numerical analysis of the ring compression process. The investigations indicate that the friction factor at 200 °C is significantly higher compared to room temperature. This essential fact has to be taken into account for the process and tool design for the rivet production using high nitrogen steel.}}, editor = {{Kuball, Clara-Maria and Jung, R and Uhe, Benedikt and Meschut, Gerson and Merklein, Marion}}, keywords = {{High nitrogen steel, Self-piercing riveting, Joining by forming, Bulk forming, Strain hardening}}, title = {{{Influence of the process temperature on the forming behaviour and the friction during bulk forming of high nitrogen steel}}}, doi = {{10.1016/j.jajp.2020.100023}}, volume = {{1}}, year = {{2020}}, } @article{9853, abstract = {{Business model innovation is typically taught in small seminars at universities. Teaching this intrinsically task-oriented subject to a large number of students is a challenge. In this paper we address this challenge by proposing an experiential and interactive approach to teaching business models in a large classroom setting.}}, author = {{Szopinski, Daniel}}, journal = {{Journal of Business Models}}, keywords = {{Business model teaching, peer assessment, experiential learning}}, number = {{3}}, pages = {{90--100}}, title = {{{Squaring the circle: Business model teaching in large classroom settings}}}, volume = {{7}}, year = {{2019}}, } @inproceedings{13107, abstract = {{In this paper, we first outline a Hypothetical Learning Trajectory (HLT), which aims at a formal understanding of the rules for manipulating integers. The HLT is based on task formats, which promote algebraic thinking in terms of generalizing rules from the analysis of patterns and should be familiar to students from their mathematics education experiences in elementary school. Second, we analyze two students' actual learning process based on Peircean semiotics. The analysis shows that the actual learning process diverges from the hypothesized learning process in that the students do not relate the different levels of the diagrams in a way that allows them to extrapolate the rule for the subtraction of negative numbers. Based on this finding, we point out consequences for the design of the tasks.}}, author = {{Schumacher, Jan and Rezat, Sebastian}}, booktitle = {{Proceedings of the Eleventh Congress of the European Society for Research in Mathematics Education (CERME11, February 6 – 10, 2019)}}, editor = {{Jankvist, Uffe Thomas and Van den Heuvel-Panhuizen, Marja and Veldhuis, Michiel}}, keywords = {{diagrammatic reasoning, hypothetical learning trajectory, induction extrapolatory method, integers, negative numbers, permanence principle, semiotics}}, location = {{Utrecht}}, publisher = {{Freudenthal Group & Freudenthal Institute, Utrecht University and ERME}}, title = {{{A Hypothetical Learning Trajectory for the Learning of the Rules for Manipulating Integers}}}, year = {{2019}}, } @inproceedings{13443, abstract = {{This work considers the problem of control and resource allocation in networked systems. To this end, we present DIRA a Deep reinforcement learning based Iterative Resource Allocation algorithm, which is scalable and control-aware. Our algorithm is tailored towards large-scale problems where control and scheduling need to act jointly to optimize performance. DIRA can be used to schedule general time-domain optimization based controllers. In the present work, we focus on control designs based on suitably adapted linear quadratic regulators. We apply our algorithm to networked systems with correlated fading communication channels. Our simulations show that DIRA scales well to large scheduling problems.}}, author = {{Redder, Adrian and Ramaswamy, Arunselvan and Quevedo, Daniel}}, booktitle = {{Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems}}, keywords = {{Networked control systems, deep reinforcement learning, large-scale systems, resource scheduling, stochastic control}}, location = {{Chicago, USA}}, title = {{{Deep reinforcement learning for scheduling in large-scale networked control systems}}}, year = {{2019}}, }