Human-like nonverbal behaviors, such as gestures or facial expressions, play a crucial role in face-to-face communication, yet their impact on user interactions with virtual agents (VAs) in real-world environments remains underexplored. This study examines how co-speech gestures influence engagement and perception in interactions with a VA deployed in a museum. Using a mixed-methods approach, we conducted an A/B test comparing a gesturing VA to a nongesturing VA. Quantitative analysis of system logs revealed no significant difference in the number of conversational turns between conditions. Qualitative findings revealed that gestures may positively influence usability by making the interaction more intuitive and reducing user confusion regarding the VA’s internal states. However, perceptions of nonverbal behavior varied, with some users finding gestures engaging while others considered them uncanny. Regardless of condition, system response times, verbal communication errors, and answer quality were key drivers of user dissatisfaction. These findings highlight both the benefits and challenges of incorporating and studying nonverbal behavior in VAs and underscore the need for robust verbal communication to support meaningful interactions.

This paper investigates the impact of a group-adaptive conversation design in two socially interactive agents (SIAs) through two real-world studies. Both SIAs – Furhat, a social robot, and MetaHuman, a virtual agent – were equipped with a conversational artificial intelligence (CAI) backend combining hybrid retrieval and generative models. The studies were carried out in an in-the-wild setting with a total of N = 188 participants who interacted with the SIAs - in dyads, triads or larger groups – at a German museum. Although the results did not reveal a significant effect of the group-sensitive conversation design on perceived satisfaction, the findings provide valuable insights into the challenges of adapting CAI for multi-party interactions and across different embodiments (robot vs. virtual agent) highlighting the need for multimodal strategies beyond linguistic pluralization. These insights contribute to the fields of Human-Agent Interaction (HAI), Human-Robot Interaction (HRI), and broader Human-Machine Interaction (HMI), providing insights for future research on effective dialogue adaptation in group settings.

The social capabilities of socially interactive agents (SIA) are a key to successful and smooth interactions between the user and the SIA. A successful start of the interaction is one of the essential factors for satisfying SIA interactions. For a service and information task in which the SIA helps with information, e.g. about the location, it is an important skill to master the opening of the conversation and to recognize which interlocutor opens the conversation and when. We are therefore investigating the extent to which the opening of the conversation can be trained using the user’s body language as an input for machine learning to ensure smooth conversation starts for the interaction. In this paper we propose the Interaction Initiation System (IIS) which we developed, trained and validated using an in-the-wild data set. In a field test at the Deutsches Museum Bonn, a Furhat robot from Furhat Robotics was used as a service and information point. Over the period of use we collected the data of N = 201 single user interactions for the training of the algorithms. We can show that the IIS, achieves a performance that allows the conclusion that this system is able to determine the greeting period and the opener of the interaction.

A thorough literature research is usually the first step when dealing with a novel topic in science. Regarding the medical domain, a popular starting point for this task is the web based search engine PubMed, which has an index of over 27 million medical publications from the MEDLINE database and other sources. Given certain search terms of interest, e.g. neurodegeneration or the drug FTY 720, results are presented by PubMed in form of textual lists which can span over several hundred pages. Thus, getting a reasonable overview over published literature for a given topic can be a very time consuming and challenging task. To facilitate a more intuitive approach to medical literature research, interactive visual interfaces can be helpful. The novel web platform ViLiP (Visual Literature Platform) is built around this idea. It provides an easy to operate interactive interface to PubMed and presents the result of a user's query in form of in-situ heat map or word cloud visualizations. The ViLiP tool is currently actively used in the neuroanatomy domain, namely in multiple-sclerosis research.

Aphasia is an acquired language disorder resulting from damage to language related networks of the brain, most often as a result of ischemic stroke or traumatic brain injury. Within the European Union, over 580000 people are affected each year. Both assessment and treatment of aphasia require the analysis of language, in particular of spontaneous speech. Factoring in therapy and diagnosis sessions, which require the presence of a speech therapist and a physician, aphasia is a resource intensive condition: It has been estimated that in Germany alone, there are 70000 new cases of stroke-related aphasia every year, 35000 of which persist over more than six months - all of which should receive formal diagnostic testing at some point. Having an automatic system for the detection and evaluation of aphasic speech would be of great benefit for the medical domain by immensely speeding up diagnostic processes and thus freeing up valuable resources for, e.g., therapy. As a first step towards building such a system, it is necessary to identify the vocal biomarkers which characterize aphasic speech. Furthermore, a database is needed which maps from recordings of aphasic speech to the type and severity of the disorder. In this paper, we present the vocal biomarkers and a description of the existing Aachen Aphasia database containing recordings and transcriptions of therapy sessions. We outline how the biomarkers and the database could be used to construct a recognition system which automatically maps pathological speech to aphasia type and severity.

The ongoing modernization of today's workplaces within the framework of industry 4.0 is leading to radical new developments and forcing fundamental changes to the way companies and factories are established. The purpose of this paper is to develop and improve a concept that organizes the workplace on a basic level in order to meet the upcoming challenge of accounting for robots as key players in it. There are several organizational structures that include the traditional hierarchical structures as well as the modern agile management models that are rising in the world of industry 4.0. Within it, the usage of robots is increasing due to the vast and multiple functions each robot is able to perform. This implies automation, but it also implies that different forms of collaboration with humans are becoming necessary as factories are tending to produce customized products. Individualized products require different methods and different skills which span different sets of abilities of humans and robots. How does this increase of robots' usage affect the applied organization structures and flows of the decision-making processes? What are necessary changes that need to be considered to maximize the efficiency and effectiveness of a workplace with robots that already existing structures do not compensate for? This paper highlights the existing gap and addresses the required changes in the organization models. Following that is an evaluation and outlook on that validates the legitimacy of the approach.

The term "Industry 4.0" symbolizes new forms of technology and artificial intelligence within production technologies. Smart robots are going to be the game changers within the factories of the future and will work with humans in indispensable teams within many processes. With this fourth industrial revolution, classical production lines are going through comprehensive modernization, e.g. in terms of in-the-box manufacturing, where humans and machines work side by side in so-called "hybrid teams". Questions about how to prepare for newly needed engineering competencies for the age of Industry 4.0, how to assess them and how to teach and train e.g. human-robot-teams have to be tackled in future engineering education. The paper presents theoretical aspects and empirical results of a series of studies, carried out to investigate the competencies of virtual collaboration and joint problem solving in virtual worlds.

Automatic emotion recognition is an interdisciplinary research field which deals with the algorithmic detection of human affect, e.g. anger or sadness, from a variety of sources, such as speech or facial gestures. Apart from the obvious usage for industry applications in human-robot interaction, acquiring the emotional state of a person automatically also is of great potential for the health domain, especially in psychology and psychiatry. Here, evaluation of human emotion is often done using oral feedback or questionnaires during doctor-patient sessions. However, this can be perceived as intrusive by the patient. Furthermore, the evaluation can only be done in a noncontinuous manner, e.g. once a week during therapy sessions. In contrast, using automatic emotion detection, the affect state of a person can be evaluated in a continuous non-intrusive manner, for example to detect early on-sets of depression. An additional benefit of automatic emotion recognition is the objectivity of such an approach, which is not influenced by the perception of the patient and the doctor. To reach the goal of objectivity, it is important, that the source of the emotion is not easily manipulable, e.g. as in the speech modality. To circumvent this caveat, novel approaches in emotion detection research the potential of using physiological measures, such as galvanic skin sensors or pulse meters. In this paper we outline a way of detecting emotion from brain waves, i.e., EEG data. While EEG allows for a continuous, real-time automatic emotion recognition, it furthermore has the charm of measuring the affect close to the point of emergence: the brain. Using EEG data for emotion detection is nevertheless a challenging task: Which features, EEG channel locations and frequency bands are best suited for is an issue of ongoing research. In this paper we evaluate the use of state of the art feature extraction, feature selection and classification algorithms for EEG emotion classification using data from the de facto standard dataset, DEAP. Moreover, we present results that help choose methods to enhance classification performance while simultaneously reducing computational complexity.

In Europe there are more than 580 000 people who suffer from aphasia - an acquired speech and language disorder that occurs because of brain damage, primarily as a result of a stroke. Especially with regards to demographic change, health care systems have to face present and future challenges to improve aphasia therapy. Thereby, immediate therapeutic measures are decisive for best possible and long-term success in language therapy. Regarding essential requirements, on the one hand, therapy intensity and frequency have to be increased significantly while on the other hand, measures need to be adjusted along everyday activities. A very promising approach to meet this requirements are augmented reality applications. They can be used to create a highly natural exercise situation, in which patients interact and practice with their personal possessions at home. This facilitates the successful and continuous transfer of learnings for the patient, contrary to being solely dependent on clinical therapy units. This paper gives an overview of the concept of a real-time software providing augmented and dynamic language therapy, which is interactive and utilizes simple user interface design, for home-based training.

In terms of current industrial manufacturing sites, a major challenge is to deal with growing complexity by enabling intelligence on the shop floor of existing production processes. A possible solution to reach this goal consists in an integration of smart cyber-physical production systems into the automation systems of a production. One promising approach to do so is based on the agent paradigm. By deploying Multi-Agent Systems into the manufacturing components, each production step is able to gain a self-representation and to achieve intelligent behavior of the entire system. One problem though is the formalization of agent based systems and their communication among each other, which is currently rather hard-coded or application-specific. In this research paper, we propose an architectural approach for a Multi-Agent System that is based on OPC UA as modeling interface and as semantic approach for the integration of agent-based systems into existing manufacturing sites. For this purpose, we define a domain ontology for the representation of intelligent software agents and for the mapping of an agent-based communication by making use of the OPC UA meta model. Due to this conceptual approach, the integration of intelligent entities such as agents into grown manufacturing systems can be performed in a structured and well-defined way as well as by using existing interfaces and semantic standards. The according agent representation intends to upgrade all production resources that can be linked through OPC UA with intelligent behavioral skills. We evaluate the proposed concept by means of an Industry 4.0 demonstrator implementing agents for the representation actual manufacturing machinery based on Raspberry Pi devices.

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In this positioning paper we present the AUDIME project approach in which we plan to evaluate the usability and social acceptance of smart and wearable devices in the context of mass-casualty-incidents. AUDIME aims to provide a platform which captures, evaluates, and provides data from various sources on an incident site. This way, triage, patient monitoring, information sharing and communication are to be improved, which simplifies decision making at executive staff level. In contrast to previous projects, AUDIME does not replace any low-tech or non-tech approaches (e.g. triage cards,) but enhances the information handling by capturing analogue information using smart or wearable devices and distributing digitalized data to qualified recipients in real-time.

The RoboCup Logistics League (RCLL) has seen major rule changes increasing the complexity, e.g. by raising the number of product variants from 3 to almost 250, and introducing new challenges like the handling of physical processing machines. We describe various aspects of our system that allowed to improve the performance in 2015 and our efforts to advance the league as a whole. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

In the RoboCup Logistics League (RCLL), games are governed by a semi-autonomous referee box. It also records tremendous amounts of data about state changes of the game or communication with the robots. In this paper, we analyze the data of the 2014 competition by means of Key Performance Indicators (KPI). KPIs are used in industrial environments to evaluate the performance of production systems. Applying adapted KPIs to the RCLL provides interesting insights about the strategies of the robot teams. When aiming for more realistic industrial properties with a 24/7 production, where teams perform shifts (without intermediate environment reset), KPIs could be a means to score the game. This could be tried first in a simulation sub-league. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

In order to study new methods of telemedicine usage in the context of emergency medical services, researchers need to prototype integrated telemedicine systems. To conduct a one-year trial phase-intended to study a new application of telemedicine in German emergency medical services-we used off-the-shelf medical devices and software to realize real-time patient monitoring within an integrated telemedicine system prototype. We demonstrate its feasibility by presenting the integrated real-time patient monitoring solution, by studying signal delay and transmission robustness regarding changing communication channel characteristics, and by evaluating issues reported by the physicians during the trial phase. Where standards like HL7 and the IEEE 11073 family are intended to enable interoperability of product grade medical devices, we show that research prototypes benefit from the use of web technologies and simple device interfaces, as they simplify product development for a manufacturer and ease integration efforts for research teams. Embracing this approach for the development of new medical devices eases the constraint to use off-the-shelf products for research trials investigating innovative use of telemedicine.

Today there is a flood of e-learning and e-learning related solutions for engineering education. It is at least a time consuming task for a teacher to find an e-learning system, which matches their requirements. To assist teachers with this information overload, a web-based recommendation system for related e-learning solutions is under development to support teachers in the field of engineering education to find a matching e-learning system within minutes. Because the e-learning market is subject of very fast changes, an agile engineering process is used to ensure the capability to react on these changes. To solve the challenges of this project, an own user-flow visual programming language and an algorithm are under development. A special software stack is chosen to accelerate the development. Instead of classical back-office software to administer and maintain the project, a web-based approach is used - even for a complex editor. The determining of the necessary catalog of related solutions within real-time is based on big data technologies, data mining methods and statistically text analysis.

Over the past decades, several disciplines like artificial intelligence, music, medicine, ergonomics or cognitive science dealt with problems concerning analyses of data associated with time intervals. Topics like pattern recognition, comparison, quality, or visualization are in focus of current research. Using these techniques in the context of data-driven decision support is quite rare even though the importance of data to support better decision making can be enormous. Reasons lie above all in limited insufficient tooling support, expensive data processing, and inapplicable requirements. In this paper, we discuss the use of time interval data and name difficulties arising when processing such data for data-driven decision support. We discuss and present solutions for overcoming the identified problems and enabling the usage of time interval data for data-driven decision support. We introduce a time interval data analysis model that provides fast access to the raw time interval data but especially to aggregated time series, mostly needed when making meaningful decisions.

Large classes at universities (>1600 students) create their own challenges for teaching and learning. Audience feedback is lacking and fine tuning of lectures, courses and exam preparation to address individual needs is very difficult to achieve. At RWTH Aachen University, a course concept and a knowledge map learning tool aimed to support individual students to prepare for exams in information science through theme-based exercises were developed and evaluated. The tool was grounded in the notion of self-regulated learning with the goal of enabling students to learn independently.

Dependence on a team of robots to carry out the exploration missions has many benefits such as speeding up the missions; provided that the coordination among robots is maintained. Many circumstances can limit the communication, which is crucial for the coordination among robots (e.g. impenetrable barriers, high temperature etc.). A periodic rendezvous strategy is considered in this paper as a work around in order to overlap communication ranges of the robots. Attending these periodic rendezvous sessions requires that the robots interrupt their current exploration progress periodically and traverse back to the rendezvous points (i.e. Interruptibility). During their trips to these points, they do not gain new knowledge since they cross already explored parts of the area. Therefore, using rendezvous strategies improves the team behavior but has a negative impact on the time efficiency. The contribution of this paper is to mitigate this negative impact of Interruptibility on explorations while maintaining the coordination among robots. The mitigation algorithm is evaluated on several graphs and its performance is compared with other rendezvous approaches where the results are promising.

Modern software development includes the usage of UML for (model-driven) analysis and design, customer communication etc. Since UML is a graphical notation, alternative forms of representation are needed to avoid barriers for developers and other users with low vision. Here, Human-usable Textual Notation (HUTN) is tested and evaluated in a user interface modeling concept to provide accessible model-driven software design.

Engineering students are, compared to their counterparts in other disciplines, less mobile resulting in limited intercultural skills. Globalization requires professionals being excellent in their fields and being able to work on a global scale at the same time. So far, engineering education has put too little stress on integrating intercultural competences into curricula. This paper shows new approaches to incorporate international experiences into higher engineering education. First, it analyzes the current situation of international student mobility in Germany, before emphasizing the general motivation for international student exchange especially in engineering science. A consortium of three excellent German engineering universities was put up to introduce new measures for increasing student mobility as is described subsequently. This paper represents work in progress. Thus, further results will be published continuously.

The majority of freshmen is overcharged in the transition from high school to academic education at the beginning of their studies. The biggest continual problems appear in mathematics. This is based on the high degree of abstraction and on the fact that the mathematical education for non-mathematicians, mainly engineering students, takes place at the beginning of the studies. Thus, deficiencies become apparent at an early stage. In order to facilitate freshmen's transition from high school to the university the Department of Mathematics offers a four-week introductory course to mathematics before the begin of each semester. The course is addressed particularly to freshmen of the engineering and natural sciences and mathematics. Additionally, a so-called mathematics computer course is offered for a part of the participants of the introductory mathematics course. In this two-week course the participants learn how to handle the Linux operating system, the employment of a computer algebra system (Maple) and obtain an introduction to the scientific text processing system LATEX.

Due to their low price and good quality, Stereo Vision Systems (SVS) are recently considered as a key factor to gather actual information about the object of interest. Today, automated highway systems (AHS) for urban and highway environment were developed without the use of a stereo vision system. In future, the application of AHS should be extended to unstructured environments (e.g. desert) and be adapted to heterogeneous vehicles. In this context, the stereo vision system could enable the platoon to be independent from environmental structure (e.g. lane markings) through its ability to detect, track, locate and recognize heterogeneous vehicles. So far, the need for high accuracy prevents SVS to be applied in automated heterogeneous platoon. In this paper a mechanism towards this is presented, where some behavioral properties have to be satisfied in terms of unstructured environment and heterogeneous platoons. Within a heterogeneous platoon, the back view of a preceding vehicle (BVPV) is considered as a reference point for the lateral and longitudinal control. The key idea of the proposed mechanism is to confirm that the distance of the BVPV can be extracted without depending on the movement of the preceding vehicle. Furthermore, the proposed mechanism has to ensure that features extracted from the back view are suitable to implement successfully the calibration process at around 10m distance. With the proposed SVS mechanism some of behavioral properties have to be satisfied in terms of unstructured environment and AHS. These properties are reliability, performance and robustness. Compared to other methods which use a SVS, the proposed mechanism distinguishes itself through adapting to dynamic environment and extracting the necessary features for the calibration process.

Mathematics is the most important discipline for engineering students besides their own subject - and it is constantly required in engineering freshmen lectures. Sometimes, mathematical content is needed in engineering lectures before it has been taught in the mathematics classroom. Thus, the engineering teachers often have to do mathematical excurses that are ineffective and unsatisfying, both for the students and the teachers. A propaedeutic dedicated to mathematical studies only, cannot be implemented within the current study regulations. Moreover, it would contradict the engineers' wish for a rapid identification with the “real” engineering subject to increase the students' motivation. Therefore, we introduced EARLY BIRD to overcome this deficiency. In EARLY BIRD I freshmen can benefit of their time between high school graduation and their enrollment at the university to attend Calculus I and Linear Algebra classes. In EARLY BIRD II Calculus II classes are offered during the winter semester break.

Due to the increase in road transportation several projects concerning automated highway systems were initiated to optimize highway capacity. In the future, the developed techniques should be applicable in unstructured environment (e.g. desert) and adaptable for heterogeneous vehicles. But before, several challenges, i.e. independency of lane markings, have to be overcome. Our solution is to consider the back view of the preceding vehicle as a reference point for the lateral and longitudinal control of the following vehicle. This solution is independent from the environmental structure as well as additional equipment like infrared emitters. Thus, both the detection and tracking process of the back view are needed to provide automated highway systems with the distance and the deviation degree of the preceding vehicle. In this paper the first step, the detection and location of the back view on video streams, is discussed. For a definite detection in a heterogeneous platoon several features of the back view are detected. A method is proposed to run rejection cascades generated by the AdaBoost classifier theory on the video stream. Compared to other methods related to object detection, the proposed method reduces the running time for the detection of the back view to 0.03–0.08 s/frame. Furthermore, the method enables a more accurate detection of the back view.

In the paper User adaptive design of active vehicle safety systems with regard to the driver behavior of elderly drivers the research project Evaluation of active vehicle safety systems and components in regard to their safety impact on elderly drivers is presented, including its most striking results. The project is funded by the Federal Ministry of Transport, Building and Urban Development (BMVBS) and aims to answer the question if active vehicle safety systems are able to support elderly people in staying mobile. Additionally, a list of criteria for designing active vehicle safety systems in the future and recommended procedures for political decisions was developed retrospectively. Therefore an extensive market research was carried out in the beginning of the project, containing a literature research, a survey with 70 elderly people and expert interviews. During the second phase test drives combined with the answering of standardized questionnaires and special workload assessments were carried out.

The emergence of the Social Web offers new opportunities for scientists to explore open virtual communities. Various approaches have appeared in terms of statistical evaluation, descriptive studies and network analyses, which pursue an enhanced understanding of existing mechanisms developing from the interplay of technical and social infrastructures. Unfortunately, at the moment, all these approaches are separate and no integrated approach exists. This gap is filled by our proposal of a concept which is composed of a universal description model, temporal network definitions, and a measurement system. The approach addresses the necessary interpretation of Social Web communities as dynamic systems. In addition to the explicated models, a software tool is briefly introduced employing the specified models. Furthermore, a scenario is used where an extract from the Wikipedia database shows the practical application of the software.

Researchers of computer science and social science are increasingly interested in the Social Web and its applications. To improve existing infrastructures, to evaluate the success of available services, and to build new virtual communities and their applications, an understanding of dynamics and evolution of inherent social and informational structures is essential. One key question is how communities which exist in these applications are structured in terms of author contributions. Are there similar contribution patterns in different applications? For example, does the so called onion model revealed from open source software communities apply to Social Web applications as well? In this study, author contributions in the open content project Wikipedia are investigated. Previous studies to evaluate author contributions mainly concentrate on editing activities. Extending this approach, the added significant content and investigation of which author groups contribute the majority of content in terms of activity and significance are considered. Furthermore, the social information space is described by a dynamic collaboration network and the topic coverage of authors is analyzed. In contrast to existing approaches, the position of an author in a social network is incorporated. Finally, a new composite calculation to evaluate author contributions in Wikis is proposed. The action, the content contribution, and the connectedness of an author are integrated into one equation in order to evaluate author activity.

The Robinson curriculum contains a novel approach to improve the engineering education, to enhance technological literacy of students from nonengineering fields and to increase in the number of students, especially young women, in the fields of engineering and natural sciences. Since robotics holds a special fascination among all the technological fields -- due to its cross-disciplinary approach as well as its popularity through movies and literature --, this field allows hands-on teaching of scientific and engineering methodologies at an early stage of the academic education, not limited to engineering students but encompassing students from all academic -- and even pre-academic -- areas.

Despite extensive social changes and intensive political efforts to establish equal opportunities, women are still a minority in the fields of natural sciences and engineering both at universities and in the related professional fields. This low ratio leads to severe consequences both for women and society.

Robotics, in particular mobile robotics, holds a special fascination among all the technological fields: Starting with the first “automatons” of ancient times (Archytas of Tarent, Heron of Alexandria) and da Vinci’s studies of androids to the modern heroes of movies and literature, robots (and in particular, humanoid robots) have always captivated the fantasy of human beings. Unsurprisingly, robotics is attracting even the interest of people who are normally more reserved and cautious towards technological fields of study. As a result, robotics is well suited to strengthen the interdisciplinary components of the academic education of all students, in particular also of students from nontechnological areas, in order to strengthen their technological interest and literacy.

Although Internet and WWW phenomena are often described using spatial metaphors, the commonest means of geographic orientation - the map - is little used in online navigation. Maps of the physical world are however available online, as are maps illustrating physical Internet topography, semantic maps showing content linkages and maps of gaming environments, usually realistic simulations. Lacking an underlying geography, maps of entire virtual spaces such as cooperative knowledge spaces seem impossible or impractical as long as their sites are conceived only as unstructured or at most hierarchical) addresses.The ViCToR project (Virtual Cooperation in Teaching and Research) at the Technische Universität Berlin uses a room metaphor to implement a shared, user-defined space for carrying out cooperative work in education and research. So far navigation in the hierarchically structured rooms is poorly developed. This paper explores the possibilities for implementing map-based domain navigation using a community-created local geography based on coordinates.

Digital media in general and the Internet in particular play a ever growing role in the storage, dissemination and retrieval of information and knowledge. Semantic annotation of the provided information is necessary to support the user in retrieving and filtering requested information. Wide-spread tools like Google have shown both the power and the limitations of statistical methods based on correlations between terms within texts. The KEA system uses a different approach. Natural language processing techniques, taking advantage of characteristic linguistic structures defined by the language used in mathematical texts, are utilized in the automatic extraction of ontologies from mathematical texts. As a result, the system creates a base of the mathematical relations and concepts by mapping the extracted ontologies on the structure of a data base. To support the retrieval and further refinement of the data stored within this mathematical knowledge base, KEA implements a number of Web 2.0 technologies in a desktop style interface. The following article presents the technology and applications of the KEA system.

The number of students in major classes for freshmen courses easily exceeds 2.000 students. In this paper, the MOSESKONTO-environment is presented - which helps computing an optimal assignment into exercise groups and provides means for tracking and managing exam registration. Based on the data from summer term 2005, already 50% of all bachelor exams were managed through the MOSESKONTO at TU Berlin.

The knowledge contained in digital lectures and articles used in eLearning platforms like Moodle and Blackboard, is creating new demands for intelligent retrieval mechanisms. One basic approach in support of such retrieval mechanisms is the generation of semantic annotation, based on ontologies describing both the field and the structure of the texts themselves. Many current approaches use statistical methods similar to the ones employed by Google to find correlations within the texts. While successful and efficient, this approach fails to take advantage of the additional information provided by the structure of the sources, or, i.e. the upper ontology used by the author. mArachna is based on natural language processing techniques, taking advantage of characteristic linguistic structures defined by the language used in mathematical texts. It creates a knowledge base from the mathematical relations presented in a text, mapping the ontology onto the structure of the knowledge base.

The knowledge contained in the growing number of scientific digital publications, particularly over the internet creates new demands for intelligent retrieval mechanisms. One basic approach in support of such retrieval mechanisms is the generation of semantic annotation, based on ontologies describing both the field and the structure of the texts themselves. Many current approaches use statistical methods similar to the ones employed by Google to find correlations within the texts. This approach neglects the additional information provided in the upper ontology used by the author. mArachna, however, is based on natural language processing techniques, taking advantage of characteristic linguistic structures defined by the language used in mathematical texts. It stores the extracted knowledge in a knowledge base, creating a low-level ontology of mathematics and mapping this ontology onto the structure of the knowledge base. The following article gives an overview over the concepts and technical implementation of the mArachna prototype.

Cooperative knowledge spaces have a high potential to improve eLTR (eLearning, eTeaching and eResearch) at universities. Since there are few implementations deployed, notably in the fields of mathematics, natural sciences, and engineering, we propose a concept for field-specific knowledge spaces for those disciplines -"ViCToR"-Spaces (virtual cooperation in teaching and research for mathematics, natural sciences and engineering). ViCToR-Spaces present novel collaborative working environments for knowledge gain and research, supporting well-established forms of scientific and technological cooperation without geographical or technological boundaries. In this article, we describe the requirements for ViCToR-Spaces, the components that are already available, and further developments

Cooperative knowledge spaces create new potentials for the experimental fields in natural sciences and engineering because they enhance the accessibility of experimental setups through virtual laboratories and remote technology, opening them for collaborative and distributed usage. A concept for extending existing virtual knowledge spaces for the means of the technological disciplines (VICToR-Spaces-virtual cooperation in teaching and research for mathematics, natural sciences and engineering) is presented. The integration of networked virtual laboratories and remote experiments (NanoLab Approach), as well as an approach to community-driven content sharing and content development within virtual knowledge spaces (NanoWiki) are described

Machine-readable semantic annotation of scientific knowledge is becoming increasingly important to manage and access the knowledge contained in an increasing number of scientific publications. At the same time, automated extraction of knowledge from natural language texts is a major technical challenge remaining largely unsolved. Scientific texts in general and mathematical texts in particular, are characterized by the use of complex language constructs with the intent to transfer knowledge. To a large extent, mathematical texts possess a strict internal structuring and can be separated into text elements such as definitions, theorems etc. These text elements are principal carriers of mathematical information. In addition, these elements show a characteristic linguistic structuring well suited for natural language processing techniques. In this paper we present mArachna, a system for extracting mathematical relations from texts and integrating them into a knowledge base. In response to user queries, parts of the knowledge base are visualized using OWL. In particular, mArachna aims to provide an overview of single fields of mathematics, as well as showing intra-field relations between mathematical objects and concepts

Virtual labs enable field specific experiments and open them for collaborative and distributed usage. In order to realize comprehensive laboratory set-ups providing a scientific broadness and user adaptivity, several challenges regarding the integration of different software technologies have to be solved. We propose an eLearning framework consisting of a learner and a course model; exercises within this framework are supplemented by virtual laboratories and computer algebra systems. We discuss the potentials of this setup on the example of the laboratory VideoEasel and its interface to Maple