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In this paper we discuss how group processes can be influenced by designing specific tools in computer supported collaborative leaning. We present the design of a shared workspace application for co-constructive tasks that is enriched by certain functions that are able to track, analyze and feed back parameters of collaboration to group members. Thereby our interdisciplinary approach is mainly based on an integrative methodology for analyzing collaboration behavior and patterns in an implicit manner combined with explicit surveyed data of group members’ attitudes and its immediate feedback to the groups. In an exploratory study we examined the influence of this feedback function. Although we could only analyze ad-hoc groups in this study, we detected some benefits of our methodology which might enrich real life Learning Communities’ collaboration processes. The data analysis in our study showed advantages of this feedback on processes of a group’s well-being as well as parameters of participation. These results provide a basis for further empirical work on problem solving groups that are supported by means of parallel interaction analysis as well as its re-use as information resource.
Resource Usage in Online Courses: Analyzing Learner’s Active and Passive Participation Patterns
(2015)
The paper analyzes the experience with an open university course for a very heterogeneous target group in which MOOC-like materials and activities were used. The course was conducted in a specifically prepared and extended Moodle environment. The analysis involves questionnaires as well as performance data that reflect the resource access on the learning platform. A special focus is put on the participants’ acceptance and usage of student-generated versus teacher-provided learning content. Network analysis techniques have been used to identify "interest clusters" of students around certain resources.
We present an architecture based on the Dynamic Field Theory for the problem of scene representation. At the core of this architecture are three-dimensional neural fields linking feature to spatial information. These three-dimensional fields are coupled to lower-dimensional fields that provide both a close link to the sensory surface and a close link to motor behavior. We highlight the updating mechanism of this architecture, both when a single object is selected and followed by the robot's head in smooth pursuit and in multi-item tracking when several items move simultaneously
Based on the concepts of dynamic field theory (DFT), we present an architecture that autonomously generates scene representations by controlling gaze and attention, creating visual objects in the foreground, tracking objects, reading them into working memory, and taking into account their visibility. At the core of this architecture are three-dimensional dynamic neural fields (DNFs) that link feature to spatial information. These three-dimensional fields couple into lower dimensional fields, which provide the links to the sensory surface and to the motor systems. We discuss how DNFs can be used as building blocks for cognitive architectures, characterize the critical bifurcations in DNFs, as well as the possible coupling structures among DNFs. In a series of robotic experiments, we demonstrate how the DNF architecture provides the core functionalities of a scene representation.
In this review, we describe current Machine Learning approaches to hand gesture recognition with depth data from time-of-flight sensors. In particular, we summarise the achievements on a line of research at the Computational Neuroscience laboratory at the Ruhr West University of Applied Sciences. Relating our results to the work of others in this field, we confirm that Convolutional Neural Networks and Long Short-Term Memory yield most reliable results. We investigated several sensor data fusion techniques in a deep learning framework and performed user studies to evaluate our system in practice. During our course of research, we gathered and published our data in a novel benchmark dataset (REHAP), containing over a million unique three-dimensional hand posture samples.
DamokleS 4.0
(2019)
Dieser interne Bericht beschreibt die Zielsetzung, Durchführung und Auswertung des Projektes Damokles 4.0. Das Projekt zielt darauf ab, neue, digitale Technologien in die Schwerindustrie einzuführen um Produktionsprozesse zu modernisieren. Unter Einsatz neuer Technologien, insbesondere mobiler Geräte, soll ein cyberphyiskalisches System (CPS) eine kontextbasierte und künstlich intelligente Unterstützung der Mitarbeiter in den Bereichen der Schwerindustrie ermöglichen. Hierzu werden typische Anwendungsfälle und die damit verbundenen Szenarien zur Unterstützung der Mitarbeiter auf Basis von neuen, flexiblen, adaptiven und mobilen Technologien, wie Augmented Reality und künstlicher Intelligenz, modelliert. Um den Prototypen einer AR-Anwendung und einer kamerabasierte Personenverfolgung zu entwickeln, hat die Hochschule Ruhr West im kleinen Technikum am Campus Bottrop eine entsprechende industrielle Umgebung simuliert. Die Projektergebnisse zeigen die Anwendbarkeit der vorgeschlagenen Softwareansätze und die Ergebnisse einer Untersuchung der psychologischen Einflüsse auf die Mitarbeiter.
The continuous evolution of learning technologies combined with the changes within ubiquitous learning environments in which they operate result in dynamic and complex requirements that are challenging to meet. The fact that these systems evolve over time makes it difficult to adapt to the constant changing requirements. Existing approaches in the field of Technology Enhanced Learning (TEL) are generally not addressing those issues and they fail to adapt to those dynamic situations. In this chapter, we investigate the notion of an adaptive and adaptable architecture as a possible solution to address these challenges. We conduct a literature survey upon the state of the art and state of practice in this area. The outcomes of those efforts result in an initial model of a Domain-specific architecture to tackle the issues of adaptability and adaptiveness. To illustrate these ideas, we provide a number of scenarios where this architecture can be applied or is already applied. Our proposed approach serves as a foundation for addressing future ubiquitous learning applications where new technologies constantly emerge and new requirements evolve.
This paper discusses the efforts carried out related to the design and development of a web-based framework that allows designing, deploying and executing mobile data collecting applications. Furthermore, it also allows analyzing and presenting the data that is generated during the mentioned process. The fact that the framework is completely web-based provides a platform independent execution of the mobile application on any mobile device with a web-browser. As a result that the whole life-cycle of creating, executing and discussing a mobile learning activity is implemented in pure web-based manner separates this work from similar efforts. In the course of this work, the current state of development of two of the components, the authoring tool and the mobile application is presented. This framework was introduced to teachers in an activity to follow up an initial study. On the basis of a workshop with teachers, we performed an explorative study regarding the technology acceptance and usability of two components of the proposed framework. The results are discussed and analyzed in this paper.
This paper presents a web-based framework that allows the creation and deployment of mobile learning activities. We present an authoring tool that allows not-technically skilled persons to design mobile learning tasks and deploy them as a web-based mobile application. Since the presented approach is based exclusively on web-technologies, the deployed mobile application can be executed via a mobile browser and therefore is platform independent. Despite previous research efforts carried out in this domain, few of the projects have addressed this course of actions from a purely web-based perspective. Through the latest development of web technologies, mobile applications have access to internal sensors like camera, microphone and GPS and therefore allow data collection within web-applications. In order to validate whether the proposed framework can be applied in educational settings, we conducted a pilot study with experienced teachers and present the results of these efforts in this paper.
This paper describes the design and development stages of a web-based framework, aiming to support the creation of mobile applications within the context of mobile learning. The suggested approach offers the opportunity to deploy and execute these applications on mobile devices. This web-based solution additionally offers the possibility to visualize the data collected by the mobile applications in a web-browser. Despite previous research efforts carried out in this domain, few of the projects have addressed these processes from a purely web-based perspective. Currently, a prototype of an authoring tool for creating mobile data collection applications is already implemented. In order to integrate and validate this solution in everyday educational settings, we are collaborating with a network of high schools. On the basis of workshops with teachers we will carry out, refinements and requirements for further enhancements will be collected and will be used to guide our coming efforts.
1. Einleitung
1.1 Hintergrund
„Der Klimawandel und der Umgang mit dessen Folgen ist eine der zentralen Herausforderungen der Menschheit im 21. Jahrhundert“ (S.Weller et al., 2016).
Seit Beginn der Industrialisierung kommt es zu einem starken Anstieg der Treibhauskonzentration in der Atmosphäre, welcher durch die erhöhte Nutzung fossiler Brennstoffe, die Ausweitung der industriellen Produktion sowie der Viehzucht und die damit einhergehende Abholzung
vieler Wälder geschuldet ist (Umweltbundesamt, 2021). Durch den Klimawandel kommt es neben der Zunahme von Hitzewellen und Trockenphasen ebenfalls zu einem Anstieg von extremen Starkregenereignissen, bei denen intensive Niederschläge in kürzester Zeit auftreten. Der Grund für die Zunahme an Starkregenereignissen ist die globale Erwärmung, da diese eine stärkere Verdunstung und einen höheren Feuchtigkeitsgehalt in der Luft bewirkt. Seit Beginn der
flächendeckenden Wetteraufzeichnungen im Jahre 1881 ist ein stetiger Anstieg der Temperatur zu verzeichnen. Im Vergleich zum Zeitraum 1881-1920 war die vergangene Dekade (2011-2020) 2 Grad Celsius wärmer (Kasper et al. September, 2021). Während Dürren als Konsequenz von längeren Trockenzeiten zu erwarten sind, kommt es durch die Starkniederschläge und einhergehende Überlastung der Kanalnetzte häufiger und intensiver zu flussbedingten
Überschwemmungen und Sturzfluten (Brasseur et al., 2016). Charakteristisch für Sturzfluten ist das Auftreten in urbanen und gebirgigen Gebieten, sowie kurze Vorlaufzeit und hohe Fließgeschwindigkeiten. Auf Grund der kurzen Vorlaufzeit ist es problematisch die Bevölkerung rechtzeitig vor den Gefahren zu warnen und präventive Maßnahmen einzuleiten (Brasseur et
al. 2016, 97–98). Es ist notwendig realitätsnahe und kurzfristige Niederschlags- und Überflutungsvorhersagen treffen zu können. Dies ermöglicht es, die Bevölkerung rechtzeitig vor drohenden Gefahren durch Sturzfluten oder Überschwemmungen zu warnen und zu schützen.
Artificial intelligence (AI) is one of the most auspicious yet controversial technologies with virtually unlimited potential to solve almost all of the existential problems humanity is facing today.1 Huge resources are poured into the development, testing and application of AI that is supposed to be utilized in almost all areas of everyday life.2 It may be used to combat genetically inherited diseases, to revolutionize the economy, to bring prosperity and equality to everyone and to counter the effects of climate change.3 With AI as the enabling technology humanity may experience a better future. Today, AI capabilities can already drastically improve analytic processing tasks and algorithmic systems and have beaten humans in games such as chess.4 Yet, AI and all of its applications bring about a myriad of ethical challenges. Revolutionary weapon systems that achieve autonomy via AI and genome-editing powered by AI are just some specific examples.5 An omnipotent AI will be either the greatest or the vilest thing that has happened to humanity in its brief existence.6 However, even today more and more computational devices are connected to each other, spurring a huge increase in global data streams that can be used to further train and enhance AI systems.
The prowess of AI for executing analytic tasks paves the way for the use of AI in more and more applications. One of these applications, that shows great promise, is the use of AI in surveillance applications.7 AI surveillance applications are proliferating at a fast rate, with a number of appli-cations already being in use today.8 These applications are aimed at accomplishing a number of policy objectives, some are in accordance with basic human laws, some are definitely not and some
1 Cf. Hawking (2018). P. 183ff
2 Cf. Hawking (2018). P. 183ff.
3 Cf. Hawking (2018). P. 183ff.
4 Cf. Burton (2015). P. 1ff.
5 Cf. Hawking (2018). P. 183ff.
6 Cf. Hawking (2018). P. 183ff.
7 Cf. Feldstein (2019). P. 1.
8 Cf. Feldstein (2019). P. 1.
2
belong in the nebulous area in between lawful and unlawful.9 But what are lawful and unlawful uses of AI surveillance systems and what are their ethical implications?
This thesis will examine the ethical implications of AI based mass surveillance systems and try to answer the first central question, if it is possible to use AI based mass surveillance applica-tions in an ethical way. Furthermore, the thesis will attempt to answer the second central ques-tion and find out how the ethical use of AI based mass surveillance systems, if this ethical use is possible, materialize. Governmental agencies will be in the focus of this discussion, as their use of the technology may have bigger ethical challenges. Yet private companies will play a part as well. In an attempt to accomplish these two aims, the thesis will inspect the basics of ethics and possible ethical theories that can be utilized to answer the questions. Normative ethics will be stud-ied first with a focus on consequentialism and utilitarianism. To gain a deeper understanding of utilitarianism, act and rule utilitarianism will be compared. Afterwards, deontological theories will be the focus of the discussion with a concentration on deontological pluralism. Next, the mentioned theories will be evaluated, discussing advantages and weak spots of the theories, to assess which theory may serve as the ethical framework of this thesis and the subsequent answer to the two main questions.
The next step will be the establishment of the AI framework. This contains the definition of AI and a distinction of terms that are commonly used in the its environment such as automation and au-tonomy. The importance of data for AI will be discussed. Afterwards, the technological basis of AI will be outlined, discussing key concepts such as machine learning and deep learning. Addi-tionally, it will be examined how an AI learns. The possible uses of AI in general will be outlined in a brief fashion, blazing the trail to discussing the moral challenges of AI. Afterwards, the current pace of AI development will be studied.
In the chapter that follows, the use of AI in surveillance technology is going to be highlighted. The possible ways of how AI can be used for surveillance purposes are reviewed here, discussing facial
9 Cf. Feldstein (2019). P. 1.
3
and behavioral recognition systems, smart cities, smart policing, communications/data driven sur-veillance and their enabling technologies. Then, the global proliferation of AI surveillance systems is going to be outlined.
Subsequently, the accordance of AI surveillance with basic human laws and rights, such as the right to privacy, will be checked to find out if the law and the international framework of human rights allow for AI surveillance or at least have restrictions that would greenlight the use of AI surveillance technology. All the aspects of the thesis, especially including the selected ethical framework, will be combined in this last section in order to enable the adaptation of a framework that allows to find out, if AI surveillance systems can be ethically permissible while also creating insights how this ethical AI surveillance system must be engineered. To finish, the thesis will end with a conclusion.
Diese Arbeit beschäftigt sich mit der Erstellung einer Administratoroberfläche für die Lehre bei Photovoltaik (PV)-Praktika in der virtuellen Realität (VR). Die erstellte Umgebung bietet, mittels Bildschirmspiegelungen, Möglichkeiten zur didaktischen Anleitung und Unterstützung der Studierenden. Das Thema wurde aufgrund einer bestehenden Lehranwendung in der VR bedeutungsvoll und zeigt deutliches Potenzial. Diese Lehranwendung wird bereits umfassend und verpflichtend in den Praktika eingesetzt. Sie bietet einen praxisnahen Aufbau von Solaranlagen und erhöht gefahrlos die Experimentierfreudigkeit. Mit ihr lassen sich die aufgebauten Anlagen technisch prüfen, simulieren und bewerten. Zudem werden die beiden Möglichkeiten zur Unterstützung der Studierenden beurteilt. Als Ergebnis wird die Umsetzung der nahezu automatisierten Administratorober-fläche verdeutlicht und ein Usability-Test aus den Praktika evaluiert.
Schlagwörter: Administratoroberfläche, Bildschirmspiegelung, C, Didaktik, im-mersiv, Oculus Quest 2, Photovoltaik, Python, Tkinter, virtuelle Realität
For face recognition from video streams speed and accuracy are vital aspects. The first decision whether a preprocessed image region represents a human face or not is often made by a feed-forward neural network (NN), e.g. in the Viisage-FaceFINDER® video surveillance system. We describe the optimisation of such a NN by a hybrid algorithm combining evolutionary multi-objective optimisation (EMO) and gradient-based learning. The evolved solutions perform considerably faster than an expert-designed architecture without loss of accuracy. We compare an EMO and a single objective approach, both with online search strategy adaptation. It turns out that EMO is preferable to the single objective approach in several respects.