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Proceedings of DELFI Workshops 2021
13.09.2021
Dortmund (Online), Deutschland
This study proposes a framework for the collaborative development of global start-up innovators in a multigenerational digital environment. Intergenerational collaboration has been identified as a strategy to support entrepreneurs during their formative years. However, integrating and fostering intergenerational collaboration remains elusive. Therefore, this study aims to identify competencies for successful global start- ups through intergenerational knowledge transfer. We used a systematic literature review to identify a competency set consisting of growth virtues, effectual creativity, technical domain, responsive teamwork, values-based organization, sustainable networking, cultural awareness, and facilitating intergenerational safety. The competency framework serves as a foundation for knowledge management research on the global innovation readiness of people to collaborate across generations in the digital age.
This study aims to determine the competing concerns of people interested in startup development and entrepreneurship by using topic modeling and sentiment analysis on a social question-and-answer (SQA) website. Understanding the underlying concerns of startup entrepreneurs is critical to society and economic growth. Therefore, greater scientific support for entrepreneurship remains necessary, including data mining from virtual social communities. In this study, an SQA platform was used to identify the sentiment of thirty concerns of people interested in startup entrepreneurship. Based on topic modeling and sentiment analysis of 18819 inquiries in various forums on an SQA, we identified additional questions about founder figures, keys to success, and the location of a startup. In addition, we found that general questions were rated more positively, especially when it came to pitching, finding good sources, disruptive innovation, idea generation, and marketing advice. On average, the identified concerns were considered 48.9 percent positive, 41 percent neutral, and 10.1 percent negative. This research establishes a critical foundation for future research and development of digital startups by outlining a variety of different concerns associated with startup development in the digital age.
Public transportation will become highly automated in the future, and at some point, human drivers are no longer necessary. Today many people are skeptical about such scenarios of autonomous public transport (abbr.: APT). In this paper, we assess users’ subjective priority of different factors that lead to personal acceptance or rejection of APT using an adapted online version of the Q-Methodology with 44 participants. We found four prototypical attitudes to which subgroups of participants relate: 1) technical enthusiasts, 2) social skeptics, 3) service-oriented non-enthusiasts, and 4) technology-oriented non-enthusiasts. We provide an unconventional perspective on APT acceptance that helps practitioners prioritize design requirements and communicate, targeting users’ specific attitudes.
This Paper presents a new service-learning setting based on the collaboration of engineering students and people with disabilities. The implementation at a German university is described and first results from two years of experience are shown. The objective of this case study is to show a transferable best practice concept with impact.
Researchers have previously utilized the advantages of a design driven by well-being and intergenerational collaboration (IGC) for successful innovation. Unfortunately, scant information exists regarding barrier dimensions and correlated design solutions in the information systems (IS) domain, which can serve as a starting point for a design oriented toward well-being in an IGC system. Therefore, in this study, we applied the positive computing approach to guide our analysis in a systematic literature review and developed a framework oriented toward well-being for a system with a multi-generational team. Our study contributes to the IS community by providing five dimensions of barriers to IGC and the corresponding well-being determinants for positive system design. In addition, we propose further research directions to close the research gap based on the review outcomes.
Understanding user needs and behavior in automated vehicles (AVs) while traveling is essential for future in-vehicle interface and service design. Since AVs are not yet market-ready, current knowledge about AV use and perception is based on observations in other transportation modes, interviews, or surveys about the hypothetical situation. In this paper, we close this gap by presenting real-world insights into the attitude towards highly automated driving and non-driving-related activities (NDRAs). Using a Wizard of Oz AV, we conducted a real-world driving study (N= 12) with six rides per participant during multiple days. We provide insights into the users’ perceptions and behavior. We found that (1) the users’ trust a human driver more than a system,(2) safety is the main acceptance factor, and (3) the most popular NDRAs were being idle and the use of the smartphone.
Self-driving cars will relief the human from the driving task. Nevertheless, the human might want to intervene in the driving process and thus needs the possibility to control the car. Switching back to fully manual controls is uncomfortable once being passive and engaging in non-driving-related activities. A more comfortable way is controlling the car with elemental maneuvers (e.g., "turn left" or "stop"). Whereas touch interaction concepts exist, contactless interaction through voice and mid-air gestures has not yet been explored for maneuver-based car control. In this paper, we, therefore, compare the general eligibility of voice and mid-air gesture with touch interaction as the primary maneuver selection mechanism in a driving simulator study. Our results show high usability for all modalities. Contactless interaction leads to a more positive emotional perception of the interaction, yet mid-air gestures lead to higher task load. Overall, voice and touch control are preferred over mid-air gestures by most users.
Learning the German language is one of the most critical challenges for refugee children in Germany. It is a prerequisite to allow communication and integration into the educational system. To solve the underlying problem, we conceptualized a set of principles for the design of language learning systems to support collaboration between teachers and refugee children, using a Design Science Research approach. The proposed design principles offer functional and non-functional requirements of systems, including the integration of open educational resources, different media types to develop visual and audio narratives that can be linked to the cultural and social background. This study also illustrates the use of the proposed design principles by providing a working prototype of a learning system. In this, refugee children can learn the language collaboratively and with freely accessible learning resources. Furthermore, we discuss the proposed design principles with various socio-technical aspects of the well-being determinants to promote a positive system design for different cultural and generational settings. Overall, despite some limitations, the implemented design principles can optimize the potential of open educational resources for the research context and derive further recommendations for further research.
Currently, car assistant systems mainly try to prevent accidents. Increasing built-in car technology also extends the potential applications in vehicles. Future cars might have virtual windshields that augment the traffic or individual virtual assistants interacting with the user. In this paper, we explore the potential of an assistant system that helps the car’s occupants to calm down and reduce stress when they experience an accident in front of them. We present requirements from a discussion (N= 11) and derive a system design from them. Further, we test the system design in a video-based simulator study (N= 43). Our results indicate that an accident support system increases perceived control and trust and helps to calm down the user.
Vor dem Hintergrund globaler Vernetzung, Digitalisierung und Big Data geht das Excel-Zeitalter seinem Ende entgegen. Neue Technologien versprechen eine höhere Effizienz und Effektivität des Controllings. Die Veränderungen umfassen dabei alle Aufgabenbereiche des Controllings – allerdings mit unterschiedlicher Geschwindigkeit und differenzierten Lösungsansätzen. Der vorliegende Beitrag untersucht drei Technologien, die im Controlling derzeit besonders stark diskutiert werden: Robotic Process Automation, Predictive Analytics und Künstliche Intelligenz. Im Rahmen eines Forschungsseminars an der Hochschule Ruhr West in Mülheim a.d.R. wurden dazu 57 Führungskräfte aus Controlling und Rechnungswesen befragt. Über 75% der befragten Unternehmen halten die Digitalisierung für wichtig, mehr als die Hälfte (52%) beabsichtigen, eine oder mehrere der drei untersuchten Technologien in den nächsten drei Jahren neu einzusetzen. In den Aufgabenbereichen ist bislang vor allem das Reporting digital unterstützt, in der Strategischen Planung und im Risikomanagement ist dagegen die Digitalisierung gering. Wesentliche Hindernisse sehen die Befragten im fehlenden Know-How und mangelnder Veränderungsbereitschaft.
Globalization and information technology enable people to join the movement of global citizenship and work without borders. However, different type of barriers existed that could affect collaboration in today’s work environment, in which different generations are involved. Although researchers have identified several technical barriers to intergenerational collaboration (iGOAL), the influence of cultural diversity on iGOAL has rarely been studied. Therefore, using a quantitative study approach, this paper investigates the impact of differences in cultural background on perceived technical and operational barriers to iGOAL. Our study reveals six barriers to IGC that are perceived differently by culturally diverse people (CDP) and non-CDP. Furthermore, CDP can foster IGC because CDP consider the barriers to be of less of a reason to avoid working with different generations than do non-CDP.
Why Should the Q-method Be Integrated Into the Design Science Research? A Systematic Mapping Study
(2019)
The Q-method has been utilized over time in various areas, including information systems. In this study, we used a systematic mapping to illustrate how the Q-method was applied within Information Systems (IS) community and proposing towards integration of Q-method into the Design Sciences Research (DSR) process as a tool for future research DSR-based IS studies. In this mapping study, we collected peer-reviewed journals from Basket-of-Eight journals and the digital library of the Association for Information Systems (AIS). Then we grouped the publications according to the process of DSR, and different variables for preparing Q-method from IS publications. We found that the potential of the Q-methodology can be used to support each main research stage of DSR processes and can serve as the useful tool to evaluate a system in the IS topic of system analysis and design
Blended learning offers learning solutions for higher educational institutions facing the industrial revolution 4.0. In this study, we investigated the influence factors student perceptions of blended learning based on gender-specific differences in Indonesia. We applied a research model to systematically assess the effect of design features on the effectiveness of blended learning indicators (intrinsic motivation and student satisfaction). Moreover, we evaluated the research model for both genders separately. Based on the quantitative survey of 223 Indonesian students, our study confirms that the design features significantly influence the effectiveness of blended learning for male and female students.
Process diagnosis is an important method for improving product quality in rolling mills. In addition, the measurement of process variables such as roll gap, cross-sectional area, velocity, and volume flow of the material during production enables the implementation of model-based control concepts to improve product quality. The non-contact speed measurement of hot wire and bar is still a big challenge due to the rough environmental conditions and is solved mainly with optical measuring methods in production. The alternative measurement principle with eddy current sensors presented in this paper enables velocity measurement at locations in a rolling mill where optical measurement methods are not suitable.
We are “not” too (young/old) to collaborate: Prominent Key Barriers to Intergenerational Innovation
(2019)
In this study, we analyzed the barriers to technology-supported intergenerational innovation to understand better how young and old can collaborate towards global innovations. Researchers in different disciplines have already identified various barriers to intergenerational collaboration. However, barriers are changing depending on the context of collaboration, and difficulties still exist to support intergenerational innovation in global settings. Therefore, we investigated the barriers that emerge when people work with someone decades older or younger. The results of our study have shown what barriers are influenced by age, what barriers exist only for senior and younger adults. The study theoretically contributes to deepening the Information Systems (IS) community's understanding of the barriers to intergenerational innovation that need to be considered when developing systems for global innovation
Digital transformation is a process of digitizing the working and living environment in which people are at the center of digitization. In this paper, we present a personas-based guideline for system developers on how the humanization of digital transformation integrates into the design process. The proposed guideline uses the positive personas from the beginning as a basis for the transformation of the working environment into the digital form. We used the literature research as a preliminary study for the process of wellbeing-driven digital transformation design, consisting of questions for structuring the required information in the positive personas as well as a potential method that could be integrated into the wellbeing-based design process.
Im Zentrum dieses Workshops stehen Erkenntnisse zur Mensch-Computer-Interaktion in sicherheitskritischen Anwendungsgebieten. Da in solchen Feldern – etwa Katastrophenmanagement, Verkehr, Produktion oder Medizin – immer häufiger MCI stattfindet, sind viele wissenschaftliche Gebiete, unter anderem die Informatik, zunehmend gefragt. Die Herausforderung besteht darin, bestehende Ansätze und Methoden zu diskutieren, anzupassen und innovative Lösungsansätze zu entwickeln.
RELEVANCE & RESEARCH QUESTION: Currently the effectiveness of Virtual Reality (VR) and Augmented Reality (AR) systems as practice teaching methods are virtually uncharted. The proof that these systems can provide the same or better learning outcomes than a text instructed practical task could represent a significant benefit for educational activities. METHODS & DATA: To fathom the effectiveness, an experimental study with the three conditions (VR, AR and a real setup) were used to teach participant how to assemble a standard computer. Each condition was divided into two parts: part one in which participants were confronted with their specific scenario, part two in which participants had to go through a real practice after one week. The learning outcome was determined by the designation of hardware parts, a quiz that queried their function and the correct assembling of the components in addition to needed time. Apart from the mere performance, the acceptance of such application in academic context and difference in evaluation by men and women were of interest. RESULTS: Results concerning the Learning Outcome showed that participants from the VR condition outperformed those learned from the real setup ((M=10.0, SD=0.0) [virtual reality] vs. (M=8.95, SD=1.27) [control]). Furthermore, results from the assembling duration assessment demonstrated that VR Group Participants completed their tasks 6.62% faster than the control group. Regarding the identification of Hardware Parts, both groups scored a significant improvement during the post condition compared to the first test run, indicating a learning progress. However, due to the VR group achieving a better outcome in average answers and a more significant difference between the trials, the results indicate a better performance by participants assigned to the VR condition. ADDED VALUE: The results revealed that VR and AR systems could exceed text-based approach in terms of learning outcome performance. The effectiveness of the systems implicates a major benefit for the educational landscape, as learning content that is not realizable in terms of cost, distance or logistics could be designed as an immersive and engaging experience.
For highly automated vehicles (AVs), new interaction concepts need to be developed. Even in AVs, the driver might want to intervene and override the automation from time to time. To create the possibility of control, we explore vehicle control through maneuver-based interventions (MBI). Thereby, we focus on explicit, contact-less interaction, which could be beneficial in future AV designs, where the driver is not necessarily bound to classical controls. We propose a set of freehand gestures and keywords for voice control derived in a user-centered design process. Further, we discuss properties, applicability and user impressions of both interaction modalities. Voice control seems to be an efficient way to select a maneuver and free-hand gestures could be used, if voice channel is blocked, e.g., through conversation with passengers.
The uprising levels of autonomous vehicles allow the drivers to shift their attention to non-driving tasks while driving (ie, texting, reading, or watching movies). However, these systems are prone to failure and, thus, depending on human intervention becomes crucial in critical situations. In this work, we propose using human actuation as a new mean of communicating take-over requests (TOR) through proprioception. We conducted a user study via a driving simulation in the presence of a complex working memory span task. We communicated TORs through four different modalities, namely, vibrotactile, audio, visual, and proprioception. Our results show that the vibrotactile condition yielded the fastest reaction time followed by proprioception. Additionally, proprioceptive cues resulted in the second best performance of the non-driving task following auditory cues.
Even though many aspects of automated driving have not yet become reality, many human factors issues have already been investigated. However, recent discussions revealed common misconceptions in both research and society about vehicle automation and the levels of automation levels. This might be due to the fact that automated driving functions are misnamed (cf. Autopilot) and that vehicles integrate functions at different automation levels (L1 lane keeping assistant, L2/L3 traffic jam assist, L4 valet parking). The user interface is one of the most critical issues in the interaction between humans and vehicles--and diverging mental models might be a major challenge here. Today's (manual) vehicles are ill-suited for appropriate HMI testing for automated vehicles. Instead, virtual or mixed reality might be a much better playground to test new interaction concepts in an automated driving setting.
Velocity Approximation of Hot Steel Rods Using Frequency Spectroscopy of the Cross-Section Area
(2019)
In this work, an approach for velocity approximation of hot steel rods based on frequency spectroscopy is presented. For this purpose, a sensor already implemented in a rolling mill for measuring the cross-sectional area of the rolling stock is used to obtain information about the velocity of the hot rods. Moreover, the effect of forward slip is briefly discussed.
Die breite Einführung autonomer Fahrzeuge, ob für den Individualverkehr oder auch den öffentlichen Nahverkehr, ist nur noch eine Frage der Zeit. Dies bedeutet unweigerlich, dass in absehbarer Zeit alle Verkehrsteilnehmer*innen mit dieser Art von Fahrzeugen in Berührung kommen werden. In diesem Artikel soll diskutiert werden, wie Ansätze des Positive Computing helfen können, die Ausgestaltung der automatisierten Fahrzeuge so vorzunehmen, dass sie zum Wohlbefinden der Menschen in Verkehrssituationen beitragen.
In the field of producing hot-rolled steel bars and wires, hot rolling mills are incomplete or barely equipped with measuring technology for recording relevant process parameters. Therefore, there is a big potential to increase product quality and to decrease costs and scrap by improving process control establishing new sensor systems. One of these crucial parameters is the roll gap,which is investigated as part of the research project PIREF. In this paper an experimental setup for examining the roll gap during a rolling process is presented and based on these results different sensor arrangements are discussed.
Relax yourself - Using Virtual Reality to enhance employees mental health and work performance
(2019)
This paper presents work-in-progress aiming to develop an actively adapting virtual reality (VR) relaxation application. Due to the immersive nature of VR technologies, people can escape from their real environment and get into a relaxing state. Goal of the application is to adapt to the users' physiological signals to foster the positive effect. Until now, a first version of the VR application was constructed and is currently evaluated in an experiment. Preliminary results of this study demonstrate that people appreciate the immersion into the virtual environment and escape from reality. Moreover, participants highlighted the option to adapt users' needs and preferences. Based on the final study data, the constructed application will be enhanced with regard to adoption and surrounding factors.
Enabling decentral collaborative innovation processes -a web based real time collaboration platform
(2018)
The main goal of this paper is to define a collaborative innovation process as well as a supporting tool. It is motivated through the increasing competition on global markets and the resultant propagation of decentralized projects with a high demand of innovative collaboration in global contexts. It bases on a project accomplished by the author group. A detailed literature review and the action design research methodology of the project led to an enhanced process model for decentral collaborative innovation processes and a basic realization of a browser based real time tool to enable these processes.The initial evaluation in a practical distributed setting has shown that the created tool is a useful way to support collaborative innovation processes.
Quality and dimensional accuracy of hot rolled steel rods depend on several process parameters. In fact many of these crucial parameters are not be sufficiently determined yet. By improving automation and process control costs and scrap of production can be decreased. As part of the research project PIREF, one of these parameters – the roll gap – is under investigation beside other topics. Before starting rolling, the roll gap is typically set to a fixed value according to the planed dimensions of the product, but the forces during the rolling of the rod cause an enlargement of the roll gap. In which way the rolls change their position and form shall be examined in our research project. Therefore a first experimental setup has been built up to determine the change in position of the rolls under applied force. This is realized by a pot core coil as sensor using impedance analysis. The first results are presented in this work as a proof-of-principle.
System design for well-being needs an appropriate tool to help designers to determine relevant requirements that can help human well-being to flourish. Personas come as a simple yet powerful tool in the early development stage of the user interface design. Considering well-being determinants in the early design process provide benefits for both the user and the development team. Therefore, in this short paper, we performed a literature study to provide a conceptual model of well-being in personas and propose positive design interventions in personas’ creation process.
Automotive user interfaces and, in particular, automated vehicle technology pose a plenty of challenges to researchers, vehicle manufacturers, and third-party suppliers to support all diverse facets of user needs. To give an example, they emerge from the variation of different usergroups ranging from inexperienced, thrill-seeking young novice drivers to elderly drivers with all their natural limitations. To allow assessing the quality of automotive user interfaces and automated driving technology already during development and within virtual test processes, the proposed workshop is dedicated to the quest of finding objective, quantifiable quality criteria for describing future driving experiences. The workshop is intended for HCI, AutomotiveUI, and “Human Factors" researchers and practitioners as well for designers and developers. In adherence to the conference main topic “Spielend einfach interagieren “, this workshop calls in particular for contributions in the area of human factors and ergonomics (user acceptance, trust, user experience, driving fun, natural user interfaces, etc.) and artificial intelligence (predictive HMIs, adaptive systems, intuitive interaction).
Automotive user interfaces and automated vehicle technology pose numerous challenges to support all diverse facets of user needs. These range from inexperienced, thrill-seeking, young novice drivers to elderly drivers with a mostly opposite set of preferences together with their natural limitations. To allow assessing the (hedonic) quality of automotive user interfaces and automated driving technology (i. e., UX) already during development, the proposed workshop is dedicated to the quest of finding objective, quantifiable criteria to describe future driving experiences. The workshop is intended for HCI, AutomotiveUI, and “Human Factors” researchers and practitioners as well for designers and developers. In adherence to the conference main topic “Interaktion – Verbindet – Alle”, this workshop calls in particular for contributions in the areas of human factors and ergonomics (user acceptance, trust, user experience, driving fun, natural user interfaces, etc.) with focus on hedonic quality and design of user experience to enhance the safety feeling in ADS.
Industry 4.0 is known as the fourth industrial revolution which refers to the integration of technologies that make the factories interoperable by seamlessly connecting machines, employees and sensors for communication. In Industry 4.0, one of the key features is the use of new technologies to recognize the current context. Thus, the employees are supported with contextual information for speeding up decision-making during various processes related to planning, production, maintenance, etc. As a contribution to this area, the work described here aims to introduce a cyber-physical system (CPS) approach to provide context-based and intelligent support to employees in heavy industries using new technologies, especially in the field of mobile devices. In this work, mobile device sensors and image processing techniques are used to recognize the context which requires specific support. In addition, new scenarios and associated processes are developed to support the employees on the basis of new, flexible, adaptive and mobile technologies.
The adoption of Open Educational Resources (OER) can support collaboration and knowledge sharing. One of the main areas of the usage OER is the internationalization, i.e., the use in a global context. However, the globally distributed co-creation of digital materials is still low. Therefore, we identify essential barriers, in particular for co-authoring of OER in global environments. We use a design science research method to introduce a barrier framework for co-authoring OER in global settings and propose a wellbeing-based system design constructed from the barrier framework for OER co-authoring tool. We describe how positive computing concepts can be used to overcome barriers, emphasizing design that promotes the author's sense of competence, relatedness, and autonomy.
Durch den technischen Fortschritt in der Spracherkennung und -verarbeitung wird Sprache als Interaktionsform auch in Fahrzeugen, z.B. zur Bedienung von Infotainmentsystem, immer populärer. Die Steuerung von teilautomatisierten Fahrzeugen über Sprache ist bisher wenig erforscht. Ziel dieser Arbeit ist es unter der grundsätzlichen Annahme der Eignung von Sprachsteuerung für teilautonome Fahrzeuge, Nutzererwartungen und spezielle Anforderungen an eine Sprachsteuerung für die grundlegenden Fahrmanöver zu identifizieren. Aus den Ergebnissen eines Expertenworkshops und einer explorativen Videostudie werden Anforderungen und Sprachkommandos abgeleitet.
Öffentliche Diskussionen zum autonomen Fahren zeigen einen hohen Anspruch, dass die Algorithmen in kritischen Fällen Entscheidungen nach ethischen Kriterien fällen. Diese für die Vielzahl von denkbaren Verkehrssituationen so zu erfassen, dass sie den Vorstellungen eines größten Teils der Bevölkerung entspricht, stellt eine große methodische Herausforderung dar. In dieser Arbeit wird untersucht, in wie weit eine überlegte Entscheidung mit dem Verhalten in einem Fahrsimulator übereinstimmt. Dabei wird bei einem großen Teil der Teilnehmer:innen ein Widerspruch zwischen geäußertem beabsichtigtem Handeln und tatsächlichem Handeln offenbar.
Rolling mills are continually improved and opti-mized by implementing innovative technology to decrease costs and scrap. Despite of the progressive automation and experience, some important process parameters can still not be determined with sufficient accuracy. As part of the research project PIREF, the velocity of the hot rolled rod shall be measured by using im-pedance analysis to estimate the volumetric flow rate of the mate-rial. For a high accuracy measurement of the impedance, a pow-erful VNA is used. To minimize errors in the measurement, caused by e.g. temperature drift, a correction of the measurement fre-quency is needed. This must be achieved without recalibration of the VNA to avoid faulty behavior of the online control. To solve this problem, an approach based on a polynomial regression is presented in this work.
Relevance & Research Question: Smartphones have become an integrated part in everyday life facilitating communication, information access, entertainment and organization anytime and anywhere. However, the omnipresence of such devices can evoke psychological dependencies and the need of being always connected resulting in discomfort when the smartphone is not accessible. While few studies have found heightened anxiety during smartphone absence (e.g. Cheever, Rosen, Carrier, & Chavez, 2014), such research is scarce. Therefore, we aimed at expanding existing research asking whether the mere imagination of smartphone absence suffices to trigger anxiety and affect user’s context evaluations.
A self-driving car that operates on the SAE automation level 3 or 4 can navigate through different traffic conditions without human input. If such a system is on its operating limits, it will emit a takeover request before shutting down. This request will likely generate a physical response of the driver. Our goal is to shed light on the stress perception of drivers in various scenarios. To this end, we have carried out a feasibility study for preparation. Two subjects drove an autonomous vehicle and during the ride ECG signals were recorded, and afterwards evaluated. Unfortunately, the stress reaction to takeover requests could not be investigated, due to the poor function of the autonomous driving mode from the vehicle, however the reaction to autopilot misconduct without warning to the driver could be investigated instead.
Wissensmanagement (WM) und IT-gestütztes Lernen sind gerade in kleinen Behörden der Öffentlichen Verwaltung (ÖV), wie z.B. in ländlichen
Gemeinden, noch ausbaufähig. Am Beispiel des EU-Projekts EAGLE werden
Projektergebnisse als Verbesserungsansätze für ein arbeitsprozessorientiertes, IT-gestütztes Lernen vorgestellt. Neuartige Plattform-Features und ihr ÖV-spezifischer Nutzen werden erläutert. Die Ergebnisse der Plattformvalidierung werden vorgestellt. Ferner werden Vorschläge gemacht, wie die Ergebnisse aus EAGLE mit WM und weiteren Wissensquellen der ÖV, wie z.B. der Registratur, zu einem Gesamtkonzept mit bereits vorhandenen Fortbildungs- und WM-Ansätzen verbunden werden können.
We present a pipeline for recognizing dynamic freehand gestures on mobile devices based on extracting depth information coming from a single Time-of-Flight sensor. Hand gestures are recorded with a mobile 3D sensor, transformed frame by frame into an appropriate 3D descriptor and fed into a deep LSTM network for recognition purposes. LSTM being a recurrent neural model, it is uniquely suited for classifying explicitly time-dependent data such as hand gestures. For training and testing purposes, we create a small database of four hand gesture classes, each comprising 40 × 150 3D frames. We conduct experiments concerning execution speed on a mobile device, generalization capability as a function of network topology, and classification ability ‘ahead of time’, i.e., when the gesture is not yet completed. Recognition rates are high (>95%) and maintainable in real-time as a single classification step requires less than 1 ms computation time, introducing freehand gestures for mobile systems.
Web based security applications have become increasingly important in the past years. Especially in times of blockchain based crypto currencies, user authentication is a critical aspect for the overall security, integrity and acceptance of such systems. While blockchain technologies provide a decentralized approach, the client side still largely relies on centralized security approaches. Those centralized approaches are easier to implement, but at the same time bear the risk of usual security flaws. Therefore, this paper presents a decentralized approach for increasing the security by adding a decentralized two-factor authentication mechanism to the execution of
operations.
In recent times, a lot of attacks against central server infrastructures have been recognized. Those infrastructures have seen attacks ranging from attacks against Internt of Things (IoT) infrastructures, via attacks against public infrastructure to attacks against cryptocurrency exchanges and blockchain based infrastructures themselves, e.g., the already almost legendary Decentralized Autonomous Organization (DAO) hack. Measured by press coverage, attacks against cryptocurrency exchanges and infrastructures seem to be among the most prominently reported attacks, probably due to the large amount of money that is stolen during those attacks and the great (but obviously still quite risky) potential (and financial involvement) of the blockchain technology. Naturally, attacks like the ones we have seen recently in crease the notion of uncertainty of blockchain technologies among the people,mreflected in lower values of cryptocurrencies in general. Obviously, this demands for an overall increase of security of cryptocurrency based technologies. Therefore, this paper provides an architectural approach, based on a proxy,to increase security of publicly available nodes of a blockchain based technology. Furthermore, it provides a first evaluation of the approach based on the results of an extensive community test of a new cryptocurrency.
In this contribution we present a novel approach to transform data from time-of-flight (ToF) sensors to be interpretable by Convolutional Neural Networks (CNNs). As ToF data tends to be overly noisy depending on various factors such as illumination, reflection coefficient and distance, the need for a robust algorithmic approach becomes evident. By spanning a three-dimensional grid of fixed size around each point cloud we are able to transform three-dimensional input to become processable by CNNs. This simple and effective neighborhood-preserving methodology demonstrates that CNNs are indeed able to extract the relevant information and learn a set of filters, enabling them to differentiate a complex set of ten different gestures obtained from 20 different individuals and containing 600.000 samples overall. Our 20-fold cross-validation shows the generalization performance of the network, achieving an accuracy of up to 98.5% on validation sets comprising 20.000 data samples. The real-time applicability of our system is demonstrated via an interactive validation on an infotainment system running with up to 40fps on an iPad in the vehicle interior.
Applying step heating thermography to wind turbine rotor blades as a non-destructive testing method
(2017)
Anonymity-preserving Methods for Client-side Filtering in Position-based Collaboration Approaches
(2017)
Increasing economic viability and safety through structural health monitoring of wind turbines
(2017)
Serious accidents with property damage or even human casualties, result from structural flaws in wind turbine rotor blades. Common maintenance practices result in long downtimes and do not lead to the required results. Therefore, the Ruhr West University of Applied Sciences and the iQbis Consulting GmbH, currently research a new structural health monitoring method for wind turbine rotor blades. The goal of this project is to build a sensor system that can detect structural weaknesses inside of rotor blades without the need of downtime for industrial climbers. This technology has the potential to prevent accidents, save lives, extend the useful life of wind turbines and optimize the production of green energy.
Checking wind turbines for damage is a common problem for operators of wind parks, as regular inspections are legally required in many countries and prevention is economically viable. While some of the common forms of damage are easily visible on the surface, structural problems can remain invisible for years before they eventually result in catastrophic failure of a rotor blade. Common forms of testing fibre composite parts like ultrasonic testing or X-ray tests are impractical due to the large dimensions of wind turbine components and their limited accessibility for any short-range methods. Active thermographic inspection of wind turbines is a promising approach to testing for structural flaws beneath the surface of rotor blades. As part of an ongoing research project, a setup for testing the general viability of this method was built and used to compare different thermographic cameras. A sample cut from a discarded rotor blade was modified to emulate structural damage. The results are promising for the development of a cost effective on-site testing system.
Process Monitoring in Steel-Mills using Impedance Analysis: VNA Improvement for Data Acquisition
(2017)
The process automation extends over every manufacturing step of a product in the steel-mill to increase the quality, quantity and energy efficiency. The product dimensions are an important part of the quality control; these must maintain the specified tolerances. Additional to the cross-sectional-area, the measured data contains much more information about the manufacturing process, e.g. eccentricity, condition of the rolls and defects of the rod. For analyzing the measured data and to gather more information about the manufacturing process it is necessary to increase the speed of the data acquisition by performing some modifications of the VNA, e.g. faster analog to digital converter and microcontroller, improved firmware and optimized values of the passive electrical components for faster time constants and transient responses.
Automotive user interfaces and, in particular, automated vehicle technology pose a plenty of challenges to researchers, vehicle manufacturers, and third-party suppliers to support all diverse facets of user needs. To give an example, they emerge from the variation of different user groups ranging from inexperienced, thrill-seeking young novice drivers to elderly drivers with all their natural limitations. To allow assessing the quality of automotive user interfaces and automated driving technology already during development and within virtual test processes, the proposed workshop is dedicated to the quest of finding objective, quantifiable quality criteria for describing future driving experiences. The workshop is intended for HCI, AutomotiveUI, and "Human Factors" researchers and practitioners as well for designers and developers. In adherence to the conference main topic "Spielend einfach interagieren" this workshop calls in particular for contributions in the area of human factors and ergonomics (user acceptance, trust, user experience, driving fun, natural user interfaces etc.) and artificial intelligence (predictive HMIs, adaptive systems, intuitive interaction).
The detection of soil erosion processes in dams, hydraulic heave failure or corrosion processes of reinforcing steel in concrete are a small selection of measuring applications in civil engineering where the impedance analysis can be used to determine the measurand. Those measuring applications are having high requirements for the measuring hardware. For example a common interface for fast data exchange, high resolution, independent functionality and easy customizability to suit the measuring application. For that reason, a well-known application for steel-mill process monitoring can be used as a development platform. This hardware platform is based on a vector network analyzer and is meeting the requirements mainly. However, a couple of modifications has to be made, like replacing the ADC for a higher sample rate, Ethernet for easy and fast data exchange and the microcontroller for more calculation power.
Practical application of object detection systems, in research or industry, favors highly optimized black box solutions. We show how such a highly optimized system can be further augmented in terms of its reliability with only a minimal increase of computation times, i.e. preserving realtime boundaries. Our solution leaves the initial (HOG-based) detector unchanged and introduces novel concepts of non-linear metrics and fusion of ROIs. In this context we also introduce a novel way of combining feature vectors for mean-shift grouping. We evaluate our approach on a standarized image database with a HOG detector, which is representative for practical applications. Our results show that the amount of false-positive detections can be reduced by a factor of 4 with a negligable complexity increase. Although introduced and applied to a HOG-based system, our approach can easily be adapted for different detectors.
Touch versus mid-air gesture interfaces in road scenarios-measuring driver performance degradation
(2016)
We present a study aimed at comparing the degradation of the driver's performance during touch gesture vs mid-air gesture use for infotainment system control. To this end, 17 participants were asked to perform the Lane Change Test. This requires each participant to steer a vehicle in a simulated driving environment while interacting with an infotainment system via touch and mid-air gestures. The decrease in performance is measured as the deviation from an optimal baseline. This study concludes comparable deviations from the baseline for the secondary task of infotainment interaction for both interaction variants. This is significant as all participants are experienced in touch interaction, however have had no experience at all with mid-air gesture interaction, favoring mid-air gestures for the long-term scenario.
Die spezifischen Herausforderungen des Fachgebiets bedürfen jedoch auch weiterhin einer Diskussion und der Entwicklung neuer Methoden und Ansätze zur Gestaltung von Informationssystemen. Diese sollen dieses Jahr adressiert werden. Generell fokussieren wir eher auf die Effekte von Technologien auf realweltliche Praktiken, als auf die isolierte Technologie. Auch der auf diesen Beiträgen basierende Workshop legt aktuelle Entwicklungen und Fragestellungen offen und gibt neue Impulse für das Forschungsgebiet. Der Workshop wird dabei zweigeteilt gestaltet: Innerhalb des ersten Teils wird den Vortragenden die Möglichkeit gegeben die eigenen Forschungsarbeiten zu präsentieren. Dabei sind sowohl designorientierte, praxisbasierte Analysen und Studien, als auch entwickelte und evaluierte Prototypen neuer Technologien von Interesse. Es wird den Vortragenden die Möglichkeit gegeben die eigenen Forschungsarbeiten teilweise in einem eher frühen Stadium in kompakter Form zu präsentieren und anschließend in Hinblick auf deren Weiterentwicklung diskutieren.
We present a publicly available benchmark database for the problem of hand posture recognition from noisy depth data and fused RGB-D data obtained from low-cost time-of-flight (ToF) sensors. The database is the most extensive database of this kind containing over a million data samples (point clouds) recorded from 35 different individuals for ten different static hand postures. This captures a great amount of variance, due to person-related factors, but also scaling, translation and rotation are explicitly represented. Benchmark results achieved with a standard classification algorithm are computed by cross-validation both over samples and persons, the latter implying training on all persons but one and testing on the remaining one. An important result using this database is that cross-validation performance over samples (which is the standard procedure in machine learning) is systematically higher than cross-validation performance over persons, which is to our mind the true application-relevant measure of generalization performance.
Given the success of convolutional neural networks (CNNs) during recent years in numerous object recognition tasks, it seems logical to further extend their applicability to the treatment of three-dimensional data such as point clouds provided by depth sensors. To this end, we present an approach exploiting the CNN’s ability of automated feature generation and combine it with a novel 3D feature computation technique, preserving local information contained in the data. Experiments are conducted on a large data set of 600.000 samples of hand postures obtained via ToF (time-of-flight) sensors from 20 different persons, after an extensive parameter search in order to optimize network structure. Generalization performance, measured by a leave-one-person-out scheme, exceeds that of any other method presented for this specific task, bringing the error for some persons down to 1.5 %.
In catastrophic events, the potential of help has grown through new technologies. Voluntary help has many forms. Within this paper different categories of voluntary help are suggested. Those categories are based on properties like organizational structures, helping process, kind of prosocial behavior and many more. A focus is clearly on the organizational structure and motivational aspects of helper groups. Examples are given for each category. The categorization’s aim is to give a brief overview of possible properties a group of system users could have.
We present a light-weight real-time applicable 3D-gesture recognition system on mobile devices for improved Human-Machine Interaction. We utilize time-of-flight data coming from a single sensor and implement the whole gesture recognition pipeline on two different devices outlining the potential of integrating these sensors onto mobile devices. The main components are responsible for cropping the data to the essentials, calculation of meaningful features, training and classifying via neural networks and realizing a GUI on the device. With our system we achieve recognition rates of up to 98% on a 10-gesture set with frame rates reaching 20Hz, more than sufficient for any real-time applications.
This contribution presents a novel approach of utilizing Time-of-Flight (ToF) technology for mid-air hand gesture recognition on mobile devices. ToF sensors are capable of providing depth data at high frame rates independent of illumination making any kind of application possible for in- and outdoor situations. This comes at the cost of precision regarding depth measurements and comparatively low lateral resolution. We present a novel feature generation technique based on a rasterization of the point clouds which
realizes fixed-sized input making Deep Learning approaches applicable using Convolutional Neural Networks. In order to increase precision we introduce several methods to reduce noise and normalize the input to overcome difficulties in scaling. Backed by a large-scale database of about half
a million data samples taken from different individuals our
contribution shows how hand gesture recognition is realiz-
able on commodity tablets in real-time at frame rates of up to 17Hz. A leave-one out cross-validation experiment
demonstrates the feasibility of our approach with classification errors as low as 1,5% achieved persons unknown to the model.
Open Educational Resources (OER) intend to support access to education for everyone. However, this potential is not fully exploited due to various barriers in the production, distribution and the use of OER. In this paper, we present requirements and recommendations for systems for global OER authoring. These requirements as well as the system itself aim at helping creators of OER to overcome typical obstacles such as lack of technical skills, different types of devices and systems as well as the cultural differences in cross-border-collaboration. The system can be used collaboratively to create OER and supports multi-languages for localization. Our paper contributes to facilitate global, collaborative e-Learning and design of authoring platforms by identifying key requirements for OER authoring in a global context.
The paper provides a contextualization process to adapt Open Knowledge Resources for the need of public administrations. By help of a matching strategy, culture and context profiles of learners and learning resources are compared. The comparison allows to draw inferences how to contextualize an open knowledge resource for own learning needs. An example is illustrated and future research fields are proposed.
Gestures are part of the interaction between humans and are currently getting more and more popular in the field of Human-Machine Interaction (HMI). First systems with mid-air gesture control are available in the automotive field of application. But it is still an open question which gestures are intuitive for the users, standards do not exist. In this paper we present a 2-step user study on expectations on touchless gestures in vehicles as part of a participatory design process.
In recent years, hardware for the production and consumption of virtual reality content has reached level of prices that make it affordable to everyone. Accordingly schools and universities are showing increased interest in implementations of virtual reality technologies for supporting their innovative educational activities. Hence, this paper presents a flexible architecture for supporting the development of virtual reality learning scenarios conveniently deployed for educational purposes. We also suggest an example of such
educational scenario for medical purposes deployable with the suggested architecture. In addition, we developed and used a questionnaire answered by 17 medical students in order to derive additional requirements for refining such scenarios. Then, we present these efforts while aiming at deployments usable also for additional domains. Finally, we summarize and mention aspects we will address
in our coming efforts while deploying such activities.
5th Workshop Automotive HMI
(2016)
Benutzerschnittstellen im Fahrzeug stellen eine besondere Herausforderung in Konzeption und Entwicklung dar, steht doch eine sichere Bedienung in allen Fahrsituationen von Fahrerassistenzsystemen wie auch Komfort- und Unterhaltungsfunktionen im Vordergrund. Zugleich treffen durch zunehmende Vernetzung die langen Entwicklungszyklen von Kraftfahrzeugen auf die hochdynamische Welt von Mobiltelefonen und Internet. Ein- und Ausgabetechnologien gehören des Weiteren zu den zentralen Mitteln der Hersteller, die Wertigkeit der im Fahrzeug eingebauten Systeme hervorzuheben. Passend zu dem Tagungsmotto „Sozial Digital – Gemeinsam Auf Neuen Wegen“ wurden in diesem Workshop insbesondere Arbeiten und Visionen präsentiert, die das Automobil bzw. HMIs im Fahrzeug als Teil einer vernetzten digitalen Welt verstehen – einer neuen Art eines sozialen Mensch-Maschine Ökosystems. Die zentrale Frage, die im Workshop diskutiert wurde war, wie Systeme in Zukunft aussehen müssen, um sowohl den Menschen als auch die Maschine optimal zu unterstützen (angelehnt an das MABA-MABA Paradigma von Fitts, 1954). Der Workshop war wiederum interdisziplinär aufgesetzt und hat Konzepte und technische Lösungen von und mit Designern, Entwicklern und „Human Factors“-Experten aus Universitäten/Hochschulen, Forschungsinstituten und der Automobilindustrie aus ganzheitlicher Sicht diskutiert.
Immer mehr ältere Menschen leben von ihren Angehörigen getrennt und können über Kommunikationsmedien wie Telefon und Skype nur eingeschränkt gemeinsame Erlebnisse erzeugen. In diesem Paper wird die technische Umsetzung eines Konzeptes vorgestellt, das es Familienmitgliedern ermöglicht über das Internet gemeinsam „Mensch-ärgere-dich-nicht“ zu spielen. Durch Videotelefonie und eine besondere Anordnung der Hardware werden die Spieler trotz räumlicher Trennung virtuell an einen Tisch gebracht und dadurch ein gemeinsames Erlebnis erzeugt. Die Clientanwendung wird dabei als plattformunabhängiger Webservice und die Videotelefonie mittels verschiedener Standards und Server realisiert.
4. Workshop Automotive HMI
(2015)
Benutzerschnittstellen im Fahrzeug stellen eine besondere Herausforderung in Konzeption und Entwicklung dar, steht doch eine sichere Bedienung in allen Fahrsituationen sowohl von Fahrerassistenzsystemen als auch von Komfort-und Unterhaltungsfunktionen im Vordergrund. Zugleich treffen durch zunehmende Vernetzung die langen Entwicklungszyklen von Kraftfahrzeugen auf die hochdynamische Welt von Mobiltelefonen und Internet. Ein-und Ausgabetechnologien gehören des Weiteren zu den zentralen Mitteln der Hersteller, die Wertigkeit der im Fahrzeug eingebauten Systeme hervorzuheben und sich gegenüber der Konkurrenz abzuheben. Dafür werden in diesem Workshop Konzepte und technische Lösungen von Designern, Entwicklern und Human Factors Experten aus Hochschulen, Forschungsinstituten und der Automobilindustrie vorgestellt und diskutiert.
In this demo paper we present a new visualization technique for dynamic networks. It displays the time slices of the dynamic network using two dimensional graph layouting algorithms and stacks these in the third dimension to show the development over time. The visualization ensures that the same node always has the same position in each time slice so that it is easy to follow its development. It also allows filtering data and influencing node appearance based on properties. Additionally we offer a two dimensional comparison view for two time slices which highlights changes in graph structure and (if available) in measures of nodes. The presented visualization technique is implemented using Web technology and is available in a Web-based analytics workbench. We demonstrate the benefits of these techniques by an analysis of a data set from a learning community.
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.
In the field of magnetic inductance tomography,
signal processing is a real challenge. This is due to the divergent
nature of magnetic fields. The sensitivity, i.e. the change in the
receiving signal by means of an electrically conductive sample
in a measuring volume depends strongly on the positioning
of the sample. Objects that are located near the transmitting
or receiving coils are very well locatable, where objects in
larger distance are hard to detect. In this paper an approach
is presented that improves the topology of the magnetic fields
in the ”magnetic induction tomography” (MIT) by changing
geometric constructions and current patterns of coils so far,
as to allow a sharper localization of objects within the space.
The aim is to level the distribution of the sensitivity in the
measuring volume, so that electrically conductive objects with
a larger distance between transmitting and receiving unit can
be detected with almost the same signal intensity as objects
close to the transmitting and receiving unit. The simulation tool
Comsolic is used for the geometric modeling making a finite
element analysis (FEA). The subsequent signal processing and
analysis of the simulation results are implemented in Matlabic .
Within this FEA the coil geometries and current patterns are
changed numerically, so that the minimum object size, that is
still detectable, is, compared to the known MIT, reduced and the
sensitivity of the system is improved. To validate the simulation in
Comsolic , first simulation results are compared with analytical
models and analyses.
Detection of influential actors in social media plays an important role for increasing the quality and efficiency of work and services in many fields such as education, marketing, etc. This work aims to introduce a new approach for the characterization of influential actors in online social media, such as Twitter. We present on a model of influence of an actor that is based on the attractiveness of the actor in terms of the number of other new actors with which he or she has established relations over time. We have used this concept and measure of influence to determine optimal seeds in a simulation of influence maximization using two empirically collected social networks for the underlying graphs.
In this paper we present an approach for People-to-People recommendations based on a Rich Context Model (RCM). We consider personal user information as contextual information used for our recommendations. The evaluation of our recommendation approach was performed on a social network of students. The obtained results do show a significant increase in performance while, at the same time, a slight increase in quality in comparison to a manual matching process. The proposed approach is flexible enough to handle different data types of contextual information and easy adaptable to other recommendation domains.
Why do barriers to the exchange of open knowledge resources change in public administrations? Experts in the public sector have been interviewed and outlined antecedents of change to certain barriers. The results are an initial step towards theorizing on barrier change and stepping beyond the current trend of categorizing difficulties to e-Learning and use of open knowledge resources. Categorizing only shows the range of potential challenges. Whether and how the barriers change, however, is seldom addressed in previous literature. The results presented in this study thus provide a new perspective on the phenomenon. Results are part of a longitudinal study about open e-Learning in the public sector across four European countries. They will provide fresh empirical input for discussions at the World Conference on E-Learning how to advance future research and practices in the domain
Die Entwicklung von vollautomatisierten Fahrzeugen wird in der gesellschaftlichen Diskussion immer präsenter. Wichtig für die Durchsetzung und verbreitete Nutzung dieser technischer Neuerungen ist jedoch vor allem die Akzeptanz der Bevölkerung – in diesem Fall nicht nur die der potenziellen KäuferInnen sondern auch die der übrigen Verkehrs-teilnehmenden. Vorgestellt wird eine explorative Online-Studie zur Akzeptanz von auto-nomen Fahren basierend auf quantitativen und qualitativen Daten einer Stichprobe von N = 89. Die Ergebnisse zeigen unter anderem eine geringe Vertrautheit mit dem Thema, ein vergleichsweise ausgeprägtes Vertrauen aber eine geringe Nutzungsabsicht.
Der Bedarf an feuerverzinkten Stahlbändern ist besonders in der Automobilindustrie sehr groß und es werden zugleich immer höhere Qualitäten gefordert. Hierbei bildet vor allem die Homogenität der Zinkschichtdicke ein entscheidendes Qualitätsmerkmal. Um das Stahlband ausreichend vor Umwelteinflüssen zu schützen, muss eine, vom Kunden spezifizierte, Mindestzinkschichtdicke aufgetragen werden. Beim hier angewandten Verzinkungsverfahren durchläuft das Band ein Zinkbad und anschließend wird das überschüssige Zink berührungs-los mittels sogenannten Abblasdüse so abgetragen, sodass eine möglichst homogene Zinkschicht erhalten bleibt. Hierzu ist es notwendig den Abstand zwischen Band und Airknife konstant zu halten. Störende Bandbewegungen führen zu inhomogene Zinkschichtdicken, welche die Qualität der Verzinkung vermindern. Diese Qualitätsverminderung und der erhöhte Zinkeinsatz soll durch geeignete Maßnahmen verringert werden. Bisher eingesetzte berührungslose Bandstabilisatoren können die Bandbewegung im Allge-meinen dämpfen, jedoch treten noch Betriebszustände auf, in denen eine inhomogene Zinkschicht sichtbar ist. Die Ursache dieser Inhomogenitäten liegt in anlagenbedingten dominanten Schwingungen des Bandes, deren Ursache zu klären ist. Im vorliegenden Beitrag wird ein Modell der Bandbewegung vorgestellt, das durch die theore-tische Modellbildung und experimentelle Identifikation erstellt worden ist. Das Modell beschreibt die Bewegung des Bandes bezüglich ausgewählter Freiheitsgrade und ermöglicht die Analyse der kritischen Betriebszustände. Darüber hinaus soll dieses Modell zur Stabilisierung des Bandes in einer modellgestützten Reglung verwendet werden.
As smart homes are being more and more popular, the needs of finding assisting systems which interface between users and home environments are growing. Furthermore, for people living in such homes, elderly and disabled people in particular and others in general, it is totally important to develop devices, which can support and aid them in their ordinary daily life. We focused in this work on sustaining privacy issues of the user during a real interaction with the surrounding home environment. A smart person-specific assistant system for services in home environment is proposed. The role of this system is the assisting of persons by controlling home activities and guiding the adaption of Smart-Home-Human interface towards the needs of the considered person. At the same time the system sustains privacy issues of it’s interaction partner. As a special case of medical assisting the system is so implemented, that it provides for elderly or disabled people person-specific medical assistance . The system has the ability of identifying its interaction partner using some biometric features. According to the recognized ID the system, first, adopts towards the needs of recognized person. Second the system represents person-specific list of medicines either visually or auditive. And third the system gives an alarm in the case of taking medicament either later or earlier as normal taking time.
We present a novel method to perform multi-class pattern classification with neural networks and test it on a challenging 3D hand gesture recognition problem. Our method consists of a standard one-against-all (OAA) classification, followed by another network layer classifying the resulting class scores, possibly augmented by the original raw input vector. This allows the network to disambiguate hard-to-separate classes as the distribution of class scores carries considerable information as well, and is in fact often used for assessing the confidence of a decision. We show that by this approach we are able to significantly boost our results, overall as well as for particular difficult cases, on the hard 10-class gesture classification task.
We present a novel approach of distributing matrix multiplications among GPU-equipped nodes in a cluster system. In this context we discuss the induced challenges and possible solutions. Additionally we state an algorithm which outperforms optimized GPU BLAS libraries for small matrices. Furthermore we provide a novel theoretical model for distributing algorithms within homogeneous computation systems with multiple hierarchies. In the context of this model we develop an algorithm which can find the optimal distribution parameters for each involved subalgorithm. We provide a detailed analysis of the algorithms space and time complexities and justify its use with a structured evaluation within a small GPU-equipped Beowulf cluster.
The influence of national culture on knowledge sharing has important implications for all organizations. However, the existing frameworks only cover a subset of relevant factors or limit the research of the framework to either organizational or national level. Hence, a more encompassing framework is needed. The question this articles answers is how does national culture influence knowledge sharing. Based on extensive literature review and interviews carried out in Finland and Japan, this article sets forth a foundation for a new framework. The framework details how national culture influences individual level and organizational level factors and technical tools. Additionally, the framework includes a new dimension, time-dimension, which is usually disregarded in knowledge sharing research. For researchers and practitioners, the derived framework provides key insight on relevant factors on knowledge sharing and national culture. Finally, future research directions are discussed.
Bei Großschadensereignissen kann es durch die Vielzahl der Alarme dazu kommen, dass die verfügbaren Rettungskräfte nicht mehr ausreichen, um die anfallenden Aufgaben zu bewältigen oder Hilfsfristen einzuhalten. Die vorliegende Arbeit beschreibt einen Ansatz, sich zusätzlicher Hilfe aus der Bevölkerung zu bedienen, die über einen Disponenten aus der vorhandenen Leitstelle koordiniert wird. Dabei stehen nicht spontan organisierte Helfer im Vordergrund, sondern Personen, die sich vorab mit einem klaren Fertigkeitsprofil und ggf. auch Ausstattung im System registriert haben. Besondere Anforderungen entstehen bei den Disponenten der Leitstelle, deren Mehrbelastung durch das neue System gering zu halten ist, als auch bei den freiwilligen Helfern, die über eine App auf dem Mobiltelefon alarmiert werden und auch darüber die Kommunikation führen sollen. Die Anforderungen beeinflussen sowohl die System-Infrastruktur als auch die Benutzerschnittstelle.
Mensch-Maschine-Interaktion in sicherheitskritischen Systemen ist ein für die Informatik und die jeweiligen Anwendungsdomänen in der Bedeutung weiter zunehmendes Thema. Dieser Workshop der GI-Fachgruppe „Mensch-Maschine-Interaktion in sicherheitskritischen Systemen" innerhalb des Fachbereichs Mensch-Computer-Interaktion soll aktuelle Entwicklungen und Fragestellungen offenlegen und neue Impulse für das Forschungsgebiet geben.
Social networking sites (SNSs) are an integral part of our daily life. With the evermore increasing appearance of SNSs, their users spend considerable time producing of different forms everyday (e.g. text, videos, photos, links, etc.) or browsing the varieties of contents in different SNSs. In this paper, we propose an architectural perspective on a framework that provides a unified environment through which users can produce and browse different contents of SNSs from one place.
With the spread of mobile devices among both, men and women, app-based games also become more popular. While traditionally, digital games are more famous among men, women seem to spend more time and money on mobile gaming. There are a lot of open questions with regard to women and gaming in general; research on gender differences in app-based mobile gaming is almost nonexistent. Taking an exploratory perspective, our study investigates gender differences in general usage patterns, attachment towards the game and motivational differences for choosing to play the famous QuizClash app. Also, we identify differences in reported and actual performance in specific categories and capture anticipation of success as well as likeliness of choosing specific knowledge categories depending on the opponents’ performance profile.
We present a novel hierarchical approach to multi-class classification which is generic in that it can be applied to different classification models (e.g., support vector machines, perceptrons), and makes no explicit assumptions about the probabilistic structure of the problem as it is usually done in multi-class classification. By adding a cascade of additional classifiers, each of which receives the previous classifier's output in addition to regular input data, the approach harnesses unused information that manifests itself in the form of, e.g., correlations between predicted classes. Using multilayer perceptrons as a classification model, we demonstrate the validity of this approach by testing it on a complex ten-class 3D gesture recognition task.
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.
Utilizing biometrie traits for privacy- and security-applications is receiving an increasing attention. Applications such as personal identification, access control, forensics appli-cations, e-banking, e-government, e-health and recently person-alized human-smart-home and human-robot interaction present some examples. In order to offer person-specific services for/of specific person a pre-identifying step should be done in the run-up. Using biometric in such application is encountered by diverse challenges. First, using one trait and excluding the others depends on the application aimed to. Some applications demand directly touch to biometric sensors, while others don't. Second challenge is the reliability of used biometric arrangement. Civilized application demands lower reliability comparing to the forensics ones. And third, for biometric system could only one trait be used (uni-modal systems) or multiple traits (Bi- or Multi-modal systems). The latter is applied, when systems with a relative high reliability are expected. The main aim of this paper is providing a comprehensive view about biometric and its application. The above mentioned challenges will be analyzed deeply. The suitability of each biometric sensor according to the aimed application will be deeply discussed. Detailed com-parison between uni-modal and Multi-modal biometric system will present which system where to be utilized. Privacy and security issues of biometric systems will be discussed too. Three scenarios of biometric application in home-environment, human-robot-interaction and e-health will be presented.
A light-weight real-time ap- plicable hand gesture recognition system for automotive applications
(2015)
We present a novel approach for improved hand-gesture recognition by a single time-of-flight(ToF) sensor in an automotive environment. As the sensor's lateral resolution is comparatively low, we employ a learning approach comprising multiple processing steps, including PCA-based cropping, the computation of robust point cloud descriptors and training of a Multilayer perceptron (MLP) on a large database of samples. A sophisticated temporal fusion technique boosts the overall robustness of recognition by taking into account data coming from previous classification steps. Overall results are very satisfactory when evaluated on a large benchmark set of ten different hand poses, especially when it comes to generalization on previously unknown persons.
We present a system for efficient dynamic hand gesture recognition based on a single time-of-flight sensor. As opposed to other approaches, we simply rely on depth data to interpret user movement with the hand in mid-air. We set up a large database to train multilayer perceptrons (MLPs) which are subsequently used for classification of static hand poses that define the targeted dynamic gestures. In order to remain robust against noise and to balance the low sensor resolution, PCA is used for data cropping and highly descriptive features, obtainable in real-time, are presented. Our simple yet efficient definition of a dynamic hand gesture shows how strong results are achievable in an automotive environment allowing for interesting and sophisticated applications to be realized.
This contribution demonstrates the efficient embedding of a single depth-camera into the automotive environment making mid-air gesture interaction for mobile applications viable in such a scenario. In this setting a new human-machine interface is implemented to give an idea of future improvements in automation processes in industrial applications. Our system is based on a data-driven approach by learning hand poses as well as gestures from a large database in order to apply them on mobile devices. We register any movement in a nearby driver area and crop data efficiently with the means of PCA transforming it into so-called feature vectors which present the input for our multi-layer perceptrons (MLPs). After MLP classification, the interpretation of user input is sent via WiFi to a tablet PC mounted into the car interior visualizing an infotainment system which the user is able to interact with. We demonstrate that by this setup hand gestures as well as hand poses are easily and efficiently interpretable insofar as that they become an intuitive and supplementary means of interaction for automotive HMI in mobile scenarios realizable in real-time.
Object detection systems which operate on large data streams require an efficient scaling with available computation power. We analyze how the use of tile-images can increase the efficiency (i.e. execution speed) of distributed HOG-based object detectors. Furthermore we discuss the challenges of using our developed algorithms in practical large scale scenarios. We show with a structured evaluation that our approach can provide a speed-up of 30-180 % for existing architectures. Due to the its generic formulation it can be applied to a wide range of HOG-based (or similar) algorithms. In this context we also study the effects of applying our method to an existing detector and discuss a scalable strategy for distributing the computation among nodes in a cluster system.