Refine
Year of publication
Document Type
- Article (64) (remove)
Language
- English (64) (remove)
Is part of the Bibliography
- no (64)
Keywords
In this study, we looked at the competencies and changes in the competency spectrum required for global start-ups in the digital age. Specifically, we explored intergenerational collaboration as an intervention in which experienced business-people from senior adult groups support young entrepreneurs. We conducted a Delphi study with 20 experts from different disciplines, considering the study context. The results of this study shed light on understanding the necessary competencies of entrepreneurs for intergenerationally supported start-up innovation by providing 27 competencies categorized as follows: intergenerational safety facilitation, cultural awareness, virtues for growth, effectual creativity, technical expertise, responsive teamwork, values-based organization, and sustainable network development. In addition, the study results also reveal the competency priorities and the minimum requirements for each competency group based on the global innovation process and can be used to develop a readiness assessment for start-up entrepreneurs.
So far, researchers have used a wellbeing-centered approach to catalyze successful intergenerational collaboration (IGC) in innovative activities. However, due to the subject’s multidisciplinary nature, there is still a dearth of comprehensive research devoted to constructing the IGC system. Thus, the purpose of this study is to fill a research void by providing a conceptual framework for information technology (IT) system designers to use as a jumping-off point for designing an IGC system with a wellbeing-oriented design. A systematic literature study was conducted to identify relevant terms and develop a conceptual framework based on a review of 75 selected scientific papers. The result consists of prominent thematic linkages and a conceptual framework related to design technology for IGC systems. The conceptual framework provides a comprehensive overview of IGC systems in the innovation process by identifying five barrier dimensions and using six wellbeing determinants as IGC catalysts. Moreover, this study discusses future directions for research on IGC systems. This study offers a novel contribution by shifting the technology design process from an age-based design approach to wellbeing-driven IGC systems. Additional avenues for investigation were revealed through the analysis of the study’s findings.
Rapid digital transformation is taking place due to the COVID-19 pandemic, forcing organisations and higher educational institutions to change their working and learning culture. This study explores the challenges of rapid digital transformation arising during the pandemic in the higher education context. This research used the Q-methodology to understand the nine challenges that higher education encountered, perceived differently as four main patterns: (1) Digital-nomad enterprise; (2) Corporate-collectivism; (3) Well-being-oriented; and (4) Pluralistic. This study broadens the current understanding of digital transformation, especially in higher education. The nine challenges and four patterns of transformation actors serve as a starting point for organisations in supporting technological choice and strategic interventions, based on individual, group, and organisational behavioural levels. Moreover, five propositions, based on the competing concerns of these challenges, establish a framework for comprehending the ecosystem that enables rapid digital transformation. Strategies, prerequisites, and key factors during the (digital) technology development process benefit the cyber-society ecosystem. As a practical contribution, Q-methodology was used to investigate perspectives on digitalisation challenges during the pandemic.
The way we communicate with autonomous cars will fundamentally change as soon as manual input is no longer required as back-up for the autonomous system. Maneuver-based driving is a potential way to allow still the user to intervene with the autonomous car to communicate requests such as stopping at the next parking lot. In this work, we highlight different research questions that still need to be explored to gain insights into how such control can be realized in the future.
Human emotion detection in automated vehicles helps to improve comfort and safety. Research in the automotive domain focuses a lot on sensing drivers' drowsiness and aggression. We present a new form of implicit driver-vehicle cooperation, where emotion detection is integrated into an automated vehicle's decision-making process. Constant evaluation of the driver's reaction to vehicle behavior allows us to revise decisions and helps to increase the safety of future automated vehicles.
How to Increase Automated Vehicles’ Acceptance through In-Vehicle Interaction Design: A Review
(2020)
Automated vehicles (AVs) are on the edge of being available on the mass market. Research often focuses on technical aspects of automation, such as computer vision, sensing, or artificial intelligence. Nevertheless, researchers also identified several challenges from a human perspective that need to be considered for a successful introduction of these technologies. In this paper, we first analyze human needs and system acceptance in the context of AVs. Then, based on a literature review, we provide a summary of current research on in-car driver-vehicle interaction and related human factor issues. This work helps researchers, designers, and practitioners to get an overview of the current state of the art.
The development of innovative measuring technology for process optimization in hot rolling mills becomes more and more relevant because of increasing demands on product quality. Measurement technology for high-resolution non-contact cross-sectional area measurement has shown that the variation in cross-sectional area contains information about the rolling process. This information can be used for the development of new measurement devices and analytical methods for process optimization. The harsh environmental conditions and strict safety regulations result in great effort when implementing a new sensor prototype in hot rolling mills. For this reason, this work presents a mechatronic test stand that can simulate the cross-sectional area variation under laboratory conditions realistically.
Autonomous driving is one of the future visions in which many vehicle manufacturers are working with high pressure.
Nowadays, it is already supported partially by high-class vehicles. A completely autonomous journey is indeed the goal, but in cars for
the public road traffic still not available. Automatic lane keeping assistants, speed regulators as well as shield and obstacle detections
are parts or precursors on the way to completely autonomous driving.
The American vehicle manufacturer Tesla is not only known for its electric drive, but also for the fact that high-pressure work is carried out on the autonomous drive. Tesla is thus the only vehicle manufacturer to use its users as so-called beta testers for its assistance systems. The progress and the function of the currently available Model S in the field of assistance systems and autonomic driving is documented and described in this paper. It is shown how good or bad the test vehicle manages scenarios in normal road traffic situations
with the assistance systems, e.g. lane keeping assistant, speed control, lane change and distance assistant, and which scenarios can
not be managed by the vehicle itself.
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.
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.
With the introduction of Apple’s iPhone, gesture control became pop-
ular and was perceived as an intuitive means of interaction. Contact-
less gestures received broad attention with the X-Box Kinect.
Current technology is limited to a small number of uses, mainly
in entertainment systems. The target of this project is to increase the
range of possible applications, e.g. to the field of automotive,
industrial applications (manufacturing plants), assisted living in con-
texts ranging from private households to hospitals (interaction for
people with disabilities) and many more.
With a rapidly ageing population, it is increasingly important to de-
velop devices for elderly and disabled people that can support and aid
them in their daily lives, helping them to live at home as long as pos-
sible. The goal of this project is to implement a human-machine inter-
action and assistance system that can offer personalised health sup-
port for elderly people, or for those who have special needs in the
home environment.
One of the technical building blocks of Cloud Computing infrastructures are Web Services. With respect to mobile devices their role as Web Service consumers is widely accepted and today a large number of mobile applications already consume Web Services in order to fulfill their task. Still, not much research is conducted, as yet, to allow deploying Web Services on mobile devices and thus uses these kinds of devices as Web Service providers. This paper presents an analysis of one already implemented approach for provisioning mobile Web Services with respect to energy/battery consumption. Here, after shortly presenting the implementation for the provisioning of mobile Web Services an evaluation of the battery consumption that results in using the approach is presented. Last but not least, an improvement with respect to the battery consumption is presented. The performance test shows that the improved approach provides a reasonable way to introduce Web Service provisioning for mobile devices.
The term “Cloud Computing” does not primarily specify new types of core technologies but rather addresses features to do with integration, inter-operability and accessibility. Although not new, virtualization and automation are cor features that characterize Cloud Computing. In this paper, we intend to explore the possibility of integrating cloud services with educational scenarios without re-defining neither the technology nor the usage scenarios from scratch. Our suggestion is based on certain solutions that have already been implemented and tested for specific cases.
Design and Evaluation of a Platform Independent Application for Mobile Access of Moodle Quizzes
(2013)
One of the latest hypes in IT is the well-known Cloud
Computing paradigm. This paradigm that showed up in recent years
is a paradigm for the dynamic usage of computational power, memory and other computational resources. With respect to hypes, the author strongly believes that the
Cloud Computing paradigm has the potential to survive the hype and to become a usual technology used for the provision of IT based services. Therefore, it will be necessary to deploy Cloud Computing based infrastructures in a professional, stable and reliable way. This would lead to the idea that the Cloud Computing paradigm needs to be concerned with respect to IT Service Management, since cloud based infrastructures have to be managed differently in comparison to a usual infrastructure. This paper discusses, based on the IT Infrastructure Library (ITIL), as the de-facto standard for IT Service Management, whether this de-facto standard might also be able to manage Cloud Computing based infrastructures, how the according processes might change and whether ITIL supports a division of labor between the customer and the service provider
of a Cloud Computing based infrastructure.
The role of mobile devices as Web Service consumers is widely accepted and a large number of mobile applications already consumes Web Services in order to fullfill their task. Nevertheless, the growing number of powerful mobile devices, e.g. mobile phones, tablets even raise the question whether these devices can not only be used as Web Service consumers but at the same time also as Web Service providers. Therefore, this paper presents an approach that allows to deploy Web Services on mobile devices by the usage of the well-known protocols and standards, e.g. SOAP/REST and WSDL.
Systems for automated image analysis are useful for a variety of tasks. Their importance is still growing due to technological advances and increased social acceptance. Especially driver assistance systems have reached a high level of sophistication. Fully or partly autonomously guided vehicles, particularly for road traffic, require highly reliable algorithms due to the conditions imposed by natural environments. At the Institut fur Neuroinformatik, methods for analyzing driving relevant scenes by computer vision are developed in cooperation with several partners from the automobile industry. We present a system extracting important information from an image taken by a CCD camera installed at the rear-view mirror in a car. The approach is divided into a sequential and a parallel phase of sensor and information processing. Three main tasks, namely initial segmentation (object detection), object tracking and object classification are realized by integration in the sequential phase and by fusion in the parallel phase. The main advantage of this approach is integrative coupling of different algorithms providing partly redundant information. q 2000 Elsevier Science B.V. All rights reserved.
Group-centered framework towards a positive design of digital collaboration in global settings
(2017)
Globally distributed groups require collaborative systems to support their work. Besides being able to support the teamwork, these systems also should promote well-being and maximize the human potential that leads to an engaging system and joyful experience. Designing such system is a significant challenge and requires a thorough understanding of group work. We used the field theory as a lens to view the essential aspects of group motivation and then utilized collaboration personas to analyze the elements of group work. We integrated well-being determinants as engagement factors to develop a group-centered framework for digital collaboration in a global setting. Based on the outcomes, we proposed a conceptual framework to design an engaging collaborative system and recommend system values that can be used to evaluate the system further.
Women are still underrepresented at the highest management levels. The think-manager-think-male phenomenon suggests that leadership is associated with male rather than female attributes. Although styling has been shown to influence the evaluation of women's leadership abilities, the relevant specific features have been left remarkably unaddressed. In a 2 × 2 × 2 × 2 (skirt/pants, with/without jewelry, loose hair/braid, with/without makeup) between-subjects design, 354 participants evaluated a woman in a photograph. Women with makeup, pants, or with jewelry were rated as more competent than women without makeup, with skirts, or without jewelry. A combination of loose hair and no makeup was perceived as warmest, and women with loose hair were more likely to be hired than those with braids. In sum, even subtle changes in styling have a strong impact on how women's leadership abilities are evaluated.
The Bitcoin whitepaper states that security of the system is guaranteed as long as honest miners control more than half of the current total computational power. The whitepaper assumes a static difficulty, thus it is equally hard to solve a cryptographic proof-of-work puzzle for any given moment of the system history. However, the real Bitcoin network is using an adaptive difficulty adjustment mechanism. In this paper we introduce and analyze a new kind of attack on a mining difficulty retargeting function used in Bitcoin. A malicious miner is increasing his mining profits from the attack, named coin-hopping attack, and, as a side effect, an average delay between blocks is increasing. We propose an alternative difficulty adjustment algorithm in order to reduce an incentive to perform coin-hopping, and also to improve stability of inter-block delays. Finally, we evaluate the presented approach and show that the novel algorithm performs better than the original algorithm of Bitcoin.
In this paper we present an approach for contextual big data analytics in social networks, particularly in Twitter. The combination of a Rich Context Model (RCM) with machine learning is used in order to improve the quality of the data mining techniques. We propose the algorithm and architecture of our approach for real-time contextual analysis of tweets. The proposed approach can be used to enrich and empower the predictive analytics or to provide relevant context-aware recommendations.
In this paper we describe an architecture for behavioral organization based on dynamical systems. This architecture
enables the generation of complex behavioral sequences, which is demonstrated using the example of approaching and
passing a door. The behavioral sequence is generated by activating and deactivating the elementary behaviors dependent
on sensory information and internal logical conditions. The architecture is demonstrated on a mobile KOALA robot and
in simulation as well.
In recent years, the number of reasonable powerful mobile devices increased. In 2011, the number of smartphones(e.g.)increased to more than 300 million units. A lot of research has already been conducted with respect of mobile devices acting as Cloud Service consumers, but
still not much effort is put on mobile devices in the role of Cloud Service providers. Therefore, this paper presents an approach that allows to utilize mobile devices like smart phones or tablets as Cloud Service providers. In order to make this a reasonable approach, some of the occurring problems are discussed and it is shown how the presented architecture is able to overcome these problems. Last
but not least, this paper
describes some performance
tests of the chosen implementa
tion for mobile Web Services.
CORA is a robotic assistant whose task is to collaborate with a human operator on simple manipulation or handling tasks. Its sensory channels comprising vision, audition, haptics, and force sensing are used to extract perceptual information about speech, gestures and gaze of the operator, and object recognition. The anthropomorphic robot arm makes goal-directed movements to pick up and hand over objects. The human operator may mechanically interact with the arm by pushing it away (haptics) or by taking an object out of the robot's gripper (force sensing). The design objective has been to exploit the human operator's intuition by modeling the mechanical structure, the senses, and the behaviors of the assistant on human anatomy, human perception, and human motor behavior.
We extend the attractor dynamics approach to generate goal-directed movement of a redundant, anthropomorphic arm while avoiding dynamic obstacles and respecting joint limits. To make the robot's movements human-like, we generate approximately straight-line trajectories by using two heading direction angles of the tool-point quite analogously to how movement is represented in the primate central nervous system. Two additional angles control the tool's spatial orientation so that it follows the tool-point's collision-free path. A fifth equation governs the redundancy angle, which controls the elevation of the elbow so as to avoid obstacles and respect joint limits. These variables make it possible to generate movement while sitting in an attractor (or, in the language of the potential field approach, in a minimum). We demonstrate the approach on an assistant robot, which interacts with human users in a shared workspace
The presented work formulates an framework in which early prediction of drivers lane change behavior is realized. We aim to build a representation of drivers lane change behavior in order to recognize and to predict driver's intentions as a first step towards a realistic driver model. In the test bed of the Institute of Neuroinformatik, based on the traffic simulator NISYS TRS 1, 10 individuals have driven in the experiments and they performed more then 150 lane change maneuvers. Lane-offset, distance to the front car and time to contact, were recorded. The acquired data was used to train - in parallel- a recurrent neural network, a feed forward neural network and a set of support vector machines. In the followed test drives the system was able of performing a lane change prediction time of 1.5 sec beforehand. The proposed approach describes a framework for lane-change detection and prediction, which will serve as a prerequisite for a successful driver model.
The harmonic and interharmonic analysis recommendations are contained in the latest International Electrotechnical Commission (IEC) standards on power quality. Measurement and analysis experiences have shown that great difficulties arise in the interharmonics detection and measurement with acceptable levels of accuracy. In this paper, the spectral leakage problems of the discrete Fourier transform due to synchronization errors of interharmonics are analyzed. The time-domain averaging is investigated for the processing of harmonics in the framework of the IEC standards. A difference filter is proposed to detect interharmonics and can be compatible with the IEC standards. Simulations and the field results show the usefulness of the proposed methods.
Detection of air trapping in chronic obstructive pulmonary disease by low frequency ultrasound
(2012)
Background: Spirometry is regarded as the gold standard for the diagnosis of COPD, yet the condition is widely underdiagnosed. Therefore, additional screening methods that are easy to perform and to interpret are needed. Recently, we demonstrated that low frequency ultrasound (LFU) may be helpful for monitoring lung diseases. The objective of this study was to evaluate whether LFU can be used to detect air trapping in COPD. In addition, we evaluated the ability of LFU to detect the effects of short-acting bronchodilator medication.Methods: Seventeen patients with COPD and 9 healthy subjects were examined by body plethysmography and LFU. Ultrasound frequencies ranging from 1 to 40 kHz were transmitted to the sternum and received at the back during inspiration and expiration. The high pass frequency was determined from the inspiratory and the expiratory signals and their difference termed F. Measurements were repeated after inhalation of salbutamol.Results: We found signi ficant differences in F between COPD subjects and healthy subjects. These differences were already significant at GOLD stage 1 and increased with the severity of COPD. Sensitivity for detection of GOLD stage 1 was 83% and for GOLD stages worse than 1 it was 91%. Bronchodilator effects could not be detected reliably.Conclusions: We conclude that low frequency ultrasound is cost-effective, easy to perform and suitable for detecting air trapping. It might be useful in screening for COPD
Background:
Detection of influential actors in social media such as Twitter or Facebook plays an important role for improving the quality and efficiency of work and services in many fields such as education and marketing.
Methods:
The work described here aims to introduce a new approach that characterizes the influence of actors by the strength of attracting new active members into a networked community. We present 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.
Results:
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.
Conclusions:
Our empirical results on the datasets demonstrate that our measure stands out as a useful measure to define the attractors comparing to the other influence measures.
Background:
Influential actors detection in social media such as twitter or Facebook can play a major role in gathering opinions on particular topics, improving the market
-
ing efficiency, predicting the trends, etc.
Proposed methods:
This work aims to extend our formally defined
T
measure to
present a new measure aiming to recognize the actor’s influence by the strength of
attracting new important actors into a networked community. Therefore, we propose a
model of the actor’s influence based on the attractiveness of the actor in relation to the
number of other attractors with whom he/she has established connections over time.
Results and conclusions:
Using an empirically collected social network for the
underlying graph, we have applied the above-mentioned measure of influence in
order to determine optimal seeds in a simulation of influence maximization. We study
our extended measure in the context of information diffusion because this measure is
based on a model of actors who attract others to be active members in a community.
This corresponds to the idea of the IC simulation model which is used to identify the
most important spreaders in a set of actors.
Keywords: Actor influence, Social media networks, Twitter, IC model, Information
diffusion, Independent cascade model, T measure
Photoluminescence (PL) in GaN or InGaN layers monitored during epitaxial growth at high temperatures permits a quasi-continuous in situ characterization of opto-electronic properties. Therefore, epitaxial parameters can now be optimized at the earliest possible stage. A pulsed and high-power UV laser was required for PL excitation at high temperatures. Herein, the underlying nonlinear mechanism was studied via time-resolved PL experiments and rate equation-based modeling. A temperature-activated and saturable path for quenching over defects was identified. Beyond the saturation threshold, reasonably-intensive PL sets in. At high temperatures not only is the near band gap-PL present, but also—as a new observation—a defect-assisted PL emerges. Apart from these specific electronic transitions in high-temperature PL of GaN, a simple, but reasonably predictive model of the luminescent thin film has been set up to track down interference fringes in the PL spectra. It is worth mentioning that the spectral PL modulation (aiming at the Purcell effect) is often mixed up with ordinary Fabry–Pérot interference. A distinction has become key to properly analyze the spectral signatures of high-temperature PL in order to provide a reliable in situ characterization of GaN layers during epitaxial growth
This experimental study demonstrates for the first time a solid-state circuitry and design for a simple compact copper coil (without an additional bulky permanent magnet or bulky electromagnet) as a contactless electromagnetic acoustic transducer (EMAT) for pulse echo operation at MHz frequencies. A pulsed ultrasound emission into a metallic test object is electromagnetically excited by
an intense MHz burst at up to 500 A through the 0.15 mm filaments of the transducer. Immediately thereafter, a smoother and quasi “DC-like” current of 100 A is applied for about 1 ms and allows an
echo detection. The ultrasonic pulse echo operation for a simple, compact, non-contacting copper coil is new. Application scenarios for compact transducer techniques include very narrow and
hostile environments, in which, e.g., quickly moving metal parts must be tested with only one, non-contacting ultrasound shot. The small transducer coil can be operated remotely with a cable
connection, separate from the much bulkier supply circuitry. Several options for more technical and fundamental progress are discussed.
A Large and Quick Induction Field Scanner for Examining the Interior of Extended Objects or Humans
(2017)
This study describes the techniques and signal properties of a large, powerful, and linear-scanning 1.5 MHz induction field scanner. The mechanical system is capable of quickly reading the volume of relative large objects, e.g., a test person. The general approach mirrors Magnetic Induction Tomography (MIT), but the details differ considerably from currently-described MIT systems: the setup is asymmetrical, and it operates in gradiometric modalities, either with coaxial excitation with destructive interference or with a single excitation loop and tilted receivers. Following this approach, the primary signals were almost completely nulled, and test objects' real or imaginary imprint was obtained directly. The coaxial gradiometer appeared advantageous: exposure to strong fields was reduced due to destructive interference. Meanwhile, the signals included enhanced components at higher spatial frequencies, thereby obtaining a gradually improved capability for localization. For robust signals, the excitation field can be powered towards the rated limits of human exposure to time-varying magnetic fields. Repeated measurements assessed the important signal integrity, which is affected by the scanner´s imperfections, particularly any motions or respiratory changes in living beings during or between repeated scans. The currently achieved and overall figure of merit for artifacts was 58 dB for inanimate test objects and 44 dB for a test person. Both numbers should be understood as worst case levels: a repeated scan with intermediate breathing and drift/dislocations requires 50 seconds, whereas a single measurement (with respiratory arrest) takes only about 5 seconds.
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.