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The healthcare sector's digital transformation necessitates the involvement of stakeholders through participation and co-creation processes. This study aims to investigate the understanding and implementation of participation and co-creation in the development of hybrid interaction technologies in healthcare. Eight interdisciplinary research projects were examined through semi-structured group interviews with 49 participants from academia, industry, and the application field. The interviews focused on participants' perspectives on project goals, user groups, access to the field, methods of participation and co-creation, and user motivation. The results highlight the diverse understandings of participation and co-creation, with some perceiving them as research-driven and others as already embedded in user- centered design. The projects emphasized user needs but often excluded stakeholders from collaborative decision-making. Challenges in achieving continuous involvement and co-decision were acknowledged. The findings underscore the need for reflexive practice and evaluation of participation and co-creation throughout the development process, as well as further research on participation across projects. By addressing these challenges and embracing participatory approaches, digital health applications can better address ethical concerns, build trust, and increase acceptance and adoption in the healthcare sector.
User-centered and Participatory Design approaches have become widespread within HCI, also when designing digital media for older adults. These methodologies are seen as crucial to adapt technology design to older people's needs and increase their acceptance of digital technology. Nevertheless, it is often difficult to reach a diverse group of older people, for instance, people with limited technology skills, limited mobility, or cognitive issues. In addition, gerontologists criticized lately how older people's participation unfolds in technology design projects, e.g. that people are pushed into the role of users. Little is known about the motivations and needs of older adults regarding their participation in HCI research. To close this gap, we conducted an online survey (N=46) and semi-structured interviews (N=8) focusing on motivations, willingness and experiences regarding participation. Results show that people are generally willing to participate due to interest in the topic, learning new things and social bonding. However, despite the conceptions within HCI that long-term engagement is crucial within participatory design, older people in the study preferred less commitment and more open formats.
Despite the higher uptake of digital media also in older age groups, there are still challenges for people of high ages and with cognitive or motoric problems, which prevent them from learning and using devices like smartphones or tablets. Tangible user interfaces provide an opportunity to connect these people to social media, thereby increasing their digital participation in society and reducing loneliness. In this paper, we discuss the challenges of intergenerational communication and research the opportunities affiliated with tangible technologies to overcome technology barriers for adults of high ages. We present a hybrid system for social media interactions between young smartphone users and their old relatives, who do not use mobile technologies. The system consists of a tangible user interface designed specifically for old adults that connects to a standard mobile messenger service. TAMI was designed in a user-centered process to fulfill the needs of older adults and tested in a longer-term field study with pairs of young and old relatives.
Over the past decades, research in room acoustics has established several derivative measures of an impulse response, some of which are incorporated in the ISO 3382 standards. These parameters intend to represent perceptual qualities, but were developed without a consistent modeling of room acoustical perception. More recent research proposed comprehensive inventories of room acoustic perception that are purely based on evaluations by human subjects, such as the Room Acoustical Quality Index (RAQI). In this work RA-QI scores acquired for 70 room impulse responses were predicted from room acoustical parameters. Except for Reverberance, the prediction of RAQI factors performed rather poor. In most cases, the sound source had a greater impact on RAQI scores. All analyses are published in an online tool, where users can upload omnidirectional and binaural impulse responses, and instantly obtain and visualize several physical descriptors, as well as predicted RAQI scores for three different sound sources. So far, acceptable prediction accuracy is achieved for Reverberance, Strength, Irregular Decay, Clarity and Intimacy. Larger data sets of evaluated impulse responses are required to improve the model performance and enable reliable predictions of room acoustical quality. Therefore, the administration of RAQI evaluations within the website is currently being developed.
The soundscape approach highlights the role of situational factors in sound evaluations; however, only a few studies have applied a multi‐domain approach including sound‐related, person‐related, and time‐varying situational variables. Therefore, we conducted a study based on the Experience Sampling Method to measure the relative contribution of a broad range of potentially relevant acoustic and non‐auditory variables in predicting indoor soundscape evaluations. Here we present the comprehensive dataset for which 105 participants reported temporally (rather) stable trait variables such as noise sensitivity, trait affect, and quality of life. They rated 6.594 situations regarding the soundscape standard dimensions, perceived loudness, and the saliency of its sound components and evaluated situational variables such as state affect, perceived control, activity, and location. To complement these subject‐centered data, we additionally crowdsourced object‐centered data by having participants make binaural measurements of each indoor soundscape at their homes using a low‐(self‐)noise recorder. These recordings were used to compute (psycho‐)acoustical indices such as the energetically averaged loudness level, the A‐weighted energetically averaged equivalent continuous sound pressure level, and the A‐weighted five‐percent exceedance level. This complex hierarchical data can be used to investigate time‐varying non‐auditory influences on sound perception and to develop soundscape indicators based on the binaural recordings to predict soundscape evaluations.
Music consumption and distribution has changed drastically in the last twenty years due to digitalization. Instead of buying music products, like CDs or even downloaded digital music files, today music is predominantly distributed via online music streaming. Therefore, it is mandatory for the music industry as well as researchers to determine which factors are affecting consumers intention to use music streaming services. This study aims to investigate drivers of Behavioral Intention (BI) to use a music streaming service. Particularly, aspects of social preferences in the context of music streaming will be explored. Therefore, a research model is created, based on the Value-based Adoption Model (VAM) (Kim et al., 2007) with an extension to take social factors into account. An online questionnaire with 102 participants was conducted to test the research model and the corresponding hypotheses. In order to evaluate reliable indications, some adjustments needed to be made resulting in a corrected research model. The final independent variables of the corrected model are Perceived Value (PV) (which is composed of Perceived Usefulness (PU) and Perceived Enjoyment (PE)), Perceived Ease of Use (PEU), Perceived Price Value (PPV), Facilitating Conditions (FC), Perceived Fairness (PF), Social Connectivity (SC), and Peer-Effects (PFX). The empirical results show that Perceived Value (PV), Perceived Price Value (PPV), and Perceived Fairness (PF) are determinants of consumers Behavioral Intention (BI) to use a music streaming service.
Forums such as Stack Overflow are used by many software developers to find a solution for a given coding problem. Found solutions, i.e. forum posts containing relevant source code, are utilized in a copy and paste manner. This behavior carries the risk that vulnerabilities contained in the source code of the forum posts are spread. Software developers should be able to identify vulnerable source code at an early stage, thereby preventing copying the corresponding source code. In this paper, we introduce the tool CopypastaVulGuard that identifies vulnerable source code in forum posts and allows software developers to omit the source code by marking the forum posts as dangerous. Our tool consists of a browser extension and a management application capable to address as examples SQL injections, remote code executions and deprecated functions based on a dump of the archive.org Stack Overflow data set. We present an evaluation of our tool's possible impact and relevance considering pros/cons and selected research questions.
Room reverberation alters the spatial impression and timbre of a sound by modulating its spectral and temporal characteristics. Thus, we argue that, on a perceptual level, reverberation basically breaks down into interaural differences and spectro-temporal cues and that the separation of a perceived timbre into a sound source and a surrounding room is a purely cognitive process. To investigate the connection between the perception of reverberation cues and timbre analysis, the sensitivity for changes in reverberation was compared to timbre perception abilities. The Timbre Perception Test was used to measure the perception of the temporal envelope, spectral centroid, and spectral flux of artificial sounds. Sensitivity for changes in reverberation time was tested with a discrimination task using speech and noise with speech-alike spectral and temporal envelopes as source signals. Musical and acoustical expertise was assessed through the Goldsmiths Musical Sophistication Index and self-reports on experience with and knowledge of acoustics. There was a considerable correlation between timbre and reverberance perception ability, but timbre perception and academic experience predicted only 41% of the variance in reverberance perception. Still, perception abilities related to similar acoustical phenomena seem to be better indicators of listening skills than self-reports on acoustical or musical expertise.
Building context-aware applications is an already widely researched topic. It is our belief that context awareness has the potential to supplement the Internet of Things, when a suitable methodology including supporting tools will ease the development of context-aware applications. We believe that a meta-model based approach can be key to achieving this goal. In this paper, we present our meta-model based methodology, which allows us to define and build application-specific context models and the integration of sensor data without any programming. We describe how that methodology is applied with the implementation of a relatively simple context-aware COVID-safe navigation app. The outcome showed that programmers with no experience in context-awareness were able to understand the concepts easily and were able to effectively use it after receiving a short training. Therefore, context-awareness is able to be implemented within a short amount of time. We conclude that this can also be the case for the development of other context-aware applications, which have the same context-awareness characteristics. We have also identified further optimization potential, which we will discuss at the conclusion of this article.
Music-related decision-making encompasses a wide range of behaviours including those associated with listening choices, composition and performance, and decisions involving music education and therapy. Although research programmes in psychology and economics have contributed to an improved understanding of music-related behaviour, historically, these disciplines have been unconnected. Recently, however, researchers have begun to bridge this gap by employing tools from behavioural economics. This article contributes to the literature by providing a discussion about the benefits of using behavioural economics in music-decision research. We achieve this in two ways. First, through a systematic review, we identify the current state of the literature within four key areas of behavioural economics-heuristics and biases, social decision-making, behavioural time preferences, and dual-process theory. Second, taking findings of the literature as a starting point, we demonstrate how behavioural economics can inform future research. Based on this, we propose the Behavioural Economics of Music (BEM), an integrated research programme that aims to break new ground by stimulating interdisciplinary research in the intersection between music, psychology, and economics.
In the EILD.nrw project, Open Educational Resources (OER) are being developed for teaching databases. Instructors can use the tools and courses in a variety of learning scenarios. Students of computer science and application subjects learn the complete life cycle of databases. For this purpose, quizzes, interactive tools, instructional videos, and courses for learning management systems are developed and published under a Creative Commons license.
Musicians and music professionals are often considered to be expert listeners for listening tests on room acoustics. However, these tests often target acoustic parameters other than those typically relevant in music such as pitch, rhythm, amplitude, or timbre. To assess the expertise in perceiving and understanding room acoustical phenomena, a listening test battery was constructed to measure the perceptual sensitivity and cognitive abilities in the identification of rooms with different reverberation times and different spectral envelopes. Performance in these tests was related to data from the Goldsmiths Musical Sophistication Index, self-reported previous experience in music recording and acoustics, and academic knowledge on acoustics. The data from 102 participants show that sensory and cognitive abilities are both correlated significantly with musical training, analytic listening skills, recording experience, and academic knowledge on acoustics, whereas general interest in and engagement with music do not show any significant correlations. The regression models, using only significantly correlated criteria of musicality and professional expertise, explain only small to moderate amounts (11%–28%) of the variance in the “room acoustic listening expertise” across the different tasks of the battery. Thus, the results suggest that the traditional criteria for selecting expert listeners in room acoustics are only weak predictors of their actual performances.
Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships
(2021)
Spectral similarity is used as a proxy for structural similarity in many tandem mass spectrometry (MS/MS) based metabolomics analyses such as library matching and molecular networking. Although weaknesses in the relationship between spectral similarity scores and the true structural similarities have been described, little development of alternative scores has been undertaken. Here, we introduce Spec2Vec, a novel spectral similarity score inspired by a natural language processing algorithm-Word2Vec. Spec2Vec learns fragmental relationships within a large set of spectral data to derive abstract spectral embeddings that can be used to assess spectral similarities. Using data derived from GNPS MS/MS libraries including spectra for nearly 13,000 unique molecules, we show how Spec2Vec scores correlate better with structural similarity than cosine-based scores. We demonstrate the advantages of Spec2Vec in library matching and molecular networking. Spec2Vec is computationally more scalable allowing structural analogue searches in large databases within seconds.
Mass spectrometry data is one of the key sources of information in many workflows in medicine and across the life sciences. Mass fragmentation spectra are generally considered to be characteristic signatures of the chemical compound they originate from, yet the chemical structure itself usually cannot be easily deduced from the spectrum. Often, spectral similarity measures are used as a proxy for structural similarity but this approach is strongly limited by a generally poor correlation between both metrics. Here, we propose MS2DeepScore: a novel Siamese neural network to predict the structural similarity between two chemical structures solely based on their MS/MS fragmentation spectra. Using a cleaned dataset of > 100,000 mass spectra of about 15,000 unique known compounds, we trained MS2DeepScore to predict structural similarity scores for spectrum pairs with high accuracy. In addition, sampling different model varieties through Monte-Carlo Dropout is used to further improve the predictions and assess the model's prediction uncertainty. On 3600 spectra of 500 unseen compounds, MS2DeepScore is able to identify highly-reliable structural matches and to predict Tanimoto scores for pairs of molecules based on their fragment spectra with a root mean squared error of about 0.15. Furthermore, the prediction uncertainty estimate can be used to select a subset of predictions with a root mean squared error of about 0.1. Furthermore, we demonstrate that MS2DeepScore outperforms classical spectral similarity measures in retrieving chemically related compound pairs from large mass spectral datasets, thereby illustrating its potential for spectral library matching. Finally, MS2DeepScore can also be used to create chemically meaningful mass spectral embeddings that could be used to cluster large numbers of spectra. Added to the recently introduced unsupervised Spec2Vec metric, we believe that machine learning-supported mass spectral similarity measures have great potential for a range of metabolomics data processing pipelines.
Sound and music are well-studied aspects of the quality of experience in restaurants; the role of the room acoustical conditions, their influence on the visitors’ soundscape evaluation and their impact on the overall customer satisfaction in restaurants, however, has received less scientific attention. The present field study therefore investigated whether sound pressure level, reverberation time, and soundscape pleasantness can predict factors associated with overall restaurant quality. In total, 142 persons visiting 12 restaurants in Berlin rated relevant acoustical and non-acoustical factors associated with restaurant quality. Simultaneously, the A-weighted sound pressure level (LA,eq,15) was measured, and the reverberation time in the occupied state (T20,occ) was obtained by measurements performed in the unoccupied room and a subsequent calculation of the occupied condition according to DIN 18041. Results from linear mixed-effects models revealed that both the LA,eq,15 and T20,occ had a significant influence on soundscape pleasantness and eventfulness, whereby the effect of T20,occ was meditated by the LA,eq,15. Also, the LA,eq,15 as well as soundscape pleasantness were significant predictors of overall restaurant quality. A comprehensive structural equation model including both acoustical and non-acoustical factors, however, indicates that the effect of soundscape pleasantness on overall restaurant quality is mediated by the restaurant’s atmosphere. Our results support and extend previous findings which suggest that the acoustical design of restaurants involves a trade-off between comfort and liveliness, depending on the desired character of the place.
Singing in different rooms: Common or individual adaptation patterns to the acoustic conditions?
(2020)
The effect of inattention and cognitive load on unpleasantness judgments of environmental sounds
(2020)
Land of High Hopes
(2019)
We are living in the era of sophisticated, state-of-the-art technology, artificial intelligence, accelerating data sciences at ultimate speed and sheer unlimited possibilities. We are able to shoot unmanned rockets equipped with vehicles into the orbit. We can afford to spend fortunes on research and development. However, and that leaves me bloodcurdling and furious, we haven´t managed yet to settle at least some of the most pressing global humanitarian needs: access to food, water, electricity, education and healthcare. So how can we be proud of any achievements? What does make us proud anyway?! ...
The “Journal of Virtual Reality and Broadcasting” is an open access E-journal covering advanced media technology for the integration of human computer interaction and modern information systems. The main focus is on the creation of synergies between such basic technologies as computer graphics and state-of-the-art broadcasting techniques.
The main goals are to publish research results in the field of Virtual Reality and Broadcasting, to provoke discussions, and to promote the exchange of ideas and information. Developments in the area have a direct effect on society, therefore social aspects will also be considered. As an interdisciplinary field Virtual Reality requires multilateral collaboration in order to enable new applications.
RB publishes articles consecutively and in electronic form only. All articles are peer-reviewed in a strict review process by at least three independent experts from the appropriate field of research and appear in the English language. The articles are organized in one volume per year with ten to twenty articles. Material that has been previously presented at conferences undergo a major revision and are extended and modified by the authors with at least 20% new material according to the Journal's policy for previously published articles. The Journal has been established in 2004.
Currently, the submission and publication of articles is free of charge. No author fees are applied.
We report about several experiments on applying mixed reality technology in the context of accessing collective memories from atomic bombs, Holocaust and Second World War. We discuss the impact of Virtual Reality, Augmented Virtuality and Augmented Reality for specific memorial locations. We show how to use a virtual studio for demonstrating an augmented reality application for a specific location in a remote session within a video conference. Augmented Virtuality is used to recreate the local environment, thus providing a context and helping the participants recollect emotions related to a certain place. This technique demonstrates the advantages of using virtual (VR) and augmented (AR) reality environments for rapid prototyping and pitching project ideas in a live remote setting.
Music listening has become a highly individualized activity with smartphones and music streaming services providing listeners with absolute freedom to listen to any kind of music in any situation. Until now, little has been written about the processes underlying the selection of music in daily life. The present study aimed to disentangle some of the complex processes among the listener, situation, and functions of music listening involved in music selection. Utilizing the experience sampling method, data were collected from 119 participants using a smartphone application. For 10 consecutive days, participants received 14 prompts using stratified-random sampling throughout the day and reported on their music-listening behavior. Statistical learning procedures on multilevel regression models and multilevel structural equation modeling were used to determine the most important predictors and analyze mediation processes between person, situation, functions of listening, and music selection. Results revealed that the features of music selected in daily life were predominantly determined by situational characteristics, whereas consistent individual differences were of minor importance. Functions of music listening were found to act as a mediator between characteristics of the situation and music-selection behavior. We further observed several significant random effects, which indicated that individuals differed in how situational variables affected their music selection behavior. Our findings suggest a need to shift the focus of music-listening research from individual differences to situational influences, including potential person-situation interactions.
Actin droplet machine
(2019)
The actin droplet machine is a computer model of a three-dimensional network of actin bundles developed in a droplet of a physiological solution, which implements mappings of sets of binary strings. The actin bundle network is conductive to travelling excitations, i.e. impulses. The machine is interfaced with an arbitrary selected set of k electrodes through which stimuli, binary strings of length k represented by impulses generated on the electrodes, are applied and responses are recorded. The responses are recorded in a form of impulses and then converted to binary strings. The machine's state is a binary string of length k: if there is an impulse recorded on the ith electrode, there is a '1' in the ith position of the string, and '0' otherwise. We present a design of the machine and analyse its state transition graphs. We envisage that actin droplet machines could form an elementary processor of future massive parallel computers made from biopolymers.
Actin filaments are conductive to ionic currents, mechanical and voltage solitons. These travelling localisations can be utilised to generate computing circuits from actin networks. The propagation of localisations on a single actin filament is experimentally unfeasible to control. Therefore, we consider excitation waves propagating on bundles of actin filaments. In computational experiments with a two-dimensional slice of an actin bundle network we show that by using an arbitrary arrangement of electrodes, it is possible to implement two-inputs-one-output circuits.
Through constant technical progress, multi-user virtual reality is transforming towards a social activity that is no longer only used by remote users, but also in large-scale location-based experiences. We evaluate the usage of realtime-tracked avatars in co-located business-oriented applications in a "guide-user-scenario" in comparison to audio only instructions. The present study examined the effect of an avatar-guide on the user-related factors of Spatial Presence, Social Presence, User Experience and Task Load in order to propose design guidelines for co-located collaborative immersive virtual environments. Therefore, an application was developed and a user study with 40 participants was conducted in order to compare both guiding techniques of a realtime-tracked avatar guide and a non-visualised guide with otherwise constant conditions. Results reveal that the avatar-guide enhanced and stimulated communicative processes while facilitating interaction possibilities and creating a higher sense of mental immersion for users. Furthermore, the avatar-guide appeared to make the storyline more engaging and exciting while helping users adapt to the medium of virtual reality. Even though no assertion could be made concerning the Task Load factor, the avatar-guide achieved a higher subjective value on User Experience. Due to the results, avatars can be considered valuable social elements in the design of future co-located collaborative virtual environments.
Multi-user virtual reality is transforming towards a social activity that is no longer only used by remote users, but also in large-scale location-based experiences. Usage of realtime-tracked avatars in co-located business-oriented applications with a ”guide-user-scenario” is examined for user-related factors of Spatial Presence, Social Presence, User Experience and Task Load. A user study was conducted in order to compare both techniques of a realtime-tracked avatar and a non-visualised guide. Results reveal that the avatar-guide enhanced and stimulated communicative processes while facilitating interaction possibilities and creating a higher sense of mental immersion for users and engagement.
This article describes the possibilities and problems that occur using the SteamVR tracking 2.0 system as a camera tracking system in a virtual studio and explains an approach for implementation and calibration within a professional studio environment. The tracking system allows for cost effective deployment. Relevant application fields are also mixed reality recording and streaming of AR and VR experiences.
Live video streaming is becoming increasingly popular as a form of interaction in social applications. One of its main advantages is an ability to immediately create and connect a community of remote users on the spot. In this paper we discuss how this feature can be used for crowdsourced completion of simple visual search tasks (such as finding specific objects in libraries and stores, or navigating around live events) and social interactions through mobile mixed reality telepresence interfaces. We present a prototype application that allows users to create a mixed reality space with a photospherical imagery as a background and interact with other connected users through viewpoint, audio, and video sharing, as well as realtime annotations in mixed reality space. Believing in the novelty of our system, we conducted a short series of interviews with industry professionals on the possible applications of our system. We discuss proposed use-cases for user evaluation, as well as outline future extensions of our system.
Augmented reality for supporting manual non-destructive ultrasonic testing of metal pipes and plates
(2018)
We describe an application of augmented reality technology for non-destructive testing of products in the metal-industry. The prototype is created with hard- and software, that is usually employed in the gaming industry, and delivers positions for creating ultra- sonic material scans (C-scans). Using a stereo camera in combination with an hmd enables realtime visualisation of the probes path, as well as the setting of virtual markers on the specimen. As a part of the implementation the downhill simplex optimization algorithm is implemented to fit the specimen to a cloud of recorded surface points. The accuracy is statistically tested and evaluated with the result, that the tracking system is accurate up to ca. 1-2 millimeters in well set-up conditions. This paper is of interest not only for research institutes of the metal-industry, but also for any areas of work, in which the enhancement with augmented reality is possible and a precise tracking is necessary.
In this paper we propose an integrated immersive augmented reality solution for a software tool supporting spacecraft design and verification. The spacecraft design process relies on expertise in many domains, such as thermal and structural engineering. The various subsystems of a spacecraft are highly interdependent and have differing requirements and constraints. In this context, interactive visualizations play an important role in making expert knowledge accessible. Recent immersive display technologies offer new ways of presenting and interacting with computer-generated content. Possibilities and challenges for spacecraft configuration employing these technologies are explored and discussed. A user interface design for an application using the Microsoft HoloLens is proposed. To this end, techniques for selecting a spacecraft component and manipulating its position and orientation in 3D space are developed and evaluated. Thus, advantages and limitations of this approach to spacecraft configuration are revealed and discussed.
Mixed reality telepresence is becoming an increasingly popular form of interaction in social and collaborative applications. We are interested in how created virtual spaces can be archived, mapped, shared, and reused among different applications. Therefore, we propose a decentralized blockchain-based peer-to-peer model of distribution, with virtual spaces represented as blocks. We demonstrate the integration of our system in a collaborative mixed reality application and discuss the benefits and limitations of our approach.
Marktdaten
(2018)
Die in der Schriftenreihe Trading verwendeten Forschungsdaten beinhalten historische Kursdaten, geliefert von Lenz+Partner AG (Deutschland), für eine Auswahl an Aktien. Die Datei „FEBRDUSA_1“ zeigt diese Auswahl in Form der deutschen Wertpapierkennnummer (Spalte „Titel“), des Handelszeitraums (Spalten „Beginn“ und „Ende“) und des Aktiennamens. Kursdaten sind in dieser Datei nicht enthalten, sondern liegen in einer umfangreichen Datenbank vor.
Die Marktdaten umfassen 867 Aktien und sind das Ergebnis eines im Jahr 2015 durchgeführten Auswahlprozesses mit dem Ziel, Datenqualität und Handelbarkeit der Aktien zu verbessern. Es wurden folgende Bedingungen gefordert:
- Die Aktien werden an der Frankfurter Börse gehandelt.
- Sie sind in einem der deutschen Aktienindizes DAX, MDAX, TECDAX, SDAX, HDAX, CDAX, Technology All Share, Prime All Share und GEX oder in den amerikanischen Aktienindizes S&P 500 oder Nasdaq 100 gelistet.
- Die Kursdaten der in Frankfurt gehandelten Aktien enden nicht vor dem Jahr 2014.
- Der (unbereinigte) Eröffnungskurs Ende 2013 beträgt mindestens 1 EUR. Diese Bedingung soll dazu beitragen, das Handeln von „penny stocks“ zu verhindern.
Die vorliegende Marktdefinition resultierte in 867 Aktien, die frühestens am 11. Dezember 2014 enden, sodass eine Auswertung der Marktdaten mit vollständigen Kurswerten bis zu diesem Zeitpunkt möglich ist. Der Markt ist groß genug, um interessante Kaufbedingungen mit einer ausreichend großen Anzahl an Kaufkandidaten zu untersuchen.
We present a system that exploits mobile rotational tracking and photospherical imagery to allow users to share their environment with remotely connected peers “on the go.” We surveyed related interfaces and developed a unique groupware application that shares a mixed reality space with spatially-oriented live video feeds. Users can collaborate through realtime audio, video, and drawings in a virtual space. The developed system was tested in a preliminary user study, which confirmed an increase in spatial and situational awareness among viewers as well as reduction in cognitive workload. Believing that our system provides a novel style of collaboration in mixed reality environments, we discuss future applications and extensions of our prototype.
Situational influences on music selection behavior in daily life: An experience sampling study
(2018)
Classification of Beyond-Reality Interaction Techniques in Spatial Human-Computer Interaction
(2018)
Cliffhanger-VR
(2018)
Acquiring human motion data from video images plays an important role in the field of computer vision. Ground truth tracking systems require markers to create high quality motion data. But in many applications it is desired to work without markers. In recent years affordable hardware for markerless tracking systems was made available at a consumer level. Efficient depth camera systems based on Time-of-Flight sensors and structured light systems have made it possible to record motion data in real time. However, the gap between the quality of marker-based and markerless systems is high. The error sources of a markerless motion tracking pipeline are discussed and a model-based filter is proposed, which adapts depending on spatial location. The proposed method is then proven to be more robust and accurate than the unfiltered data stream and can be used to visually enhance the presence of an actor within a virtual environment in live broadcast productions.
The article discusses the question of “How to convey the experience in a virtual environment to third parties?” and explains the different technical implementations which can be used for live streaming and recording of a mixed reality experience. The real-world applications of our approach include education, entertainment, e- sports, tutorials, and cinematic trailers, which can benefit from our research by finding a suitable solution for their needs. We explain and outline our Mixed Reality systems as well as discuss the experience of recorded demonstrations of different VR applications, including the need for calibrated camera lens parameters based on realtime encoder values.
A method of determining the distance of an object from an automated vehicle based on images taken by a monocular image acquiring device. The object is recognized with an object-class by means of an image processing system. Respective position data are determined from the images using a pinhole camera model based on the object-class. Position data indicating in world coordinates the position of a reference point of the object with respect to the plane of the road is used with a scaling factor of the pinhole camera model estimated by means of a Bayes estimator using the position data as observations and under the assumption that the reference point of the object is located on the plane of the road with a predefined probability. The distance of the object from the automated vehicle is calculated from the estimated scaling factor using the pinhole camera model.
Investing as Random Trial
(2017)
We introduce an investment algorithm for a market of individual securities. The investment algorithm is derived from constraints depending on investment parameters in order to limit the risk and to take into account an individual investor. One constraint is devoted to trading costs. Purchased securities are selected randomly among securities that meet the buy condition, making trading a random trial. Simulations with historical price data are demonstrated for a simple example: The buy condition is evaluated on the basis of the price relationship for two subsequent trading days and the sales condition is defined by holding securities only for one day. A trading expert evaluates the expected return for the investment algorithm with respect to the random selection. Thus, the expert informs precisely on how many market players perform using the same investment algorithm. Its findings are for a parametrized set of buy conditions simultaneously, which makes a trading expert a valuable tool for theorists as well as for practitioners. In our example, the trading expert demonstrated clearly a significant mean reversion effect for a horizon of one day.
Mobile live video streaming is becoming an increasingly popular form of interaction both in social media and remote collaboration scenarios. However, in most cases the streamed video does not take mobile devices' spatial data into account (e.g., the viewers do not know the spatial orientation of a streamer), or use such data only in specific scenarios (e.g., to navigate around a spherical video stream).
More than three decades of ongoing research in immersive modelling has revealed many advantages of creating objects in virtual environments. Even though there are many benefits, the potential of immersive modelling has only been partly exploited due to unresolved problems such as ergonomic problems, numerous challenges with user interaction and the inability to perform exact, fast and progressive refinements. This paper explores past research, shows alternative approaches and proposes novel interaction tools for pending problems. An immersive modelling application for polygon meshes is created from scratch and tested by professional users of desktop modelling tools, such as Autodesk Maya, in order to assess the efficiency, comfort and speed of the proposed application with direct comparison to professional desktop modelling tools.