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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.
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.
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.
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.
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.
This essay looks at the potentials and limitations of user research for studies on the practice of drama education. To date, this field has been dominated by impact studies. After illustrating the blind spots that are created by taking this research approach to the practice of drama education, we will present the user research perspective and look at the opportunities that it provides to generate new, differentiated knowledge. User research makes it possible to illuminate the processes of acquiring and using knowledge in terms of its delivery. It also provides a potential framework of analysis for placing these processes in the delivery context, which includes subjective learning types, relevance and institutional and social conditions. This expanded perspective will make it possible to identify the factors that foster and limit benefits and reflect them in practice.
Heterogeneous catalysts usually consist of porous, inorganic materials. Especially in the mobile application, e.g., in exhaust gas catalysis as a part of the gas line of an engine, there are loads due to vibrations and high gas velocities. It can be assumed that physical stress will lead to a loss of the catalytically active coating. The present contribution describes experimental setups and methods for a systematic and reproducible investigation of the main influences to the mass loss due to vibrational and fluid‐mechanical stress caused by particle‐free gas flows.
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.
Impact of Renewable Energy Expansion to the Balancing Energy Demand of Differential Balancing Groups
(2018)
The research addresses the present situation on the German electricity market caused by variable renewable energy sources. The increasing number of households with photovoltaic and battery storage systems and their impacts require special attention. These systems change the traditional electricity customer from the sole electricity consumer to an electricity producer and consumer in one person. These so-called prosumers differ in their actual electricity demand from the initially estimated electricity demand with standard load profile. This discrepancy results in deviations within a differential balancing group. Thereby, the main finding of this research is a significant higher balancing energy demand with the expansion of photovoltaic and battery storage systems. Hence, the standard load profile is particularly not suitable for differential balancing groups with a high penetration of solar systems and still less suitable for groups with solar and battery storage systems
Poor young people more often face health difficulties, (learning) disabilities, and are overrepresented in special schools. Consequently, youth from poor households disproportionately frequently participate in disability‐specific programs aiming to improve their educational levels and labor market opportunities. They face a double burden of disability and poverty. In our study, we look at poor and non‐poor youth with disabilities (YPWD) who participate in vocational rehabilitation (VR) and whether VR helps them (a) in transitioning into employment and (b) in leaving poverty. We examine the association between the receipt of initial basic income support (BIS) as a poverty indicator, later labor market outcomes, and earned vocational qualification using administrative data. We make use of a sample of all persons accepted for VR in 2010 (N = 36,645). We employ logit models on VR attendees’ labor market outcomes three and five years after being accepted for VR as well as on their earned vocational qualifications. Beside initial poverty status, we control for educational level, type, and degree of disability and program pattern during the VR process. Our findings show that YPWD from poor households have a decreased likelihood of a vocational certificate and employment. Additionally, they are more likely to receive BIS than young people not from poor households and thus more likely to remain poor. In conclusion, VR seems to support poor YPWD less in their school‐to‐work transitions. Thus, disability‐specific programs should be more tailored to the social situations of participants, and counsellors should be more sensitive to their social backgrounds.
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.
Thermoelectric generators (TEGs) have the ability to convert waste heat into electrical energy under unfavorable conditions and are becoming increasingly popular in academia, but have not yet achieved a broad commercial success, due to the still comparably low efficiency. To increase the efficiency and economic viability of TEGs, research is performed on the materials on one hand and on the system connection on the other. In the latter case, the net output power of the cooling system plays a key role. At first glance, passive cooling seems preferable to active cooling because it does not affect the net electrical output power. However, as shown in the present review, the active cooling is to be preferred for net output power. The situation is similar in air and water-cooling. Even though air-cooling is easier to set up, the water-cooling should be preferred to achieve higher net output power. It is shown that microchannel cooling has similar hydraulic performance to conventional cooling and inserts increase the net output power of TEG. As the review reveals that active water-cooling should be the method of choice to achieve high net output power, it also shows that a careful optimization is necessary to exploit the potential.
The population is growing constantly in urban areas. This results in an increasing demand for mobility solutions while it is also worldwide aimed to reduce greenhouse gas emissions. This paper summarizes the results of a comparative study concerning the greenhouse gas emissions (based on carbon footprint) caused by alternative urban passenger transportation systems. The emissions for the vehicles and their infrastructure are analyszed over the entire life cycle from manufacturing up to their end of life. An existing cable car sytem in La Paz, Bolivia was analysed and evaluated in comparison to other modes of transportation such as small busses, large busses and a tram. According to the system definitions and the considered balance framework the study shows that beside the use of the systems the materials and the manufacturing as well as the infrastructure have a significant impact on the total emissions over the life cycle. To put focus on the „true and real“ impacts to the society it is preferable to consider the measurement results in total absolute emissions.
We present a novel metric Spatial Recall Index to assess the performance of machine-learning (ML) algorithms for automotive applications, focusing on where in the image which performance occurs. Typical metrics like intersection-over-union (IoU), precisionrecallcurves or average precision (AP) quantify the performance over a whole database of images, neglecting spatial performance variations. But as the optics of camera systems are spatially variable over the field of view, the performance of ML-based algorithms is also a function of space, which we show in simulation: A realistic objective lens based on a Cooke-triplet that exhibits typical optical aberrations like astigmatism and chromatic aberration, all variable over field, is modeled. The model is then applied to a subset of the BDD100k dataset with spatially-varying kernels. We then quantify local changes in the performance of the pre-trained Mask R-CNN algorithm. Our examples demonstrate the spatial dependence of the performance of ML-based algorithms from the optical quality over field, highlighting the need to take the spatial dimension into account when training ML-based algorithms, especially when looking forward to autonomous driving applications.
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 Long Tail theory serves as an explanation for market change triggered through evolving online market conditions. However, it is often referred to without empirical validation, or with inconsistent findings on its applicability. Therefore, this paper analyses the applicability of the Long Tail theory to German online media offerings as of 2014 and 2016, focusing on offerings that serve information purposes (information offerings). Based on a unique dataset of commercially oriented online media offerings (Longitudinal IntermediaPlus 2014–2016), an analysis for three Long Tail characteristics (variety increase, opposing concentration between hit and niche offerings and niche market share increase) is conducted. By additionally distinguishing between political and entertainment-oriented information offerings as boundaries of democratized online market conditions the analysis reveals that the Long Tail theory is not fully applicable to any market sample, and especially not to politically oriented offerings.
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.
Markerless talent tracking is widely used for interactions and animations within virtual environments. In a virtual (tv) studio talents could be overburden by interaction tasks because camera and text require extensive attention. We take a look into animations and inter- actions within a studio, which do not require any special attention or learning. We show the generation of an artificial shadow from a talent, which ease the keying process, where separation of real shadows from the background is a difficult task. We also demonstrate animations of footsteps and dust. Furthermore, capturing talents’ height can also be used to adjust the parameters of elements in the virtual environment, like the position and scaling of a virtual display. In addition to the talents, a rigid body was tracked as placeholder for graphics, easing the interaction tasks for a talent. Two test productions show the possibilities, which subtle animations offer. In the second production, the rendering was improved (shadows, filtering, normal maps, ...) and instead of using the rigid body to move an object (a flag), the animation was only controlled by the hand’s position.
The “fair” taxation of digital business models is challenging. One of the key aspects – both policy makers and the public opinion consider as most pressuring – is the determination of intragroup transfer prices for intangibles used in digital business models. In this paper, we address the issue of a “perceived fair” taxation of the digital economy in the light of the arm’s length principle based on a survey with transfer pricing experts. The aim of the survey is not to estimate arm’s length profit allocations but rather to elicit fairness considerations in different transfer pricing related scenarios. In a digital economy framework where arm’s length profits are distributed extremely inequitably, subjects perceive this distribution of profits as most unfair compared to more balanced scenarios. Consequently, subjects propose a “fair” distribution of profits that substantially differs from the exogenously given arm’s length allocation. In scenarios with a more balanced arm’s length allocation of profits, we find that the perceived fairness for the expert groups increases while a control group of business students is almost not influenced by the arm’s length allocation of profits.
The OECD Base Erosion Profit Shifting (BEPS) Initiative as well as the current fairness oriented public discussion regarding the taxation of digital business models highlight the importance and complexity of the arm's length principle. In a theoretical model of an internationally fragmented digital good's production process, we show that fairness considerations of tax authorities (namely inequity aversion) can result in a falling apart between a perceived "fair" and arm's length distribution of profits across tax jurisdictions. Our model predicts that a multinational firm follows the fundamental paradigm of international taxation, i.e. the arm's length principle, to properly incentivize internal agents involved in the production of a digital good. However, with inequity averse tax authorities, we find that tax authorities "prefer" a more equal distribution of profits compared to the arm's length allocation. From a multinational firm's perspective, inequity aversion among tax authorities dampens the strategic effect to - in accordance with arm's length principle - shift profits to low tax countries.
Methanol Synthesis with Steel Mill Gases: Performance Investigations in an On‐Site Technical Center
(2021)