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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.
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.
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.
The links between innovativeness as a driver of economic performance, and the determinants of innovativeness have been investigated by management scholars and economists for decades, focusing mostly on “hard factors” as investment in research and development, or education. Focusing on a relatively neglected, but in times of globalization even more important aspect, the infuence of cultural characteristics on innovativeness, we apply diferent econometric models to test for links between cultural tightness and looseness on the one hand, and national innovativeness on the other hand. We fnd that cultural tightness—in the sense of homogenous and intolerant societies—has a negative link to national innovativeness, while cultural looseness—in the sense of tolerant and diverse societies—displays a positive link to national innovativeness.
In order to determine demand as precisely as possible, many businesses use several forecasting methods. The aim of forecasting is to determine future demand based on data from the past. The use of a specific method is not always easy and depends on a number of factors. To help prospective engineers find the most suitable forecasting method for a specific problem, a forecasting game was developed and then evaluated.
The paper describes the design and the evaluation of the forecasting game. In order to provide an overview of existing forecasting methods, the first part of the paper examined the mathematical fundamentals of eight different forecasting methods and outlined the requirements for their application.
The second part of the paper describes the creation of a forecasting game in which prospective engineers can learn how to determine the appropriate forecasting method for specific scenarios. In total, five scenarios covering the three different demand patterns (linear/stationary, trend and seasonal) as well as the forecast quality methods were developed and can be played through. For each scenario, the player has to choose the most appropriate forecasting method for a specific problem based on a self-created task description. To make the game as realistic as possible, a fictional company with a background story was designed.
The last part was about the evaluation of the forecasting game. For the evaluation, a student survey to gather the opinions of the students was conducted. The results of the student survey show an overall positive evaluation of the simulation game by the students. However, the test also showed that the game takes a certain amount of time. Since only 15 of the approximately 30 students who tested the game participated in the evaluation, the results are not significant.