HFTor - HfT Open Repository (Hochschule für Technik Stuttgart)
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KNIGHT Learning Analytics Architecture for Betterment of Student Education
No full textArtificial intelligence has been revolutionizing education analytics and improving student education continuously. Our innovative architecture allows students and educators to analyze activities from Learning Management Systems (LMS) such as Moodle and other data sources, to review their performance, get personalized learning experiences, and receive realistic predictions of their student’s performance. Furthermore, our proposed KNIGHT LA architecture can detect at-risk pupils early on, allowing for timely interventions and assisting teachers in making data-driven decisions. In addition to this, the learning model has the ability to minimize human bias and reliance on conventional measurements, resulting in a more egalitarian and accessible educational system. However, the ethical considerations of employing these technologies, such as privacy and the threat of biased outcomes, must be considered. Overall, incorporating smart methodologies into education analytics has significant raise of around 25% of promise for improving student education and establishing a more inclusive and equitable educational system
Maximum Fast time-weighted levels - When can a transient be seen as a Dirac impulse?
No full textIt is common practice to use maximum FAST time-weighted sound pressure levels to assess transient impact noise, as these levels correlate well with human perception of impact noise. Maximum FAST time-weighted levels are known to be dependent on the reverberation time of the receiving room. In previous studies, an analytical correction term was developed using a Dirac impulse. The correction term is used to calculate the maximum FAST time-weighted levels from peak sound pressure levels. Peak levels are independent of the reverberation time of the room. Applying the correction term makes it possible to compare measurement results from different rooms. The correction term has been validated in several studies for the standard rubber impact ball. In this paper, the influence of the source signal (Dirac impulse) on the correction term is studied. Analytical and numerical models are employed to investigate the consequences of stretching the impulse in time and of changing its shape. The results are compared with empirical solutions developed in other studies
Land resource allocation between biomass and ground-mounted PV under consideration of the food–water–energy nexus framework at regional scale
No full textAn economy’s shift towards climate neutrality requires a massive expansion of renewable energy production. Next to wind, photovoltaic (PV) and biomass will be key renewable resources in many regions. A land-use change to PV increases local electricity production, but influences regional water and biomass availability.
However, a regional quantitative guideline on biomass-PV tradeoffs on all agricultural fields under food–water–energy (FWE) nexus thinking is still missing. This work presents a comprehensive bottom-up interdependency assessment between ground-mounted PV and biomass generation on a regional scale by integrating independently established methods based on consistent input data at spatial field resolution. Furthermore, impacts on food and water availability are also quantified. Four scenarios were set up based on current policies and future trend, emphasizing PV yield, feasibility, profit, and biomass yields, respectively. The assessment and scenarios are applied to three representative German counties with distinguished land-use structures and geometries as case studies. Scenario analysis shows that the optimal technical strategy is to free the market letting individuals to maximize revenue from their lands, which likely simultaneously is good for society, achieves high PV yields with limited biomass losses, and has more significant crop water saving effects
Visualisation of Traffic Flows for Public Transport Operations - Requirements from the User's Point of View and Conception.
Get PDFThe need to optimise transport planning is essential in improving patronage of public transport systems. To this end, traffic data and other data sources are needed to make informed decisions about how to plan transport routes. These data sources are readily available in the wake of modern technology; however, due to the large volume of multiple datasets, there is a challenge of how to effectively utilize these datasets.
The main objective of this thesis is to assess how modern visualisation techniques can improve traffic data analysis and optimise transport route planning. To achieve this, a full-stack visual analysis application was developed. This application has two main user interfaces which combine statistical and geographical visualisation techniques to display relevant traffic-related information. On one interface, origin-destination information was visualised in abstract space and geographical space. On the other interface, information such as traffic peak hour, passenger count, temperature variations, etc. were also visualised.
The application was finally assessed by developing an evaluation framework. This framework was used to rate the application’s functionality, usability, credibility, aesthetics, and appropriateness of the visualisation charts. A total of sixteen (16) participants evaluated the application and they rated it highly in all criteria. The participants also gave criticisms and positive feedback which were used to improve the application
Integrating sustainability aspects in the teaching of lightweight structures and their comparison with common structures
No full textThe positive development of the construction industry with regard to CO2 emissions in recent years seemed to initiate the turnaround in the sector. Now the trend is going backwards. Despite increased investments in energy efficiency and lower energy intensity, the construction sector's energy consumption and CO2 emissions have risen again to an all-time high since the COVID 19 pandemic, according to a new report. “Years of warnings about the impacts of climate change have become a reality,” said Inger Andersen, Executive Director of the United Nations Environment Programme (UNEP). “If we do not rapidly cut emissions in line with the Paris Agreement, we will be in deeper trouble.” [6] Construction has evolved over millennia, whereby a large proportion of buildings and civil engineering structures have been designed with an emphasis on not using too much material.
But in view of the threat of global warming, mass extinction of species, energy crisis, finite fossil resources and the not inconsiderable contribution of construction, it is essential to include aspects of sustainability in every building. The awareness that we need to counteract global warming and think and plan sustainably has grown considerably over the last decades. We do
have the knowledge of how the building industry can reduce environmentally harmful actions in theory, but a fast implementation seems at the moment to be the biggest problem. This challenge raises the question of which possibilities we have in structural design and especially in the design of lightweight structures to promote a rapid and continuous conversion towards sustainable and environmentally friendly design into everyday building design and practice.
One key point besides awareness of the situation is to create a basis of understanding and tools for those who are involved in the building industry in order to make the right decisions towards more sustainable solutions in project planning and execution but also for being able to explain and provide well-founded calculations. Thus, teaching and research may contribute to a more rapid change in rethinking sustainable construction. This paper explains a teaching concept for this purpose, which is intended to promote the understanding and learning of sustainability aspects for reducing environmental impacts in construction. The teaching concept is intended to create an understanding of the considered selection of materials, comparison of materialized building components through to the sustainability concept of entire buildings and lightweight construction in three simple stages.
In addition, students should explicitly understand how the approaches they learn can be applied in practice
Examining Car Accident Prediction Techniques and Road Traffic Congestion: A Comparative Analysis of Road Safety and Prevention of World Challenges in Low-Income and High-Income Countries
No full textRoad accidents are a significant negative outcome of transportation systems, causing injuries, fatalities, traffic congestion, and economic losses. As cities expand and the number of vehicles on the road increases, traffic accidents (TAs) have become a significant problem. Studies have shown that urban development plays a more significant role in transportation safety than previously thought. Low-income countries have higher fatality rates than high-income countries, according to the Permanent International Association of Road Congress (PIARC) and the World Health Organization (WHO). Predicting and preventing the occurrence of accidents and congestion is necessary worldwide, especially in developing countries where fatality rates are higher. The objective of this study is to examine and make a comparative analysis in low-income and high-income countries of the existing literature on the global challenge of car accidents and use its prediction techniques to enhance road safety and reduce traffic congestion. The study evaluates various approaches such as logistic regression, decision tree, random forest, deep neural network, support vector machine, random forest, K-nearest neighbors, Naïve Bayes, empirical Bayes, geospatial analysis methods, and UIMA, NSGA-II, and MOPS algorithms. The research identifies current challenges, prevention ideas, and future directions for preventing accidents and congestion on the road network. Integrating GIS-based spatial statistical methods and temporal data and utilizing advanced optimization algorithms and machine learning methods can result in accurate prediction models that can help identify accident hotspots and reduce congestions and enhance traffic safety and mitigate their occurrence. Effectively preventing urban traffic congestion requires the integration of spatial data into precise accident prediction models. By employing spatial analysis, road safety planning can be enhanced, high-risk areas can be identified, interventions can be evaluated, and resources can be optimally allocated to facilitate effective road safety measures and decision-making, especially in settings with limited resources. Therefore, it is crucial to consider ML and spatial analysis techniques and advanced optimization algorithms to enhance traffic flow control, in road safety research and transport planning efforts
Messung des Spektralen Absorptionskoeffizienten (SAK) in Abwasseranlagen – Arbeitsbericht des DWA-Fachauschusses KA -13 „Automatisierung von Kläranlagen“
No full textThe Relationship between Preparation, Impression Management, and Interview Performance in high-stakes Personnel Selection: A Field Study of Airline Pilot Applicants
No full textObjective
The present study investigates how airline pilot applicants prepare for a personnel selection procedure and how this relates to their deceptive and honest impression management (IM) in the job interview and their interview performance.
Background
It is thus far unclear how preparation relates to IM in real-world and high-stakes settings. This is of particular importance for the aviation industry, because numerous commercial providers offer preparation courses for selection procedures potentially impacting selection decisions.
Method
We conducted a field study of high-stakes job interviews embedded in a selection procedure for airline pilots. Data from 100 interviewees was acquired.
Results
The variety of preparation strategies an applicant used was positively correlated with two deceptive IM (faking) strategies in the job interview. Moreover, low effort preparation via social media and guidebooks was positively correlated with overall faking. The variety of preparation and preparation via social media were also positively correlated with honest IM. However, neither the aforementioned preparation nor IM showed significant correlations with the interview performance.
Conclusion
The effects of preparation depend on the specific preparation methods used. Certain methods of preparation are positively associated with applicants’ use of IM strategies in the job interview
Modelling and Assessment of Biomass-PV Tradeoff within the Framework of the Food-Energy-Water Nexus
No full textFood, water and energy are three essential resources for human well-being, poverty reduction and sustainable development. These resources are very much linked to one another, meaning that the actions in any one particular area often can have effects in one or both of the other areas. At the same time, an economy's shift towards climate neutrality requires a massive expansion of energy production from renewable sources. Among these ground-mounted photovoltaic (PV) and biomass will be expanded massively to meet the clean energy generation goal, simultaneously influence regional water and food availability and supply security. It is crucial to understand Food-Water-Energy Nexus (FWE) nexus during the energy transition. However, current studies have limitation both methodically (qualitative assessments) and spatially (aggregated data on a national level is more available). Firstly, a consistent share input data set in geographical format was created with the resolution of building/field. An energy simulation platform (SimStadt) was then extended with new workflows on biomass potential, ground-mounted PV potential, food demand/potential, and urban water demand. Combining with existing workflows on urban building heating/electricity demand and roof PV potential, the dissertation created a complete simulation environmental covering most-relating FWE topics in energy transition with consistent input and output structures at a fine resolution. Secondly, the most representative inter-linkage between ground-mounted PV and biomass on hinterland is investigated in details with the new tools. The output data of each field from ground-mounted PV and biomass workflows are linked and ranked according to the scenarios emphasizing PV yield, feasibility, profit, or biomass. The assessment and scenarios are applied at three representative German counties with distinguished land-use structures and geometries as case studies. Results show that current policies does not guarantee the technically efficient allocation of fields. The optimal technical strategy is to follow the individual market profit drive, which is very likely, at the same time for the social good, to achieve high PV yields with limited biomass losses and more significant crop water-saving effects. The local food, water, and energy demands are also included as a metric for resource allocation on the potential side. Besides focusing on the biomass-PV tradeoff simulation and analysis, pioneer works have also been done to test the transferability of the method in cases outside Germany, and the complement of urban solid waste to agricultural biomass is explored to achieve energy autarky
