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Im Rahmen der vier Kopernikus-Projekte – Ariadne, ENSURE, P2X und SynErgie – wird die Transformation des deutschen Energiesystems hin zur Klimaneutralität analysiert. Im vorliegenden Bericht werden hierbei robuste Kernaussagen und relevante Unsicherheiten derjenigen Szenarien der Kopernikus-Schwesterprojekte dargestellt, die zur Zielsetzung die Klimaneutralität 2045 haben. Hierbei liegt der Fokus auf Indikatoren, die eine besonders hohe klimapolitische Relevanz haben.
Analysis and Improvement of Engineering Exams Toward Competence Orientation by Using an AI Chatbot
(2024)
ChatGPT is currently one of the most advanced general chatbots. This development leads to diverse challenges in higher education, like new forms of teaching and learning, additional exam methods, new possibilities for plagiarism, and many more topics. On the other side with the development of advanced AI tools, pure knowledge will be less and less important, and demands from industry will change toward graduates with higher competencies. Education has therefore to be changed from knowledge-centered toward competence centered. The goal of this article is to use ChatGPT for analyzing and improving the competence orientation of exams in engineering education. The authors use ChatGPT to analyze exams from different engineering subjects to evaluate the performance of this chatbot and draw conclusions about the competence orientation of the tested exams. The obtained information is used to develop ideas for increasing the competence orientation of exams. From this analysis, it is visible that ChatGPT gives good performance mainly where knowledge is tested. It has, however, much more problems with transfer questions or tasks where students need creativity or complex insights for finding new solutions. Based on this result, exams and also lectures can be optimized toward competence orientation.
This article describes a contactless fiber-optic position sensor. It comprises a Polymer Optical Fiber that is grinded to form a D-shaped cross-section with an exposed fiber core. This sensor has two photodiodes at both fiber ends to measure the emitted light intensity. Light is coupled using a red LED at the side face into the exposed core of the fiber at a defined position. The position of the LED at the length of the fiber is measured by calculating the optical power quotient measured by both photodiodes. To test this sensor, Polymer Optical Fibers with different side surface roughness are produced and qualified. Measurements show that the optical power quotient is reproducible and nearly linear over the length of the fiber. It is also seen that the fiber attenuation increases when grinding the fiber side-face with rougher sandpaper. Position measurements show an absolute position error of this sensor in the range of a few millimeters. Microscope images show surface defects along the polished side face of the fiber that are expected to lead to a nonuniform attenuation along the fiber and cause the position errors. Overall, it is proven that this sensor principle works as a contactless low-cost position sensor for short distances with an absolute position standard deviation error lower than 1 mm.
As more energy systems from renewable sources and the electricity market becomes more volatile, new solutions to ensure the security of supply are tested. Microgrids offer a possibility to prevent construction downtime. In order to use the energy sources and storage facilities of the microgrid effectively, load forecasting algorithms are essential. Thus, in this study a short term load forecasting model for a construction company is designed, that will be used for managing a microgrid as well as the general load consumption. This paper proposes the use of the XGBoost algorithm for the 36-hour forecast including predictors based on past measurements as well as information extracted from the timestamp. Moreover, it is shown that including load profiles attained by conventional methods has the potential to improve the accuracy of the model.
Industrial plants can provide reactive power (Q) for system- and grid-serving behavior, for which a functioning reactive power management system is essential. To make reactive power retrieval as efficient and safe as possible, the selection of reactive power sources to meet the Q-demand must consider their sensitivities and the restrictions of the industrial grid, such as operating equipment utilization or voltage limits. On this basis, a concept for a sensitivity-based control strategy that manages the reactive power retrieval of multiple reactive power sources depending on a predefined reactive power demand value is proposed. Based on the simulation of an industrial plant in the medium-voltage grid, which can provide reactive power in the form of industrial compensation systems (ICS) and generators, the operation of the algorithm is shown.
Commercially available contact angle (CA) measuring devices usually do not allow for the application of magnetic fields to the sample under test. A setup for measuring the CA of liquids on magnetosensitive surfaces has been developed specifically for investigating the surfaces of magnetoactive elastomers (MAEs). The addition of a programmable linear stage, which moves a permanent magnet, allows for fine control of the magnetic field applied to the MAE without the need for large and power-consuming electromagnets. Paired with a custom control and evaluation software, this measurement setup operates semiautomatically, limiting operator error and increasing precision, speed, as well as repeatability of static and dynamic CA measurements for different magnetoactive materials. The software is equipped with robust droplet fitting algorithms to avoid experimental challenges arising with soft magnetoactive materials, such as the curling of sample edges or diffuse non-reflective surfaces. Several application examples on MAE surfaces, both processed and unprocessed, are presented.
Acoustic emission (AE) testing recently found its application in the wafer testing sector of the semiconductor industry. To find out the mechanical robustness of semiconductor devices, contact pads on the chip surface are intentionally overstressed with an indenter tip and the appearing oxide cracks are detected with help of the generated AE signals. This is done in a customized test bench with a patented sensor-indenter system. This paper presents an improved version of the measurement setup that solves certain disadvantages of it and can be used in a standard wafer prober. The main components of the developed sensor system are a strain gauge for contact force measurement and a piezoelectric sensor element for AE signal detection. Both components are integrated on a cantilever beam which has an exchangeable indenter tip at its free end. The cantilever probe is electrically conductive to enable electrical tests via the indenter tip. This smart sensor-cantilever combination (SCC) can be mounted with several adapter components on a carrier plate to place it in a wafer prober. For both sensor elements amplifier circuits are developed to enhance their signal-to-noise ratios (SNRs). A prototype setup is shown together with simulated and experimental results to demonstrate its performance. The mechanical properties of the cantilever, as well as the force sensor and the AE crack signals, already fulfill the requirements for an implementation in a wafer prober. To further improve the sensor resolutions and detection limits, several optimizations regarding the design of the SCC are in progress.
In educational research, non-personalized learning content increases learners' cognitive load, causing them to lower their performance and sometimes drop out of the course. Personalizing learning content with learners’ unique characteristics, like learning styles, personality traits, and learning strategies, is being suggested to improve learners’ success. Several theories exist for assessing learners’ unique characteristics. By the end of 2020, 71 learning style theories have been formulated, and research has shown that combining multiple learning style theories to recommend learning paths yields better results. As of the end of 2022, there is no single research that demonstrates a relationship between the Index of Learning Styles (ILS) based Felder-Silverman learning style model (FSLSM) dimensions, Big Five (BFI-10) based personality traits, and the Learning strategies in studying (LIST-K) based learning strategies factors for personalizing learning content.
In this paper, an innovative approach is proposed to estimate the relationship between these theories and map the corresponding learning elements to create personalized learning paths. Respective questionnaires were distributed to 297 higher education students for data collection. A three-step approach was formulated to estimate the relationship between the models. First, a literature search was conducted to find existing studies. Then, an expert interview was carried out with a group of one software engineering education research professor, three doctoral students, and two master’s students. Finally, the correlations between the students' questionnaire responses were calculated. To achieve this, a Bayesian Network was built with expert knowledge from the three-step approach, and the weights were learned from collected data. The probability of individual FSLSM learning style dimensions was estimated for a new test sample. Based on the literature, the learning elements were mapped to the respective FSLSM learning style dimensions and were initiated as learning paths to the learners.
The next steps are proposed to extend this framework and dynamically recommend learning paths in real time. In addition, the individual levels of learning style dimensions, personality traits, and learning strategies can be considered to improve the recommendations. Further, using probabilities for mapping learning elements to learning styles can increase the chance of initiating multiple learning paths for an individual learner.
This paper presents the results of a data collection with the LIST-K questionnaire. This questionnaire measures students’ learning strategies and shows which strategies are particularly dominant or rather weak.
Learning strategies have long been a major area of research in educational science and psychology. In these disciplines, learning strategies are understood as intentional behaviors and cognitive skills that learners employ to effectively complete learning tasks, by selecting, acquiring, organizing, and integrating information into their existing knowledge for long-term retention.
The LIST-K, developed by Klingsieck in 2018, was chosen for accessing learning strategies due to its thematic suitability, widespread use, and test economy. It covers a total of four main categories (i.e., cognitive strategies, metacognitive strategies, management of internal resources, and management of external resources), each of which are subdivided into further subscales. With a total of 39 items answered via a 5-step Likert scale, the LIST-K can cover the topic relatively comprehensively and at the same time be completed in a reasonable amount of time of approximately 10 minutes.
The LIST-K was used as part of a combined data collection along with other questionnaires on their personal data, their preferences regarding certain learning elements, their learning style (i.e. the ILS), and personality (i.e. the BFI-10). A total of 207 students from different study programs participated via an online survey created using the survey tool "LimeSurvey". Participation in the study was voluntary, anonymously, and in compliance with the GDPR.
Overall, the results of the LIST-K show that students are willing to work intensively on relevant topics intensively and to perform beyond the requirements of the course seeking additional learning material. At the same time, however, it is apparent that the organization of their own learning process could still be improved. For example, students start repeating content too late (mean=2.70; SD=0.92) and do not set goals for themselves and do not create a learning plan (mean=3.19; SD=0.90). They also learn without a schedule (mean=2.23; SD=0.97) and miss opportunities to learn together with other students (mean=3.17; SD=0.94).
The findings of the data collection will be used to create an AI-based adaptive learning management system that will create individualized learning paths for students in their respective courses. From the results of the LIST-K, it appears that the adaptive learning management system should primarily support organizational aspects of student learning. Even small impulses (an individual schedule of when to learn what or a hierarchical structuring of the learning material) could help students to complete their courses more successfully and improve their learning.
Eye tracking has proven to be a powerful tool in a variety of empirical research areas; hence, it is steadily gaining attention. Driven by the expanding frontiers of Artificial Intelligence and its potential for data analysis, eye tracking technology offers promising applications in diverse fields, from usability research to cognitive research. The education sector in particular can benefit from the increased use of eye tracking technology - both indirectly, for example by studying the differences in gaze patterns between experts and novices to identify promising strategies, and directly by using the technology itself to teach in future classrooms.
As with any empirical method, the results depend directly on the quality of the data collected. That raises the question of which parameters educators or researchers can influence to maximize the data quality of an eye tracker. This is the starting point of the present work: In an empirical study of eye tracking as an (educational) technology, we systematically examine factors that influence the data quality, such as illumination, sampling frequency, and head orientation - parameters that can be varied without much additional effort in everyday classroom or research use - using two human subjects, an artificial face, and the Tobii Pro Spectrum.
We rely on metrics derived from the raw gaze data, such as accuracy or precision, to measure data quality. The obtained results derive practical advice for educators and researchers, such as using the lowest sampling frequency appropriate for a certain purpose. Thereby, this research fills a gap in the current understanding of eye tracker performance and, by offering best practices, enables researchers or teachers to produce data of the highest quality possible and therefore best results when using eye trackers in laboratories or future classrooms.
Universities are faced with a rising number of dropouts in recent years. This is largely due to students' limited capability of finding individual learning paths through various course materials. However, a possible solution to this problem is the introduction of adaptive learning management systems, which recommend tailored learning paths to students – based on their individual learning styles. For the classification of learning styles, the most commonly used methods are questionnaires and learning analytics. Nevertheless, both methods are prone to errors: questionnaires may give superficial answers due to lack of time or motivation, while learning analytics do not reflect offline learning behavior. This paper proposes an alternative approach to classify students' learning styles by integrating eye tracking in combination with Machine Learning (ML) algorithms.
Incorporating eye tracking technology into the classification process eliminates the potential problems arising from questionnaires or learning analytics by providing a more objective and detailed analysis of the subject's behavior. Moreover, this approach allows for a deeper understanding of subconscious processes and provides valuable insights into the individualized learning preferences of students.
In order to demonstrate this approach, an eye tracking study is conducted with 117 participants using the Tobii Pro Fusion. Using qualitative and quantitative analyses, certain patterns in the subjects' gaze behavior are assigned to their learning styles given by the validated Index of Learning Styles (ILS) questionnaire.
In short, this paper presents an innovative solution to the challenges associated with classifying students' learning styles. By combining eye tracking data with ML algorithms, an accurate and insightful understanding of students' individual learning paths can be achieved, ultimately leading to improved educational outcomes and reduced dropout rates.
Radio access network based positioning and ranging technologies become more and more important for autonomous driving. Positioning on the 5G Sidelink (SL) is discussed in Release 18 (2022-2024) of the Third Generation Partnership Project. For accurate timing-based ranging, a high temporal and spatial resolution is fundamental. The bandwidth for 5G SL positioning is limited due to sharing the existing SL resources with communication. Therefore, we send the positioning reference signal on two separate Component Carriers, i.e. we use a fragmented spectrum. We introduce a two step algorithm for estimating the time of arrival using the inflection point method. We proved a fragmented spectrum can achieve the same accuracy as a continuous spectrum.
In a three-guide coupler with multimode central waveguide, more than two modes of the entire structure participate in the coupling between the outer waveguides. Using a three-mode approximation we found simple conditions for complete power transfer between the outer waveguides: the device length has to match certain multiples of the con- ventionally defined coupling length. The specific form of the relevant modes allows us to design a magneto-optic isolator or circulator with significantly reduced device length (as compared to the conventional nonreciprocal coupler). The performance of the proposed devices is simulated by propagating-mode calculations. Estimates for admissible fabrication tolerances for the layer thicknesses are presented.
In this study, a pilot-scale trickle-bed reactor for biological methanation and various scale-up scenarios for 2023 and 2050 were investigated using LCA. A best- and worst-case scenario for technology development until 2050 was evolved using cross consistency analysis and morphological field, based on which the data for the ecological models were determined.The results show that the plant scale-up has a very positive effect on the ecological consequences of methanation. In the best-case scenario, the values are a factor of 23-780 lower than those of the actual plant today. A hot-spot analysis showed that especially electrolysis operation has a large impact on total emissions. The final Monte-Carlo simulation shows that the technology is likely to achieve a low GWP with a median of 104.0 kg CO2-eq / MWh CH4.
Energieforschung
(2016)
Energieforschung
(2019)
Über uns
Das Regensburg Center of Energy and Resources (RCER) bündelt seit 2012 die Aktivitäten der Ostbayerischen Technischen Hochschule Regensburg (OTH Regensburg) und der regionalen Wirtschaftsunternehmen auf dem Strategiefeld „Energie und Ressourcen“.
Mission: Energieforschung: vernetzen, voranbringen, vermitteln
Das RCER fördert die Vernetzung verschiedener Disziplinen der Energieforschung innerhalb der OTH Regensburg und mit externen Partnern (Firmen, Förderträgern, Forschungsinstitutionen, öffentlichen Einrichtungen). Das RCER ist Ihr Partner beim Voranbringen von Kooperationen und Forschungsvorhaben durch Unterstützung in der Antragsphase, bei der Einwerbung von Projektmitteln und Projektbegleitung im Energiebereich. Das RCER steht für die Vermittlung von Know-how, Basiswissen, aktuellen Fragen und den Technologietransfer rund um das Thema Energie zwischen Wissenschaft, Wirtschaft, Gesellschaft und Politik.
Vision
Wir sind Ihr erster Ansprechpartner und Motor für innovative Energieforschung.
Werte
Verlässlichkeit, Kompetenz, Verantwortungsbewusstsein.Regional verwurzelt und weltoffen
Energieforschung
(2023)
Über uns
Das Regensburg Center of Energy and Resources (RCER) bündelt seit 2012 die Aktivitäten der Ostbayerischen Technischen Hochschule Regensburg (OTH Regensburg) und der regionalen Wirtschaftsunternehmen auf dem Strategiefeld „Energie und Ressourcen“.
Mission: Energieforschung: vernetzen, voranbringen, vermitteln
Das RCER fördert die Vernetzung verschiedener Disziplinen der Energieforschung innerhalb der OTH Regensburg und mit externen Partnern (Firmen, Förderträgern, Forschungsinstitutionen, öffentlichen Einrichtungen). Das RCER ist Ihr Partner beim Voranbringen von Kooperationen und Forschungsvorhaben durch Unterstützung in der Antragsphase, bei der Einwerbung von Projektmitteln und Projektbegleitung im Energiebereich. Das RCER steht für die Vermittlung von Know-how, Basiswissen, aktuellen Fragen und den Technologietransfer rund um das Thema Energie zwischen Wissenschaft, Wirtschaft, Gesellschaft und Politik.
Vision
Wir sind Ihr erster Ansprechpartner und Motor für innovative Energieforschung.
Werte
Verlässlichkeit, Kompetenz, Verantwortungsbewusstsein.Regional verwurzelt und weltoffen
We investigate a system of two waveguides with leaky modes sharing a common substrate (radiatively coupled waveguides). The main advantage of such a system is the possibility of remote coupling. A perturbation theory is developed for both TE and TM polarization. Numerical calculations of dispersion curves and of the coupling length allow us to determine the limitations of the perturbation theory. We study the influence of multimode interference on the process of beating by considering the propagation of a given initial field. Finally, we propose a new design for an effective, integrated optical TE-TM polarization splitter.
Three-guide couplers with multimode central waveguides allow for remote coupling between optical channels. A simple three mode approximation turns out to be sufficient for the description of the main features of the power transfer behavior. The specific form of the relevant modes suggests the design of integrated optical isolators and circulators based on magnetic garnet materials. These novel devices are superior to conventional nonreciprocal couplers with respect to the total length and admissible fabrication tolerances. We characterize the isolation performance and the transmission loss for the proposed devices by propagating mode simulations and estimate the influence of geometry parameter deviations.
Each particular implementation of the beam propagation method (BPM) requires a special procedure allowing for radiation to leave the computational window. We propose a new approach to constructing the finite difference schemes of the BPM at the boundary of the computational window. These schemes are independent of the computed fields and allow for a similar treatment of both interior and boundary points. The new approach can be further improved by correcting the field values at the boundary points according to Hadley's method. The algorithm is easy to implement for both two- and three-dimensional structures. The new method considerably reduces computation times because the propagation matrices remain constant in longitudinally invariant sections, thus avoiding repeated LU-decompositions. The basic idea-establishing the finite difference scheme such that locally exact, approximate, or plausible solutions are recovered-may be of interest for other efforts to solve partial differential equations by the finite difference method.
Effective coupling between two remote optical waveguides without branching sections can be achieved in a three-guide system with multimode central waveguide. We investigate the nonlinear power switching of c.w. laser radiation by such radiatively coupled waveguides. It is shown that effective all-optical switches with spatially well separated input/output channels can be realized although the influence of multimode interference on the switching characteristics becomes more pronounced for increasing thickness of the central guide. Different coupling regimes are specified, and the changes in switching characteristics during the transformation from one regime to another is studied. Numerical calculations for the critical power are compared with an approximate analytical expression. It is also shown that, at a moderate input power, a small number of modes determines the switching behavior.
Control Oriented Mathematical Modeling of a Bidirectional DC-DC Converter - Part 1: Buck Mode
(2023)
Parallel connection of different batteries equipped with bidirectional DC-DC converters offers an increase of the total storage capacity, the provision of higher currents and an improvement of reliability and system availability. To share the load current among the DC-DC converters while maintaining the safe operating range of the batteries, appropriate controllers are needed. The basis for the design of these control approaches requires knowledge of both the static and dynamic characteristics of the DC-DC converter used. In this paper, the small signal analysis of a DC-DC converter in buck mode is shown using the circuit averaging technique. The paper gives an overview of all required transfer functions:. The control and line to output transfer functions for CCM and DCM relevant for average current mode control as well as for voltage control are derived and their poles and zeros are determined. This provides the basis for stability consideration, analysis of the overall control structure and controller design.
In modern vehicles, system complexity and technical capabilities are constantly growing. As a result, manufacturers and regulators are both increasingly challenged to ensure the reliability, safety, and intended behavior of these systems. With current methodologies, it is difficult to address the various interactions between vehicle components and environmental factors. However, model-based engineering offers a solution by allowing to abstract reality and enhancing communication among engineers and stakeholders. Applying this method requires a model format that is machine-processable, human-understandable, and mathematically sound. In addition, the model format needs to support probabilistic reasoning to account for incomplete data and knowledge about a problem domain. We propose structural causal models as a suitable framework for addressing these demands. In this article, we show how to combine data from different sources into an inferable causal model for an advanced driver-assistance system. We then consider the developed causal model for scenario-based testing to illustrate how a model-based approach can improve industrial system development processes. We conclude this paper by discussing the ongoing challenges to our approach and provide pointers for future work.
The third-order nonlinear susceptibility of silica glass is measured via self-phase modulation in standard single mode fibers at a wavelength of 1550 nm. To minimize the influence of polarization state changes along the propagation only meter-long fibers were investigated. With pulse durations of picoseconds a quasi-instantaneous nonlinearity with ultrafast electronic and fast nuclear-vibration contributions produces under conditions of negligible dispersion a classic and clean nonlinear phase shift following exactly the shape of the pulse power. The complex pulse envelope was retrieved from frequency optical gating spectrograms. The nonlinear fiber parameter γ could be determined with an accuracy of 3.7 percent. Considering the mode field structure and the doping influence the nonlinear refractive index of silica glass as the fiber base material was found to be n2 = 2.22 · 10−16 cm2
W ± 6.0 % for picosecond-long pulses. Comparing nonlinear phase shifts from linear and circular polarized light a nuclear-vibration contribution to the cubic fiber nonlinearity of 25 percent was estimated.
In the field of software engineering, graph-based models are used for a variety of applications. Usually, the layout of those graphs is determined at the discretion of the user. This article empirically investigates whether different layouts affect the comprehensibility or popularity of a graph and whether one can predict the perception of certain aspects in the graph using basic graphical laws from psychology (i.e., Gestalt principles). Data on three distinct layouts of one causal graph is collected from 29 subjects using eye tracking and a print questionnaire. The evaluation of the collected data suggests that the layout of a graph does matter and that the Gestalt principles are a valuable tool for assessing partial aspects of a layout.
In a distributed system, functionally equivalent nodes work together to form a system with improved availability, reliability and fault tolerance. Thereby, the purpose is to achieve a common control objective. As multiple components cooperate to accomplish tasks, coordination between them is required. Electing a node as the temporary leader can be a possible solution to perform coordination. This work presents a self-stabilizing algorithm for the election of a leader in dynamically reconfigurable bus topology-based broadcast systems with a message and time complexity of O(1). The election is performed dynamically, i.e., not only when the leader node fails, and is criterion-based. The criterion used is a performance related value which evaluates the properties of the node regarding the ability to perform the tasks of the leader. The increased demands on the leader are taken into account and a re-election is started when the criterion value drops below a predefined level. The goal here is to distribute the load more evenly and to reduce the probability of failure due to overload of individual nodes. For improved system availability and reduced fault rates, a management level consisting of leader, assistant and co-assistant is introduced. This reduces the number of required messages and the duration in case of non-initial election. For further reduction of required messages to uniquely determine a leader, the CAN protocol is exploited. The proposed algorithm selects a node with an improved failure rate and a reduced message and hence time complexity while satisfying the safety and termination constraints. The operation of the algorithm is validated using a hardware test setup.
Efficient transportation of droplets (∽10 ¹ ̶̶̶̶ 10 ² µl) and small solid objects (∽10 ¹ ̶ 10 ² mm ³ ) have important applications in many fields, such as microfluidics, lab‐on‐a‐chip devices, drug delivery, etc. A novel multifunctional surface consisting of a periodic array of micro‐lamellae from a soft magnetoactive elastomer (MAE) on a plastic substrate is reported for these purposes. The physical origin of the propulsion is the bending of soft magnetic lamellae in non‐uniform magnetic fields, which is also observed in uniform magnetic fields. The magnetoactive surface is fabricated using a facile and rapid method of laser ablation. The propulsion of items is realized using a four‐pole rotating magnet. This results in a cyclic lamellar fringe motion over the micro‐structured surface and brings an advantage of easy reciprocation of transport by rotation reversal. Two modes of object transportation are identified: “pushing” mode for precise control of droplet and solid positioning and “bouncing” mode for heavier solid objects transportation. A water droplet of 5 μl or a glass sphere with a 2.1 mm diameter can be moved at a maximum speed of 60 mm s ⁻¹ . The multifunctionality of the proposed mechatronic platform is demonstrated on the examples of selective solid‐liquid separation and droplet merging.
An immense diversity in bottle types requires high accuracy during sorting for recycling purposes by breweries. This extremely complex and time-consuming procedure can result in enormous additional costs for them. This paper presents transfer learning-based algorithms for classifying beer bottle brands using camera images, applicable in individual sorting solutions for different use cases. The problem is tackled using customised EfficientNet, InceptionResNet and VGG models along with an augmented dataset. In addition, a detailed analysis of different model and parameter combinations is performed, enabling tailor-made technologies for specific conditions and resource limitations. In accompanying validations and subsequent tests, a test accuracy of 100% in the recognition of beer brands could be achieved, proving the proposed method fully contributes to the solution of the problem.
In this paper, the results of Thermally Stimulated Depolarization Currents (TSDC)-measurements of a complex system of stacked dielectric layers, like typically appearing in semiconductor packages, is presented. Characteristics of the individual isolation layers are presented solely and the results are compared to the stack. The investigated layers are comprising polyimide film, alkali-free glass, polyolefin film and epoxy based mold compound. Measurements have been carried out in the temperature range from 19 - 195°C at varying polarization fields for every material. Various relaxation peaks, originated by different polarization mechanisms within the materials could be observed. A comparison between the TSDC-peaks of the layer stack and the individual materials is shown. Our results demonstrate, that the super positioned spectrum is getting dominated by a single portion, the mold compound.
Anhand zweier Beispiele wird ein interaktives System vorgestellt, mit welchem Live-Messungen an elektronischen Bauteilen und Schaltungen im Hörsaal durchgeführt werden können. Das System basiert auf dem USB-Messgerät „Analog Discovery 2“ der Firma Digilent, erweitert um eine Adapterplatine mit Steckbrett und eine Webcam.
Zunächst werden drei Aspekte erläutert, in welchen ein solches System positive Auswirkungen auf den Kompetenzerwerb haben kann: Praxisbezug, Aktivierung und Vernetzung. Anschließend werden die zwei Beispiele ausgeführt. In Beispiel 1 wird die persönliche Alltagserfahrung mit Akkus über interaktive Clicker-Fragen und begleitende Messungen mit dem Modell der linearen Quelle verknüpft. Die Studierenden lernen, oberflächliche Lösungen wie die Messung der Leerlaufspannung zu hinterfragen und das Verhalten realer Quellen anhand der gemessenen I-U-Kennlinien zu verstehen. Beispiel 2 zeigt kurz die Möglichkeiten auf, den abstrakten Formalismus der komplexen Wechselstromrechnung am Beispiel des Serienschwingkreises im Zeit- und Frequenzbereich
messtechnisch erlebbar zu machen.
It is shown that the advancing (ACA) and receding (RCA) contact angles of water on extremely soft (shear modulus of the order of 10 kPa) magnetoactive elastomer (MAE) films significantly depend on the applied magnetic field. The difference between these angles, known as the contact angle hysteresis, is examined. The roles of the filler concentration and material softness are elaborated. The highest change in the contact angle hysteresis (CAH) from 34° in the absence of magnetic field to 76° in a magnetic field of 0.4 T is achieved for the softest sample with the lowest mass fraction of iron particles (70 wt%). The dependence of the CAH on magnetization history (“magnetic hysteresis”) is observed. This magnetic hysteresis is clearly pronounced for the ACA and has little effect on the RCA. Magnetic field-induced changes of the surface roughness exhibit qualitatively the same hysteresis behavior with regard to the external magnetic field as the ACA. The results are promising for the development of smart surfaces for applications where the dynamic wetting has to be controlled.
This study uses holistic models of image perception to analyze and interpret eye movements during a code review. 23 participants (15 novices and 8 experts) take part in the experiment. The subjects’ task is to review six short code examples in C programming language and identify possible errors. During the experiment, their eye movements are recorded by an SMI 250 REDmobile. Additional data is collected through questionnaires and retrospective interviews. The results implicate that holistic models of image perception provide a suitable theoretical background for the analysis and interpretation of eye movements during code reviews. The assumptions of these models are particularly evident for expert programmers. Their approach can be divided into different phases with characteristic eye movement patterns. It is best described as switching between scans of the code example (global viewing) and the detailed examination of errors (focal viewing).
The problem description comes to the fore when the wide-ranging subject area of electrical engineering is combined and analyzed with different types of schools. It is becoming increasingly rare for elementary school children to come to grips with technology in the sense of recognizing functional interrelationships and understanding modes of action in the context of technical-practical confrontation. The picture at secondary schools is also rather sobering. Here, a strong focus on facts and knowledge and too little emphasis on modeling, application and problem solving lead to insufficient results in the cognitive area. In addition, a massive
shortage of engineers and specialists with a technical and scientific orientation has been predicted for years and is being increasingly observed. The motivation of students in traditional lectures is decreasing and in general there is a decline of university students in technical subjects. These problems are not only known throughout Germany, but also internationally. Especially in developing countries,
additional problems make technical education more difficult, regardless of the type of school. Therefore, this master thesis is evaluated in South Africa in order to consider as many influencing factors as possible.
"Learning is experience. Everything else is simply information." - Methods and concepts developed in the thesis build upon this quote of Albert Einstein. Teaching methods are elaborated and applied for three different age groups and school types, depending on known influencing factors. The aim of this thesis is not to produce further findings in the sense of basic research, but to show ways
in which the current situation can be steered in a different direction.
It has been shown that technology lessons in elementary/secondary schools inspire interest in technical professions in the field of electrical engineering. Furthermore, the combination of frontal teaching, for a necessary theoretical background, together with student-active, action-oriented teaching shows advantages in terms of learning efficiency and an increase in performance levels for all three
age groups. However, it could also be observed that factors such as social background, family influence and gender have partial effects on the promotion and education in the field of electrical engineering.
Nowadays, learning management systems are widely employed in all educational institutions to instruct students as a result of the increasing in online usage. Today’s learning management systems provide learning paths without personalizing them to the characteristics of the learner. Therefore, research these days is concentrated on employing AI-based strategies to personalize the systems. However, there are many different AI algorithms, making it challenging to determine which ones are most suited for taking into account the many different features of learner data and learning contents. This paper conducts a systematic literature review in order to discuss the AI-based methods that are frequently used to identify learner characteristics, organize the learning contents, recommend learning paths, and highlight their advantages and disadvantages.
This study investigates the impact of eye movement modeling examples in Software Engineering education. Software Engineering is a highly visual domain. The daily tasks of a software engineer (e.g., formulating requirements, creating UML diagrams, or conducting a code review) require in many cases the use of certain visual strategies. Although these strategies can be found for experts, it has been observed in different eye tracking studies that students have difficulties in learning and applying them. To familiarize students with these visual strategies and to provide them with a better understanding for the cognitive processes involved, a total of seven eye movement modeling examples was created. The seven eye movement modeling examples cover relevant parts of an introductory Software Engineering lecture; they are focused on typical situations in which visual strategies are applied. The results of a questionnaire-based evaluation shows that students consider the eye movement modeling examples as useful, feel supported in their learning process, and would like to see more use of them in the Software Engineering lecture. Furthermore, the students suggested that eye movement modeling examples should also be used in other lectures.
As humans, we tend to use models to describe reality. Modeling languages provide the formal frameworks for creating such models. Usually, the graphical design of individual model elements is based on subjective decisions; their suitability is determined at most by the prevalence of the modeling language. With other words: there is no objective way to compare different designs of model elements. The present paper addresses this issue: it introduces a systematic approach for evaluating the elements of graph-based modeling languages comprising 14 criteria – derived from standards, usability analyses, or the design theories ‘Physics of Notations’ and ‘Cognitive Dimensions of Notations’. The criteria come with measurement procedures and evaluation schemes based on reasoning, eye tracking, and questioning. The developed approach is demonstrated with a specific use case: three distinct sets of node elements for causal graphs are evaluated in an eye tracking study with 41 subjects.
The dropout rate at universities has been very high for years. Thereby, the inexperience and lack of knowledge of students in dealing with individual learning paths in various courses of study plays a decisive role. Adaptive learning management systems are suitable countermeasures, in which learners’ learning styles are classified using questionnaires or computationally intensive algorithms before a learning path is suggested accordingly. In this paper, a study design for student learning style classification using eye tracking is presented. Furthermore, qualitative and quantitative analyses clarify certain relationships between students’ eye movements and learning styles. With the help of classification based on eye tracking, the filling out of questionnaires or the integration of computationally or cost-intensive algorithms can be made redundant in the future.
This paper assesses the relation between personality, demographics, and learning style. Hence, data is collected from 200 participants using 1) the BFI-10 to obtain the participant’s expression of personality traits according to the five-factor model, 2) the ILS to determine the participant’s learning style according to Felder and Silverman, and 3) a demographic questionnaire. From the obtained data, we train and evaluate a Bayesian network. Using Bayesian statistics, we show that age and gender slightly influence personality and that demographics as well as personality have at least a minor effect on learning styles. We also discuss the limitations and future work of the presented approach.
This study examines how Klingsieck’s LIST-K questionnaire [22] can be shortened and adapted to the requirements of an online learning management system. In a study with 213 participants, the questionnaire is subjected to an exploitative factor analysis. In a next step, the results are evaluated in terms of their reliability. This process creates a modified factor structure for the LIST-K, comprising a total of eight factors. The reliability of the modified questionnaire is at an α of .770. The shortened version of the LIST-K questionnaire is currently being used on an experimental basis in different courses.
C is one of the most widely used programming languages - MISRA C is one of the most known sets of coding guidelines for C. This paper examines the usefulness and comprehensibility of the MISRA C:2012 guidelines in an eye tracking study. There, subjects encounter non-compliant code in four different code review settings: with no additional reference, with an actual MISRA C guideline, with a case-specific interpretation of a MISRA C guideline, and with a compliant version of the code. The data collected was analyzed not only in terms of the four presentation styles, but also by dividing the subjects into experience levels based on their semesters of study or years of work experience. Regarding the difference between actual and interpreted guidelines, we found that for interpreted guidelines the error detection rate is higher whereas the duration and frequency of visits to the guideline itself are mainly lower. This suggest that the actual guidelines are less useful and more difficult to understand. The former is contradicted by the subjects’ opinions: when surveyed, they rated the usefulness of the actual guidelines higher.
An effective method for on-demand control over the impact dynamics of droplets on a magnetoresponsive surface is reported. The surface is comprised of micrometer-sized lamellas from a magnetoactive elastomer on a copper substrate. The surface itself is fabricated using laser micromachining. The orientation of the lamellae is switched from edge-on (orthogonal to the surface) to face-on (parallel to the surface) by changing the direction of a moderate (<250 mT) magnetic field. This simple actuation technique can significantly change the critical velocities of droplet rebound, deposition, and splashing. Rebound and deposition regimes can be switched up to Weber number We < 13 ± 3, while deposition and splashing can be switched in the range of 32 < We < 52. Because a permanent magnet is used, no permanent power supply is required for maintaining the particular regime of droplet impact. The presented technology is highly flexible and enables selective fabrication and actuation of microstructures on complex devices. It has great potential for applications in soft robotics, microfluidics, and advanced thermal management.
The world is changing rapidly, mainly due to the digitalization of all areas of living. A huge amount of information is accessible via the Internet, and since it is no longer possible for individual humans to keep track of it, artificial intelligence (AI) is analyzing this data. In this rapidly changing world, students have to be educated for a successful career during their whole working life. These boundary conditions lead to completely new challenges for the education of students that are unprecedented in this form. Digitalization in education can help to cope with these challenges but can only be a means, not a goal. Personal interaction with students remains the most important task in education to address individual weaknesses and further develop strengths and talents. With the increasing amount of openly available information and the consequently increasing diversity of experiences within the group of students, differentiation is advancing to become the key to successful education. Digitization can help with this challenging task and support communication between students and their experienced instructors. But computers cannot replace human interaction and attempts to improve teaching efficiency by replacing this communication with electronic means endangers the learning success for complex concepts. This article analyzes education demands and possibilities for digitally supported teaching and learning.
Over the past decade, cars have turned gradually into real cyber physical systems. The collaboration of services between the service-oriented, cross-enterprise vehicle application frameworks has increased to generate novel, smart and complicated vehicle services. Consequently, from an interoperability perspective, semantically mapping of vehicle service component’s interface ontological models emerged as a big research interest in automotive application domain that manipulates several cross-enterprise synergy knowledge applications frameworks. The ontological metamodeling lays the foundation for building semantic bridge and exploring semantic associations between service components’ interface models based on the domain knowledge for semantic interoperability. Also, several semantic quality metrics has been defined over time for the vehicle service interface ontological metamodels. The empirically evaluated values of these metrics can be used to assess progress in cross-enterprise interoperability between the service and the clients’ APIs ontological models in vehicle domain. Despite potential benefits of semantic alignment quality metrics, the effective use of these metrics for vehicle service interface ontologies have proven elusive. Yes, such metrics can be used successfully for quantification, but then they mostly fail to provide adequate annotations in subsequent decision-making in the direction of semantic interoperability and reusability. The effective use of ontology semantic alignment quality metrics is basically hindered in the absence of the meaningful thresholds. In fact, the absence of an effective and meaningful threshold for the semantic similarity measure between various vehicle service interface ontological metamodels, motivates this research work which not only proposes a design approach to an optimized threshold for the semantic similarity metrics but also applies this threshold on few defined semantic alignment quality metrics. This paper also uses a real-world vehicle domain industrial case study to illustrate the design approach.