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CAD/CAM techniques are used increasingly in dentistry for design and fabrication of teeth restorations. An important issue is preserving occlusal contacts of teeth after restoration. Traditional techniques based on the use of casts with mechanical articulators require manual adjustment of occlusal surface, which becomes impractical when hard restoration materials like porcelain are used; they are also time and labor consuming. Most existing computer systems ignore completely such an articulation check, or perform the check at the level of a tooth and its immediate neighbors. We present a new mathematical model and a related user interface for global articulation simulation, developed for the Intelligent Dental Care System project. The aim of the simulation is elimination of the use of mechanical articulators and manual adjustment in the process of designing dental restorations and articulation diagnostic. The mathematical model is based upon differential topological modeling of the jawbs considered as a mechanical system. The user interface exploits metaphors that are familiar to dentists from everyday practice. A new input device designed specifically for use with articulation simulation is proposed.
Airborne volcanic ash particles are a known hazard to aviation. Currently, there are no means available to detect ash in flight as the particles are too fine (radii < 30 μm) for on-board radar detection and, even in good visibility, ash clouds are difficult or impossible to detect by eye. The economic cost and societal impact of the April/May 2010 Icelandic eruption of Eyjafjallajökull generated renewed interest in finding ways to identify airborne volcanic ash in order to keep airspace open and avoid aircraft groundings. We have designed and built a bi-spectral, fast-sampling, uncooled infrared camera device (AVOID) to examine its ability to detect volcanic ash from commercial jet aircraft at distances of more than 50 km ahead. Here we report results of an experiment conducted over the Atlantic Ocean, off the coast of France, confirming the ability of the device to detect and quantify volcanic ash in an artificial ash cloud created by dispersal of volcanic ash from a second aircraft. A third aircraft was used to measure the ash in situ using optical particle counters. The cloud was composed of very fine ash (mean radii ~10 μm) collected from Iceland immediately after the Eyjafjallajökull eruption and had a vertical thickness of ~200 m, a width of ~2 km and length of between 2 and 12 km. Concentrations of ~200 μg m(-3) were identified by AVOID at distances from ~20 km to ~70 km. For the first time, airborne remote detection of volcanic ash has been successfully demonstrated from a long-range flight test aircraft.
Artificial intelligence and design of experiments for resource adequacy assessment in power systems
(2024)
Musicians and music professionals are often considered to be expert listeners for listening tests on room acoustics. However, these tests often target acoustic parameters other than those typically relevant in music such as pitch, rhythm, amplitude, or timbre. To assess the expertise in perceiving and understanding room acoustical phenomena, a listening test battery was constructed to measure the perceptual sensitivity and cognitive abilities in the identification of rooms with different reverberation times and different spectral envelopes. Performance in these tests was related to data from the Goldsmiths Musical Sophistication Index, self-reported previous experience in music recording and acoustics, and academic knowledge on acoustics. The data from 102 participants show that sensory and cognitive abilities are both correlated significantly with musical training, analytic listening skills, recording experience, and academic knowledge on acoustics, whereas general interest in and engagement with music do not show any significant correlations. The regression models, using only significantly correlated criteria of musicality and professional expertise, explain only small to moderate amounts (11%–28%) of the variance in the “room acoustic listening expertise” across the different tasks of the battery. Thus, the results suggest that the traditional criteria for selecting expert listeners in room acoustics are only weak predictors of their actual performances.
Asset management for distribution networks with high penetration of distributed energy resources
(2018)
Through constant technical progress, multi-user virtual reality is transforming towards a social activity that is no longer only used by remote users, but also in large-scale location-based experiences. We evaluate the usage of realtime-tracked avatars in co-located business-oriented applications in a "guide-user-scenario" in comparison to audio only instructions. The present study examined the effect of an avatar-guide on the user-related factors of Spatial Presence, Social Presence, User Experience and Task Load in order to propose design guidelines for co-located collaborative immersive virtual environments. Therefore, an application was developed and a user study with 40 participants was conducted in order to compare both guiding techniques of a realtime-tracked avatar guide and a non-visualised guide with otherwise constant conditions. Results reveal that the avatar-guide enhanced and stimulated communicative processes while facilitating interaction possibilities and creating a higher sense of mental immersion for users. Furthermore, the avatar-guide appeared to make the storyline more engaging and exciting while helping users adapt to the medium of virtual reality. Even though no assertion could be made concerning the Task Load factor, the avatar-guide achieved a higher subjective value on User Experience. Due to the results, avatars can be considered valuable social elements in the design of future co-located collaborative virtual environments.
Augmented reality for supporting manual non-destructive ultrasonic testing of metal pipes and plates
(2018)
We describe an application of augmented reality technology for non-destructive testing of products in the metal-industry. The prototype is created with hard- and software, that is usually employed in the gaming industry, and delivers positions for creating ultra- sonic material scans (C-scans). Using a stereo camera in combination with an hmd enables realtime visualisation of the probes path, as well as the setting of virtual markers on the specimen. As a part of the implementation the downhill simplex optimization algorithm is implemented to fit the specimen to a cloud of recorded surface points. The accuracy is statistically tested and evaluated with the result, that the tracking system is accurate up to ca. 1-2 millimeters in well set-up conditions. This paper is of interest not only for research institutes of the metal-industry, but also for any areas of work, in which the enhancement with augmented reality is possible and a precise tracking is necessary.
Artificial intelligence methods based on machine learning or artificial neural networks have become indispensable in camera-based driver assistance systems, and also represent an essential building block for future autonomous driving. However, the great successes of these evaluation methods in environment perception and also driving planning are accompanied by equally great challenges in the validation and verification of these systems. One of the essential aspects for this is the required guaranteed safety of the functions under mass production conditions of the vehicles. This article explains this point of view using a detailed example from the field of camera-based driver assistance systems: the determination of inspection limits at the end of the production line. The camera is one of the most important sensor modalities for vehicle environment sensing and as such, the quality of the camera systems plays a key role in the safety argumentation of the overall system. Several illustrative application examples (role of simulations, calibration, influence of the windshield) will be presented. The basic ideas presented can be well transferred to the other sensor modalities (lidar, radar, ToF, etc.). The investigations/evidence show that doubts are allowed whether or how fast autonomous driving on level L4/5 will take hold as robotaxis or – even more challenging – in private ownership on a larger scale.
Multi-user virtual reality is transforming towards a social activity that is no longer only used by remote users, but also in large-scale location-based experiences. Usage of realtime-tracked avatars in co-located business-oriented applications with a ”guide-user-scenario” is examined for user-related factors of Spatial Presence, Social Presence, User Experience and Task Load. A user study was conducted in order to compare both techniques of a realtime-tracked avatar and a non-visualised guide. Results reveal that the avatar-guide enhanced and stimulated communicative processes while facilitating interaction possibilities and creating a higher sense of mental immersion for users and engagement.
Striving for smaller losses in turbomachinery has led to many advancements in the design of seals. Modern sealing concepts such as brush seals hold a great potential to increase the efficiency of both flight engines and stationary turbines. At the same time, in order to maintain stable operating conditions of the rotor, swirl-induced forces must be kept at a minimum in the sealing channels. Therefore, the influence of the permeable and flexible bristle pack of brush seals on the flow around the rotor surface must be known. In this paper the swirl flow in the cavities of two different seal geometries is studied experimentally and numerically. A conventional three-tooth labyrinth serves as a reference. A second seal arrangement with a bristle pack upstream of two teeth is compared with the reference labyrinth. The swirl is evaluated experimentally from total and static pressure measurements in various axial and circumferential positions. Additionally, the axial swirl distribution is calculated using computational fluid dynamics (CFD). Here, the numerical model of the brush seal is based on the porous medium approach and is calibrated using the experimental values of the leakage and the bristle clearance by adjusting the thickness of the bristle pack. The calibrated CFD model is then used to study the impact of the brush seal on the swirl component of the sealing flow. The observed significant decrease of the swirl by the brush seal shows good agreement with the experimental data. The impact of changes in bristle pack clearance on the swirl is also investigated and compared with experimental evidence. The aim is to show that the brush seals have a natural tendency to interrupt seal swirl. They can therefore be used for swirl control in order to create a beneficial impact on the dynamic stability of turbomachines.
A mobile phone the size of a candy bar offers dozens of complex functions, a masterpiece of engineering. Unfortunately, the more functions are available, the less they are accessible to the average user. The design of the user interface suffers from a lack of suitability for the tasks, does not conform to user expectations and a suboptimal self-descriptiveness. The usability of modern mobile phones was tested in a broad survey with over 1300 participants. An internet based simulation offered tasks and an online evaluation. It could be pointed out that mobile phones are not only hard to access for novices but also those who consider themselves experts have difficulties when confronted with unknown functions or another brand of phone. Approaches to increase the usability are discussed.
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.
In the context of using renewable energies and recycling climate-changing gases, methanation of CO2 provides one possibility. However, volatile availability of renewable energies for hydrogen production and fluctuating CO2streams from different sources lead to enhanced demand in investigating the influence of dynamic process operation on the catalyst performance, including detailed kinetic characterization. Reliable kinetic measurements require isothermal temperature control and absence of macrokinetic diffusion limitations. Both were investigated in this work while the determination of steady-state kinetic parameters is part of ongoing studies. Furthermore, a detailed analysis with respect to the long-term-stability of the nickel-based catalyst was performed
Virtual sets have evolved from computer-generated, prerendered 2D backgrounds to realtime, responsive 3D computer graphics and are nowadays standard repertoire of broadcasting divisions. The graphics, which are combined with real video feed becoming moresophisticated, real looking and more responsive. We will look at the recent developments and suggest further developments like integration of spatial audio into the studio production and generating interactive media streams. Educational institutes recognize the demands of the rising media industry and established new courses on media technology like the Duesseldorf University of Applied Sciences.
Classification of Beyond-Reality Interaction Techniques in Spatial Human-Computer Interaction
(2018)
Cliffhanger-VR
(2018)
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 order to improve the interactivity between users and computers, recent technologies focus on incorporating gesture recognition into interactive systems. The aim of this article is to evaluate the effectiveness of using a Myo control armband and the Kinect 2 for recognition of gestures in order to interact with virtual objects in a weather report scenario. The Myo armband has an inertial measurement unit and is able to read electrical activity produced by skeletal muscles, which can be recognized as gestures, which are trained by machine learning. A Kinect sensor was used to build up a dataset which contains motion recordings of 8 different gestures and was also build up by a gesture training machine learning algorithm. Both input methods, the Kinect 2 and the Myo armband, were evaluated with the same interaction patterns in a user study, which allows a direct comparison and reveals benefits and limits of each technique.
Computational investigation of hemodynamics in hardshell venous reservoirs: A comparative study
(2019)
Extracorporeal circulation using heart‐lung‐machines is associated with a profound activation of corpuscular and plasmatic components of circulating blood, which can also lead to deleterious events such as systemic inflammatory response and hemolysis. Individual components used to install the extracorporeal circulation have an impact on the level of activation, most predominantly membrane oxygenators and hardshell venous reservoirs as used in extracorporeal systems. The blood flows in two different hardshell reservoirs are computationally investigated. A special emphasis is placed on the prediction of an onset of transition and turbulence generation. Reynolds‐averaged numerical simulations (RANS) based on a transitional turbulence model, as well as large eddy simulations (LES) are applied to achieve an accurate prediction. In the LES analysis, the non‐Newtonian behavior of the blood is considered via the Carreau model. Blood damage potential is quantified applying the Modified Index of Hemolysis (MIH) based on the predicted flow fields. The results indicate that the flows in both reservoirs remain predominantly laminar. For one of the reservoirs, considerable turbulence generation is observed near the exit site, caused by the specific design for the connection with the drainage tube. This difference causes the MIH of this reservoir to be nearly twice as large as compared to the alternative design. However, a substantial improvement of these performance criteria can be expected by a local geometry modification.
Computational investigation of oxy-combustion of pulverized coal and biomass in a swirl burner
(2022)
Actin filaments are conductive to ionic currents, mechanical and voltage solitons. These travelling localisations can be utilised to generate computing circuits from actin networks. The propagation of localisations on a single actin filament is experimentally unfeasible to control. Therefore, we consider excitation waves propagating on bundles of actin filaments. In computational experiments with a two-dimensional slice of an actin bundle network we show that by using an arbitrary arrangement of electrodes, it is possible to implement two-inputs-one-output circuits.
The healthcare sector's digital transformation necessitates the involvement of stakeholders through participation and co-creation processes. This study aims to investigate the understanding and implementation of participation and co-creation in the development of hybrid interaction technologies in healthcare. Eight interdisciplinary research projects were examined through semi-structured group interviews with 49 participants from academia, industry, and the application field. The interviews focused on participants' perspectives on project goals, user groups, access to the field, methods of participation and co-creation, and user motivation. The results highlight the diverse understandings of participation and co-creation, with some perceiving them as research-driven and others as already embedded in user- centered design. The projects emphasized user needs but often excluded stakeholders from collaborative decision-making. Challenges in achieving continuous involvement and co-decision were acknowledged. The findings underscore the need for reflexive practice and evaluation of participation and co-creation throughout the development process, as well as further research on participation across projects. By addressing these challenges and embracing participatory approaches, digital health applications can better address ethical concerns, build trust, and increase acceptance and adoption in the healthcare sector.
The construction of a basis of a certain lattice of interest is a basic tool in many fields of algorithmic number theory. All too often we can not compute with the original lattices because of irrational numbers involved but have to work with approximations of them. While helpful bounds were shown about the reduction of lattice bases in cite{buchmann94reducing}, here we introduce the notion of a $(epsilon,delta)$-constructable basis of a lattice and determine the precision of vectors that is necessary to extend a set to a $(epsilon,delta)$-constructable basis.
Higher control engineering concepts, including artificial intelligence and model-based control, are recently becoming more popular in complex industrial applications because they enable a significant increase in efficiency. E.g., a model-based approach can be used to enhance the control and monitoring of several coupled components of a larger turbomachinery train. This requires dynamic models of the components, including all machine characteristics, which may experience a shift in their behavior over the course of their lifetime. Such changes occur due to natural fouling, wear of sub-components or external effects induced by maintenance measures. To overcome this problem, we model machine-characteristic maps with artificial neural networks, which may be used as part of prediction models in a model predictive control unit. If an appropriate data set is available, this allows us to adapt the model to the current behavior of the machine without requiring in-depth knowledge about the underlying physics of this “concept drift”, as it is known in literature. However, the training of neural networks is usually connected with high computational effort while the task needs to be executed in real-time during operation. Furthermore, in real operating conditions, machine sensors can only provide labeled data from the current operating point of the machine, which can be stationary for long operation periods of up to several months. In general, this yields only an unrepresentative data subset of the machine-characteristics, which is not sufficient to retrain the whole model to a new state. To solve these problems, we firstly reduce the model adaptation to a convex optimization problem, which can be efficiently solved in real-time conditions. Secondly, we use a specialized data management system with which we can integrate historical data to supplement the unrepresentative data subset. In this paper we show the application of the outlined method on a compressor map and discuss the advantages and requirements of the method in the context of modeling applications for industrial turbomachinery.
Process models in industrial applications, e.g. predictive maintenance or automation, are subject to both divergence from the underlying system due to their time-variant nature and to high complexity resulting from a wide operational range being covered. Hence, regression models require high accuracy for the present system state and at the same time need to be valid across the whole system operating space. While accuracy for the current system state can be gained by updating the model on the current data, the overall validity must often be retrieved from historical or design data. We propose a method to find an appropriate compromise for these two demands. A pre-trained artificial neural network (ANN) is continually updated on the current sensor data stream using convex optimisation. Thus, a unique and optimal solution is generated in each update step, while robust regression accuracy on the domain that is not covered by the arriving data subset is maintained. This is achieved by introducing a data management system to provide some historical data, constraining the optimisation problem and manipulating the architecture of the ANN. Models updated with this method show reasonable stability but display plastic behaviour at the current operating point.
Education at the University of Aizu is focussed upon computer science. Besides being the subject matter of many courses, however, the computer also plays a vital role in the educational process itself, both in the distribution of instructional media, and in providing students with valuable practical experience. All students have unlimited access (24-hours-a-day) to individual networked workstations, most of which are multimedia-capable (even video capture is possible in two exercise rooms). Without software and content tailored for computer-aided instruction, the hardware becomes an expensive decoration. In any case, there is a need to better educate the instructors and students in the use of the equipment. In the interest of facilitating effective, collaborative use of network-based computers in teaching, this article explores the impact that a network environment can have on such activities. First, as a general overview, and to examine the motivation for the use of a network environment in teaching, this article reviews a range of different styles of collaboration. Then the article shows what kind of tools are available for use, within the context of what has come to be called Computer-Supported Cooperative Work (CSCW).
Forums such as Stack Overflow are used by many software developers to find a solution for a given coding problem. Found solutions, i.e. forum posts containing relevant source code, are utilized in a copy and paste manner. This behavior carries the risk that vulnerabilities contained in the source code of the forum posts are spread. Software developers should be able to identify vulnerable source code at an early stage, thereby preventing copying the corresponding source code. In this paper, we introduce the tool CopypastaVulGuard that identifies vulnerable source code in forum posts and allows software developers to omit the source code by marking the forum posts as dangerous. Our tool consists of a browser extension and a management application capable to address as examples SQL injections, remote code executions and deprecated functions based on a dump of the archive.org Stack Overflow data set. We present an evaluation of our tool's possible impact and relevance considering pros/cons and selected research questions.
The late immersion of multi-touch sensitive displays enables the use of tangibles on multi-touch screens. There a several wide spread and/or sophisticated solutions to fulfill this need but they seem to have some flaws. One popular system at the time of writing is an overlay frame that can be placed on a normal display with the corresponding size. The frame creates a grid with infrared light emitting diodes. The disruption of this grid can be detected and messages with the positions are sent via usb to a connected computer. This system is quite robust in matters of ambient light insensitivity and also fast to calibrate. Unfortunately it is not created with the recognition of tangibles in mind and printed patterns can not be resolved. This article summarizes an attempt to create fiducials that are recognized by an infrared multi-touch frame as fingers. Those false fingers are checked by a software for known patterns. Once a known pattern (= fiducial) has been recognized its position and orientation are send with the finger positions towards the interactive software. The usability is tested with an example application where tangibles and finger touches are used in combination.
Cost optimal meter placement in low and medium voltagte grids considering stochastic dependencies
(2013)
The working paper at hand assumes that differences of innovativeness of different countries can be explained to a certain extent by cultural differences. Thus, the paper deals with the research question of which cultural dimensions have an influence on national innovativeness. Previous research mainly uses the Hofstede-dimensions to describe cultural differences and often focuses on single parameters to describe national innovativeness (e.g. number of patents per capita). This paper, instead, uses the dimensions of the GLOBE-study which builds on the findings of Hofstede but is more up-to-date and comprehensive and uses two innovation indexes – the Global Innovation Index (GII) and the Innovation Union Scoreboard (IUS) – to describe national innovativeness. The authors use correlation analysis to find relationships between the GLOBEdimensions and the innovation indexes. They find positive correlations of innovativeness (both indexes) to Future Orientation (practice scale), Gender Egalitarianism (value scale), Human Orientation (value scale) and Uncertainty Avoidance (practice scale) as well as negative correlations to In-Group Collectivism (practice scale), Future Orientation (value scale) and Uncertainty Avoidance (value scale). Some of the findings are contrary to existing hypotheses, e.g. only a weak negative correlation of Power Distance to one of the indexes. Furthermore the findings show significant differences between practice scales and value scales, especially concerning Future Orientation and Uncertainty Avoidance which deserve further examination. Overall it can be concluded that culture has an impact on national innovativeness. The different cultural dimensions of the GLOBE-study show a multi-faceted interrelationship between culture and innovation. To come to a concise answer for the question which dimensions affect national innovativeness in which way additional research will be necessary.