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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.
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.
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).
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.
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.
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.
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.
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.
Computational investigation of oxy-combustion of pulverized coal and biomass in a swirl burner
(2022)
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.