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Institute
- Institut für Informatik (378) (remove)
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Jährliches Fachgespräch zu Sensornetzen der GI/ITG Fachgruppe Kommunikation und Verteilte Systeme, 16. - 17. September 2010, Universität Würzburg
The steadily increasing usage of smart meters generates a valuable amount of high-resolution data about the individual energy consumption and production of local energy systems. Private households install more and more photovoltaic systems, battery storage and big consumers like heat pumps. Thus, our vision is to augment these collected smart meter time series of a complete system (e.g., a city, town or complex institutions like airports) with simulatively added previously named components. We, therefore, propose a novel digital twin of such an energy system based solely on a complete set of smart meter data including additional building data. Based on the additional geospatial data, the twin is intended to represent the addition of the abovementioned components as realistically as possible. Outputs of the twin can be used as a decision support for either system operators where to strengthen the system or for individual households where and how to install photovoltaic systems and batteries. Meanwhile, the first local energy system operators had such smart meter data of almost all residential consumers for several years. We acquire those of an exemplary operator and discuss a case study presenting some features of our digital twin and highlighting the value of the combination of smart meter and geospatial data.
Purpose: A study of real-time adaptive radiotherapy systems was performed to test the hypothesis that, across delivery systems and institutions, the dosimetric accuracy is improved with adaptive treatments over non-adaptive radiotherapy in the presence of patient-measured tumor motion. Methods and materials: Ten institutions with robotic(2), gimbaled(2), MLC(4) or couch tracking(2) used common materials including CT and structure sets, motion traces and planning protocols to create a lung and a prostate plan. For each motion trace, the plan was delivered twice to a moving dosimeter; with and without real-time adaptation. Each measurement was compared to a static measurement and the percentage of failed points for gamma-tests recorded. Results: For all lung traces all measurement sets show improved dose accuracy with a mean 2%/2 mm gamma-fail rate of 1.6% with adaptation and 15.2% without adaptation (p < 0.001). For all prostate the mean 2%/2 mm gamma-fail rate was 1.4% with adaptation and 17.3% without adaptation (p < 0.001). The difference between the four systems was small with an average 2%/2 mm gamma-fail rate of <3% for all systems with adaptation for lung and prostate. Conclusions: The investigated systems all accounted for realistic tumor motion accurately and performed to a similar high standard, with real-time adaptation significantly outperforming non-adaptive delivery methods.
Immersive virtual environments provide users with the opportunity to escape from the real world, but scripted dialogues can disrupt the presence within the world the user is trying to escape within. Both Non-Playable Character (NPC) to Player and NPC to NPC dialogue can be non-natural and the reliance on responding with pre-defined dialogue does not always meet the players emotional expectations or provide responses appropriate to the given context or world states. This paper investigates the application of Artificial Intelligence (AI) and Natural Language Processing to generate dynamic human-like responses within a themed virtual world. Each thematic has been analysed against humangenerated responses for the same seed and demonstrates invariance of rating across a range of model sizes, but shows an effect of theme and the size of the corpus used for fine-tuning the context for the game world.
A number of public codes exist for GPS positioning and baseline determination in off-line mode. However, no software code exists for DGPS exploiting correction factors at base stations, without relying on double difference information. In order to accomplish it, a methodology is introduced in MATLAB environment for DGPS using C/A pseudoranges on single frequency L1 only to make it feasible for low-cost GPS receivers. Our base station is at accurately surveyed reference point. Pseudoranges and geometric ranges are compared at base station to compute the correction factors. These correction factors are then handed over to rover for all valid satellites observed during an epoch. The rover takes it into account for its own true position determination for corresponding epoch. In order to validate the proposed algorithm, our rover is also placed at a pre-determined location. The proposed code is an appropriate and simple to use tool for post-processing of GPS raw data for accurate position determination of a rover e.g. Unmanned Aerial Vehicle during post-mission analysis.
Today knowledge base authoring for the engineering of intelligent systems is performed mainly by using tools with graphical user interfaces. An alternative human-computer interaction para- digm is the maintenance and manipulation of electronic documents, which provides several ad- vantages with respect to the social aspects of knowledge acquisition. Until today it hardly has found any attention as a method for knowledge engineering.
This thesis provides a comprehensive discussion of document-centered knowledge acquisition with knowledge markup languages. There, electronic documents are edited by the knowledge authors and the executable knowledge base entities are captured by markup language expressions within the documents. The analysis of this approach reveals significant advantages as well as new challenges when compared to the use of traditional GUI-based tools.
Some advantages of the approach are the low barriers for domain expert participation, the simple integration of informal descriptions, and the possibility of incremental knowledge for- malization. It therefore provides good conditions for building up a knowledge acquisition pro- cess based on the mixed-initiative strategy, being a flexible combination of direct and indirect knowledge acquisition. Further it turns out that document-centered knowledge acquisition with knowledge markup languages provides high potential for creating customized knowledge au- thoring environments, tailored to the needs of the current knowledge engineering project and its participants. The thesis derives a process model to optimally exploit this customization po- tential, evolving a project specific authoring environment by an agile process on the meta level. This meta-engineering process continuously refines the three aspects of the document space: The employed markup languages, the scope of the informal knowledge, and the structuring and organization of the documents. The evolution of the first aspect, the markup languages, plays a key role, implying the design of project specific markup languages that are easily understood by the knowledge authors and that are suitable to capture the required formal knowledge precisely. The goal of the meta-engineering process is to create a knowledge authoring environment, where structure and presentation of the domain knowledge comply well to the users’ mental model of the domain. In that way, the approach can help to ease major issues of knowledge-based system development, such as high initial development costs and long-term maintenance problems.
In practice, the application of the meta-engineering approach for document-centered knowl- edge acquisition poses several technical challenges that need to be coped with by appropriate tool support. In this thesis KnowWE, an extensible document-centered knowledge acquisition environment is presented. The system is designed to support the technical tasks implied by the meta-engineering approach, as for instance design and implementation of new markup lan- guages, content refactoring, and authoring support. It is used to evaluate the approach in several real-world case-studies from different domains, such as medicine or engineering for instance.
We end the thesis by a summary and point out further interesting research questions consid- ering the document-centered knowledge acquisition approach.
A new innovative real-time tracking method for flying insects applicable under natural conditions
(2021)
Background
Sixty percent of all species are insects, yet despite global efforts to monitor animal movement patterns, insects are continuously underrepresented. This striking difference between species richness and the number of species monitored is not due to a lack of interest but rather to the lack of technical solutions. Often the accuracy and speed of established tracking methods is not high enough to record behavior and react to it experimentally in real-time, which applies in particular to small flying animals.
Results
Our new method of real-time tracking relates to frequencies of solar radiation which are almost completely absorbed by traveling through the atmosphere. For tracking, photoluminescent tags with a peak emission (1400 nm), which lays in such a region of strong absorption through the atmosphere, were attached to the animals. The photoluminescent properties of passivated lead sulphide quantum dots were responsible for the emission of light by the tags and provide a superb signal-to noise ratio. We developed prototype markers with a weight of 12.5 mg and a diameter of 5 mm. Furthermore, we developed a short wave infrared detection system which can record and determine the position of an animal in a heterogeneous environment with a delay smaller than 10 ms. With this method we were able to track tagged bumblebees as well as hawk moths in a flight arena that was placed outside on a natural meadow.
Conclusion
Our new method eliminates the necessity of a constant or predictable environment for many experimental setups. Furthermore, we postulate that the developed matrix-detector mounted to a multicopter will enable tracking of small flying insects, over medium range distances (>1000m) in the near future because: a) the matrix-detector equipped with an 70 mm interchangeable lens weighs less than 380 g, b) it evaluates the position of an animal in real-time and c) it can directly control and communicate with electronic devices.
A new underwater 3D scanning device based on structured illumination and designed for continuous capture of object data in motion for deep sea inspection applications is introduced. The sensor permanently captures 3D data of the inspected surface and generates a 3D surface model in real time. Sensor velocities up to 0.7 m/s are directly compensated while capturing camera images for the 3D reconstruction pipeline. The accuracy results of static measurements of special specimens in a water basin with clear water show the high accuracy potential of the scanner in the sub-millimeter range. Measurement examples with a moving sensor show the significance of the proposed motion compensation and the ability to generate a 3D model by merging individual scans. Future application tests in offshore environments will show the practical potential of the sensor for the desired inspection tasks.
Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is with a colonoscopy. During this procedure, the gastroenterologist searches for polyps. However, there is a potential risk of polyps being missed by the gastroenterologist. Automated detection of polyps helps to assist the gastroenterologist during a colonoscopy. There are already publications examining the problem of polyp detection in the literature. Nevertheless, most of these systems are only used in the research context and are not implemented for clinical application. Therefore, we introduce the first fully open-source automated polyp-detection system scoring best on current benchmark data and implementing it ready for clinical application. To create the polyp-detection system (ENDOMIND-Advanced), we combined our own collected data from different hospitals and practices in Germany with open-source datasets to create a dataset with over 500,000 annotated images. ENDOMIND-Advanced leverages a post-processing technique based on video detection to work in real-time with a stream of images. It is integrated into a prototype ready for application in clinical interventions. We achieve better performance compared to the best system in the literature and score a F1-score of 90.24% on the open-source CVC-VideoClinicDB benchmark.
Mini Unmanned Aerial Vehicles (MUAVs) are becoming popular research platform and drawing considerable attention, particularly during the last decade due to their multi-dimensional applications in almost every walk of life. MUAVs range from simple toys found at electronic supermarkets for entertainment purpose to highly sophisticated commercial platforms performing novel assignments like offshore wind power station inspection and 3D modelling of buildings. This paper presents an overview of the main aspects in the domain of distributed control of cooperating MUAVs to facilitate the potential users in this fascinating field. Furthermore it gives an overview on state of the art in MUAV technologies e.g. Photonic Mixer Devices (PMD) camera, distributed control methods and on-going work and challenges, which is the motivation for many researchers all over the world to work in this field.