000 Informatik, Informationswissenschaft, allgemeine Werke
Refine
Document Type
- Article (39)
- Doctoral Thesis (23)
- Conference Proceeding (12)
- Master's Thesis (6)
- Preprint (6)
- Bachelor Thesis (5)
- Report (4)
- Book (2)
- Sound (1)
- Study Thesis (1)
Institute
- Junior-Professur Computational Architecture (26)
- Institut für Strukturmechanik (ISM) (19)
- Professur Informatik in der Architektur (10)
- Professur Bauphysik (5)
- Professur Content Management und Webtechnologien (5)
- Professur Systeme der Virtuellen Realität (5)
- Professur Informatik im Bauwesen (4)
- Professur Modellierung und Simulation - Konstruktion (4)
- Bauhaus-Institut für zukunftsweisende Infrastruktursysteme (b.is) (3)
- Professur Mediensicherheit (3)
- Universitätsbibliothek (2)
- Fachbereich Medieninformatik (1)
- Fakultät Kunst und Gestaltung (1)
- Hochschule für Musik FRANZ LISZT (1)
- In Zusammenarbeit mit der Bauhaus-Universität Weimar (1)
- Junior-Professur Augmented Reality (1)
- Materialforschungs- und -prüfanstalt an der Bauhaus-Universität (1)
- Medienkunst/Mediengestaltung (1)
- Professur Baubetrieb und Bauverfahren (1)
- Professur Bauformenlehre (1)
- Professur Baumanagement und Bauwirtschaft (1)
- Professur Graphische Datenverarbeitung (1)
- Professur Interface Design (1)
- Professur Kulturgeschichte der Moderne (1)
- Professur Medieninformatik (1)
- Professur Medienmanagement (1)
- Professur Siedlungswasserwirtschaft (1)
- Theorie und Geschichte des Design (1)
- bauhaus.institut für experimentelle Architektur (1)
Keywords
- Architektur (10)
- Maschinelles Lernen (10)
- Machine learning (7)
- machine learning (6)
- CAD (5)
- Städtebau (5)
- BIM (4)
- Deep learning (4)
- Informatik (4)
- OA-Publikationsfonds2020 (4)
Diese Arbeit beschäftigt sich mit der Nutzung von Worteinbettungen in der automatischen Analyse von argumentativen Texten. Die Arbeit diskutiert wichtige Einstellungen des Einbettungsverfahren sowie diverse Anwendungsmethoden der eingebetteten Wortvektoren für drei Aufgaben der automatischen argumentativen Analyse: Textsegmentierung, Argumentativitäts-Klassifikation und Relationenfindung. Meine Experimente auf zwei Standard-Argumentationsdatensätzen zeigen die folgenden Haupterkenntnisse: Bei der Textsegmentierung konnten keine Verbesserungen erzielt werden, während in der Argumentativitäts-Klassifikation und der Relationenfindung sich kleine Erfolge gezeigt haben und weitere bestimmte Forschungsthesen bewahrheitet werden konnten. In der Diskussion wird darauf eingegangen, warum bei der einfachen Worteinbettung in der argumentativen Analyse sich kaum nutzbare Ergebnisse erzielen lassen konnten, diese sich aber in Zukunft durch erweiterte Worteinbettungsverfahren verbessern können.
Wissen wer wo wohnt
(2012)
In cities people live together in neighbourhoods. Here they can find the infrastructure they need, starting with shops for the daily purpose to the life-cycle based infrastructures like kindergartens or nursing homes. But not all neighbourhoods are identical. The infrastructure mixture varies from neighbourhood to neighbourhood, but different people have different needs which can change e.g. based on the life cycle situation or their affiliation to a specific milieu. We can assume that a person or family tries to settle in a specific neighbourhood that satisfies their needs. So, if the residents are happy with a neighbourhood, we can further assume that this neighbourhood satisfies their needs. The socio-oeconomic panel (SOEP) of the German Institute for Economy (DIW) is a survey that investigates the economic structure of the German population. Every four years one part of this survey includes questions about what infrastructures can be found in the respondents neighbourhood and the satisfaction of the respondent with their neighbourhood. Further, it is possible to add a milieu estimation for each respondent or household. This gives us the possibility to analyse the typical neighbourhoods in German cities as well as the infrastructure profiles of the different milieus. Therefore, we take the environment variables from the dataset and recode them into a binary variable – whether an infrastructure is available or not. According to Faust (2005), these sets can also be understood, as a network of actors in a neighbourhood, which share two, three or more infrastructures. Like these networks, this neighbourhood network can also be visualized as a bipartite affiliation network and therefore analysed using correspondence analysis. We will show how a neighbourhood analysis will benefit from an upstream correspondence analysis and how this could be done. We will also present and discuss the results of such an analysis.
Volumerendering ist eine Darstellungstechnik, um verschiedene räumliche Mess- und Simulationsdaten anschaulich, interaktiv grafisch darzustellen. Im folgenden Beitrag wird ein Verfahren vorgestellt, mehrere Volumendaten mit einem Architekturflächenmodell zu überlagern. Diese komplexe Darstellungsberechnung findet mit hardwarebeschleunigten Shadern auf der Grafikkarte statt. Im Beitrag wird hierzu der implementierte Softwareprototyp "VolumeRendering" vorgestellt. Neben dem interaktiven Berechnungsverfahren wurde ebenso Wert auf eine nutzerfreundliche Bedienung gelegt. Das Ziel bestand darin, eine einfache Bewertung der Volumendaten durch Fachplaner zu ermöglichen. Durch die Überlagerung, z. B. verschiedener Messverfahren mit einem Flächenmodell, ergeben sich Synergien und neue Auswertungsmöglichkeiten. Abschließend wird anhand von Beispielen aus einem interdisziplinären Forschungsprojekt die Anwendung des Softwareprototyps illustriert.
The production of a desired product needs an effective use of the experimental model. The present study proposes an extreme learning machine (ELM) and a support vector machine (SVM) integrated with the response surface methodology (RSM) to solve the complexity in optimization and prediction of the ethyl ester and methyl ester production process. The novel hybrid models of ELM-RSM and ELM-SVM are further used as a case study to estimate the yield of methyl and ethyl esters through a trans-esterification process from waste cooking oil (WCO) based on American Society for Testing and Materials (ASTM) standards. The results of the prediction phase were also compared with artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS), which were recently developed by the second author of this study. Based on the results, an ELM with a correlation coefficient of 0.9815 and 0.9863 for methyl and ethyl esters, respectively, had a high estimation capability compared with that for SVM, ANNs, and ANFIS. Accordingly, the maximum production yield was obtained in the case of using ELM-RSM of 96.86% for ethyl ester at a temperature of 68.48 °C, a catalyst value of 1.15 wt. %, mixing intensity of 650.07 rpm, and an alcohol to oil molar ratio (A/O) of 5.77; for methyl ester, the production yield was 98.46% at a temperature of 67.62 °C, a catalyst value of 1.1 wt. %, mixing intensity of 709.42 rpm, and an A/O of 6.09. Therefore, ELM-RSM increased the production yield by 3.6% for ethyl ester and 3.1% for methyl ester, compared with those for the experimental data.
This thesis suggests cooperation as a design paradigm for human-computer interaction. The basic idea is that the synergistic co-operation of interfaces through concurrent user activities enables increased interaction fluency and expressiveness. This applies to bimanual interaction and multi-finger input, e.g., touch typing, as well as the collaboration of multiple users. Cooperative user interfaces offer more interaction
flexibility and expressivity for single and multiple users.
Part I of this thesis analyzes the state of the art in user interface design. It explores limitations of common approaches and reveals the crucial role of cooperative action in several established user interfaces and research prototypes. A review of related research in psychology and human-computer interaction offers insights to the cognitive, behavioral, and ergonomic foundations of cooperative user interfaces. Moreover, this thesis suggests a broad applicability of generic cooperation patterns and contributes three high-level design principles.
Part II presents three experiments towards cooperative user interfaces in detail. A study on desktop-based 3D input devices, explores fundamental benefits of cooperative bimanual input and the impact of interface design on bimanual cooperative behavior. A novel interaction technique for multitouch devices is presented that follows the paradigm of cooperative user interfaces and demonstrates advantages over the status quo. Finally, this thesis introduces a fundamentally new display technology that provides up to six users with their individual perspectives of a shared 3D environment. The system creates new possibilities for the cooperative interaction of
multiple users.
Part III of this thesis builds on the research results described in Part II, in particular, the multi-user 3D display system. A series of case studies in the field of collaborative virtual reality provides exemplary evidence for the relevance and applicability of the suggested design principles.
Superimposing Dynamic Range
(2009)
Replacing a uniform illumination by a high-frequent illumination enhances the contrast of observed and captured images. We modulate spatially and temporally multiplexed (projected) light with reflective or transmissive matter to achieve high dynamic range visualizations of radiological images on printed paper or ePaper, and to boost the optical contrast of images viewed or imaged with light microscopes.
Management strategies for sustainable sugarcane production need to deal with the increasing complexity and variability of the whole sugar system. Moreover, they need to accommodate the multiple goals of different industry sectors and the wider community. Traditional disciplinary approaches are unable to provide integrated management solutions, and an approach based on whole systems analysis is essential to bring about beneficial change to industry and the community. The application of this approach to water management, environmental management and cane supply management is outlined, where the literature indicates that the application of extreme learning machine (ELM) has never been explored in this realm. Consequently, the leading objective of the current research was set to filling this gap by applying ELM to launch swift and accurate model for crop production data-driven. The key learning has been the need for innovation both in the technical aspects of system function underpinned by modelling of sugarcane growth. Therefore, the current study is an attempt to establish an integrate model using ELM to predict the concluding growth amount of sugarcane. Prediction results were evaluated and further compared with artificial neural network (ANN) and genetic programming models. Accuracy of the ELM model is calculated using the statistics indicators of Root Means Square Error (RMSE), Pearson Coefficient (r), and Coefficient of Determination (R2) with promising results of 0.8, 0.47, and 0.89, respectively. The results also show better generalization ability in addition to faster learning curve. Thus, proficiency of the ELM for supplementary work on advancement of prediction model for sugarcane growth was approved with promising results.
Structural optimization has gained considerable attention in the design of structural engineering structures, especially in the preliminary phase.
This study introduces an unconventional approach for structural optimization by utilizing the Energy method with Integral Material Behavior (EIM), based on the Lagrange’s principle of minimum potential energy. An automated two-level optimization search process is proposed, which integrates the EIM, as an alternative method for nonlinear
structural analysis, and the bilevel optimization. The proposed procedure secures the equilibrium through minimizing the potential energy on one level, and on a higher level, a design objective function. For this, the most robust strategy of bilevel optimization, the nested method is used. The function of the potential energy is investigated along with its instabilities for physical nonlinear analysis through principle examples, by which the advantages and limitations using this method are reviewed. Furthermore, optimization algorithms are discussed.
A numerical fully functional code is developed for nonlinear cross section,
element and 2D frame analysis, utilizing different finite elements and is verified
against existing EIM programs. As a proof of concept, the method is applied on selected
examples using this code on cross section and element level. For the former one a
comparison is made with standard procedure, by employing the equilibrium equations
within the constrains. The validation of the element level was proven by a theoretical
solution of an arch bridge and finally, a truss bridge is optimized. Most of the
principle examples are chosen to be adequate for the everyday engineering practice, to
demonstrate the effectiveness of the proposed method.
This study implies that with further development, this method could become just as
competitive as the conventional structural optimization techniques using the Finite
Element Method.
Following restructuring of power industry, electricity supply to end-use customers has undergone fundamental changes. In the restructured power system, some of the responsibilities of the vertically integrated distribution companies have been assigned to network managers and retailers. Under the new situation, retailers are in charge of providing electrical energy to electricity consumers who have already signed contract with them. Retailers usually provide the required energy at a variable price, from wholesale electricity markets, forward contracts with energy producers, or distributed energy generators, and sell it at a fixed retail price to its clients. Different strategies are implemented by retailers to reduce the potential financial losses and risks associated with the uncertain nature of wholesale spot electricity market prices and electrical load of the consumers. In this paper, the strategic behavior of retailers in implementing forward contracts, distributed energy sources, and demand-response programs with the aim of increasing their profit and reducing their risk, while keeping their retail prices as low as possible, is investigated. For this purpose, risk management problem of the retailer companies collaborating with wholesale electricity markets, is modeled through bi-level programming approach and a comprehensive framework for retail electricity pricing, considering customers’ constraints, is provided in this paper. In the first level of the proposed bi-level optimization problem, the retailer maximizes its expected profit for a given risk level of profit variability, while in the second level, the customers minimize their consumption costs. The proposed programming problem is modeled as Mixed Integer programming (MIP) problem and can be efficiently solved using available commercial solvers. The simulation results on a test case approve the effectiveness of the proposed demand-response program based on dynamic pricing approach on reducing the retailer’s risk and increasing its profit.
In this paper, the decision-making problem of the retailers under dynamic pricing approach for demand response integration have been investigated. The retailer was supposed to rely on forward contracts, DGs, and spot electricity market to supply the required active and reactive power of its customers. To verify the effectiveness of the proposed model, four schemes for retailer’s scheduling problem are considered and the resulted profit under each scheme are analyzed and compared. The simulation results on a test case indicate that providing more options for the retailer to buy the required power of its customers and increase its flexibility in buying energy from spot electricity market reduces the retailers’ risk and increases its profit. From the customers’ perspective also the retailers’accesstodifferentpowersupplysourcesmayleadtoareductionintheretailelectricityprices. Since the retailer would be able to decrease its electricity selling price to the customers without losing its profitability, with the aim of attracting more customers. Inthiswork,theconditionalvalueatrisk(CVaR)measureisusedforconsideringandquantifying riskinthedecision-makingproblems. Amongallthepossibleoptioninfrontoftheretailertooptimize its profit and risk, demand response programs are the most beneficial option for both retailer and its customers. The simulation results on the case study prove that implementing dynamic pricing approach on retail electricity prices to integrate demand response programs can successfully provoke customers to shift their flexible demand from peak-load hours to mid-load and low-load hours. Comparing the simulation results of the third and fourth schemes evidences the impact of DRPs and customers’ load shifting on the reduction of retailer’s risk, as well as the reduction of retailer’s payment to contract holders, DG owners, and spot electricity market. Furthermore, the numerical results imply on the potential of reducing average retail prices up to 8%, under demand response activation. Consequently, it provides a win–win solution for both retailer and its customers.