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In this study, machine learning methods of artificial neural networks (ANNs), least squares support vector machines (LSSVM), and neuro-fuzzy are used for advancing prediction models for thermal performance of a photovoltaic-thermal solar collector (PV/T). In the proposed models, the inlet temperature, flow rate, heat, solar radiation, and the sun heat have been considered as the input variables. Data set has been extracted through experimental measurements from a novel solar collector system. Different analyses are performed to examine the credibility of the introduced models and evaluate their performances. The proposed LSSVM model outperformed the ANFIS and ANNs models. LSSVM model is reported suitable when the laboratory measurements are costly and time-consuming, or achieving such values requires sophisticated interpretations.
The assessment of wind-induced vibrations is considered vital for the design of long-span bridges. The aim of this research is to develop a methodological framework for robust and efficient prediction strategies for complex aerodynamic phenomena using hybrid models that employ numerical analyses as well as meta-models. Here, an approach to predict motion-induced aerodynamic forces is developed using artificial neural network (ANN). The ANN is implemented in the classical formulation and trained with a comprehensive dataset which is obtained from computational fluid dynamics forced vibration simulations. The input to the ANN is the response time histories of a bridge section, whereas the output is the motion-induced forces. The developed ANN has been tested for training and test data of different cross section geometries which provide promising predictions. The prediction is also performed for an ambient response input with multiple frequencies. Moreover, the trained ANN for aerodynamic forcing is coupled with the structural model to perform fully-coupled fluid--structure interaction analysis to determine the aeroelastic instability limit. The sensitivity of the ANN parameters to the model prediction quality and the efficiency has also been highlighted. The proposed methodology has wide application in the analysis and design of long-span bridges.
The classical Internet of things routing and wireless sensor networks can provide more precise monitoring of the covered area due to the higher number of utilized nodes. Because of the limitations in shared transfer media, many nodes in the network are prone to the collision in simultaneous transmissions. Medium access control protocols are usually more practical in networks with low traffic, which are not subjected to external noise from adjacent frequencies. There are preventive, detection and control solutions to congestion management in the network which are all the focus of this study. In the congestion prevention phase, the proposed method chooses the next step of the path using the Fuzzy decision-making system to distribute network traffic via optimal paths. In the congestion detection phase, a dynamic approach to queue management was designed to detect congestion in the least amount of time and prevent the collision. In the congestion control phase, the back-pressure method was used based on the quality of the queue to decrease the probability of linking in the pathway from the pre-congested node. The main goals of this study are to balance energy consumption in network nodes, reducing the rate of lost packets and increasing quality of service in routing. Simulation results proved the proposed Congestion Control Fuzzy Decision Making (CCFDM) method was more capable in improving routing parameters as compared to recent algorithms.
Coronary Artery Disease Diagnosis: Ranking the Significant Features Using a Random Trees Model
(2020)
Heart disease is one of the most common diseases in middle-aged citizens. Among the vast number of heart diseases, coronary artery disease (CAD) is considered as a common cardiovascular disease with a high death rate. The most popular tool for diagnosing CAD is the use of medical imaging, e.g., angiography. However, angiography is known for being costly and also associated with a number of side effects. Hence, the purpose of this study is to increase the accuracy of coronary heart disease diagnosis through selecting significant predictive features in order of their ranking. In this study, we propose an integrated method using machine learning. The machine learning methods of random trees (RTs), decision tree of C5.0, support vector machine (SVM), and decision tree of Chi-squared automatic interaction detection (CHAID) are used in this study. The proposed method shows promising results and the study confirms that the RTs model outperforms other models.
Long-span bridges are prone to wind-induced vibrations. Therefore, a reliable representation of the aerodynamic forces acting on a bridge deck is of a major significance for the design of such structures. This paper presents a systematic study of the two-dimensional (2D) fluid-structure interaction of a bridge deck under smooth and turbulent wind conditions. Aerodynamic forces are modeled by two approaches: a computational fluid dynamics (CFD) model and six semi-analytical models. The vortex particle method is utilized for the CFD model and the free-stream turbulence is introduced by seeding vortex particles upstream of the deck with prescribed spectral characteristics. The employed semi-analytical models are based on the quasi-steady and linear unsteady assumptions and aerodynamic coefficients obtained from CFD analyses.
The underlying assumptions of the semi-analytical aerodynamic models are used to interpret the results of buffeting forces and aeroelastic response due to a free-stream turbulence in comparison with the CFD model. Extensive discussions are provided to analyze the effect of linear fluid memory and quasi-steady nonlinearity from a CFD perspective. The outcome of the analyses indicates that the fluid memory is a governing effect in the buffeting forces and aeroelastic response, while the effect of the nonlinearity is overestimated by the quasi-steady models. Finally, flutter analyses are performed and the obtained critical velocities are further compared with wind tunnel results, followed by a brief examination of the post-flutter behavior. The results of this study provide a deeper understanding of the extent of which the applied models are able to replicate the physical processes for fluid-structure interaction phenomena in bridge aerodynamics and aeroelasticity.
The longitudinal dispersion coefficient (LDC) plays an important role in modeling the transport of pollutants and sediment in natural rivers. As a result of transportation processes, the concentration of pollutants changes along the river. Various studies have been conducted to provide simple equations for estimating LDC. In this study, machine learning methods, namely support vector regression, Gaussian process regression, M5 model tree (M5P) and random forest, and multiple linear regression were examined in predicting the LDC in natural streams. Data sets from 60 rivers around the world with different hydraulic and geometric features were gathered to develop models for LDC estimation. Statistical criteria, including correlation coefficient (CC), root mean squared error (RMSE) and mean absolute error (MAE), were used to scrutinize the models. The LDC values estimated by these models were compared with the corresponding results of common empirical models. The Taylor chart was used to evaluate the models and the results showed that among the machine learning models, M5P had superior performance, with CC of 0.823, RMSE of 454.9 and MAE of 380.9. The model of Sahay and Dutta, with CC of 0.795, RMSE of 460.7 and MAE of 306.1, gave more precise results than the other empirical models. The main advantage of M5P models is their ability to provide practical formulae. In conclusion, the results proved that the developed M5P model with simple formulations was superior to other machine learning models and empirical models; therefore, it can be used as a proper tool for estimating the LDC in rivers.
Temporary changes in precipitation may lead to sustained and severe drought or massive floods in different parts of the world. Knowing the variation in precipitation can effectively help the water resources decision-makers in water resources management. Large-scale circulation drivers have a considerable impact on precipitation in different parts of the world. In this research, the impact of El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO) on seasonal precipitation over Iran was investigated. For this purpose, 103 synoptic stations with at least 30 years of data were utilized. The Spearman correlation coefficient between the indices in the previous 12 months with seasonal precipitation was calculated, and the meaningful correlations were extracted. Then, the month in which each of these indices has the highest correlation with seasonal precipitation was determined. Finally, the overall amount of increase or decrease in seasonal precipitation due to each of these indices was calculated. Results indicate the Southern Oscillation Index (SOI), NAO, and PDO have the most impact on seasonal precipitation, respectively. Additionally, these indices have the highest impact on the precipitation in winter, autumn, spring, and summer, respectively. SOI has a diverse impact on winter precipitation compared to the PDO and NAO, while in the other seasons, each index has its special impact on seasonal precipitation. Generally, all indices in different phases may decrease the seasonal precipitation up to 100%. However, the seasonal precipitation may increase more than 100% in different seasons due to the impact of these indices. The results of this study can be used effectively in water resources management and especially in dam operation.
Due to the importance of identifying crop cultivars, the advancement of accurate assessment of cultivars is considered essential. The existing methods for identifying rice cultivars are mainly time-consuming, costly, and destructive. Therefore, the development of novel methods is highly beneficial. The aim of the present research is to classify common rice cultivars in Iran based on color, morphologic, and texture properties using artificial intelligence (AI) methods. In doing so, digital images of 13 rice cultivars in Iran in three forms of paddy, brown, and white are analyzed through pre-processing and segmentation of using MATLAB. Ninety-two specificities, including 60 color, 14 morphologic, and 18 texture properties, were identified for each rice cultivar. In the next step, the normal distribution of data was evaluated, and the possibility of observing a significant difference between all specificities of cultivars was studied using variance analysis. In addition, the least significant difference (LSD) test was performed to obtain a more accurate comparison between cultivars. To reduce data dimensions and focus on the most effective components, principal component analysis (PCA) was employed. Accordingly, the accuracy of rice cultivar separations was calculated for paddy, brown rice, and white rice using discriminant analysis (DA), which was 89.2%, 87.7%, and 83.1%, respectively. To identify and classify the desired cultivars, a multilayered perceptron neural network was implemented based on the most effective components. The results showed 100% accuracy of the network in identifying and classifying all mentioned rice cultivars. Hence, it is concluded that the integrated method of image processing and pattern recognition methods, such as statistical classification and artificial neural networks, can be used for identifying and classification of rice cultivars.
Calculating hydrocarbon components solubility of natural gases is known as one of the important issues for operational works in petroleum and chemical engineering. In this work, a novel solubility estimation tool has been proposed for hydrocarbon gases—including methane, ethane, propane, and butane—in aqueous electrolyte solutions based on extreme learning machine (ELM) algorithm. Comparing the ELM outputs with a comprehensive real databank which has 1175 solubility points yielded R-squared values of 0.985 and 0.987 for training and testing phases respectively. Furthermore, the visual comparison of estimated and actual hydrocarbon solubility led to confirm the ability of proposed solubility model. Additionally, sensitivity analysis has been employed on the input variables of model to identify their impacts on hydrocarbon solubility. Such a comprehensive and reliable study can help engineers and scientists to successfully determine the important thermodynamic properties, which are key factors in optimizing and designing different industrial units such as refineries and petrochemical plants.
The effect of urban form on energy consumption has been the subject of various studies around the world. Having examined the effect of buildings on energy consumption, these studies indicate that the physical form of a city has a notable impact on the amount of energy consumed in its spaces. The present study identified the variables that affected energy consumption in residential buildings and analyzed their effects on energy consumption in four neighborhoods in Tehran: Apadana, Bimeh, Ekbatan-phase I, and Ekbatan-phase II. After extracting the variables, their effects are estimated with statistical methods, and the results are compared with the land surface temperature (LST) remote sensing data derived from Landsat 8 satellite images taken in the winter of 2019. The results showed that physical variables, such as the size of buildings, population density, vegetation cover, texture concentration, and surface color, have the greatest impacts on energy usage. For the Apadana neighborhood, the factors with the most potent effect on energy consumption were found to be the size of buildings and the population density. However, for other neighborhoods, in addition to these two factors, a third factor was also recognized to have a significant effect on energy consumption. This third factor for the Bimeh, Ekbatan-I, and Ekbatan-II neighborhoods was the type of buildings, texture concentration, and orientation of buildings, respectively.
Evaporation is a very important process; it is one of the most critical factors in agricultural, hydrological, and meteorological studies. Due to the interactions of multiple climatic factors, evaporation is considered as a complex and nonlinear phenomenon to model. Thus, machine learning methods have gained popularity in this realm. In the present study, four machine learning methods of Gaussian Process Regression (GPR), K-Nearest Neighbors (KNN), Random Forest (RF) and Support Vector Regression (SVR) were used to predict the pan evaporation (PE). Meteorological data including PE, temperature (T), relative humidity (RH), wind speed (W), and sunny hours (S) collected from 2011 through 2017. The accuracy of the studied methods was determined using the statistical indices of Root Mean Squared Error (RMSE), correlation coefficient (R) and Mean Absolute Error (MAE). Furthermore, the Taylor charts utilized for evaluating the accuracy of the mentioned models. The results of this study showed that at Gonbad-e Kavus, Gorgan and Bandar Torkman stations, GPR with RMSE of 1.521 mm/day, 1.244 mm/day, and 1.254 mm/day, KNN with RMSE of 1.991 mm/day, 1.775 mm/day, and 1.577 mm/day, RF with RMSE of 1.614 mm/day, 1.337 mm/day, and 1.316 mm/day, and SVR with RMSE of 1.55 mm/day, 1.262 mm/day, and 1.275 mm/day had more appropriate performances in estimating PE values. It was found that GPR for Gonbad-e Kavus Station with input parameters of T, W and S and GPR for Gorgan and Bandar Torkmen stations with input parameters of T, RH, W and S had the most accurate predictions and were proposed for precise estimation of PE. The findings of the current study indicated that the PE values may be accurately estimated with few easily measured meteorological parameters.
Estimating the solubility of carbon dioxide in ionic liquids, using reliable models, is of paramount importance from both environmental and economic points of view. In this regard, the current research aims at evaluating the performance of two data-driven techniques, namely multilayer perceptron (MLP) and gene expression programming (GEP), for predicting the solubility of carbon dioxide (CO2) in ionic liquids (ILs) as the function of pressure, temperature, and four thermodynamical parameters of the ionic liquid. To develop the above techniques, 744 experimental data points derived from the literature including 13 ILs were used (80% of the points for training and 20% for validation). Two backpropagation-based methods, namely Levenberg–Marquardt (LM) and Bayesian Regularization (BR), were applied to optimize the MLP algorithm. Various statistical and graphical assessments were applied to check the credibility of the developed techniques. The results were then compared with those calculated using Peng–Robinson (PR) or Soave–Redlich–Kwong (SRK) equations of state (EoS). The highest coefficient of determination (R2 = 0.9965) and the lowest root mean square error (RMSE = 0.0116) were recorded for the MLP-LMA model on the full dataset (with a negligible difference to the MLP-BR model). The comparison of results from this model with the vastly applied thermodynamic equation of state models revealed slightly better performance, but the EoS approaches also performed well with R2 from 0.984 up to 0.996. Lastly, the newly established correlation based on the GEP model exhibited very satisfactory results with overall values of R2 = 0.9896 and RMSE = 0.0201.
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.
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.
The need for finding persuasive arguments can arise in a variety of domains such as politics, finance, marketing or personal entertainment. In these domains, there is a demand to make decisions by oneself or to convince somebody about a specific topic. To obtain a conclusion, one has to search thoroughly different sources in literature and on the web to compare various arguments. Voice interfaces, in form of smartphone applications or smart speakers, present the user with natural conversations in a comfortable way to make search requests in contrast to a traditional search interface with keyboard and display. Benefits and obstacles of such a new interface are analyzed by conducting two studies. The first one consists of a survey for analyzing the target group with questions about situations, motivations, and possible demanding features. The latter one is a wizard-of-oz experiment to investigate possible queries on how a user formulates requests to such a novel system. The results indicate that a search interface with conversational abilities can build a helpful assistant, but to satisfy the demands of a broader audience some additional information retrieval and visualization features need to be implemented.
Urban planners are often challenged with the task of developing design solutions which must meet multiple, and often contradictory, criteria. In this paper, we investigated the trade-offs between social, psychological, and energy potential of the fundamental elements of urban form: the street network and the building massing. Since formal mehods to evaluate urban form from the psychological and social point of view are not readily available, we developed a methodological framework to quantify these criteria as the first contribution in this paper. To evaluate the psychological potential, we conducted a three-tiered empirical study starting from real world environments and then abstracting them to virtual environments. In each context, the implicit (physiological) response and explicit (subjective) response of pedestrians were measured. To quantify the social potential, we developed a street network centrality-based measure of social accessibility.
For the energy potential, we created an energy model to analyze the impact of pure geometric form on the energy demand of the building stock. The second contribution of this work is a method to identify distinct clusters of urban form and, for each, explore the trade-offs between the select design criteria. We applied this method to two case studies identifying nine types of urban form and their respective potential trade-offs, which are directly applicable for the assessment of strategic decisions regarding urban form during the early planning stages.
Der vorliegende Beitrag beschreibt die Problematik bei der Prognose verkehrsbedingter Schadstoff-Immissionen. Im Mittelpunkt steht die Entwicklung und der Aufbau einer Simulationsumgebung zur Evaluation von umweltorientierten Verkehrsmanagement-Strategien. Die Simulationsumgebung wird über die drei Felder Verkehr, Emission, Immission entwickelt und findet zunächst Anwendung in der Evaluation verkehrlicher Maßnahmen für die Friedberger Landstraße in Frankfurt am Main.
Modern immersive telepresence systems enable people at different locations to meet in virtual environments using realistic three-dimensional representations of their bodies. For the realization of such a three-dimensional version of a video conferencing system, each user is continuously recorded in 3D. These 3D recordings are exchanged over the network between remote sites. At each site, the remote recordings of the users, referred to as 3D video avatars, are seamlessly integrated into a shared virtual scenery and displayed in stereoscopic 3D for each user from his or her perspective.
This thesis reports on algorithmic and technical contributions to modern immersive telepresence systems and presents the design, implementation and evaluation of the first immersive group-to-group telepresence system in which each user is represented as realistic life-size 3D video avatar. The system enabled two remote user groups to meet and collaborate in a consistent shared virtual environment. The system relied on novel methods for the precise calibration and registration of color- and depth- sensors (RGBD) into the coordinate system of the application as well as an advanced distributed processing pipeline that reconstructs realistic 3D video avatars in real-time. During the course of this thesis, the calibration of 3D capturing systems was greatly improved. While the first development focused on precisely calibrating individual RGBD-sensors, the second stage presents a new method for calibrating and registering multiple color and depth sensors at a very high precision throughout a large 3D capturing volume. This method was further refined by a novel automatic optimization process that significantly speeds up the manual operation and yields similarly high accuracy. A core benefit of the new calibration method is its high runtime efficiency by directly mapping from raw depth sensor measurements into an application coordinate system and to the coordinates of its associated color sensor. As a result, the calibration method is an efficient solution in terms of precision and applicability in virtual reality and immersive telepresence applications. In addition to the core contributions, the results of two case studies which address 3D reconstruction and data streaming lead to the final conclusion of this thesis and to directions of future work in the rapidly advancing field of immersive telepresence research.
In the field of engineering, surrogate models are commonly used for approximating the behavior of a physical phenomenon in order to reduce the computational costs. Generally, a surrogate model is created based on a set of training data, where a typical method for the statistical design is the Latin hypercube sampling (LHS). Even though a space filling distribution of the training data is reached, the sampling process takes no information on the underlying behavior of the physical phenomenon into account and new data cannot be sampled in the same distribution if the approximation quality is not sufficient. Therefore, in this study we present a novel adaptive sampling method based on a specific surrogate model, the least-squares support vector regresson. The adaptive sampling method generates training data based on the uncertainty in local prognosis capabilities of the surrogate model - areas of higher uncertainty require more sample data. The approach offers a cost efficient calculation due to the properties of the least-squares support vector regression. The opportunities of the adaptive sampling method are proven in comparison with the LHS on different analytical examples. Furthermore, the adaptive sampling method is applied to the calculation of global sensitivity values according to Sobol, where it shows faster convergence than the LHS method. With the applications in this paper it is shown that the presented adaptive sampling method improves the estimation of global sensitivity values, hence reducing the overall computational costs visibly.
In this work, molecular separation of aqueous-organic was simulated by using combined soft computing-mechanistic approaches. The considered separation system was a microporous membrane contactor for separation of benzoic acid from water by contacting with an organic phase containing extractor molecules. Indeed, extractive separation is carried out using membrane technology where complex of solute-organic is formed at the interface. The main focus was to develop a simulation methodology for prediction of concentration distribution of solute (benzoic acid) in the feed side of the membrane system, as the removal efficiency of the system is determined by concentration distribution of the solute in the feed channel. The pattern of Adaptive Neuro-Fuzzy Inference System (ANFIS) was optimized by finding the optimum membership function, learning percentage, and a number of rules. The ANFIS was trained using the extracted data from the CFD simulation of the membrane system. The comparisons between the predicted concentration distribution by ANFIS and CFD data revealed that the optimized ANFIS pattern can be used as a predictive tool for simulation of the process. The R2 of higher than 0.99 was obtained for the optimized ANFIS model. The main privilege of the developed methodology is its very low computational time for simulation of the system and can be used as a rigorous simulation tool for understanding and design of membrane-based systems.
Highlights are, Molecular separation using microporous membranes. Developing hybrid model based on ANFIS-CFD for the separation process, Optimization of ANFIS structure for prediction of separation process
In computer-aided design (CAD), industrial products are designed using a virtual 3D model. A CAD model typically consists of curves and surfaces in a parametric representation, in most cases, non-uniform rational B-splines (NURBS). The same representation is also used for the analysis, optimization and presentation of the model. In each phase of this process, different visualizations are required to provide an appropriate user feedback. Designers work with illustrative and realistic renderings, engineers need a
comprehensible visualization of the simulation results, and usability studies or product presentations benefit from using a 3D display. However, the interactive visualization of NURBS models and corresponding physical simulations is a challenging task because of the computational complexity and the limited graphics hardware support.
This thesis proposes four novel rendering approaches that improve the interactive visualization of CAD models and their analysis. The presented algorithms exploit latest graphics hardware capabilities to advance the state-of-the-art in terms of quality, efficiency and performance. In particular, two approaches describe the direct rendering of the parametric representation without precomputed approximations and timeconsuming pre-processing steps. New data structures and algorithms are presented for the efficient partition, classification, tessellation, and rendering of trimmed NURBS surfaces as well as the first direct isosurface ray-casting approach for NURBS-based isogeometric analysis. The other two approaches introduce the versatile concept of programmable order-independent semi-transparency for the illustrative and comprehensible visualization of depth-complex CAD models, and a novel method for the hybrid reprojection of opaque and semi-transparent image information to accelerate stereoscopic rendering. Both approaches are also applicable to standard polygonal geometry which contributes to the computer graphics and virtual reality research communities.
The evaluation is based on real-world NURBS-based models and simulation data. The results show that rendering can be performed directly on the underlying parametric representation with interactive frame rates and subpixel-precise image results. The computational costs of additional visualization effects, such as semi-transparency and stereoscopic rendering, are reduced to maintain interactive frame rates. The benefit of this performance gain was confirmed by quantitative measurements and a pilot user study.
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.
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.
A Hybrid Clustering and Classification Technique for Forecasting Short-Term Energy Consumption
(2018)
Electrical energy distributor companies in Iran have to announce their energy demand at least three 3-day ahead of the market opening. Therefore, an accurate load estimation is highly crucial. This research invoked methodology based on CRISP data mining and used SVM, ANN, and CBA-ANN-SVM (a novel hybrid model of clustering with both widely used ANN and SVM) to predict short-term electrical energy demand of Bandarabbas. In previous studies, researchers introduced few effective parameters with no reasonable error about Bandarabbas power consumption. In this research we tried to recognize all efficient parameters and with the use of CBA-ANN-SVM model, the rate of error has been minimized. After consulting with experts in the field of power consumption and plotting daily power consumption for each week, this research showed that official holidays and weekends have impact on the power consumption. When the weather gets warmer, the consumption of electrical energy increases due to turning on electrical air conditioner. Also, con-sumption patterns in warm and cold months are different. Analyzing power consumption of the same month for different years had shown high similarity in power consumption patterns. Factors with high impact on power consumption were identified and statistical methods were utilized to prove their impacts. Using SVM, ANN and CBA-ANN-SVM, the model was built. Sine the proposed method (CBA-ANN-SVM) has low MAPE 5 1.474 (4 clusters) and MAPE 5 1.297 (3 clusters) in comparison with SVM (MAPE 5 2.015) and ANN (MAPE 5 1.790), this model was selected as the final model. The final model has the benefits from both models and the benefits of clustering. Clustering algorithm with discovering data structure, divides data into several clusters based on similarities and differences between them. Because data inside each cluster are more similar than entire data, modeling in each cluster will present better results. For future research, we suggest using fuzzy methods and genetic algorithm or a hybrid of both to forecast each cluster. It is also possible to use fuzzy methods or genetic algorithms or a hybrid of both without using clustering. It is issued that such models will produce better and more accurate results.
This paper presents a hybrid approach to predict the electric energy usage of weather-sensitive loads. The presented methodutilizes the clustering paradigm along with ANN and SVMapproaches for accurate short-term prediction of electric energyusage, using weather data. Since the methodology beinginvoked in this research is based on CRISP data mining, datapreparation has received a gr eat deal of attention in thisresear ch. Once data pre-processing was done, the underlyingpattern of electric energy consumption was extracted by themeans of machine learning methods to precisely forecast short-term energy consumption. The proposed approach (CBA-ANN-SVM) was applied to real load data and resulting higher accu-racy comparing to the existing models.
2018 American Institute of Chemical Engineers Environ Prog, 2018
https://doi.org/10.1002/ep.12934
As one of its primary objectives, Computer Graphics aims at the simulation of fabrics’ complex reflection behaviour. Characteristic surface reflectance of fabrics, such as highlights, anisotropy or retro-reflection arise the difficulty of synthesizing. This problem can be solved by using Bidirectional Texture Functions (BTFs), a 2D-texture under various light and view direction. But the acquisition of Bidirectional Texture Functions requires an expensive setup and the measurement process is very time-consuming. Moreover, the size of BTF data can range from hundreds of megabytes to several gigabytes, as a large number of high resolution pictures have to be used in any ideal cases. Furthermore, the three-dimensional textured models rendered through BTF rendering method are subject to various types of distortion during acquisition, synthesis, compression, and processing. An appropriate image quality assessment scheme is a useful tool for evaluating image processing algorithms, especially algorithms designed to leave the image visually unchanged. In this contribution, we present and conduct an investigation aimed at locating a robust threshold for downsampling BTF images without loosing perceptual quality. To this end, an experimental study on how decreasing the texture resolution influences perceived quality of the rendered images has been presented and discussed.
Next, two basic improvements to the use of BTFs for rendering are presented: firstly, the study addresses the cost of BTF acquisition by introducing a flexible low-cost step motor setup for BTF acquisition allowing to generate a high quality BTF database taken at user-defined arbitrary angles. Secondly, the number of acquired textures to the perceptual quality of renderings is adapted so that the database size is not overloaded and can fit better in memory when rendered.
Although visual attention is one of the essential attributes of HVS, it is neglected in most existing quality metrics. In this thesis an appropriate objective quality metric based on extracting visual attention regions from images and adequate investigation of the influence of visual attention on perceived image quality assessment, called Visual Attention Based Image Quality Metric (VABIQM), has been proposed. The novel metric indicates that considering visual saliency can offer significant benefits with regard to constructing objective quality metrics to predict the visible quality differences in images rendered by compressed and non-compressed BTFs and also outperforms straightforward existing image quality metrics at detecting perceivable differences.
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.
INTRODUCTION
The research field of sound landscape and public life, initially drew my attention during the master class of ‘Media of the Urban’, originally ‘Medien des Urbanen, which was given by Prof. Dr. Gabriele Schabacher in the 2015 summer semester. For the relevant class, I conducted an conceptual case study in Istanbul, Beyoglu District, with the intention of analysing the perception of the space by urban sound. During the summer 2015 I recorded various sounds of different spatial settings and developed the analysis by comparing the situations. By that time, I realized the inherent property of the sound as a medium for our perception in urban context.
In the 2015-2016 winter semester, I participated in the master class of the architectural project, named ‘Build Allegory’, which was given by Prof. Dipl.-Ing. Heike Büttner. The project was situated in Berlin Westkreuz, AVUS north curve, on the highway and was originally a race track from 1921. In this context, the aim of my project was to answer various questions, main of which was, how does the architectural form shape the sound of the place? And, how does the sound of the place shape the architectural from? Since the place is still serving mainly to the vehicles, although the function has differed, the sound objects and the context have remained. Through the existence of contextual references, I started with creating a computational tool for analysing the acoustic characteristics of this urban setting, which is fundamentally providing results as the sound cloud, driven from the sound ray tracing method. Regarding to this soundscape analysis method, which I developed, this computational tool assisted me to find an optimum reciprocal relation between architecture and sound.
Since I have been working on soundscape in the context of architecture, urban situations, public life and public space, I was determined to produce a comprehensive research in this field and propound the hypothesis; the existence of the reciprocity between the social behaviours in public space and the sound landscape. In which extent does this reciprocity exist? What are the effects of the public life on the sonic configurations of the space and the other way around?
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.
Die vorliegende Arbeit untersucht das Potential von Webanwendungen in 3D zur Vermittlung von Informationen im Allgemeinen und zur Darstellung von städtebaulichen Zusammenhängen im Speziellen.
Als grundlegender Faktor der visuellen und funktionalen Qualität - welche die Wahrnehmung des Nutzers direkt beeinflusst -, erfolgt die Bewertung der Machbarkeit von 3D Webinhalten unter Anwendung einer explorativen, qualitativen Evaluierung von Webagenturen.
Darauf aufbauend wird das Potential von 3D Webanwendungen aus Nutzerperspektive untersucht, um Zusammenhänge herstellen zu können: einerseits zwischen der Machbarkeit bei der Entwicklung und anderseits die Akzeptanzkriterien beim Rezipienten betreffend.
Die empirische Studie, die mit dem Forschungspartner Bosch für diese Arbeit modelliert wurde, eruiert zum einen, inwiefern 3D im Vergleich zu 2D und 2,5D, und zum anderen WebGL im Vergleich zu bisherigen 3D Webtechnologien die visuelle Wahrnehmung und kognitive Leistungsfähigkeit des Nutzers beeinflusst.
Die Erkenntnisse der Untersuchung zeigen Parallelen zu bestehenden Studien aus web-fernen Bereichen.
Um die Bedeutung von 3D Webanwendungen zur Verbesserung von Entscheidungsprozessen in Stadtplanungsprojekten ableiten zu können, werden Aspekte zur Interaktion und visuellen Wahrnehmung in den speziellen Kontext von Stadtplanungswerkzeugen gebracht. Dabei wird überprüft, ob sich web-basierte 3D Visualisierungen sinnvoll zur Vermittlung städtebaulicher Zusammenhänge einbinden lassen und inwieweit bestehende Projekte, wie in dieser Arbeit beispielhaft das vom Fraunhofer IGD entwickelte Forschungsprojekt urbanAPI, die Technologie WebGL nutzen können.
Vor diesem Hintergrund soll die Arbeit Akzeptanzkriterien und Nutzungsbarrieren von 3D Webanwendungen auf Basis der Technologie WebGL identifizieren, um einen Beitrag zur Machbarkeit von Webanwendungen und zur Entwicklung entsprechender Stadtplanungswerkzeuge zu leisten.
Augmented Urban Model: Ein Tangible User Interface zur Unterstützung von Stadtplanungsprozessen
(2011)
Im architektonischen und städtebaulichen Kontext erfüllen physische und digitale Modelle aufgrund ihrer weitgehend komplementären Eigenschaften und Qualitäten unterschiedliche, nicht verknüpfte Aufgaben und Funktionen im Entwurfs- und Planungsprozess. Während physische Modelle vor allem als Darstellungs- und Kommunikationsmittel aber auch als Arbeitswerkzeug genutzt werden, unterstützen digitale Modelle darüber hinaus die Evaluation eines Entwurfs durch computergestützte Analyse- und Simulationstechniken.
Analysiert wurden im Rahmen der in diesem Arbeitspapier vorgestellten Arbeit neben dem Einsatz des Modells als analogem und digitalem Werkzeug im Entwurf die Bedeutung des Modells für den Arbeitsprozess sowie Vorbilder aus dem Bereich der Tangible User Interfaces mit Bezug zu Architek¬tur und Städtebau. Aus diesen Betrachtungen heraus wurde ein Prototyp entwickelt, das Augmented Urban Model, das unter anderem auf den frühen Projekten und Forschungsansätzen aus dem Gebiet der Tangible User Interfaces aufsetzt, wie dem metaDESK von Ullmer und Ishii und dem Urban Planning Tool Urp von Underkoffler und Ishii.
Das Augmented Urban Model zielt darauf ab, die im aktuellen Entwurfs- und Planungsprozess fehlende Brücke zwischen realen und digitalen Modellwelten zu schlagen und gleichzeitig eine neue tangible Benutzerschnittstelle zu schaffen, welche die Manipulation von und die Interaktion mit digitalen Daten im realen Raum ermöglicht.
Dieses Arbeitspapier beschreibt, wie ausgehend von einem vorhandenen Straßennetzwerk Bebauungsareale mithilfe von Unterteilungsalgorithmen automatisch umgelegt, d.h. in Grundstücke unterteilt, und anschließend auf Basis verschiedener städtebaulicher Typen bebaut werden können. Die Unterteilung von Bebauungsarealen und die Generierung von Bebauungsstrukturen unterliegen dabei bestimmten stadtplanerischen Einschränkungen, Vorgaben und Parametern. Ziel ist es aus den dargestellten Untersuchungen heraus ein Vorschlagssystem für stadtplanerische Entwürfe zu entwickeln, das anhand der Umsetzung eines ersten Softwareprototyps zur Generierung von Stadtstrukturen weiter diskutiert wird.
Aktionsräume in Dresden
(2012)
In vorliegender Studie werden die Aktionsräume von Befragten in Dresden über eine standardisierte Befragung (n=360) untersucht. Die den Aktionsräumen zugrundeliegenden Aktivitäten werden unterschieden in Einkaufen für den täglichen Bedarf, Ausgehen (z.B. in Café, Kneipe, Gaststätte), Erholung im Freien (z.B. spazieren gehen, Nutzung von Grünanlagen) und private Geselligkeit (z.B. Feiern, Besuch von Verwandten/Freunden). Der Aktionsradius wird unterschieden in Wohnviertel, Nachbarviertel und sonstiges weiteres Stadtgebiet. Um aus den vier betrachteten Aktivitäten einen umfassenden Kennwert für den durchschnittlichen Aktionsradius eines Befragten zu bilden, wird ein Modell für den Kennwert eines Aktionsradius entwickelt. Die Studie kommt zu dem Ergebnis, dass das Alter der Befragten einen signifikanten – wenn auch geringen – Einfluss auf den Aktionsradius hat. Das Haushaltsnettoeinkommen hat einen mit Einschränkung signifikanten, ebenfalls geringen Einfluss auf alltägliche Aktivitäten der Befragten.
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.
In vorliegender Studie werden die Wohnstandortpräferenzen der Sinus-Milieugruppen in Dresden über eine standardisierte Befragung (n=318) untersucht. Es wird unterschieden zwischen handlungsleitenden Wohnstandortpräferenzen, die durch Anhaltspunkte auf der Handlungsebene stärker in Betracht gezogen werden sollten, und Wohnstandortpräferenzen, welche eher orientierenden Charakter haben. Die Wohnstandortpräferenzen werden untersucht anhand der Kategorien Ausstattung/Zustand der Wohnung/des näheren Wohnumfeldes, Versorgungsstruktur, soziales Umfeld, Baustrukturtyp, Ortsgebundenheit sowie des Aspektes des Images eines Stadtviertels. Um die Befragten den Sinus-Milieugruppen zuordnen zu können, wird ein Lebensweltsegment-Modell entwickelt, welches den Anspruch hat, die Sinus-Milieugruppen in der Tendenz abzubilden. Die Studie kommt zu dem Ergebnis, dass die Angehörigen der verschiedenen Lebensweltsegmente in jeder Kategorie - wenn auch z.T. auf geringerem Niveau - signifikante Unterschiede in der Bewertung einzelner Wohnstandortpräferenzen aufweisen.
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.
Previous models for the explanation of settlement processes pay little attention to the interactions between settlement spreading and road networks. On the basis of a dielectric breakdown model in combination with cellular automata, we present a method to steer precisely the generation of settlement structures with regard to their global and local density as well as the size and number of forming clusters. The resulting structures depend on the logic of how the dependence of the settlements and the road network is implemented to the simulation model. After analysing the state of the art we begin with a discussion of the mutual dependence of roads and land development. Next, we elaborate a model that permits the precise control of permeability in the developing structure as well as the settlement density, using the fewest necessary control parameters. On the basis of different characteristic values, possible settlement structures are analysed and compared with each other. Finally, we reflect on the theoretical contribution of the model with regard to the context of urban dynamics.
How does it come to particular structure formations in the cities and which strengths play a role in this process? On which elements can the phenomena be reduced to find the respective combination rules? How do general principles have to be formulated to be able to describe the urban processes so that different structural qualities can be produced? With the aid of mathematic methods, models based on four basic levels are generated in the computer, through which the connections between the elements and the rules of their interaction can be examined. Conclusions on the function of developing processes and the further urban origin can be derived.
PLANUNGSUNTERSTÜTZUNG DURCH DIE ANALYSE RÄUMLICHER PROZESSE MITTELS COMPUTERSIMULATIONEN. Erst wenn man – zumindest im Prinzip – versteht, wie eine Stadt mit ihren komplexen, verwobenen Vorgängen im Wesentlichen funktioniert, ist eine sinnvolle Stadtplanung möglich. Denn jede Planung bedeutet einen Eingriff in den komplexen Organismus einer Stadt. Findet dieser Eingriff ohne Wissen über die Funktionsweise des Organismus statt, können auch die Auswirkungen nicht abgeschätzt werden. Dieser Beitrag stellt dar, wie urbane Prozesse mittels Computersimulationen unter Zuhilfenahme so genannter Multi-Agenten-Systeme und Zellulärer Automaten verstanden werden können. von
At the end of the 1960s, architects at various universities world- wide began to explore the potential of computer technology for their profession. With the decline in prices for PCs in the 1990s and the development of various computer-aided architectural design systems (CAAD), the use of such systems in architectural and planning offices grew continuously. Because today no ar- chitectural office manages without a costly CAAD system and because intensive soſtware training has become an integral part of a university education, the question arises about what influence the various computer systems have had on the design process forming the core of architectural practice. The text at hand devel- ops ten theses about why there has been no success to this day in introducing computers such that new qualitative possibilities for design result. RESTRICTEDNESS
The structure and development of cities can be seen and evaluated from different points of view. By replicating the growth or shrinkage of a city using historical maps depicting different time states, we can obtain momentary snapshots of the dynamic mechanisms of the city. An examination of how these snapshots change over the course of time and a comparison of the different static time states reveals the various interdependencies of population density, technical infrastructure and the availability of public transport facilities. Urban infrastructure and facilities are not distributed evenly across the city – rather they are subject to different patterns and speeds of spread over the course of time and follow different spatial and temporal regularities. The reasons and underlying processes that cause the transition from one state to another result from the same recurring but varyingly pronounced hidden forces and their complex interactions. Such forces encompass a variety of economic, social, cultural and ecological conditions whose respective weighting defines the development of a city in general. Urban development is, however, not solely a product of the different spatial distribution of economic, legal or social indicators but also of the distribution of infrastructure. But to what extent is the development of a city affected by the changing provision of infrastructure? As
In the Space Syntax community, the standard tool for computing all kinds of spatial graph network measures is depthmapX (Turner, 2004; Varoudis, 2012). The process of evaluating many design variants of networks is relatively complicated, since they need to be drawn in a separated CAD system, exported and imported in depthmapX via dxf file format. This procedure disables a continuous integration into a design process. Furthermore, the standalone character of depthmapX makes it impossible to use its network centrality calculation for optimization processes. To overcome this limitations, we present in this paper the first steps of experimenting with a Grasshopper component (reference omitted until final version) that can access the functions of depthmapX and integrate them into Grasshopper/Rhino3D. Here the component is implemented in a way that it can be used directly for an evolutionary algorithm (EA) implemented in a Python scripting component in Grasshopper
In this paper we introduce LUCI, a Lightweight Urban Calculation Interchange system, designed to bring the advantages of calculation and content co-ordination system to small planning and design groups by the means of an open source middle-ware. The middle-ware focuses on problems typical to urban planning and therefore features a geo-data repository as well as a job runtime administration, to coordinate simulation models and its multiple views. The described system architecture is accompanied by two exemplary use cases, that have been used to test and further develop our concepts and implementations.
The described study aims to find correlations between urban spatial configurations and human emotions. To this end, the authors measured people’s emotions while they walk along a path in an urban area using an instrument that measures skin conductance and skin temperature. The corresponding locations of the test persons were measured recorded by using a GPS-tracker (n=13). The results are interpreted and categorized as measures for positive and negative emotional arousal. To evaluate the technical and methodological process. The test results offer initial evidence that certain spaces or spatial sequences do cause positive or negative emotional arousal while others are relatively neutral. To achieve the goal of the study, the outcome was used as a basis for the study of testing correlations between people’s emotional responses and urban spatial configurations represented by Isovist properties of the urban form. By using their model the authors can explain negative emotional arousal for certain places, but they couldn’t find a model to predict emotional responses for individual spatial configurations.
Urban planning involves many aspects and various disciplines, demanding an asynchronous planning approach. The level of complexity rises with each aspect to be considered and makes it difficult to find universally satisfactory solutions. To improve this situation we propose a new approach, which complement traditional design methods with a computational urban plan- ning method that can fulfil formalizable design requirements automatically. Based on this approach we present a design space exploration framework for complex urban planning projects. For a better understanding of the idea of design space exploration, we introduce the concept of a digital scout which guides planners through the design space and assists them in their creative explorations. The scout can support planners during manual design by informing them about potential im- pacts or by suggesting different solutions that fulfill predefined quality requirements. The planner can change flexibly between a manually controlled and a completely automated design process. The developed system is presented using an exemplary urban planning scenario on two levels from the street layout to the placement of building volumes. Based on Self-Organizing Maps we implemented a method which makes it possible to visualize the multi-dimensional solution space in an easily analysable and comprehensible form.
This work presents a concept of interactive machine learning in a human design process. An urban design problem is viewed as a multiple-criteria optimization problem. The outlined feature of an urban design problem is the dependence of a design goal on a context of the problem. We model the design goal as a randomized fitness measure that depends on the context. In terms of multiple-criteria decision analysis (MCDA), the defined measure corresponds to a subjective expected utility of a user. In the first stage of the proposed approach we let the algorithm explore a design space using clustering techniques. The second stage is an interactive design loop; the user makes a proposal, then the program optimizes it, gets the user’s feedback and returns back the control over the application interface.
It's not uncommon that analysis and simulation methods are used mainly to evaluate finished designs and to proof their quality. Whereas the potential of such methods is to lead or control a design process from the beginning on. Therefore, we introduce a design method that move away from a “what-if” forecasting philosophy and increase the focus on backcasting approaches. We use the power of computation by combining sophisticated methods to generate design with analysis methods to close the gap between analysis and synthesis of designs. For the development of a future-oriented computational design support we need to be aware of the human designer’s role. A productive combination of the excellence of human cognition with the power of modern computing technology is needed. We call this approach “cognitive design computing”. The computational part aim to mimic the way a designer’s brain works by combining state-of-the-art optimization and machine learning approaches with available simulation methods. The cognition part respects the complex nature of design problems by the provision of models for human-computation interaction. This means that a design problem is distributed between computer and designer. In the context of the conference slogan “back to command”, we ask how we may imagine the command over a cognitive design computing system. We expect that designers will need to let go control of some parts of the design process to machines, but in exchange they will get a new powerful command on complex computing processes. This means that designers have to explore the potentials of their role as commanders of partially automated design processes. In this contribution we describe an approach for the development of a future cognitive design computing system with the focus on urban design issues. The aim of this system is to enable an urban planner to treat a planning problem as a backcasting problem by defining what performance a design solution should achieve and to automatically query or generate a set of best possible solutions. This kind of computational planning process offers proof that the designer meets the original explicitly defined design requirements. A key way in which digital tools can support designers is by generating design proposals. Evolutionary multi-criteria optimization methods allow us to explore a multi-dimensional design space and provide a basis for the designer to evaluate contradicting requirements: a task urban planners are faced with frequently. We also reflect why designers will give more and more control to machines. Therefore, we investigate first approaches learn how designers use computational design support systems in combination with manual design strategies to deal with urban design problems by employing machine learning methods. By observing how designers work, it is possible to derive more complex artificial solution strategies that can help computers make better suggestions in the future.
In this paper we introduce LUCI, a Lightweight Urban Calculation Interchange system, designed to bring the advantages of a calculation and content co-ordination system to small planning and design groups by the means of an open source middle-ware. The middle-ware focuses on problems typical to urban planning and therefore features a geo-data repository as well as a job runtime administration, to coordinate simulation models and its multiple views. The described system architecture is accompanied by two exemplary use cases that have been used to test and further develop our concepts and implementations.
Das Erzeugen räumlicher Konfigurationen ist eine zentrale Aufgabe im architektonischen bzw. städtebaulichen Entwurfsprozess und hat zum Ziel, eine für Menschen angenehme Umwelt zu schaffen. Der Geometrie der entstehenden Räume kommt hierbei eine zentrale Rolle zu, da sie einen großen Einfluss auf das Empfinden und Verhalten der Menschen ausübt und nur noch mit großem Aufwand verändert werden kann, wenn sie einmal gebaut wurde. Die meisten Entscheidungen zur Festlegung der Geometrie von Räumen werden während eines sehr kurzen Zeitraums (Entwurfsphase) getroffen. Fehlentscheidungen die in dieser Phase getroffen werden haben langfristige Auswirkungen auf das Leben von Menschen, und damit auch Konsequenzen auf ökonomische und ökologische Aspekte.
Mittels computerbasierten Layoutsystemen lässt sich der Entwurf räumlicher Konfigurationen sinnvoll unterstützen, da sie es ermöglichen, in kürzester Zeit eine große Anzahl an Varianten zu erzeugen und zu überprüfen. Daraus ergeben sich zwei Vorteile. Erstens kann die große Menge an Varianten dazu beitragen, bessere Lösungen zu finden. Zweitens kann das Formalisieren von Bewertungskriterien zu einer größeren Objektivität und Transparenz bei der Lösungsfindung führen. Um den Entwurf räumlicher Konfigurationen optimal zu unterstützen, muss ein Layoutsystem in der Lage sein, ein möglichst großes Spektrum an Grundrissvarianten zu erzeugen (Vielfalt); und zahlreiche Möglichkeiten und Detaillierungsstufen zur Problembeschreibung (Flexibilität), sowie Mittel anzubieten, mit denen sich die Anforderungen an die räumliche Konfiguration adäquat beschreiben lassen (Relevanz). Bezüglich Letzterem spielen wahrnehmungs- und nutzungsbezogene Kriterien (wie z. B. Grad an Privatheit, Gefühl von Sicherheit, Raumwirkung, Orientierbarkeit, Potenzial zu sozialer Interaktion) eine wichtige Rolle.
Die bislang entwickelten Layoutsysteme weisen hinsichtlich Vielfalt, Flexibilität und Relevanz wesentliche Beschränkungen auf, welche auf eine ungeeignete Methode zur Repräsentation von Räumen zurückzuführen sind. Die in einem Layoutsystem verwendeten Raumrepräsentationsmethoden bestimmen die Möglichkeiten zur Formerzeugung und Problembeschreibung wesentlich. Sichtbarkeitsbasierte Raumrepräsentationen (Sichtfelder, Sichtachsen, Konvexe Räume) eignen sich in besonderer Weise zur Abbildung von Räumen in Layoutsystemen, da sie einerseits ein umfangreiches Repertoire zur Verfügung stellen, um räumliche Konfigurationen hinsichtlich wahrnehmungs- und nutzungsbezogener Kriterien zu beschreiben. Andererseits lassen sie sich vollständig aus der Geometrie der begrenzenden Oberflächen ableiten und sind nicht an bestimmte zur Formerzeugung verwendete geometrische Objekte gebunden.
In der vorliegenden Arbeit wird ein Layoutsystem entwickelt, welches auf diesen Raumrepräsentationen basiert. Es wird ein Evaluationsmechanismus (EM) entwickelt, welcher es ermöglicht, beliebige zweidimensionale räumliche Konfigurationen hinsichtlich wahrnehmungs- und nutzungsrelevanter Kriterien zu bewerten. Hierzu wurde eine Methodik entwickelt, die es ermöglicht automatisch Raumbereiche (O-Spaces und P-Spaces) zu identifizieren, welche bestimmte Eigenschaften haben (z.B. sichtbare Fläche, Kompaktheit des Sichtfeldes, Tageslicht) und bestimmte Relationen zueinander (wie gegenseitige Sichtbarkeit, visuelle und physische Distanz) aufweisen. Der EM wurde mit Generierungsmechanismen (GM) gekoppelt, um zu prüfen, ob dieser sich eignet, um in großen Variantenräumen nach geeigneten räumlichen Konfigurationen zu suchen. Die Ergebnisse dieser Experimente zeigen, dass die entwickelte Methodik einen vielversprechenden Ansatz zur automatisierten Erzeugung von räumlichen Konfigurationen darstellt: Erstens ist der EM vollständig vom GM getrennt, wodurch es möglich ist, verschiedene GM in einem Entwurfssystem zu verwenden und somit den Variantenraum zu vergrößern (Vielfalt). Zweitens erlaubt der EM die Anforderungen an eine räumliche Konfiguration flexibel zu beschreiben (unterschiedliche Maßstäbe, unterschiedlicher Detaillierungsgrad). Letztlich erlauben die verwendeten Repräsentationsmethoden eine Problembeschreibung vorzunehmen, die stark an der Wirkung des Raumes auf den Menschen orientiert ist (Relevanz).
Die in der Arbeit entwickelte Methodik leistet einen wichtigen Beitrag zur Verbesserung evidenzbasierter Entwurfsprozesse, da sie eine Brücke zwischen der nutzerorientierten Bewertung von räumlichen Konfigurationen und deren Erzeugung schlägt.
Based on the description of a conceptual framework for the representation of planning problems on various scales, we introduce an evolutionary design optimization system. This system is exemplified by means of the generation of street networks with locally defined properties for centrality. We show three different scenarios for planning requirements and evaluate the resulting structures with respect to the requirements of our framework. Finally the potentials and challenges of the presented approach are discussed in detail.
When working on urban planning projects there are usually multiple aspects to consider. Often these aspects are contradictory and it is not possible to choose one over the other; instead, they each need to be fulfilled as well as possible. Planners typically draw on past experience when subjectively prioritising which aspects to consider with which degree of importance for their planning concepts. This practice, although understandable, places power and authority in the hands of people who have varying degrees of expertise, which means that the best possible solution is not always found, because it is either not sought or the problem is regarded as being too complex for human capabilities. To improve this situation, the project presented here shows the potential of multi-criteria optimisation algorithms using the example of a new housing layout for an urban block. In addition it is shown, how Self-Organizing-Maps can be used to visualise multi-dimensional solution spaces in an easy analysable and comprehensible form.
In this paper we introduce LUCI, a Lightweight Urban Calculation Interchange system, designed to bring the advantages of a calculation and content co-ordination system to small planning and design groups by the means of an open source middle-ware. The middle-ware focuses on problems typical to urban planning and therefore features a geo-data repository as well as a job runtime administration, to coordinate simulation models and its multiple views. The described system architecture is accompanied by two exemplary use cases that have been used to test and further develop our concepts and implementations.
Some caad packages offer additional support for the optimization of spatial configurations, but the possibilities for applying optimization are usually limited either by the complexity of the data model or by the constraints of the underlying caad system. Since we missed a system that allows to experiment with optimization techniques for the synthesis of spatial configurations, we developed a collection of methods over the past years. This collection is now combined in the presented open source library for computational planning synthesis, called CPlan. The aim of the library is to provide an easy to use programming framework with a flat learning curve for people with basic programming knowledge. It offers an extensible structure that allows to add new customized parts for various purposes. In this paper the existing functionality of the CPlan library is described.
This thesis deals with the basic design and rigorous analysis of cryptographic schemes and primitives, especially of authenticated encryption schemes, hash functions, and password-hashing schemes.
In the last decade, security issues such as the PS3 jailbreak demonstrate that common security notions are rather restrictive, and it seems that they do not model the real world adequately. As a result, in the first part of this work, we introduce a less restrictive security model that is closer to reality. In this model it turned out that existing (on-line) authenticated encryption schemes cannot longer beconsidered secure, i.e. they can guarantee neither data privacy nor data integrity. Therefore, we present two novel authenticated encryption scheme, namely COFFE and McOE, which are not only secure in the standard model but also reasonably secure in our generalized security model, i.e. both preserve full data inegrity. In addition, McOE preserves a resonable level of data privacy.
The second part of this thesis starts with proposing the hash function Twister-Pi, a revised version of the accepted SHA-3 candidate Twister. We not only fixed all known security issues
of Twister, but also increased the overall soundness of our hash-function design.
Furthermore, we present some fundamental groundwork in the area of password-hashing schemes. This research was mainly inspired by the medial omnipresence of password-leakage incidences. We show that the password-hashing scheme scrypt is vulnerable against cache-timing attacks due to the existence of a password-dependent memory-access pattern. Finally, we introduce Catena the first password-hashing scheme that is both memory-consuming and resistant against cache-timing attacks.
The increasing success of BIM (Building Information Model) and the emergence of its implementation in 3D construction models have paved a way for improving scheduling process. The recent research on application of BIM in scheduling has focused on quantity take-off, duration estimation for individual trades, schedule visualization, and clash detection.
Several experiments indicated that the lack of detailed planning causes about 30% non-productive time and stacking of trades. However, detailed planning still has not been implemented in practice despite receiving a lot of interest from researchers. The reason is associated with the huge amount and complexity of input data. In order to create a detailed planning, it is time consuming to manually decompose activities, collect and calculate the detailed information in relevant. Moreover, the coordination of detailed activities requires much effort for dealing with their complex constraints.
This dissertation aims to support the generation of detailed schedules from a rough schedule. It proposes a model for automated detailing of 4D schedules by integrating BIM, simulation and Pareto-based optimization.
Der Entwurfsraum für den Entwurf eines Tragwerks ist ein n-dimensionaler Raum, der aus allen freien Parametern des Modells aufgespannt wird.
Traditionell werden nur wenige Punkte dieses Raumes durch eine numerische (computergestützte) Simulation evaluiert, meist auf Basis der Finite-Elemente-Methode.
Mehrere Faktoren führen dazu, dass heute oft viele Revisionen eines Simulationsmodells durchlaufen werden: Zum einen ergeben sich oft Planungsänderungen, zum anderen ist oft die Untersuchung von Planungsalternativen und die Suche nach einem Optimum wünschenswert.
In dieser Arbeit soll für ein vorhandenes Finite-Elemente-Framework die sequentielle Datei-Eingabeschnittstelle durch eine Netzwerkschnittstelle ersetzt werden, die den Erfordernissen einer interaktiven Arbeitsweise entspricht. So erlaubt die hier konzipierte Schnittstelle interaktive, inkrementelle Modelländerungen sowie Status- und Berechnungsergebnis-Abfragen durch eine bidirektionale Schnittstelle.
Die Kombination aus interaktiver numerischer Simulation und Interoperabilität durch die Anwendung von Konzepten zur Bauwerks-Informations-Modellierung im Tragwerksentwurf ist Ziel dieser Dissertation. Die Beschreibung der Konzeption und prototypischen Umsetzung ist Gegenstand der schriftlichen Arbeit.
A fundamental characteristic of human beings is the desire to start learning at the moment of birth. The rather formal learning process that learners have to deal with in school, on vocational training or in university, is currently subject to fundamental changes. The increasing technologization, overall existing mobile devices, the ubiquitous access to digital information, and students being early adaptors of all these technological innovations require reactions on the part of the educational system.
This study examines such a reaction: The use of mobile learning in higher education.
Examining the subject m-learning first requires an investigation of the educational model e-learning. Many universities already established e-learning as one of their educational segments, providing a wide range of methods to support this kind of teaching.
This study includes an empirical acceptance analysis regarding the general learning behavior of students and their approval of e-learning methods. A survey on the approval of m-learning supplements the results.
Mobile learning is characterized by both the mobility of the communication devices and the users. Both factors lead to new correlations, demonstrate the potential of today's mobile devices and the probability to increase the learning performance.
The dissertation addresses these correlations and the use of mobile devices in the context of m-learning. M-learning and the usage of mobile devices not only require a reflection from a technological point of view. In addition to the technical features of such mobile devices, the usability of their applications plays an important role, especially with regard to the limited display size.
For the purpose of evaluating mobile apps and browser-based applications, various analytical methods are suitable.
The concluding heuristic evaluation points out the vulnerability of an established m-learning application, reveals the need for improvement, and shows an approach to rectify the shortcoming.
Modern digital material approaches for the visualization and simulation of heterogeneous materials allow to investigate the behavior of complex multiphase materials with their physical nonlinear material response at various scales. However, these computational techniques require extensive hardware resources with respect to computing power and main memory to solve numerically large-scale discretized models in 3D. Due to a very high number of degrees of freedom, which may rapidly be increased to the two-digit million range, the limited hardware ressources are to be utilized in a most efficient way to enable an execution of the numerical algorithms in minimal computation time. Hence, in the field of computational mechanics, various methods and algorithms can lead to an optimized runtime behavior of nonlinear simulation models, where several approaches are proposed and investigated in this thesis.
Today, the numerical simulation of damage effects in heterogeneous materials is performed by the adaption of multiscale methods. A consistent modeling in the three-dimensional space with an appropriate discretization resolution on each scale (based on a hierarchical or concurrent multiscale model), however, still contains computational challenges in respect to the convergence behavior, the scale transition or the solver performance of the weak coupled problems. The computational efficiency and the distribution among available hardware resources (often based on a parallel hardware architecture) can significantly be improved. In the past years, high-performance computing (HPC) and graphics processing unit (GPU) based computation techniques were established for the investigationof scientific objectives. Their application results in the modification of existing and the development of new computational methods for the numerical implementation, which enables to take advantage of massively clustered computer hardware resources. In the field of numerical simulation in material science, e.g. within the investigation of damage effects in multiphase composites, the suitability of such models is often restricted by the number of degrees of freedom (d.o.f.s) in the three-dimensional spatial discretization. This proves to be difficult for the type of implementation method used for the nonlinear simulation procedure and, simultaneously has a great influence on memory demand and computational time.
In this thesis, a hybrid discretization technique has been developed for the three-dimensional discretization of a three-phase material, which is respecting the numerical efficiency of nonlinear (damage) simulations of these materials. The increase of the computational efficiency is enabled by the improved scalability of the numerical algorithms. Consequently, substructuring methods for partitioning the hybrid mesh were implemented, tested and adapted to the HPC computing framework using several hundred CPU (central processing units) nodes for building the finite element assembly. A memory-efficient iterative and parallelized equation solver combined with a special preconditioning technique for solving the underlying equation system was modified and adapted to enable combined CPU and GPU based computations.
Hence, it is recommended by the author to apply the substructuring method for hybrid meshes, which respects different material phases and their mechanical behavior and which enables to split the structure in elastic and inelastic parts. However, the consideration of the nonlinear material behavior, specified for the corresponding phase, is limited to the inelastic domains only, and by that causes a decreased computing time for the nonlinear procedure. Due to the high numerical effort for such simulations, an alternative approach for the nonlinear finite element analysis, based on the sequential linear analysis, was implemented in respect to scalable HPC. The incremental-iterative procedure in finite element analysis (FEA) during the nonlinear step was then replaced by a sequence of linear FE analysis when damage in critical regions occured, known in literature as saw-tooth approach. As a result, qualitative (smeared) crack initiation in 3D multiphase specimens has efficiently been simulated.
Interactive scientific visualizations are widely used for the visual exploration and examination of physical data resulting from measurements or simulations. Driven by technical advancements of data acquisition and simulation technologies, especially in the geo-scientific domain, large amounts of highly detailed subsurface data are generated. The oil and gas industry is particularly pushing such developments as hydrocarbon reservoirs are increasingly difficult to discover and exploit. Suitable visualization techniques are vital for the discovery of the reservoirs as well as their development and production. However, the ever-growing scale and complexity of geo-scientific data sets result in an expanding disparity between the size of the data and the capabilities of current computer systems with regard to limited memory and computing resources.
In this thesis we present a unified out-of-core data-virtualization system supporting geo-scientific data sets consisting of multiple large seismic volumes and height-field surfaces, wherein each data set may exceed the size of the graphics memory or possibly even the main memory. Current data sets fall within the range of hundreds of gigabytes up to terabytes in size. Through the mutual utilization of memory and bandwidth resources by multiple data sets, our data-management system is able to share and balance limited system resources among different data sets. We employ multi-resolution methods based on hierarchical octree and quadtree data structures to generate level-of-detail working sets of the data stored in main memory and graphics memory for rendering. The working set generation in our system is based on a common feedback mechanism with inherent support for translucent geometric and volumetric data sets. This feedback mechanism collects information about required levels of detail during the rendering process and is capable of directly resolving data visibility without the application of any costly occlusion culling approaches. A central goal of the proposed out-of-core data management system is an effective virtualization of large data sets. Through an abstraction of the level-of-detail working sets, our system allows developers to work with extremely large data sets independent of their complex internal data representations and physical memory layouts.
Based on this out-of-core data virtualization infrastructure, we present distinct rendering approaches for specific visualization problems of large geo-scientific data sets. We demonstrate the application of our data virtualization system and show how multi-resolution data can be treated exactly the same way as regular data sets during the rendering process. An efficient volume ray casting system is presented for the rendering of multiple arbitrarily overlapping multi-resolution volume data sets. Binary space-partitioning volume decomposition of the bounding boxes of the cube-shaped volumes is used to identify the overlapping and non-overlapping volume regions in order to optimize the rendering process. We further propose a ray casting-based rendering system for the visualization of geological subsurface models consisting of multiple very detailed height fields. The rendering of an entire stack of height-field surfaces is accomplished in a single rendering pass using a two-level acceleration structure, which combines a minimum-maximum quadtree for empty-space skipping and sorted lists of depth intervals to restrict ray intersection searches to relevant height fields and depth ranges. Ultimately, we present a unified rendering system for the visualization of entire geological models consisting of highly detailed stacked horizon surfaces and massive volume data. We demonstrate a single-pass ray casting approach facilitating correct visual interaction between distinct translucent model components, while increasing the rendering efficiency by reducing processing overhead of potentially invisible parts of the model. The combination of image-order rendering approaches and the level-of-detail feedback mechanism used by our out-of-core data-management system inherently accounts for occlusions of different data types without the application of costly culling techniques.
The unified out-of-core data-management and virtualization infrastructure considerably facilitates the implementation of complex visualization systems. We demonstrate its applicability for the visualization of large geo-scientific data sets using output-sensitive rendering techniques. As a result, the magnitude and multitude of data sets that can be interactively visualized is significantly increased compared to existing approaches.
This thesis focuses on the analysis and design of hash functions and authenticated encryption schemes that are blockcipher based. We give an introduction into these fields of research – taking in a blockcipher
based point of view – with special emphasis on the topics of double length, double call blockcipher based compression functions. The first main topic (thesis parts I - III) is on analysis and design of
hash functions. We start with a collision security analysis of some well known double length blockcipher based compression functions and hash functions: Abreast-DM, Tandem-DM and MDC-4. We also propose new double length compression functions that have elevated collision security guarantees. We complement the collision analysis with a preimage analysis by stating (near) optimal security results for Abreast-DM, Tandem-DM, and Hirose-DM. Also, some generalizations are discussed. These are the first preimage security results for blockcipher based double length hash functions that go beyond the birthday barrier.
We then raise the abstraction level and analyze the notion of ’hash function indifferentiability from a random oracle’. So we not anymore focus on how to obtain a good compression function but, instead, on how to obtain a good hash function using (other) cryptographic primitives. In particular we give some examples when this strong notion of hash function security might give questionable advice for building a practical hash function. In the second main topic (thesis part IV), which is on authenticated encryption schemes, we present an on-line authenticated encryption scheme, McOEx, that simultaneously achieves privacy and confidentiality and is secure against nonce-misuse. It is the first dedicated scheme that achieves high standards of security and – at the same time – is on-line computable.
Web applications that are based on user-generated content are often criticized for containing low-quality information; a popular example is the online encyclopedia Wikipedia. The major points of criticism pertain to the accuracy, neutrality, and reliability of information. The identification of low-quality information is an important task since for a huge number of people around the world it has become a habit to first visit Wikipedia in case of an information need. Existing research on quality assessment in Wikipedia either investigates only small samples of articles, or else deals with the classification of content into high-quality or low-quality. This thesis goes further, it targets the investigation of quality flaws, thus providing specific indications of the respects in which low-quality content needs improvement. The original contributions of this thesis, which relate to the fields of user-generated content analysis, data mining, and machine learning, can be summarized as follows:
(1) We propose the investigation of quality flaws in Wikipedia based on user-defined cleanup tags. Cleanup tags are commonly used in the Wikipedia community to tag content that has some shortcomings. Our approach is based on the hypothesis that each cleanup tag defines a particular quality flaw.
(2) We provide the first comprehensive breakdown of Wikipedia's quality flaw structure. We present a flaw organization schema, and we conduct an extensive exploratory data analysis which reveals (a) the flaws that actually exist, (b) the distribution of flaws in Wikipedia, and, (c) the extent of flawed content.
(3) We present the first breakdown of Wikipedia's quality flaw evolution. We consider the entire history of the English Wikipedia from 2001 to 2012, which comprises more than 508 million page revisions, summing up to 7.9 TB. Our analysis reveals (a) how the incidence and the extent of flaws have evolved, and, (b) how the handling and the perception of flaws have changed over time.
(4) We are the first who operationalize an algorithmic prediction of quality flaws in Wikipedia. We cast quality flaw prediction as a one-class classification problem, develop a tailored quality flaw model, and employ a dedicated one-class machine learning approach. A comprehensive evaluation based on human-labeled Wikipedia articles underlines the practical applicability of our approach.
The automotive industry requires realistic virtual reality applications more than other domains to increase the efficiency of product development. Currently, the visual quality of virtual invironments resembles reality, but interaction within these environments is usually far from what is known in everyday life. Several realistic research approaches exist, however they are still not all-encompassing enough to be usable in industrial processes. This thesis realizes lifelike direct multi-hand and multi-finger interaction with arbitrary objects, and proposes algorithmic and technical improvements that also approach lifelike usability. In addition, the thesis proposes methods to measure the effectiveness and usability of such interaction techniques as well as discusses different types of grasping feedback that support the user during interaction. Realistic and reliable interaction is reached through the combination of robust grasping heuristics and plausible pseudophysical object reactions. The easy-to-compute grasping rules use the objects’ surface normals, and mimic human grasping behavior. The novel concept of Normal Proxies increases grasping stability and diminishes challenges induced by adverse normals. The intricate act of picking-up thin and tiny objects remains challenging for some users. These cases are further supported by the consideration of finger pinches, which are measured with a specialized finger tracking device. With regard to typical object constraints, realistic object motion is geometrically calculated as a plausible reaction on user input. The resulting direct finger-based
interaction technique enables realistic and intuitive manipulation of arbitrary objects. The thesis proposes two methods that prove and compare effectiveness and usability. An expert review indicates that experienced users quickly familiarize themselves with the technique. A quantitative and qualitative user study shows that direct finger-based interaction is preferred over indirect interaction in the context of functional car assessments. While controller-based interaction is more robust, the direct finger-based interaction provides greater realism, and becomes nearly as reliable when the pinch-sensitive mechanism is used. At present, the haptic channel is not used in industrial virtual reality applications. That is why it can be used for grasping feedback which improves the users’ understanding of the grasping situation. This thesis realizes a novel pressure-based tactile feedback at the fingertips. As an alternative, vibro-tactile feedback at the same location is realized as well as visual feedback by the coloring of grasp-involved finger segments. The feedback approaches are also compared within the user study, which reveals that grasping feedback is a requirement to judge grasp status and that tactile feedback improves interaction independent of the used display system. The considerably stronger vibrational tactile feedback can quickly become annoying during interaction. The interaction improvements and hardware enhancements make it possible to interact with virtual objects in a realistic and reliable manner. By addressing realism and reliability, this thesis paves the way for the virtual evaluation of human-object interaction, which is necessary for a broader application of virtual environments in the automotive industry and other domains.
Der inhaltlichen Qualitätssicherung von Bauwerksinformationsmodellen (BIM) kommt im Zuge einer stetig wachsenden Nutzung der verwendeten BIM für unterschiedliche Anwen-dungsfälle eine große Bedeutung zu. Diese ist für jede am Datenaustausch beteiligte Software dem Projektziel entsprechend durchzuführen. Mit den Industry Foundation Classes (IFC) steht ein etabliertes Format für die Beschreibung und den Austausch eines solchen Modells zur Verfügung. Für den Prozess der Qualitätssicherung wird eine serverbasierte Testumgebung Bestandteil des neuen Zertifizierungsverfahrens der IFC sein. Zu diesem Zweck wurde durch das „iabi - Institut für angewandte Bauinformatik” in Zusammenarbeit mit „buildingSMART e.V.“ (http://www.buildingsmart.de) ein Global Testing Documentation Server (GTDS) implementiert. Der GTDS ist eine, auf einer Datenbank basierte, Web-Applikation, die folgende Intentionen verfolgt:
• Bereitstellung eines Werkzeugs für das qualitative Testen IFC-basierter Modelle
• Unterstützung der Kommunikation zwischen IFC Entwicklern und Anwendern
• Dokumentation der Qualität von IFC-basierten Softwareanwendungen
• Bereitstellung einer Plattform für die Zertifizierung von IFC Anwendungen
Gegenstand der Arbeit ist die Planung und exemplarische Umsetzung eines Werkzeugs zur interaktiven Visualisierung von Qualitätsdefiziten, die vom GTDS im Modell erkannt wurden. Die exemplarische Umsetzung soll dabei aufbauend auf den OPEN IFC TOOLS (http://www.openifctools.org) erfolgen.
Radiodiskussion bei bauhaus.fm am 5. November 2012.
Harald S. Liehr ist Lektor und Leiter der Niederlassung Weimar des Böhlau-Verlags (Wien / Köln / Weimar), Dr. Frank Simon-Ritz ist Direktor der Universitätsbibliothek der Bauhaus-Universität Weimar.
Die Fragen stellten René Tauschke und Jean-Marie Schaldach.
Bauphysikalisches Quartett
(2012)
Quartett ist ein ebenso altes, wie auch beliebtes Kartenspiel. Vor allem bei Kindern erfreut es sich großer Beliebtheit, während in den älteren Generationen kaum jemand mit Quartettkarten spielt.
Quartettspiele speziell für Kleinkinder sind zum Großteil mit Inhalten versehen, die Wissen auf spielerische Art und Weise vermitteln. Dabei werden gute Lernerfolge in dieser Zielgruppe verzeichnet.
Wie lassen sich also diese Lernerfolge durch das Spielen mit Quartettkarten erzielen? Und wie kann dieser Effekt auch auf Studenten übertragen werden?
Ziel dieser Arbeit ist es, das Konzept des Quartettkartenspiels auf bauphysikalische Inhalte anzuwenden und gegebenenfalls die Spielprinzipien zu erweitern oder zu verändern. Dabei sind die Studenten der Fakultät Bauingenieurswesen die Zielgruppe, an die sich das Spiel richten soll.
Besondere Herausforderung ist es, unterschiedliche Objekteklassen von bauphysikalischer Relevanz in einem Spiel zusammenzubringen und vergleichbar zu machen. Das sich ergebende Quartettkartenspiel sollte nicht nur eine Objektklasse, sondern mehrere Objektklassen zum Inhalt haben. Dabei sollen die Objektklassen so gewählt werden, dass sich Kategorien mit bauphysikalischem Inhalt finden lassen.
Augenmerk sollte auch auf die Strukturierung der Lerninhalte gelegt werden, um eine leichte Übertragung des Spielkonzepts auf andere Fachdomänen zu ermöglichen. Das Ergebnis der Arbeit sind zwei fertige und spielbare Quartette.
In crowdsourcingbasierten Systemen kommt der Qualitätssicherung des durch Benutzer generierten Inhaltes große Bedeutung für die Erhaltung der Benutzbarkeit zu. Das bauphysikalische Lehrspiel "BuildVille" benutzt für die Quiz-Anwendung einen Crowdsourcing-Ansatz: Die Quiz-Fragen werden von den Benutzern selbst generiert. Mit Hilfe dieser Arbeit soll sichergestellt werden, dass fehlerhafte, irrtümlicherweise oder zum Spaß eingegebene Fragen möglichst früh erkannt, korrigiert oder von der weiteren Verbreitung ausgeschlossen werden. Dazu soll mit Hilfe einer Analyse bestehender crowdsourcingbasierter Systeme bezüglich umgesetzter Qualitätssicherungsmaßnahmen ein Konzept für die QS-Maßnahmen in BuildVille entwickelt werden.
Es ist ein Bild aus alten Tagen: ein wissbegieriger Student, auf der Suche nach fundierter wissenschaftlicher Information, begibt sich an den heiligsten Ort aller Bücher – die Universitätsbibliothek. Doch seit einiger Zeit tummeln sich Studierende nicht mehr nur in Bibliotheken, sondern auch immer häufiger im Internet. Sie suchen und finden dort digitale Bücher, sogenannte E-Books.
Wie lässt sich der Wandel durch den Einzug des E-Books in das etablierte Forschungssystem beschreiben, welche Konsequenzen lassen sich daraus ablesen und wird schließlich alles digital, sogar die Bibliothek? Diesen Fragen geht ein elfköpfiges Expertenteam aus Deutschland und der Schweiz während der zweitägigen Konferenz auf den Grund.
Bei den Weimarer E-DOC-Tagen geht es nun um die Veränderung des institutionellen Gefüges rund um das digitale Buch. Denn traditionell sind Verlage und Bibliotheken wichtige Bestandteile der Wissensversorgung in Studium und Lehre. Doch mit dem Aufkommen des E-Books verlagert sich die Recherche mehr und mehr ins Internet. Die Suchmaschine Google tritt als neuer Konkurrent der klassischen Bibliotheksrecherche auf. Aber auch Verlage müssen verstärkt auf die neuen Herausforderungen eines digitalen Buchmarktes reagieren.
In Kooperation mit der Universitätsbibliothek und dem Master-Studiengang Medienmanagement diskutieren Studierende, Wissenschaftler, Bibliothekare und Verleger, wie das E-Book unseren Umgang mit Literatur verändert. Der Tagungsband stellt alle Perspektiven und Ergebnisse zum Nachlesen zusammen.
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.
Entwurf eines Spieler-Modells für eine erweiterbare Spielplattform zur Ausbildung in der Bauphysik
(2012)
Im Projekt Intelligentes Lernen beschäftigen sich die Professuren Content Management und Web-Technologien, Systeme der Virtuellen Realität und Bauphysik der Bauhaus- Universität Weimar mit der Entwicklung innovativer Informationstechnologien für eLearning- Umgebungen. In den Teilbereichen Retrieval, Extraktion und Visualisierung großer Dokumentkollektionen, sowie simulations- und planbasierter Wissensvermittlung werden Algorithmen und Werkzeuge erforscht, um eLearning-Systeme leistungsfähiger zu machen und um somit den Lernerfolg zu optimieren.
Ziel des Projekts, auf dem Gebiet des simulationsbasierten Wissenstransfers, ist die Entwicklung eines Multiplayer Online Games (MOG) zur Ausbildungsunterstützung in der Bauphysik.
Im Rahmen der vorliegenden Bachelorarbeit wird für diese digitale Lernsoftware ein Spieler- Modell zur Verwaltung der spielerspezifischen Daten entworfen und in das bestehende Framework integriert. Der Schwerpunkt der Arbeit liegt in der Organisation der erlernten Fähigkeiten des Spielers und in der an den Wissensstand angepassten Auswahl geeigneter Spielaufgaben. Für die Anwendung im eLearning-Bereich ist die Erweiterbarkeit des Modells um neue Lernkomplexe eine wesentliche Anforderung.