• International Journal of Automotive Technology
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• v.3 no.2
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• pp.63-70
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• 2002

Future on-board vehicle control systems can be further improved through new types of mechatronic systems. In particular, these systems' capacities for interaction enhance safety, comfort and economic viability. The Automotive Engineering Department (fzd) of darmstadt University of Technology is engaged in research of the mechatronic vehicle corner, which consists of three subsystems: sensor tire, electrically actuated wheel brake and smart suspension. By intercommunication of these three systems, the brake controller receives direct, fast and permanent information about dynamic events in the tire contact area provided by the tire sensor as valuable control input. This allows to control operation conditions of each wheel brake. The information provided by the tire sensor for example help to distinguish between staightline driving and cornering as well as to determine $\mu$-split conditions. In conjunction with current information of dynamic wheel loads, tire pressures and friction tyre/road, the ideal brake force distribution can be achieved. Alike through integration of adaptive suspension bushings, elastokinematic behaviour and wheel positions can be adapted to manoeuver-oriented requirements.

• Advances in aircraft and spacecraft science
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• v.3 no.2
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• pp.149-170
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• 2016

Multi-Disciplinary Optimization (MDO) is widely used to handle the advanced design in several engineering applications. Such applications are commonly simulation-based, in order to capture the physics of the phenomena under study. This framework demands fast optimization algorithms as well as trustworthy numerical analyses, and a synergic integration between the two is required to obtain an efficient design process. In order to meet these needs, an adaptive Computational Fluid Dynamics (CFD) solver and a fast optimization algorithm have been developed and combined by the authors. The CFD solver is based on a high-order discontinuous Galerkin discretization while the optimization algorithm is a high-performance version of the Artificial Bee Colony method. In this work, they are used to address a typical aero-mechanical problem encountered in turbomachinery design. Interesting achievements in the considered test case are illustrated, highlighting the potential applicability of the proposed approach to other engineering problems.

• ETRI Journal
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• v.37 no.4
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• pp.752-765
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• 2015

We propose a novel post-processing algorithm and its very-large-scale integration architecture that simultaneously uses the passive and active stereo vision information to improve the reliability of the three-dimensional disparity in a hybrid stereo vision system. The proposed architecture consists of four steps - left-right consistency checking, semi-2D hole filling, a tiny adaptive variance checking, and a 2D weighted median filter. The experimental results show that the error rate of the proposed algorithm (5.77%) is less than that of a raw disparity (10.12%) for a real-world camera image having a $1,280{\times}720$ resolution and maximum disparity of 256. Moreover, for the famous Middlebury stereo image sets, the proposed algorithm's error rate (8.30%) is also less than that of the raw disparity (13.7%). The proposed architecture is implemented on a single commercial field-programmable gate array using only 13.01% of slice resources, which achieves a rate of 60 fps for $1,280{\times}720$ stereo images with a disparity range of 256.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.621-652
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• 2012

Software Estimations provide an inclusive set of directives for software project developers, project managers, and the management in order to produce more realistic estimates based on deficient, uncertain, and noisy data. A range of estimation models are being explored in the industry, as well as in academia, for research purposes but choosing the best model is quite intricate. Estimation by Analogy (EbA) is a form of case based reasoning, which uses fuzzy logic, grey system theory or machine-learning techniques, etc. for optimization. This research compares the estimation accuracy of some conventional data mining models with a hybrid model. Different data mining models are under consideration, including linear regression models like the ordinary least square and ridge regression, and nonlinear models like neural networks, support vector machines, and multivariate adaptive regression splines, etc. A precise and comprehensible predictive model based on the integration of GRA and regression has been introduced and compared. Empirical results have shown that regression when used with GRA gives outstanding results; indicating that the methodology has great potential and can be used as a candidate approach for software effort estimation.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.394-399
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• 2002

In this paper, Multisource data classification methods based on Bayesian formula are considered. For this decision fusion scheme, the individual data sources are handled separately by statistical classification algorithms and then Bayesian fusion method is applied to integrate from the available data sources. This method includes the combination of each expert decisions where the weights of the individual experts represent the reliability of the sources. The reliability measure used in the statistical approach is common to all pixels in previous work. In this experiment, the weight factors have been assigned to have different value for all pixels in order to improve the integrated classification accuracies. Although most implementations of Bayesian classification approaches assume fixed a priori probabilities, we have used adaptive a priori probabilities by iteratively calculating the local a priori probabilities so as to maximize the posteriori probabilities. The effectiveness of the proposed method is at first demonstrated on simulations with artificial and evaluated in terms of real-world data sets. As a result, we have shown that Bayesian statistical fusion scheme performs well on multispectral data classification.

• International Journal of High-Rise Buildings
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• v.8 no.2
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• pp.95-100
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• 2019

Whilst most research focuses on the reduction of operative energy use in buildings, the aspect of which (and how many) materials are used is often neglected and poorly explored. However, considering the continuous growth of the global population and the limited availability of resources, it is clear that focusing on operative energy alone is too short-sighted. The tasks lying ahead for architects and engineers cannot be accomplished with conventional methods of construction. With a share of 50-60% of global resource consumption, the building industry has a decisive impact on our environment. If business as usual continues, resources will be significantly depleted in a matter of decades. Therefore, researchers of the University of Stuttgart are investigating the concept of adaptivity as a promising method for saving resources in the built environment. The term adaptivity in the context of building structures was first introduced by Werner Sobek. It describes a method where sensors, actuators and control units are implemented in systems or facades in order to oppose physical impacts in an ideal way. The applicability of this method will be verified on an experimental high-rise building at the University campus in Stuttgart. Thus, this paper describes this innovative research project and depicts the concept of adaptivity in high-rise structures. Furthermore, it gives an overview of potential actuation concepts and the interdisciplinary challenges behind them.

• Advances in aircraft and spacecraft science
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• v.9 no.2
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• pp.95-102
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• 2022

The paper investigates the process of pulsation of a spherical cavity (bubble) in a liquid under the influence of a source of ultrasonic vibrations. The process of pulsation of a cavitation pocket in liquid is investigated. The Kirkwood-Bethe model was used to describe the motion. A numerical solution algorithm based on the Runge-Kutta-Felberg method of 4-5th order with adaptive selection of the integration step has been developed and implemented. It was revealed that if the initial bubble radius exceeds a certain value, then the bubble will perform several pulsations until the moment of collapse. The same applies to the case of exceeding the amplitude of ultrasonic vibrations of a certain value. The proposed algorithm makes it possible to fully describe the process of cavitation pulsations, to carry out comprehensive parametric studies and to evaluate the influence of various process parameters on the intensity of cavitation.

• The Journal of Industrial Distribution & Business
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• v.14 no.8
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• pp.9-17
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• 2023

Purpose: This study is to examine how modern art museums might develop into resilient, proactive, and adaptive enterprises. That implies that this study seeks to spur meaningful change by analyzing and comprehending the numerous facets of this issue, paving the path for a long-term future for contemporary art institutions worldwide. Research design, data and methodology: To achieve the purpose of this study, the current author has reviewed numerous relevant prior studies systemically. The technique used in this study was meticulously designed to guarantee accurate data collection and analysis, providing a thorough comprehension of the subject. An organized strategy was used, including finding, reviewing, and synthesizing earlier studies. Results: Based on the investigation of the current literature analysis, this study figured out four workable business models that might increase the prosperity of modern art museums. They result from a thorough examination of previous studies and these initiatives center on improving digital presence, enhancing community participation, diversifying revenue streams, and forming powerful alliances and partnerships. Conclusions: In sum, this study concludes that the use and integration of digital technology enable museums to reach a larger audience and open up opportunities for developing cutting-edge, interactive exhibitions that reflect modern patterns of participation and communication.

• Journal of Information Technology Applications and Management
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• v.31 no.3
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• pp.149-163
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• 2024

As conversational AI systems such as ChatGPT have become more advanced, researchers are exploring ways to use them in education. However, we need effective ways to evaluate these systems before allowing them to help teach students. This study proposes a detailed framework for testing conversational AI across three important criteria as follow. First, specialized benchmarks that measure skills include giving clear explanations, adapting to context during long dialogues, and maintaining a consistent teaching personality. Second, adaptive standards check whether the systems meet the ethical requirements of privacy, fairness, and transparency. These standards are regularly updated to match societal expectations. Lastly, evaluations were conducted from three perspectives: technical accuracy on test datasets, performance during simulations with groups of virtual students, and feedback from real students and teachers using the system. This framework provides a robust methodology for identifying strengths and weaknesses of conversational AI before its deployment in schools. It emphasizes assessments tailored to the critical qualities of dialogic intelligence, user-centric metrics capturing real-world impact, and ethical alignment through participatory design. Responsible innovation by AI assistants requires evidence that they can enhance accessible, engaging, and personalized education without disrupting teaching effectiveness or student agency.

• Journal of Environmental Policy
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• v.12 no.3
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• pp.21-47
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• 2013

The aim is to analysis landslide vulnerability in Inje, Korea, using GCI(Geospatial Correlative Integration) and probability rainfalls based on geographic information system (GIS). In order to achieve this goal, identified indicators influencing landslides based on literature review. We include indicators of exposure to climate(rainfall probability), sensitivity(slope, aspect, curvature, geology, topography, soil drainage, soil material, soil thickness and soil texture) and adaptive capacity(timber diameter, timber type, timber density and timber age). All data were collected, processed, and compiled in a spatial database using GIS. Karisan-ri that had experienced 470 landslides by Typhoon Ewinia in 2006 was selected for analysis and verification. The 50% of landslide data were randomly selected to use as training data, while the other 50% being used for verification. The probability of landslides for target years (1 year, 3 years, 10 years, 50 years, and 100 years) was calculated assuming that landslides are triggered by 3-day cumulative rainfalls of 449 mm. Results show that number of slope has comparatively strong influence on landslide damage. And inclination of $25{\sim}30^{\circ}C$, the highest correlation landslide. Improved previous landslide vulnerability methodology by adopting GCI. Also, vulnerability map provides meaningful information for decision makers regarding priority areas for implementing landslide mitigation policies.