The Place of Studio

Placing the studio within most curricula of architecture is not a particularly difficult locational task for most professionals, educators, or students. It stands in a central position. This position is held by the studio whether it is seen as the point toward which other information and activities flow (similar to the undergraduate natural science laboratory), or the point from which other activities and courses extend out (as in the American Beaux-Arts), or finally a combination of both, an ebb and flow, to and from. Ed.note: An article about studio pedagogy by a University of Nebraska faculty member who uses his students’ projects as examples

How Useful is Learning in Mitigating Mismatch Between Digital Twins and Physical Systems?

In the control of complex systems, we observe two diametrical trends: model-based control derived from digital twins, and model-free control through AI. There are also attempts to bridge the gap between the two by incorporating learning-based AI algorithms into digital twins to mitigate mismatches between the digital twin model and the physical system. One of the most straightforward approaches to this is direct input adaptation. In this paper, we ask whether it is useful to employ a generic learning algorithm in such a setting, and our conclusion is "not very". We denote an algorithm to be more useful than another algorithm based on three aspects: 1) it requires fewer data samples to reach a desired minimal performance, 2) it achieves better performance for a reasonable number of data samples, and 3) it accumulates less regret. In our evaluation, we randomly sample problems from an industrially relevant geometry assurance context and measure the aforementioned performance indicators of 16 different algorithms. Our conclusion is that blackbox optimization algorithms, designed to leverage specific properties of the problem, generally perform better than generic learning algorithms, once again finding that "there is no free lunch"

How Useful is Learning in Mitigating Mismatch Between Digital Twins and Physical Systems?

In the control of complex systems, we observe two diametrical trends: model-based control derived from digital twins, and model-free control through AI. There are also attempts to bridge the gap between the two by incorporating learning-based AI algorithms into digital twins to mitigate mismatches between the digital twin model and the physical system. One of the most straightforward approaches to this is direct input adaptation. In this paper, we ask whether it is useful to employ a generic learning algorithm in such a setting, and our conclusion is "not very". We denote an algorithm to be more useful than another algorithm based on three aspects: 1) it requires fewer data samples to reach a desired minimal performance, 2) it achieves better performance for a reasonable number of data samples, and 3) it accumulates less regret. In our evaluation, we randomly sample problems from an industrially relevant geometry assurance context and measure the aforementioned performance indicators of 16 different algorithms. Our conclusion is that blackbox optimization algorithms, designed to leverage specific properties of the problem, generally perform better than generic learning algorithms, once again finding that "there is no free lunch"

Corporate Trainers’ Intent to Adjust Training Programs for Fostering Employee Self-Efficacy

To stay current on technology trends, trainers are tasked with providing cost-effective training to meet the needs of the organization. It is not known if to develop employee self-efficacy, organizational trainers should consider making changes to their programs in accordance with (a) generational needs of employees, (b) methodology of training, and (c) position levels of employees in an organization. The purpose of this quantitative cross-sectional correlational study was to determine whether there is a correlation between organizational training professionals’ intent to make changes to training programs and if self-efficacy development is considered in generationally different individuals at different position levels within an organization. A pre-tested validated survey questionnaire was used to collect data from 146 corporate trainers based on non-probability purposive sampling. Regression analysis results R = .373; R2 = .139; adjusted R = .017, and, p = .322 would indicate low predictors of answers for the participants. Pearson correlational coefficients .204, to moderate .522, indicated organizational trainers are not consistently making changes to programs based on independent variables: methodology of training and the position levels of employees. The more predictive .405 to a high .604 results of organizational training professionals’ intent to make changes to meet the generational needs of employees, could be explained through more in-depth literature and analysis of the topic by participants. The results of organizational training professionals’ intent to make changes would support more productive training programs, which create higher levels of self-efficacy development in employees while reducing the cost of organizational training in the long-term that may lead to positive social change

Brexit – Auswirkungen auf den deutschen und europäischen Luftverkehr

Die Auswirkungen eines Brexit auf den Luftverkehr in Deutschland und Europa wären deutlich spürbar. Etwa ein Viertel der innereuropäischen Verbindungen ist potenziell vom Brexit betroffen. Bis zu 14% gelten aufgrund der Rechtslage als besonders gefährdet. Diese Verbindungen werden vor allem von Ryanair und easyJet angeboten. Sollten beide Billigflieger umstrukturieren, könnte sich die Angebotsstruktur im EU-Luftverkehr deutlich verändern. Auf der Nachfrageseite ist durch eine sinkende Wirtschaftsleistung für den deutschen Luftverkehr eine Dämpfung des Wachstums um 0,1 Prozentpunkte zu erwarten

Can Cue Location Influence Postural Sway Control in a Post-Concussion Syndrome Case?

Center for Disease Control reports the following as fall risk factors: lower extremity weakness, vision problems, and difficulty maintaining balance during walking. Greatest predictor for a fall, is prior fall within the last year. Injury from a fall leads to: fear of falls, inactivity, atrophy, higher risk for falls. Kouzake and Masani (2008) indicated that improvements in postural sway are attributed to light touch increasing proprioception, rather than through mechanical support. Examples of light touch-enhanced proprioceptive feedback: walls and assistive walking devices. Successful strategy in bimanual tasks

Reinforcement learning in real-time geometry assurance

To improve the assembly quality during production, expert systems are often used. These experts typically use a system model as a basis for identifying improvements. However, since a model uses approximate dynamics or imperfect parameters, the expert advice is bound to be biased. This paper presents a reinforcement learning agent that can identify and limit systematic errors of an expert systems used for geometry assurance. By observing the resulting assembly quality over time, and understanding how different decisions affect the quality, the agent learns when and how to override the biased advice from the expert software

Online geometry assurance in individualized production by feedback control and model calibration of digital twins

In this paper, we consider online calibration of a Digital Twin and its use for control and optimization in the assembly process of sheet metal parts. This calibration is done based on a feedback signal received by calculating the quality of the simulated assemblies as compared to the prediction made by the Digital Twin. We develop a Kalman filter-based approach for online calibration of the Digital Twin, which in turn is used by a one-step look-ahead optimizer to define an online control scheme. This control scheme balances directly predicted quality gains against reduced uncertainty whose purpose is to enable long-term quality gains. The usage of a calibrated model in a one-step look-ahead optimizer as a controller allows to incorporate the benefits of the usage of Digital Twins for individualized control, where the control parameters of a production cell are optimized in a Digital Twin based on measured properties of the production inputs, over nominal control, where control parameters are set with respect to some reference production inputs, in an approach which is able to use measured final production quality for feedback control. The proposed approach is evaluated by computer simulations of two industrial product assembly use cases. In the first case, it demonstrates significant gains in quality of the produced assemblies, while in the second case it shows negligible to small improvements. The second case is, however, rather insensitive to miscalibration, which enables only small gains

Energy efficiency of wastewater treatment plants. Overview of the literature and critical discussion of energy data

3rd IWA Specialized International Conference Ecotechnologies for Wastewater Treatment 2016 (ecoSTP16). Cambridge, UK, 27-30 jun 2016In response to strong growth in energy intensive wastewater treatment, public agencies and industry began to explore and implement measures to ensure achievement of the target indicated in the 2020 Climate and Energy Package. However, in the absence of fundamental and globally recognized approach evaluating wastewater treatment plants (WWTPs) energy performance, these policies could be economically wasteful. This paper gives an overview of the literature of WWTPs energy-use performance. Energy key performance indicators (KPIs) found are presented and critically assessed, pointing out the limits to their validity. Data from more than 430 WWTPs, together with the methods for synthesizing the information is presented. The assessment of a large data sample provided some evidence about the effect of the plant size, dilution factor and flowrate. The technology choice, plant layout and country of location were seen as important elements that contributed to the large variability observe

Monitoring and diagnosis of energy consumption in wastewater treatment plants. A state of the art and proposals for improvement

In response to strong growth in energy intensive wastewater treatment, public agencies and industry began to explore and implement measures to ensure achievement of the targets indicated in the 2020 Climate and Energy Package. However, in the absence of fundamental and globally recognized approach evaluating wastewater treatment plant (WWTP) energy performance, these policies could be economically wasteful. This paper gives an overview of the literature of WWTP energy-use performance and of the state of the art methods for energy benchmarking. The literature review revealed three main benchmarking approaches: normalization, statistical techniques and programming techniques, and advantages and disadvantages were identified for each one. While these methods can be used for comparison, the diagnosis of the energy performance remains an unsolved issue. Besides, a large dataset of WWTP energy consumption data, together with the methods for synthesizing the information, are presented and discussed. It was found that no single key performance indicators (KPIs) used to characterize the energy performance could be used universally. The assessment of a large data sample provided some evidence about the effect of the plant size, dilution factor and flowrate. The technology choice, plant layout and country of location were seen as important elements that contributed to the large variability observed