The role of the body in the experience of installation art: a case study of visitors' bodily, emotional, and transformative experiences in Tomás Saraceno's “in orbit”

Installation art, with its immersive and participatory character, has been argued to require the use and awareness of the body, which potentially constitute key parts of the artwork's experience and appreciation. Heightened body awareness is even argued to be a key to particularly profound emotional or even transformative states, which have been frequently ascribed to this genre. However, the body in the experience of installation art has rarely been empirically considered. To address this gap, we investigated the body's role in the experience of Tomás Saraceno's in orbit installation. Based on a list of self-report items created from a review of the theoretical literature, we—for the first time—captured (quantitatively and qualitatively): what kind of subjective bodily experiences visitors (N = 230) reported, how these items grouped into clusters (using network science), and how these relate to emotion, art appraisal, and transformative outcomes. Network analysis of the items determined four communities related to “interoception,” “presence,” “disturbance,” and “proprioception.” Proprioception (e.g., awareness of balance/movement/weight) turned out to be a significant determinant of art appreciation in our study, and, together with “disturbing” body experiences (feeling awkward/watched/chills), coincided with transformation. We also assessed individual differences in body awareness yet did not find that these moderate those relationships. We suggest future research on installation art based on a more unified assessment of the role of the body in embodied-enactive aesthetics and its relation to the intensity and impact of art experience in general.Peer Reviewe

Dynamic modelling and control for assessment of large-scale wind and solar integration in power systems

The integration of variable and unpredictable renewable energy sources into the current power networks introduces considerable changes in system operations. This poses enormous threats to the stability of the power system. Hence, it is essential to analyse the necessary adjustments in operation strategies in preparation for increased amounts of variable generation in existing power systems. The present study describes the dynamic modelling and integration of solar photovoltaic and wind power generation systems into a transient stability analysis toolbox. In view of the inherent connection of renewable energy generators to the electrical network through converter systems, the main contribution in the present study is the development of high‐level control functions to model converter interfaces with reference to standard grid operation codes. The dynamic models and corresponding control functions are tested using a network representing the transmission grid of the Baden‐Württemberg state in Germany as part of the assessment process to analyse the capability of the control functions for grid stability support. The simulation results show that the proposed converter control functions can equip renewable energy generators with equivalent features from a functional point of view to those of synchronous generators

A New Framework for the Analysis of Large Scale Multi-Rate Power Data

A new framework for the analysis of large scale, multi-rate power data is introduced. The system comprises high rate power grid data acquisition devices, software modules for big data management and large scale time series analysis. The power grid modeling and simulation modules enable to run power flow simulations. Visualization methods support data exploration for captured, simulated and analyzed energy data. A remote software control module for the proposed tools is provided

Reliability of 3D laser-based anthropometry and comparison with classical anthropometry

Anthropometric quantities are widely used in epidemiologic research as possible confounders, risk factors, or outcomes. 3D laser-based body scans (BS) allow evaluation of dozens of quantities in short time with minimal physical contact between observers and probands. The aim of this study was to compare BS with classical manual anthropometric (CA) assessments with respect to feasibility, reliability, and validity. We performed a study on 108 individuals with multiple measurements of BS and CA to estimate intra- and inter-rater reliabilities for both. We suggested BS equivalents of CA measurements and determined validity of BS considering CA the gold standard. Throughout the study, the overall concordance correlation coefficient (OCCC) was chosen as indicator of agreement. BS was slightly more time consuming but better accepted than CA. For CA, OCCCs for intra- and inter-rater reliability were greater than 0.8 for all nine quantities studied. For BS, 9 of 154 quantities showed reliabilities below 0.7. BS proxies for CA measurements showed good agreement (minimum OCCC > 0.77) after offset correction. Thigh length showed higher reliability in BS while upper arm length showed higher reliability in CA. Except for these issues, reliabilities of CA measurements and their BS equivalents were comparable

Impact of grid partitioning algorithms on combined distributed AC optimal power flow and parallel dynamic power grid simulationn

The complexity of most power grid simulation algorithms scales with the network size, which corresponds to the number of buses and branches in the grid. Parallel and distributed computing is one approach that can be used to achieve improved scalability. However, the efficiency of these algorithms requires an optimal grid partitioning strategy. To obtain the requisite power grid partitionings, the authors first apply several graph theory based partitioning algorithms, such as the Karlsruhe fast flow partitioner (KaFFPa), spectral clustering, and METIS. The goal of this study is an examination and evaluation of the impact of grid partitioning on power system problems. To this end, the computational performance of AC optimal power flow (OPF) and dynamic power grid simulation are tested. The partitioned OPF-problem is solved using the augmented Lagrangian based alternating direction inexact Newton method, whose solution is the basis for the initialisation step in the partitioned dynamic simulation problem. The computational performance of the partitioned systems in the implemented parallel and distributed algorithms is tested using various IEEE standard benchmark test networks. KaFFPa not only outperforms other partitioning algorithms for the AC OPF problem, but also for dynamic power grid simulation with respect to computational speed and scalability

Data-Driven Copy-Paste Imputation for Energy Time Series

A cornerstone of the worldwide transition to smart grids are smart meters. Smart meters typically collect and provide energy time series that are vital for various applications, such as grid simulations, fault-detection, load forecasting, load analysis, and load management. Unfortunately, these time series are often characterized by missing values that must be handled before the data can be used. A common approach to handle missing values in time series is imputation. However, existing imputation methods are designed for power time series and do not take into account the total energy of gaps, resulting in jumps or constant shifts when imputing energy time series. In order to overcome these issues, the present paper introduces the new Copy-Paste Imputation (CPI) method for energy time series. The CPI method copies data blocks with similar characteristics and pastes them into gaps of the time series while preserving the total energy of each gap. The new method is evaluated on a real-world dataset that contains six shares of artificially inserted missing values between 1 and 30%. It outperforms the three benchmark imputation methods selected for comparison. The comparison furthermore shows that the CPI method uses matching patterns and preserves the total energy of each gap while requiring only a moderate run-time