Presents corrections to the paper, Corrections to “Statistical Insights Into Machine Learning-Based Box Models for Pregnancy Care and Maternal Mortality Reduction: A Literature Survey”.
Presents corrections to the paper, Corrections to “Statistical Insights Into Machine Learning-Based Box Models for Pregnancy Care and Maternal Mortality Reduction: A Literature Survey”.
Machine learning algorithms are applied for measuring the performance of robot-assisted cerebral palsy rehabilitation training system. Such approach allows an analysis and predictions about the system reaction to be d...
Machine learning algorithms are applied for measuring the performance of robot-assisted cerebral palsy rehabilitation training system. Such approach allows an analysis and predictions about the system reaction to be done with high accuracy. The rehabilitation training actions of children with cerebral palsy are focused on imagination and conscious control of the face, such as left or right exercises. The aim of the designed interface interaction module is to motivate and to improve the training enthusiasm of the children with cerebral palsy to continue with the rehabilitation therapy avoiding the thoughts about the pain, tiredness and discomfort. The robot is simulated in the platform CopeliaSim.
The ongoing energy transition requires power grid extensions to connect renewable generators to consumers and to transfer power among distant areas. The process of grid extension requires a large investment of resourc...
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The paper presents need of using Kalman filtering to optimize location of mobile robotic systems and more accurate navigation. Theoretical knowledge was verified on real system represented by mobile robotic system (MR...
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By combining several existing simulators, co-simulation approaches are designed for efficient simulator development. Especially for energy systems integration simulations involving different physical domains, co-simul...
By combining several existing simulators, co-simulation approaches are designed for efficient simulator development. Especially for energy systems integration simulations involving different physical domains, co-simulation is the required approach. However, co-simulation setup is complex, time-consuming, and additionally, error-prone for large simulations, especially if visualizations are included. Therefore, for an intensive information exchange between simulators, the present paper introduces a new network-based communication concept including the co-simulation setup procedure. The proposed setup concept enables an efficient configuration for the coupling of distributed simulation modules. The evaluation of the implemented concept on an exemplary power grid simulation with integration of power-to-gas and gas-to-power components and power grid visualization shows the ability for efficient handling of a high amount of exchanged simulation data.
We investigate different formulations of economic model predictive control for thermal building control. Specifically, we study the trade-off of (possibly conflicting) objectives like temperature tracking, saving ener...
We investigate different formulations of economic model predictive control for thermal building control. Specifically, we study the trade-off of (possibly conflicting) objectives like temperature tracking, saving energy, and minimizing energy cost. We compare the proposed formulations to conventional proportional control for a modern office building. Our findings indicate that, if price incentives are sufficiently high, a concrete core activation system significantly increases the load shifting capabilities of office buildings.
—The highly non-convex AC optimal power flow problem is known to scale very poorly with respect to the number of lines and buses. To achieve improved computational speed and scalability, we apply a distributed optimi...
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The computational complexity involved in time-domain simulations, commonly used for analyzing transient stability in power systems, usually limits system studies to a few scenarios during the planning process. Complet...
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The computational complexity involved in time-domain simulations, commonly used for analyzing transient stability in power systems, usually limits system studies to a few scenarios during the planning process. Complete analysis, however, requires investigation of all possible contingencies and consideration of the continuous changes in the operating point, which necessitates fast analysis techniques during network operation. The present paper introduces a hybrid analysis approach combining a direct-method and time-domain simulations for the fast analysis of power system transients. The combined analysis relies on a Lyapunov-based direct approach using the Potential Energy Boundary Surface (PEBS) method for a fast selection of critical contingencies in the first stage. In the second stage, the critical contingencies are further investigated by time-domain simulations. Simulation results are presented using a real network of the Baden-Württemberg state (Germany) in order to illustrate the simulation process of the implemented approach.
Effective scheduling of the power exchange with an external grid is of interest for clusters of devices (including consumption, generation and storage) that aim to participate in energy markets. Scheduling is often pe...
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ISBN:
(纸本)9783800749546
Effective scheduling of the power exchange with an external grid is of interest for clusters of devices (including consumption, generation and storage) that aim to participate in energy markets. Scheduling is often performed by means of optimization-based algorithms considering uncertain forecasts of inflexible generation and consumption. In this paper, we assess the performance of a previously proposed scheduling algorithm - based on non-parametric probabilistic forecasts both in terms of power and energy - in a realistic industrial campus setting. Simulation results using real data from the KIT north campus underpin the applicability of the proposed algorithm.
The implication of the thalamus in multiple neurological pathologies makes it a structure of interest for volumetric analysis. In the present work, we have designed and implemented a multimodal volumetric deep neural ...
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