Remcom (United States)

A magnitude-least-squares radiofrequency pulse design algorithm is reported which uses interleaved exact and stochastically-generated inexact updates to escape local minima and find low-cost solutions. Inexact updates are performed using a small randomly selected minibatch of the available measurements to update RF pulse weights, which perturbs the sequence of alternating projections. Applications to RF shimming, parallel transmit spokes RF pulse design, and spectral-spatial RF pulse design are considered. Numerical and simulation studies characterized the optimal minibatch size, which was found to consistently produce lower power and lower RMSE solutions across subjects, coil geometries, resolutions and orientations. The method was validated in-vivo at 7 Tesla and produced improvements in image quality in a slice-by-slice RF-shimmed imaging sequence. Compared to conventional methods, the pulse design method can more robustly design RF pulses that correct for inhomogeneities at ultra-high field strengths, and enable pulse designs to be completed with increased computational efficiency.

Neue Entwicklungen in der Baubranche erfordern neue Konzepte. Es entstehen neue Formen der Projektbegleitung und -entwicklung, die den Fokus nicht nur auf die Prozesse richten, sondern insbesondere auf den Menschen als wichtige Ressource für eine erfolgreiche Projektumsetzung. Die Autorin erklärt mehrere solche neuen Konzepte. Wichtiger Kern ist die Erkenntnis, wie sinnvoll in diesem Kontext Mediationskompetenz ist und wie sie zielführend eingesetzt werden kann.

The application of machine learning for optimal deployment of 5G infrastructure, such as the position and the orientation of the antenna that help achieve the best signal coverage, is investigated in this paper. This avoids the need to perform on-site measurements or extensive software simulations. Multivariate Regression (MR) and Neural Network (NN) models were applied to predict the signal coverage in an indoor environment. The results showed that the average prediction error using NN for the case investigated is 7 dB for a 60-GHz operating frequency, whereas the error using the MR technique is lower than 6 dB. The unique aspect in our work is the integration of the clustering algorithm and the NN machine learning model for predicting indoor signal coverage.

An area source for exciting microstrip line in FDTD simulation is proposed and studied in this paper. More accurate S-parameters are obtained by using the area source rather than the discrete source for exciting microstrip lines. This study also shows that both voltage area source and current area source work equally well. The reason for the improvement of S-parameters calculation due to the use of the area source is explained. The simulation results obtained by using the area source are also compared with those obtained by using the waveguide port.

Wind turbines located near radar installations can significantly interfere with a radar's ability to detect its intended targets. In order to better understand and mitigate the adverse effects of wind turbines on radar, the government and wind farm community need tools that can be used to analyze the radar returns from wind turbines. Remcom's XGtd® software is a high frequency solver capable of calculating the radar cross section of electrically large objects. In this paper, interference from wind turbines is predicted using XGtd simulations and new post-processing algorithms that calculate Doppler shift quantities based on points of interaction with the rotating turbine blades. Results of the analysis are used to calculate the bistatic radar cross section and Doppler shift from two blade orientations. In addition, the time-varying monostatic radar cross section and Doppler shift for a single wind turbine are analyzed and shown to agree well with measured data from actual wind turbines.

To simulate various transmission lines and their corresponding microwave circuits and antennas in FDTD, we need the excitation sources and S-parameter extraction methods. The excitation source can be discrete source or any source which can generate many modes. The excitation source can also be of any specific mode of the transmission lines although in many cases the fundamental mode is used. If one direction excitation source [1] is used in the simulation, S-parameters can be extracted straightforwardly. However, this method is not suitable to transmission lines when their propagation constants are unknown. For two directional excitation sources, various S-parameter extraction methods have been developed and we discuss some of them as follows.

For predictions of vehicle to vehicle communications, convoy communications, and Improvised Electronic Device (IED) detection/defense operations, Remcompsilas Wireless InSite Real Time (RT) module provides a very rapid propagation prediction capability in urban environments. Previous models are either empirical and inaccurate but fast, or deterministic and high-fidelity but slow. The RT Module takes the best of both; it is deterministic and provides higher-fidelity results than empirical models and is much faster than full physics-based models, returning a point-to-point result in milliseconds. It is free of the spatial limits of empirical models. This paper will show how the Wireless InSite Real Time Module can be used to provide accurate communication and jamming predictions for mission planning tools in near real time. The RT module allows user-defined mobile objects to be placed into the urban scene and rapidly repositioned without expensive reloading of geometry. The C++ API permits developers to quickly integrate the RT capability into their Tactical Decision Aids (TDApsilas) and other graphical visualization tools.

(2008). Summing a Curious, Slowly Convergent Series. The American Mathematical Monthly: Vol. 115, No. 6, pp. 525-540.