The image source method (ISM) is often used to simulate room acoustics due to its ease of use and computational efficiency. The standard ISM is limited to simulations of room impulse responses between point sources and omnidirectional receivers. In this work, the ISM is extended using spherical harmonic directivity coefficients to include acoustic diffraction effects. These effects occur in practice when transducers are mounted on audio devices of finite spatial extent, e.g., modern smart speakers with loudspeakers and microphones. The proposed method is verified using finite element simulations of various loudspeaker and microphone configurations in a shoebox-shaped room. It is shown that the accuracy of the proposed method is related to the sizes, shapes, number, and positions of the devices inside a room. A simplified version of the proposed method, which can significantly reduce computational effort, is also presented. The proposed method and its simplified version can simulate room transfer functions more accurately than currently available image source methods and can aid the development and evaluation of speech and acoustic signal processing algorithms, including speech enhancement, acoustic scene analysis, and acoustic parameter estimation.
Objective: Brain-computer interface(BCI) is leveraged by artificial intelligence in EEG signal decoding, which makes it possible to become a new means of human-machine interaction. However, the performance of current EEG decoding methods is still insufficient for clinical applications because of inadequate EEG information extraction and limited computational resources in hospitals. This paper introduces a hybrid network that employs a Transformer with modified locally linear embedding and sliding window convolution for EEG decoding.
Mate selection plays an important role in breeding programs. The Usefulness Criterion was proposed to improve mate selection, combining information on both the mean and standard deviation of the potential offspring of a cross, particularly in clonally propagated species where large family sizes are possible. Predicting the mean value of a cross is generally easier than predicting the standard deviation, especially in outbred species when the linkage of alleles is unknown and phasing is required.
Background: Hippocampal avoidance during prophylactic cranial irradiation (HA-PCI) is proposed to reduce neurocognitive decline, while preserving the benefits of PCI. We evaluated whether (HA-)PCI induces changes in white matter (WM) microstructure and whether sparing the hippocampus has an impact on preserving brain network topology. Additionally, we evaluated associations between topological metrics with hippocampal volume and neuropsychological outcomes.
Department of Mechanical Engineering, Institute of Advanced Machines and Design, Institute of Engineering Research, Seoul National University, Seoul, Republic of Korea.
Soft sensors integrated or attached to robots or human bodies enable rapid and accurate estimation of the physical states of the target systems, including position, orientation, and force. While the use of a number of sensors enhances precision and reliability in estimation, it may constrain the movement of the target system or make the entire system complex and bulky. This article proposes a rapid, efficient framework for determining where to place the sensors on the system given the limited number of available sensors.
Since visible light communication (VLC) uses light-emitting diode (LED) as transmitters, it has dual functions of illumination and communication. To meet flexible lighting and energy-saving needs, we propose a novel, to the best of our knowledge, dimming control scheme for spectrally efficient clipping-free multilayer optical orthogonal frequency division multiplexing (CFMO-OFDM)-based VLC systems. In order to achieve high dynamic-range dimming control for LEDs, the time-domain CFMO-OFDM signals are first grouped based on frequency-domain subcarrier distribution.
