This paper deals with two critical issues about uniform circular arrays (UCAs): frequency-invariant response and steering flexibility. It focuses on some optimal design of frequency-invariant ...beampatterns in any desired direction along the sensor plane. The major contributions are as follows. 1) We explain how to include the steering information in the desired directivity pattern. 2) We show that the optimal approximation of the beamformer's beampattern with a UCA from a least-squares error perspective is the Jacobi-Anger expansion. 3) We develop an approach to the design of any desired symmetric directivity pattern, where the deduced beampattern is almost frequency invariant and its main beam can be pointed to any wanted direction in the sensor plane. 4) With the proposed approach, we derive an explicit form of the white noise gain (WNG) and the directivity factor (DF), and explain clearly the white noise amplification problem at low frequencies and the DF degradation at high frequencies. The analysis also indicates that increasing the number of microphones can always improve the WNG. We show that the proposed method is a generalization of circular differential microphone arrays. The relationship between the proposed method and the so-called circular harmonics beamformers is also discussed.
Design of Robust Differential Microphone Arrays Liheng Zhao; Benesty, Jacob; Jingdong Chen
IEEE/ACM transactions on audio, speech, and language processing,
2014-Oct., 2014-10-00, 20141001, Letnik:
22, Številka:
10
Journal Article
Recenzirano
Differential microphone arrays (DMAs), due to their small size and enhanced directivity, are quite promising in speech enhancement applications. However, it is well known that differential ...beamformers have the drawback of white noise amplification, which is a major issue in the processing of wideband signals such as speech. In this paper, we focus on the design of robust DMAs. Based on the Maclaurin's series approximation and frequency-independent beampatterns, the robust first-, second-, and third-order DMAs are proposed by using more microphones than the order plus one, and the corresponding minimum-norm filters are derived. Compared to the traditional DMAs, the proposed designs are more robust with respect to white noise amplification while they are capable of achieving similar directional gains.
It is important to study the falling-film pattern of a horizontal tube bundle in order to set up a heat and mass transfer model accurately. The falling-film pattern of a horizontal tube bundle is ...simulated in this paper. The technique is based on computational flow dynamics (CFD) for the two-phase flow of gas and water. The experimental results were used to validate the mathematical model. It indicates that the simulation results accord with experimental data well. The simulated results show that the flow pattern varies with different flow rates. Under the different flow rates, it observes the droplet, droplet-columnar, columnar, columnar-sheet and sheet flow patterns. The critical value is 0.0125 kg/s between droplet and columnar, and the critical value is 0.02 kg/s between columnar and sheet.
•The physical model based on gambit is developed and a local mesh encryption method is presented.•Experiment platform is constructed to observe the flow patterns in order to verify the accuracy of the model.•The critical value is obtained between the droplet and the columnar.•The critical value is obtained between the columnar and the sheet.•The various flow patterns can be described between two tubes under the different flow rates.
•CdSe quantum disks, whose photoluminescence peak coincide with the EQE peak of the CIGS solar cells, have been synthesized and embedded into the PMMA to form the LDS layer for CIGS solar cells.•The ...LDS layer increases the EQE of CIGS devices by up to about 162% in the range 300–460 nm.•The placement of the LDS layer upon the CIGS solar cell improved the electrical power output of the bare cell to 114%.
As the luminescent down-shifting (LDS) material, Cadmium selenide (CdSe) quantum disks (QDs) have been synthesized for improving the short-wavelength response of Cu(In, Ga)Se2 (CIGS) solar cells. The peak of the photoluminescence spectra of the as-prepared QDs is coinciding with the peak of the external quantum efficiency (EQE) of CIGS solar cell. The absorption and photoluminescence spectra of the as-prepared CdSe QDs show that the photons of wavelength below 460 nm, which could not be converted into electricity by CIGS solar cell, would be absorbed by the QDs and generating longer wavelength photons that could contribute to charge carrier generation by the cell. The QDs were embedded into the polymethylmethacrylate (PMMA) forming the colloidal fluorescent mixture. Subsequently, the mixture was applied to the surface of the solar cell as the LDS layer. It is found that the EQE of CIGS devices increases up to about 25% in the range of 300–460 nm due to LDS. The placement of the LDS layer upon the CIGS solar cell improved the electrical power output of the bare cell to 114%.
Linear microphone arrays combined with the minimum variance distortionless response (MVDR) beamformer have been widely studied in various applications to acquire desired signals and reduce the ...unwanted noise. Most of the existing array systems assume that the desired sources are in the broadside direction. In this paper, we study and analyze the performance of the MVDR beamformer as a function of the source incidence angle. Using the signal-to-noise ratio (SNR) and beampattern as the criteria, we investigate its performance in four different scenarios: spatially white noise, diffuse noise, diffuse-plus-white noise, and point-source-plus-white noise. The results demonstrate that the optimal performance of the MVDR beamformer occurs when the source is in the endfire directions for diffuse noise and point-source noise while its SNR gain does not depend on the signal incidence angle in spatially white noise. This indicates that most current systems may not fully exploit the potential of the MVDR beamformer. This analysis does not only help us better understand this algorithm, but also helps us design better array systems for practical applications.
Background
Immunogenic cell death (ICD) is a process in which dying cells stimulate an immune response. It is a regulated form of cell death that can remodel the tumor microenvironment (TME) and ...activate the immune system, making immunotherapy more effective. This work was designed to identify prognostic gene features associated with ICD in cervical cancer (CC).
Methods
Based on CC datasets and a set of ICD‐related genes obtained from public databases, we first filtered out ICD‐related genes unrelated to CC survival using univariate analysis. Subsequently, LASSO regression and multivariate Cox regression analysis were employed to develop prognostic feature genes based on ICD. For the construction and validation of the model, eight genes (CXCL1, IL1B, TNF, YKT6, PDIA3, ROCK1, CXCR3, and CLEC9A) were chosen. A nomogram was created to forecast the prognosis of CC individuals, and Kaplan–Meier curves were utilized to explore the survival disparities among different risk groups of CC individuals.
Results
ssGSEA analysis was employed to investigate immune differences between two risk groups, revealing that the low‐risk group exhibited elevated levels of immune cell infiltration, enhanced activation of immune function, and a higher immunophenoscore compared with the other group, which highlighted the relevance of ICD to TME.
Conclusion
We constructed a prognostic model based on genetic biomarkers of ICD for prognostic prediction of CC patients. Our model demonstrated excellent discriminative and calibration capabilities, providing a valuable tool for prognostic prediction and assessing the potential efficacy of immunotherapy in CC.
Differential Kronecker Product Beamforming Cohen, Israel; Benesty, Jacob; Jingdong Chen
IEEE/ACM transactions on audio, speech, and language processing,
05/2019, Letnik:
27, Številka:
5
Journal Article
Recenzirano
Differential beamformers have attracted much interest over the past few decades. In this paper, we introduce differential Kronecker product beamformers that exploit the structure of the steering ...vector to perform beamforming differently from the well-known and studied conventional approach. We consider a class of microphone arrays that enable to decompose the steering vector as a Kronecker product of two steering vectors of smaller virtual arrays. In the proposed approach, instead of directly designing the differential beamformer, we break it down following the decomposition of the steering vector, and show how to derive differential beamformers using the Kronecker product formulation. As demonstrated, the Kronecker product decomposition facilitates further flexibility in the design of differential beamformers and in the tradeoff control between the directivity factor and the white noise gain.
Beamformers have been widely used to enhance signals from a desired direction and suppress noise and interfering signals from other directions. Constant beamwidth beamformers enable a fixed beamwidth ...over a wide range of frequencies. Most of the existing approaches to design constant beamwidth beamformers are based on optimization algorithms with high computational complexity and are often sensitive to microphone mismatches. Other existing methods are based on adjusting the number of sensors according to the frequency, which simplify the design, but cannot control the sidelobe level. Here, we propose a window-based technique to attain the beamwidth constancy, in which different shapes of standard window functions are applied for different frequency bins as the real weighting coefficients of microphones. Thereby, not only do we keep the beamwidth constant, but we also control the sidelobe level. Simulation results show the advantages of our method compared with existing methods, including lower sidelobe level, higher directivity factor, and higher white noise gain.
Noise reduction, which aims at estimating a clean speech from noisy observations, has attracted a considerable amount of research and engineering attention over the past few decades. In the ...single-channel scenario, an estimate of the clean speech can be obtained by passing the noisy signal picked up by the microphone through a linear filter/transformation. The core issue, then, is how to find an optimal filter/transformation such that, after the filtering process, the signal-to-noise ratio (SNR) is improved but the desired speech signal is not noticeably distorted. Most of the existing optimal filters (such as the Wiener filter and subspace transformation) are formulated from the mean-square error (MSE) criterion. However, with the MSE formulation, many desired properties of the optimal noise-reduction filters such as the SNR behavior cannot be seen. In this paper, we present a new criterion based on the Pearson correlation coefficient (PCC). We show that in the context of noise reduction the squared PCC (SPCC) has many appealing properties and can be used as an optimization cost function to derive many optimal and suboptimal noise-reduction filters. The clear advantage of using the SPCC over the MSE is that the noise-reduction performance (in terms of the SNR improvement and speech distortion) of the resulting optimal filters can be easily analyzed. This shows that, as far as noise reduction is concerned, the SPCC-based cost function serves as a more natural criterion to optimize as compared to the MSE.
Time delay estimation (TDE) is a basic technique for numerous applications where there is a need to localize and track a radiating source. The most important TDE algorithms for two sensors are based ...on the generalized cross-correlation (GCC) method. These algorithms perform reasonably well when reverberation or noise is not too high. In an earlier study by the authors, a more sophisticated approach was proposed. It employs more sensors and takes advantage of their delay redundancy to improve the precision of the time difference of arrival (TDOA) estimate between the first two sensors. The approach is based on the multichannel cross-correlation coefficient (MCCC) and was found more robust to noise and reverberation. In this letter, we show that this approach can also be developed on a basis of joint entropy. For Gaussian signals, we show that, in the search of the TDOA estimate, maximizing MCCC is equivalent to minimizing joint entropy. However, with the generalization of the idea to non-Gaussian signals (e.g., speech), the joint entropy-based new TDE algorithm manifests a potential to outperform the MCCC-based method
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