Research on a Rice Counting Algorithm Based on an Improved MCNN and a Density Map

The thousand grain weight is an index of size, fullness and quality in crop seed detection and is an important basis for field yield prediction. To detect the thousand grain weight of rice requires the accurate counting of rice. We collected a total of 5670 images of three different types of rice seeds with different qualities to construct a model. Considering the different shapes of different types of rice, this study used an adaptive Gaussian kernel to convolve with the rice coordinate function to obtain a more accurate density map, which was used as an important basis for determining the results of subsequent experiments. A Multi-Column Convolutional Neural Network was used to extract the features of different sizes of rice, and the features were fused by the fusion network to learn the mapping relationship from the original map features to the density map features. An advanced prior step was added to the original algorithm to estimate the density level of the image, which weakened the effect of the rice adhesion condition on the counting results. Extensive comparison experiments show that the proposed method is more accurate than the original MCNN algorithm.     

Assessment and Prediction of Water Resources Vulnerability Based on a NRS-RF Model: A Case Study of the Song-Liao River Basin,China

The vulnerability of water resources is an important criterion for evaluating the carrying capacity of water resources systems under the influence of climate change and human activities. Moreover, assessment and prediction of river basins’ water resources vulnerability are important means to assess the water resources security state of river basins and identify possible problems in future water resources systems. Based on the constructed indicator system of water resources vulnerability assessment in Song-Liao River Basin, this paper uses the neighborhood rough set (abbreviated as NRS) method to reduce the dimensionality of the original indicator system to remove redundant attributes. Then, assessment indicators’ standard values after dimensionality reduction are taken as the evaluation sample, and the random forest regression (abbreviated as RF) model is used to assess the water resources vulnerability of the river basin. Finally, based on data under three different future climate and socio-economic scenarios, scenario predictions are made on the vulnerability of future water resources. The results show that the overall water resources vulnerability of the Song-Liao River Basin has not improved significantly in the past 18 years, and the overall vulnerability of the Song-Liao River Basin is in the level V of moderate to high vulnerability. In the future scenario 1, the overall water resources vulnerability of the river basin will improve, and it is expected to achieve an improvement to the level III of moderate to low vulnerability. At the same time, the natural vulnerability and vulnerability of carrying capacity will increase significantly in the future, and the man-made vulnerability will increase slowly, which will deteriorate to the level V of moderate to high vulnerability under Scenario 3. Therefore, taking active measures can significantly reduce the vulnerability of nature and carrying capacity, but man-made vulnerability will become a bottleneck restricting the fragility of the overall water resources of the river basin in the future.     

A Fast Approach to Removing Muscle Artifacts for EEG with Signal Serialization Based Ensemble Empirical Mode Decomposition

An electroencephalogram (EEG) is an electrophysiological signal reflecting the functional state of the brain. As the control signal of the brain–computer interface (BCI), EEG may build a bridge between humans and computers to improve the life quality for patients with movement disorders. The collected EEG signals are extremely susceptible to the contamination of electromyography (EMG) artifacts, affecting their original characteristics. Therefore, EEG denoising is an essential preprocessing step in any BCI system. Previous studies have confirmed that the combination of ensemble empirical mode decomposition (EEMD) and canonical correlation analysis (CCA) can effectively suppress EMG artifacts. However, the time-consuming iterative process of EEMD may limit the application of the EEMD-CCA method in real-time monitoring of BCI. Compared with the existing EEMD, the recently proposed signal serialization based EEMD (sEEMD) is a good choice to provide effective signal analysis and fast mode decomposition. In this study, an EMG denoising method based on sEEMD and CCA is discussed. All of the analyses are carried out on semi-simulated data. The results show that, in terms of frequency and amplitude, the intrinsic mode functions (IMFs) decomposed by sEEMD are consistent with the IMFs obtained by EEMD. There is no significant difference in the ability to separate EMG artifacts from EEG signals between the sEEMD-CCA method and the EEMD-CCA method (p > 0.05). Even in the case of heavy contamination (signal-to-noise ratio is less than 2 dB), the relative root mean squared error is about 0.3, and the average correlation coefficient remains above 0.9. The running speed of the sEEMD-CCA method to remove EMG artifacts is significantly improved in comparison with that of EEMD-CCA method (p < 0.05). The running time of the sEEMD-CCA method for three lengths of semi-simulated data is shortened by more than 50%. This indicates that sEEMD-CCA is a promising tool for EMG artifact removal in real-time BCI systems.     

连续调谐太赫兹回旋管非稳定振荡状态研究

太赫兹回旋管可实现高功率输出,并具有一定的频率调谐范围,是核磁共振波谱系统理想的高功率太赫兹辐射源。设计了263 GHz,TE_5,2基波连续调谐回旋管,通过磁场调节实现频率调谐范围为1.39 GHz,利用时域多模多频自洽非线性理论对设计的连续调谐回旋管非稳定振荡状态进行了研究。结果表明,在低次纵向谐波模式工作磁场范围内,当工作电流大于起振电流时,连续调谐回旋管先进入稳定状态,高次纵向谐波模式被抑制,工作模式TE_5,2的输出功率随时间不变;当电流增大,纵向谐波模式间的竞争引起回旋管由稳定状态进入到非稳定振荡状态,工作模式TE_5,2的输出功率随时间呈振荡变化且互作用效率大大降低;随着电流的进一步增大,回旋管又回到与低电流不同的稳定状态,互作用效率进一步降低。同时发现非稳定振荡状态的起始电流随着磁场增加而增大。本研究对需工作于稳定状态的面向DNP-NMR应用的连续调谐太赫兹回旋管的研制具有一定指导意义。     

基于维纳滤波的同轴电缆脉冲信号传输畸变补偿研究

由于同轴电缆的低通传输特性,脉冲信号在同轴电缆中传输时不可避免地会出现畸变,并且畸变程度会随着脉冲信号频率、带宽以及传输距离的增加而增大。创新性地将图像处理领域中的一种图像复原方法——维纳滤波法应用于脉冲信号同轴电缆传输畸变补偿,仅利用同轴电缆的S参数和输出信号即可完成输入信号的重构。并以10 m同轴电缆为对象,采用该方法分别对双指数脉冲信号、高斯调制脉冲信号、调制方波信号进行传输畸变补偿。结果表明：对于不同样式的信号,该方法均具有优异的补偿性能;并且,与工程上常用的衰减补偿法相比,该方法不仅补偿精度高,还具有高的计算效率,在同轴电缆脉冲信号传输畸变补偿中具有很好的实用价值。     

基于分数阶傅里叶变换的模式测控一体化方法

提出了一种基于分数阶傅里叶变换的模式测控一体化方法。利用分数阶傅里叶变换光路对光纤模式耦合态进行空间调制和相位调制,以实现模式的有效分解。与双重傅里叶变换（F²）法以及空间和频谱成像（S²）法相比,采用的分数阶傅里叶变换法,通过改变分数阶参数,控制模式的空间分布以及模式间的叠加状态,更易于分解出高阶模式。基于分数阶傅里叶变换的模式测量方法可在更广泛空间,研究模式的空间和相位叠加以及模式分解,也可退化为F²法和S²法。     

Influence of quantum correction on black hole shadows,photon rings,and lensing rings

We calculate photon sphere \begin{document}$r_{ph}$\end{document} and critical curve \begin{document}$b_c$\end{document} for a quantum corrected Schwarzschild black hole, finding that they violate universal inequalities proved for asymptotically flat black holes that satisfy the null energy condition in the framework of Einstein gravity. This violation seems to be a common phenomenon when considering quantum modification of Einstein gravity. Furthermore, we study the shadows, lensing rings, and photon rings in the quantum corrected Schwarzschild black hole. The violation leads to a larger bright lensing ring in the observational appearance of the thin disk emission near the black hole compared with the classical Schwarzschild black hole. Our analysis may provide observational evidence for the quantum effect of general relativity.     

在大学物理教学中培养学生的批判性思维能力——浅析开放性提问的作用

具有独立思考和批判性思维能力对于提高创新能力具有重要作用,但目前大学普通物理教学还侧重于知识的传授,缺少对学生批判性思维能力的培养和重视.本文从开放性提问的角度出发,阐述了如何在大学物理教学中培养学生独立思考的习惯和批判性思维的能力.文章举例分析了在科学历史、课程习题、演示实验和工程案例中挖掘开放性问题,通过以学为中心...     

Femtosecond laser micromachined optical waveguides in LiTaO3 crystal

By using femtosecond laser micromachining, optical wave guides in both depressed cladding and dual‐line configurations have been produced in LiTaO₃ crystal. The guiding properties and the thermal stability have been investigated for both geometries, which exhibit different performance. Depressed cladding waveguides support guidance along both extraordinary and ordinary index polarizations, while dual‐line waveguides support only extraordinary index polarization. Thermal annealing has been proved to be an effective method to reduce the propagation losses. For the cladding waveguide, the lowest propagation loss was as low as 0.38 dB/cm after the annealing treatment at 400 °C. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

偏分复用系统中偏振模色散补偿与偏分解复用一体化方案

本文建立了偏分复用系统中偏振模色散与信号偏振态变化引起信道串扰的数学模型, 分析了偏振模色散对偏分复用信道射频功率的影响, 并提出了适用于偏分复用系统的光域偏振模色散补偿与偏分解复用同时进行的方案: 用信道的射频功率作为反馈控制信号, 监测链路中偏振模色散和偏振态变化引起的信道串扰的大小, 用改进的粒子群优化算法对偏振控制器进行自适应控制, 同时完成偏振模色散补偿与偏分解复用. 在112 Gb/s偏分复用-差分正交相移键控(PDM-DQPSK)传输系统中仿真验证了该方案的有效性. 结果表明该方案可以使112 Gb/s-PDM-DQPSK传输系统完成自适应偏分解复用的同时, 在1 dB的光信噪比代价下, 使系统对偏振模色散的容忍度提高20 ps. 关键词： 偏分复用系统 信道串扰 偏振模色散 偏分解复用