Soil Apparent Electrical Conductivity (EC<Subscript>a</Subscript>) as a Means of Monitoring Changesin Soil Inorganic N on Heterogeneous Morainic Soils in SE Norway During Two Growing Seasons

An efficient method to monitor changes in soil inorganic N content during crop growth would be a useful means to guide N fertilization to ensure high yields and low N losses to the environment. In this study, soil apparent electrical conductivity (EC_a) measured by the widely used conductivity meter EM38 was tested as an indirect measurement of available N in spring barley during two cropping seasons at two sites with morainic loam in SE Norway. The experiment was constructed to maximize soil variation. In spite of the ȁ8noiseȁ9 caused by the soil heterogeneity, concentrations of inorganic N (cN_inorg) or NO₃-N were most strongly correlated with EC_a in both years and at both locations (with one exception). The measurements of EC_a reflected well the temporal variation in inorganic N content (N_inorg), and a ranking of the treatments based on EC_a fitted very well with a ranking based on N_inorg at the first three sampling times after fertilizing. The best subset of sensor variables (i.e. variables which can be measured ȁ8on-the-goȁ9 by sensor techniques in the field) described 27–69% (average 47%) of the variation in topsoil cN_inorg. When expanding the regression models to include pH as well, the degree of explanation increased significantly. In conclusion, the method of using EC_a appears to be quite robust in terms of detecting relative differences in cN_inorg, whereas a determination of absolute levels of cN_inorg with the method is unreliable.     

A Modified Nonparametric Prewhitened Covariance Estimator

Abstract. This paper proposes a fully modified version of the spectral matrix estimator (and the long‐run variance estimator as a special case) proposed originally by Xiao and Linton [Journal of Time Series Analysis (2002) Vol. 23, pp. 215–250], and derives its asymptotic results. A striking feature of the modified spectral matrix estimator is to achieve the convergence rate of O(T ^?8/9) in the mean squared error (MSE), which is usually achieved under the fourth‐order spectral window. However, this estimator does not sacrifice the positive definiteness of the resulting estimate for the rate improvement; it is Hermitian and positive definite in finite samples by construction. The faster convergence rate is established by a multiplicative bias correction of the crude spectral estimator under the second‐order spectral window. The approximations to some sensible definitions of the MSE of the estimator and the bandwidths that minimize the asymptotic MSEs are also derived. Monte Carlo results indicate that for a wide variety of processes the modified spectral matrix estimator reduces the bias without inflating the variance and thus improves the MSE, compared with the crude, bias‐uncorrected estimator.     

Measuring individual corrective reaction time using the intermittent illumination model

The corrective reaction time (t_cr) is an essential motor property when modelling hand control movements. Many studies designed experiments to estimate t_cr, but reported only group means with inconsistent definitions. This study proposes an alternative methodology using Drury's (1994) intermittent illumination model. A total of 24 participants performed circular tracking movements under five levels of visual information delay using a modified monitor in a darkened room. Measured movement speeds and the manipulated delays were used with the model to estimate t_cr of individuals and test effects of gender and path width. The results showed excellent model fits and demonstrated individual differences of t_cr, which was 273 ms on average and ranged from 87 to 441 ms. The wide range of t_cr values was due to significant effects of gender and path width. Male participants required shorter t_cr compared to female participants, especially for narrow path widths.     

一种基于多核嵌入式系统的TD-LTE同步校正方法

针对TD-LTE系统中同步性错误随机发生的问题,提出了一种通过ARM+DSP+FPGA平台的嵌入式系统实现帧号和原语的同步校正方法。该方法基于TD-LTE射频一致性测试仪表硬件平台,通过该嵌入式系统中ARM、DSP、FPGA间的协调工作,由GPMC模块通过帧号和原语两方面对系统同步性进行校正。在TD-LTE射频一致性测试仪表硬件平台中进行了验证,结果表明,该方法在实现帧号与子帧号同步校正的基础上明显提高了TD-LTE系统通信的稳定性。     

Nonparametric kernel density estimation near the boundary

Standard fixed symmetric kernel-type density estimators are known to encounter problems for positive random variables with a large probability mass close to zero. It is shown that, in such settings, alternatives of asymmetric gamma kernel estimators are superior, but also differ in asymptotic and finite sample performance conditionally on the shape of the density near zero and the exact form of the chosen kernel. Therefore, a refined version of the gamma kernel with an additional tuning parameter adjusted according to the shape of the density close to the boundary is suggested. A data-driven method for the appropriate choice of the modified gamma kernel estimator is also provided. An extensive simulation study compares the performance of this refined estimator to those of standard gamma kernel estimates and standard boundary corrected and adjusted fixed kernels. It is found that the finite sample performance of the proposed new estimator is superior in all settings. Two empirical applications based on high-frequency stock trading volumes and realized volatility forecasts demonstrate the usefulness of the proposed methodology in practice.     

主从式测量系统中传感器标定方案的研究及实现

针对主从式测量系统中传感器的标定问题,提出从上位机软件进行标定的方案,着重分析软件标定的数据采集及处理过程,并根据标定直线及标定常数的数值判定是否需要进行原点补偿。实验证明,从上位机软件角度对传感器进行标定更加简单方便,并且降低了对生产线标定人员的专业知识要求,该方法适合应用于工业现场对传感器进行标定,有较高的实际应用价值。     

含温度补偿的便携式土壤水分测定仪研制

针对现有土壤水分测定仪的不足,研制了一种新型的便携式土壤水分测定仪。传感器快速测量出土壤温、湿度数据,GPS自动获取时间、经纬度信息,数据既可临时保存在仪器的存储芯片中,又可通过GPRS/GSM将数据及时发送到后台数据库和手机用户。通过温度补偿和野外验证实验得出,温度补偿项为Δy=0.0002 t3-0.011 t2+0.444 1 t-6.423 2,仪器所有功能运行正常,测量绝对误差为-3.64%~3.82%,平均绝对误差为2.24%,精度较高,适合在地方农技和水利部门推广应用,有助于农业水利信息化水平的提高。     

用于光刻系统仿真的多边形处理算法

为提高光刻仿真效率,通过对光刻原理进行研究,提出了2种多边形处理算法,将掩模上的多边形图案进行切分优化,将其划分成若干矩形或三角形。在Linux环境下应用C语言设计出一个完整的光刻仿真系统,设计的具体光学参数为:光源波长为193nm,数值孔径为0.3~0.8,部分相干系数可调范围为0.2~0.8,可一次性仿真1μm×1μm到10μm×10μm范围内的45 nm~0.18μm工艺的复杂版图,并通过多次实验进行验证。实验结果表明:原版图图像的边缘细节得到保留,且该算法有效地减少了光刻模拟的计算复杂度与计算时间,整体效率提升20%以上,为当前智能传感器系统芯片的制造节省了宝贵时间。     

一种在扩散加权图像降噪中的算法

扩散加权图像中的噪声为莱斯噪声并且图像本身含有丰富的边界信息,因而要求对DWI图像有效降噪的同时,能够较好地保留图像的边界信息。由于BEMD算法可将图像分解为细节图像及余项图像,其所分解的细节图像包括DWI图像的边界信息以及主噪声,而余项图像则描述图像的趋势信息。因此,提出一种将二维经验模态分解算法与改进的维纳滤波器相结合的降噪算法,并将该算法应用于DWI图像的降噪中。通过实验,将所提出的算法与其他算法应用于DWI图像的降噪处理,并通过对结果的分析比较证明所提出的算法能够更有效地对DWI图像进行降噪处理。     

Discriminative multi-task objects tracking with active feature selection and drift correction

In this paper, we propose a discriminative multi-task objects tracking method with active feature selection and drift correction. The developed method formulates object tracking in a particle filter framework as multi-Task discriminative tracking. As opposed to generative methods that handle particles separately, the proposed method learns the representation of all the particles jointly and the corresponding coefficients are similar. The tracking algorithm starts from the active feature selection scheme, which adaptively chooses suitable number of discriminative features from the tracked target and background in the dynamic environment. Based on the selected feature space, the discriminative dictionary is constructed and updated dynamically. Only a few of them are used to represent all the particles at each frame. In other words, all the particles share the same dictionary templates and their representations are obtained jointly by discriminative multi-task learning. The particle that has the highest similarity with the dictionary templates is selected as the next tracked target state. This jointly sparsity and discriminative learning can exploit the relationship between particles and improve tracking performance. To alleviate the visual drift problem encountered in object tracking, a two-stage particle filtering algorithm is proposed to complete drift correction and exploit both the ground truth information of the first frame and observations obtained online from the current frame. Experimental evaluations on challenging sequences demonstrate the effectiveness, accuracy and robustness of the proposed tracker in comparison with state-of-the-art algorithms.