浅论食品化学污染及其防治策略

分析了食品化学污染的主要途径,以及这些污染物对人体健康的危害性,对食品化学污染的防治策略进行了探讨。     

A general non-local denoising model using multi-kernel-induced measures

Noises are inevitably introduced in digital image acquisition processes, and thus image denoising is still a hot research problem. Different from local methods operating on local regions of images, the non-local methods utilize non-local information (even the whole image) to accomplish image denoising. Due to their superior performance, the non-local methods have recently drawn more and more attention in the image denoising community. However, these methods generally do not work well in handling complicated noises with different levels and types. Inspired by the fact in machine learning field that multi-kernel methods are more robust and effective in tackling complex problems than single-kernel ones, we establish a general non-local denoising model based on multi-kernel-induced measures (GNLMKIM for short), which provides us a platform to analyze some existing and design new filters. With the help of GNLMKIM, we reinterpret two well-known non-local filters in the united view and extend them to their novel multi-kernel counterparts. The comprehensive experiments indicate that these novel filters achieve encouraging denoising results in both visual effect and PSNR index.     

Centroid index: Cluster level similarity measure

In clustering algorithm, one of the main challenges is to solve the global allocation of the clusters instead of just local tuning of the partition borders. Despite this, all external cluster validity indexes calculate only point-level differences of two partitions without any direct information about how similar their cluster-level structures are. In this paper, we introduce a cluster level index called centroid index. The measure is intuitive, simple to implement, fast to compute and applicable in case of model mismatch as well. To a certain extent, we expect it to generalize other clustering models beyond the centroid-based k-means as well.     

双质体振动机的应用——浅谈解决橡胶后处理装置地基振动的方法

以降低合成橡胶生产厂后处理装置各种振动机造成的地基振动为目的,对双质体振动机的隔振效能进行了定量分析。通过生产实践,总结了单质体振动机、非平衡型双质体振动机和对称平衡型双质体振动机的优缺点,给出了后者的设计计算数据。经综合分析和生产考核,认为采用对称平衡型双质体振动机是降低地基振、降低噪音、延长振动机的运转周期和使用寿命的最佳方法。     

液氯离心泵的气蚀与防治

分析了影响液氯离心泵气蚀的两种参数：允许吸上真空度、气蚀余量。提出了泵气蚀的防治措施：提高离心泵基础设计质量，在实际使用中应采用高分子聚合材料涂覆，并进行补焊、补气。     

机床噪声及降低噪声的途径

分析了机床噪声的起因，并提出了相应的降噪措施。     

关于信号滤波中的频率逼近

该文研究信号滤波中的频率逼近问题。结合N-过程和加权因子的方法构造一个新的离散测度,讨论此测度的弱*收敛性。由此测度提供了一个内积形式的定义产生的正交多项式序列-Szeg正交多项式序列。由该多项式序列的零点的性质导出滤波中的未知频率的近似形式,并给出逼近度估计。同时对频率分析问题中的多项式的次数与临界点的个数之间的关系作了一些探讨。     

基于FFT与STM32 MCU的涡街信号处理系统设计

该文针对涡街传感器输出信号的特点和低流速时涡街流量计测量精度受限的问题,设计了一种基于STM32芯片的数字涡街信号处理方法与系统,将涡街传感器输出信号通过低噪声前置放大电路,可采集低流速下的涡街信号,再通过频谱分析法FFT准确计算出涡街信号频率,有效提高了测量精度。     

人力资本价值对企业绩效影响研究——基于组织学习、组织创新的中介效应

探讨人力资本价值对企业绩效的影响能否通过组织学习、组织创新的中介作用实现。将人力资本价值的衡量要素作为自变量,组织学习、组织创新作为中介变量,企业绩效作为因变量。以224名企业员工为研究样本,构建理论模型,对变量之间的关系进行定量研究。结果表明:人力资本价值的各要素通过组织学习、组织创新的中介作用正向影响企业绩效。     

一类非线性时滞偏差分方程的不饱和解

利用频密测度和无穷双序列{um,n}不饱和解的概念,讨论了一类带有可变号系数的非线性时滞偏差分方程解的不饱和性质,给出了偏差分方程解的频密振动性的几个充分条件.