锰对低铬白口铸铁组织及硬度的影响

系统研究了Ｍｎ对水平连铸低铬白口铸铁铸态及正火态组织和硬度的影响。结果表明，Ｍｎ＞２．０％之后对组织有较大影响，由于出现（Ｍ＋Ａ）组成物，使基体硬度显著提高，这将大大改善了低铬白口铸铁中碳化物与基体硬度的相对关系。试验证实，Ｍｎ＞３％之后明显改善硬度分布均匀性。还讨论了使低铬锰白口铸铁具有最佳综合性能的合理含Ｍｎ量范围     

A continuous-time framework for least squares parameter estimation

This paper proposes a continuous-time framework for the least-squares parameter estimation method through evolution equations. Nonlinear systems in the standard state space representation that are linear in the unknown, constant parameters are investigated. Two estimators are studied. The first one consists of a linear evolution equation while the second one consists of an impulsive linear evolution equation. The paper discusses some theoretical aspects related to the proposed estimators: uniqueness of a solution and an attractive equilibrium point which solves for the unknown parameters. A deterministic framework for the estimation under noisy measurements is proposed using a Sobolev space with negative index to model the noise. The noise can be of large magnitude. Concrete signals issued from an electronic device are used to discuss numerical aspects.     

炭素厂的消烟除尘和噪声控制

针对炭素制品生产过程产生的粉尘、沥青烟气、噪声等主要涉及工业卫生及环境保护等方面的问题进行剖析，并对治理方法做了简要的介绍。     

Experimental design in soap manufacturing for optimization of fuzzified process capability index

In manufacturing industries, the quality of a product depends on the combined effect of multiple input variables working singly or together and therefore attention has been given on process capability indices to shift from single to multivariate domain. In case of multivariable domain the capability to incorporate uncertainties at the time of decision making becomes necessary. Fuzzy system is introduced to take care of this requirement. In this article the process parameters of soap manufacturing industries have been analyzed. The process capability is determined using Fuzzy Inference System rule editor based on a set of justified if then statements as applicable for the process. The data has been collected in linguistic form to derive its process capability, using a set of justified rules and the effect of each factor has been determined using Design of Experiments (DoE) and analysis of variance technique (ANOVA) for improving the soap quality from perspective of its softness. This article ventures to propose a new methodology by integrating Fuzzy with DoE providing better result followed by DoE and Fuzzy Inference system in isolation.     

Effects of personal,psychosocial and occupational factors on low back pain severity in workers

Low back pain (LBP) remains the most common work-related musculoskeletal disorder (WMSD). While most of the LBP research has focused on occupational risk factors, other underlying causal mechanisms may exist since not all workers performing the same task develop an injury. Previous research has identified three primary risk factor categories for LBP (occupational, personal and psychosocial factors); however, few studies have investigated the impact of cross categorical risk factor interactions on LBP. The objective of this study was to investigate the effects of occupational, personal and psychosocial factors, and their interactions, on LBP severity in a population of workers currently suffering from LBP. Sixty LBP patients recruited for the study through local physicians and local announcements, completed questionnaires relating to identified occupational, personal and psychosocial risk factors, and completed an Oswestry Disability Index (ODI). Multiple regression models for predicting LBP severity were developed for each risk factor category and for a combined risk factor model (which included factors from all three risk factor categories) that included two-way interactions. Results showed that the final model consisted of both main effects and interaction terms between risk factor categories and had an adjusted R² value of 0.85, a significant improvement over models developed for the individual categories. These findings illustrate the need to consider all three broad categories of risk factors simultaneously in predicting injury status and in developing effective potential intervention efforts.     

Recent studies of self-condensation and co-condensation of melamine-formaldehyde resins; cure at low temperatures

Self-condensation: recent research on the chemical pathways by which alcoholated melamine-formaldehyde (MF) resins react with themselves and on the product structures is summarized. Model compound studies suggest that bridges are less stable than widely thought unless they are in hexahydro-1,3,5-triazine ring structures. In acyclic structures they are probably less stable than bridges. Co-condensation: studies of how the composition of MF resins influences the rates of reaction with poly(ol) co-reactant show that MF resins that contain very low levels of and/or functionality are quite reactive. Reactivities of a variety of poly(ester) and acrylic coreactants were studied. By combining reactive MF resins with reactive co-reactants one can formulate high solids enamels that cure by co-condensation in 30 min at 50 to 65 °C with 0.5 parts per hundred (phr) of p-toluenesulfonic acid (p-TSA) catalyst. Cure at 25 °C appears feasible with higher catalyst levels.     

具有数据包丢失的离散随机不确定系统的线性最优满阶估值器

研究了具有数据包丢失和随机不确定性离散随机线性系统的状态估计问题.其中数据包丢失是随机的,且满足Bernoulli分布,系统矩阵中的随机不确定性由一个白色乘性噪声来描述.首先,通过配方方法,提出了最小均方意义下的无偏最优线性递推满阶滤波器.所提出的滤波器用到了当前时刻和最近时刻接收到的观测来保证线性最优性.与多项式滤波和增广滤波器相比,本文的滤波器具有较小的计算负担.然后,基于所获得的线性滤波器推导了线性最优预报器和平滑器.进一步研究了线性最优估值器的渐近稳定性,给出了稳态特性存在的一个充分条件.最后,通过两个仿真例子验证了所提估计算法的优越性.     

EMD-IT去噪算法的阈值估计方法

为解决EMD-IT去噪算法中阈值难以确定的问题,提出一种基于高斯白噪声能量分布的阈值估计方法。将含噪信号进行经验模态分解并估计各固有模态函数(IMF)中噪声的能量;根据模态单元阈值的含义,在各IMF中利用去除掉的模态单元包含的总能量等于噪声能量这一准则估计阈值。合成数据和实际心电信号的去噪仿真实验验证了该方法的有效性,其是自适应的且避免了阈值选择的主观性。     

基于引力搜索算法的分数阶变异时序回归GSA-TSGM(1,1)模型

为了利用分数阶累加算子在灰色短期预测中的高效性能,首次将分数阶累加算子引入变异时序回归模型以期取得更高的预测精度。主要方法如下：首先取湖北省链子崖某监测点1978—1987年的十年数据作为训练集并使用引力搜索算法确定最佳分数阶累加阶数,而1988—1993年的六年数据作为验证集验证提出的模型;其次对比了经典灰色模型GM(1,1)、分数阶累加灰色模型、变异时序回归模型TSGM(1,1)三种灰色模型。结果如下：首先修正了陈西江等人变异时序回归模型仿真时出现的错误,其次表明了相比于其他的模型,基于引力搜索算法的分数阶累加时序回归模型在进行灰色长期预测中具有较高的预测精度。因此,通过分数阶累加算子提高了灰色理论中长期预测模型的精度,为灰色长期预测提供了指导。     

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.