基于特征融合的调制识别增强与迁移演化

针对调制识别中单一图像的特征信息不足,区分度不够高,识别范围受限的问题。本文提出了一种基于时频图和星座图特征融合的调制识别特征增强方法,利用深度学习神经网络提取信号图像的特征,构建特征空间,通过多维特征融合,挖掘和整合不同特征的优势,增强模型算法的鲁棒性。此外运用了模型迁移的方法,仅需对分类器进行训练,大幅节约了训练时间和资源,具有很强的实时性和实用性。仿真结果显示,在0db左右的条件下,相比于单一特征图像,采用特征融合增强的方法能将信号的平均识别率提高约25%,通过模型迁移,省去了卷积神经网络的训练,所需的训练时间约为迁移前的9.6%,消耗内存约为迁移前的7.3%,同时模型的识别率损失控制在了5%以内。     

Enhanced Thermal Stability of Zinc-Based Titanate (Dielectric) Ceramics Prepared by the Modified Sol–gel Route

A multi-component substitution of Co and Ni was incorporated into ZnTiO₃ to form pure hexagonal Zn_{1− x} (Co_1/2Ni_1/2) _x TiO₃ ( x =0,0.8,0.9,1.0) dielectric ceramic powders by a modified sol–gel route, following heat treatments at 600°C for 3 h and at 800°C for 6 h. Differential scanning calorimetry measurements revealed that the order of increasing thermal stability of solid solution compound Zn_{1− x} (Co_1/2Ni_1/2) _x TiO₃ was ZnTiO₃ (945°C), Zn_0.1Ni_0.9TiO₃ (1346°C), Zn_0.1(Co_1/2Ni_1/2)_0.9TiO₃ (1390°C), and Zn_0.1Co_0.9TiO₃ (>1400°C). Both the dielectric constant and loss tangent reached a maximum at x =0.8 and then decreased with solubility, x , and measurement frequency.     

基于遗传算法优化的OCSVM双轮廓模型异常检测算法

针对Modbus工业总线协议的特殊性及工控数据样本的不均衡性,利用单类支持向量机（OCSVM）分别构建正常OCSVM模型和异常OCSVM模型,即双轮廓模态来模拟系统通信的正常模式和异常模式,从而实现工控系统异常检测。同时将遗传算法优化自变量降维应用于工控网络入侵检测场景,实现对输入自变量的降维压缩处理,防止OCSVM模型出现过拟合现象及分类准确率低的问题,提高异常检测的精度,缩减建模时间。通过仿真验证了该算法对工控网络异常检测的有效性。     

用人工神经网络预测混杂复合材料混杂效应

本研究建立一个二输入单输出的BP人工神经网络模型，并用QBASIC语言编制了相应的软件。利用该神经网络模型对混杂效应与混杂比及分散度系数间关系进行了预测。研究结果表明，网络经过61223次的迭代，预潮值误差为0．12％，具有很高的预测精度，可用于混杂复合材料混杂效应的预测。     

甲苯二异氰酸酯（TDI）的市场开拓

甲苯二异氰酸酯(TDI)是合成聚氨酯高聚物的主要原料之一,本文简要地论述了该产品的国内外发展与现状,从当前国内市场出发,认为开发面广,量大和价廉的新制品是我国TDI市场的开拓方向和当务之急,并提出了5项具体的开发项目,以有助于该产品的迅速发展。     

Pozzolanic properties of reject fly ash in blended cement pastes

Low-grade fly ash (reject fly ash, r-FA), a significant portion of the pulverized fuel ash (PFA) produced from coal-fired power plants and rejected from the ash classifying process, has remained unused due to its high carbon content and large particle size. But it may be used in certain areas, such as in solidification and stabilization processes of hazardous waste and materials for road base or subbase construction, which require relatively lower strength and reactivity. It is therefore necessary to extend research on the properties of r-FA and explore its possible applications. This paper presents experimental results of a study on the mechanical and hydration properties of cementitious materials prepared by blending r-FA with ordinary Portland cement (OPC). Parallel mixes were also prepared with the good ash [i.e., classified fine fly ash (f-FA)] for comparison. Selective chemical activators were added to the mix to study the effects of the activators on the properties of the blend system. The results show that r-FA generally has a lower rate of hydration than f-FA particularly at the early stage of hydration. Adding Ca(OH)₂ alone almost had no effect on accelerating the hydration of r-FA. But adding a small quantity of Na₂SO₄ or K₂SO₄ together with Ca(OH)₂ significantly accelerated the hydration reaction. The results of the compressive strength measurement correlated nicely with the degree of hydration results. It was also found that water-to-binder ratio (w/b) was an important factor in affecting the strength development and the hydration degree of r-FA pastes.     

重组人干扰素α2b栓剂的检定及其临床疗效

目的对重组人干扰素α2b栓剂进行质量检定及临床疗效观察。方法连续试制3批样品,进行各项质控指标的检定及宫颈糜烂的临床疗效观察。结果本品各项检定指标均符合质量要求。治疗组宫颈糜烂的有效率为74·8%,对照组的有效率为60·0%。治疗组和对照组的副反应发生率分别为9·1%和8·3%。结论重组人干扰素α2b栓剂质量稳定,安全性好,疗效确切。     

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.     

Dynamics stability in wireless sensor networks active defense model

Wireless sensor networks, which are widely used in military, industrial and transportation fields, are vulnerable to various kinds of attacks, since they are mostly deployed in a relatively open environment. Based on the evolutionary game theory, this paper proposes a proactive defense model for wireless sensor networks, in which we emphasize that the node has a limited ability to learn the evolution of rationality from different attack strategies of the attacker, and can dynamically adjust their strategies to achieve the most effective defense. Following this approach, the cost (e.g., energy consumption and wastage of machinery) has been greatly saved and the life cycle of the nodes has been extended as well. By employing the proposed model, the whole wireless sensor network can be implemented in an effective way.     

Removal of formaldehyde at low concentration using various activated carbon fibers

Adsorption of low concentration formaldehyde on pitch‐based, rayon‐based, and PAN‐based activated carbon fibers (ACFs) and an unactivated PAN‐based carbon fiber (PAN‐CF) was investigated by a dynamic method. The pore structure and surface chemistry of these samples were characterized by liquid nitrogen adsorption, elemental analysis, and X‐ray photoelectron spectroscopy. Results revealed that the pore structure, especially surface chemical composition, greatly influence the formaldehyde adsorption. PAN‐based ACFs showed the highest formaldehyde adsorption capacity because there are more abundant nitrogen‐containing groups, especially pyrrolic, pyridonic, pyridinic, and quaternary on the surface. The breakthrough time and formaldehyde adsorption capacity of one kind of PAN‐ACF were 361 min and 0.478 mmol/g, respectively. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007