维吾尔新文字大小写同形字母的识别

为有效识别出新维文中大小写同形字母,分析新维文的特点,提出一种基于模板匹配的大小写同形字母识别算法。根据同形字母中大写字母外轮廓大而小写字母外轮廓小的特点,统计字母外轮廓大小与全文字母外轮廓平均大小的比例值,进行字母的大小写判断。分析结果表明,该方法有效克服了传统模板匹配方法容易混淆同形字母的大小写的缺点,提高了系统的识别率。     

印刷哈萨克斯拉夫粘连字符的切分方法

哈萨克斯拉夫图像文本经过行切分和列切分后,存在水平方向接触和垂直方向重叠的粘连字符。为提高字符识别率,依据字符连通域的最小外接矩形切分开垂直方向重叠的粘连字符图像块;利用判决条件:字符宽度概率密度分布图、字符图像块垂直投影的波峰数目和字符图像块垂直投影波峰的对称性,分离初始粘连字符图像块中正确的单个字符图像块和实际接触的粘连字符图像块;在允许的字符宽度范围内,寻找粘连字符图像垂直投影图的极小值点,以切分实际接触的粘连字符。实验结果表明,该方法泛化能力较好且识别率有明显提高。     

尿素嵌入法制备纤维素氨基甲酸酯的研究

探讨了尿素嵌入法制备纤维素氨基甲酸酯(CC)的生产工艺。指出:选用聚合度为450~625、α-纤维素含量大于90/的纤维素浆粕,用14/~16/的氢氧化钠溶液,于40~50℃条件下活化处理30~40min后,与尿素以1∶2~3的比例混合,在137℃的二甲苯体系中反应2~3h,便可得到含氮量为2.4/~3.5/的纤维素氨基甲酸酯产物。该产物在氢氧化钠溶液中可形成良好的稳定溶液,过滤性好,可直接用于纺丝。     

Phase Distribution and Magnetic Properties of Mechanically Alloyed Hard/Soft Ferrite Nanocomposites

Improvement in the magnetic properties of hard/ soft ferrite nanocomposites was studied by varying the composition of the soft phase in SrFe₁₂O₁₉/Ni_0.5Zn_0.5Fe₂O₄ nanocomposites. The SrFe₁₂O₁₉/Ni_0.5Zn_0.5Fe₂O₄ nanocomposites were prepared using the mechanical alloying method. The samples were prepared by varying the amount of the soft phase from 10 to 50 wt% while the amount of the hard phase remained 100 wt% in the ferrite nanocomposites. X-ray diffraction (XRD), a vibrating sample magnetometer (VSM), and a transmission electron microscope (TEM) were used to characterize the samples. From the result, it was found that the nanocomposite magnet with 10 wt% of soft phase content had the highest remanence ratio, M _r / M _s , which was 0.61, while the values of the coercivity, H _c , and magnetization, M _s , measured were 4482.4 G and 9.71 emu/g, respectively, and the average particle size of the ferrite nanocomposites was < 50 nm for all the samples. It was also shown that H _c decreased as the weight percent of the soft ferrite increased, which resulted from the dipolar interaction that occurred in the ferrite nanocomposites, showing the effect of phase distribution on the magnetic properties.     

氧化镧改善钨材料性能的研究现状

制备钨合金面临着再结晶温度低、韧脆转变温度高、高温强度低及寿命短等问题。稀土氧化物氧化镧(La2O3)添加到钨合金内,再结晶温度提高、韧脆转变温度下降、高温强度提高,所以钨材料内添加La2O3是最近几年国内外的热门研究课题之一。主要介绍了高温强度强、再结晶温度低、寿命长的W-La2O3合金的最佳La2O3添加含量以及改善这些性质的一些方法,最后指出了该合金待解决的一些问题及其发展趋势。     

Fabrication of ultraviolet photoconductive sensor using a novel aluminium-doped zinc oxide nanorod-nanoflake network thin film prepared via ultrasonic-assisted sol-gel and immersion methods

Unique and novel thin films with aluminium (Al)-doped zinc oxide (ZnO) nanostructures consisting of nanorod-nanoflake networks were prepared for metal-semiconductor-metal (MSM)-type ultraviolet (UV) photoconductive sensor applications. These nanostructures were grown on a glass substrate coated with a seed layer using a combination of ultrasonic-assisted sol-gel and immersion methods. The synthesised ZnO nanorods had diameters varying from 10 to 40 nm. Very thin nanoflake structures were grown vertically and horizontally on top of the nanorod array. The thin film had good ZnO crystallinity with a root mean square roughness of approximately 13.59 nm. The photocurrent properties for the Al-doped ZnO nanorod-nanoflake thin films were more than 1.5 times greater than those of the seed layer when the sensor was illuminated with 365 nm UV light at a density of 5 mA/cm². The responsivity of the device was found to be dependent on the bias voltage. We found that similar photocurrent curves were produced over eight cycles, which indicated that the UV sensing capability of the fabricated sensor was highly reproducible. Our results provide a new approach for utilising the novel structure of Al-doped ZnO thin films with a nanorod-nanoflake network for UV sensor applications. To the best of our knowledge, UV photoconductive sensors using Al-doped ZnO thin films with a nanorod-nanoflake network have not yet been reported.     

An encoding scheme based on fractional number for querying and updating XML data

In order to facilitate the XML query processing, several labeling schemes have been proposed to directly determine the structural relationships between two arbitrary XML nodes without accessing the original XML documents. However, the existing XML labeling schemes have to re-label the pre-existing nodes or re-calculate the label values when a new node is inserted into the XML document during an update process. In this paper, we devise a novel encoding scheme based on the fractional number to encode the labels of the XML nodes. Moreover, we propose a mapping method to convert our proposed fractional number based encoding scheme to bit string based encoding scheme with the intention to minimize the label size and save the storage space. By applying our proposed bit string encoding scheme to the range-based labeling scheme and the prefix labeling scheme, the process of re-labeling the pre-existing nodes can be avoided when nodes are inserted as leaf nodes and sibling nodes without affecting the order of XML nodes. In addition, we propose an algorithm to control the increment of label size when new nodes are inserted frequently at a fix place of an XML tree. Experimental results show that our proposed bit string encoding scheme provides efficient support to the process of XML updating without sacrificing the query performance when it is applied to the range-based labeling schemes.     

Graphene‐based ternary composites for supercapacitors

The research on electrode materials for supercapacitor application continues to evolve as the request of high‐energy storage system has increased globally due to the demand for energy consumption. Over the past decades, various types of carbon‐based materials have been employed as electrode materials for high‐performance supercapacitor application. Among them, graphene is 1 of the most widely used carbon‐based materials due to its excellent properties including high surface area and excellent conductivity. To exploit more of its interesting properties, graphene is tailored to produce graphene oxide and reduced graphene oxide to improve the dispersibility in water and easy to be incorporated with other materials to form binary composites or even ternary composites. Nowadays, ternary composites have attracted enormous interest as 2 materials (binary composites) cannot satisfy the requirement of the high‐performance supercapacitor. Thus, many approaches have been employed to fabricate ternary composites by combining 3 different types of electroactive materials for high‐performance supercapacitor application. This review focuses on the supercapacitive performance of graphene‐based ternary composites with different types of active materials, ie, conducting polymers, metal oxide, and other carbon‐based materials.     

Carbothermal nitridation process of mechanically milled silica sand using Taguchi's method

This paper reported on the work performed to study the formation of silicon nitride and silicon carbide whiskers using the carbothermal nitridation process. A distinctive aspect of the present study lies in the use of the mechanical milling method to alter the regularity of the crystalline network of the silica sand. In order to optimise the processing parameters for the synthesis of silicon carbide, the concept of Taguchi's Design of Experiments was considered, the analysis being based on Taguchi's signal to noise ratio and variance techniques to obtain optimum combination of process parameters. Important factors influencing the formation of silicon carbide were the duration of the mechanical milling, followed by temperature, time and heating rate.     

Predicting the colour properties of viscose knitted fabrics using soft computing approaches

The aim of this paper was to predict the colour strength of viscose knitted fabrics by using fuzzy logic (FL) model based on dye concentration, salt concentration and alkali concentration as input variables. Moreover, the performance of fuzzy logic (FL) model is compared with that of artificial neural network (ANN) model. In addition, same parameters and data have been used in ANN model. From the experimental study, it was found that dye concentration has the main and greatest effects on the colour strength of viscose knitted fabrics. The coefficient of determination (R²), root mean square (RMS) and mean absolute errors (MAE) between the experimental colour strength and that predicted by FL model are found to be 0.977, 1.025 and 4.61%, respectively. Further, the coefficient of determination (R²), root mean square (RMS) and mean absolute errors (MAE) between the experimental colour strength and that predicted by ANN model are found to be 0.992, 0.726 and 3.28%, respectively. It was found that both ANN and FL models have ability and accuracy to predict the fabric colour strength effectively in non-linear domain. However, ANN prediction model shows higher prediction accuracy than that of Fuzzy model.