Five-Strokes Encoding Recognition of Unconstrained Handwritten Chinese Character

Keyboard input techniques are introduced into on line recognition of Chinese character with the study of chinese character five strokes encoding keyboard input method,and a new approach for on line recognition of unconstrained handwritten Chinese character,Five Strokes Encoding Recognition,is proposed.Besides,the set of character roots of Five Strokes have to be altered slightly to meet the on line recognition technique's features.     

Extracting the Strokes and Roots of Free Handwritten Chinese Character

The problems of stroke extraction and character root recognition were studied, and the strategies and the algorithms related to the problems were proposed or developed. Based on observing and studying on the writing styles and the composition features of free handwritten Chinese characters, the strategies and the algorithms, which have been showed by experimental results, have the advantages of high degree of steadiness and tolerance to character variance.     

Multi stage Classifier for Unconstrained Handwritten Numerals Recognition

A multi stage character classifier model is presented. By combining four independent algorithms, we integrate on line recognition method, off line recognition method, neural network method, tradition method into an unique pattern recognition system. The results and experiments show that our system has the merit of high recognition rate.     

A Method of Stroke Classification and Recognition in On line Handwritten Chinese Character Recognition

A method of stroke classification and recognition in on line handwritten chinese character recognition is presented.It has advantages of high degree of tolerance to stroke variance and high recognition rate.     

Conbination of On-line Methods and Off-line Methods for On-line Recognizing Un-constraint Handwritten Numerals

In this paper, we propose a scheme of recognizing un-constraint handwritten numerals,in which on-line methods and off-line methods are combined. This scheme inherits the good quality,and overcoming the defect of both on-line methods and off-line methods. Experiments show the scheme has achieved impressive performance and the preliminary results are very encourgine for recongnizing un-contraint handwritten numerals.     

A Meta-synthetic Approach for Lower-constrained Handwritten Character Recognition

A meta-synthetic network approach for conbination of multiple classifier is proposed aimed at solving the problems of character recognition. It composes of two B-Wavelet neural network classifiers and a Morlet-B-Wavelet neural network classifier.It is shown that the method is effective used in handwritten capital English character recongnizing.     

Feature Extraction and the Design of Classifier in Small Set Handwritten Chinese Character Recognition

This paper presents basic concept of feature extraction of handwritten Chinese character, and proposes a new feature extraction named superposition mesh weighting factors strokes extracting algorithm to obtain feature of small set handwritten Chinese character. Basing on the analysis model of RBFNN, an integration RBF classifier is used for small set handwritten Chinese character recognition. Then, the hybrid optimize strategy, which combines the genetic algorithm and the simulated annealing, is adopted to train RBFNN.     

A Self-Learing Chinese Character Recognition System

A method using possibility theory and fuzzy logic is introduced. Possibility functions of each feature are determined during training. Methods of fuzzy logic are used to combine the possibility of different features. This Chinese character recognition system consists of a pre-classifier and a two-level fine classifier. In order to handle deviations of the characters,a fuzzification of features is introduced. This method is used to develop single-font classifiers. The whole system consists of a font-classifiers and four single-font-classifiers.     

大白菜种质资源抽薹性及其遗传性的研究

以现蕾期和抽薹期为指标,对98份有代表性的大白菜种质资源的抽薹性进行了2年的调查和统计,结果显示,大部分材料从播种到现蕾的时间为101~112 d,占73.8%,超过116 d现蕾的材料仅占8.7%;从播种到抽薹的时间为105~116 d,占75.1%,超过120 d抽薹的材料仅占10.1%,青麻叶类型晚抽薹材料所占比率更低。对3组不同抽薹性材料组合后代DH系群体抽薹期观察统计结果显示,抽薹期相近的双亲后代抽薹期的分布较集中,双亲抽薹期相差较远的后代抽薹期的分布较分散。比早抽薹亲本抽薹早的后代DH系普遍存在,但比晚抽薹亲本抽薹晚的后代DH系极少。     

Study on ANN Based Character Recognition

The theory of Artificial Neural Networks and image processing are analyzed. ANN theory is also investigated . A Back Propagation network is used for classification. Based on the ANN and feature extraction, a character recognition and entry system is developed. Its drawbacks are discussed. Some solutions are presented. An odd feature database is constructed to promote the performance for learning. A 3 layer feedforward network has been proved that it has the ability to identify hand written characters.     

A Character Recognition Based on Feature Extraction

This thesis analyzes the theory of image processing and feature extraction, character feature is investigated in this thesis, including width, intersection, chain-code, the way of structure of character is used, a hand-written character recognition and entry system is developed. It is proved feature is simple and definite.     

青麻叶大白菜核基因雄性不育性遗传模式的研究

以稳定遗传的青麻叶类型大白菜甲型两用系2个、乙型可育株系4个及可育品系26个为材料，经过杂交、自交、测交及育性鉴定等手段，对青麻叶类型大白菜核基因雄性不育性的遗传模式进行了验证，并对青麻叶类型材料的育性基因型进行了测定。结果表明，青麻叶类型大白菜核基因雄性不育性的遗传模式符合复等位基因遗传模式；在经过多代纯化的青麻叶材料中，基因型为msms的材料所占比例最大，为65．4％，基因型为Ms^fms的材料所占比例最小，为7．7％，基因型为Ms^fMs^f的材料所占比例居中，为26．9％。     

The Basic Element Method of Recogniting Handwritten Mathematical Symbols

An on-line recognition approach for the handwritten mathematical symbols is presented. Firstly, it analyses the structures of 94 commonly used mathematical symbols and concludes that all of them consist of 10 basic elements. Secondly, it proposes a new method of basic element ordering and reduces the number of standard symbols by extracting three primary features of mathematical symbols,namely,basic element vector, relative positions between basic elements,and basic element length vector. Finally, the traditional dynamic programming method is improved by considering matching and unmatching value and adding geometric restraints.Through improved Kohn-Munkres algorithm. During the recognition test of mathematical symbols handwritten by 20 subjects, correctness rate reaches 92.52%,incorrectness rate 3.03% and refusal rate 4.45%.     

密度对新海14生育特性的影响

密度对新海14的生育进程、铃重和衣分率影响不大,但对它的株高、叶片数及蕾、铃的脱落数影响较大,即随着密度的增加株高降低,叶片数减少,蕾、铃的脱落率增高,并且铃的脱落大于蕾的脱落;对有效铃数和吐絮数影响也较大。结果表明新海14在南疆可实行高密度种植,适宜的种植密度应为27株/hm2左右。     

青椒果实性状遗传参数的分析

本文对青椒单果重、果长、果宽和果肉厚等4个果实性状的遗传参数进行了分析.结果表明:①4个果实性状的Vg/Vs比值均大,说明这些性状受基因加性效应影响大.一般配合力较高的亲本参与的组合,其F_1在这一性状上的实测值也较高.各性状配合力总效应值与实测值呈极显著的正相关.②4个果实性状的狭义遗传力较高,因此这4个性状的变异,大部分可固定遗传给后代,由F_1表现可以预测F_2表现的趋势.③4个果实性状的亲子间呈显著正相关,可根据双亲的平均值(MP)推断F_1相应的表现.     

采收期和入贮时间对猕猴桃贮后性状的影响

研究了冷藏和低乙烯气调贮藏下,采收期和入库时间对秦美猕猴桃后性状的影响。结果表明,采收期间果实可溶性固形物含量迅速升高,秦美猕猴桃的适宜采采收指标为可溶性固形物含量６．５％～８．０％,果实采后４８ｈ入库贮藏效果最佳。     

大白菜细胞核复等位基因型雄性不育系转育研究

为解决具有100%不育株率的大白菜细胞核复等位基因型雄性不育系转育难的问题,根据该不育系的遗传特性,设计了不育系的转育方案。采用常规的有性杂交、回交和自交方法,将青帮核不育系3A的不育基因转入白帮自交系C34中,育成了新的核基因雄性不育系A4。植物学性状鉴定结果表明,新育成的核不育系A4的株高、株幅、叶长、叶宽、叶柄长、叶球高、叶球粗、叶球毛重和叶球净重等的平均值和变异系数均接近于C34。     

Research on Pattern Recognizing Technique for Immunity of Blood Cells

This paper gives a new technique of automatically recognizing for immunity in pharmacological experiment. The realization of automatization of pharmacological experiment is very important and widely needed in pharmacology research and medical diagnosis. At the first, the paper introduces the system component and procession. The microscope image with complicated background is segmented. To improve the recognition speed and accuracy of the system, a way of dispatching image and multiprocessing for isolated cell is presented. The parameters of blood cells are obtained automaticly. The testing shows that the deviation of obtained pharmacological parameter doesn't exceed.     

中式生产线锅炉的选型与工程监理的管理技术

锅炉设备在食品工业中的应用范围很广,很多的食品企业都应用锅炉的蒸汽进行加热操作。介绍了中小型食品生产线对锅炉设备的选型标准及安装形式,以及锅炉蒸汽管路与食品生产线成套设备安装的工程监理,以期为在实际生产操作中选择合适的锅炉设备和降低安装成本提供参考。