碘与淀粉的相互作用及在Vc分析中的应用

本文探讨了碘与淀粉的相互作用以及碘－淀粉显色体系的稳定性。结果表明：在碘量一定时，体系的吸光度随淀粉用量的增大而增大，最后趋向稳定；在淀粉量一定时，体系的吸光度随碘用量的增大而增大，最后亦趋向稳定。碘－淀粉显色体系很不稳定，吸光度随时间呈比较明显的下降趋势，但加入复合表面活性剂可以使显色体系的稳定性大大提高。在上述结果的基础上，我们建立了测定Ｖｃ的新方法，此法具有简单、快捷、试剂易得、灵敏度高以及对浑浊试液不必分离即可直接测定等优点。该法的灵敏度为０．２５μｇ／ｍｌ，对１μｇ／ｍｌ的Ｖｃ试液进行平行测定，１０次平行测定结果的相对标准偏差为８．８６％，加标回收率为９０．５％－９３．６％，用于番石榴汁饮料中Ｖｃ的测定，结果满意。     

KAFD Arabic font database

Font recognition is useful for improving optical text recognition systems’ accuracy and time, and to restore the documents’ original formats. This paper addresses a need for Arabic font recognition research by introducing an Arabic font recognition database consisting of 40 fonts, 10 sizes (ranging from 8 to 24 points) and 4 styles (viz. normal, bold, italic, and bold–italic). The database is split into three sets (viz. training, validation, and testing). The database is freely available to researchers.¹ Moreover, we introduce a baseline font recognition system for benchmarking purposes, and report identification rates on our KAFD database and the Arabic Printed Text Image (APTI) database with 20 and 10 fonts, respectively. The best recognition rates are achieved using log-Gabor filters.     

KHATT: An open Arabic offline handwritten text database

A comprehensive Arabic handwritten text database is an essential resource for Arabic handwritten text recognition research. This is especially true due to the lack of such database for Arabic handwritten text. In this paper, we report our comprehensive Arabic offline Handwritten Text database (KHATT) consisting of 1000 handwritten forms written by 1000 distinct writers from different countries. The forms were scanned at 200, 300, and 600 dpi resolutions. The database contains 2000 randomly selected paragraphs from 46 sources, 2000 minimal text paragraph covering all the shapes of Arabic characters, and optionally written paragraphs on open subjects. The 2000 random text paragraphs consist of 9327 lines. The database forms were randomly divided into 70%, 15%, and 15% sets for training, testing, and verification, respectively. This enables researchers to use the database and compare their results. A formal verification procedure is implemented to align the handwritten text with its ground truth at the form, paragraph and line levels. The verified ground truth database contains meta-data describing the written text at the page, paragraph, and line levels in text and XML formats. Tools to extract paragraphs from pages and segment paragraphs into lines are developed. In addition we are presenting our experimental results on the database using two classifiers, viz. Hidden Markov Models (HMM) and our novel syntactic classifier.     

Study on pharyngeal and uvular consonants in foreign accented Arabic for ASR

This paper investigates the unique pharyngeal and uvular consonants of Arabic from the point of view of automatic speech recognition (ASR). Comparisons of the recognition error rates for these phonemes are analyzed in five experiments that involve different combinations of native and non-native Arabic speakers. The most three confusing consonants for every investigated consonant are discussed. All experiments use the Hidden Markov Model Toolkit (HTK) and the Language Data Consortium (LDC) WestPoint Modern Standard Arabic (MSA) database. Results confirm that these Arabic distinct consonants are a major source of difficulty for Arabic ASR. While the recognition rate for certain of these unique consonants such as // can drop below 35% when uttered by non-native speakers, there is advantage to include non-native speakers in ASR. Besides, regional differences in pronunciation of MSA by native Arabic speakers require the attention of Arabic ASR research.     

Arabic handwritten digit recognition

In this paper, we fill a gap in the literature by studying the problem of Arabic handwritten digit recognition. The performances of different classification and feature extraction techniques on recognizing Arabic digits are going to be reported to serve as a benchmark for future work on the problem. The performance of well known classifiers and feature extraction techniques will be reported in addition to a novel feature extraction technique we present in this paper that gives a high accuracy and competes with the state-of-the-art techniques. A total of 54 different classifier/features combinations will be evaluated on Arabic digits in terms of accuracy and classification time. The results are analyzed and the problem of the digit ‘0’ is identified with a proposed method to solve it. Moreover, we propose a strategy to select and design an optimal two-stage system out of our study and, hence, we suggest a fast two-stage classification system for Arabic digits which achieves as high accuracy as the highest classifier/features combination but with much less recognition time.     

Learning mixtures of point distribution models with the EM algorithm

This paper demonstrates how the EM algorithm can be used for learning and matching mixtures of point distribution models. We make two contributions. First, we show how shape-classes can be learned in an unsupervised manner. We present a fast procedure for training point distribution models using the EM algorithm. Rather than estimating the class means and covariance matrices needed to construct the PDM, the method iteratively refines the eigenvectors of the covariance matrix using a gradient ascent technique. Second, we show how recognition by alignment can be realised by fitting a mixture of linear shape deformations. We evaluate the method on the problem of learning the class-structure and recognising Arabic characters.     

Spray drying conditions for orange juice incorporated with lactic acid bacteria

This work aimed to develop an orange juice powder by spray drying with lactic acid bacteria (Lactobacillus plantarum 299v and Pediococcus acidilactici HA‐6111‐2), testing their survival both during drying and storage (room temperature and 4 °C). Initially, the best conditions for spray drying were chosen to allow the best survival of each LAB: (i) inlet air temperature of 120 °C and (ii) 0.5:2 ratio of the orange juice soluble solids and drying agent added (prebiotics: 10 DE maltodextrin or gum Arabic). Survival of LAB was not affected by drying process, and it was higher when cultures were stored at 4 °C. A slightly higher protection was conferred by 10 DE maltodextrin, in the case of L. plantarum and at 4 °C. Pediococcus acidilactici was more resistant during storage at 4 °C, with logarithmic reductions lower than 1 log‐unit. It was demonstrated that it is possible to produce a functional nondairy product, orange juice powder supplemented with prebiotic compounds, containing viable LAB for at least 7 months, when stored at 4 °C.     

A Statistical Framework for Online Arabic Character Recognition

The widely-used PDAs, touch screens, tablet-PCs are alternatives to keyboards with the advantages of being more friendly, easy, and natural. A framework for Arabic online character recognition is developed. The framework integrates the different phases of online Arabic text recognition. The used data poses several challenges such as delayed strokes handling, connectivity problems, variability, and style change of text. We process the delayed strokes at the different phases differently to improve the overall performance. This work includes feature extraction of many features, including several novel statistical features. Experimental results on challenging online Arabic characters show encouraging results.     

海藻酸钠-阿拉伯胶固定化酸性蛋白酶及其性质的研究

以海藻酸钠（SA）与阿拉伯胶（GA）为载体固定化酸性蛋白酶,以酶活回收率为评价指标,在单因素试验基础上,通过正交试验优化固定化条件。得到以SA-AG复合凝胶为载体制备固定化酸性蛋白酶的最佳工艺条件为：复合凝胶质量浓度3.5 g/100 mL,SA与AG质量比2∶1,氯化钙质量浓度7.0 g/100 mL,固定化时间1.0 h,给酶量1 540 U/g,吸附时间2.0 h,酶液pH值为3.0。此最佳条件下,固定化酸性蛋白酶酶活回收率为67.34%,酶活力为1 380 U/g。固定化酶酶学性质的研究结果表明,固定化酸性蛋白酶的最适作用温度（45 ℃）和最适反应pH值（pH=3）均与游离酶相同,但其热稳定性优于游离酶,且随着温度的升高这种优势越明显。