Thesis (MSc)--Stellenbosch University, 2002. / ENGLISH ABSTRACT:Several authors regard the subdivision of the large genus Heliophila as unsatisfactory and in need of a detailed taxonomic study. Previous studies on this genus were based exclusively on gross external morphological characters. The present study investigates patterns of variation in Heliophila in order to identify taxonomically informative characters that could be used in the subdivision of this large genus. The study differs from previous studies in Heliophila because, in addition to macro-morphology, it employs micro- morphological (SEM) and palynological evidence to elucidate the subdivisio.n of Heliophila. The study emanates from a taxonomic revision of Heliophila proposed by Sander (1860), in which he subdivided the genus into six sections, based on the variation in fruit characters. Subsequent authors ignored the sections, regarding the generic subdivision as insufficiently supported, hence unsatisfactory . The results of cluster analysis, which are based on all the characters examined in the study (overall variation), propose the subdivision of Heliophila into three main clades: Micromorphological characters of fruits, seeds, and leaves are consistently found to be more congruent with the phenogram than macro-morphological characters of the same organs. This suggests that micro-morphological characters are taxonomically informative in Heliophila and should prove very important in a future phylogenetic classification of the genus. Palynological characters were found to be of limited taxonomic importance in the subdivision of the genus. / AFRIKAANSE OPSOMMING: Verskeie outeurs beskou die onderverdeling van die groot genus Heliophila as onbevredigend, en meen dat dit 'n gedetaileerde taksonomies studie benodig. Vorige studies op hierdie genus het slegs op ekstern morfologiese kenmerke gekonsentreer. In die huidige studie word patrone van variasie in Heliophila ondersoek met die oog op 'n moontlike onderverdeling van die genus, en taksonomies betek~nisvolle kenmerke wat in hierdie verband gebruik kan word, word geidentifiseer. Die huidige stud'e verskil van vorige studies daarin dat, benewens makro-morfologiese kenmerke, dit ook mikro-~rfologiese tegnieke (SEM) en palinologiese kenmerke gebruik om 'n sinvolle subverdeling van Heliophila te probeer vind. Die huidige studie spruit uit 'n taksonomiese hersiening van Heliophila deur Sonder (1860), waarin hy voorstel dat die genus in ses seksies verdeel word op grond van variasie in vrug kenmerke. Hierdie generiese onderverdeling en die voorgestelde seksies is deur latere outeurs as onbevredigend beskou, en is meestal in die literatuur geignoreer. Die resultate van fenetiese analise, wat op alle ingeslote kenmerke gebaseer is (algehele variasie), stel voor dat Heliophila in drie hoof groepe verdeel moet word. Taksonomies belangrike kenmerke wat hierdie onderverdeling ondersteun sluit in blaartipe, variasie in blaar-oppervlakke (SEM), variasie in die aard van die saadhuid (SEM) en variasie in vrugoppervlakke (SEM). Palinologiese en makro-morfologiese kenmerke was van geringe waarde in die onderverdeling van die genus.

UDC Summary (udcS) is a selection of around 2,000 UDC numbers intended for free use, training and research of the UDC, and is published as an online database at http://www.udcc.org/ udcsummary/php/index.php. This is the first time in the UDC’s history that the scheme has been made available to any extent for free use in so many languages as a single service. By the end of 2009, this abridged scheme was available in 13 languages and at the time of writing this report there are already over 20 languages online. The UDC Summary is available in languages in which the UDC has never been translated before such as Armenian, Greek, and Hindi.

The African Studies Centre (ASC) Leiden is an independent foundation associated with Leiden University. Its aims are to undertake research on Africa in the social sciences, to maintain a specialist library and documentation department, and to facilitate the dissemination of information on Africa. The library houses a broad-based collection in the field of the social sciences and the humanities, the only collection in the Netherlands focusing entirely on Africa. Current holdings include some 75,000 books, 2,000 periodicals, of which almost 600 are current subscriptions, about 1,000 documentaries and feature films, and a growing digital collection. Approximately half the holdings are English, about a third French, and the remainder is divided between German, Dutch, Afrikaans, Portuguese and Spanish. Between 2000 and 2006, the library carried out a project to improve subject access to the ASC collection by building an African Studies Thesaurus and converting all subject codes used until then into thesaurus descriptors.

鄧國章. / Thesis (M.A.)--香港中文大學硏究院地理學部. / Includes bibliographical references (leaves 215-228). / Deng Guozhang. / Thesis (M.A.)--Xianggang Zhong wen da xue yan jiu yuan di li xue bu. / Chapter 第一章 --- 導論 --- p.1 / Chapter 1.1 --- 研究目的 --- p.1 / Chapter 1.2 --- 研究意義 --- p.7 / Chapter 1.2.1 --- 方法學上的意義 --- p.7 / Chapter 1.2.2 --- 地理學上的意義 --- p.8 / Chapter 1.2.3 --- 應用上的意義 --- p.9 / Chapter 1.3 --- 研究範圍 --- p.10 / Chapter 1.4 --- 論文結構概述 --- p.12 / Chapter 第二章 --- 文獻簡讀 --- p.15 / Chapter 2.1 --- 分類與區劃的意義 --- p.15 / Chapter 2.1.1 --- 分類與區劃 --- p.15 / Chapter 2.1.2 --- 區域的類型 --- p.18 / Chapter 2.1.3 --- 區劃的方法　 --- p.23 / Chapter 2.2 --- 氣候分類 --- p.27 / Chapter 2.2.1 --- 氣候分類的目的及意義　　 --- p.27 / Chapter 2.2.2 --- 氣候分類的類型及方法 --- p.29 / Chapter 2.2.3 --- 柯本氏氣候分類法 --- p.31 / Chapter 2.3 --- 中國氣候區劃 --- p.41 / Chapter 2.3.1 --- 中國氣候區劃歷史概況 --- p.41 / Chapter 2.3.2 --- 應用柯本氏氣候分類法於中國氣候區劃的經驗 --- p.44 / Chapter 2.4 --- 糢糊集合論於分類及區畫間題上的應用 --- p.47 / Chapter 2.4.1 --- 糢糊集合論於分類及區劃上的應用 --- p.47 / Chapter 2.4.2 --- 糢糊集合論於氣候區劃的應用 --- p.50 / Chapter 第三章 --- 研究方法 --- p.53 / Chapter 3.1 --- 應用模糊集合論於氣候分類之理論基璴 　 --- p.53 / Chapter 3.1.1 --- 集合與區域 --- p.53 / Chapter 3.1.2 --- 模糊集合的基本概念及運算 --- p.54 / Chapter 3.2 --- 氣候區的釐訂及區域界綫的劃定方法 --- p.68 / Chapter 3.2.1 --- 氣候區的描述 --- p.68 / Chapter 3.2.2 --- 氣候區的重疊與分割 --- p.75 / Chapter 3.3 --- 數據資料處理方法 --- p.80 / Chapter 3.3.1 --- 數據搜集方法 --- p.80 / Chapter 3.3.2 --- 站點分佈情況 --- p.80 / Chapter 3.3.3 --- 資料整理方法 --- p.82 / Chapter 3.4 --- 注釋 --- p.85 / Chapter 第四章 --- 柯本氏氣候分類系統的普通集合表示 --- p.86 / Chapter 4.1 --- 柯本氏氣候類型可視一組集合 --- p.86 / Chapter 4.2 --- 結果及分析 --- p.96 / Chapter 第五章 --- 柯本氏氣侯分類之模楜集合分析－隸屬度分析 --- p.99 / Chapter 5.1 --- 訂定隸屬涵數方法及區劃步驟 --- p.99 / Chapter 5.2 --- 結果及隸屬度分析 　　 --- p.108 / Chapter 5.3 --- 中國氣候區的劃定 --- p.125 / Chapter 5.4 --- 小結 --- p.140 / Chapter 第六章 --- 柯本氏氣類之模糊集合分析－分割度分析 --- p.143 / Chapter 6.1 --- 分割與區界 --- p.143 / Chapter 6.2 --- 結果及分析 --- p.146 / Chapter 6.3 --- 中國氣候區重疊地帶的劃訂 --- p.155 / Chapter 6.4 --- 小結 --- p.166 / Chapter 6.5 --- 注釋 --- p.169 / Chapter 第七章 --- 柯本氏氣候分類法的改進 --- p.170 / Chapter 7.1 --- 柯本氏氣候分類法的改善 --- p.170 / Chapter 7.2 --- 改良後的柯本氏範式之中國氣候區劃 --- p.186 / Chapter 7.3 --- 與中國植被區的劃配合情況 　 --- p.186 / Chapter 7.4 --- 與中國土壤區劃的配合情況　　 --- p.194 / Chapter 第八章 --- 後語 --- p.208 / Chapter 8.1 --- 研究結果要點重申 --- p.208 / Chapter 8.2 --- 研究限制 --- p.210 / Chapter 8.3 --- 研究展望 --- p.213 / 參考文獻 --- p.215 / 附錄 / Chapter I --- 中國各省、市、自治區志面　 --- p.229 / Chapter II --- 柯氏氣候類型的隸屬函數 --- p.235 / Chapter III --- 電腦計算程式 --- p.254 / Chapter IV --- 隸屬度計算結果 --- p.259 / Chapter （一） --- 原本的柯本氏氣候類型的隸屬度計算結果 --- p.259 / Chapter （二） --- 改良後的柯本氏氣候類型的隸屬度計算結果 --- p.265

Bibliography: v. 1, leaves 277-300 / 2 v. : ill. (some col.) ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Zoology, 1987

In this paper, we present a automatic item classification system,called AICS. This system is according the content structure that are provided from the teacher for create a content tree. This content tree can correlate the item with content. The main works of AICS classify the item and find the most similar content. After than the system compute the relationship between the item and content, AICS can automatic compute the difficulty of item and examination. The work of this research has two categories: 1. The system can show the content that are related to the item and help the teacher understand the difficulty of the examination paper quickly. 2. When after the examination, the system provide the content for student understand the irrelevant items.

For the past twenty years, taxonomy has been in a state of turmoil. This confusion brings along with it four distinct schools of thought, each of which offers a different concept of biological species. The thesis will show that these concepts are purely operational and have only a weak theoretical force. In turn, it will be argued that a sound definition of species uses the notion of natural kinds, which is itself defined in term of non-causal nomological regularities.

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Ce manuscrit étudie plusieurs problèmes de classification sous contraintes. Dans ce cadre de classification, notre objectif est de construire un algorithme qui a des performances aussi bonnes que la meilleure règle de classification ayant une propriété souhaitée. Fait intéressant, les méthodes de classification de type plug-in sont bien appropriées à cet effet. De plus, il est montré que, dans plusieurs configurations, ces règles de classification peuvent exploiter des données non étiquetées, c'est-à-dire qu'elles sont construites de manière semi-supervisée. Le Chapitre 1 décrit deux cas particuliers de la classification binaire - la classification où la mesure de performance est reliée au F-score, et la classification équitable. A ces deux problèmes, des procédures semi-supervisées sont proposées. En particulier, dans le cas du F-score, il s'avère que cette méthode est optimale au sens minimax sur une classe usuelle de distributions non-paramétriques. Aussi, dans le cas de la classification équitable, la méthode proposée est consistante en terme de risque de classification, tout en satisfaisant asymptotiquement la contrainte d’égalité des chances. De plus, la procédure proposée dans ce cadre d'étude surpasse en pratique les algorithmes de pointe. Le Chapitre 3 décrit le cadre de la classification multi-classes par le biais d'ensembles de confiance. Là encore, une procédure semi-supervisée est proposée et son optimalité presque minimax est établie. Il est en outre établi qu'aucun algorithme supervisé ne peut atteindre une vitesse de convergence dite rapide. Le Chapitre 4 décrit un cas de classification multi-labels dans lequel on cherche à minimiser le taux de faux-négatifs sous réserve de contraintes de type presque sûres sur les règles de classification. Dans cette partie, deux contraintes spécifiques sont prises en compte: les classifieurs parcimonieux et ceux soumis à un contrôle des erreurs négatives à tort. Pour les premiers, un algorithme supervisé est fourni et il est montré que cet algorithme peut atteindre une vitesse de convergence rapide. Enfin, pour la seconde famille, il est montré que des hypothèses supplémentaires sont nécessaires pour obtenir des garanties théoriques sur le risque de classification / This manuscript studies several problems of constrained classification. In this frameworks of classification our goal is to construct an algorithm which performs as good as the best classifier that obeys some desired property. Plug-in type classifiers are well suited to achieve this goal. Interestingly, it is shown that in several setups these classifiers can leverage unlabeled data, that is, they are constructed in a semi-supervised manner.Chapter 2 describes two particular settings of binary classification -- classification with F-score and classification of equal opportunity. For both problems semi-supervised procedures are proposed and their theoretical properties are established. In the case of the F-score, the proposed procedure is shown to be optimal in minimax sense over a standard non-parametric class of distributions. In the case of the classification of equal opportunity the proposed algorithm is shown to be consistent in terms of the misclassification risk and its asymptotic fairness is established. Moreover, for this problem, the proposed procedure outperforms state-of-the-art algorithms in the field.Chapter 3 describes the setup of confidence set multi-class classification. Again, a semi-supervised procedure is proposed and its nearly minimax optimality is established. It is additionally shown that no supervised algorithm can achieve a so-called fast rate of convergence. In contrast, the proposed semi-supervised procedure can achieve fast rates provided that the size of the unlabeled data is sufficiently large.Chapter 4 describes a setup of multi-label classification where one aims at minimizing false negative error subject to almost sure type constraints. In this part two specific constraints are considered -- sparse predictions and predictions with the control over false negative errors. For the former, a supervised algorithm is provided and it is shown that this algorithm can achieve fast rates of convergence. For the later, it is shown that extra assumptions are necessary in order to obtain theoretical guarantees in this case

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