第一章緒論，含研究動機及目的，本文結構。第二章含Brown-Mood的迴歸參數估計法 ，修正後的估計法，檢定迴歸參數法，在虛無假設下的近似分配及信賴區間推定法。 第三章含Daniel的迴歸參數檢定法，檢定統計量的分配，獨立變數可重複下的修正檢 定統計量的分配。第四章提出依據殘差項符號為檢定標準的方法，檢定統計量的分配 、信賴區間，一些特殊情況與應用。第五章針對所提的三種方法一一比較、分析。第 六章結論。

在處理列聯表時，適合度檢定的結果如果是顯著的話，則意味著配適的模式並不恰當，這其中一個可能的原因是資料中存在離群細格．因此我們希望能夠針對問題癥結所在，找出離群細格，使得我們的資料可以利用一個比較簡單且容易解釋的模式來做分析．在這篇論文中，我們主要依據施苑玉[1995]所提出的方法作些許的改變，使得改進後的方法可以適用於三維列聯表的所有情形．此外我們也將 Simonoff 在1988年所提出的方法，以及 BMDP 統計軟體的程序 4F ，與我們所提出的方法相比較．由模擬實驗的結果可發現我們的方法比前述兩種方法更具可行性． / When fitting a loglinear model to a contingency table, a significant goodness-of-fit can be resulted because of the existence of a few outlyingcells. Since a simpler model is easier to interpret and conveys more easilyunderstood information about a table than a complicated one, we would liketo identify those outliers so that a simpler model would fit a given data set. In this research, a modification of Shih's [1995] procedure is provided, and the revised method is now applicable to any type of models related tothree-way tables. Some data sets are simulated to compare outliers detectedusing procedures proposed by Simonoff [1988], and BMDP program 4F with our proposed method. Based on the results through simulation, our revised procedure outperforms the other two procedures most of the time.

本文主旨是在使用有限元素法（包括第一、第二、第三限元素法）對一個燃燒熱能模型之邊界值微分方程式，求其數值近似。 　　首先，由這些方法可到一些聯立方程式。其次，對各種有限元素法分別去分析它們解的存在性和誤差估計。最後，舉一個實例來討論其解的變化情形並圖示它們。 　　換句話說，從本文所得到的方程組或圖形，將可求得此微分方程式的解與個數。 / The main topic of this paper is to usee the finite element methods (contain F.E.1, F.E.2, and F.E.3) to find the numerical approximation of a model for thermal ignition. First, we obtain a system of equations for those methods. And then, we analyse the existence and the error estimate of solutions with each method. At last, we give an example to discuss those results and graph them. In a word, from those equations or graphs which are given in this paper, we will get the numerical solution and the number of solutions.

抽取出音樂當中的近似重複樣式來做音樂檢索可以減少要比對的資料量，但是使用者若使用沒有重複的旋律來查詢便會有找不到歌曲的情況。另一方面，將音樂分段成phrase可以減少樹狀索引結構的空間，亦可減少查詢處理時間，但是使用者的查詢若是跨越phrase的，也將影響查詢結果。 在本論文中，我們比較了以近似重複樣式與phrase兩種不同的音樂特徵用來做音樂檢索的效果以及效率。根據實驗顯示，使用者的查詢是重複旋律的機會大於單一phrase，所以用近似重複樣式作為音樂查詢比對資料效果是比phrase好的。而在1-D List索引結構下，近似重複樣式的效率也優於phrase。除此之外，本論文也提出了一個新的近似重複樣式抽取方法，實驗證明我們的方法是有效的。 / Extract the approximate repeating pattern from music data will decrease the volumes of music data that need to be tested when music retrieve. If the user’s query is not a repeating melody, it can’t retrieve the music that the user wants correctly. In addition, segment the music by phrase will decrease the space that tree-like index structure need, and also decrease the retrieval processing time. If the user’s query is not a single phrase, it will influence the effectiveness of retrieval. In this thesis, we compare the effectiveness and efficiency of music retrieval methods with two different music features (approximate repeating pattern and phrase). According to experiment results, the probability that user’s query is repeating melody is more than the probability that user’s query is a single phrase. Therefore, we are of the opinion that the effectiveness that use approximate repeating pattern to process retrieval is more prominent than the effectiveness that phrase to process retrieval. Furthermore, the efficiency that use approximate repeating pattern to process retrieval is more outstanding than use phrase under 1-D List index structure. Besides, a new approximate repeating pattern extraction method is proposed. Experiment results show that our approximate repeating pattern extraction method can work correctly.

台灣英語教育多以考試取向為主，許多教師進行英語字彙指導時採用填鴨式教學，致使學生無法於新的情境靈活使用字彙。 本研究旨在於探究以語料庫為本之教學對於台灣大學生在英語近似詞學習成效的影響，以台北市某一所大學86位英語學習背景及能力相似之大一生為研究對象。研究人數均分成兩班進行教學實驗，一班為實驗組，以資料觀察法進行教學，另一班為對照組，以傳統形式教學為主，每週一次五十分鐘，共進行十週。資料蒐集包含近似詞學習成就測驗前、後測，並且依據研究對象於實驗教學結束後接受語料觀察教學法回饋問卷，蒐集研究對象對於語料觀察法之反應與感知，進行量化分析。最後，透過訪談高分組和低分組學生，蒐集其質性資料進行研究探討哪些因素會影響不同英語能力學生對於資料觀察法的意願與需求。本研究發現如下: 一、近似詞教學有助於提升台灣大學生的英語字彙能力。兩組教學均在後測有 進步。但就後測成績來說，實驗組顯著優於控制組。資料觀察法之近似詞教學 均較傳統教學法更能有效提升學生的英語字彙能力。 二、在不同程度的學生學習成效上，高、低分組學生均在後測成績有進步。對於 高分組而言，實驗組後測成績顯著優於控制組後測。但對於控制組而言，實驗 組的與控制組的後測成績未呈顯著差異。 三、大部分的學生對於運用資料觀察法學習單字均給予正面回饋，也肯定資料觀 察學習法活動的效益。另外，根據高、低分組學生訪談結果發現，英語程度的 高低的確會影響學生對於資料觀察法的喜愛和需求。高分組的學生希望先以資 料觀察學習法為開端，再以傳統講解式方式做總結。但對低分組的學生而言， 喜歡參與小組討論。由於單字量的不足，低分組學生希望在語料庫為主的教材 旁能附上中文解釋，降低學習焦慮。 根據上述研究結果，本研究建議大學英語教師在教學現場能夠融入語料觀察學 習法並依照不同程度的學生進行教材設計，以助提升學生學習英語單字。 關鍵字:資料觀察學習法、近似詞、語料庫為本 / Corpus Linguistics has progressively become the center in different domains of language research. With such development of large corpora, the potential applications and possibilities of corpora in second language teaching and learning are extended. A discovery-based authentic learning environment is provided as well as created by such corpus-based language learning. Synonym or near-synonym learning is a difficult aspect of vocabulary learning, but a linguistic phenomenon with ubiquity. Hence, this research aims to investigate the effectiveness of the application of data-driven learning (DDL) approach in near-synonyms instruction and compare the teaching effect on the high and low achievers through the near-synonyms instruction. Participants of this study were given instruction throughout the eight-week corpus-based teaching with materials compiled by the teacher. This is a quasi-experimental study consisting of comparison between two experimental conditions, with a pre-post test and control-experimental group design, followed by qualitative method of semi-structure interviews and questionnaire provided to the experimental group of EFL university students in Taiwan. Two intact classes of 86 college students participated in this study. The quantitative analysis of the pre- and posttest scores and questionnaire were conducted through descriptive statistics and frequency analysis in order to explain the learning effects and learners’ perceptions. The results of the study revealed that: (1) participants in the experimental group made significant improvement in the posttest; (2) EFL high proficiency learners with DDL approach performed better than high achievers who were taught by the traditional method. However, low achievers may not be able to benefit from DDL approach in the form of concordance teaching materials; (3) the majority of the participants had positive feedback on DDL activities. Also, types of preferred DDL activities were strongly influenced by students’ proficiency level. Low achievers preferred activities that should involve Chinese translation as the supplementary note while as for the high achievers, they were looking for the teacher’s explanation of words’ usages and functions in the end. This study demonstrates the importance in illuminating the dynamic relationship between DDL approach and second language near-synonyms learning, as well as provides English EFL teachers with a better concept to incorporate corpus or concordance lines into vocabulary instruction. Key words: data-driven Learning, near-synonym, corpus-based approach

国立情報学研究所で電子化したコンテンツを使用している。

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第18050号 / 理博第3928号 / 新制||理||1566(附属図書館) / 30908 / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)教授 佐々 真一, 准教授 篠本 滋, 准教授 武末 真二 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第20905号 / 理博第4357号 / 新制||理||1625(附属図書館) / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)教授 國廣 悌二, 教授 大西 明, 教授 川合 光 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

本研究旨在建立廣義線性模式下之D-與A-最適設計(optimal designs)，並依不同處理結構(treatment structure)分成完全隨機設計(completely randomized design, CRD)與隨機集區設計(randomized block design, RBD)兩部分探討。 根據完全隨機設計所推導出之行列式的性質與理論結果，我們首先提出一個能快速大幅限縮尋找D-最適正合(exact)設計範圍的演算法。解析解的部分，則從將v個處理的變異數分為兩類出發，建立其D-最適近似(approximate)設計，並由此發現 (1) 各水準對應之樣本最適配置的上下界並非與水準間不同變異有關，而是與有多少處理之變異相同有關；(2) 即使是變異很大的處理，也必須分配觀察值，始能極大化行列式值。此意味著當v較大時，均分應不失為一有效率(efficient)的設計。至於正合設計，我們僅能得出某一處理特別大或特別小時的D-最適設計，並舉例說明求不出一般解的原因。 除此之外，我們亦求出當三個處理的變異數皆不同時之D-最適近似設計，以及v個處理皆不同時之A-最適近似設計。 至於最適隨機集區設計的建立，我們的重點放在v=2及v=3的情形，並假設集區樣本數(block size)為給定。當v=2時，各集區對應之行列式值不受其他集區的影響，故僅需依照完全隨機設計之所得，將各集區之行列式值分別最佳化，即可得出D-與A-最適設計。值得一提的是，若進一步假設各集區中兩處理變異的比例(>1)皆相同，且集區大小皆相同，則將各處理的「近似設計下最適總和」取最接近的整數，再均分給各集區，其結果未必為最適設計。當v=3時，即使只有2個集區，行列式也十分複雜，我們目前僅能證明當集區內各處理的變異相同時(不同集區之處理變異可不同)，均分給定之集區樣本數為D-最適設計。當集區內各處理的變異不全相同時，我們僅能先以2個集區為例，類比完全隨機設計的性質，舉例猜想當兩集區中處理之變異大小順序相同時，各處理最適樣本配置的多寡亦與變異大小呈反比。由於本研究對處理與集區兩者之效應假設為可加，因此可合理假設集區中處理之變異大小順序相同。 / The problem of finding D- and A-optimal designs for the zero- and one-way elimination of heterogeneity under generalized linear models is considered. Since GLM designs rely on the values of parameters to be estimated, our strategy is to employ the locally optimal designs. For the zero-way elimination model, a theorem-based algorithm is proposed to search for the D-optimal exact designs. A formula for the construction of D-optimal approximate design when values of unknown parameters are split into two, with respective sizes m and v-m, are derived. Analytic solutions provided to the exact counterpart, however, are restricted to the cases when m=1 and m=v-1. An example is given to explain the problem involved. On the other hand, the upper bound and lower bound of the optimal number of replicates per treatment are proved dependent on m, rather than the unknown parameters. These bounds imply that designs having as equal number of replications for each treatment as possible are efficient in D-optimality. In addition, a D-optimal approximate design when values of unknown parameters are divided into three groups is also obtained. A closed-form expression for an A-optimal approximate design for comparing arbitrary v treatments is given. For the one-way elimination model, our focus is on studying the D-optimal designs for v=2 and v=3 with each block size given. The D- and A-optimality for v=2 can be achieved by assigning units proportional to square root of the ratio of two variances, which is larger than 1, to the treatment with smaller variance in each block separately. For v=3, the structure of determinant is much more complicated even for two blocks, and we can only show that, when treatment variances are the same within a block, design having equal number of replicates as possible in each block is a D-optimal block design. Some numerical evidences conjecture that a design satisfying the condition that the number of replicates are inversely proportional to the treatment variances per block is better in terms of D-optimality, as long as the ordering of treatment variances are the same across blocks, which is reasonable for an additive model as we assume.

在處理列聯表(Contingency table)資料時，一般我們常用卡方適合度檢定(chi-squared goodess-of-fit test)來判定模式配適的好壞。如果這個檢定是顯著的，則意謂著配適的模式並不恰當，我們則希望進一步探討可能的原因何在。這其中的一個可能原因是資料中存在所謂的離群細格(outlying cell)，這些細格的觀測次數和其他細格的觀測次數呈現某種不一致的現象。 　　在以往的文獻中，離群細格的偵測，通常藉由不同定義的殘差(residual)作為工具，進而衍生出各種不同的偵測方法。只是，這些探討基本上僅局限於二維列聯表的情形，對於高維度的列聯表，並沒有作更進一步的詮釋。Brown (1974)提出一個逐步偵測的方法，可依序找出所有可能的離群細格，直到近似獨立(quasi-independence)的模式假設不再顯著為止。但是我們認為他所引介的這個方法所牽涉的計算程序似乎過於繁複，因此藉由簡化修改計算過程，我們提供了另一種離群細格偵測的方法。依據模擬實驗的結果發現，本文所介紹的方法與Brown的方法作比較只有過之而無不及。此外我們也探討了應用此種方法到三維列聯表的可行性和可能遭遇到的困難。 / Chi-squared goodness-of-fit tests are usually employed to test whether a model fits a contingency table well. When the test is significant, we would then like to identify the sources that cause significance. The existence of outlying cells that contribute heavily to the test statistic may be one of the reasons. 　　Brown (1974) offered a stepwise criteria for detecting outlying cells in two-way con-tingency tables. In attempt to simplify the lengthy calculations that are required in Brown's method, we suggest an alternative procedure in this study. Based on simulation results, we find that the procedure performs reasonably well, it even outperforms Brown's method on several occasions. In addition, some extensions and issues regarding three-way contingency tables are also addressed.