京都大学 / 0048 / 新制・課程博士 / 博士(法学) / 甲第22204号 / 法博第237号 / 新制||法||167(附属図書館) / 京都大学大学院法学研究科法政理論専攻 / (主査)教授 服部 高宏, 教授 船越 資晶, 准教授 近藤 圭介 / 学位規則第4条第1項該当 / Doctor of Laws / Kyoto University / DGAM

本文主要是研究統計理論中的聯立信賴區間估計法，針對雙特徵數的指數母體，研究 位置特徵數的差異狀況。也就是要找出位置特徵數的所有複合比，所有對比的聯立信 賴區間。全文共分四章。第一章緒論，說明研究動機、目的及方法。第二章指數分布 的順序統計式，由於本文所使用的估計方法會使用到順序統計式，所以在本章中特別 研究順序統計式的某些線性組合，找出某些特殊的性質；並且將Tanis （１９６３） 提出的理論擴展至第二型設限數據。第三章位置特徵數的聯立信賴區間，藉由第二章 中導出的定理以Tukey 法及Holder不等式法找出聯立信賴區間，並且比較這些方法的 優劣。第四章結論及建議。全文共一冊，約兩萬字。

專家系統自1965年發展至今，其發展是與日遽增，在邁入二十一世紀這個新紀元，傳統的專家系統遭遇到不同以往的問題，不僅處理的問題複雜度提高之外，在建置系統的過程中需要更多專家提供其寶貴的意見，以期讓系統在處理問題的層面能更加寬廣及增進其彈性和效用。因此，多專家系統能夠解決傳統上單一專家先天上的限制。Gaines和Shaw於1989年在其論著中指出，利用一群專家的知識來發展專家系統其效益比單一專家來的更好。 然而，在多專家的專家系統中會產生案例選取的衝突，過去大都依賴人為的經驗法則判斷。如此一來，不僅在處理的時間成本上產生耗損，其選取案例的公信力亦容易令人產生存疑。此外在相關的研究上，絕大多數都未對於此一衝突提出另外一套較具公正性的解決辦法。 針對此一現象，本研究發現欲解決其中之案例衝突，可以藉由群體決策和多評準決策領域中尋求解決之辦法，透過本研究一連串的文獻蒐集與探討，得到Nemawashi決策模式可以加以導入應用，因此，本研究嘗試引用案例式推論（Case-Base Reasoning）、Nemawashi 決策模式，提出一個整合多專家的意見和解決其案例產生衝突的方法。 / Expert system has been in speeding development since 1965. With the advent of the 21st century, the traditional expert system is encountering problems different from the past. With the rising complexity of nowadays problems, it requires valuable opinions from more professionals in the construction of expert system. The multi-expert knowledge can not only broaden the scope in which the system handles problems, but also enhance the system’s flexibility and efficiency. Thus, multi-expert system outsmarts the conventional expert system which is restricted by the voice of a single expert. Gaines and Shaw in 1989 commented that the expert system was better quipped with a group of experts than with one single expert. Nevertheless, multi-expert system contains the problem of case conflict. To undermine the conflict, it is common for people to resort to experts’ judgments and their personal experiences. Consequently, the multi-expert system has the disadvantage of consuming time in the process of case selection. Moreover, the case selected out of this process may be unconvincing due to its overdependence on human decisions. As to the problem of case conflict, most of the researches related to multi-expert system do not propose other more objective solutions. Focus on the problem mentioned above, this study tends to solve case conflict through the use of Group Decision and Multiple Criteria Decision-Making (MCDM). After the collection and analysis of data, the study finds out that Nemawashi Decisions are effective in handling the problem of case conflict. Thus, this study attempts to apply Nemawashi Decisions in Case-Base Reasoning in order to combine opinions from different experts and to solve the case conflict in the multi-expert system.

AspectFun是一個實驗性的剖面導向函式語言，它主要的特色在於具備能以靜態織入方式實現的多型剖面、高階剖面以及依據動態流程觸發的剖面。 本論文提出一個AspectFun語言的編譯器，其編譯過程分為四個主要步驟：語法結構轉換、剖面織入、剖面轉函式與整合動態流程判斷資訊。其中剖面織入是最複雜的步驟，必須仰賴可能是多型的型態資訊，選取適當的剖面整合到程式指定的切點處。這部份的織入工作，我們的編譯器是依據一套以靜態型態推論規則發展而來的轉譯規則，先將AspectFun程式轉譯成的剖面與函式整合在一起的中介格式，再翻譯為可執行的Haskell程式來完成。此外，本系統也是使用Haskell程式語言開發，並採用Monad技術將系統模組化，以達到最佳的可維護性、擴充性與閱讀性。本論文介紹系統的實作面，解釋AspectFun系統架構、語法、原理和實作帶來的貢獻以及限制。 / AspectFun is an experimental aspect-oriented functional language. Its main features include polymorphic aspects via static weaving, second-order aspects and control-flow triggered aspects. This thesis presents a type-directed compiler for AspectFun. Our compilation processes consists of four major steps: syntax de-sugaring, aspect weaving, translating aspects to normal functions, and integrating control flow information. The most complicated one is aspect weaving. Due to polymorphism in aspects, it is completely dependent on type information inferable from the aspects and the context they are used. We base our weaving step on a set of type-directed translation rules. In particular, the weaving step is further divided into two stages. First, an AspectFun program is translated into an intermediate form in which all aspects applicable at a context are chained together and integrated with context. Second, all aspects are translated into ordinary functions and any chain of aspects are transformed to a sequence of function calls in as an executable Haskell program. Moreover, the complier itself is implemented in Haskell. We fully utilize the monad mechanism of Haskell to modularize our compiler and achieve the goals of good maintainability, extensibility and readability.

近年來，由於網際網路的興起，網際網路已成為新聞媒體重要的傳播管道之一，許多新聞網站如雨後春筍般的成立，而讀者也樂於使用這類更加便利、高互動性的新聞網站。但是媒體使用網路作為傳播管道，同時也面臨在傳統傳播模式所未遭遇的新挑戰，網路新聞媒體被迫需要創造獨特的內容吸引使用者，也需發展具黏性的社群經營服務，才能與其他具有類似社群互動機制的Web 2.0網站一較長短，留住廣大的使用者群。 本研究嘗試利用新聞為日常生活人們獲得資訊不可或缺管道的獨特優勢，提出一套有效利用新聞使用社群集體智慧(Collective Intelligence）機制，能夠自動化依據使用者顯隱性回饋，針對每篇新聞分析出分歧度、熱門度、話題性三個社群資訊，並以上述三個社群資訊挑選出合適的焦點新聞，以此促進新聞社群使用者對於焦點新聞的討論與互動，進而提昇新聞傳播的效益與新聞社群的凝聚力。實驗結果證實，本研究所提出的機制確實能夠探勘出滿足大多數使用者關注焦點新聞資訊的需求，並且對於輔助記者掌握讀者對於新聞資訊需求及促進新聞社群經營方面都有很大的助益。 / In recent years, due to the rise of the information and communication technologies, the internet has become one of most important communication channel for Journalism. A long with drastically flourished on-line Journalism, models of readers’ information reception changed while they are enjoyed more convenient and interactive websites providing instant information. At the same time, while mass media utilize internet as communication channel, it has also brought unprecedented challenge to traditional communication. On-line Journalism has not only need to create unique content (information) to attract readers; but it also need to develop a more engaging community management services to interact with other communities with similar mechanisms of Web 2.0 sites to retain user’s attention. This study attempts to exam the proposed on-line journalism system for University Press community, which could automatically analyze readers’ community dataset of University newspaper; including opinion deviation indicators, popularity indicator, and topicality indicator of each news (information). This system selects targeted news (information) according to above indicators to promote discussion and interactivity within readers’ community in hope to promote efficiency of news (information) communication and engagement within readers’ community. Experiment results reveal this proposed mechanism could satisfy most readers’ need for headline news; as well as assist Journalists’ understanding on their readers’ need while promoting on-line journalism social networking management.

由於目前政治版圖的研究仍停留在資料描述的階段，描述選票在地理區域差異的程度，較缺乏定性與定量以及理論建構的研究。所以本文打算從政治版圖分析出發，借由一些探索性的研究，嘗試將政治版圖的概念操作化，並嘗試去解釋影響政治版圖變動的因素。本文想要探索的目標有三個，第一：政治版圖的定義，包含的面向，以及測量的方法。第二：嘗試結合目前國內由總體資料從事選舉研究的兩種分析方法－集群分析以及區位推論模型(Ecological Inference Model)。第三：嘗試結合個體資料以及總體資料研究途徑，藉由個體資料研究途徑中投票行為研究所累積的研究發現，解釋政治版圖這個現象。 本文從政治版圖的強度與穩定度兩個面向出發，以台北縣三次立委選舉(1995、1998、2001)為例，分析各政黨政治版圖的變動。並以投票行為研究中影響選民投票決定的三個主要因素：政黨認同、議題取向、候選人評價等因素來解釋政黨政治版圖的強弱以及穩定與變遷。

本文之研究旨在應用貝氏方法，并配合經濟計量模型體系，以探討為使達成預定目標 ，而期望損失為最小情形下之控制變數最適控制值的決定。全文共分為五章，玆分別 扼要說明如下： 第一章緒論計分三節分別就從事本研究的研究動機與目的、研究方法、及研究範圍與 限制作一敘述。 第二章貝氏推論之研討計分五節。為探討貝氏方法在統計推論上之應用，本章將依序 就其立論根據，事前、事後情報來源，推定及其應用作一詳細的介紹。 第三章共分為五節就應用貝氏方法求解最適控制值的理論部份逐次加以探討。於第四 章中將就依此方法，嘗以臺灣實際的個案作一實例應用，以求解強力貨幣在70年第二 季至71年第三季等六季之最適控制值。并就所得結果作一檢討，而作成第五章之結論 。

首先我要譴責你！就是你！正在看這本論文打算印這篇摘要的你！ 我知道你懶得看完整本論文，所以只想印這篇摘要應付了事， 哈！我偏不寫，看你怎麼辦？！ 其實這篇論文整本都是精華，字字珠璣，是無法摘要的。

本研究發展可以在任意網頁上進行閱讀標註之合作式閱讀標註系統，並透過探勘集體智慧方式，在合作式閱讀標註系統上發展「優質標註萃取」及「達人標註萃取」機制，來輔助學習者進行數位文本閱讀學習，以達到提昇閱讀理解成效的目的。此外，本研究也進一步探討透過「優質標註萃取」及「達人標註萃取」機制過濾掉一部份品質較差的標註，是否可有效降低閱讀標註文本時產生的認知負荷。 本研究將學習者分成實驗組1（達人標註）、實驗組2（優質標註）與控制組（所有標註）三組，並分別進行約80分鐘的合作式閱讀標註學習活動。其中控制組的成員採用「呈現所有標註之合作式閱讀標系統」支援閱讀學習；而實驗組1的成員則透過「呈現達人標註之合作式閱讀標註系統」來進行閱讀學習；實驗組2則透過「呈現優質標註之合作式閱讀標註系統」來進行閱讀學習。合作式閱讀標註活動要求學習者在指定時間內閱讀本研究指定的文本（化學科普之文章），同時利用「合作式閱讀標註系統」進行閱讀標註撰寫與分享。閱讀標註活動結束後，學習者將進行所閱讀文本之閱讀理解評量以及認知負荷量表填寫，據此瞭解學習者的閱讀理解成效及認知負荷程度。 研究結果顯示，採用具有「優質標註萃取」機制所得標註支援閱讀學習，有助於過濾品質不佳的閱讀標註，並提供更簡潔易找尋之優質標註支援閱讀學習，進而提昇閱讀理解成效，由於閱讀時更容易找到所需的優質資訊，因此亦較有助於提昇學習者不同面向概念的閱讀理解成效；此外，本研究基於每位學習者的有效標註，在考量標註層次及標註數量下，評估每位學習者的“標註能力”，採用優質標註支援閱讀學習的實驗組2（優質標註）學習者中，標註能力越高的學習者，其閱讀理解成效也較佳；而本研究將學習者依照閱讀理解後測成績高低，分成高分組及低分組後顯示，控制組（所有標註）與實驗組2（優質標註）的組別中，均呈現出低分組學習者的認知負荷顯著高於高分組學習者的現象；除此之外，本研究比較三組採用不同標註呈現方式之合作式閱讀標註系統進行閱讀學習之學習者時，結果發現，採用三種不同閱讀標註呈現方式組別學習者之認知負荷無顯著差異。 最後，本研究歸納研究者在研究過程及結果中之發現，提出發展結合合作式閱讀標註的有效閱讀學習策略、探討各類型標註眼動行為對於閱讀理解成效影響與擴展合作式閱讀標註系統支援行動閱讀學習等未來研究議題之初步架構，供後續研究參考以進行更深入之探究。 / A Collaborative Reading Annotation System, which can be randomly proceeded reading annotations on any web pages, is developed in this study. Furthermore, Quality Annotation Extraction and Master Annotation Extraction are developed on the Collaborative Reading Annotation System by mining collective intelligence for assisting learners in proceeding reading digital texts and promoting the reading comprehension performance. The effect of removing some bad-quality annotations through Quality Annotation Extraction and Master Annotation Extraction on reducing the cognitive load when reading annotation texts is further discussed in this study. The learners are divided into Experiment Group 1 (Master Annotation), Experiment Group 2 (Quality Annotation), and Control Group (All Annotation) for 80-minute collaborative reading annotation learning. Control Group uses Collaborative Reading Annotation System with all annotations for promoting reading; Experiment Group 1 proceeds reading through Collaborative Reading Annotation System with master annotations; and, Experiment Group 2 applies Collaborative Reading Annotation System with quality annotations to reading. The learners are requested to read the assigned texts (articles of popular science in chemistry) in the assigned period and write and share the reading annotations with the Collaborative Reading Annotation System. Afterwards, the learners are evaluated the reading comprehension of the texts and fill in the cognitive load scale for understanding the reading comprehension performance and the cognitive load. The research results show that utilizing the annotations acquired by Quality Annotation Extraction for promoting reading could filter out unfavorable reading annotations and provide quality annotations, which are more easily searched for promoting reading, to further enhance the reading comprehension performance. Since the quality information can be more easily searched, it could better assist learners in promoting reading comprehension performance in various aspects. Moreover, based on the valid annotations of each learner, the annotation ability is evaluated the annotation level and quantity. Learners with higher annotation ability in Experiment Group 2 (Quality Annotation) present better reading comprehension performance. Based on the reading comprehension post-test results, the learners are divided into high-score and low-score groups. The cognitive load of low-score learners in both Control Group (All Annotation) and Experiment Group 2 (Quality Annotation) is higher than it of high-score learners. Besides, the cognitive load among the three groups applying the Collaborative Reading Annotation System with different annotations to reading does not appear significant differences. Finally, developing effective reading strategies with Collaborative Reading Annotation, discussing the effects of various annotations on reading comprehension performance, and expanding Collaborative Reading Annotation System for promoting mobile reading are proposed as the preliminary framework for future research, with which in-depth exploration could be preceded in successive research.

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