• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 1
  • 1
  • 1
  • Tagged with
  • 2
  • 2
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Visuell hierarki och läsmönster : en studie om kontrast, storlek och positionering

Sova, Jemi, Karim, Bobby January 2013 (has links)
Syftet med denna uppsats är att identifiera den mest effektiva egenskapen av en text eller sida för att uppnå visuell hierarki, som är ett verktyg för att få det önskade flödet av uppmärksamhet i en sida eller webbsida genom att ge vissa element en viss vikt i kontrast, storlek och placering. Vi vill ge en möjlighet för vidare forskning snarare än att ge en slutsats som ger ett slutgiltigt svar på frågeställningarna. Det finns fler sätt att manipulera text för att uppnå önskad visuell hierarki men vi valde de vanligaste. Detta arbete är baserat på ett experiment som görs på 50 deltagare med ett onlinefrågeformulär och tre självgjorda bilder där vi kan utvärdera resultaten, jämföra dem med andra teorier och beräkna den mest effektiva uppmärksamhetsgivaren. Vi har också utvecklat en hypotes om vad resultatet kommer att visa. Vår studie föreslår att kontrasten i färg kan vara den viktigaste faktorn för att uppnå och upprätthålla visuell hierarki. / The purpose of this paper is to identify the most effective property of a text or a page to achieve visual hierarchy, which is a tool for getting the desired flow of attention in a page or a web page by giving certain elements a degree of weight in contrast, size and positioning.We want to give an opportunity for further research rather than an absolute conclusion of how it really is. There are more ways to manipulate text to achieve the desired visual hierarchy but we choose the most common. This paper is based on an experiment involving 50 participants with an online questionnaire and three self-made pictures where we will evaluate the results, compare them with other theories and calculate the most effective enhancer of attention. We have also developed a hypothesis on what the results will show. Our study proposes that contrast in color might be the most important factor to achieve and maintain visual hierarchy.
2

基於眼動軌跡之閱讀模式分析 / Classification of reading patterns based on gaze information

張晉文, Chang, Chin Wen Unknown Date (has links)
閱讀是吸收知識的途徑,不同的閱讀模式所帶來的閱讀成效也會不同。如何透過機器學習的方式,從凝視點找出閱讀行為的關聯性,將是本研究的目標。實驗選擇低成本眼動儀紀錄讀者閱讀過程中的眼動資料,採用dispersion-based演算法找出凝視點,以計算凝視點特徵,包含凝視時間、凝視距離、凝視位置以及凝視方向。 本研究將閱讀模式分成五種類別,包含快讀、慢讀、精讀、跳讀與關鍵字識別,透過不同文章的呈現,引導30位測試者遵循其內容進行閱讀,藉此收集不同行為模式的眼動資料。實驗流程中所有的眼動資料會隨機被分成為兩份,依序建立不同維度的訓練資料,由交叉驗證的分類結果找出理想之特徵與維度。以每次挑選6位測試者的眼動數據為測試資料進行5次分類驗證,其平均正確率為78.24%、74.19%、93.75%、87.96%以及96.20%,均達到不錯的分類結果。 / Reading is one of the paths to acquire knowledge. The efficiency is different when different reading patterns are involved. It is the objective of this research to classify reading patterns from fixation data using machine learning techniques. In our experiment, a low-cost eye tracker is employed to record the eye movements during the reading process. A dispersion-based algorithm is implemented to identify fixation from the recorded data. Features pertaining to fixation including duration, path length, landing position and fixation direction are extracted for classification purposes. Five categories of reading pattern are defined and investigated in this study, namely, speed reading, slow reading, in-depth reading, skim-and-skip, and keyword spotting. We have recruited thirty subjects to participate in our experiment. The participants are instructed to read different articles using specific styles designated by the experimenter in order to assign label to the collected data. Feature selection is achieved by analyzing the predictive results of cross-validation from the training data obtained from all subjects. The average classification accuracies in five-fold cross-validation are 78.24%, 74.19%, 93.75%, 87.96% and 96.20% using the eye movements of the six randomly selected subjects as test data.

Page generated in 0.0687 seconds