Sin Ka Wai. / Thesis (M.Sc.)--Chinese University of Hong Kong, 1992. / Includes bibliographical references (leaves [81]-[82]). / PREFACE / ABSTRACT / CONTENT / Chapter §1. --- INTRODUCTION / Chapter §1.1 --- The Chinese language --- p.1 / Chapter §1.2 --- Chinese information processing system --- p.2 / Chapter §1.3 --- Chinese character recognition --- p.4 / Chapter §1.4 --- Multi-stage tree classifier Vs Single-stage tree classifier in Chinese character recognition --- p.6 / Chapter §1.5 --- Decision Tree / Chapter §1.5.1 --- Basic Terminology of a decision tree --- p.7 / Chapter §1.5.2 --- Structure design of a decision tree --- p.10 / Chapter §1.6 --- Motivation of the project --- p.12 / Chapter §1.7 --- Objects of the project --- p.14 / Chapter §1.8 --- Development environment --- p.14 / Chapter §2. --- APPROACH 1 - UNSUPERVISED LEARNING / Chapter §2.1 --- Idea --- p.15 / Chapter §2.2 --- Feature Extraction / Chapter §2.2.1 --- Feature selection criteria --- p.15 / Chapter §2.2.2 --- 4C code --- p.20 / Chapter §2.2.3 --- Regional code --- p.22 / Chapter §2.2.4 --- Walsh Transform --- p.24 / Chapter §2.2.5 --- Black dot density projection profile --- p.26 / Chapter §2.2.6 --- Corner features --- p.28 / Chapter §2.3 --- Clustering Method -K-MEANS & Other Algorithms --- p.32 / Chapter §2.4 --- Pros & Cons --- p.35 / Chapter §2.5 --- Decision Table --- p.37 / Chapter §2.6 --- The Optimum Classifier & its Implemen- tation difficulties --- p.39 / Chapter §3. --- APPROACH 2 - SUPERVISED LEARNING --- p.43 / Chapter §4. --- POSSIBLE IMPROVEMENT / Chapter §4.1 --- Training and Test Sample Reduction --- p.46 / Chapter §4.2 --- Noise Filtering --- p.46 / Chapter §4.3 --- Decision with Overlapping --- p.52 / Chapter §4.4 --- Back Tracking for Holes --- p.56 / Chapter §4.5 --- Fuzzy Decision with Tolerance Limit --- p.59 / Chapter §4.6 --- Different Tree Architecture --- p.63 / Chapter §4.7 --- Building Decision Tree by Entropy Reduction Method --- p.65 / Chapter §5. --- EXPERIMENTAL RESULTS & THE IMPROVED MULTISTAGE CLASSIFIER / Chapter §5.1 --- Experimental Results --- p.70 / Chapter §5.2 --- Conclusion --- p.81 / Chapter §6. --- IMPROVED MULTISTAGE TREE CLASSIFIER / Chapter §6.1 --- The Optimal Multistage Tree Classifier --- p.83 / Chapter §6.2 --- Performance Analysis --- p.84 / Chapter §7. --- FURTHER DISCRIMINATION BY CONTEXT CONSIDERATION --- p.87 / Chapter §8. --- CONCLUSION / Chapter §8.1 --- Advantage of the Classifier --- p.89 / Chapter §8.2 --- Limitation of the Classifier --- p.90 / Chapter §9. --- AREA OF FUTURE RESEARCH AND IMPROVEMENT / Chapter §9.1 --- Detailed Analysis at Each Terminal Node --- p.91 / Chapter §9.2 --- Improving the Noise Filtering Technique --- p.92 / Chapter §9.3 --- The Use of 4 Corner Code --- p.93 / Chapter §9.4 --- Increase in the Dimension of the Feature Space --- p.95 / Chapter §9.5 --- 1-Tree Protocol with Entropy Reduction --- p.96 / Chapter §9.6 --- The Use of Human Intelligence --- p.97 / APPENDICES / Chapter A.1 --- K-MEANS / Chapter A.2 --- Maximum Distance Algorithm & ISODATA Algorithm / Chapter A.3 --- Approach Two - Supervised Learning / Chapter A.4 --- Theories on Statistical Discriminant Analysis / Chapter A.5 --- An Example of Misclassification Table / Chapter A.6 --- "Listing of the Program ""CHDIS.C""" / Chapter A.7 --- Further Discrimination by Context Consideration / Chapter A.8 --- Passage used in Testing the Performance of the Classifier with Context Consideration / Chapter A.9 --- A Partial List of Semantically Related Chinese Characters / REFERENCE

Suen Tow Sunny. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 65-67). / Introduction --- p.1 / Chapter 1. --- ACCESS with an Extendible User-friendly X/Chinese Interface --- p.4 / Chapter 1.1. --- System requirement --- p.4 / Chapter 1.1.1. --- User interface issue --- p.4 / Chapter 1.1.2. --- Development issue --- p.5 / Chapter 1.2. --- Development decision --- p.6 / Chapter 1.2.1. --- X window system --- p.6 / Chapter 1.2.2. --- X/Chinese toolkit --- p.7 / Chapter 1.2.3. --- C language --- p.8 / Chapter 1.2.4. --- Source code control system --- p.8 / Chapter 1.3. --- System architecture --- p.9 / Chapter 1.4. --- User interface --- p.10 / Chapter 1.5. --- Sample screen --- p.13 / Chapter 1.6. --- System extension --- p.14 / Chapter 1.7. --- System portability --- p.18 / Chapter 2. --- Study on Algorithms for Automatically Correcting Characters in Chinese Cangjie-typed Text --- p.19 / Chapter 2.1. --- Chinese character input --- p.19 / Chapter 2.1.1. --- Chinese keyboards --- p.20 / Chapter 2.1.2. --- Keyboard redefinition scheme --- p.21 / Chapter 2.2. --- Cangjie input method --- p.24 / Chapter 2.3. --- Review on existing techniques for automatically correcting words in English text --- p.26 / Chapter 2.3.1. --- Nonword error detection --- p.27 / Chapter 2.3.2. --- Isolated-word error correction --- p.28 / Chapter 2.3.2.1. --- Spelling error patterns --- p.29 / Chapter 2.3.2.2. --- Correction techniques --- p.31 / Chapter 2.3.3. --- Context-dependent word correction research --- p.32 / Chapter 2.3.3.1. --- Natural language processing approach --- p.33 / Chapter 2.3.3.2. --- Statistical language model --- p.35 / Chapter 2.4. --- Research on error rates and patterns in Cangjie input method --- p.37 / Chapter 2.5. --- Similarities and differences between Chinese and English typed text --- p.41 / Chapter 2.5.1. --- Similarities --- p.41 / Chapter 2.5.2. --- Differences --- p.42 / Chapter 2.6. --- Proposed algorithm for automatic Chinese text correction --- p.44 / Chapter 2.6.1. --- Sentence level --- p.44 / Chapter 2.6.2. --- Part-of-speech level --- p.45 / Chapter 2.6.3. --- Character level --- p.47 / Conclusion --- p.50 / Appendix A Cangjie Radix Table --- p.51 / Appendix B Sample Text --- p.52 / Article 1 --- p.52 / Article 2 --- p.53 / Article 3 --- p.56 / Article 4 --- p.58 / Appendix C Error Statistics --- p.61 / References --- p.65

by Lam Chin-keung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 129-135 (2nd gp.)). / ACKNOWLEDGMENTS --- p.I / ABSTRACT --- p.II / TABLE OF CONTENTS --- p.III / LIST OF FIGURES --- p.VI / LIST OF TABLES --- p.VIII / Chapter CHAPTER 1 --- INTRODUCTION --- p.1 / Chapter 1.1 --- Motivations --- p.1 / Chapter 1.2 --- Objectives --- p.3 / Chapter 1.3 --- More to go --- p.3 / Chapter 1.4 --- Chapter Summary --- p.4 / Chapter CHAPTER 2 --- RELATED WORK --- p.6 / Chapter 2.1 --- Chinese Related Work --- p.6 / Chapter 2.1.1 --- Chinese Natural Language --- p.6 / Chapter 2.1.2 --- Chinesized Query Language From English --- p.7 / Chapter 2.2 --- High Level Database Query Language --- p.8 / Chapter 2.2.1 --- Relational Algebra vs Relational Calculus --- p.9 / Chapter 2.2.2 --- Procedural vs Declarative --- p.10 / Chapter 2.2.3 --- Natural Language (NL) vs Restricted Natural Language (RNL) --- p.11 / Chapter 2.3 --- Database Query Interface --- p.13 / Chapter 2.3.1 --- Linear Textual Interface --- p.13 / Chapter 2.3.2 --- Form-based Interface --- p.14 / Chapter 2.3.3 --- Graphical Interface --- p.14 / Chapter 2.4 --- Remarks --- p.14 / Chapter CHAPTER 3 --- DESIGN PRINCIPLES --- p.16 / Chapter 3.1 --- Underlying Data Model of the new language --- p.16 / Chapter 3.2 --- Problems Under Attack --- p.17 / Chapter 3.2.1 --- Naturalness --- p.17 / Chapter 3.2.2 --- Procedural vs Declarative --- p.19 / Chapter 3.2.3 --- Supports of Chinese Characters --- p.21 / Chapter 3.3 --- Design Principles --- p.22 / Chapter 3.4 --- Chapter Summary --- p.26 / Chapter CHAPTER 4 --- LANGUAGE DEFINITION --- p.28 / Chapter 4.1 --- Language Overvew --- p.28 / Chapter 4.2 --- The Data Manipulation Language --- p.29 / Chapter 4.2.1 --- Relational Operators --- p.30 / Chapter 4.2.2 --- Rail-Track Diagram of Chiql --- p.32 / Chapter 4.2.3 --- The 11-template --- p.33 / Chapter 4.2.4 --- Chiql Examples --- p.37 / Chapter 4.2.5 --- Common Language Constructs --- p.39 / Chapter 4.2.6 --- ONE issue about GROUP BY and RESTRICTION --- p.41 / Chapter 4.3 --- Other Language Features --- p.42 / Chapter 4.3.1 --- Aggregate Functions --- p.43 / Chapter 4.3.2 --- Attribute Alias --- p.44 / Chapter 4.3.3 --- Conditions in Chinese --- p.45 / Chapter 4.3.4 --- Unquantifed Predicates --- p.45 / Chapter 4.3.5 --- sorting --- p.47 / Chapter 4.4 --- Treatment of Quantified Predicates --- p.48 / Chapter 4.5 --- The Data Definition Language --- p.52 / Chapter 4.5.1 --- Create Table --- p.52 / Chapter 4.5.2 --- Drop Table --- p.54 / Chapter 4.5.3 --- Alter Table --- p.54 / Chapter 4.5.4 --- Insert Row --- p.56 / Chapter 4.5.5 --- Delete Row --- p.56 / Chapter 4.5.6 --- Update Row --- p.57 / Chapter 4.5.7 --- Remarks on DDL --- p.58 / Chapter 4.6 --- Chapter Summary --- p.59 / Chapter CHAPTER 5 --- END-USER INTERFACE --- p.61 / Chapter 5.1 --- EUI Overview --- p.61 / Chapter 5.2 --- Design Principles --- p.62 / Chapter 5.2.1 --- Language Independent Aspects --- p.62 / Chapter 5.2.2 --- Language Dependent Aspects --- p.64 / Chapter 5.3 --- Complex Condition Handling --- p.68 / Chapter 5.4 --- Input Sequences of the EUI --- p.71 / Chapter 5.5 --- Query Formulation： An Example --- p.73 / Chapter 5.6 --- Chapter Summary --- p.85 / Chapter CHAPTER 6 --- CHIQL TO SQL TRANSLATIONS --- p.86 / Chapter 6.1 --- Related Work --- p.87 / Chapter 6.2 --- Translation Overview --- p.87 / Chapter 6.2.1 --- "Pass One:Mapping( Input = Chiql, Output = multi-statement SQL)" --- p.89 / Chapter 6.2.2 --- "Pass Two:Nesting(Input = multi-statement SQL, Output = single statement SQL)" --- p.92 / Chapter 6.2.3 --- Technical Difficulties in Chiql/SQL Translation --- p.99 / Chapter 6.3 --- Chapter Summary --- p.106 / Chapter CHAPTER 7 --- EVALUATION --- p.108 / Chapter 7.1 --- Expressiveness Test --- p.108 / Chapter 7.1.1 --- Results --- p.109 / Chapter 7.1.2 --- Implications --- p.111 / Chapter 7.2 --- Usability Evaluation --- p.111 / Chapter 7.2.1 --- Evaluation Methodology --- p.112 / Chapter 7.2.2 --- Result:Completion Time --- p.113 / Chapter 7.2.3 --- Result: Additional Help --- p.116 / Chapter 7.2.4 --- Result： Query Error --- p.116 / Chapter 7.2.5 --- Result： Overall Score --- p.118 / Chapter 7.2.6 --- User Comments --- p.120 / Chapter 7.3 --- Chapter Summary --- p.120 / Chapter CHAPTER 8 --- CONCLUSIONS --- p.122 / Chapter 8.1 --- Thesis Conclusions --- p.122 / Chapter 8.2 --- Future Work --- p.124 / REFERENCES / APPENDIX

by Jian-Zhuang Liu. / Thesis (Ph.D.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (p. 183-196). / Microfiche. Ann Arbor, Mich.: UMI, 1998. 3 microfiches ; 11 x 15 cm.

by Law Tak Ming. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 91-96). / by Law Tak Ming. / Chapter 1. --- INTRODUCTION --- p.1 / Chapter 1.1 --- The Structure of Chinese Characters --- p.3 / Chapter 1.1.1 --- Pixels (像素) --- p.4 / Chapter 1.1.2 --- Strokes (筆劃) --- p.4 / Chapter 1.1.3 --- Basic Stroke Types (Segment Type)基本筆劃（筆段) --- p.4 / Chapter 1.1.4 --- Compound-segment Stroke (複合筆劃) --- p.5 / Chapter 1.1.5 --- Total Stroke types --- p.6 / Chapter 1.1.6 --- Stroke Sequence (筆順) --- p.6 / Chapter 1.1.7 --- Segments as Basic Features --- p.7 / Chapter 1.1.8 --- Geographic Structure of Components --- p.7 / Chapter 1.2 --- Stroke Distribution of Chinese Characters --- p.10 / Chapter 1.3 --- Radical --- p.10 / Chapter 1.4 --- The Comparison between ON-line and Off-line Chinese Character Recognition Approach --- p.11 / Chapter 1.5 --- Commercial Product Comparison --- p.14 / Chapter 1.6 --- Related Works --- p.17 / Chapter 1.7 --- Objectives --- p.29 / Chapter 2. --- PREPROCESSING --- p.31 / Chapter 2.1 --- Smoothing and Sampling --- p.32 / Chapter 2.2 --- Interpolation --- p.34 / Chapter 2.3 --- DEHOOKING --- p.37 / Chapter 2.4 --- Stroke Segmentation --- p.39 / Chapter 3. --- DATA LEARNING --- p.41 / Chapter 3.1 --- Definition of Terms --- p.41 / Chapter 3.2 --- Definition of Direction type --- p.42 / Chapter 3.3 --- Data Base Structure --- p.43 / Chapter 3.4 --- Learning Algorithms of Segments --- p.45 / Chapter 3.4.1 --- Learning of the Coordinates --- p.48 / Chapter 3.4.2 --- Learning of Direction Type --- p.48 / Chapter 3.4.3 --- Learning of Slope Angle --- p.50 / Chapter 3.5 --- Learning of the Tolerance of Coordinate --- p.50 / Chapter 3.6 --- Stroke Relation Coding --- p.51 / Chapter 4. --- PRECLASSIFICATION --- p.54 / Chapter 4.1 --- Decision Path Classification --- p.56 / Chapter 4.2 --- First-Two-Ending-One Classification Method --- p.57 / Chapter 4.3 --- Stroke Type Matching Algorithm --- p.61 / Chapter 5. --- RECOGNITION STAGE --- p.64 / Chapter 5.1 --- Connected Strokes Handling --- p.65 / Chapter 5.2 --- Stroke Sequence Free Matching Algorithm --- p.70 / Chapter 5.3 --- Preliminary Character Distance Measure --- p.72 / Chapter 5.4 --- Detailed Matching Techniques --- p.74 / Chapter 5.5 --- Segments Sequence Within a Compound-segment Stroke Compatibility --- p.75 / Chapter 5.5.1 --- Length and Slope Orientation Similarities --- p.78 / Chapter 5.5.2 --- Segment Similarity Measure Function --- p.79 / Chapter 5.6 --- Stroke Relation Influences --- p.79 / Chapter 5.7 --- Final Character Similarity Measure --- p.81 / Chapter 6. --- RESULTS AND CONCLUSIONS --- p.83 / Chapter 6.1 --- Experiment Results --- p.83 / Chapter 6.2 --- Analysis --- p.85 / Chapter 6.3 --- Conclusion --- p.87

No description available.

abstract: This work considers the design of separating input signals in order to discriminate among a finite number of uncertain nonlinear models. Each nonlinear model corresponds to a system operating mode, unobserved intents of other drivers or robots, or to fault types or attack strategies, etc., and the separating inputs are designed such that the output trajectories of all the nonlinear models are guaranteed to be distinguishable from each other under any realization of uncertainties in the initial condition, model discrepancies or noise. I propose a two-step approach. First, using an optimization-based approach, we over-approximate nonlinear dynamics by uncertain affine models, as abstractions that preserve all its system behaviors such that any discrimination guarantees for the affine abstraction also hold for the original nonlinear system. Then, I propose a novel solution in the form of a mixed-integer linear program (MILP) to the active model discrimination problem for uncertain affine models, which includes the affine abstraction and thus, the nonlinear models. Finally, I demonstrate the effectiveness of our approach for identifying the intention of other vehicles in a highway lane changing scenario. For the abstraction, I explore two approaches. In the first approach, I construct the bounding planes using a Mixed-Integer Nonlinear Problem (MINLP) formulation of the given system with appropriately designed constraints. For the second approach, I solve a linear programming (LP) problem that over-approximates the nonlinear function at only the grid points of a mesh with a given resolution and then accounting for the entire domain via an appropriate correction term. To achieve a desired approximation accuracy, we also iteratively subdivide the domain into subregions. This method applies to nonlinear functions with different degrees of smoothness, including Lipschitz continuous functions, and improves on existing approaches by enabling the use of tighter bounds. Finally, we compare the effectiveness of this approach with the existing optimization-based methods in simulation and illustrate its applicability for estimator design. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2018

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第21214号 / 情博第667号 / 新制||情||115(附属図書館) / 京都大学大学院情報学研究科システム科学専攻 / (主査)教授 杉江 俊治, 教授 太田 快人, 教授 大塚 敏之 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DGAM

In the last decade, many studies and performances within the field of interactive dance have been made. Interactive dance means involving technology into the dance, which opens opportunities to execute a dance in another way than used to. The studies in the past have often involved manipulation of music, but not many studies seem to involve manipulating real-time music produced by a live musician. Hence, this study consisted of a musician and a dancer investigating in the co-play between the two artists through sensory technology in a project called SENSITIV. More specifically, the investigation focused on the input design, i.e. the placement and processing of the motion sensors, for an interactive system, and how the involvement of the sensory technology affects the dance. Inertia-based motion sensors were worn by the dancer, by which the real-time sound produced by the musician was manipulated through the movements of the dancer. This created in turn an interaction within the intermediate connection, where the dancer came to act as a co-musician. Two studies were conducted, where in the first study a prototype was developed and designed in a first-person perspective, and the second study tested the developed prototype on a larger group of dancers. The results showed that placement on the outer parts, such as wrist and ankles, were the most suitable. It was further found that for reaching a positive experience, in terms of feeling in control with dancing with sensors involved, it requires some time as having an understanding and knowledge of the system is needed. / Under det senaste årtiondet har många studier och projekt gjorts inom interaktiv dans. Interaktiv dans betyder att involvera teknik till dansen, vilket öppnar upp många möjligheter till att utföra dans på annat sätt än vad man vanligtvis är van vid. Många av dessa studier har ofta involverat manipulation av musik men få verkar ha involverat realtidsmusik producerat av en live-musiker. Därför har denna studie utförts tillsammans med en musiker och dansare för att undersöka samspelet mellan dessa två parter genom sensorteknik i ett utformat projekt kallat för SENSITIV. Mer specifikt så har undersökningen haft fokus på input-designen, dvs. placeringen och bearbetningen av sensorerna, för ett interaktivt system, samt hur involveringen av sensorteknik påverkar dansen. Rörelsesensorer var burna av dansaren som på så vis kunde genom sina rörelser manipulera realtidsmusiken som var producerad av musikern. Detta skapade i sin tur en interaktion i den mellanliggande förbindelsen, där dansaren kom att agera som en medmusiker. Två studier var uppförda där den första hade fokus på att utforma och utveckla en prototyp ur ett förstapersonsperspektiv, medan den andra studien hade fokus på att testa prototypen på en större grupp av dansare. Resultaten visade att placering av sensorer på de yttre kroppsdelarna, så som armar och ben, var mest lämpligt. För att nå en positiv upplevelse i termer av att känna kontroll med att dansa med sensorer, visade det sig att denna prototyp krävde mer tid att bli utforskad då en förståelse och kunskap av systemet behövdes.

This thesis presents the development and use of MECHIN, an interactive graphical preprocessor for data input to spatial mechanism analysis and synthesis codes. A goal in the development of this preprocessor is to produce a graphical data input program that is both graphics device-independent and not structured for the input of data to any particular mechanism processing program. To achieve device-independence, the proposed graphics standard PHIGS (Programmer's Hierarchical Interactive Graphics System) is used for the graphics support software. Program development strategies including screen layout and user interfaces for three-dimensional data input are discussed. The program structure is also described and presented along with a complete listing of the program code to aid in future modifications and additions. Finally, a description of the use of the program is presented along with several examples of mechanism data input for synthesis and analysis. / Master of Science