Dissertations / Theses on the topic 'Jigsaw puzzle'

Development of a jigsaw based puzzle game for Android called PuzzleUp. The idea is that user takes a picture in real time and breaks it into jigsaw pieces that has to be put together. It also features a multiplayer mode on local area network (LAN).The main programming language used is Java and the main development environment is Android Studio (Based on JetBrains Idea) and AllJoyn has been used for inter-device communication to ensure maximum compatibility.

This thesis examines the problem of the automated re-assembly of jigsaw puzzles. The objectives of this research are as follows: to provide a clear statement of the jigsaw puzzle re-assembly problem; to find out which solution technique is best suited to this problem; to determine the level of sensitivity of the proposed solution technique when solving different variations of this problem; and to explore solution methods for solving incomplete jigsaw puzzles (puzzles with missing pieces). The jigsaw puzzle re-assembly problem has been investigated only intermittently in the research literature. This work presents an extensive examination of the suitability and efficiency of the standard solution techniques that can be applied to this problem. A detailed comparison between different solution methods including Genetic Algorithms, Simulated Annealing, Tabu Search and Constraint Satisfaction Programming, shows that a constraint-based approach is the most efficient method of generating solutions to the jigsaw puzzle problem. The proposed re-assembly algorithm is successful. Consequently, it can be used in development of automated solution generators for other problems in the same domain, thus creating new theoretical and applied directions in this field of research. One potential theoretical line of research concerns jigsaw puzzles that do not have a complete set of puzzle pieces. These incomplete puzzles represent a difficult aspect of this problem that is outlined but can not be resolved in the current research. The computational experiments conducted in this thesis demonstrate that the proposed algorithm being optimised to re-assemble the jigsaw puzzles is not efficient when applied to the puzzles with missing pieces. Further work was undertaken to modify the proposed algorithm to enable efficient re-assembly of incomplete jigsaw puzzles. Consequently, an original heuristic strategy, termed Empty Slot Prediction, was developed to support the proposed algorithm, and proved successful when applied to certain sub-classes of this problem. The results obtained indicate that no one algorithm can be used to solve the multitude of possible scenarios involved in the re-assembly of incomplete jigsaw puzzles. Other variations of the jigsaw puzzle problem that still remain unsolved are presented as avenues for future research. The solution of this problem involves a number of procedures with significant applications in other computer-related areas such as pattern recognition, feature and shape description, boundary-matching, and heuristic modelling. It also has more practical applications in robotic vision and reconstruction of broken artefacts in archaeology.

This thesis examines the problem of the automated re-assembly of jigsaw puzzles. The objectives of this research are as follows: to provide a clear statement of the jigsaw puzzle re-assembly problem; to find out which solution technique is best suited to this problem; to determine the level of sensitivity of the proposed solution technique when solving different variations of this problem; and to explore solution methods for solving incomplete jigsaw puzzles (puzzles with missing pieces). The jigsaw puzzle re-assembly problem has been investigated only intermittently in the research literature. This work presents an extensive examination of the suitability and efficiency of the standard solution techniques that can be applied to this problem. A detailed comparison between different solution methods including Genetic Algorithms, Simulated Annealing, Tabu Search and Constraint Satisfaction Programming, shows that a constraint-based approach is the most efficient method of generating solutions to the jigsaw puzzle problem. The proposed re-assembly algorithm is successful. Consequently, it can be used in development of automated solution generators for other problems in the same domain, thus creating new theoretical and applied directions in this field of research. One potential theoretical line of research concerns jigsaw puzzles that do not have a complete set of puzzle pieces. These incomplete puzzles represent a difficult aspect of this problem that is outlined but can not be resolved in the current research. The computational experiments conducted in this thesis demonstrate that the proposed algorithm being optimised to re-assemble the jigsaw puzzles is not efficient when applied to the puzzles with missing pieces. Further work was undertaken to modify the proposed algorithm to enable efficient re-assembly of incomplete jigsaw puzzles. Consequently, an original heuristic strategy, termed Empty Slot Prediction, was developed to support the proposed algorithm, and proved successful when applied to certain sub-classes of this problem. The results obtained indicate that no one algorithm can be used to solve the multitude of possible scenarios involved in the re-assembly of incomplete jigsaw puzzles. Other variations of the jigsaw puzzle problem that still remain unsolved are presented as avenues for future research. The solution of this problem involves a number of procedures with significant applications in other computer-related areas such as pattern recognition, feature and shape description, boundary-matching, and heuristic modelling. It also has more practical applications in robotic vision and reconstruction of broken artefacts in archaeology.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Management
Faculty of Commerce and Management
Full Text

Computer and Information Science
Ph.D.
Shape is very essential for detecting and recognizing objects. It is robust to illumination, color changes. Human can recognize objects just based on shapes, thus shape based object detection and recognition methods have been popular in many years. Due to problem of segmentation, some researchers have worked on silhouettes instead of real images. The main problem in this area is object recognition and the difficulty is to handle shapes articulation and distortion. Previous methods mainly focus on one to one shape similarity measurement, which ignores context information between shapes. Instead, we utilize graph-transduction methods to reveal the intrinsic relation between shapes on 'shape manifold'. Our methods consider the context information in the dataset, which improves the performance a lot. To better describe the manifold structure, we also propose a novel method to add synthetic data points for densifying data manifold. The experimental results have shown the advantage of the algorithm. Moreover, a novel diffusion process on Tensor Product Graph is carried out for learning better affinities between data. This is also used for shape retrieval, which reaches the best ever results on MPEG-7 dataset. As shapes are important and helpful for object detection and recognition in real images, a lot of methods have used shapes to detect and recognize objects. There are two important parts for shape based methods, model construction and object detection, recognition. Most of the current methods are based on hand selected models, which is helpful but not extendable. To solve this problem, we propose to construct model by shape matching between some silhouettes and one hand decomposed silhouette. This weakly supervised method can be used not only learn the models in one object class, but also transfer the structure knowledge to other classes, which has the similar structure with the hand decomposed silhouette. The other problem is detecting and recognizing objects. A lot of methods search the images by sliding window to detect objects, which can find the global solution but with high complexity. Instead, we use sampling methods to reduce the complexity. The method we utilized is particle filter, which is popular in robot mapping and localization. We modified the standard particle filter to make it suitable for static observations and it is very helpful for object detection. Moreover, The usage of particle filter is extended for solving the jigsaw puzzle problem, where puzzle pieces are square image patches. The proposed method is able to reach much better results than the method with Loopy Belief Propagation.
Temple University--Theses

The Diploma thesis is concerned with coupling of images. In the first part theoretical bases necessary for successful fulfilling of the assignment are described. The second part deals with the procedures that lead to composition of the jigsaw puzzle. The last part concentrates on controlling the program. The aim of the thesis is to propound an algorithm for solving a puzzle.

Ce travail de recherche a pour objectif de tester les effets de la classe puzzle, ou « Jigsaw classroom », sur les apprentissages. La méthode Jigsaw est une pédagogie coopérative créée par Aronson et collaborateurs dans les années 1970, afin de favoriser l’inclusion des minorités ethniques (e.g, Mexicain·es et Afro-Américain·es) dans les écoles nouvellement désegréguées. Selon la théorie de l’interdépendance sociale les effets positifs de l’apprentissage coopératif dépendent de la structuration des interactions entre individus (Deutsch, 1949 ; Johnson & Johnson, 1989). Dans Jigsaw, la structuration de cette interdépendance provient essentiellement de la distribution de ressources complémentaires : chaque individu dispose d’une « pièce du puzzle » à reconstituer à l’aide des autres membres du groupe. La coordination des efforts entre membres devrait amener ces dernier‧es à mettre en place des interactions facilitatrices (e.g., comportements d’entraide, explications et questionnements) et aboutir à un meilleur apprentissage. Toutefois, bien que cette méthode soit présentée par ses concepteur·rices comme un outil efficace pour améliorer l’apprentissage des élèves, les preuves empiriques tendent à manquer. Dans cette thèse, l’efficacité de Jigsaw sera questionnée à travers une analyse de la littérature scientifique, ainsi qu’une méta-analyse sur les travaux récents et un ensemble d’études expérimentales menées auprès d’élèves de sixième. À notre connaissance, bien que certaines recherches testant les effets de Jigsaw soient compilées dans des méta-analyses (Kyndt et al., 2013), il n’existe pas à ce jour de méta-analyses testant spécifiquement les effets de Jigsaw sur les apprentissages. À travers six chapitres, nous tenterons d’apporter des éléments permettant d’évaluer l’efficacité de la méthode Jigsaw sur les apprentissages. Dans le chapitre 1, nous présentons la théorie de l’interdépendance sociale, plusieurs définitions et manières de structurer de la coopération entre élèves ainsi qu’une revue des leurs effets sur les apprentissages. Nous développons l’idée qu’il existe des différences d’efficacité entre les pédagogies coopératives créées entre les années 1960 et 2000 (Newmann & Thompson, 1987 ; Johnson et al., 2000), et que certaines d’entre elles n’ont pas encore fait l’objet d’une validation empirique solide. Le chapitre 2 examine l’une d’elle en détail : Jigsaw (Aronson et al., 1978 ; Aronson & Patnoe, 2011). Nous y décrivons l’évolution des études empiriques menées depuis sa création jusqu’à ce jour. Le chapitre 3 pointe certaines limites de cette littérature, notamment par rapport à la puissance statistique et les procédures méthodologiques, ainsi que les impacts qu’elles peuvent avoir sur l’estimation de l’efficacité de Jigsaw sur les apprentissages. Nous y développons aussi notre hypothèse de recherche, son opérationnalisation ainsi que les outils et procédures statistiques que nous utilisons dans les chapitres empiriques : tests d’équivalence (Lakens, 2017), plus petite taille d’effet d’intérêt (Hattie, 2009) et méta-analyses (Borenstein et al., 2010 ; Goh et al., 2016). Le chapitre 4 présente les résultats d’une méta-analyse des effets de Jigsaw sur les apprentissages, à travers des articles empiriques publiés entre les années 2000 et 2020. Nous testons plusieurs modérateurs (e.g., niveau scolaire, discipline étudiée, type de Jigsaw, localisation des recherches) afin de quantifier la dispersion des effets de Jigsaw et de mieux comprendre l’hétérogénéité entre les études. Le chapitre 5 synthétise cinq études menées auprès de populations de collégien·nes français·es dans lesquelles nous testons l’efficacité de Jigsaw sur les apprentissages comparativement à des conditions de travail individuelles (études 1 et 2), ou d’enseignement habituel avec des enseignant‧es volontaires (études 3A, 3B et 3C). [...]
The objective of this thesis is to test the effect of the Jigsaw classroom on learning. The Jigsaw classroom is a cooperative technique created by Aronson and his colleagues in the 1970s to promote the inclusion of ethnic minorities (e.g., Mexican and African-American) in desegregated schools. Although this method is presented by its developers as an effective tool for improving student learning, empirical evidence is lacking. According to the social interdependence theory, the structure of interactions between individuals determine the effects of cooperative learning (Deutsch, 1949; Johnson & Johnson, 1989). In Jigsaw, this structure comes from the distribution of complementary resources: each individual owns a “jigsaw piece”, namely a piece of information which requires the coordination of efforts among members to answer a problematic. With the help of other group members, promotive interactions (e.g., helping behaviors, explanations and questioning) should emerge which results in a better learning for the members. In this thesis, Jigsaw's effectiveness will be evaluated through a review of the scientific literature, as well as a meta-analysis of recent research and a set of experimental studies conducted among french sixth graders. To our knowledge, the experimental study of Jigsaw’s effects on learning in student populations is almost non-existent in the scientific literature and even though some research testing these effects is compiled in meta-analyses (Kyndt et al., 2013), there are no meta-analyses to date that specifficaly adress the question of Jigsaw's effects on learning. Hence, the research presented in this manuscript will attempt to evaluate the effectiveness of the Jigsaw method on learning. In Chapter 1, we present “social interdependence theory” (Johnson & Johnson, 1989, 2002, 2005), several definitions and ways of structuring cooperation between students, as well as a review of their effects on learning. Chapter 2 examines one of these cooperative technique in detail: Jigsaw (Aronson et al., 1978; Aronson & Patnoe, 2011). We describe the evolution of empirical studies conducted from its conception to the present day. Chapter 3 points out some of the limitations of this literature, particularly in terms of statistical power, and the impacts it may have on the estimation of Jigsaw's effectiveness on learning. We also develop our main hypothesis, its operationalization and the statistical tools and procedures we use in the empirical chapters: equivalence tests (Lakens, 2017), smallest effect size of interest (Hattie, 2009) and meta-analyses (Borenstein et al., 2010; Goh et al., 2016). Chapter 4 presents the results of a meta-analysis of Jigsaw's effects on learning, which synthesized empirical articles published between 2000 and 2020. We test several moderators (e.g., grade level, discipline, type of Jigsaw, location of research) in order to quantify the dispersion of Jigsaw effects and to assess heterogeneity between studies. Chapter 5 compiles five studies conducted among french sixth graders in which we test the effectiveness of Jigsaw on learning, compared to an “individual” (studies 1 and 2) or a “teaching as usual’ condition (studies 3A, 3B and 3C). The results of this chapter are interpreted with regard to the meta-analysis and the debates related to the structure of Jigsaw. In the last chapter of this manuscript, we summarize the main results developed trough the theoretical and empirical chapters. The contributions and limitations of our research are developed, as well as theoretical and practical perspectives to overcome them in view of future research

A college education offers people social and economic benefits, yet youth from foster care backgrounds are less likely than their peers to attain a college education, which places this already vulnerable population at higher risk for a lifetime of living on the margins of society. Foster alumni face multiple obstacles to accessing and persisting in higher education. To facilitate and support the success of this frequently overlooked population, professionals in higher education need to understand these obstacles. Little is known about the experiences of youth with foster care backgrounds as they transition into and through higher education. Although existing research has reported the academic, health, and social effects of having been in foster care, little is known about why foster alumni do not persist in higher education. This study used student-development theory, specifically Schlossberg’s transition theory, Tinto’s theory of student departure, and Bourdieu’s work on social and cultural capital to provide a conceptual framework through which to view the lived experiences of youth with foster care backgrounds. Because, for many youths with foster care backgrounds, the pathway to the baccalaureate degree is through a community college, this study examined and explored the transition experiences of foster alumni about to begin or currently enrolled at an Oregon Community College. The study explored the factors that challenge and facilitate foster alumni persistence towards the attainment of a college degree.

A college education offers people social and economic benefits, yet youth from foster care backgrounds are less likely than their peers to attain a college education, which places this already vulnerable population at higher risk for a lifetime of living on the margins of society. Foster alumni face multiple obstacles to accessing and persisting in higher education. To facilitate and support the success of this frequently overlooked population, professionals in higher education need to understand these obstacles. Little is known about the experiences of youth with foster care backgrounds as they transition into and through higher education. Although existing research has reported the academic, health, and social effects of having been in foster care, little is known about why foster alumni do not persist in higher education. This study used student-development theory, specifically Schlossberg's transition theory, Tinto's theory of student departure, and Bourdieu's work on social and cultural capital to provide a conceptual framework through which to view the lived experiences of youth with foster care backgrounds. Because, for many youths with foster care backgrounds, the pathway to the baccalaureate degree is through a community college, this study examined and explored the transition experiences of foster alumni about to begin or currently enrolled at an Oregon Community College. The study explored the factors that challenge and facilitate foster alumni persistence towards the attainment of a college degree.

This thesis examines the meaning(s) of ‘development’ within a rural village in Sichuan province, China... Importantly, this thesis is a unique snapshot account containing grassroots stories about what development means from the voice and perspective of average Han villagers in a single village in contemporary rural China. (Taken from Abstract)
Doctor of Philosophy

L’objectif de cette thèse est de développer des méthodes sémantiques de réassemblage dans le cadre compliqué des collections patrimoniales, où certains blocs sont érodés ou manquants.Le remontage de vestiges archéologiques est une tâche importante pour les sciences du patrimoine : il permet d’améliorer la compréhension et la conservation des vestiges et artefacts anciens. Certains ensembles de fragments ne peuvent être réassemblés grâce aux techniques utilisant les informations de contour et les continuités visuelles. Il est alors nécessaire d’extraire les informations sémantiques des fragments et de les interpréter. Ces tâches peuvent être accomplies automatiquement grâce aux techniques d’apprentissage profond couplées à un solveur, c’est-à-dire un algorithme de prise de décision sous contraintes.Cette thèse propose deux méthodes de réassemblage sémantique pour fragments 2D avec érosion, ainsi qu’un jeu de données et des métriques d’évaluation.La première méthode, Deepzzle, propose un réseau de neurones auquel succède un solveur. Le réseau de neurones est composé de deux réseaux convolutionnels siamois entraînés à prédire la position relative de deux fragments : il s'agit d'une classification à 9 classes. Le solveur utilise l’algorithme de Dijkstra pour maximiser la probabilité jointe. Deepzzle peut résoudre le cas de fragments manquants et surnuméraires, est capable de traiter une quinzaine de fragments par puzzle, et présente des performances supérieures à l’état de l’art de 25%.La deuxième méthode, Alphazzle, s’inspire d’AlphaZero et de recherche arborescente Monte Carlo (MCTS) à un joueur. Il s’agit d’une méthode itérative d’apprentissage profond par renforcement : à chaque étape, on place un fragment sur le réassemblage en cours. Deux réseaux de neurones guident le MCTS : un prédicteur d’action, qui utilise le fragment et le réassemblage en cours pour proposer une stratégie, et un évaluateur, qui est entraîné à prédire la qualité du résultat futur à partir du réassemblage en cours. Alphazzle prend en compte les relations entre tous les fragments et s’adapte à des puzzles de taille supérieure à ceux résolus par Deepzzle. Par ailleurs, Alphazzle se place dans le cadre patrimonial : en fin de réassemblage, le MCTS n’accède pas à la récompense, contrairement à AlphaZero. En effet, la récompense, qui indique si un puzzle est bien résolu ou non, ne peut être qu’estimée par l’algorithme, car seul un conservateur peut être certain de la qualité d’un réassemblage
The objective of this thesis is to develop semantic methods of reassembly in the complicated framework of heritage collections, where some blocks are eroded or missing.The reassembly of archaeological remains is an important task for heritage sciences: it allows to improve the understanding and conservation of ancient vestiges and artifacts. However, some sets of fragments cannot be reassembled with techniques using contour information or visual continuities. It is then necessary to extract semantic information from the fragments and to interpret them. These tasks can be performed automatically thanks to deep learning techniques coupled with a solver, i.e., a constrained decision making algorithm.This thesis proposes two semantic reassembly methods for 2D fragments with erosion and a new dataset and evaluation metrics.The first method, Deepzzle, proposes a neural network followed by a solver. The neural network is composed of two Siamese convolutional networks trained to predict the relative position of two fragments: it is a 9-class classification. The solver uses Dijkstra's algorithm to maximize the joint probability. Deepzzle can address the case of missing and supernumerary fragments, is capable of processing about 15 fragments per puzzle, and has a performance that is 25% better than the state of the art.The second method, Alphazzle, is based on AlphaZero and single-player Monte Carlo Tree Search (MCTS). It is an iterative method that uses deep reinforcement learning: at each step, a fragment is placed on the current reassembly. Two neural networks guide MCTS: an action predictor, which uses the fragment and the current reassembly to propose a strategy, and an evaluator, which is trained to predict the quality of the future result from the current reassembly. Alphazzle takes into account the relationships between all fragments and adapts to puzzles larger than those solved by Deepzzle. Moreover, Alphazzle is compatible with constraints imposed by a heritage framework: at the end of reassembly, MCTS does not access the reward, unlike AlphaZero. Indeed, the reward, which indicates if a puzzle is well solved or not, can only be estimated by the algorithm, because only a conservator can be sure of the quality of a reassembly

碩士
中華科技大學
電子工程研究所碩士班
105
The main purpose of this paper is to develop a PC jigsaw puzzle game. In the first step, a C# program is developed for cutting a picture into some adjacent hexagonal small graphs for the next step to design the jigsaw puzzle game. The main reason for using hexagonal small graphs to create jigsaw puzzle game is to complete the puzzle, in addition to putting the hexagon's small graph in the correct position, and turning the graph to the correct angle to fit into the puzzle, which can increase the fun and difficulty. In the first step, we first design the distribution of the regular hexagonal small graphs to be cut, and give the appropriate number of each hexagonal small graph, and then derive the equations around hexagonal small graphs. And then study to find the relationship between the number of small graph and the numbers of equations. And then use these relationships to write the C# program. The results of the developed the cutting program show that the correct hexagonal small graphs can be cut from a large picture according to the previous design to meet the needs of subsequent jigsaw puzzle game design. The proposed jigsaw puzzle game is a game created with Unity3D. This jigsaw puzzle game is interesting than other jigsaw puzzle because the puzzle angle and position are needed both correct to complete this picture of jigsaw puzzle game.

碩士
玄奘大學
應用心理學系碩士在職專班
102
Jigsaw puzzle game is a great tool of edutainment which can train the kids’ perceptual, cognitive, motor and even creative abilities all at once. It has become the most popular product in the market of preschool education all over the world. However, jigsaw puzzle games made by different publishers always have significant differences with their number of pieces, design styles, rules for cutting into pieces, and the provision of the outer frame for reference. These differences will correspondingly cause the difference of the level of difficulty. For the reason, this study aimed to invent new designing rules for jigsaw puzzle games to provide kids at different developmental levels with different levels of jigsaw puzzle games. The study used a three-way experiment to investigate the main effects and interactions of the cutting rule of jigsaw puzzle, the instructing style and the age of participant. The author introduced the Recognition-by-Component theory and cut puzzle pieces into two versions, one to reserve geons and the other to reserve junctions. The instruction style was accordingly divided into two versions, one to cue geons and the other to cue local conjunctions. As for the age of participant, kindergarten kids and students from the second and fourth grades at preliminary schools were recruited to join in this study. As the results indicated, except for the main effect of age, there was no any other significant main effect or interaction at this study. The post hoc comparisons revealed that kindergarten kids need more time than school students to complete these jigsaw puzzle games. The article also discussed several possible confounding variables and suggested some directions for further studies. Keywords: jigsaw puzzle game, geon, object recognition

碩士
元智大學
電機工程學系甲組
107
For solving the jigsaw puzzle, when the original image can be accessed. First the SIFT algorithm is used to extract and match the feature points between each piece of the puzzle and the original image. Then, the RANSAC (RANdom Sample Consensus) is used to eliminate incorrect matching pairs. By using the result of RANSAC, the transformation matrix（TM） between the piece of puzzle and the original image can be obtained. The TM contains the coordinates and the rotation angle information. Finally, the TM parameters are applied to the robotic arm to solve the puzzle. However, due to the working space of the robotic arm is limited, we design a pre-rotation algorithm of the robotic arm to reduces running time. Compared with the method of the histogram based full search, the feature point matching method can greatly reduce almost 88.5% computation time. Otherwise, without the original image, the four edges color information in all piece of puzzle is extracted. To calculate the similarity of adjacent pieces by the similarity formula, and apply the concept of Hausdorff distance, the best piece of the puzzle can be obtained to form the initial combination. Through the main track, second combination, and third combination to complete the puzzle reconstruction. Based on the experimental results, among the 25 test images, the average success rate reaches 87.1% when each image cut into 35 pieces, and 17 of them are 100% accuracy. When cut into 70 pieces, 77.8% is obtained in average, and 13 of them are 100% accuracy. Referring to the experimental results, In the case of with the original image, the proposed method eliminates the requirement to adjust the SIFT threshold and it can reduce the calculation time to complete the puzzle. Without the original image, it can complete the puzzle without presetting the position of any piece of puzzle. The proposed method can be applied to many other fields, such as industrial automation, robot vision, banknote rebuilding or archaeological restoration.

碩士
國立彰化師範大學
統計資訊研究所
106
Data hiding means that the sender embedded the secret bits into a digital media and transmits it to the receiver by an agreed method, and only the legal receiver can retrieve the secret bits according to the agreed method. In this study, we use grayscale images as the cover media. There are three requirements in the data hiding field: payload, imperceptibility (stego-image quality) and robustness. In general, it is a trade-off between the payload and the robustness to certain attacks while keeping an acceptable level of stego-image quality. The least significant bit (LSB) substitution method and pixel-value differencing (PVD) method are two well-known irreversible data hiding methods. Both methods have the advantages of high payload and low distortion. LSB method directly replaces the bits of the cover pixel with secret bits for embedding. In PVD method, the difference of two pixels in the cover image is calculated to determine the number of bits to be embedded in these two pixels and a pre-defined range table. The technique can embed a large number of secret bits into the cover image with high imperceptibility. In this study, we divide the cover image into different size of jigsaw puzzle pieces by using logistic map function to enhance robustness and security and embedding the secret bits by two different methods. The experimental results show that the one of proposed method achieves high payload and low distortion with strong robustness and security and the another one method increases a lot of payloads, the image quality slightly decreased, but the naked eye cannot be detected as it makes use of the characteristic of human vision sensitivity.

Thesis (Ph.D.)--York University, 2006. Graduate Programme in Psychology.
Typescript. Includes bibliographical references (leaves 114-121. Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:NR29486

Relatório de estágio de mestrado em Ensino do Inglês no 1º Ciclo do Ensino Básico
Este relatório de estágio é parte integrante do Mestrado em Ensino do Inglês no 1.º Ciclo do Ensino Básico, no âmbito do qual foi desenvolvido o projeto de investigação-ação intitulado “Let’s be a jigsaw puzzle: o trabalho de projeto na promoção da aprendizagem cooperativa”. Este projeto foi realizado em duas escolas do 1.º Ciclo do Ensino Básico do distrito de Braga: primeiramente numa turma mista do 3.º e 4.º anos de escolaridade e, posteriormente, numa turma do 3.º ano. O seu objeto de estudo foi a aprendizagem cooperativa na aprendizagem do Inglês no 1.º Ciclo do Ensino Básico, com recurso a atividades em pares e/ou grupo, e momentos de partilha, como apresentações orais, dando ênfase à partilha de conhecimentos, ao espírito colaborativo e ao respeito pelo outro. O projeto teve como objetivos conhecer perceções e atitudes dos alunos relativamente à aprendizagem de Inglês e ao trabalho cooperativo; promover competências sociais e comunicativas através de trabalhos de projeto; promover competências de co/autorregulação da aprendizagem; avaliar o potencial dos trabalhos de projeto na aprendizagem cooperativa e na aprendizagem do Inglês. Foram desenvolvidas estratégias pedagógicas direcionadas para o trabalho cooperativo, e foi recolhida informação através de questionários iniciais e de autorregulação, que serviram para avaliar o impacto e a adequação das mesmas. Os resultados obtidos através dos questionários e da observação de aulas e do comportamento e atitudes das crianças, demonstraram que o trabalho cooperativo facilita a aprendizagem do Inglês, fortalecendo os laços afetivos entre as crianças. Para além disso, o processo de autorregulação permitiu que as crianças desenvolvessem o seu espírito crítico e a sua autonomia. Assim, recomenda-se a aprendizagem cooperativa na lecionação do Inglês, sobretudo pela possibilidade de associar aprendizagens linguísticas com o desenvolvimento de valores democráticos, num constante ambiente de partilha. No que concerne a limitações dentro da sala de aula, foram sentidas algumas dificuldades na gestão do tempo e na monitorização das atividades realizadas em grupo; também as crianças sentiram dificuldades na execução de algumas tarefas. A maior limitação deste projeto deve-se ao facto de as aulas previstas para o mesmo não terem sido todas lecionadas devido ao encerramento das escolas resultante da pandemia COVID-19.
This teaching report is part of the Master's Program in Teaching English in the Primary Education, in which an action research project entitled "Let’s be a jigsaw puzzle: project work in the promotion of cooperative learning" was developed. This report was carried out in two schools of primary education of the district of Braga: firstly in a mixed-ability class with 3rd and 4th grade and, afterwards, in a 3rd grade class. Its object of study was cooperative learning in the learning of English in the Primary Education, using activities in pairs and/or group, and moments of sharing, such as oral presentations, emphasizing the sharing of knowledge, collaborative spirit and respect for the other. The project aimed to know perceptions and attitudes of students regarding English learning and cooperative work; promote social and communicative skills through project work; promote co/self-regulation skills in learning; assess the potential of project work in cooperative learning and in learning English. Pedagogical strategies were developed and aimed at cooperative work, and information was collected through initial and self-regulation questionnaires, which served to assess the impact and adequacy of these strategies. The results obtained through questionnaires and observation of classes and the behavior and attitudes of the children, demonstrated that cooperative work facilitates the learning of English, strengthening the affective bonds between children. In addition, the process of self-regulation has allowed children to develop their critical spirit and autonomy. Thus, cooperative learning in English teaching is recommended, especially because of the possibility of associating linguistic learning with the development of democratic values in a constantly sharing environment. Regarding limitations within the classroom, some difficulties were experienced regarding time management and monitoring of group activities; also, the children experienced difficulties in performing some tasks. The greatest limitation of this project is due to the fact that the lessons planned for it were not all taught due to the closure of schools resulting from the pandemic COVID-19.

碩士
國立臺北教育大學
數位科技設計學系(含玩具與遊戲設計碩士班)
103
In this study, game-based learning theory, design applications combined with augmented reality perspective 3D jigsaw puzzles for students after-school learning earth sciences. Three-dimensional jigsaw puzzle for the media, through the 3d virtual allows users to interact with the Earth. The study is divided into three stages, first, a design applications combined with augmented reality three-dimensional puzzle of aids to elementary school students to learn earth science. Second, after the completion, so that elementary school students be tested, fill ARCS motivation questionnaire before and after the test, last, analyze the effectiveness of the students after teaching aids. In 55 elementary school students as the research object, aids testing. After this aids in ARCS motivation, A. (Attention) and C. (Confidence) have significantly improved, but R. (Relevance) and S. (Satisfaction) no significant difference. Moreover, high motivation in learning outcomes performance is better. The average post-test study results are significantly increased. Female students C. (Confidence) and S. (Satisfaction) are significantly higher than male students. This set of teaching aids prove feasible, I recommend this model can be applied to different teaching aids learning content.

碩士
國立臺北教育大學
數位科技設計學系(含玩具與遊戲設計碩士班)
103
The puzzle game is one of the methods in teaching innovation and learning achievement that helps to train the students’ abilities of observation and logical reasoning. Since earth science is an important course of twelve-year basic education in Taiwan, this study adopted the Cretaceous dinosaurs as theme and strata and fossils as contents to develop an innovative teaching tool combined with augmented realityies and puzzles. This study adopted quasi-experimental tests on 103 fifth-grade students to evaluate the effect. The result shows: 1.The jigsaw puzzle game-based learning and which combines with augmented reality may enhance the students’ learning achievement; 2.The augmented reality combined with puzzles of digital game-based learning has a positive motivation effect; 3.The augmented reality combined with puzzles of digital game-based learning helps to motivate the students’ creation. The measures of the experiments show that the teaching tools developed by the study do help enhance the students' learning motivation and learning achievement. It is suggested to be introduced to apply as teaching tools and helps to improve the students' learning willingness and understanding.

How does DNA make the abundant and diverged life world? To address this question, a DNA “Jigsaw Puzzle” structure model was proposed and first tested by comprehensively analyzing the genome of the model dicot plant, Arabidopsis thaliana. However, it is unknown whether this model is held in other species. Here we report the studies of the DNA structure model using the monocot plant model species, rice (Oryza sativa), and the single-celled model species, yeast (Saccharomyces cerevisiae). Analyses of the genomes sequenced so far revealed that the genome of an organism consists of a limited number of sequence-specialized, so-called fundamental function elements. For a higher organism, these elements often include genes (GEN), retro-transposable elements (RTE), DNA transposable elements (DTE), simple sequence repeats (SSR) and low complex repeats (LCR). Datasets were developed for RTE, DTE, SSR, LCR and GEN as well as genes categorized into different function categories from the sequences of the rice and yeast genomes using appropriate window sizes. The datasets were subjected to statistical analyses to test the DNA “Jigsaw Puzzle” structure model in terms of the unambiguousness, correlation, uniqueness and selection of their genome-constituting element arrays. The analyses were conducted with a series of window sizes of the sequences at both the whole genome and individual chromosome levels, both including and excluding the centromeric regions. The results showed that all fundamental function elements of the genomes as well as the genes categorized into different function categories were arrayed in the genomes in an unambiguous manner resembling linear “Jigsaw Puzzles” at the whole genome and/or individual chromosome levels, no matter whether the centromeric regions were included or excluded. The analyses revealed that arraying of the genomic elements was correlated significantly and uniquely for each chromosome and each species. This further confirmed the non-random arraying characteristic of the genomic elements for the DNA “Jigsaw Puzzle” structure model and suggested that the DNA “Jigsaw Puzzle” structure is unique for an organism, which has probably resulted from natural selection. These results unambiguously support the hypothesis of the DNA “Jigsaw Puzzle” structure model. Since the content, arraying and interaction pattern of the fundamental function elements were shown to be unique for each organism, variations of an organism in its DNA “Jigsaw Puzzle” array would lead to phenotypic variations, thus resulting in different organisms. Moreover, the fundamental function elements constituting a genome, as the four nucleotides (A, T, G and C) of DNA, could be arrayed into an infinite number of DNA molecules, thus giving different forms of organisms. Therefore, the DNA “Jigsaw Puzzle” structure model would provide a novel, but convincing explanation for the abundance, diversity and complexity of living organisms in the world.

碩士
世新大學
數位多媒體設計學系
107
The purpose of this study was to explore the study of augmented Reality (Augmented Reality,ar) combined with jigsaw puzzle, with one autistic student and two students with ADHD in the Republic of China Autism Foundation, a consortium.In this study, the withdrawal design (A-B-M) of a single test method was used to analyze learning effectiveness and maintain effectiveness and attention, and the self-variant was the Osmo-tangram course, and the learning effect and maintenance effectiveness and attention of the shape combination cognition were determined by the change. There are two purposes of this study：（1）To explore the learning effect and maintenance effect of Osmo-tangram on the shape combination cognition of children with small autism and attention deficit hyperactivity disorder in ascending countries；（2）To explore the effect of Osmo-tangram on the attention of children with small autism in ascending countries and children with attention deficit hyperactivity disorder.After Osmo-tangram, the researchers analyzed the data collected with visual analysis and C statistics, and the results summarized the following conclusions： （1）After the intervention of Osmo-tangram course, the combination cognitive ability and learning effect of the subjects were improved, and the effect was still maintained after the completion of the Osmo-tangram course. （2）Through the intervention of Osmo-tangram course teaching, through the teaching method and the animation and special effects appearing in the process, it does enhance the focus of the subjects, and can still maintain the focus at the end of the course.

碩士
中華大學
工業管理學系碩士班
102
This research investigates the learning curve of elementary students playing a jigsaw puzzle. Fifteen males and fifteen females were recruited as human subjects for the study. Their ages were 11.98 (±0.32) yrs. The subjects were split into three groups. They spelled the puzzle once every other day, every four day, and every seven day and continued for five times. The jigsaw was purchased from a local market. It comprised 100 pieces. The time to finish the jigsaw puzzle was recorded using a stopwatch. A total of 150 trials were collected. The data were analyzed using descriptive statistics and analysis of variance (ANOVA). Duncan’s multiple range tests were conducted. Regression models were also built for the learning curves. The results showed that gender was not significant in affecting the time to complete the jigsaw puzzles even though males spent a little shorter time than females did. Due to the learning effects, the time to complete the puzzle was becoming shorter after the subjects had experience in completing the puzzle. The improvement in the spelling time was more apparent in the early stage and then slowed down. The results of the study provide information concerning learning behaviors and effects for elementary students doing similar hand-manipulation games or tasks.