Relevant bibliographies by topics / Jigsaw puzzle

Academic literature on the topic 'Jigsaw puzzle'

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Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Jigsaw puzzle"

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Verdine, Brian N., Georgene L. Troseth, Robert M. Hodapp, and Elisabeth M. Dykens. "Strategies and Correlates of Jigsaw Puzzle and Visuospatial Performance by Persons With Prader-Willi Syndrome." American Journal on Mental Retardation 113, no. 5 (September 1, 2008): 343–55. http://dx.doi.org/10.1352/2008.113:342-355.

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Abstract Some individuals with Prader-Willi syndrome exhibit strengths in solving jigsaw puzzles. We compared visuospatial ability and jigsaw puzzle performance and strategies of 26 persons with Prader-Willi syndrome and 26 MA-matched typically developing controls. Individuals with Prader-Willi syndrome relied on piece shape. Those in the control group used a different, picture-focused strategy. Individuals with Prader-Willi syndrome performed better than did the control group on an achromatic interlocking puzzle, whereas scores on puzzles with pictures (interlocking or noninterlocking) did not differ. Visuospatial scores related to performance on all puzzles in the control group and on the noninterlocking puzzle in the Prader-Willi syndrome group. The most proficient jigsaw puzzlers with Prader-Willi syndrome tended to be older and have shape-based strategies.
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Foreman, Robert Long. "Jigsaw Puzzle." River Teeth: A Journal of Nonfiction Narrative 17, no. 1 (2015): 25–27. http://dx.doi.org/10.1353/rvt.2015.0027.

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Brandler, Sondra. "The Jigsaw Puzzle." Social Work With Groups 11, no. 1-2 (October 28, 1988): 99–109. http://dx.doi.org/10.1300/j009v11n01_08.

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Zhang, Xuewei, and XiaoJie Liu. "JAVA Jigsaw Puzzle." International Journal of Advanced Pervasive and Ubiquitous Computing 9, no. 3 (July 2017): 1–14. http://dx.doi.org/10.4018/ijapuc.2017070101.

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With the development of society, the computer has become an indispensable part of people's daily life, especially in the study, and it plays an important role in their respective fields. Under the influence of the rapid development of computer, computer games are also thriving. Jigsaw puzzle is one of them. It has a wide range of applications, but also for young and old. The game can not only exercise manual ability, observation ability, but also cultivate the ability of cooperation between people.
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Sanches, MariaM, AnaI Pinto, PauloL Filipe, and JoaoM Silva. "“Jigsaw puzzle” advancement flap." Journal of Cutaneous and Aesthetic Surgery 11, no. 4 (2018): 248. http://dx.doi.org/10.4103/jcas.jcas_38_18.

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Collins, James P. "Studying Nature's Jigsaw Puzzle." Ecology 87, no. 7 (July 2006): 1867–68. http://dx.doi.org/10.1890/0012-9658(2006)87[1867:snjp]2.0.co;2.

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Verkuyten, Maykel, Borja Martinovic, and Anouk Smeekes. "The Multicultural Jigsaw Puzzle." Personality and Social Psychology Bulletin 40, no. 11 (September 9, 2014): 1480–93. http://dx.doi.org/10.1177/0146167214549324.

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Cadet, Peggy. "Solving the Jigsaw Puzzle." Narrative Inquiry in Bioethics 5, no. 2 (2015): E1—E3. http://dx.doi.org/10.1353/nib.2015.0043.

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Shephard, G. C. "A jigsaw problem." Mathematical Gazette 93, no. 526 (March 2009): 58–65. http://dx.doi.org/10.1017/s0025557200184189.

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Recently, when solving a jigsaw puzzle, I noticed that many of the pieces were symmetric in some sense; they had either reflective or rotational symmetry. This made me wonder if it was possible for all the pieces in a puzzle to be different shapes, and yet have some prescribed symmetry.
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Kusnanto, Kusnanto, Eska Dwi Prajayanti, and Harmayetty Harmayetty. "JIGSAW PUZZLE IMPROVE FINE MOTOR ABILITIES OF UPPER EXTREMITIES IN POST-STROKE ISCHEMIC CLIENTS." Jurnal Ners 12, no. 1 (June 5, 2017): 142. http://dx.doi.org/10.20473/jn.v12i1.2790.

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Introduction: Ischemic stroke is a disease caused by focal cerebral ischemia, where is a decline in blood flow that needed for neuronal metabolism, leading to neurologic deficit include motor deficit such as fine motor skills impairment. Therapy of fine motor skills disorders is to improve motor function, prevent contractures and complications. These study aimed to identify the effect of playing Jigsaw Puzzle on muscle strength, extensive motion, and upper extremity fine motor skills in patients with ischemic stroke at Dr. Moewardi Hospital, Surakarta. Methods: Experimental Quasi pre-posttest one group control. The number of samples were 34 respondents selected using purposive sampling technique. The samples were divided into intervention and control groups. The intervention group was 17 respondents who were given standard treatment hospital and played Jigsaw Puzzle 2 times a day for six days. Control group is one respondent given by hospital standard therapy without given additional Jigsaw Puzzle game. Evaluation of these research is done on the first and seventh day for those groups. Result: The results showed that muscle strength, the range of joint motion and fine motor skills of upper extremities increased (p = 0.001) significantly after being given the Jigsaw Puzzle games. These means playing Jigsaw Puzzle increase muscle strength, the range of joint motion and upper extremity fine motor skill of ischemic stroke patients. Discussion and conclusion: Jigsaw puzzle game administration as additional rehabilitation therapy in upper extremity fine motor to minimize the occurrence of contractures and motor disorders in patients with ischemic stroke. Jigsaw puzzle game therapy capable of creating repetitive motion as a key of neurological rehabilitation in Ischemic Stroke. This study recommends using jigsaw puzzle game as one of intervention in the nursing care of Ischemic Stroke patients.
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Dissertations / Theses on the topic "Jigsaw puzzle"

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Noursobhi, Soroush. "Puzzle Up : Android Jigsaw Puzzle Game." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13460.

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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.
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Tybon, Robert, and n/a. "Generating Solutions to the Jigsaw Puzzle Problem." Griffith University. School of Management, 2004. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20041101.085937.

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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.
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Tybon, Robert. "Generating Solutions to the Jigsaw Puzzle Problem." Thesis, Griffith University, 2004. http://hdl.handle.net/10072/366062.

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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
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O'Brien, Rachel. "Putting together the jigsaw puzzle : women's sense of self following an episode of postpartum psychosis." Thesis, University of Surrey, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.540729.

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Salter, B. W. Jim. "A jigsaw puzzle : assessing the English vocabulary level of junior secondary students in Hong Kong /." Thesis, Hong Kong : University of Hong Kong, 2002. http://sunzi.lib.hku.hk/hkuto/record.jsp?B25262750.

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Yang, Xingwei. "Shape Based Object Detection and Recognition in Silhouettes and Real Images." Diss., Temple University Libraries, 2011. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/111091.

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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
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Bárnet, Lukáš. "Spojování nepřekrývajících se obrazů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219685.

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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.
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Stanczak, Arnaud. "La méthode de la "classe puzzle" est-elle efficace pour améliorer l'apprentissage ?" Thesis, Université Clermont Auvergne‎ (2017-2020), 2020. http://www.theses.fr/2020CLFAL013.

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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
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Sullivan-Vance, Karen. "A Million Piece Jigsaw Puzzle| Transition Experiences of Foster Youth Accessing Higher Education through Community College." Thesis, Portland State University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10825438.

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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.

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Sullivan-Vance, Karen A. "A Million Piece Jigsaw Puzzle: Transition Experiences of Foster Youth Accessing Higher Education through Community College." PDXScholar, 2018. https://pdxscholar.library.pdx.edu/open_access_etds/4413.

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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.
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Books on the topic "Jigsaw puzzle"

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Muri, Jenn. Jigsaw puzzle. Seattle, WA: Peanut Butter Pub., 1999.

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Blackstone, Alice. Alice's jigsaw puzzle. Omaha, Neb. (6715 Corby, Omaha 68104): A. Blackstone, 1998.

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Hunt, Roderick. The jigsaw puzzle. (Oxford): Oxford University Press, 1993.

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Angove, Wendy. The jigsaw puzzle tree. [Great Britain]: Angove, 2003.

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Splash!: A jigsaw puzzle book. Waipahu, Hawaiʻi: Island Heritage, 2008.

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McCann, Chris. Master pieces: The art history of jigsaw puzzles. Portland, Or: Collectors Press, 1998.

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Jones, Jan. Jigsaw Puzzle. Start Publishing LLC, 2013.

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Kennedy, Neil. Jigsaw Puzzle. FLP Media Group, 2021.

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Sousa, Chantel de. Office Jigsaw Puzzle: 500 Piece Jigsaw Puzzle. Smith Street Books, 2020.

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Spartels, Stephanie. Legendary Lizzo Jigsaw Puzzle: 500 Piece Jigsaw Puzzle. Smith Street Books, 2022.

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Book chapters on the topic "Jigsaw puzzle"

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Pritchard, Jacki. "The jigsaw puzzle." In Dealing with Different Types of Losses Using Hypnotherapy Scripts, 169–71. New York: Routledge, 2022. http://dx.doi.org/10.4324/9781032245706-37.

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Castro-Manzano, José Martín. "Syllogistic with Jigsaw Puzzle Diagrams." In Diagrammatic Representation and Inference, 657–71. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91376-6_58.

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Issar, Arie S., and Mattanyah Zohar. "Constructing the Jigsaw Puzzle of Palaeo-Climates." In Climate Change — Environment and Civilization in the Middle East, 13–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-06264-7_2.

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Michaux, Bernard. "The final piece of the jigsaw puzzle." In Biogeology: Evolution in a Changing Landscape, 224–42. Boca Raton : CRC Press, [2020] | Series: CRC biogeography series: CRC Press, 2019. http://dx.doi.org/10.1201/9780429053443-9.

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Cozier, Yvette C., Elizabeth V. Arkema, Juan V. Rodriguez, Jeffrey S. Berman, and Praveen Govender. "Epidemiology of sarcoidosis: solving the jigsaw puzzle." In Sarcoidosis, 8–24. Sheffield, United Kingdom: European Respiratory Society, 2022. http://dx.doi.org/10.1183/2312508x.10031120.

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Alexander, Ian. "Keynote Talk Piecing Together the Requirements Jigsaw-Puzzle." In Requirements Engineering: Foundation for Software Quality, 1. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14192-8_1.

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Martin-Brualla, Ricardo, Yanling He, Bryan C. Russell, and Steven M. Seitz. "The 3D Jigsaw Puzzle: Mapping Large Indoor Spaces." In Computer Vision – ECCV 2014, 1–16. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10578-9_1.

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Khoroshiltseva, Marina, Ben Vardi, Alessandro Torcinovich, Arianna Traviglia, Ohad Ben-Shahar, and Marcello Pelillo. "Jigsaw Puzzle Solving as a Consistent Labeling Problem." In Computer Analysis of Images and Patterns, 392–402. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89131-2_36.

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Hammoudeh, Zayd, and Chris Pollett. "Clustering-Based, Fully Automated Mixed-Bag Jigsaw Puzzle Solving." In Computer Analysis of Images and Patterns, 205–17. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64698-5_18.

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Holmes, Courtney M. "A Jigsaw Puzzle as a Metaphor for Crisis Response." In Metaphors in Counselor Education and Supervision, 45–49. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003196266-6.

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Conference papers on the topic "Jigsaw puzzle"

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Tepichin, E. "Jigsaw puzzle holography: image pseudocoloring." In 16th Congress of the International Commission for Optics: Optics as a Key to High Technology. SPIE, 1993. http://dx.doi.org/10.1117/12.2308657.

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Kersten, Martin L. "The Database Architecture Jigsaw Puzzle." In 2008 IEEE 24th International Conference on Data Engineering (ICDE 2008). IEEE, 2008. http://dx.doi.org/10.1109/icde.2008.4497404.

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Pinto-Albuquerque, Maria, and Awais Rashid. "Tackling the requirements jigsaw puzzle." In 2014 IEEE 22nd International Requirements Engineering Conference (RE). IEEE, 2014. http://dx.doi.org/10.1109/re.2014.6912265.

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Shih, Huang-Chia, and Chien-Liang Lu. "Divide-and-conquer Jigsaw Puzzle Solving." In 2018 IEEE Visual Communications and Image Processing (VCIP). IEEE, 2018. http://dx.doi.org/10.1109/vcip.2018.8698731.

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Boglione, M. "The jigsaw puzzle of scalar mesons." In QUARK CONFINEMENT AND THE HADRON SPECTRUM VI: 6th Conference on Quark Confinement and the Hadron Spectrum - QCHS 2004. AIP, 2005. http://dx.doi.org/10.1063/1.1920979.

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Cho, Taeg Sang, Shai Avidan, and William T. Freeman. "A probabilistic image jigsaw puzzle solver." In 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2010. http://dx.doi.org/10.1109/cvpr.2010.5540212.

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Cao, Dai, Lifang Chen, and Yuan Liu. "Solving jigsaw puzzle with symbol matrixes." In 2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS). IEEE, 2016. http://dx.doi.org/10.1109/icis.2016.7550797.

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Shaoze Lei and Changshui Zhang. "Solve JIGSAW puzzle problems with Co-Normalization." In 2011 17th International Conference on Digital Signal Processing (DSP). IEEE, 2011. http://dx.doi.org/10.1109/icdsp.2011.6004872.

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McGill-Smith, Sophie, and Richard Green. "Jigsaw Puzzle Solver to Locate Piece Position." In 2019 International Conference on Image and Vision Computing New Zealand (IVCNZ). IEEE, 2019. http://dx.doi.org/10.1109/ivcnz48456.2019.8961019.

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Sivamuni, Kalaimagal, and Sujoy Bhattacharya. "Assembling pieces of the MOOCs jigsaw puzzle." In 2013 IEEE International Conference in MOOC, Innovation and Technology in Education (MITE). IEEE, 2013. http://dx.doi.org/10.1109/mite.2013.6756375.

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Reports on the topic "Jigsaw puzzle"

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Sullivan-Vance, Karen. A Million Piece Jigsaw Puzzle: Transition Experiences of Foster Youth Accessing Higher Education through Community College. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.6310.

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