Relevant bibliographies by topics / Integration and transfer learning

Academic literature on the topic 'Integration and transfer learning'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Integration and transfer learning"

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Boitel, Craig, Kathleen Farkas, Laurentine Fromm, and M. C. “Terry” Hokenstad. "Learning Transfer Principles in a Comprehensive Integration Model." Journal of Teaching in Social Work 29, no. 4 (November 15, 2009): 400–417. http://dx.doi.org/10.1080/08841230903249687.

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Peng, Minshi, Yue Li, Brie Wamsley, Yuting Wei, and Kathryn Roeder. "Integration and transfer learning of single-cell transcriptomes via cFIT." Proceedings of the National Academy of Sciences 118, no. 10 (March 3, 2021): e2024383118. http://dx.doi.org/10.1073/pnas.2024383118.

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Large, comprehensive collections of single-cell RNA sequencing (scRNA-seq) datasets have been generated that allow for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets or transfer knowledge from one to the other to better understand cellular identity and functions. Here, we present a simple yet surprisingly effective method named common factor integration and transfer learning (cFIT) for capturing various batch effects across experiments, technologies, subjects, and even species. The proposed method models the shared information between various datasets by a common factor space while allowing for unique distortions and shifts in genewise expression in each batch. The model parameters are learned under an iterative nonnegative matrix factorization (NMF) framework and then used for synchronized integration from across-domain assays. In addition, the model enables transferring via low-rank matrix from more informative data to allow for precise identification in data of lower quality. Compared with existing approaches, our method imposes weaker assumptions on the cell composition of each individual dataset; however, it is shown to be more reliable in preserving biological variations. We apply cFIT to multiple scRNA-seq datasets of developing brain from human and mouse, varying by technologies and developmental stages. The successful integration and transfer uncover the transcriptional resemblance across systems. The study helps establish a comprehensive landscape of brain cell-type diversity and provides insights into brain development.
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Pop, Ioan, and Ilie Soritau. "Sustainable Integrative All-Life Learning as Pragmatic Level in the DIMLAK hetero-hierarchic paradigm to Achieve Advanced Knowledge." DIALOGO 9, no. 1 (December 5, 2022): 200–208. http://dx.doi.org/10.51917/dialogo.2022.9.1.15.

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A new transdisciplinary perspective on the integration of knowledge is introduced in the context of the informergic society/economy (KBS/E) to achieve, share and implement the knowledge giving the openness to a better understanding of the world, using sustainable, integrative all-life learning. A new more complete perspective on the well-known system of knowledge integration, based on a five steps scale in a synergistic-generative transdisciplinary process to achieve, transfer and implement knowledge in the knowledge-based society/economy (KBS/E) context is configured, connecting DIMLAK knowledge paradigm to Knowledge Integration Management (KIM). It presents a possible connection between the all¬life, sustainable, integrative learning and the DIMLAK hetero-hierarchic paradigm of knowledge in the biblical context, the heaven ladder from Sychar.
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Li, Zhichao, and Jinwei Dong. "A Framework Integrating DeeplabV3+, Transfer Learning, Active Learning, and Incremental Learning for Mapping Building Footprints." Remote Sensing 14, no. 19 (September 22, 2022): 4738. http://dx.doi.org/10.3390/rs14194738.

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Convolutional neural network (CNN)-based remote sensing (RS) image segmentation has become a widely used method for building footprint mapping. Recently, DeeplabV3+, an advanced CNN architecture, has shown satisfactory performance for building extraction in different urban landscapes. However, it faces challenges due to the large amount of labeled data required for model training and the extremely high costs associated with the annotation of unlabelled data. These challenges encouraged us to design a framework for building footprint mapping with fewer labeled data. In this context, the published studies on RS image segmentation are reviewed first, with a particular emphasis on the use of active learning (AL), incremental learning (IL), transfer learning (TL), and their integration for reducing the cost of data annotation. Based on the literature review, we defined three candidate frameworks by integrating AL strategies (i.e., margin sampling, entropy, and vote entropy), IL, TL, and DeeplabV3+. They examine the efficacy of AL, the efficacy of IL in accelerating AL performance, and the efficacy of both IL and TL in accelerating AL performance, respectively. Additionally, these frameworks enable the iterative selection of image tiles to be annotated, training and evaluation of DeeplabV3+, and quantification of the landscape features of selected image tiles. Then, all candidate frameworks were examined using WHU aerial building dataset as it has sufficient (i.e., 8188) labeled image tiles with representative buildings (i.e., various densities, areas, roof colors, and shapes of the building). The results support our theoretical analysis: (1) all three AL strategies reduced the number of image tiles by selecting the most informative image tiles, and no significant differences were observed in their performance; (2) image tiles with more buildings and larger building area were proven to be informative for the three AL strategies, which were prioritized during the data selection process; (3) IL can expedite model training by accumulating knowledge from chosen labeled tiles; (4) TL provides a better initial learner by incorporating knowledge from a pre-trained model; (5) DeeplabV3+ incorporated with IL, TL, and AL has the best performance in reducing the cost of data annotation. It achieved good performance (i.e., mIoU of 0.90) using only 10–15% of the sample dataset; DeeplabV3+ needs 50% of the sample dataset to realize the equivalent performance. The proposed frameworks concerning DeeplabV3+ and the results imply that integrating TL, AL, and IL in human-in-the-loop building extraction could be considered in real-world applications, especially for building footprint mapping.
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Müller, Burkhard. "Single-Use Versus Mixed-Use Learning of Transformations: Evidence for Conceptual Integration." Experimental Psychology 49, no. 1 (January 2002): 45–56. http://dx.doi.org/10.1027/1618-3169.49.1.45.

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Abstract. The principle of use-specificity proposes that “compiled” knowledge encapsulates the knowledge use in the acquisition context. The efficiency of knowledge use should be a monotone function of use-specific practice. Transfer between different uses of function concepts should decrease with increasing practice. In contrast, the hypothesis of conceptual integration proposes that conceptually integrated knowledge can be used flexibly. The efficiency of knowledge use should be a monotone function of concept-specific practice. The probability to integrate a feature is assumed to depend on its relevance within the acquisition context. Transfer between different uses of function concepts should increase with increasing practice. In Experiment 1, the effects of practicing a single versus two different uses of symbolic functions on learning and subsequent transfer were investigated at 1 day and 2 consecutive days of practice. In Experiment 2, these effects were investigated for 4 days of practice. The findings support the hypothesis of conceptual integration. Performance was mainly a function of concept-specific training. Limited usability of acquired knowledge was rare and disappeared completely at higher levels of practice.
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Malykh, Ludmila Mikhailovna, and Nadezhda Alekseevna Shutova. "MULTILINGUAL READING AS A TOOL OF LANGUAGE LEARNING INTEGRATION." Russian Journal of Multilingualism and Education 13 (December 28, 2021): 34–46. http://dx.doi.org/10.35634/2500-0748-2021-13-34-46.

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The paper explores the effects of multilingual reading with students studying several foreign languages. The importance of this study is determined by the search for better practices leading to the incorporation of all language experience of the students when proceeding with a new language. Multilingual reading is defined as a skill aiming at simultaneous perception and comprehension of several written texts in different languages translated from one authentic text. The aim of the paper is to demonstrate the potential of multilingual reading in the formation of metacognitive strategies of comparison, transfer and code switching in the process of studying French and English after Russian (the students‟ native tongue). The paper examines the causes of referring to reading as a universal language skill for the enrichment of the students‟ repertoire of multilingual activities; the goals of multilingual reading; existing approaches to reading in a foreign language which have led to the idea of multilingual reading. The conclusion is drawn that to implement multilingual reading a certain level of mastery of a language under study is expected. Multilingual reading is best for incorporating into the language teaching after second foreign language is introduced. This is the time when a student is considered to be a sophisticated reader in his / her native tongue and first foreign language. The main goal of multilingual reading is to form the students‟ metacognitive strategies of comparison, transfer and code switching. The most appropriate literary genre for starting multilingual reading is popular science. Relative simplicity of its structural organization allows the readers to comprehend its meaning avoiding difficulties of reading a work of fiction full of specific stylistic devices. Besides, popular science incorporates features of science, colloquial, journalistic and feature literature styles. All things considered, popular science becomes a universal tool of multilingual reading.
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Vilsmaier, Ulli, Moritz Engbers, Philip Luthardt, Rina Marie Maas-Deipenbrock, Sebastian Wunderlich, and Roland W. Scholz. "Case-based Mutual Learning Sessions: knowledge integration and transfer in transdisciplinary processes." Sustainability Science 10, no. 4 (September 19, 2015): 563–80. http://dx.doi.org/10.1007/s11625-015-0335-3.

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Nakakoji, Yoshitaka, and Rachel Wilson. "Interdisciplinary Learning in Mathematics and Science: Transfer of Learning for 21st Century Problem Solving at University." Journal of Intelligence 8, no. 3 (September 1, 2020): 32. http://dx.doi.org/10.3390/jintelligence8030032.

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Transfer of learning, the application of learning to different contexts over time, is important to all learning for development. As 21st century skills specifically aim to be “generic,” there is an assumption that they can be transferred from context to context. We investigate the process of transfer in problem solving, with specific focus on mathematical problem solving tasks. Problem solving is highly valued in 21st century workplaces, where mathematical skills are also considered to be foundational in STEM and of paramount importance. This study examines the transfer of first semester mathematics learning to problem solving in second semester physics at university. We report on: (1) university students’ (n = 10) “think-aloud” accounts of the process of transfer; and (2) students’ (n = 10) and academics’ (n = 8) perspectives on transfer processes and problem solving. Think-aloud accounts show students’ recursive use of interpretation, integration, planning and execution thinking processes and highlight the meta-cognitive strategies used in transfer. Academics’ and students’ perspectives on transfer show disparities. Understanding these perspectives is important to current initiatives to integrate and optimise 21st century learning within universities. We argue that renewed attention on the concept of transfer is needed if the generic aims of 21st century skills are to be understood and promoted.
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Khamroev, Rustam. "Integration role of information technologies in knowledge transfer." Общество и инновации 2, no. 1/S (February 10, 2021): 170–77. http://dx.doi.org/10.47689/2181-1415-vol2-iss1/s-pp170-177.

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The article examines the importance of introducing information technology into the education system, the impact of information technology on the quality of education. The creation and use of electronic textbooks in the learning process is recommended. This is important in a situation of insufficient provision of educational and methodological literature, as well as a way to resolve the contradiction between the desire to cover as much demonstration material as possible and practical. Since it takes time and some skill to master the specialized programming environment, e-tutorials can be created in a well-studied presentation preparation program. The use of software products based on the concept of “electronic patient” is emphasized. The article calls for the acquisition of knowledge, professional skills and abilities, and practical skills are not so much therapeutic and diagnostic manipulations as mastered methods of productive mental activity that provide correct, quick and economical diagnosis and effective treatment. The article will be useful to students, university professors, staff, and management personnel of the education system.
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Pyrozhenko, Vadym. "Integration of Social Knowledge by Government: A New Synthetic Model of Integration as Learning and Potential Research Directions." Administration & Society 52, no. 1 (February 28, 2018): 4–30. http://dx.doi.org/10.1177/0095399718760591.

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This article explores the potential of business knowledge management and sociology of knowledge to theorize the integration of social knowledge by government. It understands social knowledge as dispersed societal knowledge emerging in contemporary information societies. The proposed synthetic model of knowledge integration builds on Donald Schön’s idea of integration as learning and the ideal of government as a learning system. The article develops a new definition of social knowledge. It identifies knowledge management theories of interorganizational knowledge transfer and sociology of knowledge theories of the macro-contexts of knowledge production as most relevant to further theorize knowledge integration by government.
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Dissertations / Theses on the topic "Integration and transfer learning"

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Brenner, Aimee Michelle. "Investigating the Practices in Teacher Education that Promote and Inhibit Technology Integration in Early Career Teachers." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/39472.

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In an attempt to promote the transfer of technology integration knowledge and skills in preservice teachers, studies have attempted to identify effective instructional technology integration practices on the part of the teacher education program, as well as exemplary programs themselves (Hofer, 2005; Mergendoller et al., 1994; Strudler & Wetzler, 1999). A significant number of studies focus on examining various components of technology integration plans within teacher education programs, but few have extended this examination to determine if transfer is evidenced in the practices of graduates. The purpose of this study, therefore, was to identify instructional technology integration strategies and practices in preservice teacher education that contribute to the transfer of technology integration knowledge and skills to the instructional practices of early career teachers. This study employed a two-phase, sequential explanatory strategy, where quantitative data were collected via an online survey during the first phase and then interview data were collected during the second phase. The targeted sample population for this research study consisted of male and female early career teachers who had completed a graduate level teacher education program through the School of Education (SOE) at a large, research university located in the Southeast. Overall, these early career teachers assessed themselves as being proficient users of instructional technologies and feeling comfortable with their level of technology integration in the classroom. Out of nine qualities demonstrated in literature to promote learning transfer of technology integration knowledge and skills, the early career teachers reported the top three factors found in the study institution to be: the modeling of effective uses of technology integration by faculty in content-specific areas; opportunities to reflect upon technology integration practices in the classroom; and opportunities to practice and experiment with instructional technologies. The early career teachers reported the three top barriers inhibiting technology integration in their classrooms as being: too much content to cover; lack of time to design and implement technology-enhanced lessons; and a lack of software resources. Although a majority of the early career teachers reported that the teacher education program overall prepared them to integrate technology into the classroom, they also reported that opportunities to practice technology integration and having access to expert guidance during their field experiences were lacking. Several suggestions were made by study respondents and these included: providing more opportunities to experiment and play with instructional technologies like SmartBoards; faculty support with regards to implementing and practicing with technology integration in field experiences; and technology courses that focus on up-to-date instructional technology tools within each of the content areas. Findings from this study might be useful to teacher educators and researchers because it provides naturalistic recommendations (Stake, 1995) on how to improve their programs that are corroborated by the literature, and it offers an adapted survey that can be utilized to investigate technology integration transfer from the teacher education period to the early classroom practice period of new teachers.
Ph. D.
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Glaister, Karen. "Learning and transfer of dosage calculations: An evaluation of integrative and computerised instructional approaches." Thesis, Glaister, Karen (1998) Learning and transfer of dosage calculations: An evaluation of integrative and computerised instructional approaches. Masters by Research thesis, Murdoch University, 1998. https://researchrepository.murdoch.edu.au/id/eprint/52195/.

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Dosage calculations are an essential skill for current nurse practitioners. The challenge for educators is to determine how the learner can be best assisted to learn and apply both general and specific knowledge and skills. This fundamental issue of providing instruction that is meaningful and able to be utilised in another setting is an age-old concern. It can be seen from the posology literature that outcomes from a diversity of instructional attempts have generally been limited. This exploratory field study investigated the effect of specifically prepared instructional approaches upon learning outcome and also the learners' ability to transfer this knowledge. The research is grounded in both transfer of learning and metacognitive-regulatory theory. Three instructional approaches were developed and considered in this study. The computerised learning approach was designed to encourage the low-road of learning providing for automaticity in skill performance. The integrative learning approach incorporated process-oriented instruction to support high-road learning and also repetitive practice to foster the low-road of learning. In addition, it included small group discussion to address the affective component of mathematical phobia often intrinsic to dosage calculations. The third approach combined the strategies provided in both the computerised and integrative learning approaches. Based upon the literature, it was assumed that the integrative approach would be most effective in developing all forms of knowledge, particularly conditional knowledge, and consequently greater performance in far transfer tasks would be evidenced. Furthermore, this effect would be greatest in those learners who reported a negative attitude towards mathematics and mathematical testing and who also lacked self-regulation or external-regulation of learning. The combination of the computerised and integrative approach was expected to enhance the low-road of learning and consequently greater performance on near transfer tasks would be evidenced. Evaluation used a methodological mix of both quantitative and qualitative approaches. The findings were not entirely conclusive, although they did offer some support to the study claims and interesting insight into other issues that need to be accounted for in exploratory field studies of this type. Overall, it appeared that computerised learning might have been more influential in the development of procedural knowledge. However, when learners reported higher levels of negative attitudes towards mathematics and mathematical testing the integrative approach was more effective than the computerised approach in developing procedural knowledge. There was some evidence to suggest that when the learner reported being highly self-regulated or reliant on external-regulation, procedural knowledge development was interfered with when they received the combination of computerised and integrative learning. Although not statistically proven the integrative approach did result in higher scores on conditional knowledge measures in both the first and second post-tests. However when the effect of negative attitudes towards mathematics and mathematical testing was accounted for, then statistical support was evident, indicating that the integrative approach was more effective than the computerised approach under these circumstances. This effect was also noted when the learner reported a medium level of self-regulation. Generally the reported level of metacognitive-regulation did not appear to influence the treatment effects. None of the treatments examined demonstrated greater effectiveness on measures of far transfer. These results support the findings of earlier studies both within the posology and transfer of learning literature asserting that the phenomenon of transfer can be elusive and does not naturally ensue from attempts made to improve upon instructional approaches. However due to institutional constraints the intervention period in the present study was markedly short affecting the integrity of the conceptual framework underlying the study. Despite this, the statistical evidence from the study suggests that both the integrative and computerised learning approach are worthy inclusions into future instructional approaches aimed towards developing competency in dosage calculations.
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Chapman, Shelley Ann. "A Theory of Curriculum Development in the Professions: An Integration of Mezirow's Transformative Learning Theory with Schwab's Deliberative Curriculum Theory." [Yellow Springs, Ohio] : Antioch University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1173793131.

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Thesis (Ph. D.)--Antioch University, 2007.
Title from PDF t.p. (viewed Apr. 10, 2007). Advisor: Jon F. Wergin. Keywords: transformative learning theory, deliberative curriculum theory, graduate professional education, theory building, higher education. Includes bibliographical references (p. 377-399).
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Katzenbach, Michael. "Individual Approaches in Rich Learning Situations Material-based Learning with Pinboards." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-80328.

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Active Approaches provide chances for individual, comprehension-oriented learning and can facilitate the acquirement of general mathematical competencies. Using the example of pinboards, which were developed for different areas of the secondary level, workshop participants experience, discuss and further develop learning tasks, which can be used for free activities, for material based concept formation, for coping with heterogeneity, for intelligent exercises, as tool for the presentation of students’ work and as basis for games. The material also allows some continuous movements and can thus prepare an insightful usage of dynamic geometry programs. Central Part of the workshop is a work-sharing group work with learning tasks for grades 5 to 8. The workshop will close with a discussion of general aspects of material-based learning.
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Johnson, Travis Steele. "Integrative approaches to single cell RNA sequencing analysis." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1586960661272666.

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Mogofe, Romulus Asaph. "Integrating language literacy skills in teaching physical sciences in Riba Cross District, South Africa." Thesis, University of Limpopo, 2016. http://hdl.handle.net/10386/1590.

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Thesis (M. A. (Education)) -- University of Limpopo, 2016
Poor performance, by English Language Learners (ELLs), in Science examinations remains a thorny issue in countries where English is not the home language. Research around the world and the Department of Basic Education in South Africa have long recommended the integration of Language Literacy skills in the teaching of Physical Sciences in order to solve this issue. Despite that, learners’ poor performance in Physical Sciences examinations has been found to be positively related to low language literacy skills. The questions are: Do Physical Sciences teachers integrate language literacy skills in teaching the subject?; If yes, to what extent is the integration of language literacy skills practiced in Physical Sciences classroom? In an attempt to answer the above questions, a quantitative survey was carried out in Riba Cross District of Sekhukhune Region of Limpopo Province in South Africa. 211 learners and five teachers from selected nine schools took part in the study and questionnaires were used to collect data. Data were analysed using descriptive and inferential statistics and the Statistical Package for the Social Sciences (SPSS) version 22 was used. The results indicate that Language Literacy skills are integrated into the teaching of Physical Sciences in Riba Cross District, despite concerns raised by the teachers. The areas of concern include letting learners to argue using evidences and writing reports. Furthermore, schools with large classes have challenges in integrating Language Literacy Skills in the teaching of Physical Sciences. Therefore, further studies are recommended which should integrate both qualitative and quantitative approaches in school contexts.
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Gardner, Trevor. "Wireless Power Transfer Roadway Integration." DigitalCommons@USU, 2017. https://digitalcommons.usu.edu/etd/6866.

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Electric vehicles represent a major accomplishment in the energy and transportation industry. Unfortunately, they are restricted to a small travel range because of limited battery life. Successful integration of wireless power transfer (WPT) systems into the infrastructure would remove the range restrictions of EVs. To successfully integrate this technology, several requirements must be met. First, the embedment process cannot interfere with the electrical performance of the inductive power transfer (IPT) system. Second, the presence of the IPT system in the pavement structure cannot negatively affect the roadway’s lifespan. Several systems were directly embedded in roadway materials. The electrical properties of the systems were monitored during the embedment process. Then modifications were made to the IPT systems to optimize the embedment process. These modifications were then applied to a full scale IPT system which is being used to dynamically charge EVs. To test the structural performance of the systems, tensile stresses were applied to the pads to simulate traffic loading conditions. These tensile stresses were applied under cyclic loading conditions to simulate fatigue conditions found in roadways. The number of cycles, and stress at failure was recorded an analyzed. The electrical properties of the IPT pads was also measured and analyzed during the fatigue loading conditions.
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Shell, Jethro. "Fuzzy transfer learning." Thesis, De Montfort University, 2013. http://hdl.handle.net/2086/8842.

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The use of machine learning to predict output from data, using a model, is a well studied area. There are, however, a number of real-world applications that require a model to be produced but have little or no data available of the specific environment. These situations are prominent in Intelligent Environments (IEs). The sparsity of the data can be a result of the physical nature of the implementation, such as sensors placed into disaster recovery scenarios, or where the focus of the data acquisition is on very defined user groups, in the case of disabled individuals. Standard machine learning approaches focus on a need for training data to come from the same domain. The restrictions of the physical nature of these environments can severely reduce data acquisition making it extremely costly, or in certain situations, impossible. This impedes the ability of these approaches to model the environments. It is this problem, in the area of IEs, that this thesis is focussed. To address complex and uncertain environments, humans have learnt to use previously acquired information to reason and understand their surroundings. Knowledge from different but related domains can be used to aid the ability to learn. For example, the ability to ride a road bicycle can help when acquiring the more sophisticated skills of mountain biking. This humanistic approach to learning can be used to tackle real-world problems where a-priori labelled training data is either difficult or not possible to gain. The transferral of knowledge from a related, but differing context can allow for the reuse and repurpose of known information. In this thesis, a novel composition of methods are brought together that are broadly based on a humanist approach to learning. Two concepts, Transfer Learning (TL) and Fuzzy Logic (FL) are combined in a framework, Fuzzy Transfer Learning (FuzzyTL), to address the problem of learning tasks that have no prior direct contextual knowledge. Through the use of a FL based learning method, uncertainty that is evident in dynamic environments is represented. By combining labelled data from a contextually related source task, and little or no unlabelled data from a target task, the framework is shown to be able to accomplish predictive tasks using models learned from contextually different data. The framework incorporates an additional novel five stage online adaptation process. By adapting the underlying fuzzy structure through the use of previous labelled knowledge and new unlabelled information, an increase in predictive performance is shown. The framework outlined is applied to two differing real-world IEs to demonstrate its ability to predict in uncertain and dynamic environments. Through a series of experiments, it is shown that the framework is capable of predicting output using differing contextual data.
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Alexander, John W. "Transfer in reinforcement learning." Thesis, University of Aberdeen, 2015. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=227908.

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The problem of developing skill repertoires autonomously in robotics and artificial intelligence is becoming ever more pressing. Currently, the issues of how to apply prior knowledge to new situations and which knowledge to apply have not been sufficiently studied. We present a transfer setting where a reinforcement learning agent faces multiple problem solving tasks drawn from an unknown generative process, where each task has similar dynamics. The task dynamics are changed by varying in the transition function between states. The tasks are presented sequentially with the latest task presented considered as the target for transfer. We describe two approaches to solving this problem. Firstly we present an algorithm for transfer of the function encoding the stateaction value, defined as value function transfer. This algorithm uses the value function of a source policy to initialise the policy of a target task. We varied the type of basis the algorithm used to approximate the value function. Empirical results in several well known domains showed that the learners benefited from the transfer in the majority of cases. Results also showed that the Radial basis performed better in general than the Fourier. However contrary to expectation the Fourier basis benefited most from the transfer. Secondly, we present an algorithm for learning an informative prior which encodes beliefs about the underlying dynamics shared across all tasks. We call this agent the Informative Prior agent (IP). The prior is learnt though experience and captures the commonalities in the transition dynamics of the domain and allows for a quantification of the agent's uncertainty about these. By using a sparse distribution of the uncertainty in the dynamics as a prior, the IP agent can successfully learn a model of 1) the set of feasible transitions rather than the set of possible transitions, and 2) the likelihood of each of the feasible transitions. Analysis focusing on the accuracy of the learned model showed that IP had a very good accuracy bound, which is expressible in terms of only the permissible error and the diffusion, a factor that describes the concentration of the prior mass around the truth, and which decreases as the number of tasks experienced grows. The empirical evaluation of IP showed that an agent which uses the informative prior outperforms several existing Bayesian reinforcement learning algorithms on tasks with shared structure in a domain where multiple related tasks were presented only once to the learners. IP is a step towards the autonomous acquisition of behaviours in artificial intelligence. IP also provides a contribution towards the analysis of exploration and exploitation in the transfer paradigm.
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Badley, Kenneth Rea. "Integration" and "the integration of faith and learning." Thesis, University of British Columbia, 1986. http://hdl.handle.net/2429/26769.

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This study attempts to determine what use the term "integration" has in educational discourse, specifically as it appears in the popular phrase in Christian higher education, "the integration of faith and learning." Chapter I records that many educators see widespread disintegration in contemporary education. This perceived disintegration has led to many calls and proposals for educational integration. While educators perceive this increased need for integration, what "integration" means is less and less clear. By surveying actual usage in educational writing, this thesis distinguishes four general senses of "integration": fusion, incorporation, correlation, and dialogical (in Appendix A and Chapter III). It then explores further typical elements of meaning in educational uses of "integration" (Chapter IV). Chapters III and IV reveal and discuss a number of points of contention between educators as to the "meaning of integration." Chapter V identifies five main sources of the confusion that often accompanies uses of "integration." It is a positive term and frequently is employed primarily for its value as a slogan. Different educators give "integration" at least three different psychological meanings. The same word is used to denote both processes and end states. It is a polymorphous term whose meaning is not clear until what is being integrated is specified. It is a terra that invites conception-building, though conceptions are rarely announced as such; usually educators' visions of what ought to be come cloaked as definitions of terms. "The integration of faith and learning" suffers from every weakness that "integration" itself encounters. Its popularity in certain sectors of church education is understandable when considered in its historical context: some branches of the church that once largely abandoned higher education are now trying to express a new interest in it. "Integration" is a choice word to serve as a slogan that expresses a certain conception of Christian education. Beyond its function as a slogan, and despite the other problems that frequently accompany its use, "integration" does have use in education, partly because integration is an important concept in education.
Education, Faculty of
Graduate
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Books on the topic "Integration and transfer learning"

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Leontiy, Halyna. Multikulturelles Deutschland im Sprachvergleich: Das Deutsche im Fokus der meist verbreiteten Migrantensprachen : ein Handbuch für DaF-Lehrende und Studierende, für Pädagogen/-innen und Erzieher/-innen. Berlin: Lit, 2013.

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Short, Deborah. Integrating language and content instruction: Strategies and techniques. Washington, DC (1118 22nd St., NW, Washington 20037): National Clearinghouse for Bilingual Education, 1991.

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Snow, Marguerite Ann. The adjunct model of language instruction: Integrating language and content at the university. [Los Angeles, Calif.]: Center for Language Education and Research, University of California, Los Angeles, 1988.

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J, Fallows Stephen, and Steven Christine, eds. Integrating key skills in higher education: Employability, transferable skills, and learning for life. London: Kogan Page, 2000.

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Hohensee, Charles, and Joanne Lobato, eds. Transfer of Learning. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65632-4.

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Jemison, David. Strategic capability transfer in acquisition integration. Fontainbleau: INSEAD, 1986.

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Daffron, Sandra Ratcliff, and Sandra Ratcliff Daffron. Successful transfer of learning. Malabar, Fla: Krieger Pub. Co., 2011.

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Wehby, North Mary, ed. Successful transfer of learning. Malabar, Fla: Krieger Pub. Co., 2011.

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Hall, D. D. The transfer of learning. Norwich: University of East Anglia, 1992.

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Razavi-Far, Roozbeh, Boyu Wang, Matthew E. Taylor, and Qiang Yang, eds. Federated and Transfer Learning. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-11748-0.

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Book chapters on the topic "Integration and transfer learning"

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Lim, Doo Hun, and Brent Nowell. "Integration for Training Transfer: Learning, Knowledge, Organizational Culture, and Technology." In Transfer of Learning in Organizations, 81–98. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02093-8_6.

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Kilbrink, Nina. "Transfer of Learning Through Integration of Theory and Practice in Technical Vocational Education." In Transfer, Transitions and Transformations of Learning, 69–84. Rotterdam: SensePublishers, 2013. http://dx.doi.org/10.1007/978-94-6209-437-6_6.

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Gomaa, Walid. "Deep Architectures in Visual Transfer Learning." In Vision, Sensing and Analytics: Integrative Approaches, 1–27. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75490-7_1.

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Wang, Jingxian, Miao Li, Jian Zhang, WeiHui Zeng, and XuanJiang Yang. "DCNN Transfer Learning and Multi-model Integration for Disease and Weed Identification." In Image and Graphics Technologies and Applications, 216–27. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9917-6_21.

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Shapiee, Muhammad Nur Aiman, Muhammad Ar Rahim Ibrahim, Mohd Azraai Mohd Razman, Muhammad Amirul Abdullah, Rabiu Muazu Musa, and Anwar P. P. Abdul Majeed. "The Classification of Skateboarding Tricks by Means of the Integration of Transfer Learning and Machine Learning Models." In Embracing Industry 4.0, 219–26. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6025-5_20.

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Yao, Pei, and Liang Feng. "Integrating Policy Reuse with Learning from Demonstrations for Knowledge Transfer in Deep Reinforcement Learning." In Communications in Computer and Information Science, 659–67. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-92307-5_77.

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Bouchey, Bettyjo, Jill Castek, and John Thygeson. "Multimodal Learning." In Innovative Learning Environments in STEM Higher Education, 35–54. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-58948-6_3.

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AbstractThe widespread use of technology in the digital age continually shapes how individuals consume knowledge and learn. In the digital age, ideas are shared and represented in multiple formats and through the integration of multiple modes. Technological advances, coupled with considerations of the changing needs of today’s learners, call for exploring new directions for multimodal teaching and learning. Yet, society’s increasing reliance on, and use of, technologies for communication and learning has introduced expanded forms of meaning-making. Information and communication technologies (ICTs) and the online networks that are facilitated by their use encourage educators to transform the way education is delivered. Learning environments are in need of becoming transformed so students are able to use immersive technologies to expand their learning opportunities. This chapter explores emerging trends and pedagogies in multimodal learning that seek to take advantage of the digital tools, texts, and learning approaches that are continually shaping the ways learning occurs inside and outside of higher education.This chapter is outlined to highlight what is found in the literature on multimodal instruction, what findings were realized at eXploring the Future of Innovative Learning Environments (X-FILEs) workshops, and lastly how multimodal instruction can be used to transform the classroom of the future. Throughout this chapter, readers will get to know a student of the future, Juan Delgado. He attends a 4-year university in Dallas, Texas, and is majoring in Mechanical Engineering taking his Introduction to the Fundamentals of Science course. Each aspect of the learning process as it relates to multimodal instruction in 2023 is outlined through the experiences of Juan to situate the impact to learners.
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Shapiee, Muhammad Nur Aiman, Muhammad Ar Rahim Ibrahim, Mohd Azraai Mohd Razman, Muhammad Amirul Abdullah, Rabiu Muazu Musa, Noor Azuan Abu Osman, and Anwar P. P. Abdul Majeed. "The Classification of Skateboarding Tricks by Means of the Integration of Transfer Learning Models and K-Nearest Neighbors." In Lecture Notes in Electrical Engineering, 439–50. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4597-3_40.

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Singkaew, Chan, and Sumalee Chaijaroen. "Development of Constructivist Web-Based Learning Environment Model to Enhance Problem-Solving and Transfer of Learning on Student in Industrial: Integration Between Pedagogy and Neuroscience." In Lecture Notes in Computer Science, 399–408. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63885-6_45.

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Mangayarkarasi, R., C. Vanmathi, Rachit Jain, and Priyansh Agarwal. "A Study and Comparative Analysis of Various Use Cases of NLP Using Sequential Transfer Learning Techniques." In Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics, 101–20. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003038450-7.

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Conference papers on the topic "Integration and transfer learning"

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Park, Myoung Soo. "Transfer learning capability of Evolving Logic Network." In Integration (IRI). IEEE, 2011. http://dx.doi.org/10.1109/iri.2011.6009556.

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Weiss, Karl R., and Taghi M. Khoshgoftaar. "Analysis of Transfer Learning Performance Measures." In 2017 IEEE International Conference on Information Reuse and Integration (IRI). IEEE, 2017. http://dx.doi.org/10.1109/iri.2017.43.

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Wen-Ting Chen, Jung-Chuan Yen, and Man-Kwan Shan. "Integration of transfer of learning to the adaptive learning environment." In Fifth IEEE International Conference on Advanced Learning Technologies (ICALT'05). IEEE, 2005. http://dx.doi.org/10.1109/icalt.2005.173.

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Hirchoua, Badr, Imadeddine Mountasser, Brahim Ouhbi, and Bouchra Frikh. "Evolutionary Deep Reinforcement Learning Environment: Transfer Learning-Based Genetic Algorithm." In iiWAS2021: The 23rd International Conference on Information Integration and Web Intelligence. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3487664.3487698.

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Rosario, Grant, Thomas Sonderman, and Xingquan Zhu. "Deep Transfer Learning for Traffic Sign Recognition." In 2018 IEEE International Conference on Information Reuse and Integration for Data Science (IRI). IEEE, 2018. http://dx.doi.org/10.1109/iri.2018.00034.

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Montella, Sebastien, Lina Rojas-Barahona, Frederic Bechet, Johannes Heinecke, and Alexis Nasr. "Transfer Learning and Masked Generation for Answer Verbalization." In Proceedings of the Workshop on Structured and Unstructured Knowledge Integration (SUKI). Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.suki-1.6.

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Zhou, Peng, Xiuling Wang, Ulises Morales, and Xiaoli Yang. "Integration of Virtual Reality and CFD Techniques for Thermal Fluid Education." In ASME 2017 Heat Transfer Summer Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/ht2017-4793.

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Engineering courses such as thermodynamics, fluid mechanics and heat transfer always involve many abstract math, physics concepts and equations — which are difficult to teach and understand. As fundamental courses in engineering programs, they are sometimes taught in big class size — where students may not receive adequate attention and assistance from instructors. To improve the teaching and learning efficiency, we proposed to develop virtual reality based interactive modules for learning computational fluid dynamics. In this paper, case-study learning module is demonstrated for conduction heat transfer. The programming languages of C# and Unity3D were used for the software development. Computational fluid dynamics simulation results obtained from ANSYS/FLUENT were incorporated in the program. The program has the integrated modules of mobility, interactivity, and controllability for the 3D modeling and simulations. Each module was developed separately for facilitating the program management, extension, and upgrades in the future. The developed interactive programs, incorporating rich, interactive, and engaging learning contexts, will help students gain and apply knowledge to solve real-world problems in mechanical engineering.
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Min Wu, Atsushi Yamashita, and Hajime Asama. "Rule abstraction and transfer in reinforcement learning by decision tree." In 2012 IEEE/SICE International Symposium on System Integration (SII 2012). IEEE, 2012. http://dx.doi.org/10.1109/sii.2012.6427332.

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Weiss, Karl R., Taghi M. Khoshgoftaar, and Oneeb Rehman. "Designing a Testing Framework for Transfer Learning Algorithms (Application Paper)." In 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI). IEEE, 2016. http://dx.doi.org/10.1109/iri.2016.27.

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Wang, Ningwei, Hongzhe Liu, and Cheng Xu. "Deep Learning for The Detection of COVID-19 Using Transfer Learning and Model Integration." In 2020 IEEE 10th International Conference on Electronics Information and Emergency Communication (ICEIEC). IEEE, 2020. http://dx.doi.org/10.1109/iceiec49280.2020.9152329.

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Reports on the topic "Integration and transfer learning"

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Lytvynova, Svitlana, Oleksandr Burov, Nataliia Demeshkant, Viacheslav Osadchyi, Сергій Олексійович Семеріков, Світлана Григорівна Литвинова, Олександр Юрійович Буров, Наталія Андріївна Демешкант, and В'ячеслав Володимирович Осадчий. Proceedings of the VI International Workshop on Professional Retraining and Life-Long Learning using ICT: Person-oriented Approach (3L-Person 2021) co-located with 17th International Conference on ICT in Education, Research, and Industrial Applications: Integration, Harmonization, and Knowledge Transfer (ICTERI 2021), Kherson, Ukraine, October 1, 2021. Криворізький державний педагогічний університет, March 2022. http://dx.doi.org/10.31812/123456789/6988.

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Proceedings of the VI International Workshop on Professional Retraining and Life-Long Learning using ICT: Person-oriented Approach (3L-Person 2021) co-located with 17th International Conference on ICT in Education, Research, and Industrial Applications
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Lozano-Perez, Tomas, and Leslie Kaelbling. Effective Bayesian Transfer Learning. Fort Belvoir, VA: Defense Technical Information Center, March 2010. http://dx.doi.org/10.21236/ada516458.

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Kumar, Sharad. Localizing Little Landmarks with Transfer Learning. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.6703.

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Klenk, Matthew, and Kenneth D. Forbus. Learning Domain Theories via Analogical Transfer. Fort Belvoir, VA: Defense Technical Information Center, January 2007. http://dx.doi.org/10.21236/ada470404.

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Waaili, Salim A., Sally Byrd, Susan Conrad, Ryan Curran, Susan Dass, Shantell Hampton, George Koduah, Debra Moore, and James Turner. Learning Asset Technology Integration Support Tool Design Document. Fort Belvoir, VA: Defense Technical Information Center, May 2010. http://dx.doi.org/10.21236/ada523974.

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Cohen, Paul, and Carole Beal. LGIST: Learning Generalized Image Schemas for Transfer. Fort Belvoir, VA: Defense Technical Information Center, February 2008. http://dx.doi.org/10.21236/ada491488.

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Kong, Q., A. Price, and S. Myers. Preliminary Transfer Learning Results on Israel Data. Office of Scientific and Technical Information (OSTI), April 2022. http://dx.doi.org/10.2172/1860678.

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Gorski, Nicholas A., and John E. Laird. Investigating Transfer Learning in the Urban Combat Testbed. Fort Belvoir, VA: Defense Technical Information Center, September 2007. http://dx.doi.org/10.21236/ada478847.

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Van Lehn, Kurt. Long Term Learning: Integration of Knowledge Acquisition and Knowledge Compilation. Fort Belvoir, VA: Defense Technical Information Center, January 1994. http://dx.doi.org/10.21236/ada274775.

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Thuc Bui, Michael Read, and Lawrence ives. Integration of Heat Transfer, Stress, and Particle Trajectory Simulation. Office of Scientific and Technical Information (OSTI), May 2012. http://dx.doi.org/10.2172/1040617.

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