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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Lee, Ga-Eun, Eric Mauro, Vincent Parissi, Cha-Gyun Shin, and Paul Lesbats. "Structural Insights on Retroviral DNA Integration: Learning from Foamy Viruses." Viruses 11, no. 9 (August 22, 2019): 770. http://dx.doi.org/10.3390/v11090770.
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Foamy viruses (FV) are retroviruses belonging to the Spumaretrovirinae subfamily. They are non-pathogenic viruses endemic in several mammalian hosts like non-human primates, felines, bovines, and equines. Retroviral DNA integration is a mandatory step and constitutes a prime target for antiretroviral therapy. This activity, conserved among retroviruses and long terminal repeat (LTR) retrotransposons, involves a viral nucleoprotein complex called intasome. In the last decade, a plethora of structural insights on retroviral DNA integration arose from the study of FV. Here, we review the biochemistry and the structural features of the FV integration apparatus and will also discuss the mechanism of action of strand transfer inhibitors.
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Li, Nan, William Cohen, and Ken Koedinger. "Integrating Transfer Learning in Synthetic Student." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (July 5, 2010): 1943–44. http://dx.doi.org/10.1609/aaai.v24i1.7784.
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Building an intelligent agent, which simulates human-level learning appropriate for learning math, science, or a second language, could potentially benefit both education in understanding human learning, and artificial intelligence in creating human-level intelligence. Recently, we have proposed an efficient approach to acquiring procedural knowledge using transfer learning. However, it operated as a separate module. In this paper, we describe how to integrate this module into a machine-learning agent, SimStudent, that learns procedural knowledge from examples and through problem solving. We illustrate this method in the domain of algebra, after which we consider directions for future research in this area.
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Volkova, Nataliia, Olga Lebid’, and Anastasiia Tokarieva. "Interdisciplinary Integration as the Basis of a Complex Approach to the Doctors of Philosophy Training Program." Bulletin of Luhansk Taras Shevchenko National University 1, no. 1 (349) (2022): 5–19. http://dx.doi.org/10.12958/2227-2844-2022-1(349)-1-5-19.
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The article is devoted to the analysis of interdisciplinary integration as a foundation for improving the effectiveness of scientific, theoretical and practical training of a new generation of teachers for professional and higher education. The key terms of the studied phenomenon – integration, integrative learning, integrative knowledge, «transferable skills» are considered. The four levels of integration possible in the learning process are described. Examples of foreign experience in the implementation of an integrated approach into the educational process in France, America, Finland, England are discussed, which can be used in the implementation of an integrated approach to the organization of the educational process in Ukrainian HEIs. The phenomenon of interdisciplinary integration is presented as a process of harmonizing the content of disciplines so that they reflect their singularity, continuity and holistic character of a professional activity, which leads to the strengthening of interdisciplinary links while maintaining theoretical and practical integrity of these disciplines. The results of implementing the integrated approach are described. As a result, future doctors of philosophy gain the ability to construct logical connections and ask research questions, find the necessary information, compare concepts and create integrative schemes for a holistic understanding of a phenomenon or a situation, transfer knowledge from one field to another and from one situation to a different one. Particular focus in the article is put on the questions of interdisciplinary integration in the system of future doctors of philosophy training.
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Shapiee, Muhammad Nur Aiman, Muhammad Ar Rahim Ibrahim, Muhammad Amirul Abdullah, Rabiu Muazu Musa, Noor Azuan Abu Osman, Anwar P.P Abdul Majeed, and Mohd Azraai Mohd Razman. "The Classification of Skateboarding Tricks : A Transfer Learning and Machine Learning Approach." MEKATRONIKA 2, no. 2 (October 27, 2020): 1–12. http://dx.doi.org/10.15282/mekatronika.v2i2.6683.
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The skateboarding scene has arrived at new statures, particularly with its first appearance at the now delayed Tokyo Summer Olympic Games. Hence, attributable to the size of the game in such competitive games, progressed creative appraisal approaches have progressively increased due consideration by pertinent partners, particularly with the enthusiasm of a more goal-based assessment. This study purposes for classifying skateboarding tricks, specifically Frontside 180, Kickflip, Ollie, Nollie Front Shove-it, and Pop Shove-it over the integration of image processing, Trasnfer Learning (TL) to feature extraction enhanced with tradisional Machine Learning (ML) classifier. A male skateboarder performed five tricks every sort of trick consistently and the YI Action camera captured the movement by a range of 1.26 m. Then, the image dataset were features built and extricated by means of three TL models, and afterward in this manner arranged to utilize by k-Nearest Neighbor (k-NN) classifier. The perception via the initial experiments showed, the MobileNet, NASNetMobile, and NASNetLarge coupled with optimized k-NN classifiers attain a classification accuracy (CA) of 95%, 92% and 90%, respectively on the test dataset. Besides, the result evident from the robustness evaluation showed the MobileNet+k-NN pipeline is more robust as it could provide a decent average CA than other pipelines. It would be demonstrated that the suggested study could characterize the skateboard tricks sufficiently and could, over the long haul, uphold judges decided for giving progressively objective-based decision.
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Sugiharti, Endang, Riza Arifudin, Dian Tri Wiyanti, and Arief Broto Susilo. "Integration of convolutional neural network and extreme gradient boosting for breast cancer detection." Bulletin of Electrical Engineering and Informatics 11, no. 2 (April 1, 2022): 803–13. http://dx.doi.org/10.11591/eei.v11i2.3562.
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With the most recent advances in technology, computer programming has reached the capabilities of human brain to decide things for almost all healthcare systems. The implementation of Convolutional Neural Network (CNN) and Extreme Gradient Boosting (XGBoost) is expected to improve the accurateness of breast cancer detection. The aims of this research were to; i) determine the stages of CNN-XGBoost integration in diagnosis of breast cancer and ii) calculate the accuracy of the CNN-XGBoost integration in breast cancer detection. By combining transfer learning and data augmentation, CNN with XGBoost as a classifier was used. After acquiring accuracy results through transfer learning, this reasearch connects the final layer to the XGBoost classifier. Furthermore, the interface design for the evaluation process was established using the Python programming language and the Django platform. The results: i) the stages of CNN-XGBoost integration on histopathology images for breast cancer detection were discovered. ii) Achieved a higher level of accuracy as a result of the CNN-XGBoost integration for breast cancer detection. In conclusion, breast cancer detection was revealed through the integration of CNN-XGBoost through histopathological images. The combination of CNN and XGBoost can enhance the accuracy of breast cancer detection.
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Pons, José Amenós, Aoife Ahern, and Pedro Guijarro Fuentes. "L1 French learning of L2 Spanish past tenses: L1 transfer versus aspect and interface issues." Studies in Second Language Learning and Teaching 7, no. 3 (September 15, 2017): 489–515. http://dx.doi.org/10.14746/ssllt.2017.7.3.7.
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This paper examines the process of acquiring L2s that are closely related to the L1 through data on how adult French speakers learning L2 Spanish in a formal setting develop knowledge and use of past tenses in this L2. We consider the role of transfer and simplification in acquiring mental representations of the L2 grammar, specifically in the area of tense and aspect, and how learners deal with integrating grammatically encoded, lexical and discursive information, including mismatching feature combinations leading to particular inferential effects on interpretation. Data is presented on the Spanish past tenses (simple and compound past, pluperfect, imperfect and progressive forms) from two tasks, an oral production filmretell and a multiple-choice interpretation task, completed by learners at A2, B1, B2 and C1 CEFR levels (N = 20-24 per level). L1 influence is progressively attenuated as proficiency increases. Difficulties were not always due to negative L1 transfer, but related also to grammar-discourse interface issues when integrating linguistic and pragmatic information in the interpretation process. This has clear implications for the teaching of closely related languages: instruction should not only focus on crosslinguistic contrasts, but also prioritize uses requiring complex interface integration, which are harder to process.
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Zhao, Xinzhuo, Shouliang Qi, Baihua Zhang, He Ma, Wei Qian, Yudong Yao, and Jianjun Sun. "Deep CNN models for pulmonary nodule classification: Model modification, model integration, and transfer learning." Journal of X-Ray Science and Technology 27, no. 4 (September 4, 2019): 615–29. http://dx.doi.org/10.3233/xst-180490.
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Bogicevic-Milikic, Biljana, and Ana Aleksic. "International human resource management and organizational learning." Ekonomski anali 50, no. 167 (2005): 171–98. http://dx.doi.org/10.2298/eka0567171b.
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Global companies are pressed by the need to simultaneously manage globally since they consider the whole world as their own market, and locally, because the global market consists of various different and weakly connected market segments. The need to be global and local at the same time presents, perhaps the most important challenge for management of global companies in 21st century. Searching this balance presents also an important challenge for human resource management (HRM), regarding the ways of accomplishing it. HRM is expected to contribute to achievement of global competitive advantage worldwide efficiency, local responsiveness, as well as transfer of learning within global organizations. The transfer of learning gains on its importance as many authors see it as the main motive of establishing global companies. However, regardless of recognized significance of organizational learning for global companies, international HRM literature simply lacks studies related to transfer of learning, recommendations about how to develop this organizational ability, how to improve it and measure, and how to provide permanency of the learning process. Therefore, the aim of this paper is through reviewing the relevant literature, to shed light on different aspects of the responsiveness-integration paradigm and its implications on the transfer of learning in global companies.
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Gourisaria, Mahendra Kumar, Rakshit Agrawal, Vinayak Singh, Manoj Sahni, and Linesh Raja. "Comparison of Garbage Classification Frameworks Using Transfer Learning and CNN." International Journal of Social Ecology and Sustainable Development 13, no. 9 (January 4, 2022): 1–23. http://dx.doi.org/10.4018/ijsesd.313973.
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With the never-ending increase in the population, garbage and other waste materials have become one of the major hurdles in forming a healthy environment. The proliferation in the development of such schemes and integration of technology brings up the concept of smart waste management based on its biodegradability. These proposed models can be found useful to the smart waste development program and other likely schemes which require the classification of garbage based on their images. The experiment uncovers the reasons behind the working of VGG19 and A9 architecture CNN-based models which were found to provide the best results in accurately detecting the type of garbage. Experimental evaluation was based on 27 models including out of which A9 and VGG19 models were found to be the most efficient ones with 92.24% and 86.35% accuracy, respectively, which are further compared in detail for understanding these models better.
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Xue, Chun Yan. "Development Direction of Machine Learning in the Era of Big Data." Advanced Materials Research 971-973 (June 2014): 1590–93. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.1590.
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The core objective of Big Data technology is trying to dig out valuable information from massing huge variety of data structures. In order to achieve these goals, Big Data technology must be combined with machine learning. The uniqueness of Big Data has also brought unprecedented challenges to machine learning, in order to cope with these challenges machine learning should focus on the development of semi-supervised learning method, integrated learning with device integration and transfer learning method.
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Sajeva, Maurizio, Marjo Maidell, and Jonne Kotta. "A Participatory Geospatial Toolkit for Science Integration and Knowledge Transfer Informing SDGs Based Governance and Decision Making." Sustainability 12, no. 19 (September 30, 2020): 8088. http://dx.doi.org/10.3390/su12198088.
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While the specialisation of science is important for understanding specific systems, the isolation of scientific schools in their disciplinary silos makes it harder to understand the interactions within and between systems and limits the wisdom about the whole systems’ sustainability. Science integration and its practical implementation is a key factor of success for sustainable development. The aim of this paper is to present a participatory geospatial toolkit developed during the BONUS MARES project that enables science integration and knowledge transfer informing SDGs based governance and decision making. This was realized through the Eco-GAME (Governance Assessment Matrix Exercise) framework, trans-disciplinary social learning for the meta-evaluation of existing knowledge about human-nature systems interaction—manifested through ecosystem services. The Eco-GAME was applied to a participatory geospatial toolkit that translates complex ecological knowledge on ecosystems, ecosystem functions, and services produced into more usable forms to inform evidence-based decision-making in pursuit of the Sustainable Development Goals (SDGs). This is the first attempt, in the context of geospatial applications, to support dynamic interaction, trans-disciplinary social-learning, and multi-dimensional appreciation of ecosystem services for integrating ecological, non-economic and economic knowledge and methods. The toolkit is being implemented in the MAREA project.
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Deneve, Sophie. "Bayesian Spiking Neurons II: Learning." Neural Computation 20, no. 1 (January 2008): 118–45. http://dx.doi.org/10.1162/neco.2008.20.1.118.
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In the companion letter in this issue (“Bayesian Spiking Neurons I: Inference”), we showed that the dynamics of spiking neurons can be interpreted as a form of Bayesian integration, accumulating evidence over time about events in the external world or the body. We proceed to develop a theory of Bayesian learning in spiking neural networks, where the neurons learn to recognize temporal dynamics of their synaptic inputs. Meanwhile, successive layers of neurons learn hierarchical causal models for the sensory input. The corresponding learning rule is local, spike-time dependent, and highly nonlinear. This approach provides a principled description of spiking and plasticity rules maximizing information transfer, while limiting the number of costly spikes, between successive layers of neurons.
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Ricucci, Roberta. "Learning by sharing and integration of second-generation: the Italian case." Migration Letters 13, no. 2 (May 1, 2016): 193–202. http://dx.doi.org/10.33182/ml.v13i2.301.
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The aim of the paper is to show how - apart from rhetoric about interculturalism and good integration practices - today's second generations in Italy are still facing stereotypes or outright discrimination. Comparison with historical minorities and with internal migration has left little trace in the memory of many Italians of knowledge of, and ability to manage, relations with otherness in the daily practices of many institutions (from schools to social-health services). It is a situation of “suspension of memory” delaying or negatively influencing insertion processes: in other words, the assumption that people learn from history and successfully repeat today policies which have been implemented in the past is contradicted in everyday practice. And second generations are the living proof of this lack of knowledge transfer. The academic, socialisation and identity problems facing the children of immigration today could have been reduced if teachers, educators and social workers had benefitted from experience of the past.
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Smits, Emely, and Janice Ferguson. "Integration Tutorials and Seminars: A Creative Learning Approach for Occupational Therapy Curricula." Canadian Journal of Occupational Therapy 67, no. 3 (April 2000): 86–92. http://dx.doi.org/10.1177/000841740006700301.
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This paper, the first of two companion papers, describes a creative learning approach. Integration Tutorials and Seminars were developed to address concerns of regional fieldwork-education coordinators and preceptors about the ability of third-year student occupational therapists to integrate and apply academic and theoretical knowledge during fieldwork. This ability can be gained through experiential learning in the academic setting and is essential for the effective transfer of academic learning into the students' fieldwork-education experiences (Dale, 1994; Fidler, 1996; McCaugherty, 1991; Neistadt, 1996). The Modified Learning Model of Svinicki and Dixon (1987) was used as a template for an academic course fostering experiential learning. An important secondary goal was to nurture student self-directedness in learning using the philosophy of the Staged Self-Directed Learning Model (Grow, 1991). Case studies were used as a vehicle for engaging and challenging the students. The philosophy, guidelines and process of the Integration Tutorials and Seminars are presented and have the potential to be adapted for occupational therapy curricula around the globe.
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Gxekwa, Nozuko, and Nomsa Satyo. "The use of isiXhosa children’s poetry as a tool to integrate literacy, mathematics and life skills in Foundation Phase: Grade R-3." South African Journal of Childhood Education 7, no. 1 (December 14, 2017): 7. http://dx.doi.org/10.4102/sajce.v7i1.530.
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Literature helps us understand and make sense of the world around us. It is a part of education, which broadens one’s mind about how to understand, transfer knowledge and provide meaningful and authentic learning. Thus, this article aims to highlight how some elements of isiXhosa children’s poetry can be used to help pre-service teachers to teach and integrate mathematics and life skills with literacy in Foundation Phase (FP). This approach of using poems for integration strengthens concepts and skills in more than one subject area. The theoretical framework that informed the article is integrative learning. The data in this article were generated through non-participant classroom observations and non-structured interviews with the participants of the study and the researchers adopted the interpretative phenomenological analysis method for data analysis. This article was prompted by findings of lack of understanding of integrative teaching and learning and lack of teaching resources in isiXhosa to enhance integrative teaching and learning in FP intervention undertaken with 25 first year isiXhosa-speaking FP students.
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Phye, Gary D., and Sue A. Johnson. "Cognitive training: Improving problem-solving transfer skills of learning disabled students." Educational and Child Psychology 26, no. 3 (2009): 59–70. http://dx.doi.org/10.53841/bpsecp.2009.26.3.59.
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AbstractThe effectiveness of cognitive training with the Cognitive Training for Children Programme (Klauer & Phye, 1994) and other forms of the Klauer training programmes has been recently reviewed (Klauer & Phye, 2008). Numerous meta-analyses confirm the wide spread effectiveness of training inductive reasoning skills with different ability groups at varying ages in various settings. The majority of these studies were conducted in Germany. The present study was designed to determine the effectiveness of the English form of the Cognitive Training for Children Programme (Klauer & Phye, 1994) in a clinical setting. Theoretically, focus was on the impact of meaningful practice with inductive reasoning strategies on the growth of problem-solving transfer ability of learning disabled children. Future research efforts involving an integration of dynamic assessment techniques, and the cognitive analysis of practice using the Cognitive Training for Children Programme is recommended.
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Pop, Ioan G., Mihai-Florin Talpos, and Igor Prisac. "A Transdisciplinary Approach on the Advanced Sustainable Knowledge Integration." Balkan Region Conference on Engineering and Business Education 1, no. 1 (November 1, 2015): 215–25. http://dx.doi.org/10.1515/cplbu-2015-0025.
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AbstractThe paper presents a new, transdisciplinary approach on the DIKW (Data, Information, Knowledge, and Wisdom) hierarchy, offering arguments that the hierarchy is unsound and even methodologically undesirable. The purpose of the paper is to identify a new and more complete perspective on knowledge integration. This model is based on another scale, in a synergistic-generative transdisciplinary manner, in order to transfer and implement knowledge in the knowledge based society/economy context. The new knowledge pattern, named DIMLAK (Data, Information, Messages, Learning, and Advanced Knowledge) is reconfigured to explain the way the advanced knowledge is achieved as a top level of the transdisciplinary integrated and integrative knowledge system. The proposed model is working complementarily as breadth through depth approach, opening a new vision in the knowledge achieving process.
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Huraj, Ladislav, Tibor Horak, Peter Strelec, and Pavol Tanuska. "Mitigation against DDoS Attacks on an IoT-Based Production Line Using Machine Learning." Applied Sciences 11, no. 4 (February 19, 2021): 1847. http://dx.doi.org/10.3390/app11041847.
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Industry 4.0 collects, exchanges, and analyzes data during the production process to increase production efficiency. Internet of Things (IoT) devices are among the basic technologies used for this purpose. However, the integration of IoT technology into the industrial environment faces new security challenges that need to be addressed. This is also true for a production line. The production line is a basic element of industrial production and integrating IoT equipment allows one to streamline the production process and thus reduce costs. On the other hand, IoT integration opens the way for network cyberattacks. One possible cyberattack is the increasingly widely used distributed denial-of-service attack. This article presents a case study that demonstrates the devastating effects of a DDOS attack on a real IoT-based production line and the entire production process. The emphasis was mainly on the integration of IoT devices, which could potentially be misused to run DDoS. Next, the verification of the proposed solution is described, which proves that it is possible to use the sampled flow (sFlow) stream to detect and protect against DDoS attacks on the running production line during the production process.
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Yang, Peihao, Jiarui Chen, Lihao Wu, and Sheng Li. "Fault Identification of Electric Submersible Pumps Based on Unsupervised and Multi-Source Transfer Learning Integration." Sustainability 14, no. 16 (August 10, 2022): 9870. http://dx.doi.org/10.3390/su14169870.
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The ratio between normal data and fault data generated by electric submersible pumps (ESPs) in production is prone to imbalance, and the information carried by the fault data generally as a minority sample is easily overwritten by the normal data as a majority sample, which seriously interferes with the fault identification effect. For the problem that data imbalance under different working conditions of ESPs causes the failure data to not be effectively identified, a fault identification method of ESPs based on unsupervised feature extraction integrated with migration learning was proposed. Firstly, new features were extracted from the data using multiple unsupervised methods to enhance the representational power of the data. Secondly, multiple samples of the source domain were obtained by multiple random sampling of the training set to fully train minority samples. Thirdly, the variation between the source domain and target domain was reduced by combining weighted balanced distribution adaptation (W-BDA). Finally, several basic learners were constructed and combined to integrate a stronger classifier to accomplish the ESP fault identification tasks. Compared with other fault identification methods, our method not only effectively enhances the performance of fault data features and improves the identification of a few fault data, but also copes with fault identification under different working conditions.
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Darimi, Ismail. "INFORMATION AND COMMUNICATION TECHNOLOGIES SEBAGAI MEDIA PEMBELAJARAN PENDIDIKAN AGAMA ISLAM EFEKTIF ERA TEKNOLOGI INFORMASI." Cyberspace: Jurnal Pendidikan Teknologi Informasi 1, no. 2 (November 1, 2017): 111. http://dx.doi.org/10.22373/cs.v1i2.2030.
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Adapting to the technological era, learning activities are required to reduce the use of lecture methods and can be enriched in the use of instructional media, the role of learning media becomes increasingly important. ICT is a program, for tools, manipulation and convey information. The learning process of PAI can further facilitate the search for information, manipulation, management and transfer of science or transfer of information, so that the integration of ICT in the learning process becomes an important role in developing students' thinking ability, developing skills in the field of ICT to smooth the learning process, ICT especially in PAI lessons, and transforming schools into creative and dynamic learning institutions so that students are motivated, always curious in PAI learning. Broadly speaking media can be classified into graphics, audio, silent projections, games and simulations. Effective learning requires good planning of one of the media that will be used in the learning process. ICT is a very effective medium in learning PAI in the era of technology
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Kim, Young Rae, and Mi Sun Park. "Creating a Virtual World for Mathematics." Journal of Education and Training Studies 6, no. 12 (October 29, 2018): 172. http://dx.doi.org/10.11114/jets.v6i12.3601.
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A virtual world was created using the popular sandbox game Minecraft to support the development of preservice teachers’ knowledge for teaching mathematics. Preservice teachers explored the virtual world for a geometry activity involving area and volume problems. They then discussed how this integration of technology could support students’ effective learning of mathematics in a meaningful way. The findings of the study demonstrated that to a certain extent the Minecraft activity supported the transfer of knowledge from preservice teachers’ mathematics content knowledge to their mathematics pedagogical and instructional practice knowledge. Preservice teachers appreciated the usefulness and effectiveness of the Minecraft activity in enhancing the teaching and learning of mathematics by visualizing mathematical concepts in the virtual world. This integration of technology also gave them an opportunity for professional growth. Although this study focuses on preservice teachers’ perspectives on the Minecraft activity, the technology integration using Minecraft will also be beneficial for students because it engages them in active and discovery learning.
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Azizi, Bisotoon. "The Study of Relationship between Organizational Learning and Organizational Performance." Revista Administração em Diálogo - RAD 19, no. 1 (January 1, 2017): 164. http://dx.doi.org/10.20946/rad.v19i1.32657.
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The aim of this study was to investigate the relationship between organizational learning and organizational performance among companies operating in the insurance industry of Tehran in Iran. The present study is a descriptive one in terms of the purpose and the method of data collection. The statistical population of the study was all insurance companies in the city of Tehran and 120 insurance companies were selected due to the lack of detailed statistical reference to their number. For this purpose, people were asked some questions who it was authorized to represent the name. The questionnaire is a tool for collecting data. The Gomez questionnaire et al. (2005) was used to measure organizational learning which includes four factors: management commitment, system perspective, openness and experimentation, transfer and integration of knowledge. To measure the organizational performance, the Yang et al. questionnaire (2004) is used. To determine the validity of data collection, the questionnaire was presented to six professors of management at various universities. The validity of questionnaire through the coordination of jury was about %100. The reliability of the questionnaire was conducted on thirty subjects, Cronbach alpha coefficient was calculated 0.91 and 0.85 for organizational learning and organizational performance, respectively. For data analysis, Pearson correlation coefficient and multiple regressions were used. The results showed that there is a positive relationship between organizational learning and its four dimensions (management commitment, vision systems, open space, and experimentation, transfer and integration of knowledge) and organizational performance of Tehran insurance companies.
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Setiawan Sumadi, Fauzi Dwi, Alrizal Rakhmat Widagdo, Abyan Faishal Reza, and Syaifuddin. "SD-Honeypot Integration for Mitigating DDoS Attack Using Machine Learning Approaches." JOIV : International Journal on Informatics Visualization 6, no. 1 (March 26, 2022): 39. http://dx.doi.org/10.30630/joiv.6.1.853.
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Distributed Denial of Services (DDoS) is still considered the main availability problem in computer networks. Developing a programmable Intrusion Prevention System (IPS) application in a Software Defined Network (SDN) may solve the specified problem. However, the deployment of centralized logic control can create a single point of failure on the network. This paper proposed the integration of Honeypot Sensor (Suricata) on the SDN environment, namely the SD-Honeypot network, to resolve the DDoS attack using a machine learning approach. The application employed several algorithms (Support Vector Machine (SVM), Multilayer Perceptron (MLP), Gaussian Naive Bayes (GNB), K-Nearest Neighbors (KNN), Classification and Regression Trees (CART), and Random Forest (RF)) and comparatively analyzed. The dataset used during the emulation utilized the extracted Internet Control Message Protocol (ICMP) flood data from the Suricata sensor. In order to measure the effectiveness of detection and mitigation modules, several variables were examined, namely, accuracy, precision, recall, and the promptness of the flow mitigation installation process. The Honeypot server transmitted the flow rule modification message for blocking the attack using the Representational State Transfer Application Programming Interface (REST API). The experiment results showed the effectiveness of CART algorithm for detecting and resolving the intrusion. Despite the accuracy score pointed at 69-70%, the algorithm could promptly deploy the mitigation flow within 31-49ms compared to the SVM, which produced 93-94% accuracy, but the flow installation required 112-305ms. The developed CART module can be considered a solution to prevent the attack effectively based on the analyzed variable.
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Kato, Tsuyoshi, Kinya Okada, Hisashi Kashima, and Masashi Sugiyama. "A Transfer Learning Approach and Selective Integration of Multiple Types of Assays for Biological Network Inference." International Journal of Knowledge Discovery in Bioinformatics 1, no. 1 (January 2010): 66–80. http://dx.doi.org/10.4018/jkdb.2010100205.
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Inferring the relationship among proteins is a central issue of computational biology and a diversity of biological assays are utilized to predict the relationship. However, as experiments are usually expensive to perform, automatic data selection is employed to reduce the data collection cost. Although data useful for link prediction are different in each local sub-network, existing methods cannot select different data for different processes. This article presents a new algorithm for inferring biological networks from multiple types of assays. The proposed algorithm is based on transfer learning and can exploit local information effectively. Each assay is automatically weighted through learning and the weights can be adaptively different in each local part. The authors’ algorithm was favorably examined on two kinds of biological networks: a metabolic network and a protein interaction network. A statistical test confirmed that the weight that our algorithm assigned to each assay was meaningful.
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Race, Alan M., Daniel Sutton, Gregory Hamm, Gareth Maglennon, Jennifer P. Morton, Nicole Strittmatter, Andrew Campbell, et al. "Deep Learning-Based Annotation Transfer between Molecular Imaging Modalities: An Automated Workflow for Multimodal Data Integration." Analytical Chemistry 93, no. 6 (February 3, 2021): 3061–71. http://dx.doi.org/10.1021/acs.analchem.0c02726.
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Watanabe, Shigeru. "Interocular transfer of learning in the pigeon: Visuo-motor integration and separation of discriminanda and manipulanda." Behavioural Brain Research 19, no. 3 (March 1986): 227–32. http://dx.doi.org/10.1016/0166-4328(86)90022-7.
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Gu, Qitao, Qun Dai, Huihui Yu, and Rui Ye. "Integrating Multi-Source Transfer Learning, Active Learning and Metric Learning paradigms for Time Series Prediction." Applied Soft Computing 109 (September 2021): 107583. http://dx.doi.org/10.1016/j.asoc.2021.107583.
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Aidossov, N., Vasilios Zarikas, Aigerim Mashekova, Yong Zhao, Eddie Yin Kwee Ng, Anna Midlenko, and Olzhas Mukhmetov. "Evaluation of Integrated CNN, Transfer Learning, and BN with Thermography for Breast Cancer Detection." Applied Sciences 13, no. 1 (January 1, 2023): 600. http://dx.doi.org/10.3390/app13010600.
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Breast cancer comprises a serious public health concern. The three primary techniques for detecting breast cancer are ultrasound, mammography, and magnetic resonance imaging (MRI). However, the existing methods of diagnosis are not practical for regular mass screening at short time intervals. Thermography could be a solution to this issue because it is a non-invasive and low-cost method that can be used routinely as a self-screening method. The research significance of this work lies in the implementation and integration of multiple different AI techniques for achieving diagnosis based on breast thermograms from several data sources. The data sources contain 306 images. The concept of transfer learning with several pre-trained models is implemented. Bayesian Networks (BNs) are also used to have interpretability of the diagnosis. A novel feature extraction from images (related to temperature) has been implemented and feeds the BNs. Finally, all methods and the classification results of pre-trained models are compared. It is found that the best result amongst the transfer learning concept is achieved with MobileNet, which delivered 93.8% accuracy. Furthermore, the BN achieves an accuracy of 90.20%, and finally, the expert model that combines CNNs and BNs gives an accuracy of 90.85%, even with a limited amount of data available. The integration of CNN and BN aims to overcome the hardship of interpretability. These approaches demonstrate high performance with added interpretability compared to previous works. In conclusion, the deep neural network provides promising results in breast cancer detection. It could be an ideal candidate for Breast Self-Exam (BSE), the goal recommended by WHO for mass screening.
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Hirsch, Pierro, Mohamed-Amine Choukou, and François Bellavance. "Transfer of Training in Basic Control Skills from Truck Simulator to Real Truck." Transportation Research Record: Journal of the Transportation Research Board 2637, no. 1 (January 2017): 67–73. http://dx.doi.org/10.3141/2637-08.
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A series of studies was done at a large truck driver-training center as part of its ongoing cycle of development and implementation of simulator-based training. This project was motivated by the need to accelerate the learning of basic vehicle control skills to allow more time for safety-critical skills. The first studies focused on gearshifting and the second on backing maneuvers. All studies measured the transfer of driving skills learned in the truck simulator to the real truck. The results show that basic vehicle control skills learned on the truck simulator transferred to a real truck and that the learning time required on the truck simulator compared with the real truck was at least equal if not shorter in many cases. A major strength of this project is to complete integration into the normal operations of the training school’s program by using regular teachers and students. The only nonroutine aspects were the extra performance measurements by independent evaluators. Naturalistic studies are prone to confounding factors. Therefore, the consistent evidence of transfer of basic skills from the truck simulator to the real truck across multiple phases with slightly different designs demonstrates the robustness of the findings. Given the success of simulator-based training in aviation, the evidence of successful transfer of training in this study is not surprising. The greater challenge is the future integration of efficient truck-driving simulator-based learning into existing training programs to allow additional time to learn more safety-critical driving skills.
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Celestin, Bekolo Ngoa, and Shao Yufen. "The Influence of Pre-training Factors on Motivation to Transfer Learning at the Post Training Stage." Human Resource Research 2, no. 1 (March 23, 2018): 1. http://dx.doi.org/10.5296/hrr.v2i1.12483.
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Transfer of training is the ultimate aim of training investment and the key to maintain competitive advantage in today’s rapidly changing operating environment where organizational success often depends on the motivation with which employee can learn and apply new ideas and information. While previous researches have focused on factors at the training stage influencing motivation to transfer training at the post-training stage, this study investigates the influence of pre-training factors. Particularly, pre-training performance self-efficacy, learning readiness, perceived content validity, and organization openness to change. The result should assist managers and trainers to ascertain the trainee state of preparedness before the training program to anticipate successful transfer of learning from the workshop to the workplace. A survey of high and vocational school teachers in Thailand participating in 5 days training on cloud computing integration in teaching was made using the Learning Transfer Inventory System (LTIS). Results show that learning readiness, perceived content validity, and organization openness to change influence the motivation to transfer at the post-training stage. Thus, framing the training program in the way trainees can answer to the questions “can I do this task?”, “do I want to do this task and why?” at the pre-training stage influence motivation to transfer. An implication to managers is that employees’ selection for training should take into consideration trainees’ perceptions in order to anticipate motivation to transfer at the post-training stage.
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Martínez, Luis A., Lizeth Rodríguez, Carlos M. Flores, Carlos A. Cisneros, Mario W. Chávez, Idis A. Lemus, and René I. Ariza. "On Net Zero Energy Building Design Methodology: A Case Study Examining Learning as Measured by Interdisciplinary Knowledge Acquisition." Advances in Environmental and Engineering Research 04, no. 01 (January 3, 2023): 1–36. http://dx.doi.org/10.21926/aeer.2301001.
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Net zero energy building design methodologies include integrative approaches and numerical tools to provide optimal performance and cost-effective results. Team integration, characterized by knowledge transfer between disciplines, has yet to be quantified for the design processes of these buildings. This article proposes a specific methodology for designing net zero energy buildings, tested through a case study design process conducted in an academic setting at Universidad Centroamericana in El Salvador, with the participation of students and faculty members. Through a survey, interdisciplinary knowledge transfer between team members was measured. We found that, without additional instruction, team participants outperformed a control group without project involvement by 16.4% (P < 0.002, t-test) in terms of interdisciplinary knowledge. This result implies that designers acquire new knowledge from other disciplines by interacting and solving design problems, although such acquisition is not uniform between disciplines. Remarkably, results show that the disciplinary groups that acquired the most knowledge about each other are Mechanical Engineering students and Architecture students. These results help us understand how to improve the design process, limit boundaries for disciplinary interactions, and determine which specific knowledge gaps to target per discipline in engineering and architecture education.
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Hu, Kuo-Jui, Chia-Pin Chueh, and Yuh-Shihng Chang. "The Empirical Research on Transfer of Cultural Meaning from Commodity to Customer—A Case Study for Hotel Staying Experience." Sustainability 14, no. 2 (January 17, 2022): 1033. http://dx.doi.org/10.3390/su14021033.
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This purpose of this article is to explore the case for the integration of art, aesthetics, and the atmosphere of local life into hotel interior designs. We used statistical empirical methods to verify whether the transformation of cultural elements into tourism products can really bring tourists to feel cultural meaning. In this study, we use the “Movement of meaning” model proposed by McCracken as a validation of how consumers feel the effects of cultural learning through the consumption of hotel stays. This research focuses on the integration of local culture and hotel consumption in the part of cultural learning, and particularly on the second stage of the meaning trajectory: hotel tourists feel the cultural meaning transfer when they consume and stay. In order to objectively investigate the influence of cultural products on guest consumption experience, we asked more than 187 hotel guests for their data to understand their perceptions of artistic experience and cultural meaning through questionnaires. The contribution of our research is to provide a framework for testing the validity of cultural meanings transformed into commodity consumption for tourism. The value of this research lies in our empirical research on how people perceive the beauty of local culture, and how the combination of cultural elements and hotel design allows customers to experience the cultural meaning benefits. The quantitative verification method of this research for the “meaning movement” model can be used as an operational procedure for tourism relative research, especially for verifying the effectiveness of cultural meaning transmission by integrating culture into tourism products.
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Gierig, Sina, Frank Merkle, Cynthia Pawelke, and Gisela Müller-Plath. "Simulation in perfusion: evaluating the efficacy of a specific training with eye-tracking." Perfusion 35, no. 8 (May 18, 2020): 717–23. http://dx.doi.org/10.1177/0267659120918779.
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Background: With the aim of integrating simulation training into the training of perfusionists, we examined whether the participants were able to transfer a specific learning content to the same and different situations and assessed their feedback on the simulation training. Eye-tracking was tested as a measure and supplemented by additional measures. Methods: A 2 × 2 mixed design was used, with test time (pre- and post-test) and training group (same and different content training) as factors. In the pre- and post-test, the participant had to handle a critical situation on the cardiopulmonary bypass, namely, a drop in arterial partial oxygen pressure. Between the two test times, the participant practised under guidance the handling of either the same critical situation (Group 1) or a different one, that is, impaired venous return (Group 2). Dependent measures were fixations of the eyes on specific areas of interest on the heart-lung machine, measures of latency and subjective assessments. Moreover, participants gave feedback on the simulation training. Results: Fixation analyses showed that the training led to an increased gaze on areas of interest relevant to the drop in arterial partial oxygen pressure in both groups, with a significant increase only for Group 1. The surveys revealed a great interest in the integration of simulation training into education. Conclusion: In combination with other measures, eye-tracking is suitable for the evaluation of simulation training. Due to the positive training effects and positive participant feedback, the integration of simulation into the training of perfusionists is advocated. Concerning transfer of learning content, more research is needed.
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Reihenova, Austra. "INTEGRATED LEARNING IN THE MATHEMATICS AND NATURAL SCIENCES LEARNING PROCESS IN HIGH SCHOOL." SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference 2 (May 21, 2019): 445. http://dx.doi.org/10.17770/sie2019vol2.3929.
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The article discusses the integrated process of learning mathematics at secondary school. The content of teaching mathematics must be arranged in such a way that the student develops an overall understanding of the world. The aim of the article is to emphasize the depth of comprehension of the content of the subject of the student’s interest, because based on the understanding of the content of the subject, new knowledge will be integrated and new skills will be developed that the student will be able to transfer to other subjects by solving problem situations. The topicality of the article is related to the integration approach, that the main focus is not to focus on the content of the subjects of mathematics and physics, but on the scientific processes that unite the contents of these subjects. Theoretical basis of the research is the system theory, which is based on the approach of learning cognition and constructivism. In the research, students' complex tests and questionnaires with open questions were used for data acquisition. The article uses a case study design to analyse data.
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Zhou, Zongwei, Jae Shin, Ruibin Feng, R. Todd Hurst, Christopher B. Kendall, and Jianming Liang. "Integrating Active Learning and Transfer Learning for Carotid Intima-Media Thickness Video Interpretation." Journal of Digital Imaging 32, no. 2 (November 6, 2018): 290–99. http://dx.doi.org/10.1007/s10278-018-0143-2.
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Gao, Wenjian, Chuanyun Xu, Gang Li, Yang Zhang, Nanlan Bai, and Mengwei Li. "Cervical Cell Image Classification-Based Knowledge Distillation." Biomimetics 7, no. 4 (November 10, 2022): 195. http://dx.doi.org/10.3390/biomimetics7040195.
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Current deep-learning-based cervical cell classification methods suffer from parameter redundancy and poor model generalization performance, which creates challenges for the intelligent classification of cervical cytology smear images. In this paper, we establish a method for such classification that combines transfer learning and knowledge distillation. This new method not only transfers common features between different source domain data, but also realizes model-to-model knowledge transfer using the unnormalized probability output between models as knowledge. A multi-exit classification network is then introduced as the student network, where a global context module is embedded in each exit branch. A self-distillation method is then proposed to fuse contextual information; deep classifiers in the student network guide shallow classifiers to learn, and multiple classifier outputs are fused using an average integration strategy to form a classifier with strong generalization performance. The experimental results show that the developed method achieves good results using the SIPaKMeD dataset. The accuracy, sensitivity, specificity, and F-measure of the five classifications are 98.52%, 98.53%, 98.68%, 98.59%, respectively. The effectiveness of the method is further verified on a natural image dataset.
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Fu, Qiming, QingSong Liu, Zhen Gao, Hongjie Wu, Baochuan Fu, and Jianping Chen. "A Building Energy Consumption Prediction Method Based on Integration of a Deep Neural Network and Transfer Reinforcement Learning." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 10 (January 8, 2020): 2052005. http://dx.doi.org/10.1142/s0218001420520059.
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With respect to the problem of the low accuracy of traditional building energy prediction methods, this paper proposes a novel prediction method for building energy consumption, which is based on the seamless integration of the deep neural network and transfer reinforcement learning (DNN-TRL). The method introduces a stack denoising autoencoder to extract the deep features of the building energy consumption, and shares the hidden layer structure to transfer the common information between different building energy consumption problems. The output of the DNN model is used as the input of the Sarsa algorithm to improve the prediction performance of the target building energy consumption. To verify the performance of the DNN-TRL algorithm, based on the data recorded by American Power Balti Gas and Electric Power Company, and compared with Sarsa, ADE-BPNN, and BP-Adaboost algorithms, the experimental results show that the DNN-TRL algorithm can effectively improve the prediction accuracy of the building energy consumption.
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Kirpitchenko, Liudmila. "Comparing Experiences of Academic Mobility and Migration." Comparative Sociology 13, no. 2 (May 8, 2014): 215–34. http://dx.doi.org/10.1163/15691330-12341301.
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Abstract Academic mobility and accompanying migration have become increasingly evident as manifestations of globalization and internationalization of education worldwide. This paper aims to provide some insights into intercultural communication in academia by comparing experiences of students and academics who partake in academic mobility or/and academic migration. It seeks to reflect on how differences in cultural patterns impact on the integrational experiences and outcomes of academic learning and everyday interactions. Two contrasting cultural patterns of collectivism and individualism are explored, as they are displayed in intercultural interactions among migrants and hosting societies. To expose this contrast effectively, this paper focuses on the Russian-speaking mobile academics and compares their intercultural experiences in academia of two countries—Italy and Australia. In-depth interviews were conducted with twenty-two academic migrants or/and mobile academics on their experiences, views and perceptions of intercultural integration in two diverse settings. This paper explores diverse aspects of intercultural dialogue and compares perceptions of intercultural integration and feelings of wellbeing. It analyses evolving empirical manifestations of cosmopolitanism in everyday intercultural interactions and argues that postmodern cosmopolitan milieu facilitates intercultural integration and enables knowledge transfer and creation of shared cultural meanings.
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Choi, Soonri, Namjung Kim, Seohyun Choi, and Dongsik Kim. "EMPHASIS MANIPULATION EFFECT IN TERMS OF THE LEAST-ABLED SETS ON COGNITIVE LOAD, TRANSFER, AND INSTRUCTIONAL EFFICIENCY." Problems of Education in the 21st Century 77, no. 2 (April 28, 2019): 228–43. http://dx.doi.org/10.33225/pec/19.77.228.
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This research suggests emphasis manipulation on constituent skills of least-abled sets, improves coordination and integration of knowledge, skills, and attitudes on cognitive load, transfer, and instructional efficiency. The participants were divided into two groups. Competency levels for the designated skill sets were evaluated, and a pre-test was performed on both groups. The research applied an educational design based on individual learner’s least-abled sets of constituent skills and identified the design’s effectiveness on complex learning. One group was provided with the whole learning contents according to emphasis manipulation sequencing method, and the other group was provided personalized learning contents according to a method based on the least-abled sets of constituent skills emphasis manipulation. The group received materials constructed with emphasis manipulation, learned the whole constituent skills of learning contents and carried out conventional tasks. However, treatment group received materials constructed with the least-abled sets of constituent skills emphasis manipulation, learned only the least-abled constituent skills and carried out conventional tasks. This research suggests that teaching with the least-abled sets of constituent skills helps to reduce expertise-reversal effect and improve results of cognitive load, transfer and instructional efficiency. Keywords: cognitive load, complex tasks, emphasis manipulation, instructional efficiency, learning transfer.
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Li, Ke, Mark Peterson, and Jiahui Wan. "Digital Gaming in the Language Classroom." International Journal of Computer-Assisted Language Learning and Teaching 12, no. 1 (January 2022): 1–25. http://dx.doi.org/10.4018/ijcallt.291110.
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Despite the increasing awareness of digital games’ potential for language learning, only a handful of studies focus on their integration into classrooms. Informed by bridging activities, this mixed methods case study recruited six students to engage in instructed gameplay in class and game-related activities after class. Both qualitative and quantitative data were collected and analyzed so as to measure participants’ learning outcome, document their engagement, and explore their perceptions of game-based language learning. Results suggest progress in vocabulary recall and transfer. Participants also reported gains in writing and listening, satisfaction with the project, along with a positive attitude towards GBLL. Moreover, it is found that the instructor has a pivotal role to play in pre-game set-up, in-game guidance and post-game feedback. The study yields empirical evidence regarding the benefits of GBLL and may hold pedagogical implications for the integration of games into educational settings. The limitations of this research and future directions are also discussed.