Relevant bibliographies by topics / Using Different Aspects in Learning

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Using Different Aspects in Learning'

Author: Grafiati
Published: 5 June 2025
Last updated: 16 July 2025

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Journal articles on the topic "Using Different Aspects in Learning"

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CANTAŞ, Gökhan. "ONTOLOGY MATCHING AND MANAGEMENT USING MACHINE LEARNING ASPECTS." Journal of Natural Sciences and Mathematics of UT-JNSM 9, no. 17-18 (2024): 219–27. http://dx.doi.org/10.62792/ut.jnsm.v9.i17-18.p2817.

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Industry 4. zero is a brand-new generation of data era that ambitions to expand expertise bases for tracking developments in enterprise 4. zero. This paper proposes a framework to cope with the improvement of Knowledge Bases for Monitoring Trends in Industry4.zero.In this framework, we suggest an ontological model (COInd4 ontology) for the manufacturing area that describes the assets and strategies within side the manufacturing unit, and sensor observations are analysed via way of means of remark affects the use of contextual data past classical reasoning mechanism for stopping the forecasted
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Darlis, Tiara Saputri, Fairuz Fairuz, Ninuk Lustiyantie, and Uwes Anis Chaeruman. "Multicultural Aspects of 21st Century Learning Using Digital Posters." JETL (Journal of Education, Teaching and Learning) 6, no. 2 (2021): 169. http://dx.doi.org/10.26737/jetl.v6i2.2548.

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21st century learning is learning that has the characteristics of being accessible, digital oriented, big data science and this learning is not limited to the distance of space and time. Poster presentation is a general form of educational information that is easily accessible, can be spread quickly with the presence of television, gadgets and the internet. This research method is descriptive qualitative method. While the research data in the form of educational posters. The results of this study are in the form of poster media requirements that are used as educational media, namely; 1) The co
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Saleh, Mostafa S. "Building Interoperable Learning Objects Using Reduced Learning Object Metadata." E-Learning and Digital Media 2, no. 3 (2005): 299–313. http://dx.doi.org/10.2304/elea.2005.2.3.9.

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The new e-learning generation depends on Semantic Web technology to produce learning objects. As the production of these components is very costly, they should be produced and registered once, and reused and adapted in the same context or in other contexts as often as possible. To produce those components, developers should use learning standards to describe these objects in order to support interoperability. IEEE Learning Object Metadata (LOM) is the most dominant standard for describing learning objects, in which 76 different elements are used to describe the different aspects of e-learning.
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WAN MOHD ISA, WAN ABDUL RAHIM, Zulinda Ayu Zulkipli, and Mimi Nurakmal Mustapa. "A Conceptual Framework of Blended Learning for Self-Directed Learners in the Social Context: Case of Mobile Learning." Social and Management Research Journal 14, no. 1 (2017): 51. http://dx.doi.org/10.24191/smrj.v14i1.5279.

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Currently, the factors for adopting m-learning revolve around higher education settings. However, the factors surrounding different cultural and background context of the user in using m-learning in different contexts are not fully explored, especially in the social context. Thus, there are needs to understand blended learning for self-directed learners from different communities. The main objectives of this paper are (i) to develop a conceptual framework of blended learning for self-directed learners in the social context by using mobile learning as the case study and (ii) to provide recommen
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SPIKOL, DANIEL, and MARCELO MILRAD. "PHYSICAL ACTIVITIES AND PLAYFUL LEARNING USING MOBILE GAMES." Research and Practice in Technology Enhanced Learning 3, no. 3 (2008): 275–95. https://doi.org/10.58459/rptel.2008.3275-295.

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The combination of informal learning and mobile outdoor games can be seen as a rel- evant arena for conducting novel learning activities that involve children in different tasks including physical motion, problem solving, inquiry and collaboration. These are activities that support different cognitive and social aspects of learning. Co-design and human centric design practices have been the focus of current research efforts in the field of educational technologies but not as prevalent in mobile games to support learning. In our current research we are exploring which design methods are appropr
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Devaiah, KN, and HB Anita. "Classification of architectural designs using Deep Learning." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 2471–74. https://doi.org/10.35940/ijeat.C5621.029320.

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Architecture style of buildings play’s an important role in various aspects. Architectural style or the construction method affects the human health in multiple ways. Many dynasties are ruled India and constructed various types of monuments. So, In this proposed work popular dynasties like Hoysala dynasty, Vijayanagar empire, Mughal empire, Nizam’s of Hyderabad, Chalukya dynasty etc. are considered for creating dataset for the work. The architects of those times had really good knowledge about the different scientific methods to be used for construction. This project aims at classi
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Azabdaftari, Behrooz, and Mohammad Amin Mozaheb. "Comparing vocabulary learning of EFL learners by using two different strategies: mobile learning vs. flashcards." EuroCALL Review 20, no. 2 (2012): 47. http://dx.doi.org/10.4995/eurocall.2012.11377.

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<p>Vocabulary acquisition is one of the most important aspects of language learning. There are a number of techniques and technologies which enhance vocabulary learning in the year 2012, e.g. wordlists, flashcards and m-learning. Mobile phones are among those devices which not only meet the expectations of their users for communication, but are also good devices for language learning. Mobile phones can be used anywhere and anytime, and students are free to use them inside or outside the classroom setting. The present study compared the use of two strategies for vocabulary learning (i.e.
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Shah, Uzair, Vivien Hodgson, and Kiran Trehan. "Teachers' experiences of using Learning Technology in Pakistan." Proceedings of the International Conference on Networked Learning 8 (April 2, 2012): 303–11. http://dx.doi.org/10.54337/nlc.v8.9101.

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Advancements in learning technology, such as computers, mobile devices and the Internet, have extended correspondence with faculty members, facilitated administrative activities and encouraged linkage and connections with other students beyond normal university office hours. Education technologists are exploiting the benefits of technology to transform teaching methods in universities and promote interaction and collaboration; aspects important to Networked Learning. Despite the extensive use of learning technology, limited research has been conducted to understand how faculty members experien
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Svennevik, Hanna, Michael A. Riegler, Steven Hicks, Trude Storelvmo, and Hugo L. Hammer. "Prediction of Cloud Fractional Cover Using Machine Learning." Big Data and Cognitive Computing 5, no. 4 (2021): 62. http://dx.doi.org/10.3390/bdcc5040062.

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Climate change is stated as one of the largest issues of our time, resulting in many unwanted effects on life on earth. Cloud fractional cover (CFC), the portion of the sky covered by clouds, might affect global warming and different other aspects of human society such as agriculture and solar energy production. It is therefore important to improve the projection of future CFC, which is usually projected using numerical climate methods. In this paper, we explore the potential of using machine learning as part of a statistical downscaling framework to project future CFC. We are not aware of any
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Bulatovic, Marija, and Jelena Medar-Zlatkovic. "Serbian teachers’ conceptions of different aspects of planning cooperative learning in the classroom." Zbornik Instituta za pedagoska istrazivanja 56, no. 1 (2024): 53–78. http://dx.doi.org/10.2298/zipi2401053b.

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Having in mind the significance of students? mutual cooperation in the learning process, we conducted a study with the aim of understanding teachers? perspectives on different aspects of planning cooperative learning in the classroom. The sample comprised 19 teachers employed at primary and secondary schools in Belgrade, Pancevo, and the municipality of Obrenovac. The data was collected using the interview technique and processed via thematic content analysis. The findings suggest that although teachers shaped cooperative learning by creating different assignments for students, they most often
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Dissertations / Theses on the topic "Using Different Aspects in Learning"

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Danker, Anton, and Wiklund Jacob Wirgård. "Using Transfer Learning to classify different stages of Alzheimer’s disease." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301784.

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The identification of Alzheimer’s disease through the application of various machine learning techniques on neuroimaging data of the likes of MRI is an area of study which has seen intense levels of research in recent years. While many machine learning techniques have existed for a long time, recent advances in Deep Learning and Computer Vision have allowed for better performing predictive models. In this report we present a Convolutional Neural Network & Transfer Learning based approach to classify various stages of Alzheimer’s disease with a high degree of accuracy. Furthermore we invest
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Saleh, Shahin. "Deep Active Learning for Image Classification using Different Sampling Strategies." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-300056.

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Convolutional Neural Networks (CNNs) have been proved to deliver great results in the area of computer vision, however, one fundamental bottleneck with CNNs is the fact that it is heavily dependant on the ground truth, that is, labeled training data. A labeled dataset is a group of samples that have been tagged with one or more labels. In this degree project, we mitigate the data greedy behavior of CNNs by applying deep active learning with various kinds of sampling strategies. The main focus will be on the sampling strategies random sampling, least confidence sampling, margin sampling, entrop
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Roselli, Néstor. "Collaborative construction using chat in different tasks." Pontificia Universidad Católica del Perú, 2012. http://repositorio.pucp.edu.pe/index/handle/123456789/101459.

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The objective of this research was to characterize the chat collaborative interaction of two partners in six kinds of cognitive tasks. The central hypothesis was that the task nature determines a particular kind of collaborative interaction. The six tasks tested were: to solve a logical problem, to compose a story, to read a data table, to rank opinions, to bring a scientific explanation of a domestic situation, to interpret the signification of a literature text. The 11 dyads of the sample were formed by university students. Results show significant differences between the tasks concerning th
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White, Sherry A. (Sherry Anne). "Comparison of Remediation Methods in Different Hydrogeologic Settings Using Bioplume II." Thesis, University of North Texas, 1996. https://digital.library.unt.edu/ark:/67531/metadc278039/.

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A contaminant fate and transport computer model, Bioplume II, which allows simulation of bioremediation in ground water systems, was used to compare the effects of 11 remediation scenarios on a benzene plume. The plume was created in three different hydrogeologic settings from the simulation of an underground gasoline storage tank leak.
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Gutschmidt, Andrea. "Evaluation of anti-tuberculosis responses in humans using different complementary immunological techniques." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/79835.

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Thesis (MSc MedSc)--Stellenbosch University, 2013.<br>ENGLISH ABSTRACT: Background The QuantiFERON In-Tube (QFT IT) assay is an Interferon-gamma release assay (IGRA) which is currently used to detect Mycobacterium tuberculosis (M. tb) infection. It however cannot differentiate between latent infection and active tuberculosis (TB) disease. In an attempt to improve this tool to accurately diagnose active TB, the release of a variety of markers should be assessed in combination with Interferon gamma (IFN- γ). Luminex analysis was previously done on QFT plasma and promising candidates were
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Stouffer, Eric M. "The neurobiology of latent learning in the rat using salt appetite and its dissociation from conditioning /." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=102731.

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The brain areas required for latent learning in the rat are not currently understood. Previous tasks used to assess latent learning, defined as the acquisition of neutral information that does not immediately influence behavior, have shared characteristics that prevented their use to determine the neurobiology of latent learning. This thesis describes a new task called the Latent Cue Preference (LCP) task, derived from the Conditioned Cue Preference (CCP) task that has been successfully used to determine the brain areas required for conditioning in the rat and other animals. In the LCP task, w
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Lagula, Daniel, and Filip Karlsson. "Comparison of Two Different Methods of Generating Physics-Based Character Animation using Reinforcement Learning." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20227.

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In the area of Physics-Based Animation using Reinforcement Learning (RL), multiple games and virtual simulations have had it as an objective throughout the years because of the added realism it brings to motions of characters. It also brings a realistic and practical interaction between the characters and their environment. By using a physically simulated ragdoll and Reinforcement Learning, the ragdoll can learn how to walk and balance. This has the potential of bringing realistic and interactive real-time animations, of normally rigid animations, to life. No longer do animators have to animat
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Fonseca, Eduardo. "Training sound event classifiers using different types of supervision." Doctoral thesis, Universitat Pompeu Fabra, 2021. http://hdl.handle.net/10803/673067.

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The automatic recognition of sound events has gained attention in the past few years, motivated by emerging applications in fields such as healthcare, smart homes, or urban planning. When the work for this thesis started, research on sound event classification was mainly focused on supervised learning using small datasets, often carefully annotated with vocabularies limited to specific domains (e.g., urban or domestic). However, such small datasets do not support training classifiers able to recognize hundreds of sound events occurring in our everyday environment, such as kettle whistles
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Cheltuitor, Alexandru, and Niklas Jones-Quartey. "Predicting Multimodal Rehabilitation Outcomes using Machine Learning." Thesis, Uppsala universitet, Institutionen för informatik och media, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-413568.

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Chronic pain is a complex health issue and a major cause of disability worldwide. Although multimodal rehabilitation (MMR) has been recognized as an effective form of treatment for chronic pain, some patients do not benefit from it. If treatment outcomes could be reliably predicted, then patients who would benefit more from MMR could be prioritized over others. Machine learning has been proven capable of accurately predicting outcomes in other healthcare related domains. Therefore, this study aims to investigate the use of it to predict outcomes of MMR, using data from the Swedish Quality Regi
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Williams, Kevin. "Using experiential learning to facilitate pharmacy students' understanding of patients' medication practice in chronic illness." Thesis, Rhodes University, 2006. http://hdl.handle.net/10962/d1003955.

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This study originates from experiences which led me to question the way pharmacists are equipped to advise and support the medicine-taking practice of patients using chronic medication. The study offers a critical theoretical consideration of underlying perspectives informing pharmacy education. I propose following a critical realist ontological perspective, a social realist understanding of social structure and human agency, and a sociocultural epistemology. Based on these perspectives, I consider a sociological critique of ‘health’, ‘disease’, ‘illness’ and ‘sickness’ perspectives on medicin
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Books on the topic "Using Different Aspects in Learning"

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Healy, Jane M. Different learners: Identifying, preventing, and helping your children's learning problems. Simon & Schuster, 2009.

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Zull, James E. From brain to mind: Using neuroscience to guide change in education. Stylus Pub., 2011.

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Wood, W. W. (Willy Wray), 1957-, ed. The rock 'n' roll classroom: Using music to manage mood, energy, and learning. Corwin Press, 2013.

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Tokuhama-Espinosa, Tracey. The new science of teaching and learning: Using the best of mind, brain, and education science in the classroom. Teachers College Press, 2010.

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Maugeri, Giuseppe. L’insegnamento dell’italiano a stranieri Alcune coordinate di riferimento per gli anni Venti. Fondazione Università Ca’ Foscari, 2021. http://dx.doi.org/10.30687/978-88-6969-523-0.

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This book develops the theme of teaching Italian abroad, starting from the awareness of the motivations for foreign students to study the Italian language and the different methodological procedures in order to teach it.For this purpose, the book focuses on the problems concerning the training of teachers of Italian to foreigners and on the many aspects of teaching Italian in order to propose both a methodological reflection on the edulinguistic project and educational solutions aimed at improving the quality of the students’ learning.Part 1The first part focuses on edulinguistic teaching visi
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1958-, Thompson Thomas C., ed. Most excellent differences: Essays on using type theory in the composition classroom. Center For Applications of Psychological Type, Inc., 1996.

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Doug, Johnson. Learning right from wrong in the digital age: An ethics guide for parents, teachers, librarians, and others who care about computer-using young people. Linworth Pub., 2003.

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Hagai, Irit. Yesh li yeled aḥer: ʻal horot li-yeladim liḳuye lemidah, ḳeshev ṿe-rikuz, mi-yanḳut ṿe-ʻad bagrut = I have a different child. Modan, 2014.

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Davidson, Fred. Testcraft: A teacher's guide to writing and using language test specifications. Yale University Press, 2002.

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Davidson, Fred. Testcraft: A teacher's guide to writing and using language test specifications. Yale University Press, 2002.

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Book chapters on the topic "Using Different Aspects in Learning"

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Khekare, Ganesh, Anil V. Turukmane, Chetan Dhule, Pooja Sharma, and Lokesh Kumar Bramhane. "Experimental Performance Analysis of Machine Learning Algorithms." In Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2456-9_104.

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AbstractMachine Learning models and algorithms have become quite common these days. Deep Learning and Machine Learning algorithms are utilized in various projects, and now, it has opened the door to several opportunities in various fields of research and business. However, identifying the appropriate algorithm for a particular program has always been an enigma, and that necessitates to be solved ere the development of any machine learning system. Let’s take the example of the Stock Price Prediction system, it is used to identify the future asset prediction of a industry or other financial aspects traded on a related transaction. Now, it is a daunting task to find the right algorithm or model for such a purpose that can predict accurate values. There are several other systems such as recommendation systems, sales prediction of a mega-store, or predicting what are the chances of a driver meeting an accident based on his past records and the road they’ve taken. These problem statements require to be built using the most suitable algorithm and identifying them is a necessary task. This is what the system does, it compares a set of machine learning algorithms while determining the appropriate algorithm for the selected predictive system using the required data sets. The objective is to develop an interface that can be used to display the result matrix of different machine learning algorithms after being exposed to different datasets with different features. Besides that, one can determine the most suitable (or optimal) models for their operations, using these fundamentals. For experimental performance analysis several technologies and tools are used including Python, Django, Jupyter Notebook, Machine Learning, Data Science methodologies, etc. The comparative performance analysis of best known five time series forecasting machine learning algorithms viz. linear regression, K – nearest neighbor, Auto ARIMA, Prophet, and Support Vector Machine is done. Stock market, earth and sales forecasting data is used for analysis.
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Ranjan, R., A. Panchal, S. Karpe, and S. Menon. "Machine Learning Strategy for Subgrid Modeling of Turbulent Combustion Using Linear Eddy Mixing Based Tabulation." In Lecture Notes in Energy. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-16248-0_7.

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AbstractThis chapter describes the use of machine learning (ML) algorithms with the linear-eddy mixing (LEM) based tabulation for modeling of subgrid turbulence-chemistry interaction. The focus will be on the use of artificial neural network (ANN), particularly, supervised deep learning (DL) techniques within the finite-rate kinetics framework. We discuss the accuracy and efficiency aspects of two different strategies, where LEM based tabulation is used in both of them. While in the first approach, referred to as LANN-LES, the subgrid reaction-rate term is obtained efficiently using ANN in the conventional LEMLES framework, in the other approach referred to as TANN-LES, the filtered reaction rate terms are obtained using ANN. First, we assess the implications of the employed network architecture, and the associated hyperparameters, such as the amount of training and test data, epoch, optimizer, learning rate, sample size, etc. Afterward, the effectiveness of the two strategies is examined by comparing with conventional LES and LEMLES approaches by considering canonical premixed and non-premixed configurations. Finally, we describe the key challenges and future outlook of the use of ML based subgrid modelling within the finite-rate kinetics framework.
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Keser, Ahmet Esat, and Onur Behzat Tokdemir. "Machine Learning-Based Construction Planning and Forecasting Model." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/979-12-215-0289-3.71.

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Construction planning and scheduling are crucial aspects of project management that require a lot of time and resources to manage effectively. Machine learning and artificial intelligence techniques have shown great potential in improving construction planning and scheduling by providing more accurate insights into project progress and forecasting. This paper proposed a machine learning model that utilizes regularly updated site data to generate predictions of quantity variances from the plan and enable a more accurate forecast of future progress based on historical data on concrete activities. Also, the outputs of this model can be used when creating a schedule for a new project. New schedules created with the help of this model will be more consistent and reliable due to its vast data pool and ability to generate realistic forecasts from this data. The model utilizes data from completed and other ongoing projects to generate insights and provide a more accurate and efficient construction planning and scheduling solution. Within the scope of this study, different attributes of concrete pouring activities of different projects and locations were used as input data for a machine learning process, and then, using this model on test data, the forecast concrete quantities were obtained. This model provides a more advanced solution than traditional project management tools by incorporating machine learning techniques while significantly improving construction planning, scheduling accuracy, and efficiency, leading to more successful projects and increased profitability for construction companies
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Keser, Ahmet Esat, and Onur Behzat Tokdemir. "Machine Learning-Based Construction Planning and Forecasting Model." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.71.

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Construction planning and scheduling are crucial aspects of project management that require a lot of time and resources to manage effectively. Machine learning and artificial intelligence techniques have shown great potential in improving construction planning and scheduling by providing more accurate insights into project progress and forecasting. This paper proposed a machine learning model that utilizes regularly updated site data to generate predictions of quantity variances from the plan and enable a more accurate forecast of future progress based on historical data on concrete activities. Also, the outputs of this model can be used when creating a schedule for a new project. New schedules created with the help of this model will be more consistent and reliable due to its vast data pool and ability to generate realistic forecasts from this data. The model utilizes data from completed and other ongoing projects to generate insights and provide a more accurate and efficient construction planning and scheduling solution. Within the scope of this study, different attributes of concrete pouring activities of different projects and locations were used as input data for a machine learning process, and then, using this model on test data, the forecast concrete quantities were obtained. This model provides a more advanced solution than traditional project management tools by incorporating machine learning techniques while significantly improving construction planning, scheduling accuracy, and efficiency, leading to more successful projects and increased profitability for construction companies
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Tipi, Nicoleta. "Simulation Games in Teaching Operations and Supply Chain Management." In Creativity and Critique in Digital Learning and Teaching. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-68086-1_13.

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Abstract This chapter aims to bring forward ways to develop and incorporate simulation games within digital teaching with specific emphasis to operations and supply chain management. Using simulation games in digital teaching presents learners with different opportunities to engage with learning abstract concepts that bring an increased level of complexity, such as learning about supply chain systems. Simulation games can be constructed and embedded into the curriculum not only to help learners understand theories, but also to experience activities and events as they may happen in practice. In the area of operations and supply chain management, advanced mathematical modelling is required to cover aspects such as inventory control, distribution planning, forecasting, vehicle routing, resources allocation and optimisation. When using simulations, abstract mathematical concepts can be presented in a more meaningful, practical way. Therefore, incorporating simulation games in digital teaching allows the development of knowledge and skills that not only help in demonstrating complex theories, but also in using business analytics. The use of analytics can enhance students’ numerical, analytical and critical thinking skills and contribute to enhancing student employability. Within this chapter, key characteristics to be considered when developing simulation games for digital teaching are identified. They are then tested, following a framework for simulation games model development that may be adopted by tutors in their practice. The chapter incorporates a simulation game example that tutors may wish to incorporate in their teaching.
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Xu, Xiaoyu, and Qiaoping Zhang. "A Comparative Analysis of the Linear Equation Unit in Secondary Mathematics Textbooks in Chinese-English Bilingual Schools." In Recent Advances in Mathematics Textbook Research and Development. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-8426-4_56.

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AbstractChinese–English bilingual programs in China advocate using both English and Chinese in instruction. Mathematics teachers in these schools need to use English as the medium of instruction to achieve the learning objectives of the school mathematics curriculum and also meet the English proficiency goals. Mathematics textbooks play a crucial role in teaching and learning within such a learning environment. This study presents a comparative study aiming to examine how linear equation unit is arranged in secondary school mathematics textbooks (i.e., IB, IGCSE, and Chinese textbooks) in Chinese-English bilingual schools. It explores the similarities and differences in these three series of textbooks. Four aspects of linear equations in different textbooks are compared: the number of examples, the distribution of contents, the learning activities, chapter review exercises. The results show that the three textbooks have different approaches and priorities that emphasize the positions and weights of the linear equation unit. The textbooks in China contain the highest percentage of linear equation contents and pay the most attention to explaining and analyzing how to set the unknown variable and using the concept of the linear equation to solve real-life problems. The findings can enrich teachers’ and researchers’ knowledge of mathematics textbooks in international schools in China and put forward some suggestions to improve the effectiveness of using textbooks in such schools.
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Alcorta de Bronstein, A., and J. M. Timm. "Transformational Sustainability Entrepreneurship: Encouraging Students to Become Real Change Agents." In Transforming Entrepreneurship Education. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11578-3_5.

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AbstractEntrepreneurial Education needs to be transformed. Our seminar called Transformational Sustainability Entrepreneurship aims at meeting this need by guiding students to become change agents for tackling the grand societal challenges of our time. In this chapter, we explain the five fundamental aspects in which this seminar is designed for students’ transformational learning experience. The seminar itself is divided into three phases: Understanding, Creative Thinking, and Pitching with an overarching reflection process. We introduce the concept, which we have been using for four years at two different universities, for others to apply and use in their own teaching activities.
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Patankar, Nikhil, Soham Dixit, Akshay Bhamare, Ashutosh Darpel, and Ritik Raina. "Customer Segmentation Using Machine Learning." In Recent Trends in Intensive Computing. IOS Press, 2021. http://dx.doi.org/10.3233/apc210200.

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Nowadays Customer segmentation became very popular method for dividing company’s customers for retaining customers and making profit out of them, in the following study customers of different of organizations are classified on the basis of their behavioral characteristics such as spending and income, by taking behavioral aspects into consideration makes these methods an efficient one as compares to others. For this classification a machine algorithm named as k-means clustering algorithm is used and based on the behavioral characteristic’s customers are classified. Formed clusters help the company to target individual customer and advertise the content to them through marketing campaign and social media sites which they are really interested in.
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Datta, Suchandra, Soumili Dey, Anal Acharya, and Debabrata Datta. "Blended Learning." In Digital Pedagogies and the Transformation of Language Education. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-6745-6.ch012.

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Evolution of new technologies introduces new methods by which students can gain knowledge and professors can impart it. Each learning method offers its own distinctive advantages and disadvantages which affect students having different learning preferences and temperaments in different ways. The study aims to investigate student's attitude towards two modes of learning, namely traditional learning and e-learning and uncover the underlying factor structure governing student appraisal of such systems. The aspects of each type of learning that are attractive to students are shown. Further, the two modes of learning are compared using different statistical techniques, and the findings are used to decide whether a mixture of traditional and e-learning is indeed the way ahead.
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Garg, Ruchi, Sushil Kumar, and Sonali Gupta. "Study on Medical Image Detection Using Deep Learning." In Smart Healthcare for Sustainable Urban Development. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-2508-4.ch001.

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The growing development of deep learning and its increasingly widespread use signals a trend to convert to a new standard in each application area, consolidating itself as a general purpose technology. In the general analysis of innovations based on the use of deep learning on different applications of medical images, it can be inferred that its use is increasingly widespread and that it is driving greater innovations and transformations at an increasingly greater speed. Additionally, it is evident that the use of deep learning in medical imaging for the diagnosis of various anomalies incorporates a significant number of the elements and methodological and organizational aspects identified under this study (e.g., invention methods from the perspective of application of deep learning). Therefore, this study emphasizes various aspects of deep learning models to have opted as a ready reference while examining the medical images as a de-facto standard.
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Conference papers on the topic "Using Different Aspects in Learning"

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Parać, Roko, Lorenzo Nodari, Leo Ardon, Daniel Furelos-Blanco, Federico Cerutti, and Alessandra Russo. "Learning Robust Reward Machines from Noisy Labels." In 21st International Conference on Principles of Knowledge Representation and Reasoning {KR-2023}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/kr.2024/85.

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This paper presents PROB-IRM, an approach that learns robust reward machines (RMs) for reinforcement learning (RL) agents from noisy execution traces. The key aspect of RM-driven RL is the exploitation of a finite-state ma- chine that decomposes the agent’s task into different sub- tasks. PROB-IRM uses a state-of-the-art inductive logic pro- gramming framework robust to noisy examples to learn RMs from noisy traces using the Bayesian posterior degree of be- liefs, thus ensuring robustness against inconsistencies. Piv- otal for the results is the interleaving between RM learning and policy lear
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Holanda, João Pedro, Melissa Sales, Marcus Ferraz, and Roney Santos. "Morphological Classification of Galaxies with Different Grayscale Images Using Deep Learning." In Encontro Nacional de Inteligência Artificial e Computacional. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/eniac.2023.234521.

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In recent years, several images of galaxies have been collected by telescopes, so that they could be morphologically analyzed using artificial intelligence devices. Thus, this work aims to analyze new image processing approaches, using grayscale conversion algorithms, in order to explore their influence on CNN (Convolutional Neural Networks). Images from the Galaxies10 DECals dataset of two different types of galaxies were used, which were grayscaled and analyzed separately on the CNN. Aspects such as the influence of redshift and the average pixel value have been studied, since grayscale conv
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Poddar, Lahari, Wynne Hsu, and Mong Li Lee. "Quantifying Aspect Bias in Ordinal Ratings using a Bayesian Approach." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/530.

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User opinions expressed in the form of ratings can influence an individual's view of an item. However, the true quality of an item is often obfuscated by user biases, and it is not obvious from the observed ratings the importance different users place on different aspects of an item. We propose a probabilistic modeling of the observed aspect ratings to infer (i) each user's aspect bias and (ii) latent intrinsic quality of an item. We model multi-aspect ratings as ordered discrete data and encode the dependency between different aspects by using a latent Gaussian structure. We handle the Gaussi
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Marcacini, Ricardo, and Emanuel Silva. "Aspect-based Sentiment Analysis using BERT with Disentangled Attention." In LatinX in AI at International Conference on Machine Learning 2021. Journal of LatinX in AI Research, 2021. http://dx.doi.org/10.52591/lxai2021072416.

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Aspect-Based Sentiment Analysis (ABSA) tasks aim to identify consumers’ opinions about different aspects of products or services. BERT-based language models have been used successfully in applications that require a deep understanding of the language, such as sentiment analysis. This paper investigates the use of disentangled learning to improve BERT-based textual representations in ABSA tasks. Motivated by the success of disentangled representation learning in the field of computer vision, which aims to obtain explanatory factors of the data representations, we explored the recent DeBERTa mod
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Marcacini, Ricardo, and Emanuel Silva. "Aspect-based Sentiment Analysis using BERT with Disentangled Attention." In LatinX in AI at International Conference on Machine Learning 2021. Journal of LatinX in AI Research, 2021. http://dx.doi.org/10.52591/lxai2021072410.

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Aspect-Based Sentiment Analysis (ABSA) tasks aim to identify consumers’ opinions about different aspects of products or services. BERT-based language models have been used successfully in applications that require a deep understanding of the language, such as sentiment analysis. This paper investigates the use of disentangled learning to improve BERT-based textual representations in ABSA tasks. Motivated by the success of disentangled representation learning in the field of computer vision, which aims to obtain explanatory factors of the data representations, we explored the recent DeBERTa mod
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Marcacini, Ricardo, and Emanuel Silva. "Aspect-based Sentiment Analysis using BERT with Disentangled Attention." In LatinX in AI at International Conference on Machine Learning 2021. Journal of LatinX in AI Research, 2021. http://dx.doi.org/10.52591/2021072410.

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Aspect-Based Sentiment Analysis (ABSA) tasks aim to identify consumers’ opinions about different aspects of products or services. BERT-based language models have been used successfully in applications that require a deep understanding of the language, such as sentiment analysis. This paper investigates the use of disentangled learning to improve BERT-based textual representations in ABSA tasks. Motivated by the success of disentangled representation learning in the field of computer vision, which aims to obtain explanatory factors of the data representations, we explored the recent DeBERTa mod
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Cardoso, Breno, and Denilson Pereira. "Evaluating an Aspect Extraction Method for Opinion Mining in the Portuguese Language." In Symposium on Knowledge Discovery, Mining and Learning. Sociedade Brasileira de Computação, 2020. http://dx.doi.org/10.5753/kdmile.2020.11969.

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The opinion issued by consumers of products and services has become increasingly valued, both by other consumers and by companies. The automatic interpretation of review texts to generate information is of paramount importance. With opinion mining at the aspect level, it is possible to extract and summarize opinions about different components of a product or service. This paper evaluates the behavior of a method for extracting aspects using natural language processing tools for the Portuguese language. The aim is to investigate the maturity of the tools for Portuguese compared to the already c
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Oproiu, Gabriela carmen. "METHODOLOGICAL ASPECTS OF DESIGNING ONLINE TEACHING ACTIVITIES." In eLSE 2017. Carol I National Defence University Publishing House, 2017. http://dx.doi.org/10.12753/2066-026x-17-142.

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During the recent years there has been an increase in the use of electronic learning platforms in all educational systems. Learning platforms as virtual learning environments are considered necessary for developing e-learning activities. The Virtual Learning Environment (VLE) is a specific system built around computers, software and Internet access to support teaching, learning and assessment. As a result of the increase in using ICT tools in education it should be noted that more universities integrated VLE in traditional courses in order to satisfy student learning needs and improve teaching
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Leite, Kleyton Sartori, Felipe Gomes Da Silva, Bruno do Amaral Crispim, Felipe Merey, Alexeia Barufatti Grisolia, and Willian Paraguassu Amorim. "Automatic Detection of Erythrocytes in Fishes using Clustering Segmentation and Supervised Learning." In XV Workshop de Visão Computacional. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/wvc.2019.7620.

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The growth of urban areas and the population has favored the increase in pollution and consequently the contamination of river waters. This clue has aroused interest in several aspects, mainly related to the fate and possible effects that these contaminants can cause to human health. The analysis of erythrocytes in fish is an efficient mechanism to identify the presence of genetical terations that maybe being caused by emergent contaminants. This article presents a new proposal for automatic identification of erythrocytes in fish using SLIC segmentation approach and connected components, adjusted
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Galhardi, Lucas, Rodrigo C. Thom De Souza, and Jacques Brancher. "Automatic Grading of Portuguese Short Answers Using a Machine Learning Approach." In Simpósio Brasileiro de Sistemas de Informação. Sociedade Brasileira de Computação (SBC), 2020. http://dx.doi.org/10.5753/sbsi.2020.13133.

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Short answers are routinely used in learning environments for students’ assessment. Despite its importance, teachers find the task of assessing discursive answers very time-consuming. Aiming at assisting in this problem, this work explores the Automatic Short Answer Grading (ASAG) field using a machine learning approach. The literature was reviewed and 44 papers using different techniques were analyzed considering many aspects. A Portuguese dataset was build with more than 7000 short answers. Different approaches were experimented and a final model was created with their combination. The model
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Reports on the topic "Using Different Aspects in Learning"

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Karki, Shanta. Applying the River of Life Method to Support Reflection and Learning in Terre des hommes Nepal. Institute of Development Studies, 2023. http://dx.doi.org/10.19088/clarissa.2023.005.

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The RoL method is a visual narrative method that helps people tell stories of the past, present, and future. Individuals can use this method to introduce themselves in a fun and descriptive way. A group can use it to understand and reflect on the past and imagine the future of a project. Besides, it can also be used to build a shared view of a process over time while acknowledging different and perhaps contradictory perspectives. The method uses drawings rather than text, making it useful in groups that do not share a common language. Metaphors from a river are used to explore aspects of a sto
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Shapovalov, Viktor B., Yevhenii B. Shapovalov, Zhanna I. Bilyk, Artem I. Atamas, Roman A. Tarasenko, and Vitaliy V. Tron. Centralized information web-oriented educational environment of Ukraine. [б. в.], 2019. http://dx.doi.org/10.31812/123456789/3251.

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The modern development of science and technology has provided high quantity of information. This information must be systemized and classified. For taxonomization of educational materials, it was proposed to use existing graph-generators and graph-visualizers of the TODOS IT platform. A separate aspect of the TODOS IT platform is the possibility of using a centralized web-oriented learning environment. Creation of the system and transdisciplinary knowledge is a problem of modern education, which can be solved by creating a centralized web-oriented educational environment. Using this approach i
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Almås, Ingvild, Orazio Attanasio, Jyotsna Jalan, Francisco Oteiza, and Marcella Vigneri. Using data differently and using different data. Centre for Excellence and Development Impact and Learning (CEDIL), 2018. http://dx.doi.org/10.51744/cip8.

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The lack of adequate measures to capture relevant factors, and the prevalence of measurement error in existing ones, often constitute the main impediment to robust policy evaluation. Random assignment of a given treatment, when feasible, may allow for the identification of causal effects, given that the necessary measurements are available. Measurement challenges include: (a) adequately measuring outcomes of interest; (b) measuring factors that relate to the mechanisms of estimated impacts; and (c) conducting a robust evaluation in areas where the RCT methodology is not feasible. In this paper
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Iatsyshyn, Anna V., Valeriia O. Kovach, Volodymyr O. Lyubchak, et al. Application of augmented reality technologies for education projects preparation. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3856.

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After analysis of scientific literature, we defined that concept of “augmented reality” has following synonyms: “advanced reality”, “improved reality”, “enriched reality”, “mixed reality” and “hybrid reality”. Analysis of scientific literature and own practical experience of the use of augmented reality technologies application in educational practices allowed to state next: augmented reality technologies have a great potential for application in education; there are some cases of augmented reality use for school education; positive aspects of augmented reality technologies application in high
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Kohut, Uliana, and Mariya Shyshkina. Providing the Fundamentalisation of Operations Research Learning Using MAXIMA System. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4464.

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In the article, the problems of using the systems of computer mathe- matics (SCM) as a tool to provide the fundamental component of operations re- search learning and students research activities support are considered. The role of SCM in the process of bachelors of informatics training and special aspects of pedagogical applications of these systems in the “Operations research” study is defined. The analysis of the basic concepts of the fundamentalisation of educa- tion and in particular the basic concepts of the fundamentalisation of informatics disciplines learning is summarized. The attemp
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Oliveira, Lucas Gabriel Martins de. Which One Predicts Better?: Comparing Different GDP Nowcasting Methods Using Brazilian Data. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0005004.

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The objective of this paper is to develop a basic framework for the implementation of a GDP nowcasting strategy using Brazilian data. Our goal is to identify a scalable strategy that allows us to project the Brazilian GDP in real time at any point during the current quarter. In the paper we detail the survey of classical techniques and also of techniques usually known by market practitioners as "machine learning methods". We survey the literature since the first work on estimating business cycles and document the evolution of this literature until the insertion of machine learning methods. Add
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Marienko, Maiia V., Yulia H. Nosenko, and Mariya P. Shyshkina. Personalization of learning using adaptive technologies and augmented reality. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4418.

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The research is aimed at developing the recommendations for educators on using adaptive technologies and augmented reality in personalized learning implementation. The latest educational technologies related to learning personalization and the adaptation of its content to the individual needs of students and group work are considered. The current state of research is described, the trends of development are determined. Due to a detailed analysis of scientific works, a retrospective of the development of adaptive and, in particular, cloud-oriented systems is shown. The preconditions of their ap
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Aguiar, Brandon, Paul Bianco, and Arvind Agarwal. Using High-Speed Imaging and Machine Learning to Capture Ultrasonic Treatment Cavitation Area at Different Amplitudes. Florida International University, 2021. http://dx.doi.org/10.25148/mmeurs.009773.

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The ultrasonic treatment process strengthens metals by increasing nucleation and decreasing grain size in an energy efficient way, without having to add anything to the material. The goal of this research endeavor was to use machine learning to automatically measure cavitation area in the Ultrasonic Treatment process to understand how amplitude influences cavitation area. For this experiment, a probe was placed into a container filled with turpentine because it has a similar viscosity to liquid aluminum. The probe gyrates up and down tens of micrometers at a frequency of 20 kHz, which causes c
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Shyshkina, Mariya, and Uliana Kohut. The Method of Using the Maxima System for Operations Research Learning. [б. в.], 2019. http://dx.doi.org/10.31812/123456789/3172.

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In the article, the problems of using the systems of computer mathematics (SCM) as a tool to support the teaching and research activities in the field of informatics and mathematics disciplines training are investigated. The role of SCM in the process of bachelors of informatics training and special aspects of pedagogical applications of these systems in the “Operations research” study is defined. The aim of the article is the justification of the Maxima system use of in the process of “Operations research” teaching in pedagogical university as enchasing the investigative approach to learning
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DeJaeghere, Joan, Vu Dao, Bich-Hang Duong, and Phuong Luong. Inequalities in Learning in Vietnam: Teachers’ Beliefs About and Classroom Practices for Ethnic Minorities. Research on Improving Systems of Education (RISE), 2021. http://dx.doi.org/10.35489/bsg-rise-wp_2021/061.

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Global and national education agendas are concerned with improving quality and equality of learning outcomes. This paper provides an analysis of the case of Vietnam, which is regarded as having high learning outcomes and less inequality in learning. But national data and international test outcomes may mask the hidden inequalities that exist between minoritized groups and majority (Kinh) students. Drawing on data from qualitative videos and interviews of secondary teachers across 10 provinces, we examine the role of teachers’ beliefs, curricular design and actions in the classroom (Gale et al.
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