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Relevant bibliographies by topics / Cloud computing Blended learning

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Academic literature on the topic 'Cloud computing Blended learning'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "Cloud computing Blended learning"

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Sun, Zeyu, and Yunxing Shu. "Analysis of Blended Learning Scheme Based on Cloud Computing Assisted Instructions." International Journal of Emerging Technologies in Learning (iJET) 11, no. 03 (2016): 51. http://dx.doi.org/10.3991/ijet.v11i03.5535.

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With the development of science and technology, cloud computing technology has been widely applied in a variety of engineering fields, while its application and promotion in the education is always neglected. In this paper, the cloud computing assisted hybrid learning scheme is put forward based on the analysis of the cloud computing technology and the hybrid method. Firstly, the cloud computing platform architecture and key technology are explained. Secondly, the four stages of the blended learning scheme model are established in accordance with its guiding ideology and construction principle

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Kerimbaev, N. N., V. S. Jotsov, and M. J. Bolyskhanova. "APPLICATION OF CLOUD TECHNOLOGIES IN BLENDED LEARNING METHODS." BULLETIN Series of Physics & Mathematical Sciences 72, no. 4 (2020): 202–7. http://dx.doi.org/10.51889/2020-4.1728-7901.31.

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This article provides an overview of scientific papers on the importance of using cloud technologies. The use of cloud technologies and cloud computing services in higher education is dictated by modern requirements. Currently, one of the tasks set for higher education institutions to improve the field of education is the implementation of blended teaching methods. From this point of view, the article discusses methods and techniques that give advantages in blended learning using modern cloud technologies. It is also reported that cloud technologies can be applied to both traditional education

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Soykan, Emrah, and Fezile Ozdamli. "The Impact of M-Learning Activities on the IT Success and M-Learning Capabilities of the Special Education Teacher Candidates." World Journal on Educational Technology: Current Issues 8, no. 3 (2016): 267. http://dx.doi.org/10.18844/wjet.v8i3.1019.

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The advantages of using mobile devices and cloud computing services in education are accepted by many researchers. Also, in educating students who are in need of special education, the use of cloud computing services is inevitable. So, this case requires teacher candidates who are planning to teach in those special education centers to be able to use these technologies sufficiently, be able to perceive positively and in order to be able to follow future improvements and innovations. Therefore, the aim of this study is to identify the perceptions of teacher candidates’ mobile learning implement

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Ciric, Vladimir, Ivan Milentijevic, Oliver Vojinovic, and Nemanja Manic. "Cost Estimation of Blended Learning Course Delivery Through Public Cloud." JUCS - Journal of Universal Computer Science 25, no. (4) (2019): 310–33. https://doi.org/10.3217/jucs-025-04-0310.

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There is a lot of educational institutions that own blended learning platforms, and even more that do not. The era of cloud computing offers a possibility for those who do not own such platforms to utilize public cloud resources for courses delivery. The goal of this paper is design and cost estimation of flexible blended learning platform suitable for cloud implementation. In this paper we present technical requirements and create a mathematical model which allows one to estimate the cost of course delivery through public cloud. As a basis for the cost estimation, a model of blended learning

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Fransisca, Monica, and Yuliawati Yunus. "Validitas Pengembangan Media Pembelajaran Blended Learning Berbasis Cloud Computing Tingkat Sekolah Menengah Atas Kota Padang." Prosiding Seminar Nasional Riset Information Science (SENARIS) 1 (September 30, 2019): 103. http://dx.doi.org/10.30645/senaris.v1i0.13.

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The purpose of this research was to create an E-Learning as learning media with the implementation of Blended learning models combined with Cloud computing. These products will be designed interactively, effectively, and efficiently in accordance with lesson courses on subjects in high school with online system. The research method used is Research and Development with the stages of development of 4D (Define, Design, Develop, Disseminate), in this research the product will be tested for feasibility by validity testing. Based on the results of the validity test conducted by system experts and c

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Cao, Chang. "A New Cloud with IoT-Enabled Innovation and Skill Requirement of College English Teachers on Blended Teaching Model." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 6s (2023): 127–37. http://dx.doi.org/10.17762/ijritcc.v11i6s.6816.

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The blended teaching model is a type of educational approach that combines traditional classroom-based instruction with online learning experiences. In this model, students are given access to digital content, resources, and tools, which they can use to supplement their in-person classroom instruction. The blended teaching model is also sometimes referred to as the hybrid learning model. IoT-SDNCT (IoT enabled SDN reinforcement learning with Cloud Technological Innovation and Skill Requirement of College English Teachers on Blended Teaching Model) is a proposed system that aims to revolutioniz

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Xin, Liao. "Scalable Computing Infrastructure for Online and Blended Learning Environments." Scalable Computing: Practice and Experience 24, no. 3 (2023): 597–607. http://dx.doi.org/10.12694/scpe.v24i3.2293.

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With the growing popularity of online learning and blended learning, as well as the rapid development of cloud computing and big data technology, scalable computing infrastructure has become an indispensable part of building a modern education platform. Method: Five experiments were conducted to test the scalability and reliability of computing infrastructure based on online and blended learning environments. The experiments include the performance comparison of online learning platforms based on different virtualization technologies, the performance comparison of online and hybrid learning en

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Wu, Xiao. "Cloud-Based Collaborative English Online and Offline Hybrid Teaching." Wireless Communications and Mobile Computing 2022 (April 21, 2022): 1–11. http://dx.doi.org/10.1155/2022/8048646.

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In the information age, teachers are not the only source of information. The traditional teaching method brings problems such as passive learning and low interest in learning. This paper is aimed at studying how to analyze and study the hybrid teaching of English online and offline based on cloud collaboration and describing edge computing. This paper proposes the problem of mixed teaching of English online and offline. This question builds on the fundamentals of cloud collaboration. Therefore, the concept and related algorithms are expounded, and the case design and analysis of blended teachi

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Sholihatin, Endang, Gendut Sukarno, Arista Pratama, Indrawati Yuhertiana, Sukirmiyadi Sukirmiyadi, and Nanang Haryono. "PENGUATAN KOMPETENSI MENGAJAR GURU DALAM MEMBUAT INOVASI PEMBELAJARAN BLANDED LEARNING DI SMP MUHAMMADIYAH 14 LAMONGAN." Jurnal Layanan Masyarakat (Journal of Public Services) 5, no. 2 (2021): 316. http://dx.doi.org/10.20473/jlm.v5i2.2021.316-324.

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AbstractThe face-to-face school learning process in the midst of the covid pandemic is carried out online. This is based on the policy of the Ministry of Education, Circular Letter Number 4 of 2020 regarding the implementation of education policies in the emergency period of the spread of the corona virus. The pandemic condition with the online learning process requires schools and teachers to innovate in the teaching and learning process. With the aim of strengthening the teaching competence of teachers in making learning innovations, the community partnership program is carried out based on

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Malele, Vusumuzi. "Cybersecurity Cloud-Based Online Learning: A Literature Review Approach." Journal of Information Systems and Informatics 5, no. 4 (2023): 1623–32. http://dx.doi.org/10.51519/journalisi.v5i4.583.

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Cloud-based online learning is the electronic learning activity that supports teaching and learning (T&L) that could be done from anywhere and in the world. Some of its benefits are scalability and affordability that could in a decision-making support on the mechanisms of material selection. Cloud computing has been adopted by most universities around the world. In this regard, lecturers and students will use it to facilitate T&L; however, due to concerns of information technology or systems security, cloud-based online learning users are also not immune. In this regard, the users coul

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Dissertations / Theses on the topic "Cloud computing Blended learning"

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Gera, Amit. "Provisioning for Cloud Computing." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1293740673.

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Singh, Vivek Kumar. "Essays on Cloud Computing Analytics." Scholar Commons, 2019. https://scholarcommons.usf.edu/etd/7943.

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This dissertation research focuses on two key aspects of cloud computing research – pricing and security using data-driven techniques such as deep learning and econometrics. The first dissertation essay (Chapter 1) examines the adoption of spot market in cloud computing and builds IT investment estimation models for organizations adopting cloud spot market. The second dissertation essay (Chapter 2 and 3) studies proactive threat detection and prediction in cloud computing. The final dissertation essay (Chapter 4) develops a secured cloud files system which protects organizations using cloud co

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Wong, Wai Ho. "Predicting Demand in Cloud Computing Environments." Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/9497.

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Cloud computing is a new computing paradigm that enables elastic on-demand pay-per-use access to shared computational resources. However, there are current limitations on the elasticity of cloud resources specifically deployment delays and mismatches in pricing granularity. Demand prediction - the estimation of future demand - serves to mitigate these limitations of elasticity. The focus of this thesis is the demand predictor that operates within the context of cloud resource management. It fulfils three tasks: 1) learn demand patterns from past demand behaviour; 2) predict upcoming demand

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Andersson, Mattias, and Christopher Ludvigsson. "Cloud Computing : Lärplattform i molnet." Thesis, Uppsala universitet, Institutionen för informatik och media, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-155080.

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Cloud computings framväxt har möjliggjort tillhandhållande av datorresurser online och erbjuder två väsentliga egenskaper, dels upplevda oändliga resurser och dels betalning per resursförbrukning. Lärplattformar används idag i stor utsträckning av de svenska universiteten och högskolorna som studieverktyg. Detta medför bättre möjligheter för distanskurser och e-inlärning. Att kombinera cloud computing med en lärplattform är idag möjligt och bör därför ge skolorna fördelar. Om lärplattformen driftas som molntjänst av extern leverantör bör också kraven se annorlunda ut. Syftet med uppsatsen är a

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Agrawal, Harsh. "CloudCV: Deep Learning and Computer Vision on the Cloud." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/71381.

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We are witnessing a proliferation of massive visual data. Visual content is arguably the fastest growing data on the web. Photo-sharing websites like Flickr and Facebook now host more than 6 and 90 billion photos, respectively. Unfortunately, scaling existing computer vision algorithms to large datasets leaves researchers repeatedly solving the same algorithmic and infrastructural problems. Designing and implementing efficient and provably correct computer vision algorithms is extremely challenging. Researchers must repeatedly solve the same low-level problems: building and maintaining a clust

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Naranjo, Delgado Diana María. "Serverless Computing Strategies on Cloud Platforms." Doctoral thesis, Universitat Politècnica de València, 2021. http://hdl.handle.net/10251/160916.

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[ES] Con el desarrollo de la Computación en la Nube, la entrega de recursos virtualizados a través de Internet ha crecido enormemente en los últimos años. Las Funciones como servicio (FaaS), uno de los modelos de servicio más nuevos dentro de la Computación en la Nube, permite el desarrollo e implementación de aplicaciones basadas en eventos que cubren servicios administrados en Nubes públicas y locales. Los proveedores públicos de Computación en la Nube adoptan el modelo FaaS dentro de su catálogo para proporcionar computación basada en eventos altamente escalable para las aplicaciones. Por

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Piovesan, Sandra Dutra. "U-SEA: UM AMBIENTE DE APRENDIZAGEM UBÍQUO UTILIZANDO CLOUD COMPUTING." Universidade Federal de Santa Maria, 2011. http://repositorio.ufsm.br/handle/1/5388.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>The diffusion of the learning virtual environments use shows a great potential to the applications development that meet the needs in the education area. In view of the importance of a more dynamic application and one that can adapt itself to the needs of the students, it was proposed and developed the U-SEA (oblique adapted teaching system). This system was built based on the learning virtual environment Moodle and on the module Mle-Moodle, available in an infrastructure of Cloud-Computing and has as a main finality the adaptation

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Liverani, Tommaso. "Federated Learning per Applicazioni Edge Cloud su Piattaforma fog05." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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Federated learning è sicuramente una delle tecniche di machine learning di maggiore interesse attualmente. Esso trova applicazione nello scenario fog computing in cui risulta spesso necessario mantenere la riservatezza dei dati mantenuti nei nodi fog. La riservatezza dei dati è infatti una delle caratteristiche peculiari dei processi di federated learning. In tali scenari risulta particolarmente utile impiegare una piattaforma con supporto alla migrazione che potrà essere utilizzato per implementare determinati meccanismi come il bilanciamento di carico. Questo supporto potrà quindi esser

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Della, Penna Roberto. "Edge Cloud Computing Middleware per Predictive Maintenance in Industria 4.0." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20065/.

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Il paradigma Edge Cloud Computing ha assunto, negli ultimi anni, un ruolo sempre più importante, soprattutto nel contesto di Industria 4.0, in cui la nascita di nuovi modelli di business basati sull’acquisizione e l’analisi di dati si sono scontrati con le limitazioni imposte dal modello architetturale classico introdotto dal paradigma Cloud Computing. In particolare, la latenza, il consumo di banda, e la dipendenza da un’infrastruttura centralizzata sono stati i fattori abilitanti per l’evoluzione del modello a due livelli, composto da sorgenti dati e infrastruttura cloud, verso l’introduzion

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Khan, Syeduzzaman. "A PROBABILISTIC MACHINE LEARNING FRAMEWORK FOR CLOUD RESOURCE SELECTION ON THE CLOUD." Scholarly Commons, 2020. https://scholarlycommons.pacific.edu/uop_etds/3720.

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The execution of the scientific applications on the Cloud comes with great flexibility, scalability, cost-effectiveness, and substantial computing power. Market-leading Cloud service providers such as Amazon Web service (AWS), Azure, Google Cloud Platform (GCP) offer various general purposes, memory-intensive, and compute-intensive Cloud instances for the execution of scientific applications. The scientific community, especially small research institutions and undergraduate universities, face many hurdles while conducting high-performance computing research in the absence of large dedicated cl

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Books on the topic "Cloud computing Blended learning"

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Ma, Will W. K., Chen Li, Chun Wai Fan, Leong Hou U, and Angel Lu, eds. Blended Learning. Intelligent Computing in Education. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4442-8.

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Shrawankar, Urmila, and Prerna Mishra. Cloud Computing for Smart Education and Collaborative Learning. Chapman and Hall/CRC, 2025. https://doi.org/10.1201/9781003472537.

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Vostokov, Dmitry. Python Debugging for AI, Machine Learning, and Cloud Computing. Apress, 2024. http://dx.doi.org/10.1007/978-1-4842-9745-2.

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Pani, Subhendu Kumar, Somanath Tripathy, Talal Ashraf Butt, Sumit Kundu, and George Jandieri. Applications of Machine Learning in Big-Data Analytics and Cloud Computing. River Publishers, 2022. http://dx.doi.org/10.1201/9781003337218.

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Chao, Lee. Cloud computing for teaching and learning: Strategies for design and implementation. Information Science Reference, 2012.

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Chao, Lee. Cloud computing for teaching and learning: Strategies for design and implementation. Information Science Reference, 2012.

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Sun, Fuchun, Hesheng Wang, Han Long, Yifei Wei, and Hongqi Yu, eds. Proceedings of the 3rd International Conference on Machine Learning, Cloud Computing and Intelligent Mining (MLCCIM2024). Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2468-3.

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Sun, Fuchun, Hesheng Wang, Han Long, Yifei Wei, and Hongqi Yu, eds. Proceedings of the 3rd International Conference on Machine Learning, Cloud Computing and Intelligent Mining (MLCCIM2024). Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-1698-5.

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Bai, Haishi. Zen of Cloud: Learning Cloud Computing by Examples, Second Edition. Taylor & Francis Group, 2019.

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Bai, Haishi. Zen of Cloud: Learning Cloud Computing by Examples, Second Edition. Taylor & Francis Group, 2019.

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Book chapters on the topic "Cloud computing Blended learning"

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Yang, Harrison Hao. "The Development of Collaborative Action Research through Cloud Computing Document-Sharing Services and Blended Learning Process." In Hybrid Learning. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32018-7_10.

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Setiana, Desi, and Norainna Besar. "Blended Learning, Big Data, Social Networking, and Cloud Computing: A Shifting Paradigm." In Digital Education. Apple Academic Press, 2024. http://dx.doi.org/10.1201/9781032670782-6.

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Wang, Xiaolin. "The Construction of College English Blended Learning Model Based on Live Online Teaching Under Cloud Computing." In Lecture Notes in Electrical Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0115-6_290.

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Rennie, Frank, and Keith Smyth. "Cloud computing." In Digital Learning: The Key Concepts, 2nd ed. Routledge, 2019. http://dx.doi.org/10.4324/9780429425240-33.

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Cheng, Hsin-Pai, Patrick Yu, Haojing Hu, et al. "Towards Decentralized Deep Learning with Differential Privacy." In Cloud Computing – CLOUD 2019. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23502-4_10.

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Simeonov, Dimitar, and D. R. Avresky. "Proactive Software Rejuvenation Based on Machine Learning Techniques." In Cloud Computing. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12636-9_13.

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Gupta, Pramod, Naresh Kumar Sehgal, and John M. Acken. "Cloud Computing Concepts." In Introduction to Machine Learning with Security. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-59170-9_4.

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Vojtesek, Jiri, and Jan Hutak. "Using Multimedia in Blended Learning." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19807-7_25.

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Lin, Peng, Kejiang Ye, and Cheng-Zhong Xu. "Dynamic Network Anomaly Detection System by Using Deep Learning Techniques." In Cloud Computing – CLOUD 2019. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23502-4_12.

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Bisong, Ekaba. "What Is Cloud Computing?" In Building Machine Learning and Deep Learning Models on Google Cloud Platform. Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4470-8_1.

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Conference papers on the topic "Cloud computing Blended learning"

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Mishra, Pratik, Sandeep Hans, Diptikalyan Saha, and Pratibha Moogi. "Optimizing Cloud Workloads: Autoscaling with Reinforcement Learning." In 2024 IEEE 17th International Conference on Cloud Computing (CLOUD). IEEE, 2024. http://dx.doi.org/10.1109/cloud62652.2024.00033.

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Choi, Wonmi, Juyoung Ahn, Yeonho Yoo, Chuck Yoo, and Gyeongsik Yang. "Harmonia: Accurate Federated Learning with All-Inclusive Dataset." In 2024 IEEE 17th International Conference on Cloud Computing (CLOUD). IEEE, 2024. http://dx.doi.org/10.1109/cloud62652.2024.00041.

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Capogrosso, Luigi, Shengjie Xu, Enrico Fraccaroli, Marco Cristani, Franco Fummi, and Samarjit Chakraborty. "Learning-Enabled CPS for Edge-Cloud Computing." In 2024 IEEE 14th International Symposium on Industrial Embedded Systems (SIES). IEEE, 2024. https://doi.org/10.1109/sies62473.2024.10767956.

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Makala, Daniel, and Li Zongmin. "Application of Deep Learning in Tourist." In International Conference on Cognitive & Cloud Computing. SCITEPRESS - Science and Technology Publications, 2024. https://doi.org/10.5220/0013342500004646.

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Lata, Manju, and Vibhu Sharma. "Cloud Computing Based Blended Learning: Quality Assurance Challenges." In 2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE). IEEE, 2024. http://dx.doi.org/10.1109/ic3se62002.2024.10593466.

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Porumb, Cosmin, Sanda Porumb, Ionut Hoza, and Bogdan Orza. "CLOUD COMPUTING AND ITS APPLICATION TO BLENDED LEARNING IN ENGINEERING." In eLSE 2012. Editura Universitara, 2012. http://dx.doi.org/10.12753/2066-026x-12-132.

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The education process in engineering means theory and practice, individual study, group-based projects or experimental work that involves equipment, simulation/emulation software packages and laboratory applications. In order to develop e-learning platforms for higher and postgraduate education in engineering, new methodologies should be taken into consideration: project- and problem based learning, virtual laboratory (remote access to laboratory infrastructure and task evaluation) or remote assistance for diploma projects and mobility grants. This paper presents new blended learning methodolo

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Blomgren, Connie, Martha Cleveland-Innes, and Elena Chudaeva. "Global Viewpoints on Open Educational Resources for Blended Learning." In Tenth Pan-Commonwealth Forum on Open Learning. Commonwealth of Learning, 2022. http://dx.doi.org/10.56059/pcf10.5737.

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OER are considered a key component to meeting the United Nations Sustainable Development Goal 4 (Quality Education) as well as being foundational to meeting the other remaining sixteen goals. For several years, the Blended Learning Practice MOOC has been offered in a partnership between Athabasca University and the Commonwealth of Learning. The Global Viewpoints on Open Educational Resources for Blended Learning research project analyszed mooc data to explore the following research question: What are the impressions of cMOOC participants with regards to Open Educational Resources as part of bl

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"Blended Learning Using Lms-Moodle with Cloud Computing to Enhance Analytical Thinking for Undergraduate Students." In 2019 the 9th International Workshop on Computer Science and Engineering. WCSE, 2019. http://dx.doi.org/10.18178/wcse.2019.03.020.

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Gong, Rui, and Qi Chen. "Research on application of cloud computing technology in blended learning based on access control model." In 2021 2nd International Conference on Information Science and Education (ICISE-IE). IEEE, 2021. http://dx.doi.org/10.1109/icise-ie53922.2021.00114.

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"The Effects of Blended Learning Model via Learning Environment on Cloud Computing to Enhance Creative Products of Undergraduate Students." In Dec. 25-26, 2017 Bangkok (Thailand). URST, 2017. http://dx.doi.org/10.17758/urst.iah1217409.

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Reports on the topic "Cloud computing Blended learning"

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Korobeinikova, Tetiana I., Nataliia P. Volkova, Svitlana P. Kozhushko, et al. Google cloud services as a way to enhance learning and teaching at university. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3854.

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The article is devoted to the issue of a cloud-based learning system implementation as a powerful strategy for future specialists’ training at higher educational establishments. Using cloud computing in self-work management of the university courses is essential to equip students with a workload of appropriate educational materials and variable activities for professional training. Theoretical and empirical research methods were applied to select the appropriate services and tools for organizing students’ self-work at university. Critical analysis of scientific literature, synthesis of the dat

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Proskura, Svitlana L., and Svitlana H. Lytvynova. The approaches to Web-based education of computer science bachelors in higher education institutions. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3892.

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The problem of organizing of Web-based education of bachelors, and the bachelors of computer science in particular, is relevant for higher education institutions. The IT industry puts forward new requirements for future IT professionals training. This, in its turn, requires the educational process modernization: content specification, updating of forms, methods and means of training to meet the demands of socio-economic development of the society in general and bachelors of computer science in particular. The article analyzes and clarifies the notion of Web-based education of bachelors; as wel

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Brand, James, Mert Demirer, Connor Finucane, and Avner Kreps. Firm Productivity and Learning in the Digital Economy: Evidence from Cloud Computing. National Bureau of Economic Research, 2024. http://dx.doi.org/10.3386/w32938.

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Pasupuleti, Murali Krishna. Securing AI-driven Infrastructure: Advanced Cybersecurity Frameworks for Cloud and Edge Computing Environments. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv225.

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Abstract: The rapid adoption of artificial intelligence (AI) in cloud and edge computing environments has transformed industries by enabling large-scale automation, real-time analytics, and intelligent decision-making. However, the increasing reliance on AI-powered infrastructures introduces significant cybersecurity challenges, including adversarial attacks, data privacy risks, and vulnerabilities in AI model supply chains. This research explores advanced cybersecurity frameworks tailored to protect AI-driven cloud and edge computing environments. It investigates AI-specific security threats,

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Markova, Oksana M., Serhiy O. Semerikov, Andrii M. Striuk, Hanna M. Shalatska, Pavlo P. Nechypurenko, and Vitaliy V. Tron. Implementation of cloud service models in training of future information technology specialists. [б. в.], 2019. http://dx.doi.org/10.31812/123456789/3270.

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Leading research directions are defined on the basis of self-analysis of the study results on the use of cloud technologies in training by employees of joint research laboratory “Сloud technologies in education” of Kryvyi Rih National University and Institute of Information Technology and Learning Aids of the NAES of Ukraine in 2009-2018: cloud learning technologies, cloud technologies of blended learning, cloud-oriented learning environments, cloud-oriented methodological systems of training, the provision of cloud-based educational services. The ways of implementation SaaS, PaaS, IaaS cloud

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Gavryliuk, Olga. Comparison of available cloud-based learning technologies for the preparation of Bachelor of Statistics. RVV TSDPU im. V. Vynnychenka, 2019. https://doi.org/10.33407/lib.naes.id/eprint/717067.

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In the article the conceptual-terminological apparatus of the research is presented, such concepts as cloud technologies, cloud services, technologies of training, cloud-oriented learning technologies, competence, professional competence are considered. The advantages of cloud technologies, which consist of the dynamism of the provision of computing resources and software-hardware, the ability to customize it to personal usage needs. Besides, access to multi-sectoral e-learning resources may be provided on a specially set cloud server or placed on other electronic data carriers that are access

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Oleksiuk, Vasyl P., and Olesia R. Oleksiuk. Methodology of teaching cloud technologies to future computer science teachers. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3891.

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The article deals with the problem of training future computer science teachers for the use of cloud technologies. The authors analyzed courses from leading universities to study cloud technologies. On this basis the model of application and studying of cloud technologies in the process of training of future teachers of informatics was developed. The basic principles of this model are proposed: systematic, gradual, continuous. It contains target, content, operating and effective component. Therefore, the stages of using cloud computing technology were proposed: as a means of organizing learnin

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Gavryliuk, Olga. The use of cloud-based learning technologies to shape the professional competencies of future bachelors of statistics: a conceptual terminology research tool. National Pedagogical Dragomanov University, 2019. https://doi.org/10.33407/lib.naes.id/eprint/715382.

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In the article the conceptual-terminological apparatus of the research is presented, such concepts as cloud technologies, cloud services, technologies of training, cloud-oriented learning technologies, competence, professional competence are considered. The advantages of cloud technologies, which consist of the dynamism of the provision of computing resources and software-hardware, the ability to customize it to personal usage needs. Besides, access to multi-sectoral e-learning resources may be provided on a specially set cloud server or placed on other electronic data carriers that are access

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Varina, Hanna B., Viacheslav V. Osadchyi, Kateryna P. Osadcha, Svetlana V. Shevchenko, and Svitlana H. Lytvynova. Peculiarities of cloud computing use in the process of the first-year students' adaptive potential development. [б. в.], 2021. http://dx.doi.org/10.31812/123456789/4453.

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Technologies based on cloud computing is one of the demanded and actively developing areas of the modern information world. Cloud computing refers to an innovative technology that allows you to combine IT resources of various hardware platforms into a single whole and provide the user with access to them via a local network or the global Internet. Cloud services from various providers offer users access to their resources via the Internet via free or shareware cloud applications, the hardware and software requirements of which do not imply that the user has high-performance and resource-consum

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Pasupuleti, Murali Krishna. Next-Generation Extended Reality (XR): A Unified Framework for Integrating AR, VR, and AI-driven Immersive Technologies. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv325.

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Abstract: Extended Reality (XR), encompassing Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), is evolving into a transformative technology with applications in healthcare, education, industrial training, smart cities, and entertainment. This research presents a unified framework integrating AI-driven XR technologies with computer vision, deep learning, cloud computing, and 5G connectivity to enhance immersion, interactivity, and scalability. AI-powered neural rendering, real-time physics simulation, spatial computing, and gesture recognition enable more realistic and adap

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