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Готові списки джерел за темами / Auto-generative learning objects

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Добірка наукової літератури з теми "Auto-generative learning objects"

Автор: Grafiati

Опубліковано: 3 червня 2025

Оновлено: 31 липня 2025

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Статті в журналах з теми "Auto-generative learning objects"

1

Ciprian-Bogdan, Chirila. "BRAIN Journal - Auto-generative Learning Objects in Online Assessment of Data Structures Disciplines." BRAIN - Broad Research in Artificial Intelligence and Neuroscience 8, no. 1 (2017): 24–34. https://doi.org/10.5281/zenodo.1045033.

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ABSTRACT Nowadays, regional IT industry lacks human resources because of the pressure created on the labor market by the high-value economic projects. Tutors tend to be more and more loaded with teaching, research, and administrative tasks. Students tend to use more and more electronically devices like laptops, tablets, and mobile phones in their learning sessions. In this context, universities should rely more on technologies like: LMSs (Learning Management Systems), MOOCs (Massive Open Online Courses), and why not GLOs (Generative Learning Objects) or evenAGLOs (Auto-generative Learning Obje

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Zhang, Yan, Xi Liu, Shiyun Wa, Shuyu Chen, and Qin Ma. "GANsformer: A Detection Network for Aerial Images with High Performance Combining Convolutional Network and Transformer." Remote Sensing 14, no. 4 (2022): 923. http://dx.doi.org/10.3390/rs14040923.

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There has been substantial progress in small object detection in aerial images in recent years, due to the extensive applications and improved performances of convolutional neural networks (CNNs). Typically, traditional machine learning algorithms tend to prioritize inference speed over accuracy. Insufficient samples can cause problems for convolutional neural networks, such as instability, non-convergence, and overfitting. Additionally, detecting aerial images has inherent challenges, such as varying altitudes and illuminance situations, and blurred and dense objects, resulting in low detecti

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Maldonado-Romo, Javier, and Mario Aldape-Pérez. "Interoperability between Real and Virtual Environments Connected by a GAN for the Path-Planning Problem." Applied Sciences 11, no. 21 (2021): 10445. http://dx.doi.org/10.3390/app112110445.

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Path planning is a fundamental issue in robotic systems because it requires coordination between the environment and an agent. The path-planning generator is composed of two modules: perception and planning. The first module scans the environment to determine the location, detect obstacles, estimate objects in motion, and build the planner module’s restrictions. On the other hand, the second module controls the flight of the system. This process is computationally expensive and requires adequate performance to avoid accidents. For this reason, we propose a novel solution to improve conventiona

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Chen, Yushi, Lingbo Huang, Lin Zhu, Naoto Yokoya, and Xiuping Jia. "Fine-Grained Classification of Hyperspectral Imagery Based on Deep Learning." Remote Sensing 11, no. 22 (2019): 2690. http://dx.doi.org/10.3390/rs11222690.

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Hyperspectral remote sensing obtains abundant spectral and spatial information of the observed object simultaneously. It is an opportunity to classify hyperspectral imagery (HSI) with a fine-grained manner. In this study, the fine-grained classification of HSI, which contains a large number of classes, is investigated. On one hand, traditional classification methods cannot handle fine-grained classification of HSI well; on the other hand, deep learning methods have shown their powerfulness in fine-grained classification. So, in this paper, deep learning is explored for HSI supervised and semi-

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Valdés, Julio J., and Alain B. Tchagang. "Novel machine learning insights into the QM7b and QM9 quantum mechanics datasets." Journal of Computational Chemistry, February 8, 2024. http://dx.doi.org/10.1002/jcc.27295.

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AbstractThis paper (i) explores the internal structure of two quantum mechanics datasets (QM7b, QM9), composed of several thousands of organic molecules and described in terms of electronic properties, and (ii) further explores an inverse design approach to molecular design consisting of using machine learning methods to approximate the atomic composition of molecules, using QM9 data. Understanding the structure and characteristics of this kind of data is important when predicting the atomic composition from physical‐chemical properties in inverse molecular designs. Intrinsic dimension analysi

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Ahn, Sungyong. "On That <em>Toy-Being</em> of Generative Art Toys." M/C Journal 26, no. 2 (2023). http://dx.doi.org/10.5204/mcj.2947.

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Exhibiting Procedural Generation Generative art toys are software applications that create aesthetically pleasing visual patterns in response to the users toying with various input devices, from keyboard and mouse to more intuitive and tactile devices for motion tracking. The “art” part of these toy objects might relate to the fact that they are often installed in art galleries or festivals as a spectacle for non-players that exhibits the unlimited generation of new patterns from a limited source code. However, the features that used to characterise generative arts as a new meditative genre, s

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Дисертації з теми "Auto-generative learning objects"

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Shahid, Mustafizur Rahman. "Deep learning for Internet of Things (IoT) network security." Electronic Thesis or Diss., Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAS003.

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L’internet des objets (IoT) introduit de nouveaux défis pour la sécurité des réseaux. La plupart des objets IoT sont vulnérables en raison d'un manque de sensibilisation à la sécurité des fabricants d'appareils et des utilisateurs. En conséquence, ces objets sont devenus des cibles privilégiées pour les développeurs de malware qui veulent les transformer en bots. Contrairement à un ordinateur de bureau, un objet IoT est conçu pour accomplir des tâches spécifiques. Son comportement réseau est donc très stable et prévisible, ce qui le rend bien adapté aux techniques d'analyse de données. Ainsi,

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Тези доповідей конференцій з теми "Auto-generative learning objects"

1

Costea, Felicia mirabela, Ciprianbogdan Chirila, and Vladimirioan Cretu. "REDESIGNING EDUCATIONAL TOOLS USING AUTO-GENERATIVE LEARNING OBJECTS." In eLSE 2019. Carol I National Defence University Publishing House, 2019. http://dx.doi.org/10.12753/2066-026x-19-118.

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Technology development affects all areas of social life. In the digital age we live in, education must keep up with new trends. This can be achieved by transforming how learning is organized into a modern, efficient and flexible one. Young people in our society are almost technology dependent, using electronic devices for both learning, socializing and leisure. The field of e-learning has significant potential for research as it is a quite new concept in the current socio-economic context of Romania. Digital technology produces certain changes in the learning environment such as virtual learni

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CHIRILA, Ciprian-Bogdan. "Harnessing Auto-Generative Learning Objects in Serious Games." In International Conference on Virtual Learning - VIRTUAL LEARNING - VIRTUAL REALITY (17th edition). The National Institute for Research & Development in Informatics - ICI Bucharest (ICI Publishing House), 2022. http://dx.doi.org/10.58503/icvl-v17y202223.

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Costea, Feliciamirabela, Ciprianbogdan Chirila, and Vladimirioan Cretu. "AUTO-GENERATIVE LEARNING OBJECTS FOR MIDDLE SCHOOL ARITHMETIC." In eLSE 2018. Carol I National Defence University Publishing House, 2018. http://dx.doi.org/10.12753/2066-026x-18-258.

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Nowadays middle school students tend to use more and more gadgets like tablets, smart phones and laptops. Learning materials tend to become electronic having automatic evaluation mechanisms like quizzes, tests, etc. The learning materials usually have static content. Even LMS supported evaluations implemented by quizzes have static questions and answers and the only solution to create diversity for the student is to shuffle the order or both questions and answers. In this context there is a high interest in the topic of reusable learning designs in order to create dynamic content. These offer

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Costea, Felicia-Mirabela, Ciprian-Bogdan Chirila, and Vladimir-Ioan Cretu. "Auto-Generative Learning Objects for Learning Linked Lists Concepts." In 2020 International Symposium on Electronics and Telecommunications (ISETC). IEEE, 2020. http://dx.doi.org/10.1109/isetc50328.2020.9301136.

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Costea, Felicia mirabela, Ciprianbogdan Chirila, and Vladimirioan Cretu. "A USE CASE FOR ARITHMETIC AUTO-GENERATIVE LEARNING OBJECTS IN PANDEMIC." In eLSE 2021. ADL Romania, 2021. http://dx.doi.org/10.12753/2066-026x-21-087.

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During the COVID-19 pandemic the educational processes were interrupted in most of the countries in the world. Governments switched from face-to-face education to online sessions using learning management systems and video and audio communication tools. Pupils connect to online classes using laptops, tablets, and sometimes using mobile phones. These methods are exhausting and tiring for the pupils, so a limit of half of the time used in the face-to-face classes was set for the online classes. This approach restricts the number of hours a tutor works directly with their students. Probably the t

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Costea, Felicia-Mirabela, Ciprian-Bogdan Chirila, and Vladimir-Loan Cretu. "Towards Auto-Generative Learning Objects for Industrial IT Services." In 2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI). IEEE, 2018. http://dx.doi.org/10.1109/saci.2018.8441004.

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Costea, Felicia-Mirabela, Ciprian-Bogdan Chirila, Oana-Sorina Chirila, and Vladimir-Ioan Cretu. "On the Generation of Random Data for Auto-Generative Learning Objects." In 2019 IEEE 13th International Symposium on Applied Computational Intelligence and Informatics (SACI). IEEE, 2019. http://dx.doi.org/10.1109/saci46893.2019.9111603.

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Chirila, Ciprian-Bogdan, and Gaultier Parain. "Metamodels for Auto-Generative Learning Objects Dedicated to Unix Operating System Disciplines." In 2018 22nd International Conference on System Theory, Control and Computing (ICSTCC). IEEE, 2018. http://dx.doi.org/10.1109/icstcc.2018.8540680.

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Costea, Felicia-Mirabela, Ciprian-Bogdan Chirila, and Vladimir-Ioan Cretu. "Middle School Arithmetic Auto-Generative Learning Objects to Support Learning in the COVID-19 Pandemic." In 2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI). IEEE, 2021. http://dx.doi.org/10.1109/saci51354.2021.9465595.

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Chirila, Ciprianbogdan, and Remy Raes. "GENERIC ONLINE ALGORITHM INTERPRETER WITH DYNAMIC DATA VISUALIZATIONS. CASE STUDY ON SORTING ALGORITHMS." In eLSE 2017. Carol I National Defence University Publishing House, 2017. http://dx.doi.org/10.12753/2066-026x-17-122.

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Анотація:

Nowadays IT is present in our everyday life like: cars, phones, clothes, watches, houses etc. In this context the developing industry for such products is in a continuous need of specialists. One of the basic features of IT specialists is the ability to program, namely to be able to write code to be understood by machines and devices. Each year company representatives ask universities to double the number of graduates. Teaching students to write code is a complex and hard task proved by very high dropout rate after the first year of study in the distance learning programs. In order to ameliora

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