Academic literature on the topic 'Self-adaptation, Data-driven, Machine learning, Software architecture'
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Journal articles on the topic "Self-adaptation, Data-driven, Machine learning, Software architecture"
Lopes, Rui Pedro, Bárbara Barroso, Leonel Deusdado, André Novo, Manuel Guimarães, João Paulo Teixeira, and Paulo Leitão. "Digital Technologies for Innovative Mental Health Rehabilitation." Electronics 10, no. 18 (September 14, 2021): 2260. http://dx.doi.org/10.3390/electronics10182260.
Full textRodríguez-Gracia, Diego, José A. Piedra-Fernández, Luis Iribarne, Javier Criado, Rosa Ayala, Joaquín Alonso-Montesinos, and Capobianco-Uriarte Maria de las Mercedes. "Microservices and Machine Learning Algorithms for Adaptive Green Buildings." Sustainability 11, no. 16 (August 9, 2019): 4320. http://dx.doi.org/10.3390/su11164320.
Full textPark, Seunghyun, and Jin-Young Choi. "Malware Detection in Self-Driving Vehicles Using Machine Learning Algorithms." Journal of Advanced Transportation 2020 (January 17, 2020): 1–9. http://dx.doi.org/10.1155/2020/3035741.
Full textThembelihle, Dlamini, Michele Rossi, and Daniele Munaretto. "Softwarization of Mobile Network Functions towards Agile and Energy Efficient 5G Architectures: A Survey." Wireless Communications and Mobile Computing 2017 (2017): 1–21. http://dx.doi.org/10.1155/2017/8618364.
Full textAlexander, Francis J., James Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, et al. "Co-design Center for Exascale Machine Learning Technologies (ExaLearn)." International Journal of High Performance Computing Applications 35, no. 6 (September 27, 2021): 598–616. http://dx.doi.org/10.1177/10943420211029302.
Full textKondratenko, Yuriy, Igor Atamanyuk, Ievgen Sidenko, Galyna Kondratenko, and Stanislav Sichevskyi. "Machine Learning Techniques for Increasing Efficiency of the Robot’s Sensor and Control Information Processing." Sensors 22, no. 3 (January 29, 2022): 1062. http://dx.doi.org/10.3390/s22031062.
Full textAkbari, Ali, Jonathan Martinez, and Roozbeh Jafari. "Facilitating Human Activity Data Annotation via Context-Aware Change Detection on Smartwatches." ACM Transactions on Embedded Computing Systems 20, no. 2 (March 2021): 1–20. http://dx.doi.org/10.1145/3431503.
Full textNawrocki, Piotr, and Bartlomiej Sniezynski. "Adaptive Context-Aware Energy Optimization for Services on Mobile Devices with Use of Machine Learning." Wireless Personal Communications 115, no. 3 (August 13, 2020): 1839–67. http://dx.doi.org/10.1007/s11277-020-07657-9.
Full textKretsis, Aristotelis, Ippokratis Sartzetakis, Polyzois Soumplis, Katerina Mitropoulou, Panagiotis Kokkinos, Petros Nicopolitidis, Georgios Papadimitriou, and Emmanouel Varvarigos. "ARMONIA: A Unified Access and Metro Network Architecture." Applied Sciences 10, no. 23 (November 24, 2020): 8318. http://dx.doi.org/10.3390/app10238318.
Full textAlwakeel, Lyan, and Kevin Lano. "Functional and Technical Aspects of Self-management mHealth Apps: Systematic App Search and Literature Review." JMIR Human Factors 9, no. 2 (May 25, 2022): e29767. http://dx.doi.org/10.2196/29767.
Full textDissertations / Theses on the topic "Self-adaptation, Data-driven, Machine learning, Software architecture"
VAIDHYANATHAN, KARTHIK. "Data-Driven Self-Adaptive Architecting Using Machine Learning." Doctoral thesis, Gran Sasso Science Institute, 2021. http://hdl.handle.net/20.500.12571/15976.
Full textBook chapters on the topic "Self-adaptation, Data-driven, Machine learning, Software architecture"
Burdescu, Dumitru Dan, and Marian Cristian Mihaescu. "Improvement of Self-Assessment Effectiveness by Activity Monitoring and Analysis." In Monitoring and Assessment in Online Collaborative Environments, 198–217. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-786-7.ch011.
Full textConference papers on the topic "Self-adaptation, Data-driven, Machine learning, Software architecture"
Wu, Dazhong, Janis Terpenny, Li Zhang, Robert Gao, and Thomas Kurfess. "Fog-Enabled Architecture for Data-Driven Cyber-Manufacturing Systems." In ASME 2016 11th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/msec2016-8559.
Full textSong, Zhengyi, and Young Moon. "CyberManufacturing System: A Solution for Sustainable Manufacturing." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-86092.
Full textNagaraj, Guru, Prashanth Pillai, and Mandar Kulkarni. "Deep Similarity Learning for Well Test Model Identification." In SPE Middle East Oil & Gas Show and Conference. SPE, 2021. http://dx.doi.org/10.2118/204675-ms.
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