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Model Asset eXchange

Alex Bozarth, Patrick Titzler, Xin Wu, Hong Xu, Frederick R. Reiss, Vijay Bommireddipalli, Brendan Dwyer, Fei Hu, Daniel Jalova, Karthik Muthuraman, Nick Pentreath, Simon Plovyt (+2 others)
2019 Proceedings of the 28th ACM International Conference on Information and Knowledge Management - CIKM '19  
To address this issue, we propose a system, called Model Asset Exchange (MAX), that avails developers of easy access to state-of-the-art DL models.  ...  A recent trend observed in traditionally challenging fields such as computer vision and natural language processing has been the significant performance gains shown by deep learning (DL).  ...  To address this issue, we propose a system, called Model Asset Exchange (MAX), that avails developers of easy access to state-ofthe-art DL models.  ... 
doi:10.1145/3357384.3357860 dblp:conf/cikm/BozarthDHJMPPQS19 fatcat:lt6wdaok2nfzhgrgw375774tne

Data Management in Industry 4.0: State of the Art and Open Challenges [article]

Theofanis P. Raptis, Andrea Passarella, Marco Conti
2019 arXiv   pre-print
in the physical deployments, up to the cloud and applications level.  ...  holistic survey of the recent literature from which we derive a taxonomy of the latest advances on industrial data enabling technologies and data centric services, spanning all the way from the field level deep  ...  However, it is a nontrivial task to train a deep learning model efficiently since the deep learning model often includes a great number of parameters.  ... 
arXiv:1902.06141v2 fatcat:4uvwquinx5h65dy4udx24bhrmm

Distributed Analytics Framework for Integrating Brownfield Systems to Establish Intelligent Manufacturing Architecture [chapter]

Vigneashwara Pandiyan, Wahyu Caesarendra
2020 Industry 4.0 - Current Status and Future Trends  
It is regarded as a new manufacturing model where the entire product life cycle can be simplified using various smart sensors, data-driven decision-making models, visualisation, intelligent devices, and  ...  In today's factories, most machines are brownfield systems and are not connected to any IoT platforms.  ...  The deep learning model is defined to identify four weld seam states. The VGG-16 network is retrained to identify the weld seam states.  ... 
doi:10.5772/intechopen.90472 fatcat:77vipfuqdvcbfetwzntkkofphe

6G Enabled Industrial Internet of Everything: Towards a Theoretical Framework

Prafulla Kumar Padhi, Feranando Charrua-Santos
2021 Applied System Innovation  
to ruminate significant findings.  ...  Judiciously, sequential methodology is best suited for this emerging discipline research to create significant new knowledge in the literature contributing eternal insights to expound valuable contexts  ...  Acknowledgments: The authors would like to greatly thank Fundação para a Ciência e Tecnologia (FCT) and C-MAST (Center for Mechanical and Aerospace Science and Technologies), under project UIDB/00151/2020  ... 
doi:10.3390/asi4010011 fatcat:jeiko2cywvglnecglwjrwwxgnu

mt5se: An Open Source Framework for Building Autonomous Traders [article]

Paulo André Lima de Castro
2021 arXiv   pre-print
These initiatives include traditional neural networks, fuzzy logic, reinforcement learning but also more recent approaches like deep neural networks and deep reinforcement learning.  ...  Many AI techniques have been tested for building autonomous agents able to trade financial assets.  ...  machine learning models, as discussed in sec- to trade financial assets.  ... 
arXiv:2101.08169v2 fatcat:t6mdo5kfynev3djqtfgmbqdv4m

Influence of Knowledge Sharing on Students' Learning Ability under the Background of "5G+AI"

Jie Zhao
2022 International Journal of Emerging Technologies in Learning (iJET)  
The willingness and behavior of knowledge sharing provide a huge space for students to improve their learning ability.  ...  The willingness to share knowledge has a positive role in promoting the improvement of students' learning ability.  ...  Test of KMO and Bartlett KMOP value 0.756 Approximate chi-square 851.158 Bartlett sphericity test Df 120 P value 0 Table 4 . 4 Summary of the regression coefficient of model X → Y Non-standardized path  ... 
doi:10.3991/ijet.v17i01.28533 doaj:2a365ad922964c85af6d3cd2fcbc7d1e fatcat:5mv6zmizuzbvncr4epxjg6l5pu

AI-Aided Integrated Terrestrial and Non-Terrestrial 6G Solutions for Sustainable Maritime Networking [article]

Salwa Saafi, Olga Vikhrova, Gábor Fodor, Jiri Hosek, Sergey Andreev
2022 arXiv   pre-print
To cope with the increased complexity of managing these integrated systems, this article advocates the use of artificial intelligence and machine learning-based approaches to meet the service requirements  ...  Due to recent advancements in integrating high-capacity and ultra-reliable terrestrial and non-terrestrial networking technologies, ubiquitous maritime connectivity is becoming a reality.  ...  Learning Delay and Network Reaction Time In distributed learning under model or data split architecture, the involved nodes need to periodically communicate ML model parameters over the network.  ... 
arXiv:2201.06947v2 fatcat:u7owlfpmz5f43jlbkvh2ztfvti

Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges

Hazim Shakhatreh, Ahmad H. Sawalmeh, Ala Al-Fuqaha, Zuochao Dou, Eyad Almaita, Issa Khalil, Noor Shamsiah Othman, Abdallah Khreishah, Mohsen Guizani
2019 IEEE Access  
Civil infrastructure is expected to dominate the more that 45 Billion market value of UAV usage. In this survey, we present UAV civil applications and their challenges.  ...  Smart UAVs are the next big revolution in UAV technology promising to provide new opportunities in different applications, especially in civil infrastructure in terms of reduced risks and lower cost.  ...  Zhang et al. in [305] use deep reinforcement learning to determine the fastest path to a charging station.  ... 
doi:10.1109/access.2019.2909530 fatcat:xgknpyuqazhpvferjkkdohxmtu

Seven Defining Features of Terahertz (THz) Wireless Systems: A Fellowship of Communication and Sensing [article]

Christina Chaccour, Mehdi Naderi Soorki, Walid Saad, Mehdi Bennis, Petar Popovski, Merouane Debbah
2021 arXiv   pre-print
These seven defining features allow us to shed light on how to re-engineer wireless systems as we know them today so as to make them ready to support THz bands.  ...  Effectively, these channel limitations lead to unreliable intermittent links as a result of a short communication range, and a high susceptibility to blockage and molecular absorption.  ...  The work in [53] proposed a generative adversarial network (GAN) approach that pre-trains a deep-reinforcement learning (RL) RIS-enhanced architecture • Increased LoS probability. • Improved multi-path  ... 
arXiv:2102.07668v2 fatcat:lg3dphy2zvhlhhwrpo7omwwp4i

Fast Connectivity Construction via Deep Channel Learning Cognition in Beyond 5G D2D Networks

Sang-Hoon Lee, Sangwon Seo, Soochang Park, Tae-Sung Kim
2022 Electronics  
To handle the problems, a fast connectivity construction scheme, denoted by LMK, is proposed with a deep neural network dealing with learning on radio signal information in order to achieve the LLC.  ...  , also known as device-to-device (D2D).  ...  IoT is leading to the substantial deployment of ubiquitous computing with many applications built around various types of sensors and actuators.  ... 
doi:10.3390/electronics11101580 fatcat:j2nqa3e425ditdg7smh5cchbye

Blockchain for AI: Review and Open Research Challenges

Khaled Salah, M. Habib Ur Rehman, Nishara Nizamuddin, Ala Al-Fuqaha
2019 IEEE Access  
INDEX TERMS Artificial intelligence, machine learning, blockchain, cybersecurity, smart contracts, consensus protocols.  ...  Blockchain technology has the ability to automate payment in cryptocurrency and to provide access to a shared ledger of data, transactions, and logs in a decentralized, secure, and trusted manner.  ...  , learning, and model deployment.  ... 
doi:10.1109/access.2018.2890507 fatcat:ikgb5ov7kzecdgehdyychbqz3e

Minerva: User-centered science operations software capability for future human exploration

Matthew Deans, Jessica J. Marquez, Tamar Cohen, Matthew J. Miller, Ivonne Deliz, Steven Hillenius, Jeffrey Hoffman, Yeon Jin Lee, David Lees, Johannes Norheim, Darlene S. S. Lim
2017 2017 IEEE Aerospace Conference  
In June of 2016, the Biologic Analog Science Associated with Lava Terrains (BASALT) research project conducted its first field deployment, which we call BASALT-1.  ...  Scientists and mission operators were provided a suite of ground software tools that we refer to collectively as Minerva to carry out their work.  ...  Surface science and exploration with humans and robotic assets are ubiquitous elements of each of these mission scenarios.  ... 
doi:10.1109/aero.2017.7943609 fatcat:zl6qmjj3mzgq7bdeiuqkss75ny

A Survey on Metaverse: Fundamentals, Security, and Privacy [article]

Yuntao Wang, Zhou Su, Ning Zhang, Dongxiao Liu, Rui Xing, Tom H. Luan, Xuemin Shen
2022 arXiv   pre-print
However, severe privacy invasions and security breaches (inherited from underlying technologies or emerged in the new digital ecology) of metaverse can impede its wide deployment.  ...  Metaverse, as an evolving paradigm of the next-generation Internet, aims to build a fully immersive, hyper spatiotemporal, and self-sustaining virtual shared space for humans to play, work, and socialize  ...  Inspired by biological neural networks, deep learning (DL) has gained exciting advances in practice and becomes the hottest paradigm in the AI realm. 6) Blockchain: To be persistent, the metaverse should  ... 
arXiv:2203.02662v2 fatcat:k5ba4o3lbbarljwgrrqftamlue

D2.1 5G Security: Current Status and Future Trends

Grant Millar, Anastasios Kafchitsas, Orestis Mavrooulos, Anastasios Kourtis, George Xilouris, Maria Christopoulou, Stavros Kolometsos, Edgardo Montes De Oca, Huu Nghia Nguyen, Antonio Pastor, Sonia Fernandez, Diego Lopez (+18 others)
2020 Zenodo  
This deliverable aims to provide a basis for the identification of use cases and the development of 5G security enablers in INSPIRE-5Gplus.  ...  standardization effort in the domain of 5G security, the relevant 5G projects, and open source initiatives; and a description of future trends and technologies in 5G networks, their limitations, and gaps related to  ...  .  Ability of the RCA to grasp the network structure (model representation) ever evolving.  Devise the most relevant learning and diagnostic methods-approaches with a special focus on Deep learning   ... 
doi:10.5281/zenodo.3947893 fatcat:bg7jnn5ph5fv3gjp7pqacy3us4

AI-Inspired Non-Terrestrial Networks for IIoT: Review on Enabling Technologies and Applications

Emmanouel T. Michailidis, Stelios M. Potirakis, Athanasios G. Kanatas
2020 IoT  
In this regard, this paper sheds light on the potential role of artificial intelligence (AI) techniques, including machine learning (ML) and deep learning (DL), in the provision of challenging NTN-based  ...  support ultra-reliable and low-latency communications (URLLC) and offer ubiquitous and uninterrupted interconnectivity.  ...  Evolutionary ML techniques are deep learning (DL) [97] and deep RL (DRL) [98] , which use multi-layered ANNs to deliver high accuracy and aim to teach a system how to autonomously learn through direct  ... 
doi:10.3390/iot1010003 fatcat:xkjxfh6r2fd27jyuxazfc6lbqu
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