Accelerated development of multi-component alloys in discrete design space using Bayesian multi-objective optimisation by Osman Mamun, Markus Bause, Bhuiyan Shameem Mahmood Ebna Hai

“…This approach is particularly advantageous for deployment in massively parallel high-throughput synthesis facilities and advanced computing architectures.…”
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Evaluation and comparison of methods for neuronal parameter optimization using the Neuroptimus software framework. by Máté Mohácsi, Márk Patrik Török, Sára Sáray, Luca Tar, Gábor Farkas, Szabolcs Káli

“…Neuroptimus also offers several features to support more advanced usage, including the ability to run most algorithms in parallel, which allows it to take advantage of high-performance computing architectures. We used the common interface provided by Neuroptimus to conduct a detailed comparison of more than twenty different algorithms (and implementations) on six distinct benchmarks that represent typical scenarios in neuronal parameter search. …”
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Similarity Learning and Generalization with Limited Data: A Reservoir Computing Approach by Sanjukta Krishnagopal, Yiannis Aloimonos, Michelle Girvan

“…We present two Reservoir Computing architectures, which loosely resemble neural dynamics, and show that a Reservoir Computer (RC) trained to identify relationships between image pairs drawn from a subset of training classes generalizes the learned relationships to substantially different classes unseen during training. …”
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AI augmented edge and fog computing for Internet of Health Things (IoHT) by Deepika Rajagopal, Pradeep Kumar Thimma Subramanian

“…This study aims to examine future and existing fog and edge computing architectures and methods that have been augmented with artificial intelligence (AI) for use in healthcare applications, as well as defining the demands and challenges of incorporating fog and edge computing technology in IoHT, thereby helping healthcare professionals and technicians identify the relevant technologies required based on their need for developing IoHT frameworks for remote healthcare. …”
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Enhancement of convolutional neural network for urban environment parking space classification by S. Rahman, M. Ramli, F. Arnia, R. Muharar, M. Ikhwan, S. Munzir

“…EfficientParkingNet's lightweight computing architecture can increase the speed of information on parking availability to users.CONCLUSION: EfficientParkingNet is more efficient in determining the availability of parking spaces compared to mAlexnet, but still cannot match Yolo+MobileNet. …”
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