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Haojie Lian, Xinhao Li, Leilei Chen, Xin Wen, Mengxi Zhang, Jieyuan Zhang and Yilin Qu
Neural radiance fields and neural reflectance fields are novel deep learning methods for generating novel views of 3D scenes from 2D images. To extend the neural scene representation techniques to complex underwater environments, beyond neural reflectanc...
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Paul Lee, Gerasimos Theotokatos and Evangelos Boulougouris
Autonomous ships are expected to extensively rely on perception sensors for situation awareness and safety during challenging operations, such as reactive collision avoidance. However, sensor noise is inevitable and its impact on end-to-end decision-maki...
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Hua Huang, Zhenfeng Peng, Jinkun Hou, Xudong Zheng, Yuxi Ding and Han Wu
Disc buckle steel pipe brackets are widely used in building construction due to the advantages of its simple structure, large-bearing capacity, rapid assembling and disassembling, and strong versatility. In complex construction projects, the uncertaintie...
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Shuo Wang, Kailun Feng and Yaowu Wang
In construction planning, decision making has a great impact on final project performance. Hence, it is essential for project managers to assess the construction planning and make informed decisions. However, disproportionately large uncertainties occur ...
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Sani. I. Abba, Jamilu Usman, Ismail Abdulazeez, Dahiru U. Lawal, Nadeem Baig, A. G. Usman and Isam H. Aljundi
The need for reliable, state-of-the-art environmental investigations and pioneering approaches to address pressing ecological dilemmas and to nurture the sustainable development goals (SDGs) cannot be overstated. With the power to revolutionize desalinat...
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Xuan Di, Rongye Shi, Zhaobin Mo and Yongjie Fu
For its robust predictive power (compared to pure physics-based models) and sample-efficient training (compared to pure deep learning models), physics-informed deep learning (PIDL), a paradigm hybridizing physics-based models and deep neural networks (DN...
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Yinghui Wang, Wenjun Wang, Minglai Shao and Yueheng Sun
Network alignment (NA) offers a comprehensive way to build associations between different networks by identifying shared nodes. While the majority of current NA methods rely on the topological consistency assumption, which posits that shared nodes across...
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Shao-Ming Lee and Ja-Ling Wu
Recently, federated learning (FL) has gradually become an important research topic in machine learning and information theory. FL emphasizes that clients jointly engage in solving learning tasks. In addition to data security issues, fundamental challenge...
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Tarek Berghout, Mohamed-Djamel Mouss, Leïla-Hayet Mouss and Mohamed Benbouzid
Machine learning prognosis for condition monitoring of safety-critical systems, such as aircraft engines, continually faces challenges of data unavailability, complexity, and drift. Consequently, this paper overcomes these challenges by introducing adapt...
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Paul K. Davis
This paper discusses challenges for M&S if it is to be increasingly important to decision aiding and policy analysis. It suggests an approach that?from the outset of a policy analysis project?incorporates M&S of a varied resolution with the inten...
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