Abstract Background Hand injuries impose a heavy burden on manufacturing-intensive regions, yet the spatio-temporal patterns of regional risk and their macro-level correlates remain poorly understood. Most existing studies focus on individual-level risk factors and rely on single data sources, leading to “one-size-fits...
Ye Chen, xiaoqun Qin, Shouping Chen· BMC Public Health· 0 citations
To address the superposition of normal thermal disturbances and fault characteristics in building heating, ventilation, and air conditioning (HVAC) systems, as well as conflicts among different diagnostic evidence sources, a physics-constrained dynamic graph and multi-source evidence fusion method for fault alarm detec...
Jie Yu, Bo Hu, Guangjun Li· Scientific Reports· 0 citations
Study region This study evaluates flood prediction for three northern New Jersey watersheds. The municipalities, Englewood, Irvington, and Paterson, New Jersey, are susceptible to flooding, but vary in watershed size and extent of riverine influence. Study focus This study develops a spatio-temporal neural network that...
Ahmad Ibrahim, Firas Gerges, Viravid Na Nagara et al.· Journal of Hydrology: Region...· 0 citations
Out-of-distribution (OOD) generalization remains a key challenge for heterogeneous graph neural networks (HGNNs), which often exhibit substantial performance degradation under real-world distribution shifts. While Group Distributionally Robust Optimization (GroupDRO) has proven effective in promoting OOD generalization...
Yunfei Wang, Yanghui Fu, Shixuan Liu et al.· Information Processing & Man...· 0 citations
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Major Depressive Disorder (MDD) represents a major global health burden, characterized by high recurrence rates and an increased risk of suicide. Traditional clinical diagnoses rely primarily on subjective scales, which limits their objectivity in accurately distinguishing MDD subtypes.To address these challenges, this...
Yuchen Liang, Xuelin Gu, Jun Wang et al.· Computer Methods in Biomecha...· 0 citations
Abstract Accurate prediction of spatial concentration fields within biomaterials is important for mass-transfer analysis and computational modeling of transport processes. This study develops an interpretable data-driven framework for spatially resolved mass-transport prediction by coupling finite element mass-transfer...
Ammar Abdulghani Melaibari, Nidal H. Abu‐Hamdeh, Khalid H. Almitani et al.· Scientific Reports· 0 citations
Information propagation over graph-structured data depends critically on the quality of node representations learned by graph neural networks (GNNs). However, how different GNN architectures organize embedding spaces and how these representations influence downstream propagation behavior remain insufficiently under...
Cooperative localization (CL) is a key enabler for future cooperative intelligent transportation system applications. By sharing and fusing multisource information, it can provide high-accuracy localization for connected autonomous vehicles in GNSS-denied or limited environments. Practical CL scenarios often involve he...
Sheng-Sheng Xing, Hai-Gen Min, Xia Wu et al.· IEEE Internet of Things Jour...· 0 citations
Multi-UAV systems in Space-Air-Ground Integrated Networks (SAGINs) offer solutions for diverse applications, but realizing their full potential in search and rescue (SAR) is challenged by complex terrains, limited infrastructure, and dynamic interferences. These demanding environments reveal shortcomings in jointly opt...
Peng-Xin Zhao, Hong-Bing Cheng, Hang-Yu Zhang et al.· IEEE Transactions on Mobile...· 0 citations
Multi-vehicle collaborative perception (MvCP) is a promising paradigm to enhance the capability of autonomous driving (AD). However, meeting the low latency and high accuracy requirements in a distributed, dynamic, and heterogeneous vehicular network is challenging. In this paper, we formulate a distributed framework e...
Wen-Zhao Zhang, Shu-Jun Han, Xiao-Dong Xu et al.· IEEE Transactions on Mobile...· 0 citations
With the rapid advancement of mobile technology and ubiquitous computing, spatial crowdsourcing has emerged as a promising computing paradigm. The growing complexity of spatial tasks has increasingly driven the demand for coordination among interdependent tasks and the cooperative participation of mobile workers, which...
Lin-Shen Luan, Wei Chen, Ran Feng et al.· IEEE Transactions on Mobile...· 0 citations
Adversarial example detectors are often tied to the classifier backbone they were trained on, limiting reuse when the protected model is replaced or upgraded. Directly transferring such detectors across backbones is challenging because different networks generally produce incompatible internal representations. We propo...
Arash Vashagh, R. Razavi-Far· arXiv (Cornell University)· 0 citations
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
MIT News · Artificial Intelligence· news.mit.eduJul 15, 2026
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.
Microsoft Research Blog· microsoft.comJul 13, 2026
Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduJul 6, 2026
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
