Delay-tolerant networks (DTNs), originally developed for interplanetary communication, have emerged as a key enabler for reliable data delivery in resource-constrained and intermittently connected Internet of Things (IoT) environments, including disaster-affected regions, infrastructure-limited rural deployments, and m...
Usama Shaker Hachim, Asma' Abu-Samah, Nor Fadzilah Abdullah et al.· IEEE Internet of Things Jour...· 0 citations
Due to the complex nonlinear coupling between circuit topology and environmental changes, precise maximum power point tracking under partial shading conditions remains a challenge. Existing data-driven methods typically view photovoltaic (PV) arrays as unstructured feature vectors or Euclidean grids, which fail to capt...
Temporal knowledge graph reasoning (TKGR) aims to predict future facts based on historical event facts. However, the traditional embedding-based methods lack interpretability and the rule-based methods are prone to falling into spurious correlation traps. Note that the recent large language model (LLM)-based methods ar...
Qin Liu, Yang-Yang Chen, Guang-Hui Wen· IEEE Internet of Things Jour...· 0 citations
Uncrewed aerial vehicle (UAV) networks integrated with blockchain technology have been increasingly adopted to enable secure and decentralized coordination in distributed aerial systems. Within blockchain systems, the consensus mechanism plays a critical role in guaranteeing the consistency of shared data. However, the...
Zixu Zhou, Xuefei Zhang, Yao Sun et al.· IEEE Internet of Things Jour...· 0 citations
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Energy-efficient neuromorphic hardware with ultralow power consumption is increasingly promising for edge–artificial intelligence (AI) applications. Most digital neuromorphic hardware is designed with asynchronous circuits as they naturally match the sparsity and event-driven features of neuromorphic computing. However...
Jian Zhang, Yuan Hua, Ji-Lin Zhang et al.· IEEE Transactions on Compute...· 1 citation
Mobile Energy Storage Systems (MESSs) are critical for improving distribution network resilience under extreme weather events. However, the mathematical model for MESS routing and scheduling is essentially a high-dimensional mixed-integer nonlinear stochastic optimization problem. To accurately and rapidly obtain the r...
Changxu Jiang, Pengwei Zhuang, Hao Xu et al.· IEEE Transactions on Sustain...· 3 citations
Introduction Applying artificial intelligence to functional magnetic resonance imaging (fMRI) has advanced the modelling of neural activity, but deep architectures such as graph neural networks (GNNs) require large samples, limiting their use in the small cohorts typical of task-based fMRI. Shallow neural networks (SNN...
José Diogo Marques dos Santos, Maria Beatriz Ramos, Luís Paulo Reis et al.· Frontiers in Behavioral Neur...· 0 citations
Operating environments, including road infrastructure, traffic flow, weather conditions, and mileage, directly influence driving behavior. Because driving behavior ultimately determines road traffic safety, it is critical to determine whether operating environments create conditions that may induce unsafe driving pract...
朱龙岳, Dalin Qian, Sixian Li et al.· Figshare· 0 citations
Graphs are widely used to describe objects and their interactions in physically-informed real-world networking scenario including transportation, networking and energy, etc. Graph neural network (GNN) is the latest deep learning (DL) model for processing graph-structured data, widely applied in various tasks, e.g., p...
Yu-Feng Wang, Xin-Ying-Jian-Gan-Zhi-De-Shen-Jing-Jia-Gou-Sou-Suo Wang, Jian-Hua Ma et al.· Artificial Intelligence Revi...· 0 citations
Virtual laboratory and graph neural surrogate for origami-inspired super-expandable scaffolds in distraction osteogenesis: co-rotational beam and pore-scale Stokes solvers, an STL-to-graph front end, a multi-task heteroscedastic Scaffold Graph Network, parametric baselines, and the optimisation, ablation and repetition...
Sagor Das, Md. Tamzid Islam, Sanzida Afrin et al.· Zenodo (CERN European Organi...· 0 citations
Artificial Intelligence (AI) is driving a significant transformation in microbiology and environmental metagenomics, shifting the field from a descriptive framework towards a predictive and systems-level understanding. The advent of metagenomics has enabled direct analysis of microbial communities from environmental sa...
Tanuj Khatnoria, Tejaswini Karale, Simranpreet Kaur Natt et al.· Archives of Current Research...· 0 citations
Aging is accompanied by gradual changes in brain structure and cognition, but these changes do not unfold in the same way for every individual. Some people maintain cognitive function into late life, whereas others experience decline in memory, executive function, processing speed, or other cognitive domains. This vari...
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.
