The rapid advancement of Artificial Intelligence (AI) and edge computing has increased the demand for accurate and low-latency remote sensing image classification; however, conventional cloud-centric approaches face challenges related to processing latency, communication overhead, and efficient analysis of diverse land...
Yu-Li Song, Hong-Dong Zhang· Discover Internet of Things· 0 citations
Transform your manufacturing operations for the Industry 4.0 era with this essential guide, which delivers the practical AI and soft computing strategies you need to master complexity, optimize efficiency, and build resilient, smart production systems. The advancement of manufacturing technologies has consistently been...
A substantive technical treatment of Explainable AI for RIS scenarios is provided, detailing how SHAP value attribution, Grad-CAM saliency mapping over RIS element indices, and Transformer attention maps can be applied to interpret black-box DRL policies and CNN-based models used for continuous phase-shift and beamform...
The convergence of artificial intelligence (AI) and the Internet of Things (IoT) is increasing interest in how intelligence is distributed across cloud, edge, fog, and device layers. This study maps the 2020-2026 development of cloud-linked AI-IoT research using Scopus metadata. The reported Scopus query required AI or...
Osman Diriye Hussein, Adam Muhudin, Mohamed Abdirahman Addow et al.· Zenodo (CERN European Organi...· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
Abstract§23.27 §6.4 found that, restricted to one defect per arm, grouping the holonomy angle by (transportclass, δ, (k1+k2) mod 5) gives a pure lookup for vertex-figure class T: 24 keys (6 per δ), each mapping to a single angle. §23.31 §6 tested the same grouping, using the same transport-class test, on classes M and...
Daniel Andrés Chillemi· Zenodo (CERN European Organi...· 0 citations
Infrared and visible image fusion combines complementary thermal and structural information from the two modalities into a single composite image. Existing methods have two critical limitations: (1) inadequate utilization of visible structural information causes blurred edges, and (2) modality-specific and shared respo...
Shun-Li Liu, An-Jie Chen, Qiao Luo et al.· Italian National Conference...· 0 citations
Can local physical learning destroy the conducting structure needed to define its own task? We study the Euclidean projected conductance-gradient flow of a finite passive resistor network with two fixed-potential terminals, one output, and one interior scalar target, under an explicit prune-and-continue convention for...
Oleg Dolgikh· Zenodo (CERN European Organi...· 0 citations
Digital twins (DTs) optimise resource allocation and intelligent network management but face severe synchronisation lag and intense spectral bottlenecks in ultra-dense 6G networks. Transitioning from passive, data-heavy digital mirrors to cognitive, semantic-empowered digital twins (SE-DTs) is essential to overcome con...
Ekolama Solomon Malcolm, Onu Kingsley Eyiogwu· Zenodo (CERN European Organi...· 0 citations
Background. Vision Transformers (ViTs) lead many visual-recognition benchmarks, but their memory and compute demands exceed the budgets of Artificial Intelligence of Things (AIoT) devices by orders of magnitude. Work claiming to close that gap reports latency, energy and memory on incomparable hardware and under unstat...
Hung Ho-Dac, Tru Huynh, Len Van Vo· Zenodo (CERN European Organi...· 0 citations
Executing deep learning models on sub-watt edge devices is severely constrained by memory bandwidth limits and control-path overheads. This research presents a custom hardware-software co-design using an open-source 32-bit RISC-V architecture optimized with specialized packed low-precision (INT8/INT4) vector extensions...
JEFF SHERWIN TIZON· Zenodo (CERN European Organi...· 0 citations
This parametric study investigates the structural behaviour of rigid pavement slabs resting on treated and untreated
expansive subgrades. The research analyses the response of the pavement system when subjected to critical wheel loading
applied at both the edge and interior zones of the slab. The parametric variations...
C. Satyasri, G. S. V. Prasad Raju· International Journal for Re...· 0 citations
Smart manufacturing improves flexibility in conventional mass production processes by leveraging cutting-edge computing technologies. This approach maintains efficiency and cost-effectiveness while enabling the on-demand production of highly customized products. The testing and development of novel materials that facil...
Sandip Kunar, T. Jagadeesha, Anusha Mylavarapu et al.· Soft Computing in Advanced M...· 0 citations
For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
MIT News · Artificial Intelligence· news.mit.eduOct 15, 2026
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
