Y H Dong, Zhuo Liu, Ruiqi Liang, Jinze He, X R Xue, Xiaokai Li, Sheng Liu, Yuanmu Yang
Charis E Shiny, S Annapurna, C Lakshana, Anusha Fakirappa Bogur, S Ramesh, G R Naik
Abstract: 5G is rolled out and next generation 6G networks are also being developed, ultra-low latency (URLL) communication as a standard is critical in supporting the plethora of applications, spanning autonomous vehicles, immersive extended reality experience, etc. However, tra…
Research article: Shadow Banking Detection with Graph Neural Networks: Mapping Unofficial Lending Networks
Neural networks are extraordinarily effective and almost entirely opaque: their competence is real but unreadable, and adapting them means retraining usually via a data-center process, not something that happens in the moment, in context. Symbolic systems are the inverse, legible…
Gilbert Ugwuanyi, Akpado Kenneth Aghaegbunam
Nigeria's oil and gas pipeline network spanning over 5,000 km of trunk lines and more than 3,000 km of flow lines loses an estimated one billion US dollars annually to pipeline failures, environmental incidents, and non-productive time. The dominant monitoring approach in operati…
Deep Neural Networks (DNNs) exhibit acute vulnerabilities to intermediate activation layer perturbations engineered through out-of-distribution (OOD) noise injection and feature-steering gradient updates. Conventional defensive paradigms—such as adversarial retraining or external…
Current quantum portfolio optimization pipelines rely on Random Matrix Theory (RMT) forcorrelation matrix cleaning, a static linear method that cannot adapt when market regimesshift. Meanwhile, D-Wave's own operational audit shows the quantum processor runs for just0.68% of total…