Results 251 to 260 of about 25,829 (292)

Stop Using Limiting Stimuli as a Measure of Sensitivities of Energetic Materials

Propellants, Explosives, Pyrotechnics, EarlyView.
ABSTRACT Accurately estimating the sensitivity of explosive materials is a potentially life‐saving task that requires standardised protocols across nations. One of the most widely applied procedures worldwide is the so‐called ‘1‐In‐6’ test from the United Nations (UN) Manual of Tests in Criteria, which estimates a ‘limiting stimulus’ for a material. In
Dennis Christensen, Geir Petter Novik
wiley   +1 more source

Nonlinear Receding‐Horizon Differential Game for Drone Racing Along a Three‐Dimensional Path

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Drone racing requires high‐speed navigation through three‐dimensional paths, posing significant challenges in control engineering. Existing control methods lack a feedback control framework that simultaneously addresses nonlinear drone dynamics and multi‐agent competitive interactions, such as overtaking or obstructing opponents.
Kijin Sung, Kenta Hoshino, Akihiko Honda, Takeya Shima, Toshiyuki Ohtsuka   +4 more
wiley   +1 more source

Adaptive Multi-Model Hierarchical Federated Learning for Robust IoT Intrusion Detection. [PDF]

Sensors (Basel)
Latif S, Djenouri D.
europepmc   +1 more source

Deep Reinforcement Learning‐Based Control for Real‐Time Hybrid Simulation of Civil Structures

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Real‐time Hybrid Simulation (RTHS) is a cyber‐physical technique that studies the dynamic behavior of a system by combining physical and numerical components that are coupled through a boundary condition enforcer. In structural engineering, the numerical components are subjected to environmental loads that become dynamic displacements of the ...
Andrés Felipe Niño, Alejandro Palacio‐Betancur, Piedad Miranda‐Chiquito, Juan David Amaya, Christian E. Silva, Mariantonieta Gutierrez Soto, Luis Felipe Giraldo   +6 more
wiley   +1 more source

Secure yet fragile: adversarial vulnerabilities of federated vision-language models in medical AI. [PDF]

Sci Rep
Fime AA, Samiha TZ, Hossain MZ, Zaman S, Shibli AM, Shahid AR, Ni Z, Imteaj A.   +7 more
europepmc   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

Responsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen, Siwei Yang, Xiangqian Cui, Ziheng Liu, Hang Wang, Yongqiang Li, Peng He, Miao Wang, Guqiao Ding   +8 more
wiley   +1 more source

Generating imperceptible adversarial examples via low-frequency aware transfer attacks on battery management systems. [PDF]

Sci Rep
Min K, Joo Y, Hong J, Kim H, Lee S, Son Y.   +5 more
europepmc   +1 more source

Lacking data? No worries! How synthetic images can alleviate image scarcity in wildlife surveys: A case study with muskox (Ovibos moschatus)

Remote Sensing in Ecology and Conservation, EarlyView.
This study investigates the integration of synthetic imagery, created with diffusion‐based models, to supplement limited training data and improve muskox (Ovibos moschatus) detection in zero‐shot (ZS) and few‐shot (FS) settings. ZS models detected more than 80% of muskoxen in real images, confirming the potential of synthetic data as a substitute for ...
Simon Durand, Samuel Foucher, Alexandre Delplanque, Joëlle Taillon, Jérôme Théau   +4 more
wiley   +1 more source

When collaboration fails: persuasion driven adversarial influence in multi agent large language model debate. [PDF]

Sci Rep
Kraidia I, Qaddara I, Almutairi A, Alzaben N, Belhouari SB.   +4 more
europepmc   +1 more source

Deep learning‐based super‐resolution reconstruction and improved YOLOv9 for efficient benthos detection: a case study at Lake Hamana, Japan

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents a UAV‐based framework that integrates deep learning‐based super‐resolution reconstruction and an enhanced YOLO detector to improve centimetre‐scale benthic organism monitoring. Using hermit crabs in Lake Hamana, a coastal lagoon in Japan, as a case study, the method substantially enhanced small‐object detection performance ...
Fan Zhao, Bangzhang Ma, Dianhan Xi, Jiaqi Wang, Yijia Chen, Yongying Liu, Xinlei Shao, Mowen Zhang, Guocheng Zhang, Jundong Chen, Katsunori Mizuno   +10 more
wiley   +1 more source