9 papers · ranked by Valyu relevance
Hassam Ullah Sheikh, Ladislau Bölöni
—Many cooperative multi-agent problems require agents to learn individual tasks while contributing to the collective success of the group. This is a challenging task for current state-of-the-art multi-agent reinforcement algorithms that are designed to either maximize the global reward of the team or the individual…
Zhidong Zhu, Xiaoying Deng, Jian Dong, Cheng Feng + 2 more
'Antonio Lázaro'] Frequency agility refers to the rapid variation of the carrier frequency of adjacent pulses, which is an effective radar active antijamming method against frequency spot jamming. Variation patterns of traditional pseudo-random frequency hopping methods are susceptible to analysis and decryption…
Wei Qi, Hao Sun, Lichen Yu, Shuo Xiao + 5 more
When an unmanned aerial vehicle (UAV) performs tasks such as power patrol inspection, water quality detection, field scientific observation, etc., due to the limitations of the computing capacity and battery power, it cannot complete the tasks efficiently. Therefore, an effective method is to deploy edge servers near…
Tim Goppelsroeder, Rasmus Jensen
We propose MADDPG-K, a scalable extension to Multi-Agent Deep Deterministic Policy Gradient (MADDPG) that addresses the computational limitations of centralized critic approaches. Centralized critics, which condition on the observations and actions of all agents, have demonstrated significant performance gains in…
Swarup Subudhi, Ghansham Chandel, Vishal Sivasankar, Siddhartha Das
Magnetic nanoparticles (MNPs) have been extensively used for drug delivery, on-demand material deposition, etc. In this study, we demonstrate the capability to extract MNPs on-demand from a magnetic nanoparticle laden drop (MNLD) (i.e., a drop of stable aqueous dispersion of MNPs) suspended inside a highly viscous…
Murdhy A. Aldawsari, Saad Jamhan Aldosari, Atef Ismail, Marwa M. Emam
Breast cancer, a leading cause of mortality among women worldwide, necessitates early detection through mammography. Yet, automated classification remains challenging due to class imbalance, limited datasets, and the need for both local and global feature extraction. While convolutional neural networks (CNNs) excel in…
Di Xu, Qihui Lyu, Dan Ruan, Ke Sheng
Background and Purpose: Dual-energy computed tomography (DECT) utilizes separate X-ray energy spectra to improve multi-material decomposition (MMD) for various diagnostic applications. However accurate decomposing more than two types of material remains challenging using conventional methods. Deep learning (DL) methods…
Michael W. Rutherford, Tracy Nolan, Linmin Pei, Ulrike Wagner + 9 more
- 1 University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA - 2 Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA - 3 Ellumen, Inc., Silver Spring, MD, USA - 4 Deloitte Consulting LLP, New York, NY, USA - 5 National Cancer Institute, National Institute of Health (NIH)…
Authors not listed
The rise of antibiotic resistance has necessitated the exploration of unconventional sources for novel antimicrobial agents. One emerging novel frontier is "de-extinct" molecules – bioactive peptides, antibiotics, and other bioactive agents reconstructed from ancient or extinct organisms – a groundbreaking convergence…