Search results for "Throughput"
showing 3 items of 483 documents
Visual Contrast Modulates Operant Learning Responses in Larval Zebrafish.
2018
The larval zebrafish is a promising vertebrate model organism to study neural mechanisms underlying learning and memory due to its small brain and rich behavioral repertoire. Here, we report on a high-throughput operant conditioning system for zebrafish larvae, which can simultaneously train 12 fish to associate a visual conditioned pattern with electroshocks. We find that the learning responses can be enhanced by the visual contrast, not the spatial features of the conditioned patterns, highlighted by several behavioral metrics. By further characterizing the learning curves as well as memory extinction, we demonstrate that the percentage of learners and the memory length increase as the co…
Underwater Multirobot Cooperative Intervention MAC Protocol
2020
This work introduces a Medium Access Control (MAC) protocol designed to allow a group of underwater robots that share a wireless communication channel to effectively communicate with each other. The goal of the Underwater Multirobot Cooperative Intervention MAC (UMCI-MAC) protocol presented in this work is to minimize the end to end delay and the jitter. The access to the medium in UMCI-MAC follows a Time Division Multiple Access (TDMA) strategy which is arbitrated by a master, which also has the capability to prioritize the transmission of some nodes over the rest of the network. Two experiments have been carried out with a team of four Autonomous Underwater Vehicles (AUV) in order to comp…
Trajectory Design and Resource Allocation for Multi-UAV Networks : Deep Reinforcement Learning Approaches
2023
The future mobile communication system is expected to provide ubiquitous connectivity and unprecedented services over billions of devices. The unmanned aerial vehicle (UAV), which is prominent in its flexibility and low cost, emerges as a significant network entity to realize such ambitious targets. In this work, novel machine learning-based trajectory design and resource allocation schemes are presented for a multi-UAV communications system. In the considered system, the UAVs act as aerial Base Stations (BSs) and provide ubiquitous coverage. In particular, with the objective to maximize the system utility over all served users, a joint user association, power allocation and trajectory desi…