Results 61 to 70 of about 3,932,809 (294)

Channel Path Loss Prediction Using Satellite Images: A Deep Learning Approach

IEEE Transactions on Machine Learning in Communications and Networking
With the advancement of communication technology, there is a higher demand for high-precision and high-generalization channel path loss models as it is fundamental to communication systems.
Chenlong Wang, Bo Ai, Ruisi He, Mi Yang, Shun Zhou, Long Yu, Yuxin Zhang, Zhicheng Qiu, Zhangdui Zhong, Jianhua Fan   +9 more
doaj   +1 more source

Empirical Comparison of Propagation Models for Relay-Based Networks in Urban Environments

IEEE Access, 2022
We investigate propagation characteristics for wireless channels, applicable to Integrated Access and Backhaul (IAB) and relay-based networks with lamppost-height nodes at 5.5 GHz.
Virginia Silva, Rodolfo Feick, Luciano Ahumada, Reinaldo A. Valenzuela, Milan S. Derpich, Mauricio Rodriguez   +5 more
doaj   +1 more source

Raman‐based label‐free microscopic analysis of the pancreas in living zebrafish larvae

FEBS Open Bio, EarlyView.
Forward stimulated Raman scattering (F‐SRS) and epi coherent anti‐Stokes Raman scattering (E‐CARS) allow label‐free discrimination of distinct subcellular structures in the pancreas of living zebrafish larvae. Given the straightforward applicability, we anticipate broad implementation of Raman microscopy in other organs and across various biomedical ...
Noura Faraj, Eline M. F. de Lange, Klaas A. Sjollema, Ben N. G. Giepmans   +3 more
wiley   +1 more source

Widest Path in Networks with Gains/Losses

Axioms
In this paper, the generalized widest path problem (or generalized maximum capacity problem) is studied. This problem is denoted by the GWPP. The classical widest path problem is to find a path from a source (s) to a sink (t) with the highest capacity among all possible s-t paths. The GWPP takes into account the presence of loss/gain factors on arcs as
Javad Tayyebi, Mihai-Lucian Rîtan, Adrian Marius Deaconu   +2 more
openaire   +3 more sources

Directed evolution of enzymes at the crossroads of tradition and innovation

FEBS Open Bio, EarlyView.
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova, Andrej Mirossay, Erik Sedlak   +2 more
wiley   +1 more source

Progress report on the PATH Through Life Study [PDF]

, 2000
We finished interviewing people in their 20s in March this year, by which time we had interviewed 2404 people. Analysis of the 20-plus data is well under way. Our research team is currently preparing articles for scientific journals.
PATH Through Life Project
core  

Path loss.

, 2016
Path loss values as function of the distance between the implanted antenna and the external antenna and representation of the fitted model.
Antonietta Stango (3233310), Kamya Yekeh Yazdandoost (3233307), Francesco Negro (205592), Dario Farina (292195)   +3 more
core   +1 more source

A new flow chip in combination with multiphoton microscopy as a protocol for longitudinal 3D imaging of tissue calcification under shear stress

FEBS Open Bio, EarlyView.
Miniaturized flow chip platform enabling continuous perfusion and longitudinal multiphoton 3D imaging of vascular smooth muscle cell constructs under physiological flow. Brightfield imaging guides region selection, while CellTracker Green and mRuby‐labeled fetuin‐A visualize cells and mineral deposition, respectively. Magnesium supplementation markedly
Vytautas Kučikas, Aaron D. Morgan, Ignas Čiurlionis, Christian Böhm, Stefan Jockenhövel, Willi Jahnen‐Dechent, Marc A. M. J. van Zandvoort   +6 more
wiley   +1 more source

Lorawan-Based RSSI-Trilateration Model for Node Location: A Simulation Integrating Flora and Omnet++

Transport and Telecommunication
This work presents the employing of LoRaWAN (Long Range Wide Area Network) for location applications through a network simulation to determine a mobile node position. We rely on FLoRa (Framework for LoRa) and OMNeT++ (Objective Modular Network Testbed in
Yi Loor Jiawey D., Espinal Albert, Sanchez Padilla V.   +2 more
doaj   +1 more source

Optimal Stopping Theory-Based Online Node Selection in IoT Networks for Multi-Parameter Federated Learning

IEEE Transactions on Machine Learning in Communications and Networking
Federated Learning (FL) has attracted the interest of researchers since it hinders inefficient resource utilization by developing a global learning model based on local model parameters (LMP).
Seda Dogan-Tusha, Faissal El Bouanani, Marwa Qaraqe   +2 more
doaj   +1 more source