Results 121 to 130 of about 184,942 (303)

Space-shift sampling of graph signals

open access: yes, 2016
A novel scheme for sampling graph signals is proposed. Space-shift sampling can be understood as a hybrid scheme that combines selection sampling -- observing the signal values on a subset of nodes - and aggregation sampling - observing the signal values
Leus, G.J.T.   +5 more
core   +2 more sources

A Monte Carlo Tree Search with Reinforcement Learning and Graph Relational Attention Network for Dynamic Flexible Job Shop Scheduling Problem

open access: yesBig Data and Cognitive Computing
The dynamic flexible job shop scheduling problem (DFJSP) with machine faults, considering the recovery condition and variable processing time, is studied to determine the rescheduling scheme when machine faults occur in real time.
Yu Jia, Rui Yang, Qiuyu Zhang
doaj   +1 more source

Adaptor protein CIN85 potentiates the motility of osteosarcoma cells via the Akt/mTOR and MMP2‐COL3A1 axis

open access: yesMolecular Oncology, EarlyView.
CIN85 is highly expressed in osteosarcoma, particularly in metastatic lesions. Its overexpression increases cell migration and Matrigel invasion, while silencing CIN85 suppresses these behaviors. Transcriptome analysis shows that CIN85 regulates MMP2, COL3A1, and Akt/mTOR signaling. Targeting these pathways reverses CIN85‐induced motility, highlighting
Iryna Horak   +10 more
wiley   +1 more source

On social networks and collaborative recommendation [PDF]

open access: yes, 2009
Social network systems, like last.fm, play a significant role in Web 2.0, containing large amounts of multimedia-enriched data that are enhanced both by explicit user-provided annotations and implicit aggregated feedback describing the personal ...
Stathopoulos, Vassilios   +8 more
core   +1 more source

3D Object Detection Based on Graph Network Fusion Sampling Strategy

open access: yesJournal of Harbin University of Science and Technology
In the 3D target detection technology based on point cloud, there are problems like high cost of point cloud calculation and large gap between target scales, which lead to low target detection efficiency.
LI Wenju   +5 more
doaj   +1 more source

Longitudinal circulating tumor DNA profiling in patients with advanced endometrial cancer using an off‐the‐shelf targeted NGS panel

open access: yesMolecular Oncology, EarlyView.
Intratumour heterogeneity complicates precision management of advanced endometrial cancer. Circulating tumor DNA (ctDNA) offers a minimally invasive strategy to capture tumor evolution and therapeutic resistance. Here, we compare tumor‐agnostic NGS with tumor‐informed ddPCR, outlining their relative sensitivity, concordance, and clinical implications ...
Carlos Casas‐Arozamena   +15 more
wiley   +1 more source

Reconfigurable boson sampling [PDF]

open access: yes
openTheory • Introduction to Quantum Theory Introduction to quantum theory, Fock state, quadrature operator, and the related phase-space relations, including the Wigner function.
CAUZZO, ANDREA
core  

Dynamic Sensor Placement Based on Sampling Theory for Graph Signals

open access: yesIEEE Open Journal of Signal Processing
In this paper, we consider a sensor placement problem where sensors can move within a network over time. Sensor placement problem aims to select $K$ sensor positions from $N$ candidates where $K < N$. Most existing methods assume that sensor positions
Saki Nomura   +3 more
doaj   +1 more source

Interaction of HS1BP3 with cortactin modulates TKS5 localisation, cell secretion and cancer malignancy

open access: yesMolecular Oncology, EarlyView.
Here, we demonstrate that HS1BP3 interacts with Cortactin through a proline‐rich region (PRR3.1) and show that this interaction, and HS1BP3 itself, promote cancer cell proliferation and invasion. Inhibition of this interaction leads to build‐up of TKS5 in multivesicular endosomes and altered secretion of CD63 and CD9, providing an explanation for the ...
Arja Arnesen Løchen   +9 more
wiley   +1 more source

Graph Signal Sampling via Reinforcement Learning

open access: yes, 2019
We model the sampling and recovery of clustered graph signals as a reinforcement learning (RL) problem. The signal sampling is carried out by an agent which crawls over the graph and selects the most relevant graph nodes to sample.
Jung, A., Abramenko, O.
core   +1 more source

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