AIMC Topic:
Computer Simulation
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Learning Mobile Manipulation through Deep Reinforcement Learning.
Sensors (Basel, Switzerland)
Feb 10, 2020
Mobile manipulation has a broad range of applications in robotics. However, it is usually more challenging than fixed-base manipulation due to the complex coordination of a mobile base and a manipulator. Although recent works have demonstrated that d...
In silico prediction of blood cholesterol levels from genotype data.
PloS one
Feb 10, 2020
In this work we present a framework for blood cholesterol levels prediction from genotype data. The predictor is based on an algorithm for cholesterol metabolism simulation available in literature, implemented and optimized by our group in the R lang...
Rolling Locomotion of Cable-Driven Soft Spherical Tensegrity Robots.
Soft robotics
Feb 7, 2020
Soft spherical tensegrity robots are novel steerable mobile robotic platforms that are compliant, lightweight, and robust. The geometry of these robots is suitable for rolling locomotion, and they achieve this motion by properly deforming their struc...
Exploring linearity of deep neural network trained QSM: QSMnet.
NeuroImage
Feb 7, 2020
Recently, deep neural network-powered quantitative susceptibility mapping (QSM), QSMnet, successfully performed ill-conditioned dipole inversion in QSM and generated high-quality susceptibility maps. In this paper, the network, which was trained by h...
Drug-target interaction prediction with tree-ensemble learning and output space reconstruction.
BMC bioinformatics
Feb 7, 2020
BACKGROUND: Computational prediction of drug-target interactions (DTI) is vital for drug discovery. The experimental identification of interactions between drugs and target proteins is very onerous. Modern technologies have mitigated the problem, lev...
Advantages of aquatic animals as models for bio-inspired drones over present AUV technology.
Bioinspiration & biomimetics
Feb 7, 2020
Robotic systems are becoming more ubiquitous, whether on land, in the air, or in water. In the aquatic realm, aquatic drones including ROVs (remotely operated vehicles) and AUVs (autonomous underwater vehicles) have opened new opportunities to invest...
Predicting 10-Year Risk of End-Organ Complications of Type 2 Diabetes With and Without Metabolic Surgery: A Machine Learning Approach.
Diabetes care
Feb 6, 2020
OBJECTIVE: To construct and internally validate prediction models to estimate the risk of long-term end-organ complications and mortality in patients with type 2 diabetes and obesity that can be used to inform treatment decisions for patients and pra...
RefDNN: a reference drug based neural network for more accurate prediction of anticancer drug resistance.
Scientific reports
Feb 5, 2020
Cancer is one of the most difficult diseases to treat owing to the drug resistance of tumour cells. Recent studies have revealed that drug responses are closely associated with genomic alterations in cancer cells. Numerous state-of-the-art machine le...
Deep learning for prediction of cardiac indices from photoplethysmographic waveform: A virtual database approach.
International journal for numerical methods in biomedical engineering
Feb 4, 2020
Deep learning methods combined with large datasets have recently shown significant progress in solving several medical tasks. However, collecting and annotating large datasets can be a very cumbersome and expensive task. We tackle these problems with...
A Comparison between Mouse, , and Robot Odor Plume Navigation Reveals Advantages of Mouse Odor Tracking.
eNeuro
Feb 4, 2020
Localization of odors is essential to animal survival, and thus animals are adept at odor navigation. In natural conditions animals encounter odor sources in which odor is carried by air flow varying in complexity. We sought to identify potential min...
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