AIMC Topic: User-Computer Interface

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Finger Gesture Spotting from Long Sequences Based on Multi-Stream Recurrent Neural Networks.

Sensors (Basel, Switzerland)
Gesture spotting is an essential task for recognizing finger gestures used to control in-car touchless interfaces. Automated methods to achieve this task require to detect video segments where gestures are observed, to discard natural behaviors of us...

Haptic Teleoperation of UAVs Through Control Barrier Functions.

IEEE transactions on haptics
This article presents a novel approach to haptic teleoperation. Specifically, we use control barrier functions (CBFs) to generate force feedback to help human operators safely fly quadrotor UAVs. CBFs take a control signal as input and output a contr...

DeepECA: an end-to-end learning framework for protein contact prediction from a multiple sequence alignment.

BMC bioinformatics
BACKGROUND: Recently developed methods of protein contact prediction, a crucially important step for protein structure prediction, depend heavily on deep neural networks (DNNs) and multiple sequence alignments (MSAs) of target proteins. Protein seque...

Towards Mixed-Initiative Human-Robot Interaction: Assessment of Discriminative Physiological and Behavioral Features for Performance Prediction.

Sensors (Basel, Switzerland)
The design of human-robot interactions is a key challenge to optimize operational performance. A promising approach is to consider mixed-initiative interactions in which the tasks and authority of each human and artificial agents are dynamically defi...

Automated tracheal intubation in an airway manikin using a robotic endoscope: a proof of concept study.

Anaesthesia
Robotic endoscope-automated via laryngeal imaging for tracheal intubation (REALITI) has been developed to enable automated tracheal intubation. This proof-of-concept study using a convenience sample of participants, comprised of trained anaesthetists...

Predicting drug-target interactions from drug structure and protein sequence using novel convolutional neural networks.

BMC bioinformatics
BACKGROUND: Accurate identification of potential interactions between drugs and protein targets is a critical step to accelerate drug discovery. Despite many relative experimental researches have been done in the past decades, detecting drug-target i...

ROBOKOP KG and KGB: Integrated Knowledge Graphs from Federated Sources.

Journal of chemical information and modeling
A proliferation of data sources has led to the notional existence of an implicit Knowledge Graph (KG) that contains vast amounts of biological knowledge contributed by distributed Application Programming Interfaces (APIs). However, challenges arise w...

A novel one-class classification approach to accurately predict disease-gene association in acute myeloid leukemia cancer.

PloS one
Disease causing gene identification is considered as an important step towards drug design and drug discovery. In disease gene identification and classification, the main aim is to identify disease genes while identifying non-disease genes are of les...

Machine Learning Models Based on Molecular Fingerprints and an Extreme Gradient Boosting Method Lead to the Discovery of JAK2 Inhibitors.

Journal of chemical information and modeling
Developing Janus kinase 2 (JAK2) inhibitors has become a significant focus for small-molecule drug discovery programs in recent years because the inhibition of JAK2 may be an effective approach for the treatment of myeloproliferative neoplasm. Here, ...

Development of New Methods Needs Proper Evaluation-Benchmarking Sets for Machine Learning Experiments for Class A GPCRs.

Journal of chemical information and modeling
New computational approaches for virtual screening applications are constantly being developed. However, before a particular tool is used to search for new active compounds, its effectiveness in the type of task must be examined. In this study, we co...