Care of terminally ill / Palliative care

Predicting intersection crash frequency using connected vehicle data: A framework for geographical random forest.

Accurate crash frequency prediction is critical for proactive safety management. The emerging connected vehicles technology provides us with a wealth of vehicular motion data, which enables a better connection between crash frequency and driving behaviors. However, appropriately dealing with the spatial dependence of crash frequency and multitudinous driving features has been a difficult but criti...

Iterative deep neural networks based on proximal gradient descent for image restoration.

The algorithm unfolding networks with explainability of algorithms and higher efficiency of Deep Neural Networks (DNN) have received considerable attention in solving ill-posed inverse problems. Under the algorithm unfolding network framework, we propose a novel end-to-end iterative deep neural network and its fast network for image restoration. The first one is designed making use of proximal gra...

Self-supervised machine learning for live cell imagery segmentation.

Segmenting single cells is a necessary process for extracting quantitative data from biological microscopy imagery. The past decade has seen the adven...

A review of critical challenges in MI-BCI: From conventional to deep learning methods.

Brain-computer interfaces (BCIs) have achieved significant success in controlling external devices through the Electroencephalogram (EEG) signal proce...

Patient-Specific Exercises with the Development of an End-Effector Type Upper Limb Rehabilitation Robot.

End-effector type upper limb rehabilitation robots (ULRRs) are connected to patients at one distal point, making them have simple structures and less ...

An improved path planning algorithm based on artificial potential field and primal-dual neural network for surgical robot.

Safety and accuracy are essential for path planning in a surgical navigation system. In this paper, an improved path planning algorithm is proposed to...

A robot-assisted acoustofluidic end effector.

Liquid manipulation is the foundation of most laboratory processes. For macroscale liquid handling, both do-it-yourself and commercial robotic systems...

Digital Twin for a Multifunctional Technology of Flexible Assembly on a Mechatronics Line with Integrated Robotic Systems and Mobile Visual Sensor-Challenges towards Industry 5.0.

A digital twin for a multifunctional technology for flexible manufacturing on an assembly, disassembly, and repair mechatronics line (A/D/RML), assist...

Current Applications of Robot-Assisted Ultrasound Examination.

Despite advances in miniaturization and automation, the need for expert acquisition of a full echocardiogram, including Doppler, has restricted access...

A wearable soft robot that can alleviate the pain and fear of the wearer.

Social soft robotics may provide a new solution for alleviating human pain and fear. Here, we introduce a hand-held soft robot that can be clenched by...

sEMG-Based Gain-Tuned Compliance Control for the Lower Limb Rehabilitation Robot during Passive Training.

The lower limb rehabilitation robot is a typical man-machine coupling system. Aiming at the problems of insufficient physiological information and uns...

A Force-Feedback Methodology for Teleoperated Suturing Task in Robotic-Assisted Minimally Invasive Surgery.

With robotic-assisted minimally invasive surgery (RAMIS), patients and surgeons benefit from a reduced incision size and dexterous instruments. Howeve...

Using Artificial Neural Networks to Model Errors in Biochemical Manipulation of DNA Molecules.

In recent years, the non-biological applications of DNA molecules have made considerable progress; most of these applications were performed in vitro,...

Class-Imbalanced Deep Learning via a Class-Balanced Ensemble.

Class imbalance is a prevalent phenomenon in various real-world applications and it presents significant challenges to model learning, including deep ...

GPCA: A Probabilistic Framework for Gaussian Process Embedded Channel Attention.

Channel attention mechanisms have been commonly applied in many visual tasks for effective performance improvement. It is able to reinforce the inform...

De-identifying Australian hospital discharge summaries: An end-to-end framework using ensemble of deep learning models.

Electronic Medical Records (EMRs) contain clinical narrative text that is of great potential value to medical researchers. However, this information i...

Sam's Net: A Self-Augmented Multistage Deep-Learning Network for End-to-End Reconstruction of Limited Angle CT.

Limited angle reconstruction is a typical ill-posed problem in computed tomography (CT). Given incomplete projection data, images reconstructed by con...

A Novel Velocity-Based Control in a Sensor Space for Parallel Manipulators.

It is a challenging task to track objects moving along an unknown trajectory. Conventional model-based controllers require detailed knowledge of a rob...

Self-supervised graph neural network with pre-training generative learning for recommendation systems.

The case assignment system is an essential system of case management and assignment within the procuratorate and is an important aspect of judicial fa...

Towards End-to-End Text Spotting in Natural Scenes.

Text spotting in natural scene images is of great importance for many image understanding tasks. It includes two sub-tasks: text detection and recogni...