AIMC Topic: Workload

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Optimization of Edge Resources for Deep Learning Application with Batch and Model Management.

Sensors (Basel, Switzerland)
As deep learning technology paves its way, real-world applications that make use of it become popular these days. Edge computing architecture is one of the service architectures to realize the deep learning based service, which makes use of the resou...

Federated learning with workload-aware client scheduling in heterogeneous systems.

Neural networks : the official journal of the International Neural Network Society
Federated Learning (FL) is a novel distributed machine learning, which allows thousands of edge devices to train models locally without uploading data to the central server. Since devices in real federated settings are resource-constrained, FL encoun...

Development and evaluation of design guidelines for cognitive ergonomics in human-robot collaborative assembly systems.

Applied ergonomics
Industry 4.0 is the concept used to summarize the ongoing fourth industrial revolution, which is profoundly changing the manufacturing systems and business models all over the world. Collaborative robotics is one of the most promising technologies of...

Intraoperative workload during robotic radical prostatectomy: Comparison between multi-port da Vinci Xi and single port da Vinci SP robots.

Applied ergonomics
The goal of this study was to quantify and compare prospective self-reported intraoperative workload and teamwork during robot-assisted radical prostatectomy (RARP) for multi-port da Vinci Xi (MP) and single-port da Vinci SP (SP) robots. The self-rep...

A deep learning network based on multi-scale and attention for the diagnosis of chronic atrophic gastritis.

Zeitschrift fur Gastroenterologie
BACKGROUND AND STUDY AIM: Chronic atrophic gastritis plays an important role in the process of gastric cancer. Deep learning is gradually introduced in the medical field, and how to better apply a convolutional neural network (CNN) to the diagnosis o...

Facilitating the Work of Unmanned Aerial Vehicle Operators Using Artificial Intelligence: An Intelligent Filter for Command-and-Control Maps to Reduce Cognitive Workload.

Human factors
OBJECTIVE: Evaluating the ability of a Gibsonian-inspired artificial intelligence (AI) algorithm to reduce the cognitive workloads of military Unmanned Aerial Vehicle (UAV) operators.

Human Robot Collaboration for Enhancing Work Activities.

Human factors
OBJECTIVE: Trade-offs between productivity, physical workload (PWL), and mental workload (MWL) were studied when integrating collaborative robots (cobots) into existing manual work by optimizing the allocation of tasks.

A neurotechnological aid for semi-autonomous suction in robotic-assisted surgery.

Scientific reports
Adoption of robotic-assisted surgery has steadily increased as it improves the surgeon's dexterity and visualization. Despite these advantages, the success of a robotic procedure is highly dependent on the availability of a proficient surgical assist...

Cross-Task Cognitive Workload Recognition Based on EEG and Domain Adaptation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Cognitive workload recognition is pivotal to maintain the operator's health and prevent accidents in the human-robot interaction condition. So far, the focus of workload research is mostly restricted to a single task, yet cross-task cognitive workloa...