Staffing & Scheduling

A unified parameter model based on machine learning for describing microbial transport in porous media.

The transport and retention of microorganisms are typically described using attachment/detachment and straining/liberation models. However, the parameters in the models varied significantly, posing a significant challenge to describe microbial transport under different environmental conditions. A neural network (ANN) model was developed in this study to link the parameters in the model with the fa...

Adjustable Parameters and the Effectiveness of Adjunct Robot-Assisted Gait Training in Individuals with Chronic Stroke.

The aims of this study were (1) to compare the effect of robot-assisted gait orthosis (RAGO) plus conventional physiotherapy with the effect of conventional therapy alone on functional outcomes, including balance, walking ability, muscle strength, daily activity, and cognition, in chronic stroke patients, and (2) to determine the association of adjustable parameters of RAGO on functional outcomes....

Design of Travel Route Identification and Scheduling System Based on Artificial Intelligence-Aided Image Segmentation.

This study designs a travel recognition and scheduling system using artificial intelligence and image segmentation techniques. To address the problem ...

A Resilient and Effective Task Scheduling Approach for Industrial Human-Robot Collaboration.

Effective task scheduling in human-robot collaboration (HRC) scenarios is one of the great challenges of collaborative robotics. The shared workspace ...

Deep Learning-Based Optimization Algorithm for Enterprise Personnel Identity Authentication.

Enterprise strategic management is not only an important part of enterprise work, but also an important factor to deepen the reform of management syst...

Construction of a Landscape Design and Greenery Maintenance Scheduling System Based on Multimodal Intelligent Computing and Deep Neural Networks.

Digitalization brings challenges and new opportunities to the development of landscape gardening, "smart gardening," which is a product of landscape g...

A Prediction Model of Human Resources Recruitment Demand Based on Convolutional Collaborative BP Neural Network.

This paper presents an in-depth study and analysis of the prediction model of force resource recruitment demand using a convolutional neural network c...

Approximation in shift-invariant spaces with deep ReLU neural networks.

We study the expressive power of deep ReLU neural networks for approximating functions in dilated shift-invariant spaces, which are widely used in sig...

Neuromorphic computing chip with spatiotemporal elasticity for multi-intelligent-tasking robots.

Recent advances in artificial intelligence have enhanced the abilities of mobile robots in dealing with complex and dynamic scenarios. However, to ena...

Contemporary Value Assessment of Marxist Ideology under the Context of Deep Learning.

As a conceptual superstructure, ideology plays a very important role in national security, social stability, and healthy economic development. As a re...

Structure of cytoplasmic ring of nuclear pore complex by integrative cryo-EM and AlphaFold.

INTRODUCTION The nuclear pore complex (NPC) is the molecular conduit in the nuclear membrane of eukaryotic cells that regulates import and export of b...

A Novel Interannual Rainfall Runoff Equation Derived from Ol'Dekop's Model Using Artificial Neural Networks.

In water resources management, modeling water balance factors is necessary to control dams, agriculture, irrigation, and also to provide water supply ...

Deep Learning-Based Method for Compound Identification in NMR Spectra of Mixtures.

Nuclear magnetic resonance (NMR) spectroscopy is highly unbiased and reproducible, which provides us a powerful tool to analyze mixtures consisting of...

Improving work detection by segmentation heuristics pre-training on factory operations video.

The measurement of work time for individual tasks by using video has made a significant contribution to a framework for productivity improvement such ...

The current status of robotic colorectal surgery training programmes.

Robotic-assisted colorectal surgery (RACS) is steadily increasing in popularity with an annual growth in the number of colorectal procedures undertake...

Accelerating multi-echo chemical shift encoded water-fat MRI using model-guided deep learning.

PURPOSE: To accelerate chemical shift encoded (CSE) water-fat imaging by applying a model-guided deep learning water-fat separation (MGDL-WF) framewor...

Characteristic Analysis and Route Optimization of Heterogeneous Neural Network in Logistics Allocation System.

Logistics distribution vehicle scheduling plays an important role in the supply chain. With the wide application of e-commerce technology and the incr...

Weighted Incremental-Decremental Support Vector Machines for concept drift with shifting window.

We study the problem of learning the data samples' distribution as it changes in time. This change, known as concept drift, complicates the task of tr...

Magnetic-Powered Janus Cell Robots Loaded with Oncolytic Adenovirus for Active and Targeted Virotherapy of Bladder Cancer.

A unique robotic medical platform is designed by utilizing cell robots as the active "Trojan horse" of oncolytic adenovirus (OA), capable of tumor-sel...

Design of a Fuzzy Logic Evaluation to Determine the Ergonomic Risk Level of Manual Material Handling Tasks.

In this work, we propose a fuzzy inference as a decision support system built in the MATLAB Fuzzy Logic Designer for evaluating manual material handli...