AIMC Topic: Research Design

Clear Filters Showing 221 to 230 of 682 articles

Graph-Based Bayesian Optimization for Large-Scale Objective-Based Experimental Design.

IEEE transactions on neural networks and learning systems
Design is an inseparable part of most scientific and engineering tasks, including real and simulation-based experimental design processes and parameter/hyperparameter tuning/optimization. Several model-based experimental design techniques have been d...

Research on Application of Ecological Sports Innovation in Efficient Development Based on DCN Deep Learning.

Computational intelligence and neuroscience
With the continuous improvement of social and economic level, the relationship between human and nature is deteriorating. The ecological concept has been attached importance, so the concept of ecological sports has been born. For physical education, ...

Rolling Bearing Fault Detection System and Experiment Based on Deep Learning.

Computational intelligence and neuroscience
The current situation of frequent small-scale accidents shows that the existing methods have not completely solved the problem of bearing failures, and new research methods need to be used to complete the study of bearing failures. To prevent the fai...

From real-world electronic health record data to real-world results using artificial intelligence.

Annals of the rheumatic diseases
With the worldwide digitalisation of medical records, electronic health records (EHRs) have become an increasingly important source of real-world data (RWD). RWD can complement traditional study designs because it captures almost the complete variety...

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

Scientific reports
The case assignment system is an essential system of case management and assignment within the procuratorate and is an important aspect of judicial fairness and efficiency. However, existing methods mostly use manual or random case assignment, which ...

Artificial intelligence (AI) for home support interventions in dementia: a scoping review protocol.

BMJ open
INTRODUCTION: Dementia has become one of the significant causes of disability and dependency among older people globally. The proportion of people with dementia who are cared for at home has soared. The rapid growth of technology and data has stimula...

Addi-Reg: A Better Generalization-Optimization Tradeoff Regularization Method for Convolutional Neural Networks.

IEEE transactions on cybernetics
In convolutional neural networks (CNNs), generating noise for the intermediate feature is a hot research topic in improving generalization. The existing methods usually regularize the CNNs by producing multiplicative noise (regularization weights), c...

PDC: Pearl Detection with a Counter Based on Deep Learning.

Sensors (Basel, Switzerland)
Pearl detection with a counter (PDC) in a noncontact and high-precision manner is a challenging task in the area of commercial production. Additionally, sea pearls are considered to be quite valuable, so the traditional manual counting methods are no...

Machine Learning Assisted Prediction of Power Conversion Efficiency of All-Small Molecule Organic Solar Cells: A Data Visualization and Statistical Analysis.

Molecules (Basel, Switzerland)
Organic solar cells are famous for their cheap solution processing. Their industrialization needs fast designing of efficient materials. For this purpose, testing of large number of materials is necessary. Machine learning is a better option due to c...

A SuperLearner Approach to Predict Run-In Selection in Clinical Trials.

Computational and mathematical methods in medicine
A critical early step in a clinical trial is defining the study sample that appropriately represents the target population from which the sample will be drawn. Envisaging a "run-in" process in study design may accomplish this task; however, the tradi...