Kim Phuc Tran

Orcid: 0000-0002-6005-1497

According to our database1, Kim Phuc Tran authored at least 43 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Analyzing out-of-control signals of T<sup>2</sup> control chart for compositional data using artificial neural networks.
Expert Syst. Appl., March, 2024

2023
Incorporating principal component analysis into Hotelling T2 control chart for compositional data monitoring.
Comput. Ind. Eng., December, 2023

The Shewhart-type RZ control chart for monitoring the ratio of autocorrelated variables.
Int. J. Prod. Res., October, 2023

Monitoring autocorrelated compositional data vectors using an enhanced residuals Hotelling T2 control chart.
Comput. Ind. Eng., July, 2023

Optimal design and evaluation of adaptive EWMA monitoring schemes for Inverse Maxwell distribution.
Comput. Ind. Eng., July, 2023

Trans-Lighter: A light-weight federated learning-based architecture for Remaining Useful Lifetime prediction.
Comput. Ind., June, 2023

Analyzing abnormal pattern of hotelling T2 control chart for compositional data using artificial neural networks.
Comput. Ind. Eng., June, 2023

AnoFed: Adaptive anomaly detection for digital health using transformer-based federated learning and support vector data description.
Eng. Appl. Artif. Intell., May, 2023

Proof of Swarm Based Ensemble Learning for Federated Learning Applications.
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023

2022
Designing ECG monitoring healthcare system with federated transfer learning and explainable AI.
Knowl. Based Syst., 2022

Forecasting Sales Profiles of Products in an Exceptional Context: COVID-19 Pandemic.
Int. J. Comput. Intell. Syst., 2022

Detection of Poisoning Attacks with Anomaly Detection in Federated Learning for Healthcare Applications: A Machine Learning Approach.
CoRR, 2022

Explainable Anomaly Detection for Industrial Control System Cybersecurity.
CoRR, 2022

Light-weight federated learning-based anomaly detection for time-series data in industrial control systems.
Comput. Ind., 2022

The effects of measurement errors on estimating and assessing the multivariate process capability with imprecise characteristic.
Comput. Ind. Eng., 2022

Federated Learning-Based Explainable Anomaly Detection for Industrial Control Systems.
IEEE Access, 2022

2021
Artificial Intelligence for Smart Manufacturing: Methods and Applications.
Sensors, 2021

Design of a variable sampling interval exponentially weighted moving average median control chart in presence of measurement errors.
Qual. Reliab. Eng. Int., 2021

Forecasting and Anomaly Detection approaches using LSTM and LSTM Autoencoder techniques with the applications in supply chain management.
Int. J. Inf. Manag., 2021

The effect of measurement errors on the performance of the Exponentially Weighted Moving Average control charts for the Ratio of Two Normally Distributed Variables.
Eur. J. Oper. Res., 2021

Lightweight Transformer in Federated Setting for Human Activity Recognition.
CoRR, 2021

Detecting cyberattacks using anomaly detection in industrial control systems: A Federated Learning approach.
Comput. Ind., 2021

A deep reinforcement learning based multi-criteria decision support system for optimizing textile chemical process.
Comput. Ind., 2021

LocKedge: Low-Complexity Cyberattack Detection in IoT Edge Computing.
IEEE Access, 2021

Long Term Demand Forecasting System for Demand Driven Manufacturing.
Proceedings of the Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems, 2021

2020
Performance of the MEWMA-CoDa control chart in the presence of measurement errors.
Qual. Reliab. Eng. Int., 2020

CUSUM control charts with variable sampling interval for monitoring the ratio of two normal variables.
Qual. Reliab. Eng. Int., 2020

Effect of the measurement errors on two one-sided Shewhart control charts for monitoring the ratio of two normal variables.
Qual. Reliab. Eng. Int., 2020

A Deep Reinforcement Learning Based Multi-Criteria Decision Support System for Textile Manufacturing Process Optimization.
CoRR, 2020

Multi-Objective Optimization of the Textile Manufacturing Process Using Deep-Q-Network Based Multi-Agent Reinforcement Learning.
CoRR, 2020

A reinforcement learning based decision support system in textile manufacturing process.
CoRR, 2020

2019
A Synthetic median control chart for monitoring the process mean with measurement errors.
Qual. Reliab. Eng. Int., 2019

On the performance of coefficient of variation charts in the presence of measurement errors.
Qual. Reliab. Eng. Int., 2019

Monitoring the ratio of two normal variables using variable sampling interval exponentially weighted moving average control charts.
Qual. Reliab. Eng. Int., 2019

An EWMA control chart for the multivariate coefficient of variation.
Qual. Reliab. Eng. Int., 2019

A data-driven approach for Network Intrusion Detection and Monitoring based on Kernel Null Space.
EAI Endorsed Trans. Ind. Networks Intell. Syst., 2019

Wearable Sensor Data Based Human Activity Recognition using Machine Learning: A new approach.
CoRR, 2019

2018
Steady-state ARL analysis of ARL-unbiased EWMA-RZ control chart monitoring the ratio of two normal variables.
Qual. Reliab. Eng. Int., 2018

Monitoring compositional data using multivariate exponentially weighted moving average scheme.
Qual. Reliab. Eng. Int., 2018

One-Sided Synthetic Control Charts for Monitoring the Coefficient of Variation with Measurement Errors.
Proceedings of the 2018 IEEE International Conference on Industrial Engineering and Engineering Management, 2018

2017
On the Performance of Shewhart median Chart in the Presence of Measurement Errors.
Qual. Reliab. Eng. Int., 2017

Run Rules median control charts for monitoring process mean in manufacturing.
Qual. Reliab. Eng. Int., 2017

2016
Monitoring the Ratio of Two Normal Variables Using EWMA Type Control Charts.
Qual. Reliab. Eng. Int., 2016


  Loading...