29 citations · 51 across the 16 of their papers we have counts for
17 papers
BREAD: Baseline-Referenced Explanations for Anomaly Diagnosis
Jiaqi Qiu, Rob Goedhart, Jannis Kurtz +1
Artificial Intelligence (AI)-based prospective anomaly detection methods are increasingly deployed in high-dimensional and nonlinear settings. Among these approaches, AI-based stat…
Reliable Decision Support with LLMs: A Framework for Evaluating Consistency in Binary Text Classification Applications
Fadel M. Megahed, Ying-Ju Chen, L. Allision Jones-Farmer +3
This study introduces a framework for evaluating consistency in large language model (LLM) binary text classification, addressing the lack of established reliability assessment met…
Adapting OpenAI's CLIP Model for Few-Shot Image Inspection in Manufacturing Quality Control: An Expository Case Study with Multiple Application Examples
Fadel M. Megahed, Ying-Ju Chen, Bianca Maria Colosimo +5
This expository paper introduces a simplified approach to image-based quality inspection in manufacturing using OpenAI's CLIP (Contrastive Language-Image Pretraining) model adapted…
Non-Progressive Influence Maximization in Dynamic Social Networks
Yunming Hui, Shihan Wang, Melisachew Wudage Chekol +2
The influence maximization (IM) problem involves identifying a set of key individuals in a social network who can maximize the spread of influence through their network connections…
Domain-Informed Negative Sampling Strategies for Dynamic Graph Embedding in Meme Stock-Related Social Networks
Yunming Hui, Inez Maria Zwetsloot, Simon Trimborn +1
Social network platforms like Reddit are increasingly impacting real-world economics. Meme stocks are a recent phenomena where price movements are driven by retail investors organi…
Social Network Datasets on Reddit Financial Discussion
Zezhong Wang, Siyang Hao, Inez Maria Zwetsloot +1
Stock markets are impacted by a large variety of factors including news and discussions among investors about investment opportunities. With the emergence of social media, new oppo…
An Algorithm for Modelling Escalator Fixed Loss Energy for PHM and sustainable energy usage
Xuwen Hu, Jiaqi Qiu, Yu Lin +5
Prognostic Health Management (PHM) is designed to assess and monitor the health status of systems, anticipate the onset of potential failure, and prevent unplanned downtime. In rec…
An LSTM-Based Predictive Monitoring Method for Data with Time-varying Variability
Jiaqi Qiu, Yu Lin, Inez Zwetsloot
The recurrent neural network and its variants have shown great success in processing sequences in recent years. However, this deep neural network has not aroused much attention in…
Introducing ChatSQC: Enhancing Statistical Quality Control with Augmented AI
Fadel M. Megahed, Ying-Ju Chen, Inez Zwetsloot +3
We introduce ChatSQC, an innovative chatbot system that combines the power of OpenAI's Large Language Models (LLM) with a specific knowledge base in Statistical Quality Control (SQ…
Remaining Useful Life Modelling with an Escalator Health Condition Analytic System
Inez M. Zwetsloot, Yu Lin, Jiaqi Qiu +5
The refurbishment of an escalator is usually linked with its design life as recommended by the manufacturer. However, the actual useful life of an escalator should be determined by…
A Real Time Monitoring Approach for Bivariate Event Data
Inez Maria Zwetsloot, Tahir Mahmood, Funmilola Mary Taiwo +1
Early detection of changes in the frequency of events is an important task, in, for example, disease surveillance, monitoring of high-quality processes, reliability monitoring and…
A Change-Point Based Control Chart for Detecting Sparse Changes in High-Dimensional Heteroscedastic Data
Zezhong Wang, Inez Maria Zwetsloot
Because of the curse-of-dimensionality, high-dimensional processes present challenges to traditional multivariate statistical process monitoring (SPM) techniques. In addition, the…
A Review of Dispersion Control Charts for Multivariate Individual Observations
Jimoh Olawale Ajadi, Zezhong Wang, Inez Maria Zwetsloot
A multivariate control chart is designed to monitor process parameters of multiple correlated quality characteristics. Often data on multivariate processes are collected as individ…
Multivariate Time-Between-Events Monitoring -- An overview and some (overlooked) underlying complexities
Inez Maria Zwetsloot, Tahir Mahmood, William H. Woodall
We review methods for monitoring multivariate time-between-events (TBE) data. We present some underlying complexities that have been overlooked in the literature. It is helpful to…
Should Observations be Grouped for Effective Monitoring of Multivariate Process Variability?
Jimoh Olawale Ajadi, Inez Maria Zwetsloot
A multivariate dispersion control chart monitors changes in the process variability of multiple correlated quality characteristics. In this article, we investigate and compare the…
Monitoring dynamic networks: a simulation-based strategy for comparing monitoring methods and a comparative study
Lisha Yu, Inez M. Zwetsloot, Nathaniel T. Stevens +2
Recently there has been a lot of interest in monitoring and identifying changes in dynamic networks, which has led to the development of a variety of monitoring methods. Unfortunat…
Monitoring data quality for telehealth systems in the presence of missing data
Tahir Mahmood, Philipp Wittenberg, Inez Maria Zwetsloot +2
Background: All-in-one station-based health monitoring devices are implemented in elder homes in Hong Kong to support the monitoring of vital signs of the elderly. During a pilot s…