Chee Peng Lim
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View article: Trajectory tracking of a SCARA robot using intelligent active force control
Trajectory tracking of a SCARA robot using intelligent active force control Open
Trajectory tracking with disturbance rejection is a challenging problem in robotics, particularly in applications involving selective compliance articulated robot arms (SCARA). In this paper, we address the trajectory tracking problem with…
View article: Learning-Based Approximate Nonlinear Model Predictive Control Motion Cueing
Learning-Based Approximate Nonlinear Model Predictive Control Motion Cueing Open
Motion Cueing Algorithms (MCAs) encode the movement of simulated vehicles into movement that can be reproduced with a motion simulator to provide a realistic driving experience within the capabilities of the machine. This paper introduces …
View article: Current and future roles of artificial intelligence in retinopathy of prematurity
Current and future roles of artificial intelligence in retinopathy of prematurity Open
Retinopathy of prematurity (ROP) is a severe condition affecting premature infants, leading to abnormal retinal blood vessel growth, retinal detachment, and potential blindness. While semi-automated systems have been used in the past to di…
View article: Evaluating the impact of music tempo on drivers and their performance using an artificial intelligence model: a multi-source data approach
Evaluating the impact of music tempo on drivers and their performance using an artificial intelligence model: a multi-source data approach Open
Traffic accidents are a major global health and economic concern. As such, research into understanding driving behaviors becomes essential to minimize the associated risks. Among various factors that can influence driving behaviors, listen…
View article: A lightweight CNN model for UAV-based image classification
A lightweight CNN model for UAV-based image classification Open
For many unmanned aerial vehicle (UAV)-based applications, especially those that need to operate with resource-limited edge networked devices in real-time, it is crucial to have a lightweight computing model for data processing and analysi…
View article: Vision‐Language Hazard Reasoning for Driver Distraction and Workload Estimation
Vision‐Language Hazard Reasoning for Driver Distraction and Workload Estimation Open
Driver distraction and cognitive overload are major contributors to road accidents, especially in semi‐automated driving where humans must remain situationally aware. We propose an agentic reasoning approach for jointly detecting external …
View article: Object-Level Cross-View Geolocalization With Location Enhancement and Multihead Cross Attention
Object-Level Cross-View Geolocalization With Location Enhancement and Multihead Cross Attention Open
Cross-view geolocalization determines the location of a query image, captured by a drone or ground-based camera, by matching it to a georeferenced satellite image. While traditional approaches focus on image-level localization, many applic…
View article: Adaptive Contrast Enhancement With Lesion Focusing (ACELF)
Adaptive Contrast Enhancement With Lesion Focusing (ACELF) Open
This study introduces an innovative image processing algorithm, namely Adaptive Contrast Enhancement with Lesion Focusing (ACELF), which is aimed at enhancing the visualization of brain lesions images. Despite the advancements in medical i…
View article: Optimized Sliding Mode Frequency Controller for Power Systems Integrated Energy Storage System With Droop Control
Optimized Sliding Mode Frequency Controller for Power Systems Integrated Energy Storage System With Droop Control Open
This paper proposes an adaptive-based single-phase higher-order sliding mode controller (SMC) optimized by the honey badger algorithm (HBA). The developed control method is employed for load frequency control (LFC) in electrical power syst…
View article: Real-Time Digital Assistance for Exercise: Exercise Tracking System with MediaPipe Angle Directive Rules
Real-Time Digital Assistance for Exercise: Exercise Tracking System with MediaPipe Angle Directive Rules Open
This paper focuses on developing an exercise tracking system capable of recognizing simple exercises, such as push-ups, pull-ups, and sit-ups, with high accuracy, leveraging human pose estimation techniques to enhance prediction performanc…
View article: Short-Term Photovoltaic Power Forecasting Using PV Data and Sky Images in an Auto Cross Modal Correlation Attention Multimodal Framework
Short-Term Photovoltaic Power Forecasting Using PV Data and Sky Images in an Auto Cross Modal Correlation Attention Multimodal Framework Open
The accurate prediction of photovoltaic (PV) power generation is crucial for improving virtual power plant (VPP) efficiency and power system stability. However, short-term PV power forecasting remains highly challenging due to the signific…
View article: Functional near-infrared spectroscopy (fNIRS) and Eye tracking for Cognitive Load classification in a Driving Simulator Using Deep Learning
Functional near-infrared spectroscopy (fNIRS) and Eye tracking for Cognitive Load classification in a Driving Simulator Using Deep Learning Open
Motion simulators allow researchers to safely investigate the interaction of drivers with a vehicle. However, many studies that use driving simulator data to predict cognitive load only employ two levels of workload, leaving a gap in resea…
View article: Predicting cognitive load in immersive driving scenarios with a hybrid CNN-RNN model
Predicting cognitive load in immersive driving scenarios with a hybrid CNN-RNN model Open
One debatable issue in traffic safety research is that cognitive load from sec-ondary tasks reduces primary task performance, such as driving. Although physiological signals have been extensively used in driving-related research to assess …
View article: Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis
Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis Open
Functional near-infrared spectroscopy (fNIRS) is employed as a non-invasive method to monitor functional brain activation by capturing changes in the concentrations of oxygenated haemoglobin (HbO) and deoxygenated haemo-globin (HbR). Vario…
View article: Addressing the Inconsistency in Bayesian Deep Learning via Generalized Laplace Approximation
Addressing the Inconsistency in Bayesian Deep Learning via Generalized Laplace Approximation Open
In recent years, inconsistency in Bayesian deep learning has attracted significant attention. Tempered or generalized posterior distributions are frequently employed as direct and effective solutions. Nonetheless, the underlying mechanisms…
View article: Cervical cancer classification using sparse stacked autoencoder and fuzzy ARTMAP
Cervical cancer classification using sparse stacked autoencoder and fuzzy ARTMAP Open
Cervical cancer (CC) is affecting women predominantly, and early diagnosis could cure this cancer. This study aims to
\ndesign and develop an effective deep learning-based classification model to detect early CC stages using clinical data.…
View article: Anomaly Detection in the Automotive Stamping Process: An Unsupervised Machine Learning Approach
Anomaly Detection in the Automotive Stamping Process: An Unsupervised Machine Learning Approach Open
In metal forming, such as stamping of automotive parts, unsupervised machine learning models offer a transformative approach to real-time quality control, especially when labelled data are scarce. Leveraging clustering algorithms and autoe…
View article: An optimized microstrip antenna to generate intense localized heating at target sites for maximum effect
An optimized microstrip antenna to generate intense localized heating at target sites for maximum effect Open
Nowadays, the use of electromagnetic waves in medical applications has become common, and hyperthermia is one of the popular areas. Nonetheless, designing effective antennas for electromagnetic hyperthermia poses a key challenge. In design…
View article: Minimal operation region prediction for networked control robotic manipulators subject to time‐varying delays and disturbances
Minimal operation region prediction for networked control robotic manipulators subject to time‐varying delays and disturbances Open
Due to the disturbances and varying latency, a teleoperated robotic manipulator might not comply with the master control commands. Although prior studies on minimising the impact of network latency and disturbances on teleoperated robots w…