Yuefeng Li
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View article: Machine learning-based real-time crash risk forecasting for pedestrians
Machine learning-based real-time crash risk forecasting for pedestrians Open
Recent developments in artificial intelligence (AI) have made significant improvements in understanding and enhancing pedestrian safety—a vulnerable road user group that receives less attention than motorized road users do. Specifically, A…
View article: Automated contrastive optimization of class-based feature distribution for noncontinuous dataset
Automated contrastive optimization of class-based feature distribution for noncontinuous dataset Open
Discrete data and categorical data classification is an essential task across domains such as machine learning, data mining, decision-making, and statistical analysis, aimed at categorizing observations into distinct classes based on their…
View article: Machine Learning for Privacy Threat Classification: A Systematic Review
Machine Learning for Privacy Threat Classification: A Systematic Review Open
Privacy threat classification plays a vital role in protecting sensitive information in today’s digital landscape, especially across domains such as the Internet of Things (IoT), smart devices, and cloud-based services. As traditional rule…
View article: RETRACTED: Wee et al. Triaging Medical Referrals Based on Clinical Prioritisation Criteria Using Machine Learning Techniques. Int. J. Environ. Res. Public Health 2022, 19, 7384
RETRACTED: Wee et al. Triaging Medical Referrals Based on Clinical Prioritisation Criteria Using Machine Learning Techniques. Int. J. Environ. Res. Public Health 2022, 19, 7384 Open
The journal retracts and remove the article Triaging Medical Referrals Based on Clinical Prioritisation Criteria Using Machine Learning Techniques [...]
View article: Detection of TCP and MQTT-Based DoS/DDoS Attacks on MUD IoT Networks
Detection of TCP and MQTT-Based DoS/DDoS Attacks on MUD IoT Networks Open
Mitigating cyberattacks on IoT networks is critical and remains a significant challenge, as such attacks can cause severe damage to the network systems and services. Moreover, the large volume of devices in IoT networks presents another ch…
View article: A Comprehensive Survey on Spectral Clustering with Graph Structure Learning
A Comprehensive Survey on Spectral Clustering with Graph Structure Learning Open
Spectral clustering is a powerful technique for clustering high-dimensional data, utilizing graph-based representations to detect complex, non-linear structures and non-convex clusters. The construction of a similarity graph is essential f…
View article: Addressing sparse data challenges in recommendation systems: A systematic review of rating estimation using sparse rating data and profile enrichment techniques
Addressing sparse data challenges in recommendation systems: A systematic review of rating estimation using sparse rating data and profile enrichment techniques Open
E-commerce recommendation systems enhance the user experience by providing customized suggestions tailored to user preferences. They analyze user interactions, such as ratings, to identify user preferences and recommend relevant items acco…
View article: Overcoming Bert's Limitations in Uncertainty: A Novel Two-Stage Solution for Multi-Class Medical Text Classification
Overcoming Bert's Limitations in Uncertainty: A Novel Two-Stage Solution for Multi-Class Medical Text Classification Open
View article: Self-Organizing Granular Encoding for Discrete Data Clustering
Self-Organizing Granular Encoding for Discrete Data Clustering Open
View article: Energy Consumption Modeling for Wi-Fi HaLow Networks
Energy Consumption Modeling for Wi-Fi HaLow Networks Open
Wi-Fi HaLow (IEEE 802.11ah) has emerged as a promising solution which can support Internet of Things (IoT) applications where energy efficiency and extended coverage are important. A key feature of Wi-Fi HaLow is the Target Wake Time (TWT)…
View article: Attention-Enhanced Deep Learning for Accurate Musculoskeletal X-Ray Classification
Attention-Enhanced Deep Learning for Accurate Musculoskeletal X-Ray Classification Open
View article: Fine-Grained Feature Extraction in Key Sentence Selection for Explainable Sentiment Classification Using BERT and CNN
Fine-Grained Feature Extraction in Key Sentence Selection for Explainable Sentiment Classification Using BERT and CNN Open
Online product reviews provide valuable insights into customer sentiment toward products; however, they often contain multiple sentences with redundant and non-essential content, making it harder to extract critical information. Identifyin…
View article: Integrating machine learning and extreme value theory for estimating crash frequency-by-severity via AI-based video analytics
Integrating machine learning and extreme value theory for estimating crash frequency-by-severity via AI-based video analytics Open
Traffic conflict techniques rely heavily on the proper identification of conflict extremes, which directly affects the prediction performance of extreme value models. Two sampling techniques, namely, block maxima and peak over threshold, f…
View article: Adaptive Weighted Multi-kernel Learning for Blast-Induced Flyrock Distance Prediction
Adaptive Weighted Multi-kernel Learning for Blast-Induced Flyrock Distance Prediction Open
In the field of civil and mining engineering, blasting operations are widely and frequently used for rock excavation, However, some undesirable environmental problems induced by blasting operations cannot be ignored. Blast-induced flyrock …
View article: An Architecture of Enhanced Profiling Assurance for IoT Networks
An Architecture of Enhanced Profiling Assurance for IoT Networks Open
Attacks launched from IoT networks can cause significant damage to critical network systems and services. IoT networks may contain a large volume of devices. Protecting these devices from being abused to launch traffic amplification attack…
View article: Generalisable deep Learning framework to overcome catastrophic forgetting
Generalisable deep Learning framework to overcome catastrophic forgetting Open
Generalisation across multiple tasks is a major challenge in deep learning for medical imaging applications, as it can cause a catastrophic forgetting problem. One commonly adopted approach to address these challenges is to train the model…
View article: Nonnegative Matrix Factorization in Dimensionality Reduction: A Survey
Nonnegative Matrix Factorization in Dimensionality Reduction: A Survey Open
Dimensionality Reduction plays a pivotal role in improving feature learning accuracy and reducing training time by eliminating redundant features, noise, and irrelevant data. Nonnegative Matrix Factorization (NMF) has emerged as a popular …
View article: A stacked deep multi-kernel learning framework for blast induced flyrock prediction
A stacked deep multi-kernel learning framework for blast induced flyrock prediction Open
Blasting operations are widely and frequently used for rock excavation in Civil and Mining constructions. Flyrock is one of the most important issues induced by blasting operations in open pit mines, and therefore needs to be well predicte…
View article: Business chatbots with deep learning technologies: state-of-the-art, taxonomies, and future research directions
Business chatbots with deep learning technologies: state-of-the-art, taxonomies, and future research directions Open
With the support of advanced hardware and software technology, Artificial Intelligence (AI) techniques, especially the increasing number of deep learning algorithms, have spawned the popularization of online intelligent services and accele…
View article: Revisiting the hybrid approach of anomaly detection and extreme value theory for estimating pedestrian crashes using traffic conflicts obtained from artificial intelligence-based video analytics
Revisiting the hybrid approach of anomaly detection and extreme value theory for estimating pedestrian crashes using traffic conflicts obtained from artificial intelligence-based video analytics Open
Pedestrians represent a group of vulnerable road users who are at a higher risk of sustaining severe injuries than other road users. As such, proactively assessing pedestrian crash risks is of paramount importance. Recently, extreme value …
View article: Autoencoders and their applications in machine learning: a survey
Autoencoders and their applications in machine learning: a survey Open
Autoencoders have become a hot researched topic in unsupervised learning due to their ability to learn data features and act as a dimensionality reduction method. With rapid evolution of autoencoder methods, there has yet to be a complete …
View article: A phrase-based questionnaire–answering approach for automatic initial frailty assessment based on clinical notes
A phrase-based questionnaire–answering approach for automatic initial frailty assessment based on clinical notes Open
Frailty stands out as a particularly challenging multidimensional geriatric syndrome in the elderly population, often resulting in diminished quality of life and heightened mortality risk. Negative consequences encompass a heightened likel…
View article: A stacked multiple kernel support vector machine for blast induced flyrock prediction
A stacked multiple kernel support vector machine for blast induced flyrock prediction Open
As a widely used rock excavation method in Civil and Mining construction works, the blasting operations and its induced side effects are always investigated by the existing studies. The occurrence of flyrock is regarded as one of the most …
View article: A Semantics-enhanced Topic Modelling Technique: Semantic-LDA
A Semantics-enhanced Topic Modelling Technique: Semantic-LDA Open
Topic modelling is a beneficial technique used to discover latent topics in text collections. But to correctly understand the text content and generate a meaningful topic list, semantics are important. By ignoring semantics, that is, not a…
View article: Self-Organizing Granular Encoding for Discrete Data in Neural Network-Based Clustering
Self-Organizing Granular Encoding for Discrete Data in Neural Network-Based Clustering Open
View article: Multi-aspect attentive text representations for simple question answering over knowledge base
Multi-aspect attentive text representations for simple question answering over knowledge base Open
With the deepening of knowledge base research and application, question answering over knowledge base, also called KBQA, has recently received more and more attention from researchers. Most previous KBQA models focus on mapping the input q…
View article: DAC-HPP: deep attributed clustering with high-order proximity preserve
DAC-HPP: deep attributed clustering with high-order proximity preserve Open
Attributed graph clustering, the task of grouping nodes into communities using both graph structure and node attributes, is a fundamental problem in graph analysis. Recent approaches have utilized deep learning for node embedding followed …
View article: k-outlier removal based on contextual label information and cluster purity for continuous data classification
k-outlier removal based on contextual label information and cluster purity for continuous data classification Open
Outlier detection is extensively adopted in machine learning applications to identify rare but significant objects in a data distribution that deviate from the majority of objects. However, none of the existing outlier definitions use the …
View article: Real-time crash risk forecasting using Artificial-Intelligence based video analytics: A unified framework of generalised extreme value theory and autoregressive integrated moving average model
Real-time crash risk forecasting using Artificial-Intelligence based video analytics: A unified framework of generalised extreme value theory and autoregressive integrated moving average model Open
With the recent advancements in computer vision and artificial intelligence, traffic conflicts occurring at an intersection and associated traffic characteristics can be obtained at the granular level of a signal cycle in real-time. This c…
View article: Deep Transfer Learning with Enhanced Feature Fusion for Detection of Abnormalities in X-ray Images
Deep Transfer Learning with Enhanced Feature Fusion for Detection of Abnormalities in X-ray Images Open
Medical image classification poses significant challenges in real-world scenarios. One major obstacle is the scarcity of labelled training data, which hampers the performance of image-classification algorithms and generalisation. Gathering…