Hua‐Liang Wei
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View article: Eosinophilic Liver Abscess Mimicking Intrahepatic Cholangiocarcinoma on 18F-FDG PET-CT: A Case Report
Eosinophilic Liver Abscess Mimicking Intrahepatic Cholangiocarcinoma on 18F-FDG PET-CT: A Case Report Open
Background and Clinical Significance: Eosinophilic liver abscess (ELA) is a rare benign condition that can mimic malignant liver tumors on imaging studies. The diagnostic challenge is further compounded when 18F-FDG PET-CT demonstrates hig…
View article: A Novel Interpretable Lightweight Ensemble Learning Method for Static and Dynamic Medical and Healthcare Data Classification
A Novel Interpretable Lightweight Ensemble Learning Method for Static and Dynamic Medical and Healthcare Data Classification Open
In the medical field, efficient and accurate classification of sequential and structured data is crucially important and useful for early diagnosis and treatment. Traditional machine learning models struggle with the complexity and nonline…
View article: Anatomical landmark-guided laparoscopy for migrant fishbone - induced pancreatic abscesses: a case series study and review of the literature
Anatomical landmark-guided laparoscopy for migrant fishbone - induced pancreatic abscesses: a case series study and review of the literature Open
Introduction Pancreatic abscesses resulting from gastrointestinal fishbone migration represent rare yet clinically challenging surgical emergencies, with standardized management protocols remaining undefined. Methods We analyzed three cons…
View article: Climate proofing maize through optimizing manure fertilization
Climate proofing maize through optimizing manure fertilization Open
View article: Exact solution of the relationship between the eigenvalue discreteness and the behavior of eigenstates in Su-Schrieffer-Heeger lattices
Exact solution of the relationship between the eigenvalue discreteness and the behavior of eigenstates in Su-Schrieffer-Heeger lattices Open
Eigenstate localization and bulk-boundary correspondence are fundamental phenomena in one-dimensional (1D) Su-Schrieffer-Heeger (SSH) lattices. The eigenvalues discreteness and the eigenstates localization exhibit a high degree of consiste…
View article: EEG Signal Processing Techniques and Applications—2nd Edition
EEG Signal Processing Techniques and Applications—2nd Edition Open
Electroencephalography (EEG), as a well-established, non-invasive tool, has been successfully applied to a wide range of conditions due to its many evident advantages, such as economy, portability, easy operation, easy accessibility, and w…
View article: Unifying Mixed Boolean-Arithmetic Obfuscation by Architectural and Anti-Generalization Hardening
Unifying Mixed Boolean-Arithmetic Obfuscation by Architectural and Anti-Generalization Hardening Open
View article: An intelligent state evaluation and maintenance arrangement system for wind turbines based on digital twin
An intelligent state evaluation and maintenance arrangement system for wind turbines based on digital twin Open
Wind power is an important green and sustainable source of power generation. However, the construction of wind farms does not only need a large amount of initial investment but also highly expensive maintenance cost for their operations du…
View article: PRG: Prompt-Based Distillation Without Annotation via Proxy Relational Graph
PRG: Prompt-Based Distillation Without Annotation via Proxy Relational Graph Open
In this paper, we propose a new distillation method for extracting knowledge from Large Foundation Models (LFM) into lightweight models, introducing a novel supervision mode that does not require manually annotated data. While LFMs exhibit…
View article: Predicting the Atlantic Meridional Overturning Circulation Using Nonlinear System Identification Methods and the NARMAX Model
Predicting the Atlantic Meridional Overturning Circulation Using Nonlinear System Identification Methods and the NARMAX Model Open
The Atlantic Meridional Overturning Circulation (AMOC) plays an important role in the coupled ocean-climate system and in global climate change. The analysis of its own behaviour and the understanding its links to other climate dynamics is…
View article: North Atlantic atmospheric circulation indices: Links with summer and winter temperature and precipitation in north‐west Europe, including persistence and variability
North Atlantic atmospheric circulation indices: Links with summer and winter temperature and precipitation in north‐west Europe, including persistence and variability Open
Variability in seasonal weather in north‐west Europe is substantially determined by jet stream variability. The North Atlantic Oscillation (NAO) has been well studied as a key representation of this jet stream variability, but other circul…
View article: Probabilistic seasonal forecasts of North Atlantic atmospheric circulation using complex systems modelling and comparison with dynamical models
Probabilistic seasonal forecasts of North Atlantic atmospheric circulation using complex systems modelling and comparison with dynamical models Open
Dynamical seasonal forecast models are improving with time but tend to underestimate the amplitude of atmospheric circulation variability and to have lower skill in predicting summer variability than in winter. Here, we construct Nonlinear…
View article: Supervised Feature Selection based on the Law of Total Variance
Supervised Feature Selection based on the Law of Total Variance Open
Feature selection is a fundamental pre-processing step in machine learning that decreases data dimensionality by removing superfluous and irrelevant features. This study proposes a supervised feature selection method based on feature relev…
View article: Editorial: New theories, models, and AI methods of brain dynamics, brain decoding and neuromodulation
Editorial: New theories, models, and AI methods of brain dynamics, brain decoding and neuromodulation Open
The human brain is highly dynamic and complex, supporting a remarkable range of functions by dynamically integrating and coordinating different brain regions and networks across multiple spatial and temporal scales. Research on the human b…
View article: Multi-task learning using non-linear autoregressive models and recurrent neural networks for tide level forecasting
Multi-task learning using non-linear autoregressive models and recurrent neural networks for tide level forecasting Open
Tide level forecasting plays an important role in environmental management and development. Current tide level forecasting methods are usually implemented for solving single task problems, that is, a model built based on the tide level dat…
View article: Modelling Short-Term Appliance Energy Use with Interpretable Machine Learning: A System Identification Approach
Modelling Short-Term Appliance Energy Use with Interpretable Machine Learning: A System Identification Approach Open
The modelling and analysis of appliance energy use (AEU) of residential buildings are important for energy consumption control, energy management and maintenance, building performance evaluation, and so on. Although some traditional machin…
View article: Application of soft-DTW for Time Series Data Averaging Inside a Rotating Detonation Combustor
Application of soft-DTW for Time Series Data Averaging Inside a Rotating Detonation Combustor Open
Applications of high-speed diagnostics can help understand the structure and dynamics of detonation waves in RDCs. Phase averaging can be applied to resolve the circumferential detonation structure. However, a high level of stochasticity h…
View article: Complex systems modelling of UK winter wheat yield
Complex systems modelling of UK winter wheat yield Open
Wheat is one of the most important global crops, understanding the drivers of wheat yield has significant societal benefits. Climate variables are particularly important in determining interannual variations in wheat yield, either as prima…
View article: An Adaptive Interval Construction Based GRU Model for Short-Term Wind Speed Interval Prediction Using Two Phase Search Strategy
An Adaptive Interval Construction Based GRU Model for Short-Term Wind Speed Interval Prediction Using Two Phase Search Strategy Open
The application of wind power is greatly restricted due to the volatility and intermittency of wind. It is a challenging task to quantify the uncertainty of wind speed prediction. To tackle such a challenge, an adaptive interval constructi…
View article: An Integrated Observer Framework Based Mechanical Parameters Identification for Adaptive Control of Permanent Magnet Synchronous Motor
An Integrated Observer Framework Based Mechanical Parameters Identification for Adaptive Control of Permanent Magnet Synchronous Motor Open
An integrated observer framework based mechanical parameters identification approach for adaptive control of permanent magnet synchronous motors is proposed in this paper. Firstly, an integrated observer framework is established for mechan…
View article: An effective zero-shot learning approach for intelligent fault detection using 1D CNN
An effective zero-shot learning approach for intelligent fault detection using 1D CNN Open
Data-driven fault detection techniques have attracted extensive attention in engineering, industry and many other areas in recent years. In many real applications, the following situation often occurs: data for certain types of faults (uns…
View article: Recent Advances in AI-enabled Automated Medical Diagnosis
Recent Advances in AI-enabled Automated Medical Diagnosis Open
Emotion is an important part of people's daily life, particularly relevant to the mental health of people. Emotional diagnosis is closely related to the nervous system, which can well reflect people's mental conditions in response to the s…
View article: SimpleTrack: Rethinking and Improving the JDE Approach for Multi-Object Tracking
SimpleTrack: Rethinking and Improving the JDE Approach for Multi-Object Tracking Open
Joint detection and embedding (JDE) methods usually fuse the target motion information and appearance information as the data association matrix, which could fail when the target is briefly lost or blocked in multi-object tracking (MOT). I…
View article: SimpleTrack: Rethinking and Improving the JDE Approach for Multi-Object Tracking
SimpleTrack: Rethinking and Improving the JDE Approach for Multi-Object Tracking Open
Joint detection and embedding (JDE) based methods usually estimate bounding boxes and embedding features of objects with a single network in Multi-Object Tracking (MOT). In the tracking stage, JDE-based methods fuse the target motion infor…
View article: Switched PI Control Based MRAS for Sensorless Control of PMSM Drives Using Fuzzy-Logic-Controller
Switched PI Control Based MRAS for Sensorless Control of PMSM Drives Using Fuzzy-Logic-Controller Open
With the use of sensorless control strategy, mechanical position sensors can be removed from the gearbox, so as to decrease the maintenance costs and enhance the system robustness. In this paper, a switching PI control based model referenc…
View article: Hybrid Deep Learning Model for Short-Term Wind Speed Forecasting Based on Time Series Decomposition and Gated Recurrent Unit
Hybrid Deep Learning Model for Short-Term Wind Speed Forecasting Based on Time Series Decomposition and Gated Recurrent Unit Open
Accurate wind speed prediction has been becoming an indispensable technology in system security, wind energy utilization, and power grid dispatching in recent years. However, it is an arduous task to predict wind speed due to its variable …
View article: Modelling COVID-19 Pandemic Dynamics Using Transparent, Interpretable, Parsimonious and Simulatable (TIPS) Machine Learning Models: A Case Study from Systems Thinking and System Identification Perspectives
Modelling COVID-19 Pandemic Dynamics Using Transparent, Interpretable, Parsimonious and Simulatable (TIPS) Machine Learning Models: A Case Study from Systems Thinking and System Identification Perspectives Open
Since the outbreak of COVID-19, an astronomical number of publications on the pandemic dynamics appeared in the literature, of which many use the susceptible infected removed (SIR) and susceptible exposed infected removed (SEIR) models, or…
View article: A Modified Dynamic Time Warping (MDTW) Approach and Innovative Average Non-Self Match Distance (ANSD) Method for Anomaly Detection in ECG Recordings
A Modified Dynamic Time Warping (MDTW) Approach and Innovative Average Non-Self Match Distance (ANSD) Method for Anomaly Detection in ECG Recordings Open
ECGs objectively reflects the working conditions of the hearts as these signals contain vast physiological and pathological information. In this work, in order to improve the efficiency and accuracy of "best so far" time series analysis-ba…
View article: Quasi-Linear Transfer Function: A New Method for Frequency Domain Analysis of Nonlinear Systems
Quasi-Linear Transfer Function: A New Method for Frequency Domain Analysis of Nonlinear Systems Open
A new concept, called quasi-linear transfer functions (QLTF), which can be used to characterize the output frequency behaviour of nonlinear systems, is introduced based on the well-known Volterra series representation. By using the new con…
View article: Modelling COVID-19 Pandemic Dynamics Using Transparent, Interpretable, Parsimonious and Simulatable (TIPS) Machine Learning Models: A Case Study from Systems Thinking and System Identification Perspectives
Modelling COVID-19 Pandemic Dynamics Using Transparent, Interpretable, Parsimonious and Simulatable (TIPS) Machine Learning Models: A Case Study from Systems Thinking and System Identification Perspectives Open
Since the outbreak of COVID-19, an astronomical number of publications on the pandemic dynamics appeared in the literature, of which many use the susceptible infected removed (SIR) and susceptible exposed infected removed (SEIR) models, or…