Browsing ODA Open Digital Archive by Author "Zhang, Jianhua"
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Assessing cognitive mental workload via EEG signals and an ensemble deep learning classifier based on denoising autoencoders
Yang, Shuo; Yin, Zhong; Wang, Yagang; Zhang, Wei; Wang, Yongxiong; Zhang, Jianhua (Computers in Biology and Medicine;Volume 109, June 2019, Journal article; Peer reviewed, 2019-04-26)To estimate the reliability and cognitive states of operator performance in a human-machine collaborative environment, we propose a novel human mental workload (MW) recognizer based on deep learning principles and utilizing ... -
Automatic Analysis of Large-scale Nanopore Data Using Hidden Markov Models
Zhang, Jianhua; Liu, Xiuling (IFAC-PapersOnLine;Volume 53, Issue 2, 2020, Peer reviewed; Journal article, 2020-04-14)In this paper we developed a modified Hidden Markov Model (HMM) to analyze the raw nanopore experimental data. Traditionally, prior to further analysis the measured nanopore data must be pre-filtered, but the filtering ... -
Classifying Mental Workload Levels Using Semi-Supervised Learning Technique
Zhang, Jianhua; Li, Jianrong (IFAC-PapersOnLine;Volume 53, Issue 2, Peer reviewed; Journal article, 2021-04-14)Real-time monitoring and analysis of human operator’s mental workload (MWL) is crucial for development of adaptive/intelligent human-machine cooperative systems in various safety/mission-critical application fields. Although ... -
Cross-Subject emotion recognition from EEG using Convolutional Neural Networks
Zhong, Xiaolong; Yin, Zhong; Zhang, Jianhua (Chinese Control Conference (CCC);2020 39th Chinese Control Conference (CCC), Peer reviewed; Journal article, 2020-09-09)Using electroencephalogram (EEG) signals for emotion detection has aroused widespread research concern. However, across subjects emotional recognition has become an insurmountable gap which researchers cannot step across ... -
EEG-based affect classification with machine learning algorithms
Zhang, Jianhua; Yin, Zhong; Chen, Peng (Chapter, 2023)In this paper, we aim to study the EEG-based emotion recognition problem. First, we use clustering algorithm to determine the target class of emotions and perform binary classification of emotion along its arousal and ... -
An ELM-based Deep SDAE Ensemble for Inter-Subject Cognitive Workload Estimation with Physiological Signals
Zheng, Zhanpeng; Yin, Zhong; Zhang, Jianhua (Chinese Control Conference (CCC);2020 39th Chinese Control Conference (CCC), Conference object, 2020-09-09)Evaluating operator cognitive workload (CW) levels in human-machine systems based on neurophysiological signals is becoming the basis to prevent serious accidents due to abnormal state of human operators. This study proposes ... -
EMG Signals based Human Action Recognition via Deep Belief Networks
Zhang, Jianhua; Ling, Chen; Li, Sunan (IFAC-PapersOnLine;Volume 52, Issue 19, 2019, Journal article; Peer reviewed, 2019-12-24)Electromyography (EMG) signals can be used for action classification. Nonetheless, due to their nonlinear and time-varying properties, it is difficult to classify the EMG signals and it is critical to use appropriate ... -
Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review
Zhang, Jianhua; Yin, Zhong; Chen, Peng; Nichele, Stefano (Information Fusion;Volume 59, July 2020, Peer reviewed; Journal article, 2020-01-31)In recent years, the rapid advances in machine learning (ML) and information fusion has made it possible to endow machines/computers with the ability of emotion understanding, recognition, and analysis. Emotion recognition ... -
EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality
Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (Lecture Notes in Computer Science;Volume 12104, Conference object, 2020-04-09)Dynamical systems possess a computational capacity that may be exploited in a reservoir computing paradigm. This paper presents a general representation of dynamical systems which is based on matrix multiplication. That ... -
Hierarchical MPC of Hybrid Power Systems based on Fuzzy Discrete Abstraction
Zhang, Jianhua; Xia, Jiajun (IFAC-PapersOnLine;Volume 53, Issue 2, 2020, Peer reviewed; Journal article, 2020-04-14)A hierarchical control approach is proposed for hybrid systems with discrete-valued input based on fuzzy discrete abstraction and model predictive control (MPC) scheme. The system is firstly abstracted to a discrete event ... -
Household Energy Consumption Prediction: A Deep Neuroevolution Approach
Soudaei, Alexander; Zhang, Jianhua; Elmi, Mohamed Ahmed; Tsechoev, Mikael; Khan, Zishan; Osman, Ahmed Abbas (Chapter, 2023)Accurate energy consumption prediction can provide insights to make better informed decisions on energy purchase and generation. It also can prevent overloading and make it possible to store energy more efficiently. In ... -
Individual-Specific Classification of Mental Workload Levels Via an Ensemble Heterogeneous Extreme Learning Machine for EEG Modeling
Zhang, Jianhua; Tao, J.; Yin, Z.; Liu, L.; Tian, Y.; Sun, Z. (Symmetry;Volume 11, Issue 7, Journal article; Peer reviewed, 2019-07-16)In a human–machine cooperation system, assessing the mental workload (MW) of the human operator is quite crucial to maintaining safe operation conditions. Among various MW indicators, electroencephalography (EEG) signals ... -
Instantaneous mental workload assessment using time–frequency analysis and semi-supervised learning
Zhang, Jianhua; Li, Jianrong; Wang, Rubin (Cognitive Neurodynamics;volume 14, issue 5, Peer reviewed; Journal article, 2020-05-12)The real-time assessment of mental workload (MWL) is critical for development of intelligent human–machine cooper- ative systems in various safety–critical applications. Although data-driven machine learning (ML) approach ... -
Instantaneous Mental Workload Recognition Using Wavelet-Packet Decomposition and Semi-Supervised Learning
Zhang, Jianhua; Li, Jianrong; Nichele, Stefano (IEEE Symposium Series on Computational Intelligence (SSCI);2019 IEEE Symposium Series on Computational Intelligence (SSCI), Conference object, 2020-02-20)The real-time monitoring of human operator's mental workload (MWL) is crucial for development of adaptive/intelligent human-machine cooperative systems in various safety/mission-critical application fields. Although ... -
Manifold feature fusion with dynamical feature selection for cross-subject emotion recognition
Hua, Yue; Zhong, Xiaolong; Zhang, Bingxue; Yin, Zhong; Zhang, Jianhua (Brain Sciences;Volume 11 / Issue 11, Peer reviewed; Journal article, 2021-10-23)Affective computing systems can decode cortical activities to facilitate emotional human– computer interaction. However, personalities exist in neurophysiological responses among different users of the brain–computer ... -
A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality
Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (Cognitive Neurodynamics;, Journal article; Peer reviewed, 2020-06-11)Although deep learning has recently increased in popularity, it suffers from various problems including high computational complexity, energy greedy computation, and lack of scalability, to mention a few. In this paper, ... -
Operator Performance Prediction based on Fuzzy Modeling Approach
Zhang, Jianhua; Yin, Zhong (IFAC-PapersOnLine;Volume 53, Issue 2, 2020, Peer reviewed; Journal article, 2021-04-14)In this paper, physiological signals were measured from five participants, each participating in two sessions of experiment with identical experimental procedure. A simulation platform, AutoCAMS (Automation-enhanced Cabin ... -
Physiological-signal-based mental workload estimation via transfer dynamical autoencoders in a deep learning framework
Yin, Zhong; Zhao, Mengyuan; Zhang, Wei; Wang, Yongxiong; Wang, Yagang; Zhang, Jianhua (Neurocomputing;Volume 347, 28 June 2019, Journal article; Peer reviewed, 2019-02-19)Evaluating operator mental workload (MW) in human-machine systems via neurophysiological signals is crucial for preventing unpredicted operator performance degradation. However, the feature of physiological signals is ... -
Prediction and correlation analysis of ventilation performance in a residential building using artificial neural network models based on data-driven analysis
Kim, Moon Keun; Cremers, Bart; Liu, Jiying; Zhang, Jianhua; Wang, Junqi (Sustainable Cities and Society (SCS);Volume 83, August 2022, 103981, Peer reviewed; Journal article, 2022-06-14)This study investigates approaches to evaluate prediction and correlation how significantly mechanical and natural ventilation rate and local weather conditions affect the actual ventilation performance of a residential ... -
Recognition of cognitive load with a stacking network ensemble of denoising autoencoders and abstracted neurophysiological features
Cao, Zixuan; Yin, Zhong; Zhang, Jianhua (Peer reviewed; Journal article, 2020)