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Authors: Che, Gaofeng | Yu, Zhen

Article Type: Research Article

Abstract: In this work, the output-feedback fault-tolerant tacking control issue for underactuated autonomous underwater vehicle (AUV) with actuators faults is investigated. Firstly, an output-feedback error tacking system is constructed based on the theoretical model of underactuated AUV with actuators faults. Then, an adaptive dynamic programming (ADP) based fault-tolerant control controller is developed. In our proposed control scheme, a neural-network observer is designed to approximate the system states with actuators faults. An online policy iteration algorithm is designed with critic network and action network in order to improve the tracking accuracy. Based on Lyapunov stability theorem, the stability of the error tracking …system is guaranteed by the proposed controller. At last, the simulation results show that the underactuated AUV achieves better tracking performance. Show more

Keywords: Adaptive dynamic programming (ADP), fault-tolerant tracking control, actuators faults, neural network observer, autonomous underwater vehicle (AUV)

DOI: 10.3233/JIFS-223976

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 5871-5883, 2023

Authors: Che, Gaofeng | Yu, Zhen

Article Type: Research Article

Abstract: This work investigates trajectory-tacking control problem for underactuated autonomous underwater vehicles (AUV) with unknown dynamics. Due to the unknown dynamics, an action-critic networks based adaptive dynamic programming (ADP) scheme combined with backstepping approach is designed, which can achieve high-level system stability and tracking control accuracy. Firstly, the backstepping approach is introduced into the kinematic model of underactuated AUV and produces a virtual velocity control which is taken as the desired velocity input of the dynamic model of underactuated AUV. Secondly, the error tracking system is constructed according to the dynamic model of underactuated AUV. Thirdly, the critic neural network and …the action neural network are employed to transform the trajectory-tracking control problem into optimal control problem based on policy iteration algorithm. At last simulation results are given to verify the effectiveness of the proposed control scheme. Show more

Keywords: Adaptive dynamic programming (ADP), backstepping approach, tracking control, autonomous underwater vehicle (AUV)

DOI: 10.3233/JIFS-230232

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2851-2863, 2024

Authors: Che, Gaofeng | Liu, Lijun | Yu, Zhen

Article Type: Research Article

Abstract: In this paper, an iterative adaptive dynamic programming algorithm is proposed to deal with the optimal trajectory-tracking control problems for autonomous underwater vehicle. Two iteration procedures are used in the method, which are the i -iteration and the j -iteration.The i -iteration aims to obtain iterative trajectory-tracking control laws and the j -iteration aims to obtain iterative value functions in the i -iteration. The optimal tracking control problem is converted into an optimal regulation problem by system transformation. Then the optimal regulation problem is solved by the policy iteration adaptive dynamic programming algorithm. The policy iteration algorithm is the interacting …policy and value iteration algorithms. The neural networks are used to realize the proposed algorithm and the convergence and optimality properties of the proposed algorithm are analysed. Finally, simulation example is given to show the performance of the iterative adaptive dynamic programming algorithm. Show more

Keywords: adaptive dynamic programming, autonomous underwater vehicle, discrete-time, neural network, trajectory-tracking control

DOI: 10.3233/JIFS-190294

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4205-4215, 2019

Authors: He, Xinzi | Yu, Zhen | Wang, Tianfu | Lei, Baiying | Shi, Yiyan

Article Type: Research Article

Abstract: BACKGROUND: Dermoscopy imaging has been a routine examination approach for skin lesion diagnosis. Accurate segmentation is the first step for automatic dermoscopy image assessment. OBJECTIVE: The main challenges for skin lesion segmentation are numerous variations in viewpoint and scale of skin lesion region. METHODS: To handle these challenges, we propose a novel skin lesion segmentation network via a very deep dense deconvolution network based on dermoscopic images. Specifically, the deep dense layer and generic multi-path Deep RefineNet are combined to improve the segmentation performance. The deep representation of all available layers is aggregated to form the global feature maps using …skip connection. Also, the dense deconvolution layer is leveraged to capture diverse appearance features via the contextual information. Finally, we apply the dense deconvolution layer to smooth segmentation maps and obtain final high-resolution output. RESULTS: Our proposed method shows the superiority over the state-of-the-art approaches based on the public available 2016 and 2017 skin lesion challenge dataset and achieves the accuracy of 96.0% and 93.9%, which obtained a 6.0% and 1.2% increase over the traditional method, respectively. CONCLUSIONS: By utilizing Dense Deconvolution Net, the average time for processing one testing images with our proposed framework was 0.253 s. Show more

Keywords: Dermoscopy image, skin lesion segmentation, deep residual network, dense deconvolution net, hierarchical supervision

DOI: 10.3233/THC-174633

Citation: Technology and Health Care, vol. 26, no. S1, pp. 307-316, 2018

Authors: He, Wei | Chu, Xiumin | Zhou, Yumeng | Jiang, Zhonglian | Yu, Zhen | Sotelo, Miguel Angel | Li, Zhixiong

Article Type: Research Article

Abstract: The Three Gorges ship lock, as one of the world leading navigational architectures, plays a significant role in the inland water transport of China. The rapid development of marine transportation increases great pressure on the maritime monitoring and administration in the ship locks. Hence, it is essential to explore the navigational risk factors. This study proposes a new dynamics model to investigate the evolution mechanism of navigational risk in Three Gorges ship lock. Intelligent expert system was used to analyze the risk factors. Experimental validation results demonstrate that the weather may impact the ship navigational safety with a high risk …probability. Meanwhile, the navigational risk in flood season is relatively higher than that in dry season due to the increase of flow velocity and rain fall. The present study may provide useful insights to the evolution of inland navigational risk as well as maritime administration in the Three Gorges ship lock. Show more

Keywords: Ship lock, intelligent expert system, data mining, field data, navigational risk

DOI: 10.3233/JIFS-179481

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 1197-1202, 2020

Authors: Zhang, Liang | Huang, Yi | Ling, Junjun | Zhuo, Wenlei | Yu, Zhen | Shao, Mengmeng | Luo, Yunbo | Zhu, Yi

Article Type: Research Article

Abstract: BACKGROUND: Liver carcinoma is a major cause of cancer-related death worldwide. Up to date, the mechanisms of liver cancerigenesis and development have not been fully understood. Multi-genes and pathways were involved in the tumorigenesis of liver cancer. OBJECTIVE: The aim of the present study was to screen key genes and pathways in liver cancerigenesis and development by using bioinformatics methods. METHODS: A dataset GSE64041 were retrieved from GEO database and the differentially expressed genes (DEGs) were screened out. Then the DEG functions were annotated by gene ontology (GO) and pathway enrichment analysis, respectively. The hub genes were further selected by …protein-protein interaction (PPI) analysis. Afterwards, the mRNA and protein expressions as well as the prognostic values of the hub genes were assessed. RESULTS: As a result, 208 up-regulated and 82 down-regulated genes were screened out. These DEGs were mainly enriched in cell cycle and metabolism-related pathways. Through PPI analysis, TOP2A, PRDM10, CDK1, AURKA, BUB1, PLK1, CDKN3, NCAPG, BUB1B and CCNA2 were selected as hub genes, which were all over-expressed in liver cancers relative to those in normal tissues, respectively. Among them, PLK1 and CCNA2 were suggested to be prognostic factors for liver carcinoma. CONCLUSION: In conclusion, the present study identified several hub genes, and cell cycle and metabolism-related pathways that may play critical roles in the tumorigenesis of liver cancer. Future validation laboratory experiments are required to confirm the results. Show more

Keywords: Liver carcinoma, hub genes, cell cycle, prognosis, bioinformatics

DOI: 10.3233/CBM-171160

Citation: Cancer Biomarkers, vol. 22, no. 3, pp. 511-521, 2018

Authors: Leow, Yi Jin | Soo, See Ann | Kumar, Dilip | Zailan, Fatin Zahra Binte | Sandhu, Gurveen Kaur | Vipin, Ashwati | Lee, Faith Phemie Hui En | Ghildiyal, Smriti | Liew, Shan Yao | Dang, Chao | Tanoto, Pricilia | Tan, Isabelle Yu Zhen | Chong, Wayne Freeman Weien | Mohammed, Adnan Azam | Ng, Kok Pin | Kandiah, Nagaendran

Article Type: Research Article

Abstract: Background: Mild behavioral impairment (MBI) is one of the earliest observable changes when a person experiences cognitive decline and could be an early manifestation of underlying Alzheimer’s disease neuropathology. Limited attention has been given to investigating the clinical applicability of behavioral biomarkers for detection of prodromal dementia. Objective: This study compared the prevalence of self-reported MBI and vascular risk factors in Southeast Asian adults to identify early indicators of cognitive impairment and dementia. Methods: This cohort study utilized baseline data from the Biomarkers and Cognition Study, Singapore (BIOCIS). 607 participants were recruited and classified into three groups: cognitively normal (CN), …subjective cognitive decline (SCD), and mild cognitive impairment (MCI). Group comparisons of cognitive-behavioral, neuroimaging, and blood biomarkers data were applied using univariate analyses. Multivariate logistic regression analyses were conducted to investigate the association between cerebrovascular disease, vascular profiles, and cognitive impairment. Results: SCD had significantly higher depression scores and poorer quality of life (QOL) compared to CN. MCI had significantly higher depression scores; total MBI symptoms, MBI-interest, MBI-mood, and MBI-beliefs; poorer sleep quality; and poorer QOL compared to CN. Higher Staals scores, glucose levels, and systolic blood pressure were significantly associated with MCI classification. Fasting glucose levels were significantly correlated with depression, anxiety, MBI-social, and poorer sleep quality. Conclusions: The results reflect current research that behavioral changes are among the first symptoms noticeable to the person themselves as they begin to experience cognitive decline. Self-reported questionnaires may aid in early diagnoses of prodromal dementia. Behavioral changes and diabetes could be potential targets for preventative healthcare for dementia. Show more

Keywords: Alzheimer’s disease, biomarkers, diabetes, mild behavioral impairment, mild cognitive impairment

DOI: 10.3233/JAD-230898

Citation: Journal of Alzheimer's Disease, vol. 97, no. 4, pp. 1727-1735, 2024