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Article ; Online: Feedforward-feedback-enhanced model-free adaptive iterative learning control with measurement disturbance and data dropout for an autonomous bus trajectory tracking system.

Liu, Shida / Huang, Wei / Ren, Ye / Wang, Li / Ji, Honghai

2024 Volume 107, Issue 1, Page(s) 368504241229560

Abstract: This article presents an innovative enhanced model-free adaptive iterative learning control approach suited for autonomous bus trajectory tracking systems that may experience measurement disruptions and random data dropouts. Data loss can occur ... ...

Abstract	This article presents an innovative enhanced model-free adaptive iterative learning control approach suited for autonomous bus trajectory tracking systems that may experience measurement disruptions and random data dropouts. Data loss can occur independently and randomly at different times and in different iterations with varying probabilities, leading to successive data dropouts on both the time and iteration axes. The proposed enhanced model-free adaptive iterative learning control controller incorporates a data compensation mechanism to compensate for missing data, ensuring excellent control performance. This data-driven control strategy requires only input/output data for controller design. The convergence and effectiveness of the proposed approach are verified through rigorous mathematical analysis and simulation outcomes.
Language	English
Publishing date	2024-03-16
Publishing country	England
Document type	Journal Article
ZDB-ID	128412-5
ISSN	2047-7163 ; 0036-8504 ; 0302-1785
ISSN (online)	2047-7163
ISSN	0036-8504 ; 0302-1785
DOI	10.1177/00368504241229560
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Article ; Online: Analysis of the intervention effect and self-satisfaction of sports dance exercise on the psychological stress of college students.

Zheng, Changliang / Ji, Honghai

Work (Reading, Mass.)

2021 Volume 69, Issue 2, Page(s) 637–649

Abstract: Background: College students are a high-risk subpopulation of psychological disorders. The problem of various adverse phenomena and consequences caused by excessive pressure on college students has gradually become the focus of social and psychological ... ...

Abstract	Background: College students are a high-risk subpopulation of psychological disorders. The problem of various adverse phenomena and consequences caused by excessive pressure on college students has gradually become the focus of social and psychological academic circles. However, studies related to individual self-concept and psychological pressure are rare. Objective: To explore the impact of sports dance exercises on college students' psychological pressure and improve the psychological effects of their self-satisfaction. Methods: College students were taken as research objects, randomly divided into a control group and an observation group. The observation group is intervened with sports dance exercises. The observation group was intervened with sports dance exercises. The stress response characteristic questionnaire and multidimensional self-satisfaction rating scale were utilized to measure college students' conditions before and after the intervention. Finally, the obtained data were statistically analyzed. Results: Generally, the psychological stress response of college students was mild, with self-satisfaction and various dimensions at a moderately higher level. No significant differences were discovered in the psychological stress response and self-satisfaction level between the control group and the observation group before intervention (P > 0.05), which were homogeneous. Compared with the data obtained before the intervention, after the intervention, the control group scores were slightly reduced in all dimensions of the psychological stress response and self-satisfaction. In contrast, the scores were significantly increased in the experimental group (P < 0.05). Psychological stress response could reliably explain 30.4%of the total self-satisfaction variance (P < 0.01). The negative self-evaluation was the most important variable affecting self-satisfaction, followed by poor interpersonal communication and poor sleeping quality. Conclusions: Sports dance exercises could alleviate the psychological stress of college students and improve their self-satisfaction. Colleges and universities should include sports dance in the content of optional public courses and encourage more college students to actively participate in sports dance exercises to improve their mental health.
MeSH term(s)	Exercise ; Humans ; Personal Satisfaction ; Sports ; Stress, Psychological ; Students ; Universities
Language	English
Publishing date	2021-06-11
Publishing country	Netherlands
Document type	Journal Article ; Randomized Controlled Trial
ZDB-ID	1394194-x
ISSN	1875-9270 ; 1051-9815
ISSN (online)	1875-9270
ISSN	1051-9815
DOI	10.3233/WOR-213505
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Article ; Online: The influence of physical exercise on college students' mental health and social adaptability from the cognitive perspective.

Ji, Honghai / Zheng, Changliang

Work (Reading, Mass.)

2021 Volume 69, Issue 2, Page(s) 651–662

Abstract: Background: the relationship between physical exercise (PE) and mental health (MH) had been an important research topic in exercise psychology. With the development of society, the increasingly fierce social competition had put forward higher and higher ...

Abstract	Background: the relationship between physical exercise (PE) and mental health (MH) had been an important research topic in exercise psychology. With the development of society, the increasingly fierce social competition had put forward higher and higher requirements for college students' social adaptability (SA). As members of the new era, college students were expected to not only have innovative knowledge concept, solid knowledge foundation, and healthy psychology, but also have the ability to adapt to the changes in the environment, know how to get along with others, and deal with problems alone. Objective: this study aimed to evaluate the PE, MH, and SA of college students, and to analyze the internal relationships among PE, MH, and SA. Methods: based on questionnaire survey, college students were randomly selected for investigation and the data were statistically processed. Results: there were significant differences in the MH of students of different genders, majors, grades, and origins. There was a significant difference between the amount of exercise and the MH of college students. The amount of exercise was positively correlated with the MH level of college students, and there was also a positive correlation between PE and MH. The SA of the physical exercisers was average, but the SA of the non-physical exercisers was poor. There was a significant difference between the SA of the physical exercisers and the non-physical exercisers. There were significant differences in the SA between physical exercisers and non-physical exercisers of different genders, majors, grades, and origins. Physical exercisers who participated in team sports were more socially adaptable. There was no significant difference in the SA of physical exercisers of different genders, majors, and origins, and the SA of senior students was stronger. Conclusions: PE had a positive effect on college students' MH and social adaptation ability. Colleges and universities could improve their MH and social adaptation ability by arranging appropriate PE.
MeSH term(s)	Cognition ; Exercise ; Female ; Humans ; Male ; Mental Health ; Students ; Universities
Language	English
Publishing date	2021-05-28
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1394194-x
ISSN	1875-9270 ; 1051-9815
ISSN (online)	1875-9270
ISSN	1051-9815
DOI	10.3233/WOR-213506
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Article: The efficacy of cetuximab plus PD-1 inhibitors as salvage therapy in PD-1 refractory patients with recurrent or metastatic head and neck squamous cell carcinoma.

Hui, Rongrong / Liu, Xiulan / Fan, Zongyu / Ji, Honghai / Wei, Dongliang / Ren, Guoxin

Journal of Cancer

2024 Volume 15, Issue 6, Page(s) 1668–1674

Abstract: Purpose: ...

Abstract	Purpose:
Language	English
Publishing date	2024-01-27
Publishing country	Australia
Document type	Journal Article
ZDB-ID	2573318-7
ISSN	1837-9664
ISSN	1837-9664
DOI	10.7150/jca.92689
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Article ; Online: Enhancing assisted diagnostic accuracy in scalp psoriasis: A Multi-Network Fusion Object Detection Framework for dermoscopic pattern diagnosis.

Ji, Honghai / Li, Jiaqi / Zhu, Xiaoyang / Fan, Lingling / Jiang, Weiwei / Chen, Yang

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)

2024 Volume 30, Issue 4, Page(s) e13698

Abstract: Background: Dermoscopy is a common method of scalp psoriasis diagnosis, and several artificial intelligence techniques have been used to assist dermoscopy in the diagnosis of nail fungus disease, the most commonly used being the convolutional neural ... ...

Abstract	Background: Dermoscopy is a common method of scalp psoriasis diagnosis, and several artificial intelligence techniques have been used to assist dermoscopy in the diagnosis of nail fungus disease, the most commonly used being the convolutional neural network algorithm; however, convolutional neural networks are only the most basic algorithm, and the use of object detection algorithms to assist dermoscopy in the diagnosis of scalp psoriasis has not been reported. Objectives: Establishment of a dermoscopic modality diagnostic framework for scalp psoriasis based on object detection technology and image enhancement to improve diagnostic efficiency and accuracy. Methods: We analyzed the dermoscopic patterns of scalp psoriasis diagnosed at 72nd Group army hospital of PLA from January 1, 2020 to December 31, 2021, and selected scalp seborrheic dermatitis as a control group. Based on dermoscopic images and major dermoscopic patterns of scalp psoriasis and scalp seborrheic dermatitis, we investigated a multi-network fusion object detection framework based on the object detection technique Faster R-CNN and the image enhancement technique contrast limited adaptive histogram equalization (CLAHE), for assisting in the diagnosis of scalp psoriasis and scalp seborrheic dermatitis, as well as to differentiate the major dermoscopic patterns of the two diseases. The diagnostic performance of the multi-network fusion object detection framework was compared with that between dermatologists. Results: A total of 1876 dermoscopic images were collected, including 1218 for scalp psoriasis versus 658 for scalp seborrheic dermatitis. Based on these images, training and testing are performed using a multi-network fusion object detection framework. The results showed that the test accuracy, specificity, sensitivity, and Youden index for the diagnosis of scalp psoriasis was: 91.0%, 89.5%, 91.0%, and 0.805, and for the main dermoscopic patterns of scalp psoriasis and scalp seborrheic dermatitis, the diagnostic results were: 89.9%, 97.7%, 89.9%, and 0.876. Comparing the diagnostic results with those of five dermatologists, the fusion framework performs better than the dermatologists' diagnoses. Conclusions: Studies have shown some differences in dermoscopic patterns between scalp psoriasis and scalp seborrheic dermatitis. The proposed multi-network fusion object detection framework has higher diagnostic performance for scalp psoriasis than for dermatologists.
MeSH term(s)	Humans ; Dermatitis, Seborrheic ; Scalp ; Artificial Intelligence ; Psoriasis ; Neural Networks, Computer ; Dermoscopy/methods ; Skin Neoplasms/diagnosis
Language	English
Publishing date	2024-04-15
Publishing country	England
Document type	Journal Article
ZDB-ID	1229160-2
ISSN	1600-0846 ; 0909-752X ; 1397-1344
ISSN (online)	1600-0846
ISSN	0909-752X ; 1397-1344
DOI	10.1111/srt.13698
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Article ; Online: [Retracted] MicroRNA‑655 suppresses cell proliferation and invasion in oral squamous cell carcinoma by directly targeting metadherin and regulating the PTEN/AKT pathway.

Wang, Qiang / Lv, Longkun / Li, Yuan / Ji, Honghai

Molecular medicine reports

2022 Volume 27, Issue 1

Abstract: Following the publication of this paper, it was drawn to the Editors' attention by a concerned reader that the data in the centre panel shown for the cell invasion assays in Fig. 2C were strikingly similar to data appearing in different form in other ... ...

Abstract	Following the publication of this paper, it was drawn to the Editors' attention by a concerned reader that the data in the centre panel shown for the cell invasion assays in Fig. 2C were strikingly similar to data appearing in different form in other articles by different authors. Owing to the fact that the contentious data in the above article had already been published elsewhere prior to its submission to
Language	English
Publishing date	2022-11-16
Publishing country	Greece
Document type	Retraction of Publication
ZDB-ID	2469505-1
ISSN	1791-3004 ; 1791-2997
ISSN (online)	1791-3004
ISSN	1791-2997
DOI	10.3892/mmr.2022.12897
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Article ; Online: Data–driven online modelling for a UGI gasification process using modified lazy learning with a relevance vector machine

Liu Shida / Ji Honghai / Hou Zhongsheng / Zuo Jiashuo / Fan Lingling

International Journal of Applied Mathematics and Computer Science, Vol 31, Iss 2, Pp 321-

2021 Volume 335

Abstract: A modified lazy learning algorithm combined with a relevance vector machine (MLL-RVM) is presented to address a data-driven modelling problem for a gasification process inside a united gas improvement (UGI) gasifier. During the UGI gasification process, ... ...

Abstract	A modified lazy learning algorithm combined with a relevance vector machine (MLL-RVM) is presented to address a data-driven modelling problem for a gasification process inside a united gas improvement (UGI) gasifier. During the UGI gasification process, the measured online temperature of the produced crude gas is a crucial aspect. However, the gasification process complexities, especially severe changes in the temperature versus infrequent manipulation of the gasifier and the unknown noise in collected data, pose difficulties in dynamics process descriptions via conventional first principles. In the MLL-RVM, a novel weighted neighbour selection method is adopted based on the proposed dynamic cost functions. Moreover, the RVM is utilized in the implementation and design of the proposed online local modelling owing to its short test time and sparseness. Furthermore, the leave-one-out cross-validation technique is used for local model validation, by which the modelling performance is further improved. The MLL-RVM is applied to a series of real data collected from a pragmatic UGI gasifier, and its effectiveness is verified.
Keywords	data-driven modelling ; ugi gasification process ; relevance vector machine ; modified lazy learning ; Mathematics ; QA1-939 ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	670
Language	English
Publishing date	2021-06-01T00:00:00Z
Publisher	Sciendo
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Parotid metastasis of rare lung adenocarcinoma: A case report.

Yan, Ru-Xi / Dou, Lin-Bo / Wang, Zi-Jia / Qiao, Xue / Ji, Hong-Hai / Zhang, Yan-Cong

World journal of clinical cases

2024 Volume 12, Issue 6, Page(s) 1182–1189

Abstract: Background: Lung cancer (LC) is the leading cause of malignancy-related deaths worldwide. The most common sites of metastasis include the nervous system, bone, liver, respiratory system, and adrenal glands. LC metastasis in the parotid gland is very ... ...

Abstract	Background: Lung cancer (LC) is the leading cause of malignancy-related deaths worldwide. The most common sites of metastasis include the nervous system, bone, liver, respiratory system, and adrenal glands. LC metastasis in the parotid gland is very rare, and its diagnosis presents a challenge. Here, we report a case of parotid metastasis in primary LC. Case summary: The patient was a 74-year-old male who was discovered to have bilateral facial asymmetry inadvertently two years ago. The right earlobe was slightly swollen and without pain or numbness. Computed tomography (CT) examination showed bilateral lung space-occupying lesions. Pulmonary biopsy was performed and revealed adenocarcinoma (right-upper-lung nodule tissue). Positron emission tomography-CT examination showed: (1) Two hypermetabolic nodules in the right upper lobe of the lung, enlarged hypermetabolic lymph nodes in the right hilar and mediastinum, and malignant space-occupying lesion in the right upper lobe of the lung and possible metastasis to the right hilar and mediastinal lymph nodes; and (2) multiple hypermetabolic nodules in bilateral parotid glands. Parotid puncture biopsy was performed considering lung adenocarcinoma metastasis. Gene detection of lung biopsy specimens revealed an Conclusion: This case report highlights the challenging diagnosis of parotid metastasis in LC given its rare nature. Such lesions should be differentiated from primary tumors of the parotid gland. Simple radiological imaging is unreliable, and puncture biopsy is needed for final diagnosis of this condition.
Language	English
Publishing date	2024-03-07
Publishing country	United States
Document type	Case Reports
ISSN	2307-8960
ISSN	2307-8960
DOI	10.12998/wjcc.v12.i6.1182
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Article ; Online: A Novel Genetic Neural Network Algorithm with Link Switches and Its Application in University Professional Course Evaluation.

Ji, Honghai / Zhou, Jinyao / Liu, Shida / Wang, Li / Fan, Lingling

Computational intelligence and neuroscience

2022 Volume 2022, Page(s) 9564443

Abstract: This study exploits a novel enhanced genetic neural network algorithm with link switches (EGA-NNLS) to model the professional university course evaluating system. Various indices should be employed to evaluate the learning effect of a professional course ...

Abstract	This study exploits a novel enhanced genetic neural network algorithm with link switches (EGA-NNLS) to model the professional university course evaluating system. Various indices should be employed to evaluate the learning effect of a professional course comprehensively and objectively, and the traditional artificial evaluation methods cannot achieve this goal. The presented data-driven modeling method, EGA-NNLS, combines a neural network with link switches (NN-LS) with an enhanced genetic algorithm (EGA) and the Levenberg-Marquardt (LM) algorithm. It employs an optimized network structure combined with EGA and NN-LS to learn the relationships between the system's input and output from historical data and uses the network's gradient information via the LM algorithm. Compared with the traditional backpropagation neural network (BPNN), EGA-NNLS achieves a faster convergence speed and higher evaluation precision. In order to verify the efficiency of EGA-NNLS, it is applied to a collection of experimental data for modeling the professional university course evaluating system.
MeSH term(s)	Algorithms ; Humans ; Neural Networks, Computer ; Universities
Language	English
Publishing date	2022-05-24
Publishing country	United States
Document type	Journal Article
ZDB-ID	2388208-6
ISSN	1687-5273 ; 1687-5273
ISSN (online)	1687-5273
ISSN	1687-5273
DOI	10.1155/2022/9564443
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Article ; Online: Data-Driven Distributed Information-Weighted Consensus Filtering in Discrete-Time Sensor Networks With Switching Topologies.

Ji, Honghai / Wei, Yuzhou / Fan, Lingling / Liu, Shida / Hou, Zhongsheng / Wang, Li

IEEE transactions on cybernetics

2023 Volume 53, Issue 12, Page(s) 7548–7559

Abstract: This article proposes a data-driven distributed filtering method based on the consensus protocol and information-weighted strategy for discrete-time sensor networks with switching topologies. By introducing a data-driven method, a linear-like state ... ...

Abstract	This article proposes a data-driven distributed filtering method based on the consensus protocol and information-weighted strategy for discrete-time sensor networks with switching topologies. By introducing a data-driven method, a linear-like state equation is designed by utilizing only the input and output (I/O) data without a controlled object model. In the identification step, data-driven adaptive optimization recursive identification (DD-AORI) is exploited to identify the recurrence of time-varying parameters. It is proved that for discrete-time switching networks, estimation errors of all nodes are ultimately bounded when data-driven distributed information-weighted consensus filtering (DD-DICF) is executed. The algorithm combines with the received neighbors and direct or indirect observations for the target node to produce modified gains, resulting in a novel state estimator containing an information interaction mechanism. Subsequently, convergence analysis is performed on the basis of the Lyapunov equation to guarantee the boundedness of DD-DICF estimate error. Simulations verify the performance of the DD-DICF against the theoretical results as well as in comparison with some existing filtering algorithms.
Language	English
Publishing date	2023-11-29
Publishing country	United States
Document type	Journal Article
ISSN	2168-2275
ISSN (online)	2168-2275
DOI	10.1109/TCYB.2022.3166649
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