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Advanced Technologies for Modeling and Optimization of Control Systems and...
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Advanced Technologies for Modeling and Optimization of Control Systems and Biomedical Engineering

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E2: Control Theory and Mechanics".

Deadline for manuscript submissions: 20 December 2025 | Viewed by 450

Special Issue Editor

Dr. Shen Yan

E-Mail Website
Guest Editor
College of Mechanical & Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China
Interests: cyber-physical power systems; modeling and control of microgrids; artificial pancreas systems; medical image processing

Special Issue Information

Dear Colleagues,

Advanced technologies such as Cyber-Physical Systems (CPSs), the Internet of Things (IoT), and Artificial Intelligence (AI) are revolutionizing traditional control systems and biomedical systems. This Special Issue focuses on cutting-edge developments in the modeling and optimization of control systems and biomedical systems, addressing both theoretical innovations and practical implementations across diverse industrial and technological domains. With the increasing complexity of modern dynamic systems, this Special Issue highlights novel methodologies for system identification, controller design, and performance enhancement under constraints, as well as their applications in industrial automation, biomedical engineering, and smart grids, amongst other fields. Particularly in the field of biomedical engineering, emphasis is placed on AI-embedded technologies to improve the accuracy and efficiency of medical image processing and to optimize diagnosis and treatment.

Dr. Shen Yan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • control systems
  • cyber-physical systems
  • networked control systems
  • IoT-based systems
  • artificial intelligence
  • dynamic systems
  • biomedical engineering

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Published Papers (1 paper)

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Research

19 pages, 2252 KiB  
Article
Enhanced ResNet50 for Diabetic Retinopathy Classification: External Attention and Modified Residual Branch
by Menglong Feng, Yixuan Cai and Shen Yan
Mathematics 2025, 13(10), 1557; https://doi.org/10.3390/math13101557 - 9 May 2025
Viewed by 362
Abstract
One of the common microvascular complications in diabetic patients is diabetic retinopathy (DR), which primarily impacts the retinal blood vessels. As the course of diabetes progresses, the incidence of DR gradually increases, and, in serious situations, it can cause vision loss and even [...] Read more.
One of the common microvascular complications in diabetic patients is diabetic retinopathy (DR), which primarily impacts the retinal blood vessels. As the course of diabetes progresses, the incidence of DR gradually increases, and, in serious situations, it can cause vision loss and even blindness. Diagnosing DR early is essential to mitigate its consequences, and deep learning models provide an effective approach. In this study, we propose an improved ResNet50 model, which replaces the 3 × 3 convolution in the residual structure by introducing an external attention mechanism, which improves the model’s awareness of global information and allows the model to grasp the characteristics of the input data more thoroughly. In addition, multiscale convolution is added to the residual branch, which further improves the ability of the model to extract local features and global features, and improves the processing accuracy of image details. In addition, the Sophia optimizer is introduced to replace the traditional Adam optimizer, which further optimizes the classification performance of the model. In this study, 3662 images from the Kaggle open dataset were used to generate 20,184 images for model training after image preprocessing and data augmentation. Experimental results show that the improved ResNet50 model achieves a classification accuracy of 96.68% on the validation set, which is 4.36% higher than the original architecture, and the Kappa value is increased by 5.45%. These improvements contribute to the early diagnosis of DR and decrease the likelihood of blindness among patients. Full article
(This article belongs to the Special Issue Advanced Technologies for Modeling and Optimization of Control Systems and Biomedical Engineering)
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