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Enhanced Nature Inspired-Support Vector Machine for Glaucoma Detection

Computers, Materials & Continua 2023年第7期76卷 1151-1172页

作者： Jahanzaib Latif Shanshan Tu Chuangbai Xiao Anas Bilal Sadaqat Ur Rehman Zohaib Ahmad Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information TechnologyBeijing University of Technology100124BeijingChina College of Information Science Technology Hainan Normal UniversityHainan ProvinceHaikou571158China Department of Computer Science University of SalfordManchesterUK Faculty of Information Technology Beijing University of Technology Chaoyang District BeijingChina

Glaucoma is a progressive eye disease that can lead to blindness if left *** detection is crucial to prevent vision loss,but current manual scanning methods are expensive,time-consuming,and require specialized *** study presents a novel approach to Glaucoma detection using the Enhanced Grey Wolf Optimized Support Vector Machine(EGWO-SVM)*** proposed method involves preprocessing steps such as removing image noise using the adaptive median filter(AMF)and feature extraction using the previously processed speeded-up robust feature(SURF),histogram of oriented gradients(HOG),and Global *** enhanced Grey Wolf Optimization(GWO)technique is then employed with SVM for *** evaluate the proposed method,we used the online retinal images for glaucoma analysis(ORIGA)database,and it achieved high accuracy,sensitivity,and specificity rates of 94%,92%,and 92%,*** results demonstrate that the proposed method outperforms other current algorithms in detecting the presence or absence of *** study provides a novel and effective approach to Glaucoma detection that can potentially improve the detection process and outcomes.

关键词： Glaucoma detection grey golf optimization support vector machine feature extraction image classification

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Task Offloading of Intelligent Building Based on Dependency-Aware in Edge Computing

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Recent Patents on Mechanical engineering 2023年第5期16卷 373-385页

作者： Lingzhi, Yi Jianxiong, Huang Yahui, Wang Jiao, Long Bote, Luo Jiangyong, Liu College of Information Engineering Xiangtan University& Hunan Engineering Research Center of Multi-energy Cooperative Control Technology Hunan Xiangtan411105 China College of Electrical and Information Engineering Hunan University Hunan Changsha410082 China Willfar Information Technology Co. Ltd Hunan Changsha410205 China

Background: With the rapid development of artificial intelligence, the traditional cloud computing model has serious bandwidth and energy consumption problems when storing and pro-cessing massive amounts of raw data. To address this problem, recent patents have investigated methods for intelligent task offloading and allocation in mobile edge computing. Objective: A Directed Acyclic Graph (DAG) task unloading model is established to reduce the problem of task delay and energy consumption in edge networks. At the same time, Modified Tuna Swarm Optimization (MTSO) is used to improve execution efficiency. Methods: Firstly, this paper integrates (i) inter-task dependencies;(ii) heterogeneity of computing re-sources in the edge network;and (iii) interference of wireless channels in the edge network. A DAG task offloading model is developed to reduce latency and energy consumption. The end users are guided to offload their tasks/sub-tasks to the most appropriate servers in the edge network, thus minimizing the end-to-end latency of all tasks in the edge network. Secondly, the MTSO algorithm is used to coordinate the dependencies and priorities of subtasks to improve execution efficiency. Results: The experimental results show that when the number of users including subtasks is 10, the final edge server utilization rate is as high as 92%. A more fine-grained segmentation scheme can reduce the average delay of tasks and improve the utilization rate of edge servers. Conclusion: The approach proposed in this paper reduces the end-to-end latency and improves resource utilization in complex applications under the premise of ensuring task dependency. It will relieve the pressure on the cloud and has certain engineering application value. © 2023 Bentham Science Publishers.

关键词： Mobile edge computing

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An image segmentation method of pulverized coal for particle size analysis

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International Journal of Mining Science and technology 2023年第9期33卷 1181-1192页

作者： Xin Li Shiyin Li Liang Dong Shuxian Su Xiaojuan Hu Zhaolin Lu Affiliated Hospital of China University of Mining and Technology Xuzhou 221002China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China School of Chemical Engineering&Technology China University of Mining and TechnologyXuzhou 221116China Advanced Analysis and Computation Center China University of Mining and TechnologyXuzhou 221116China

An important index to evaluate the process efficiency of coal preparation is the mineral liberation degree of pulverized coal,which is greatly influenced by the particle size and shape distribution acquired by image ***,the agglomeration effect of fine powders and the edge effect of granular images caused by scanning electron microscopy greatly affect the precision of particle image *** this study,we propose a novel image segmentation method derived from mask regional convolutional neural network based on deep learning for recognizing fine coal ***,an atrous convolution is introduced into our network to learn the image feature of multi-sized powders,which can reduce the missing segmentation of small-sized agglomerated ***,a new mask loss function combing focal loss and dice coefficient is used to overcome the false segmentation caused by the edge *** final comparative experimental results show that our method achieves the best results of 94.43%and 91.44%on AP50 and AP75 respectively among the comparison *** addition,in order to provide an effective method for particle size analysis of coal particles,we study the particle size distribution of coal powders based on the proposed image segmentation method and obtain a good curve relationship between cumulative mass fraction and particle size.

关键词： Pulverized coal Image segmentation Deep learning Particle size analysis

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Differentiable Automatic Data Augmentation by Proximal Update for Medical Image Segmentation

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1315-1318页

作者： Wenxuan He Min Liu Yi Tang Qinghao Liu Yaonan Wang College of Electrical and Information Engineering Hunan UniversityChangsha 410082 National Engineering Research Center of Robot Visual Perception and Control Technology Changsha 410082China

Dear editor,This letter presents an automatic data augmentation algorithm for medical image *** increase the scale and diversity of medical images,we propose a differentiable automatic data augmentation algorithm based on proximal update by finding an optimal augmentation ***,on the one hand,a dedicated search space is designed for the medical image segmentation *** the other hand,we introduce a proximal differentiable gradient descent strategy to update the data augmentation policy,which would increase the searching *** of the experiments indicate that the proposed algorithm significantly outperforms state-of-the-art methods,and search speed is 10 times faster than state-of-the-art methods.

关键词： editor policy Image

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A Line Complex-Based Evolutionary Algorithm for Many-Objective Optimization

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IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1150-1167页

作者： Liang Zhang Qi Kang Qi Deng Luyuan Xu Qidi Wu the Department of Control Science and Engineering Tongji UniversityShanghai 201804 the Jiangsu Province Support Software Engineering R&D Center for Modern Information Technology Application in Enterprise Suzhou 215104China the Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 200092China

In solving many-objective optimization problems(MaO Ps),existing nondominated sorting-based multi-objective evolutionary algorithms suffer from the fast loss of selection *** candidate solutions become nondominated during the evolutionary process,thus leading to the failure of producing offspring toward Pareto-optimal front with *** we find a more effective way to select nondominated solutions and resolve this issue?To answer this critical question,this work proposes to evolve solutions through line complex rather than solution points in Euclidean ***,Plücker coordinates are used to project solution points to line complex composed of position vectors and momentum *** position vectors of the solution points,momentum vectors are used to extend the comparability of nondominated solutions and enhance selection ***,a new distance function designed for high-dimensional space is proposed to replace Euclidean distance as a more effective distancebased *** on them,a novel many-objective evolutionary algorithm(MaOEA)is proposed by integrating a line complex-based environmental selection strategy into the NSGAⅢ*** proposed algorithm is compared with the state of the art on widely used benchmark problems with up to 15 *** results demonstrate its superior competitiveness in solving MaOPs.

关键词： Environmental selection line complex many-objective optimization problems(MaOPs) Plücker coordinate

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H8 voltage control of islanded microgrid three-phase inverter: a model-free integral reinforcement learning approach 3

H8 voltage control of islanded microgrid three-phase inverte...

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3rd Conference on Fully Actuated System Theory and Applications, FASTA 2024

作者： Zhou, Linna Li, Fuxing Li, Gonghe Liu, Xiaomin Yang, Chunyu China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Ministry of Education Engineering Research Center of Intelligent Control for Underground Space Xuzhou221116 China

ISBN: (纸本)9798350373691

In this paper, an inner-loop control method based on the integral reinforcement learning (IRL) algorithm is proposed to address the challenges of uncertain inverter model parameters and strong disturbances caused by nonlinear and unbalanced loads. Firstly, the mathematical model of an LC-type off-grid inverter is established in the d-q axis, and the off-grid inverter voltage control problem is transformed into an H8 tracking problem by introducing the augmented system. The reference signal of the inverter output voltage, together with the original state, are defined as the state of the augmented system. An initial control gain along with exploration noises are conducted on the inverter to collect augmented state data and disturbance data (output current). Then, by utilizing the principles of zero-sum game theory, the tracking Hamilton-Jacobi-Isaacs (HJI) equation is derived, and the IRL algorithm is proposed to solve this equation. The Kronecker products containing state values, control inputs, and disturbance values are calculated based on the measurement data, and the iterative inverter voltage control strategy is derived. Next, it is proven that the proposed control policy ensures the asymptotic stability of the augmented system and satisfies the L2 gain condition. Finally, the effectiveness of the proposed algorithm is verified through simulation. © 2024 IEEE.

关键词： Reinforcement learning

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Positive definiteness of fourth-order partially symmetric tensors

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Applied Mathematics(A Journal of Chinese Universities) 2023年第4期38卷 581-590页

作者： WANG Hua-ge School of Mathematics and Information Science Henan Normal UniversityXinxiang 453007China Engineering Technology Research Center of Neurosense and Control of Henan Province Xinxiang Medical UniversityXinxiang 453003China

In this paper,we consider the positive definiteness of fourth-order partially symmetric ***,two analytically sufficient and necessary conditions of positive definiteness are provided for fourth-order two dimensional partially symmetric ***,we obtain several sufficient conditions for rank-one positive definiteness of fourth-order three dimensional partially symmetric tensors.

关键词： partially symmetric tensor positive de niteness rank-one positive de nite

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A Parameter Adaptive Model Predictive control for Virtual Coupling

A Parameter Adaptive Model Predictive Control for Virtual Co...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Zhu, Yu Zhang, Yadong School of Information Science and Technology Southwest Jiaotong University Chengdu611765 China Sichuan Engineering Research Center of Train Operation Control Technology Chengdu611765 China

ISBN: (纸本)9789819639564

Virtual coupling technology is currently a focal point within the railway industry. Through vehicle-to-vehicle communication, virtual coupling allows trains to form a unified train unit, thereby reducing inter-train spacing and enhancing transportation efficiency. The complexity of tracking operations and the shorter spacing between virtual coupled trains place high demands on controller performance. This paper designs an adaptive model predictive control (MPC), enabling automatic adjustment of control parameters with the train's operation. Firstly, this paper establishes a train dynamics model based on an improved single-point mass model. Secondly, considering the characteristics of train tracking operations, this paper formulates rules for varying control parameters, thus designing an adaptive MPC. Finally, to validate the effectiveness of the method, simulations were conducted using three heterogeneous trains for virtual coupling target tracking. The results indicate that compared to fixed-parameter MPC, the method proposed in this paper improves computational efficiency by 5% and reduces inter-train spacing tracking error by 16%. The effectiveness of the proposed control approach has been demonstrated, providing a reference for further research on dynamic adjustment of control parameters in train operation processes. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Self adjusting control systems

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Toxicological responses of A549 and HCE-T cells exposed to fine particulate matter at the air–liquid interface

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Environmental Science and Pollution Research 2024年第18期31卷 27375-27387页

作者： Chen, Wankang Ge, Pengxiang Deng, Minjun Liu, Xiaoming Lu, Zhenyu Yan, Zhansheng Chen, Mindong Wang, Junfeng Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science & ampTechnology Nanjing210044 China Ningxia Meteorological Service Center Yinchuan750002 China

Fine particulate matter (PM2.5) can enter the human body in various ways and have adverse effects on human health. Human lungs and eyes are exposed to the air for a long time and are the first to be exposed to PM2.5. The "liquid immersion exposure method" has some limitations that prevent it from fully reflecting the toxic effects of particulate matter on the human body. In this study, the collected PM2.5 samples were chemically analyzed. An air–liquid interface (ALI) model with a high correlation to the in vivo environment was established based on human lung epithelial cells (A549) and immortalized human corneal epithelial cells (HCE-T). The VITROCELL Cloud 12 system was used to distribute PM2.5 on the cells evenly. After exposure for 6 h and 24 h, cell viability, apoptosis rate, reactive oxygen species (ROS) level, expression of inflammatory factors, and deoxyribonucleic acid (DNA) damage were measured. The results demonstrated significant dose- and time-dependent effects of PM2.5 on cell viability, cell apoptosis, ROS generation, and DNA damage at the ALI, while the inflammatory factors showed dose-dependent effects only. It should be noted that even short exposure to low doses of PM2.5 can cause cell DNA double-strand breaks and increased expression of γ-H2AX, indicating significant genotoxicity of PM2.5. Increased abundance of ROS in cells plays a crucial role in the cytotoxicity induced by PM2.5 exposure These findings emphasize the significant cellular damage and genotoxicity that may result from short-term exposure to low levels of PM2.5. © The Author(s) 2024.

关键词： Cell death

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Judgment of blast furnace iron-tapping status based on data differential processing and dynamic window analysis algorithm

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Progress in Natural Science:Materials International 2023年第4期33卷 450-457页

作者： Youcheng Zong Zixian Wang Xiang Liu Yi Nian Jianian Pan Chaojie Zhang Yingxue Wang Jianhua Chu Liqiang Zhang The Intelligent Metallurgy Research Institute School of Metallurgical Engineering Anhui University of Technology Department of Technical Quality Manufacturing Management Division(Technical Center) Anhui Changjiang Steel Co. Ltd. National Engineering Research Center for Public Safety Risk Perception and Control by Big Data(RPP) China Academic of Electronics and Information Technology

Ironmaking plants hold a core position in steel production. Efficient level detection and iron-tapping status judgment can accurately measure the liquid level and predict the amount of molten iron in the ladle, thereby ensuring production safety and improving production efficiency. At present, the judgment of the start and end statuses of blast furnace iron-tapping mainly relies on manual visual inspection. However, due to the high-temperature environment on-site and interference from iron powder, gunning mud, and other dust, operators find it challenging to make accurate judgments. To address these issues, this study proposes a robust and accurate method for judging the iron-tapping status of blast furnaces. This study collected four million on-site liquid level data, underwent interpolation, noise reduction, normalization, and other preprocessing steps, and then used differential processing to calculate the iron-tapping rate. Combined with dynamic window feature analysis, it effectively captured the change characteristics of the liquid level in the ladle under different iron-tapping *** simulated on-site experiments, the method achieved a 96.6 % accuracy rate for iron-tapping status *** real-time iron-tapping status judgment method based on differential processing of liquid level data and dynamic window feature analysis proposed in this study demonstrates high precision and robustness in the complex environment of ironmaking plants. This technology not only improves the production efficiency of the iron and steel link but also frees on-site operators from the harsh working environment, eliminating human errors in judgments and omissions, further promoting the intelligent process of ironmaking plants.

关键词： Blast furnace iron-tapping Molten iron level Radar level gauge Iron-tapping status judgment Data differential processing Sliding window

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