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5th International Conference on Intelligent Control, Measurement and Signal Processing, ICMSP 2023

作者： Li, Zhiqiang Li, Shoubo You, Junheng Lei, Ping Zhang, Xia Wu, Jun Chen, Yan Li, Tinghua Technology Center China Tobacco Yunnan Industrial Co. Ltd. Kunming China Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming China

ISBN: (纸本)9798350336030

Electromagnetic heated-cigarettes device generates heat through electromagnetic induction in order to heat tobacco. However, due to the small surface area of the heating element, which is located in the shielding cavity wrapped by the induction coil, it is difficult to achieve accurate temperature measurement, which leads to the difficulty of quality control of electromagnetic heated-cigarettes device and the large temperature difference of the device, and it is difficult to ensure the user's smoking experience;According to the thermal characteristics of metal materials, the detection platform of electromagnetic heated-cigarettes device is designed, which is not only suitable for small surface, shielding cavity and electromagnetic environment, but also does not change the structure of heated-cigarette device. The results show that the thermal properties of 1J85 and 1J50 Permalloy show a linear relationship in the range of 200°C to 400°C, and the temperature can be measured by measuring the elongation of the material;The thermal properties of 1J79 and 4J36 Permalloy are nonlinear, which can be used to detect the elongation of materials at fixed point temperature. If the material has linear thermal characteristics, the measured temperature error of each batch of cigarette device is ≤ 3°C Or if the material has nonlinear thermal characteristics, the measured elongation error of each batch of cigarette device at the fixed point temperature (such as 350°C) is ≤ 0.02mm, which can ensure the consistency of the heating temperature of the electromagnetic heated-cigarettes device for quantitative production and ensure the product quality of the device. © 2023 IEEE.

关键词： Thermal expansion

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Adaptive Non-backstepping Output-Feedback Control for Hydraulic Servo System Subject to Uncertain Dynamics 19th

Adaptive Non-backstepping Output-Feedback Control for Hydrau...

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19th Chinese Intelligent Systems Conference, CISC 2023

作者： Li, Chenghuan Ma, Jun Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment Kunming University of Science and Technology Kunming650500 China

ISBN: (纸本)9789819968855

In this paper, a novel non-backstepping adaptive control approach is presented for the hydraulic servo systems, aiming to mitigate the "explosion of complexity" issue and achieve matching of full-state known conditions. This approach enables one-step control through coordinate transformation. To address the control singularity problem, two radial basis function neural networks (RBFNNs) are utilized to estimate the separate sets of lumped unknown dynamics. Additionally, an adaptive controller is designed where the neural network weights are updated online using a weight error variable. This ensures that the estimated weights converge closely to their true values, allowing for accurate identification of the unknown dynamics. Theoretical analysis and numerical simulation are conducted verity the correctness and effectiveness of the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Backstepping

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Optimal Structure Exploration of Bayesian Network Based on Dealing with the Route Choice Model 6

Optimal Structure Exploration of Bayesian Network Based on D...

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6th International Conference on Computer information science and Application technology, CISAT 2023

作者： Wang, Ziyi Zeng, Yufei Wang, Rui College of Big Data and Intelligent Engineering Southwest Forestry University Kunming China College of Computer Science and Technology Harbin Institute of Technology Yichun China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China

ISBN: (纸本)9781510668546

Route selection in residents' travel is a key link in travel decision-making in transportation systems. In existing studies, discrete choice models are often used to describe residents' travel path choices. However， with today's highly developed big data, the traditional discrete choice model is too simple to represent residents' travel path choices, ignoring the connection between various factors. Therefore, a big data-driven approach is proposed to solve this problem in this paper. Driven by research data and with the introduction of the Bayesian network model, the paper adopts a hill-climbing search strategy to improve the search efficiency, uses a variety of scoring functions to train data, which optimizes the Bayesian network structure. The experimental results show that the model fully considers the causation between the independent variables, which is more logical and makes the construction of the resident travel route selection model more accurate and efficient. © 2023 SPIE.

关键词： Bayesian networks

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Sparse Attention-based Hierarchical Node Representation for Spatial Domain Identification

Sparse Attention-based Hierarchical Node Representation for ...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Peng, Wei Ping, Zhihao Dai, Wei Fu, Xiaodong Liu, Li Liu, Lijun Yu, Ning Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming China Computer Technology Application Key Lab of Yunnan Province Kunming University of Science and Technology Kunming China State University of New York The College at Brockport Department of Computing Sciences BrockportNY14422 United States

ISBN: (纸本)9798350386226

Using deep learning models on spatial transcriptomics data to identify the spatial domain is crucial for uncovering the spatial distribution of cells and gene expression patterns within tissues, essential for understanding complex biological processes and disease mechanisms. Existing methods for spatial domain partitioning often rely on predefined adjacency relationships at a single scale, overlooking the hierarchical structure and functional characteristics of biological tissues. In this paper, we propose SpaNFM, a novel method that leverages sparse attention-based hierarchical node representation and multi-view contrastive learning for spatial domain identification in spatial transcriptomics data. The SpaNFM first treats each spot as a node and constructs two views using different data augmentation techniques based on tissue image information, gene expression profiles, and spatial coordinates of cells. Subsequently, SpaNFM utilizes a sparse attention-based hierarchical node fusion module to generate coarse-grained node representations. This fine-to-coarse hierarchical structure integrates complementary information from multi-granularity node features and reduces model complexity due to the decreased node size. The model parameters are updated using gene expression reconstruction loss and contrastive loss on the coarse-grained node representations from the two views. Finally, the learned node features are subjected to downstream clustering using the Leiden algorithm. We tested SpaNFM on the human dorsolateral prefrontal cortex dataset. The results demonstrate that SpaNFM outperforms other state-of-the-art methods in most cases. The data and code are available at: https://***/weiba/SpaNFM © 2024 IEEE.

关键词： Contrastive Learning

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Adaptive Sensitivity Amplification Control with Q-Learning for Cable-Driven Lower-Limb Exoskeletons 42

Adaptive Sensitivity Amplification Control with Q-Learning f...

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42nd Chinese Control Conference, CCC 2023

作者： Zhong, Linzhen Wang, Xiaodong Gao, Guanbin Xing, Yashan Zhang, Faxiang Kunming University of Science and Technology Faculty of Information Engineering & Automation Kunming650500 China Kunming University of Science & Technology Faculty of Mechanical & Electrical Engineering Kunming650500 China Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment Kunming650500 China

ISBN: (纸本)9789887581543

This paper proposes a sensitivity amplification control (SAC) based on Q-learning for the cable-driven lower-limb exoskeleton (CDLEX) to guarantee the tracking performance and achieve comfortable human-robot interaction (HRI). There is no requirement for direct measurement of HRI in the SAC scheme, hence the force/torque sensors are avoided. For the purpose of accommodating the uncertainties of the interaction environment, such as the individual gaits and suddenly changing walking trajectories, the Q-learning algorithm is utilized to realize online parameter tuning of SAC. Finally, comparative numerical simulations are included to verify the effectiveness of the control scheme. © 2023 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Human robot interaction

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Prediction and Optimization of the Thermal Properties of TiO_(2)/Water Nanofluids in the Framework of a Machine Learning Approach

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Fluid Dynamics & Materials Processing 2023年第8期19卷 2181-2200页

作者： Jiachen Li Wenlong Deng Shan Qing Yiqin Liu Hao Zhang Min Zheng Sate Key Laboratory of Complex Nonferrous Clean Utilization Kunming University of Science and TechnologyKunming650093China Faculty of Metallurgical and Energy Engineering Kunming University of Science and TechnologyKunming650093China Jiangxi Guoxing Intelligent Energy Co. Ganzhou330300China Faculty of Media and Information Engineering Yunnan Open UniversityKunming650500China

In this study,comparing multiple models of machine learning,a multiple linear regression(MLP),multilayer feed-forward artificial neural network(BP)model,and a radial-basis feed-forward artificial neural network(RBF-BP)model are selected for the optimization of the thermal properties of TiO_(2)/water *** particular,the least squares support vector machine(LS-SVM)method and radial basis support vector machine(RB-SVM)method are ***,curve fitting is performed by means of multiple linear regression in order to obtain bivariate correlation functions for thermal conductivity and viscosity of the *** the aforementioned models are used for a predictive analysis of the dependence of its thermal conductivity and viscosity on temperature and volume *** results show that the least squares support vector machine(LS-SVM)has a prediction accuracy higher than the other *** model predicts the thermal conductivity of TiO_(2)/water MSE=1.0853×10^(-6),R2=0.99864,MAE=0.00092,RMSE=0.00104,and the viscosity of TiO_(2)/water MSE=8.1397×10^(-6),R2=0.99995,MAE=0.00074,RMSE=0.0009.

关键词： Nanofluids viscosity thermal conductivity machine learning predictive modeling

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A prioritization approach based on a cross-network model of SDGs 3

A prioritization approach based on a cross-network model of ...

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3rd International Symposium on Computer technology and information science, ISCTIS 2023

作者： Song, Qiuyue Wu, Rongxing Yunnan University of Finance and Economics Faculty of Finance Yunnan Province Kunming650221 China Kunming University of Science and Technology Faculty of Information Engineering and Automation Yunnan Province Kunming650500 China

ISBN: (纸本)9798350325386

To create a world of shared prosperity, the Sustainable Development Goals (SDGs) promote cooperation among all people. In order to better explore the influence relationship between SDGs, this paper appropriately discusses solutions from a network perspective. We modeled the interactions between multiple SDGs through network analysis. We selected 17 specific policy development goals based on the degree of sustainability achieved in Germany in recent years. Then we developed a first-order network model based on a cross-influence matrix and test the validity of the model. This study finds the priority of each objective and proposes the highest priority. © 2023 IEEE.

关键词： Sustainable development

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Power System Fault Diagnosis Based on Multi-Sensor Data Fusion for Large-Scale Railway Maintenance Equipment

Power System Fault Diagnosis Based on Multi-Sensor Data Fusi...

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2022 International Conference on Computer engineering and Artificial Intelligence, ICCEAI 2022

作者： Wang, H.R. Wang, Fan Li, Junming Zhu, Guifu Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming China Information Technology Construction Management Center Kunming University of Science and Technology Kunming China

ISBN: (数字)9781665468039

ISBN: (纸本)9781665468039

In order to solve the defects in the accuracy, reliability and applicability of the current tamper diesel engine fault diagnosis, this paper establishes the causes of symptoms and the corresponding sample sets, introduces the concepts of fuzzy logic and fuzzy neural network structure for the complexity and fuzziness of engine tampering, and applies them to the turbocharger tampering system. Finally, using Matlab simulation, the results show that the combination of neural network and fuzzy logic can provide a more detailed description of the fault phenomena compared with the commonly used neural network and fuzzy theory fault diagnosis methods, making up for the respective deficiencies of fuzzy theory and neural network. It has good application prospects in the field of fault diagnosis of large railroad maintenance equipment © 2022 IEEE.

关键词： Failure analysis

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Overview of traditional denoising and deep learning-based denoising 6

Overview of traditional denoising and deep learning-based de...

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6th International Conference on Mechatronics and Intelligent Robotics, ICMIR 2022

作者： Wen, Jian Shao, Jianfei Shao, Jianlong Pu, Hongfei Faculty of Information Engineering and Automation Kunming University of Science and Technology Yunnan Kunming650500 China

ISBN: (纸本)9781510656635

Image denoising is a classical problem in the current field of computer vision. The goal of the task of image denoising is to use techniques to preserve as much clear detail of the original image as possible when the image has external noise. The essence of the image denoising process is to reduce the noise in the digital image and to recover and reconstruct the original clear image. The reason for image noise is that during image transmission and acquisition, the integrity of the image cannot be guaranteed due to environmental, acquisition equipment, human and other factors, so the image will inevitably be damaged by different degrees of noise. In medical, military, and optoelectronics fields, there is an extremely high demand for image realism, so the task of image denoising becomes very important. In this paper, we will discuss a history of image denoising techniques and analyze the denoising methods into traditional denoising and deep learning based denoising. © 2022 SPIE.

关键词： Image denoising

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A novel protocol of RFID tag identification using a single mobile reader

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International Journal of information and Communication technology 2021年第4期19卷 423-431页

作者： Li, Xiaowu Li, Runxin Jia, Lianyin Ding, Jiaman You, Jinguo Fan, Hongbo Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650504 China

Classic RFID tag anti-collision protocols mainly aim at the identification of tags in small area. That is, all unidentified tags are located in the reader’s read-write region. When there is one or more tag outside the reader coverage area, multi-reader RFID system is an effective method of identifying all tags. However, the cost of multi-reader RFID system is much higher than that of a single reader system. There are many other tag identification scenes where tag distribution area is only slightly larger than a reader coverage area. For the scene, in the paper, we let the all tags, including outside the reader coverage area, have an opportunity to enter the reader coverage area by moving reader and be identified. The scene is called single mobile reader systems (SMRS) at the paper. However, SMRS cause the tag reappearance phenomenon (TRP), which leads to the multiple identification problem of tag (MIPT). TRP and MIPT make low the effective tag identification efficiency happen. In the paper, we propose an improved EPC C1G2 protocol, which can decrease MIPT effectively and increase tag identification efficiency. Copyright © 2021 Inderscience Enterprises Ltd.

关键词： Radio frequency identification (RFID)

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