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IEEE Instrumentation and Measurement technology Conference

作者： Valerio Brunacci Alessio De Angelis Dave Zachariah Department of Engineering University of Perugia Perugia Italy Department of Information Technology Division of Systems and Control Uppsala University Uppsala Sweden

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

Robust localization, which is the accurate measurement of the position of a user or device in the presence of obstructions or challenging environments, is a fundamental building block for numerous applications. The standard positioning methods and technologies do not provide satisfactory measurement accuracy in such challenging environments. Therefore, in this paper, a robust localization method is investigated and characterized experimentally. The robust method is capable of estimating the position of a mobile node based on distance measurements with respect to known-position anchors. The method is characterized by means of experiments using the ultra wide band ranging technology. Experimental results in a non line of sight (NLOS) scenario show that the robust localization method may reduce the error by a factor of 4 with respect to the standard method, i.e. the nonlinear least squares. In fact, the robust method results in a median error of approximately 5 cm, whereas the standard method results in a median positioning error of approximately 20 cm.

关键词： Location awareness Accuracy Position measurement Distance measurement Mobile nodes Instrumentation and measurement Nonlinear optics

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Event-Triggered SMC for Networked Markov Jumping Systems With Channel Fading and Applications: Genetic Algorithm

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IEEE Transactions on Cybernetics 2023年第10期53卷 6503-6515页

作者： Qi, Wenhai Zhang, Ning Zong, Guangdeng Su, Shun-Feng Yan, Huaicheng Yeh, Ruey-Huei Qufu Normal University School of Engineering Rizhao276826 China Chengdu University School of Information Science and Engineering Chengdu610106 China Tiangong University School of Control Science and Engineering Tianjin300387 China National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106 Taiwan East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process of Ministry of Education Shanghai200237 China National Taiwan University of Science and Technology Department of Industrial Management Taipei106 Taiwan

The event-triggered sliding-mode control (SMC) for discrete-time networked Markov jumping systems (MJSs) with channel fading is investigated by means of a genetic algorithm. In order to reduce resource consumption in the transmission process, an event-triggered protocol is adopted for networked MJSs. A key feature is that the signal transmission is inevitably affected by fading phenomenon due to delay, random noise, and amplitude attenuation in a networked environment. With the aid of a common sliding surface, an event-triggered SMC law is designed by adjusting the system network mode. Under the framework of stochastic Lyapunov stability, sufficient conditions are constructed to ensure the mean-square stability of the closed-loop networked MJSs, and the sliding region is reached around the specified sliding surface. Moreover, based on the iteration optimizing accessibility of objective function, an effective SMC approach under genetic algorithm is proposed to minimize the convergence region around the sliding surface. Finally, the effectiveness of the proposed method is proved by the F-404 aircraft model. © 2013 IEEE.

关键词： Markov processes

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Micro-Spatial Attention with Sparse Constraint for Self-Supervised Learning for Oleaginous Yeast Image Representation

Micro-Spatial Attention with Sparse Constraint for Self-Supe...

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IEEE Visual Communications and Image Processing (VCIP)

作者： Kazuma Ohtomo Yukina Kitahara Ryosuke Harakawa Akihiro Nakamura Yosuke Shida Wataru Ogasawara Masahiro Iwahashi Department of Information Science and Control Engineering Nagaoka University of Technology Department of Science of Technology Innovation Nagaoka University of Technology Department of Electrical Electronics and Information Engineering Nagaoka University of Technology Department of Bioengineering Nagaoka University of Technology

Feature representation of oleaginous yeast images is essential for non-invasively observing their cultivation status. However, conventional methods are difficult to capture the visual characteristics of oleaginous yeasts at the extremely local spatial regions. To tackle this problem, this paper proposes micro-spatial attention with sparse constraints for self-supervised learning. Specifically, we newly design a micro-spatial attention module to focus on the extremely local spatial regions for feature representation. Unlike the existing spatial attention module, which requires the guide information (e.g., labels and textual queries) to focus on specific regions, our proposed module employs a sparse constraint. By combining the sparse constraint with self-supervised learning, we can automatically focus on essential regions, which appear in extremely local regions. This improves the feature representation power for oleaginous yeast images with micro-spatial contexts. Experiments on real Lipomyces starkeyi datasets, a specific type of oleaginous yeasts, confirm the superiority of our method. Moreover, our method realized clustering of oleaginous yeast images, enabling us to non-invasively observe the cultivation trends over time.

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Robust Path Loss Map Construction based on LDFF-Net 43

Robust Path Loss Map Construction based on LDFF-Net

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43rd Chinese control Conference, CCC 2024

作者： Du, Wenhao Jin, Jian Gong, Wei Li, Li Jiao, Zhenzhen China Academy of Information and Communications Technology Beijing China Tongji University The Department of Control Science and Engineering Shanghai China Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Shanghai China Beijing Teleinfo Technology Co. Ltd. CAICT iF-Labs Beijing China

ISBN: (纸本)9789887581581

When transmitter characteristics are unknown, path loss inference model depend on electromagnetic signal samples to deduce signal propagation characteristics. Due to spatial discontinuities in sampling data, these models require advanced inferential techniques to address missing data and enhance accuracy, highlighting existing methods' need for improved precision in electromagnetic mapping. In response to the aforementioned requirement, this paper proposes a deep learning framework named LDFF-Net to generate continuous path loss values in geographic space, thereby creating path loss maps. This framework is characterized by a lightweight feature fusion strategy, a multi-level autoencoder structure, and a progressively enhanced dilated convolution structure. It learns the propagation characteristics of electromagnetic signals through measured electromagnetic data and the distribution of urban buildings. Experiments conducted on open-source datasets have demonstrated that this model achieves an accuracy that is 10 % higher than the most advanced methods in various scenarios and experimental setups, while also exhibiting superior robustness. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Lightweight Feature Fusion Strategy Multi-Level Autoencoder Path Loss Map

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Unlocking nitrogen management potential via large-scale farming for air quality and substantial co-benefits

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National Science Review 2024年第10期11卷 212-222页

作者： Baojie Li Hong Liao Ke Li Ye Wang Lin Zhang Yixin Guo Lei Liu Jingyi Li Jianbing Jin Yang Yang Cheng Gong Teng Wang Weishou Shen Pinya Wang Ruijun Dang Kaihua Liao Qing Zhu Daniel J.Jacob Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control School of Environmental Science and Engineering Nanjing University of Information Science and Technology Laboratory for Climate and Ocean-Atmosphere Studies Department of Atmospheric and Oceanic Sciences School of Physics Peking University Earth Ocean and Atmospheric Sciences Thrust Function Hub Hong Kong University of Science and Technology (Guangzhou) College of Earth and Environmental Sciences Lanzhou University Department of Biogeochemical Signals Max Planck Institute for Biogeochemistry College of Oceanography Hohai University John A.Paulson School of Engineering and Applied Sciences Harvard University Key Laboratory of Watershed Geographic Sciences Nanjing Institute of Geography and Limnology Chinese Academy of Sciences

China's sustained air quality improvement is hindered by unregulated ammonia（NH3） emissions from inefficient nitrogen management in smallholder farming. Although the Chinese government is promoting a policy shift to large-scale farming, the benefits of this, when integrated with nitrogen management, remain unclear. Here we fill this gap using an integrated assessment, by combining geostatistical analysis,high-resolution emission inventories, farm surveys and air quality modeling. Smallholder-dominated farming allows only 13%–31% NH3reduction, leading to limited PM2.5decreases nationally due to non-linear PM2.5chemistry. Conversely, large-scale farming would double nitrogen management adoption rates, increasing NH3reduction potential to 48%–58% and decreasing PM2.5by 9.4–14.0 μg·m-3in polluted regions. The estimated PM2.5reduction is conservative due to localized NH3-rich conditions under large-scale livestock farming. This strategy could prevent over 300 000 premature deaths and achieve a net benefit of US $68.4–86.8 billion annually, unlocking immense benefits for air quality and agricultural sustainability.

关键词： nitrogen management large-scale farming air quality ammonia emission

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UKF-Based Multi-sensor Data Processing Algorithm for SLAM 9

UKF-Based Multi-sensor Data Processing Algorithm for SLAM

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9th International Conference on control Science and Systems engineering, ICCSSE 2023

作者： Xu, Kun Zhang, Boheng Li, Jiangang Wang, Guizhong Sun, Mingjian School of Information Science and Engineering Harbin Institute of Technology Weihai China Harbin Institute of Technology Department of Control Science and Engineering Harbin China Co. Ltd. Shenzhen China Hebei Key Laboratory of Grid Advanced Measurement Monitor Jinyanhagong Industrial Technology Research Institute Zhangjiakou China

ISBN: (纸本)9798350339055

Simultaneous localization and mapping (SLAM) algorithm is widely used in unmanned and robotic applications. SLAM usually uses sensor data, which are from the LiDAR, the inertial measurement unit (IMU) and the wheeled odometry, to build maps of the surrounding environment. However, the motion distortion of LiDAR data and the error accumulation of wheeled odometry can affect the accuracy of the front-end odometry of the SLAM algorithm, which can lead to serious errors in the maps created. Therefore, in order to solve the problem of poor map construction results of SLAM algorithm due to various types of sensor errors. we propose the traceless Kalman filtering based (UKF-based) multi-sensor data processing algorithm. Firstly, the proposed algorithm uses the UKF to fuse IMU and wheeled odometry data to reduce the cumulative error of wheeled odometry. And then the algorithm uses IMU and corrected wheeled odometry data and combines with the motion states of the robot to solve the motion distortion problem of LiDAR data. Finally, we verified the effectiveness of the proposed algorithm for wheeled odometry data correction in Gazebo simulation environment and real environment experiments, and compared the mapping effectiveness of SLAM by using the original data and the data processed by our algorithm. The experimental results show that the map construction effect of SLAM algorithm is significantly improved when using the sensor data processed by the algorithm. Experimental validation on the robot shows that the proposed algorithm has universal applicability and good compatibility. © 2023 IEEE.

关键词： Sensor data fusion

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Polarization dependences of the laser in 4H-SiC wafer slicing

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Optics Express 2025年第10期33卷 20682-20698页

作者： Sun, Mengping Zhao, Shusen Du, Jiabao Han, Shifei Jiang, Lu Lin, Xuechun Wang, Xubao Laboratory of All-Solid-State Light Sources Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China School of Physics and Optoelectronic Engineering Beijing University of Technology Beijing100124 China Engineering Technology Research Center of All-Solid-State Lasers Advanced Manufacturing Beijing100083 China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing101407 China State Key Laboratory of Precision Space-Time Information Sensing Technology Beijing100084 China Key Laboratory of Photonic Control Technology Tsinghua University Ministry of Education Beijing100084 China Department of Precision Instrument Tsinghua University Beijing100084 China

This study focuses on the influence of the polarization of incident light in the laser slicing of 4H-SiC wafers. The structure of longitudinal damage within the material after laser modification was measured and analyzed. The impact of laser pulse energy on this structure was studied. Differences in longitudinal damage under different polarization states were compared. In addition, the effects of laser polarization on the modification of line width and lateral crack propagation were investigated. A vector diffraction model was established to analyze the propagation characteristics of beams with different polarization states during focusing. The results indicate that a linearly polarized beam perpendicular to the scanning direction offers superior modification efficacy compared to other directions of linear polarization and circular polarization. Azimuthally and radially polarized beams substantially decrease the length of longitudinal damage and reduce the difficulty of delamination. Compared to the linearly polarized beam perpendicular to the scanning direction, the azimuthally polarized beam reduces the longitudinal damage length by 49.3% and the delamination stress by 47.0%. In comparison, the radially polarized beam reduces the longitudinal damage length by 39.4% and the delamination stress by 53.8%. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Circular polarization

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Multi-dimensional Quantile Regression Using Polynomial Function Fitting for Insulin Sensitivity Forecasting

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IFAC-PapersOnLine 2024年第24期58卷 327-331页

作者： Bálint Szabó Petra Pintér Ákos Antal Ákos Szlávecz J. Geoffrey Chase Balázs Benyó Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Hungary Department of Oral Diagnostics Faculty of Dentistry Semmelweis University Hungary University of Canterbury Christchurch New Zealand

A significant portion of patients in the intensive care unit experience hyperglycemia, meaning abnormally high blood sugar levels. Prolonged hyperglycemia poses numerous risks, leading to organ damage in the medium-term and potentially life-threatening conditions. Therefore, insulin dosing is essential to regulate the blood sugar levels of hyperglycemic patients. The STAR protocol is an insulin dosing support, a so-called tight glycemic control protocol that uses insulin sensitivity among the patient's physiological parameters to characterize their current state. Estimating the patient's future SI is crucial for determining optimal treatment. Various methods exist for this estimation, and different metrics are available for evaluating these methods. The challenge in the estimation task is to determine not the expected value of future SI but its 90% confidence interval, which is necessary for implementing clinical protocols. The research presented in the article developed SI estimation methods using quantile regression, polynomial fitting, and neural network-based approaches. Multiple previous insulin sensitivity values were used as input parameters to improve prediction accuracy.

关键词： Five to ten keywords preferably chosen from the IFAC keyword list

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3D bioprinting of in vitro porous hepatoma models:establishment,evaluation,and anticancer drug testing

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Bio-Design and Manufacturing 2024年第2期7卷 137-152页

作者： Xiaoyuan Wang Zixian Liu Qianqian Duan Boye Zhang Yanyan Cao Zhizhong Shen Meng Li Yanfeng Xi Jianming Wang Shengbo Sang Shanxi Key Laboratory of Micro Nano Sensors and Artificial Intelligence Perception College of Electronic Information and Optical EngineeringTaiyuan University of TechnologyTaiyuan 030024China Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan 030024China Shanxi Institute of 6D Artificial Intelligence Biomedical Science Taiyuan 030031China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan 030024China Department of Pathology Shanxi Provincial Cancer HospitalTaiyuan 030024China General Hospital of Taiyuan Iron and Steel Company Taiyuan 030809China

Traditional tumor models do not tend to accurately simulate tumor growth in vitro or enable personalized treatment and are particularly unable to discover more beneficial targeted *** address this,this study describes the use of threedimensional(3D)bioprinting technology to construct a 3D model with human hepatocarcinoma SMMC-7721 cells(3DP-7721)by combining gelatin methacrylate(GelMA)and poly(ethylene oxide)(PEO)as two immiscible aqueous phases to form a bioink and innovatively applying fluorescent carbon quantum dots for long-term tracking of *** GelMA(10%,mass fraction)and PEO(1.6%,mass fraction)hydrogel with 3:1 volume ratio offered distinct pore-forming characteristics,satisfactorymechanical properties,and biocompatibility for the creation of the 3DP-7721 *** analysis and quantitative real-time fluorescence polymerase chain reaction(PCR)were used to evaluate the biological properties of the *** with the two-dimensional culture cell model(2D-7721)and the 3D mixed culture cell model(3DM-7721),3DP-7721 significantly improved the proliferation of cells and expression of tumor-related proteins and ***,we evaluated the differences between the three culture models and the effectiveness of antitumor drugs in the three models and discovered that the efficacy of antitumor drugs varied because of significant differences in resistance proteins and genes between the three *** addition,the comparison of tumor formation in the three models found that the cells cultured by the 3DP-7721 model had strong tumorigenicity in nude *** evaluation of the levels of biochemical indicators related to the formation of solid tumors showed that the 3DP-7721 model group exhibited pathological characteristics of malignant tumors,the generated solid tumors were similar to actual tumors,and the deterioration was *** research therefore acts as a foundation for the application of 3DP-7721 models in drug devel

关键词： 3D bioprinting Hepatoma tumor models Drug screening Antitumor drug development

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Synthesis of TiO_(2) Nanospikes for Dual Antibacterial Activity

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Biomedical and Environmental Sciences 2023年第10期36卷 983-986页

作者： LI Ze Ping CHEN Zhi Yuan YANG Ming Yan YI Wei Song School of Electronic and Information Engineering Hubei University of Science and TechnologyXianning 437100HubeiChina Key Laboratory of Optoelectronic Information and Intelligent Control Hubei University of Science and TechnologyXianning 437100HubeiChina School of Nuclear Technology and Chemistry&Biology Hubei University of Science and TechnologyXianning 437100HubeiChina Department of Rehabilitation Xianning Hospital of Traditional Chinese MedicineXianning 437100HubeiChina College of Science Huazhong Agricultural UniversityWuhan 430070HubeiChina

Bacterial infections on medical and public surfaces have caused considerable harm to human life and have gained widespread *** surface coating strategies,including the use of antibiotics,metal ions,quaternary ammonium... 详细信息

关键词： gained coating quaternary

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