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Stabilizing SiPM output with adaptive temperature compensation in portable real-time PCR devices

ISA Transactions 2025年 162卷 144-149页

作者： Li, Gui-Ping Ding, Wei Liang, Wen-Jing Shi, Yu Department of Computer Science and Technology Beijing Normal University-Hong Kong Baptist University United International College Zhuhai519087 China Faculty of Electrical Engineering and Automation Changshu Institute of Technology Changshu215500 China Hema Medical Instrument Co. Ltd Zhuhai519087 China

Real-time Polymerase Chain Reaction (PCR) technology is essential in clinical pathogen measurement due to its high sensitivity, specificity, and accuracy. Portable real-time PCR instruments, known for their quick response, mobility, and efficiency, are crucial for controlling emerging infectious diseases at the grassroots level. Silicon photomultipliers (SiPMs), with their high gain, sensitivity, low bias voltage, magnetic field insensitivity, and compactness, are widely used in various applications, including real-time PCR instruments. However, the gain of SiPM is temperature-dependent, which affects performance stability. In grassroots measurement environments, inadequate heat dissipation during equipment operation can alter SiPM working temperatures, impacting performance. To address this, we propose an innovative technique using a pair of Polymethyl Methacrylate(PMMA) polymer reference samples to stabilize SiPM output against temperature variations. This method effectively controls SiPM output fluctuations within 1%, even with temperature changes exceeding 10∘C, enhancing the stability, portability, and cost-effectiveness of fluorescence PCR instrument optical systems. © 2025

关键词： High gain Polymethyl Methacrylate Real-time PCR Silicon photo-multiplier Temperature compensation

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The Prediction of COVID-19 Pandemic Situation in Indonesia Using SVR and SIR Algorithm

The Prediction of COVID-19 Pandemic Situation in Indonesia U...

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International Conference on Information Technology, Information Systems and Electrical engineering (ICITISEE)

作者： Ainul Yaqin Majid Rahardi Ferian Fauzi Abdulloh Kusnawi Slamet Budiprayitno Siti Fatonah Faculty of Computer Science Universitas Amikom Yogyakarta Yogyakarta Indonesia Department of Electrical and Automation Engineering Vocational Faculty Institut Teknologi Sepuluh Nopember Surabaya Indonesia

The COVID-19 epidemic, which initially surfaced at the end of 2019, has since expanded to every corner of the globe and has profoundly impacted all facets of human existence. This case started to emerge in Indonesia at the end of February 2020, and until this point, there has been a spike in new patients. Researchers have run several models and projections for COVID-19 cases in Indonesia, but the results are not yet entirely reliable. Predictions produced at the national level must take into account these variations in patterns because this is likely related to the distinct patterns in each region. In this study, the prediction process will be conducted for cases of COVID-19 by using the SVR algorithm and mathematical models to predict reproduction numbers. SVR analysis to overcome the problem of nonlinearity of data in model formation. The modeling is done based on the SIR model, whose parameters are estimated based on the data. Testing result by using 3 kernels is different on each test, prediction of data cases and the level of mistake room are by using Kernel ’ RBF ‘ with a value of C = 1E3, and gamma = 0.1 with the value of MAPE and MSE respectively are 4.5% and 4.2.

关键词： COVID-19 Analytical models Sociology Prediction algorithms Mathematical models Data models Kernel

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Hybrid Water Quality Prediction with Graph Attention and Spatio-Temporal Fusion

Hybrid Water Quality Prediction with Graph Attention and Spa...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Lin, Yongze Qiao, Junfei Bi, Jing Yuan, Haitao Gao, Han Zhou, MengChu Beijing University of Technology Faculty of Information Technology Beijing100124 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Chinese Academy of Environmental Planning Beijing100012 China New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ07102 United States

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Spatio-temporal prediction has a wide range of applications in many fields, e.g., air pollution, weather forecasting, and traffic forecasting. Water quality prediction is also one of spatio-temporal prediction tasks. However, it faces the following challenges: 1) Water quality in river networks has complex spatial dependencies;2) There are complex nonlinear relations in water quality time series;and 3) It is difficult to realize long-term forecasting. To address these challenges, this work proposes a spatio-temporal prediction model called a Graph Attention-based Spatio-Temporal (GAST) neural network. GAST investigates spatial and temporal dependencies of water quality time series. First, we introduce a temporal attention mechanism to capture time series dependencies, which can effectively handle nonlinear relationships in time series. Second, we adopt a spatial attention mechanism to extract spatial dependencies of river networks and fuse temporal features of spatial nodes. Third, we adopt a temporal convolution residual mechanism based on the spatio-temporal fusion, which improves the accuracy of long-term series prediction. This work adopts two real-world datasets to evaluate the proposed GAST and experiments demonstrate that GAST outperforms several state-of-the-art methods in terms of prediction accuracy. © 2022 IEEE.

关键词： Time series

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Data-Driven DLT3 Federated Deep Reinforcement Learning for Secure and Efficient Autonomous Driving

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IEEE Transactions on Consumer Electronics 2025年

作者： Fei, Rong Li, Qianxi Wang, Kan Khan, Fazlullah Alturki, Ryan Lan, Dapeng Xi’an University of Technology School of Computer and Engineering Xi’an710000 China University of Nottingham Ningbo China School of Computer Science Faculty of Science and Engineering Ningbo315104 China Umm Al-Qura University College of Computing Department of Software Engineering Makkah21955 Saudi Arabia Chinese Academy of Sciences Shenyang Institute of Automation Shenyang110003 China

As autonomous vehicles (AVs) become increasingly widespread, the intelligent driving control and safety concerns have emerged. Recent advents in Internet of Things (IoTs) and 6G technologies have vastly boosted AVs’ sensing and communication capabilities, thereby enabling the high-speed and real-time data exchange. However, efficiently utilizing data while safeguarding the privacy remains challenges. Thus, we propose a federated learning (FL) framework with the privacy protection to facilitate the deep reinforcement learning (DRL) for longitudinal vehicle safety tracking control. First, the proposed framework enables the efficient information sharing and policy updates via encrypted policy gradient transmission. Then, the twin delayed deep deterministic policy gradient (TD3) method makes the velocity decision in the local model, while the dual long short-term memory (LSTM) network captures the temporal trajectory information. Finally, stacked denoising autoencoders (SDAE) is used to extract high-level environmental features, and the dual-LSTM-TD3 (DLT3)-SDAE model is introduced to enhance the policy decision efficiency and accuracy. Experimental results demonstrate that within the FL framework supported by homomorphic encryption, the DLT3-SDAE-based AV agent surpasses other DRL methods in terms of collision avoidance and average rewards, in the LAF environment. The safety, efficiency and comfort of the DLT3-SDAE AV agent are also evaluated and demonstrated. © 1975-2011 IEEE.

关键词： Deep reinforcement learning

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Discrete-time Formation Control With Attitude Alignment: A Geometric Approach under Ergodic Products

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IEEE Transactions on Control of Network Systems 2025年

作者： Li, Zhen Tang, Yang Zhang, Wenbing Fan, Yongqing Huang, Tingwen Xi-an University of Posts and Telecommunications School of Automation Xian710121 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Shanghai200237 China Yangzhou University Department of Mathematics Jiangsu225002 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

Assuming agents possess sensing capabilities and dynamics relative to their body coordinate frames, this paper addresses a displacement-based strategy for discrete-time formation control through attitude synchronization. Unlike the Eulerian approximation, the first challenge lies in developing discrete-time models that capture both position and attitude motions, thereby complementing existing continuous-time systems with a discretized version. Then, two leader-following control protocols are designed, incorporating a jointly-connected topology to relax the connectivity requirements. The analysis of these systems often relies on the Lyapunov function, the existence of which may be hard to guarantee. Consequently, geometric properties of several polytopes are explored under the dynamic topologies and time-varying parameters. By extending the ergodicity results to leader-following scenarios, these properties are characterized as positively invariant sets. This invariance, which is independent of the existence of the Lyapunov function or the solvability of its associated criteria, provides a beneficial tool for analyzing time-variant systems. Utilizing this invariance and some mathematical techniques, the desired formation shape can be achieved in the cases where the attitudes of the followers synchronize with the leader. Finally, a numerical simulation validates the results. © 2014 IEEE.

关键词： Lyapunov functions

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A Comprehensive Methodology of Field-Oriented Control Design With Parameter Variation Analysis for Interior Permanent Magnet Synchronous Machine Drives

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IEEE Access 2025年 13卷 89524-89541页

作者： Tiago Davi Curi Busarello Abdullah Bubshait Oruganti V. S. R. Varaprasad Abdulhakeem Alsaleem Marcelo Godoy Simões Department of Control Automation and Computation Engineering Federal University of Santa Catarina Florianopolis Brazil Department of Electrical Engineering College of Engineering King Faisal University Al Ahsa Saudi Arabia Smart Transportation Electrification and Energy Research (STEER) Group Department of Electrical Computer and Software Engineering Faculty of Engineering and Applied Science Ontario Tech University Oshawa ON Canada Department of Electrical Engineering College of Engineering Qassim University Buraydah Saudi Arabia School of Technology and Innovations University of Vaasa Vaasa Finland

This paper proposes a comprehensive methodology for Field-Oriented Control (FOC) with parameter variation analysis for Interior Permanent Magnet Synchronous Machines (IPMSM). The modeling approach for an IPMSM is first presented, followed by a step-by-step procedure for designing a vector-controlled strategy. The formulation is based on a dq-rotating reference frame aligned with the rotor shaft position. A key distinction of this methodology from traditional approaches is that the current controller is designed in the time domain based on desired time constants, while the speed control is formulated within a frequency response domain framework. The proposed hybrid approach enables accurate tuning of the Proportional-Integrator (PI) controllers for both current and speed control loops. Additionally, a parameter variation analysis is conducted to enhance the proposed methodology. The validity region for the design procedure is presented, ensuring that for any wide speed variation of the machine, loop gains are properly tuned. One of the main advantages of the proposed methodology is that it provides a fast, reliable, and accurate technique for implementing IPMSM drive systems. Results from a Controller Hardware-in-the-Loop (C-HIL) setup with an external microcontroller are presented. The comprehensive design approach is validated under two different IPMSM parameter sets, demonstrating its effectiveness.

关键词： PI control Stators Tuning Mathematical models Velocity control Rotors Vectors Stator windings Robustness Microcontrollers

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Multi-Domains Personalized Local Differential Privacy Frequency Estimation Mechanism for Utility Optimization

SSRN

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SSRN 2024年

作者： Li, Yunfei Fu, Xiaodong Liu, Li Ding, Jiaman Peng, Wei Jia, Lianyin Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Graduate School Yunnan University of Finance and Economics Kunming650221 China Yunnan Provincial Key Laboratory of Computer Technology Application Kunming University of Science and Technology Kunming650500 China

Local Differential Privacy (LDP) has garnered considerable attention in recent years because it does not rely on trusted third parties and has low interactivity and high operational efficiency. However, current LDP frequency estimation mechanisms aggregate data using different privacy budgets within the same data domain, overlooking the aggregation requirements across different data domains. This limits the potential for enhancing the data utility under fixed privacy budgets and meeting user preferences in multiple data domains and privacy budgets. To address this issue, we define a Multi-Domains Personalized Local Differential Privacy (MDPLDP) model that allows users to freely choose data domains and privacy budgets according to their privacy preferences. Furthermore, based on the MDPLDP model, two new frequency estimation mechanisms are proposed: MDPLDP-Generalized Randomized Response and MDPLDP-basic Randomized Aggregatable Privacy-Preserving Ordinal Response. These mechanisms support cross-domains data aggregation and optimize data utility by adjusting the data domains and increasing privacy budgets. Theoretical analysis reveals that these new mechanisms have lower estimation errors than the traditional LDP mechanisms. Experiments on real and synthetic datasets demonstrate that the proposed mechanisms effectively reduce estimation errors and enhance the utility of data-frequency estimation. © 2024, The Authors. All rights reserved.

关键词： Frequency estimation

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Potato: A Data-Oriented Programming 3D Simulator for Large-Scale Heterogeneous Swarm Robotics

arXiv

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arXiv 2023年

作者： Li, Jinjie Han, Liang Yu, Haoyang Wang, Zhaotian Yang, Pengzhi Yan, Ziwei Ren, Zhang The School of Automation Science and Electrical Engineering Beihang University Beijing100191 China The Sino-French Engineer School Beihang University Beijing100191 China The Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 CD Netherlands

nonlinear dynamic models is crucial for algorithms development for swarm robotics. However, existing platforms are mainly developed based on Object-Oriented Programming (OOP) and either use simple kinematic models to pursue a large number of simulating nodes or implement realistic dynamic models with limited simulating nodes. In this paper, we develop a simulator based on Data-Oriented Programming (DOP) that utilizes GPU parallel computing to achieve large-scale swarm robotic simulations. Specifically, we use a multi-process approach to simulate heterogeneous agents and leverage PyTorch with GPU to simulate homogeneous agents with a large number. We test our approach using a nonlinear quadrotor model and demonstrate that this DOP approach can maintain almost the same computational speed when quadrotors are less than 5,000. We also provide two examples to present the functionality of the platform. Copyright © 2023, The Authors. All rights reserved.

关键词： Dynamic models

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Microwave Filtering Sensor for Simultaneous Materials Characterization and Wireless Communication

Microwave Filtering Sensor for Simultaneous Materials Charac...

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IEEE SENSORS

作者： Zhuowei Zhang Kam-Weng Tam Gang Zhang Chi-Hou Chio Desen Li Xin Zhou Qiwei Chen Junxiao Liu Kong Ngai Cheng Teng Hon-Pan Sio Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macao SAR China School of Electrical and Automation Engineering Nanjing Normal University Nanjing China Macao Science Centre Macao SAR China Zhuhai Wujing Technology Co. Ltd Zhuhai China Laxen Technology Ltd Zhuhai China

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

In this paper, a dual functional component integrated with bandpass filter (BPF) and material sensing function is proposed, at the first time. By applying two dual mode ring resonators with defected ground structure, the dielectric properties of loaded materials under test (MUTs) can be detected based on the frequency drift of the transmission poles and zero, without affecting the bandpass filtering response for communication. To verify this design method, a demonstrated dual functional component integrated with bandpass filtering for 5GHz Wi-Fi channel and sensor for detecting the permittivity is implemented. Measured results are in good agreement with the simulated ones, indicating the feasibility of the proposed method.

关键词： Band-pass filters Wireless communication Filtering Resonant frequency Microwave communication Microwave theory and techniques Sensors Permittivity Microwave filters Wireless fidelity

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Overview of Hormonal Substances Used in Fish Reproduction 10

Overview of Hormonal Substances Used in Fish Reproduction

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10th E-Health and Bioengineering Conference, EHB 2022

作者： Nica, Aurelia Simionov, Ira-Adeline Antache, Alina Cristea, Dragos-Sebastian Petrea, Stefan-Mihai Cristea, Victor Food Science Food Engineering Biotechnology and Aquaculture Department Food Science and Engineering Faculty „Dunărea de Jos" University of Galati Domnească Street no. 47 Galați800008 Romania Faculty of Automation Computer Sciences Electronics and Electrical Engineering "Dunarea de Jos" University of Galati 111 Domneascǎ Street Galaţi800201 Romania Faculty of Economics and Business Administration "Dunarea de Jos" University of Galati 47 Domneascǎ Street Galaţi800201 Romania Applied Science Department Transboarding Faculty "Dunărea de Jos" University of Galaţi Galați800008 Romania

ISBN: (纸本)9781665485579

The process of fish breeding is extensively applied in fish farms and it is influenced by either environmental factors (in case of natural reproduction) and by the use of exogenous hormones (in case of artificial reproduction). Reproducing some species under controlled conditions without hormonal preparations is not possible. Many hormonal agents have been previously described in the scientific literature as beneficial in the fish breeding process. The effectiveness of these agents varies. This paper reviews some of the basic hormonal substances and describes the results of artificial reproduction. The most frequently encountered substances that give the best results are: Carp pituitary homogenate (CPH), Ovopel and Ovaprim. It can be concluded that in order to ensure the success of reproduction, the doses applied are particularly important, as well as the way of administration of the agent. © 2022 IEEE.

关键词： Fish

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