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SSRN 2024年

作者： Hu, Jingfang Xu, Hua Wu, Jianfeng Shen, Yu Mulchandani, Ashok Gao, Guowei Xie, Jianwei Beijing Key Laboratory of Sensor Beijing Information Science and Technology University Beijing100101 China Laboratory of Toxicant Analysis Academy of Military Medical Sciences Beijing100850 China Department of Chemical and Environmental Engineering University of California RiversideCA92521 United States Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100192 China

Botulinum neurotoxin A (BoNT/A), a lethal bacterial enzyme, is the most toxic biotoxin known to humans. Rapid and effective detection of active BoNT/A is highly significant for food safety and medical diagnosis. Herein, a new low-cost, rapid, portable and easy-to-use paper device was proposed and developed to ultrasensitively determine active BoNT/A. Gold nanoparticles (AuNPs)/graphdiyne (GDY) composite materials with high conductivity and good biocompatibility were synthesized on paper-based electrode to improve electrical conductivity and provide a specific recognition interface for SNAP-25 peptide immobilization. A two-step enzymatic amplification strategy was introduced into the sensing interface, which involved the first enzymatic reaction of target-triggered enzymatic cleavage of SNAP-25 peptide and the second enzymatic reaction of alkaline phosphatase (ALP)-induced enzymatic catalysis of silver deposition on AuNPs/GDY, followed by the recognition of BoNT/A via electrochemical stripping analysis of the deposited silver, resulting in an enhanced response and magnified more than 8-fold sensitivity of the biosensor. In addition, a rotary working electrode was designed and integrated into the paper device to avoid cross-contamination on auxiliary electrodes. The proposed lab-on-paper biosensor offers a quantitative detection of active BoNT/A with a linear range of 5～100 pg/mL and a limit of detection (LOD) of 1 pg/mL (S/N=3). As a demonstration, the biosensor was successfully applied to detect the active BoNT/A in various complex matrices, including bottled water, milk, and human serum, without any sample preconcentration or purification, showing great potential for the early diagnosis of active BoNT/A in low-cost, sensitive and reliable point-of-care (POC) devices. © 2024, The Authors. All rights reserved.

关键词： Gold nanoparticles

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Text classification method of Dongba classics based on catboost algorithm 8

Text classification method of Dongba classics based on catbo...

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8th International Symposium on Test Automation and Instrumentation, ISTAI 2020

作者： Zhang, Xue Wu, Guo X. Key laboratory of Modern Measurement and Control Technology Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781839535635

In view of the inheritance and protection of the excellent Dongba culture of Naxi nationality in Yunnan Province, the problem of automatic text classification is put forward in the field of artificial intelligence. Based on the large amount of text data obtained from Dongba classic collection of Lijiang Dongba Culture Research Institute, Dongba text data set was established and labeled;the Dongba text was classified according to the ceremony by a machine learning algorithm named catboost. The experimental results on six ritual categories of the final 300 datasets show that the classification accuracy of catboost algorithm is 87.5%, and the recall rate is 86.7%. The Dongba text data set is not perfect, meanwhile, the types of rituals and the number of texts in the corpus can be further *** study attempts to use catboost algorithm to solve the problem of text classification in Dongba classics. Experiments show that the algorithm is reasonable and effective, and has practical application value. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Machine learning

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Path optimization method of industrial robot-based research in bogie appearance inspection 8

Path optimization method of industrial robot-based research ...

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8th International Symposium on Test Automation and Instrumentation, ISTAI 2020

作者： Li, Guo D. Xu, Bao J. Wu, Guo X. Key laboratory of Modern Measurement and Control Technology Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781839535635

To solve the problem of robot path planning in bogie appearance inspection, the real situation of large tasks is simulated. In this paper, greedy algorithm[1] is used to simulate artificial path selection. Aiming at the problem of poor global search ability and easy to fall into local optimal solution, simulated annealing algorithm and improved A* ant colony algorithm are proposed. To verify the applicability of the algorithm, these three algorithms are used for 100 path points and 50 path points. Experiments show that the simulated annealing algorithm has improved in terms of computing speed, and the improved A* ant colony algorithm has advantages in search accuracy and stability. The greater the number of tasks, the more obvious the advantages of the model, and the higher the proportion of path shortening. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Simulated annealing

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The research of traffic cones detection based on Haar-like features and adaboost classification

The research of traffic cones detection based on Haar-like f...

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9th International Symposium on Test Automation & Instrumentation (ISTAI 2022)

作者： M. Xie Q. Su L. Wang Z. Zhang B. Ding X. Xu C. Wang Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology University Haidian District Beijing People's Republic of China

Road recognition plays an important role in the field of unmanned driving. As a common road traffic sign, traffic cones are widely used for indicating temporary roads under certain situations. This paper presents a method to identify traffic cones based on data collected by machine vision system. The real-time captured road image is firstly transformed from RGB color space to HSI color space, and then, the ROI (region of interest) of traffic cone target is extracted by Haar-like feature. Thirdly, four special weak classifiers with Haar-like features and a strong classifier which trained by AdaBoost algorithm are used for recognizing the traffic cones. In this experiment, a strong classifier which composes of 40 weak classifiers is developed, and 9298 positive and negative samples are used for training and calculating the weights of weak classifiers. The experimental results show that 93.4% traffic cones could be successfully detected whereas 6.6% are missing due to overlay in straight road section with long distances away. In addition, the cone detection time in one frame of road image is less than 50ms which indicates the system can meet the detection requirements of the temporary road at low speed.

关键词： computer vision feature extraction image classification image colour analysis learning (artificial intelligence) object detection road safety road traffic road vehicles roads robot vision traffic engineering computing

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Determination of hyperfine splittings and Landé gJ factors of 5s2S1/2 and 5p2P1/2,3/2 states of Cd+111,113 for microwave frequency standards

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Physical Review A 2022年第1期106卷 012821-012821页

作者： J. Z. Han R. Si H. R. Qin N. C. Xin Y. T. Chen S. N. Miao C. Y. Chen J. W. Zhang L. J. Wang State Key Laboratory of Precision Measurement Technology and Instruments Key Laboratory of Photon Measurement and Control Technology of Ministry of Education Department of Precision Instrument Tsinghua University Beijing 100084 China Shanghai EBIT Lab Key Laboratory of Nuclear Physics and Ion-Beam Application Institute of Modern Physics Department of Nuclear Science and Technology Fudan University Shanghai 200433 China Department of Physics Tsinghua University Beijing 100084 China

Regarding microwave frequency standards based on trapped ions, we report on the determination of the hyperfine splittings and the Landé gJ factors of Cd+111,113. The hyperfine splittings and Landé gJ factors of the 5s2S1/2 and 5p2P1/2,3/2 states of Cd+111,113 are calculated using the multiconfiguration Dirac-Hartree-Fock scheme. Furthermore, the hyperfine splittings of the 5p2P3/2 state of Cd+111,113 are derived based on the laser-induced fluorescence spectroscopy. The Cd+ ions are confined in a linear Paul trap and sympathetically cooled by laser-cooled Ca+ ions. The calculated values and the derived values are cross-checked, thereby guaranteeing the reliability of our results. The results provided in this paper can improve the signal-to-noise ratio of the clock transition and the accuracy of the second-order Zeeman shift correction, thus further improving the stability and accuracy of the microwave frequency standards based on trapped Cd+111,113 ions.

关键词： Atomic & molecular structure Atomic spectra Atomic, optical & lattice clocks Cooling & trapping Electron correlation calculations for atoms & ions Fine & hyperfine structure Optical pumping

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Research on Dynamic Rule Mining Method for Incremental Small Sample Experimental Data

Research on Dynamic Rule Mining Method for Incremental Small...

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International Conference on Electronics Information and Emergency Communication

作者： Weiguang Bai Jie Sun Yun Yang Beijing Key Laboratory of High-speed Transport Intelligent Diagnostic and Health Management Beijing Aerospace Measurement&Control Technology Co. Ltd Beijing China Shaanxi Qinchuan Intelligent Machine Tool Research Institute Co. Ltd Xi'an Shaanxi China

In terms of fault diagnosis and prediction, new equipment mainly has the characteristics of small data samples and increasing sample size. In the rulemaking process, there are problems such as incomplete data, insufficient rules support, low accuracy data and information completeness, the current method is difficult to automatically correct forward rules based on continuously accumulated data. There is a lack of basic models and algorithms for rule correction, This method establishes an initial rule library after modeling system faults based on knowledge and data fusion. When a system fault occurs, it will exhibit various abnormal phenomena, and the collection of different types of abnormal phenomena (i.e. fault phenomena) corresponds to typical faults.

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Coastal Wind Speed Retrieval From HY-2C Scatterometer Based On Light Gradient Boosting Model

Coastal Wind Speed Retrieval From HY-2C Scatterometer Based ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Biao Zhang Jingyi Liu Lanjie Zhang Xuehua Li Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China Key Laboratory of Microwave Remote Sensing National Space Science Center Chinese Academy of Sciences Beijing China

In this paper, the sea surface wind speed (SSWS) retrieval accuracy for HaiYang-2C (HY-2C) scatterometer in the coastal regions is evaluated. To improve coastal SSWS accuracy, we use the European Centre for Medium-range Weather Forecast Reanalysis 5th Generation (ECMWF ERA5) data as the reference output to establish the coastal multi-interval SSWS retrieval model based on the light gradient boosting model (LGBM). Compared with the ERA5 wind speed, the root mean square error (RMSE) of the LGBM-based model in the low, medium, and high wind speed ranges is 36.36%, 33.33%, and 34.52% lower than that of the HY-2C wind product, respectively. This paper also compares the SSWS retrieval results with the National Data Buoy Center buoy measurements. Compared to the HY-2C L2B wind product, the RMSE is reduced by 21.05%. This paper provides a dependable reference to coastal SSWS retrieval of HY-2C scatterometer observations.

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Structural reliability analysis based on improved parallel sampling algorithm

Structural reliability analysis based on improved parallel s...

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10th International Symposium on Test Automation & Instrumentation (ISTAI 2024)

作者： Yifan Yu Liyong Wang Ximing Zhang College of Mechanical & Energy Engineering Beijing University of Technology Beijing People's Republic of China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing People's Republic of China China North Vehicle Research Institute Beijing People's Republic of China

ISBN: (数字)9781837241910

Aiming at the problem of computational inefficiency of traditional reliability analysis methods when dealing with large-scale structural systems, this paper proposes a reliability analysis method that improves the parallel sample algorithm. The method adopts the Kriging model to fit the performance function and introduces the mean square error to evaluate the uncertainty of the sample points; In addition, the positional relationship between the sample points is taken into consideration to avoid overfitting the model; To improve the efficiency of the model fitting, the sample points are divided into multiple clusters using the Mini batch k-means clustering algorithm in parallel computation. Finally, it is verified by multiple random variable cases that the method can significantly improve the computational efficiency while guaranteeing the relative error compared with other reliability analysis methods.

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Coastal SEA Surface Salinity Retrieval Analysis from SMAP Mission using Machine Learning

Coastal SEA Surface Salinity Retrieval Analysis from SMAP Mi...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： YanFang Lv YiFan Zhang JingYi Liu LanJie Zhang Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China Key Laboratory of Microwave Remote Sensing National Space Science Center Chinese Academy of Sciences Beijing China

Sea surface salinity (SSS) plays an essential role in the study of global climate change. Especially, high accuracy coastal SSS is of great significance for marine aquaculture and other aspects. SMAP is a high resolution satellite equipped with radars and radiometers for measuring soil moisture, which can also achieve observations of SSS. Based on SMAP L2B V5.0 data, to improve the coastal SSS retrieval accuracy, this paper proposes a method for retrieving SSS in coastal regions using deep neural networks (DNN) and analyzes the impact of different variables on retrieving SSS. By comparing the retrieval results of DNN with HYCOM SSS and in situ SSS, the root mean square errors (RMSE) of DNN SSS were 0.36 psu and 0.45 psu, respectively. Compared to SMAP SSS products from physical retrieval algorithm, the RMSE of DNN SSS decreased by 1.38 psu and 1.23 psu, respectively. The results indicate that using DNN to retrieve SSS in coastal regions can achieve high accuracy.

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Motion Planning of Mobile Robot Based on Goal-orientated Hierarchical Smoothing Optimization JPS Algorithm

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Jiqiren/Robot 2023年第4期45卷 439-450页

作者： Wang, Liyong Ma, Shaobo Wang, Chao Ding, Bingchao Li, Boxiong Wang, Haodong Su, Qinghua Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology University Beijing100192 China

Due to lack of direction guidance in the path search process of JPS (jump point search) algorithm, there are many redundant points, turning points and uneven paths on the planned path. Therefore, a GHSO-JPS (goal-oriented hierarchical smoothing optimization JPS) algorithm is proposed. Besides that, the multi-segment polynomial method and the collision penalty algorithm based on repulsive potential field are applied to trajectory optimization. By the attractive potential field, the search is focused on the goal direction, and irrelevant jump points in the search are reduced. Then, a hierarchical smoothing optimization strategy is adopted to eliminate redundant points and turning points in the path. Besides that, both the path point amount and the path length are reduced while improving the path smoothness. Finally, the multi-segment polynomial method is used to optimize the trajectory, and the penalty function against trajectory collision based on repulsive potential field is built to improve the trajectory safety. The real vehicle experiments are executed in the areas of laboratory and university, to analyze the proposed algorithm and compare with JPS, A∗, RRT (rapidly-exploring random tree) algorithms. As the result, the proposed alogrithm shows the best performances among the 4 algorithms. Compared with the traditional JPS algorithm, the search time of the proposed algorithm is reduced by 41.6%, the amount of jump points is reduced by 55.5%, the path length is reduced by 3.22 m, and number of path points and total turning angle are reduced by 89.8% and 81.8% respectively, in the university area. Compared with A∗ and RRT algorithms, the planning time of the proposed algorithm is reduced by 70.4% and 93.7% respectively, and the total turning angle of the planned optimal path is reduced by 90.3% and 97.1% respectively. In conclusion, the proposed algorithm is of a better path planning performance, a higher efficiency and a better ability of trajectory optimization th

关键词： Motion planning

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