138 results on '"Changbin Yu"'
Search Results
2. MRMPro: a web-based tool to improve the speed of manual calibration for multiple reaction monitoring data analysis by mass spectrometry
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Ruimin Wang, Hengxuan Jiang, Miaoshan Lu, Junjie Tong, Shaowei An, Jinyin Wang, and Changbin Yu
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MRMPro ,MRM ,Mass spectrometry ,Batch inspection ,Web service ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Biology (General) ,QH301-705.5 - Abstract
Abstract Background As a gold-standard quantitative technique based on mass spectrometry, multiple reaction monitoring (MRM) has been widely used in proteomics and metabolomics. In the analysis of MRM data, as no peak picking algorithm can achieve perfect accuracy, manual inspection is necessary to correct the errors. In large cohort analysis scenarios, the time required for manual inspection is often considerable. Apart from the commercial software that comes with mass spectrometers, the open-source and free software Skyline is the most popular software for quantitative omics. However, this software is not optimized for manual inspection of hundreds of samples, the interactive experience also needs to be improved. Results Here we introduce MRMPro, a web-based MRM data analysis platform for efficient manual inspection. MRMPro supports data analysis of MRM and schedule MRM data acquired by mass spectrometers of mainstream vendors. With the goal of improving the speed of manual inspection, we implemented a collaborative review system based on cloud architecture, allowing multiple users to review through browsers. To reduce bandwidth usage and improve data retrieval speed, we proposed a MRM data compression algorithm, which reduced data volume by more than 60% and 80% respectively compared to vendor and mzML format. To improve the efficiency of manual inspection, we proposed a retention time drift estimation algorithm based on similarity of chromatograms. The estimated retention time drifts were then used for peak alignment and automatic EIC grouping. Compared with Skyline, MRMPro has higher quantification accuracy and better manual inspection support. Conclusions In this study, we proposed MRMPro to improve the usability of manual calibration for MRM data analysis. MRMPro is free for non-commercial use. Researchers can access MRMPro through http://mrmpro.csibio.com/ . All major mass spectrometry formats (wiff, raw, mzML, etc.) can be analyzed on the platform. The final identification results can be exported to a common.xlsx format for subsequent analysis.
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- 2024
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3. Injectiondesign: web service of plate design with optimized stratified block randomization for modern GC/LC-MS-based sample preparation
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Miaoshan Lu, Hengxuan Jiang, Ruimin Wang, Shaowei An, Jiawei Wang, and Changbin Yu
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InjectionDesign ,Plate design ,Mass spectrometry ,Block randomization ,Stratified balancing ,Metabolomics ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Biology (General) ,QH301-705.5 - Abstract
Abstract Background Plate design is a necessary and time-consuming operation for GC/LC-MS-based sample preparation. The implementation of the inter-batch balancing algorithm and the intra-batch randomization algorithm can have a significant impact on the final results. For researchers without programming skills, a stable and efficient online service for plate design is necessary. Results Here we describe InjectionDesign, a free online plate design service focused on GC/LC-MS-based multi-omics experiment design. It offers the ability to separate the position design from the sequence design, making the output more compatible with the requirements of a modern mass spectrometer-based laboratory. In addition, it has implemented an optimized block randomization algorithm, which can be better applied to sample stratification with block randomization for an unbalanced distribution. It is easy to use, with built-in support for common instrument models and quick export to a worksheet. Conclusions InjectionDesign is an open-source project based on Java. Researchers can get the source code for the project from Github: https://github.com/CSi-Studio/InjectionDesign . A free web service is also provided: http://www.injection.design .
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- 2023
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4. G-Aligner: a graph-based feature alignment method for untargeted LC–MS-based metabolomics
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Ruimin Wang, Miaoshan Lu, Shaowei An, Jinyin Wang, and Changbin Yu
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LC–MS ,Feature alignment ,Multidimensional assignment problem ,Combinatorial optimization ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Biology (General) ,QH301-705.5 - Abstract
Abstract Background Liquid chromatography–mass spectrometry is widely used in untargeted metabolomics for composition profiling. In multi-run analysis scenarios, features of each run are aligned into consensus features by feature alignment algorithms to observe the intensity variations across runs. However, most of the existing feature alignment methods focus more on accurate retention time correction, while underestimating the importance of feature matching. None of the existing methods can comprehensively consider feature correspondences among all runs and achieve optimal matching. Results To comprehensively analyze feature correspondences among runs, we propose G-Aligner, a graph-based feature alignment method for untargeted LC–MS data. In the feature matching stage, G-Aligner treats features and potential correspondences as nodes and edges in a multipartite graph, considers the multi-run feature matching problem an unbalanced multidimensional assignment problem, and provides three combinatorial optimization algorithms to find optimal matching solutions. In comparison with the feature alignment methods in OpenMS, MZmine2 and XCMS on three public metabolomics benchmark datasets, G-Aligner achieved the best feature alignment performance on all the three datasets with up to 9.8% and 26.6% increase in accurately aligned features and analytes, and helped all comparison software obtain more accurate results on their self-extracted features by integrating G-Aligner to their analysis workflow. G-Aligner is open-source and freely available at https://github.com/CSi-Studio/G-Aligner under a permissive license. Benchmark datasets, manual annotation results, evaluation methods and results are available at https://doi.org/10.5281/zenodo.8313034 Conclusions In this study, we proposed G-Aligner to improve feature matching accuracy for untargeted metabolomics LC–MS data. G-Aligner comprehensively considered potential feature correspondences between all runs, converting the feature matching problem as a multidimensional assignment problem (MAP). In evaluations on three public metabolomics benchmark datasets, G-Aligner achieved the highest alignment accuracy on manual annotated and popular software extracted features, proving the effectiveness and robustness of the algorithm.
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- 2023
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5. Column storage enables edge computation of biological big data on 5G network
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Miaoshan Lu, Junjie Tong, Weidong Fang, Jinyin Wang, Shaowei An, Ruimin Wang, Hengxuan Jiang, and Changbin Yu
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column storage ,edge computing ,mass spectrum ,aird-slice ,data compression ,Biotechnology ,TP248.13-248.65 ,Mathematics ,QA1-939 - Abstract
With the continuous improvement of biological detection technology, the scale of biological data is also increasing, which overloads the central-computing server. The use of edge computing in 5G networks can provide higher processing performance for large biological data analysis, reduce bandwidth consumption and improve data security. Appropriate data compression and reading strategy becomes the key technology to implement edge computing. We introduce the column storage strategy into mass spectrum data so that part of the analysis scenario can be completed by edge computing. Data produced by mass spectrometry is a typical biological big data based. A blood sample analysed by mass spectrometry can produce a 10 gigabytes digital file. By introducing the column storage strategy and combining the related prior knowledge of mass spectrometry, the structure of the mass spectrum data is reorganized, and the result file is effectively compressed. Data can be processed immediately near the scientific instrument, reducing the bandwidth requirements and the pressure of the central server. Here, we present Aird-Slice, a mass spectrum data format using the column storage strategy. Aird-Slice reduces volume by 48% compared to vendor files and speeds up the critical computational step of ion chromatography extraction by an average of 116 times over the test dataset. Aird-Slice provides the ability to analyze biological data using an edge computing architecture on 5G networks.
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- 2023
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6. Effects of calcium glycerophosphate concentration on micro-arc oxidation coating of Mg alloy
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Wenshuo Xu, Zhou Li, Hongwei Wang, Huancai Li, Chuanzhong Chen, Xuchang Liu, Mingjie Kuang, Jinhe Dou, and Changbin Yu
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Magnesium alloys ,Micro-arc oxidation ,CaP ,Coating ,Bioactivity ,Mining engineering. Metallurgy ,TN1-997 - Abstract
Due to its good biocompatibility and compatible hardness with human bones, magnesium (Mg) alloy is considered as a promising material for bone nails and implants. However, Mg and its alloys are characteristics of active chemical properties and high corrosion rate, which is detrimental to the recovery of patients implanted with Mg alloy bone scaffold. In the present work, to retard the corrosion of the Mg alloy, calcium glycerophosphate (C3H7CaO6P•H2O) was added in the electrolyte to form the micro-arc oxidation (MAO) coatings. Various experimental techniques such as XRD, SEM and EDS have been used to characterize the surface morphology and phase composition of MAO coatings. MAO coatings of different CaP content were studied to explore the synergetic effect between the biocompatibility and corrosive properties by means of electrochemical measurements, hemolysis and pyrogen test. The results showed that higher CaP content can improve the biocompatibility and corrosion resistance while decelerating the hemolysis rate.
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- 2023
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7. StackZDPD: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio
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Jinyin Wang, Miaoshan Lu, Ruiming Wang, Shaowei An, Cong Xie, and Changbin Yu
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Medicine ,Science - Abstract
Abstract As the pervasive, standardized format for interchange and deposition of raw mass spectrometry (MS) proteomics and metabolomics data, text-based mzML is inefficiently utilized on various analysis platforms due to its sheer volume of samples and limited read/write speed. Most research on compression algorithms rarely provides flexible random file reading scheme. Database-developed solution guarantees the efficiency of random file reading, but nevertheless the efforts in compression and third-party software support are insufficient. Under the premise of ensuring the efficiency of decompression, we propose an encoding scheme “Stack-ZDPD” that is optimized for storage of raw MS data, designed for the format “Aird”, a computation-oriented format with fast accessing and decoding time, where the core compression algorithm is “ZDPD”. Stack-ZDPD reduces the volume of data stored in mzML format by around 80% or more, depending on the data acquisition pattern, and the compression ratio is approximately 30% compared to ZDPD for data generated using Time of Flight technology. Our approach is available on AirdPro, for file conversion and the Java-API Aird-SDK, for data parsing.
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- 2022
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8. Aird: a computation-oriented mass spectrometry data format enables a higher compression ratio and less decoding time
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Miaoshan Lu, Shaowei An, Ruimin Wang, Jinyin Wang, and Changbin Yu
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Mass spectrometry ,Aird ,Compressor ,ZDPD ,DIA ,DDA ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Biology (General) ,QH301-705.5 - Abstract
Abstract Background With the precision of the mass spectrometry (MS) going higher, the MS file size increases rapidly. Beyond the widely-used open format mzML, near-lossless or lossless compression algorithms and formats emerged in scenarios with different precision requirements. The data precision is often related to the instrument and subsequent processing algorithms. Unlike storage-oriented formats, which focus more on lossless compression rate, computation-oriented formats concentrate as much on decoding speed as the compression rate. Results Here we introduce “Aird”, an opensource and computation-oriented format with controllable precision, flexible indexing strategies, and high compression rate. Aird provides a novel compressor called Zlib-Diff-PforDelta (ZDPD) for m/z data. Compared with Zlib only, m/z data size is about 55% lower in Aird average. With the high-speed decoding and encoding performance of the single instruction multiple data technology used in the ZDPD, Aird merely takes 33% decoding time compared with Zlib. We have downloaded seven datasets from ProteomeXchange and Metabolights. They are from different SCIEX, Thermo, and Agilent instruments. Then we convert the raw data into mzML, mgf, and mz5 file formats by MSConvert and compare them with Aird format. Aird uses JavaScript Object Notation for metadata storage. Aird-SDK is written in Java, and AirdPro is a GUI client for vendor file converting written in C#. They are freely available at https://github.com/CSi-Studio/Aird-SDK and https://github.com/CSi-Studio/AirdPro . Conclusions With the innovation of MS acquisition mode, MS data characteristics are also constantly changing. New data features can bring more effective compression methods and new index modes to achieve high search performance. The MS data storage mode will also become professional and customized. ZDPD uses multiple MS digital features, and researchers also can use it in other formats like mzML. Aird is designed to become a computing-oriented data format with high scalability, compression rate, and fast decoding speed.
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- 2022
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9. Spatial Distribution Characteristics and Influencing Factors on the Retail Industry in the Central Urban Area of Lanzhou City at the Scale of Daily Living Circles
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Chenyu Lu, Changbin Yu, Yu Xin, and Wendi Zhang
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retail industry ,spatial distribution ,influencing factors ,daily living circles ,Lanzhou ,Geography (General) ,G1-922 - Abstract
Using a people-centered approach to new urbanization, China has committed to building high-quality living environments through improving urban livability and promoting a stronger sense of belonging among residents. Retail stores serve as one of the most immediate and accessible destinations for residents’ consumption, and their spatial configuration has a direct impact on residents’ satisfaction and happiness in their daily lives. In this context, for the present study we selected the central urban area of Lanzhou City as the case study area. Based on POI data and using the daily life circle as the basic unit, we applied methods such as kernel density analysis, hotspot analysis, and the Shannon–Weaver index to analyze spatial distribution patterns of the retail industry. Furthermore, we applied Geodetector to analyze the impacts of four factors that are closely related to the retail industry: economic level, convenience level, market demand, and location. The conclusions are as follows: In the central urban area of Lanzhou, the retail industry exhibits a belt distribution pattern along the Yellow River. The density of distribution gradually decreases from the city center toward the outskirts, forming four prominent agglomeration centers. Overall, within the central urban area of Lanzhou, the spatial distribution of the retail industry at the scale of daily living circles shows that only a small proportion of the industry demonstrates noticeable clustering effects. In terms of spatial patterns, the retail industry at the scale of the daily living circles demonstrates similar characteristics in terms of diversity and agglomeration distribution. It exhibits a decreasing trend from the urban core toward the peripheral areas. The agglomeration distribution pattern of the retail industry in the central urban area of Lanzhou is considerably influenced by market demand, economic level, convenience, and location. The spatial distribution of the retail industry in the central urban area is primarily influenced by economic factors and convenience, while market demand plays a major role and location has a relatively minimal impact.
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- 2023
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10. Global asymptotic stability of a general biased min‐consensus protocol
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Yuanqiu Mo, Lanlin Yu, and Changbin Yu
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Optimisation techniques ,Interpolation and function approximation (numerical analysis) ,Combinatorial mathematics ,Stability in control theory ,Control engineering systems. Automatic machinery (General) ,TJ212-225 - Abstract
Abstract In this paper, a general biased min‐consensus protocol for continuous‐time multi‐agent systems is presented. In this protocol, agents considered as sources maintain static states, while the state of each non‐source agent evolves using a general min‐consensus‐like function, which takes the states of its neighbours and a biased term as inputs. The properties of the general function have been identified so that the proposed protocol can achieve global asymptotic stability. Unlike conventional consensus protocols where a network of agents reach an agreement on certain quantities of interest, agents under the general biased min‐consensus protocol will converge to different states but can generate various design results pertaining to complex combinatorial optimization problems, such as the shortest path problem and its variants.
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- 2021
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11. Green Manure Amendment Increases Soil Phosphorus Bioavailability and Peanut Absorption of Phosphorus in Red Soil of South China
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Chiming Gu, Weisheng Lv, Xing Liao, Margot Brooks, Yinshui Li, Changbin Yu, Lu Yang, Xiaoyong Li, Wenshi Hu, Jing Dai, Wei Zheng, and Lu Qin
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soil phosphorus components ,organic farming ,winter fallow ,green manure return ,peanut production ,Agriculture - Abstract
Peanut (Arachis hypogaea L.) is one of the most important crops produced worldwide. Peanut is the dominant crop in the typical upland red soil areas of China; however, phosphorus bioavailability in red soil is very low, which severely affects peanut production. To improve the phosphorus bioavailability, which substantially promotes the green development of peanut production, a peanut–green manure rotation field experiment was conducted with six treatments (milkvetch; radish; brassica rape; mustard rape; winter fallow and no-tillage), commencing in September 2017 in the red soil area of Jiangxi province, China. The results show that compared with no-tillage (NT) treatments, different green manure returning treatments had significant effects on soil pH, soil phosphorus components and available potassium content. The particulate phosphorus and soil available phosphorus contents in the green manure treatments were significantly higher than those in the winter fallow (WF) treatment. Compared with the WF treatment, the content of particulate phosphorous in brassica rape (BR), radish (R) and milkvetch (MV) treatments was significantly increased by 6.55%, 3.66% and 2.50%, respectively; the available phosphorus content in mustard rape (MR), BR, R and MV was significantly increased by 20.93%, 25.60%, 23.76% and 18.10%, respectively. In addition, the total phosphorus content of peanut shell in the MV and R treatment was significantly higher than that in the WF treatment, increasing by 33.47% and 60.66%, respectively. Compared with the WF treatment, the peanut biomass of MR, BR and R treatments increased significantly by 19.51%, 29.83% and 19.77%, respectively. The total phosphorus accumulation in all green manure treatments was higher than that in the WF treatment, and the MV treatment reached a significant level at 18.83%. Based on these results, the particulate phosphorus (PP) and available phosphorus were significantly affected by different green manure treatments; green manure amendment improves peanut phosphorus uptake. The use of green manure (especially milkvetch and brassica rape) can be recommended to improve phosphorus bioavailability and yield of peanut in red soil areas.
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- 2023
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12. Author Correction: StackZDPD: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio
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Jinyin Wang, Miaoshan Lu, Ruimin Wang, Shaowei An, Cong Xie, and Changbin Yu
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Medicine ,Science - Published
- 2022
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13. Tactile–Visual Fusion Based Robotic Grasp Detection Method with a Reproducible Sensor
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Yaoxian Song, Yun Luo, and Changbin Yu
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Tactile sensor ,Tactile–visual dataset ,Multi-modal fusion ,Deep learning ,Grasp detection ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
Robotic grasp detection is a fundamental problem in robotic manipulation. The conventional grasp methods, using vision information only, can cause potential damage in force-sensitive tasks. In this paper, we propose a tactile–visual based method using a reproducible sensor to realize a fine-grained and haptic grasping. Although there exist several tactile-based methods, they require expensive custom sensors in coordination with their specific datasets. In order to overcome the limitations, we introduce a low-cost and reproducible tactile fingertip and build a general tactile–visual fusion grasp dataset including 5,110 grasping trials. We further propose a hierarchical encoder–decoder neural network to predict grasp points and force in an end-to-end manner. Then comparisons of our method with the state-of-the-art methods in the benchmark are shown both in vision-based and tactile–visual fusion schemes, and our method outperforms in most scenarios. Furthermore, we also compare our fusion method with the only vision-based method in the physical experiment, and the results indicate that our end-to-end method empowers the robot with a more fine-grained grasp ability, reducing force redundancy by 41%. Our project is available at https://sites.google.com/view/tvgd
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- 2021
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14. Green Manure Amendment Can Reduce Nitrogen Fertilizer Application Rates for Oilseed Rape in Maize–Oilseed Rape Rotation
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Chiming Gu, Wei Huang, Yue Li, Yinshui Li, Changbin Yu, Jing Dai, Wenshi Hu, Xiaoyong Li, Margot Brooks, Lihua Xie, Xing Liao, and Lu Qin
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green manure ,nitrogen application ,chemical fertilizer reduction ,oilseed rape ,maize–oilseed rape rotation ,Botany ,QK1-989 - Abstract
Excessive use of chemical fertilizers has led to a reduction in the quality of arable land and environmental pollution. Using green manure to replace chemical fertilizers is one of the most effective solutions. To study the effect of green manure on the requirement for nitrogen fertilizer in oilseed rape, a field experiment with maize–oilseed rape rotation was conducted. Green manure was intercropped between rows of maize and returned after the maize harvest, with no green manure intercropped as control. Different nitrogen fertilizer treatments (0, 65%, 75% and 100% N rates, respectively) were applied during the oilseed rape season. The results showed that with a 35% reduction in nitrogen application rate, the rapeseed grain yield was significantly higher with the maize intercropping with green manure returned to the field than with the maize monocropping treatment at the same nitrogen level. Under conditions of intercropping and return of green manure, compared with the full standard rate of nitrogen fertilizer treatment, a reduction in nitrogen application of 25–30% in the rape season had no significant effect on rape yield. The agronomic efficiency of nitrogen fertilizer on oilseed rape increased significantly, by 47.61–121%, with green manure incorporation. In addition, green manure incorporation significantly increased the soil organic matter content and the soil-available nitrogen content when chemical nitrogen fertilization was abandoned. Benefit analysis showed that a 25–35% reduction in chemical nitrogen fertilizer applied to oilseed rape crops could be achieved by intercropping green manure in the maize season before the sowing of rapeseed in the experimental area. In the long-term, this measure would increase nitrogen utility, reduce production costs, and have concomitant environmental benefits of improving the quality of cultivated land.
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- 2021
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15. Inverse kinematics-based motion planning for dual-arm robot with orientation constraints
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Jiangping Wang, Shirong Liu, Botao Zhang, and Changbin Yu
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Electronics ,TK7800-8360 ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
This article proposes an efficient and probabilistic complete planning algorithm to address motion planning problem involving orientation constraints for decoupled dual-arm robots. The algorithm is to combine sampling-based planning method with analytical inverse kinematic calculation, which randomly samples constraint-satisfying configurations on the constraint manifold using the analytical inverse kinematic solver and incrementally connects them to the motion paths in joint space. As the analytical inverse kinematic solver is applied to calculate constraint-satisfying joint configurations, the proposed algorithm is characterized by its efficiency and accuracy. We have demonstrated the effectiveness of our approach on the Willow Garage’s PR2 simulation platform by generating trajectory across a wide range of orientation-constrained scenarios for dual-arm manipulation.
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- 2019
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16. Evolution of cooperation in synergistically evolving dynamic interdependent networks: fundamental advantages of coordinated network evolution
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Zhihu Yang, Changbin Yu, Jonghyuk Kim, Zhi Li, and Long Wang
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coevolution ,cooperation ,coordinated linking dynamics ,dynamic interdependent networks ,Science ,Physics ,QC1-999 - Abstract
Real networks are not only multi-layered yet also dynamic. The role of coordinated network evolution regarding dynamic multi-layer networks where both network and strategy evolution simultaneously show diverse interdependence by layers remains poorly addressed. Here, we propose a general and simple coevolution framework to analyze how coordination of different dynamical processes affects strategy propagation in synergistically evolving interdependent networks. The strategic feedback constitutes the main driving force of network evolution yet the inherent cross-layer self-optimization functions as its compensation. We show that these two ingredients often catalyze a better performance of network evolution in propagating cooperation. Coordinated network evolution may be a double-edged sword to cooperation and the network-adapting rate plays a crucial role in flipping its double-sided effect. It often economizes the cost and time consumption for driving the system to the full cooperation phase. Importantly, strongly coupled slow-tuned networks can outperform weakly coupled fast-regulated networks in solving social dilemmas, highlighting the fundamental advantages of coordinated network evolution and the importance of synergistic effect of dynamical processes in upholding human cooperation in multiplex networks.
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- 2019
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17. Evolution of cooperation driven by majority-pressure based interdependence
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Zhihu Yang, Changbin Yu, Jonghyuk Kim, Zhi Li, and Long Wang
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co-evolution ,cooperation ,social dilemmas ,interdependent networks ,Science ,Physics ,QC1-999 - Abstract
The evolution of cooperation on interdependent networks is arousing increasing concern based on the fact that more and more complex systems in the real-world have been proven to be organized in the form of multi-layer networks rather than single-layer networks. In this study, we examine the effects of self-organized interdependence on the evolution and stabilization of cooperation with social dilemmas depicted by the Prisoner’s Dilemma Game (PDG) and the Public Goods Game (PGG) in which agents with the most common strategy have the chance to be rewarded proportionally to the fitness of corresponding agents belonging to the other network. We show that such a type-free rewarding rule, independent of game strategy, establishes a time-varying interdependence between two initially independent populations whereby cooperation is highly promoted as well as stabilized both in the two-player PDG and in the multi-player PGG. Majority-pressure based interdependence at stake has proven pretty neutral in regard to game strategy because it is contingent on strategy configuration rather than strategy itself, which thus gives birth to homologous communities, including cooperative as well as non-cooperative, and thereby an enhanced spatial reciprocity between non-identical networks is triggered. Of particular interest is the double-edged sword effect of network interdependence on cooperation although in most instances the heavier the interdependence, the better the evolution of cooperation. Furthermore, interpretations of the nontrivial relationship between cooperation and benchmark threshold measuring the strategy’s local popularity highlight that rewarding the minimum majority is optimal for the evolution of cooperation in such scenario. Finally, we claim our observations are also quite robust with respect to mutation.
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- 2018
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18. Analysis of the Spatial Variation of Network-Constrained Phenomena Represented by a Link Attribute Using a Hierarchical Bayesian Model
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Zhensheng Wang, Yang Yue, Qingquan Li, Ke Nie, and Changbin Yu
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network-constrained ,points of interests ,hierarchical Bayesian model ,attribute-based method ,local indicators of network-constrained clusters (LINCS) ,Geography (General) ,G1-922 - Abstract
The spatial variation of geographical phenomena is a classical problem in spatial data analysis and can provide insight into underlying processes. Traditional exploratory methods mostly depend on the planar distance assumption, but many spatial phenomena are constrained to a subset of Euclidean space. In this study, we apply a method based on a hierarchical Bayesian model to analyse the spatial variation of network-constrained phenomena represented by a link attribute in conjunction with two experiments based on a simplified hypothetical network and a complex road network in Shenzhen that includes 4212 urban facility points of interest (POIs) for leisure activities. Then, the methods named local indicators of network-constrained clusters (LINCS) are applied to explore local spatial patterns in the given network space. The proposed method is designed for phenomena that are represented by attribute values of network links and is capable of removing part of random variability resulting from small-sample estimation. The effects of spatial dependence and the base distribution are also considered in the proposed method, which could be applied in the fields of urban planning and safety research.
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- 2017
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19. 2.5D Image based Robotic Grasping
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Yaoxian, Song, Chun, Cheng, Yuejiao, Fei, Xiangqing, Li, and Changbin, Yu
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Computer Science - Robotics - Abstract
We consider the problem of robotic grasping using depth + RGB information sampling from a real sensor. we design an encoder-decoder neural network to predict grasp policy in real time. This method can fuse the advantage of depth image and RGB image at the same time and is robust for grasp and observation height.We evaluate our method in a physical robotic system and propose an open-loop algorithm to realize robotic grasp operation. We analyze the result of experiment from multi-perspective and the result shows that our method is competitive with the state-of-the-art in grasp performance, real-time and model size. The video is available in https://youtu.be/Wxw_r5a8qV0, Comment: 6 pages, 5 figures, submitted to ANZCC 2019
- Published
- 2019
20. Alpha-Tri: a deep neural network for scoring the similarity between predicted and measured spectra improves peptide identification of DIA data
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Jian Song and Changbin Yu
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Statistics and Probability ,Computational Mathematics ,Computational Theory and Mathematics ,Molecular Biology ,Biochemistry ,Computer Science Applications - Abstract
Motivation Peptide identification of data-independent acquisition (DIA) mass spectrometry applying the peptide-centric approach heavily relies on the spectral library matching, such as the fragment intensity similarity. If the intensity similarity is calculated through all possible fragment ions of a targeted peptide instead of just a few fragment ions provided by the spectral library, the matching will be more comprehensive and reliable, and thus the identification will be more confident. In addition, the emergence of high precision spectrum predictors, like Prosit, also makes it possible to capitalize on the predicted spectrum, which contains all possible fragment ion intensities, to calculate the intensity similarity for DIA data. Results In this work, we propose Alpha-Tri, a neural-network-based model to calculate intensity similarity as a post-processing score using the predicted spectrum, measured spectrum and correlation spectrum (triple-spectrum). The predicted spectrum is generated by Prosit, the measured spectrum is retrieved from the apex of the chromatograms of all possible fragment ions and the correlation spectrum is used to indicate the present probabilities of these fragment ions as the link between the precursor and its fragment ions is lost in DIA. By adopting a data-driven method, Alpha-Tri is able to learn the intensity similarity from the triple-spectrum. This learned value is appended to initial scores from DIA-NN, allowing the ensuing statistical validation tool to report more peptides at the same false discovery rate (FDR). In our evaluation of the HeLa dataset with gradient lengths ranging from 0.5 to 2 h, Alpha-Tri delivered 3.0–7.2% gains in peptide detections at 1% FDR. On LFQbench dataset, a mixed-species dataset with known ratios, Alpha-Tri identified more peptides and proteins fell within the valid ratio ranges by up to 8.6% and 7.6%, respectively, compared with DIA-NN solely. Availability and implementation The original datasets for benchmarks are downloaded from the ProteomeXchange with the identifiers PXD005573, PXD000954 and PXD002952. Source code is available at https://github.com/YuAirLab/Alpha-Tri.
- Published
- 2022
21. Deep Robotic Grasping Prediction with Hierarchical RGB-D Fusion
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Yaoxian Song, Jun Wen, Dongfang Liu, and Changbin Yu
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Control and Systems Engineering ,Computer Science Applications - Published
- 2022
22. CXCL9, IL2RB, and SPP1, potential diagnostic biomarkers in the co-morbidity pattern of atherosclerosis and non-alcoholic steatohepatitis
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Xize Wu, Changbin Yuan, Jiaxiang Pan, Yi Zhou, Xue Pan, Jian Kang, Lihong Ren, Lihong Gong, and Yue Li
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Bioinformatics ,Differentially expressed genes ,Weighted gene co-expression network analysis ,Immune infiltration microenvironment ,Medicine ,Science - Abstract
Abstract Non-alcoholic steatohepatitis (NASH) is a hepatocyte inflammation based on hepatocellular steatosis, yet there is no effective drug treatment. Atherosclerosis (AS) is caused by lipid deposition in the endothelium, which can lead to various cardiovascular diseases. NASH and AS share common risk factors, and NASH can also elevate the risk of AS, causing a higher morbidity and mortality rate for atherosclerotic heart disease. Therefore, timely detection and diagnosis of NASH and AS are particularly important. In this study, differential gene expression analysis and weighted gene co-expression network analysis were performed on the AS (GSE100927) and NASH (GSE89632) datasets to obtain common crosstalk genes, respectively. Then, candidate Hub genes were screened using four topological algorithms and externally validated in the GSE43292 and GSE63067 datasets to obtain Hub genes. Furthermore, immune infiltration analysis and gene set variation analysis were performed on the Hub genes to explore the underlying mechanisms. The DGIbd database was used to screen candidate drugs for AS and NASH. Finally, a NASH model was constructed using free fatty acid-induced human L02 cells, an AS model was constructed using lipopolysaccharide-induced HUVECs, and a co-morbidity model was constructed using L02 cells and HUVECs to verify Hub gene expression. The result showed that a total of 113 genes common to both AS and NASH were identified as crosstalk genes, and enrichment analysis indicated that these genes were mainly involved in the regulation of immune and metabolism-related pathways. 28 candidate Hub genes were screened according to four topological algorithms, and CXCL9, IL2RB, and SPP1 were identified as Hub genes after in vitro experiments and external dataset validation. The ROC curves and SVM modeling demonstrated the good diagnostic efficacy of these three Hub genes. In addition, the Hub genes are strongly associated with immune cell infiltration, especially macrophages and γ–δ T cell infiltration. Finally, five potential therapeutic drugs were identified. has-miR-185 and hsa-miR-335 were closely related to AS and NASH. This study demonstrates that CXCL9, IL2RB, and SPP1 may serve as potential biomarkers for the diagnosis of the co-morbidity patterns of AS and NASH and as potential targets for drug therapy.
- Published
- 2024
- Full Text
- View/download PDF
23. Recording and Modeling the Seasonal Growth of Suaeda Heteroptera at Liao River Estuary, China, Based on the Wetland Image Monitoring System (WIMS)
- Author
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Yicong Wang, Xianmeng Liang, Yang Yu, Changbin Yu, Min Yang, and Guojun Wu
- Abstract
Wetland ecology monitoring is an important technical guarantee for the protection and restoration of fragile wetland environments. In view of the degradation of the functional vegetation Suaeda heteroptera ( S. heteroptera ) in the Liao River Estuary wetland, an online monitoring method named the Wetland Image Monitoring System (WIMS) was established to obtain real-time, continuous, high spatial and temporal resolution data about the area and height of S. heteroptera . Based on the monitoring data, we confirmed the best model to describe the change process of the area and height for S. heteroptera . The results showed that the growth of S. heteroptera could be divided into three stages: in April and May, the area and height of the S. heteroptera increased rapidly; from June to September, the growth rate slowed down; after October, the area and height of S. heteroptera gradually stabilized. The modeling results showed that the Bertalanffy model had the best simulation performance on the change of the area. While for the height simulation, the segment model composed of the linear and Gompertz models could effectively reduce the simulation error and improve the fit accuracy compared with the single model. In addition, the WIMS has the potential to capture other important ecological factors in small regions, such as benthic animals, birds, waterlogging condition, etc. This observing method can provide high-resolution and abundant data for further exploration of the degradation of typical ecosystems under climate change and human activities.
- Published
- 2022
24. Manipulation Planning with Soft Constraints by Randomized Exploration of the Composite Configuration Space
- Author
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Jiangping Wang, Botao Zhang, Changbin Yu, and Shirong Liu
- Subjects
0209 industrial biotechnology ,Inverse kinematics ,Computer science ,business.industry ,Probabilistic logic ,Robotics ,02 engineering and technology ,Space (mathematics) ,Computer Science Applications ,Computer Science::Robotics ,Orientation (vector space) ,020901 industrial engineering & automation ,Control and Systems Engineering ,Path (graph theory) ,Motion planning ,Artificial intelligence ,Configuration space ,business ,Algorithm - Abstract
In this paper, an efficient and probabilistic complete planning algorithm called Composite-space RRT is presented to address motion planning with soft constraints for spherical wrist manipulators. Firstly, we propose a novel configuration space termed Composite Configuration Space (“Composite Space” for short), which is composed of the joint space and the task space. Then, collision-free paths are generated in the composite space by the Rapidly-exploring Random Trees (RRT) algorithm. Finally, the planned paths in the composite space are mapped into the corresponding joint-space paths by a local planner. As the analytical inverse kinematics (IK) of the spherical wrist is used in the local planner, the proposed Composite-space RRT algorithm is characterized by high efficiency and no numerical iteration. Moreover, this approach can effectively improve the smoothness of the end-effector orientation path. The effectiveness of the proposed algorithm is demonstrated on the Willow Garage’s PR2 simulation platform with two typical orientation-constrained cases.
- Published
- 2021
25. Solve the Puzzle of Instance Segmentation in Videos: A Weakly Supervised Framework with Spatio-Temporal Collaboration
- Author
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Liqi Yan, Qifan Wang, Siqi Ma, Jingang Wang, and Changbin Yu
- Subjects
FOS: Computer and information sciences ,Computer Vision and Pattern Recognition (cs.CV) ,Media Technology ,Computer Science - Computer Vision and Pattern Recognition ,Electrical and Electronic Engineering - Abstract
Instance segmentation in videos, which aims to segment and track multiple objects in video frames, has garnered a flurry of research attention in recent years. In this paper, we present a novel weakly supervised framework with \textbf{S}patio-\textbf{T}emporal \textbf{C}ollaboration for instance \textbf{Seg}mentation in videos, namely \textbf{STC-Seg}. Concretely, STC-Seg demonstrates four contributions. First, we leverage the complementary representations from unsupervised depth estimation and optical flow to produce effective pseudo-labels for training deep networks and predicting high-quality instance masks. Second, to enhance the mask generation, we devise a puzzle loss, which enables end-to-end training using box-level annotations. Third, our tracking module jointly utilizes bounding-box diagonal points with spatio-temporal discrepancy to model movements, which largely improves the robustness to different object appearances. Finally, our framework is flexible and enables image-level instance segmentation methods to operate the video-level task. We conduct an extensive set of experiments on the KITTI MOTS and YT-VIS datasets. Experimental results demonstrate that our method achieves strong performance and even outperforms fully supervised TrackR-CNN and MaskTrack R-CNN. We believe that STC-Seg can be a valuable addition to the community, as it reflects the tip of an iceberg about the innovative opportunities in the weakly supervised paradigm for instance segmentation in videos.
- Published
- 2022
- Full Text
- View/download PDF
26. Green Manure Amendment Can Reduce Nitrogen Fertilizer Application Rates for Oilseed Rape in Maize–Oilseed Rape Rotation
- Author
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Margot Brooks, Lu Qin, Yinshui Li, Wenshi Hu, Chiming Gu, Jing Dai, Xing Liao, Lihua Xie, Li Xiaoyong, Changbin Yu, Yue Li, and Wei Huang
- Subjects
Rapeseed ,oilseed rape ,nitrogen application ,chemistry.chemical_element ,Environmental pollution ,Plant Science ,green manure ,chemical fertilizer reduction ,maize–oilseed rape rotation ,Article ,Green manure ,Ecology, Evolution, Behavior and Systematics ,Ecology ,biology ,Monocropping ,Soil organic matter ,Botany ,Sowing ,Intercropping ,biology.organism_classification ,Nitrogen ,chemistry ,Agronomy ,QK1-989 ,Environmental science - Abstract
Excessive use of chemical fertilizers has led to a reduction in the quality of arable land and environmental pollution. Using green manure to replace chemical fertilizers is one of the most effective solutions. To study the effect of green manure on the requirement for nitrogen fertilizer in oilseed rape, a field experiment with maize–oilseed rape rotation was conducted. Green manure was intercropped between rows of maize and returned after the maize harvest, with no green manure intercropped as control. Different nitrogen fertilizer treatments (0, 65%, 75% and 100% N rates, respectively) were applied during the oilseed rape season. The results showed that with a 35% reduction in nitrogen application rate, the rapeseed grain yield was significantly higher with the maize intercropping with green manure returned to the field than with the maize monocropping treatment at the same nitrogen level. Under conditions of intercropping and return of green manure, compared with the full standard rate of nitrogen fertilizer treatment, a reduction in nitrogen application of 25–30% in the rape season had no significant effect on rape yield. The agronomic efficiency of nitrogen fertilizer on oilseed rape increased significantly, by 47.61–121%, with green manure incorporation. In addition, green manure incorporation significantly increased the soil organic matter content and the soil-available nitrogen content when chemical nitrogen fertilization was abandoned. Benefit analysis showed that a 25–35% reduction in chemical nitrogen fertilizer applied to oilseed rape crops could be achieved by intercropping green manure in the maize season before the sowing of rapeseed in the experimental area. In the long-term, this measure would increase nitrogen utility, reduce production costs, and have concomitant environmental benefits of improving the quality of cultivated land.
- Published
- 2021
27. Consensus for Expressed and Private Opinions under Self-Persuasion
- Author
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Yun Luo, Chun Cheng, and Changbin Yu
- Subjects
0209 industrial biotechnology ,Psychological research ,020208 electrical & electronic engineering ,02 engineering and technology ,Bounded confidence ,Group norms ,Political correctness ,020901 industrial engineering & automation ,Control and Systems Engineering ,0202 electrical engineering, electronic engineering, information engineering ,Cognitive dissonance ,Peer pressure ,Psychology ,Social psychology ,Opinion formation ,Self persuasion - Abstract
As recognized in psychological research, there is often a difference between an agent’s expressed opinion and private opinion (or belief). This occurs for different reasons, such as political correctness or peer pressure. The opinion expressed by an agent is the result of pressure to follow the (average) opinions expressed by the group to which the agent belongs, or to follow group norms. The agent’s private opinion is unknown to others, but evolved under the influence of other agents’ expressed opinions. This paper proposes an opinion formation model based on the theory of bounded confidence, and studies the dynamic process of expressed and private opinions in time-varying networks. At the same time, the self-persuasion effect of agents in the dissonance between expressed and private opinions is considered. Here, group pressure establishes the motive force from private opinion to expressed opinion, while self-persuasion establishes the reverse connection. We find that group pressure can effectively reduce the gap of opinions between the group, but does not always promote consensus. Furthermore, the self-persuasion effect of agents can ensure the realization of group consensus.
- Published
- 2020
28. Game of the Byzantine Generals on Time-Varying Graphs
- Author
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Yuke Li and Changbin Yu
- Subjects
0209 industrial biotechnology ,Sequence ,Theoretical computer science ,Computer science ,020208 electrical & electronic engineering ,ComputingMilieux_PERSONALCOMPUTING ,02 engineering and technology ,Decision rule ,Graph ,020901 industrial engineering & automation ,Control and Systems Engineering ,0202 electrical engineering, electronic engineering, information engineering ,Coordination game ,Byzantine fault tolerance - Abstract
In this paper, we propose a game of the Byzantine Generals, which is a coordination game of agents seeking consensus by strategically transmitting information on a sequence of time-varying communication graphs. The first scenario of the game is where the generals cannot communicate with others at the same "level" in the communication graph. The second scenario is where those generals can. In either scenario, we examine the influences of the number of traitors and the decision rule held by the generals on equilibrium predictions of the game.
- Published
- 2020
29. Stack-ZDPD: A Novel Encoding Scheme for Mass Spectrometry Data
- Author
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Changbin Yu, Miaoshan Lu, Shaowei An, Jinyin Wang, Ruiming Wang, and Cong Xie
- Subjects
Scheme (programming language) ,Stack (abstract data type) ,Computer science ,Encoding (memory) ,Parallel computing ,Mass spectrometry ,computer ,computer.programming_language - Abstract
As the pervasive, standardized format for interchange and deposition of raw mass spectrometry (MS) proteomics and metabolomics data, text-based mzML is inefficiently utilized on various analysis platforms due to its sheer volume of samples and limited read/write speed. Database-developed solution guarantees the efficiency of random file reading, but nevertheless the efforts in compression and third-party software support are insufficient, while most research on compression algorithms rarely provides flexible random file reading scheme. Under the premise of ensuring the efficiency of decompression, we propose an encoding scheme “Stack-ZDPD” that is optimized for storage of raw MS data, designed for the format “Aird”, a computation-oriented format with fast accessing and decoding time, where the core compression algorithm is “ZDPD”. Stack-ZDPD reduces the volume of data stored in mzML format by around 80% or more, depending on the data acquisition pattern, and the compression ratio is approximately 30% compared to ZDPD for data generated using Time of Flight technology. Our approach is available on Airdpro, for file conversion and the Java-API Aird SDK, for data parsing.
- Published
- 2021
30. Tactile–Visual Fusion Based Robotic Grasp Detection Method with a Reproducible Sensor
- Author
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Luo Yun, Yaoxian Song, and Changbin Yu
- Subjects
Fusion ,General Computer Science ,Multi modal fusion ,Computer science ,business.industry ,Deep learning ,GRASP ,Grasp detection ,QA75.5-76.95 ,Tactile–visual dataset ,Multi-modal fusion ,Computational Mathematics ,Tactile sensor ,Electronic computers. Computer science ,Computer vision ,Artificial intelligence ,business - Abstract
Robotic grasp detection is a fundamental problem in robotic manipulation. The conventional grasp methods, using vision information only, can cause potential damage in force-sensitive tasks. In this paper, we propose a tactile–visual based method using a reproducible sensor to realize a fine-grained and haptic grasping. Although there exist several tactile-based methods, they require expensive custom sensors in coordination with their specific datasets. In order to overcome the limitations, we introduce a low-cost and reproducible tactile fingertip and build a general tactile–visual fusion grasp dataset including 5,110 grasping trials. We further propose a hierarchical encoder–decoder neural network to predict grasp points and force in an end-to-end manner. Then comparisons of our method with the state-of-the-art methods in the benchmark are shown both in vision-based and tactile–visual fusion schemes, and our method outperforms in most scenarios. Furthermore, we also compare our fusion method with the only vision-based method in the physical experiment, and the results indicate that our end-to-end method empowers the robot with a more fine-grained grasp ability, reducing force redundancy by 41%. Our project is available at https://sites.google.com/view/tvgd
- Published
- 2021
31. Alpha-XIC: a deep neural network for scoring the coelution of peak groups improves peptide identification by data-independent acquisition mass spectrometry
- Author
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Jian Song and Changbin Yu
- Subjects
Statistics and Probability ,chemistry.chemical_classification ,Artificial neural network ,business.industry ,Alpha (ethology) ,Pattern recognition ,Peptide ,Mass spectrometry ,Biochemistry ,Computer Science Applications ,Computational Mathematics ,Identification (information) ,Text mining ,Computational Theory and Mathematics ,Similarity (network science) ,chemistry ,Data Noise ,Data-independent acquisition ,Artificial intelligence ,business ,Molecular Biology ,Mathematics - Abstract
Motivation The peptide-centric identification methodologies of data-independent acquisition (DIA) data mainly rely on scores for the mass spectrometric signals of targeted peptides. Among these scores, the coelution scores of peak groups constructed by the chromatograms of peptide fragment ions have a significant influence on the identification. Most of the existing coelution scores are achieved by artificially designing some functions in terms of the shape similarity, retention time shift of peak groups. However, these scores cannot characterize the coelution robustly when the peak group is in the circumstance of interference. Results On the basis that the neural network is more powerful to learn the implicit features of data robustly from a large number of samples, and thus minimizing the influence of data noise, in this work, we propose Alpha-XIC, a neural network-based model to score the coelution. By learning the characteristics of the coelution of peak groups derived from the being analyzed DIA data, Alpha-XIC is capable of yielding robust coelution scores even for peak groups with interference. With this score appending to initial scores generated by the accompanying identification engine DIA-NN, the ensuing statistical validation can report the identification result and recover the misidentified peptides. In our evaluation of the HeLa dataset with gradient lengths ranging from 0.5 to 2 h, Alpha-XIC delivered 9.4–16.2% improvements in the number of identified precursors at 1% false discovery rate. Furthermore, Alpha-XIC was tested on LFQbench, a mixed-species dataset with known ratios, and increased the number of peptides and proteins fell within valid ratios by up to 16.4% and 17.8%, respectively, compared to the initial identification by DIA-NN. Availability and implementation Source code is available at https://github.com/YuAirLab/Alpha-XIC.
- Published
- 2021
32. Alpha-Frag: a deep neural network for fragment presence prediction improves peptide identification
- Author
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Changbin Yu, Fangfei Zhang, and Jian Song
- Subjects
chemistry.chemical_classification ,Artificial neural network ,business.industry ,Peptide ,Pattern recognition ,Mass spectrometry ,Alpha (programming language) ,Identification (information) ,Similarity (network science) ,chemistry ,Fragment (logic) ,Enumeration ,Artificial intelligence ,business ,Mathematics - Abstract
Identification of peptides in mass spectrometry-based proteomics typically relies on spectra matches. As MS/MS spectra record presence and intensity of fragment ions, the match should take both fragment presence similarity and intensity similarity into consideration. Fragment presence similarity can be calculated with the help of fragment presence prediction such as theoretical enumeration of all possible fragment ions or selecting non-zero intensity ions from the result of fragment intensity prediction, but neither of these two methods is accurate enough. In this work, we developed a deep neural network based model, Alpha-Frag, to predict precisely the fragment ions that should be present for a given peptide. Alpha-Frag modelled fragment presence prediction as a multi-label classification task and trained with ProteomeTools dataset. In terms of intersection over union (IoU), Alpha-Frag achieved an average of >0.7 and outperformed the benchmarks across the validation datasets. Furthermore, fragment presence similarity was calculated based on presence prediction and incorporated into the peptide statistical validation tools as an additional score to improve peptide identifications. Our preliminary experiments show that this score led to a maximum increase of 26.8% (FDR 0.1%) and 21.6% (FDR 1%) for the DDA and the DIA identification, respectively.Significance StatementA better prediction of fragmentation for peptides in mass spectrometry (MS) is beneficial to the peptide identification. As the MS/MS spectra record two-dimensional information of fragment ions derived from precursors, mass-to-charge ratio (m/z) and their corresponding intensities, besides the fragment intensity prediction, it is necessary to study the presence prediction. Although the presence prediction can be realized by enumerating all the possible fragmentation patterns of a peptide with equal probability or by selecting non-zero intensity fragment ions from the result of fragment intensity prediction, neither of these two methods is accurate enough. In this study, deep learning is leveraged to precisely predict the fragment ions of a given peptide. Based on the fragment presence prediction, fragment presence similarity between experimental spectra and predicted spectra can be calculated which is proved to promote the peptide detections both for DDA and for DIA data.
- Published
- 2021
33. Dimensional-Invariance Principles in Coupled Dynamical Systems: A Unified Analysis and Applications
- Author
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Changbin Yu and Zhiyong Sun
- Subjects
Coupling ,0209 industrial biotechnology ,Dynamical systems theory ,Computer science ,Linear system ,02 engineering and technology ,Invariant (physics) ,Mathematical proof ,Dynamical system ,Computer Science Applications ,Consensus dynamics ,Matrix (mathematics) ,020901 industrial engineering & automation ,Control and Systems Engineering ,Control system ,Statistical physics ,Electrical and Electronic Engineering ,Invariant (mathematics) ,Subspace topology - Abstract
In this paper, we will study coupled dynamical systems and investigate dimension properties of the subspace spanned by solutions of each individual system. Relevant problems on collinear dynamical systems and their variations are discussed recently by Montenbruck et al. in [1] , while in this paper we aim to provide a unified analysis to derive the dimensional-invariance principles for networked coupled systems, and to generalize the invariance principles for networked systems with more general forms of coupling terms. To be specific, we consider two types of coupled systems, one with scalar couplings and the other with matrix couplings. Via the rank-preserving flow theory , we show that any scalar-coupled dynamical system (with constant, time-varying, or state-dependent couplings) possesses the dimensional-invariance principles, in that the dimension of the subspace spanned by the individual systems’ solutions remains invariant. For coupled dynamical systems with matrix coefficients/couplings, necessary and sufficient conditions (for constant, time-varying, and state-dependent couplings) are given to characterize dimensional-invariance principles. The proofs via a rank-preserving matrix flow theory in this paper simplify the analysis in [1] , and we also extend the invariance principles to the cases of time-varying couplings and state-dependent couplings. Furthermore, subspace-preserving property and signature-preserving flows are also developed for coupled networked systems with particular coupling terms. These invariance principles provide insightful characterizations to analyze transient behaviors and solution evolutions for a large family of coupled systems, such as multiagent consensus dynamics, distributed coordination systems, formation control systems, etc.
- Published
- 2019
34. Event-Triggered Algorithms for Leader–Follower Consensus of Networked Euler–Lagrange Agents
- Author
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Qingchen Liu, Jiahu Qin, Mengbin Ye, and Changbin Yu
- Subjects
0209 industrial biotechnology ,Adaptive algorithm ,Computer science ,Multi-agent system ,020208 electrical & electronic engineering ,02 engineering and technology ,Function (mathematics) ,Network topology ,Graph ,Computer Science Applications ,Human-Computer Interaction ,020901 industrial engineering & automation ,Control and Systems Engineering ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,Piecewise ,Graph (abstract data type) ,Algorithm design ,Electrical and Electronic Engineering ,Algorithm ,Software - Abstract
This paper proposes three different distributed event-triggered control algorithms to achieve leader–follower consensus for a network of Euler–Lagrange agents. We first propose two model-independent algorithms for a subclass of Euler–Lagrange agents without the vector of gravitational potential forces. By model-independent, we mean that each agent can execute its algorithm with no knowledge of the agent self-dynamics. A variable-gain algorithm is employed when the sensing graph is undirected; algorithm parameters are selected in a fully distributed manner with much greater flexibility compared to all previous work studying event-triggered consensus problems. When the sensing graph is directed, a constant-gain algorithm is employed. The control gains must be centrally designed to exceed several lower bounding inequalities, which require limited knowledge of bounds on the matrices describing the agent dynamics, bounds on network topology information, and bounds on the initial conditions. When the Euler–Lagrange agents have dynamics that include the vector of gravitational potential forces, an adaptive algorithm is proposed. This requires more information about the agent dynamics but allows for the estimation of uncertain parameters associated with the agent self-dynamics. For each algorithm, a trigger function is proposed to govern the event update times. The controller is only updated at each event, which ensures that the control input is piecewise constant and thus saves energy resources. We analyze each controller and trigger function to exclude Zeno behavior.
- Published
- 2019
35. Evolution of Social Power in Social Networks With Dynamic Topology
- Author
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Mengbin Ye, Changbin Yu, Tamer Basar, Ji Liu, and Brian D. O. Anderson
- Subjects
FOS: Computer and information sciences ,0209 industrial biotechnology ,Computer science ,Topology (electrical circuits) ,Systems and Control (eess.SY) ,Dynamical Systems (math.DS) ,02 engineering and technology ,Network topology ,Topology ,Upper and lower bounds ,020901 industrial engineering & automation ,Convergence (routing) ,FOS: Electrical engineering, electronic engineering, information engineering ,FOS: Mathematics ,0202 electrical engineering, electronic engineering, information engineering ,Computer Science - Multiagent Systems ,Mathematics - Dynamical Systems ,Electrical and Electronic Engineering ,Social and Information Networks (cs.SI) ,Sequence ,Social network ,business.industry ,Stochastic process ,Computer Science - Social and Information Networks ,Computer Science::Social and Information Networks ,Computer Science Applications ,Control and Systems Engineering ,Computer Science - Systems and Control ,020201 artificial intelligence & image processing ,business ,Constant (mathematics) ,Multiagent Systems (cs.MA) - Abstract
The recently proposed DeGroot-Friedkin model describes the dynamical evolution of individual social power in a social network that holds opinion discussions on a sequence of different issues. This paper revisits that model, and uses nonlinear contraction analysis, among other tools, to establish several novel results. First, we show that for a social network with constant topology, each individual's social power converges to its equilibrium value exponentially fast, whereas previous results only concluded asymptotic convergence. Second, when the network topology is dynamic (i.e., the relative interaction matrix may change between any two successive issues), we show that each individual exponentially forgets its initial social power. Specifically, individual social power is dependent only on the dynamic network topology, and initial (or perceived) social power is forgotten as a result of sequential opinion discussion. Last, we provide an explicit upper bound on an individual's social power as the number of issues discussed tends to infinity; this bound depends only on the network topology. Simulations are provided to illustrate our results., Comment: Extended version of submitted journal paper. Includes additional simulation details
- Published
- 2018
36. Multimodal Aggregation Approach for Memory Vision-Voice Indoor Navigation with Meta-Learning
- Author
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Yaoxian Song, Dongfang Liu, Changbin Yu, and Liqi Yan
- Subjects
FOS: Computer and information sciences ,Meta learning (computer science) ,Computer science ,Computer Vision and Pattern Recognition (cs.CV) ,Feature extraction ,Computer Science - Computer Vision and Pattern Recognition ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,02 engineering and technology ,010501 environmental sciences ,01 natural sciences ,Visualization ,Human–computer interaction ,0202 electrical engineering, electronic engineering, information engineering ,Task analysis ,RGB color model ,Robot ,020201 artificial intelligence & image processing ,0105 earth and related environmental sciences - Abstract
Vision and voice are two vital keys for agents' interaction and learning. In this paper, we present a novel indoor navigation model called Memory Vision-Voice Indoor Navigation (MVV-IN), which receives voice commands and analyzes multimodal information of visual observation in order to enhance robots' environment understanding. We make use of single RGB images taken by a first-view monocular camera. We also apply a self-attention mechanism to keep the agent focusing on key areas. Memory is important for the agent to avoid repeating certain tasks unnecessarily and in order for it to adapt adequately to new scenes, therefore, we make use of meta-learning. We have experimented with various functional features extracted from visual observation. Comparative experiments prove that our methods outperform state-of-the-art baselines., Comment: 8 pages, 6 figures, 2 tables, accepted at 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020)
- Published
- 2020
37. Aird: A computation-oriented mass spectrometry data format enables higher compression ratio and less decoding time
- Author
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Jinyin Wang, Miaoshan Lu, Shaowei An, Changbin Yu, and Ruimin Wang
- Subjects
Lossless compression ,File size ,Computer science ,Search engine indexing ,Open format ,Compression ratio ,Data compression ratio ,JSON ,computer ,computer.programming_language ,Data compression ,Computational science - Abstract
With the precision of mass spectrometer going higher and the emergence of data independence acquisition (DIA), the file size is increasing rapidly. Beyond the widely-used open format mzML (Deutsch 2008), near-lossless or lossless compression algorithms and formats have emerged. The data precision is often related to the instrument and subsequent processing algorithms. Unlike storage-oriented formats, which focusing more on lossless compression and compression rate, computation-oriented formats focus as much on decoding speed and disk read strategy as compression rate. Here we describe “Aird", an opensource and computation-oriented format with controllable precision, flexible indexing strategies and high compression rate. Aird uses JavaScript Object Notation (JSON) for metadata storage, multiple indexing, and reordered storage strategies for higher speed of data randomly reading. Aird also provides a novel compressor called Zlib-Diff-PforDelta (ZDPD) for m/z data compression. Compared with Zlib only, m/z data size is about 65% lower in Aird, and merely takes 33% decoding time.AvailabilityAird SDK is written in Java, which allow scholars to access mass spectrometry data efficiently. It is available at https://github.com/Propro-Studio/Aird-SDK AirdPro can convert vendor files into Aird files, which is available at https://github.com/Propro-Studio/AirdPro
- Published
- 2020
38. 2.5D Image-based Robotic Grasping
- Author
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Yaoxian Song, Qingchen Liu, Li Xiangqing, Chun Cheng, Fei Yuejiao, and Changbin Yu
- Subjects
Robotic systems ,Artificial neural network ,Data sampling ,Computer science ,business.industry ,Robustness (computer science) ,GRASP ,Computer vision ,Artificial intelligence ,business ,Rgb image ,Image based - Abstract
We consider the problem of robotic grasping by 2. 5D image data sampling from a real sensor. We design an encoder-decoder neural network to predict grasping policy in real-time which enhances the robustness for the policy generation at different observation heights by fusing depth image and RGB image. We propose an open-loop algorithm to realize robotic grasp operation and evaluate our method in a physical robotic system. The result shows that our method is competitive with the state-of-the-art in grasp performance, real-time and model size. The video is available in https://youtu.be/Wxw_r5a8qV0.
- Published
- 2019
39. Facile synthesis of chiral indolines through asymmetric hydrogenation of in situ generated indoles
- Author
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Jie Wang, Yong-Gui Zhou, and Changbin Yu
- Subjects
In situ ,010405 organic chemistry ,Chemistry ,Organic Chemistry ,Asymmetric hydrogenation ,Condensation ,Enantioselective synthesis ,Optically active ,010402 general chemistry ,01 natural sciences ,Combinatorial chemistry ,0104 chemical sciences ,Intramolecular force ,Reactivity (chemistry) ,Brønsted–Lowry acid–base theory - Abstract
A concise and enantioselective procedure for the synthesis of optically active indolines has been developed through intramolecular condensation, deprotection and palladium-catalyzed asymmetric hydrogenation in a one-pot process with up to 96% ee. A strong Bronsted acid played an important role in both the formation of indoles and asymmetric hydrogenation process. This strategy could be scaled-up with excellent reactivity and enantioselectivity.
- Published
- 2018
40. Global Adaptive Controller for Linear Systems With Unknown Input Delay
- Author
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Chao Huang and Changbin Yu
- Subjects
0209 industrial biotechnology ,Delay calculation ,Supervisor ,Adaptive control ,020208 electrical & electronic engineering ,Linear system ,Elmore delay ,02 engineering and technology ,Computer Science Applications ,020901 industrial engineering & automation ,Control and Systems Engineering ,Robustness (computer science) ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,Feedback controller ,Electrical and Electronic Engineering ,Actuator ,Mathematics - Abstract
In this note, a switching-type delay-adaptive predictor feedback controller is proposed to globally stabilize linear systems with unknown input delay. The idea of our method is to take advantage of the robustness of feedback laws to delay estimate error that is sufficiently small. We first prove that, when the delay estimate is sufficiently close to the true delay, there is a Lyapunov–Krasovskii functional that is strictly decreasing, and asymptotic regulation is achievable. Then, with the help of the Lyapunov–Krasovskii functional as a supervisor, the switching logic plays the role of adjusting the estimated delay online to make it sufficiently close to the true delay. The result of this note shows that, global adaptive stabilization of linear systems with unknown input delay is achievable, with a logic-based switching control law.
- Published
- 2017
41. Distributed Averaging Using Periodic Gossiping
- Author
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Ji Liu, Brian D. O. Anderson, Changbin Yu, Shaoshuai Mou, Fenghua He, and A. Stephen Morse
- Subjects
0209 industrial biotechnology ,Schedule ,020206 networking & telecommunications ,02 engineering and technology ,Tree (graph theory) ,Computer Science Applications ,Combinatorics ,Edge coloring ,020901 industrial engineering & automation ,Tree structure ,Rate of convergence ,Consensus ,Computer Science::Systems and Control ,Control and Systems Engineering ,Gossip ,0202 electrical engineering, electronic engineering, information engineering ,Electrical and Electronic Engineering ,Invariant (mathematics) ,Mathematics - Abstract
The distributed averaging problem is a consensus problem whose objective is to devise a protocol which will enable all the members of a group of autonomous agents to compute the average of the initial values of their individual consensus variables in a distributed manner. Periodic gossiping is a deterministic method for solving the distributed averaging problem by stipulating that each pair of agents which are allowed to gossip, do so repeatedly in accordance with a prespecified periodic schedule. Agent pairs which are allowed to gossip correspond to edges on a given connected, undirected graph. In general, the rate at which the agents' consensus variables converge to the desired average value depends on the order in which the gossips occur over a period. The main contributions of this paper are first to characterize the classes of periodic gossip sequences which have the same convergence rate and second to prove that if the graph of allowable gossips is a tree with each edge restricted to gossiping once per period, the convergence rate is quite surprisingly, fixed and invariant over all possible periodic gossip sequences the graph allows. To arrive at these results, a new and unusual graph theoretic concept, namely the transfer function of a node of an undirected graph, is used. Among all the trees with the same number of edges, optimal tree structures, which yield the fastest convergence rate, can then be sought.
- Published
- 2017
42. On the Analysis of the DeGroot-Friedkin Model with Dynamic Relative Interaction Matrices * *This work was supported by the Australian Research Council (ARC) under the ARC grants DP-130103610 and DP-160104500, by the National Natural Science Foundation of China (grant 61375072), and by Data61-CSIRO (formerly NICTA). The work of Liu and Başar was supported in part by Office of Naval Research (ONR) MURI Grant N00014-16-1-2710, and in part by NSF under grant CCF 11-11342
- Author
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Tamer Basar, Mengbin Ye, Brian D. O. Anderson, Ji Liu, and Changbin Yu
- Subjects
0209 industrial biotechnology ,Mathematical optimization ,Sequence ,Social network ,business.industry ,Group (mathematics) ,Computer science ,Multi-agent system ,020208 electrical & electronic engineering ,Behavioural sciences ,02 engineering and technology ,Network topology ,020901 industrial engineering & automation ,Control and Systems Engineering ,0202 electrical engineering, electronic engineering, information engineering ,business ,Set (psychology) ,Simulation - Abstract
This paper analyses the DeGroot-Friedkin model for evolution of the individuals’ social powers in a social network when the network topology varies dynamically (described by dynamic relative interaction matrices). The DeGroot-Friedkin model describes how individual social power (self-appraisal, self-weight) evolves as a network of individuals discuss opinions on a sequence of issues. We seek to study dynamically changing relative interactions because interactions may change depending on the issue being discussed. Specifically, we study relative interaction matrices which vary periodically with respect to the issues. This may reflect a group of individuals, e.g. a government cabinet, that meet regularly to discuss a set of issues sequentially. It is shown that individuals’ social powers admit a periodic solution. Initially, we study a social network which varies periodically between two relative interaction matrices, and then generalise to an arbitrary number of relative interaction matrices.
- Published
- 2017
43. Coverage Control of Unicycle Agents under Constant Speed Constraints * *The work of Q. Liu, M. Ye and C. Yu was supported by the Australian Research Council (ARC) under the ARC grants DP-130103610 and DP-160104500, by the National Natural Science Foundation of China (grant 61375072), by Data61-CSIRO (formerly NICTA) and a China Scholarship Council PhD scholarship. The work of J. Qin was supported in part by the National natural Science Foundation of China under Grant 61473269 and in part by the Youth Innovation Promotion Association of Chinese Academy of Sciences
- Author
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Changbin Yu, Mengbin Ye, Jiahu Qin, Zhiyong Sun, and Qingchen Liu
- Subjects
0209 industrial biotechnology ,Computer science ,020208 electrical & electronic engineering ,Regular polygon ,02 engineering and technology ,020901 industrial engineering & automation ,Control and Systems Engineering ,Control theory ,Orientation (geometry) ,Bounded function ,0202 electrical engineering, electronic engineering, information engineering ,Coverage control ,Constant (mathematics) ,Voronoi diagram - Abstract
This paper studies the problem of optimal coverage control over a convex bounded region by a group of unicycle-type mobile agents with constant speeds. We further assume that the constant speeds for different agents may be non-identical. Thus, a unicycle is controlled solely via steering of its orientation in which a virtual centre is defined for each unicycle. A basic controller is proposed which asymptotically drive the virtual centres to a Centroidal Voronoi configuration, thus achieving the optimal coverage objective. At the Centroidal Voronoi configuration, each unicycle executes steady-state circular orbit about its virtual centre. To overcome a drawback of the basic controller that requires a careful selection of initial conditions, a modified switching controller is proposed which achieves a Centroidal Voronoi configuration for arbitrarily chosen initial conditions. Simulations for both the basic and modified controllers are presented for a five-unicycle group.
- Published
- 2017
44. Bearing-Only Measurement Self-Localization, Velocity Consensus and Formation Control
- Author
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Mengbin Ye, Brian D. O. Anderson, and Changbin Yu
- Subjects
Physics ,020301 aerospace & aeronautics ,0209 industrial biotechnology ,Bearing (mechanical) ,Plane (geometry) ,education ,Process (computing) ,Aerospace Engineering ,02 engineering and technology ,Interval (mathematics) ,Tracking (particle physics) ,Topology ,law.invention ,Shape control ,Computer Science::Multiagent Systems ,020901 industrial engineering & automation ,0203 mechanical engineering ,law ,Control theory ,Self localization ,Electrical and Electronic Engineering ,Control (linguistics) - Abstract
Self-localization and formation control tasks are considered when each agent in a multiagent formation observes its neighbors but does not communicate. Each agent is restricted to a predefined motion type on a 2-D plane and collects bearing-only measurements over a time interval to localize neighboring agents. The localization process is used by a three agent formation to achieve velocity consensus combined with formation shape control. Simulations are provided and noisy bearing measurements are investigated.
- Published
- 2017
45. Distributed attitude and translation consensus for networked rigid bodies based on unit dual quaternion
- Author
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Changbin Yu and Yinqiu Wang
- Subjects
0209 industrial biotechnology ,Mechanical Engineering ,General Chemical Engineering ,020208 electrical & electronic engineering ,Biomedical Engineering ,Aerospace Engineering ,02 engineering and technology ,Translation (geometry) ,Topology ,Industrial and Manufacturing Engineering ,020901 industrial engineering & automation ,Consensus ,Control and Systems Engineering ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,Electrical and Electronic Engineering ,Dual quaternion ,Unit (ring theory) ,Mathematics - Abstract
Summary This paper provides unified solutions for distributed attitude and translation consensus problems for networked fully actuated rigid bodies under the fixed and undirected communication topology with the tool of unit dual quaternion. We investigate two kinds of consensus, that is, leaderless consensus and leader-following consensus with a static leader. Firstly, the dynamics of rigid bodies are presented by unit dual quaternion. The control inputs of rigid bodies are also obtained from unit dual quaternion. Secondly, we propose a distributed consensus law in the form of dual quaternion to guarantee that the attitudes and translations of all rigid bodies reach consensus, respectively, without a leader. Thirdly, the leader-following consensus problem with a static leader is studied. With the proposed leader-following consensus law, the states of all rigid bodies converge to the corresponding states of the static leader, including the attitude and the translation. Finally, numerical examples are provided to validate the effectiveness of the theoretical results. Copyright © 2017 John Wiley & Sons, Ltd.
- Published
- 2017
46. Distributed model-independent consensus of Euler-Lagrange agents on directed networks
- Author
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Changbin Yu, Mengbin Ye, and Brian D. O. Anderson
- Subjects
0209 industrial biotechnology ,Mathematical optimization ,Computer science ,Mechanical Engineering ,General Chemical Engineering ,Multi-agent system ,020208 electrical & electronic engineering ,Biomedical Engineering ,Aerospace Engineering ,02 engineering and technology ,Directed graph ,Upper and lower bounds ,Industrial and Manufacturing Engineering ,Computer Science::Multiagent Systems ,Matrix (mathematics) ,020901 industrial engineering & automation ,Control and Systems Engineering ,Control theory ,Robustness (computer science) ,0202 electrical engineering, electronic engineering, information engineering ,Electrical and Electronic Engineering ,Laplacian matrix ,Connectivity - Abstract
Summary This paper proposes a distributed model-independent algorithm to achieve leaderless consensus on a directed network where each fully-actuated agent has self-dynamics described by Euler–Lagrange equations of motion. Specifically, we aim to achieve consensus of the generalised coordinates with zero generalised velocity. We show that on a strongly connected graph, a model-independent algorithm can achieve the consensus objective at an exponential rate if an upper bound on the initial conditions is known a priori. By model-independent, we mean that each agent can execute the algorithm with no knowledge of the equations describing the self-dynamics of any agent. For design of the control laws which achieve consensus, a control gain scalar and a control gain matrix are required to satisfy several inequalities involving bounds on the matrices of the agent dynamic model, bounds on the Laplacian matrix describing the network topology and the set of initial conditions; design of the algorithm therefore requires some knowledge on the bounds of the agent dynamical parameters. Because only bounds are required, the proposed algorithm offers robustness to uncertainty in the parameters of the multiagent system. We systematically show that additional relative velocity information improves the performance of the controller. Numerical simulations are provided to show the effectiveness of the algorithm. Copyright © 2016 John Wiley & Sons, Ltd.
- Published
- 2016
47. Cooperative Event-Based Rigid Formation Control
- Author
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Changbin Yu, Qingchen Liu, Brian D. O. Anderson, Na Huang, and Zhiyong Sun
- Subjects
FOS: Computer and information sciences ,0209 industrial biotechnology ,Computer science ,Event (relativity) ,Distributed computing ,Control (management) ,FOS: Physical sciences ,02 engineering and technology ,Systems and Control (eess.SY) ,Pattern Formation and Solitons (nlin.PS) ,Computer Science - Robotics ,020901 industrial engineering & automation ,Control theory ,Convergence (routing) ,0202 electrical engineering, electronic engineering, information engineering ,FOS: Electrical engineering, electronic engineering, information engineering ,FOS: Mathematics ,Computer Science - Multiagent Systems ,Electrical and Electronic Engineering ,Mathematics - Optimization and Control ,business.industry ,Multi-agent system ,020208 electrical & electronic engineering ,SIGNAL (programming language) ,Nonlinear Sciences - Pattern Formation and Solitons ,Automation ,Computer Science Applications ,Human-Computer Interaction ,Control and Systems Engineering ,Optimization and Control (math.OC) ,Control system ,Computer Science - Systems and Control ,business ,Robotics (cs.RO) ,Software ,Multiagent Systems (cs.MA) - Abstract
This article discusses cooperative stabilization control of rigid formations via an event-based approach. We first design a centralized event-based formation control system, in which a central event controller determines the next triggering time and broadcasts the event signal to all the agents for control input update. We then build on this approach to propose a distributed event control strategy, in which each agent can use its local event trigger and local information to update the control input at its own event time. For both cases, the triggering condition, event function, and triggering behavior are discussed in detail, and the exponential convergence of the event-based formation system is guaranteed.
- Published
- 2019
- Full Text
- View/download PDF
48. Elementary operations for rigidity restoration and persistence analysis of multi‐agent system
- Author
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Yun Hou and Changbin Yu
- Subjects
Discrete mathematics ,0209 industrial biotechnology ,Mathematical optimization ,Control and Optimization ,Multi-agent system ,Rigidity (psychology) ,0102 computer and information sciences ,02 engineering and technology ,Directed graph ,01 natural sciences ,Computer Science Applications ,Human-Computer Interaction ,020901 industrial engineering & automation ,Two-dimensional space ,010201 computation theory & mathematics ,Control and Systems Engineering ,Control theory ,Graph (abstract data type) ,Electrical and Electronic Engineering ,Graph operations ,Mathematics - Abstract
This work focuses on the construction of rigid formation from non-rigid ones in the two-dimensional space. Analogously to operations of Henneberg sequence aiming to guarantee the minimal rigidity of formation, two new operations are introduced, allowing one to sequentially build any rigid graph by connecting non-rigid ones. A systematic construction sequence is developed based on proposed operations, and is shown to be able to restore rigidity by introducing minimum number of new edges during the construction process. Further applications of the proposed operations are also presented, one of which is successfully employed in the problem of persistence analysis of directed graphs, and can verify the persistence of a given graph with a speed two times faster comparing with existing solution.
- Published
- 2016
49. Leader Tracking of Euler-Lagrange Agents on Directed Switching Networks Using A Model-Independent Algorithm
- Author
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Changbin Yu, Brian D. O. Anderson, Mengbin Ye, and Discrete Technology and Production Automation
- Subjects
Control and Optimization ,Computer Networks and Communications ,Computer science ,Systems and Control (eess.SY) ,Network topology ,Tracking error ,Exponential growth ,SYSTEMS ,FOS: Electrical engineering, electronic engineering, information engineering ,switching network ,distributed algorithm ,Directed graph ,Approximation algorithm ,model independent ,tracking ,Dwell time ,Control and Systems Engineering ,Distributed algorithm ,Signal Processing ,SYNCHRONIZATION ,Euler-Lagrange agent ,Graph (abstract data type) ,Computer Science - Systems and Control ,CONSENSUS ,Algorithm - Abstract
In this paper, we propose a discontinuous distributed model- independent algorithm for a directed network of Euler- Lagrange agents to track the trajectory of a leader with nonconstant velocity. We initially study a fixed network and show that the leader tracking objective is achieved semiglobally exponentially fast if the graph contains a directed spanning tree. By model independent, we mean that each agent executes its algorithm with no knowledge of the parameter values of any agent's dynamics. Certain bounds on the agent dynamics (including any disturbances) and network topology information are used to design the control gain. This fact, combined with the algorithm's model independence, results in robustness to disturbances and modeling uncertainties. Next, a continuous approximation of the algorithm is proposed, which achieves practical tracking with an adjustable tracking error. Last, we show that the algorithm is stable for networks that switch with an explicitly computable dwell time. Numerical simulations are given to show the algorithm's effectiveness.
- Published
- 2018
- Full Text
- View/download PDF
50. Localization Bias Reduction in Wireless Sensor Networks
- Author
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Brian D. O. Anderson, Yiming Ji, Junming Wei, and Changbin Yu
- Subjects
Noise measurement ,business.industry ,Structure (category theory) ,Graph theory ,Function (mathematics) ,Expression (mathematics) ,symbols.namesake ,Control and Systems Engineering ,Electronic engineering ,Taylor series ,symbols ,Wireless ,Electrical and Electronic Engineering ,business ,Wireless sensor network ,Algorithm ,Mathematics - Abstract
In this paper, a novel bias-reduction method is proposed to analytically express and reduce the bias arising in sensor network localization problems, thereby improving the localization accuracy. The proposed bias-reduction method mixes Taylor series and a maximum-likelihood estimate and leads to an easily calculated analytical bias expression in terms of a known maximum-likelihood cost function. In contrast to existing contributions, this paper considers a sensor network as a whole when the bias is investigated by introducing the geometric structure of the sensor network into the proposed bias-reduction method via the rigidity matrix, a concept drawn from graph theory. The maximum-likelihood cost function is related to the rigidity matrix resulting in the final analytical expression of localization bias in terms of the rigidity matrix. Another important contribution of this paper is that, in addition to the presented simulation results, experimental results obtained by using a wireless localization system, which is developed based on reconfigurable software-defined radios (SDRs), are also provided to verify the performance of the proposed bias-reduction method. Both the simulation and experimental results demonstrate that the proposed method can reduce the bias, thereby improving the localization accuracy in different scenarios.
- Published
- 2015
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