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International Conference on Guidance, Navigation and Control, ICGNC 2022

作者： Xue, Zhentao Chen, Jian Cao, Yuanyang Zhang, Zichao Liu, Xuzan College of Engineering China Agricultural University Beijing China Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities MNR Shanghai China Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural Resources Shenzhen China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijng China

ISBN: (纸本)9789811966125

Multi-drone logistics transportation and distribution have gradually become the focus of future logistics. So as to solve the multi-UAV logistics planning problem, the goal of this paper is to minimize the cost of take-off and variable-load flight, and builds a multi-UAV logistics planning model with constraints such as flight distance and logistics load. The Improved Genetic Simulated Annealing Algorithm(IGSAA) adds the SA mechanism on the basis of the classical GA, selectively adds non-optimal solutions and non-constrained solutions, and adopts the Improved Large Neighborhood Search Algorithm (ILNSA) to generate special algorithms with three strategies. By continuously updating the population iteration and selectively adding the probability according to the temperature change, the optimal UAV logistics planning is finally optimized. Finally, the simulation results close to reality show that compared with the initial random solution and the classical genetic algorithm, the improved genetic simulated annealing algorithm proposed in this paper reduces the flight cost of UAV by 16.78% and 8.49%, respectively, and can obtain lower transportation costs. Drone logistics solution. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Drones

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Remote Sensing Image Semantic Segmentation Based on Fusion of Transformer and Lightweight Deeplabv3+

Remote Sensing Image Semantic Segmentation Based on Fusion o...

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International Conference on Guidance, Navigation and Control, ICGNC 2022

作者： Cao, Yuanyang Chen, Jian Xue, Zhentao Zhang, Zichao Hu, Gui College of Engineering China Agricultural University Beijing China Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities MNR Shanghai China Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural Resources Shenzhen China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijng China

ISBN: (纸本)9789811966125

Aiming at the problems that the classification of remote sensing image datasets is not balanced so that the accuracy of semantic segmentation is not high and the segmentation effect of scarce samples is poor. Transformer encoder with multihead self-attention mechanism is integrated into Deeplabv3+ network, and the attention mechanism is used to enhance the ability to capture global information, so as to improve the precision requirement of scarce categories in remote sensing semantic segmentation task. The algorithm firstly uniformly crops high-resolution remote sensing images into low-resolution image information for batch training and reducing information loss. Secondly, MobileNetV2, a lightweight backbone feature extraction network, is used to replace Xception network of Deeplabv3+. Finally, Transformer encoder based on multihead self-attention mechanism is connected in series with atrous spatial pyramid pooling (ASPP) of Deeplabv3+ encoder region to increase its segmentation precision by enhancing feature learning of scarce category samples in deep feature information. The experimental result shows that the proposed model called TransDeeplabv3+ gets 67.67% mIoU and 81.86% mPA on GID remote sensing dataset. Compared with Deeplabv3+ model, mIoU and mPA are improved by 9.46% and 8.52% respectively. TransDeeplabv3+ can effectively increase the precision because of the ability of increasing attention to the scarce species samples and solve the problem of the decrease of segmentation accuracy due to unbalanced data categories. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Semantic Segmentation

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Advancing biological fluorescence microscopy with deep learning:a bibliometric perspective

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Medical data Mining 2022年第4期5卷 42-55页

作者： Li Fu Cheng-Liang Yin Jia-Lei Wang Xiao-Zhu Liu College of Materials and Environmental Engineering Hangzhou Dianzi UniversityHangzhou 310018China Medical Big Data Research Center Medical Innovation Research Division of PLA General HospitalBeijing 100853China National Engineering Laboratory for Medical Big Data Application Technology Chinese PLA General HospitalBeijing 100853China Department of Algorithm Shining3D Technology Company LimitidHangzhou 311258China Department of Cardiology The Second Affiliated Hospital of Chongqing Medical UniversityChongqing 400010China

Background:Fluorescence microscopy has increasingly promising applications in life *** bibliometrics-based review focuses on deep learning assisted fluorescence microscopy imaging ***:Papers on this topic retrieved by Core Collection on Web of Science between 2017 and July 2022 were used for the *** addition to presenting the representative papers that have received the most attention,the process of development of the topic,the structure of authors and institutions,the selection of journals,and the keywords are analyzed in detail in this ***:The analysis found that this topic gained immediate popularity among scholars from its emergence in 2017,gaining explosive growth within three *** phenomenon is because deep learning techniques that have been well established in other fields can be migrated to the analysis of fluorescence *** 2020 onwards,this topic tapers off but has attracted a few stable research groups to tackle the remaining *** this topic has been very popular,it has not attracted scientists from all over the *** USA,China,Germany,and the UK are the key players in this *** analysis and clustering are applied to understand the different focuses on this ***:Based on the bibliometric analysis,the current state of this topic to date and future perspectives are summarized at the end.

关键词： deep learning fluorescence microscopy signal-to-noise ratio convolutional neural network cell segmentation

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Validation of right coronary artery lumen area from cardiac computed tomography against intravascular ultrasound

Validation of right coronary artery lumen area from cardiac ...

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作者： Cui, Hengfei Xia, Yong Zhang, Yanning Zhong, Liang National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an710072 China School of Computer Science and Engineering Northwestern Polytechnical University Xi’an710072 China National Heart Centre Singapore 5 Hospital Drive Singapore169609 Singapore

Quantification of coronary artery disease (CAD) from cardiac computed tomography angiography (CTA) is important both structurally (lumen area stenosis) and functionally (combined with computational fluid dynamics to determine fractional flow reserve) for assessment of ischemic stenosis and to guide treatment. Hence, it is important to have CTA image processing technique for segmentation and reconstruction of coronary arteries. In this study, we developed segmentation and reconstruction techniques, based on fast marching and Runge–Kutta methods for centerline extraction, and surface mesh generation. The accuracy of the reconstructed models was validated with direct intravascular ultrasound (IVUS) measurements in 1950 cross sections within 4 arteries. High correlation was found between CTA and IVUS measurements for lumen areas (r= 0.993 , p2, 6 mm 2, 7 mm 2 and 8 mm 2, all ROC values >0.99). We conclude that our technique has sufficient accuracy for quantifying coronary lumen area. The accuracy and efficiency demonstrated that our approach can facilitate quantitative evaluation of coronary stenosis and potentially help in real-time assessment of CAD. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Runge Kutta methods

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Designing preamplifier for sensing atmospheric electrostatic field strength via supercapacitive sensor

Designing preamplifier for sensing atmospheric electrostatic...

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2020 International Symposium on Electronic Information technology and Communication engineering, ISEITCE 2020

作者： Wu, Changhao Xiong, Yi Zeng, Wei National Engineering Research Center for Agro-Ecological Big Data Analysis and Application School of Electronics and Information Engineering Anhui University Hefei230601 China Science and Technology Institute Hubei Key Laboratory of Biomass Fibers and Eco-Dyeing and Finishing Wuhan Textile University Wuhan430073 China School of Physics and Technology Moe Key Laboratory of Artificial Micro- and Nano-Structures Center for Electron Microscopy Wuhan University Wuhan430072 China

In order to effectively obtain the signal from sensor, the analogy signal needs to be amplified and then converted into a digital signal for matching to the sensor characteristics. With a supercapacitive electric field sensor based on graphene aerogel, the response current signal from the electric field sensor is weak and unstable. Herein, a high gain and low noise preamplifier is developed, and an amplifier circuit with double T-type feedback network is proposed to reduce the Johnson noise for the amplifier. This design can reduce the thermal noise of resistance by using the smaller resistance under the same gain, and it can effectively reduce the interference of peak noise by adding the feedback capacitance, so as to improve the detection accuracy. The simulation results show that under the same gain condition, the Johnson noise can be reduced by 46% and the detection accuracy can be improved by 12% compared with the traditional T-type feedback network. © Published under licence by IOP Publishing Ltd.

关键词： Feedback amplifiers

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Seasonal and Period Division Method for Dynamic Passenger Flow of High-Speed Railway 5th

Seasonal and Period Division Method for Dynamic Passenger Fl...

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5th International Conference on Smart Vehicular technology, Transportation, Communication and applications, VTCA 2022

作者： Han, Hui Zou, Xinqian Gao, Yiyuan Guo, Xiuyun China Railway Beijing Group Co. Ltd. Beijing300010 China School of Transportation and Logistics Southwest Jiaotong University Chengdu610031 China National and Local Joint Engineering Laboratory of Comprehensive Intelligent Transportation Southwest JiaoTong University Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Beijing China

ISBN: (纸本)9789819908479

With the large-scale construction of China's high-speed railway network, the demand for passenger flow is growing and varies in different seasons. Therefore, refinement operational requirements are increasingly prominent. However, the passenger flow itself has time-varying characteristics, and the division of passenger flow seasons and periods is divided by manual methods and experience subjectively. As a result, it is difficult to adjust it dynamically with the passenger flow changing dynamically. There are few studies on the seasons and periods of the division about high-speed railway passenger flow at home and abroad. In this study, the seasonal and period division methods of high-speed railway passenger flow were studied, the dynamic characteristics of passenger flow were analyzed, and the annual passenger flow fluctuation was considered. Then, the high-speed railway passenger flow was divided into seasons by using the firefly affinity propagation algorithm. Meanwhile, the high-speed railway passenger flow was divided into periods by employing the orderly clustering algorithm with the consideration of the daily passenger flow fluctuation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Clustering algorithms

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MyWAL:performance optimization by removing redundant input/output stack in key-value store

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Frontiers of Information technology & Electronic engineering 2023年第7期24卷 980-993页

作者： Xiao ZHANG Mengyu LI Michael NGULUBE Yonghao CHEN Yiping ZHAO School of Computer Science Northwestern Polytechnical UniversityXi'an 710072China MIIT Key Laboratory of Big Data Storage and Management Northwestern Polytechnical UniversityXi'an 710072China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Northwestern Polytechnical UniversityXi'an 710072China School of Software Northwestern Polytechnical UniversityXi'an 710072China

Based on a log-structured merge(LSM)tree,the key-value(KV)storage system can provide high reading performance and optimize random writing *** is widely used in modern data storage systems like e-commerce,online analytics,and real-time *** LSM tree stores new KV data in the memory and flushes to disk in *** prevent data loss in memory if there is an unexpected crash,RocksDB appends updating data in the write-ahead log(WAL)before updating the ***,synchronous WAL significantly reduces writing *** this paper,we present a new WAL mechanism named *** directly manages raw devices(or partitions)instead of saving data on a traditional file *** can avoid useless metadata updating and write data sequentially on *** results show that MyWAL can significantly improve the data writing performance of RocksDB compared to the traditional WAL for small KV data on solid-state disks(SSDs),as much as five to eight times *** non-volatile memory express soild-state drives(NVMe SSDs)and non-volatile memory(NVM),MyWAL can improve data writing performance by 10%–30%.Furthermore,the results of YCSB(Yahoo!Cloud Serving Benchmark)show that the latency decreased by 50%compared with SpanDB.

关键词： Key-value(KV)store Log-structured merge(LSM)tree Non-volatile memory(NVM) Non-volatile memory express soild-state drive(NVMe SSD) Write-ahead log(WAL)

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An improved cellular automata model of traffic flow with look-ahead potential1

An improved cellular automata model of traffic flow with loo...

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Chinese Automation Congress (CAC)

作者： Xiao Ma Yu-Hu Liu National Engineering Laboratory of Integrated Transportation Big Data Application Technology School of Mathematics Southwest Jiaotong University Chengdu China

ISBN: (纸本)9781665426480

This paper presents an improved automata model for traffic flow based upon models for cellular automata and traffic flow. The proposed model is concerned with the headway and multiple velocities. The proposed model enforces the stochastic rules for moving a car on the basis of traffic in front of it. Rules for updating the velocity of car relies upon the location of the car as well as front traffic and their velocities. In particular, by using numerical simulations, the model proposed in this study can reach the steady-state more quickly for random perturbations.

关键词： Analytical models Perturbation methods Electric shock Automata Stochastic processes Numerical simulation Numerical models

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Service Decomposition method for multimodal data exchange scenarios 3

Service Decomposition method for multimodal data exchange sc...

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3rd International Conference on Computer Science and Management technology, ICCSMT 2022

作者： Jiang, Deyou Huang, Lei Tian, Hanyu Xie, Yujie Li, Xiaoming Beijing Jiaotong University School of Economics and Management Beijing China Beijing Jingwei Information Technologies Limited Company National Engineering Laboratory of Comprehensive Transportation Big Data Application Technology Beijing China Institute of Computing Technologies China Academy of Railway Sciences Beijing China

ISBN: (纸本)9798350320404

Influenced by the complexity of multimodal data exchange scenarios and their differences in data flow graph construction, the objective basis of existing service decomposition methods is not sufficient, and the granularity of the results is too large and difficult to be decomposed. To address this problem, this paper presents a service decomposition method for multimodal data exchange scenarios. This method reconstructs the differentially constructed data flow diagram by unified rules at the stage of requirement analysis and design, and then completes the fine-grained division of microservices around documents based on service-decomposed rules. The case study shows that the method is more effective than the existing method in the multimodal data exchange scenario. © 2022 IEEE.

关键词： Electronic data interchange

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Research on Optimization of Operation Organization of Transship Trains in Railway Hub 5th

Research on Optimization of Operation Organization of Transs...

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5th International Conference on Smart Vehicular technology, Transportation, Communication and applications, VTCA 2022

作者： Song, Zongying Li, Yi Yue, Mengyuan Liu, Kun Lv, Miaomiao China Shenhua Energy Co. Ltd. Beijing10011 China School of Transportation and Logistics Southwest Jiaotong University Chengdu610031 China National and Local Joint Engineering Laboratory of Comprehensive Intelligent Transportation Southwest Jiaotong University Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu China

ISBN: (纸本)9789819908479

Taking the transship trains of the railway hub as the research object, a study was carried out on the optimization of the operation organization of the transship trains in the hub. With the goal of minimizing the running cost of transship trains, an optimization model of the operation organization of transship trains in railway hubs is constructed under the condition that the trains can be picked up and delivered on time. At the same time, the railway hub case is selected, the model is used to analyze, the improved SA algorithm is designed to solve it, and the model and algorithm are verified. The results show that the constructed model and algorithm can make full use of resources such as dispatching vehicles on the premise of realizing the timely pickup and delivery of trains in the hub, and obtain a suitable operation plan for transship trains in the hub, so as to minimize the overall operating cost, so as to achieve the optimization of the operation organization of transship trains in railway hubs improves the efficiency of cargo transportation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Railroads

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