|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Semantic information processing in industrial networks显示文摘The industrial Internet of things(industrial IoT, IIoT) aims at connecting everything, which poses severe challenges to existing wireless communication. To handle the demand for massive access in future industrial networks, semantic information processing is integrated into communication systems so as to improve the effectiveness and efficiency of data transmission. The semantic paradigm is particularly suitable for the purpose-oriented information exchanging scheme in industrial networks. To illustrate its applicability, typical industrial data are investigated, i.e., time series and images. Simulation results demonstrate the superiority of semantic information processing, which achieves a better rate-utility tradeoff than conventional signal processing. | Yao Shengshi Wang Sixian Dai Jincheng Niu Kai Xu Wenjun Zhang Ping | 2022 | The Journal of China Universities of Posts and Telecommunications2022，29，1： | 2 |
| 2 | Digital twins in smart farming:An autoware-based simulator for autonomous agricultural vehicles显示文摘Digital twins can improve the level of control over physical entities and help manage complex systems by integrating a range of technologies.The autonomous agricultural machine has shown revolutionary effects on labor reduction and utilization rate in field works.Autonomous vehicles in precision agriculture have the potential to improve competitiveness compared to current crop production methods and have become a research hotspot.However,the development time and resources required in experiments have limited the research in this area.Simulation tools in unmanned farming that are required to enable more efficient,reliable,and safe autonomy are increasingly demanding.Inspired by the recent development of an open-source virtual simulation platform,this study proposed an autoware-based simulator to evaluate the performance of agricultural machine guidance based on digital twins.Oblique photogrammetry using drones is used to construct threedimensional maps of fields at the same scale as reality.A communication format suitable for agricultural machines was developed for data input and output,along with an inter-node communication methodology.The conversion,publishing,and maintenance of multiple coordinate systems were completed based on ROS(Robot Operating System).Coverage path planning was performed using hybrid curves based on Bézier curves,and it was tested in both a simulation environment and actual fields with the aid of Pure Pursuit algorithms and PID controllers. | Xin Zhao Wanli Wang Long Wen Zhibo Chen Sixian Wu Kun Zhou Mengyao Sun Lanjun Xu Bingbing Hu Caicong Wu | 2023 | International Journal of Agricultural and Biological Engineering2023，16，4： | 0 |
| 3 | The impact of key parameters on the cycle efficiency of multi-stage RCAES system显示文摘Due to the uncertainty and anti-peaking nature,large scale integration of renewable energy imposes great challenges to the operation and dispatch of power systems.Compressed air energy storage(CAES)system provides new ideas to solve this problem as its characteristics of fast regulating,flexible location and long-service life.Especially,regenerative compressed air energy storage(RCAES)system is widely concerned as its capability of heat recovery in the compression process.The cycle efficiency is a key indicator of RCAES system which can be significantly impacted by the key parameters of the systems including compression ratio,exhaust air pressure of throttle(EAPT)and the maximum working pressure(MWP)of compressed air storage vessel(CASV).However,current research mostly focuses on the thermodynamic process and few studies have focused on the impact of key parameters on RCAES system.Based on the efficiency evaluation method which was formulated through the electricalmechanical-thermal dynamic process and measurable parameters,the impact of key parameters on the cycle efficiency of RCAES system is analyzed in this paper and a practical RCAES design scheme is adopted for case study. | Bin LIU Laijun CHEN Shengwei MEI Feng LIU Junjie WANG Sixian WANG | 2014 | Journal of Modern Power Systems and Clean Energy2014，2，4： | 0 |
| 4 | Construction of a Cu@hollow TS-1 nanoreactor based on a hierarchical full-spectrum solar light utilization strategy for photothermal synergistic artificial photosynthesis显示文摘The artificial photosynthesis technology has been recognized as a promising solution for CO_(2) utilization.Photothermal catalysis has been proposed as a novel strategy to promote the efficiency of artificial photosynthesis by coupling both photochemistry and thermochemistry.However,strategies for maximizing the use of solar spectra with different frequencies in photothermal catalysis are urgently needed.Here,a hierarchical full-spectrum solar light utilization strategy is proposed.Based on this strategy,a Cu@hollow titanium silicalite-1 zeolite(TS-1)nanoreactor with spatially separated photo/thermal catalytic sites is designed to realize high-efficiency photothermal catalytic artificial photosynthesis.The space-time yield of alcohol products over the optimal catalyst reached 64.4μmol g−1 h−1,with the selectivity of CH3CH2OH of 69.5%.This rationally designed hierarchical utilization strategy for solar light can be summarized as follows:(1)high-energy ultraviolet light is utilized to drive the initial and difficult CO_(2) activation step on the TS-1 shell;(2)visible light can induce the localized surface plasmon resonance effect on plasmonic Cu to generate hot electrons for H2O dissociation and subsequent reaction steps;and(3)low-energy near-infrared light is converted into heat by the simulated greenhouse effect by cavities to accelerate the carrier dynamics.This work provides some scientific and experimental bases for research on novel,highly efficient photothermal catalysts for artificial photosynthesis. | Sixian Zhu Qiao Zhao Hongxia Guo Li Liu Xiao Wang Xiwei Qi Xianguang Meng Wenquan Cui | 2024 | Carbon Energy2024，6，2： | 0 |
| 5 | Learning Discriminatory Information for Object Detection on Urine Sediment Image显示文摘In clinical practice,the microscopic examination of urine sediment is considered an important in vitro examination with many broad applications.Measuring the amount of each type of urine sediment allows for screening,diagnosis and evaluation of kidney and urinary tract disease,providing insight into the specific type and severity.However,manual urine sediment examination is labor-intensive,time-consuming,and subjective.Traditional machine learning based object detection methods require hand-crafted features for localization and classification,which have poor generalization capabilities and are difficult to quickly and accurately detect the number of urine sediments.Deep learning based object detection methods have the potential to address the challenges mentioned above,but these methods require access to large urine sediment image datasets.Unfortunately,only a limited number of publicly available urine sediment datasets are currently available.To alleviate the lack of urine sediment datasets in medical image analysis,we propose a new dataset named UriSed2K,which contains 2465 high-quality images annotated with expert guidance.Two main challenges are associated with our dataset:a large number of small objects and the occlusion between these small objects.Our manuscript focuses on applying deep learning object detection methods to the urine sediment dataset and addressing the challenges presented by this dataset.Specifically,our goal is to improve the accuracy and efficiency of the detection algorithm and,in doing so,provide medical professionals with an automatic detector that saves time and effort.We propose an improved lightweight one-stage object detection algorithm called Discriminatory-YOLO.The proposed algorithm comprises a local context attention module and a global background suppression module,which aid the detector in distinguishing urine sediment features in the image.The local context attention module captures context information beyond the object region,while the global background suppression module emphasizes objects in uninformative backgrounds.We comprehensively evaluate our method on the UriSed2K dataset,which includes seven categories of urine sediments,such as erythrocytes(red blood cells),leukocytes(white blood cells),epithelial cells,crystals,mycetes,broken erythrocytes,and broken leukocytes,achieving the best average precision(AP)of 95.3%while taking only 10 ms per image.The source code and dataset are available at https://github.com/binghuiwu98/discriminatoryyolov5. | Sixian Chan Binghui Wu Guodao Zhang Yuan Yao Hongqiang Wang | 2024 | Computer Modeling in Engineering & Sciences2024，138，1： | 0 |
| 6 | Effects of Tuina on Obesity-Induced Insulin Resistance and Cognitive Dysfunction显示文摘This paper discusses the mechanism of insulin resistance in obesity from the research progress of Chinese and Western medicine and its oxidative stress,inflammatory reaction and abnormal lipid metabolism in cognitive dysfunction.It also reviews the research progress of massage,one of the external treatment methods of traditional Chinese medicine,in the treatment of insulin resistance and cognitive dysfunction in obesity,in order to provide more new ideas and new ways for clinical diagnosis and treatment of insulin resistance and related cognitive dysfunction caused by obesity. | Mingjun LIU Xiaochao GANG Chongwen ZHONG Shaotao CHEN Yuxing TAI Yi TAN Likun ZHENG Zhengri CONG Sixian WANG Peizhe LI Qifan GUAN Yiduo LI | 2023 | Medicinal Plant2023，14，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员