检索结果-内蒙古大学图书馆

6th International Conference on Geoscience and Remote Sensing Mapping, GRSM 2024

作者： Deng, Fengying Qiao, Baojun Li, Kaitao Zhao, Limin Chen, Xingfeng Li, Jiaguo Liu, Jun Sun, Yuan Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China Aerospace Information Research Institute Chinese Academy of Science Beijing China School of Space Information Space Engineering University Beijing China

ISBN: (纸本)9781510688018

Wind turbine detection is essential for the power industry and regulatory agencies to efficiently and accurately determine their number and spatial distribution. Under complex underlying surface conditions, the detection accuracy of conventional methods is low, especially when dealing with multi-scale wind turbine targets. In addition, the underutilization of the near-infrared (NIR) band limits the capability of optical remote sensing sensors in wind turbine detection. To address the above problems, this paper proposes a wind turbine detection algorithm YOLOv8m-BD based on high spatial resolution four-band reflectance images using YOLOv8m as the baseline model. Firstly, the four-band image is input through channel adaptation modification. Next, the CSPDarknet53 to 2-stage FPN (C2f) module is enhanced by introducing deformable convolution (DCN) to expand the receptive field. Finally, the effectiveness of our design was validated through extensive experiments on a self-built wind turbine dataset. Compared to the YOLOv8m baseline model that only inputs RGB three bands, the improved YOLOv8m-BD achieves an accuracy of 96.4% and a false alarm rate of 2.0%, an increase of 3.4% in accuracy and a decrease of 2.5% in false alarm rate. © 2025 SPIE.

关键词： Proximity sensors

来源：评论

学校读者我要写书评

暂无评论

Geological big data utilization in public health

Geological big data utilization in public health

引用

2024 International Conference on Remote Sensing and Digital Earth, RSDE 2024

作者： Wang, Liang Jia, Liqiong Yang, Shuqi Li, Sixia Yan, Hongwei Natural Resources Integrated Survey Command Center China Geological Survey Beijing100055 China Applied Geology Data Research Center Laboratory for Big Data and Decision Beijing100055 China Development and Research Center China Geological Survey Beijing100037 China Research Center of Applied Geology China Geological Survey Sichuan Chengdu610036 China

ISBN: (数字)9781510688223

ISBN: (纸本)9781510688216

This research delves into the uses of big data, in public health and emphasizes its crucial role in assessing health risks,data control of disease transmission and allocation of public health *** big data,serving as an resource could shed light on the complex connection between environmental factors and public health introducing new predictive models for health risks evidence based strategies, for mitigating diseases and sensible distribution of public health resources. Facing challenges related to data accuracy and privacy protection as technical processing issues doesn't diminish the undeniable value of using this technology for making well informed decisions, in public health matters. Looking ahead to the synergy of advancements and regulatory improvements in disciplines and anticipating the integration of extensive geological data, into public health initiatives promises to enhance the precision and effectiveness of managing healthcare systems in the future. © 2025 SPIE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Cost Effective and Sensitive Electrochemical Detection of Dopamine on Laser Driven Sensor

Cost Effective and Sensitive Electrochemical Detection of Do...

引用

International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Mrinal Vashisth Amrit L. Hui Department of Psychology National Research Tomsk State University Tomsk Russian Federation Research Laboratory of Applied Big Data Analysis National Research Tomsk State University Tomsk Russian

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

In this research, a cost-effective sensor was developed for the electrochemical detection for dopamine in the biological samples. The optimal laser parameters were used to fabricate graphene oxide (GO) material to obtain the highly stable laser induced graphene oxide (LIGO) sensor. The surface behavior of the sensor was studied by scanning electron microscope (SEM), Raman spectroscopy (RS) and electrochemical characterization were carried out vis cyclic voltammetry. The electroactive surface area of sensor was studied which shows the remarkable electron transfer mobility. The sensor shows promising linear concentration range (1–100 μM) and lower limit of detection (0.1μM). The LIGO sensor also demonstrates good reproducibility and stability. Moreover, the LIGO sensor showed the sensitive detection for dopamine concentration in serum and urine with good regain. However, low cost and highly efficient LIGO sensor shows tremendous application on real detection of dopamine.

关键词： Scanning electron microscopy Costs Graphene Power lasers Surface morphology Surface emitting lasers Laser stability Reproducibility of results Surface treatment Substrates

来源：评论

学校读者我要写书评

暂无评论

Correction to: Well-Balanced Fifth-Order Finite Volume WENO Schemes with Constant Subtraction Technique for Shallow Water Equations

引用

Journal of Scientific Computing 2025年第1期103卷 1-4页

作者： Zhao, Lidan Tao, Zhanjing Zhang, Min School of Mathematics Jilin University Changchun China National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing China Chongqing Research Institute of Big Data Peking University Chongqing China

来源：评论

学校读者我要写书评

暂无评论

Laser Driven Flexible Ultra-Robust Sensor for Bioelectronic Applications

Laser Driven Flexible Ultra-Robust Sensor for Bioelectronic ...

引用

International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

Nowadays there is an importance of flexible carbon-based sensors for sensitive detection of human skin interference signal to develop biomedical applications. In this research, the cost effective, flexible sensor has been fabricated based on laser induced graphene oxide (LIG) on green substrate for the acquisition of biomedical signal. The ecofriendly laser reduction process was used to develop highly stable sensor, which enhanced the biomedical signal. The newly fabricated flexible dry sensor is studied to overcome the limitation of currently available sensor. The sensor surface morphology was characterized by Scanning Electron Microscopy (SEM), and Fourier Transform Infrared Spectroscopy (FTIR) was performed to analyze the absorption processes bands of Graphene oxide (GO). These sensors are flexible and adhere more compatibly to human skin. In terms of performance, the fabricated LIG sensor show low impedance as compared to commercial sensor for bio-signal detection. The fabricated sensor has recorded low signal to noise ratio (SNR) as compared to commercial sensor. Furthermore, the developed sensor was tested for temperature, strain, and breathing sensing. The results indicate that the developed sensor is reusable without gel. Finally, the developed dry sensor provides good biocompatibility, excellent skin and sensor contact and no significant irritation on skin.

关键词： Temperature sensors Surface impedance Scanning electron microscopy Graphene Surface morphology Sensor phenomena and characterization Skin Biosensors Surface treatment Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Sensitive EEG Brain Signal Detection for RGB Color Using Laser Integrated Electrode

Sensitive EEG Brain Signal Detection for RGB Color Using Las...

引用

International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Amrit L. Hui Mrinal Vashisth Research Laboratory of Applied Big Data Analysis National Research Tomsk State University Tomsk Russian Federation Department of Psychology National Research Tomsk State University Tomsk Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

The sensor technology has allowed for sensitive detection of Electroencephalography (EEG) signals. In this work, the ecofriendly flexible laser induced graphene oxide (LIG) electrode was fabricated for Red, Green and Blue (RGB) neural signal detection. The flexible recycle substrate was used for the fabrication of the electrodes. The laser engraving process was performed on the graphene oxide electrodes which enhanced the surface area of electrode. The laser optimization was done to obtain suitable conductive electrode. The electrode surface morphology was studied by impedance method and scanning electron microscopy (SEM). The integrated circuit was fabricated in order to achieve highly sensitive neural signals for RGB colors. The 18 dry LIG electrode setup was employed to investigate RGB color neural signals in 15 participants. The obtained RGB neural signals are smooth due to good conductivity of dry LIG electrodes as compared to commercial electrodes. The performance of dry LIG electrodes is promising than commercial electrode. The fabrication cost of dry LIG electrode is ten times cheaper than commercially manufactured electrode.

关键词： Electrodes Scanning electron microscopy Surface impedance Image color analysis Graphene Measurement by laser beam Surface morphology Electroencephalography Surface treatment Signal detection

来源：评论

学校读者我要写书评

暂无评论

A unifying moving mesh method for curves, surfaces, and domains based on mesh equidistribution and alignment

arXiv

引用

arXiv 2025年

作者： Zhang, Min Huang, Weizhang National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing100871 China Chongqing Research Institute of Big Data Peking University Chongqing401121 China Department of Mathematics University of Kansas LawrenceKS66045 United States

A unifying moving mesh method is developed for general m-dimensional geometric objects in d-dimensions (d ≥ 1 and 1 ≤ m ≤ d) including curves, surfaces, and domains. The method is based on mesh equidistribution and alignment and does not require the availability of an analytical parametric representation of the underlying geometric object. Mathematical characterizations of shape and size of m-simplexes and properties of corresponding edge matrices and affine mappings are derived. The equidistribution and alignment conditions are presented in a unifying form for m-simplicial meshes. The equation for mesh movement is defined based on the moving mesh PDE approach, and suitable projection of the nodal mesh velocities is employed to ensure the mesh points stay on the underlying geometric object. The analytical expression for the mesh velocities is obtained in a compact matrix form. The nonsingularity of moving meshes is proved. Numerical results for curves (m = 1) and surfaces (m = 2) in two and three dimensions are presented to demonstrate the ability of the developed method to move mesh points without causing singularity and control their concentration. Copyright © 2025, The Authors. All rights reserved.

关键词： Mesh generation

来源：评论

学校读者我要写书评

暂无评论

Five-user quantum virtual local area network with an AlGaAs entangled photon source

引用

Science China(Physics,Mechanics & Astronomy) 2025年第3期68卷 61-73页

作者： Cheng Qian Hongkai Tian Xu Jing Yichen Liu Zhe Chen Huiran Luo Yuan Du Xiaodong Zheng Tangsheng Chen Yuechan Kong Hua-Lei Yin Dong Jiang Bin Niu Liangliang Lu Key Laboratory of State Manipulation and Advanced Materials in Provincial Universities School of Physical Science and TechnologyNanjing Normal UniversityNanjing210023China School of Internet Anhui UniversityHefei230039China National Key Laboratory of Solid-State Microwave Devices and Circuits Nanjing Chip Valley Industrial Technology InstituteNanjing Electronic Devices InstituteNanjing210016China Research Center for Quantum Optics and Quantum Communication School of ScienceQingdao University of TechnologyQingdao266520China Department of Physics and Beijing Key Laboratory of Opto-electronic Functional Materials and Micro-nano Devices Key Laboratory of Quantum State Construction and Manipulation(Ministry of Education)Renmin University of ChinaBeijing100872China Beijing Academy of Quantum Information Sciences Beijing100193China National Engineering Research Center of Agro-Ecological Big Data Analysis and Application Anhui UniversityHefei230601China National Laboratory of Solid-State Microstructures and School of Physics Nanjing UniversityNanjing210093China Hefei National Laboratory Hefei230088China

The promotion of quantum network applications demands the scalable connection of quantum *** is preferable to set up multiple logical networks coexisting on a single physical network infrastructure to accommodate a larger number of *** we present a quantum virtual network architecture that offers this level of scalability,without being constrained to a fixed physical-layer network relying solely on passive multiplexing *** architecture can be understood as arising from the superposition of a fully connected entanglement distribution network and port-based virtual local area network,which group multiusers by access *** terms of hardware,we leverage a semiconductor chip with a high figure-of-merit modal overlap to directly generate high-quality polarization entanglement,and a streamlined polarization analysis module,which requires only one single-photon detector for each end *** experimentally perform the BBM92 QKD protocol on the five-user quantum virtual network and demonstrate voice and image encryption on a campus area *** results may provide insights into the realization of large-scale quantum networks with integrated and cost-efficient photonic architecture.

关键词： quantum network quantum entanglement distribution integrated photonics image and voice encryption

来源：评论

学校读者我要写书评

暂无评论

A deep learning lightweight model for real-time captive macaque facial recognition based on an improved YOLOX model

引用

Zoological research 2025年第2期46卷 339-354页

作者： Jia-Jin Zhang Yu Gao Bao-Lin Zhang Dong-Dong Wu Key Laboratory of Genetic Evolution&Animal Models Kunming Natural History Museum of ZoologyKunming Institute of ZoologyChinese Academy of SciencesKunmingYunnan 650201China College of Big Data Yunnan Agricultural UniversityKunmingYunnan 650201China National Resource Center for Non-Human Primates Kunming Primate Research Centerand National Research Facility for Phenotypic&Genetic Analysis of Model Animals(Primate Facility)Kunming Institute of ZoologyChinese Academy of SciencesKunmingYunnan 650107China Yunnan Key Laboratory of Biodiversity Information KunmingYunnan 650223China Center for Excellence in Animal Evolution and Genetics Chinese Academy of SciencesKunmingYunnan 650201China

Automated behavior monitoring of macaques offers transformative potential for advancing biomedical research and animal ***,reliably identifying individual macaques in group environments remains a significant *** study introduces ACE-YOLOX,a lightweight facial recognition model tailored for captive ***-YOLOX incorporates Efficient Channel Attention(ECA),Complete Intersection over Union loss(CIoU),and Adaptive Spatial Feature Fusion(ASFF)into the YOLOX framework,enhancing prediction accuracy while reducing computational *** integrated approaches enable effective multiscale feature *** a dataset comprising 179400 labeled facial images from 1196 macaques,ACE-YOLOX surpassed the performance of classical object detection models,demonstrating superior accuracy and real-time processing *** Android application was also developed to deploy ACE-YOLOX on smartphones,enabling on-device,real-time macaque *** experimental results highlight the potential of ACE-YOLOX as a non-invasive identification tool,offering an important foundation for future studies in macaque facial expression recognition,cognitive psychology,and social behavior.

关键词： YOLOX Macaque Facial recognition Identity recognition Animal welfare

来源：评论

学校读者我要写书评

暂无评论

Adaptive disentangled target representation for unsupervised domain adaptation in remote sensing segmentation

引用

Engineering Applications of Artificial Intelligence 2025年 156卷

作者： Lu, Runuo Dong, Shoubin Jia, Jianxin Wang, Xusheng Liu, Kai Chen, Jinsong Guo, Shanxin Zheng, Xiaorou Guangdong Provincial Key Laboratory of Multimodal Big Data Intelligent Analysis School of Computer Science and Engineering South China University of Technology Guangzhou510641 China Department of Photogrammetry and Remote Sensing Finnish Geospatial Research Institute EspooFI-02150 Finland Center for Geo-Spatial Information Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen Engineering Laboratory of Ocean Environmental Big Data Analysis and Application Shenzhen518055 China

Due to the significant differences between the source and target domains, semantic segmentation models for remote sensing images trained on the source domain often struggle to generalize effectively to new target domains, leading to performance degradation. Most solutions disentangle features into domain-invariant features shared by both domains and domain-specific features unique to each domain, relying primarily on the domain-invariant features for model construction and inference. However, during this process, critical domain-specific features as essential information are often discarded as noise, leading to a reduction in segmentation accuracy. To address these issues, this study proposes an unsupervised domain adaptation, called ChameleonRS. ChameleonRS separates the domain-invariant features and the domain-specific features by disentanglement learning, and introduces a multi-level feature alignment module to enhance the representation of domain-invariant features. More importantly, it aligns predictions based on domain-invariant features with those based on fused invariant and specific features using contrastive learning, effectively capturing target-specific features. This study explores two cross-domain semantic segmentation tasks: (I) Geographic location variation. (II) Geographic location and imaging mode variation. Results show that under setting (I), ChameleonRS outperforms the state-of-the-art method by 4.79% in Intersection over Union (IoU) and 6.51% in the F1 score. Under setting (II), it achieves improvements of 4.46% and 4.82% in IoU and F1 score. Results demonstrate the superiority and adaptability of ChameleonRS under varying geographical and imaging conditions, effectively mitigating the generalization issues caused by distribution differences, and thereby promoting the development and application of remote sensing technologies in practical scenarios. © 2025 Elsevier Ltd

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：