检索结果-内蒙古大学图书馆

High-resolution tumor marker detection based on microwave photonics demodulated dual wavelength fiber laser sensor

Opto-Electronic Advances 2024年第12期7卷 61-77页

作者： Jie Hu Weihao Lin Liyang Shao Chenlong Xue Fang Zhao Dongrui Xiao Yang Ran Yue Meng Panpan He Zhiguang Yu Jinna Chen Perry Ping Shum Department of Electronic and Electrical Engineering Southern University of Science and TechnologyShenzhen 518055China School of Electrical Information Engineering Hunan Institute of TechnologyHengyang 421002China Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications Institute of Photonics TechnologyJinan UniversityGuangzhou 510632China Department of Clinical Laboratory Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 511436China Medcaptain Medical Technology Co. Ltd.Shenzhen 518055China

The specific detection of tumor markers is crucial in early tumor screening and subsequent treatment *** ac-curately distinguish the signal response caused by trace markers,the high demodulation resolution of the sensor is *** this paper,we propose a dual-wavelength fiber laser sensing system enhanced with microwave photonics de-modulation technology to achieve high-resolution tumor marker *** sensing system can simultaneously perform spectral wavelength-domain and frequency-domain *** results demonstrate that this system's refractive index(RI)sensitivity reaches 1083 nm/RIU by wavelength analysis and-1902 GHz/RIU by frequency analysis,with ideal detection resolutions of 1.85×10^(-5)RIU and 5.26×10^(-8)RIU,*** with traditional wavelength domain analysis,the demodulation resolution is improved by three orders of magnitude,based on the same sensing *** validate its biosensing performance,carcinoembryonic antigen-related cell adhesion molecule 5(CEACAM5)is selected as the detection *** results show that the improved sensing system has a limit of detection(LOD)of 0.076 ng/mL and a detection resolution of 0.008 ng/*** results obtained from human serum samples are consistent with clinical data,highlighting the strong clinical application potential of the proposed sens-ing system and analysis method.

关键词： optical fiber sensor optical fiber laser microwave photonics demodulation high-resolution detection tumor marker detection

来源：评论

学校读者我要写书评

暂无评论

RESEARCH ON ACCIDENT PREDICTION OF NUCLEAR POWER PLANTS BASED ON DEEP LEARNING 31

RESEARCH ON ACCIDENT PREDICTION OF NUCLEAR POWER PLANTS BASE...

引用

2024 31st International Conference on Nuclear engineering, ICONE 2024

作者： Wei, Lv Tong, Li Bo, Wang Sichao, Tan Jiangkuan, Li Ruifeng, Tian Heilongjiang Provincial Key Laboratory of Nuclear Power System and Equipment College of Nuclear Science and Technology Harbin Engineering University Harbin150001 China Key Laboratory of Nuclear Safety and Advanced Nuclear Energy Technology School of Nuclear Science and Technology Harbin Engineering University Harbin150001 China

ISBN: (纸本)9780791888261

Based on the bidirectional long short-term memory network (BILSTM) and the long short-term memory network (LSTM), this paper uses the rolling update mechanism (RU) to obtain the time series training set data and test set data of the original data, and predicts the water level and pressure changes of the Pressurizer after the LOCA accident in nuclear power plants, so as to provide a certain reference for the prediction of LOCA accidents in nuclear power plants. Specifically, the following conclusions are obtained: Compared with the LSTM model, the BILSTM model has better prediction results and less prediction loss. Although the average error of the prediction results of the two models is 10-3 orders of magnitude, the average error of BILSTM is reduced by more than 20% compared with LSTM. © 2024 by ASME.

关键词： Nuclear reactor accidents

来源：评论

学校读者我要写书评

暂无评论

Effect of dissolved organic nitrogen on the bloom of Prorocentrum donghaiense and Karenia spp. in the East China Sea coastal waters

引用

Acta Oceanologica Sinica 2024年第6期43卷 71-85页

作者： Xiaoru Cui Guangming Zhen Jing Zhao Keqiang Li Xiulin Wang Key Laboratory of Marine Chemistry Theory and Technology/Frontiers Science Center for Deep Ocean Multispheres and Earth System of Ministry of Education Ocean University of ChinaQingdao 266100China College of Environmental Science and Engineering Ocean University of ChinaQingdao 266100China College of Chemistry and Chemical Engineering Ocean University of ChinaQingdao 266100China

Understan ding the mechanism of harmful algal bloom formation is vital for effectively preventing algal bloom outbreaks in coastal *** *** in the East China Sea show a significant correlation with nutrient ***,the impact of key components of nutrients,especially dissolved organic nitrogen(DON),on the blooms of Karenia *** not *** research is still *** this study,the cruise observations,field mesocosm-flask culture experiments,and a multinitrogen-tri-phytoplankton-detritus model(NTPD) are combined to reveal the quantitative influence of nutrient regimes on the shift of Prorocentrum donghaiense and Karenia *** the East China *** has a synchronism rhythm of *** spp.-diatom loop in the field culture experiment,which is consistent with the results of the cruise *** results showed that the processes of terrigenous DON(TeDON) and dissolved inorganic nitrogen(DIN:NO_(3)^(-)-N,NH_(4)^(+)-N) absorption promoted *** to become the dominant algae in the community;whereas the processes of DON from *** absorption promoted Karenia *** become the dominant algae in ambient DIN *** addition,the three-dimensional fluorescence components of humus C,tyrosine and fulvic acid can indicate the processes of growth and extinction of *** and Karenia spp.,*** study infers that *** and Karenia *** shift mechanism associated with the nutrient regime in coastal waters,which provides a scientific basis for the environmental management of coastal eco system health.

关键词： Karenia spp. Prorocentrum donghaiense nutrients multinitrogen-tri-phytoplankton-detritus model three-dimensional fluorescence

来源：评论

学校读者我要写书评

暂无评论

Analysis on the Influence of Regional Agricultural Planting Factors on Grain Yield Based on Genetic Feedback Process Neural Network 1

引用

15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Tian, Yuan Liang, Yongquan College of Computer Science and Engineering Shandong University of Science and Technology Shandong Qingdao China Provincial Key Laboratory for Information Technology of Wisdom Mining of Shandong Province Shandong University of Science and Technology Shandong Qingdao China

ISBN: (数字)9789819700684

ISBN: (纸本)9789819700677

With the accumulation of Agricultural Big Data, the management and decision-making of agricultural planting production based on single factor expose the problem of lack of comprehensive analysis. In this paper, considering the high dimensions and time-varying characteristics of agricultural big data, a new time series analysis model based on Genetic Feedback Process Neural Network (GFPNN) is proposed to analyze the influence of regional agricultural planting factors on grain yield. Take China as an example, the data of 11 agricultural planting factors in China from 1980 to 2020 constitute a time series. Analyze the time series by GFPNN to establish the influence model of agricultural planting factors on grain yield. Results show that this model can estimate grain yield with an accuracy of 97.83%, which is more accurate and efficient than traditional neural network. It can evaluate the influence of changes in agricultural planting factors on grain yield. It can be a reference for taking measures to deal with the change of grain yield and making grain policy;in the long run, developing and introducing appropriate agricultural machinery, popularizing efficient water-saving irrigation technology, further investing in rural education, and reducing planting costs can improve the grain yield to a certain extent. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Time series analysis

来源：评论

学校读者我要写书评

暂无评论

Weakly Aligned Multi-spectral Pedestrian Detection via Cross-Modality Differential Enhancement and Multi-scale Spatial Alignment 27th

Weakly Aligned Multi-spectral Pedestrian Detection via Cros...

引用

27th International Conference on Pattern Recognition, ICPR 2024

作者： Shao, Zhenzhou Chen, Yongxin Zou, Yibo Zhang, Jie Guan, Yong The College of Information Engineering Beijing Key Laboratory of Light Industrial Robot and Safety Verification Capital Normal University Beijing100048 China The School of Optoelectronic Science and Engineering Soochow University Suzhou China The College of Information Science and Technology University of Chemical Technology Beijing China

ISBN: (纸本)9783031781124

Multi-spectral pedestrian detection has attracted extensive attention in recent years. In particular, the combination of RGB and thermal infrared images allows the around-the-clock applications, even in the poor illumination conditions. Considering the fact that RGB and thermal infrared (RGB-T) image pairs are not well aligned, it leads to the inaccuracy of pedestrian detection. To this end, this paper proposes a Multi-scale Alignment and Differential Enhancement Network (MADENet) for multi-spectral pedestrian detection, consisting of Cross-Modality Differential Enhancement Module (CDEM) and Multi-scale Spatial Alignment Module (MSAM). CDEM module is embedded in the backbone to suppress the redundant features and extract complementary information between modalities, and MSAM module is designed to align the RGB-T features by the transformation of thermal features using features of RGB image as the reference. The proposed network is evaluated on the public KAIST dataset across different scenarios. Experimental results demonstrate that the proposed method outperforms the state-of-the-art methods. Miss rate using all test set can reach 8.01. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Robust AUC maximization for classification with pairwise confidence comparisons

引用

Frontiers of Computer science 2024年第4期18卷 73-83页

作者： Haochen SHI Mingkun XIE Shengjun HUANG College of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 211106China College of Electronic and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Nanjing 211106China

Supervised learning often requires a large number of labeled examples,which has become a critical bottleneck in the case that manual annotating the class labels is *** mitigate this issue,a new framework called pairwise comparison(Pcomp)classification is proposed to allow training examples only weakly annotated with pairwise comparison,i.e.,which one of two examples is more likely to be *** previous study solves Pcomp problems by minimizing the classification error,which may lead to less robust model due to its sensitivity to class *** this paper,we propose a robust learning framework for Pcomp data along with a pairwise surrogate loss called *** provides an unbiased estimator to equivalently maximize AUC without accessing the precise class ***,we prove the consistency with respect to AUC and further provide the estimation error bound for the proposed *** studies on multiple datasets validate the effectiveness of the proposed method.

关键词： method pairwise weakly

来源：评论

学校读者我要写书评

暂无评论

High-Resolution Urban Flows Forecasting With Coarse-Grained Spatiotemporal Data

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2023年第2期4卷 315-327页

作者： Xu, Zhenyi Kang, Yu Cao, Yang Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei230088 China Department of Automation University of Science and Technology of China Hefei230026 China Chinese Academy of Sciences Key Laboratory of Technology in GeoSpatial Information Processing and Application System Beijing100192 China

Urban flow monitoring and forecasting systems play important roles in smart city management. However, due to the long-lasting and enormous deployment cost of ubiquitous traffic monitoring devices (e.g., loop detectors, traffic video detection), it is very difficult to predict flow in high-resolution (HR) with limited monitoring devices. The existing spatiotemporal network based methods usually predict the urban flow in the same spatial scale without considering the spatial correlations between coarse-grained and fine-grained urban flows. To tackle these issues, we propose a HR spatiotemporal transformer network (HRSTT) to predict fine-grained urban flow. Specifically, residual convolution units are employed to constructs the high-level features of three-view temporal (e.g., closeness, period, and trend) flow data. Then, a transformer block is designed to jointly learn the spatiotemporal dynamic features of each temporal flow with self-attention mechanism. For the external factors (e.g., holidays, weather conditions) are extracted by embedding dense networks, which are fused with high level coarse-grained flow feature maps with gated-fusion scheme. Finally, the coarse-grained fusion feature maps are transferred to the distributional upsampling module, generating the fined-grained flow map of target predicted time. Furthermore, the proposed model is evaluated with several baselines on real-world TaxiBJ datasets, demonstrating the state-of-the-art performance of our approach on the fine-grained urban flow forecasting problem. © 2020 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning-Based Approach for Anomaly Detection for Secure Cloud Computing Environments

A Machine Learning-Based Approach for Anomaly Detection for ...

引用

2023 International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2023

作者： Parameswarappa, Priya Shah, Taral Lanke, Govinda Rajulu University of the Cumberlands School of Technology United States Pace Univerty School of Information System United States Birla Institute of Technology and Science Data Science and Engineering India

ISBN: (纸本)9781665474511

The concept of "cloud computing"has been presented as a promising strategy for providing online service hosting and distribution. Despite the widespread adoption of cloud computing, security remains a top priority. Several secure methods have been devised to safeguard communication in such scenarios, with the majority of these solutions based on attack signatures. Unfortunately, these technologies cannot always detect every possible danger. A machine learning method was recently outlined. The judgment could be inaccurate if the training set is missing examples from a certain category. In this research, an innovative firewall strategy for safe cloud-based computing is presented using machine learning system. The proposed methods estimate the final assault category categorization by combining the judgments of the nodes from the past with the decision of the machine learning algorithm in the present, a technique termed most frequent decision. Both learning efficiency and system precision are improved by this method. Our results are based on UNSW-NB-15, a publicly available dataset. According to the evidence provided by our data, it improves anomaly detection by 97.68 percent. A Machine Learning-Based Approach for Anomaly Detection for Secure Cloud Computing Environments © 2023 IEEE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Stabilizing zinc anode using zeolite imidazole framework functionalized separator for durable aqueous zinc-ion batteries

引用

Journal of Energy Chemistry 2024年第3期90卷 23-31,I0003页

作者： Weisong Zhang Xinyan Zhu Ling Kang Ziyu Peng Jing Zhu Liang Pan Lei Dai Shude Liu Ling Wang Yongguang Liu Zhangxing He School of Chemical Engineering North China University of Science and TechnologyTangshan 063009HebeiChina Shanghai Key Laboratory of Multidimensional Information Processing East China Normal UniversityShanghai 201620China College of Textiles Donghua UniversityShanghai 201620China

Aqueous zinc-ion batteries(AZIBs) hold great promise as a viable alternative to lithium-ion batteries owing to their high energy density and environmental ***,AZIBs are consistently plagued by the formation of zinc dendrites and concurrent side reactions,which significantly diminish their overall service life,In this study,the glass fiber separator(GF) is modified using zeolite imidazole salt framework-8(ZIF-8),enabling the development of efficient ***-8,which is abundant in nitrogen content,efficiently regulates the desolvation of [Zn(H_(2)O)_(6)]^(2+) to inhibit hydrogen ***,it possesses abundant nanochannels that facilitate the uniform deposition of Zn~(2+) via a localized action,thereby hindering the formation of *** insulating properties of ZIF-8 help prevent Zn^(2+) and water from trapping electron reduction at the layer surface,which reduces corrosion of the zinc ***,ZIF-8-GF achieves the even transport of Zn^(2+) and regulates the homogeneous deposition along the Zn(002) crystal surface,thus significantly enhancing the electrochemical performance of the AZIBs,In particular,the Zn|Zn symmetric cell with the ZIF-8-GF separator delivers a stable cycle life at0.5 mA cm^(-2) of 2300 *** Zn|ZIF-8-GF|MnO_(2) cell exhibits reduced voltage polarization while maintaining a capacity retention rate(93.4%) after 1200 cycles at 1.2 A g^(-1) The unique design of the modified diaphragm provides a new approach to realizing high-performance AZIBs.

关键词： Aqueous zinc-ion batteries Separators modifications ZIF-8 Zn deposition Dendrite-free

来源：评论

学校读者我要写书评

暂无评论

Molecular Code-Division Multiple-Access for Nano-Sensor Networks: Signaling, Detection, and Performance

引用

IEEE Sensors Journal 2025年第12期25卷 23003-23017页

作者： Gao, Weidong Shi, Lu Yang, Lie-Liang Wuxi University College of Electronic Information Engineering Jiangsu Province Engineering Research Center of Photonic Devices and System Integration for Communication Sensing Convergence Wuxi214105 China Chongqing University of Science and Technology School of Intelligent Technology and Engineering Chongqing401331 China University of Southampton School of Electronics and Computer Science SO17 1BJ United Kingdom

o accomplish relatively complex tasks of, such as, monitoring in vivo, information collected by different nano-sensors (NSs) is usually sent via multiple-access channels to fusion centers (FCs) for further processing.o accomplish relatively complex tasks of, such as, monitoring in vivo, information collected by different nano-sensors (NSs) is usually sent via multiple-access channels to fusion centers (FCs) for further processing.T Relying on two types of molecules, in this paper, a molecular code-division multiple-access (MoCDMA) scheme is designed for multiple NSs to simultaneously send information to an access-point (AP) in a diffusive molecular communications (DMC) environment. We assume that different NSs may have different distances from AP, which generates ‘nearfar’ effect. Correspondingly, the uniform and channel-inverse based molecular emission schemes are proposed for NSs to emit information molecules. To facilitate the design of different signal detection schemes, the received signals by AP are represented in different forms. Specifically, by considering the limited computational power of nano-devices, three low-complexity detectors are designed in the principles of matched-filtering (MF), zero-forcing (ZF), and minimum mean-square error (MMSE). The noise characteristics in MoCDMA systems and the complexity of various detection schemes are analyzed. The error performance of the MoCDMA systems with various molecular emission and detection schemes is demonstrated and compared. Our studies and performance results demonstrate that MoCDMA constitutes a promising scheme for supporting multiple-access transmission in DMC, while the channel-inverse based transmission can ensure the fairness of communication qualities (FoCQ) among different NSs. Furthermore, different detection schemes may be implemented to attain a good trade-off between implementation complexity and communication reliability. © 2001-2012 IEEE.

关键词： Mean square error

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：