检索结果-内蒙古大学图书馆

3rd International Symposium on Sensor Technology and control, ISSTC 2024

作者： Fu, Maixia Zhang, Tiantian Liu, Zhonghao Liu, Mengyi Wang, Dongdong Ministry of Education Henan University of Technology Key Laboratory of Grain Information Processing and Control Zhengzhou450001 China Henan University of Technology College of Information Science and Engineering Zhengzhou450001 China

ISBN: (纸本)9798331541637

A terahertz refractive index sensor constructed with graphene metamaterial absorber has been proposed. The sensor features a patterned graphene structure, consisting of an independent circular ring and a special structure formed by intersecting cross and square patterns. Under normal incidence of TM and TE polarized light, the sensor exhibits a low-frequency peak at 1.55 THz with maximum absorption rates of 9 9. 4 5% and a high-frequency peak at 3.83 THz with maximum absorption rates of 9 9. 5 0%. The quality factors (Q factor) of the two peaks are 31 and 65, respectively. Unlike traditional metal sensors, the absorption peaks of this sensor can achieve dynamic tunability through adjusting the graphene's Fermi level. By varying the analyte's thickness and refractive index, the maximum sensitivity of the two absorption peaks can reach 495 GHz RIU and 895 GHz/ RIU. The corresponding figures of merit (FOM) are 9.9 and 15.2, respectively. The sensor proposed here are applied to detect hemoglobin biomolecule content and has shown excellent sensing performance in our simulations. Therefore, the present work has broad potential for applications in biomedical and medical diagnostic fields. © 2024 IEEE.

关键词： Q factor measurement

来源：评论

学校读者我要写书评

暂无评论

Echo state network based symbol detection in chaotic baseband wireless communication

引用

Digital Communications and Networks 2023年第6期9卷 1319-1330页

作者： Huiping Yin Chao Bai Haipeng Ren Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of TechnologyXi'an710048China Xi'an Key Laboratory of Intelligent Equipment Xi'an Technological UniversityXi'an710021China

The Chaotic Baseband Wireless Communication System(CBWCS)is expected to eliminate the Inter-Symbol Interference(ISI)caused by multipath propagation by using the optimal decoding threshold that is the sum of the ISI caused by past decoded bits and the ISI caused by future transmitting ***,the current technique is only capable of removing partial effects of the ISI,because only past decoded bits are available for the suboptimal decoding threshold *** unavailability of the future information needed for the optimal decoding threshold is an obstacle to further improve the Bit Error Rate(BER)*** contrast to the previous method using Echo State Network(ESN)to predict one future bit,the proposed method in this paper predicts the optimal decoding threshold directly using *** proposed ESN-based threshold prediction method simplifies the symbol decoding operation by avoiding the iterative prediction of the output waveform points using ESN and accumulated error caused by the iterative *** this approach,the calculation complexity is reduced compared to the previous ESN-based *** proposed method achieves better BER performance compared to the previous *** reason for this superior result is ***,the proposed ESN is capable of using more future symbols information conveyed by the ESN input to obtain more accurate threshold rather than the previous method in which only one future symbol was ***,the proposed method here does not need to estimate the channel information using Least Squared(LS)method,which avoids the extra error caused by inaccurate channel information *** results and experiment based on a wireless open-access research platform under a practical wireless channel show the effectiveness and superiority of the proposed method.

关键词： Chaotic baseband wireless communication system(CBWCS) Inter-symbol interference(ISI) Echo state network(ESN) Threshold prediction

来源：评论

学校读者我要写书评

暂无评论

Research on grain Yield Prediction Model Based on Wavelet transform and LSTM 3

Research on Grain Yield Prediction Model Based on Wavelet tr...

引用

3rd International Seminar on Artificial Intelligence, Networking, and information Technology, AINIT 2022

作者： Zhu, Chunhua Li, Pengle Key Laboratory of Grain Information Processing and Control Henan University of Technology Ministry of Education China College of Information Science and Engineering Henan University of Technology China Henan Key Laboratory of grain photoelectric detection and control Henan University of Technology Zhengzhou Henan China

ISBN: (数字)9781510662971

ISBN: (纸本)9781510662964

To improve the accuracy of grain yield prediction, a grain yield prediction model based on wavelet transform and long short-term memory (LSTM) is proposed. Firstly, the original data is decomposed by wavelet transform algorithm to obtain a series of sub-sequences of different scales, and then LSTM prediction models are built for the sub-sequences, finally wavelet reconstruction is used to obtain the predicted yield and analyze the model performance. The article uses China's 1999-2018 grain yield as experimental data. The experiment shows that the method proposed in this article has excellent performance in both short-term and medium-term predictions compared to the existing methods. © 2023 SPIE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Mitigation of polycyclic aromatic hydrocarbons(PAHs)in roasted beef patties by cold plasma treatment and products quality evaluation

引用

Food Science and Human Wellness 2024年第5期13卷 2993-3005页

作者： Yuke Hou Yangjian Hu Min Li Jiahui Nong Fengyuan Xie Yuhan Fan Jianhao Zhang Xianming Zeng Minyi Han Xinglian Xu Xia Wang Key Laboratory of Animal Products Processing Ministry of AgricultureKey Laboratory of Meat Processing and Quality ControlMinistry of EducationJiangsu Synergetic Innovation Center of Meat Production and ProcessingCollege of Food Science and TechnologyNanjing Agricultural UniversityNanjing 2100095China Center for Food and Drug Safety Inspection of Maanshan Maanshan Administration for Market RegulationMaanshan 243000China Henan Key Laboratory of Cold Chain Food Quality and Safety Control Zhengzhou University of Light IndustryZhengzhou 450001China Collaborative Innovation Center for Modern Grain Circulation and Safety Key Laboratory of Grains and Oils Quality Control and ProcessingCollege of Food Science and EngineeringNanjing University of Finance and EconomicsNanjing 210023China

The cold plasma(CP)technique was applied to alleviate the contamination of polycyclic aromatic hydrocarbon(PAH)in this *** different CP treatments methods were implemented in the production of beef patties,to investigate their inhibition and degradation capacity on *** 5 different cooking oils and fats addition,the inhibition mechanism of in-package cold plasma(ICP)pretreatment was explored from the aspect of raw patties fatty acids composition *** results of principal component analysis showed that the first two principal components accounted for more than 80%of the total variation in the original data,indicating that the content of saturated fatty acids was significantly positively correlated with the formation of *** pretreatment inhibited the formation of PAHs by changing the composition of fatty acids,which showed that the total amount of polyunsaturated fatty acids decreased and the total amount of monounsaturated fatty acids *** discrimination tests demonstrated there were discernable differences between 2 CP treated samples and the controls,utilization of the ICP pretreatment in meat products processing was expected to achieve satisfying eating *** conclusion,CP treatment degraded PAHs through stepwise ring-opening oxidation in 2 reported pathways,the toxicity of PAHs contaminated products was alleviated after CP treatment.

关键词： Roasted beef Polycyclic aromatic hydrocarbons Cold plasma Mitigation mechanism Product quality evaluation

来源：评论

学校读者我要写书评

暂无评论

Enhanced Tube-Based Event-Triggered Stochastic Model Predictive control With Additive Uncertainties

引用

IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 596-605页

作者： Chenxi Gu Xinli Wang Kang Li Xiaohong Yin Shaoyuan Li Lei Wang the School of Control Science and Engineering Shandong University IEEE the School of Electronic and Electrical Engineering University of Leeds the Qingdao University of Science and Technology the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China

This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.

关键词： Event-triggered mechanism heating, ventilation, and air conditioning (HVAC) control probabilistic reachable set stochastic model predictive control

来源：评论

学校读者我要写书评

暂无评论

Underwater images enhancement using contrast limited adaptive parameter settings histogram equalization

引用

Multimedia Tools and Applications 2024年 1-15页

作者： Chen, Yahui Liang, Yitao College of Information Science and Engineering Henan University of Technology Henan Zhengzhou China Henan Key Laboratory of Grain Photoelectric Detection and Control Henan Zhengzhou China

CLAHE is widely used in underwater image processing because of its excellent performance in contrast enhancement. The selection of the clip point formula is the core problem of the CLAHE methods, and the selection of suitable clipping value has become the focus of some extended methods. In this paper, an automatic CLAHE underwater image enhancement algorithm is proposed. The method determines the clipping value according to the high-order moment dynamic features of each block of the underwater image. By quantifying the dynamic features of each block in the image more precisely, and then adding it to the clipping value formula, the contrast and details of the underwater image can be effectively enhanced. In order to effectively improve the saturation and brightness of underwater images, this paper chooses a more accurate and intuitive HSV model. Experimental results show that our methods enhance the contrast subjectively, while suppressing the amplification of noise very well, and also increase the saturation of underwater images. In objective metrics, our method obtains the best values in underwater quality assessment (UIQM), SSIM, and PSNR. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Underwater imaging

来源：评论

学校读者我要写书评

暂无评论

Novel £2,1-Norm Based Least Square Regression Method for Classification 9

Novel £2,1-Norm Based Least Square Regression Method for Cl...

引用

9th International Conference on information, Cybernetics, and Computational Social Systems, ICCSS 2023

作者： Jin, Junwei Yan, Qiuling Zhu, Chunhua Qin, Zhenghao Li, Lei Henan University of Technology Ministry of Education Key Laboratory of Grain Information Processing and Control China Henan Key Laboratory of Grain Photoelectric Detection and Control China Henan University of Technology College of Information Science and Engineering China Unmanned System Research Institute Northwestern Polytechnical University China

ISBN: (纸本)9798350342239

In the realm of linear regression, the concept of utilizing relaxed regression targets for classification has shown considerable success. However, it suffers from a lack of strong discriminative ability. In this study, we build upon the theory of relaxed regression targets and propose a more concise and discriminative model for multi-class classification. Our approach introduces the £2,1-norm regularized term to enhance the efficacy and compactness of the learned projection matrix. This regularization term not only generates a sparse row structure but also facilitates feature selection during the training phase. Consequently, both the accuracy of classification and the convergence speed of the model are improved. Furthermore, when compared to various variants of the linear regression model, our designed method exhibits superior performance in image classification. Through extensive experiments conducted on image databases, we provide evidence that our proposed approach excels in recognition capability, surpassing the performance of state-of-The-Art methods in terms of classification accuracy. © 2023 IEEE.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Relation-Aware Facial Expression Recognition Using Contextual Residual Network with Attention Mechanism 17th

Relation-Aware Facial Expression Recognition Using Contextua...

引用

17th International Conference on Computer Science and Education, ICCSE 2022

作者： Li, Xue Zhu, Chunhua Zhou, Fei Key Laboratory of Grain Information Processing and Control Ministry of Education Henan University of Technology Henan Zhengzhou China College of Information Science and Engineering Henan University of Technology Henan Zhengzhou China Henan Key Laboratory of Grain Photoelectric Detection and Control Henan University of Technology Henan Zhengzhou China

ISBN: (纸本)9789819924424

With the existence of occlusion or posture changes, facial expression recognition (FER) under uncontrolled conditions is difficult. To obtain a discriminative representation for challenging expression recognition, we present a relation-aware FER model, referred to attention-coordinated contextual residual network (ACRN), which contains a contextual residual network (CRNet) and attention module (AM). Firstly, multi-level features of facial expression are extracted by CRNet. There are some contextual convolution (CoConv) blocks in CRNet to integrate expression information in facial space;then, AM is embedded into each stage of CRNet to coordinate contextual information from CoConv blocks across the channel and spatial location, weighting multi-level expression features to differentiate their importance;finally, to highlight expression-related facial areas, the output of CRNet will be fed into AM, which can focus on salient features. The experiments on Affectnet-7 and RAF_DB datasets have shown that ACRN can both explore the interaction of facial information and capture subtle features related to expression, thus obtaining a better recognition performance. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

C2P-Net: Comprehensive Depth Map to Planar Depth Conversion for Room Layout Estimation

引用

IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年第7期47卷 5350-5367页

作者： Zhang, Weidong Zhou, Mengjie Cheng, Jiyu Liu, Ying Zhang, Wei Xi'an University of Posts & Telecommunications School of Communications and Information Engineering China Xi'an Key Laboratory of Image Processing Technology and Applications for Public Security China Shandong University School of Control Science and Engineering China Ministry of Education Key Laboratory of Machine Intelligence and System Control China

Room layout estimation seeks to infer the overall spatial configuration of indoor scenes using perspective or panoramic images. As the layout is determined by the dominant indoor planes, this problem inherently requires the reconstruction of these planes. Some studies reconstruct indoor planes from perspective images by learning pixel-level or instance-level plane parameters. However, directly learning these parameters has the problems of susceptibility to occlusions and position dependency. In this paper, we introduce the Comprehensive depth map to Planar depth (C2P) conversion, which reformulates planar depth reconstruction into the prediction of a comprehensive depth map and planar visibility confidence. Based on the parametric representation of planar depth we propose, the C2P conversion is applicable to both panoramic and perspective images. Accordingly, we present an effective framework for room layout estimation that jointly learns the comprehensive depth map and planar visibility confidence. Due to the differentiability of the C2P conversion, our network autonomously learns planar visibility confidence by constraining the estimated plane parameters and reconstructed planar depth map. We further propose a novel approach for 3D layout generation through sequential planar depth map integration. Experimental results demonstrate the superiority of our method across all evaluated panoramic and perspective datasets. © 1979-2012 IEEE.

关键词： Layout Three-dimensional displays Image reconstruction Estimation Cameras Floors Cognition Transforms Training Semantics

来源：评论

学校读者我要写书评

暂无评论

Applications of artificial intelligence to lipid nanoparticle delivery

引用

Particuology 2024年第7期90卷 88-97页

作者： Ye Yuan Yuqi Wu Jiabei Cheng Kaiyuan Yang Yilin Xia Hongguang Wu Xiaoyong Pan Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education of ChinaChina Songjiang Research Institute Songjiang District Central HospitalShanghai Jiao Tong University School of MedicineShanghaiChina

Lipid nanoparticles(LNPs)are nanocarriers composed of four lipid components and can be used for gene therapy,protein replacement,and vaccine ***,LNPs also face several challenges,such as toxicity,immune activation,and low delivery *** overcome these challenges,artificial intelligence can be used to optimize the design and formulation of LNPs,as well as to predict their properties and ***,antibody-targeted conjugation can be used to enhance the specificity and selectivity of LNPs by attaching an antibody that recognizes a specific antigen on the cell surface to LNPs.

关键词： Artificial intelligence Lipid nanoparticles Antibody Targeted conjugation

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：