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arXiv 2024年

作者： Chen, Donghao Liu, Binkun College of Information Science and Engineering Henan University of Technology Zhengzhou China Key Laboratory of Grain Information Processing and Control Henan University of Technology Zhengzhou China

Temperature fluctuations significantly affect microorganism growth and pest activity in grain stacks. Thus, precise monitoring and forecasting of grain stack temperature are essential for maintaining the quality and safety of grain storage. This paper proposes a multi-model fusion approach to predict grain temperature using historical temperature data of stored grains and meteorological data from the region. Based on the proposed approaches, four distinct machine learning models, namely Adaboost, decision tree, extra trees, and random forest, are first developed. These models are then fine-tuned through parameter optimization to enhance their predictive capabilities. Subsequently, the optimized models are combined to form different ensemble models. In essence, the fusion process integrates the predictions of each individual model as new feature inputs into the prediction model. Furthermore, the study utilizes the random forest to identify the key factors influencing grain temperature, providing insights into the importance of different influencing factors. The experimental results demonstrate that the fusion models proposed in this paper have achieved higher prediction accuracy and robustness compared with the traditional prediction methods (i.e., single-model prediction). Additionally, the analysis of feature importance also offers empirical evidence for understanding the factors influencing grain temperature. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

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Design of fast Fourier transform-digital beamforming based algorithm on water level measurement

Design of fast Fourier transform-digital beamforming based a...

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2024 International Conference on Automation control, Algorithm, and Intelligent Bionics, ACAIB 2024

作者： Feng, Nianshun Pu, Jiaoyang Li, Qinying Hu, Xuejie Liang, Peiyu Tian, Yue Fujian Key Laboratory of Communication Network and Information Processing Xiamen university of Technology Xiamen China Henan Yellow River Information Center Office China

ISBN: (纸本)9781510682597

This research proposes a fast Fourier transform-digital beamforming (FFT-DBF) based strategy for water level measurements on a bridge environment, utilizing linear frequency modulated continuous wave (LFMCW) radar. This paper presents two factors that affect the accuracy of LFMCW ranging on the bridge environment. By introducing a digital beamforming (DBF) algorithm, the waves from the undesired directions (UDs) are filtered. Moreover, the waves reflected by the strong stationary reflectors (SSRs) are filtered under the two-dimensional fast Fourier transform (2D-FFT) algorithm and the specialized cell averaging constant false alarm rate detector(CA-CFAR) algorithm. By using DBF, the main beam is able to point to the DD on the beam direction diagram. Simulation results show that the waves reflected from SSRs can be easily distinguished from the waves reflected by the water after processing the 2D-FFT and the CA-CFAR algorithm. More specifically, the results show that the estimation accuracy and stability can be further improved by using the FFT-DBF based strategy. © 2024 SPIE.

关键词： Fast Fourier transforms

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Terahertz Refractive Index Sensor Based on Tunable Graphene Metamaterial Absorber

Terahertz Refractive Index Sensor Based on Tunable Graphene ...

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Sensor technology and control (ISSTC), International Symposium on

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

ISBN: (数字)9798331541637

ISBN: (纸本)9798331541644

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 $\mathbf{9 9. 4 5 \%}$ and a high-frequency peak at 3.83 THz with maximum absorption rates of $\mathbf{9 9. 5 0 \%}$. 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 $495 \mathrm{GHz} / \mathrm{RIU}$ and 895 $\mathrm{GHz} /$ 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.

关键词： Q-factor Structural rings Sensitivity Absorption Fermi level Graphene Refractive index Metamaterials Surface plasmon resonance Biomedical imaging

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GITANet: Group Interactive Threshold-based Attention Network for Hyperspectral Image Classification

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IEEE Transactions on Multimedia 2025年

作者： Duan, Yule Chen, Chuang Fu, Maixia Gong, Xiuwen Niu, Yingying Luo, Fulin The University of Sydney Faculty of Engineering NSW2006 Australia Henan University of Technology Key Laboratory of Grain Information Processing and Control Ministry of Education Zhengzhou450001 China Henan University of Technology Key Laboratory of Grain Photoelectric Detection and Control Zhengzhou450001 China Chongqing University College of Computer Science Chongqing400044 China

Group convolution networks have shown great potential in hyperspectral image (HSI) classification because of their ability to divide total spectral bands into multiple groups and focus on fine discrimination within different spectral ranges. Most group convolution networks process parallel spectral groups independently;however, they neglect the important relevance of nearby spectral ranges. Moreover, the feature maps from different spectral groups are not considered for recalibration in the existing attention. To address these issues, we propose a novel group interactive threshold attention network (GITANet). In the network, a stratified-split-concatenation strategy, which not only splits all bands into multiple groups for intragroup convolution but also propagates the intergroup information via the stratified concatenation operation between different groups, is designed for bandwise group convolution. Relying on the high dependencies among nearby spectra, the cross-group interactive attention block is designed to encourage significant spectral features. Subsequently, from different spectral ranges, a learnable threshold generation block is built to estimate the information validity of each pixel. On the basis of this threshold, soft threshold spatial attention is developed in the bandwise encoderdecoder architecture, which emphasizes high-value spatial areas during the fusion of group convolutional features. Therefore, complementary and discriminative spectral-spatial features are obtained to improve the performance of HSI classification. The experimental results on three HSI datasets illustrate that GITANet is superior to several state-of-the-art networks. © 1999-2012 IEEE.

关键词： Convolution

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A Low Complexity Beam Selection Method for MmWave Massive MIMO Systems

A Low Complexity Beam Selection Method for MmWave Massive MI...

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Ubiquitous Communication (Ucom), International Conference on

作者： Chunhua Zhu Qinwen Ji Xinying Guo The Key Laboratory of Grain Information Processing and Control The Henan Key Laboratory of Grain Photoelectric Detection and Control Henan University of Technology Zhengzhou China Henan Engineering Laboratory of Grain Condition Intelligent Detection and Application Henan University of Technology Zhengzhou China

The levels of inter-user interference (IUI) usually vary due to the different geographical locations of users, but, most existing beam selection methods apply the same beam selection criteria for all users, which is detrimental to maintain an attractive trade-off between complexity and system performance. Considering the discrepancy of IUI comprehensively, a low complexity beam selection method for millimeter-wave massive multiple-input multiple-output (MIMO) systems is proposed. Firstly, a candidate beam set (CBS) is constructed in light of the sparsity and power distribution of the beamspace channel, thereby all users are classified into non-interfering users (NIUs), low-interference users (LIUs) and high-interference users (HIUs). For NIUs, the beams with large power are selected from CBS under the magnitude maximization (MM) criterion; for LIUs, a novel MM criterion with a tabu list is designed, which can effectively tackle the drawback of assigning shared beams in traditional MM; for HIUs, the incremental algorithm based on the sum-rate maximization criterion is developed to find the optimal beams from CBS. Simulation results validate that the proposed method can achieve almost the same sum-rate performance as the existing methods with the lower computational complexity.

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Systematic Cloud-Based Optimization: Twin-Fold Moth Flame Algorithm for VM Deployment and Load-Balancing

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Intelligent Automation & Soft Computing 2024年第3期39卷 477-510页

作者： Umer Nauman Yuhong Zhang Zhihui Li Tong Zhen Information Science and Engineering College Henan University of TechnologyZhengzhou450001China School of Artificial Intelligence and Big Data Henan University of TechnologyZhengzhou450001China Key Laboratory of Grain Information Processing and Control Ministry of EducationHenan University of TechnologyZhengzhou450001China

Cloud computing has gained significant recognition due to its ability to provide a broad range of online services and ***,existing commercial cloud computing models demonstrate an appropriate design by concentrating computational assets,such as preservation and server infrastructure,in a limited number of large-scale worldwide data *** the deployment of virtual machines(VMs)is crucial in this scenario to ensure system dependability,performance,and minimal latency.A significant barrier in the present scenario is the load distribution,particularly when striving for improved energy consumption in a hypothetical grid computing *** design employs load-balancing techniques to allocate different user workloads across several virtual *** address this challenge,we propose using the twin-fold moth flame technique,which serves as a very effective optimization *** intentionally designed the twin-fold moth flame method to consider various restrictions,including energy efficiency,lifespan analysis,and resource *** provides a thorough approach to evaluating total costs in the cloud computing *** assessing the efficacy of our suggested strategy,the study will analyze significant metrics such as energy efficiency,lifespan analysis,and resource *** investigation aims to enhance cloud computing techniques by developing a new optimization algorithm that considers multiple factors for effective virtual machine placement and load *** proposed work demonstrates notable improvements of 12.15%,10.68%,8.70%,13.29%,18.46%,and 33.39%for 40 count data of nodes using the artificial bee colony-bat algorithm,ant colony optimization,crow search algorithm,krill herd,whale optimization genetic algorithm,and improved Lévy-based whale optimization algorithm,respectively.

关键词： Optimizing cloud computing deployment of virtual machines load-balancing twin-fold moth flame algorithm grid computing computational resource distribution data virtualization

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Efficient and fine-grained access control with fully-hidden policies for cloud-enabled IoT

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Digital Communications and Networks 2025年第2期11卷 473-481页

作者： Qi Li Gaozhan Liu Qianqian Zhang Lidong Han Wei Chen Rui Li Jinbo Xiong School of Computer Science Nanjing University of Posts and TelecommunicationsNanjing 210023China Key Laboratory of Cryptography of Zhejiang Province Hangzhou Normal UniversityHangzhou 311121China Tongda College of Nanjing University of Posts and Telecommunications Yangzhou 225127China Henan Key Laboratory of Network Cryptography Technology Zhengzhou 450001China School of Computer Science and Technology Xidian UniversityXi'an 710071China State Key Laboratory of Tibetan Intelligent Information Processing and Application Qinghai Normal UniversityXining 810008China Faculty of Software Fujian Normal UniversityFuzhou 350108China

Ciphertext-Policy Attribute-Based Encryption(CP-ABE)enables fine-grained access control on ciphertexts,making it a promising approach for managing data stored in the cloud-enabled Internet of *** existing schemes often suffer from privacy breaches due to explicit attachment of access policies or partial hiding of critical attribute ***,resource-constrained IoT devices,especially those adopting wireless communication,frequently encounter affordability issues regarding decryption *** this paper,we propose an efficient and fine-grained access control scheme with fully hidden policies(named FHAC).FHAC conceals all attributes in the policy and utilizes bloom filters to efficiently locate them.A test phase before decryption is applied to assist authorized users in finding matches between their attributes and the access *** attacks are thwarted by providing unauthorized users with invalid *** heavy computational overhead of both the test phase and most of the decryption phase is outsourced to two cloud ***,users can verify the correctness of multiple outsourced decryption results *** analysis and performance comparisons demonstrate FHAC's effectiveness in protecting policy privacy and achieving efficient decryption.

关键词： Access control Policy hiding Verifiable outsourced computation Cloud IoT

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Graphene-Based Terahertz Tunable Double-Broadband Perfect Absorber

SSRN

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SSRN 2024年

作者： Fu, Maixia Liu, Zhonghao Duan, Yule Zhou, Fei Li, Yinsheng Key Laboratory of Grain Information Processing and Control Ministry of Education Henan University of Technology Zhengzhou450001 China College of Information Science and Engineering Henan University of Technology Zhengzhou450001 China

The rapid advancement of terahertz(THz) technology has sparked significant interest in exploring tunable broadband functionaldevices. In this study, we propose an antisymmetric graphene skeletonized structure to achieve a terahertz double-perfect broadbandabsorber. This absorber consists of a gold (Au) substrate, a TOPAS dielectric layer, and C4 regular antisymmetric-patternedgraphene embedded in the polymer. It exhibits two unpolarized perfect absorbing broadbands through the resonance mechanisms oflocalized surface-isolated exciton resonance and electromagnetic dipole resonance. The results indicate high absorbance exceeding90% across two distinct frequency ranges of 0.93-2.03 THz and 4.16-5.3 THz. The dual-broadband absorption feature stems fromthe pronounced aggregation effect of the "Hollow-out corner" on the electric field, enabling modulation of the second Harmonicwhile leaving the first Harmonic largely unaffected. The absorber’s response can be dynamically tuned through adjusting the Fermienergy level and structural parameters of graphene. Our design opens up possibilities for diverse applications, in photodetectors,THz modulation, and stealth technologies. © 2024, The Authors. All rights reserved.

关键词： Graphene

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MmWave MIMO: An LAMP-Based Network with Deep Residual Learning Combining the Prior Channel information for Beamspace Sparse Channel Estimation 21

MmWave MIMO: An LAMP-Based Network with Deep Residual Learni...

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21st IEEE International Conference on Communication technology, ICCT 2021

作者： Ji, Qinwen Zhu, Chunhua Guo, Xinying Henan University of Technology Henan Key Laboratory of Grain Photoelectric Detection and Control Henan University of Technology Key Lab. of Grain Information Processing and Control School of Information Science and Engineering Zhengzhou China

ISBN: (纸本)9781665432061

In mmWave MIMO systems relying on lens antenna arrays, beamspace sparse channel estimation is one of the key technologies to improve system performance. One new beamspace sparse channel estimation scheme with deep residual learning is proposed, which introduces the channel prior information following the Gaussian mixture distribution and the residual processing unit. Firstly, the prior-aided GM-LAMP network is employed to obtain a preliminary estimation;then the deep residual learning network is designed to reduce the impact of channel noise. Compared with existing methods, the proposed algorithm can improve estimation accuracy with the lower computational complexity. © 2021 IEEE.

关键词： MIMO systems

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Efficient Frame Optimization Scheme for PSAM Assisted Transmission over Rician Fading Channel

Efficient Frame Optimization Scheme for PSAM Assisted Transm...

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information Communication and Software Engineering (ICICSE), IEEE International Conference on

作者： Yuqian Yan Zhongyang Yu Mengmeng Xu Hengzhou Xu Hai Zhu Chunhua Zhu School of Computer Science Henan University of Engineering Zhengzhou China Key Laboratory of Grain Information Processing Control (Henan University of Technology) Ministry of Education Zhengzhou China

ISBN: (数字)9798350351699

ISBN: (纸本)9798350351705

In this paper, we discuss the commonly used pilot-symbol-assisted-modulation (PSAM) assisted transmission and its corresponding frame optimization problem over Rician fading channel. Specifically, we design a generalized PSAM (G-PSAM) format based on the standard PSAM (S-PSAM) format and derive its approximate joint data-aided & non-data-aided Cramér-Rao bound (DA&NDA CRB) when the pilot-aided channel estimation is considered. Then, with the approximate DA&NDA CRB and the classical control-variate method (CVM), an efficient optimization scheme of the G-PSAM format is proposed, which is asymptotically optimal in terms of the mean-square error (MSE) estimation performance. Simulation results reveal the superiority of the optimized G-PSAM (OG-PSAM) format over the S-PSAM format for both short-packet and long-packet transmissions. Also, a practical example of the joint DA&NDA aided carrier synchronization is provided.

关键词： Fading channels Simulation Rician channels Estimation Channel estimation Mean square error methods Synchronization

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