检索结果-内蒙古大学图书馆

SSRN 2022年

作者： Li, Zhihua Deng, Jiaxi Zhang, Jing Qiao, Cailin Yang, Mei Xu, Guoren Luo, Xiaogang Huo, Danqun Hou, Changjun Ministry of Education College of Bioengineering Chongqing University Chongqing400044 China State Key Laboratory of Urban Water Resources & Environment Harbin Institute of Technology Harbin150090 China Chongqing Key Laboratory of Bio-perception & Intelligent Information Processing School of Microelectronics and Communication Engineering Chongqing University Chongqing400044 China

In this work, a novel and effective ratio fluorescent probe Eu-BTB was prepared for the detection of Cu2+ using 1,3, 5-tri (4-carboxyphenyl) benzene (H3BTB) as ligand and Eu3+ as metal framework, which showed excellent fluorescence performance in the detection of Cu2+. The BTB of the probe can achieve "antenna effect" with Eu3+, which can sensitize Eu3+ emission effectively while maintaining its own emission. Copper ions can competitively bind to BTB, thus inhibiting the antenna effect. In the concentration range of 0.05-10 μM, the ratio of fluorescence intensity and copper ion concentration showed a good linear relationship, and the detection limit was as low as 10 nM, corresponding time was 3 minutes. The fluorescence probe has been successfully applied to the detection of copper ions in water in different environments, the standard method Inductively coupled plasma mass spectrometry(ICP-MS) proved that the results were reliable. which confirmed the potential of Eu-BTB probe in the rapid and accurate detection of Cu2+ in different environmental water samples. © 2022, The Authors. All rights reserved.

关键词： Fluorescence

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Cell-Free Massive MIMO-OFDM for High-Speed Train Communications

arXiv

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arXiv 2022年

作者： Zheng, Jiakang Zhang, Jiayi Björnson, Emil Li, Zhetao Ai, Bo The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Department of Computer Science KTH Royal Institute of Technology Kista Sweden The Hunan International Scientific and Technological Cooperation Base of Intelligent Network Key Laboratory of Intelligent Computing & Information Processing Ministry of Education Xiangtan University Hunan411105 China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China

Cell-free (CF) massive multiple-input multiple-output (MIMO) systems show great potentials in low-mobility scenarios, due to cell boundary disappearance and strong macro diversity. However, the great Doppler frequency offset (DFO) leads to serious inter-carrier interference in orthogonal frequency division multiplexing (OFDM) technology, which makes it difficult to provide high-quality transmissions for both high-speed train (HST) operation control systems and passengers. In this paper, we focus on the performance of CF massive MIMO-OFDM systems with both fully centralized and local minimum mean square error (MMSE) combining in HST communications. Considering the local maximum ratio (MR) combining, the large-scale fading decoding (LSFD) cooperation and the practical effect of DFO on system performance, exact closed-form expressions for uplink spectral efficiency (SE) expressions are derived. We observe that cooperative MMSE combining achieves better SE performance than uncooperative MR combining. In addition, HST communications with small cell and cellular massive MIMO-OFDM systems are compared in terms of SE. Numerical results reveal that the CF massive MIMO-OFDM system achieves a larger and more uniform SE than the other systems. Finally, the train antenna centric (TA-centric) CF massive MIMO-OFDM system is designed for practical implementation in HST communications, and three power control schemes are adopted to optimize the propagation of TAs for reducing the impact of the DFO. Copyright © 2022, The Authors. All rights reserved.

关键词： MIMO systems

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Online Attentive Kernel-Based Temporal Difference Learning

arXiv

引用

arXiv 2022年

作者： Yang, Guang Chen, Xingguo Yang, Shangdong Wang, Huihui Dong, Shaokang Gao, Yang The the Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications National Engineering Laboratory for Agri-Product Quality Traceability Beijing Technology and Business University China The State Key Laboratory for Novel Software Technology Nanjing University China The PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology China

With rising uncertainty in the real world, online Reinforcement Learning (RL) has been receiving increasing attention due to its fast learning capability and improving data efficiency. However, online RL often suffers from complex Value Function Approximation (VFA) and catastrophic interference, creating difficulty for the deep neural network to be applied to an online RL algorithm in a fully online setting. Therefore, a simpler and more adaptive approach is introduced to evaluate value function with the kernel-based model. Sparse representations are superior at handling interference, indicating that competitive sparse representations should be learnable, non-prior, non-truncated and explicit when compared with current sparse representation methods. Moreover, in learning sparse representations, attention mechanisms are utilized to represent the degree of sparsification, and a smooth attentive function is introduced into the kernel-based VFA. In this paper, we propose an Online Attentive Kernel-Based Temporal Difference (OAKTD) algorithm using two-timescale optimization and provide convergence analysis of our proposed algorithm. Experimental evaluations showed that OAKTD outperformed several Online Kernel-based Temporal Difference (OKTD) learning algorithms in addition to the Temporal Difference (TD) learning algorithm with Tile Coding on public Mountain Car, Acrobot, CartPole and Puddle World tasks. Copyright © 2022, The Authors. All rights reserved.

关键词： Learning algorithms

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Orthogonal Dual Graph Regularized Nonnegative Matrix Factorization 11th

Orthogonal Dual Graph Regularized Nonnegative Matrix Factori...

引用

11th International Conference on Image and Graphics, ICIG 2021

作者： He, Jinrong Shi, Yanxin Bai, Zongwen Bao, Zeyu Key Laboratory of Agricultural Internet of Things Ministry of Agriculture and Rural Affairs Northwest A&F University Shaanxi Yangling712100 China College of Mathematics and Computer Science Yan‘an University Yan‘an716000 China Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service Northwest A&F University Shaanxi Yangling712100 China Shaanxi Key Laboratory of Intelligent Processing for Big Energy Data Yanan University Shaanxi Yan’an716000 China University of Science and Technology of China Anhui Hefei230026 China

ISBN: (纸本)9783030873578

Nonnegative matrix factorization (NMF) is a classical low-rank approximation method of data matrix, which decomposes a high-dimensional data matrix into two nonnegative low-rank matrices, namely basis matrix and coefficient matrix. In order to capture the local geometric structure of original dataset, manifold learning methods are incorporated into NMF framework. Motivated by recent progress in dual graph regularization, by considering the geometric structures of both the data manifold and the feature manifold, Orthogonal Dual-graph NMF (ODNMF) algorithms were proposed, which imposed orthogonality constraints on basis matrix or coefficient matrix. Since the projection directions were mutually orthogonal, the representation power of data samples was enhanced, thus ODNMF methods are more robust for data clustering. The extensive experimental results on UCI, text and face image data sets have demonstrated the superiority of the proposed methods. © 2021, Springer Nature Switzerland AG.

关键词： Matrix algebra

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IoT Service Description and Composition Method with Knowledge Graph

Journal of Network Intelligence

引用

Journal of Network Intelligence 2022年第4期7卷 1047-1065页

作者： Tang, Zheng-Yi Liu, Chuan Lian, Zhi-Zhu Wang, Jin-Shui Hossain, Md. Alamgir School of Computer Science and Mathematics Fujian University of Technology Xuefu South Road Fujian Province Fuzhou City350118 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Xiyuangong Road Fujian Province Fuzhou City350121 China Key Laboratory of Hunan Province for Mobile Business Intelligence Hunan University of Technology and Business Yuelu Road Hunan Province Changsha City410205 China Department of Management Hajee Mohammad Danesh Science and Technology University Dinajpur5200 Bangladesh

Service computing techniques have achieved remarkable results in solving the cohesiveness problem of Web applications and are therefore introduced into the IoT do-main to break the trend of inlining IoT systems. However, compared with the traditional Internet, IoT has richer elements and semantic connotations, so the existing service description framework needs to be improved and extended. In this paper, we propose an ontology description framework for IoT services, design corresponding inference rules, and give a storage method for IoT services by integrating the knowledge graph technology for the strongly associated characteristics of IoT services. On this basis, an algorithm for combining IoT services based on graph planning is proposed. The experimental results show that the proposed method in this paper can provide richer entity semantics and ef-fectively improve the efficiency and success rate of IoT service composition. © The Authors.

关键词： Ontology

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Improved hybrid query tree anti-collision algorithm 8th

Improved hybrid query tree anti-collision algorithm

引用

8th International Conference on Computer Engineering and Networks, CENet 2018

作者： Deng, Hongwei Li, Lang Liang, Xiaoman School of Computer Science and Technology Hengyang Normal University HengyangHunan421002 China School of Information Science and Engineering Central South University ChangshaHunan410083 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002 China

ISBN: (纸本)9783030146795

An improved algorithm based on the hybrid query tree (HQT) algorithm is proposed in this work. Tags are categorized according to the combined information of the highest bit of collision and second-highest bit of collision. Then, these tags are used to decide the postponement of several delayed-response time slots, to diminish the collision probability. The performance analysis results show that this algorithm is superior to the query tree (QT) and HQT algorithms. It reduces the query time and system communication traffic and improves the tag identification efficiency. © Springer Nature Switzerland AG 2020.

关键词： Trees (mathematics)

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A General Framework of Reversible Data Hiding with Controlled Contrast Enhancement

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Computers, Materials & Continua 2020年第1期62卷 157-177页

作者： Shaowei Weng Yiyun Liu Yunqing Shi Bo Ou Chunyu Zhang Cuiping Wang School of Information Engineering Guangdong University of TechnologyGuangzhou510006China Guangdong Key Laboratory of Intelligent Information Processing and Shenzhen Key Laboratory of Media Security Shenzhen UniversityShenzhen518060China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07103 USA College of Computer Science and Electronic Engineering Hunan UniversityChangsha410082China School of Information Engineering Xizang Minzu UniversityXianyang712082China School of Electronic Information Qingdao UniversityQingdao266071China

This paper proposes a two-step general framework for reversible data hiding(RDH)schemes with controllable contrast *** first step aims at preserving visual perception as much as possible on the basis of achieving high embedding capacity(EC),while the second step is used for increasing image *** the second step,some peak-pairs are utilized so that the histogram of pixel values is modified to perform histogram equalization(HE),which would lead to the image contrast ***,for HE,the utilization of some peak-pairs easily leads to over-enhanced image contrast when a large number of bits are ***,in our proposed framework,contrast over-enhancement is avoided by controlling the degree of contrast *** the second step can only provide a small amount of data due to controlled contrast enhancement,the first one helps to achieve a large amount of data without degrading visual *** RDH method which can achieve high EC while preserve good visual quality,can be selected for the first *** fact,Gao et al.’s method is a special case of our proposed *** addition,two simple and commonly-used RDH methods are also introduced to further demonstrate the generalization of our framework.

关键词： Reversible data hiding controlled contrast enhancement general framework PEE-based RDH method IT-based RDH method

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STABLE CLASSES OF HARMONIC MAPPINGS

arXiv

引用

arXiv 2023年

作者： Liu, Gang Ponnusamy, Saminathan Starkov, Victor V. College of Mathematics and Statistics Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Normal University Hunan Hengyang421002 China Department of Mathematics Indian Institute of Technology Madras Chennai600 036 India Lomonosov Moscow State University Moscow Center of Fundamental and Applied Mathematics Moscow Russia Department of Mathematics University of Petrozavodsk ul. Lenina 33 Petrozavodsk185910 Russia

Let H0 denote the set of all sense-preserving harmonic mappings f = h + g in the unit disk D, normalized with h(0) = g(0) = g′(0) = 0 and h′(0) = 1. In this paper, we investigate some properties of certain subclasses of H0, including inclusion relations and stability analysis by precise examples, coefficient bounds, growth, covering and distortion theorems. As applications, we build some Bohr inequalities for these subclasses by means of subordination. Among these subclasses, six classes consist of functions f = h + g ∈ H0 such that h + ǫg is univalent (or convex) in D for each |ǫ| = 1 (or for some |ǫ| = 1, or for some |ǫ| ≤ 1). Simple analysis shows that if the function f = h + g belongs to a given class from these six classes, then the functions h + ǫg belong to corresponding class for all |ǫ| = 1. We call these classes as stable *** Codes Primary: 30A10, 30B10, 30H05, 31A05, 30C62, 30C80, Secondary 30C35, 30C45 Copyright © 2023, The Authors. All rights reserved.

关键词： Harmonic analysis

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An Ultra-Sensitive Dual-Signal Ratio Electrochemical Aptamer Biosensor for Detection of Her2

SSRN

引用

SSRN 2022年

作者： Zhang, Ya Xu, Ying Li, Ning Qi, Na Yang, Mei Peng, Lan Hou, Changjun Huo, Danqun Key Laboratory for Biorheological Science and Technology Ministry of Education Bioengineering College Chongqing University Chongqing 400044 China Chongqing University China Chongqing Key Laboratory of Bio-perception & Intelligent Information Processing School of Microelectronics and Communication Engineering Chongqing University Chongqing 400044 China National Facility for Translational Medicine Shanghai Jiao Tong University Shanghai 200240 China

Electrochemical biosensor technology has the characteristics of simple fabrication, low loss, high sensitivity, short consumption time and easy to carry, which is conducive to its rapid application. However, its accuracy and stability still need to be improved. Herein, a dual-signal ratio electrochemical aptamer biosensor, improve detection accuracy due to its self-calibration capability，was constructed to detect breast cancer biomarker - HER2. The dopamine (PDA) and 3,3',5,5' -tetramethylbenzidine (TMB) were selected as electroactive materials, with the ZIF-67 loaded PDA (ZIF-67@PDA) as the capture probe, and bimetal Cu/UiO-66 loaded TMB as the signal identification probe. In the presence of the HER2, ZIF-67@PDA probe trapping HER2 will lead to the weakening of the electrode conductivity to weaken the electrochemical signal of PDA, however, the modification of the signal probe will lead to the enhancement of the electrochemical signal of TMB. By calculating the ratio of the two electrochemical signal, the high sensitivity, specificity and ratio of the target can be achieved. It can sensitive detection of HER2 biomarkers in only 30 min with the detection range are 0.75 to 40 pg/mL and detection limits as low as 4 fg/mL. The dual-signal ratio biosensor has low detection limit, short detection time and simple method, which can accurately detect the target in complex biological samples, and has important theoretical significance. © 2022, The Authors. All rights reserved.

关键词： Probes

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Hexagonal Convolutional Neural Network for Spatial Transcriptomics Classification

Hexagonal Convolutional Neural Network for Spatial Transcrip...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jing Gao Fa Zhang Kai Hu Xuefeng Cui Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan China Institute of Computing Technology Chinese Academy of Sciences Beijing China Key Laboratory of Medical Imaging and Artificial Intelligence of Hunan Province Xiangnan University Chenzhou China School of Medical Technology Beijing Institute of Technology Beijing China School of Computer Science and Technology Shandong University Qingdao China

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Recent advances in spatial transcriptomics have enabled the comprehensive measurement of transcriptional profiles while retaining the spatial contextual information. Identifying spatial domains is a critical step in the analysis of spatially resolved transcriptomics. Existing unsupervised methods perform poorly on this task owing to the large amount of noise and dropout events in the transcriptomic profiles. To address this problem, we first extend an unsupervised algorithm to a supervised learning method that can identify useful features and reduce noise hindrance. Second, inspired by the classical convolution in convolutional neural networks (CNNs), we designed a regular hexagonal convolution to compensate for the missing gene expression patterns from adjacent nodes. Compared with the graph convolution in graph neural networks (GNNs), our hexagonal convolution can preserve the relative spatial location information of different nodes in graph-structured data. Third, based on the hexagonal convolution, a novel hexagonal Convolutional Neural Network (hexCNN) is proposed for spatial transcriptomics classification. Finally, we compared the proposed hexCNN with existing methods on the DLPFC dataset. The results show that hexCNN achieves a classification accuracy of 87.2% and an average Rand index (ARI) of 78.2% (1.9% and 3.3% higher than those of GNNs).

关键词： Visualization Convolution Supervised learning Interference Spatial databases Graph neural networks Convolutional neural networks

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