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1st International Conference on Information Science and Engineering, ICISE2009

作者： Jin, Hailiang Liu, Huijie Key Laboratory of Mine Spatial Information Technologies State Bureau of Surveying and Mapping Henan Polytechnic University Jiaozuo China Key Laboratory of Advanced Design and Intelligent Computing Dalian University Dalian China

ISBN: (纸本)9780769538877

GIS has the function of powerful spatial data process and 3D visualization analysis. In this paper, by using available remote sensing image, DEM data for experiment, we realize 3D terrain visualization and terrain analysis, the technology of how to display huge volume of digital elevation model(DEM)data is introduced, and spatial analysis is studied based on the terrain created using DEM. In the end, the paper introduces the process of the implementation in brief. ©2009 IEEE.

关键词： Data visualization

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GP-Net: Global Perceptual Network with Adaptive Gradient Clipping for Emotional Image Classification 8

GP-Net: Global Perceptual Network with Adaptive Gradient Cli...

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8th International Conference on intelligent computing and Signal Processing, ICSP 2023

作者： Wang, Xiaohua Yang, Jie Hu, Min Wu, Xia Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer Science and Information Engineering Hefei China

ISBN: (纸本)9798350302455

Traditional image emotion recognition focuses only on the emotion information embedded in the subject or part of the image, while ignoring the global emotion information. In this paper, we propose a new network based on Vision Transformer: a global perception network, containing a main module and a background module. The main module enhances the weighting of objects by showing the interdependencies between modelled channels. The background module further searches for emotional information in the background. In addition, we employ multi-task learning and Adaptive Gradient Clipping to improve the network. Extensive experiments show that our proposed method outperforms the state-of-the-art methods for image sentiment analysis. © 2023 IEEE.

关键词： Image classification

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Temporal Attention Based TCN-BIGRU Model for Energy Time Series Forecasting

Temporal Attention Based TCN-BIGRU Model for Energy Time Ser...

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2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering, CSAIEE 2021

作者： Li, Liang Hu, Min Ren, Fuji Xu, Haijun Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine HeFei China Graduate School of Advanced Technology Science University of Tokushima Tokushima Japan

ISBN: (纸本)9781665422048

Over the years, energy time series forecasting has been widely studied and has played an important role in various fields, such as electric energy forecasting, solar energy forecasting, etc. In energy time series forecasting, it is crucial to building forecasting models for long series in order to obtain accurate forecasting results. Since the use of long series can cause the accuracy of the model to decrease. In this paper, we propose a deep learning model (TCNTA-BiGRU) based on a bi-directional gated cyclic unit (BiGRU) with a temporal attention mechanism to address the problem of accuracy degradation in long sequence tasks. First, in order to capture long-term dependencies, this paper divide the dataset and input it into a temporal convolutional network (TCN) to transform long sequences into multiple short sequences, which not only solves the problem that to cause gradient explosion or disappearance when processing long sequences, but also reduces the spatial complexity. Then, BiGRU is used to learn historical and future information and capture more short-term dependencies. Moreover, in order to enhance the model's ability to focus on data periodicity, a temporal attention mechanism is introduced. Additionally the autoregressive module is used to increase the linear fitting ability of the model. The model proposed in this paper is applied to the Electricity and Solar Energy datasets and the results show a better performance relate to existing deep learning models. © 2021 IEEE.

关键词： Solar energy

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Anion-manipulated coordination-catalyzed tandem reaction to construct multinuclear dysprosium-based single-molecule magnets

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Journal of Molecular Structure 2025年 1342卷

作者： Fan Yang Yu-Lin Duan Jia-Nan Xie Hai-Ling Wang Guang-Jun Lu Hua-Hong Zou School of Chemistry and Pharmaceutical Sciences Guangxi Key Laboratory of Brain-inspired Computing and Intelligent Chips School of Electronic and Information Engineering Guangxi Normal University Guilin 541004 PR China Guangxi Center for Food and Drug Evaluation & Inspection Nanning 530004 PR China School of Chemistry and Chemical Engineering Guangxi Key Laboratory of Electrochemical Energy Materials Guangxi University Nanning 530004 PR China Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education) Nankai University Tianjin 300071 PR China

The in situ tandem reaction manipulated by anions and catalyzed by Dy(III) ions has emerged as a novel strategy for constructing polynuclear dysprosium-based single-molecule magnets. Herein, we utilized two different anions, NO 3 ⁻ and Cl⁻, to regulate the differential coordination-catalyzed in situ tandem reactions of o -vanillin and thiodiacylhydrazine, obtaining the linearly arranged trinuclear dysprosium complex 1 and the trapezoidally arranged tetranuclear dysprosium complex 2 , respectively. Specifically, o -vanillin and thiodiacylhydrazine underwent a multi-step coordination-catalyzed in situ tandem reaction to form a complex ligand similar to vanillin azine, (L 1 ) 2 ⁻, and then further self-assembled with another unilateral acylhydrazone ligand (L 2 )⁻ to obtain the trinuclear dysprosium complex 1 ; two molecules of o -vanillin and one molecule of thiodiacylhydrazine underwent a Schiff base reaction to obtain the bilateral acylhydrazone ligand (L 3 ) 3 ⁻, and then further self-assembled to obtain the tetranuclear dysprosium complex 2 . Magnetic tests indicated that complex 1 exhibited single-molecule magnet behavior under zero direct current field, while complex 2 only showed low-temperature frequency-dependent behavior. In addition, we also analyzed the magnetic property differences of complexes 1 and 2 through theoretical calculations. To the best of our knowledge, this is the first example of obtaining polynuclear complexes with different magnetic behaviors through anion-regulated coordination-catalyzed in situ multi-step tandem reactions, which not only provides a new perspective for the development of lanthanide complex crystal engineering but also offers new ideas for the development of multinuclear lanthanide-based single-molecule magnets.

关键词： Ligands

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CloudLCA: finding the lowest common ancestor in metagenome analysis using cloud computing

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Protein & Cell 2012年第2期3卷 148-152页

作者： Guoguang Zhao Dechao Bu Changning Liu Jing Li Jian Yang Zhiyong Liu Yi Zhao Runsheng Chen Bioinformatics Research Group Key Laboratory of Intelligent Information ProcessingAdvanced Computing Research LaboratoryInstitute of Computing TechnologyChinese Academy of SciencesBeijing 100190China Bioinformatics Laboratory and National Laboratory of Biomacromolecules Institute of BiophysicsChinese Academy of SciencesBeijing 100101China State Key Laboratory for Molecular Virology and Genetic Engineering National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and PreventionBeijing 100176China Graduate School of the Chinese Academy of Sciences Beijing 100190China

Estimating taxonomic content constitutes a key problem in metagenomic sequencing data ***,extracting such content from high-throughput data of next-generation sequencing is very time-consuming with the currently available ***,we present CloudLCA,a parallel LCA algorithm that significantly improves the efficiency of determining taxonomic composition in metagenomic data *** show that CloudLCA(1)has a running time nearly linear with the increase of dataset magnitude,(2)displays linear speedup as the number of processors grows,especially for large datasets,and(3)reaches a speed of nearly 215 million reads each minute on a cluster with ten thin *** comparison with MEGAN,a well-known metagenome analyzer,the speed of CloudLCA is up to 5 more times faster,and its peak memory usage is approximately 18.5%that of MEGAN,running on a fat *** can be run on one multiprocessor node or a *** is expected to be part of MEGAN to accelerate analyzing reads,with the same output generated as MEGAN,which can be import into MEGAN in a direct way to finish the following ***,CloudLCA is a universal solution for finding the lowest common ancestor,and it can be applied in other fields requiring an LCA algorithm.

关键词： CloudLCA metagenome analysis cloud computing

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Robust stability of interactional genetic regulatory networks with reaction-diffusion terms

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Advances in Difference Equations 2017年第1期2017卷 1-20页

作者： Zou, Chengye Wei, Xiaopeng Zhang, Qiang Zhou, Changjun Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian 116024 China Key Laboratory of Advanced and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China

We have analyzed the stability of interactional genetic regulatory networks with reaction-diffusion terms under Dirichlet boundary conditions in this article. Corresponding to interaction between unstable genetic regulatory networks and stable genetic regulatory networks, the model is given, and a stability criterion is proposed through construction of appropriate Lyapunov-Krasovskii functions and linear matrix inequalities (LMI). By means of a numerical simulation, we have proved the effectiveness and correctness of the theorem, and we analyzed the factors that influence the stability for interactional genetic regulatory networks. © 2017, The Author(s).

关键词： Dirichlet boundary interactional genetic regulatory networks linear matrix inequalities reaction-diffusion

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Phasor Domain Transmission Line Fault Locating with Three Phase Distributed Parameter Modeling

Phasor Domain Transmission Line Fault Locating with Three Ph...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Liu, Yu Tan, Zhenyu Xie, Jiahao Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology School of Electronic Science & Applied Physics Hefei University of Technology Hefei Anhui China

ISBN: (纸本)9781538677032

Accurate fault locating reduces power outage time and operational costs. In this paper, a novel phasor domain transmission line fault locating algorithm is proposed. Best implementation requires GPS synchronized measurements at both terminals of the line. First, the model of the transmission line with fault is constructed using three phase distributed parameter modeling with neutral conductors and grounding representation. The model is without the assumption that the transmission line is geometrically balanced. Next, the state estimation algorithm is utilized to solve the model of the transmission line with fault, where the fault location is included as a state. Numerical experiments demonstrate that the method has higher accuracy than traditional fault locating methods, independent of fault types, locations and impedances.

关键词： Three Phase Distributed Parameter Modeling State Estimation (SE) Fault Locating

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Dual-axial self-attention network for text classification

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Science China(Information Sciences) 2021年第12期64卷 80-90页

作者： Xiaochuan ZHANG Xipeng QIU Jianmin PANG Fudong LIU Xingwei LI State Key Laboratory of Mathematical Engineering and Advanced Computing Shanghai Key Laboratory of Intelligent Information Processing Fudan University School of Computer Science Fudan University

Text classification is an important task in natural language processing and numerous studies aim to improve the accuracy and efficiency of text classification models. In this study, we propose an effective and efficient text classification model which is based on self-attention solely. The recently proposed multidimensional self-attention significantly improved the performance of self-attention. However, existing models suffer from two major limitations:(1) the previous multi-dimensional self-attention models are quite timeconsuming;(2) the dependencies of elements along the feature axis are not taken into account. To overcome these problems, in this paper, a much more computational efficient multi-dimensional self-attention model is proposed, and two parallel self-attention modules, called dual-axial self-attention, are applied to capture rich dependencies along the feature axis as well as the text axis. A text classification model is then *** experimental results on eight representative datasets show that the proposed text classification model can obtain state-of-the-art results and the proposed self-attention outperforms conventional self-attention models.

关键词： text classification dual-axial self-attention feature-axial dependency

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Image encryption algorithm based on DNA sequences for the big image

Image encryption algorithm based on DNA sequences for the bi...

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International Conference on Multimedia Information Networking and Security

作者： Zhou, Shihua Zhang, Qiang Wei, Xiaopeng School of Mechanical Engineering Dalian University of Technology Dalian China Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian China

ISBN: (纸本)9780769542584

With the fast development of Internet technology and information processing technology, the image is commonly transmitted via the Internet. People enjoy the convenience and shortcut, but people have to face to the obsession that the important image information in transmission is easily intercepted by unknown persons or hackers. In order to enhance the image information security, image encryption becomes an important research direction. An image encryption algorithm based on DNA sequences for the big image is presented in this paper. The main purpose of this algorithm is to reduce the big image encryption time. This algorithm is implemented by using the natural DNA sequences as main keys. The first part is the process of pixel scrambling. The original image is confused in the light of the scrambling sequence is generated by the DNA sequence. The second part is the process of pixel replacement. The pixel gray values of the new image and the one of the three encryption templates are generated by the other DNA sequence are XORed bit-by-bit in turn. The experimental result demonstrates that the image encryption algorithm is feasible and simple. Through performance analysis, this algorithm is robust against all kinds of attacks and owns higher security. © 2010 IEEE.

关键词： DNA sequences

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A rigid structure matching-based noise data processing approach for human motion capture

A rigid structure matching-based noise data processing appro...

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International Workshop on Digital Media and Digital Content Management, DMDCM 2011

作者： Wei, Xiaopeng Xiao, Boxiang Zhang, Qiang Liu, Rui Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian China School of Mechanical Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9780769544137

A noise data processing algorithm based on rigid structure matching for human motion capture (MoCap) is presented in this paper. The noise model is related to parts of human body, but not to trajectories of markers as most used in traditional approaches. Three issues are addressed in this method: rigid structure matching, semantic restriction and noise reduction, and they are three steps of data processing. First, human body is divided into seven main parts: head, chest, waist, hands and legs, and all parts' candidate parts are generated by algorithm of rigid structure matching from motion data. Missing markers can be automatically reconstructed by existing markers on a same rigid structure. Subsequently, one group of parts with most possibility is determined as initial processed data by semantic restriction. Finally, an impulse noise model is found based on the analysis of data, and the noise has been filtered. At the end, the main conclusions of this research are drawn, and the advantages and limitations of this approach are discussed respectively. The algorithm presented can be easily implemented and performed, and the processed motion data can be expediently used in human body animation. The efficiency of the method is illustrated by the experiments. © 2011 IEEE.

关键词： Rigid structures

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