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Community Search in Spatial Uncertain Network

Community Search in Spatial Uncertain Network

引用

2021 Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021

作者： Zhang, Wenqian Zhong, Yingli Yang, Yan School of Computer Science Technology Heilongjiang University Harbin150080 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin150080 China

Community search is to explore valuable target community structure from a large social network. In real community, every point has a geographic location information, and many edges are uncertain. Such a network is called spatial uncertain network. In order to meet the existing needs, this paper studies the community search in the spatial uncertain network so that the searched communities can be relatively close in the geographical location and the relationship between each other is also very close. Based on the spatial uncertain graph, this paper proposes K-R-τ community, and proposes a linear algorithm and a two-dimensional algorithm for community search in the spatial uncertain network. A large number of experiments are carried out on several real datasets, and the results show that the algorithm proposed in this paper is effective and accurate. © Published under licence by IOP Publishing Ltd.

关键词： Social networking (online)

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Double Loss Block Neural Architecture Search 10

Double Loss Block Neural Architecture Search

引用

10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022

作者： Liu, Yang Lu, Jun College of Computer Science and Technology Heilongjiang University Harbin150080 China Heilongjiang University Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin150080 China

ISBN: (数字)9781665422079

ISBN: (纸本)9781665422079

Neural architecture search aims to automatically design network architectures by machines, which is expected to bring about a new revolution in machine learning. Despite high expectations, the effectiveness and efficiency of existing neural architecture search solutions are unclear, and the inefficiency of neural architecture search solutions is mainly attributed to inaccurate architecture evaluation. In this work, this paper divides the large search space of neural architecture search into multiple modules, effectively reducing the error caused by shared parameters to ensure that the candidate architectures in the modules are fully trained. By adopting a block search method, this paper can Evaluate all candidate architectures in a module, addressing the problem of inaccurate evaluation. In addition, high-quality data is necessary. Under the guidance of the teacher model, combined with the ground truth, the neural architecture search is supervised by the double loss function. Under the constraint of the same amount of computation, the method in this paper achieves 77.3% top-level accuracy on ImageNet., which is 1.0% higher than the efficient network EfficientNet-B0, and 0.3% higher than the DNA method without additional computation. Therefore, the double loss block neural architecture search model proposed in this paper significantly improves the effectiveness of neural architecture search. © 2022 IEEE.

关键词： Distillation

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Research on F Statistic parallel Algorithm Based on GPU

Research on F Statistic Parallel Algorithm Based on GPU

引用

2016 IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference(IMCEC 2016)

作者： Xingkun Liu Jun Lu Ruiqing Jing Jinliang Zheng Jun Li College of Comp uter Science and Technology Heilongjiang University Key Laboratory of Database and Parallel Comp uting of Heilongjiang Province

ISBN: (纸本)9781509001668

The experimental data is soybean gene variation information *** individual biological information is extracted from the soybean gene file and the value of the relationship between populations is *** the degree of differentiation of the two populations of wild soybean and cultivated soybean is ***,the easy parallel serial algorithm is *** accordi ng to the independence of the operational object,the partial algorithm can be paralleled is parallel processed with GPU multi thread ***,the result and the time of the serial/parallel algorithm are analyzed and *** experimental results show that the GPU algorithm efficiency is much higher than the serial algorithm *** pro vides a quick calculation scheme to handle massive biological data.

关键词： F statistics GPU differentiation mutation

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Human Pose Estimation Network Based On MultiHeatmap Fusion 5

Human Pose Estimation Network Based On MultiHeatmap Fusion

引用

5th Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2024

作者： Zhao, Yangguang Lu, Jun College of Computer Science and Technology Heilongjiang University Key Laboratory of Database and Parallel Computingof Heilongjiang Province Haerbin China

ISBN: (纸本)9798350374407

Estimating human pose in complex multi-frame situations is a challenging task and has attracted intensive research by many researchers. Although 3D human pose estimation methods have achieved remarkable results in scenes based on single images, their performance often fails once these model transformations are applied to video sequences. Common problems with these models include inability to cope with motion blur, out-of-focus videos, and occlusion of human poses. In order to solve the above problems, this paper proposes a feature extraction and representation model MHMF, which is used in the feature extraction stage of the model. The initial features extracted by the backbone network HRNet-w32 are guided by the heat map to the attention layer, which improves the network's attention to important areas for predicting key points of human posture. At the same time, the integration of the aggregation heat map and the backbone network heat map improves the spatiotemporal consistency of the key points. In addition, to improve the accuracy of mesh pose estimation under occlusion, this paper proposes a transformer-based NewDSTformer model. By adjusting the structure of the Transformer encoder, increasing the encoder level and combining it with the dynamic progressive attention masking method. The model can adapt to different input situations, handle the positional relationship of local key points, and be able to perform accurate detection even under occlusion. It was evaluated on the 3DPW data set and improved the accuracy by $0.3 \%$, indicating that this paper effectively improved the performance of 3D human mesh reconstruction. © 2024 IEEE.

关键词： Mesh generation

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Improving rating estimation in recommender using demographic data and expert opinions

Improving rating estimation in recommender using demographic...

引用

2011 IEEE 2nd International Conference on Software Engineering and Service Science, ICSESS 2011

作者： Yun, Long Yang, Yan Wang, Jing Zhu, Ge Dept. of Computer Science and Technology Heilongjiang University Key Lab. of Database and Parallel Computing Heilongjiang Province Harbin China

ISBN: (纸本)9781424496969

Memory-based collaborative filtering algorithms have been widely adopted in many popular recommender systems, however the rating data are very sparse, which affects prediction accuracy greatly. To solve this problem, we use expert opinions to improve prediction accuracy. Firstly, we propose a novel similarity measure in order to highlight users' background. Then, combining users' ratings with expert opinions, the prediction get a right balance in both expert professional opinions and similar users. Finally, since SVD-based collaborative filtering algorithms shows good performance on the prevention of noise, we use it to smooth the prediction. Experiments of MovieLens have shown that our proposed method improves recommendation quality obviously. © 2011 IEEE.

关键词： Collaborative filtering

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The parallel processing for promoter data base on OpenMP

The parallel processing for promoter data base on OpenMP

引用

International Conference on Electronic Engineering and Information Science, ICEEIS 2015

作者： Shi, Y. Lu, J. Zheng, J.J. College of Computer Science and Technology Heilongjiang University China College of Computer Science and Technology Heilongjiang University Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (纸本)9781138027725

The promoters of Arabidopsis and the Poplar are parallel processed and analyzed in this paper. The mainly works include three parts: First, The Motif data are parallel matched with both plant promoter data based on OpenMP. Then, the matching result is processed by frequent mining technology. The experimental result shows that the parallel processing time based on OpenMP is far less than the serial time. Second, to increase the calculation accuracy, the algorithm of solving the P value is improved by the prime split method. At last, according to the frequent process result, the shared frequent items of the two plants are analyzed. © 2015 Taylor & Francis Group, London.

关键词： Application programming interfaces (API)

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Cross-Modality Encoder Representations Based On External Attention Mechanism 3

Cross-Modality Encoder Representations Based On External Att...

引用

3rd International Conference on Neural Networks, Information and Communication Engineering, NNICE 2023

作者： Zheng, Yudong Lu, Jun College of Computer Science and Technology Heilongjiang University Harbin China College of Computer Science and Technology Heilongjiang University Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (纸本)9798350335972

With the prevalence of deep learning, people use multi-modality information for interpretation and reasoning. In this paper, a cross-modality encoder CMEEA (cross-modality encoder representation based on external attention mechanism) is adopted to improve the accuracy of the model. The two external storage units of CMEEA can be regarded as a dictionary of the whole dataset to improve the performance of the network, while learning more representative features of the input and reducing the computational cost. This paper uses five pretraining tasks that help the model learn internal modal and cross-modal relationships. It also verifies the generalizability of the model by applying the pretraining cross-modal model to the visual inference task NLVR2, and improves the previous results by 0.1%. By fine-tuning the pretrain parameters, the model improves by 1.3% on visual question answering (VQA). © 2023 IEEE.

关键词： Deep learning

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Research on combinatorial encryption method

Research on combinatorial encryption method

引用

2014 International Conference on Information Science, Electronics and Electrical Engineering, ISEEE 2014

作者： Lu, Jun Mo, Juan Lv, Xingfeng Zhang, Zhuo College of Computer Science and Technology Heilongjiang University College of CS HLJU Harbin China Key Laboratory of Database and Parallel Computing Heilongjiang Province KLDPC HLJU Harbin China

ISBN: (纸本)9781479931965

Combinatorial encryption algorithm is advanced. Combinatorial encryption method makes use of the variety of ordinal in universal combination code. Firstly, the theory of universal combinatorial coding is expatiated. Secondly, researches are done in combinatorial encryption characteristic, key generating method, encryption and decryption algorithms. At last, key space is analyzed. Combinatorial encryption technology breaks through the thought of encryption. It is based on combinatorial theory and the code element is adopted as the basic unit in encryption computing. Furthermore, the key generating method is unique. Combinatorial encryption technology makes a new attempt to cipher system. © 2014 IEEE.

关键词： Cryptography

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A New Feature Fusion Method Based on Pre-Training Model for Sequence Labeling 6

A New Feature Fusion Method Based on Pre-Training Model for ...

引用

6th International Conference on Data Storage and Data Engineering, DSDE 2023

作者： Yu, Shichuan Yang, Yan School of Computer Science and Technology Heilongjiang University Harbin China Heilongjiang University Heilongjiang Key Laboratory of Database and Parallel Computing Harbin China

ISBN: (纸本)9798350333145

To fuse vocabulary features into the pre-training model is the mainstream data feature processing method for sequence labelling tasks. In general, the feature fusion methods that have been proposed at present are direct fusion outside the pre-training model or fusion of lexical features using attention mechanism. However, the study found that this way of vocabulary enhancement does not conform to the word formation rules of modern Chinese. In the Chinese language, it is easy to fuse irrelevant or even incorrect lexical features into the sequence using the above feature processing methods, which is bad for the experimental results of the Chinese sequence labelling task. To solve these problems, we propose to use Cosine Similarity Adapter to process lexical features in Chinese sequence labelling tasks. CSBERT is a hybrid model using this structure based on BERT, which conforms to the word formation rules of modern Chinese to a certain extent. It can fuse the features of the word into the character or eliminate the features of the word in the character according to the cosine similarity between the character vector and a word vector. The experimental results show that CSBERT has better ability to label Chinese sequences than the benchmark model. CSBERT has achieved the best experimental results such as F1-Score on 7 open datasets and the best ability of multi-label classification, which proves that the model has good practical value. © 2023 IEEE.

关键词： Classification (of information)

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Influence Maximization in Microblog Social Network 7

Influence Maximization in Microblog Social Network

引用

7th International Conference on Information Science and Control Engineering, ICISCE 2020

作者： Ma, Zhengyi Yang, Yan Heilongjiang University School of Computer Science Technology Harbin China Key Laboratory of Database and Parallel Computing Harbin China

ISBN: (纸本)9781728164069

In recent years, the continuous rise of social networks has promoted the research of maximizing influence. Therefore, it is more and more important to mine a group of users with the largest influence range in social network, which is also of great significance for the promotion of some products. To solve the above problems, this paper studies the influence maximization in microblog social network, and proves that the problem is NP hard, and the objective function of the problem satisfies monotonicity and submodule. An effective algorithm is proposed to solve this problem. The algorithm fully considers the nature of microblog social network and microblog users, and measures the influence of users themselves with activity, communication power and coverage. Based on the independent cascade model, a communication model is designed according to the influence of users and the interaction times between users. Through the experiment on the real microblog data set, it is proved that the algorithm has good performance in the propagation range and operation efficiency, and the propagation effect is more in line with the reality. © 2020 IEEE.

关键词： Economic and social effects

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