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检索条件"机构=Heilongjiang Province Key Laboratory for Database and Parallel Computing"

共 138 条记录，以下是21-30 订阅

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Using gaussian mixture model to fix errors in SFS approach based on propagation 2nd

Using gaussian mixture model to fix errors in SFS approach b...

引用

2nd International Conference on Young Computer Scientists, Engineers and Educators, ICYCSEE 2016

作者： Huang, Wenmin Ma, Jiquan Zhang, Enbin College of Computer Science and Technology Heilongjiang University Harbin China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (纸本)9789811020520

A new Gaussian mixture model is used to improve the quality of propagation method for SFS in this paper. The improved algorithm can overcome most difficulties of propagation SFS method including slow convergence, interdependence of propagation nodes and error accumulation. To slow convergence and interdependence of propagation nodes, stable propagation source and integration path are used to make sure that the reconstruction work of each pixel in the image is independent. A Gaussian mixture model based on prior conditions is proposed to fix the error of integration. Good result has been achieved in the experiment for Lambert composite image of the front illumination. © Springer Science+Business Media Singapore 2016.

关键词： Errors

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An Incremental Partitioning Graph Similarity Search Based on Tree Structure Index 6th

An Incremental Partitioning Graph Similarity Search Based on...

引用

6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020

作者： Li, Yuhang Yang, Yan Zhong, Yingli School of Computer Science Technology Heilongjiang University Harbin China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (纸本)9789811579806

Graph similarity search is a common operation of graph database, and graph editing distance constraint is the most common similarity measure to solve graph similarity search problem. However, accurate calculation of graph editing distance is proved to be NP hard, and the filter and verification framework are adopted in current method. In this paper, a dictionary tree based clustering index structure is proposed to reduce the cost of candidate graph, and is verified in the filtering stage. An efficient incremental partition algorithm was designed. By calculating the distance between query graph and candidate graph partition, the filtering effect was further enhanced. Experiments on real large graph datasets show that the performance of this algorithm is significantly better than that of the existing algorithms. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Large dataset

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Visible-Infrared Image Fusion Based on Double- Density Wavelet and Thermal Exchange Optimization 5

Visible-Infrared Image Fusion Based on Double- Density Wavel...

引用

5th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2021

作者： Guo, Hao Chen, Jingyu Yang, Xuan Jiao, Qingliang Liu, Ming Beijing Institute of Environmental Features Beijing China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

Infrared and visible image fusion has been a hot issue in image fusion. However, the parameters and result image have many proposed. In this paper, a novel visible infrared image fusion algorithm based on double-density wavelet and thermal exchange optimization is proposed. The pre-processed infrared and visible images are decomposed into detail layers and background layers by double-density wavelet transform. Thermal exchange optimization is used to estimate the number of layers and weight thresholds of decomposition. Experimental shows that both visual effects and quantitative analysis of proposed algorithm can get the best results. © 2021 IEEE.

关键词： Image fusion

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Negative influence maximization in social networks 4th

Negative influence maximization in social networks

引用

4th International Conference of Pioneer Computer Scientists, Engineers and Educators, ICPCSEE 2018

作者： Zhu, Jinghua Li, Bochong Zhang, Yuekai Li, Yaqiong School of Computer Science and Technology Heilongjiang University Harbin150001 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (纸本)9789811322020

Influence maximization is one of the key research problems in social networks due to its wide applications like spread of ideas and viral marketing of products. Most of the existing work focus on social networks containing only positive relationships (e.g. friend or trust) between users, but in reality social networks containing both positive and negative relationships (e.g. foe or distrust). Ignoring the negative relations may lead to over-estimation of positive influence in practical applications. Thus, in this paper, we study influence maximization problem with negative effects (NIM). To address the NIM problem, we use the polarity Independent Cascade (IC-P) diffusion model which extends the standard Independent Cascade (IC) model with negative opinions. Then we propose the positive influence maximization algorithm (PIM) and negative influence maximization (NIM) problem. We prove that influence function of the NIM problem is monotonic and submodular, so we propose a CELF based algorithm (CELF_NIM) to solve it. Experiments results show that our algorithm has matching influence spread compared with greedy algorithm and achieves several orders of magnitude time improvement. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Economic and social effects

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Research on parallel Algorithms of Uncertain Combinational Coding 10

Research on Parallel Algorithms of Uncertain Combinational C...

引用

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

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

ISBN: (数字)9781665422079

ISBN: (纸本)9781665422079

In this era of rapid development of information science and technology, data coding technology has been widely used in multimedia, computer, communication and other fields. Non-deterministic combined coding is further explored in deterministic combined coding. It is a kind of lossless coding. In combinatorial mathematics, the operation of the combination number calculates the ordinal number of the sequence to be coded. On the basis of the deterministic combination coding, the adjacent identical elements are eliminated and processed separately, which reduces the length of the ordinal number. At the same time, the reference sequence is encoded to further save space. However, the ordinal calculation of the non-deterministic combination coding is still a complicated process, and the coding speed is still slow. This article uses openMP technology to parallelize the ordinal calculation part of the non-deterministic combination coding. The running time of coded ordinal on the eight-core CPU is 23.38% of the original, which is 4.28 times optimized, and the overall coding time efficiency of the 17 segmented file instances has been improved about 2.94 times. It indicates the effectiveness of the parallel strategy in this article. Finally, this article analyzes the experimental results. © 2022 IEEE.

关键词： Number theory

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Contrastive Enhanced Filter Model Based on Bidirectional Transformer for Sequential Recommendation 5

Contrastive Enhanced Filter Model Based on Bidirectional Tra...

引用

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

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

ISBN: (纸本)9798350374407

Transformer-based sequential recommendation is highly powerful as it can capture short-term and long-term sequential recommendation. It plays a crucial role in personalized recommendation systems, aiming to extract dynamic and diverse preference information from users' realtime growing behaviors. This is mainly due to its unique selfattention mechanism, which utilizes item-item interactions within the sequences. However, in online platforms, due to the interweaving of items in user behavior, user behavior data inevitably contains noise. Currently, most methods model user preferences in the time domain, overlooking the influence of frequency patterns on user behavior. To address this issue, this paper shifts the perspective to the frequency domain and proposes a novel contrast-enhanced filtering model for sequential recommendation based on the bidirectional Transformer, called CEFRec. Specifically, the paper designs a filtering layer on top of the bidirectional Transformer, allowing learnable filters to operate on different layers' spectra. This enables the model to capture various frequency patterns and adaptively attenuate noise information within the frequency domain. Next, the model combines the cloze task mask and dropout masks to generate high-quality positive samples and utilizes contrastive learning to enhance the quality of user embeddings learned from the frequency domain. Finally, experimental results on three public benchmark datasets demonstrate that the CEFRec model outperforms state-of-theart sequential recommendation models. © 2024 IEEE.

关键词： Contrastive Learning

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Prediction Based Reverse Auction Incentive Mechanism for Mobile Crowdsensing System 13th

Prediction Based Reverse Auction Incentive Mechanism for Mob...

引用

13th Annual International Conference on Combinatorial Optimization and Applications, COCOA 2019

作者： Wang, Zhen Zhu, Jinghua Li, Doudou School of Computer Science and Technology Heilongjiang University Harbin150001 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (纸本)9783030364113

With the rapid development of the Internet, Mobile Crowdsensing System (MCS) is widely used in various fields. Because of the insufficient number of users’ participation and the insufficient amount of uploaded sensing data, the research of incentive mechanism is particularly important in MCS. Reverse auction mechanism is one of the efficient incentive mechanism in MCS. The platform is responsible for publishing a group of tasks which are bidded by the workers, and only the winning workers are authorized to complete the tasks. One of the critical factors for successful bidding is the distance between the tasks and the workers. However, most workers in MCS always keep moving. So this paper proposes a prediction based reverse auction incentive mechanism—RMMP. We use the Semi-Markov model to predict the position of workers at the next moment. According to the predicated positions, our reverse auction incentive mechanism selects the winner workers with the minimum movement distance and bidding price. Experiment results on real dataset show that our RMMP mechanism has remarkable performance compared with the existing mechanisms. © 2019, Springer Nature Switzerland AG.

关键词： Forecasting

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OMA: A multi-channel MAC protocol with opportunistic media access in wireless sensor networks

OMA: A multi-channel MAC protocol with opportunistic media a...

引用

International Conference on Mobile Ad-hoc and Sensor Networks

作者： Li, Jinbao Zhang, Desheng Guo, Longjiang School of Computer Science and Technology Heilongjiang University Harbin Heilongjiang 150080 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin Heilongjiang 150080 China

ISBN: (纸本)9780769543154

To tackle control channel saturation problems, this paper proposes OMA, an asynchronous duty cycle based multi-channel MAC protocol with opportunistic media access for wireless sensor networks. By adopting opportunistic media access, OMA effectively alleviates, if not completely eliminates, control channel saturation problems. More importantly, OMA is fully distributed with no requirements of time synchronization or multi-radio. Therefore, OMA is very easy to be implemented in resource-constrained sensor nodes. Via the theoretical analysis, the opportunistic probability with which a node opportunistically access the control channel is obtained. To validate the effectiveness of opportunistic media access, extensive simulations and real testbed experiments were conducted. The simulation and experimental results show that when the number of channels is large or the network loads are heavy, OMA improves energy efficiency and throughput significantly compared with other works in the literature. © 2010 IEEE.

关键词： Sensor nodes

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Joint routing, scheduling and channel assignment in multi-power multi-radio wireless sensor networks

Joint routing, scheduling and channel assignment in multi-po...

引用

30th IEEE International Performance, computing and Communications Conference, IPCCC 2011

作者： Li, Jinbao Guo, Xiaohang Guo, Longjiang School of Computer Science and Technology Heilongjiang University Harbin Heilongjiang 150080 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin Heilongjiang 150080 China

ISBN: (纸本)9781467300100

Power control is a complex issue in routing since the increase of transmission power supplies more opportunities to select optimal routes due to the fact that more links are available. However, conversely, it also implies higher interference and hence decreases the performance of routing. Since multi-radio multi-channel schemes can efficiently mitigate interferences through allowing more concurrent transmissions, therefore, it is worth to investigate the routing scheme in Multi-Power Multi-Radio (MPMR) wireless sensor networks (WSNs). In this paper, we study the joint routing, scheduling, channel assignment and power control problem in MPMR WSNs, which is proven a NP-Hard problem. We first formulate the optimal routing problem as a linear programming problem. Subsequently, we develop a distributed routing protocol based on the random walk method which can efficiently decrease the computational complexity in large-scale WSNs by avoiding solving the linear programming problem. Theoretical analysis and simulations show that the routing based on MPMR can improve the data transmission efficiency and the proposed cross-layer routing scheme significantly reduces the energy consumption and the end-to-end transmission delay. © 2011 IEEE.

关键词： Wireless sensor networks

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OCO: A multi-channel MAC protocol with opportunistic cooperation for wireless sensor networks

OCO: A multi-channel MAC protocol with opportunistic coopera...

引用

International Workshop on Wireless Network Algorithm and Theory

ISBN: (纸本)9780769543222

To handle the triple hidden terminal problems, this paper proposes OCO, an asynchronous multi-channel MAC protocol with opportunistic cooperation for wireless sensor networks. By adopting opportunistic cooperation, OCO effectively alleviates, if not eliminates, the triple hidden terminal problems. More importantly, OCO is fully distributed with no requirements of time synchronization or multi-radio scheme, so it is easy to be implemented on the real sensor nodes. Via the theoretical analysis, the opportunistic probability that a node cooperates with its neighbor is obtained. To validate the effectiveness of opportunistic cooperation, extensive simulations and real testbed experiments were conducted. The simulation and experimental results show that when the number of channels is large or the network loads are heavy, OCO improves energy efficiency and throughput significantly compared with other works in the literature. © 2010 IEEE.

关键词： Sensor nodes

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