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International Conference on Information Science and Control Engineering (ICISCE)

作者： Penghui Dong Yan Yang School of Computer Science and Technology Heilongjiang University Harbin China Key Laboratory of Database and Parallel Computing Heilongjiang Province Harbin China

This paper solves the problem of approximate nearest neighbor queries on high-dimensional large data sets. The two most representative methods to solve the approximate nearest neighbor query problem on high-dimensional and large-scale data sets are based on inverted multi-index and based on inverted index. The query algorithm based on the inverted multi-index requires frequent access operations to the memory, which causes more waste of resources than the query operation based on the distance order. Traditional query algorithms based on inverted indexes need to divide the entire feature space into a large number of regions to ensure the accuracy of query results when solving the problem of high-dimensional large data sets, so a large amount of space resources are required. Based on the inverted index, a query algorithm is proposed. Through the subdivision process of Voronoi Cells that are initially divided into part of the original data set, the purpose is to significantly improve the high-dimensional data set without dividing a large number of regions. On the query performance, and avoid frequent access operations to the random access memory. Theoretical analysis and experimental results show that the proposed method not only effectively improves the query processing efficiency, but also ensures the accuracy of the query.

关键词： Information science Control engineering Query processing Memory management Random access memory Approximation algorithms Partitioning algorithms

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M&M: A Multi-channel MAC Protocol with Multiple Channel Reservation for Wireless Sensor Networks

M&M: A Multi-channel MAC Protocol with Multiple Channel Rese...

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International Conference on Cyber-Enabled Distributed computing and Knowledge Discovery, CyberC

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

In this paper, a multi-channel MAC protocol, called M&M, with multiple channel reservation is proposed to tackle the channel conflict problem. M&M is fully distributed with no requirements of time synchronization or multi-radio, so it is very practical to implement M&M in resource-constrained sensor nodes. M&M can make nodes to choose one actually idle channel for communications from all assumed idle channels. Therefore, M&M can greatly alleviate, if not completely eliminate, packet collisions resulted by the channel conflict, and thus conserve more energy to prolong the lifetime of WSNs. To investigate the values of multiple channel reservation, extensive simulation and real test bed experiments are conducted. The results show that when the number of channels becomes larger or loads are heavy, M&M improves energy efficiency and throughput significantly.

关键词： Wireless sensor networks Throughput Receivers Synchronization Media Access Protocol Media

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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...

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IEEE/IFIP International Conference on Embedded and Ubiquitous computing, EUC

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

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 test bed experiments were con-ducted. 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.

关键词： Receivers Wireless sensor networks Throughput Ad hoc networks Media Access Protocol Media

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Contrastive Enhanced Filter Model Based on Bidirectional Transformer for Sequential Recommendation

Contrastive Enhanced Filter Model Based on Bidirectional Tra...

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

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

ISBN: (数字)9798350374407

ISBN: (纸本)9798350374414

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.

关键词： Adaptation models Time-frequency analysis Electric potential Filters Image processing Noise Contrastive learning Transformers Time-domain analysis Recommender systems

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Mining recent approximate frequent items in wireless sensor networks

Mining recent approximate frequent items in wireless sensor ...

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6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009

作者： Ren, Meirui Guo, Longjiang School of Computer Science and Technology Heilongjiang University Harbin China Data Base and Parallel Computing Key Laboratory of Heilongjiang Province China School of Computer Science and Technology Harbin Institute of Technology China

ISBN: (纸本)9780769537351

Mining Frequent Items from sensory data is a major research problem in wireless sensor networks(WSNs) and it can be widely used in environmental monitoring. Conventional Lossy Counting algorithm can be applied to solve this problem in centralized manner. However, centralized algorithm brings severely data collision in WSNs, and results in inaccurate mining results. In this paper, we present D-FIMA, a distributed frequent items mining algorithm. D-FIMA, running at every sensor node, establishes items aggregation tree via forwarding mining request beforehand, and each node maintains local approximate frequent items. The root of the aggregation tree outputs the final global approximate frequent items. Theoretical analysis and the simulation results show that energy consumption of D-FIMA is much less than the centralized algorithm, and mining results of D-FIMA is more accurate than the centralized algorithm. © 2009 IEEE.

关键词： Sensor nodes

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Influence Maximization in Microblog Social Network

Influence Maximization in Microblog Social Network

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International Conference on Information Science and Control Engineering (ICISCE)

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

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.

关键词： Information science Power measurement Control engineering Social networking (online) Blogs Linear programming

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ShuffleVITNet: Mobile-Friendly Vision Transformer With Less-Memory

ShuffleVITNet: Mobile-Friendly Vision Transformer With Less-...

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International Joint Conference on Neural Networks (IJCNN)

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

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Traditional Convolutional Neural Networks (CNNs) can efficiently acquire local features, while ViT uses a Transformer structure that captures global contextual information. In this paper, a new high-performance lightweight target detector is designed by combining the respective advantages of CNN and ViT: ShuffleViTNet. In this paper, we improve the VIT Block in MobileVIT, firstly, we use channel-by-channel convolution to replace the normal convolution to reduce the memory access cost (MAC), number of parameters (Parmas) and floating-point operations (FLOPs) in the model inference. The 1×1 convolution is then used to fuse the local features learned by the convolution with the global features learned by the Transofmer, which further lightens the model and allows for easier modification of the number of channels and migration to other lightweight neural networks. Finally a lightweight network friendly to mobile devices is constructed using the improved VIT Block. On the ImageNet-1k dataset, ShuffleViTNet achieves 75.2% Top-1 accuracy, the model’s floating-point operation is 536.5 MFLOPs, which is 44.0% less compared to MobileViT-XS, and the cost of memory accesses for model inference is saved by about 25.6%, and the required memory is saved by about 66.37%. For the object detection task on the MS-COCO dataset, ShuffleViTNet obtains higher mAP accuracy. The experimental results show that ShuffleViTNet is a high-performance lightweight network and can be well applied to downstream tasks.

关键词： Accuracy Costs Convolution Computational modeling Neural networks Memory management Object detection

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Multi-pattern matching methods based on numerical computation

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Telkomnika - Indonesian Journal of Electrical Engineering 2013年第3期11卷 1497-1505页

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

Multi-pattern matching methods based on numerical computation are advanced in this paper. Firstly it advanced the multiple patterns matching algorithm based on added information. In the process of accumulating of information, the select method of byte-accumulate operation will affect the collision odds , which means that the methods or bytes involved in the different matching steps should have greater differences as much as possible. In addition, it can use balanced binary tree to manage index to reduce the average searching times, and use the characteristics of a given pattern set by setting the collision field to eliminate collision further. In order to reduce the collision odds in the initial step, the information splicing method is advanced, which has greater value space than added information method, thus greatly reducing the initial collision odds. Multiple patterns matching methods based on numerical computation fits for large multi-pattern matching. © 2013 Universitas Ahmad Dahlan.

关键词： Numerical methods

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BIVD: Improved Side Adapter Network based on BiFormer

BIVD: Improved Side Adapter Network based on BiFormer

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

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

ISBN: (数字)9798350374407

ISBN: (纸本)9798350374414

Currently, most open vocabulary models rely on CLIP (Contrastive Language-Image Pre-training) to classify masked regions, but CLIP models still have many drawbacks. The traditional transformer model is context aware through self attention, but this local context based mechanism is limited by the sequence length of information, it can also impact model effect. Inspired by the article BiFormer, This article replaces the traditional transformer model in the Side Adapter Network (SAN) model with a variant module BIVD block based on BiFormer blocks. This model follows the latest transformer model and extracts features using a four layer feature pyramid structure, For the reduced spatial resolution caused by patch merging, add a Visual-Decoder to reshape the visual vector sequence into a spatial feature map, and restore it to the original resolution through convolution and upsampling. This can enhance the extracted feature information through a feature pyramid without affecting the fusion with CLIP layer features. But the cost is increasing the cost of the model. This article was tested on 5 commonly used datasets and showed a stable improvement in accuracy.

关键词： Adaptation models Vocabulary Visualization Costs Semantic segmentation Feature extraction Transformers Decoding Spatial resolution Context modeling

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Research on Linkage Disequilibrium Method Based on OpenMP

Research on Linkage Disequilibrium Method Based on OpenMP

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International Conference on Information Science and Control Engineering (ICISCE)

作者： Jun Lu Jun Li Ruiqing Jing Qiong Wang Cheng Chang Jiaxing Guo 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)9781509025367

Linkage disequilibrium method is applied for the research on inferring population genetics, LD mapping, haploid type diversity analysis and so on. Soybean genotypes are adopted as the data source and linkage disequilibrium parallel algorithm is implemented by OpenMP technology. In this algorithm, single nucleotide polymorphism sites are divided by using sliding windows into groups, adjacent sites allele in a window of each chromosome are parallel calculated and store the LD results. According to the experimental data, the serial and parallel algorithms are compared and analyzed. The conclusion shows that the OpenMP parallel technology can effectively improve the efficiency of linkage disequilibrium analysis method. It is a realistic significance for processing massive biological information data.

关键词： Biological cells Couplings Genetics Instruction sets Sociology Statistics parallel algorithms

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