Search Results - "Song, Aibo"

A New Low-Rank Structurally Incoherent Algorithm for Robust Image Feature Extraction by Ge, Hongmei, Song, Aibo

“…In order to solve the problem in which structurally incoherent low-rank non-negative matrix decomposition (SILR-NMF) algorithms only consider the…”
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Probe Request Based Device Identification Attack and Defense by Gu, Xiaolin, Wu, Wenjia, Gu, Xiaodan, Ling, Zhen, Yang, Ming, Song, Aibo

“…Wi-Fi network has an open nature so that it needs to face greater security risks compared to wired network. The MAC address represents the unique identifier of…”
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MMSRC: A Multidirection Multiscale Spectral-Spatial Residual Network for Hyperspectral Multiclass Change Detection by Ge, Hongmei, Tang, Yongsheng, Bi, Zuolin, Zhan, Tianming, Xu, Yang, Song, Aibo

“…Recently, deep convolutional neural network (CNN) hyperspectral change detection methods have achieved significant improvement. However, most CNN hyperspectral…”
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Distributed storage system for electric power data based on Hbase by Jin, Jiahui, Song, Aibo, Gong, Huan, Xue, Yingying, Du, Mingyang, Dong, Fang, Luo, Junzhou

“…Managing massive electric power data is a typical big data application because electric power systems generate millions or billions of status, debugging, and…”
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A Sampling-Based Hybrid Approximate Query Processing System in the Cloud by Yuxiang Wang, Junzhou Luo, Aibo Song, Fang Dong

“…Sampling-based approximate query processing method provides the way, in which the users can save their time and resources for 'Big Data' analytical…”
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QoS Preference-Aware Replica Selection Strategy Using MapReduce-Based PGA in Data Grids by Runqun Xiong, Junzhou Luo, Aibo Song, Bo Liu, Fang Dong

“…Data replication is an important technique to reduce access latency and bandwidth consumption in Grid environment. As one of the major functions of data…”
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Identifying critical nodes in power networks: A group-driven framework by Liu, Yangyang, Song, Aibo, Shan, Xin, Xue, Yingying, Jin, Jiahui

“…Cascading failures can easily occur and cause a major blackout in power systems when a critical devices breaks down. It is an essential problem to evaluate the…”
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Sensitive and effective imaging of carbon monoxide in living systems with a near-infrared fluorescent probe by Xu, Zhencai, Song, Aibo, Wang, Fangwu, Chen, Hongwei

“…CO, a gas molecule that is harmful to living organisms, has a high affinity with hemoglobin, which will cause severe hypoxia. However, in recent years,…”
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A local random walk model for complex networks based on discriminative feature combinations by Song, Aibo, Liu, Yangyang, Wu, Zhiang, Zhai, Mingyu, Luo, Junzhou

“…•A local random walk model based on discriminative feature combinations is proposed.•Selecting discriminative feature combinations can improve predictive…”
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Efficiently Translating Complex SQL Query to MapReduce Jobflow on Cloud by Wu, Zhiang, Song, Aibo, Cao, Jie, Luo, Junzhou, Zhang, Lu

“…MapReduce is a widely-used programming model in cloud environment for parallel processing large-scale data sets. The combination of the high-level language…”
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Relation-oriented few-shot knowledge graph prototype networks by Xue, Yingying, Song, Aibo, Jin, Jiahui, Peng, Hui, Qiu, Jingyi, Fang, Xiaolin, Zhai, Xiaorui

“…Knowledge graph (KG) embedding has been widely researched, but it suffers from some problems in the few-shot scenarios. The topological and semantic connection…”
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TEA-RFFI: Temperature adjusted radio frequency fingerprint-based smartphone identification by Gu, Xiaolin, Wu, Wenjia, Zhou, Yusen, Song, Aibo, Yang, Ming, Ling, Zhen, Luo, Junzhou

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BAR: An Efficient Data Locality Driven Task Scheduling Algorithm for Cloud Computing by Jiahui Jin, Junzhou Luo, Aibo Song, Fang Dong, Runqun Xiong

“…Large scale data processing is increasingly common in cloud computing systems like MapReduce, Hadoop, and Dryad in recent years. In these systems, files are…”
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Relation-based multi-type aware knowledge graph embedding by Xue, Yingying, Jin, Jiahui, Song, Aibo, Zhang, Yingxue, Liu, Yangyang, Wang, Kaixuan

“…Knowledge graph (KG) embedding projects the graph into a low-dimensional space and preserves the graph information. An essential part of a KG is the ontology,…”
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Efficient Data and Task Co-Scheduling for Scientific Workflow in Geo-Distributed Datacenters by Jian Chen, Jinghui Zhang, Aibo Song

“…Scientific workflow usually needs to be performed in multiple collaborative datacenters for the requirement of accessing community-wide resources. However, the…”
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Intra- and inter-semantic with multi-scale evolving patterns for dynamic graph learning by Xue, Yingying, Song, Aibo, Fang, Xiaolin, Jin, Jiahui, Sun, Xiangguo, Zhang, Yingxue

“…Dynamics and heterogeneity are two principal challenges in recent graph learning research and are promising to solve many real-world applications better…”
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Intelligent online catastrophe assessment and preventive control via a stacked denoising autoencoder by Liu, Yangyang, Zhai, Mingyu, Jin, Jiahui, Song, Aibo, Lin, Jikeng, Wu, Zhiang, Zhao, Yixin

“…In all areas of engineering, catastrophe assessment is an essential prerequisite for remedial action schemes. Modelers constantly push for more accurate…”
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Graph partition–based data and task co‐scheduling of scientific workflow in geo‐distributed datacenters by Zhang, Jinghui, Chen, Jian, Zhan, Jun, Jin, Jiahui, Song, Aibo

“…Summary Most large‐scale scientific workflows take place in multiple collaborative datacenters for access to community‐wide resources, while adhering to each…”
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Semantic access control in grid computing by Wang Xiaopeng, Luo Junzhou, Song Aibo, Ma Teng

“…Grid computing provides a computational infrastructure supporting flexible, secure, coordinated resource sharing among dynamic collections of individuals,…”
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FedAda: Fast-convergent adaptive federated learning in heterogeneous mobile edge computing environment by Zhang, Jinghui, Cheng, Xinyu, Wang, Cheng, Wang, Yuchen, Shi, Zhan, Jin, Jiahui, Song, Aibo, Zhao, Wei, Wen, Liangsheng, Zhang, Tingting

“…With rapid advancement of Internet of Things (IoT) and social networking applications generating large amounts of data at or close to the network edge, Mobile…”
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