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On charactering of information propagation in online social networks

Journal of Networks 2013年第1期8卷 124-131页

作者： Han, Xiaoting Niu, Li School of Economics and Management Beihang University Beijing China Key Laboratory of Ministry of Education for Data Engineering and Knowledge Engineering Renmin University of China Beijing China School of Information Resource Management Renmin University of China Beijing China

Recent years have witnessed the explosive growth of online social networks (OSNs), which provide a perfect platform for observing the information propagation. Based on the theory of complex network analysis, considering each node in OSNs as an agent, an information propagation model called IP-OSN has been proposed in this paper, and numerical simulation experiments have been extensively conducted, which show the mechanism of information propagation in OSNs. It can be seen from the experimental results that along with the information spreading scope will be larger while time passing. Moreover, from the network structure perspective, some interesting findings are got. First, the number of initial known nodes has a certain impact on the information propagation speed;however it doesn't affect the number of final known and unknown nodes. Then, the number of neighbors has a great impact on the information propagation process and results. Finally, percentage of different user type is the decisive factor for information propagation either in final node number or propagation speed. This paper attempts to complement the theoretical framework of information propagation and complex networks, and thus to further promote the practice of information control in OSNs. © 2013 ACADEMY PUBLISHER.

关键词： Social networking (online)

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Combining Global and Sequential Patterns for Multivariate Time Series Forecasting

Combining Global and Sequential Patterns for Multivariate Ti...

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IEEE International Conference on Big data

作者： Zhaoxi Li Jun He Hongyan Liu Xiaoyong Du Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China Beijing China School of Economics and Management Tsinghua g University Beijing China

ISBN: (数字)9781728162515

ISBN: (纸本)9781728162522

Multivariate time series forecasting is very important for many applications. Many studies have been conducted for accurate and interpretable prediction methods. However, existing methods either cannot take both times series and covariates into consideration, lacking of interpretability, or ignore global trends across multivariate time series. In this paper, we aim to solve these issues. To this end, we propose a new model named TEDGE for accurate and interpretable time series prediction. In this model, we extract global trends hidden across multivariate times series to improve prediction accuracy. Meanwhile, we utilize a deep recurrent model with attention mechanism to find long-and short-term sequential patterns hidden in individual time series with interpretability. We conduct experiments on several datasets to evaluate the proposed models performance. Results demonstrate the superior performance of our proposed model.

关键词： Conferences Time series analysis Predictive models Big data Market research data models Forecasting

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PromptGCN: Bridging Subgraph Gaps in Lightweight GCNs

arXiv

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arXiv 2024年

作者： Ji, Shengwei Tian, Yujie Liu, Fei Li, Xinlu Wu, Le The School of Artificial Intelligence and Big Data Hefei University Hefei China The School of Computer Science and Information Engineering Hefei University of Technology Hefei China The Key Laboratory of Knowledge Engineering with Big Data Ministry of Education China

Graph Convolutional Networks (GCNs) are widely used in graph-based applications, such as social networks and recommendation systems. Nevertheless, large-scale graphs or deep aggregation layers in full-batch GCNs consume significant GPU memory, causing out of memory (OOM) errors on mainstream GPUs (e.g., 29GB memory consumption on the Ogbn-products graph with 5 layers). The subgraph sampling methods reduce memory consumption to achieve lightweight GCNs by partitioning the graph into multiple subgraphs and sequentially training GCNs on each subgraph. However, these methods yield gaps among subgraphs, i.e., GCNs can only be trained based on subgraphs instead of global graph information, which reduces the accuracy of GCNs. In this paper, we propose PromptGCN, a novel prompt-based lightweight GCN model to bridge the gaps among subgraphs. First, the learnable prompt embeddings are designed to obtain global information. Then, the prompts are attached into each subgraph to transfer the global information among subgraphs. Extensive experimental results on seven large-scale graphs demonstrate that PromptGCN exhibits superior performance compared to baselines. Notably, PromptGCN improves the accuracy of subgraph sampling methods by up to 5.48% on the Flickr dataset. Overall, PromptGCN can be easily combined with any subgraph sampling method to obtain a lightweight GCN model with higher accuracy. Copyright © 2024, The Authors. All rights reserved.

关键词： Graphics processing unit

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Formal Analysis of Trusted Computing: One Case Study

Formal Analysis of Trusted Computing: One Case Study

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WRI International Conference on Communications and Mobile Computing, CMC

作者： HongWei Zhou JinHui Yuan Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Beijing China School of Information Renmin University of China Beijing China Institute of Electronic Technology Zhengzhou Information Engineering University of China Zhengzhou China

LS 2 is the logic to reason about the property of trusted computing. However, it lacks the capability of modeling the isolation provided by virtualization which is often involved in previous trusted computing system. With the support of changed LS 2 , we model three types of isolation. Moreover, we formally analyze the integrity measurement property of TrustVisor proposed recently which provides the isolated execution environment for security-sensitive code.

关键词： TV Computational modeling Analytical models Virtual machining Time measurement Access control

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B-IRP: An Improving Integrity Report Protocol for Remote Attestation

B-IRP: An Improving Integrity Report Protocol for Remote Att...

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WRI International Conference on Communications and Mobile Computing, CMC

Trusted platform module (TPM) has little computation capability, and it is the performance bottleneck of remote attestation. In the scenario where the server is the attestation-busy entity which answers attestation requirement frequently, the massive delay is inevitable. Without the modification to TPM, we propose Batch Integrity Report Protocol (BIRP) to overcome the performance bottleneck. B-IRP bundles these requirements in interval as a batch requirement, and creates the response messages for these requirements with one expensive TPM operation. Discussion shows that B-IRP has improved the performance without loss of security.

关键词： Protocols Servers Security Software Software measurement Computer architecture Delay

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3D printed optical fibre preforms from silica contained resin 6

3D printed optical fibre preforms from silica contained resi...

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6th International Workshop on Specialty Optical Fibers and Their Applications, WSOF 2019

作者： Chu, Yushi Canning, John Fu, Xinghu Luo, Yanhua Cook, Kevin Zhang, Jianzhong Peng, Gang-Ding Tech Lab School of Electrical and Data Engineering University of Technology Sydney SydneyNSW2007 & 2019 Australia Photonics and Optical Communications School of Electrical Engineering and Telecommunications University of New South Wales SydneyNSW2052 Australia The Key Laboratory for Special Fiber and Fiber Sensor of Hebei Province School of Information Science and Engineering Yanshan University Qinhuangdao066004 China Key Lab of In-Fiber Integrated Optics of Ministry of Education School of Science Harbin Engineering University Harbin150001 China

3D printed glass optical fiber preforms have been fabricated from silica containing resin. The fabrication process includes resin preparation, preform printing, debinding and sintering. Results demonstrate the silica ... 详细信息

ISBN: (纸本)9781510631618

关键词： Sintering

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Facile synthesis of zinc-based organic framework for aqueous Hg (Ⅱ) removal: Adsorption performance and mechanism

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Nano Materials Science 2021年第4期3卷 429-439页

作者： Biao Zeng Wei Wang Sijin He Guo Lin Wenjia Du Jun Chang Zhao Ding The State Key Laboratory of Refractories and Metallurgy Wuhan University of Science and TechnologyWuhan430081PR China Key Laboratory for Ferrous Mtallurgy and Resources Utilization of Ministry of Education Wuhan University of Science and TechnologyWuhan430081PR China China E-port Data Center Division of Chengdu Chengdu610041PR China Electrochemical Innovation Lab Department of Chemical EngineeringUniversity College London(UCL)LondonWC1E 68TUK College of Material and Chemical Engineering Tongren University Tongren554300GuizhouPR China Department of Mechanical Materials and Aerospace Engineering Illinois Institute of TechnologyChicagoIL60616 USA

Mercury(Hg)ions can lead to a serious impact on the environment;therefore,it was necessary to find an effective method for absorbing these toxic Hg ***,the adsorbent(Zn-AHMT)was synthesized from zinc nitrate and 4-amino 3-hydrazine-5 mercapto-1,2,4-triazole(AHMT)by one-step method and,characterized the microstruc-ture and absorption performance by fourier transform infrared spectroscopy(FTIR),field emission scanning electron microscopy(FESEM),X-ray diffraction(XRD),Brunauer-Emmett Teller(BET),Thermal Gravimetric Analyzer(TGA)and X-ray photoelectron spectroscopy(XPS).Through a plethora of measurements,we found that the maximum adsorption capacity was 802.8 mg/g when the optimal pH of Zn-AHMT was *** isothermal and kinetic experiments confirm that the reaction process of Zn-AHMT was chemisorption,while the adsorption process conforms to the Hill model and pseudo second order kinetic *** experiments showed that the adsorption process was spontaneous and *** experiments were performed in the simulated wastewater containing Mn,Mg,Cr,Al,Co,Ni,Hg *** results showed that the Zn-AHMT has a stronger affinity for Hg *** removal rate of Zn-AHMT remained above 98%,indicating that the Zn-AHMT had a good stability validated by three adsorption-desorption repeatable *** to the XPS results,the adsorption reaction of Zn-AHMT was mainly attributed to the chelation and ion *** was further explained by both density functional theory(DFT)calculation and frontier molecular orbital *** therefore propose the adsorption mechanism of *** adsorption reaction facilitates via the synergistic action of S and N ***,the bonding between the adsorbent and the N atom has been proved to be more *** study demonstrated that Zn-AHMT had a promising application prospect in mercury removal.

关键词： Metal-organic frameworks(MOFs) Hg(Ⅱ) Selectivity Adsorption mechanism

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Joint-Motion Mutual Learning for Pose Estimation in Video 24

Joint-Motion Mutual Learning for Pose Estimation in Video

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32nd ACM International Conference on Multimedia, MM 2024

作者： Wu, Sifan Chen, Haipeng Yin, Yifang Hu, Sihao Feng, Runyang Jiao, Yingying Yang, Ziqi Liu, Zhenguang College of Computer Science and Technology Jilin University Changchun China A STAR Singapore Singapore Georgia Institute of Technology AtlantaGA United States School of Artificial Intelligence Jilin University Changchun China The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Institute of Blockchain and Data Security Hangzhou China

ISBN: (纸本)9798400706868

Human pose estimation in videos has long been a compelling yet challenging task within the realm of computer vision. Nevertheless, this task remains difficult because of the complex video scenes, such as video defocus and self-occlusion. Recent methods strive to integrate multi-frame visual features generated by a backbone network for pose estimation. However, they often ignore the useful joint information encoded in the initial heatmap, which is a by-product of the backbone generation. Comparatively, methods that attempt to refine the initial heatmap fail to consider any spatio-temporal motion features. As a result, the performance of existing methods for pose estimation falls short due to the lack of ability to leverage both local joint (heatmap) information and global motion (feature) dynamics. To address this problem, we propose a novel joint-motion mutual learning framework for pose estimation, which effectively concentrates on both local joint dependency and global pixel-level motion dynamics. Specifically, we introduce a context-aware joint learner that adaptively leverages initial heatmaps and motion flow to retrieve robust local joint feature. Given that local joint feature and global motion flow are complementary, we further propose a progressive joint-motion mutual learning that synergistically exchanges information and interactively learns between joint feature and motion flow to improve the capability of the model. More importantly, to capture more diverse joint and motion cues, we theoretically analyze and propose an information orthogonality objective to avoid learning redundant information from multi-cues. Empirical experiments show our method outperforms prior arts on three challenging benchmarks. © 2024 ACM.

关键词： Motion estimation

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IKGN: Intention-aware knowledge Graph Network for POI Recommendation

IKGN: Intention-aware Knowledge Graph Network for POI Recomm...

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IEEE International Conference on data Mining (ICDM)

作者： Xiaoyu Zhu Chenyang Bu Bingbing Dong Shengwei Ji Yi He Xindong Wu Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China) Hefei University of Technology School of Computer Science and Information Engineering Hefei University of Technology China School of Artificial Intelligence and Big Data Hefei University China Department of Computer Science Old Dominion University USA Research Center for Knowledge Engineering Zhejiang Lab China

Point-of-Interest (POI) recommendation, pivotal for guiding users to their next interested locale, grapples with the persistent challenge of data sparsity. Whereas knowledge graphs (KGs) have emerged as a favored tool to mitigate the issue, existing KG-based methods tend to overlook two crucial elements: the intention steering users’ location choices and the high-order topological structure within the KG. In this paper, we craft an Intention-aware knowledge Graph (IKG) that harmonizes users’ visit histories, movement trajectories, and location categories to model user intentions. Building upon IKG, our novel Intention-aware knowledge Graph Network (IKGN) delves deeper into the POI recommendation by weighing and propagating node embeddings through an attention mechanism, capturing the unique locational intent of each user. A sequential model like GRU is then employed to ensure a comprehensive representation of users’ short- and long-term location preferences. An empirical study on two real-world datasets validates the effectiveness of our proposed IKGN, with it markedly outshining seven benchmark rival models in both Recall and NDCG metrics. The code of IKGN is available at https://***/Jungle123456/IKGN.

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Marginal Value-Based Edge Resource Pricing and Allocation for Deadline-Sensitive Tasks

Marginal Value-Based Edge Resource Pricing and Allocation fo...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Puwei Wang Zhouxing Sun Ying Zhan Haoran Li Xiaoyong Du School of Information Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Renmin University of China Beijing China Guizhou University of Finance and Economics Guiyang City China

In edge computing (EC), resource allocation is to allocate computing, storage and networking resources on the edge nodes (ENs) efficiently and reasonably to tasks generated by users. Due to the resource-limitation of ENs, the tasks often need to compete for the resources. Pricing mechanisms are widely used to deal with the resource allocation problem, and the valuations of tasks play a critical role in the price mechanisms. However, users naturally are not willing to expose the valuations of their tasks due to conflicts of interests. Current research works usually adopt truthful auctions to motivate the users to report honestly the valuations of their tasks. In this paper, we introduce the marginal value to estimate the valuations of tasks, and propose a marginal value-based pricing mechanism using the incentive theory, which motivates the tasks with higher marginal values to actively request more resources. The EC platform sets the resource prices using the price mechanism, and then the users determine their resource requests relying on the resource prices and the valuations of their tasks. After receiving the deadline-sensitive tasks from the users, the resource allocation can be modeled as a knapsack problem with the deadline constraints. Extensive experimental results demonstrate that our approach is computationally efficient and is promising in enhancing the utility of the EC platform and the tasks.

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