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Efficient Algorithms for Maximizing Group Influence in Social Networks

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Tsinghua science and Technology 2022年第5期27卷 832-842页

作者： Peihuang Huang Longkun Guo Yuting Zhong college of mathematics and Data science Minjiang UniversityFuzhou 350108China College of Mathematics and Computer Science Fuzhou UniversityFuzhou 350116China

In social network applications,individual opinion is often influenced by groups,and most decisions usually reflect the majority’s opinions.This imposes the group influence maximization(GIM) problem that selects k initial nodes,where each node belongs to multiple groups for a given social network and each group has a weight,to maximize the weight of the eventually activated groups.The GIM problem is apparently NP-hard,given the NP-hardness of the influence maximization(IM) problem that does not consider groups.Focusing on activating groups rather than individuals,this paper proposes the complementary maximum coverage(CMC) algorithm,which greedily and iteratively removes the node with the approximate least group influence until at most k nodes remain.Although the evaluation of the current group influence against each node is only approximate,it nevertheless ensures the success of activating an approximate maximum number of groups.Moreover,we also propose the improved reverse influence sampling(IRIS) algorithm through fine-tuning of the renowned reverse influence sampling algorithm for GIM.Finally,we carry out experiments to evaluate CMC and IRIS,demonstrating that they both outperform the baseline algorithms respective of their average number of activated groups under the independent cascade(IC)model.

关键词： complementary maximum coverage(CMC) improved reverse influence sampling(IRIS) group influence maximization(GIM) independent cascade(IC)model

Timely Data Delivery for Energy-Harvesting IoT Devices

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Chinese Journal of Electronics 2022年第2期31卷 322-336页

作者： LU Wenwei GONG Siliang ZHU Yihua School of computer science and Technology Zhejiang University of Technology College of Mathematics and Computer Science Zhejiang A&F University

The devices in the Internet of things(Io T) gain capability of sustainable operation when they harvest energy from ambient sources. Fluctuation in the harvested energy may cause the energy-harvesting IoT devices to suffer from frequent energy shortage, which may bring in intolerable packet delay or packet discarding. It is important to design a low-delay packet delivery scheme that adapts to variation in the harvested energy.In this paper, we present the timely data delivery(TDD)scheme for the IoT devices. Using Markov chain, we develop a probability model for the TDD scheme, which leads to the expected number of packets delivered in an operation cycle, the expected numbers of packets waiting in the data buffer in an operation cycle and an energy-harvesting cycle, and the expected packet delay. Additionally, we formulate the optimization problem that minimizes the packet delay in the TDD scheme, and the solution to the optimization problem yields the optimal parameters for the IoT devices to determine when to harvest energy and when to deliver data under the TDD scheme.The simulation results show that the proposed TDD scheme outperforms the existing schemes in terms of packet delay.

关键词： Internet of things Energy harvesting Data delivery Energy management IEEE 802.15.4 standard

The Novel Instance Segmentation Method Based on Multi-Level Features and Joint Attention

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Chinese Journal of Electronics 2023年第5期32卷 1160-1168页

作者： XU Bowen LU Yinan WU Tieru GUO Xiaoxin college of computer science and Technology Jilin University college of mathematics Jilin University

Instance segmentation is an important task in computer vision. In order to enhance the multilevel features expression ability of the segmentation networks, a novel module is proposed in this paper. Firstly,we design a weighted bi-directional feature fusion way by computing the weight distribution function of bi-directional feature pyramid network. Secondly, we propose a joint attention mechanism to effectively filter different levels of feature information by adopting serial and parallel ways to combine the channel attention and spatial attention modules. At the same time, the module uses dynamic convolution to stabilize the calculation speed while improve the 6.7% mean average precision of segmentation.The experiments on the COCO dataset demonstrate that the module can effectively improve the performance of the existing instance segmentation networks.

关键词： Instance segmentation Feature fusion Attention mechanism Dynamic convolution Deep neural network

ChatGPT is a Remarkable Tool—For Experts

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Data Intelligence 2024年第1期6卷 240-296页

作者： Amos Azaria Rina Azoulay Shulamit Reches School of computer science Ariel UniversityIsrael Department of computer science Jerusalem College of TechnologyIsrael Department of mathematics Jerusalem College of TechnologyIsrael

This paper investigates the capabilities of ChatGPT as an automated assistant in diverse domains,including scientific writing,mathematics,education,programming,and healthcare.We explore the potential of ChatGPT to enhance productivity,streamline problem-solving processes,and improve writing style.Furthermore,we highlight the potential risks associated with excessive reliance on ChatGPT in these fields.These limitations encompass factors like incorrect and fictitious responses,inaccuracies in code,limited logical reasoning abilities,overconfidence,and critical ethical concerns of copyright and privacy violation.We outline areas and objectives where ChatGPT proves beneficial,applications where it should be used judiciously,and scenarios where its reliability may be limited.In light of observed limitations,and given that the tool's fundamental errors may pose a special challenge for non-experts,ChatGPT should be used with a strategic methodology.By drawing from comprehensive experimental studies,we offer methods and flowcharts for effectively using ChatGPT.Our recommendations emphasize iterative interaction with ChatGPT and independent verification of its outputs.Considering the importance of utilizing ChatGPT judiciously and with expertise,we recommend its usage for experts who are well-versed in the respective domains.

关键词： limitations utilizing Tool

Cooperative output regulation for linear uncertain MIMO multi-agent systems by output feedback

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science China(Information sciences) 2018年第9期61卷 218-231页

作者： Ying ZHANG Youfeng SU College of Mathematics and Computer Science Fuzhou University

In this paper, we study the cooperative output regulation problem for a class of general linear uncertain multi-input multi-output(MIMO) multi-agent systems subject to a well-defined vector relative degree. By proposing some suitable internal model, the problem is first converted into the auxiliary cooperative stabilization problem of the augmented system in the so-called strict feedback normal form. This auxiliary problem is then solved by some developed robust control techniques, such as multiple high-gain feedback and mixed distributed observer, leading to an effective distributed output feedback regulator synthesis for the original cooperative output regulation problem.

关键词： cooperative control output regulation MIMO output feedback vector relative degrees

CLASSIFICATIONS OF DUPIN HYPERSURFACES IN LIE SPHERE GEOMETRY

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Acta Mathematica Scientia 2024年第1期44卷 1-36页

作者： Thomas E.CECIL Department of mathematics and computer science College of the Holy CrossWorcesterMA01610USA

This is a survey of local and global classification results concerning Dupin hypersurfaces in S^(n)(or R^(n))that have been obtained in the context of Lie sphere geometry.The emphasis is on results that relate Dupin hypersurfaces to isoparametric hypersurfaces in spheres.Along with these classification results,many important concepts from Lie sphere geometry,such as curvature spheres,Lie curvatures,and Legendre lifts of submanifolds of S^(n)(or R^(n)),are described in detail.The paper also contains several important constructions of Dupin hypersurfaces with certain special properties.

关键词： Dupin hypersurfaces isoparametric hypersurfaces Lie sphere geometry Lie sphere transformations Lie curvatures

Upper bound of Kahler angles on the β-symplectic critical surfaces

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Frontiers of mathematics in China 2022年第4期17卷 511-519页

作者： Yuxia ZHANG Xiangrong ZHU College of Mathematics and Computer Science Zhejiang Normal UniversityJinhua321004China

Let(M,g)be a Kähler surface andΣbe aβ-symplectic critical surface in M.If L_(q)(Σ)is bounded for some q>3,then we give a uniform upper bound for the Kähler angle onΣ.This bound only depends on M,q,βand the Lq fun... 详细信息

关键词： Kähler surface β-symplectic critical surfaces Kähler angle L_(β)functional

Static tainting extraction approach based on information flow graph for personally identifiable information

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science China(Information sciences) 2020年第3期63卷 156-172页

作者： Yi LIU Lejian LIAO Tian SONG School of computer science and Technology Beijing Institute of Technology College of Mathematics and Computer Science Yan'an University

Personally identifiable information(PII) is widely used for many aspects such as network privacy leak detection, network forensics, and user portraits. Internet service providers(ISPs) and administrators are usually concerned with whether PII has been extracted during the network transmission process. However,most studies have focused on the extractions occurring on the client side and server side. This study proposes a static tainting extraction approach that automatically extracts PII from large-scale network traffic without requiring any manual work and feedback on the ISP-level network traffic. The proposed approach does not deploy any additional applications on the client side. The information flow graph is drawn via a tainting process that involves two steps: inter-domain routing and intra-domain infection that contains a constraint function(CF) to limit the "over-tainting". Compared with the existing semantic-based approach that uses network traffic from the ISP, the proposed approach performs better, with 92.37% precision and 94.04%recall. Furthermore, three methods that reduce the computing time and the memory overhead are presented herein. The number of rounds is reduced to 0.0883%, and the execution time overhead is reduced to 0.0153%of the original approach.

关键词： personally identifiable information network privacy leak detection static tainting network traffic analysis information flow graph inter-domain routing intra-domain infection constraint function

Entity Burst Discriminative Model for Cumulative Citation Recommendation

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Journal of Beijing Institute of Technology 2019年第2期28卷 356-364页

作者： Lerong Ma College of Mathematics and Computer Science Yan’an University

Knowledge base acceleration-cumulative citation recommendation(KBA-CCR)aims to detect citation-worthiness documents from a chronological stream corpus for a set of target entities in a knowledge base.Most previous works only consider a number of semantic features between documents and target entities in the knowledge base,and then use powerful machine learning approaches such as logistic regression to classify relevant documents and non-relevant documents.However,the burst activities of an entity have been proved to be a significant signal to predict potential citations.In this paper,an entity burst discriminative model(EBDM)is presented to substantially exploit such burst features.The EBDM presents a new temporal representation based on the burst features,which can capture both temporal and semantic correlations between entities and documents.Meanwhile,in contrast to the bag-of-words model,the EBDM can significantly decrease the number of non-zero entries of feature vectors.An extensive set of experiments were conducted on the TREC-KBA-2012 dataset.The results show that the EBDM outperforms the performance of the state-of-the-art models.

关键词： knowledge base burst features cumulative citation recommendation discriminative model