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Search Results (26)
  • Open Access

    ARTICLE

    Robust and Discriminative Feature Learning via Mutual Information Maximization for Object Detection in Aerial Images

    Xu Sun, Yinhui Yu*, Qing Cheng

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4149-4171, 2024, DOI:10.32604/cmc.2024.052725 - 12 September 2024

    Abstract Object detection in unmanned aerial vehicle (UAV) aerial images has become increasingly important in military and civil applications. General object detection models are not robust enough against interclass similarity and intraclass variability of small objects, and UAV-specific nuisances such as uncontrolled weather conditions. Unlike previous approaches focusing on high-level semantic information, we report the importance of underlying features to improve detection accuracy and robustness from the information-theoretic perspective. Specifically, we propose a robust and discriminative feature learning approach through mutual information maximization (RD-MIM), which can be integrated into numerous object detection methods for aerial images.… More >

  • Open Access

    ARTICLE

    A Bitcoin Address Multi-Classification Mechanism Based on Bipartite Graph-Based Maximization Consensus

    Lejun Zhang1,2,3,*, Junjie Zhang1, Kentaroh Toyoda4, Yuan Liu2, Jing Qiu2, Zhihong Tian2, Ran Guo5

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 783-800, 2024, DOI:10.32604/cmes.2023.043469 - 30 December 2023

    Abstract Bitcoin is widely used as the most classic electronic currency for various electronic services such as exchanges, gambling, marketplaces, and also scams such as high-yield investment projects. Identifying the services operated by a Bitcoin address can help determine the risk level of that address and build an alert model accordingly. Feature engineering can also be used to flesh out labeled addresses and to analyze the current state of Bitcoin in a small way. In this paper, we address the problem of identifying multiple classes of Bitcoin services, and for the poor classification of individual addresses… More >

  • Open Access

    ARTICLE

    Energy Efficiency Maximization in Mobile Edge Computing Networks via IRS assisted UAV Communications

    Ying Zhang1, Weiming Niu2, Supu Xiu1,3, Guangchen Mu3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1865-1884, 2024, DOI:10.32604/cmes.2023.030114 - 17 November 2023

    Abstract In this paper, we investigate the energy efficiency maximization for mobile edge computing (MEC) in intelligent reflecting surface (IRS) assisted unmanned aerial vehicle (UAV) communications. In particular, UAV can collect the computing tasks of the terrestrial users and transmit the results back to them after computing. We jointly optimize the users’ transmitted beamforming and uploading ratios, the phase shift matrix of IRS, and the UAV trajectory to improve the energy efficiency. The formulated optimization problem is highly non-convex and difficult to be solved directly. Therefore, we decompose the original problem into three sub-problems. We first More >

  • Open Access

    ARTICLE

    Maximizing Influence in Temporal Social Networks: A Node Feature-Aware Voting Algorithm

    Wenlong Zhu1,2,*, Yu Miao1, Shuangshuang Yang3, Zuozheng Lian1,2, Lianhe Cui1

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3095-3117, 2023, DOI:10.32604/cmc.2023.045646 - 26 December 2023

    Abstract Influence Maximization (IM) aims to select a seed set of size k in a social network so that information can be spread most widely under a specific information propagation model through this set of nodes. However, most existing studies on the IM problem focus on static social network features, while neglecting the features of temporal social networks. To bridge this gap, we focus on node features reflected by their historical interaction behavior in temporal social networks, i.e., interaction attributes and self-similarity, and incorporate them into the influence maximization algorithm and information propagation model. Firstly, we propose… More >

  • Open Access

    ARTICLE

    A Positive Influence Maximization Algorithm in Signed Social Networks

    Wenlong Zhu1,2,*, Yang Huang1, Shuangshuang Yang3, Yu Miao1, Chongyuan Peng1

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1977-1994, 2023, DOI:10.32604/cmc.2023.040998 - 30 August 2023

    Abstract The influence maximization (IM) problem aims to find a set of seed nodes that maximizes the spread of their influence in a social network. The positive influence maximization (PIM) problem is an extension of the IM problem, which consider the polar relation of nodes in signed social networks so that the positive influence of seeds can be the most widely spread. To solve the PIM problem, this paper proposes the polar and decay related independent cascade (IC-PD) model to simulate the influence propagation of nodes and the decay of information during the influence propagation in… More >

  • Open Access

    ARTICLE

    Secrecy Efficiency Maximization in Intelligent Reflective Surfaces Assisted UAV Communications

    Hui Wei, Leibing Yan*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1805-1824, 2023, DOI:10.32604/cmes.2023.028072 - 26 June 2023

    Abstract This paper focuses on the secrecy efficiency maximization in intelligent reflecting surface (IRS) assisted unmanned aerial vehicle (UAV) communication. With the popularization of UAV technology, more and more communication scenarios need UAV support. We consider using IRS to improve the secrecy efficiency. Specifically, IRS and UAV trajectories work together to counter potential eavesdroppers, while balancing the secrecy rate and energy consumption. The original problem is difficult to solve due to the coupling of optimization variables. We first introduce secrecy efficiency as an auxiliary variable and propose relaxation optimization problem, and then prove the equivalence between More >

  • Open Access

    ARTICLE

    An Influence Maximization Algorithm Based on Improved K-Shell in Temporal Social Networks

    Wenlong Zhu1,*, Yu Miao1, Shuangshuang Yang2, Zuozheng Lian1, Lianhe Cui1

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3111-3131, 2023, DOI:10.32604/cmc.2023.036159 - 31 March 2023

    Abstract Influence maximization of temporal social networks (IMT) is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread. To solve the IMT problem, we propose an influence maximization algorithm based on an improved K-shell method, namely improved K-shell in temporal social networks (KT). The algorithm takes into account the global and local structures of temporal social networks. First, to obtain the kernel value Ks of each node, in the global scope, it layers the network according to the temporal characteristic… More >

  • Open Access

    ARTICLE

    IC Pattern Based Power Factor Maximization Model for Improved Power Stabilization

    N. Hariharan1,*, Y. Sukhi2, N. Kalaiarasi1

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 401-414, 2023, DOI:10.32604/iasc.2023.030768 - 29 September 2022

    Abstract The voltage fluctuation in electric circuits has been identified as key issue in different electric systems. As the usage of electricity growing in rapid way, there exist higher fluctuations in power flow. To maintain the flow or stability of power in any electric circuit, there are many circuit models are discussed in literature. However, they suffer to maintain the output voltage and not capable of maintaining power stability. To improve the performance in power stabilization, an efficient IC pattern based power factor maximization model (ICPFMM) in this article. The model is focused on improving the… More >

  • Open Access

    ARTICLE

    Metaheuristics-based Clustering with Routing Technique for Lifetime Maximization in Vehicular Networks

    P. Muthukrishnan*, P. Muthu Kannan

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1107-1122, 2023, DOI:10.32604/cmc.2023.031962 - 22 September 2022

    Abstract Recently, vehicular ad hoc networks (VANETs) finds applicability in different domains such as security, rescue operations, intelligent transportation systems (ITS), etc. VANET has unique features like high mobility, limited mobility patterns, adequate topology modifications, and wireless communication. Despite the benefits of VANET, scalability is a challenging issue which could be addressed by the use of cluster-based routing techniques. It enables the vehicles to perform intercluster communication via chosen CHs and optimal routes. The main drawback of VANET network is the network unsteadiness that results in minimum lifetime. In order to avoid reduced network lifetime in… More >

  • Open Access

    ARTICLE

    Topology Driven Cooperative Self Scheduling for Improved Lifetime Maximization in WSN

    G. Brindha1,*, P. Ezhilarasi2

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 445-458, 2023, DOI:10.32604/csse.2023.027329 - 16 August 2022

    Abstract In Wireless Sensor Network (WSN), scheduling is one of the important issues that impacts the lifetime of entire WSN. Various scheduling schemes have been proposed earlier to increase the lifetime of the network. Still, the results from such methods are compromised in terms of achieving high lifetime. With this objective to increase the lifetime of network, an Efficient Topology driven Cooperative Self-Scheduling (TDCSS) model is recommended in this study. Instead of scheduling the network nodes in a centralized manner, a combined approach is proposed. Based on the situation, the proposed TDCSS approach performs scheduling in… More >

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