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  • Open Access

    ARTICLE

    Traffic Flow Prediction with Heterogenous Data Using a Hybrid CNN-LSTM Model

    Jing-Doo Wang1, Chayadi Oktomy Noto Susanto1,2,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3097-3112, 2023, DOI:10.32604/cmc.2023.040914 - 08 October 2023

    Abstract Predicting traffic flow is a crucial component of an intelligent transportation system. Precisely monitoring and predicting traffic flow remains a challenging endeavor. However, existing methods for predicting traffic flow do not incorporate various external factors or consider the spatiotemporal correlation between spatially adjacent nodes, resulting in the loss of essential information and lower forecast performance. On the other hand, the availability of spatiotemporal data is limited. This research offers alternative spatiotemporal data with three specific features as input, vehicle type (5 types), holidays (3 types), and weather (10 conditions). In this study, the proposed model… More >

  • Open Access

    ARTICLE

    Decentralized Heterogeneous Federal Distillation Learning Based on Blockchain

    Hong Zhu*, Lisha Gao, Yitian Sha, Nan Xiang, Yue Wu, Shuo Han

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3363-3377, 2023, DOI:10.32604/cmc.2023.040731 - 08 October 2023

    Abstract Load forecasting is a crucial aspect of intelligent Virtual Power Plant (VPP) management and a means of balancing the relationship between distributed power grids and traditional power grids. However, due to the continuous emergence of power consumption peaks, the power supply quality of the power grid cannot be guaranteed. Therefore, an intelligent calculation method is required to effectively predict the load, enabling better power grid dispatching and ensuring the stable operation of the power grid. This paper proposes a decentralized heterogeneous federated distillation learning algorithm (DHFDL) to promote trusted federated learning (FL) between different federates… More >

  • Open Access

    ARTICLE

    Topic-Aware Abstractive Summarization Based on Heterogeneous Graph Attention Networks for Chinese Complaint Reports

    Yan Li1, Xiaoguang Zhang1,*, Tianyu Gong1, Qi Dong1, Hailong Zhu1, Tianqiang Zhang1, Yanji Jiang2,3

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3691-3705, 2023, DOI:10.32604/cmc.2023.040492 - 08 October 2023

    Abstract Automatic text summarization (ATS) plays a significant role in Natural Language Processing (NLP). Abstractive summarization produces summaries by identifying and compressing the most important information in a document. However, there are only relatively several comprehensively evaluated abstractive summarization models that work well for specific types of reports due to their unstructured and oral language text characteristics. In particular, Chinese complaint reports, generated by urban complainers and collected by government employees, describe existing resident problems in daily life. Meanwhile, the reflected problems are required to respond speedily. Therefore, automatic summarization tasks for these reports have been More >

  • Open Access

    ARTICLE

    A Multilevel Hierarchical Parallel Algorithm for Large-Scale Finite Element Modal Analysis

    Gaoyuan Yu1, Yunfeng Lou2, Hang Dong3, Junjie Li1, Xianlong Jin1,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2795-2816, 2023, DOI:10.32604/cmc.2023.037375 - 08 October 2023

    Abstract The strict and high-standard requirements for the safety and stability of major engineering systems make it a tough challenge for large-scale finite element modal analysis. At the same time, realizing the systematic analysis of the entire large structure of these engineering systems is extremely meaningful in practice. This article proposes a multilevel hierarchical parallel algorithm for large-scale finite element modal analysis to reduce the parallel computational efficiency loss when using heterogeneous multicore distributed storage computers in solving large-scale finite element modal analysis. Based on two-level partitioning and four-transformation strategies, the proposed algorithm not only improves… More >

  • Open Access

    ARTICLE

    Heterogeneity beyond tumor heterogeneity—SULF2 involvement in Wnt/β-catenin signaling activation in a heterogeneous side population of liver cancer cells

    DONGYE YANG1,#,*, DONGDONG GUO2,3,#, YUNMEI PENG2, DONGMENG LIU1, YANQIU FU1, FEN SUN2, LISHI ZHOU1, JIAQI GUO1, LAIQING HUANG2,3,*

    BIOCELL, Vol.47, No.9, pp. 2037-2049, 2023, DOI:10.32604/biocell.2023.028863 - 28 September 2023

    Abstract Introduction: Sulfatase 2 (SULF2), an endogenous extracellular sulfatase, can remove 6-O-sulfate groups of glucosamine residues from heparan sulfate (HS) chains to modulate the Wnt/β-catenin signaling pathway, which plays an important role in both liver carcinogenesis and embryogenesis. Side population (SP) cells are widely identified as stem-like cancer cells and are closely related to carcinoma metastasis, recurrence, and poor patient prognosis. However, the roles of SULF2 in SP cells of hepatomas are unclear, and the underlying mechanism is undefined. Objectives: This study aimed to compare the heterogeneity between SP cells and non-side population (NSP) cells derived from… More > Graphic Abstract

    Heterogeneity beyond tumor heterogeneity—SULF2 involvement in Wnt/β-catenin signaling activation in a heterogeneous side population of liver cancer cells

  • Open Access

    ARTICLE

    An Efficient Heterogeneous Ring Signcryption Scheme for Wireless Body Area Networks

    Qingqing Ning, Chunhua Jin*, Zhiwei Chen, Yongliang Xu, Huaqi Lu

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2061-2078, 2023, DOI:10.32604/csse.2023.040483 - 28 July 2023

    Abstract Wireless body area networks (WBANs) are an emerging technology for the real-time monitoring of physiological signals. WBANs provide a mechanism for collecting, storing, and transmitting physiological data to healthcare providers. However, the open wireless channel and limited resources of sensors bring security challenges. To ensure physiological data security, this paper provides an efficient Certificateless Public Key Infrastructure Heterogeneous Ring Signcryption (CP-HRSC) scheme, in which sensors are in a certificateless cryptosystem (CLC) environment, and the server is in a public key infrastructure (PKI) environment. CLC could solve the limitations of key escrow in identity-based cryptography (IBC)… More >

  • Open Access

    ARTICLE

    Competitive and Cooperative-Based Strength Pareto Evolutionary Algorithm for Green Distributed Heterogeneous Flow Shop Scheduling

    Kuihua Huang1, Rui Li2, Wenyin Gong2,*, Weiwei Bian3, Rui Wang1

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2077-2101, 2023, DOI:10.32604/iasc.2023.040215 - 21 June 2023

    Abstract This work aims to resolve the distributed heterogeneous permutation flow shop scheduling problem (DHPFSP) with minimizing makespan and total energy consumption (TEC). To solve this NP-hard problem, this work proposed a competitive and cooperative-based strength Pareto evolutionary algorithm (CCSPEA) which contains the following features: 1) An initialization based on three heuristic rules is developed to generate a population with great diversity and convergence. 2) A comprehensive metric combining convergence and diversity metrics is used to better represent the heuristic information of a solution. 3) A competitive selection is designed which divides the population into a… More >

  • Open Access

    ARTICLE

    Heterogeneous Fault-Tolerant Aggregate Signcryption with Equality Test for Vehicular Sensor Networks

    Yang Zhao1, Jingmin An1, Hao Li1, Saru Kumari2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 555-575, 2023, DOI:10.32604/cmes.2023.026808 - 23 April 2023

    Abstract The vehicular sensor network (VSN) is an important part of intelligent transportation, which is used for real-time detection and operation control of vehicles and real-time transmission of data and information. In the environment of VSN, massive private data generated by vehicles are transmitted in open channels and used by other vehicle users, so it is crucial to maintain high transmission efficiency and high confidentiality of data. To deal with this problem, in this paper, we propose a heterogeneous fault-tolerant aggregate signcryption scheme with an equality test (HFTAS-ET). The scheme combines fault-tolerant and aggregate signcryption, which… More > Graphic Abstract

    Heterogeneous Fault-Tolerant Aggregate Signcryption with Equality Test for Vehicular Sensor Networks

  • Open Access

    REVIEW

    Heterogeneous Network Embedding: A Survey

    Sufen Zhao1,2, Rong Peng1,*, Po Hu2, Liansheng Tan2

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 83-130, 2023, DOI:10.32604/cmes.2023.024781 - 23 April 2023

    Abstract Real-world complex networks are inherently heterogeneous; they have different types of nodes, attributes, and relationships. In recent years, various methods have been proposed to automatically learn how to encode the structural and semantic information contained in heterogeneous information networks (HINs) into low-dimensional embeddings; this task is called heterogeneous network embedding (HNE). Efficient HNE techniques can benefit various HIN-based machine learning tasks such as node classification, recommender systems, and information retrieval. Here, we provide a comprehensive survey of key advancements in the area of HNE. First, we define an encoder-decoder-based HNE model taxonomy. Then, we systematically More > Graphic Abstract

    Heterogeneous Network Embedding: A Survey

  • Open Access

    ARTICLE

    Network Intrusion Detection in Internet of Blended Environment Using Ensemble of Heterogeneous Autoencoders (E-HAE)

    Lelisa Adeba Jilcha1, Deuk-Hun Kim2, Julian Jang-Jaccard3, Jin Kwak4,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3261-3284, 2023, DOI:10.32604/csse.2023.037615 - 03 April 2023

    Abstract Contemporary attackers, mainly motivated by financial gain, consistently devise sophisticated penetration techniques to access important information or data. The growing use of Internet of Things (IoT) technology in the contemporary convergence environment to connect to corporate networks and cloud-based applications only worsens this situation, as it facilitates multiple new attack vectors to emerge effortlessly. As such, existing intrusion detection systems suffer from performance degradation mainly because of insufficient considerations and poorly modeled detection systems. To address this problem, we designed a blended threat detection approach, considering the possible impact and dimensionality of new attack surfaces… More >

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