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  • Open Access

    ARTICLE

    Binary Oriented Feature Selection for Valid Product Derivation in Software Product Line

    Muhammad Fezan Afzal1, Imran Khan1, Javed Rashid1,2,3, Mubbashar Saddique4,*, Heba G. Mohamed5

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3653-3670, 2023, DOI:10.32604/cmc.2023.041627

    Abstract Software Product Line (SPL) is a group of software-intensive systems that share common and variable resources for developing a particular system. The feature model is a tree-type structure used to manage SPL’s common and variable features with their different relations and problem of Crosstree Constraints (CTC). CTC problems exist in groups of common and variable features among the sub-tree of feature models more diverse in Internet of Things (IoT) devices because different Internet devices and protocols are communicated. Therefore, managing the CTC problem to achieve valid product configuration in IoT-based SPL is more complex, time-consuming, and hard. However, the CTC… More >

  • Open Access

    ARTICLE

    Research on Multi-Blockchain Electronic Archives Sharing Model

    Fang Yu1, Wenbin Bi2, Ning Cao3,*, Jun Luo4, Diantang An5, Liqiang Ding4, Russell Higgs6

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3921-3931, 2023, DOI:10.32604/cmc.2023.028330

    Abstract The purpose of introducing blockchain into electronic archives sharing and utilization is to break the information barrier between electronic archives sharing departments by relying on technologies such as smart contract and asymmetric encryption. Aiming at the problem of dynamic permission management in common access control methods, a new access control method based on smart contract under blockchain is proposed, which improves the intelligence level under blockchain technology. Firstly, the Internet attribute access control model based on smart contract is established. For the dynamic access of heterogeneous devices, the management contract, permission judgment contract and access control contract are designed; Secondly,… More >

  • Open Access

    ARTICLE

    A Secure Device Management Scheme with Audio-Based Location Distinction in IoT

    Haifeng Lin1,2, Xiangfeng Liu2, Chen Chen2, Zhibo Liu2, Dexin Zhao3, Yiwen Zhang4, Weizhuang Li4, Mingsheng Cao5,6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 939-956, 2024, DOI:10.32604/cmes.2023.028656

    Abstract Identifying a device and detecting a change in its position is critical for secure devices management in the Internet of Things (IoT). In this paper, a device management system is proposed to track the devices by using audio-based location distinction techniques. In the proposed scheme, traditional cryptographic techniques, such as symmetric encryption algorithm, RSA-based signcryption scheme, and audio-based secure transmission, are utilized to provide authentication, non-repudiation, and confidentiality in the information interaction of the management system. Moreover, an audio-based location distinction method is designed to detect the position change of the devices. Specifically, the audio frequency response (AFR) of several… More >

  • Open Access

    ARTICLE

    SCADA Data-Based Support Vector Machine for False Alarm Identification for Wind Turbine Management

    Ana María Peco Chacón, Isaac Segovia Ramírez, Fausto Pedro García Márquez*

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2595-2608, 2023, DOI:10.32604/iasc.2023.037277

    Abstract Maintenance operations have a critical influence on power generation by wind turbines (WT). Advanced algorithms must analyze large volume of data from condition monitoring systems (CMS) to determine the actual working conditions and avoid false alarms. This paper proposes different support vector machine (SVM) algorithms for the prediction and detection of false alarms. K-Fold cross-validation (CV) is applied to evaluate the classification reliability of these algorithms. Supervisory Control and Data Acquisition (SCADA) data from an operating WT are applied to test the proposed approach. The results from the quadratic SVM showed an accuracy rate of 98.6%. Misclassifications from the confusion… More >

  • Open Access

    ARTICLE

    An Overview of Seismic Risk Management for Italian Architectural Heritage

    Lucio Nobile*

    Structural Durability & Health Monitoring, Vol.17, No.5, pp. 353-368, 2023, DOI:10.32604/sdhm.2023.028247

    Abstract The frequent occurrence of seismic events in Italy poses a strategic problem that involves either the culture of preservation of historical heritage or the civil protection action aimed to reduce the risk to people and goods (buildings, bridges, dams, slopes, etc.). Most of the Italian architectural heritage is vulnerable to earthquakes, identifying the vulnerability as the inherent predisposition of the masonry building to suffer damage and collapse during an earthquake. In fact, the structural concept prevailing in these ancient masonry buildings is aimed at ensuring prevalent resistance to vertical gravity loads. Rarely do these ancient masonry structures offer relevant resistance… More >

  • Open Access

    ARTICLE

    Explainable Artificial Intelligence-Based Model Drift Detection Applicable to Unsupervised Environments

    Yongsoo Lee, Yeeun Lee, Eungyu Lee, Taejin Lee*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1701-1719, 2023, DOI:10.32604/cmc.2023.040235

    Abstract Cybersecurity increasingly relies on machine learning (ML) models to respond to and detect attacks. However, the rapidly changing data environment makes model life-cycle management after deployment essential. Real-time detection of drift signals from various threats is fundamental for effectively managing deployed models. However, detecting drift in unsupervised environments can be challenging. This study introduces a novel approach leveraging Shapley additive explanations (SHAP), a widely recognized explainability technique in ML, to address drift detection in unsupervised settings. The proposed method incorporates a range of plots and statistical techniques to enhance drift detection reliability and introduces a drift suspicion metric that considers… More >

  • Open Access

    ARTICLE

    Task Offloading and Resource Allocation in IoT Based Mobile Edge Computing Using Deep Learning

    Ilyоs Abdullaev1, Natalia Prodanova2, K. Aruna Bhaskar3, E. Laxmi Lydia4, Seifedine Kadry5,6,7, Jungeun Kim8,*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1463-1477, 2023, DOI:10.32604/cmc.2023.038417

    Abstract Recently, computation offloading has become an effective method for overcoming the constraint of a mobile device (MD) using computation-intensive mobile and offloading delay-sensitive application tasks to the remote cloud-based data center. Smart city benefitted from offloading to edge point. Consider a mobile edge computing (MEC) network in multiple regions. They comprise N MDs and many access points, in which every MD has M independent real-time tasks. This study designs a new Task Offloading and Resource Allocation in IoT-based MEC using Deep Learning with Seagull Optimization (TORA-DLSGO) algorithm. The proposed TORA-DLSGO technique addresses the resource management issue in the MEC server,… More >

  • Open Access

    ARTICLE

    Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm

    Ali S. Alghamdi1, Mohana Alanazi2, Abdulaziz Alanazi3, Yazeed Qasaymeh1,*, Muhammad Zubair1,4, Ahmed Bilal Awan5, M. G. B. Ashiq6

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2163-2192, 2023, DOI:10.32604/cmes.2023.029453

    Abstract To maximize energy profit with the participation of electricity, natural gas, and district heating networks in the day-ahead market, stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources, has been carried out. This has been done using a new meta-heuristic algorithm, improved artificial rabbits optimization (IARO). In this study, the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method (TPEM). The IARO algorithm is applied to calculate the best capacity of hub energy equipment, such as solar and wind renewable energy sources, combined heat and power (CHP) systems, steam… More >

  • Open Access

    ARTICLE

    Real Time Vehicle Status Monitoring under Moving Conditions Using a Low Power IoT System

    M. Vlachos1,*, R. Lopardo2, A. Amditis1

    Journal on Internet of Things, Vol.4, No.4, pp. 235-261, 2022, DOI:10.32604/jiot.2022.040820

    Abstract In the era of the Internet of Things (IoT), the ever-increasing number of devices connected to the IoT networks also increases the energy consumption on the edge. This is prohibitive since the devices living on the edge are generally resource constrained devices in terms of energy consumption and computational power. Thus, trying to tackle this issue, in this paper, a fully automated end-to-end IoT system for real time monitoring of the status of a moving vehicle is proposed. The IoT system consists mainly of three components: (1) the ultra-low power consumption Wireless Sensor Node (WSN), (2) the IoT gateway and… More >

  • Open Access

    ARTICLE

    The Management of Mental Health, and Service Networks in Italy

    Silvia Carbone*

    International Journal of Mental Health Promotion, Vol.25, No.8, pp. 927-935, 2023, DOI:10.32604/ijmhp.2023.027784

    Abstract Madness has attracted and frightened for centuries, and talking about this means discussing how this diversity was built and managed in different social contexts and historical periods. Not all societies have had, and still have, the same relationship with madness. It is only with the affirmation of the Modern State, and of Capitalism, that the idea of “normality” indispensable to be able to conceive diversity as something dangerously distant and different from the norm takes over. In our post-modern society, people with mental illness in Italy can resort to specialists and social-health services. But the heterogeneous answers given after the… More > Graphic Abstract

    The Management of Mental Health, and Service Networks in Italy

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