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  • Open Access

    ARTICLE

    Radio Labeling Associated with a Class of Commutative Rings Using Zero-Divisor Graph

    Azeem Haider1,*, Ali N.A. Koam1, Ali Ahmad2

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 787-794, 2021, DOI:10.32604/iasc.2021.019391 - 20 August 2021

    Abstract Graph labeling is useful in networks because each transmitter has a different transmission capacity to send or receive wired or wireless links. An interference of signals can occur when transmitters that are close together receive close frequencies. This problem has been modeled mathematically in the radio labeling problem on graphs, where vertices represent transmitters and edges indicate closeness of the transmitters. For this purpose, each vertex is labeled with a unique positive integer, and to minimize the interference, the difference between maximum and minimum used labels has to be minimized. A radio labeling for a… More >

  • Open Access

    ARTICLE

    Performance Comparison of PoseNet Models on an AIoT Edge Device

    Min-Jun Kim1, Seng-Phil Hong2, Mingoo Kang1, Jeongwook Seo1,*

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 743-753, 2021, DOI:10.32604/iasc.2021.019329 - 20 August 2021

    Abstract In this paper, we present an oneM2M-compliant system including an artificial intelligence of things (AIoT) edge device whose principal function is to estimate human poses by using two PoseNet models built on MobileNet v1 and ResNet-50 backbone architectures. Although MobileNet v1 is generally known to be much faster but less accurate than ResNet50, it is necessary to analyze the performances of whole PoseNet models carefully and select one of them suitable for the AIoT edge device. For this reason, we first investigate the computational complexity of the models about their neural network layers and parameters… More >

  • Open Access

    ARTICLE

    Energy-Efficiency Model for Residential Buildings Using Supervised Machine Learning Algorithm

    Muhammad Shoukat Aslam1, Taher M. Ghazal2,3, Areej Fatima4, Raed A. Said5, Sagheer Abbas1, Muhammad Adnan Khan6,7,*, Shahan Yamin Siddiqui1,8, Munir Ahmad1

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 881-888, 2021, DOI:10.32604/iasc.2021.017920 - 20 August 2021

    Abstract The real-time management and control of heating-system networks in residential buildings has tremendous energy-saving potential, and accurate load prediction is the basis for system monitoring. In this regard, selecting the appropriate input parameters is the key to accurate heating-load forecasting. In existing models for forecasting heating loads and selecting input parameters, with an increase in the length of the prediction cycle, the heating-load rate gradually decreases, and the influence of the outside temperature gradually increases. In view of different types of solutions for improving buildings’ energy efficiency, this study proposed a Energy-efficiency model for residential More >

  • Open Access

    ARTICLE

    A Resource-constrained Edge IoT Device Data-deduplication Method with Dynamic Asymmetric Maximum

    Ye Yang1, Xiaofang Li2, Dongjie Zhu3,*, Hao Hu3, Haiwen Du4, Yundong Sun4, Weiguo Tian3, Yansong Wang3, Ning Cao1, Gregory M.P. O’Hare5

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 481-494, 2021, DOI:10.32604/iasc.2021.019201 - 11 August 2021

    Abstract Smart vehicles use sophisticated sensors to capture real-time data. Due to the weak communication capabilities of wireless sensors, these data need to upload to the cloud for processing. Sensor clouds can resolve these drawbacks. However, there is a large amount of redundant data in the sensor cloud, occupying a large amount of storage space and network bandwidth. Deduplication can yield cost savings by storing one data copy. Chunking is essential because it can determine the performance of deduplication. Content-Defined Chunking (CDC) can effectively solve the problem of chunk boundaries shifted, but it occupies a lot More >

  • Open Access

    ARTICLE

    Security Empowered System-on-Chip Selection for Internet of Things

    Ramesh Krishnamoorthy*, Kalimuthu Krishnan

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 403-418, 2021, DOI:10.32604/iasc.2021.018560 - 11 August 2021

    Abstract Due to the rapid growth of embedded devices, the selection of System-on-Chip (SoC) has a stronger influence to enable hardware security in embedded system design. System-on-chip (SoC) devices consist of one or more CPUs through wide-ranging inbuilt peripherals for designing a system with less cost. The selection of SoC is more significant to determine the suitability for secured application development. The design space analysis of symmetric key approaches including rivest cipher (RC5), advanced encryption standard (AES), data encryption standard (DES), international data encryption algorithm (IDEA), elliptic curve cryptography (ECC), MX algorithm, and the secure hash… More >

  • Open Access

    ARTICLE

    Decision Making Algorithmic Approaches Based on Parameterization of Neutrosophic Set under Hypersoft Set Environment with Fuzzy, Intuitionistic Fuzzy and Neutrosophic Settings

    Atiqe Ur Rahman1,*, Muhammad Saeed1, Sultan S. Alodhaibi2, Hamiden Abd El-Wahed Khalifa3,4

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 743-777, 2021, DOI:10.32604/cmes.2021.016736 - 22 July 2021

    Abstract Hypersoft set is an extension of soft set as it further partitions each attribute into its corresponding attribute-valued set. This structure is more flexible and useful as it addresses the limitation of soft set for dealing with the scenarios having disjoint attribute-valued sets corresponding to distinct attributes. The main purpose of this study is to make the existing literature regarding neutrosophic parameterized soft set in line with the need of multi-attribute approximate function. Firstly, we conceptualize the neutrosophic parameterized hypersoft sets under the settings of fuzzy set, intuitionistic fuzzy set and neutrosophic set along with More >

  • Open Access

    REVIEW

    Multi-Disease Prediction Based on Deep Learning: A Survey

    Shuxuan Xie, Zengchen Yu, Zhihan Lv*

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 489-522, 2021, DOI:10.32604/cmes.2021.016728 - 22 July 2021

    Abstract In recent years, the development of artificial intelligence (AI) and the gradual beginning of AI’s research in the medical field have allowed people to see the excellent prospects of the integration of AI and healthcare. Among them, the hot deep learning field has shown greater potential in applications such as disease prediction and drug response prediction. From the initial logistic regression model to the machine learning model, and then to the deep learning model today, the accuracy of medical disease prediction has been continuously improved, and the performance in all aspects has also been significantly More >

  • Open Access

    ARTICLE

    A Lightweight Blockchain for IoT in Smart City (IoT-SmartChain)

    Zakariae Dlimi*, Abdellah Ezzati, Saïd Ben Alla

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2687-2703, 2021, DOI:10.32604/cmc.2021.018942 - 21 July 2021

    Abstract The smart city is a technological framework that connects the city’s different components to create new opportunities. This connection is possible with the help of the Internet of Things (IoT), which provides a digital personality to physical objects. Some studies have proposed integrating Blockchain technology with IoT in different use cases as access, orchestration, or replicated storage layer. The majority of connected objects’ capacity limitation makes the use of Blockchain inadequate due to its redundancy and its conventional processing-intensive consensus like PoW. This paper addresses these challenges by proposing a NOVEL model of a lightweight… More >

  • Open Access

    ARTICLE

    Intelligent Microservice Based on Blockchain for Healthcare Applications

    Faisal Jamil1, Faiza Qayyum1, Soha Alhelaly2, Farjeel Javed3, Ammar Muthanna4,5,*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2513-2530, 2021, DOI:10.32604/cmc.2021.018809 - 21 July 2021

    Abstract Nowadays, the blockchain, Internet of Things, and artificial intelligence technology revolutionize the traditional way of data mining with the enhanced data preprocessing, and analytics approaches, including improved service platforms. Nevertheless, one of the main challenges is designing a combined approach that provides the analytics functionality for diverse data and sustains IoT applications with robust and modular blockchain-enabled services in a diverse environment. Improved data analytics model not only provides support insights in IoT data but also fosters process productivity. Designing a robust IoT-based secure analytic model is challenging for several purposes, such as data from… More >

  • Open Access

    ARTICLE

    A Lightweight Certificate-Based Aggregate Signature Scheme Providing Key Insulation

    Yong-Woon Hwang, Im-Yeong Lee*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1747-1764, 2021, DOI:10.32604/cmc.2021.018549 - 21 July 2021

    Abstract Recently, with the advancement of Information and Communications Technology (ICT), Internet of Things (IoT) has been connected to the cloud and used in industrial sectors, medical environments, and smart grids. However, if data is transmitted in plain text when collecting data in an IoT-cloud environment, it can be exposed to various security threats such as replay attacks and data forgery. Thus, digital signatures are required. Data integrity is ensured when a user (or a device) transmits data using a signature. In addition, the concept of data aggregation is important to efficiently collect data transmitted from… More >

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