Home / Journals / IASC / Vol.31, No.3, 2022
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    ARTICLE

    Classification Similarity Network Model for Image Fusion Using Resnet50 and GoogLeNet

    P. Siva Satya Sreedhar1,*, N. Nandhagopal2
    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1331-1344, 2022, DOI:10.32604/iasc.2022.020918
    Abstract The current trend in Image Fusion (IF) algorithms concentrate on the fusion process alone. However, pay less attention to critical issues such as the similarity between the two input images, features that participate in the Image Fusion. This paper addresses these two issues by deliberately attempting a new Image Fusion framework with Convolutional Neural Network (CNN). CNN has features like pre-training and similarity score, but functionalities are limited. A CNN model with classification prediction and similarity estimation are introduced as Classification Similarity Networks (CSN) to address these issues. ResNet50 and GoogLeNet are modified as the classification branches of CSN v1,… More >

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    ARTICLE

    Industrial Datasets with ICS Testbed and Attack Detection Using Machine Learning Techniques

    Sinil Mubarak1, Mohamed Hadi Habaebi1,*, Md Rafiqul Islam1, Asaad Balla1, Mohammad Tahir2, Elfatih A. A. Elsheikh3, F. M. Suliman3
    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1345-1360, 2022, DOI:10.32604/iasc.2022.020801
    Abstract Industrial control systems (ICS) are the backbone for the implementation of cybersecurity solutions. They are susceptible to various attacks, due to openness in connectivity, unauthorized attempts, malicious attacks, use of more commercial off the shelf (COTS) software and hardware, and implementation of Internet protocols (IP) that exposes them to the outside world. Cybersecurity solutions for Information technology (IT) secured with firewalls, intrusion detection/protection systems do nothing much for Operational technology (OT) ICS. An innovative concept of using real operational technology network traffic-based testbed, for cyber-physical system simulation and analysis, is presented. The testbed is equipped with real-time attacks using in-house… More >

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    ARTICLE

    A Modelling and Scheduling Tool for Crowd Movement in Complex Network

    Emad Felemban1, Faizan Ur Rehman2,*, Akhlaq Ahmad2, Muhamad Felemban3
    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1361-1375, 2022, DOI:10.32604/iasc.2022.020235
    Abstract Managing events pose a unique challenge to the stakeholders and authorities to control the crowd in all three phases of the event (pre, during and post), ensuring crowd safety. One of the fundamental keys to provide crowd safety is to consider the mobility infrastructure hosting the crowd, i.e., routes, areas, entrances and exits. During Hajj, where millions of pilgrims worldwide fulfil the annual event’s rites, mina encampment incorporates pilgrims performing recurring stoning ritual conducted over multi-level Jamarat bridge. Pilgrims mobility through the available complex road network, to and back from the Jamarat bridge, forces upon authorities in charge to set… More >

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    ARTICLE

    IoT and Machine Learning Based Stem Borer Pest Prediction

    Rana Muhammad Nadeem1, Arfan Jaffar2, Rana Muhammad Saleem3,*
    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1377-1392, 2022, DOI:10.32604/iasc.2022.020680
    (This article belongs to this Special Issue: Soft Computing Methods for Intelligent Automation Systems)
    Abstract Global climatic changes have severe impacts on agricultural productivity. Enhanced pest attacks on crops are one of the major impacts on sustainable developments in agriculture to come up with the needs of the ever-increasing human population. Early warning of a pest attack is important for Integrated Pest Management (IPM) activities to be effective. Early warning of pest attacks is also important for judicious use of pesticides for efficient use of resources for minimal impacts on the environment. Sugarcane is the major cash crop and is also severely affected by different types of pests. This study proposed stem borer attack prediction… More >

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    ARTICLE

    Time-Efficient Fire Detection Convolutional Neural Network Coupled with Transfer Learning

    Hanan A. Hosni Mahmoud, Amal H. Alharbi, Norah S. Alghamdi*
    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1393-1403, 2022, DOI:10.32604/iasc.2022.020629
    Abstract The detection of fires in surveillance videos are usually done by utilizing deep learning. In Spite of the advances in processing power, deep learning methods usually need extensive computations and require high memory resources. This leads to restriction in real time fire detection. In this research, we present a time-efficient fire detection convolutional neural network coupled with transfer learning for surveillance systems. The model utilizes CNN architecture with reasonable computational time that is deemed possible for real time applications. At the same time, the model will not compromise accuracy for time efficiency by tuning the model with respect to fire… More >

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    ARTICLE

    Enhancing Detection of Malicious URLs Using Boosting and Lexical Features

    Mohammad Atrees*, Ashraf Ahmad, Firas Alghanim
    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1405-1422, 2022, DOI:10.32604/iasc.2022.020229
    Abstract A malicious URL is a link that is created to spread spams, phishing, malware, ransomware, spyware, etc. A user may download malware that can adversely affect the computer by clicking on an infected URL, or might be convinced to provide confidential information to a fraudulent website causing serious losses. These threats must be identified and handled in a decent time and in an effective way. Detection is traditionally done through the blacklist usage method, which relies on keyword matching with previously known malicious domain names stored in a repository. This method is fast and easy to implement, with the advantage… More >

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    ARTICLE

    Real Time Feature Extraction Deep-CNN for Mask Detection

    Hanan A. Hosni Mahmoud, Norah S. Alghamdi, Amal H. Alharbi*
    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1423-1434, 2022, DOI:10.32604/iasc.2022.020586
    Abstract COVID-19 pandemic outbreak became one of the serious threats to humans. As there is no cure yet for this virus, we have to control the spread of Coronavirus through precautions. One of the effective precautions as announced by the World Health Organization is mask wearing. Surveillance systems in crowded places can lead to detection of people wearing masks. Therefore, it is highly urgent for computerized mask detection methods that can operate in real-time. As for now, most countries demand mask-wearing in public places to avoid the spreading of this virus. In this paper, we are presenting an object detection technique… More >

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    ARTICLE

    IIoT Framework Based ML Model to Improve Automobile Industry Product

    S. Gopalakrishnan1,*, M. Senthil Kumaran2
    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1435-1449, 2022, DOI:10.32604/iasc.2022.020660
    Abstract In the automotive industry, multiple predictive maintenance units run behind the scenes in every production process to support significant product development, particularly among Accessories Manufacturers (AMs). As a result, they wish to maintain a positive relationship with vehicle manufacturers by providing 100 percent quality assurances for accessories. This is only achievable if they implement an effective anticipatory strategy that prioritizes quality control before and after product development. To do this, many sensors devices are interconnected in the production area to collect operational data (humanity, viscosity, and force) continuously received from machines and sent to backend computers for control operations and… More >

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    ARTICLE

    A Fuzzy MCDM Model of Supplier Selection in Supply Chain Management

    Jui-Chung Kao1, Chia-Nan Wang2,*, Viet Tinh Nguyen3 and Syed Tam Husain3
    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1451-1466, 2022, DOI:10.32604/iasc.2022.021778
    (This article belongs to this Special Issue: Fuzzy Sets and Soft Computing)
    Abstract According to a new study by the International Labor Organization (ILO), the COVID-19 pandemic has had a strong impact on the garment industry in the Asia-Pacific region. A sharp drop in retail sales in key export markets has affected workers and businesses across supply chains. To ensure the effectiveness and efficiency of garment supply chain, choosing a sustainable supplier should be a main concern of all businesses. The supplier selection problem in garment industry involves multiple quantitative and qualitative criteria. There have been many research and literatures about the development and application of Multicriteria Decision Making (MCDM) models in solving… More >

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    ARTICLE

    Periodic Solutions for Two Dimensional Quartic Non-Autonomous Differential Equation

    Saima Akram1,*, Allah Nawaz1, Muhammad Bilal Riaz2, Mariam Rehman3
    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1467-1482, 2022, DOI:10.32604/iasc.2022.019767
    (This article belongs to this Special Issue: Recent Trends in Computational Methods for Differential Equations)
    Abstract In this article, the maximum possible numbers of periodic solutions for the quartic differential equation are calculated. In this regard, for the first time in the literature, we developed new formulae to determine the maximum number of periodic solutions greater than eight for the quartic equation. To obtain the maximum number of periodic solutions, we used a systematic procedure of bifurcation analysis. We used computer algebra Maple 18 to solve lengthy calculations that appeared in the formulae of focal values as integrations. The newly developed formulae were applied to a variety of polynomials with algebraic and homogeneous trigonometric coefficients of… More >

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