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  • Open Access

    ARTICLE

    A Multi-Simplex Imperialist Competitive Paradigm for Solving Nonlinear Physical Systems

    Javaid Ali1, Shaukat Iqbal2, Salem Alkhalaf3,*

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 149-166, 2022, DOI:10.32604/iasc.2022.021788

    Abstract This paper proposes a novel gradient free multi-simplex topology fabric aided imperialist competitive algorithm (ICA) for solving nonlinear systems of algebraic equations by transforming them to equivalent global optimization problems. The high dependence of traditional gradient based solvers of such systems on initial guesses and the Jacobeans resulting in false convergence is the main motivation behind the present work. The present work provides a mechanism for enhancing exploitation powers of imperialist search phase of the algorithm and hence improves the convergence speed. The variants emerging from the proposed approach are applied to diverse nonlinear systems arising in different scientific areas… More >

  • Open Access

    ARTICLE

    Massive MIMO Codebook Design Using Gaussian Mixture Model Based Clustering

    S. Markkandan1,*, S. Sivasubramanian2, Jaison Mulerikkal3, Nazeer Shaik4, Beulah Jackson5, Lakshmi Naryanan6

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 361-375, 2022, DOI:10.32604/iasc.2022.021779

    Abstract The codebook design is the most essential core technique in constrained feedback massive multi-input multi-output (MIMO) system communications. MIMO vectors have been generally isotropic or evenly distributed in traditional codebook designs. In this paper, Gaussian mixture model (GMM) based clustering codebook design is proposed, which is inspired by the strong classification and analytical abilities of clustering techniques. Huge quantities of channel state information (CSI) are initially saved as entry data of the clustering process. Further, split into N number of clusters based on the shortest distance. The centroids part of clustering has been utilized for constructing a codebook with statistic… More >

  • Open Access

    ARTICLE

    Scrambling Based Riffle Shift on Stego-Image to Channelize the Ensured Data

    R. Bala Krishnan1, M. M. Anishin Raj2, N. Rajesh Kumar1, B. Karthikeyan3, G. Manikandan3,*, N. R. Raajan4

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 221-235, 2022, DOI:10.32604/iasc.2022.021775

    Abstract In recent years information hiding has got much attention as it acts as an alternate option for secured communication. The Secret content would get imbedded with the image using various possible image embodiment techniques, in which the Least Significant Bit (LSB) substitution is one of the preferred content embodiment strategy; however, asserting the quality and the originality of the content embedded image (stego) is yet a grievous concern in the field of Information Security. In this article, a proficient Scrambling Based Haar Wavelet Transform (SBHWT) approach has been sought to ensure the novelty of the stego-image that supports the safe… More >

  • Open Access

    ARTICLE

    Strengthening Software Make vs. Buy Decision: A Mixed-Method Approach

    Farooq Javeed1, Basit Shahzad2, Asadullah Shaikh3, Mana Saleh Al Reshan3,*, Saba Ahmad1, Hani Alshahrani3, Khairan Rajab3

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 193-205, 2022, DOI:10.32604/iasc.2022.021769

    Abstract Over the past few decades, multiple software development process models, tools, and techniques have been used by practitioners. Despite using these techniques, most software development organizations still fail to meet customer’s needs within time and budget. Time overrun is one of the major reasons for project failure. There is a need to come up with a comprehensive solution that would increase the chances of project success. However, the “make vs. buy” decision can be helpful for “in time” software development. Social media have become a popular platform for discussion of all sorts of topics, so software development is no exception.… More >

  • Open Access

    ARTICLE

    Optimization of Heat Treatment Scheduling for Hot Press Forging Using Data-Driven Models

    Seyoung Kim1, Jeonghoon Choi1, Kwang Ryel Ryu2,*

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 207-220, 2022, DOI:10.32604/iasc.2022.021752

    Abstract Scheduling heat treatment jobs in a hot press forging factory involves forming batches of multiple workpieces for the given furnaces, determining the start time of heating each batch, and sorting out the order of cooling the heated workpieces. Among these, forming batches is particularly difficult because of the various constraints that must be satisfied. This paper proposes an optimization method based on an evolutionary algorithm to search for a heat treatment schedule of maximum productivity with minimum energy cost, satisfying various constraints imposed on the batches. Our method encodes a candidate solution as a permutation of heat treatment jobs and… More >

  • Open Access

    ARTICLE

    Machine Learning for Modeling and Control of Industrial Clarifier Process

    M. Rajalakshmi1, V. Saravanan2, V. Arunprasad3, C. A. T. Romero4, O. I. Khalaf5, C. Karthik1,*

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 339-359, 2022, DOI:10.32604/iasc.2022.021696

    Abstract In sugar production, model parameter estimation and controller tuning of the nonlinear clarification process are major concerns. Because the sugar industry’s clarification process is difficult and nonlinear, obtaining the exact model using identification methods is critical. For regulating the clarification process and identifying the model parameters, this work presents a state transition algorithm (STA). First, the model parameters for the clarifier are estimated using the normal system identification process. The STA is then utilized to improve the accuracy of the system parameters that have been identified. Metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and State Transition… More >

  • Open Access

    ARTICLE

    Target Classification of Marine Debris Using Deep Learning

    Anum Aleem1, Samabia Tehsin1,*, Sumaira Kausar1, Amina Jameel2

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 73-85, 2022, DOI:10.32604/iasc.2022.021583

    Abstract Marine Debris is human-created waste dumped into the sea or ocean. It pollutes the aquatic environment and hence very dangerous for ocean species. Removal of marine debris from ocean is necessary to eliminate pollution and to secure aquatic life. A robust and automatic system is essential that detects unnecessary litter of plastic and other garbage at real-time. In this study, we have proposed deep learning based architecture for the detection and classification of marine debris. Histogram Equalization technique combined with Median Filter is used to enhance the contrast of images and to remove noise. Experiments are performed on challenging Forward… More >

  • Open Access

    ARTICLE

    Coronavirus Decision-Making Based on a Locally -Generalized Closed Set

    M. A. El Safty1,*, S. A. Alblowi2, Yahya Almalki3, M. El Sayed4

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 483-498, 2022, DOI:10.32604/iasc.2022.021581

    Abstract Real-world applications now deal with a massive amount of data, and information about the world is inaccurate, incomplete, or uncertain. Therefore, we present in our paper a proposed model for solving problems. This model is based on the class of locally generalized closed sets, namely, locally simply* alpha generalized closed* sets and locally simply* alpha generalized closed** sets (briefly, -sets and -sets), based on simply* alpha open set. We also introduce various concepts of their properties and their relationship with other types, and we are studying several of their properties. Finally, we apply the concept of the simply* alpha open… More >

  • Open Access

    ARTICLE

    Development of IoT Based Fish Monitoring System for Aquaculture

    Abu Taher Tamim1, Halima Begum1, Sumaiya Ashfaque Shachcho1, Mohammad Monirujjaman Khan1,*, Bright Yeboah-Akowuah2, Mehedi Masud3, Jehad F. Al-Amri4

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 55-71, 2022, DOI:10.32604/iasc.2022.021559

    Abstract Aquaculture mainly refers to cultivating aquatic organisms providing suitable environments for various purposes, including commercial, recreational, public purposes. This paper aims to enhance the production of fish and maintain the aquatic environment of aquaculture in Bangladesh. This paper presents the way of using Internet of Things (IoT) based devices to monitor aquaculture’s basic needs and help provide things needed for the fisheries. Using these devices, various parameters of water will be monitored for a better living environment for fish. These devices consist of some sensors that will detect the Potential of Hydrogen (pH) level, the water temperature, and there will… More >

  • Open Access

    ARTICLE

    Video Surveillance-Based Urban Flood Monitoring System Using a Convolutional Neural Network

    R. Dhaya1,*, R. Kanthavel2

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 183-192, 2022, DOI:10.32604/iasc.2022.021538

    Abstract The high prevalence of urban flooding in the world is increasing rapidly with the rise in extreme weather events. Consequently, this research uses an Automatic Flood Monitoring System (ARMS) through a video surveillance camera. Initially, videos are collected from a surveillance camera and converted into video frames. After converting the video frames, the water level can be identified by using a Histogram of oriented Gradient (HoG), which is used to remove the functionality. Completing the extracted features, the frames are enhanced by using a median filter to remove the unwanted noise from the image. The next step is water level… More >

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