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  • Open Access

    ARTICLE

    Effect of Inclined Tension Crack on Rock Slope Stability by SSR Technique

    Ch. Venkat Ramana*, Niranjan Ramchandra Thote, Arun Kumar Singh

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1205-1214, 2023, DOI:10.32604/iasc.2023.031838 - 29 September 2022

    Abstract The tension cracks and joints in rock or soil slopes affect their failure stability. Prediction of rock or soil slope failure is one of the most challenging tasks in the earth sciences. The actual slopes consist of inhomogeneous materials, complex morphology, and erratic joints. Most studies concerning the failure of rock slopes primarily focused on determining Factor of Safety (FoS) and Critical Slip Surface (CSS). In this article, the effect of inclined tension crack on a rock slope failure is studied numerically with Shear Strength Reduction Factor (SRF) method. An inclined Tension Crack (TC) influences… More >

  • Open Access

    ARTICLE

    High Linear Voltage Gain in QZNC Through Synchronizing Switching Circuits

    S. Harika1,*, R. Seyezhai1, A. Jawahar2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 895-910, 2023, DOI:10.32604/iasc.2023.031829 - 29 September 2022

    Abstract The solar powered systems require high step-up converter for efficient energy transfer. For this, quasi-impedance network converter has been introduced. The quasi-impedance network converter (QZNC) is of two types: type-1 and type-2 configuration. Both the type-1 and type-2 QZNC configurations have drooping voltage gain profile due to presence of high switching noise. To overcome this, a new quasi-impedance network converter synchronizing the switching circuit with low frequency noise has been proposed. In this paper, the proposed QZNC configuration utilizes the current controlling diode to prevent the output voltage drop. Thus, the suggested topology provides linear More >

  • Open Access

    ARTICLE

    Activation Functions Effect on Fractal Coding Using Neural Networks

    Rashad A. Al-Jawfi*

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 957-965, 2023, DOI:10.32604/iasc.2023.031700 - 29 September 2022

    Abstract Activation functions play an essential role in converting the output of the artificial neural network into nonlinear results, since without this nonlinearity, the results of the network will be less accurate. Nonlinearity is the mission of all nonlinear functions, except for polynomials. The activation function must be differentiable for backpropagation learning. This study’s objective is to determine the best activation functions for the approximation of each fractal image. Different results have been attained using Matlab and Visual Basic programs, which indicate that the bounded function is more helpful than other functions. The non-linearity of the… More >

  • Open Access

    ARTICLE

    Stage-Wise Categorization and Prediction of Diabetic Retinopathy Using Ensemble Learning and 2D-CNN

    N. M. Balamurugan1,*, K. Maithili2, T. K. S. Rathish Babu3, M. Adimoolam4

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 499-514, 2023, DOI:10.32604/iasc.2023.031661 - 29 September 2022

    Abstract Diabetic Eye Disease (DED) is a fundamental cause of blindness in human beings in the medical world. Different techniques are proposed to forecast and examine the stages in Prognostication of Diabetic Retinopathy (DR). The Machine Learning (ML) and the Deep Learning (DL) algorithms are the predominant techniques to project and explore the images of DR. Even though some solutions were adapted to challenge the cause of DR disease, still there should be an efficient and accurate DR prediction to be adapted to refine its performance. In this work, a hybrid technique was proposed for classification… More >

  • Open Access

    ARTICLE

    Hybrid Multi-Object Optimization Method for Tapping Center Machines

    Ping-Yueh Chang1, Fu-I Chou1, Po-Yuan Yang2,*, Shao-Hsien Chen3

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 23-38, 2023, DOI:10.32604/iasc.2023.031609 - 29 September 2022

    Abstract This paper proposes a hybrid multi-object optimization method integrating a uniform design, an adaptive network-based fuzzy inference system (ANFIS), and a multi-objective particle swarm optimizer (MOPSO) to optimize the rigid tapping parameters and minimize the synchronization errors and cycle times of computer numerical control (CNC) machines. First, rigid tapping parameters and uniform (including 41-level and 19-level) layouts were adopted to collect representative data for modeling. Next, ANFIS was used to build the model for the collected 41-level and 19-level uniform layout experiment data. In tapping center machines, the synchronization errors and cycle times are important… More >

  • Open Access

    ARTICLE

    Combined Linear Multi-Model for Reliable Route Recommender in Next Generation Network

    S. Kalavathi1,*, R. Nedunchelian2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 39-56, 2023, DOI:10.32604/iasc.2023.031522 - 29 September 2022

    Abstract Network analysis is a promising field in the area of network applications as different types of traffic grow enormously and exponentially. Reliable route prediction is a challenging task in the Large Scale Networks (LSN). Various non-self-learning and self-learning approaches have been adopted to predict reliable routing. Routing protocols decide how to send all the packets from source to the destination addresses across the network through their IP. In the current era, dynamic protocols are preferred as they network self-learning internally using an algorithm and may not entail being updated physically more than the static protocols.… More >

  • Open Access

    ARTICLE

    Weighted PageRank Algorithm Search Engine Ranking Model for Web Pages

    S. Samsudeen Shaffi1,*, I. Muthulakshmi2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 183-192, 2023, DOI:10.32604/iasc.2023.031494 - 29 September 2022

    Abstract As data grows in size, search engines face new challenges in extracting more relevant content for users’ searches. As a result, a number of retrieval and ranking algorithms have been employed to ensure that the results are relevant to the user’s requirements. Unfortunately, most existing indexes and ranking algorithms crawl documents and web pages based on a limited set of criteria designed to meet user expectations, making it impossible to deliver exceptionally accurate results. As a result, this study investigates and analyses how search engines work, as well as the elements that contribute to higher… More >

  • Open Access

    ARTICLE

    Identifying Cancer Disease Using Softmax-Feed Forward Recurrent Neural Classification

    P. Saranya*, P. Asha

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1137-1149, 2023, DOI:10.32604/iasc.2023.031470 - 29 September 2022

    Abstract In today’s growing modern world environment, as human food activities are changing, it is affecting human health, thus leading to diseases like cancer. Cancer is a complex disease with many subtypes that affect human health without premature treatment and cause death. So the analysis of early diagnosis and prognosis of cancer studies can improve clinical management by analyzing various features of observation, which has become necessary to classify the type in cancer research. The research needs importance to organize the risk of the cancer patients based on data analysis to predict the result of premature… More >

  • Open Access

    ARTICLE

    Efficient Hardware Design of a Secure Cancellable Biometric Cryptosystem

    Lamiaa A. Abou Elazm1,2, Walid El-Shafai3,4, Sameh Ibrahim2, Mohamed G. Egila1, H. Shawkey1, Mohamed K. H. Elsaid2, Naglaa F. Soliman5, Hussah Nasser AlEisa6,*, Fathi E. Abd El-Samie3

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 929-955, 2023, DOI:10.32604/iasc.2023.031386 - 29 September 2022

    Abstract Biometric security is a growing trend, as it supports the authentication of persons using confidential biometric data. Most of the transmitted data in multimedia systems are susceptible to attacks, which affect the security of these systems. Biometric systems provide sufficient protection and privacy for users. The recently-introduced cancellable biometric recognition systems have not been investigated in the presence of different types of attacks. In addition, they have not been studied on different and large biometric datasets. Another point that deserves consideration is the hardware implementation of cancellable biometric recognition systems. This paper presents a suggested… More >

  • Open Access

    ARTICLE

    Real-Time Safety Helmet Detection Using Yolov5 at Construction Sites

    Kisaezehra1, Muhammad Umer Farooq1,*, Muhammad Aslam Bhutto2, Abdul Karim Kazi1

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 911-927, 2023, DOI:10.32604/iasc.2023.031359 - 29 September 2022

    Abstract The construction industry has always remained the economic and social backbone of any country in the world where occupational health and safety (OHS) is of prime importance. Like in other developing countries, this industry pays very little, rather negligible attention to OHS practices in Pakistan, resulting in the occurrence of a wide variety of accidents, mishaps, and near-misses every year. One of the major causes of such mishaps is the non-wearing of safety helmets (hard hats) at construction sites where falling objects from a height are unavoidable. In most cases, this leads to serious brain… More >

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