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  • Open Access

    ARTICLE

    Weed Recognition for Depthwise Separable Network Based on Transfer Learning

    Yanlei Xu1, Yuting Zhai1, Bin Zhao1, Yubin Jiao2, ShuoLin Kong1, Yang Zhou1,*, Zongmei Gao3

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 669-682, 2021, DOI:10.32604/iasc.2021.015225

    Abstract For improving the accuracy of weed recognition under complex field conditions, a weed recognition method using depthwise separable convolutional neural network based on deep transfer learning was proposed in this study. To improve the model classification accuracy, the Xception model was refined by using model transferring and fine-tuning. Specifically, the weight parameters trained by ImageNet data set were transferred to the Xception model. Then a global average pooling layer replaced the full connection layer of the Xception model. Finally, the XGBoost classifier was added to the top layer of the model to output results. The performance of the proposed model… More >

  • Open Access

    ARTICLE

    Machine Learning in Detecting Schizophrenia: An Overview

    Gurparsad Singh Suri1, Gurleen Kaur1, Sara Moein2,*

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 723-735, 2021, DOI:10.32604/iasc.2021.015049

    Abstract Schizophrenia (SZ) is a mental heterogeneous psychiatric disorder with unknown cause. Neuroscientists postulate that it is related to brain networks. Recently, scientists applied machine learning (ML) and artificial intelligence for the detection, monitoring, and prognosis of a range of diseases, including SZ, because these techniques show a high performance in discovering an association between disease symptoms and disease. Regions of the brain have significant connections to the symptoms of SZ. ML has the power to detect these associations. ML interests researchers because of its ability to reduce the number of input features when the data are high dimensional. In this… More >

  • Open Access

    ARTICLE

    Computational Intelligence Approach for Municipal Council Elections Using Blockchain

    Fatmah Baothman*, Kawther Saeedi, Khulood Aljuhani, Safaa Alkatheri, Mashael Almeatani, Nourah Alothman

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 625-639, 2021, DOI:10.32604/iasc.2021.014827

    Abstract Blockchain is an innovative technology that disrupts different industries and offers decentralized, secure, and immutable platforms. Its first appearance is connected with monetary cryptocurrency transactions, followed by adaptation in several domains. We believe that blockchain can provide a reliable environment by utilizing its unique characteristics to offer a more secure, costless, and robust mechanism suitable for a voting application. Although the technology has captured the interest of governments worldwide, blockchain as a service is still limited due to lack of application development experience, technology complexity, and absence of standardized design, architecture, and best practices. Therefore, this study aims to build… More >

  • Open Access

    ARTICLE

    A Multi-Agent Stacking Ensemble Hybridized with Vaguely Quantified Rough Set for Medical Diagnosis

    Ali M. Aseere1,*, Ayodele Lasisi2

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 683-699, 2021, DOI:10.32604/iasc.2021.014811

    Abstract In the absence of fast and adequate measures to combat them, life-threatening diseases are catastrophic to human health. Computational intelligent algorithms characterized by their adaptability, robustness, diversity, and recognition abilities allow for the diagnosis of medical diseases. This enhances the decision-making process of physicians. The objective is to predict and classify diseases accurately. In this paper, we proposed a multi-agent stacked ensemble classifier based on a vaguely quantified rough set, simple logistic algorithm, sequential minimal optimization (SMO), and JRip. The vaguely quantified rough set (VQRS) is used for feature selection and eradicating noise in the data. There are two classifier… More >

  • Open Access

    ARTICLE

    Threshold Parameters Selection for Empirical Mode Decomposition-Based EMG Signal Denoising

    Hassan Ashraf1, Asim Waris1,*, Syed Omer Gilani1, Muhammad Umair Tariq1, Hani Alquhayz2

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 799-815, 2021, DOI:10.32604/iasc.2021.014765

    Abstract Empirical Mode Decomposition (EMD) is a data-driven and fully adaptive signal decomposition technique to decompose a signal into its Intrinsic Mode Functions (IMF). EMD has attained great attention due to its capabilities to process a signal in the frequency-time domain without altering the signal into the frequency domain. EMD-based signal denoising techniques have shown great potential to denoise nonlinear and nonstationary signals without compromising the signal’s characteristics. The denoising procedure comprises three steps, i.e., signal decomposition, IMF thresholding, and signal reconstruction. Thresholding is performed to assess which IMFs contain noise. In this study, Interval Thresholding (IT), Iterative Interval Thresholding (IIT),… More >

  • Open Access

    ARTICLE

    CMMI Compliant Workflow Models to Establish Configuration Management Integrity in Software SMEs

    Islam Ali1, Musawwer Khan1, Waqar Mehmood1, Wasif Nisar1, Waqar Aslam2, Muhammad Qaiser Saleem3, Majzoob K. Omer3, Muhammad Shafiq4,*

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 605-623, 2021, DOI:10.32604/iasc.2021.014639

    Abstract Capability Maturity Model Integration (CMMI) is a world-renowned framework for software process improvement, which specifies “What-To-Do” in terms of requirements. However, it leaves the “How-To-Do” part regarding implementation to implementers. The software industry especially software SMEs (SSMEs) faces difficulties in implementing the Specific Practices (SPs) of Various Process Areas (PAs). Configuration Management Process Area (CM-PA) is usually ignored despite its acknowledged importance in the software development process. Establishing integrity is one of the three Specific Goals (SGs) that CMMI ver. 1.3 requires for successful implementation of CM-PA. This goal is achieved through the implementation of two SPs (i.e., 3.1 and… More >

  • Open Access

    ARTICLE

    Detection of COVID-19 Enhanced by a Deep Extreme Learning Machine

    Aaqib Inam1,*, Zhuli1, Ayesha Sarwar1, Salah-ud-din2, Ayesha Atta3, Iftikhar Naaseer4, Shahan Yamin Siddiqui5,6, Muhammad Adnan Khan7

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 701-712, 2021, DOI:10.32604/iasc.2021.014235

    Abstract The outbreak of coronavirus disease 2019 (COVID-19) has had a tremendous effect on daily life and a great impact on the economy of the world. More than 200 countries have been affected. The diagnosis of coronavirus is a major challenge for medical experts. Early detection is one of the most effective ways to reduce the mortality rate and increase the chance of successful treatment. At this point in time, no antiviral drugs have been approved for use, and clinically approved vaccines have only recently become available in some countries. Hybrid artificial intelligence computer-aided systems for the diagnosis of disease are… More >

  • Open Access

    ARTICLE

    A Big Data Approach to Black Friday Sales

    Mazhar Javed Awan1,2,*, Mohd Shafry Mohd Rahim2, Haitham Nobanee3,4,5, Awais Yasin6, Osamah Ibrahim Khalaf7, Umer Ishfaq2

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 785-797, 2021, DOI:10.32604/iasc.2021.014216

    Abstract Retail companies recognize the need to analyze and predict their sales and customer behavior against their products and product categories. Our study aims to help retail companies create personalized deals and promotions for their customers, even during the COVID-19 pandemic, through a big data framework that allows them to handle massive sales volumes with more efficient models. In this paper, we used Black Friday sales data taken from a dataset on the Kaggle website, which contains nearly 550,000 observations analyzed with 10 features: qualitative and quantitative. The class label is purchases and sales (in U.S. dollars). Because the predictor label… More >

  • Open Access

    ARTICLE

    Design and Development of Collaborative AR System for Anatomy Training

    Chung Le Van1, Trinh Hiep Hoa1, Nguyen Minh Duc1, Vikram Puri1, Tung Sanh Nguyen2, Dac-Nhuong Le3,4,*

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 853-871, 2021, DOI:10.32604/iasc.2021.013732

    Abstract Background: Augmented Reality (AR) incorporates both real and virtual objects in real-time environments and allows single and multi-users to interact with 3D models. It is often tricky to adopt multi-users in the same environment because of the devices’ latency and model position accuracy in displaying the models simultaneously. Method: To address this concern, we present a multi-user sharing technique in the AR of the human anatomy that increases learning with high quality, high stability, and low latency in multiple devices. Besides, the multi-user interactive display (HoloLens) merges with the human body anatomy application (AnatomyNow) to teach and train students, academic… More >

  • Open Access

    ARTICLE

    A Fast and Accurate Vascular Tissue Simulation Model Based on Point Primitive Method

    Xiaorui Zhang1,2,*, Hailun Wu1, Wei Sun1, Aiguo Song3, Sunil Kumar Jha4

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 873-889, 2021, DOI:10.32604/iasc.2021.013541

    Abstract Virtual surgery simulation is indispensable for virtual vascular interventional training system, which provides the doctor with visual scene between catheter and vascular. Soft tissue deformation, as the most significant part, determines the success or failure of the virtual surgery simulation. However, most soft tissue deformation model cannot simultaneously meet the requirement of high deformation accuracy and real-time interaction. To solve the challenge mentioned above, this paper proposes a fast and accurate vascular tissue simulation model based on point primitive method. Firstly, the proposed model simulates a deformation of the internal structure of the vascular tissue by adopting a point primitive… More >

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