Ali M. Aseere^1,*, 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 >

Hassan Ashraf¹, Asim Waris^1,*, 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 >

Islam Ali¹, Musawwer Khan¹, Waqar Mehmood¹, Wasif Nisar¹, Waqar Aslam², Muhammad Qaiser Saleem³, Majzoob K. Omer³, Muhammad Shafiq^4,*

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 >

Aaqib Inam^1,*, Zhuli¹, Ayesha Sarwar¹, Salah-ud-din², Ayesha Atta³, Iftikhar Naaseer⁴, Shahan Yamin Siddiqui^5,6, 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 >

Mazhar Javed Awan^1,2,*, Mohd Shafry Mohd Rahim², Haitham Nobanee^3,4,5, 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 >

Chung Le Van¹, Trinh Hiep Hoa¹, Nguyen Minh Duc¹, Vikram Puri¹, Tung Sanh Nguyen², Dac-Nhuong Le^3,4,*

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 >

Xiaorui Zhang^1,2,*, 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 >

Xiaohong Ji¹, Junjun Du¹, Guoqing Jia^1,*, Weidong Fang^2,3

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 737-746, 2021, DOI:10.32604/iasc.2021.013009

Abstract As a new non-orthogonal multiple access technology for 5G massive machine type communication scenario, the sparse code multiple access (SCMA) has greatly improved the spectrum efficiency due to the high connection density. SCMA combines QAM (Quadrature Amplitude Modulation) modulation and sparse spreading into a codebook set to obtain forming gain. The user binary bit data is directly mapped into multi-dimensional codewords in the transmitter. The receiver uses the message passing algorithm (MPA) for multi-user detection to achieve efficient decoding. However, MPA is a good solution for SCMA, though its high complexity limits the application in practical systems. In order to… More >

Anuj Kumar Singh¹, Mohammed Alshehri^2,*, Shashi Bhushan³, Manoj Kumar³, Osama Alfarraj⁴, Kamal Raj Pardarshani⁵

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 761-769, 2021, DOI:10.32604/iasc.2021.012806

Abstract Wireless sensor networks (WSNs) have been used in numerous delicate checking, observation, and surveillance systems that use sensitive data. When a WSN utilizes various data clustering techniques, data is moved to the cluster head (CH) of the corresponding cluster area. Cluster Head further communicates the information to the sink node. In a WSN, a network owner (NO) does not validate a sensor before connecting to the network, so faulty nodes may likely attach to the network to sense the data and attempt to release the information to unauthorized persons. Further, a malicious node may become a mobile node (MN) equipped… More >

Krishnan Muthumayil^1,*, Thangaiyan Jayasankar², Nagappan Krishnaraj³, Mohamed Yacin Sikkandar⁴, Prakash Nattanmai Balasubramanian⁵, Chokkalingam Bharatiraja⁶

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 771-784, 2021, DOI:10.32604/iasc.2021.012462

Abstract Wireless Multimedia Sensor Networks (WMSN) provides valuable information for scalar data, images, audio, and video processing in monitoring and surveillance applications. Multimedia streaming, however, is highly challenging for networks as energy restriction sensor nodes limit the potential data transmission bandwidth and lead to reduced throughput. WMSN’s two key design challenges, which can be achieved by the clustering process, are energy efficiency and throughput maximization. The use of the clustering technique helps to organise the sensor nodes into clusters, and between each cluster a cluster head (CH) will be chosen. This paper introduces a new Artificial Fish Swarm Optimization Algorithm (AFSA)… More >