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  • 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 >

  • Open Access

    ARTICLE

    Low Complexity Decoding Algorithm for Uplink SCMA Based on Aerial Spherical Decoding

    Xiaohong Ji1, Junjun Du1, Guoqing Jia1,*, Weidong Fang2,3

    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 >

  • Open Access

    ARTICLE

    Secure and Energy Efficient Data Transmission Model for WSN

    Anuj Kumar Singh1, Mohammed Alshehri2,*, 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 >

  • Open Access

    ARTICLE

    Maximizing Throughput in Wireless Multimedia Sensor Network using Soft Computing Techniques

    Krishnan Muthumayil1,*, 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 >

  • Open Access

    ARTICLE

    Mammographic Image Classification Using Deep Neural Network for Computer-Aided Diagnosis

    Charles Arputham1,*, Krishnaraj Nagappan2, Lenin Babu Russeliah3, AdalineSuji Russeliah4

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 747-759, 2021, DOI:10.32604/iasc.2021.012077

    Abstract Breast cancer detection is a crucial topic in the healthcare sector. Breast cancer is a major reason for the increased mortality rate in recent years among women, specifically in developed and underdeveloped countries around the world. The incidence rate is less in India than in developed countries, but awareness must be increased. This paper focuses on an efficient deep learning-based diagnosis and classification technique to detect breast cancer from mammograms. The model includes preprocessing, segmentation, feature extraction, and classification. At the initial level, Laplacian filtering is applied to identify the portions of edges in mammogram images that are highly sensitive… More >

  • Open Access

    ARTICLE

    Vehicle Re-Identification Model Based on Optimized DenseNet121 with Joint Loss

    Xiaorui Zhang1,2,*, Xuan Chen1, Wei Sun2, Xiaozheng He3

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3933-3948, 2021, DOI:10.32604/cmc.2021.016560

    Abstract With the increasing application of surveillance cameras, vehicle re-identification (Re-ID) has attracted more attention in the field of public security. Vehicle Re-ID meets challenge attributable to the large intra-class differences caused by different views of vehicles in the traveling process and obvious inter-class similarities caused by similar appearances. Plentiful existing methods focus on local attributes by marking local locations. However, these methods require additional annotations, resulting in complex algorithms and insufferable computation time. To cope with these challenges, this paper proposes a vehicle Re-ID model based on optimized DenseNet121 with joint loss. This model applies the SE block to automatically… More >

  • Open Access

    ARTICLE

    A Reliable and Scalable Internet of Military Things Architecture

    Omar Said1,3, Amr Tolba2,3,*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3887-3906, 2021, DOI:10.32604/cmc.2021.016076

    Abstract Recently, Internet of Things (IoT) technology has provided logistics services to many disciplines such as agriculture, industry, and medicine. Thus, it has become one of the most important scientific research fields. Applying IoT to military domain has many challenges such as fault tolerance and QoS. In this paper, IoT technology is applied on the military field to create an Internet of Military Things (IoMT) system. Here, the architecture of the aforementioned IoMT system is proposed. This architecture consists of four main layers: Communication, information, application, and decision support. These layers provided a fault tolerant coverage communication system for IoMT things.… More >

  • Open Access

    ARTICLE

    Reconstructing the Time-Dependent Thermal Coefficient in 2D Free Boundary Problems

    M. J. Huntul*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3681-3699, 2021, DOI:10.32604/cmc.2021.016036

    Abstract The inverse problem of reconstructing the time-dependent thermal conductivity and free boundary coefficients along with the temperature in a two-dimensional parabolic equation with initial and boundary conditions and additional measurements is, for the first time, numerically investigated. This inverse problem appears extensively in the modelling of various phenomena in engineering and physics. For instance, steel annealing, vacuum-arc welding, fusion welding, continuous casting, metallurgy, aircraft, oil and gas production during drilling and operation of wells. From literature we already know that this inverse problem has a unique solution. However, the problem is still ill-posed by being unstable to noise in the… More >

  • Open Access

    ARTICLE

    Joint Frequency and DOA Estimation with Automatic Pairing Using the Rayleigh–Ritz Theorem

    Haiming Du1,*, Han Gao1, Wenjing Jia2

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3907-3919, 2021, DOI:10.32604/cmc.2021.015969

    Abstract This paper presents a novel scheme for joint frequency and direction of arrival (DOA) estimation, that pairs frequencies and DOAs automatically without additional computations. First, when the property of the Kronecker product is used in the received array signal of the multiple-delay output model, the frequency-angle steering vector can be reconstructed as the product of the frequency steering vector and the angle steering vector. The frequency of the incoming signal is then obtained by searching for the minimal eigenvalue among the smallest eigenvalues that depend on the frequency parameters but are irrelevant to the DOAs. Subsequently, the DOA related to… More >

  • Open Access

    ARTICLE

    A User-friendly Model for Ransomware Analysis Using Sandboxing

    Akhtar Kamal1, Morched Derbali2, Sadeeq Jan1,*, Javed Iqbal Bangash3, Fazal Qudus Khan2, Houssem Jerbi4, Rabeh Abbassi4, Gulzar Ahmad5

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3833-3846, 2021, DOI:10.32604/cmc.2021.015941

    Abstract Ransomware is a type of malicious software that blocks access to a computer by encrypting user’s files until a ransom is paid to the attacker. There have been several reported high-profile ransomware attacks including WannaCry, Petya, and Bad Rabbit resulting in losses of over a billion dollars to various individuals and businesses in the world. The analysis of ransomware is often carried out via sandbox environments; however, the initial setup and configuration of such environments is a challenging task. Also, it is difficult for an ordinary computer user to correctly interpret the complex results presented in the reports generated by… More >

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