Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (3,428)
  • Open Access

    ARTICLE

    A Learning-based Static Malware Detection System with Integrated Feature

    Zhiguo Chen1,*, Xiaorui Zhang1,2, Sungryul Kim3

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 891-908, 2021, DOI:10.32604/iasc.2021.016933 - 01 March 2021

    Abstract The rapid growth of malware poses a significant threat to the security of computer systems. Analysts now need to examine thousands of malware samples daily. It has become a challenging task to determine whether a program is a benign program or malware. Making accurate decisions about the program is crucial for anti-malware products. Precise malware detection techniques have become a popular issue in computer security. Traditional malware detection uses signature-based strategies, which are the most widespread method used in commercial anti-malware software. This method works well against known malware but cannot detect new malware. To… More >

  • Open Access

    ARTICLE

    Multi-Model Fuzzy Formation Control of UAV Quadrotors

    Abdul-Wahid A. Saif1, Mohammad Ataur-Rahman1, Sami Elferik1, Muhammad F. Mysorewala1, Mujahed Al-Dhaifallah1,*, Fouad Yacef2

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 817-834, 2021, DOI:10.32604/iasc.2021.015932 - 01 March 2021

    Abstract In this paper, the formation control problem of a group of unmanned air vehicle (UAV) quadrotors is solved using the Takagi–Sugeno (T–S) multi-model approach to linearize the nonlinear model of UAVs. The nonlinear model sof the quadrotor is linearized first around a set of operating points using Taylor series to get a set of local models. Our approach’s novelty is in considering the difference between the nonlinear model and the linearized ones as disturbance. Then, these linear models are interpolated using the fuzzy T–S approach to approximate the entire nonlinear model. Comparison of the nonlinear… 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 - 01 March 2021

    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… 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 - 01 March 2021

    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… 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 - 01 March 2021

    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… More >

  • Open Access

    ARTICLE

    Implementation of a Subjective Visual Vertical and Horizontal Testing System Using Virtual Reality

    Sungjin Lee1, Min Hong2, Hongly Va1, Ji-Yun Park3,*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3669-3679, 2021, DOI:10.32604/cmc.2021.015706 - 01 March 2021

    Abstract Subjective visual vertical (SVV) and subjective visual horizontal (SVH) tests can be used to evaluate the perception of verticality and horizontality, respectively, and can aid the diagnosis of otolith dysfunction in clinical practice. In this study, SVV and SVH screen version tests are implemented using virtual reality (VR) equipment; the proposed test method promotes a more immersive feeling for the subject while using a simple equipment configuration and possessing excellent mobility. To verify the performance of the proposed VR-based SVV and SVH tests, a reliable comparison was made between the traditional screen-based SVV and SVH More >

  • Open Access

    ARTICLE

    An Intelligent Cluster Optimization Algorithm for Smart Body Area Networks

    Adil Mushtaq1, Muhammad Nadeem Majeed1, Farhan Aadil2, Muhammad Fahad Khan2, Sangsoon Lim3,*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3795-3814, 2021, DOI:10.32604/cmc.2021.015369 - 01 March 2021

    Abstract Body Area Networks (BODYNETs) or Wireless Body Area Networks (WBAN), being an important type of ad-hoc network, plays a vital role in multimedia, safety, and traffic management applications. In BODYNETs, rapid topology changes occur due to high node mobility, which affects the scalability of the network. Node clustering is one mechanism among many others, which is used to overcome this issue in BODYNETs. There are many clustering algorithms used in this domain to overcome this issue. However, these algorithms generate a large number of Cluster Heads (CHs), which results in scarce resource utilization and degraded… More >

  • Open Access

    ARTICLE

    Efficient MCDM Model for Evaluating the Performance of Commercial Banks: A Case Study

    Mohamed Abdel-Basset1, Rehab Mohamed1, Mohamed Elhoseny2, Mohamed Abouhawash2,3, Yunyoung Nam4,*, Nabil M. AbdelAziz1

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2729-2746, 2021, DOI:10.32604/cmc.2021.015316 - 01 March 2021

    Abstract Evaluation of commercial banks (CBs) performance has been a significant issue in the financial world and deemed as a multi-criteria decision making (MCDM) model. Numerous research assesses CB performance according to different metrics and standers. As a result of uncertainty in decision-making problems and large economic variations in Egypt, this research proposes a plithogenic based model to evaluate Egyptian commercial banks’ performance based on a set of criteria. The proposed model evaluates the top ten Egyptian commercial banks based on three main metrics including financial, customer satisfaction, and qualitative evaluation, and 19 sub-criteria. The proportional… More >

  • Open Access

    ARTICLE

    A Novel Green IoT-Based Pay-As-You-Go Smart Parking System

    Andrea Sant1, Lalit Garg1,*, Peter Xuereb1, Chinmay Chakraborty2

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3523-3544, 2021, DOI:10.32604/cmc.2021.015265 - 01 March 2021

    Abstract The better management of resources and the potential improvement in traffic congestion via reducing the orbiting time for parking spaces is crucial in a smart city, particularly those with an uneven correlation between the increase in vehicles and infrastructure. This paper proposes and analyses a novel green IoT-based Pay-As-You-Go (PAYG) smart parking system by utilizing unused garage parking spaces. The article also presents an intelligent system that offers the most favorable prices to its users by matching private garages’ pricing portfolio with a garage’s current demand. Malta, the world’s fourth-most densely populated country, is considered More >

  • Open Access

    ARTICLE

    Minimum Error Entropy Based EKF for GPS Code Tracking Loop

    Dah-Jing Jwo1,*, Jen-Hsien Lai2

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2883-2898, 2021, DOI:10.32604/cmc.2021.015102 - 01 March 2021

    Abstract This paper investigates the minimum error entropy based extended Kalman filter (MEEKF) for multipath parameter estimation of the Global Positioning System (GPS). The extended Kalman filter (EKF) is designed to give a preliminary estimation of the state. The scheme is designed by introducing an additional term, which is tuned according to the higher order moment of the estimation error. The minimum error entropy criterion is introduced for updating the entropy of the innovation at each time step. According to the stochastic information gradient method, an optimal filer gain matrix is obtained. The mean square error… More >

Displaying 2501-2510 on page 251 of 3428. Per Page