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  • Open Access

    ARTICLE

    Hybrid Invasive Weed Improved Grasshopper Optimization Algorithm for Cloud Load Balancing

    K. Naveen Durai*, R. Subha, Anandakumar Haldorai

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 467-483, 2022, DOI:10.32604/iasc.2022.026020

    Abstract In cloud computing, the processes of load balancing and task scheduling are major concerns as they are the primary mechanisms responsible for executing tasks by allocating and utilizing the resources of Virtual Machines (VMs) in a more optimal way. This problem of balancing loads and scheduling tasks in the cloud computing scenario can be categorized as an NP-hard problem. This problem of load balancing needs to be efficiently allocated tasks to VMs and sustain the trade-off among the complete set of VMs. It also needs to maintain equilibrium among VMs with the objective of maximizing throughput with a minimized time… More >

  • Open Access

    ARTICLE

    Analysis of Brushless DC Motor Using Enhanced Fopid Controller with ALO Algorithm

    K. Prathibanandhi1,*, R. Ramesh2, C. Yaashuwanth3

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 543-557, 2022, DOI:10.32604/iasc.2022.025860

    Abstract The delivery of combined benefits of Alternating Current (AC) motor and Direct Current (DC) Motor makes the Brushless Direct Current (BLDC) motors as a unique feature in numerous industrial applications. The possibilities of running the motor at very high speed with extensive operating life span of BLDC with miniature and its compact design make it an un-ignorable option for Electrical Engineers. With many advantages, till managing as well as controlling the speed of BLDC is complicated. This work is intended to come up with an effective control of speed of the motor through Torque Ripple Minimization Route and an Enhanced-Fractional… More >

  • Open Access

    ARTICLE

    Self-Balancing Vehicle Based on Adaptive Neuro-Fuzzy Inference System

    M. L. Ramamoorthy1, S. Selvaperumal2,*, G. Prabhakar3

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 485-497, 2022, DOI:10.32604/iasc.2022.025824

    Abstract The scope of this research is to design and fuse the sensors used in the self-balancing vehicle through Adaptive Neuro-Fuzzy Inference systems (ANFIS) algorithm to optimize the output. The self-balancing vehicle is a wheeled inverted pendulum, which is extremely complex, nonlinear and unstable. Homogeneous and Heterogeneous sensors are involved in this sensor fusion research to identify the best feasible value among them. The data fusion algorithm present inside the controller of the self-balancing vehicle makes the inputs of the homogeneous sensors and heterogeneous sensors separately for ameliorate surrounding perception. Simulation is performed by modeling the sensors in Simulink. The outcomes… More >

  • Open Access

    ARTICLE

    Energy Efficient Clustering and Optimized LOADng Protocol for IoT

    Divya Sharma1,*, Sanjay Jain2, Vivek Maik3

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 357-370, 2022, DOI:10.32604/iasc.2022.025637

    Abstract In recent years, the use of Internet of Things (IoT) devices has increased exponentially due to the advancement of information and communication technologies. Wireless sensor networks (WSNs) are vital in the development of IoT and include low-cost smart devices for data collection. However, such smart devices hold some restrictions in terms of calculation, processing, storage, and energy resources. With such constraints, one of the primary difficulties for the WSN is to achieve the lowest possible energy consumption across the network. This article aims to develop an Energy-Efficient cluster-based Lightweight On-Demand Ad hoc Distance Vector Routing Protocol–Next Generation (LOADng) routing protocol… More >

  • Open Access

    ARTICLE

    Computer Aided Coronary Atherosclerosis Plaque Detection and Classification

    S. Deivanayagi1,*, P. S. Periasamy2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 639-653, 2022, DOI:10.32604/iasc.2022.025632

    Abstract Coronary artery disease (CAD) remains a major reason for increased mortality over the globe, comprising myocardial infarction and ischemic cardiomyopathy. The CAD is highly linked to coronary stenosis owing to the encumbrance of atherosclerotic plaques. Particularly, diversified atherosclerotic plaques are highly responsible for major cardiac adverse events over the calcified and non-calcified plaques. There, the recognition and classification of atherosclerotic plaques play a vital role to prevent and intervene in CAD. The process of detecting various class labels of the atherosclerotic plaques is significant to identify the disease at the earlier stages. Since several automated coronary plaque recognition models are… More >

  • Open Access

    ARTICLE

    CAD of BCD from Thermal Mammogram Images Using Machine Learning

    D. Banumathy1,*, Osamah Ibrahim Khalaf2, Carlos Andrés Tavera Romero3, J. Indra4, Dilip Kumar Sharma5

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 667-685, 2022, DOI:10.32604/iasc.2022.025609

    Abstract Lump in the breast, discharge of blood from the nipple, and deformation of the nipple/breast and its texture are the symptoms of breast cancer. Though breast cancer is very common in women, men can also get breast cancer. In the early stages, BCD makes use of Thermal Mammograms Breast Images (TMBI). The cost of treatment can be severely reduced in the early stages of detection. Based on the techniques of segmentation, the Breast Cancer Detection (BCD) works. Moreover, by providing a balanced, reliable and appropriate second opinion, a tremendous role has been played by ML in medical practices due to… More >

  • Open Access

    ARTICLE

    Gender-specific Facial Age Group Classification Using Deep Learning

    Valliappan Raman1, Khaled ELKarazle2,*, Patrick Then2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 105-118, 2022, DOI:10.32604/iasc.2022.025608

    Abstract Facial age is one of the prominent features needed to make decisions, such as accessing certain areas or resources, targeted advertising, or more straightforward decisions such as addressing one another. In machine learning, facial age estimation is a typical facial analysis subtask in which a model learns the different facial ageing features from several facial images. Despite several studies confirming a relationship between age and gender, very few studies explored the idea of introducing a gender-based system that consists of two separate models, each trained on a specific gender group. This study attempts to bridge this gap by introducing an… More >

  • Open Access

    ARTICLE

    Motor Torque Measurement Using Dual-Function Radar Polarized Signals of Flux

    B. Chinthamani1,*, N. S. Bhuvaneswari2, R. Senthil Kumar3, N. R. Shanker4

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 515-530, 2022, DOI:10.32604/iasc.2022.025410

    Abstract Motor Torque (MT) measurement plays a vital role for evaluating the performance of squirrel cage induction motor during operating conditions. Accurate and continuous measurements of MT provide information regarding driving load capacity, performance degradation of motor, reduces downtime and increases the efficiency. Traditional inline torque sensors-based measurement becomes inaccurate during abrupt change in load during starting condition of motor due to torque spikes. Mounting of torque sensor on motor is a major problem during torque measurement. Improper mounting of sensor acquires signals from other inefficient driveline components such as gearbox, couplings, and bearing. In this paper, we propose a non-contact… More >

  • Open Access

    ARTICLE

    Background Subtraction in Surveillance Systems Using Local Spectral Histograms and Linear Regression

    S. Hariharan1,*, R. Venkatesan2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 407-422, 2022, DOI:10.32604/iasc.2022.025309

    Abstract Background subtraction is a fundamental and crucial task for computer vision-based automatic video analysis due to various challenging situations that occur in real-world scenarios. This paper presents a novel background subtraction method by estimating the background model using linear regression and local spectral histogram which captures combined spectral and texture features. Different linear filters are applied on the image window centered at each pixel location and the features are captured via these filter responses. Each feature has been approximated by a linear combination of two representative features, each of which corresponds to either a background or a foreground pixel. These… More >

  • Open Access

    ARTICLE

    Multi-Agent with Multi Objective-Based Optimized Resource Allocation on Inter-Cloud

    J. Arravinth*, D. Manjula

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 133-147, 2022, DOI:10.32604/iasc.2022.025292

    Abstract Cloud computing is the ability to provide new technologies and standard cloud services. One of the essential features of cloud computing is the provision of “unlimited” computer resources to users on demand. However, single cloud resources are generally limited and may not be able to cope with the sudden rise in user needs. Therefore, the inter-cloud concept is introduced to support resource sharing between clouds. In this system, each cloud can tap the resources of other clouds when there are not enough resources to meet the demands of the consumer. In cloud computing, allocating the available resources of service nodes… More >

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