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  • Open Access

    ARTICLE

    VANET: Optimal Cluster Head Selection Using Opposition Based Learning

    S. Aravindkumar*, P. Varalakshmi

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 601-617, 2022, DOI:10.32604/iasc.2022.023783 - 05 January 2022

    Abstract

    Traffic related accidents and route congestions remain to dwell significant issues in the globe. To overcome this, VANET was proposed to enhance the traffic management. However, there are several drawbacks in VANET such as collision of vehicles, data transmission in high probability of network fragmentation and data congestion. To overcome these issues, the Enhanced Pigeon Inspired Optimization (EPIO) and the Adaptive Neuro Fuzzy Inference System (ANFIS) based methods have been proposed. The Cluster Head (CH) has been selected optimally using the EPIO approach, and then the ANFIS has been used for updating and validating the

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  • Open Access

    ARTICLE

    Overhauled Approach to Effectuate the Amelioration in EEG Analysis

    S. Beatrice*, Janaki Meena

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 331-347, 2022, DOI:10.32604/iasc.2022.023666 - 05 January 2022

    Abstract Discovering the information about several disorders prevailing in brain and neurology is by no means a new scientific technique. A neurological disorder of any human being can be analyzed using EEG (Electroencephalography) signal from the electrode’s output. Epilepsy (spontaneous recurrent seizure) detection is usually carried out by the physicians using a visual scanning of the signals produced by EEG, which is onerous and may be inaccurate. EEG signal is often used to determine epilepsy, for its merits, such as non-invasive, portable, and economical, can exhibit superior temporal tenacity. This paper surveys the existing artifact removal… More >

  • Open Access

    ARTICLE

    Optimized Compressive Sensing Based ECG Signal Compression and Reconstruction

    Ishani Mishra1,*, Sanjay Jain2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 415-428, 2022, DOI:10.32604/iasc.2022.022860 - 05 January 2022

    Abstract In wireless body sensor network (WBSN), the set of electrocardiograms (ECG) data which is collected from sensor nodes and transmitted to the server remotely supports the experts to monitor the health of a patient. However, due to the size of the ECG data, the performance of the signal compression and reconstruction is degraded. For efficient wireless transmission of ECG data, compressive sensing (CS) frame work plays significant role recently in WBSN. So, this work focuses to present CS for ECG signal compression and reconstruction. Although CS minimizes mean square error (MSE), compression rate and reconstruction More >

  • Open Access

    ARTICLE

    Adaptive XGBOOST Hyper Tuned Meta Classifier for Prediction of Churn Customers

    B. Srikanth1,*, Swarajya Lakshmi V. Papineni2, Gutta Sridevi3, D. N. V. S. L. S. Indira4, K. S. R. Radhika5, Khasim Syed6

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 21-34, 2022, DOI:10.32604/iasc.2022.022423 - 05 January 2022

    Abstract In India, the banks have a formidable edge in maintaining their customer retention ratio for past few decades. Downfall makes the private banks to reduce their operations and the nationalised banks merge with other banks. The researchers have used the traditional and ensemble algorithms with relevant feature engineering techniques to better classify the customers. The proposed algorithm uses a Meta classifier instead of an ensemble algorithm with an adaptive genetic algorithm for feature selection. Churn prediction is the number of customers who wants to terminate their services in the banking sector. The model considers twelve… More >

  • Open Access

    ARTICLE

    Decision Tree Based Key Management for Secure Group Communication

    P. Parthasarathi1,*, S. Shankar2

    Computer Systems Science and Engineering, Vol.42, No.2, pp. 561-575, 2022, DOI:10.32604/csse.2022.019561 - 04 January 2022

    Abstract Group communication is widely used by most of the emerging network applications like telecommunication, video conferencing, simulation applications, distributed and other interactive systems. Secured group communication plays a vital role in case of providing the integrity, authenticity, confidentiality, and availability of the message delivered among the group members with respect to communicate securely between the inter group or else within the group. In secure group communications, the time cost associated with the key updating in the proceedings of the member join and departure is an important aspect of the quality of service, particularly in the… More >

  • Open Access

    ARTICLE

    Strengthened Initialization of Adaptive Cross-Generation Differential Evolution

    Wei Wan1, Gaige Wang1,2,3,*, Junyu Dong1

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1495-1516, 2022, DOI:10.32604/cmes.2021.017987 - 30 December 2021

    Abstract Adaptive Cross-Generation Differential Evolution (ACGDE) is a recently-introduced algorithm for solving multiobjective problems with remarkable performance compared to other evolutionary algorithms (EAs). However, its convergence and diversity are not satisfactory compared with the latest algorithms. In order to adapt to the current environment, ACGDE requires improvements in many aspects, such as its initialization and mutant operator. In this paper, an enhanced version is proposed, namely SIACGDE. It incorporates a strengthened initialization strategy and optimized parameters in contrast to its predecessor. These improvements make the direction of crossgeneration mutation more clearly and the ability of searching More >

  • Open Access

    ARTICLE

    Thermogram Adaptive Efficient Model for Breast Cancer Detection Using Fractional Derivative Mask and Hybrid Feature Set in the IoT Environment

    Ritam Sharma1, Janki Ballabh Sharma1, Ranjan Maheshwari1, Praveen Agarwal2,3,4,5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 923-947, 2022, DOI:10.32604/cmes.2022.016065 - 13 December 2021

    Abstract In this paper, a novel hybrid texture feature set and fractional derivative filter-based breast cancer detection model is introduced. This paper also introduces the application of a histogram of linear bipolar pattern features (HLBP) for breast thermogram classification. Initially, breast tissues are separated by masking operation and filtered by Grmwald–Letnikov fractional derivative-based Sobel mask to enhance the texture and rectify the noise. A novel hybrid feature set using HLBP and other statistical feature sets is derived and reduced by principal component analysis. Radial basis function kernel-based support vector machine is employed for detecting the abnormality… More >

  • Open Access

    ARTICLE

    A Dominating Set Routing Scheme for Adaptive Caching in Ad Hoc Network

    Raed Alsaqour1, Ammar Al-hamadani2, Maha Abdelhaq3,*, Joud Almeheimidy3

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1587-1603, 2022, DOI:10.32604/iasc.2022.021127 - 09 December 2021

    Abstract Current efforts for providing an efficient dynamic source routing protocol (DSR) for use in multi-hop ad-hoc wireless are promising. This is since DSR has a unique characteristic in that it uses source routing, instead of relying on the routing table at each intermediate device. This study addresses the current challenges facing DSR protocol in terms of the dynamic changes of the route and how to update such changes into the route cache of the DSR. The challenges typically persist when a sudden route break occurs resulting in a delay in updating the new node location… More >

  • Open Access

    ARTICLE

    Noisy ECG Signal Data Transformation to Augment Classification Accuracy

    Iqra Afzal1, Fiaz Majeed1, Muhammad Usman Ali2, Shahzada Khurram3, Akber Abid Gardezi4, Shafiq Ahmad5, Saad Aladyan5, Almetwally M. Mostafa6, Muhammad Shafiq7,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2191-2207, 2022, DOI:10.32604/cmc.2022.022711 - 07 December 2021

    Abstract In this era of electronic health, healthcare data is very important because it contains information about human survival. In addition, the Internet of Things (IoT) revolution has redefined modern healthcare systems and management by providing continuous monitoring. In this case, the data related to the heart is more important and requires proper analysis. For the analysis of heart data, Electrocardiogram (ECG) is used. In this work, machine learning techniques, such as adaptive boosting (AdaBoost) is used for detecting normal sinus rhythm, atrial fibrillation (AF), and noise in ECG signals to improve the classification accuracy. The… More >

  • Open Access

    ARTICLE

    HELP-WSN-A Novel Adaptive Multi-Tier Hybrid Intelligent Framework for QoS Aware WSN-IoT Networks

    J. Sampathkumar*, N. Malmurugan

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2107-2123, 2022, DOI:10.32604/cmc.2022.019983 - 07 December 2021

    Abstract Wireless Sensor Network is considered as the intermediate layer in the paradigm of Internet of things (IoT) and its effectiveness depends on the mode of deployment without sacrificing the performance and energy efficiency. WSN provides ubiquitous access to location, the status of different entities of the environment and data acquisition for long term IoT monitoring. Achieving the high performance of the WSN-IoT network remains to be a real challenge since the deployment of these networks in the large area consumes more power which in turn degrades the performance of the networks. So, developing the robust… More >

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