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Search Results (5)
  • Open Access

    ARTICLE

    Selective Mapping Scheme for Universal Filtered Multicarrier

    Akku Madhusudhan*, Sudhir Kumar Sharma

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1273-1282, 2023, DOI:10.32604/iasc.2023.030765 - 05 January 2023

    Abstract The next step in mobile communication technology, known as 5G, is set to go live in a number of countries in the near future. New wireless applications have high data rates and mobility requirements, which have posed a challenge to mobile communication technology researchers and designers. 5G systems could benefit from the Universal Filtered Multicarrier (UFMC). UFMC is an alternate waveform to orthogonal frequency-division multiplexing (OFDM), in filtering process is performed for a sub-band of subcarriers rather than the entire band of subcarriers Inter Carrier Interference (ICI) between neighbouring users is reduced via the sub-band More >

  • Open Access

    ARTICLE

    Improved Interleaved Single-Ended Primary Inductor-Converter for Single-Phase Grid-Connected System

    T. J. Thomas Thangam*, K. Muthu Vel

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3459-3478, 2023, DOI:10.32604/iasc.2023.025521 - 17 August 2022

    Abstract The generation of electricity based on renewable energy sources, particularly Photovoltaic (PV) system has been greatly increased and it is simply instigated for both domestic and commercial uses. The power generated from the PV system is erratic and hence there is a need for an efficient converter to perform the extraction of maximum power. An improved interleaved Single-ended Primary Inductor-Converter (SEPIC) converter is employed in proposed work to extricate most of power from renewable source. This proposed converter minimizes ripples, reduces electromagnetic interference due to filter elements and the continuous input current improves the power… More >

  • Open Access

    ARTICLE

    Crow Search Algorithm with Improved Objective Function for Test Case Generation and Optimization

    Meena Sharma, Babita Pathik*

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1125-1140, 2022, DOI:10.32604/iasc.2022.022335 - 17 November 2021

    Abstract Test case generation and optimization is the foremost requirement of software evolution and test automation. In this paper, a bio-inspired Crow Search Algorithm (CSA) is suggested with an improved objective function to fulfill this requirement. CSA is a nature-inspired optimization method. The improved objective function combines branch distance and predicate distance to cover the critical path on the control flow graph. CSA is a search-based technique that uses heuristic information for automation testing, and CSA optimizers minimize test cases generated by satisfying the objective function. This paper focuses on generating test cases for all paths,… More >

  • Open Access

    ARTICLE

    Paddy Leaf Disease Detection Using an Optimized Deep Neural Network

    Shankarnarayanan Nalini1,*, Nagappan Krishnaraj2, Thangaiyan Jayasankar3, Kalimuthu Vinothkumar4, Antony Sagai Francis Britto5, Kamalraj Subramaniam6, Chokkalingam Bharatiraja7

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1117-1128, 2021, DOI:10.32604/cmc.2021.012431 - 22 March 2021

    Abstract Precision Agriculture is a concept of farm management which makes use of IoT and networking concepts to improve the crop. Plant diseases are one of the underlying causes in the decrease in the number of quantity and quality of the farming crops. Recognition of diseases from the plant images is an active research topic which makes use of machine learning (ML) approaches. A novel deep neural network (DNN) classification model is proposed for the identification of paddy leaf disease using plant image data. Classification errors were minimized by optimizing weights and biases in the DNN… More >

  • Open Access

    ARTICLE

    A Novel Forgery Detection in Image Frames of the Videos Using Enhanced Convolutional Neural Network in Face Images

    S. Velliangiri1,*, J. Premalatha2

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 625-645, 2020, DOI:10.32604/cmes.2020.010869 - 12 October 2020

    Abstract Different devices in the recent era generated a vast amount of digital video. Generally, it has been seen in recent years that people are forging the video to use it as proof of evidence in the court of justice. Many kinds of researches on forensic detection have been presented, and it provides less accuracy. This paper proposed a novel forgery detection technique in image frames of the videos using enhanced Convolutional Neural Network (CNN). In the initial stage, the input video is taken as of the dataset and then converts the videos into image frames. More >

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