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  • Open Access

    ARTICLE

    An Artificial Neural Network-Based Model for Effective Software Development Effort Estimation

    Junaid Rashid1, Sumera Kanwal2, Muhammad Wasif Nisar2, Jungeun Kim1,*, Amir Hussain3

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1309-1324, 2023, DOI:10.32604/csse.2023.026018 - 15 June 2022

    Abstract In project management, effective cost estimation is one of the most crucial activities to efficiently manage resources by predicting the required cost to fulfill a given task. However, finding the best estimation results in software development is challenging. Thus, accurate estimation of software development efforts is always a concern for many companies. In this paper, we proposed a novel software development effort estimation model based both on constructive cost model II (COCOMO II) and the artificial neural network (ANN). An artificial neural network enhances the COCOMO model, and the value of the baseline effort constant More >

  • Open Access

    ARTICLE

    Combined Signal Processing Based Techniques and Feed Forward Neural Networks for Pathological Voice Detection and Classification

    T. Jayasree1,*, S.Emerald Shia2

    Sound & Vibration, Vol.55, No.2, pp. 141-161, 2021, DOI:10.32604/sv.2021.011734 - 21 April 2021

    Abstract This paper presents the pathological voice detection and classification techniques using signal processing based methodologies and Feed Forward Neural Networks (FFNN). The important pathological voices such as Autism Spectrum Disorder (ASD) and Down Syndrome (DS) are considered for analysis. These pathological voices are known to manifest in different ways in the speech of children and adults. Therefore, it is possible to discriminate ASD and DS children from normal ones using the acoustic features extracted from the speech of these subjects. The important attributes hidden in the pathological voices are extracted by applying different signal processing More >

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