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  • Open Access


    Women Entrepreneurship Index Prediction Model with Automated Statistical Analysis

    V. Saikumari*, V. Sunitha

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1797-1810, 2023, DOI:10.32604/iasc.2023.034038

    Abstract Recently, gender equality and women’s entrepreneurship have gained considerable attention in global economic development. Prior to the design of any policy interventions to increase women’s entrepreneurship, it is significant to comprehend the factors motivating women to become entrepreneurs. The non-understanding of the factors can result in the endurance of low living standards and the design of expensive and ineffectual policies. But female involvement in entrepreneurship becomes higher in developing economies compared to developed economies. Women Entrepreneurship Index (WEI) plays a vital role in determining the factors that enable the flourishment of high potential female entrepreneurs which enhances economic welfare and… More >

  • Open Access


    Big Data Analytics with Artificial Intelligence Enabled Environmental Air Pollution Monitoring Framework

    Manar Ahmed Hamza1,*, Hadil Shaiba2, Radwa Marzouk3, Ahmad Alhindi4, Mashael M. Asiri5, Ishfaq Yaseen1, Abdelwahed Motwakel1, Mohammed Rizwanullah1

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3235-3250, 2022, DOI:10.32604/cmc.2022.029604

    Abstract Environmental sustainability is the rate of renewable resource harvesting, pollution control, and non-renewable resource exhaustion. Air pollution is a significant issue confronted by the environment particularly by highly populated countries like India. Due to increased population, the number of vehicles also continues to increase. Each vehicle has its individual emission rate; however, the issue arises when the emission rate crosses the standard value and the quality of the air gets degraded. Owing to the technological advances in machine learning (ML), it is possible to develop prediction approaches to monitor and control pollution using real time data. With the development of… More >

  • Open Access


    Securing Privacy Using Optimization and Statistical Models in Cognitive Radio Networks

    R. Neelaveni1,*, B. Sridevi2, J. Sivasankari3

    Computer Systems Science and Engineering, Vol.42, No.2, pp. 523-533, 2022, DOI:10.32604/csse.2022.021433

    Abstract Cognitive Radio Networks (CRN) are the possible and ideal solution for meeting the spectrum needs of next-generation communication systems. CRN is a promising alternative approach that allows spectrum sharing in many applications. The licensed users considered Primary Users (PU) and unlicensed users as Secondary Users (SU). Time and power consumption on security issues are considered degrading factors in performance for improving the Quality of Service (QoS). Irrespective of using different optimization techniques, the same methodology is to be updated for the task. So that, learning and optimization go hand in hand. It ensures the security in CRN, risk factors in… More >

  • Open Access


    Statistical models for evaluating the genotype-environment interaction in maize (Zea mays L.)

    Kandus1 M, D Almorza3, R Boggio Ronceros2, JC Salerno1

    Phyton-International Journal of Experimental Botany, Vol.79, pp. 39-46, 2010, DOI:10.32604/phyton.2010.79.039

    Abstract Our objective was to determine the genotype-environment interaction (GxE) in a hybrid integrated by maize lines either carrying or not balanced lethal systems. Experiments were conducted in three locations over a period of two years considering each yearlocation combination as a different environment. Yield data were analysed using the Additive Main Effects and Multiplicative Interaction (AMMI) model and the Sites Regression Analysis (SREG). Results were represented by biplots. The AMMI analysis was the best model for determining the interaction. More >

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