درخت حوزه‌های تخصصی

In this paper, we have extended our literature survey with experimental implementation. Analyzing numerous Artificial Intelligence (AI) techniques in software engineering (SE) can help understand the field better; the outcomes will be more effective when used with it. Our manuscript shows various AI-based algorithms that include Machine learning techniques (ML), Artificial Neural Networks (ANN), Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN), Natural Language Processing (NLP), Genetic Algorithms (GA) applications. Software testing using Ant Colony Optimization (ACO) approach, predicting software maintainability with Group Method of Data Handling (GMDH), Probabilistic Neural Network (PNN), and Software production with time series analysis technique. Furthermore, data is the fuel for AI-based model testing and validation techniques. We have also used NASA dataset promise repository in our script. There are various applications of AI in SE, and we have experimentally demonstrated one among them, i.e., software defect prediction using AI-based techniques. Moreover, the expected future trends have also been mentioned; these are some significant contributions to the research

Agriculture is one of the essential sources of occupation and revenue in India. Conferring to existing statistics, most agriculturalists are facing severe losses due to poor farming yield. Farming activities are challenged by various environmental factors that affect agricultural productivity to a greater extent. The present farming situation is above the average of the process involves more biochemical bases for managing the diseases and other destructing facts. The foremost problems they are facing in day-to-day farming tasks are crop or plant diseases affecting productivity. Also, the growth of weeds along with field crops has been another challenge.  The technology has developed to rectify the problems using some machine learning algorithms like Random Forest algorithms, Decision trees, Naïve Bayes, KNN, K-Means clustering, Support vector machines. The result has been evaluated and observed through the performance evaluation metrics using confusion matrix, accuracy, precision, Sensitivity, specificity with the observations, research, and studies. The statistics have expressed the overall accuracy of 98% by achieving the detection of diseases in plants and by removing the weeds that ruin the growth of plants.

INTRODUCTION: Women's empowerment has been introduced as a mechanism to improve the quality of women's work and personal life, one of the basic principles of protecting human rights and eradicating poverty. This study aimed to investigate the effect of social capital, social support, and Internet use on the empowerment of working women with a mediating role in socioeconomic status. METHODS: In this descriptive survey study, 4,000 women were studied working in the RCS of Tehran province, Iran. About 384 samples were selected due to Cochran's formula by a simple random method. The required data were collected using some questionnaires, namely the Social Capital (Hoff and Heisman, 2009), subjective assessment of the socioeconomic status (Nabavi et al., 2007), Social Support (Sherburne and Stewart, 1991), the researcher-made questionnaire of Internet Use and Women’s Empowerment. FINDINGS: The results showed that social capital, social support, and the use of the Internet had a direct impact on the empowerment of women, and socioeconomic status played a mediating role in the relationship between social capital and empowerment. It was also found that socioeconomic status played a mediating role in the relationship between social support and the empowerment of working women. CONCLUSION: According to the results, attention to the components of social capital, social support, and the use of the Internet and cyberspace provided the basis for the empowerment of working women, while in this process the key role of women's socioeconomic status should not be overlooked. However, managers' attention to strengthening organizational trust and women's participation in decision-making, providing conditions for good communication, training, and promoting women's media literacy, would increase the socioeconomic status proportionately and improve women's empowerment.