The study’s goal is to evaluate how microfinance initiatives affect women’s empowerment in Bangladesh. For this study, we analyzed data on a variety of women’s empowerment-related issues, including both beneficial and detrimental elements that stand in the way of women’s empowerment. Therefore, in order to accomplish the specified goal, we choose a suitable and intentional methodology. We employ diverse data gathering approaches to examine the gathered data and achieve the primary goal of the research project. It presents the positive effects of microfinance on women, such as (1) the enhancement of women’s authority in financial affairs; and (2) the augmentation of their ability to make decisions in household; and (3) community matters following their participation in the microfinance program. This also provides an analysis of the data pertaining to the adverse effects of microfinance on women. It examines how women encounter various challenges and engage in unethical behaviors after obtaining a loan, leading to heightened levels of stress following their participation in the microfinance program. This study looks into the advantages and disadvantages of Grameen Bank’s microcredit program for women. A questionnaire gathered primary data for this study from women participating in the microfinance program in Gopalgonj. To collect information and comprehend respondent behavior, I used case study, analytical and descriptive study design. Regression analysis, correlation, and percentage are used to examine the data. The findings indicate that women’s decision-making skills have improved due to their financial stability, but they have also experienced increased life challenges and high levels of stress.

This paper presents a practical approach to empowering software entrepreneurship in Saudi Arabia through a unique course offered by the Software Engineering department at Prince Sultan University. The course, SE495 Emergent Topics in Software Engineering: Software Entrepreneurship, combines software engineering and entrepreneurship to equip students with the necessary skills to develop innovative software solutions that solve real-world problems. The course covers a range of topics, including platform development, market research, and pitching to investors, and features guest speakers from the industry. By the end of the course, students will have gained a deep understanding of the software development process and its intersection with entrepreneurship and will be able to develop a working prototype of a software solution that solves a real-world problem. The course’s practical approach ensures that students are well-prepared to navigate the complexities of the digital and software sectors and succeed in an ever-changing business landscape.

Among contemporary computational techniques, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are favoured because of their capacity to tackle non-linear modelling and complex stochastic datasets. Nondeterministic models involve some computational intricacies when deciphering real-life problems but always yield better outcomes. For the first time, this study utilized the ANN and ANFIS models for modelling power generation/electric power output (EPO) from databases generated in a combined cycle power plant (CCPP). The study presents a comparative study between ANNs and ANFIS to estimate the power output generation of a combined cycle power plant in Turkey. The inputs of the ANN and ANFIS models are ambient temperature (AT), ambient pressure (AP), relative humidity (RH), and exhaust vacuum (V), correlated with electric power output. Several models were developed to achieve the best architecture as the number of hidden neurons varied for the ANNs, while the training process was conducted for the ANFIS model. A comparison of the developed hybrid models was completed using statistical criteria such as the coefficient of determination (R²), mean average error (MAE), and average absolute deviation (AAD). The R² of 0.945, MAE of 3.001%, and AAD of 3.722% for the ANN model were compared to those of R² of 0.9499, MAE of 2.843% and AAD of 2.842% for the ANFIS model. Even though both ANN and ANFIS are relevant in estimating and predicting power production, the ANFIS model exhibits higher superiority compared to the ANN model in accurately estimating the EPO of the CCPP located in Turkey and its environment.

This study aims to determine the extent of gender inequality in human resource development in Indonesia against Association of South East Asian Nations (ASEAN). This research using secondary data from various relevant sources. There are five dimensions that and are important for measuring gender equality, namely economic participation, economic opportunities, political empowerment, educational attainment, and health and welfare. The assessment was carried out on Indonesia and other countries in Southeast Asia. The results of the study show that Indonesia has the lowest gender development index (GDI) score compared to the average in ASEAN. Then, gender empowerment measure (GEM) Indonesia increased slowly. The most striking gap is in the income dimension, where men’s income far exceeds women’s income. This happens because women work less than men because women are more traditional in domestic roles in Indonesia, where women are prioritized in managing the household. However, for political indicators, there has been an increase in the number of women in parliament, but the target has not yet reached 30 percent of the total number of women in parliament. This situation shows that there is a reduction in the gender gap in the economy and politics. But the number is still too small, it is necessary to increase the equally distributed equivalent percentage (EDEP) for the Economic Participation Index, Parliamentary Representation Index and Income Index.

This study validates the Intercultural Competence and Inclusion in Education Scale (ICIES), a novel instrument designed to assess students’ perceptions of inclusivity and intercultural competence in multiethnic secondary schools. Using a sample of 276 high school students from Western Romania, the ICIES identified three dimensions: ethnic appreciation and support, intercultural engagement and integration, and school unity and cohesion. Exploratory factor analysis confirmed the scale’s structural validity, while network analysis revealed key interconnections among its components. Findings highlight the critical role of inclusive teaching strategies and school cohesion in fostering intercultural competence. The ICIES provides educators and policymakers with actionable insights for designing interventions that promote empathy, mutual respect, and a sense of belonging in diverse school settings. These results contribute to the development of educational policies aimed at fostering inclusion and addressing the needs of increasingly multicultural classrooms.