Social system and strategic entry of women entrepreneur into informal economy in Lagos, Nigeria

Strategic entry of women into entrepreneurial activities and subsequent entrepreneurial development in informal economy within the social system has received little academic attention in spite of the fact that, entrepreneurship development is important to economic growth and decent work. It has also been found to promote quality of life. The focus of this paper is to examine the influence of social system in strategic entry of women into informal economic activities in Nigeria, using Yoruba women textile traders at Balogun market, Lagos State, South-West, Nigeria as a case study. The paper is anchored on Social action theory by Max Weber. The paper utilized only qualitative method of data collection. Eight focus group discussions, and forty In-depth – interviews were used to collect information from the women participants who were purposively chosen. The data reveal that parents, family members, and social friends had great influence in strategic entry of women into textile trading at Balogun market and subsequent development of women entrepreneurial activities. This information is essential towards policy formulation for women entrepreneurial development in informal economy

Gender recognition using local binary pattern and Naive Bayes Classifier

Human face provides important visual information for gender perception. Ability to recognize a particular gender is very important for the purpose of differentiation. Automatic gender classification has many important applications, for example, intelligent user interface, surveillance, identity authentication, access control and human-computer interaction amongst others. Gender recognition is a fundamental task for human beings, as many social functions critically depend on the correct gender perception. Consequently, real-world applications require gender classification on real-life faces, which is much more challenging due to significant appearance variations in unconstrained scenarios. In this study, Local Binary Pattern is used to detect the occurrence of a face in a given image by reading the texture change within the regions of the image, while Naive Bayes Classifier was used for the gender classification. From the results obtained, the gender correlation was 100% and the highest accuracy of the result obtained was 99%.The system can be employed for use in scenarios where real time gender recognition is required.Keywords: Gender, Local Binary Pattern, Naïve Bayes, Recognitio

Bibliometric analysis of contributions to COVID-19 research in Malaysia

Introduction: The advent of COVID-19 has led to an exponential rise in related publications to provide a knowledge driven approach to tame the tide of infection and impact in all spheres. This study gives an insight into COVID-19 research publication pattern in Malaysia using bibliometric analysis. Method: COVID-19 publications on Scopus database between January 1, 2020, and August 26, 2022, were extracted using predetermined search strings. Inclusion and exclusion criteria were set, and data was extracted from the database. Descriptive statistics was used to summarize our findings. Results: A total of 3,553 COVID-19 related papers were retrieved out of global count of 392,613 and 16,466 for Southeast Asia (SEA). This implies that 0.9% and 21.6% is contributed globally and SEA respectively. Indonesia, Malaysia and Singapore are the three top countries with highest research outputs in the region. This may be correlated to high GDP per capita, research and development, and research and development expenditure. Most of the publications are article/original research (n = 2832, 67%). Ministry of Higher education is the top funding sponsor and Universiti Malaya is the highest contributor and the most cited (n = 466, 4920 citations). The majority of publications are from physical sciences (30.3%), but medicine subcategory produced the highest number of papers (1,586). The top journal was International Journal of Environmental and Public Health (n = 96 publications). Most active collaborating country was the United Kingdom and most active author was from Monash University. Conclusion: Malaysian institutions have made profound contributions to COVID-19 research globally and in SEA. However, there is a need for continuous efforts to improve research outputs on the topic