Open-source software (OSS) has emerged as a transformative tool whose implementation has the potential to modernise many libraries around the world in the digital age. OSS is a type of software which permits its users to inspect, share, modify, and enhance through its freely accessed source code. The accessibility and openness of the source code permits users to manipulate, change, and improve the way in which a piece of software, program, or application works. OSS solutions therefore provide cost-effective alternatives that enable libraries to enhance their technological infrastructure without being constrained by proprietary systems. Hence, many countries have initiated and formulated policies and legislative frameworks to support the implementation and use of OSS library solutions such as DSpace, Alfresco, and Greenstone. The purpose of the study reported on was to investigate the leveraging of OSS to modernise public libraries in South Africa. Content analysis was adopted as the research methodology for this qualitative study, which was based on a literature review integrating insights from the researchers’ experiences with the use of OSS in libraries The findings of the study reveal that the use of OSS has the potential to modernise public libraries, especially those located outside cities or urban areas. These libraries are often less well equipped with the necessary technology infrastructure to meet the demands of the digital age, such as online books and open access materials. The study culminated in an OSS framework that may be implemented to modernise public libraries. This framework may help public libraries to integrate OSS solutions and further allow users access to digital services.

Online shopping has eliminated the need to visit physical commercial centres. As a result, trips to these centres have shifted from primarily shopping-motives to leisure, companionship, and dining. The shifting in consumer behaviour is implicated in the growing spatial agglomeration of restaurants/cafes within commercial centres in European cities. Conversely, in southern cities, various casual restaurants/cafes also serve as leisure and companionship hubs. However, their spatial patterns are less explained. This article aims to elucidate the spatial pattern of these diverse restaurants/cafes in a typical southern city, Surabaya City. In this study, we employ the term ‘food services’ to encompass the various types of restaurants/cafes found in southern cities. We gather Points of Interest (POIs) data about food services via web scraping on Google Maps, then map out their spatial distribution across 116 spatial units of Surabaya City. Utilising k-means cluster analysis, we classify these 116 spatial units into six distinct clusters based on the composition of food service variants. Our findings show that City Centres and Sub-City Centres are locations for different types of restaurants/cafes. The City Centre is typically a location for fine dining restaurants and cafes, whereas Sub-City Centres are locations for fast casual dining and fast food restaurants. Cafes and fast food restaurants are centralised throughout downtown areas. Casual food service restaurants, such as casual style dining, coffee shops, and food stalls, are dispersed along business, residential zones, and periphery areas without intense domination of any specific variant.

The economy, unemployment, and job creation of South Africa heavily depend on the growth of the agricultural sector. With a growing population of 60 million, there are approximately 4 million small-scale farmers (SSF) number, and about 36,000 commercial farmers which serve South Africa. The agricultural sector in South Africa faces challenges such as climate change, lack of access to infrastructure and training, high labour costs, limited access to modern technology, and resource constraints. Precision agriculture (PA) using AI can address many of these issues for small-scale farmers by improving access to technology, reducing production costs, enhancing skills and training, improving data management, and providing better irrigation infrastructure and transport access. However, there is a dearth of research on the application of precision agriculture using artificial intelligence (AI) by small scale farmers (SSF) in South Africa and Africa at large. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) and Bibliometric analysis guidelines were used to investigate the adoption of precision agriculture and its socio-economic implications for small-scale farmers in South Africa or the systematic literature review (SLR) compared various challenges and the use of PA and AI for small-scale farmers. The incorporation of AI-driven PA offers a significant increase in productivity and efficiency. Through a detailed systematic review of existing literature from inception to date, this study examines 182 articles synthesized from two major databases (Scopus and Web of Science). The systematic review was conducted using the machine learning tool R Studio. The study analyzed the literature review articled identified, challenges, and potential societal impact of AI-driven precision agriculture.

This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context.

Public signs in scenic spots play the role of guidance, instruction and warning, and are of great significance to promote the development of scenic spots. Guang’an District has a strong historical and cultural heritage and the rapid development of tourism, but the English translation of public signs in the scenic spot has become increasingly prominent, mainly including nonstandard translation, spelling errors, logical confusion and grammatical errors. In order to promote the solution of such problems, this paper will analyze the current situation of English translation of public signs in Guang’an scenic spots, and put forward solutions to the problems of English translation of public signs through hiring professional translators, cultural difference training and regional cooperation.

Carbonated soft drinks (CSDs) have long been a mainstay of the beverage business but changing consumer tastes and rising health awareness have necessitated a thorough study of the variables impacting consumer choices. This study intends to explore the complex web of customer preferences, purchasing behaviour, and perceptions related to carbonated soft drinks. This research analyses how numerous variables, including gender, affect these preferences and choices via careful examination. The purpose of thepresent research is to determine the perception of consumer influencing customer choice preferences for the consumption of carbonated soft drinks, influence of gender and the role of advertisement in finalizing the choice. It would be helpful to do further research to better understand how these highlighted variables affect purchasing choices, especially gender-based variances. The important influence of gender on consumer behaviour has been acknowledged. For this study, a structured questionnaire was distributed through online social media to individuals of 12–45 years of age from the period of April–May 2023. For analysis of the data collected, SPSS 22.0 was used. The study has confirmed that consumption of Coca-Cola is higher than any other soft drink in almost the entire country. The factors like youthfulness, tradition, status symbol and level of carbonation have different influences on the buying behavior of male and female consumers.