With the rapid development of modern AI painting, Chinese university fine arts education is facing numerous challenges and opportunities. This paper analyzes the impact of modern AI painting on traditional art creation and its implications for student skill development. Additionally, it explores the key areas where Chinese university fine arts education needs to transform, including curriculum, teaching methods, and teacher training, while proposing corresponding strategies.

Tourism is one of the important sectors that support Indonesia’s economic growth. The tourism sector itself plays a strategic role in increasing the country’s foreign exchange. However, during the Covid-19 pandemic, tourism became one of the most affected sectors. Electronic visa on arrival (e-VOA) is a form of digital transformation in immigration services offered by the Indonesian government to increase the number of tourist arrivals during the recovery of the national economy, especially in the tourism sector, after the Covid-19 pandemic. This study provides an in-depth insight into how e-VOA functions as a digital transformation tool in the immigration and tourism sectors. By exploring the impact of e-VOA implementation, this article contributes to the understanding of how digitalisation can improve the efficiency of administrative processes and support the recovery of the tourism sector in post-pandemic Bali. This study uses qualitative approaches and methods with descriptive analysis techniques to create an objective description of a situation through numbers or statistical data. The results of this study show that e-VOA services effectively contribute to an increase in the number of foreign tourists in Bali. It also has a positive impact on the economic growth of tourism-related businesses in Bali.

The economy of Pakistan has faced many challenges due to COVID-19, leading to numerous systemic failures and leaving it struggling to recover. This research aims to shed light on the specific challenges faced by Pakistani textile companies during the pandemic. Comprehensive data was collected from one hundred fifty-three textile managers in Pakistan. Upon examining the impact of COVID-19 on businesses, it has been found that the most pressing issues revolved around working capital and strategies for generating new sales. Interestingly, many of these businesses were well-prepared in the digital realm, readily embracing digital knowledge and seizing opportunities by pivoting to the production of personal protective equipment (PPE) and N95 masks. This study aims to evaluate the early consequences of COVID-19 on Pakistan’s textile industry. Considering the scarcity of research on these challenges and opportunities, our work contributes to a better understanding of the hurdles the textile sector faces. Furthermore, it sets the groundwork for future research in this domain. It provides valuable insights for textile businesses, enabling them to align their strategies with the ever-evolving digital marketing landscape.

This paper provides a comprehensive review of SURF (speeded up robust features) feature descriptor, commonly used technique for image feature extraction. The SURF algorithm has obtained significant popularity because to its robustness, efficiency, and invariance to various image transformations. In this paper, an in-depth analysis of the underlying principles of SURF, its key components, and its use in computer vision tasks such as object recognition, image matching, and 3D reconstruction are proposed. Furthermore, we discuss recent advancements and variations of the SURF algorithm and compare it with other popular feature descriptors. Through this review, the aim is to provide a clear understanding of the SURF feature descriptor and its significance in the area of computer vision.

Increasing number of smart cities, the rise of technology and urban population engagement in urban management, and the scarcity of open data for evaluating sustainable urban development determines the necessity of developing new sustainability assessment approaches. This study uses passive crowdsourcing together with the adapted SULPiTER (Sustainable Urban Logistics Planning to Enhance Regional freight transport) methodology to assess the sustainable development of smart cities. The proposed methodology considers economic, environmental, social, transport, communication factors and residents’ satisfaction with the urban environment. The SULPiTER relies on experts in selection of relevant factors and determining their contribution to the value of a sustainability indicator. We propose an alternative approach based on automated data gathering and processing. To implement it, we build an information service around a formal knowledge base that accumulates alternative workflows for estimation of indicators and allows for automatic comparison of alternatives and aggregation of their results. A system architecture was proposed and implemented with the Astana Opinion Mining service as its part that can be adjusted to collect opinions in various impact areas. The findings hold value for early identification of problems, and increasing planning and policies efficiency in sustainable urban development.

Today’s automation of the audit process increasingly relies on electronic auditing, especially computer-assisted audit techniques (CAATs), and has become a global necessity. Therefore, this study aims to explore the influence of technological, organizational, and environmental (TOE) factors on audit firms’ adoption of CAATs in developing countries, focusing on Ethiopia. The research employed a quantitative approach and gathered 113 valid responses from certified external auditors in Ethiopian audit firms. The data was then analyzed through the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The findings show that relative advantage and compatibility are the significant technological attributes influencing CAAT adoption in Ethiopian audit firms. Besides, auditors’ information technology (IT) competency was a significant organizational attribute influencing CAAT adoption. Environmental attributes such as the complexity of the client’s accounting information system (AIS) and the professional body support significantly impact the adoption of CAATs. Additionally, the size of an audit firm reduces the impact of clients’ AIS complexity on the adoption of CAATs in Ethiopian audit firms. The findings underscore the significance of CAAT adoption in audit firms and offer valuable insights for policymakers and standard setters in crafting legislation for the Ethiopian audit industry. This study represents the first scholarly effort to provide evidence of CAAT adoption in audit firms in developing countries like Ethiopia.