In agriculture, crop yield and quality are critical for global food supply and human survival. Challenges such as plant leaf diseases necessitate a fast, automatic, economical, and accurate method. This paper utilizes deep learning, transfer learning, and specific feature learning modules (CBAM, Inception-ResNet) for their outstanding performance in image processing and classification. The ResNet model, pretrained on ImageNet, serves as the cornerstone, with introduced feature learning modules in our IRCResNet model. Experimental results show our model achieves an average prediction accuracy of 96.8574% on public datasets, thoroughly validating our approach and significantly enhancing plant leaf disease identification.

The evolution of the internet has led to the emergence of social media (SM) platforms, offering dynamic environments for user interaction and content creation. Social media, characterized by user-generated content, has become integral to electronic communication, fostering higher engagement and interaction. This study aims to explore the utilization of SM marketing, particularly in Higher Education Institutions (HEIs), focusing on Széchenyi István University’s academic social network sites (SNS) as a case study to enhance student engagement and satisfaction. The primary objective of this study is to review recent academic literature on SM marketing, especially for HEI marketing, and investigate the potential of the University’s SNS platforms as a case study in increasing student engagement. First a systematic literature review was conducted using Scopus and Science Direct databases to analyze recent research in academic SM. Then the article examined the University’s website and SNS platforms using the Facepager program to collect and analyze posts’ content. The findings from the literature review and observation indicate the growing importance of SM in higher education marketing. The university’s use of various SM strategies, such as visual storytelling, multimedia content, blogs, and user-generated content, contributes to increased student engagement of the university’s values.

With the rapid development of modernization and the reform and development of quality education, the main direction and goal of vocational colleges in the new era is to cultivate high-level skilled talents required by the times. With the development of globalization and the refined division of labor in industrial technology, the requirements of various industries for high-level skilled talents with the ability to adapt to market development are gradually increasing. This article focuses on exploring and analyzing the demand for hospital imaging technology talents under the rapid development of the new era industry, and discovering the problems in talent cultivation in vocational colleges. In response to the existing problems, actively utilizing college resources and practical opportunities, innovating the college school cooperation mode and teaching methods for imaging technology majors in vocational colleges, and gradually expanding into a standardized, scientific, and developable college cooperation mode for vocational education, Implement the national strategic plan for cultivating quality talents in vocational colleges, focus on doing a good job in the work of "cultivating morality and talents", adhere to the "three education" reform, and improve the quality of talent cultivation.

This research was conducted using a survey research method to investigate the influence of Artificial Intelligence (AI) on Nigerian students’ academic performances in tertiary institutions. Nigerian tertiary institutions have an estimated population of about 2.5 million students across the universities, polytechnics, monotechnics, and colleges of education. A sample size of 509 was used. The researchers adopted an online questionnaire (Google Form) to administer questions to respondents across Nigeria to elicit responses from the respondents bordering on their awareness and the use of AI and its attendant impacts on their academic performance. Five research objectives were raised for the proper investigation of this study. From the findings of the study, the researchers found that the majority of Nigerian students use AI and that AI has positive impacts on the educational performance of Nigerian students. It was also found that Nigerian students have training on the use of AI for educational purposes and that they are more familiar with Snapchat AI and ChatGPT. Conclusively, AI is useful to students in the sense that it enhances their knowledge of their courses, improves their learning and speaking skills, and helps them to have a quick understanding of their course by way of simplifying technical aspects of their courses. The researchers therefore recommend as follows: Nigerian tertiary institutions should formally train students as well as teachers on the use of AI for academic purposes so that they can understand the ethical implications of the use of AI. Using AI for writing could be interpreted to mean examination malpractice, and this should not be condoned in the educational sector; however, at the moment, a small number of students used AI for examinations. Albeit, the appropriate use of AI should be fully integrated into Nigerian tertiary institutions’ curricula.

The urgency of adapting urban areas to the increasing impacts of climate change has prompted the scientific community to seek new approaches in partnership with public entities and civil society organizations. In Malaysia, Penang Island has developed a nature-based urban climate adaptation program (PNBCAP) seeking to increase urban resilience, reduce urban heat and flooding, strengthening social resilience, and build institutional capacity. The project includes a strong knowledge transfer component focused on encouraging other cities in the country to develop and implement adaptation policies, projects, and initiatives. This research develops a model adopting the most efficient processes to accelerate the transfer of knowledge to promote urban adaptation based on the PNBCAP. The methodology is developed based on a review of literature focused on innovation systems and change theories. The integration of success strategies in adaptation contributes to informing the creation of solutions around the alliance of local, state, and national government agencies, scientific institutions, and civil society organizations, in a new framework designated the Malaysian Adaptation Sharing Hub (MASH). MASH is structured in 3-steps and will function as an accelerator for the implementation of urban climate adaptation policies, with the target of creating 2 new adaptation-related policies to be adopted annually by each city member, based on knowledge gathered in the PNBCAP. It is concluded that, to speed up urban adaptation, it is necessary to reinforce and promote the sharing of knowledge resulting from or associated with pilot projects.