Competency-based education is one of the many important educational objectives in the cultivation of senior vocational talents. In the past education model, the importance of achievement is greater than ability. Teachers rely on the scores of test papers to classify students' grades. Competency-based education has changed this situation very well, paying special attention to students' ability training. This paper mainly studies how to better promote the reform and innovation of English teaching in higher vocational colleges and strengthen students' learning ability and vocational skills while ensuring students' ability development.

Our previous research on social innovation examined the process, levels, and stakeholders of social innovation, as well as its relationship with technical and technological innovation. The present study analyzes the spatial image created by the social innovation potential and investigates its relationship with the economic power of the neighborhoods. The most important conclusion of the study is that the basic territorial inequality dimensions are the same in the case of both the social innovation potential and the district’s economic strength. The difference is primarily to be found in concentration, as economic power is much more concentrated in the capital and the most important economic and tourism centers than the social innovation potential. We can therefore state that developments based on social innovation can solve a lot of the highly concentrated spatial structure in Hungary.

Managing business development related to the innovation of intelligent supply chains is an important task for many companies in the modern world. The study of management mechanisms, their content and interrelations of elements contributes to the optimization of business processes and improvement of efficiency. This article examines the experience of China in the context of the implementation of intelligent supply chains. The study uses the methods of thematic search and systematic literature review. The purpose of the article is to analyze current views on intelligent supply chain management and identify effective business management practices in this area. The analysis included publications devoted to various aspects of supply chain management, innovation, and the implementation of digital technologies. The main findings of the article are as follows: Firstly, the key elements of intelligent supply chain management mechanisms are identified, secondly, successful experiences are summarized and the main challenges that companies face in their implementation are identified. In addition, the article focuses on the gaps in research related to the analysis of successful experiences and the reasons for achieving them.

This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.

Transit-oriented development is a concept that focuses on developing areas in and around transit nodes to create added value. The concept concentrates on integrating mass public transport networks with non-motorized modes of transport, minimizing the usage of motorized vehicles, and fostering the growth of dense, mixed-use areas with medium to high spatial intensity. This research examines the effects of altering the business model to create Transit Oriented Development (TOD) in Jakarta, contrasting it with PT Moda Raya Transports (PT MRT). We collected data by conducting in-depth interviews with experts and distributing questionnaires to seven respondents who work at this We used the Business Model Canvas (BMC) to identify business models and the internal resources needed for the implementation process. process. Therefore, six elements in BMC were used to conduct changes, and based on the results, RBV analysis was pe PT MRT needs to enhance its internal power to a competitive advantage level in order to effectively manage changes. We need to conduct further research on how the business model can influence the creation of transit-oriented development areas.