This study conducts a comparative analysis of various machine learning and deep learning models for predicting order quantities in supply chain tiers. The models employed include XGBoost, Random Forest, CNN-BiLSTM, Linear Regression, Support Vector Regression (SVR), K-Nearest Neighbors (KNN), Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), Bidirectional LSTM (BiLSTM), Bidirectional GRU (BiGRU), Conv1D-BiLSTM, Attention-LSTM, Transformer, and LSTM-CNN hybrid models. Experimental results show that the XGBoost, Random Forest, CNN-BiLSTM, and MLP models exhibit superior predictive performance. In particular, the XGBoost model demonstrates the best results across all performance metrics, attributed to its effective learning of complex data patterns and variable interactions. Although the KNN model also shows perfect predictions with zero error values, this indicates a need for further review of data processing procedures or model validation methods. Conversely, the BiLSTM, BiGRU, and Transformer models exhibit relatively lower performance. Models with moderate performance include Linear Regression, RNN, Conv1D-BiLSTM, Attention-LSTM, and the LSTM-CNN hybrid model, all displaying relatively higher errors and lower coefficients of determination (R²). As a result, tree-based models (XGBoost, Random Forest) and certain deep learning models like CNN-BiLSTM are found to be effective for predicting order quantities in supply chain tiers. In contrast, RNN-based models (BiLSTM, BiGRU) and the Transformer show relatively lower predictive power. Based on these results, we suggest that tree-based models and CNN-based deep learning models should be prioritized when selecting predictive models in practical applications.

The quest for quality postgraduate research productivity through education is on the increase. However, in the context of the African society, governance structures and policies seem to be impacting on the quality level of the provided education. Hence, this conceptual study explored the roles of governance structures and policies in enhancing and ensuring quality postgraduate education programmers in African institutions of higher learning. To this end, various relevant literature was reviewed. The findings showed amongst others that governance structures and policies affect the quality of education provided. Meanwhile, other factors such as curriculum, foreign influence, lack of resources, training, amongst others contribute to the quality of education provided. The study concludes that there is need for the current structures of governance and the designed and implemented policies for postgraduate education to be reviewed and adjusted towards ensuring the desired transformation.

This inquiry endeavors to meticulously examine the intricate dynamics of the symbiotic developmental interplay among the gaming, tourism, and economic sectors in Macau. Utilizing the methodology of deviation standardization, the data undergoes scrupulous processing, invoking the entropy method to ascertain the weights of diverse evaluative indices. The developmental trajectories of Macau’s gaming, tourism, and economic domains spanning the years 2011 to 2021 are fastidiously gauged. Subsequently, a sophisticated coupled coordination model is employed to delve into the nuanced systemic interdependencies characterizing their developmental relationships. From 2011 to 2021, the holistic progression of Macao’s gaming and tourism sectors has exhibited a discernible ascent over the temporal continuum. Concurrently, the degree of coupling coordination has advanced from a state of near coordination to a commendable level of synchronized development. The overarching system of Macau’s gaming and tourism industries has transitioned from a state of disarray to one of ordered harmony, with the correlative impact of Macau’s tourism sector being adeptly realized. The supporting role played by Macau’s gaming industry in fortifying the tourism sector is conspicuously manifest. The alignment and coordination between Macau’s gaming and tourism sectors exhibit fluctuations across distinct developmental stages. During phases of nascent development in both the gaming and tourism domains, a palpable imbalance prevails. Elements such as the proliferation of gaming enterprises, international tourism revenue, aggregate output value of gaming establishments, market share held by gaming enterprises, and the profit margins thereof have, to a certain extent, impinged upon the harmonized evolution of the tripartite subsystems. This study proffers recommendations to foster the optimization and elevation of the industrial structure while championing the integration and advancement of diverse sectors. It advocates for the amplification of the propulsive impetus intrinsic to the gaming industry, coupled with the enrichment of the tourism product portfolio. Furthermore, it espouses the establishment of an effective mechanism for high-quality development, tailored to the exigencies of the contemporary era. This involves the implementation of precise policies, the facilitation of amalgamated progress in gaming and tourism, and an unwavering commitment to sustainable development through the interconnected alignment of gaming, tourism, and the broader economy. The findings of this study furnish a scientific foundation for the strategic industrial planning and developmental initiatives undertaken by relevant departments in Macau.

Given the issues of urban-rural educational inequality and difficulties for children from poor families to succeed, this study explores the impact mechanism of internet usage on rural educational investment in China within the context of the digital divide. Using data from the 2019 China Household Finance Survey (CHFS), this study analyzed the educational investment decisions of 2064 rural households. Results indicate that in the Eastern region, a high level of educational investment is primarily influenced by the per capita income of the family, with social capital and internet usage also playing supportive roles. In the Northeastern region, the key factor is the diversity of internet usage, specifically using both a smartphone and a computer. In the Central region, factors such as the diversity of internet usage, subjective risk attitudes, the appropriate age of the household head, and per capita income of the family contribute to higher levels of educational investment. In the Western region, the dominant factors are the diversity of internet usage, subjective usage and per capita income of the family. These factors enhance expected returns on the high level of educational investment and boost farmers’ confidence. High internet usage rates significantly promote diverse and stable educational investment decisions, providing evidence for policymakers to bridge the urban-rural education gap.

This study examines innovative teaching approaches’ effect on the quality of education for prospective primary teachers. A mixed-methods approach combining qualitative and quantitative data collection techniques was employed. Initially, the two data sets were analyzed separately—qualitative data through thematic analysis and quantitative data through statistical methods. The themes emerging from the qualitative analysis were then cross-referenced with the quantitative findings to evaluate whether the trends supported each other. For instance, if a qualitative theme indicated that teachers felt more confident using innovative methods, this was supported by quantitative data showing improvements in teacher performance scores or student outcomes. The study had 200 participants, and the study findings revealed a significant positive impact of innovative teaching approaches on the quality of education for future primary teachers. Participants reported increased engagement, improved critical thinking, and enhanced adaptability in classroom settings. The study findings reveal that innovative approaches significantly improve the quality of education for prospective primary teachers by fostering more interactive, technology-enhanced, and student-centered learning environments. To maintain these improvements, it is essential to invest in infrastructure, provide ongoing support for teacher educators, and continuously update curricula to reflect emerging educational technologies and practices. These findings emphasize the importance of innovation in teacher training to meet the evolving demands of primary education.