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In order to achieve real-time stable tracking of moving targets and improve the accuracy and success rate of the tracking system, a kernel correlation filtering-based target tracking method with scale adaptation and feature fusion is proposed to address the situation that the traditional kernel correlation filtering algorithm does not track well when the target is obscured or motion blurred. Firstly, in the feature extraction process, color features are added after the original directional gradient histogram features to improve the recognition capability of target features, that is HOG features are fused with CN features, then a scale pyramid is constructed to perform scale estimation to achieve scale adaptation of the target, and finally the model is updated through a multi-peak detection mechanism. Through testing on the OTB2015 dataset, the accuracy and success rate of the algorithm has been further improved, and the algorithm is able to accurately identify targets and track them effectively.

With the rapid advancement of China's urbanization, industrialization, and marketization, and the in-depth implementation of the rural revitalization strategy, the response of the territorial system of human-environment interaction in rural areas is intense, and the agricultural industry has shown a diversified development trend. Sorting and summarizing the existing research on domestic agricultural functions is important for promoting sustainable agricultural development in the new era, accelerating agricultural transformation and upgrading, and comprehensively revitalizing rural areas. Domestic scholars attach great importance to agricultural development and the services that the agricultural industry provides to society. Geographers have used their disciplinary advantages and have gradually integrated multidisciplinary theories and methods to conduct numerous studies on the conceptual connotations, theoretical bases, classification systems, measurements and evaluations, spatiotemporal processes, influencing factors, and optimization paths of agricultural functions. The academic circle has initially formed the geographical research paradigm of "theoretical basis-spatial pattern- evolution process-influence mechanism-optimal regulation." This study reviews the research progress of agricultural function in China from the perspective of geography and draws the following conclusions: 1) Based on the sorting of the definition of agricultural function in China, this paper defines agricultural function as the role or utility of agriculture, that is, the services and responsibilities that the whole agricultural industry chain renders to the whole society at different times and spaces, including providing products, solving employment problems, inheriting culture, maintaining social stability, and providing ecological services. Furthermore, it has comprehensive, cross-sectional, and regional characteristics. 2) The theoretical basis of agricultural function research includes the territorial system of human-environment interaction, agricultural multifunction, agricultural location, and agricultural function stage theories. Geographers can further improve and enrich relevant theories of agricultural functions through continuous research. 3) Considering the contribution and support of agricultural development to regional socioeconomic development and residents' lives, the researchers divided agricultural functions into product supply, economic development, social security, ecological maintenance, cultural leisure, and so on, and the spatial changes and regional characteristics of agricultural functions were further studied using GIS and RS technology and a geographic mathematical model. 4) The development of agricultural functions is affected by regional natural conditions, economic level, science, and technology. Scholars systematically integrate natural, social, economic, and other factors; scientifically diagnose each factor's mode, direction, and intensity of action in different geographical environments; and perform functional zoning and optimization based on the regional geographical environment and main influencing factors, thus promoting the transformation and development of agricultural functions toward specialization and diversification. 5) Based on summarizing the achievements of agricultural function research conducted by domestic scholars, the shortcomings of existing research in fundamental theory, method and data innovation, scale correlation, and multidisciplinary integration are discussed, and the need to improve the theoretical framework system of research in the future to promote multi-factor, multi-scale, and multi-objective systematic research is proposed. In addition, it is necessary to focus on the transforming of agricultural functions, and strengthening the integration of multidisciplinary, big data and new technological means.

Research Findings: The goal of the present study was to examine the moderating role of child effortful control (EC) in the relation between shyness and social-emotional adjustment difficulties among young Chinese children. Participants included 195 children (117 boys, 78 girls, Mage = 4.28 years, SD = 0.31) enrolled in 6 classes attending kindergartens, Shanghai, People's Republic of China. Mothers provided ratings of their children's temperament (shyness, EC) at Time 1, teachers and mothers rated children's social-emotional adjustment at Time 2 (one and a half years later). Results from SPSS PROCESS MACRO revealed several significant interaction effects between shyness and EC in the prediction of outcome variables. Follow-up simple slope analyses indicated that among children with higher levels of EC, shyness was negatively related to mother-reported social-emotional adjustment difficulties, while among children with lower levels of EC, shyness was not associated with mother-reported social-emotional adjustment difficulties. However, among children with lower levels of EC, shyness was positively associated with teacher reported social-emotional adjustment difficulties. In contrast, among children with higher levels of EC, shyness was not associated with teacher-reported social-emotional adjustment difficulties. Practice or Policy: The findings provide evidence to suggest that the combination of shyness and EC may contribute to children's social adjustment, which in turn may promote or attenuate socio-emotional adjustment difficulties.

Research Findings: Parental control is considered to be an important aspect of parenting. However, the meaning and the function of parental control are still controversial, especially when the cultural context is considered. The purpose of the present research was to explore the meaning and the function of parental control in Chinese culture. The participants were 189 preschoolers at age 4 to 5 and their mothers and teachers from Shanghai, China. Mothers were interviewed about the control strategies they utilize when they need to exert control over their children. Information on child surgency, compliance, and aggression was obtained from mothers and teachers. Chinese mothers reported control strategies that were classified into six categories. It was found that coercive behavioral control was most frequently used. Coercive behavioral control was negatively associated with child compliance and positively associated with child aggression. Other forms of control strategies and their links to child compliance and aggression were also examined. The role of child surgency in moderating the effects of maternal control strategies on child compliance and aggression was discussed. Practice or Policy: The present study highlighted the importance of understanding the cultural meaning of parental control.

Artificial intelligence (AI) plays a pivotal role as a technical facilitator in the domain of building energy management. This paper presents the construction of a sophisticated model for building energy management, leveraging data-driven techniques and machine learning methodologies inherent to AI. The model encompasses three integral modules: characterization of building energy consumption, screening for anomalies in energy consumption, and forecasting of energy usage. Characterization is performed through a data analysis approach. At the same time, anomaly detection utilizes a Gaussian mixture model for data mining and modeling, enabling dynamic and precise identification of states of high energy consumption following clustering analysis. Additionally, the model employs cyclic features and DEEM to accurately predict future energy consumption patterns. The efficacy of this robust energy management model was validated through a case study at Hospital A, located in Changsha, Hunan Province, China. Notably, the total energy consumption at this facility witnessed a modest increase of 1.65% in 2023 compared to the previous year, with a projection of a substantial 24.62% rise in 2024. The surgery building, among various functional units of the hospital, was identified as the most energy-intensive, anticipated to utilize 4.03 million kgce in 2024. Furthermore, the disparity between actual electrical energy and oil consumption in 2023 and those forecasted was contained within 8% and 10%, respectively, underscoring the model’s high predictive accuracy.

How to realize the unity of safety, comfort, and economy of building structures has been a hot spot of concern in the field of construction engineering. This paper searches for optimal particles using a hybrid optimization strategy and optimizes the weights of each index in the fitness function into the same interval. Then dynamic inertia weights are used to improve the performance of the algorithm, and an enhanced adaptive particle swarm algorithm is obtained. After selecting the optimization variables for the building design, the objective function and constraints are designed, and the improved particle swarm algorithm is used to solve the optimal design of the intelligent building. The total weight of the target building structure was reduced after optimization, and 47.04% of the building materials were saved. The outer diameter of the steel pipe concrete at the lowest level of the building increases from 1.73m to 2.06m after optimization, which fulfills the law of column change in building design. It has also been found that the wind resistance of the optimized building structure has improved. This paper provides a reliable basis for the application of adaptive algorithms in building design optimization, and the proposed method also provides an effective reference for the field of construction engineering.

Under the background of big data development, students have diverse and multi-level demands for music aesthetic education teaching. This paper studies the implementation strategy of aesthetic education in college music teaching under the threshold of big data, mainly through data analysis, predictive modeling and simulation, multi-faceted analysis, and the design of personalized music teaching intervention. By training DNN model experimental conclusion and analysis, the DNN model in the original set R-squared reached 0.8037, the largest performance among all models, compared to multiple linear regression, in multi-level multi-neuron activation, through the sigmoid activation of each level and linear calculation between levels, in backpropagation to update the weights and bias, trained to be able to more The DNN is finally selected as the best model for music learners’ performance prediction. The DNN is finally selected as the best model for music learners’ performance prediction. The advantages of big data mining music aesthetic education resources are exploited to create an open aesthetic education teaching space for students.