Accurate knowledge point sequences and clear learning paths are the compass for learners to travel in the sea of massive knowledge, they can point out the way for learners and improve their learning experience. Generating knowledge point sequences and learning paths based on knowledge reasoning is conductive to optimizing the allocation of educational resources and improving the quality of higher education, and this has a profound influence on the reform of the entire educational field. In view of this, this study explored the generation of knowledge point sequences and the recommendation of learning paths based on knowledge reasoning. At first, the learning behavior of learners was subjected to collaborative analysis based on three aspects of knowledge points: learning frequency, learning duration, and pause/ skip frequency, and the specific method of generating subject knowledge point sequences based on the metrics of difficulty differences was given. Then, a sequence sampling method that matches the features of Entity-Relationship (ER) diagram was proposed, which enables the system to dynamically adjust the recommended knowledge points and learning paths according to learners’ learning progress with the help of biased random walks, thereby giving personalized and dynamic learning recommendations. At last, the validity of the proposed method was verified by experimental results.
The construction industry is a pillar industry of Chinese national economy, but also one of the industries with high accident rates. This paper analyzed Chinese construction industry in recent years, production safety situation, which indicated that the building production safety accidents and deaths continued to decline, construction safety production and the overall situation was getting better and better. After management analysis of safety production in construction industry, strengthening the government functions, truly serving people oriented from government to business, and enhancing the safety culture were real solutions of construction management.
As the urgency of global climate change mitigation accelerates, green integrated-energy systems have emerged as essential components of sustainable energy solutions. The thermal subsystem, responsible for heating and cooling functions, serves as a pivotal element, with its steady-state characteristics exerting a significant influence on the overall system's performance and efficiency. Current methodologies for steady-state analysis, however, are often characterized by inaccuracies and oversights, primarily due to model simplification and the disregard of critical parameters. Moreover, these techniques demonstrate deficiencies when handling intricate interactions or non-linear relationships. This research introduces an innovative approach for examining the steady-state characteristics of the thermal subsystem, addressing the limitations inherent in existing methods. Initially, comprehensive mathematical models were constructed for each unit within the thermal subsystem-heat pumps, boilers, and chillers-incorporating numerous physical processes and parameters to enhance model fidelity. Following this, the steadystate power of the thermal subsystem was assessed to ascertain performance and efficiency under various operational conditions. Subsequent to this evaluation, an analysis of the interaction between the thermal subsystem and the primary system was conducted, estimating the thermal subsystem's impact on the overarching system. Through this multifaceted examination, a more precise and holistic understanding of the thermal subsystem's steady-state characteristics was gleaned, offering valuable insights for the optimization of integrated-energy system design and operation. These findings not only have the potential to augment energy efficiency and environmental sustainability, fostering the advancement and application of green technologies, but also offer a significant resource for engineers, scientists, policy makers, and other stakeholders for the informed design, optimization, and policy formulation of thermal subsystems.
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