Discourse Construction of Ideological and Political Education in Colleges and Universities under Multidisciplinary Discourse Theory

The discourse construction of ideological and political education in colleges and universities is an important task to strengthen the leadership and discourse power of ideological work in colleges and universities. The relevant theories of western multidisciplinary discourse research provide rich theoretical reference for the discourse construction of ideological and political education in colleges and universities. Based on linguistics, sociology, political science, philosophy and other disciplines, ideological and political education in colleges and universities should reasonably absorb its theoretical achievements on the sociality, power, democracy and authenticity of discourse, providing theoretical and practical references for the construction of ideological and political education discourse in colleges and universities in terms of content, power, expression and value

Least squares-based iterative identification methods for linear-in-parameters systems using the decomposition technique

By extending the least squares-based iterative (LSI) method, this paper presents a decomposition-based LSI (D-LSI) algorithm for identifying linear-in-parameters systems and an interval-varying D-LSI algorithm for handling the identification problems of missing-data systems. The basic idea is to apply the hierarchical identification principle to decompose the original system into two fictitious sub-systems and then to derive new iterative algorithms to estimate the parameters of each sub-system. Compared with the LSI algorithm and the interval-varying LSI algorithm, the decomposition-based iterative algorithms have less computational load. The numerical simulation results demonstrate that the proposed algorithms work quite well

Belief rule-base expert system with multilayer tree structure for complex problems modeling

Belief rule-base (BRB) expert system is one of recognized and fast-growing approaches in the areas of complex problems modeling. However, the conventional BRB has to suffer from the combinatorial explosion problem since the number of rules in BRB expands exponentially with the number of attributes in complex problems, although many alternative techniques have been looked at with the purpose of downsizing BRB. Motivated by this challenge, in this paper, multilayer tree structure (MTS) is introduced for the first time to define hierarchical BRB, also known as MTS-BRB. MTS- BRB is able to overcome the combinatorial explosion problem of the conventional BRB. Thereafter, the additional modeling, inferencing, and learning procedures are proposed to create a self-organized MTS-BRB expert system. To demonstrate the development process and benefits of the MTS-BRB expert system, case studies including benchmark classification datasets and research and development (R&D) project risk assessment have been done. The comparative results showed that, in terms of modelling effectiveness and/or prediction accuracy, MTS-BRB expert system surpasses various existing, as well as traditional fuzzy system-related and machine learning-related methodologie

Pore-scale fluid flow simulation coupling lattice Boltzmann method and pore network model

The lattice Boltzmann method and pore network model are two types of the most popular pore-scale fluid flow simulation methods. As a direct numerical simulation method, lattice Boltzmann method simulates fluid flow directly in the realistic porous structures, characterized by high computational accuracy but low efficiency. On the contrary, pore network model simulates fluid flow in simplified regular pore networks of the real porous media, which is more computationally efficient, but fails to capture the detailed pore structures and flow processes. In past few years, significant efforts have been devoted to couple lattice Boltzmann method and pore network model to simulate fluid flow in porous media, aiming to combine the accuracy of lattice Boltzmann method and efficiency of pore network model. In this mini-review, the recent advances in pore-scale fluid flow simulation methods coupling lattice Boltzmann method and pore network model are summarized, in terms of single-phase flow, quasi-static two-phase drainage flow and dynamic two-phase flow in porous media, demonstrating that coupling the lattice Boltzmann method and pore network model offers a promising and effective approach for addressing the up-scaling problem of flow in porous media.Cited as: Zhao, J., Liu, Y., Qin, F., Fei, L. Pore-scale fluid flow simulation coupling lattice Boltzmann method and pore network model. Capillarity, 2023, 7(3): 41-46. https://doi.org/10.46690/capi.2023.06.0