Exploring the Determinants of Artificial Intelligence (AI) Literacy: Digital Divide,Computational Thinking,Cognitive Absorption

To effectively utilize artificial intelligence (AI)-based technologies such as ChatGPT and realize their novel ethical issues, individuals must have a variety of knowledge and skills about AI. Such knowledge and skills have led to the emergence of AI literacy. Despite the importance of AI literacy in everyday life, little is known about its determinants. To better understand the determinants of AI literacy, we attempted to build a research model relying on previous research and different theoretical frameworks. The model incorporated digital divide, cognitive absorption, and computational thinking. As a major finding from the current study, computational thinking was found to be a significant determinant of AI literacy, which facilitate using, recognizing, and evaluating AI-based technologies. Moreover, we found out that individuals with physical access to information and communication technologies (ICTs) are more expected to use and recognize AI. Also, motivation and skills in using ICTs enable individuals to better evaluate the outcomes of AI-based technologies. The findings also showed that convenient access to ICTs contributes to a deep involvement with AI-based technologies in the use. Further, individuals with higher motivation and skills to use AI technologies are likely to have a pleasant experience after using these technologies.     

Effects of bottom profile on the circulation and classification of particles in cylindrical hydrocyclones

The cylindrical hydrocyclone has been increasingly used in coarse classification due to its reduced fine particle entrainment, but the loss of coarse particles to overflow remains an intractable problem. Based on the notion that the strong circulation flow caused by the flat bottom structure bears primary responsibility for the problem, this study designs eight unique bottom profiles to regulate the particle circulating flow and attempts to correlate particle circulation flow with classification performance. The effects of the bottom profile on flow field characteristics, particle spatial distribution, circulation flow rates, and grade efficiency are explored in detail using validated models in a Φ200 mm cylindrical hydrocyclone. The findings suggest that bottom profiles have the greatest effect on the axial velocity near the bottom and the grade efficiency of intermediate and coarse particles, while all unique designs have the potential to lower turbulence intensity. An ascending segment near the wall or a descending segment near the axis can help to mitigate the misplacement of coarse particles by reducing particle circulation flow without affecting the entrainment of fines appreciably. Additionally, two circles are found on each side of the cut plane, which is conducive to releasing coarse particles from the circulation flow. Regulation of particle circulation flow by adjusting bottom profile parameters can improve separation performance.     

普通本科院校信息与计算科学专业实习实训方案设计

分析当前普通高校信息与计算科学专业学生实习实训模式存在的主要问题,并针对这些问题提出一些解决方案;探讨适合学生实习实训要求的企业实训模式,以安庆师范学院信息与计算科学专业学生实习实训模式为例,对学生实习实训的计划和实施过程进行了阐述。实践表明,新的实训模式能够使学生取得良好的实习实训效果。     

量子计算智能导论教学探索

随着智能信息处理技术的飞速发展,越来越多的学生对量子计算智能导论这门课产生了浓厚的兴趣。我们结合教学实践,将该门课程的教学内容划分为理论型和实践型,注重理论与实际应用相结合,以具体实例引导教学,从而加深学生对理论的理解,进而培养学生的实践能力和科研兴趣。本文介绍了这种教学方法。     

Parameterized complexity of control problems in Maximin election

Elections are a central model in a variety of areas. This paper studies parameterized computational complexity of five control problems in the Maximin election. We obtain the following results: constructive control by adding candidates is W[2]-hard with respect to the parameter “number of added candidates”; both constructive and destructive control by adding/deleting voters are W[1]-hard with respect to the parameter “number of added/deleted voters”.     

A modified Guruswami-Sudan algorithm for decoding Reed-Solomon codes

We tighten a key estimate, which dictates the computational complexity of Guruswami-Sudan algorithm, on the lower bound of the degrees of freedom, and then propose a modified decoding algorithm for Reed-Solomon codes beyond half the minimum distance. The computational complexity of the modified algorithm is lower than the Guruswami-Sudan algorithm for the medium to high rate Reed-Solomon codes, and has the same asymptotic complexity as the algorithm proposed by Wu. Besides we also claim that our modified algorithm outperforms Wu's algorithm to some extent.     

小学校园建筑设计和小学校园VI设计的一致性

完整的导入小学VI不仅为学校提炼并凸显人无我有的校本特色,达到对内凝聚人心、激发活力,对外吸引公众视线、业超同行,同时也可以从视觉、行为、理念上队少年儿童起到良好的引导作用。与小学VI统一的校园建筑设计可以更好的从视觉上展现校园视觉形象的完整性,使学生能够产生更好的自豪感和归属感,使社会和家长产生更多的信任感。为此,有针对地对小学校园VI设计和小学校园建筑设计的一致性研究就更显重要。     

Three dimensional numerical simulations of long-span bridge aerodynamics, using block-iterative coupling and DES

The design of long-span bridges often depends on wind tunnel testing of sectional or full aeroelastic models. Some progress has been made to find a computational alternative to replace these physical tests. In this paper, an innovative computational fluid dynamics (CFD) method is presented, where the fluid-structure interaction (FSI) is solved through a self-developed code combined with an ANSYS-CFX solver. Then an improved CFD method based on block-iterative coupling is also proposed. This method can be readily used for two dimensional (2D) and three dimensional (3D) structure modelling. Detached-Eddy simulation for 3D viscous turbulent incompressible flow is applied to the 3D numerical analysis of bridge deck sections. Firstly, 2D numerical simulations of a thin airfoil demonstrate the accuracy of the present CFD method. Secondly, numerical simulations of a U-shape beam with both 2D and 3D modelling are conducted. The comparisons of aerodynamic force coefficients thus obtained with wind tunnel test results well meet the prediction that 3D CFD simulations are more accurate than 2D CFD simulations. Thirdly, 2D and 3D CFD simulations are performed for two generic bridge deck sections to produce their aerodynamic force coefficients and flutter derivatives. The computed values agree well with the available computational and wind tunnel test results. Once again, this demonstrates the accuracy of the proposed 3D CFD simulations. Finally, the 3D based wake flow vision is captured, which shows another advantage of 3D CFD simulations. All the simulation results demonstrate that the proposed 3D CFD method has good accuracy and significant benefits for aerodynamic analysis and computational FSI studies of long-span bridges and other slender structures.     

On the effect of wind direction and urban surroundings on natural ventilation of a large semi-enclosed stadium

Natural ventilation of buildings refers to the replacement of indoor air with outdoor air due to pressure differences caused by wind and/or buoyancy. It is often expressed in terms of the air change rate per hour (ACH). The pressure differences created by the wind depend - among others - on the wind speed, the wind direction, the configuration of surrounding buildings and the surrounding topography. Computational Fluid Dynamics (CFD) has been used extensively in natural ventilation research. However, most CFD studies were performed for only a limited number of wind directions and/or without considering the urban surroundings. This paper presents isothermal CFD simulations of coupled urban wind flow and indoor natural ventilation to assess the influence of wind direction and urban surroundings on the ACH of a large semi-enclosed stadium. Simulations are performed for eight wind directions and for a computational model with and without the surrounding buildings. CFD solution verification is conducted by performing a grid-sensitivity analysis. CFD validation is performed with on-site wind velocity measurements. The simulated differences in ACH between wind directions can go up to 75% (without surrounding buildings) and 152% (with surrounding buildings). Furthermore, comparing the simulations with and without surrounding buildings showed that neglecting the surroundings can lead to overestimations of the ACH with up to 96%.     

Topology‐based Smoothing of 2D Scalar Fields with C1‐Continuity

Data sets coming from simulations or sampling of real‐world phenomena often contain noise that hinders their processing and analysis. Automatic filtering and denoising can be challenging: when the nature of the noise is unknown, it is difficult to distinguish between noise and actual data features; in addition, the filtering process itself may introduce “artificial” features into the data set that were not originally present. In this paper, we propose a smoothing method for 2D scalar fields that gives the user explicit control over the data features. We define features as critical points of the given scalar function, and the topological structure they induce (i.e., the Morse‐Smale complex). Feature significance is rated according to topological persistence. Our method allows filtering out spurious features that arise due to noise by means of topological simplification, providing the user with a simple interface that defines the significance threshold, coupled with immediate visual feedback of the remaining data features. In contrast to previous work, our smoothing method guarantees a C¹‐continuous output scalar field with the exact specified features and topological structures.