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Sports characteristics and physiological signals serve as critical benchmarks for analyzing athletic performance and enhancing training methodologies. This study explores the design and development of an advanced smart wearable device system tailored for monitoring sports training. This system is engineered to track athletic performance in real-time by integrating embedded wearable devices with sophisticated software. It primarily encompasses the recognition of human movement states, detection of electrocardiogram (ECG) signals, and monitoring of respiratory signals, thereby facilitating comprehensive analysis of human physiological parameters and movement metrics. This, in turn, supports athletes in optimizing their training routines. Empirical results from the study indicate that the mean-square error for both ECG and respiratory signals recorded during testing approximated ±0.8Hz, falling within the predetermined error tolerance range. Additionally, analyses of joint angle variations during running activities confirmed the efficacy of the proposed smart wearable system in improving sports performance.

This study explores the application of extensive data analysis to library information resources, focusing on enhancing the efficiency of resource utilization and user satisfaction through personalized recommendation services. We employ cluster analysis algorithms, and least squares support vector machines to model library users’ borrowing behaviors. Additionally, we use the Apriori algorithm and collaborative filtering to recommend books effectively. This study’s experimental outcomes show a notable 11.36% increase in the index of network resource demand satisfaction, indicating a significant enhancement in the library’s ability to meet resource update demands. The adoption of big data analytics has been instrumental in advancing library information management and expanding extensive data services. The findings underscore the pivotal role of big data in enhancing the efficiency of information resource utilization and elevating user satisfaction, mainly through personalized recommendations.

This paper discusses the implementation and application of MATLAB tools in the teaching of engineering majors so as to improve the quality of education and students’ mathematical application ability. Using the programming and GUI graphical interface design functions of MATLAB, the method of establishing the graphical user interface of the mathematical experiment module closely links the experimental content with the practical teaching of mathematical modeling. With the help of the operation functions provided by the system, we can set the experiment parameters and design the experiment interface ourselves to deepen our intuitive understanding of the mathematical content learned. After the pilot teaching in the mechanism major of University Z, 22 individuals failed to reach course objective 1, and 40 individuals were unable to reach course objective 2. The number of individuals passing the three lab reports increased continuously, from 40 to 57 in Class 1 and from 34 to 56 in Class 2. The math scores in the three exams improved significantly, and the distribution of the scores went from concentrating on scores below 60 to focusing on scores between 70–89. As a result, the teaching method for MATLAB tools application was effective.

Face orientation recognition is a crucial component of human behavior analysis. Challenges such as face occlusion and varying lighting conditions frequently degrade recognition accuracy. This study introduces an innovative approach using the Kinect sensor’s skeleton tracking technology to capture face orientation images across different lighting scenarios. To enhance image quality, techniques such as light attenuation and compensation are applied. Furthermore, multiple feature vectors based on face orientation are extracted and fused, followed by the optimization of the Extreme Learning Machine (ELM) model through the Archimedean Optimization Algorithm (AOA). The developed AOA-ELM model for face orientation recognition is compared with traditional models, including Back Propagation (BP), Radial Basis Function (RBF), standard ELM, and Genetic Algorithm enhanced ELM (GA-ELM). The AOA-ELM model exhibits superior performance in estimating face orientation amidst lighting disturbances, achieving an accuracy exceeding 95% in varied lighting conditions, thereby outperforming other classification models.

Based on the geometry and structural concepts of calligraphy, this paper comprehensively considers the optimization of character structure and geometric lines and realizes the optimization of the echo relationship between strokes so as to obtain the design of Chinese characters that meet the aesthetic requirements of calligraphy. Based on the quantitative statistics of 3650 character components “structure body” and structural data, we summarize the finer structural guidance for design teaching. Using the calligraphy layout optimization method to optimize the calligraphy and its artistic design, the visual effect of the beautified Chinese characters can be observed. The findings indicate that the graphical design of Chinese character calligraphy is entirely based on geometric transformation. In the statistical analysis of the geometric structures of 3650 Chinese character calligraphy, there are 3391 types of geometric structures. The growth rate of the number of types gradually slows down when the structure depiction reaches the 4th layer. Therefore, the structure depiction should be divided into 8 layers, which can make the design teaching more refined. The optimized beautification degree of the logo design of a brand in the wine industry and the logo of the emblem of a sports meeting is more beautiful and aesthetically pleasing. Therefore, the method of this paper can achieve the beautification effect.

In order to understand the online international dissemination of Chinese culture through online games, this paper constructs a computational model of cultural dissemination based on a hypergraph. The model constructs a network topology based on hypergraph theory, divides the states of individuals spreading Chinese cultural information in online social networks, and calculates the transfer probability of individual states based on the rules of cultural information spreading. The analysis of the algorithms reveals that the maximum infection ratio of the model in this paper decreases slowly, and the coverage rate of immune nodes reaches 0.9, indicating good stability and adaptation performance. The model accurately simulates the process of Chinese culture diffusion in the Minecraft community. The mean value of the evaluation of the six entries on learning motivation and attitude is 3.73 points, which indicates that the use of Minecraft helps improve students’ motivation for learning about Chinese culture.

College English reading instruction represents a crucial component in enhancing students’ overall linguistic competencies. The advent of cognitive psychology has facilitated the application of the SOLO categorization theory as a novel approach to augmenting students’ proficiency in English reading. This study devises a teaching model tailored to college English reading based on the SOLO categorization theory and implements a systematic research design to evaluate its effectiveness. The efficacy of this model is assessed by comparing the changes in English reading learning attitudes, scores, and capabilities between an experimental group and a control group, using pre-and post-test results. The findings indicate that the mean difference in the English reading learning attitudes between the two groups expanded from 0.09 at the pre-test stage to 0.54 at the post-test stage. Moreover, the experimental group exhibited a substantially greater increase in English reading scores, with an improvement of 14.16, compared to 3.68 in the control group. In terms of English reading abilities, the experimental group outperformed the control group across four dimensions, with increases of 2.86, 1.04, 1.76, and 3.28, respectively. Overall, the university English reading teaching model grounded in SOLO classification theory significantly enhances students’ attitudes towards English reading and effectively boosts their reading achievements and capabilities.

The computer-aided writing system first builds an English writing corpus, which mainly includes several aspects such as corpus selection, corpus preprocessing, formula algorithm design, sentence breaking, and judging whether the sentences are aligned or not. Anchor alignment cannot perform a job alone; it must work in conjunction with named entity recognition technology to study the connection and role between the two. Jieba participle utilizes the idea of the HMM model, which is researched and calculated by the Viterbi algorithm, to recognize new words outside the dictionary. A computer-assisted writing system is introduced into English language teaching to promote conscious and deep student participation, activate classroom teaching, and improve learning effectiveness. The results showed that there was also a significant correlation between text length and English writing ability (P=0.003) and on T-units and English writing ability (P=0.001). Statistical significance was reached for all three indicators of text length (P=0.001), T-units (P=0.001), and English writing proficiency (P=0.002) between groups of high and low subgroups. The vocabulary recommendation function usage record revealed that each student used it 6.21 times on average and had a liking for it 4.32 times on average. 20 students agreed that the system was helpful for their writing. The two groups of students’ writing scores differed significantly (0.001) from their respective pre-test scores. The computerized writing instruction system was more helpful for the student’s performance.

The lever method facilitates a straightforward analysis of the motion dynamics of an automatic transmission under various gear settings, offering a simple and intuitive approach to examining planetary gear transmissions. Specifically, the equivalent lever diagram for a parallel-double planetary gear transmission comprises four component points. From a control perspective, a transmission system with two planetary rows can accommodate up to two reduction gears, one direct gear, one overdrive gear, and one reverse gear. In contrast, the equivalent lever diagram for a parallel three-planetary gear transmission includes five component points, with such systems typically supporting up to three reduction gears, one direct gear, two overdrive gears, and two reverse gears. This methodological approach underscores the lever diagram’s utility in delineating the functional capabilities of complex transmission systems.

On the turbocharger, two forms of intake pipe, bending and torsion, are usually used, which leads to a vortex at the inlet of the blade. It has been found that double vortices and massive vortices play a significant role in the working characteristics of the compressor. This project intends to conduct a systematic theoretical and experimental study on the effects of vortex deformation under two different working conditions of bending and torsion on the internal flow field, tip leakage flow field, and impeller load of the impeller. It has been found that the presence of a vortex near the blade entrance changes the static pressure and inflow angle near the blade entrance. The reverse transfer of vortex flow and vortex flow caused by vortex has three critical effects on the working characteristics of the compressor: 1. The change of circumferential static pressure and the pressure gradient of the flow in the impeller. 2. The location and density of the leakage flow on the top surface are significantly changed. 3. Adjust the impeller load’s change and fluctuation when it rotates.