This study examines the relationship between career aspiration and career adaptability, and focuses on the mediating effect of coping efficacy. A total of 377 students of higher vocational education were measured using the career aspiration scale, the coping efficacy scale and the career adaptability scale, and the study showed these results. (1) There were significant differences in career aspiration in terms of whether they are student leaders , coping efficacy in terms of whether they were student leaders, and career adaptability in terms of whether they were student leaders, whether they are the only child of their parents，whether they have received career counseling, and whether they participated in parttime jobs, internships or social practices. And there were also significant differences in career aspiration and career adaptability in terms of the interaction of gender and whether they have received career counseling. (2) Career aspiration and its three dimensions were positively correlated with coping efficacy and coping efficacy was also positively with career adaptability and its four dimensions. (3)career aspiration was a significant direct positive predictor of career adaptability. When the mediating variable coping efficacy was included, career aspiration could still significantly predict career adaptability, coping efficacy mediated the relationship between career aspiration and career adaptability. Career education can enhance career adaptability of students in higher vocational education by improving their coping efficacy.

Ammonia synthesis is vital for fertilizer production, but the traditional Haber-Bosch process is energyintensive and environmentally burdensome due to its high-temperature and high-pressure operations. Plasma-catalytic ammonia synthesis offers a sustainable alternative, generating large datasets under various experimental conditions. To optimize energy efficiency, we established a database with 305 data points and 7 experimental parameters, each linked to its corresponding energy efficiency. We employed an Extreme Gradient Boosting (XGBoost) regression tree model, achieving an average R² value of 0.9434 for predictions. Bayesian Optimization (BO), using Gaussian Process Regression as a surrogate model, systematically explored the experimental parameter space. It utilized XGBoost predictions to identify parameter combinations that maximized energy efficiency. After 50 iterations, the optimal parameters were identified: 6.4 g catalyst mass, 50 mm grounding electrode length, nickel metal catalyst, Al₂O₃ catalyst support, 5 W power, 160 ml·min⁻¹ flow rate, and a 1:2 feed ratio. Under these conditions, the energy efficiency of plasma-catalytic ammonia synthesis improved to 1.49 g·kW·h⁻¹, a 22.1% increase from the highest value of 1.22 g·kW·h⁻¹ in the dataset.

With the gradual improvement of the resilience and vitality of the tourism market, promoting the high quality development of the tourism industry with the new development concept has become an important fundamental issue for the sustainable growth of the regional green economy. The article measures and analyzes the level of high-quality development of Guizhou’s tourism industry from 2012 to 2021 on the basis of constructing an evaluation index system for high-quality development of tourism, using methods such as entropy value method and gray correlation analysis. The results found that: the average value of the development index of Guizhou’s tourism high-quality development subsystem is ranked in the order of GD, ED, ID, SD, OD and CD, the level of green development and effective development of Guizhou’s tourism industry is higher, while the level of coordinated development of the tourism industry and the level of openness are insufficient; HQD, ID, GD, OD, SD and ED show a fluctuating upward trend, while CD is in a fluctuating downward state, and the tourism high-quality development system of Guizhou has gone through a fluctuating upward trend. Guizhou tourism high-quality development system has experienced three stages of evolution, namely, “stable rise, rapid rise and fluctuating rise”, and the level of Guizhou tourism high-quality development and the development level of its various sub-systems have been affected by the New Crown Epidemic to varying degrees, with a greater impact on the level of open development of the tourism industry. GDP, per capita park green space area and tourism high-quality development index correlation is larger, while the total amount of SO2 emission and tourism high-quality development index correlation ranked at the bottom, tourism industry R & D funding is the most important factor affecting the level of high-quality development of Guizhou’s tourism industry, and the total amount of SO2 emission has the smallest impact on it. On this basis, countermeasures for the high-quality development of Guizhou’s tourism industry are proposed.

In this paper, the vibration characteristics of the helical cylindrical gear split-torque transmission system with diaphragm coupling misalignment are studied. Firstly, the 14-DOF nonlinear simulation model of the helical cylindrical gear split-torque transmission system are established. To improve the model accuracy, time-varying mesh stiffness, random backlash, mesh error and bending deformation of shaft are considered respectively. Secondly, according to the nonlinear simulation model, the differential equations are established, and the differential equations are sovled with the time-varying stiffness of diaphragm coupling misalignment. Finally, the relationship between the phase of bolt group in diaphragm coupling and the asymmetric property of the split-torque transmission system is determined by numerical methods. The results show that the asymmetric property of split-torque transmission system could be effectively improved by changing the phase of bolt group in diaphragm coupling. The method is proven effectiveness by a modification work involved in this paper, and have reference significance for solving engineering problems.

Due to the complexity of genome structure and technical conditions, wheat genome structure variation has not yet been comprehensively and accurately detected and evaluated for genetic effects. The aim of this study is to construct a method based on deep learning algorithm to accurately detect genomic structure variation in wheat. The method converts genomic data into image form by genomic structure variation image generation algorithm. A gene structure variation prediction model is constructed based on deep learning, and efficient and accurate structure variation prediction is realized by automatically extracting and analyzing the variation features in the image. The experimental results show that this method has better detection performance than other structural variation detection methods based on third-generation sequencing data, especially in the structural variation detection of the “Sequencing and Assembly of Spring Wheat Genome in China” project, and the accuracy, precision, and recall rate of this method are all over 90%. This study provides a novel deep learning framework for efficiently detecting structural variants in the wheat genome, and provides powerful technical support for genetic improvement and breeding research of wheat.

This paper analyzes and evaluates high school examination questions based on machine learning. The study first introduces Bloom’s classification method and constructs a categorized dataset of high school exam questions according to three steps of data collection, data annotation and data analysis. Then an automatic assessment model (WoBERT-CNN) based on WoBERT and Text-CNN is designed. The semantic similarity of word vector mapping is used to label the cases for determination, the improved WoBERT encoder is used to represent the text in word vectors, Text-CNN is used as a text classifier to extract the textual semantic features, and the features are integrated and screened, so as to realize the automatic classification of the cases in Bloom’s taxonomy. Finally, based on the deep representation framework, the text information of the test questions is deeply mined and utilized to establish the relationship between the text of the test questions and the actual difficulty, and to realize the difficulty prediction of the test questions.The classification accuracy of the WoBERT-CNN model reaches more than 92%.The prediction error range of the H-MIDP model on the score rate of the test questions is between 1.3% and 3.2%, which is not too far from the real value. In conclusion, the automatic assessment model and difficulty prediction model designed in this paper can be applied in the analysis and evaluation of high school test questions, helping the high school test paper proposition and talent cultivation strategy.

Aiming at the limitations of the sample weight updating mechanism of the traditional Adaboost algorithm, the article proposes three improved algorithms based on the joint weight updating mechanism to solve the problems of sample distribution imbalance, etc. The MW_UA algorithm is centered on the updating of the proportion of the sample weight, the OW_UA algorithm realizes the updating of the weight of the sample set based on the classification effect of the initial samples, the MAR_UA algorithm employs sample The MAR_UA algorithm uses the sample Margin to quantify the degree of difficulty of sample classification and then obtain the corresponding sample weights. The performance test experiments and prediction simulation experiments of the improved algorithm are based on the MWSP and Caltech datasets. The experimental results show that the average accuracy and F1 score of MAR_UA algorithm in the two datasets are over 90%, which is the best performance among all the improved algorithms. The algorithm also shows optimal prediction error convergence performance in both datasets, and the training error can be converged to the minimum within 40 times of training. When the algorithm is applied to the simulation experiment of pedestrian recognition, it has the best recognition effect in the sunny environment, with a detection rate of 94.1%. In addition, the error between its predicted and real values of offshore wind speed is no more than 0.2 m/s, and the ERMS and EMA are reduced by 63.52% and 55.5%, respectively, compared with the traditional Adaboost. This study optimizes the weight updating mechanism of the joint Adaboost algorithm using various methods, which can provide new ideas for the optimization research of the weight updating mechanism.

With the maturity of digital display technology, its application scope is also more and more extensive, and there are more and more application cases in the protection and inheritance of minority hand-weaving skills. This paper builds a general framework for the design of the digital inheritance system for the handloom weaving techniques of the Miao family in southern Sichuan, and applies three-dimensional modeling technology, three-dimensional animation technology, digital imaging technology and interactive interface design to complete the preliminary establishment of the digital display system for the handloom weaving techniques of the Miao people in southern Sichuan. Combined with the information dissemination characteristics of mobile intelligent terminals, relevant improvement programs are proposed. At the same time, the optimization and improvement of the digital display system is further improved to meet the needs of users. Comparing the users’ experience and perception of the digital display system, the system designed in this paper is superior to R-Space in terms of functional scope and technology, and the average score of the system designed in this paper is 4.193, which is higher than the score of 3.985 of the R-Space system, and the system designed in this paper has a higher score. At the same time, the user’s satisfaction with the system’s interactivity is more stable in the three aspects of login start, system home page, and Chuannan humanities resources. In the login start, the scores of very satisfied, more satisfied, and general are 2, 3, and 2.5 respectively, which indicates that the user’s experience of this paper’s system is better.

With the purpose of exploring the mechanism of change in Chinese relational clauses, this paper firstly includes transitive verbs, intransitive verbs and adjectives in the study of relational clauses, and carries out a comparative analysis from the perspectives of syntactic form, semantic expression, and distribution of thesis elements, and finds that relational clauses constituted by transitive verbs are indeed the most typical members of Chinese relational clauses. Then, we examine its performance in the type of relativization, main clause syntactic position of core words, vitality pattern, and structural features, and conclude that the argument elements of the relational clauses present a vitality contrast pattern and have a simpler structure with an average of about 4 syllables, while the distribution of the central words of the Chinese relational clauses conforms to the order of the noun-dominant syntactic position. Finally, ERP technology is used to explore the processing advantages of subject-relative clauses and to regulate the vitality and denotation of the verbal thesis elements of the clauses, and it is found that the difference in processing difficulty between subject and object-relative clauses increases when the subject of the clauses is a vital noun and the object is a non-vital noun.

The field of urban scene image segmentation is a crucial task in the field of computer vision. Aiming at the problems of large parameter count and insufficient image segmentation accuracy of the traditional DeepLabV3+ model, an improved lightweight DeepLabV3+ model is designed. The overall performance of the model is improved by replacing the Xception backbone network with MobileNetV2, introducing the band pooling module and the densely connected null pyramid module in ASPP, and using the GD-FAM multi-feature fusion module in the fusion stage. Using Cityscapes as the dataset, the model experiment results show that compared with the traditional Deeplabv3+ model, this paper’s method increases the target category IoUs of urban scenes such as pedestrians, cyclists, and columns by 3.1%, 4.41%, and 6.74%, respectively. Therefore, the segmentation effect of the model in this paper is significantly better than the segmentation effect of other models. The mIoU of the MobileNetV2 backbone network is 4.91% higher than the baseline model. The loss function change curve of the model shows that it tends to converge after 100 iterations. In summary, the overall segmentation performance of the improved model is significantly improved.