Reviewerly/exHarmony huggingface dataset:
Training Simulation System of Aviation Electromechanical Specialty Based on Multimodal Information Processing

Traditional training simulation system has the problems of low recognition accuracy and long response time because of its poor perception effect on learning dynamic target. Therefore, this study designed a practical training simulation system based on multi-modal information processing for aviation electromechanical specialty. In the hardware part, the RS422 interface circuit is used to transmit the working state of the board, and the loopback clock circuit is used to transmit the signals of the multi-board. In the software part, after the component model library of the training simulation system is established, the learning object perception model is established through multi-modal information processing, and the multi-modal teaching information is integrated. Finally, a professional training simulation teaching module is designed to meet the various needs of training teaching. In the experiment, the system presented in this paper is compared with two traditional systems, and it is found that the system presented in this paper can effectively improve the recognition accuracy of gesture rules and speech keywords, and effectively shorten the time for the system to process user requests.
Extraction Method of Emotional Elements of Online Learning Text Information Based on Natural Language Processing Technology

The current methods of extracting emotional elements of text information generally adopt the principle of template matching, the algorithm is complex. Due to the limitations of the selected template, the network learning text information emotion elements cannot be comprehensively extracted, so the extraction accuracy and efficiency are low. In order to solve the above problems, this paper studies the emotional element extraction method of online learning text information based on natural language processing technology. Preprocess the online learning text information and find new words; Split the preprocessed text into sentences to generate transaction items; Frequent noun items are mined by association rules, irrelevant nouns are filtered by filtering algorithm, and the emotional elements of text information are extracted; Using the credibility analysis algorithm to judge the emotional polarity of text, and using the RNN neural network algorithm in natural language processing technology, the emotional elements of online learning text information are extracted. The test data show that the extraction time of the proposed feature extraction method is reduced by at least 35%, and the extraction accuracy of the method is improved to 80%, and the extraction result is more reliable.
Online Teaching Method of Biochemistry Course of Nursing Specialty Based on Association Rules

The content of biochemistry course of nursing specialty is relatively abstract, which is difficult for students to understand and has low learning enthusiasm. In order to improve students’ learning enthusiasm and improve the overall teaching effect, an online teaching method of biochemistry course of nursing specialty based on association rules was studied. The problems existing in online teaching are summarized and analyzed. Based on the existing problems and on the basis of in-depth understanding of data mining theory, association rules algorithm is applied to online learning behavior analysis, online examination score analysis, teaching resource recommendation and teaching quality evaluation to mine the hidden and useful knowledge in teaching data and realize the effective combination of teaching and learning in online teaching. The test results show that under the application of this method, the accuracy of course recommendation is maintained at about 80%, which improves the overall teaching effect.
Image Watermark Removal Method of Classroom Teaching Recording and Broadcasting System Based on Deep Learning

In order to improve the image watermark efficiency of the classroom teaching recording and broadcasting system, a method for removing the image watermark of the classroom teaching recording and broadcasting system was designed based on deep learning. For image denoising and correction processing, use the color palette to adjust the processing color to obtain the image correction effect; use the median value of all pixels around the neighborhood pixels to replace the pixel value of the current pixel point to perform image filtering processing; then the classroom teaching recording and broadcasting system Image detail similarity calculation, according to the calculation results to characterize the details of the image spatial structure information, and realize the image watermark removal of the classroom teaching recording and broadcasting system through deep learning. The research shows that the method designed this time can improve the accuracy of watermark removal and reduce the removal time.
Simulation Analysis of Entrepreneurial Behavior Selection Mechanism of Higher Vocational College Students Based on Teaching Big Data

In order to make higher vocational students’ entrepreneurial behavior selection mechanism more comprehensive and reduce the proportion of noise in the data, a higher vocational college students’ entrepreneurial behavior selection mechanism is designed. Obtain the talent training objectives of higher vocational colleges, strengthen the training of entrepreneurial skills, identify the characteristics of entrepreneurial decision-making, extract the constituent elements of students’ entrepreneurial behavior by using teaching big data, obtain other required entrepreneurial resources through specific channels, and build a selection mechanism. Experimental results: the average proportion of noise data in the entrepreneurial behavior selection mechanism of Higher Vocational College Students in this paper is 5.397%. After integrating the teaching big data, the entrepreneurial behavior selection mechanism of higher vocational college students is more comprehensive and reduces the proportion of noise.
Intelligent Statistical Method of Accounting Information Teaching Data Based on SVM

Aiming at the problem of poor data fitting results caused by large sample loss in the classification of intelligent statistical method of accounting information teaching data, an intelligent statistical method of accounting information teaching data based on SVM is proposed. Because the distribution of accounting information teaching data is seriously unbalanced, an unbalanced processing mechanism is established to improve the ability of data recognition. Design multiple binary SVM models, synthesize the accounting information teaching data label results predicted by multiple binary SVM based on the fusion strategy, build an intelligent statistical model, and finally output the statistical results of the classification status of the data label. Chi square goodness of fit test and K-S test are carried out for the intelligent statistical method. The results show that the data goodness of fit of the intelligent statistical method of accounting information teaching data based on SVM is higher than that based on latent variable model and weighted distance, so it has better data quality.
Online Training System of Distribution Network Equipment Operation and Maintenance Security Based on Cloud Model

Electricity demand is more and more big, the distribution of power distribution network equipment is becoming more and more complex, and the need for operational safety training, and the safety of the traditional functions of the system of online training modules are not comprehensive, unable to meet the demand of the current operational safety training, so based on cloud model to design new equipment operational safety online training system, the hardware part of the design of the ARM processor and FPGA chip, In the software part, the online training module of operation and maintenance safety is established, the online training database is designed based on the cloud model, and the online training of distribution network equipment operation and maintenance safety is realized, and the system test is carried out. The results show that the designed online training system of distribution network equipment operation and maintenance safety has good performance and certain application value.
Mobile Terminal-Based Remote Counseling Education System for Middle School Students’ Mental Health

Mental health education is conducive to the improvement of personality, so college students’ mental health education has gradually received attention, and it is necessary to comprehensively consider optimizing students’ psychological quality and improving students’ mental health level. The traditional mental health distance counseling education system has gradually been unable to meet the current teaching needs, so based on the mobile terminal, a new mental health distance counseling education system for middle school students is designed. The hardware part designs the time counter and storage, and the software part designs the mental health distance counseling education framework first. Secondly, based on the mobile terminal, a distance counseling education model for middle school students’ mental health is constructed. Finally, a functional module of mental health remote counseling is designed, and an auxiliary teaching database is designed. The system test results show that the designed mental health distance counseling education system has good performance, can achieve efficient distance education, and has certain application value. The system can be used as a reference for follow-up mental health distance counseling education.
Real-Time Tracking Method of Students’ Targets in Wushu Distance Teaching Based on Deep Learning

The development of information technology has promoted the development of distance education, and Wushu teaching has gradually changed from traditional face-to-face teaching to distance education. In order to improve the teaching effect, it is necessary to track the teaching objects in real time. In order to improve the real-time tracking of students’ goals in Wushu distance learning, a real-time tracking method of Wushu distance learning goals based on deep learning is designed. The experimental results show that the designed real-time tracking method has a short tracking delay, which proves its effectiveness.
Teaching and Training System of Power Grid Monitoring Technology Based on Multimodal Information Processing

In view of the poor teaching function and operation performance of the existing power grid monitoring technology course training system, the optimal design of the power grid monitoring technology course teaching training system is realized by using multi-modal information processing technology from three aspects of hardware, database and software functions. Firstly, adjust the operation mode of the system server, refit the curriculum teaching information collector, system communication network architecture, embedded processor, memory and other hardware equipment, and use the optimization circuit to realize the connection of hardware equipment. Then set the unified storage mode of data, and build the system database combined with the logical relationship between data. Based on this, a virtual training scene of power grid monitoring technology course teaching is constructed, in which the implementation process of power grid monitoring technology is simulated, and the course resources are retrieved by using multimodal information processing technology. Experiments show that compared with the traditional system, the functional operation success rate and throughput of the system in this paper are higher.
Multimodal Information Processing Method of College English Course Online Education System

In order to process the information in the online education system more efficiently, this study designs a multi-modal information processing method for the online education system of college English courses. This study mainly deals with video information, image text information and audio information in the system. Firstly, based on structured processing, the video data stream is divided into organic whole with certain logical structure, and the visual feature information and visual invariant feature are extracted. The multi-branch convolutional neural network is designed and the text features are extracted. Convolutional neural network is used to extract audio features from the system. Finally, a functional model of multi-modal information fusion is designed to realize the fusion processing of multi-modal information. Experimental results show that this method has high data fusion efficiency and timeliness.
Effect Evaluation of Online Basic Japanese Lessons Based on Data Mining Algorithm

Aiming at the problem of inaccurate evaluation of traditional Japanese teaching ability, an online education effect evaluation algorithm of basic Japanese course based on data mining algorithm is proposed. Using data mining algorithm to collect the online education content of basic Japanese course; Establish the constraint parameter index, optimize the evaluation algorithm, improve the quality of teaching evaluation, and achieve the goal of Japanese teaching ability evaluation. Finally, experiments show that the online education effect evaluation of basic Japanese course based on data mining algorithm has good evaluation ability, and improves the accuracy and efficiency of teaching ability evaluation.
Construction of Multimedia Online Education Platform Based on Fuzzy Neural Network

The current multimedia online education platform has low resource utilization and response rate. In order to effectively solve this problem, this paper will study the construction of multimedia online education platform based on fuzzy neural network. The hardware framework of online education platform is built with FPGA as the control core, and the platform resources are mined and processed by fuzzy neural network. Use cloud computing to design platform resource scheduling and improve platform operation efficiency. Through experiments, it is verified that the recommendation accuracy of the platform is higher than 90%, the response rate and processing speed of the platform are significantly improved, and the practical application effect is better.
Design of Tibetan Vocabulary Online Learning System Based on Multi-terminal Integration

Provide auxiliary tools for Tibetan vocabulary learning, and solve the problems of long response time and poor application performance of existing online learning systems. Using the multi-terminal fusion technology, the optimized design of the Tibetan vocabulary online learning system is realized from the three aspects of hardware, database and software functions. Adjust the connection mode of the server, and modify hardware devices such as embedded processors and resource collectors. Use the optimized system circuit to connect hardware devices to complete the optimization of the hardware system. Collect Tibetan vocabulary online learning resource data, and connect each database table according to the logical relationship between the data. With the support of hardware devices and databases, set permissions for different users and choose the online learning mode of Tibetan vocabulary. Use multi-terminal fusion technology to achieve resource integration. Realize system functions such as Tibetan vocabulary learning information retrieval, online interactive practice, and online testing. Through system testing, it is found that the operating success rate of the designed system reaches 99.2%, and the response time is less than 6000ms. And through the application of the design system, the students’ Tibetan language scores have been significantly improved.
Design and Implementation of Mobile Intelligent Education System Based on Cloud Architecture

Because there are many intelligent education features, and the current mobile intelligent education system uses relatively backward education feature extraction technology, the extracted education features are fuzzy, resulting in excessive CPU utilization during the operation of the system. In order to solve this problem, a mobile intelligent education system based on cloud architecture is designed. Hardware part: adopt the active serial FPGA configuration method, load the program that controls the FPGA chip; Software part: use mobile internet technology to identify the type of mobile learning, optimize the traditional format, obtain intelligent education features under the support of cloud architecture, and calculate service resources. The distance to the user’s location is used to build a course resource management model and improve the intelligence of the education system. The experimental results show that the average CPU occupancy rates of the designed system and the other two systems are 20.169%, 30.087%, and 29.987%, respectively, indicating that the performance of the mobile intelligent education system integrated with the cloud architecture is better.
Construction of Teaching Quality Evaluation Model of Hotel Management Specialty Based on Association Rules

In order to solve the problem of low evaluation accuracy and efficiency in the existing teaching quality evaluation methods, this paper proposes and constructs a new teaching quality evaluation model of hotel management specialty based on association rules. Set SERVQUAL Association evaluation objective, design two-way evaluation structure, and establish G1 internal association weight evaluation system. On this basis, the entropy method is used to complete the construction of the related teaching quality evaluation model. The final model test results show that: compared with the initial teaching evaluation model, the evaluation accuracy of the teaching quality evaluation model under the association rules designed in this paper is higher, indicating that it has practical application value and social significance.
Research on Online Mathematics Teaching Resource Integration Model Based on Deep Neural Network

Improving the quality of resource integration is one of the effective ways to improve the utilization of teaching resources. Therefore, aiming at the online mathematics course, this research uses the deep neural network as the basic means to carry out a new design of the teaching resource integration model. First, the overall design is carried out, including the model architecture, resource data transmission mode, data management mode, model function design and cloud platform configuration. Then, using the elastic computing technology in the field of deep neural network technology, based on the collection of relevant resources, the cloud storage and management of resources are implemented with the mathematics course courseware as the core and the extensible software as the support. Finally, in the deep neural network, the dynamically expandable and virtualized storage resources are used to provide the storage and access services of teaching resources, and the integration effect is improved by classifying the resource categories when uploading resources. Compared with the traditional model, the results show that the characteristics of this model are more prominent, and the application advantages in accuracy and resource reading speed are obvious.
Data Optimization Query Method of Online Education System Based on Decision Tree

The traditional online education system data query method has the problem of unclear track data type, which leads to a long query time. To solve this problem, this study designs a data optimization query method of online education system based on decision tree. According to the teaching objectives of teachers and the characteristics of courses, extract the course characteristics of online education system, and adjust the data segmentation process, so as to extract the grid memory query index structure. Then select a field as the segmentation basis and mark, and use the decision tree to identify the trajectory data type. Finally, set the data optimization query mode by continuously predefined query interval. The experimental results show that compared with the other two query methods, the query time of this method is less, which shows that the application performance of the data optimization query method of online education system integrated with decision tree is better.
Research on Data Classification of Online English Teaching Platform Based on Deep Neural Network

Due to the diversity of online English teaching platform data, the accuracy of its classification results is low. Therefore, a data classification method of online English teaching platform based on deep neural network is proposed. In order to reduce the difference attribute between the data, the data of online English teaching platform are normalized. On this basis, the attributes are discretized, the corresponding attribute codes are established, and two constraints are constructed. The deep neural network is used to classify the data of online English teaching platform. The test results show that the accuracy of data classification can reach more than 98.0%.
Collaborative Filtering Recommendation Method for Online Teaching Resources of Elderly Care Specialty

The explosive growth of the number and scale of online education resources makes it difficult for learners of elderly care to obtain the online teaching resources they need in time. However, the traditional resource collaborative filtering recommendation method has the disadvantage of low recommendation accuracy. To solve this problem, this study proposed a recommendation method for collaborative filtering of online teaching resources in elderly care. The organizational form of online teaching resources for elderly care major was deeply analyzed, and then the learning behavior data of learners were collected and analyzed, and the preferences of target learners were calculated. Based on this, the BP neural network is used to construct the target learner preference model, and then the collaborative filtering algorithm is used to predict the score of online teaching resources, so as to realize the recommendation of collaborative filtering of online teaching resources. Experimental data show that compared with traditional methods, the proposed method has higher recommendation accuracy and recall rate, which proves the effectiveness of the proposed method.
Design of Intelligent Financial Education Assistant System Based on Blockchain

The traditional financial education assistant system has the problems of long response speed and poor anti-interference effect of financial education information transmission. Therefore, an intelligent financial education assistant system based on blockchain is designed. Collect intelligent financial education data according to the data warehouse technology, analyze the collected intelligent financial education data through statistical analysis methods, build an auxiliary decision-making model based on the comprehensive financial data, and use the blockchain to realize the design of intelligent financial education auxiliary system, so as to realize the data conversion of intelligent financial education. The experimental results show that the average response speed of the intelligent financial education assistant system and the other two intelligent financial education assistant systems are 60.530 s, 67.220 s and 68.133 s respectively; When the noise intensity is 50 dB, 80 dB and 120 dB, the design system always has a high education information transmission accuracy, which shows that the design system can improve the Financial Education Assistance Effect of the intelligent financial education assistance system, and that the intelligent financial education assistance system integrated with the blockchain technology has better performance.