bluuebunny/crossref_metadata_2025_split huggingface dataset:
Artificial Intelligence-based Digital Fault Diagnosis and Prediction for Power Grids
Authors: Niu Deling , Lu Tonghe , Wei Changchao , Li Wei , Wang Wenjie 
Published: August 2024

Abstract
When power grid faults occur, especially complex faults, there are many uncertainties such as switch and protection mis-operation, the power system response will be complicated, which causes many difficulties in power grid fault diagnosis. This paper uses the word2vec model vectorization to process the digitized alarm information during grid faults. The processed fault features are input into the DPCNN model to extract global features of the alarm information. Then, the fully connected layer is used to classify grid faults accurately. Subsequently, a convolution module based on the self-attention mechanism is proposed to achieve accurate prediction of grid faults, and the ReLU function and Dropout strategy are used to realize the optimization of the grid fault diagnosis and prediction model. The simulation model test results reveal that the proposed model can effectively diagnose and predict grid faults, with an average accuracy of 97.05% and 95.93%, respectively. The response time for fault diagnosis in this paper’s model for the empirical application of grid diagnosis is reduced from 6.32 minutes to 0.96 seconds, significantly improving diagnosis efficiency compared to the traditional method. This paper provides an effective method for diagnosing and predicting power grid faults and a solution for improving the management of power grids.
Research on Marine Target Detection and Recognition Based on YOLO Algorithm
Authors: Zhang Huayue , Wu Fan , Wang Xuan 
Published: August 2024

Abstract
Marine target detection is a crucial technology for developing and utilizing marine resources, and fast and accurate detection of marine organisms is of great research significance for sustainable development and protection of marine resources. In this paper, we first discuss the convolutional neural network and attention mechanisms in deep learning and then present the YOLO series of algorithms for target detection. Then, we take ResNeXt50 as the backbone network, introduce the global attention mechanism and ASFF module to establish the GA-YOLOv5s model for marine life target detection and recognition, and also design the training strategy of the model through migration learning. Simulation experiments are planned to verify the analysis after considering the feasibility of the GA-YOLOv5s model for marine target detection and recognition. The YOLO algorithm, based on multiple improved strategies, improves the mAP@0.5 of marine target detection and recognition by 5.68%. The detection speed of the model after incorporating the GAM module is 48.51FPS; the model using ASFF mAP@0.5 increased by 3.38%; and the average precision and recall of the model for marine target detection and recognition are 82.79% and 80.17%, respectively. Based on the YOLO algorithm, accurate detection and recognition of marine targets can be achieved, which provides reliable technical support for enhancing the exploitation and protection of marine resources.
Mining the Performance Characteristics of Yao Nationality Musical Instruments under Multivariate Statistical Analysis
Authors: Li Pengpeng 
Published: August 2024

Abstract
In the context of the rapid development of modernization and urbanization, the inheritance and research of music and musical instruments by ethnic minorities are facing great challenges. It is, therefore, of enormous significance to uncover the performance characteristics of ethnic minority musical instruments. This paper focuses on four categories of Yao musical instruments, namely reed instruments, air-pipe instruments, wind instruments, and percussion instruments. We mine the performance features of Yao musical instruments using MFCC feature extraction, perceptual linear prediction parameter extraction, and other methods. The performance of this paper’s algorithm is explored by comparing the detection and recognition accuracy of its algorithm with SVM on four types of musical instruments. The performance characteristics of Yao musical instruments are explored by analyzing the timbre characteristics, auditory characteristics, and beat statistics of the four instruments. This paper’s algorithm significantly outperforms the SVM algorithm in the recognition correct rate of four different types of musical instruments, with differences of 2.1905%, 7.1574%, 5.3758%, and 3.6962%, respectively. The extracted performance features of Yao music instruments reveal that reed instruments and air-pipe instruments have a superior timbral effect than wind instruments and percussion instruments. The sound of pneumatic instruments and wind instruments is the best when it comes to audibility, and the beats of reed instruments and wind instruments are the best among the four instruments.
Computational Modeling and Environmental Adaptation Analysis of Heritage in Historic Districts
Authors: Gao Yun 
Published: August 2024

Abstract
The rapid development of urbanization brings a lot of problems, and the protection of the heritage of historical and cultural districts needs to formulate the protection strategy according to the local environmental adaptation and continuously improve and amend it. In this paper, a model is developed for the environmental adaptation mechanism of the heritage of historical and cultural districts, and the spatial structure of the heritage of historical and cultural districts is calculated using spatial statistical methods. Subsequently, an environmental calculation simulation model is proposed based on ENVI-met software, which combines the spatial structure to simulate and analyze the environment of the Shengjin Tower Historical and Cultural District Heritage in Nanchang City, and analyze its environmental adaptability. The test results show that the environmental simulation model proposed in this paper can accurately simulate the environmental change values of the heritage of the historical and cultural district according to the values of external environmental factors. The results of the analysis of the Shengjin Tower Historical and Cultural District Heritage show that the plots in the districts have an average thermal environment adaptation degree of 1.02, and the average air environment adaptation degree is 1.08. Meanwhile, West Street shows higher performance in air environment adaptation degree, with an average of 1.10. The adaptive degree of the plots in the downwind direction is poor, and they are easily affected by the external environment. This paper lays the foundation for other studies on the environmental adaptation of heritage in historical and cultural districts, and the conservation strategies proposed in terms of symbiosis, wholeness, and dynamic sustainability provide references for the conservation and inheritance of heritage in historical and cultural districts.
Discussion on the Development of Teaching Mode of College Students’ Mental Health Education in the Internet Era
Authors: Dong Yang 
Published: August 2024

Abstract
The psychological problems of college students under the rapid development of big data on the Internet have aroused widespread concern in society, and mental health affects the normal learning life of college students. This paper analyzes the psychological status quo of college students using the internet, proposes a mining process for mental health education data, and performs data preprocessing. The application of the Apriori algorithm in data mining was analyzed, and it was found that the algorithm has problems such as too long matching times and too many item sets. Improvements were made on this basis, and the improved Apriori algorithm was applied to the analysis of college students’ psychological problems. It was found that interpersonal tension and sensitivity, depression, and anxiety were the most common psychological problems. In addition, in the teaching mode comparison experiment, the Internet+ mental health education program based on association rules had a good influence effect on students. Students’ physical and emotional feelings exceeded 4.00 points, and their satisfaction with the course reached 4.65 points, so the internet+mental health education course based on association rules has some promotion value.
Research on the construction of the curriculum system of “integration of courses and certificates” for the 1+X Certificate in Early Childhood Care in the era of big data
Authors: Fu Kuiliang 
Published: August 2024

Abstract
The new era is increasing the demand for complex technical and skill talents, and the reform of talent training in vocational education is also imperative. Starting from the real demand, this paper takes the construction of a professional curriculum system under the 1+X certificate system as the entry point, proposes a 1+X early childhood care certificate “class-certificate integration” curriculum system construction method, and takes the preschool education major of M school as an example for successful acceptance. Specifically, the evaluation indexes of the curriculum system construction under the CIPP model are constructed, the weights are calculated by using the FAHP-CRITIC combined weighting method, and the cloud model comprehensively assesses the construction effectiveness. On this basis, the fsQCA method was used to further explore the in-depth construction of the 1+X early childhood care certificate “course-certificate integration” program in the era of big data. The data show that the comprehensive cloud index parameters for the effectiveness of the construction of School M’s curriculum system are 78.1, 0.558, and 0.016. It has initially achieved a certain degree of success. Under the combined effect of high professional strength, high teaching quality, high education funding, and high investment, the effectiveness of the curriculum system shows a high level (consistency = 0.949689 > 0.9). The curriculum system can be further optimized in the era of big data by building a curriculum teaching resource base and strengthening professional teaching skills.
Model run monitoring and parameter modification methods
Authors: Chen Jichen 
Published: August 2024

Abstract
The stability and safety of industrial process operations have a decisive impact on the high-quality development of the economy and industry. However, the traditional model is difficult to adapt to the increasingly complex production process. In this paper, based on the probabilistic linear discriminant analysis model, we construct a fault monitoring model for industrial process operation, and through kernel density estimation, we judge whether the statistical indexes exceed the control limit so as to determine whether the industrial operation system has a fault. Using a genetic algorithm, the parameters of the model are optimized and modified to find the optimal value of the model. The performance of the model and its practical application were analyzed through the Tennessee-Istman process, and the effect of parameter modification was investigated. The experiments indicate that the KPLDA model’s parameter modification improves its ability to recognize faults with smaller amplitude, with only three minor errors, and provides more accurate fault reporting on data samples. The KPLDA model’s prediction range basically overlapped with the actual measurements until sample point 80, and the prediction trend of gray score values above 0.95 in the range of sample points 120-200 differed slightly from the actual measurements, with better prediction results overall.
Exploring the Teaching Mode of Civics and Politics of Implicit Courses in Applied Colleges and Universities under the Background of Industry-Teaching Integration
Authors: Yue Weiting 
Published: August 2024

Abstract
The industrial-education fusion The civics and politics teaching system, a combination of ideological and political education, industrial frontier cultivation, and professional competence education, has the potential to foster a synergistic effect and enhance the talent cultivation mechanisms of applied colleges and universities. In this paper, we look at how applied colleges and universities teach implicit course ideology and politics in a world where industry and education are coming together. To do this, we came up with a design scheme for implicit course ideology and politics, which will be used as a guide for teaching engineering majors at an applied college and university in Hangzhou starting in 2022. An evaluation system of implicit course Civics teaching effect based on AHP hierarchical analysis index empowerment is built to measure the quality of Civics teaching and find out how well this paper’s program works. The comprehensive evaluation of five first-level indicators for college engineering majors yields scores of 8.60, 8.42, 8.51, 8.41, and 8.56 points, with three rated as excellent, two as good, and a total score of 8.50 points rated as excellent. The results reveal a significant difference between the experimental and control classes in five categories following a controlled test, with the average of the five post-test Civics dimensions being 11.43 points higher than that of the control classes. The implicit curriculum civics teaching model proposed in this paper is able to promote the overall improvement of students’ civics literacy. This study has provided a useful exploration of the innovation model of curriculum civics teaching and provides a reference for the construction of curriculum civics in applied colleges and universities.
Integration and Development of Colleges and Folk Art from the Perspective of Aesthetic Education
Authors: Li Chunjiang 
Published: August 2024

Abstract
Folk art as an aesthetic education resource can greatly expand the aesthetic education time, space, and the upper limit of education objects. Based on the value of contemporary aesthetic education of folk art, the teaching mode of integrating folk art in colleges and universities is designed, which is divided into three theoretical modules: investigation module, and practice module. To confirm the role of the teaching mode designed above in promoting aesthetic education in colleges and universities, the effect of the teaching mode is analyzed by combining questionnaires and independent samples t-tests. The data show that there is a significant difference between the experimental group and the control group in the dimensions of aesthetic ability (p>0.05). In addition, the mean and standard deviation of the experimental group’s art theory assessment score is 82.17±9.44 points, and the mean and standard deviation of the control group’s art theory assessment score is 74.48±8.05 points, and there is a very significant difference in the same assessment scores (p<0.05). This study explores the aesthetic value of folk art, can enrich the diversity of aesthetic education resources, helps to build a complete context of contemporary aesthetic education, and, at the same time, is of practical significance for the development of aesthetic education in colleges and universities.
Table tennis stroke technique and fitness improvement based on strength training
Authors: Zhuang Yuan , Li Yunjie , Zhuang Xuan 
Published: August 2024

Abstract
Table tennis is regarded as the national ball of China, and in the actual process of competition, athletes should have both high technical and tactical levels and good physical fitness. This paper focuses on the changes in hitting skills and physical fitness of table tennis players after strength training. In order to establish a scientific training system and improve training efficiency, this paper designs a physical fitness monitoring method using big data technology. The monitoring method initially uses the backpropagation algorithm to process the physical fitness data of the athletes. To reduce the computational amount of frequent item sets, it is recommended to use the Apriori algorithm combined with the DC_Apriori algorithm for data mining on processed physical fitness data. Finally, the physical fitness training results analyzed by this fitness monitoring method were synthesized to develop a reasonable strength training program for table tennis players. The athletes were tested for changes in table tennis hitting skills and physical fitness before and after 4 weeks of strength training. By comparing with the athletes who underwent traditional physical training, it was found that the average score of table tennis batting skills of the strength training group based on big data analysis was significantly higher than the average score of the traditional physical training group. Comparative analysis of athletes’ physical fitness from four aspects: speed, strength, sensitivity, and endurance. Strength training based on big data analysis can significantly improve the physical fitness quality of table tennis players.
The impact of strengthening practical teaching in vocational education on improving students’ employability
Authors: Wei Hanwu 
Published: August 2024

Abstract
Practice teaching is an important part of the teaching system and plays a pivotal role in improving the quality of talent training. The study outlines the mechanism by which practical teaching affects students’ employability in vocational education and proposes a practical teaching model for vocational education. We analyze the implementation of teaching practices in vocational education from the perspectives of teachers and students, using a vocational undergraduate college in GX City as the object of investigation. On this basis, relevant components of practice teaching are selected, research hypotheses about practice teaching and students’ employability enhancement are designed, and after collecting data, correlation analysis and multiple regression analysis are carried out to explore the role of practice teaching in influencing students’ employability enhancement. Students generally believe that the current practical teaching is insufficient in internship and practice (59.12%) and cannot mobilize learning interest (48.72%) and that the effect of practical teaching needs to be improved through the adjustment of teaching mode. All variables of practical teaching had a significant positive effect on the improvement of students’ employability (P<0.01) and explained 65.1% of the improvement of employability. The results of the study indicate that strengthening practical teaching in vocational education in terms of teaching program improvement, teaching base construction, teaching internship construction, teaching faculty formation, and teaching management standardization can improve the development of students’ employability.
Current Situation, Problems and Countermeasures of Community Home Nursing Service in the Internet+ Era
Authors: Zhao Fangfang 
Published: August 2024

Abstract
The problem of population aging is intensifying worldwide. The proportion of the elderly population is gradually increasing, and the wisdom of elderly care will become a social development trend. This paper explores the status quo and problems of community home care services in the Internet+ era through a questionnaire survey on the supply of intelligent community care services. Based on this basis, a smart community home care system is developed based on Internet of Things (IoT) technology. Embedded control modules such as sensors and buzzer alarms are used to collect information about the posture and vital signs of older adults and to issue an alarm when they fall. Zigbee technology is used to design the communication module of the system so that communication messages can be sent in case of emergency help to older adults. The Mahony fusion-based fall detection algorithm is utilized to determine the falls of older adults and combined with a beeping alarm to ensure real-time monitoring of the personal safety of older people. An empirical study was designed to analyze the satisfaction and perceived importance of the home care system for elderly users, and the results show that the average value of the satisfaction and perceived importance scores of the elderly users participating in the study is above 3.9, and the standard deviation is small. This paper’s smart community home care information system’s feasibility and effectiveness have been fully proven by the result.
The Application of Image Graphic Visual Communication Techniques in Artistic Creation from the Perspective of Digital Media
Authors: Cai Qiong 
Published: August 2024

Abstract
This paper first studies the connection between computer image graphics and visual communication and analyses the use of image graphics and visual communication technology in artistic creation. It denoises the image and proposes a method for enhancing blurred light images based on visual communication technology. It also outlines the process of applying computer graphic image processing technology to the field of visual communication design. Then VR technology is combined with visual communication and art design, a 3D image virtual reconstruction system based on visual communication effects is designed, and a 3D image graphical visual art creation method is constructed. Finally, we analyzed the impact of virtual reality art creation in terms of aesthetic evaluation, experience impact, and satisfaction. The results showed that the simple main effect of expression was significant when intensity was perceived for three different types of emotions, as shown by the simple effect analysis of expression on the type of emotion, which were FA(2, 160)=43.05, p<0.001, FB(2, 160)=10.45, p<0.001, and FA*B(2, 160)=12.36, p <0.001. This study complements the research on virtual aesthetics and, at the same time, provides a new research direction for the diversified and integrated development of art.
Research on intelligent control and sensor application strategy of motor based on RFID technology
Authors: Cao Min 
Published: August 2024

Abstract
People widely use permanent magnet brushless DC motors because of their simple structure, high operating efficiency, simple control, and easy maintenance. This paper constructs an EFID sensor network by merging EFID and sensor technologies and then designs the motor’s intelligent control system and strategy around it. In this paper, the SVR-PSO algorithm is used to localize the motor rotor, which nonlinear SVR trains to construct a nonlinear system of equations for calculating the position of the target tag, and then the PSO algorithm is used to seek the position coordinates of the target tag. The fuzzy PID is utilized to control the brushless DC motor, and the integral separation method is adopted to improve the control strategy. The SVR-PSO positioning algorithm and the improved fuzzy PID control strategy are applied and analyzed. For 12 tags to be measured, the positioning accuracy of SVR-PSO has improved by 56.8% compared to that of LANDMARC. Although SVR-PSO’s positioning algorithm is influenced by mutual coupling and multipath effects, the overall accuracy is still superior to that of LANDMARC. Based on the fuzzy PID controller optimized by the integral separation method, the motor rotational speed has a fast response, a small overshoot, and a small fluctuation of rotational speed, and can automatically regulate and restore stability under the situation of a sudden change of load. The motor speed response is fast, the overshoot is small, and the speed fluctuation is small, and the motor speed can be automatically adjusted and stabilized under the sudden load change, which has better dynamic and static performance than the traditional PID controller and fuzzy PID controller. The purpose of this paper is to provide a strategy reference for the use of RFID technology in the intelligent control of motors.