bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis and Evaluation of Ecotourism Resources in China Based on RIAM Model
Authors: Li Jingke
Published: September 2023

A comprehensive assessment of ecotourism resources is needed for the sustainable development of ecotourism in China. In this paper, based on the scientific classification of ecological resources, the RIAM model for the environmental impact assessment of ecotourism resources is established, and the indicator sets are obtained based on a fast matrix calculation combining semi-quantitative and qualitative. Then, the hierarchical analysis method is used to calculate the weights of different indicators for the established indicator sets. Finally, an empirical analysis of the resources of Huangtengxia Ecotourism Area was conducted based on the comprehensive assessment model. It was found that the bio-ecological impact index of Huangtengxia was [6,8,-2,15,7], and the economic return impact index was [4,7,10,-5,8]. Taken together, the overall evaluation of ecological tourism resources in Huangtengxia has a total score of 72, which belongs to the middle to the upper level of similar tourism resource regions in China. This study establishes a scientific evaluation system of ecotourism resources in Huangtengxia, which provides a valuable reference template for the evaluation of ecotourism resources in China.
Research on fault feature extraction and early warning of rolling bearing vibration signal of generator set
Authors: Ma Yan , Si Jun , Yan Qiuzhen , Wang Jun
Published: September 2023

The study of fault feature extraction and early warning of rolling bearing vibration signal of generator sets is beneficial for the timely diagnosis of bearing faults, thus improving the service life of generators. In this paper, a combined EEMD-GRU-MC prediction method is adopted to predict the model based on GRU through the data decomposition of EEMD, and the predicted model residuals are corrected using MC. The analysis and diagnosis of the algorithmic model are used to determine the fault characteristics of the generator’s vibration signals for diagnosis, and the analysis and diagnosis of the characteristics are verified using experiments with publicly available data sets from the Bearing Data Center at the Paderborn University School of Mechanical Engineering in Paderborn, Germany. Diagnosis can be performed with an accuracy of 99.6% under condition load K
0 and 99.9% close to 100% under condition load K
3 . The accuracy is the highest at this point, while the diagnostic accuracy at conditional load K
1 is only 99.8%, the lowest at this point. However, the accuracy under condition load K
2 is also 99.5%. Therefore, the diagnostic accuracy with EEMD-GRU-MC is around 99%. In this study, the EEMD-GRU-MC model can be used to extract the fault characteristics and early warning of the rolling bearing vibration signal of generator sets.
Construction of customer-aware grid interactive service system based on neural network model
Authors: Zhou Baowei , Ling Yongxiang , Cao Sheng , Su Hongbang , Qi Xiaoxuan , Zhang Yaling
Published: September 2023

Neural network models have advantages in spatial and temporal information processing, which provide new ideas for the construction of customer-aware grid interactive service system. In this paper, firstly, the spatio-temporal fusion deep neural network model based on the attention mechanism is used to extract spatial and temporal information by convolutional neural network and gated recurrent neural network, respectively. The attention mechanism is also introduced to assign weights to various types of features to improve prediction accuracy. Secondly, the global information of the attention mechanism of the channel on the feature map is fully utilized to solve the problem of inadequate extraction of feature information from a single model, and then the grid interactive service system is constructed. The results show that the model proposed in this paper has higher prediction accuracy with root mean square error, coefficient of determination, and prediction accuracy of 0.972, 1.742, and 0.935, respectively. To verify the performance of the cache-based curve service in handling customer-perceived grid interactions, minute samples are created, where the maximum number of minute sample records is 3.5 million. Thus, it is shown that by introducing the attention mechanism can effectively improve the computational efficiency of the model, get better prediction results, and meet the demand for efficient and stable customer-aware interactive service system.
Research on the construction of personalized learning system supported by big data in education
Authors: Zhao Xuekong , Lao Li
Published: September 2023

In order to optimize the drawbacks of current personalized learning systems on the market, a big data algorithm is used to optimize the personalized learning system. This paper first analyzes the system model, constructs the basic framework of the system, and optimizes the algorithm based on a collaborative filtering algorithm that converts user behavior into ratings and recommends personalized learning content for learners. Since learning resources and learners are interconnected, this connection is analyzed by an ant colony algorithm to provide the optimal path for students to learn and create a personalized learning path. After comparing the student models, we understand that the clearer the description of students’ interests, the clearer the accuracy returned, where User A and User C have the highest similarity of 99% and accuracy of 85% and 88% respectively, proving the feasibility of the system. The personalized learning system supported by big data in education can optimize the drawbacks of the current personalized learning system in the market, meet the concept of teaching according to student’s abilities, and outperform the learning system in the market.
Research on the innovation of the path of ideological and political education in universities based on data mining
Authors: Rao Suyu
Published: September 2023

This paper first describes the parallel association rule mining method for the big data implementation process. To perform similar item merging, each data item in the dataset is scanned, the dataset is divided, and then the similarity degree is calculated. And the dynamic support threshold is obtained based on the idea of genetic iteration of the genetic algorithm to obtain the optimal solution. In order to conduct data mining, the mining process is then transferred to the MapReduce computing platform while the data output from the Map step is parallel LZO compressed. Finally, in the age of big data, the ideological and political work in colleges is mined and analyzed using a data mining algorithm, and route innovation remedies are proposed. According to the current state of ideological and political education, 77.6% of respondents believe that the ideological and political management system is not ideal, and 61.48 percent believe that the ideological and political content is fragmented and that data-based information makes it challenging to supervise. The immaturity of new media development and the growth of technological challenges amounted to 46%. After creative approaches, ideological and political education teaching satisfaction has grown by 15-20 percentage points. Ideological and political education at universities under the impact of big data should grab the possibilities and overcome the difficulties to achieve sustainability and innovative development.
Research on high quality development system of vocational education based on improved particle swarm optimization algorithm
Authors: Zhang Qiang , Lyu Lixin
Published: September 2023

This paper first investigates the implementation process of the particle swarm algorithm by introducing the weight factorωto make the algorithm population iterative, using the particles to perform a local search and make them stay near the optimal solution of the algorithm to find the best. Then, we discuss the improvement of the particle swarm optimization algorithm by adding inertia weightωand shrinkage factor to improve the performance of the algorithm and analyze the convergence of the optimization algorithm to determine the convergence conditions and the state of the system. Finally, the improved particle swarm algorithm was used to evaluate the development status of vocational education, analyze its problems, and propose countermeasures for high-quality development. In terms of problems, 68% believe that there is a misalignment in management. 69% believe that the internal management system of the school is not perfect. 66% believe that the school does not have enough funds for the cultivation of talents. As for the learning atmosphere, 294 people think the learning atmosphere is weak, and 487 people think the learning atmosphere is average. The study of this paper is important for the development and optimization of vocational education.
The Planning & Designing of Urban Building Water Supply and Drainage Engineering in AI Era
Authors: Jiang Yunfeng
Published: September 2023

To explore how to improve the quality of urban building water supply and drainage engineering and further promote the economic construction of urban buildings, this paper combines artificial intelligence with water supply and drainage engineering of urban buildings. A detailed analysis of water supply and drainage engineering is unfolded, and the combination of BP neural network algorithm and particle swarm algorithm is used to improve the convergence accuracy of the algorithm and network generalization ability to optimize the BP neural network algorithm and construct the artificial intelligence algorithm model. Through experiments in the artificial intelligence algorithm model, the actual output quality parameter is 82, and the difference with the desired output quality parameter of 81 is 1, while in the ordinary design, the actual output quality parameter is 70, and the difference with the desired output quality parameter is 11, get in the artificial intelligence model the desired output and the expected output close. It shows that combining artificial intelligence with urban building water supply and drainage engineering can improve the quality of the project, which is more accurate and superior to the ordinary design and reduce the project cost.
Analysis of the technical and tactical evolution characteristics of college men’s soccer based on simulated annealing algorithm
Authors: Wang Zhe
Published: September 2023

This paper aims to investigate the technical and tactical evolution characteristics of college men’s soccer, and improve and optimize the simulated annealing algorithm by analyzing its operation process, so as to improve its operational efficiency and accuracy of results. The optimized model is used to analyze the data of the last 5 matches of men’s college soccer teams and study the offensive, defensive, and shooting characteristics of men’s college soccer teams. The results show that in terms of offensive techniques, the number of passes made by men’s college soccer teams is not small, among which 2589 passes were made in the 13th match, 1108 passes in the 14th match, and 938 passes in the 15th match, but the success rate is very low, and all of them are ineffective passes, which are not purposeful and offensive enough. The study in this paper summarizes the evolution characteristics of the technical tactics of college men’s soccer and improves the guidance for the improvement and development of college men’s soccer technical tactics.
Research on fabric yarn detection based on improved fast R-CNN algorithm
Authors: Zhang Yang
Published: September 2023

For the current commercially available fabric yarn detection, which is based on traditional machine vision methods and relies heavily on manually designed features, an improved Faster R-CNN algorithm is proposed in this paper. In this paper, based on the Faster R-CNN algorithm, the deformable convolutional Resnet-50 network is fused to improve the learning ability of woven yarn features. By designing a multi-scale model for the detection of fine features in fabric yarns, a cascade network is introduced to improve the detection accuracy and localization accuracy of woven yarns, and an optimized loss function is constructed to reduce the effect of sample imbalance. Through the experiments of the improved fast R-CNN algorithm for fabric yarn detection, we can find that the confidence level of SSD algorithm detection is 58%, and the confidence level of the original Faster R-CNN algorithm detection is 78%, while the improved Faster R-CNN can not only accurately frame the finesse problem, but also the confidence level is as high as 97%. So this paper, based on the improved Faster R-CNN algorithm, can pinpoint the problem of fabric yarn detection, improve the learning ability of detection, and can meet the current demand for fabric yarn detection in the market.
A Green Supply Chain Management Strategy for E-Commerce Based on Multiple Blockchain Technology
Authors: Qu Min , Xu Tianpei , Ju Changzhi
Published: September 2023

In this paper, firstly, the e-commerce green supply chain management strategy of multivariate blockchain is explored, and digital assets are traded on the e-commerce supply chain platform through the information anchoring model. Secondly, the Diffie-Hellman algorithm is used to generate the key, the AES algorithm is used to encrypt the information, and the account data, transaction data and IoT data, are stored in three independent chains. Finally, the selection strategies of different e-commerce sales models and the green supply chain management strategies of e-commerce platforms are visually analyzed through numerical arithmetic examples. The results show that when E
0 = 10, it is optimized by the ecological R&D efforts of supply chain members. When E
0 = 50, the greenness of the product is decreasing. When it finally tends to the steady state, E
∞
C > E
∞
BR > E
∞
MR. The three green supply chain management models proposed in this study are conducive to enhancing consumer utility and in line with the sustainable development strategy.
The innovation path of agricultural products e-commerce marketing mode under the background of “live broadcast + short video”
Authors: Zhou Yan , Lu Liu , Liu Lijun , ZiJian Ji
Published: September 2023

In order to evaluate the dependability and validity of the scale, this paper first examines the features of farming direct seeding. It then builds a scale that includes charm, expertise, interactivity, spatial presence, perceived value, platform notoriety, and buy intention. The project’s internal coherence and logic are confirmed by extracting the common factors using the principal component analysis method, followed by factor rotation using the maximum variance method. In order to confirm the relationship between anchor characteristics, spatial presence, perceived value, platform reputation, and purchase intention, we conduct an empirical study on the impact of live-streaming media characteristics on consumers’ purchase intentions. We also conduct correlation analysis, regression analysis, adjustment effect test, and hypothesis test. Interactivity has a considerable positive impact on perceived value, as evidenced by the magnitude of the standardized regression coefficient of 0.138 and Sig=0.019005. Professionalism has a strong positive impact on perceived value, as shown by the standardized regression coefficient of professionalism on perceived value, which is 0.292, Sig=0.0000.05. Living agricultural products must combine their own qualities and concentrate on the marketing and selling their wares.
Exploration of the innovative development path of university civic education based on data mining algorithm
Authors: Luo Weigang
Published: September 2023

Addressing the issues of a single form, insufficient targeting, a lack of synergy, and the inability to create a customized collaborative education process in the current college Civic Education curriculum setting, This paper develops a recommendation system for a college Civic Education curriculum based on enhanced collaborative filtering technology. It adopts an enhanced algorithm of cooperative filtering based on the combination, and by having to introduce a gradual forgetting curve relying on the time-sensitive change of user interest, it more effectively resolves. The standard algorithm is outdated, inefficient, and not very adaptable. A similar classification method for college Civics courses is then constructed after data mining is performed to filter out the data noise present in the data set. Via empirical validation, it is discovered that the optimization method obtains an average accuracy of 78.83% when the amount of cycles is 40. When the number of cycles is 40, the recall rate of the optimized algorithm is the highest, and the recall rate is 78%. In terms of recommendation popularity comparison, the optimization algorithm popularity starts to be higher than the traditional algorithm when the number of cycles exceeds 80. Therefore, the system has excellent practicality and resilience, and it operates steadily, which is of positive significance for creating an atmosphere of collaborative and win-win university thinking and political education for teachers and students with various forms and individual innovation.
Analysis of the application of Internet multimedia technology in the mixed teaching of public physical education
Authors: Qi Xiangjun
Published: September 2023

In order to explore how to change the singularity of the existing public physical education teaching mode, this paper introduces Internet multimedia technology to analyze physical education. Firstly, the characteristics of Internet multimedia technology were analyzed to construct a fuzzy evaluation model based on Internet multimedia technology divided into index weights, primary fuzzy evaluation, and secondary fuzzy evaluation. Secondly, some teaching indicators were statistically categorized through the method of a statistical survey, and the results of the survey were calculated to eliminate indicators lower than 85%, and the evaluation system of public physical education mixed teaching indicators was constructed. Finally, it was concluded through the experiment that 52.11% of the experts think the application level of Internet multimedia technology in public physical education hybrid teaching is now advanced and in an acceptable state. There are 36.27% of experts think that the application level is now intermediate and needs to be reduced to an acceptable level according to the program regulations. 11.82% of the experts believe that the application level is now low, unacceptable, and needs to be rectified immediately. Thus, it is concluded that public physical education based on Internet technology can enrich the existing physical education model and increase the diversity of physical education models.
Exploring the relationship between digital transformation of enterprises and “information infrastructure” in the new infrastructure perspective - based on industrial connection
Authors: Wang Wei
Published: September 2023

This paper aims to investigate the relationship between enterprise digital transformation and “information infrastructure” by analyzing the mechanism of enterprise digital transformation under the new infrastructure, constructing an input-output analysis model and a double difference model, and conducting a parallel trend test on the two models, bringing in the data between enterprise digital transformation and “information infrastructure” on the model, and studying the relationship between the two and the degree of influence. The relationship between the two and the degree of influence is investigated by bringing in the data of “information infrastructure”. The resulting data show that artificial intelligence accounts for 25.4% of digital transformation, followed by IoT at 19.7% and 3D printing at 1.4% of digital transformation. The change in the number of state-owned enterprises and non-state-owned enterprises before and after digital transformation is the largest in the range of 0-50%, with 44.4% change in the number of state-owned enterprises and 31.25% change in the number of non-state-owned enterprises. The research in this paper provides favorable data and analysis to prove that “information infrastructure” drives the digital transformation of enterprises.
Exploring the reform of college mental health education based on multi-source data
Authors: Chen Lingjing
Published: September 2023

With the primary study emphasis on feature extraction, this article first suggests an algorithm for identifying students’ mental health issues based on multi-source data and employs one-dimensional convolutional neural networks to extract the online trajectory patterns of pupils from online behavior segments. Anomaly ratings were computed based on student consumption statistics from the cafeteria in order to depict the dietary variations among students. Next, a DeepPsy-based algorithm for identifying pupils with mental health issues was recommended after the algorithm suggested in the preceding phase was improved. A two-dimensional convolutional neural network was used to build the Internet trajectory matrix and retrieve the daily Internet trajectory pattern. A long and short-term memory network was used to record the time-dependent connection between each day, and a deep learning network was created by fusing the fundamental features and the Internet trajectory pattern. Through experimental research, the DeepPsy model was able to detect 75.5% of pupils with mental health issues and obtained a Recall of 0.755, outperforming the multi-source-based algorithm by 19.5%. Obsessive-compulsive symptoms took the top spot among the many variables influencing mental health, coming in at 22.8%, followed by interpersonal sensitivity at 17.25%. Depression came in third with a proportion of 10.76%. As a result, instructors can use the algorithm suggested in this article to spot pupils who may be suffering from undiagnosed mental health issues.
Analysis of high quality collaborative development path of university civic education based on Rete’s pattern matching algorithm
Authors: Lv Tiantian
Published: September 2023

The prerequisites for the separation of fuzzy sets for the assessment of ideological and political education in colleges are first looked at in this essay. Then the implementation of the quality evaluation algorithm is discussed, the factors associated with the system and the corresponding data are selected, then the theoretical domain of the data is defined, the set contained in the theoretical domain is calculated, and the final value of the non-fuzzy values is calculated by the nonfuzzification method. To get the evaluation findings, the evaluation method is then used to build a thorough evaluation factor set and evaluation set, choose the weight coefficients, and create the fuzzy connection matrix. The assessment method is then used to examine the existing state of political and ideological education, identify its challenges, and provide solutions for high-quality growth. In terms of regional development, the eastern area is ranked 0-6, the middle region −2 to 3, and the western region −2 to 2 in terms of ideological and political development. 80% of instructors agree that learning should incorporate the primary job of building moral education when it comes to growth approaches. 39% think that the curricular strategy needs to be improved. 54% of respondents think that teaching practices should be standardized in schools. 44% think that teaching strategies need to be improved. Based on the Rete pattern matching algorithm and fuzzy evaluation algorithm, it is important for the development and construction of college ideology and politics.
Analysis of the effect of user-understanding-based retrieval system improvement on the application of intelligent archive management
Authors: Wang Shouzhong
Published: September 2023

As a precipitation and accumulation of history, archives management has gradually tended to be digitalized and informalized with the continuous updating and development of modern technology. In this paper, we first study the retrieval system and focus on the Boolean model, vector model, and probabilistic model in information retrieval technology. The matching relationship between documents and queries is detected from the document set for the user’s query, and a relevance retrieval system based on user understanding is proposed to solve the matching problem. The amount of information that needs to be retrieved is growing exponentially, and how a user perceives the information is crucial to the process. Then, in order to solve the problem of insufficient retrieval efficiency caused by the explosive growth of wisdom files, the retrieval system is creatively optimized on the basis of the ant colony algorithm, which effectively improves the efficiency of wisdom file management. The efficiency of the optimized retrieval system is verified and analyzed in an experimental simulation environment. The findings demonstrate that when the amount of archives rises, the retrieval effectiveness of the improved ant colony algorithm described in this study marginally improves, but in 10~35s. As the inventory of the Smart Archives increases, the content retrieval of the archives will become more and more frequent. This study improves retrieval efficiency and serves as a good demonstration for the construction of archival management information technology.
A study on the influence of soccer culture on physical education in China's universities based on linear regression analysis
Authors: Yang Hui
Published: September 2023

With the continuous deep integration of the Internet and education, soccer culture has been popularized in the field of physical education, and its influence on physical education in Chinese colleges and universities has been deepened. This paper firstly constructs the evaluation index system of soccer culture on the teaching ability of physical education in Chinese colleges and universities based on the linear regression model and logistic regression model in the context of the Internet, determines the final evaluation index system, calculates the weight coefficients of the indexes, and derives the relative importance of each index through comparison. Secondly, the relative scores of indicators are determined according to the weights of the evaluation index system of teaching ability of physical education, and the influence of football culture on physical education in Chinese colleges and universities is analyzed. The numerical values show that the mean scores of experts’ scores of teaching ability as well as the coefficient of variation, have changed, which obviously can show that the modified indicators of teaching innovation ability have a higher degree of expert recognition. The means of the four indicators were 4.86, 4.7, 4.7, and 4.65, with standard deviations of 0.34713, 0.5, 0.5, and 0.56721, and coefficients of variation of 7.34%, 6.25%, 6.25%, and 12.45%. Thus, it is feasible to analyze the influence of soccer culture on physical education in Chinese colleges and universities using linear regression models and logistic regression models based on Internet technology.
A hybrid online and offline teaching model of professional English for Internet+ education platform
Authors: Li Lin
Published: September 2023

Blended teaching combines the advantages of online teaching and offline teaching, which breaks the limitation of time and space to a certain extent and is of great significance to helping learners improve their learning efficiency and teachers’ teaching level and quality. This paper firstly designs a blended teaching model for the background of Internet+ education and improves the functional design of each part of the model. Secondly, the extreme gradient prediction model of students’ academic level is proposed for the blended model, and a strong learner is formed by integrating multiple weak learners to correct the misclassification. Finally, the blended model of instruction is evaluated and analyzed. The model achieves an accurate prediction accuracy of 65% for MEDIUM students and 75% for PERFECT students, with an average prediction accuracy of 58.4%, which is more than 50%, and can predict students’ academic level situations more accurately. The functional indicators all scored 74.4, the efficiency indicators all scored 71.35, and the usability of the platform exceeded 70. The Internet+education platform’s professional-type English, the online and offline hybrid teaching model, can effectively improve learners’ learning efficiency, as well as improve teachers’ teaching standards and quality.
Research on online and offline double-loop teaching of college students’ mental health education based on cluster analysis algorithm
Authors: Bai Yang , Ma Yulong
Published: September 2023

In this paper, a knowledge difficulty clustering algorithm (MIBKPC) based on multidimensional time-series data and learning path networks is proposed. The algorithm integrates the cyclic learning sequence, forgetting behavior and system interaction degree formed by learners learning some of the more difficult knowledge points, and constructs a computational model for the difficulty similarity of knowledge points based on system interaction behavior so as to better portray the difficulty similarity of knowledge points based on system interaction behavior. Then a knowledge point difficulty clustering algorithm (MFSKPC) based on multidimensional time-series data and maximum frequent subgraphs is proposed. The algorithm extracts the maximum frequent subgraphs of the atlas based on the learner’s directed learning path atlas using the gSpan-based maximum frequent subgraph mining algorithm and portrays the difficulty similarity of knowledge points based on system interaction behaviors by combining the system interaction degree and the maximum frequent subgraphs. In the accuracy comparison, the clustering accuracy of the MFSKPC algorithm for advanced learners was higher than that of the MIBKPC algorithm for both K=3 and K =5 conditions by 7.89% and 8.29%, respectively. In the comparative analysis of double-loop psychological instruction, the experimental class improved its pre and post-test scores by an average of 2.38 points, while the control group improved by an average of only 1.88 points. The experiment showed that the double-loop teaching based on the MFSKPC algorithm was more effective.
Research on the innovative development model of ideological and political education based on big data and self-media environment
Authors: Li Lu
Published: September 2023

This paper aims to explore the innovative development model of ideological and political education. By establishing a Civic and Political Science teaching platform, two functions of classroom interaction and online dual-teacher interaction are designed under nine ideological and political teaching modules. The VR technology and system framework are analyzed, and the corresponding MDP algorithm is constructed. The algorithm model was used to analyze the percentage of students’ favorite Civics classrooms and the acceptance level of VR teaching classrooms. The result data show that only 27.5% of students like Civics class, 51.53% of students maintain a neutral attitude towards Civics class again emotionally, and 16.36% of students do not like Civics class. 70.1% of students prefer the means of communication of Internet platform tools. 16.58% of students prefer the means of communication of newspapers and magazines, 50.2% of students prefer the means of video communication, and 35.26% of students prefer the means of video communication. 35.26% of students prefer book communication. This paper provides reference data and models for the development of ideological and political education innovation.
Research on the immersive multimedia virtual interactive experience technology of the Great Wall World Heritage based on VR vision system
Authors: Wang Xiaofen , Wang Yanzhen , Yuan Pengjun , Yu Kaiyue
Published: September 2023

This paper constructs an immersive multimedia virtual interactive experience technology with the Great Wall World Heritage Site as the experimental object. By analyzing the VR vision system and algorithm, the process of stereo vision perception and the general algorithm of somatic image production are explained. The distance equation and depth calculation in stereoscopic projection are studied, and the virtual interactive experience technology is constructed and applied to the World Heritage Site of the Great Wall. The result data show that the immersive multimedia virtual interactive experience technology highlights the real feeling of users more, in which the model has 50% of the influence on the real feeling, the mapping has 15%, the lighting has 15%, and the rendering has 10%. The youth population has a higher percentage of interest in the virtual field, accounting for 50%, 65%, and 60%, respectively, while the middle-aged stage has a more average degree of interest in the virtual field, with 50% of the average interest, 30% of happy to experience, 25% of not interested and 50% of interested. This thesis is conducive to enriching the project of the Great Wall World Heritage Site and providing an effective reference for technological innovation of immersive multimedia virtual interactive experience.
Simultaneous localization and mapping of mobile robots with multi-sensor fusion
Authors: Zhang Kui , Cui Haihua , Yan Xiaomei
Published: September 2023

Simultaneous localization and map building of mobile robots is an important research direction in robotics, and multi-sensor fusion is one of the key technologies for mobile robots to achieve autonomous navigation. In this paper, firstly, based on the framework of the SLAM system, we analyze the extraction of FAST feature points and BRIEF feature descriptor matching and propose the CSD-ORB algorithm. Secondly, the FKCS-LD algorithm based on the fusion map key frame and center selection strategy is proposed. The suitable multi-sensor fusion SLAM system is selected to build the back-end optimization algorithm based on the bit-pose map. Finally, we complete the comparison experiments of the multi-sensor fusion SLAM system on standard data sets, robot hardware assembly and software environment construction, and actual field testing. The experimental data show that the trajectory calculation accuracy can be further improved by using local map tracking, i.e., the current frame and local keyframe to calculate the bit pose, in which the maximum error is 6 cm, the root mean square error is reduced to 3.6 cm, the maximum value of local optimization is 0.66034, the minimum value is 0.146232, the average is 0.32812, and the median is 0.33023. The experiment proves that the multi-sensor fusion SLAM system can achieve centimeter-level accuracy and has global consistency and real-time performance, and can effectively complete the task of simultaneous robot positioning and map building.
Study on the optimization of the cultivation path of finance professionals in universities in the digital era
Authors: Yang Xiaoying
Published: September 2023

The rapid development of big data technology is bound to affect the development direction of finance majors in colleges and universities and put forward new challenges to the cultivation of talents. This paper first analyzes the data mining concept, process as well as methods and selects the clustering analysis method, K-means algorithm, and NMF algorithm of big data technology. Secondly, data pre-processing is carried out for students’ learning behavior, learning evaluation, and professional ability data, which makes the subsequent data mining results more reliable. Finally, the judgment matrix is constructed for the training of college finance professionals, and the consistency test of the matrix is carried out to form the absolute indexes of the primary indexes and the relative weight values of the secondary indexes, and the absolute weights of the secondary indexes are obtained through calculation, which finally forms the weights about the student learning behavior, learning evaluation and professional competence evaluation indexes. The learning percentages of student learning clusters are: 16.1%, 19.3%, 30.1%, 34.4%. The innovation and collaboration ability of finance students has been improved, and the deep processing feedback ability of financial knowledge content has been strengthened. Thus, the wide application of big data technology provides a new path for the training of finance professionals in colleges and universities.
The integration of flipped classroom into university physical education teaching reform practice from the perspective of multimedia
Authors: Feng Bin , Zhao Jingjing
Published: September 2023

With the development of multimedia, the flipped classroom is deeply loved by educators with its unique, flexible and efficient features, which meet the requirements of physical education reform from a multimedia perspective. In this paper, we first use a genetic algorithm to arrange the physical education course information in a real number coding way to form chromosomes and initial populations. Then the individual fitness F is determined, the outstanding parent individuals are selected, the chaotic crossover and chaotic mutation operations are performed, and the end conditions are judged. According to the calculation of the fitness function, this ensures the diversity of the population and also eliminates the conflicting course plan programs. Then, 83 students from two classes at Guizhou Normal University were used as experimental subjects to explore the effect of integrating flipped classroom teaching into physical education, and the volleyball skills of students in the experimental and control groups were tested in the form of teaching-examination separation. The results showed that there was a significant difference between the volleyball skill test results of students in the experimental and control groups t=2.071, p=0.042, less than 0.05, indicating that the volleyball skill level of the experimental group was better than that of the control group after experiencing 32 credit hours of volleyball teaching. This study promotes the reform of physical education teaching and is of great significance to the development of physical education.
Construction of a screening and evaluation system for anti-hepatitis B virus drugs based on quadratic exponential smoothing model
Authors: Xu Yangding , Hong Yi , Tong Ying , Xiong Zhixiang
Published: September 2023

Exploring the construction of an anti-hepatitis B virus drug screening and evaluation system is to better develop anti-HBV virus drugs. In this paper, we analyzed the types of hepatitis B virus present in different hepatocytes, starting from the hepatitis B cell line model. Based on the quadratic, exponential smoothing model, a QES-LSTM viral gene detection model was constructed by introducing a long and short term memory neural network, and experimental analysis of the sensitivity and specificity of viral gene detection was conducted for this model. From the sensitivity experiments, the sensitivity of HBV DNA, DHBV DNA and DHBV cccDNA were 60 copies/ml, 60 copies/ml and 10 copies/ml, respectively. From the specificity experiments, the mean values of specificity of HBV DNA, DHBV DNA, and DHBV cccDNA were 0.489, 0.481, 0.429, respectively, 0.429, which showed positive amplification compared to other types. This indicates that effective discrimination of HBV viral genes is needed in the construction of an anti-HBV virus drug screening and evaluation system, which in turn allows targeted screening of drugs for the treatment of the HBV virus.
Research on computer network information image data processing based on machine learning
Authors: Mei Haifeng , Sun Li
Published: September 2023

In this paper, we aim to progress the efficiency and accuracy of information processing and security detection in computer networks by introducing convolutional neural networks in machine learning algorithms that are capable of multi-scaling from the channel attention module and spatial attention module in extracting image information. Global maximum pooling and global averaging are done for the feature maps generated by both modules to get the clearest feature maps by dimensionality reduction. The loss function is used to calculate the feature maps to reduce the data loss generated during data extraction and finally complete the image data processing. To verify the effectiveness of the proposed platform, network images containing different amounts of data are input into the platform, and the accuracy and loss of data extraction are obtained. The results show that the data extraction accuracy of the reduced platform is up to 100%, which is 6% higher than other platforms. The number of data losses in other platforms is more than twice of this paper, while the number of losses in this paper can be controlled within 5. It can be seen that convolutional neural network in machine learning improves the accuracy of data extraction from computer network information images and reduces the loss in data extraction.
Intersection Between Spirituality and Neuroscience: Biological Bases of Transcendental Experiences
Authors: Rodrigues Michele Aparecida Cerqueira , Barbosa Fernando Campos , Lopes Gabriel César Dias , Santacroce Luigì , Lopes Pollyanna Carvalho Pereira
Published: September 2023

Objective: The objective of this study is to investigate the relationship between religion, spirituality and neuroscience, with a focus on understanding the biological bases of religious experiences. The study aims to analyze how different spiritual practices affect the human brain, identify the brain regions involved, and examine the impact of these practices on mental health and emotional well-being. Furthermore, we seek to discuss the ethical implications of including religious themes in medical and psychological practice.
 
Method: The study uses a qualitative literature review approach in English and Portuguese, based on national and international sources. Scientific articles, case studies and research related to the neuroscience of religion and spirituality were analyzed. The data was collected and organized to identify the biological foundations of spiritual experiences, the social and psychological implications, as well as the ethical issues associated with this theme.
 
Results and conclusion: The results indicate that different spiritual practices activate several brain areas, including the frontal cortex, prefrontal cortex, nucleus accumbens and striatum, associated with rewards, emotions, moral reasoning and concentration. The mystical mind is considered an innate capacity of the human brain, enabling transcendental experiences in all cultures. Furthermore, the frequent practice of spirituality can lead to profound brain changes, favoring discernment, empathy and better decisions. Religiosity and spirituality have a positive impact on mental health, helping to cope with anxiety, fears and promoting emotional well-being.
 
Research implications: This study has significant implications in the area of mental health and clinical practice, highlighting the importance of considering patients' spirituality and religiosity as an integral part of their emotional health. Furthermore, the research paves the way for a greater understanding of the biological bases of religious and spiritual experiences, which may have applications in clinical treatments and the promotion of psychological well-being. The ethical implications raised are also relevant for healthcare professionals, who must approach these issues with sensitivity and respect, avoiding the imposition of personal values. On a broader scale, research contributes to intercultural understanding and peaceful coexistence between different religious groups, promoting tolerance and mutual respect.
Effect of immediate postpartum umbilical cord pH on fetal discomfort and neonatal outcome
Authors: Mohamed Fawaz , Alatawi Samah , Busaleh Zainab , Shamtoot Fatima , Alonze Saad , Almohana Alhanoof , Alonizi Thamer , AlAnazi Samer
Published: September 2023

Objective: This study aimed to assess the effect of immediate postpartum umbilical cord pH on fetal discomfort and neonatal outcomes.
Methods: A descriptive cross-sectional study was conducted in the Department of Gynecology at King Saud Medical City from March 2022 to July 2023. Around 47 full-term expected women who experienced abnormal cardiotocography during the active or latent stages of labor were included in this study.
Results: Around 29 women (61.7%) of the total participants were primigravida, while others were gravida 2 (14.8%), gravida 4 (8.5%), and gravida 7 (2.1%), with significant fetal bradycardia. Cesarean delivery was necessary in 17% of instances, with late decelerations occurring in 37 (78.7%) and persistent varied decelerations with loss of baseline variability occurring in 2 (4.2%) cases. The correlation between the umbilical cord pH and the appearance, pulse, grimace, activity, and respiration (APGAR) score at 0 minutes was highly significant (r= 0.821, p = 0.001), and the correlation between the umbilical cord pH and the APGAR score at 5 minutes was also highly significant (r = 783, p = 0.001).
Conclusion: The most accurate way to diagnose birth asphyxia is by measuring the pH of the cord blood, which should be done in all high-risk deliveries. Doing so might assist in the prevention or lessening of neonatal morbidity and mortality by ensuring that the newborn receives proper care upon delivery.
Awareness and knowledge assessment of bronchial asthma among the general population in Saudi Arabia
Authors: Alsadoun Fahad , Ojayban Faisal , Banaeem Abdullah , Alruzayhi Ibrahim , Hezam Norah , Alqasim Abdullah , Alkhudairi Abdulelah , Alsomali Rawan
Published: September 2023

Objective: This study aimed to determine the level of knowledge and awareness of bronchial asthma among the general population in Saudi Arabia.
Methods: This cross-sectional study was conducted in Saudi Arabia during the year 2023 using a questionnaire survey with a sample size of 385.
Results: The study revealed that 9.7% of participants had asthma. Around 50.4% reported having siblings with asthma. The majority showed satisfactory awareness of asthma-related information, with 79.2% correctly identifying it as a chronic disease. Additionally, 89.1% knew asthma was not infectious, and 69.3% recognized that it could lead to health complications, while 55.6% were aware it could be fatal. Most participants correctly recognized common asthma symptoms. However, awareness of dry cough as a symptom was lower at 58.6%. Common risk factors like family history, allergies, and smoking were well-known.
Conclusion: While there is a reasonable level of awareness regarding asthma as a chronic condition and its prevalence, efforts should be made to raise awareness about the potential severity and life-threatening nature of the disease. Moreover, continuous education initiatives targeting specific sociodemographic groups can further enhance asthma knowledge and improve asthma management and outcomes across the population.