bluuebunny/crossref_metadata_2025 huggingface dataset:
An eco-friendly route for green synthesis of ZnO-CoFe2O4 nanoparticles from cardamom and ginger extract as an efficient electrochemical catalyst for water oxidation
Authors: Kamyab Aynaz , Khojasteh Mir Hadi Banan , Asadpour-Zeynali Karim
Published: December 2023

Water splitting has been one of the potential techniques as a clean and renewable energy resource for the fulfillment of world energy demands. One of the major aspects of this procedure is the exploitation of efficient and inexpensive electrocatalysts due to the fact that the water oxidation procedure is accompanied by a delayed reaction. In this research, ZnO-CoFe2O4 nanostructure was successfully synthesized via the green method and green resources from cardamom seeds and ginger peels for oxygen evolution reaction (OER). The modified Glassy carbon electrode (GCE) with ZnO-CoFe2O4 is effective for the electrochemical water oxidation interaction since it has sufficient electrical strength and excellent catalytic performance. The creation of rice-like and small granular structures of ZnO-CoFe2O4 nano-catalysts was confirmed by characterization methods such as XRD, FESEM, EDS and MAP. According to the achieved results, in the electrolysis of water, with in-cell voltage of 1.40 V and 50 mA cm–2 for current density in a 0.1 M KOH electrolyte and OER only has 170 mV overpotentials.
Frequency and clinicopathologic associations of microsatellite instability and PD-L1 expression in Vietnamese patients with gastric cancer
Authors: Thinh Pham Van , Dung Tran Ngoc , Thang Vi Thuat , Chung Nguyen Thanh , Linh Nguyen Thuy , Hien Nguyen Thu , Tien Truong Dinh , Tung Dang Son , Tra Dang Thai , Hanh Nguyen Mai , Khuong Kieu Van , Huy Pham Xuan , De Nguyen Van , Chung Dang Thanh
Published: December 2023

Background: Our study aimed to determine the frequency of microsatellite instability (MSI) and characterize the associations between MSI status, PD-L1 expression, and clinicopathological features in Vietnamese patients with gastric cancer. Methods: We performed a retrospective cohort study that analyzed 87 patients with gastric cancer who underwent gastrectomy from January 2020 to March 2023. MSI status was assessed by immunohistochemistry for mismatch repair proteins. PD-L1 expression was evaluated by tumor proportion score (TPS) and combined positive score (CPS). Associations between MSI, PD-L1, and clinicopathologic factors were analyzed. Results: MSI-high (MSI-H) was identified in 13.8% of tumors and significantly associated with intestinal subtype, moderate differentiation, necrosis, tumor-infiltrating lymphocytes, and PD-L1 positivity. Lymphatic invasion correlated with increased TPS. Intestinal classification correlated with higher CPS. Conclusion: MSI-H identifies a subset of gastric cancers with distinct features. PD-L1 expression is associated with aggressive disease parameters. Biomarker-based stratification may guide personalized therapy.
Analysis of Enterprise Accounting Data Management Evaluation Model Based on Maturity Modeling
Authors: Duan Fei
Published: December 2023

This paper takes the capability of accounting data management in Company D as the research object and constructs a maturity model of accounting data management. The idea of the maturity model’s gradient is used to divide key process domains and practices and then create a set of accounting data management index systems. Meanwhile, the fuzzy element evaluation and analysis method is applied to the evaluation of accounting data management maturity of enterprises, and “maturity level, evaluation index, and quantitative value” are defined as the basic elements of fuzzy elements. Finally, based on the evaluation results, the evaluation indicators at all levels of the accounting data management maturity model of Company D are analyzed. The results show that the evaluation value of the cost management capability and decision support capability of Company D is 3.1678 and 2.9518, which can ensure the authenticity, timeliness and reliability of accounting data to a certain extent. This paper provides new ideas for the research of enterprise accounting management evaluation, which has certain theoretical significance and practical value.
A study of the relationship between parents’ educational behavior and children’s psychological development based on linear regression models
Authors: Yao Xuan , Li Jing
Published: December 2023

The purpose of this paper is to investigate the linear relationship between parenting and children’s psychological development and to analyze the strength of the relationship between them by using linear regression models. A one-dimensional nonparametric regression model with matrices is employed to handle the linear relationship between parenting and children’s psychological development. Combining parameter estimation and great-likelihood estimation was used to determine the maximum parameter value for the sample relationship. To ensure that the parameters that affect parenting and children’s mental health development conform to the model, we used the expectation and variance of the parameter estimates. The results show that good and bad parenting behavior affects children’s mental health. Benign parenting has a contributing effect on children’s emotional influence; children’s perception of safety is 0.75, and more stable emotions and stability are 0.85. When children are well educated, children’s three perceptions are 0.65, and self-perception is 0.8.
Framework and Change Path Analysis for the Improvement of Accountants’ Data Analysis Capability in the Era of “Digitization”
Authors: Lin Xiaohong , Yi Yanwei
Published: December 2023

This paper first analyzes the importance of data analysis skills and uses information mining to discover valuable accounting knowledge. Secondly, in the process of calculating the weights of indicators, the Bayesian network classifier is used to enhance the data mining technology, filtering and processing the interfering information and redundant information to ensure the effectiveness of professional competence data acquisition. Finally, the framework of professional competence of accounting talents was constructed, the path of accountants’ change was analyzed, and the design of the numerical intelligence curriculum system was completed. The results show that the rating of data analysis ability is 4.63, and the average score of the others is roughly around 4, which proves the feasibility of the Numerical Intelligence Curriculum System.
Geotechnical investigation measures and techniques in construction engineering based on multi-source data fusion
Authors: Pei Hanrui
Published: December 2023

Geotechnical investigation is an important aspect of construction engineering. In order to optimize this link, this paper analyzes the current status of the application of geotechnical investigation in construction engineering through the fusion of multidimensional spatial data interpolation of geotechnical geology as well as the structural design of geotechnical profiles by combining with triangular mesh search algorithm. On this basis, the parameter prediction of the fusion of multi-source parameter data in geotechnicals was carried out by determining the estimated variance and weight coefficients. In addition, the optimal interpolation algorithm was selected through the indoor test and in-situ test, and the accuracy of the modeling of the soil and the prediction of the geotechnical parameters were analyzed. The results show that the modeling width error is between [0.04,0.20], the length error is between [0.7,0.23], the planar accuracy error is around 0.2cm, the depth error is within 0.02cm, and the errors of the actual and predicted values of the rock and map parameters are within 0.1 and 0.09, respectively. Geotechnical investigation measures and techniques in construction engineering based on multi-source data fusion can optimize construction engineering.
Representation and effectiveness based on big data analytics: optimizing the construction of leadership team structures
Authors: Wu Duomei
Published: December 2023

The optimization of leadership team structure is the research object of this paper, and the regression model in big data analysis is explored as the research method. Neighboring sample information is introduced through the network structure diagram, the regression model with neighboring sample information is constructed, the corresponding estimation method of regression coefficients is proposed, and the proof of the error bounds of the proposed estimation is given. Finally, the method is applied to analyze the results after optimizing the corporate leadership team structure. It includes regression analysis of the non-heterogeneous, heterogeneous, and overall structures of the leadership team and examines the moderating effect of salary heterogeneity on the results. The results show that the number of applications for invention patents and the number of authorized patents in the enterprise reaches 3 times to 5 times the number before the change, respectively, and in the regression analysis of the heterogeneous structure of the leadership team on the development of the enterprise R
2 =0.134, F value=2.186, which indicates that the heterogeneity of the years of working experience has a very significant positive effect on the development of the enterprise.
Fuzzy Neural Network Algorithm Applied to the Construction of a Prediction Model for Online Buying Behavior
Authors: Cheng Miao
Published: December 2023

In this paper, we first preprocessed the user’s shopping behavior data, set the prediction goal, constructed the features of the user’s online purchasing behavior prediction model, and classified and selected the constructed features based on the SVM-RFE algorithm. Then, on the basis of the fuzzy neural network algorithm of fuzzy theory, the network purchasing behavior prediction model was constructed by combining the assessment indexes of the prediction model results as well as the 5-fold cross-validation method. Finally, the evaluation results of the prediction model are examined and compared with common prediction algorithms to confirm the performance of the algorithm in this paper. The results show that the average relative error of model training can reach 0.013, and the absolute error with the actual value ranges between [0.01, 0.06]. On the same test set, the F1 value of the prediction model in this paper is between [0.88, 0.91], and the F1 value of the algorithm on each test set has a small difference of only 0.03, and the F1 value of the other prediction models has a maximum difference of 0.09. The prediction model constructed in this paper has a good prediction effect and robustness.
The impact of the concept of “tailor-made teaching” on the cultivation of higher vocational art and design professionals in the era of artificial intelligence
Authors: Tao Yinghong
Published: December 2023

This paper first studied the education concept of tailor-made teaching, explored the influence of tailor-made teaching on the cultivation of professional ability, and constructed the talent cultivation model of art majors based on tailor-made teaching. Then, we constructed the influencing factor analysis model, extracted the relevant principal components, calculated the Spearman correlation coefficient, established the multiple linear regression analysis model, estimated the model parameters, and tested the model. Finally, we analyzed the influence of the concept of tailor-made teaching on talent cultivation mode, cultivation effect and cultivation evaluation, and carried out correlation analysis, regression analysis and mediation effect test on the influencing factors. The results show that the mean value of the evaluation of the education model of “tailor-made education” ranges from 3.78 to 4.35, which is at a relatively satisfactory level. The sig value of the relationship between “teaching according to student’s abilities” and the quality of talent training is 0.000, indicating that “teaching according to student’s abilities” has a significant positive effect on the quality of talent training.
Exploration and Practice of Labour Education in Higher Vocational Colleges and Universities in the New Era Based on Big Data Analysis
Authors: Chen Yumo
Published: December 2023

To enhance the labor literacy of college students, this paper examines big data in labor education. Firstly, it visualizes and preprocesses labor education big data and designs a method to analyze labor education big data based on an improved ant colony clustering algorithm. Secondly, it examines the labor education of higher vocational colleges in the new era and establishes an evaluation index system for higher vocational labor education in the new era. Finally, labor education is examined using the improved ant colony clustering algorithm, and the practical effects of labor education are examined. Practice shows that ant colony clustering clusters labor education in higher vocational colleges into three categories, in which the proportion of category 1 is 0.28, the proportion of category 2 is 0.41, the proportion of category 3 is 0.31, and the effects of labor concepts, labor knowledge, labor skills, labor qualities, and labor literacy have been improved by 0.27, 0.29, 0.29, 0.26, and 0.24, respectively. Higher vocational colleges and universities of the new era of labor education can improve the labor literacy of working college students.
Using cognitive mapping to analyze the aesthetic value of music education in colleges and universities
Authors: Kuang Xue , Liu Chang
Published: December 2023

In this paper, firstly, on the basis of cognitive mapping, music data are processed in four directions, namely, sound spectrum extraction, audio superposition, audio tempo, and tone intensity adjustment, and then audio sequences are sliced and diced, so that the cognitive mapping can be more focused on capturing localized useful information. Then, the BERT model is used to encode the music sequences so that the output music sequences already contain aesthetic and emotional features and the cognitive mapping-based music emotion analysis model is constructed according to the music emotion learning layer, the emotion feature aggregation layer, and the full connectivity layer, and analyzes the aesthetic value of music education in colleges and universities. According to the results, the BERT model had a difference of 0.13% on the MED dataset and 0.03% on the MTD dataset. On the mean value of the aesthetic value of traditional music, introverted personality (3.61) was higher than extroverted personality (3.52). This study has a positive effect on the cultivation of aesthetic value in music education in colleges and universities and proposes effective ways to enhance aesthetic value in college and university music teaching.
The Path of Meishan Cultural Renewal and Expansion Based on Data Association Rules
Authors: Li Tao
Published: December 2023

Metadata and data association rules are combined in this paper to create an aggregation framework for Meishan cultural digital resources. Meishan cultural digital resources are standardized through the use of metadata standards. The accuracy of metadata is evaluated in conjunction with trustworthiness. Metadata association rules are employed to evaluate the degree of association in Meishan cultural data. Enhance the efficiency of data association analysis by enhancing the Apriori algorithm. The algorithm is applied to the association analysis of Meishan culture data, and the degree of association between different digital resources and Meishan culture is determined by combining the data. The results show that the highest correlation with Meishan culture is the digital resources of documentaries and skills, with a correlation degree of 0.9, and the lowest correlation is the book resources, with a correlation degree of 0.65. The number of nodes in the period of 1-6 and the time consumed by each dataset is in the interval of (7000,1100).
Historical stylistic evolution of traditional temple murals based on time series analysis
Authors: Wang Jiong
Published: December 2023

In this paper, firstly, on the basis of time series analysis, considering the validity of data research data, it is necessary to carry out the pre-processing process of independent variables and dependent variables of temple frescoes and then select the characteristic variables of temple frescoes, and get the multivariate time series of temple frescoes through wavelet correlation analysis of the characteristic variables of temple frescoes. Then, construct the classification model of temple frescoes based on the multivariate time series through the image processing of temple frescoes, get the feature values applicable to the model classification, considering the accuracy and convergence of the model classification, the temple frescoes features are needed to be extracted and trained, and at the same time, the evolution of the historical style of the traditional temple frescoes is analyzed by examples. The results show that in terms of performance, the method of this paper achieves 90.34% accuracy, and the comparison results of two indicators, recall and F1 value, also show that this paper shows good performance compared with the other four models. In the correlation analysis, it is found that there is a significant correlation between the rich artistic heritage of dynasties (P=0.66>0.05), the economic prosperity of dynasties (P=0.75>0.05) and the evolution of the historical style of temple frescoes, and it is proposed that traditional temple frescoes are protected and developed paths.
Application of traditional cultural elements in modern interior design in the era of artificial intelligence
Authors: Wang Jue
Published: December 2023

This paper applies traditional cultural elements to modern interior design and first analyzes the expression types of traditional cultural elements. Secondly, the color and pattern elements in traditional cultural elements are extracted by color matrix and SIFT algorithm, and the pattern and color elements are applied to modern interior design using an intelligent recommendation algorithm. Next, the layout elements of traditional cultural elements are modeled, and the automatic layout algorithm is created to be utilized in modern interior design. Finally, the performance of extracting traditional cultural elements and their application are analyzed. The results show that the recognition rate of various colors is above 0.88, the extraction accuracy of the overall traditional cultural pattern elements is around 0.9, the overall degree of the graphic color element recommendation is greater than 0.88, the hierarchical difference between the traditional cultural layout and the intelligent layout is between [0.001, 0.01], and the functional difference is between (0, 0.02], and all of the automatic layout algorithms can be completed within 0.2s.
Research on English Intercultural Teaching Mode in Colleges and Universities under the Background of Industry-Teaching Integration
Authors: Wang Xiaoru , Liu Nian
Published: December 2023

In order to improve the practical ability of English in colleges and universities, this paper puts forward the concept of AKEE teaching based on English intercultural communicative competence under the background of integration of industry and education and designs the intercultural teaching mode of college English based on AKEE teaching under this concept, and constructs the teaching quality evaluation index system of the intercultural teaching mode of English in colleges and universities in the light of the teaching content. On this basis, the English intercultural teaching model was constructed based on the entropy weight-TOPSIS method, and the selected indicators were tested for validity using principal component analysis, and the final evaluation results were obtained by calculating the entropy weights. The results show that in the order of comprehensive evaluation, teaching effect>teacher quality>teaching content>teaching resources>teaching quality feedback, with the mean values of 0.811, 0.804, 0.803, 0.799 and 0.798, respectively. Intercultural teaching of English in colleges and universities can improve the teaching effect as well as the quality of teachers.
Exploration and Practice of Online-Offline Hybrid Teaching Mode in Teaching Higher Education Courses under the Background of Internet+
Authors: Wang Yisha
Published: December 2023

In this paper, a Bayesian approach and a recommendation algorithm are used to construct a method for evaluating students’ competence in a hybrid teaching model. The Bayesian method is used to create a mathematical description of the student’s ability level. The purpose of classification is achieved by extracting features of students’ learning results and preference directions using the simple Bayesian method. According to the recommendation algorithm, the recommended objects’ content features are retrieved, and teaching resources with high matching degrees are recommended for students. The recommendation algorithm in this paper can effectively determine the ability level of students, as demonstrated by the results. The probability of the highest P1 mastery rate among A-E students is 0.3179 for B students, and the probability of the highest P2 mastery rate is 0.1409 for D students. The average score of the experimental class that implements blended teaching is 76.631, while the average score of the control class is 73.7841, and the experimental class is 2.8469 points higher than the control class. 2.8469 points. This study promotes the development and progress of blended teaching to a certain extent.
The Path of Red Culture Integrating into Civic Education in Colleges and Universities Based on Big Data Analysis
Authors: Yang Fengyu
Published: December 2023

This paper firstly proposes the EWM-TOPSIS method for evaluating the degree of integration of red culture into the Civic-Creative Education of colleges and universities, constructs the corresponding evaluation index system, utilizes the EWM method for the calculation of the index weights and carries out a comprehensive evaluation through the TOPSIS method. Secondly, the necessity and value performance of the integration of red culture into Civic Education is analyzed. Finally, the evaluation index system was utilized to verify the examples of red culture integrated into Civic Creation Education in colleges and universities. The results show that the weight value of revolutionary tradition education in the red culture integration into college CIC education is the highest at 0.1294, and the comprehensive evaluation results of the five colleges and universities show that School A scores the highest at 85.49 points. This shows that the integration of red culture into college CIC education needs to focus on the educational purpose and educational context so as to promote the better integration of red culture into college CIC education and to enhance students’ understanding and development of red culture.
Research on Employment Stability Evaluation and Influencing Factors of College Graduates under Data Mining Technology
Authors: Qi Guifen
Published: December 2023

In this paper, while analyzing the specific performance of college graduates’ employment behavioral decision-making changes and significant differences in employment choices, we use data mining technology to analyze the data on the employment stability of college graduates, select gray correlation analysis and hierarchical analysis to determine the index weights of employment stability and construct an evaluation model of employment stability of college graduates. This paper makes an empirical study on the factors affecting the employment stability of college graduates, analyzing the differences in employment stability in terms of gender, education, type of graduation institution and location of the unit. The analysis shows sig<0.05, which means that it shows a significant difference at the level of 0.05, then there is a significant difference in the employment stability of college graduates in the early stage of graduation in terms of education and the type of graduation institution. Thus, we should strengthen the awareness of college graduates about their education and their advantages so as to promote the stable employment of graduates.
Information Service Innovation in College Libraries Based on Big Data Analysis
Authors: Li Zhuyu
Published: December 2023

This paper first proposes a real-time recommendation technique based on user images and utilizes multi-dimensional small data fusion for user image construction, which in turn gives a personalized wisdom service recommendation structure. Secondly, user long and short-term preference fusion is carried out by introducing a self-attention mechanism and GRU network, and then personalized retrieval recommendation based on user long and short-term preference is realized. Finally, an investigation is carried out to determine the effectiveness of the personalized wisdom information service model through empirical analysis. The results show that the mean value of literature and history in the user portrait category III is 1.553, the change in the borrowing of books in the I major category decreased by 31.94% from 2018 to 2022, and the average satisfaction of users for the personalized recommendation service is 83.52%. This shows that the personalized intelligent information service model of the college library can realize the innovation of library information service and further improve the satisfaction of users for the college libraries.
Diversified Curriculum Innovation for Japanese Language Education in Colleges and Universities under the Deep Learning Model
Authors: Zhou Rui
Published: December 2023

This paper constructs a diversified Japanese language course recommendation model based on the autoencoder network model using deep learning, which includes stack autoencoder, self-attention mechanism encoder, and relevance decoder. A system for evaluating the quality of Japanese language education was constructed using hierarchical analysis. The correlation between the Japanese listening test and the degree of innovation of diversified Japanese language education courses and the influence of the innovation of diversified Japanese language education courses on students’ Japanese language performance were analyzed, respectively. The study showed that the correlation coefficient between the Japanese listening test score and the diversified Japanese language education program was 0.865, and the students who received the diversified Japanese language education program scored 7 points higher than the students who received the traditional Japanese language education program.
The impact of corporate human resource management on corporate structure and image power based on grey correlation analysis
Authors: Tao Xianting
Published: December 2023

This paper uses a gray correlation algorithm to analyze the relationship between enterprise human resource management, enterprise structure, and enterprise image. By determining the sequence of characteristics and the sequence of factors of human resource management, the main factors affecting corporate structure and corporate image are analyzed. The gray correlation axiom and gray correlation degree are used to determine the degree of influence that human resource management has on enterprise structure and image. The gray correlation between the three is calculated by combining the steps of gray correlation calculation and gray correlation analysis. The results show that from the results of correlation coefficient calculation, the correlation coefficient of human resource management on enterprise structure and imagination is high. The correlation coefficient between enterprise structure and leadership level is 0.598, and the correlation coefficient between leadership level and employee turnover rate is 0.541. Human resource management can influence the degree of embodiment of the enterprise to a certain extent, and when the enterprise’s human resource management is perfected, the embodiment of the enterprise’s product image degree is the highest at 0.75, and that of the visual image is 0.7.
Rule of Law Guarantee for Ecological Security of Inner Mongolian Grassland Based on Big Data Analysis
Authors: Wu Rihan , Zhu Lehua
Published: December 2023

This paper carries out an environmental law big data analysis using big data computing based on the legislative framework of biodiversity in Inner Mongolia grassland. For the research and analysis of the rule of law guarantee for the ecological security of the Inner Mongolian grassland, it first establishes the early warning of the ecological security of the Inner Mongolian grassland through the gray prediction model and verifies the accuracy and feasibility of the prediction model precision. According to the early warning results of the ecological security of the Inner Mongolian grassland, it is suggested to enhance the legalization of grassland ecological compensation. The R
2 GM (1, 1) prediction model of Inner Mongolia grassland reaches 0.86, which shows that the prediction accuracy is good. The ecological security evaluation of Inner Mongolia from 2025 to 2035 presents, in terms of type, a safer state region > safer state region > mildly alerted state region > moderately alerted state region > seriously alerted state, and the percentage of each grade increases or decreases. Without distinguishing occupations, 93.3%-98.6% of all herders and grassland managers supported that grassland ecological compensation should be legalized. This shows that the construction of the rule of law guarantee for grassland ecological security in Inner Mongolia is an inevitable trend of development.
Multi-coordinated scheduling application of small and medium-sized source network, load and storage system under blockchain technology
Authors: Xu Yang , Yin Xiaozhe , Jiang Xueping , Liu Yan , Zhou Zheng
Published: December 2023

This paper firstly analyzes the small and medium-sized source-grid-load-storage system and mathematically models the system structure based on the power supply model, the grid model, the load model and the energy storage model. Secondly, based on blockchain technology, the multivariate coordinated scheduling objectives and constraints of small and mediumsized source-grid load-storage systems are modeled through the Cosmos platform, and the model is optimized and solved by the Gray Wolf optimization algorithm. Finally, the impact of multivariate coordinated scheduling on small and medium-sized source-network load storage systems is examined using the parameters of the example and the micro-network design. The results show that compared to the total operating cost before optimization, the total operating cost decreased by 1163.7 yuan. In terms of the peak-valley difference of load electricity consumption, the peak-valley difference before the implementation of the demand response is 0.48, the peak-valley difference of load after the implementation of the demand response is 0.35, and the real-time residual capacity of the energy storage device is always maintained between 60 and 250 kW. The multivariate dispatch model based on this study has a positive impact on small and medium-sized distribution grids with source-grid load-storage systems.
Process Exploration of New Materials for Building Decoration Engineering Based on Multi-Objective Planning Modeling
Authors: Zhang Xiang
Published: December 2023

Firstly, on the basis of the multi-objective planning model, we determine the objective function of building energy consumption, the objective function of material cost and the objective function of uncomfortable time percentage. We propose to use a multi-objective genetic algorithm to obtain the Pareto frontier solution for the decision variables of the model by selecting them. The target constraints are determined based on the construction of the building decoration project, and the model of remodeling material cost-schedule-carbon emission’ is constructed. The discrete simulation model of the decoration project is constructed based on the design parameters of the enclosure structure and air conditioning. Considering the structural rigor of the research and analysis, it is necessary to set and explain the parameters of the simulation model, and the materials of the decoration project are studied and analyzed. The results show that on the engineering case analysis, the value of building energy consumption, building cost and the value of uncomfortable time percentage have increased by 23%-45% compared with the value before optimization. In the simulation model, the optimized construction solution’s carbon emission, cost, and duration were reduced by 6.22%, 10.65%, and 45.48%, respectively, compared to the original solution. This study illustrates the aesthetic performance and functional performance on the basis of the process of new materials, which is a guiding reference value for the application of new materials in architectural decoration engineering.
Financial Management Strategies for Corporate Investments Based on Integer Linear Programming Models
Authors: Zhao Jin , Wang Ying
Published: December 2023

This paper first gives the financial management strategy of enterprise investment, mainly from determining the financial management model of enterprise investment, improving the centralized management level of funds and optimizing the enterprise investment decision-making process in three aspects. Then, build the financial management model based on integer linear programming through the enterprise investment theory to find the effective investment of assets, the use of absolute deviation risk measurement model to reduce the risk of investment so that the maximization of returns and maintain the stability of returns. Lastly, we utilize Enterprise B as the research object for empirical analysis. From the analysis of investment efficiency, the increment of total assets and net profit is increasing; the increment of total assets in 2022 is 58 million more than that of 2015, and the increment of net profit in 2022 is 49 million more than that of 2015. The data shows that the financial management strategy of business investment improves the investment efficiency of the company and enhances the overall operation of the company’s space.
Piano Playing Gesture Recognition Based on Multiple Intelligences Theory
Authors: Zhang Jiahui
Published: December 2023

In this paper, firstly, in order to solve the piano playing recognition problem in the field of artificial intelligence, based on the theory of multiple intelligences, the VGG-16 deep network migration learning algorithm is applied to estimate and acquire the piano playing gesture posture. Secondly, combined with the Iterative Update Extended Kalman Filter (IUEKF) algorithm, the micro-inertial sensor fixation of the piano-playing gesture is realized, which in turn is conducive to improving the piano-playing gesture recognition accuracy. Then, we obtain real-time piano-playing gesture information through a Kinect somatosensory device, construct a piano-playing gesture recognition model based on migration learning on the basis of obtaining piano-playing gesture features, and confirm the effectiveness of the model through the experimental study of piano-playing recognition. The results show that in piano-playing gesture recognition, the recognition accuracy of this paper’s method remains above 0.9, and the application of this paper’s method can effectively improve the recognition accuracy of piano-playing gestures. On piano playing pedal action recognition, this paper’s method shows that the average F-measure scores of these two strategies are 0.924 and 0.944, respectively, which are better compared to other methods. This study provides an effective case for applying AI techniques to piano performance recognition and broadens the scope of AI applications.
A Flipped Classroom Teaching Model of College Mathematics in Colleges and Universities Based on the Background of Deep Learning
Authors: Ding Han
Published: December 2023

Based on the flipped classroom in the context of deep learning, this paper combines the teaching design of university mathematics in colleges and universities with the learning characteristics of college students and designs and builds a flipped classroom teaching model of university mathematics in colleges and universities in the context of deep learning. To analyze the application effect of the university mathematics flipped classroom teaching model in colleges and universities, we first analyze the differences in the deep learning level of college students and propose the evaluation model of the flipped classroom teaching model, evaluate the application of the model and analyze the evaluation results, then analyze the independent learning ability of college students in a pre and post-test, and finally analyze the participation of college students. There are significant differences in the four dimensions of students’ deep learning awareness, learning motivation, learning engagement, and learning strategies, i.e., p<0.05. The final scores of college mathematics in classes A and B are 40.11 and 36.98. It shows that the effect of flipped classroom teaching in college mathematics is better in class A than in class B. The total value of the independent learning ability of the students in this class before and after the practice increased by 6.8468 points. In the flipped classroom, 37.2 % of the students thought that they completed the task poorly, which was related to the content of practicing the flipped classroom. University math teachers should guide students at the right time to improve their ability to divergence and analogical reasoning.
Research on the Innovative Path of Ideological and Political Education in Colleges and Universities in the Context of Deep Learning
Authors: Cao Muyuan
Published: December 2023

To construct an automatic question-and-answer system for Civics, a neural network and a self-attention mechanism are combined in this paper. Through the input layer of the neural network, the model remembers the semantic information of the Civics text that has been processed. Dynamic feature extraction is used to categorize and classify Civics questions in the system and determine the type of questions. The GLU network is used to predict the answers to the Civics and Politics questions, and the predicted results are normalized by combining the Softmax function, and the category with the highest probability is selected as the answer. The main mode of teaching afterward was to combine the automatic question-and-answer system with teaching. The results show that in the question and answer system, the highest accuracy rate is the practical cognition type of questions, with the accuracy rate fluctuating in the range of (0.8-0.9), and the accuracy rate of truth type and method type of questions fluctuates up and down in the range of 0.7. The percentage of students in the high marking stage increased by 0.1. In Civic Behavior, students’ patriotism increased by 0.15, and spirituality increased by 0.3.
Cosine and Sine Addition and Subtraction Law with an Automorphism
Authors: Aserrar Youssef , Elqorachi Elhoucien
Published: December 2023

Let S be a semigroup. Our main results are that we describe the complex-valued solutions of the following functional equations

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\matrix{ {g\left( {x\sigma \left( y \right)} \right) = g\left( x \right)g\left( y \right) + f\left( x \right)f\left( y \right),} & {x,y \in S,} \cr {f\left( {x\sigma \left( y \right)} \right) = f\left( x \right)g\left( y \right) + f\left( y \right)g\left( x \right),} & {x,y \in S,} \cr }

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\matrix{ {f\left( {x\sigma \left( y \right)} \right) = f\left( x \right)g\left( y \right) - f\left( y \right)g\left( x \right),} & {x,y \in S,} \cr }

where σ : S → S is an automorphism that need not be involutive. As a consequence we show that the first two equations are equivalent to their variants. We also give some applications.
A Competitive Parkinson-Based Binary Volleyball Premier League Metaheuristic Algorithm for Feature Selection
Authors: Naka Edjola
Published: December 2023

A novel proposed Binary Volleyball Premier League algorithm (BVPL) has shown some promising results in a Parkinson’s Disease (PD) dataset related to fitness and accuracy [1]. This paper evaluates and provides an overview of the efficiency of BVPL in feature selection compared to various metaheuristic optimization algorithms and PD datasets. Moreover, an improved variant of BVPL is proposed that integrates the opposite-based solution to enlarge search domains and increase the possibility of getting rid of the local optima. The performance of BVPL is validated using the accuracy of the k-Nearest Neighbor Algorithm. The superiority of BVPL over the competing algorithms for each dataset is measured using statistical tests. The conclusive results indicate that the BVPL exhibits significant competitiveness compared to most metaheuristic algorithms, thereby establishing its potential for accurate prediction of PD. Overall, BVPL shows high potential to be employed in feature selection.
Comparing Different Oversampling Methods in Predicting Multi-Class Educational Datasets Using Machine Learning Techniques
Authors: Tariq Muhammad Arham , Sargano Allah Bux , Iftikhar Muhammad Aksam , Habib Zulfiqar
Published: December 2023

Predicting students’ academic performance is a critical research area, yet imbalanced educational datasets, characterized by unequal academic-level representation, present challenges for classifiers. While prior research has addressed the imbalance in binary-class datasets, this study focuses on multi-class datasets. A comparison of ten resampling methods (SMOTE, Adasyn, Distance SMOTE, BorderLineSMOTE, KmeansSMOTE, SVMSMOTE, LN SMOTE, MWSMOTE, Safe Level SMOTE, and SMOTETomek) is conducted alongside nine classification models: K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Support Vector Machine (SVM), Logistic Regression (LR), Extra Tree (ET), Random Forest (RT), Extreme Gradient Boosting (XGB), and Ada Boost (AdaB). Following a rigorous evaluation, including hyperparameter tuning and 10 fold cross-validations, KNN with SmoteTomek attains the highest accuracy of 83.7%, as demonstrated through an ablation study. These results emphasize SMOTETomek’s effectiveness in mitigating class imbalance in educational datasets and highlight KNN’s potential as an educational data mining classifier.
The revolution is dead, long live the demolition: Education and labor market consequences of student riots
Authors: Ozturk Ahmet , Tumen Semih
Published: December 2023

The 1970s witnessed violent, widespread, and highly-politicized student protests in Turkey. Small protests turned into bloody street clashes, the death toll exceeded 5,000, and a military coup came in—which resulted in mass arrests. The universities were at the center of violent conflict. We study the education and labor market consequences of this political turmoil on the cohorts exposed to educational disruptions. First, we document that the number of new admissions and graduates in post-secondary education declined significantly due to the turmoil. The decline in post-secondary graduation ratio is 6.6 percentage points for the exposed individuals. Second, we estimate a counterfactual wage distribution for the exposed cohorts and check whether the turmoil affected their wage and occupation distributions. We show that the decline in educational attainment pushed the exposed population toward medium- and low-income occupations, and compressed their wages toward the minimum wage. Finally, we use the unexpected decline in post-secondary education as an instrument to estimate returns to college. We find that the college-premium is around 15 percent per year for men.
Immunoreactivity of p21, MMP-1 and CB2 receptor proteins in cutaneous canine mast cell tumours: an association with the three-tier grading system
Authors: Bulak Kamila , Kycko Anna , Śmiech Anna , Łopuszyński Wojciech
Published: December 2023

Introduction

Mast cell tumours (MCTs) arise in the dermis and subcutaneous tissues in animals and humans and are one of the most common neoplasms of the skin in dogs. Cannabinoid type 2 receptor (CB2R), cyclin-dependent kinase inhibitor (p21) and matrix metalloproteinase 1 (MMP-1) are potential targets for novel anti-tumour therapeutic strategies. This study evaluated by immunohistochemical means the reactivity of p21, MMP-1 and CB2R proteins in association with a three-tier grading system in cutaneous canine MCTs.

Material and Methods

Formalin-fixed, paraffin-embedded canine MCTs were processed for histochemical analysis and immunohistochemical staining using antibodies against p21, MMP-1 and CB2R. The results were analysed statistically.

Results

The strongest p21 immunolabelling was detected in grade 3 MCTs, while grade 1 tumours showed mild or no detectable p21 immunoreactivity (P-value < 0.001). Strong immunolabelling of MMP-1 was the most common in grade 1 tumours (P-value < 0.001) and CB2R was significantly less frequent in grade 3 tumours than in grade 1 (P-value < 0.001) and grade 2 (P-value < 0.001).

Conclusion

High immunoreactivity of MMP-1 can be a marker of grade 1 MCTs in dogs, whereas p21 protein overexpression can be a marker of grade 3 canine MCTs. Strong CB2R immunoreactivity with simultaneous underexpression of p21 and high immunoreactivity of MMP-1 proteins may indicate that the use of cannabinoids in grade 1 MCTs in dogs is practicable.
New insight on chlamydiae
Authors: Szymańska-Czerwińska Monika , Zaręba-Marchewka Kinga , Niemczuk Krzysztof
Published: December 2023

This article provides an overview of the current knowledge on chlamydiae, which are intracellular bacteria belonging to the Chlamydiaceae family. Whole-genome sequencing leads to great increases in the available data about Chlamydia spp. Recently, novel chlamydial taxons in various hosts living in different environments have been recognised. New species and taxons with Candidatus status have been recorded mainly in birds and reptiles. Chlamydia gallinacea is an emerging infectious agent in poultry with indirectly confirmed zoonotic potential. Recently, a new group of avian C. abortus strains with worldwide distribution in various wild bird families has been described. The definition of C. abortus species became outdated with the discovery of these strains and has been amended. It now includes two subgroups, mammalian and avian, the latter including all isolates hitherto referred to as atypical C. psittaci or C. psittaci/C. abortus intermediates.
Patriarchal logics and gender inequalities through the financialization of housing
Authors: Martín-Gago Paula , Vives-Miró Sònia
Published: December 2023

This study aims to examine the current knowledge about the relationships between financialization, housing issues, patriarchal logic, and gender inequalities to identify gaps in knowledge, which, in turn, can be considered as topics of scientific interest for future research. To this end, the study provides an exhaustive review of current academic debate regarding the abovementioned topics from the perspectives of critical urban geography, urban political economy, sociology, and gender and feminist studies. This study points out that the patriarchal roots of the financialization of housing originate from the exclusion of housing from the social provision and from its conversion to a financial asset, subordinating its use value to its exchange value. This logic strengthens gender inequalities in the form of women facing a higher debt burden to pay for housing, an increase in their unpaid reproductive labor and salaried labor, and the reinforcement of the gendered division of labor.