bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Sales Dynamic Forecasting Method Based on Time Series Analysis in Global Supply Chain Environment
Authors: Zhu Huiru
Published: November 2024

This paper uses time series analysis to forecast sales dynamics in a global supply chain environment. The study selects supermarket chain data with typical time series characteristics and extracts features from it. We combine the delay operator’s difference operation with the ARMA model to construct the ARIMA model, which predicts and analyzes the sales volume of the supermarket chain dataset from 2016 to 2018. To address the issue of time series models being susceptible to nonlinear characteristics and random variables, this paper integrates the ARIMA model and the random forest RF model into a simple weighted average, forming the ARIMA-RF model. The accuracy of the model for sales volume prediction has greatly improved compared to the ARIMA model and RF model, with an accuracy rate as high as 99%. Meanwhile, the ARIMA-RF model has the smallest RMSE value among all the compared models and has the highest prediction accuracy among all the models for the sales volume in the 3rd quarter of 2018.
Research on Dynamic Monitoring and Evaluation Model of Cadre Building in Colleges and Universities
Authors: Yao Jiaqin
Published: November 2024

In today’s context of rapid development of higher education, college cadres as the core force to promote the development of the school, its construction and management is particularly important. This paper adopts B/S architecture and MVC design, introduces the dynamic monitoring mechanism of the construction of college cadres, and builds a dynamic monitoring system. The assessment model adopting the multiple regression method is used to evaluate the cadre force’s response to changes in work efficiency through real-time and comprehensive data collection and analysis. The dynamic monitoring system’s online situation on Saturday and Sunday is not as good as it is on Monday to Friday, as found in this paper’s research. And dynamic monitoring can increase the willingness of cadres to learn different subjects and improve their knowledge. Dynamic monitoring can also enhance the average grade of the cadres, and the average grade after the implementation of dynamic monitoring is approximately 9.88 points higher than before monitoring. Overall, the cadre’s satisfaction with dynamic monitoring is high, with an evaluated satisfaction score of 4.92 on the nine indicators of the survey. A one-unit increase in “Monitoring management” is associated with a 0.694 increase in the work efficiency of the cadres, which is the most influential factor in dynamic monitoring. In conclusion, dynamic monitoring helps to provide strong data support for the construction of college cadres and to build high-quality, professional college cadres.
A study on the relationship between career planning education strategies and student development based on big data analysis
Authors: Li Bing , Yang Ting
Published: November 2024

In an environment where the number of college graduates is increasing year by year, the education of college students in career planning is particularly important. However, the practical aspects of teaching pose additional challenges. Based on big data analysis technology, this paper designs an optimization strategy for career planning education. We have established a joint school-enterprise model of career management for college graduates to streamline career matching in career planning education. We then use the improved SARIMA-BP neural network model to predict the trend of career demand, providing students with personalized career planning advice and employment guidance. Clear career planning, setting clear development goals, studying diligently, understanding one’s strengths and weaknesses, and understanding the demand for professional competence in career positions all demonstrate significant positive correlations, with correlation coefficients greater than 0.5. This indicates the necessity of a career planning education strategy based on big data analysis and its positive promotion effect on students’ development.
Research on the process of pickling cucumber with compound pickling agent and its optimization
Authors: Shi Shouji
Published: November 2024

Pickled cucumber is a favorite pickle product of the general public, but the long-term or excessive consumption of traditional high-salt pickles seriously threatens people’s health. In this paper, after the subject samples were pickled according to the process flow, one-way and orthogonal tests were designed to experiment with the optimum additive amount of composite pickling agent for cucumber, and meanwhile, the amino acid content of cucumber in different pickling methods was calculated. The Gaussian process regression model’s learning process was optimized by choosing the squared exponential covariance function. The cuckoo search algorithm is proposed, and the improvement of the cuckoo search algorithm is achieved by combining step length adaptive change calculation and chaotic sequences. Jointly improve the cuckoo search algorithm and Gaussian process algorithm, construct the agent model of the pickled cucumber recipe, get the final pickled cucumber recipe parameter design results, and verify the optimization effect of the process through the control experiment. The experimental results show that the best pickling combination is the composite pickling agent with 0.1% addition of acetic acid, 1.5% addition of mannitol and 0.06% addition of calcium lactate, and the sensory score of the cucumber pickled from that place is 92.8564. After optimization, the amino acid content of the cucumber pickled using the composite pickling agent is only 0.03889g/100g, and the quality of the cucumber has been improved.
Visual Perception Modeling and Aesthetic Effect Evaluation of Interior Design Integrating Natural Elements
Authors: Liu Hui
Published: November 2024

The reasonable integration of natural elements in interior design needs to follow the principles of aesthetic color matching and visual perception theory. In this paper, we constructed an aesthetic assessment model for natural elements in interior design based on visual perception, using aesthetic color features, texture features, and higher-order semantic features. Firstly, we calculate the color histogram of the HSV distortion map to obtain the distortion’s description. The texture features are extracted using GLCM combined with LBP to capture the spatial relationships of different gray levels in the image within the global range. Smoothing the LBP features reduces the impact of noise on feature extraction, and the attention mechanism is employed to exclude redundant information in higher-order semantic features. The model is constructed and then tested on four datasets, including LIVE, to assess the aesthetic effect of visually perceived images, and it is found that the model in this paper performs at a better level in the four image libraries. Three practitioners applied the model to carry out interior design for a project, and the final work was rated by experts at 86 or above, with a mean score range of 82 to 92 for each dimension. In the process of using the model to evaluate the design draft for improvement and optimization, the model provides the designers with the functions of checking and filling the gaps in composition, light, and other aspects and optimizing the aesthetic color assessment so that they can complete a balanced and high-quality interior design work with natural elements, and all the dimensions of the aesthetic assessment have been paid attention to and optimized, and the overall interior design effect is more balanced, and this paper’s model meets the design expectations.
Legal and Ethical Considerations of Computer-Assisted Data-Legal Decision Support Systems in Digital Governance
Authors: Chen Long
Published: November 2024

Computer technology provides technical guarantee for legal decision-making and digital governance, and also brings related legal and ethical topics. The functional requirements of the data legal decision support system are examined in this paper, and the architecture design is completed by adopting the MVC pattern and three-layer B/S architecture. Based on this basis, the network topology and database design of the system have been completed. The analysis shows that there is a significant positive correlation (β=0.173, 0.127, 0.378) between the frequency of use, the length of use, the position of the user and the quality of decision-making of the legal decision-making support system and that the speed of approving a certain type of contract of Company M using this system has been increased by as much as 80.67%, and that litigation costs of 10.8 million yuan are saved after the system partially replaces the external lawyers. In addition, users have a positive evaluation of the system’s professionalism. The legal and ethical considerations related to this decision support system in digital governance are examined in this paper.
Exploring the Reform and Innovation Path of Physical Education in Colleges and Universities under the Background of Internet
Authors: Lv Pin
Published: November 2024

The Internet background and the rapid change in science and technology promote the innovation of traditional college physical education, and the study uses the OpenPose method to detect the key points of students’ bodies in physical education and evaluate their postures. Meanwhile, based on the extraction of feature information of students’ movement postures, the DTW algorithm solves the problem of the inconsistent length of the video sequence of movement postures, matches students’ movement postures, and determines whether the activities of various joints are standardized during students’ movement. The evaluation index system of college physical education is constructed to evaluate the college physical education teaching method proposed in this paper. Apply the method of this paper in practice, using the method of comparing and analyzing the students’ academic interest, physical fitness, motor skills and motor posture before and after the experiment to explore the effectiveness of this paper’s method. The evaluation of the physical education method scored the highest on the secondary index of technology application, the lowest on learning resources, and the highest on the tertiary index of “the ability to use modern educational technology” and “timely and accurate student feedback”. The lowest scores were for “reasonable layout of learning space” and “completeness of facilities”. Before the experiment, the P value of the tennis program of the two groups of male and female students in the 10 dimensions of academic interest, physical fitness and motor skills and the mobility specification of 4 types of joints was greater than 0.05. After the experiment, the two groups of male and female students performed better than the control group in academic interest, physical fitness, motor skills and the mobility specification of joints, and the P value of the two groups of male and female students was less than 0.05. This paper shows that the OpenPose-based approach to physical education in higher education has yielded positive outcomes.
A Study on the Construction of Knowledge Mapping for Teaching English Politeness in Global Cultural Communication in the Information Age
Authors: Bao Lina
Published: November 2024

In this paper, based on the characteristics of teaching English polite phrases, the acquired research data are subjected to the segmentation operation, and a graph convolutional neural network is used to iteratively train them, finally completing the modeling of the knowledge graph of English polite phrases and determining the parameters of the model. The constructed knowledge graph is ready to be introduced into the English polite language teaching activities, and a model for teaching English polite language has been designed based on it. Simulation experiments and independent sample t-tests are used to validate and analyze the knowledge graph model and the teaching model, respectively. Upon analysis, it was found that the model in this paper could quickly and accurately identify the number of times the English verbs of polite phrases appeared, which was reflected in the fact that Promise appeared five times and Praise appeared four times. After the teaching intervention, the English test scores of students in Group E (Mean: 15.994) were significantly higher than those of Group C (Mean: 12.152), and the difference between the scores of the two groups was statistically significant (t=6.811, P=0.002<0.05), which confirmed that the English politeness language teaching model of the Knowledge Graph has a facilitating effect on the students’ English scores, and at the same time, summarized the effect of English politeness language education in cultural communication. This study improves the quality of English polite language teaching and students’ learning effect so that the informatization of English polite language teaching in colleges and universities can be further developed and plays a role in promoting global cultural communication.
Research on Virtual Character Behavior Simulation and Control Algorithm in Digital Movie Production
Authors: Cao Qinfan
Published: November 2024

Aiming at the inefficient design of virtual character behavior in traditional digital movies, this paper proposes to construct a virtual character behavior and control model. The virtual character’s behavior is constructed using a behavior tree, and perception and decision-making behavior models are created to optimize the visual perception of the virtual character. After the behavioral modeling is completed, the action controller is used to generate the character’s behavioral actions, combined with the physical dynamics method to capture the character’s trajectory, and the feedback control theory is applied to output the character’s joint rotation data information to realize the behavioral control of the virtual character. In the digital movie scene design of firefighters fighting and rescuing, the acquisition and execution time of a single behavioral modeling sample of this paper’s virtual character behavioral modeling method is 0.01s~0.03s, and the maximum running iteration time is 63.83s, which is faster than the agent-based behavioral modeling method. Compared to the traditional virtual character behavioral control method, which has an offset of more than 4mm, the virtual character firefighter generated in this paper has an offset of less than 0.3mm, which provides better control accuracy.
Innovative Practice and Teaching Reform Strategies of Artificial Intelligence Technology in the Teaching of Higher Vocational Food Testing
Authors: Chen Xiangjun , Duan Chunyan , Hu Zhenlong
Published: November 2024

The modern practice of teaching food safety testing technology at a higher vocational level emphasizes the cultivation of innovative and application-oriented talents, combining theory with practice. This paper integrates the classroom system reform and practical teaching system reform needs and puts forward the basic + professional + expansion of the three modules, innovative practice teaching mode. The reform of food testing teaching, through the introduction of relevant food safety hot news or topics, the use of the “introduction, measurement, learning, practice, solid, evaluation” six-step teaching method, and innovative classroom teaching links. Analyze the spectral data model commonly used in food testing, solve the parameter optimization problem for the SVM model, and improve the professional technology for food testing. Utilizing virtual reality technology to build a test operation environment, build an environment for practical food testing, and update the traditional test operation. Simulate the optimization of the scene for food testing in a virtual operation environment. Comparative analysis of various learning dimensions of higher vocational students to illustrate the role of higher vocational food testing teaching reform using the six-step teaching method. The satisfaction levels of senior students with traditional teaching and teaching reform are 3.45 and 4.25, respectively, and the difference between them is 0.8.
A Quantitative Study of Chineseized Musical Styles in the Piano Composition of the Yellow River Concerto Based on Audio Analysis
Authors: Dai Liping
Published: November 2024

The piano concerto “Yellow River”is one of the most influential works in Chinese piano concertos. This paper designs an ANN beat classification model based on audio analysis, calculates the beat cycle of the piano piece, and synthesizes the beats of the piano piece using the PSOLA algorithm, presenting an audio analysis of the piano concerto “The Yellow River”. Collate the compositional techniques and layout elements, musical characteristics, and points of nationalistic performance styles of the piano concerto“Yellow River”. Verify the universality of the audio analysis technique for the piano piece by identifying beats from different musical styles. The validity of the ANN-based audio analysis is determined by the piano keys and the audio selections of the piano concerto of “The Yellow River”. Select the classic performance version of the “Yellow River” piano concerto and count the total duration of different performance versions. Combining the designed audio analysis technique for piano compositions, the performance speeds and average speeds of each version are visually organized. Analyze the creative expression of the performance speed on the emotion and style of the piano concerto of “The Yellow River”. In the whole work, the solo piano melody has 187 beats in total. Yin Chengzong, Lang Lang, and Wan Jieni have the same average speed as 70.3 beats, 72.4 beats, and 59.3 beats, respectively. The overall tempo design of Yin Chengzong and Lang Lang has obvious peaks, and Yin Chengzong’s playing speed has a higher degree of ups and downs. The music has a more fluid feel, and the playing speed is used to demonstrate the immense momentum.
Research on Strategies to Enhance the Interactive Experience of Content Analysis and Practical Parenting of Civic and Political Education in Colleges and Universities in the Era of Big Data
Authors: Guo Yanping , Hao Binbin , Li Meijie
Published: November 2024

In the context of the big data era, the quality of ideological and political education puts forward higher requirements, while practical parenting highlights the higher value of ideological and political education in colleges and universities. This paper focuses on the three core elements of the operation mechanism, optimization mechanism, and evaluation mechanism to enhance the interactive experience of ideological and political education and practical parenting for college students. In the operation mechanism, a social practice composite parenting structure is innovatively proposed. In the optimization mechanism, three types of practical education mechanisms are proposed: leading type, teaching type, and service type. In the evaluation mechanism, the evaluation index system for practice parenting effectiveness is proposed, and dimensionless processing is utilized to eliminate the influence of the index scale. The judgment matrix is constructed using the hierarchical structure model. Empirical analysis is used to explore the effectiveness of the innovative, practical parenting mechanism for promoting ideological and political education in universities, using the pilot university H as an example. The results show that University H has the optimal teaching management dimension (0.31), the second best practice parenting infrastructure (0.20), and the practice teaching (0.06) dimension, less desirable, among the seven first-level evaluation dimensions. Therefore, in the work of ideological education in colleges and universities, it is necessary to strengthen the countermeasures from the aspects of improving ideological understanding, perfecting the organizational system, increasing the financial guarantee, and constructing the incentive system so as to comprehensively improve the effectiveness of practical education activities for college students.
Research on Intelligent Multimedia Technology Path of College Students’ Mental Health Education in Higher Vocational Colleges and Universities
Authors: Ji Difei
Published: November 2024

Multimedia in modern educational technology has the advantages of being infectious and easy to stimulate students’ interest, which can change students’ perception of things and enhance their mental health awareness when carrying out mental health education in higher vocational schools after analysing the advantages of the application of modern educational technology in mental health education. Taking the visual characteristics of multimedia learning screen as an entry point, we explore the internal logic and law of its influence on students’ learning emotions, hoping to use the learning screen carrying emotional value as an intermediate medium. Subsequently, a CNN-based emotion recognition model is constructed to analyse learners’ expressions, visual emotion preferences and the emotions of the learning screen, and adaptively adjust the key visual features of the learning screen so as to regulate the learners’ learning emotions, stimulate the learners’ interest in learning, and guide the learners’ emotional state. Based on this, a method of using intelligent multimedia technology to promote students’ mental health education is proposed. Combined with the results of teaching experiments, it can be seen that this paper’s innovative mental health education method has improved students’ positive academic emotions significantly, negative academic emotions improved to a certain extent, and the level of mental health has been further improved.
Strategies for Cultivating Students’ Spatial Imagination in Art Courses of Colleges and Universities Assisted by Virtual Reality Technology
Authors: Li Junjun
Published: November 2024

With the continuous progress of society and the deepening of the new curriculum reform process, art curriculum education needs to enable students to improve their spatial imagination in a positive emotional experience. This paper promotes the integration of virtual reality technology into art curriculum education with the help of IVLE technology. It is proposed to improve students’ spatial imagination in the art curriculum by applying practice courses, establishing practice environments, and selecting practice objects. The purpose of the virtual reality spatial cognition assessment dataset is to assess students’ spatial imagination. Extract the performance and behavioral characteristics of students, respectively, and use the Lasso regression algorithm to add regularization terms behind the loss function of the linear regression model to reduce the problem of covariance. The model was trained and evaluated through simulation experiments. All the prediction points of the Lasso regression model were within the 95% confidence interval, and the mean value of the difference score was 0.0909, with the maximum of the true value and the predicted value not exceeding 2. Comparing the effects of traditional art course education and immersive art course teaching with VR technology on the enhancement of spatial imagination, from the later stage of the experiment, all the dimension scores of the experimental group’s spatial imagination were higher than those of the control group, and the total scores were higher than the total scores of the control group. The score difference between the control group and the scores is 5.886 points. Virtual reality technology has a greater effect on cultivating students’ spatial imagination.
A Study of Administrative Data Security Operation Strategies in Higher Education
Authors: Li Tao , Xu Jiang
Published: November 2024

Good data security management is the foundation and prerequisite for data-enabled higher education and improving the modernized governance capacity and governance level of higher education. Accordingly, the study proposes a data security management system based on a blockchain scenario as a data security operation strategy for higher education administration. The FAHP-FCE model for evaluating the level of data security is constructed based on fuzzy hierarchical analysis and fuzzy comprehensive evaluation. The system of this paper is applied to University Z for administrative data security operation and comprehensive evaluation. The comprehensive evaluation score of administrative data security management of the university is 82.542, and the evaluation result is five levels, which is good, and verifies that the data security management system based on blockchain technology can manage the administrative data of the university securely.
Criminal law regime for electronic money crimes in the context of the digital economy
Authors: Li Zhe
Published: November 2024

E-money is a product of the fusion and development of network technology and digital economy, which has the attributes of data, property and money, and the current Criminal Law’s regulatory response to e-money crimes has highlighted the inadequacy. In order to improve the criminal law regulation of e-money crimes, this paper combines the Siamese-BiLSTM model based on the attention mechanism and TextRank algorithm to design a similar case retrieval model for e-money crimes, in order to analyze the loopholes of the criminal law regulation and the reasons for their emergence, and thus to give the path suggestions. Compared with the baseline model Siamese-BiLSTM, the accuracy and F1 value of the improved model in this paper are improved by 5.09% and 5.20% on average, respectively, and the removal of any module leads to a decrease in model performance. This indicates that the improvement of the e-money crime similar case retrieval model based on SBA+TextRank in this paper is better, and it is applicable to the similarity calculation of legal case texts. This paper provides a feasible path for improving the criminal law system for e-money crimes.
Informatization of the Traditional Literature of Donglu Drums and Its Supporting Role for Inheritance
Authors: Ma Xintao , Liu Na
Published: November 2024

In the face of a large amount of information on access to the literature resources of Donglu Drum, there is an urgent need for a tool to conduct in-depth research and analysis of this information to discover valuable laws so as to better guide the literature library’s inheritance work on Donglu Drum. This paper first improves the K-Means algorithm, using clustering methods to achieve a cluster analysis of literature access to understand the access information of literature access to the East Road drum literature resources, according to the clustering results of the number of different groups of people to understand the access to the literature resources and make a literature incorporation countermeasures for the literature preferences of the group of people with a larger number of access. Then, the Apriori algorithm is improved, and the association rules are used to analyse and mine the information of the literature accessers so that the literature librarians can carry out personalized services according to the preferences of the literature accessers, guide the accessers to access the relevant literature and improve the efficiency of their access to the literature, and at the same time, enhance their interest in the East Road Drums. Questionnaire survey results in 11 people think that with the use of algorithms combined with the digital library, their interest in understanding the East Road drums can be increased, 10 people said that they are willing to go to the offline close to appreciate the East Road drums opera. It shows that the efficient East Road Drum literature informatisation based on cluster mining and association rule mining has enhanced the interest of the masses in East Road Drum, and at the same time, it has supported the inheritance of East Road Drum to a certain extent.
A Study on the Strategies and Applications of Internet Financial Tools in E-Commerce to Promote Rural Common Wealth
Authors: Qi Yue
Published: November 2024

The insufficiency of Internet financial tools seriously restricts the development of rural e-commerce and its utility play in China. In this paper, after studying the common wealth mechanism of Internet financial tools in e-commerce, we use the entropy power method to measure the level of the rural common wealth, and use the panel regression model, Dagum’s Gini coefficient, and spatial econometrics model to study the relationship between Internet financial tools, e-commerce, and rural common wealth. The results show that the overall level of rural common wealth in China has increased significantly, but the gap between regions has widened, showing the development trend of ‘high in the east, fast in the centre, stable in the west and lagging in the northeast’. Internet financial tools can help rural e-commerce play a significant role in narrowing the income gap between urban and rural areas and promoting common prosperity in rural areas, but this effect may vary significantly depending on the geographical location, digital technology and e-commerce development level of each region. The article provides valuable policy insights for promoting the synergy development of rural e-commerce and Internet financial tools to achieve a common prosperity.
A legal study of transparency and fairness in algorithm-driven legal decision support systems
Authors: Rong Shengji
Published: November 2024

Nowadays, more and more legal decisions are being made with the help of machine learning models and algorithmic drives. Avoiding or reducing human bias in the decision-making process is extremely important for the fairness and transparency of the algorithms in legal decision support systems, and also profoundly affects the fairness and transparency of legal support systems. The article develops a system for supporting legal decisions based on the decision tree. By improving the traditional decision tree algorithm, the decision tree can be used to mine and classify unknown legal text data samples. Finally, the transparency and fairness of the legal decision support system proposed in this paper are legally researched, and legal decision accuracy is measured. Through experimental research, this paper concludes that the average accuracy of decision-making in commercial and copyright cases is 89% and 91%, and overall, the legal decision support system based on the decision tree proposed in this paper has good decision-making accuracy.
Computer Vision Based Multimedia Advertising Effect Enhancement Strategy in E-Commerce Practice
Authors: Wang Liang
Published: November 2024

In the context of today’s Internet-developed era, novel advertisement design is part of the enterprise marketing means. To improve the effectiveness of multimedia advertising on e-commerce practices, the study developed a multimedia advertising design system based on a generative adversarial network. The study proposes a generative adversarial network mechanism for computer vision technology, constructs an intelligent generation model of advertisement images using the generative adversarial network, designs a multimedia advertisement image interaction system, and explores the visual communication effect of multimedia advertisements. In order to test the significance of the advertisement image generation model for the display of advertisement images, a performance comparison test is conducted with other image generation models, and then the multimedia advertisement proposed in this paper is put into e-commerce practice. The study shows that the advertisement image generation model can accurately generate multimedia advertisement images, and the generation of multimedia advertisements based on the antagonistic network has a significant effect on the pleasant mood of e-commerce customers (p>0.005). Therefore, the multimedia advertising enhancement strategy proposed in this paper is conducive to mobilizing customers’ positive mood in e-commerce, and its practical effect is significant.
Sentiment Propensity Analysis of a Multimodal Chinese Corpus Using Fuzzy Logic
Authors: Chen Chunrong
Published: November 2024

In the face of massive multimodal information, it has become one of the current research hotspots to categorize it according to its sentiment so as to guide users to find valuable information from a large amount of data. Based on the application of fuzzy logic in sentiment analysis, this paper designs a method to analyze sentiment tendencies in a multimodal Chinese corpus. Firstly, text, audio, and video features of the multimodal Chinese corpus are extracted, and a fuzzy sentiment dictionary is constructed. Then, the double hesitant fuzzy set is used to reduce the intensity of the sentiment, and the fuzzy sentiment value is calculated. Then, the fusion of sentiment lexicon, intuitionistic fuzzy inference, and fuzzy comprehensive evaluation model is used to obtain the final sentiment tendency analysis results. The models constructed based on different lexicons all converge after 4 epochs, indicating that the model has strong feature learning ability. After combining the sentiment lexicon, the accuracy of the model’s sentiment classification improves by 2.27%. Compared with other common sentiment classification models, the precision rate, recall rate and F1 value of this paper’s model are improved by 2.41%-6.57%, 2.36%-4.91% and 2.38%-5.58%, respectively. The result of inclination to positive in the sentiment analysis of this paper’s model is 82.3%, with a difference of only 1% from the average value of 83.3% of user evaluation, and it is better than the analysis model of plain text (80.8%), which proves that the multimodal sentiment analysis model in this paper can correctly complete the analysis of sentiment inclination of the review data. This paper provides a new feasible approach for the propensity analysis of multimodal sentiment.
Security and Risk Control of Enterprise Supply Chain Finance in the Context of Digital Economy
Authors: Chen Xi
Published: November 2024

The widespread application of new-generation information technologies, such as the Internet of Things (IoT), has brought about significant changes in the operating environments of enterprises and the supply chains in which they operate. At the same time, enterprises aim to maximize profits while minimizing enterprise risks. This paper examines the risk assessment of enterprises in supply chain finance based on the relevant literature review. First of all, after combing and defining the relevant applications of digital technology in enterprise risk prevention and control, a Logistic enterprise risk assessment model under supply chain finance is constructed, and the parameters of the model are optimally selected and estimated for testing. The main factors affecting enterprise risk are analyzed from four dimensions: enterprise, core enterprise, financing asset risk and supply chain-related aspects, and a set of index systems suitable for enterprise risk assessment under supply chain finance is established by using correlation analysis, RF and Lasso regression methods. x3, x4, x5, x6, x7, x9 and x15 are negatively correlated with the enterprise risk, and the gross profit margin and the top five customers’ gross profit margin are negatively correlated with the enterprise risk, while sales and profit margin are negatively correlated with the top five customers’ gross profit margin. The correlation between enterprise credit risk and gross margin and the proportion of sales revenue from the top five customers is positive. The accuracy of prediction of the evaluation model is 93.3%. It can be seen that the proposed logistic assessment model is reasonable and effective, and can be practically applied in the security and risk control of enterprise supply chain finance.
Dynamic analysis of nonlinear features for high-precision fault diagnosis of large pumps and compressors in oil and gas fields
Authors: Cui Jian , Dong Lei , Sun Xueyi , Yang Xiaotong , Lei Ming
Published: November 2024

The nonlinear and dynamic complexity of the oil and gas engineering system itself leads to an increase in the chances of accidents in the system, and the financial and material losses caused by system failures are incalculable. The study proposes a new fault diagnosis method based on evidence theory and the KPCA algorithm, and analyzes the fault characteristics of large pumps, compressors, and other high-precision equipment under high-speed operation. A set of fault feature vectors reflecting the change of nonlinear characteristics of the system is extracted, and the similarity between the patterns is used to obtain the mass function of each evidence. The simulation experiment results show that the fault diagnosis accuracy, leakage rate and F1 score of the DS-KPCA algorithm in the TE process dataset are 97.56%, 1.98% and 98.99%, respectively, and the method is significantly better than the traditional method in fault detection. Practical application shows that in the production process of oil and gas fields, this rapid fault processing method is characterized by clarity, speed, and accuracy, which significantly improves the efficiency and accuracy of fault processing.
Research on logistics cooperative scheduling method based on multi-intelligent body system in supply chain management
Authors: Guo Yirong , Zhang Xuefeng , Zhang Shaoqing
Published: November 2024

Collaborative scheduling of logistics is one of the core problems in supply chain management. In this paper, a multi-intelligent system is used to establish the path planning algorithm of intelligent bodies and optimize logistics scheduling in the supply chain by improving the ant colony algorithm. The improved MAPPO algorithm is obtained by introducing the deformation encoder and attention mechanism on the basis of MAPPO to realize information synergy between multiple intelligences. The candidate order table is established to update the local and global pheromones, and the ACO algorithm is improved with the help of adaptive adjustment of volatility coefficients to avoid the basic ACO algorithm from falling into a local optimum in the object classification scheduling problem. The improved MAPPO algorithm significantly outperforms other algorithms in terms of convergence speed and stability in multi-intelligent body fixed and non-fixed goal path planning, and the path planning results and reasoning time also show obvious superiority among the compared algorithms. Taking the logistics scheduling of peaches as an example, the algorithm in this paper can significantly save costs and reduce the delayed pre-cooling cost to 0, effectively solving the problem of pre-cooling delay in logistics scheduling.
Research on Informatization Construction and Teaching Reform Path of Physical Education Teaching in Colleges and Universities
Authors: Li Hao
Published: November 2024

Firstly, the improved OpenPose is used to obtain the skeletal point coordinate data and normalized, and then the human gesture features are extracted according to the spatial geometric relationship of human morphology to improve the differentiation degree of the gesture features on similar actions in the basic sports actions, which is used for the gesture matching of the basic sports actions. On this basis, the DTW posture matching algorithm based on human differentiated posture features is proposed, which realizes the posture matching and carries out the evaluation and result feedback of students’ sports movements. Finally, we construct a sports movement evaluation system based on the aforementioned method, which compares the movement video with the standard movement from the template library and provides feedback on the movement’s evaluation results. The system allows teachers to access the learning situations of numerous students’ movements, while the system provides feedback for movement learners to adjust their movements, thereby facilitating a convenient and informative interaction in sports movement teaching. After seven weeks of experimentation, there is a significant difference between the assessment scores of the experimental group and the control group, and 90% of the students are satisfied with the application of the sports movement assessment teaching system to assist teaching. It proves that the intelligent teaching structure and diversified teaching methods promote students’ learning efficiency and performance, significantly improve students’ motivation to learn physical education courses, and further improve the demand for an information-based teaching environment.
A Study on Optimizing Teaching Assessment Methods in Mathematical Modeling Courses by Combining Big Data Analytics Techniques
Authors: Li Yanyan
Published: November 2024

In this paper, starting from the teaching practice of mathematical modeling courses in colleges and universities, the application of fuzzy mathematical theory in teaching evaluation systems is studied, and the fuzzy evaluation model established by using fuzzy mathematics is analyzed and designed in depth, and the fuzzy matrix arithmetic process is given to realize the construction of a fuzzy comprehensive judging model. Given the substantial volume of data gathered to assess the teaching performance of teachers in mathematical modeling courses, direct classification is a challenging task. This paper introduces an unsupervised K-means algorithm that quickly classifies all the collected data and builds a teaching evaluation system for university mathematical modeling courses using relevant web development techniques. This paper's teaching evaluation system is helpful for teachers to improve their teaching situation and adjust their teaching strategies in a timely manner. The cluster analysis organized the teachers into four categories: excellent, good, moderate, and poor. The evaluation results were obtained after evaluating the fuzzy comprehensive evaluation model. The system's evaluation results in this paper demonstrate a confidence level of more than 0.85. It shows that the system is more reasonable, and its use accelerates the efficiency of teaching evaluation in the mathematical modeling course in colleges and universities, which greatly improves teaching management.
Optimization of sustainable development path of grassland ecotourism in Hulunbeier City based on data mining technology
Authors: Zhao Yiding , Chang An
Published: November 2024

In recent years, the status of ecotourism in mass tourism has gradually increased, among which the grassland ecotourism market is booming. The study uses data mining techniques to extract POI data for grassland ecotourism in Hulunbeier City. The mined POI data of grassland ecotourism in Hulunbeier City are analyzed by using nearest-neighbor distance index analysis, multi-distance spatial clustering, kernel density estimation, standard deviation ellipse, and geodetector model to explore the spatial agglomeration characteristics of grassland ecotourism in Hulunbeier City, the grassland tourism development pattern, and the influencing factors of grassland ecotourism. Accordingly, the sustainable development of grassland tourism in Hulunbuir City is proposed. The nearest neighbor index (NNI) value of grassland tourism in Hulunbuir City is 0.64 (less than 1), and the NNI index of the 13 flags (cities and districts) under the jurisdiction of Hulunbuir City is less than 1, which indicates that the grassland tourism industry is characterized by agglomeration and distribution within the city of Hulunbuir. The grassland ecotourism industry in Hulunbuir City presents a spatial distribution pattern of “multi-core agglomeration” with large agglomeration and small dispersion. The high-density cores are located in New Barkhu Left Banner, Manzhouli, Hailar District, Chenbalhu Banner, and Ergunar City. There are eight subdivided types of grassland tourism development patterns in Hulunbeier City. The four major categories of single dominant, double dominant, strong integrated, and weak integrated accounted for 34.11%, 23.55%, 7.09%, and 35.25% of the total, respectively. The spatial distribution of tourism in Hulunbeier Grassland is more influenced by natural geographic factors than socio-economic factors.
Kinetic modelling of olanzapine interactions with ciprofloxacin and norfloxacin in adult male Wistar rats: unraveling the mechanism of drug-drug interaction
Authors: Chirali Ana-Elena , Ciocotişan Iulia Maria , Vlase Ana-Maria , Muntean Dana Maria , Vlase Laurian
Published: November 2024

This study aimed to investigate the kinetic modelling of drug-drug interactions between olanzapine and the antibiotics fluoroquinolone, ciprofloxacin and norfloxacin, using a three-step compartmental modelling approach. Olanzapine is metabolized mainly by CYP1A2, which is inhibited by both antibiotics, affecting its disposition in the body. The proposed models evaluated the absorption, distribution, metabolism, and excretion of olanzapine and its main metabolite, N-desmethyl olanzapine, given alone and during co-administration with antibiotics. Ciprofloxacin completely inhibited presystemic metabolism, resulting in a 2.2-fold increase in olanzapine exposure, whereas norfloxacin reduced but did not eliminate this metabolic pathway, resulting in a 3.2-fold increase in olanzapine exposure. Both antibiotics also reduced the clearance of N-desmethyl olanzapine, leading to increased concentrations of the metabolite. These results provide insight into the kinetic interactions between olanzapine and fluoroquinolones, helping to optimize dosing strategies when co-administration is nedeed.
An Examination of Civil Servants’ Assessment of the New Civil Service Reforms in Kazakhstan
Authors: Issenova Gulnara , Bokayev Baurzhan , Nauryzbek Madina , Torebekova Zulfiya , Kosherbayeva Aigul , Amirova Aigerim
Published: November 2024

In recent years, Kazakhstan has demonstrated a strong commitment to make the civil service system open and transparent to its citizens. The country has introduced an e-government system to improve access to information and allow public consultation on civil service. Reforms of the civil service aim to reduce corruption in the civil service and to ensure a transition to a career-based model, meritocracy, and result-based remuneration.

This study aims to expand the literature on the civil servants’ appraisal toward new civil service reforms both in Kazakhstan and in worldwide. As a part of the broad investigation, this research provides the results of a sociological survey examining the assessment of civil servants toward recent civil service reforms in Kazakhstan. The survey has been conducted among 14,250 respondents aged 20 years and older from 14 regions of Kazakhstan, including three cities of republican significance and the capital city of the country – Astana. According to the survey results, civil servants are satisfied with the current state of the civil service system in Kazakhstan. The items on satisfaction mainly refer to the working conditions in the government agencies like work schedules and organizational climate. The research further reveals factors influencing the general evaluation of civil servants, as well as the most critical problems in the national civil service system.