bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study of the Intersection of Traditional Calligraphy and Digital Media Art
Authors: Xiong Peijun
Published: July 2024

As a classic representative of traditional culture, Chinese calligraphy art has more and more obvious advantages in today’s digital media art creation. In this paper, the calligraphic text image is binarized by the OTSU method, the image enhancement is realized by linear gray value stretching, and the optimal tilt correction method is used to preprocess the traditional calligraphic text image and make a font library. Based on the data from the calligraphy font library, an immersive digital interactive context of traditional calligraphy is designed using digital media art. Pix2Pix network is introduced to combine with the PatchGAN network to establish a style migration network for traditional calligraphy text images, and three different types of loss functions are designed to ensure the accurate generation of traditional calligraphy text. The L1 loss of this paper’s model in generating traditional calligraphy characters is only 0.0359 at the lowest, the similarity values of the generated samples of calligraphy characters are mainly between 90% and 96%, and the maximum error of the relative position and relative size of the radicals is only 1.18%. The average value of the G2R indicator for the users’ images of calligraphic characters was 75.23%, and 89.86% of the users indicated that they were basically satisfied with the immersive interactive context of traditional calligraphy. Traditional calligraphy can achieve digital transformation and provide audiences with more diverse cultural experiences by relying on digital media art.
Research on Online-Offline Blended Teaching of Piano Course in Higher Vocational Colleges under the Background of Internet
Authors: Zhang Fang
Published: July 2024

Online teaching is becoming an important means of education, but for the piano course, how to organically combine online and offline teaching has been the focus of educators. To improve this situation, this paper proposes a neural network model for piano performance evaluation as an auxiliary means of blended teaching. The model uses bidirectional LSTM training data, introduces an attention mechanism to optimize data recognition efficiency, and finally generates performance evaluation through a softmax classification algorithm. After implementing online-offline hybrid piano teaching in combination with this evaluation model, 66.72% of the students believed that the new teaching method could stimulate learning initiatives. The piano performance test scores showed that the post-test times for single-note playing, mixed intervals and chords, and two-handed ensemble playing in the experimental group were reduced by 38 seconds, 45 seconds, and 7 minutes, respectively, and were significantly higher than those in the control group. This indicates that the performance evaluation model has good performance and application effectiveness.
The Promoting Effect of Organic Integration of Sports and Aesthetic Education on College Students’ Mental Health in the New Era
Authors: Zou Jinding , Zheng Sheng
Published: July 2024

College sports is an important part of college education, has the important function of fitness and heart health, and is an important way to cultivate the mental health of college students. This paper selects a representative number of colleges and universities from a certain region as the object of investigation, measures the organic integration of college sports and aesthetic education, and proposes the whole-process teaching design for the organic integration of college sports and aesthetic education after digging into the implementation of aesthetic education in college sports courses. On this basis, two natural classes in a college are taken as experimental objects to carry out intervention experiments on the integration of physical education and aesthetic education, diagnose the mental health level of college students by using the symptom self-assessment scale, and compare the mental health level of college students before and after the experiment by using the mathematical statistics method. The current teaching methods of physical education and aesthetic education are relatively traditional, focusing on the lecture-question-and-answer method (84.8%), the movement demonstration method (77.6%), and the movement decomposition and overall practice method (64.8%). After the teaching experiment, the mental health of the students in the two classes showed significant differences in each factor item (p < 0.05). The mental health level of the students in the class that used the integration of sports and aesthetic education for teaching was reduced by 16.83% and 13.77% compared with the pre experimentation and the control class, respectively. The organic integration of sports and aesthetic education has a certain promotion effect on the mental health of college students.
Shear behavior of web huge rectangular opening RC beams
Authors: Du Min , Guo Rui
Published: July 2024

Opening in the web of reinforced concrete (RC) beams will destroy the integrity of the beam and weaken the mechanical properties of the RC beam, such as the bearing capacity and stiffness. The three-point loading test and finite element analysis were carried out on 10 RC beams with a huge rectangular opening in the web. The effects of stirrups around the holes on the shear properties of RC opening beams, such as bearing capacity, deformation capacity, and stirrup strain, were studied, and the shear transfer mechanism of RC beams at the openings was explained by using the strut-and-tie model. The finite element test results are consistent with the actual test results, as shown by the results. When the hole width is small, the reinforcement of stirrups at the hole side can significantly improve the shear capacity of the specimen, but it can also cause chord shear failure. When the hole height is small, with the strengthening of the chord stirrup, the ultimate bearing capacity of the specimen increases, but it can still result in hole-side shear failure. The curve of stiffness degradation is approximately logarithmic. Moreover, according to the finite element stress vector diagram, the shear transfer mechanism of the perforated beam based on the strut-and-tie model has been proved.
A study on automated improvement of securities trading strategies using machine learning optimization algorithms
Authors: Chen Yi
Published: July 2024

Automation in securities trading offers advantages over human subjective trading, such as immunity to subjective emotional factors, high efficiency, and the ability to monitor multiple stocks simultaneously, making it a cutting-edge development path in the securities trading industry. In this paper, we first apply the concept of time-frequency decomposition, gradually moving from the first-order moments of securities prices to the higher-order moments. We then combine this with the EMD time-frequency decomposition method to analyze the securities price sequence and extract the characteristics of the securities price fluctuations. Finally, we use the differential long- and short-term memory network to construct an automatic optimization trading system. We compare the system’s performance with traditional technical analysis indexes, as well as the annualized returns of PPO and A2C models on various securities, to verify its performance under unilateral rising, oscillating rising, and plummeting quotes. Finally, we conducted a live test on 1000 GEM stocks. The system in this paper outperforms all traditional technical indicators, with an average annualized return of 71.85% at the lowest and 127.27% at the highest among 5 securities, demonstrating excellent performance. In the three quotes of Ningde Times, Aier Dental, and Goldfish that are rising one way, rising and falling over time, and rising again, the annualized returns of this paper’s system are 77.13%, 67.16%, and 12.66%, which are higher than those of the PPO and A2C models.
Research on Sports Training Mode of College Athletes Based on Column Generation Algorithm of Recursive Matrix
Authors: Li Xiangmin
Published: July 2024

Athlete training optimization is an important part of sports management, and the scientific management program is of practical significance for athletes to improve their sports level. This paper collects sports training data for cluster analysis, establishes the optimization function of the distance from the data point to the center of the class, solves it, and determines the consistency matrix to judge the data category. Establish the column generation optimization model, get the linear programming model based on the matrix change column generation, in the process of transforming the model to solve the recursive matrix recursive relationship formula and solve the objective function. According to the solution of the optimization function to adjust the athletes’ sports training program. After the test, it was found that the pre-and post-test scores of the three tests of the experimental class were improved by 1.03 seconds, 1.05 meters, and 1.33 meters, respectively, and were significantly ahead of the scores of the control group. According to the satisfaction analysis, 76.67% of students were satisfied with the training effect. It indicates that the new training mode improved by the algorithm has good application effects.
Research on the optimization of teaching content for cloud computing technology in secondary school labor education curriculum
Authors: Mo Dongxia , Mo Bohai
Published: July 2024

Labor education is an important educational course for secondary school students to learn and grow comprehensively. This paper first collects the current improvement direction of secondary school labor education through relevant questionnaires and then introduces cloud computing technology to design an online learning platform for secondary school labor education courses, which assists teachers in completing the labor teaching process. The design of the platform adopts MVC development mode, AJAX asynchronous refresh technology, and other key technologies, analyzes the requirements from three aspects of objectives, performance, and functions, and finally realizes five major modules, including user management, course management, and evaluation management. To address the problem of insufficient evaluation of labor courses, this paper constructs a model of students’ online learning behavior based on the K-means algorithm in the application process of the platform and evaluates the behavior of students’ online participation in labor education courses. By standardizing students’ platform learning information data and analyzing and calculating the learning behaviors of 300 students can be divided into 4 categories, accounting for 16.0%, 34.3%, 23.0%, and 26.7%, respectively, and the teachers of the labor courses can formulate personalized teaching plans for each type of labor learning behavior.
Research on the Future Trends of the Integration of Artificial Intelligence and Fashion Design of Clothing
Authors: Sun Ning , Cao Botao , Mu Xichan
Published: July 2024

Along with the flow of clothing designer personnel, clothing style design technology will be lost, so the intelligent design of the clothing industry, with the development of artificial intelligence technology, has received great attention. In this paper, based on the real-time style migration algorithm to study and design the local pattern of clothing, based on the principle of real-time style migration of images with perceptual loss function, it is proposed to optimize the real-time style migration network by using the group normalization method to obtain the style migration image that is more in line with the visual habit. The fusion of the style migration image with the garment base map through Poisson fusion achieves the end-to-end intelligent design of garment local patterns. The AdaIN-based style migration network model designed in this paper has an average accuracy of 75.758% when trained. Then, the model is applied to the clothing fashion design to evaluate the effect of the garment. The average scores of the overall, front, side, and back evaluation of the dressing effect of the garment are 4.04, 4.15, 4.01, and 3.92, respectively. The garments show a better effect. AI technology will bring more innovative possibilities to the clothing fashion industry and inject new vitality into the fashion industry.
Applying Decision Analysis and System Dynamics Community Governance in the Evaluation of Juvenile Delinquency Prevention Strategies
Authors: Chen Dan
Published: July 2024

From the perspective of juvenile delinquency prevention theory, this paper explores the current situation of juvenile delinquency in rural areas of W County and the mechanism of relevant functional departments in local community governance based on the questionnaire survey method. Then, six juvenile delinquency prevention service programs are selected as the object of evaluation research, and the intelligent decision analysis system of system dynamics is used as the tool of evaluation research to evaluate the six juvenile delinquency prevention programs systematically and comprehensively. The following conclusions were obtained after the analysis. The crime rate of rural youths in County W is as high as 15.8%, with a wide range of crimes. 81.6% of the relevant departments in community governance did not establish rural juvenile records, and about 13% of the departments did not conduct crime prevention training. The Green Clay People Juvenile Crime Prevention Program, which uses social connection theory as a strategy, has an evaluation value of 0.242, and the completion rate of the agreed service indicators specified in the contract is more than 100%. The overall evaluation of the six programs was 87% satisfied. Therefore, the intelligent decision analysis system in this paper has been well applied in the evaluation of juvenile crime prevention strategies, with the progress and development of society, and will occupy an important position in the future for a considerable time.
The Construction of Intelligent Platform in Ideological and Political Education in Colleges and Universities
Authors: Chen Tingting , Liang Jian
Published: July 2024

Based on the feasibility of a personalized teaching platform and user requirements, this paper puts forward the overall architecture design and database design scheme of a personalized teaching platform in ideological and political education, which mainly consists of three functional modules, namely, the knowledge mapping module, ideological and political education course recommendation module, and learning effect evaluation module. After crawling the initial data based on the LTP model, the ideological and political education course resources were extracted and integrated to complete the construction of the knowledge graph module. The ideological and political education course recommendation module is created using the KGCNN algorithm, and then the learning effect evaluation module is constructed by combining the online behavior of students. After testing the system’s performance, the application effect of the teaching platform is assessed. The results show that KGCNN aggregation layer space in the interval of 10~100 can embed data with power law distribution more effectively, and the KGCNN algorithm also has certain advantages in the field of modeling personalized teaching platforms for ideological and political education. The number of experimental classes and ordinary classes with final grades in the L1 band increased by 21.90% and 7.17%, respectively, compared to the midterm, indicating that the personalized teaching platform for ideological and political education courses can effectively promote the improvement of student’s academic performance, and the enhancement effect of students with high levels is more significant.
A Study on Coping with the Psychology of Employment and Entrepreneurship Stress among College Students under the Cognitive Interaction Model (CIM)
Authors: Dang Xiling
Published: July 2024

It is especially important to solve the psychological pressure of college students’ employment if they want to complete their employment and get better development. This paper proposes a cognitive interaction model based on the full information emotion theory and develops the psychological analysis of employment and entrepreneurial pressure on college students on this basis. In the construction of the cognitive interaction model, the basic assumptions of the all-information affective theory are first proposed, the concepts of the individual’s a priori information, a posteriori information, actual information, and expected information are introduced, the individual’s emotional model is established, and the assumption of information-emotional equivalence is proposed. Combining the PDA model with the information theory of emotional motivation completes the model construction based on this basic assumption. In the model performance test, the accuracy of emotion dimension recognition in this paper’s model is more than 95%, which is better than other models. Taking college students in 2 general colleges and universities in Hunan Province, China, as the research object, the study shows that the total psychological mean score of college students’ employment and entrepreneurship stress is 2.75, and the stress psychology is at a medium level. In the data of the randomly sampled student samples, 70% of the student’s emotional tendencies are anxiety, and anxiety is the mainstream emotion of college students. College students’ feelings of employment and entrepreneurship stress and negative coping styles are both at a high-intensity level.
Sentiment analysis of art and design works using deep learning
Authors: Dang Zhonghua
Published: July 2024

Deep learning technology has the characteristics of automatic learning, nonlinear modeling, etc., which makes the machine algorithm better adapt to the data so as to better complete the task of sentiment analysis. The purpose of this paper is to explore the application of deep learning technology in the emotional analysis of art design works. After combining the emotion construction mechanism of art design works, based on the superior performance of convolutional neural network image recognition, it is introduced into the emotion analysis of art design works, combined with the attention mechanism model, to construct the emotion analysis model of art design works based on deep learning. Art design works are collected as the experimental dataset. The emotion analysis effect of this paper’s model for art design works is evaluated through the comparison of emotion classification indexes. The comparison of ROC curves of different models, and the emotion instance analysis of art design works is carried out. The experiments show that the experimental accuracy, precision, recall, and F1 value of this paper’s model range from 81% to 86%, and the F1 and ROC values are improved by 2.3% to 7.0% and 1.7% to 4.2% compared with the comparison model, which reflects the high accuracy and precision of this paper’s model for the sentiment analysis of art design works. Seven emotional patterns were found in tea art design works, and the model can be used to analyze the emotions of art design works.
A Study on the Application of Social Network Analysis Based Approach in the Optimization of Cultural Communication Paths and Efficiency
Authors: Dong Rui
Published: July 2024

The optimization of cultural communication paths is an important part of Chinese culture’s continued dialogue with the world in the face of increasingly fierce international competition. In this paper, we use social network analysis to collect relevant data on the microblogging platform and analyze the overall network structure of “The Belt and Road Initiative” using network density, network distance, and clustering coefficients. Using social network analysis metrics, we calculate the node position of the network path of “The Belt and Road Initiative” and analyze the influence of each microblog account. We filter the cultural communication topics of “The Belt and Road Initiative”, scrutinize the participating regions, and establish the characteristics of the cooperation mode within this cultural communication. “The Belt and Road Initiative” has a network density of 0.247, 0.281, and 0.295, respectively, which indicates that the network density of these three topics is small and there is less information exchange, but the cohesive force of cultural communication is stronger. “People’s Daily,” “Central Committee of the Communist Youth League,” and “Phoenix Video” have high intermediary centrality (712.256, 700.425, and 695.253, respectively). The high intermediary centrality indicates that these nodes have a great influence on the flow of resources in the information dissemination network and can accelerate the efficiency of the “Belt and Road Initiative” cultural dissemination path.
An Exploration of Tourism Marketing Strategies of “Ethnicity + Folklore + Folk Lodging” in Guizhou Province Based on Echo State Network Modeling
Authors: Kang Ting , Lan Nan
Published: July 2024

Due to the improvement of national consumption levels, the Guizhou tourism industry plays an increasingly important role in the economy of Guizhou province, and the proportion of tourism revenue to GDP is increasing. We combine the improved FOA algorithm with an echo-state network, taking into account the characteristics of Guizhou tourism demand, to construct an AFOA-ESN prediction model for Guizhou tourism demand. The new algorithm fixes the problems with the old Drosophila algorithm by changing the number of Drosophila populations, the size of the search step, and the best place for the first iteration. This makes the new algorithm better at local searches and more efficient. We select the annual data on the number of travelers to Guizhou from ten provinces as the dataset and apply the simulation analysis method to test the effectiveness of the previously mentioned prediction model. The data show that among the ten sets of experiments, the AFOA-ESN prediction model has seven times the smallest MAPE value, while the AFOA-ESN model has six times the smallest MSE value. In addition, the consumption structure of Guizhou tourism tourists from 2010 to 2022 did not change much in this stage, showing the development of shock, sensitivity, and vulnerability. Based on the analysis results, we propose the tourism marketing strategy of “Ethnicity + Folklore + Folk Lodging.” This study selects forecast information suitable for the tourism industry and provides the necessary reference for decision-making in tourism-related departments.
The Promotion of Students’ Critical Thinking Skills through the Integration of English Civics Elements into EFL Classrooms
Authors: Lan Jing
Published: July 2024

As education advances with the times, traditional English EFL teaching can no longer fully adapt to the current educational situation. This paper studies the mining of the Civics element in English teaching integrates it into EFL classroom teaching, and constructs the morality cultivation EFL critical thinking ability teaching strategy based on the critical thinking ability model. The effects of applying this teaching strategy are analyzed and compared to the six dimensions of critical thinking ability: interpretation, analysis, evaluation, reasoning, explanation, and self-regulation ability. The exploration of critical thinking ability development and individual teacher factors is conducted. After the teaching experiment, the experimental group improved by 12.08 points, while the control group only improved by 0.46 points, indicating a significant difference between the two groups’ scores. The Sig. The values of the experimental group in the six dimensions are less than 0.05, and the Sig. The values of the control group are greater than 0.05. The teaching strategy of moral cultivation in EFL critical thinking ability has an obvious effect on improving students’ critical thinking abilities. There is a correlation between the development of critical thinking ability and teachers’ education, and teachers with master’s degrees are better than teachers with bachelor’s degrees.
Personalized Recommendation System for English Teaching Resources in Colleges and Universities Based on Collaborative Recommendation
Authors: Qu Zhihua
Published: July 2024

In recent years, with the rapid development of the Internet and education informatization, online teaching has become a popular education mode in the information age, providing learners with very rich teaching resources. In this paper, we construct a personalized system and co-recommendation technology for English teaching resources, and we improve the traditional co-recommendation algorithm and propose hybrid recommendations. The performance of the system is evaluated experimentally to compare the effectiveness of the performance of the four systems. The improved recommendation algorithm is superior to the other three recommendation algorithms in each dataset in the system. The average grade mean of the experimental class assisted by the hybrid recommendation system in teaching English in colleges and universities in the latter two experiments is 27.54, which is higher than that of the comparison class of 25.33, and the T-value is 1.81>1.645. The improved personalized recommender system has good validity and stability in both performance and practical application.
Modeling the Investment Efficiency and Risk Assessment of Great Health Industry in the Context of Digital Economy
Authors: Shen Lei
Published: July 2024

With the development of the economy and society, people pay more and more attention to physical health. In order to make the big health enterprises in the long term at the level of smooth development, it is necessary to carry out an in-depth study on the investment efficiency and potential risk of the big health industry. This study constructs an investment efficiency evaluation method based on the DEA model. Firstly, the comprehensive efficiency is decomposed through the CCR model to further obtain the output results. Then, the effectiveness of enterprise investment is evaluated. The changes in the investment efficiency of the big health industry and other sample decision-making units are analyzed through the DEA-Malmquist model to output the trend of the overall investment efficiency. Logistic regression, support vector machine, and random forest models are used to assess the risk of the large health industry, respectively, and several classifiers are trained. When predicting the final sample, the voting or mean value method is used to count the effect of classification. The overall mean value of big health enterprises hovered between 0.96 and 0.98 in five years, indicating that the comprehensive investment efficiency of the big health industry is relatively stable. The average AUC value of the random forest model is 0.635, which is 0.028 higher than the average AUC value of the support vector machine; thus, it is concluded that there is no great fluctuation in the investment efficiency of the big health industry under the background of the digital economy, and the random forest model is more suitable for the risk assessment of the big health industry.
Improvement of Inventory Management and Demand Forecasting by Big Data Analytics in Supply Chain
Authors: Tang Weiping
Published: July 2024

Inventory management plays a very important role in the process of business operation, providing favorable backing for the smooth operation of production and sales. In this paper, LightGBM and PSO-LSTM models in big data technology are combined to improve inventory management and demand forecasting in supply chains. Then, the relationship between inventory, order, and forecast is elaborated, the two-level inventory cost components and the relationship between them are analyzed, the model constraints are formulated, and a mathematical model for two-level multi-cycle inventory control is constructed. Finally, the single demand forecasting model is compared with the improved model to explore the optimization effect of inventory management after the application of the LightGBM-PSO-LSTM model. The LightGBMPSO-LSTM model is the best fit and can be used for actual demand forecasting. After the optimization of inventory management, the inventory turnover ratio of Company H increased from 8.2 in 2022 to the maximum value of 9.2 in 2023, and the OTIF achievement rate of sales orders increased from 97.9% in 2022 to 99.3% in 2023. This paper provides a successful example of optimizing supply chain inventory management using big data analytics.
Research on defect recognition technology of transmission line based on visual macromodeling
Authors: Li Yang , Li Yan , Wang Qi , Wang Wanguo , Liu Guangxiu , Li Zhenyu , Wu Hefeng , Jiang Shihao
Published: July 2024

In order to improve the defect recognition efficiency of transmission lines, the industry is currently using aerial images for automatic visual defect detection to ensure the safe operation of transmission lines. This paper proposes a method for defect recognition from coarse to fine, based on convolutional neural networks and connected domain algorithms, to improve recognition accuracy. The recognition speed is improved by using the knowledge distillation method of target detection networks based on decoupled features, adversarial features, and attention features. It has been found that the optimized recognition model improves the precision rate by 7%, the recall rate by 8%, and the average accuracy rate by 10%. The FPS of the model optimized by knowledge distillation is 62.5, and the average value of the FPS of other versions of this model is 47.35. It is believed that the two optimization ideas introduced in this paper can enhance the previous transmission line defect recognition algorithm in terms of accuracy and recognition speed.
Evaluation of the Benefits of an Intelligent Health Monitoring System in the Care of Geriatric Patients
Authors: Wang Yue
Published: July 2024

Collaborating with intelligent health monitoring in the clinical care of elderly patients can enhance understanding of changes in their body functions, thereby improving their quality of life and preventing complications. This paper focuses on the user characteristics and needs of geriatric patients, builds an intelligent health monitoring system based on C/S architecture, and develops a health data collection process for geriatric patients using smart wearables. We use the VMD algorithm to reduce the noise in the physiological signal data of elderly patients, then input it into a time-sequence convolutional network to extract the corresponding ECG signal features. We then combine this data with the LSTM model to classify the ECG signals, enabling us to diagnose the health of elderly patients. We established a continuity of care program based on the intelligent health monitoring system and designed a comparison experiment to evaluate the impact of the application. The VMD algorithm can recognize the insignificant signal peaks between 1.5s and 5.5s, and the health diagnosis model has the highest classification accuracy of 99.24% for ECG beats. In the continuity of care model, the elderly patients’ physiological function score was 68.42±4.76, and their serum ALB level was 35.79±6.72 g/L, which was 17.42% higher than the control group’s level after the intervention. It also helped the elderly patients’ mental health. The intelligent health monitoring system can dynamically acquire the physiological characteristics of elderly patients in real time and generate visualization results to help medical staff customize personalized care plans.
A time-series analysis of the evolution of scientific and technological concepts in the change of social thinking in modern China
Authors: Liu Yong
Published: July 2024

Exploring the evolutionary process of the concept of science and technology in modern Chinese society is conducive to the innovation of the current path of science education popularization and scientific and technological literacy enhancement. In this paper, we construct a sampling selection algorithm using Bayesian and MCMC and then design a parameter derivation model. Assuming the model prior distribution hyperparameters and using the likelihood function to derive the specific form of the posterior probability distribution, an approximate integral calculation is carried out in order to directly derive the parameters to be estimated, and the BVAR-MCMC model is constructed. Using the model to analyze the temporal changes in the evolution of scientific and technological concepts in modern China, it is finally found that the changes in social and technological concepts during the Republican period were even stronger than those in the late Qing period. Influenced by the increasing scale of cross-cultural exchanges due to the gradual opening up of the gateway, cross-cultural open exchanges have the highest impulse value and the longest duration on the evolution of scientific and technological concepts, with the impulse of the Late Qing and the Republic of China phases above 1, and the duration of the positive influence covers the whole time series. The impulse values of the late Qing and the Republic of China are 2.68 and 3.59, respectively, and the education popularization rate, economic development level, the speed of technological life progress, and the degree of civilization and freedom of the social atmosphere have different degrees of influence on the evolution of scientific and technological concepts in the time series of modern history. This study innovates the statistical research method for modern history and conducts a pioneering exploratory study on the evolutionary process of modern social ideas change.
Analyzing the Impact of ESP Teaching Models on Enhancing Non-English Majors’ English Application Skills
Authors: Wu Yanbei
Published: July 2024

The development of globalization has led to the rising demand of society and enterprises for the English application ability of students in colleges and universities, and the enhancement of the English application ability of non-English majors has become the key research direction of English teaching in colleges and universities under this trend. In this paper, we study this issue, highlighting the urgency of innovating the English teaching mode for non-English majors through the current situation of the passing rate of the English application ability examination and the main problems of the cultivation of English application ability of non-English majors. Gray correlation analysis is used to study the correlation between the English teaching mode, job requirements and other factors and the English application ability of non-English majors to provide data support for the introduction of ESP teaching mode. The ESP teaching mode is proposed, the teaching experiment is designed, and the results of the experimental and control classes are tested before and after participating in the experiment to assess the role of the ESP teaching mode in improving the English application ability of non-English majors as well. In the study of students’ satisfaction with the teaching of application abilities under the ESP mode, the overall satisfaction is high. Non-English majors are rated 11.87% more satisfied with the teaching effect under the ESP teaching model than English majors.
A Study of the Impact of Smart Contract Technology on the Understanding and Application of Contract Law from the Perspective of the Legal Profession
Authors: Yan Qingli
Published: July 2024

This paper constructs the logical framework of the smart contract model based on the sale and purchase contract transaction, integrating the legal framework and the smart contract. The smart contract model merges blockchain technology’s decentralized features with smart contracts to create a decentralized service mode for sale and purchase transactions. The classification of transaction attributes optimizes and adjusts the matching degree calculation method to meet the needs of both buyers and sellers. The matching degree determines the total satisfaction of both buyers and sellers. The simulation experiment model is designed to analyze the matching results, and the experimental results indicate that the overall utility value range is between 0.1 and 0.5, resulting in a higher level of satisfaction for both parties involved. Applying the model to actual purchase and sale transaction contracts, the expected profit of transaction users after using smart contracts is 26,300 yuan higher than that without using smart contracts. The accuracy and confidence scores of experienced users are 0,8886 and 4.0493, respectively, when evaluating their perceptions of the use of smart contracts. Smart contracts can help participants identify sales and purchase problems and provide innovative perspectives on the application of contract law.
A Computerized Information Security Communication Method Based on Deep Learning Theory
Authors: Kang Yingyun
Published: July 2024

We urgently need to explore the communication security guarantee mechanism to ensure the security of transmitting important information, and the steganographic communication model plays a crucial role in achieving this security. In this paper, we focus our research on secure communication methods using images, a widely used multimedia transmission medium. We design two covert communication models, LSTM-ACGAN and CNN-GAN, to enhance the security of deep image steganography algorithms while also improving their generalization ability. This paper’s model is compared with three current mainstream steganographic communication models on a dataset, and the CNN-GAN model is applied to a confidential unit dataset transmission. The research reveals that the two models in this paper possess the ability to detect across multiple domains, remain unaffected by specific domains, and require only 30%–33% of the parameters and arithmetic operations compared to mainstream models. Furthermore, they exhibit greater versatility and practicability, with training accuracy reaching 90% or higher. The model presented in this paper can meet the computer information security communication task after several rounds of iteration and meets the design expectations. This study provides a useful exploration for the establishment of computer information security guarantee mechanisms and designs a proven secure covert communication scheme.
Optimal scheduling of deep peaking compensation for electric utilities considering multiple types of adjustable resources
Authors: Li Mengyu , Feng Bo , Li Ji , Zhang Yangrui , Gao Xuezhe , An Yagang
Published: July 2024

This paper first analyzes the peak compensation process of electric power units in electric power enterprises, studies the carbon emission model of unit operation and the cost calculation method, then constructs an optimized dispatch model of deep peak compensation in electric power enterprises based on the factors of peaking subject and object and multiple types of adjustable resources, determines the critical peaking rate, and calculates the coefficient of the unit’s peaking capacity and the coefficient of the system’s peaking demand. Finally, based on the model, single-day and multi-day data from the regional power grid were analyzed, and the energy losses of the system units in summer and spring were compared before and after optimization. The results show that the average load factor of coal power units after the optimal dispatch of regional grid peak compensation is increased from 62%-68% before optimization to more than 91%, and the overall energy consumption of the system is reduced by 30.95% in the summer and 39.93% in the spring, which is of theoretical and practical significance for alleviating the scheduling pressure on the grid and the control problems of the power units.
Development of Construction Logistics Strategy in Real Estate through Innovation Hubs
Authors: Vijayakumar Anandhu , Davidova Jelena
Published: July 2024

There is an importance for innovation hubs in the field of real estate development as they enhance sustainability, promote technological developments and encourage collaboration. The innovation hubs help to integrate modern technologies, which decrease the associated costs and increase productivity. Moreover, innovation hubs allow the systematic organization of construction activities and achieve sustainable development goals. This paper aims to evaluate the multiple factors influencing construction logistics in developing the real estate sector through innovation hubs. The research used quantitative methodology and relied on two data acquisition techniques. The primary or unpublished data is obtained through an online survey, and secondary data is procured through already published articles and journals. The obtained survey data is analysed using factor analysis. The main factors are performance factors, optimization factors, ecological factors and growth factors. The authors developed a model according to factor analysis results. The recommendations are implementing innovative forums which help to update and adopt innovative technologies. Also, performance analysis mechanisms should be implemented to analyse workers’ productivity.
Concerning on different types of transthoracic echocardiography
Authors: Chernov M. Yu. , Alekhin M. N. , Mitkova M. D. , Mitkov V. V.
Published: July 2024

The article discusses the evolution of transthoracic echocardiography due to the introduction into clinical practice of new technologies and methods of cardiac ultrasound and the development of pocket ultrasound devices. Often, new technologies did not replace the old ones but were used as an addition to them, which led to an increase in the duration and complexity of the examination. On the other hand, the use of portable ultrasound machines has made it possible to perform point-of-care transthoracic echocardiography, but it has been limited by solving a specific clinical problem. It became clear that different clinical situations require examinations that differ in complexity, labor intensity, levels of experience, and training of the doctors. Various types, features, and place in the clinical practice of transthoracic echocardiography are presented. The necessity of changing approaches to both accounting for effort estimates depending on the protocols and volumes of examinations and to planning the work of ultrasound and functional diagnostics departments is substantiated. Ways to solve problems that hinder the introduction of targeted, including focused, examinations into routine clinical practice are proposed.
DESIGNING ROGUELITE PLATFORMER GAME “BONE AND SOUL” BASED ON WINDOWS
Authors: Wirawan Jason , Pragantha Jeanny , Haris Darius Andana
Published: July 2024

The game "Bone and Soul" is a roguelite platformer game that tells the journey of a character who has been deceived by the Demon King. After being deceived, the only thing that remain is bones and half of his soul. Therefore, the main character will climb the Demon King's Tower to fight against him and reclaim his lost half soul. The Demon King's Tower is composed of various rooms and are procedurally generated. As the game progresses, the main character will acquire other characters to help him defeat the demon king. Bone and Soul is a 2D pixelated game created using the Unity game engine and can be played on the PC platform.
BLOCKCHAIN IN EMPLOYING RISK MITIGATION FOR INDUSTRY SUPPLY CHAIN
Authors: Yosua Andrew , Juliana Helena , Gozali Lina
Published: July 2024

PT. XYZ is a pesticide company in Indonesia. Based on previous research, risk analysis was carried out and one source of risk was obtained, namely raw materials that did not meet specifications, which was then proposed to be mitigated by evaluating supplier performance. Where this involves a lot of data so it requires efficient and effective data storage and access. Blockchain with its characteristics can be used to meet these needs. Data collection was carried out employing a literature study on the company's official website, research, and publications that had been carried out at the company to obtain historical data. In this regard, a simulation will be carried out using a website, namely a blockchain demo. The design stage starts with identifying system requirements, creating use case diagrams, compiling activity diagrams, determining subprocesses, and selecting information
PEDESTRIAN REACTIONS WHEN PASSING BY IN THE SIDEWALKS
Authors: SALIM Frensten , Suryo PUTRANTO Leksmono
Published: July 2024

Walking is a daily activity made by a human being. It is a part of transportation system which facilitates people movement from one place to another, especially when the trip is impossible to be conducted by vehicles. Therefore, sidewalks should be integrated with overall transportation system, including with parking lots and public transport stops. The aim of this research is to understand pedestrian reactions when passing by in the sidewalks. Data collection was conducted using online questionnaires. Analysis was done by both one sample t-test and independent samples t-test. The main result was that the current standard of sidewalk width, needs to be widen from 1.5 m to 2 m in urban setting.
INTANGIBLE CULTURAL HERITAGE WEBSITE PROGRAM
Authors: Rusdi Zyad , Lim Carlene , Dewayani Ery
Published: July 2024

The Indonesian nation has a long history of diverse cultural journeys. A number of intangible cultural heritages need to be preserved which refers to the 2003 UNESCO Convention. One of the best solutions for preserving intangible cultural heritage is to use information technology, namely websites. It is very appropriate to use a website to preserve intangible cultural heritage, which means introducing and promoting intangible cultural heritage to the wider community, especially the younger generation. The creation of the Intangible Cultural Heritage Website Program aims to help BPNB (Cultural Value Preservation Center) in the DKI Jakarta, Lampung, West Java and Banten areas. BPNB has a function to preserve and promote the acculturation of cultural heritage values to the wider community. The previous research is already conducted and the result was the user interface design of the website. The user interface design was seen as suitable already by BPNB. The next stage was to develop the database using MySQL and the website using PHP. Waterfall model was used to develop the website. User Acceptance Test have been carried out and the results are the website was successfully installed at BPNB Bandung, the users also says that the website is really helpful to document the intangible cultural heritage and also to socialize to the public. The users already seen the website and accepts the website fully. There was feedback from user which is to create the Android version of the website so it can be accessed more easily.
QUALITY IMPROVEMENT THROUGH DESIGN AND MANUFACTURE OF TOTE BAG PROTOTYPES USING QUALITY FUNCTION DEPLOYMENT METHOD (CASE STUDY IN SMEs X)
Authors: Sukania I Wayan , Widodo Lamto , Lorensa Fanny , Juyanto Jennifer
Published: July 2024

Every consumer wants a quality product. Likewise, consumer needs for quality tote bag products. A quality tote bag describes the suitability of the specifications of the tote bag with the needs and desires of consumers. Research to improve the quality of tote bag products was conducted at an MSME in Indonesia that sells tote bag products in one of the largest marketplaces in Indonesia. Based on the results of the initial data collection, information was obtained that the quality of the tote bag could still be improved. Therefore it is necessary to do research to produce a better tote bag design. The Quality Function Deployment (QFD) approach is used to improve the design and specifications of the tote bag product. The research began by gathering information from respondents regarding the needs and desires regarding the tote bag product. The needs and desires that have been identified will become the basis for the development of tote bag products using the House of Quality (HoQ) method. Through the design stages produced several concepts to be selected according to predetermined criteria. Two types of tote bag designs were prototyped to be assessed by consumers. The survey results prove that consumers prefer the newest tote bag product compared to the previous tote bag product.