bluuebunny/crossref_metadata_2025 huggingface dataset:
The Study of State Protective Forest Strips of the European Part of the Russian Federation: Analytical Review
Authors: Мартынюк А.А. , Турчин Т.Я. , Корнеев А.Б.
Published: July 2024

Анализируются вопросы экологической и экономической значимости государственных лесных полос, приведена краткая история их создания. Отмечено, что созданные более 60 лет назад государственные защитные лесные полосы образуют зеленый экологический каркас степных территорий, являясь своеобразными форпостами в борьбе с засухой и суховеями на землях сельскохозяйственного назначения, защищая берега рек и водоемов от заиления и разрушения. Дано описание технологических особенностей создания и выращивания государственных защитных лесных полос, включая подбор ассортимента древесно-кустарниковых пород, схем их смешения, способов создания лесных культур и агротехнических уходов за ними, ухода за лесами. В настоящее время жесткие почвенно-климатические условия в сочетании с возрастными характеристиками созданных насаждений привели к ухудшению их состояния и показателей роста на значительной части площадей. Это требует разработки научно обоснованной системы мер по повышению устойчивости и долговечности сохранившихся государственных защитных лесных полос, а также по созданию новых защитных лесных насаждений в степной и сухостепной зонах страны.

The issues of ecological and economic significance of state forest strips are analyzed, a brief history of their creation is given. It is noted that the state protective forest strips created more than 60 years ago form a green ecological framework of steppe territories, being a kind of outposts in the fight against drought and dry winds on agricultural lands, protecting the banks of rivers and reservoirs from siltation and destruction. The description of the technological features of the creation and cultivation of state protective forest strips, including the selection of an assortment of tree and shrub species, schemes of their mixing, methods of creating forest crops and agrotechnical care for them, forest care is given. Currently, harsh soil and climatic conditions combined with the age characteristics of the created plantings have led to a deterioration of their condition and growth indicators on a significant part of the areas. This requires the development of a scientifically sound system of measures to increase the stability and durability of the preserved state protective forest strips, as well as to create new protective forest plantations in the steppe and dry-steppe zones of the country.
Forestry in Bulgaria
Authors: Жидкова Е.В.
Published: July 2024

В статье представлен анализ современного состояния лесного хозяйства Болгарии. Рассмотрены лесные ресурсы, формы собственности на леса и управление лесным хозяйством. Приведены данные о разнообразии флоры и породного состава лесов, их происхождении, возрастной структуре. Проанализированы тенденции изменения среднего запаса древесины на 1 га, данные об объёмах заготовки древесины и видах рубок лесов.

The article presents an analysis of the current state of forestry in Bulgaria. Forest resources, forms of ownership of forests and forestry management are considered. Data on the diversity of flora and species composition of forests, their origin, age structure, trends in the average timber stock per 1 ha are given. Data are given on the volume of timber harvesting and types of forest felling.
Carbon Stock in Living Biomass of Russian Forests: New Quantification Based on Data from the First Cycle of the State Forest Inventory
Authors: Филипчук А.Н. , Малышева Н.В. , Золина Т.А. , Селезнев А.А.
Published: July 2024

На основе результатов измерений на постоянных пробных площадях первого цикла государственной инвентаризации лесов (ГИЛ) выполнена количественная оценка запасов углерода в фитомассе лесов России. Общий запас углерода в надземной и подземной фитомассе по состоянию на 2020 г. рассчитан в размере 46,9±0,4×109 т С при среднем значении 52,1±0,5 т С га-1. Общий запас древесины в лесах, по данным ГИЛ, составил 113,1×109м3. Согласно данным государственного лесного реестра (ГЛР), являющегося основным источником сводной информации о лесах России, запас древесины достигает 83,1×109 м3. В связи с уточненным и значительно большим по сравнению с ГЛР общим запасом древесины, оценка запасов углерода в фитомассе оказалась примерно на 35 % выше, чем сообщалось ранее. Неопределенность суммарных и средних запасов углерода по данным ГИЛ (примерно ±1 %) оказалась существенно ниже, чем в предыдущих исследованиях (±15–30 %). Рассмотрены метод учета запасов углерода в фитомассе и результаты расчетов запасов углерода для лесных земель всей страны с распределением по единицам административного деления и лесного районирования. Полученная оценка запасов углерода на основе репрезентативной выборки может существенно повысить актуальность и достоверность национальной отчетности по лесам.

The carbon stock in living forest biomass was quantified based on first-cycle State Forest Inventory (SFI) measurements in permanent sample plots. The total carbon stock in above- and below-ground living biomass was assessed to be 46.9±0.4×109 tons C and average carbon stock at 52.1±0.5 t С ha-1as of 2020. The State Forest Register (SFR), the primary source of consolidated information on Russia’s forests, estimates the forest growing stock to be 83.1×109 m3. The total growing stock volume in the forests, according to the SFI amounted to 113.1×109 m3. Owing to the updated and significantly higher growing stock volume, the estimate of carbon stock in living biomass is approximately 35 % higher than previously reported. The uncertainty of the total and average carbon stocks based on SFI data was substantially lower (approximately 1 %) than that reported in previous studies (15–30 %). Methods of accounting for the carbon stock in living biomass, the results of calculations for forest lands throughout the country, units of the administrative division, and forest zoning were considered. Assessment of living biomass based on representative sampling can substantially improve the relevance and reliability of national forest reporting.
Results of Molecular Genetic Analysis for Phytosanitary Diagnostics of Forest-Forming Species of the Baikal Natural Territory
Authors: Бедрицкая Т.В. , Воинков А.А. , Арефьева М.А. , Антонова Т.И.
Published: July 2024

Повышенная антропогенная нагрузка обусловливает снижение устойчивости лесных насаждений к воздействию патогенных грибов – возбудителей многих болезней. Их своевременное выявление и идентификация – необходимая процедура для разработки стратегии по организации защиты лесов. Молекулярно-генетический анализ относится к одному из самых высокоэффективных методов диагностики фитопатогенных организмов. В статье приведены результаты молекулярно-генетического обследования лесных насаждений и посадочного материала лесных питомников Байкальской природной территории. Идентифицирован состав микробиоты хвойных древесных растений. Выявлено более 80 видов грибной микрофлоры. Обнаружены виды грибов, не имеющие морфологического описания, с неизвестным болезнетворным потенциалом. Установлено, что ряд диагностированных микозов, а также бактериальная водянка переносятся насекомыми. Рекомендован постоянный лесопатологический и генетический мониторинг выявленных инфекционных заболеваний в лесных питомниках и насаждениях.

Increased anthropogenic load causes a decrease in the resistance of forest plantation to the effects of pathogenic fungi – the causative agents of many diseases. Their timely detection and identification are a necessary procedure for developing a strategy for organizing forest protection. Molecular genetic analysis is one of the most highly effective methods for diagnosing phytopathogenic organisms. The article presents the results of a molecular genetic examination of forest plantations and planting material from forest nurseries of the Baikal natural territory. The composition of the microbiota of coniferous woody plants has been identified. More than 80 species of fungal microflora have been identified. Fungal species with no morphological description and unknown pathogenic potential have been discovered. It has been established that a number of diagnosed mycoses, as well as bacterial dropsy are transmitted by insects. Permanent forest pathological monitoring and genetic monitoring of identified infectious diseases in forest nurseries and plantings is recommended.
Geneza i potencjalne wykorzysta nie zeolitu na obszar ze Moncongloe, Maros, Sulawesi Południowe, Indonezja
Authors: Nur Irzal , Taba Paulina , Idrus Arifudin , Irfan Ulva Ria , Sufriadin Sufriadin , Widodo Sri , Anas Aryanti Virtanti , Ardian Muhammad Ridha , Anjelina Adelia Dwirisa
Published: July 2024

Na obszarze Moncongloe w regencji Maros w prowincji Sulawesi Południowej w Indonezji zidentyfikowano mineralizację zeolitu w porfirowym ryolicie i zielonym tufie w sekwencji wulkaniczno- osadowej, należącej do mioceńskiej formacji Camba. W artykule opisano najnowsze badania mineralizacji zeolitu na podstawie danych terenowych i laboratoryjnych, które koncentrowały się na jej aspektach genetycznych i potencjalnych zastosowaniach w oparciu o jej właściwości mineralogiczne i chemiczne. Prace laboratoryjne zastosowane w tym badaniu obejmują analizę mineralogiczną (petrografia i XRD) oraz masową analizę chemiczną (XRF dla głównych tlenków, ICP-OES i ICP-MS dla pierwiastków śladowych). Badania mikroskopowe i XRD wskazują, że zeolit jest typem filipsytu, który jest związany ze smektytem i powstał jako produkt przemiany pierwotnych fenokryształów skalenia K, a także drobnokrystalicznej masy gruntowej i szkła wulkanicznego. Obecność zeolitu typu filipsytowego związanego ze smektytem została również potwierdzona przez skład chemiczny. Mineralizacja zeolitu związana ze smektytem na badanym obszarze powstała w wyniku procesu przemiany przez płyn hydrotermalny w alkalicznej wodzie morskiej, od późnego miocenu do pliocenu. Można zatem stwierdzić, że w tym przedziale czasowym nastąpiły zmiany hydrotermalne. Magma tworząca wulkaniczne skały macierzyste, to magma serii zasadowej, o składzie pośrednim do kwaśnego, pochodząca ze strefy subdukcji. Zeolit typu filipsytu bogaty w K na badanym obszarze może być stosowany m.in. do: usuwania ołowiu z wody oraz parakwatu ze ścieków, ekstrakcji potasu z wody morskiej, usuwania toru z roztworów węglanowych, jako katalizator w knoevenagelu, a także jako suplement diety dla zwierząt domowych, do wchłaniania amoniaku w wodzie oraz do terapii raka jelita grubego.
Research on multi-objective optimization and prediction of building construction carbon emission based on multi-dimensional data analysis
Authors: Zhang Junqiang
Published: July 2024

Carbon emission from building construction is an important issue in the construction industry, and the continuous application of management and assessment techniques forms a new trend of carbon emission reduction. This paper establishes a multi-objective optimization model for building construction carbon emission based on multidimensional data analysis of four objectives: schedule, cost, quality, and carbon emission. The particle swarm algorithm is improved by dynamically adjusting the inertia weight factor and penalty function to deal with constraints and is used to solve the multi-objective optimization model. Building construction cases are selected to predict and analyze the combinations of optimal execution modes under different teams, to compare the optimization results of configuration schemes and the efficiency of algorithms, and to further propose the practical path of carbon emission reduction in building construction. The study addresses the construction combination mode that meets the needs of various decision-makers, and the team 3 combination mode has the lowest carbon emission (228.41kg). The multi-objective optimization scheme under carbon emission constraints optimizes between 3.93% and 21.78% in the four objective dimensions. This paper further expands the scope of the multi-objective optimization model for building construction focusing on the “low carbon” objective, improves the feasibility of the configuration scheme, and then promotes the green and stable development of the construction industry.
A new approach to solving isomorphism problems of classical dynamical systems using algebraic structures
Authors: Zhang Lijuan
Published: July 2024

There exists a fixed rule in classical dynamical systems that describes a point in geometric space over time. In this paper, based on the algebraic structure perspective, the dynamical system is defined as a category characterized by ordered state projections, and the dynamical system is inscribed using the algebraic structure, covering the phase space, continuous self-maps containing a single parametric variable, and the dynamical system itself. Meanwhile, two types of self-isomorphisms of algebraic maps are explored. One is the self-isomorphism of ideal inclusion maps on an algebra Mn(Fq) consisting of full matrices of order n over a finite field Fq
. The second is the self-isomorphism of ideal relational graphs on a finite field Fq
. It is proved that any self-isomorphism problem of graph Mn
(Fq
) when n >3 can be used with both criteria on it. Finally, a classical model of a dynamical system obtained from f(x) = cos x iterations is studied and its global convergence is discussed. Numerical experimental results show that the discrete dynamical system generated by function f(x) = cos x iteration has a unique ω limit point of 0.735, indicating that the stability and predictability of classical dynamical systems can be achieved using algebraic structures, as well as revealing the complexity, instability, and chaos of the system.
Application and Innovation of Chinese Characteristic Cultural Elements in Cultural and Creative Product Design in the Information Age
Authors: Zhang Na , Zhang Ruijie
Published: July 2024

In recent years, with the interaction and integration of modern cultural and creative industries with Chinese excellent traditional culture, various innovative cultural and creative products have been introduced, ushering in new opportunities for the inheritance and development of Chinese excellent traditional culture. In order to integrate Chinese cultural elements into the design of cultural and creative products. This paper draws on the characteristics of DNA inheritance and mutation in living organisms to construct a multi-objective optimization model of DNA elements, and by applying the model to the analysis stage of cultural and creative product design, the designed products can be more completely integrated into the elements of Chinese characteristic culture to effectively guide the design practice of cultural and creative products. This paper takes Dunhuang Tang Dynasty Feitian cultural elements as an example for practical research through the integration of Dunhuang Tang Dynasty Feitian cultural elements of a series of cultural and creative products for the satisfaction survey from the symbolic perception, beautiful shape, functional and practical, cultural connotations, innovation and novelty of the five dimensions of the design effect assessment, the furniture category of cultural and creative products scored the highest, the average value of 4.766, the cultural and creative products in the symbolic perception of the dimensions of the score is high. It shows that in the Dunhuang Tang Dynasty, Feitian cultural and creative products can be perceived as symbols of the characteristic culture of the period.
The Application of Quantitative Methods in Assessing the Effectiveness of Litigation Legal Strategies - An Example of the Case Study Approach
Authors: Zhang Wei , Zheng Chenghua
Published: July 2024

In legal practice litigation cases, the selection of a litigation strategy significantly impacts both the litigation process and the overall outcome of the case. The study mainly applies quantitative methods to evaluate the effectiveness of legal strategies for litigation. We collect relevant legal strategy texts after analyzing relevant civil litigation cases in China. We then use text mining methods, such as regular expressions, jieba participles, and Word2Vec training word vectors, to refine high-frequency words in text data related to litigation legal strategies. This process establishes a quantitative evaluation index system for assessing the effectiveness of litigation legal strategies. We select litigation legal strategy cases as the evaluation object, utilizing the PMC index to determine and evaluate the effectiveness of each strategy. The sample litigation legal strategies have a mean PMC index of 6.69, indicating a good overall level. Only one strategy is considered acceptable, with the remaining 87.5% rated as good. Deficient litigation solutions and thought paths, with a mean value below 0.8, hinder the effectiveness of litigation legal strategies. We recommend optimizing and improving them to enhance their effectiveness.
Research on rural landscape garden planning and plantscape construction method based on digital twin technology under rural revitalization strategy
Authors: Zhao Jiayu
Published: July 2024

This paper integrates the landscape information model, designs the digital twin rural landscape architecture, and analyzes the advantages of the digital twin rural landscape model. The practical application of digital twin technology is examined from the planning and design stage to the construction stage. Considering the actual construction site layout and the consumption of construction materials, the NSGA-II algorithm is selected to optimize the dynamic layout of temporary facilities by combining multi-objective optimization theory. Using the digital twin to drive the dynamic layout of the construction site, a digital twin-driven construction site layout mechanism is proposed in combination with BIM technology. The actual construction scheduling tasks are used to analyze the feasibility of the construction site layout scheme generated using digital twin technology. Analyze the construction of rural landscape gardens planned using digital twin technology in terms of ecological, social, and economic benefits. The convergence minimum is achieved at 0.15 and 0.09 when comparing the number of iterations between the initialized layout and the digital twin-driven layout. The corresponding scheme reaches its optimal state during the construction stage and can provide the most suitable site arrangement scheme during that stage. The rural landscape garden planned by the digital twin technology can generate an economic return value of 71.756 yuan/m² per year, which can further promote rural revitalization.
Research on the Reform and Development of Ideological and Political Theory Classes for College Students in the Context of Practical Parenting
Authors: Wang Quan
Published: July 2024

In the context of practical education, deepening the reform of quality education and implementing the fundamental task of cultivating moral integrity have become the guidelines and the basis for the development of curriculum reform in colleges and universities. This study conducts data mining based on the association rule model on the influencing factors of the reform of the Civic and Political Theory Course in colleges and universities to obtain the key influencing factors in the process of the reform of the theory course. Then, under the perspective of deep learning, the idea of practical parenting is integrated, and the structural framework of Civic and Political Theory course reform is designed from four directions: learning theme, learning objectives, learning activities, and evaluation feedback, and finally, the course reform method of this paper is examined through teaching practice. The results show that the influence weights of self-factors, school education factors, family factors, and social factors are 0.3022, 0.3521, 0.1381, and 0.2076, respectively, with self-factors and school education as the key influencing factors. After the teaching practice, the P-value of each dimension of the students under the curriculum reform based on this paper is less than 0.05, and the grade of the Civics and Political Science Theory course is improved from 81.47 to 90.45, which is an increase of 7.49 points compared with the class of the regular course. The reform method based on deep learning in this study can promote students’ development and improve their academic performance, which provides a reference for the research on the reform and development of the Civics and Political Science Theory course.
Research on the Development of New Sensors and Sensor Detection Technology in the Context of Big Data
Authors: Wang Jiahui
Published: July 2024

In the context of big data, traditional detection algorithms can no longer meet today’s needs. For traditional sensors, there are shortcomings such as long working times, high complexity, and high false detection rates. This paper proposes a new type of sensor and an algorithm for detecting anomalies in sensors based on Flink. The sensor network senses the monitoring targets in the monitoring area in real time and transmits them to the end users through wireless communication. Then, the fusion rule for target detection in sensor networks is studied. Then, the detection algorithm is computed using Flink and predicted using a sliding window and ARIMA model on the Flink platform. Then, the confidence intervals of the prediction results are calculated, and the outliers are evaluated. Finally, the K-Means++ algorithm is used for clustering and probability assessment of previously obtained outliers. Then, compared with traditional sensors, comparative analysis shows that the proposed method in this paper has some advantages in terms of both sensitivity (S) and quality factor (Q). The value of S is more than 320 than the 2D PhC sensor array. The value of Q is more than 5295 than the 2D PhC sensor array. This paper’s new sensor detection method is more diverse than the traditional method. The detection time is reduced. The detection accuracy is also improved compared to the traditional method. It can be summarized by comparison that the new sensor in this paper is more excellent than the traditional method of detection.
Research on the application method of agricultural machinery engineering automation based on multimodal characteristics
Authors: Wang Xianggeng , Fan Yujia
Published: July 2024

Agricultural operators can predict the yield of wheat at different stages of growth, development, and harvesting and take different measures to realize precise management. The purpose of this paper is to apply agricultural mechanical engineering automation to wheat yield prediction, and a UAV multimodal data wheat yield prediction model is developed using the RMGF algorithm. Different data sources, such as vertical distribution of terrain and spatial variability, canopy height and wheat plant height, canopy temperature difference, vegetation spectral characteristics, and vegetation index, were extracted using an agricultural UAV. Then GF decomposition algorithm based on MSD decomposes the multimodal image into an approximate image and detail image, and after optimization of the fused weight map using RSA, the fused image is obtained by IMST according to the optimized weight map. The model was used to carry out regression analysis of yield prediction for three types of wheat, heat-tolerant, medium heat-tolerant, and high-temperature-sensitive, and finally predicted the wheat yield from 2015 to 2024 in a production area. It was found that the R² of the RMGF multimodal model in this paper predicted the three kinds of wheat yields as 0.7936, 0.8609, and 0.9262 with excellent accuracy results. The predicted yields were basically in line with the actual yields in the high-yield portion, with large prediction errors above 9000 kg/ha. The prediction error for wheat was within 0-2.26%, and the predicted yield in a main wheat production area was 7050 kg/ha in 2024. This study provides a feasible method for large-scale yield estimation in the main production area, which contributes to high-throughput plant phenotyping and agricultural precision reform.
Audit Risk Assessment Model Construction by Incorporating Deep Learning Techniques
Authors: Yan Zhenzheng
Published: July 2024

While risk-oriented auditing has gradually emerged as a new trend in current internal auditing, the absence of specific risk assessment methods in related internal auditing standards has made it a common challenge for many enterprise internal auditing organizations and personnel to effectively implement and conduct risk assessments. This research focuses on integrating deep learning technology to construct an audit risk assessment model, first describing the problem of audit risk assessment and then validating it using the CNN-LSTM method. We select the appropriate indicators for audit risk assessment assignment after screening the sample data to ensure their qualitative and quantitative comparability. We construct a CNN-LSTM audit risk assessment model based on the above data. We use two input methods, the convolutional neural network and the long- and short-term memory network, to enhance the assessment model’s learning ability. We then choose 12 enterprise companies as data cases, with Company A serving as the representative for the CNN-LSTM-based assessment model’s performance simulation test and risk level assessment. We compare the four models, and the CNN-LSTM model’s AUC exceeds 0.5 in the confusion matrix and ROC curve graph, confirming the usefulness of CNN-LSTM in audit risk assessment.
Research and Practice of Digital Economy Helping Rural Industry Revitalization in the Information Age
Authors: Zhao Yixing
Published: July 2024

Based on the construction and development of digital economy-enabled rural industry revitalization in a region, this paper conducts theoretical analysis on the degree of promotion of rural industry revitalization from three aspects, namely, production conditions, capacity, and benefits. In order to verify the influence mechanism of the digital economy on rural industry revitalization, a regression measurement model oriented to the digital economy and rural revitalization is constructed based on the evaluation index system, and the entropy weight method is used to calculate the comprehensive evaluation index of rural industry revitalization and the comprehensive evaluation index of the digital economy. Determine the variables and data sources and conduct an empirical analysis of the digital economy contributing to rural revitalization from the perspective of informationization. The data show that the mean value of the digital economy index (Dige) is 0.2482, the minimum value is 0.0043, and the maximum value is 0.951, indicating that there are large differences in the development of the digital economy among different regions and that the eastern region has a more significant advantage in the rural industry (0.2258) as well as in the digital economy (0.3076), compared with the western region and the central region. In addition, the R² of the baseline regression (Model 1) is 0.5782, and the R² after replacing the explanatory variables using the entropy method index (Model 2) is 0.6881, based on the results suggesting that the development of the digital economy has a facilitating effect on the development of rural industries. The efficiency of resource utilization in rural areas is improved by this study, which releases the potential for agricultural development and further promotes the strategy of rural revitalization.
Multimodal biometric fusion sentiment analysis of teachers and students based on classroom surveillance video streaming
Authors: Zhang Tianxing , Dahlan Hadi Affendy Bin , Xie Zengsheng , Wu Jinfeng , Chen Yingping , Pan Qianying , Huang Ying
Published: July 2024

In the education system, teachers and students as the main body of the classroom; their emotional state in the classroom school is an important indicator of the effectiveness of the classroom. This study first explores biometric recognition, based on the needs of the classroom curriculum and the classroom monitoring as a sensor, to propose a multimodal biometric fusion detection method based on the fusion of face and gait recognition. The PCA algorithm is used to optimize the face recognition as well as the occlusion situation in the classroom to improve gait recognition, and then the face and gait are fused based on the decision layer to achieve the detection and recognition of the identity situation of teachers and students. On this basis, an expression recognition model is established using the attention mechanism, and an emotion analysis system is designed for the classroom curriculum. According to the empirical evidence of multimodal biometric fusion sentiment analysis, the mAP accuracy of this paper’s fusion method is 100% in Euclidean distance, and the accuracy is higher than 99% in cosine distance, which is obviously better than other methods, and the accuracy of this paper’s fusion recognition is above 95% under any condition limitations. At the same time, the correct rate of recognition of emotions such as listening, appreciation, resistance, doubt, and inattention are all higher than 85%, and the five indexes of average absolute error, Pearson correlation coefficient, Accuarcy5, Accuarcy2, and F12 score of this paper’s sentiment analysis have achieved the best results comparing with other sentiment analysis models, which proves the generalization and validity of this paper’s sentiment analysis.
Exploring the Impact and Innovative Application of Piano Art Instruction in the Context of Deep Learning
Authors: Zhao Qinghua
Published: July 2024

Social progress and technological development have brought sweeping changes to the field of art education. The innovative development of piano art instruction, as a part of art education, has a significant impact on students and the academic world. The study proposes a deep learning-based model for piano art instruction, taking into account the current state of piano art instruction, and investigates the impact of this model on students’ piano playing skills and appreciation of music art. The experimental group’s students improved their playing skills in the eight dimensions of fingering, timbre, pitch, rhythm, musical expression, emotional output, body language, and stage image. Except for timbre and stage image, the p-values of the experimental group and the control group in the other six dimensions of piano playing skills were less than 0.05, which effectively improved. In terms of music art appreciation, the total number of excellences in the three dimensions of aesthetic perception, artistic performance, and cultural understanding was 118, 131, and 126, respectively, and the total number of excellences in the experimental group was 32, 45, and 39. Obviously, piano art instruction based on deep learning has a positive impact on the students’ piano-playing skills and ability to appreciate music art.
Innovative Improvement of Business Laboratory Management Efficiency under the Internet+ Mode
Authors: Zhou Keyan
Published: July 2024

The laboratory is an important place for talent cultivation and scientific research activities. However, at present, there are problems such as backward management mode and low management efficiency in the laboratory. This paper combines the “Internet +” technology to study the effective means to improve the efficiency of business laboratory management. Through the Internet of Things, Android, and other key technologies, we can build an intelligent business laboratory management platform. The management level of the business laboratory management platform designed in this paper is evaluated and classified using the neural network algorithm. The designed and completed intelligent management platform for business labs contains functional modules such as intelligent control, equipment management, faculty management, and user management. The evaluation study found that the management level score of university laboratories after applying the intelligent management platform for business laboratories maintains more than 85 points in general, and the evaluation grade shows an excellent level of A grade.
Research on Teaching Quality Evaluation Model of Higher Mathematics Based on Hierarchical Analysis Approach
Authors: Deng Jin
Published: July 2024

The teaching quality of higher mathematics courses plays a pivotal role in the cultivation of students’ quality and the improvement of their abilities. In this paper, information entropy is added to the hierarchical analysis method to improve it and then combined with the fuzzy synthesis method to construct a model for evaluating the quality of mathematics teaching. The higher mathematics teaching course at a university is selected as the research object, and the constructed model for evaluating the quality of higher mathematics teaching is applied to the teaching of higher mathematics in classrooms. The evaluation index system for higher mathematics teaching quality is established by combining relevant literature, and the improved AHP is used for weighting. Then, the index data is collected through questionnaires to analyze the differences and assess the teaching quality of different genders and majors and then to propose strategies to improve the teaching quality of higher mathematics. The significant effects of teaching methods (0.184), teaching effectiveness (0.176), and teaching content (0.170) on the teaching quality of higher mathematics were revealed. The quality of teaching higher mathematics in the sample universities is located at a good level with scores between 8 and 9 on each evaluation index, with the best performance of 8.934 for teaching content. The evaluation model for higher mathematics teaching quality established by the research has validity and feasibility.
The Network Effect of Internet+Education Models in English Collaborative Learning Across Locations
Authors: Geng Cong
Published: July 2024

This paper establishes an English off-site collaborative learning system based on B/S architecture so that English learning is no longer restricted by time and space. This study investigates the influencing factors of network effects by introducing continuous learning behaviors in an online English off-site collaborative learning platform, and explores how course network size, course network diversity, and course strong linkage factors affect network effects. Two language classes in the College of Foreign Languages of a university were selected as research subjects to conduct an empirical study to test the effectiveness of the off-site collaborative learning teaching model. The results showed that the correlation coefficients of course network size, course network diversity, and course strong ties in the learning process were 0.341, 0.394, and 0.263, respectively, all of which were positively related to persistent behavior. In further testing the hypotheses, the main effects of course network size, course network diversity, and course strong ties were all significant (p<0.001). English off-site collaborative learning can improve students’ English performance and interest, which can develop their learning habits in the direction of making.
Research on the quantitative model of the communication effect of Civic and Political Education for social platform data
Authors: Tang Wenyan
Published: July 2024

Social platforms have revolutionized the lives of the public, provided a resourceful educational platform for the ideological and political education of college students, and become the distribution center of ideological and political education information and the amplifier of social opinion. In this paper, we concentrate on the dissemination of data related to ideological and political education on social platforms. We start by segmenting the text and then use the IF-IDF algorithm, the Text Rank algorithm, and the LDA theme model to process various text features. Simultaneously, we will employ a sentiment dictionary and simple Bayesian analysis, along with a convolutional neural network, to measure the impact of emotion propagation. The microblogging user’s comment data for the Civics communication emotion analysis concluded that the user group of the initial period of the Civics education activities will produce some negative emotions, while at the same time, the positive emotion has been maintaining an upward trend. While the negative emotions began to decline and slow down, the user group with the highest positive emotion reached a value of 6.35464.
Application of Digital RMB Smart Contracts in Grid Smart Payment Settlement
Authors: Hou Dongliang , Yang Qing , Hao Shanshan
Published: July 2024

The use of smart contract technology for contract execution and real-time payment can ensure the timely availability of funds, thus ensuring the security and authenticity of data in power grid transactions. In this paper, we design a digital RMB smart contract model based on blockchain technology and use the hexadecimal model to create, deploy, and execute smart contract functions. And through the DTSC algorithm, smart contracts can be applied to the grid smart payment settlement. At the same time, a privacy protection algorithm for transaction data is proposed, and finally, the grid smart payment settlement system is designed based on smart contracts and privacy protection algorithms. Simulation test results show that the cost required for the digital RMB smart contract proposed in this paper is lower than the existing schemes in terms of invocation and deployment costs. The average chain code invocation delay in smart contract technology decreases when the transaction sending rate increases from 250TPS to 300TPS. Moreover, the on-chain operation time of this system is only 2.69 seconds, which meets the demand of practical power grid smart payment settlement applications. This paper sets the foundation for the efficient operation of the grid smart payment and settlement system and provides a guarantee for payment and settlement security.
Remote sensing monitoring and early warning modeling of soil salinization process
Authors: Li Xiaoxiong , Ma Yanjun , Li Qiang , Yang Qingyi
Published: July 2024

In this paper, according to the process of remote sensing monitoring of soil salinity and alkalinity process as well as the conditions, the remote sensing images were radiometrically corrected and aligned, and the remote sensing images were enhanced by using digital models to change the gray structure relationship of the image elements and change the gray value of the image elements, and then the changes in the patches of the remote sensing images were analyzed to extract the soil salinity and alkalinity data. In this paper, we also used statistical methods to analyze the acidity and salinity characteristics of soil samples, the soil spectral reflectance characteristics, and the sensitive bands for estimating the soil acidity and salinity characteristics, and we performed the multispectral inversion analysis of soil salinity on the basis of the spectral data. The results show that the remote sensing monitoring and early warning model of the soil salinization process established in this paper has a coefficient of determination R
2 =0.697, RMSE=0.946, p=1.06*10-7 in the research calculations, and the root-mean-square error between predicted and measured values RMSE=2.33, which indicates that this model has a better performance in monitoring and prediction. The theoretical significance and practical value of this study are crucial for protecting the ecological environment and managing soil salinization.
An Exploration of the Application of Augmented Reality Technology in Improving Interactivity in Physical Education Teaching and Training
Authors: Wang Juanjuan , Cai Jie
Published: July 2024

This paper elaborates on the technology related to augmented reality interaction, introduces in depth the augmented reality device HoloLens, including its composition and the principle of generating indoor three-dimensional data, and designs a teaching interaction model of augmented reality fusion learning environment. The Kinect somatosensory device is introduced into the teaching interaction model, and virtual interactions between virtual objects and real objects are accomplished by judging the human body’s position and posture changes in real time. Group experiments were conducted to examine the learning effect of augmented reality-based technology with or without interactive behavior in terms of interest in sports learning. According to the findings, the augmented reality physical education interactive teaching experiment resulted in a 23-point increase in the average value of physical education knowledge mastery level test scores. Further one-way ANOVA was conducted and the p-value of the scores of group B of the experiment with interaction before and after teaching was 0.001, which is less than 0.05. Augmented reality sports interactive teaching can significantly enhance students’ interest in sports learning, attention to sports, and so on. Therefore, the augmented reality sports interactive teaching technique mentioned in this paper serves as an effective way to improve students’ performance and interest in sports education.
Edge computing-based big data privacy preservation in motion trajectory prediction for martial arts training
Authors: Wang Xue , Peng Xinxin
Published: July 2024

The development of big data technology has brought about sweeping changes in many fields. Privacy protection has become a key concern for big data users. The study constructs a geographically indistinguishable location-based privacy protection mechanism based on differential privacy and geographic indistinguishability and further constructs an edge computing-based privacy protection model for martial arts movement trajectories. The performance of an edge computing-based privacy protection model for martial arts sports trajectory is examined by comparing it to other models in terms of quality of service loss, privacy protection strength, and range counting queries. And explore the effects of service type and number of users on the system. The perturbation distance on all three time periods of the Geo-In method proposed in this paper is the smallest among the five methods, and the perturbation distance decreases with the increase of the privacy budget, and the loss of quality of service is minimized. The Geo-In algorithm’s perturbed locations have less semantic similarity to the real locations of martial arts training, resulting in stronger privacy protection of the locations. Range counting queries experience a decrease in relative error as the number of users and query range increase.
Cultivation of International Vision and Communication Ability for English Majors in the Context of Cross-Cultural Communication
Authors: Qiu Yue
Published: July 2024

In this paper, business English majors from secondary vocational schools in province G were selected as the survey object to investigate the level of their intercultural communicative competence. The English intercultural literacy assessment system was determined using fuzzy hierarchical analysis, followed by the weight coefficients of indicators at all levels. Comparative experiments and questionnaires were employed to investigate if the four-in-one model teaching could enhance students’ intercultural communication competence. The results show that the average value of the current status of intercultural communication competence of Business English majors is 3.013, which is a low level. The weight of intercultural communication skills in the assessment of intercultural literacy is 0.414. The four-in-one model of teaching can significantly enhance the dimensions of intercultural communicative engagement, international perspective, communication skills, and communicative pleasure with p-values of 0.001, 0.012, 0.028, and 0.012, respectively. The experimental class’s mean total score on the posttest of intercultural communicative competence was 86.85, a 6.25-point improvement over the control group.
Research on Product Model Generation and Visual Presentation Incorporating Computational Aesthetics
Authors: Zhang Xinjia
Published: July 2024

In the era of aesthetic economy, users pay more and more attention to the aesthetic quality and emotional experience of products. The study discusses the intelligent design method of product model integrating computational aesthetics, combines the advantages of variational self-encoder and generative adversarial network, constructs a generative model based on VAE-GAN, and quantitatively analyzes the product images generated by the VAE-GAN network to explore the effect of the products it generates. Then, take the car form generated by the model as an example, establish the visual presentation quantitative index system of the product model form layout, and evaluate the visual presentation effect of the generated car model after applying gray correlation analysis to assign the indexes. The VAE-GAN model has a better generative effect, and its SSIM value is greater than 0.8 in most of the training phases. Among them, the product model generated after 2000 steps of training is the most excellent, with the highest evaluation score. The product model is the most outstanding, with the highest evaluation score of 1.92. The overall visual presentation effect of the product forms generated by the model is good, and the comprehensive evaluation scores are above 0.6. The VAE-GAN model can be used for product generation, and the visual presentation evaluation method that integrates computational aesthetics can realize the aesthetic evaluation of product forms, which can help designers make design creations and program decisions.
A study on the application of neural style transformation technique in personalized art creation
Authors: Zhao Yongtao
Published: July 2024

In this paper, using the loss function of image stylization, combined with the development of image stylization based on deep learning, the proposed convolutional neural network in the style of image conversion fitting and overfitting response. Based on this, the multi-scale feature fusion method is chosen to train the style conversion network, with the help of deep feature extraction of the image for style conversion, reconstruct the multi-scale feature fusion image, and send it to the decoder for deep coding to realize the style conversion. To evaluate the effectiveness of the proposed multi-scale feature fusion style conversion algorithm, the content loss and style loss parameters of the algorithm are analyzed using the lightweight encoder and VGG encoder, respectively. Calculate the number of algorithmic model parameters and the amount of computation. Analyze the change in the iteration number of the personalized art style conversion process and select the performance evaluation index to evaluate the results of the personalized art style image conversion process. In the process of personalized art style conversion, the multi-scale feature fusion algorithm network proposed in this paper can basically reconstruct the original image after 1000 iterations. Personalized style image reconstruction has a PSNR of 25.26 dB when the number of iterations is 1000. With the deepening of training, the reconstruction effect becomes better and better, and the advantages of personalized art style image conversion applications are significant.