bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intellectual Property Protection Issues and Solutions in Cross-Border Big Data Streams
Authors: Zhang Tianyu 
Published: July 2024

Abstract
This paper utilizes the hierarchical analysis method to create an intellectual property protection index model to measure the level and hierarchy of intellectual property protection from the judicial, administrative, and social perspectives and proposes solutions accordingly. From the standpoint of time series prediction, the deep learning theory time series is applied to fully explore the time series characteristics of the flow and a comprehensive assessment of the development status of online intellectual property protection from 2019-2024 is made. According to the findings, pornographic content is the most serious IPR infringement problem in cross-border big data flows, accounting for approximately 38% of all violations. Cases concerning domain name infringement show a gradual upward trend from 2014-2023. The automatic fulfillment index in the judicial protection index is the lowest, at 2.3, and it is important to strengthen this aspect in the future. The overall index of 75.6 in 2019 to 90.1 in 2023 indicates that the trend of intellectual property protection in China is generally positive.
The Interplay of Chinese Monetary Policy, the Offshore Renminbi Market, and Capital Flows: An Empirical Analysis via State Space Models
Authors: Zhang Weiran , Zhang Jiahui , Zhang Hongyang 
Published: July 2024

Abstract
This paper proposes state space modeling and Kalman filtering as the theoretical foundation to explore the impact of China’s monetary policy on the offshore RMB market and capital flows. In the state space model, the relationship between observable and unobservable variables is established, with the Hidden Markov Model representing the state vector as a first-order Markov process to estimate unobservable variables. Additionally, a variable parameter state space model is proposed to alter the relationship between explanatory variables and the dependent variable. Kalman filtering, as the core of the state space model solution algorithm, calculates the likelihood function through prediction error decomposition to estimate unknown parameters. The optimal lag of the model is determined to be 2 after constructing the VAR model in the empirical analysis, and the first-order autoregressive model is used to calculate variable parameters. The elasticity coefficient of the depth of development of the offshore RMB market on capital flows is the most significant variable, with a value of 0.96. Following this, the RMB exchange rate has an elasticity coefficient of 0.78.
Research on Corpus-based Graphic Analysis of Ceramic Science and Technology Texts and Its Application in Multimodal English Teaching
Authors: Jing Wang 
Published: July 2024

Abstract
With the continuous development of English education, the use of multimodal teaching methods in English instruction has gradually increased. This paper analyzes the characteristics of multimodal discourse and explores the principles of multimodal selection in English teaching. On this basis, a corpus-based graphic analysis framework for ceramic science and technology is constructed. A graphic matching model for ceramic science and technology text is established by combining text feature extraction and graphic feature extraction. The model is optimized using word vector distance and angular similarity measure algorithms, and an English-Chinese bilingual corpus is constructed based on web crawling. Empirical analysis shows that the metrics in text matching in the FK dataset have improved by 0.10% to 2.70% compared to CAAN. Image matching has been enhanced by 1.28% to 2.19%. The average value for both MS and FKMS datasets is 75.85%. Textbook A contains 582 more images with equal relationships than Textbook B and 155 fewer images with unequal relationships. This demonstrates that Textbook A provides a better way for teachers to guide students’ interpretation in multimodal English teaching. This study enhances English teaching and student skill development and also verifies the effectiveness of the graphic analysis method applied in English teaching.
The relationship between Cooperative Education and Occupational Aspiration of physical education students in the context of Artificial intelligence: the chain mediating role of employability and self-efficacy
Authors: Zhang Hui , Zhou Yi , Zhang Yuzhong 
Published: July 2024

Abstract
Under the new situation, the state vigorously supports physical education, and the cooperation between industry, academia, and research is increasingly showing an important role in physical education and students’ careers. In this paper, under the background of artificial intelligence, combined with the “government, industry, academia, research and utilization” cultivation mode, we constructed an industry-academia-research cooperative education model of physical education based on a cloud platform. Based on the edge structure model, a mediation effect test model was designed to verify the interlocking mediating roles of employability and self-efficacy in the relationship between cooperative education and physical education students’ career aspirations. Correlation analysis showed that there was a significant correlation (0.816) between physical education students’ acceptance of industry-academia-research cooperative education and career aspirations, and the correlation between cooperative education and employability and self-efficacy was strong. The mediation effect test found that both employability and self-efficacy had a significant mediating effect between cooperative education and career aspirations (P<0.05), and there was a chain mediating effect between the two. The application of the industry-university-research cooperative education model in this paper can promote the formation of good career aspirations among physical education students and provide a new direction for their future employment.
Exploring the Construction of BTI Translation Technology Course in the Context of New Liberal Arts
Authors: Chen Jun 
Published: July 2024

Abstract
Translation technology education represents a critical yet underdeveloped aspect in the training of Bachelor of Translation and Interpreting (BTI) students in higher education institutions. This paper delves into the implications of the emergent liberal arts paradigms on BTI education. It addresses the challenges inherent in existing BTI translation technology courses by proposing a novel instructional system rooted in machine learning. Specifically, the system utilizes a deep learning Sequence-to-Sequence (Seq2Seq) model to facilitate the transformation of source language text sequences into target language equivalents. Furthermore, the system integrates collaborative filtering to tailor content recommendations, thereby achieving functionalities such as real-time translation, personalized content suggestion, and adaptive learning. Subsequent to the system’s validation, the translation technology curriculum was restructured, and its efficacy was evaluated through a controlled pedagogical trial spanning one academic year. Performance metrics from the system’s deployment indicate robust outcomes in both development and test environments, with Bilingual Evaluation Understudy (BLEU) scores of 26.79, 26.34, 24.15, and 24.52, respectively—each surpassing competing models by a minimum margin of 2.5 points. The pedagogical trial further evidenced substantial academic gains; the average score of students in the experimental cohort rose from 12.79 to 17.44, marking an increase of 4.65 points. These enhancements substantiate the efficacy of both the bespoke BTI instructional translation system and the redesigned course framework. This investigation furnishes valuable insights and viable strategies for the amalgamation of information technology with BTI education, as well as for the innovation of translation technology curricula. It contributes to the enhancement of the BTI curriculum architecture within universities and promotes the evolution of translation technology pedagogy.
Application of electrical automation technology in factory production of edible fungi
Authors: Guan Jian , Yan Hui , Wu Qingshan , Lu Jianwei , Liu Xuguo , Shang Wenchao 
Published: July 2024

Abstract
With the gradual increase in the degree of factory production of edible fungi, automated control of the growth environment of edible fungi is particularly important. This paper utilizes the advantages of electrical automation technology to monitor the growth environment of edible fungi and regulate the environmental parameters of edible fungi factory production. Combined with the working principle of automation control systems, the fuzzy PID control algorithm is used to optimize the automatic control of edible mushroom factory production. By controlling and regulating the temperature and humidity of the growth environment of edible fungi, you can differentiate the automatic growth environment of edible fungi. Using fuzzy PID control technology to regulate the environmental conditions required for the growth and development process of PU Mushroom 1, we compared the seasonal mushroom production of PU Mushroom 1 with the mushroom production after applying the control system of the edible fungus growth environment. We compared the growth of the control area and the application area in terms of the rate of infection by stray bacteria at the mycelium stage of the almond abalone mushroom. The indoor temperature profile of the edible mushroom production environment controlled by fuzzy PID changed gradually, and the difference in temperature between day and night was reduced by 4.41°C compared to that outside. Regulating the opening of the greenhouse roller shutter prevented the indoor humidity from rising rapidly with the increase of outdoor moisture, which played a good role in humidity reduction. After applying the edible mushroom growth environment control system, the average yield of fresh mushrooms was 322.377g/bag, which was 33.7% higher than that of seasonal mushroom production. It shows that the application of automatic control technology for edible mushroom factory production can accurately assess and regulate the temperature, humidity, and other environmental conditions during the growth and development of edible mushrooms, which can promote the production capacity of edible mushrooms.
Optimization strategy of mixed-integer linear planning in logistics distribution
Authors: Li Yuhua 
Published: July 2024

Abstract
The evolution of the logistics and distribution industry, notably the express delivery sector, has significantly increased its prevalence in everyday life. This escalation necessitates an ongoing innovation in logistics strategies and enhancements in service quality, positioning these elements at the heart of industry focus. This study initially addresses the vehicular route planning issue within logistics distribution, selecting Company A as a case study to examine inherent logistical challenges. Subsequently, it develops an optimal route planning model under time constraints. It is converted into a mixed-integer linear programming model through techniques such as variable substitution and segmented linear approximation. This conversion facilitates rapid solutions by mathematical planning solvers. The research contrasts the logistics and distribution performance before and after optimization to assess the efficacy of the proposed strategies. Findings indicate that optimized vehicular route planning achieves a more equitable distribution of delivery tasks, along with substantial improvements in the complexity of transportation routes and the reduction of travel distances. Specifically, the optimization results in a significant decrease in the penalty costs associated with the vehicles, with the penalty cost for the third vehicle involved in the study reduced by 66.40%. This evidence supports the implementation of scientific vehicle scheduling strategies by logistics firms, underscoring the model’s practical implications.
Application and effect evaluation of computer simulation technology in ideological and political education
Authors: Sun Guoyang 
Published: July 2024

Abstract
The application of computer simulation technology can help students understand and learn ideological and political education in depth. This paper puts forward the development path of Civic and Political Education on the basis of computer simulation technology. It correspondingly constructs a computer simulation technology framework centered on students’ digital portraits and virtual scene technology. Sentiment analysis algorithm based on the BERT model and improved FastText text classification algorithm is used to extract the characteristic indexes of Civic and Political courses and realize the construction of digital portraits of Civic and Political courses and students. By adding a Gaussian curvature operator and implementing an edge-splitting strategy to optimize the narrow triangular surface, grid simplification of the QEM algorithm can be achieved to improve the consumption problem of computer scene resources. An experiment is being conducted on the effects of using computer simulation technology in Civic and Political Education at X High School in G City, Ningxia Hui Autonomous Region, China. Students in the experimental class supported by this technology improved their overall Civics score to 39.7 after the experiment, which was 4.02 higher than that of the control class. The mean values of all dimensions in the Civics knowledge level of the experimental class were higher than those of the control class, except for the dimension of knowledge transfer, which all showed a significant difference (P<0.05). In Civics Teaching Behavior and Ideal Conviction, each index score is greater than 4, indicating good performance in Civics Teaching.
Model analysis of flow-induced vibration (LIV) in submarine oil and gas pipeline
Authors: Qiu Yu , Xia Dongmei , Xie Jinhuang , Zhang Xuanhuan , Wei Dingwen , Li Yan 
Published: July 2024

Abstract
In order to realistically simulate the flow-induced vibration of submarine oil and gas pipelines, this paper assembles a gas-liquid two-phase flow vibration device, develops a detailed and comprehensive experimental procedure, and sets the flow aperture, flow pressure, flow depth, flow direction, and gas-liquid phase apparent flow rate and other variables. According to the different types of pipelines, the multiphase flow-induced vibration of submarine oil and gas pipelines can be categorized into straight pipe vibration and elbow pipe vibration, and combined with the theoretical knowledge of fluid dynamics and the equations of motion to construct a multiphase flow-induced vibration model of submarine oil and gas pipelines and discuss the vibration mechanism of submarine oil and gas pipelines in two-phase liquid flow. Combined with the corresponding experimental parameters, the vibration phenomenon induced by gas-liquid two-phase flow in submarine oil and gas pipelines is experimentally analyzed. It is analyzed that the first-order intrinsic frequency of the submarine oil and gas pipeline is kept at 23.2 Hz when the value of the Reynolds number of the in-pipe flow ranges from 2.53 × 104 to 1.08 × 107. The first-order intrinsic frequency of the submarine oil and gas pipeline monotonically decreases with the increase of the Reynolds number of the in-pipe flow. In addition, when Ul=0.4m/s, the average standard deviation of the data is only 1.114m/s² with the rise of Ug, indicating that the vibration intensity of the fluid on the subsea oil and gas pipeline increases gradually with the increase of the apparent flow velocity of the liquid phase. By analyzing the multiphase flow problem of oil and gas pipelines, this study is of great significance in improving the efficiency of oil and gas transportation.
Physical properties of two-dimensional black phosphorus and its application in optoelectronics
Authors: Yao Yin , You Haipeng , Bai Jianhui 
Published: July 2024

Abstract
Two-dimensional layered materials have gained significant attention in recent years as novel materials. By fabricating devices from these materials and evaluating their electrical and optoelectronic properties, we can preliminarily assess their potential applications in electronics and optoelectronics. This paper analyzes the physical properties of two-dimensional black phosphorus from both electronic and optical perspectives. Optoelectronic devices based on black phosphorus are fabricated, and their applications in basic photonics and bio-photonics are explored. A tunneling acceleration sensor is developed by integrating two-dimensional black phosphorus with a cantilever beam structure. The sensitivity, repeatability, and response time of the sensor are tested through simulation experiments. The experimental results show that the photocurrent of the 2D black phosphorus-based photodetector increases from about 103
A□W
−1 to about 105
A□W
−1 when the measurement temperature decreases from 250K to 25K at a power density of 10mW/cm2. The sensor was subjected to repeated loading and unloading under the application of 200g weights, and the capacitance output fluctuated back and forth between 40 and 450pF and remained essentially unchanged in the steady state, with stable capacitance performance and a fast response time of about 20S.
Research on Text Classification of Power Work Orders Based on RoBERTa-RCNN and Channel Attention Mechanism
Authors: Yu Yifan , Li Jing 
Published: July 2024

Abstract
Given the scarcity of algorithms for classifying power grid work order texts, coupled with challenges such as sparse features, lack of structure, and large data scale, this paper proposes a text classification model based on the Roberta-RCNN framework that incorporates a channel attention mechanism. The model employs the Roberta model for word vectors, masks entities and word semantic units, and links them to the Transformer encoding layer to encode the word embedding vectors output by the Roberta layer. This approach addresses model overfitting and enhances generalization ability. The RCNN model employs a channel attention mechanism to optimize feature extraction, allowing the model to focus more on learning feature representations from various channels, followed by softmax classification. Experimental results on the THUCNews short text dataset demonstrate improved evaluation metrics compared to existing methods. Comparative experiments on a self-compiled power grid work order dataset show that the proposed algorithm model achieves higher accuracy compared to other models. This indicates its effectiveness in extracting feature information from text and addressing the challenges of power grid work order text classification with promising classification performance.
A CFD simulation method study on the aerodynamic characteristics of particle suspension in tobacco stem shreds separating
Authors: Zhou Yuanzhen , Dai Tiansheng , Duan Yishan , Xu Shuhao , Yang Zhixiong , Li Peiwen , Pu Xuewen , Zhang Baode , Liu Jie 
Published: July 2024

Abstract
To solve the problem of high tobacco content and serious tobacco waste caused by poor equipment parameter settings in the tobacco stem shreds air separation process of the existing air separator of tobacco cutting workshop, this paper proposes a computational fluid dynamics (CFD) simulation analysis strategy for the aerodynamic characteristics of particle suspension in the air separator of tobacco cutting workshop. Firstly, in response to the problem that CFD numerical simulation software can only be applied to spherical models and cannot directly simulate the process of tobacco stem shreds selection, the discrete element analysis strategy DEM is introduced for fusion improvement, achieving effective simulation analysis of tobacco stem shreds selection process. Secondly, in response to the existing literature not considering the movement of the cut stem particles in the air separator and neglecting the particle collision during the tobacco stem shreds separation process, which leads to a certain deviation in the analysis data, a collision simulation model considering the radial movement distance between the stem and the floating chamber wall of the air separation device is introduced, which is fed back into the DEM-CFD fusion numerical simulation process to deeply optimize the parameters and improve the recovery efficiency of tobacco consumption. Finally, a domestic cigarette factory brand tobacco stem shreds and sticks were used as the experimental object for simulation analysis, and the optimal separation negative pressure of the air separator of the tobacco cutting workshop was obtained, verifying the effectiveness of the proposed method.
Research on Equipment Optimization of Tobacco Stem Shreds Air Separator Based on Particle Suspension Characteristics
Authors: Duan Yishan , Zhou Yuanzhen , Dai Tiansheng , Xu Shuhao , Yang Zhixiong , Li Peiwen , Pu Xuewen , Zhang Baode , Liu Jie 
Published: July 2024

Abstract
To solve the problems of low model simulation accuracy and slow simulation algorithm running speed that is not suitable for actual production needs caused by neglecting particle motion collision in the existing air separator of tobacco cutting workshop during the tobacco stem shreds air separation process, this paper proposes an equipment optimization research strategy based on particle suspension characteristics for the Tobacco Stem Shreds Air separator. Firstly, using the principles of suspension separation and inertial separation, a two-stage separation device for tobacco stem shreds is designed, and a two-stage separation chamber model is established. Computational fluid dynamics (CFD) numerical simulation is used to study the separation chamber of the tobacco stem shreds two-stage separation device. Secondly, the Discrete Element Simulation Platform is introduced to improve and enhance the CFD strategy, and it is used for simulation analysis of the Tobacco Stem Shreds Air separator process to solve the problem of ignoring collisions during particle motion solely using the CFD strategy. Finally, a parallel computing strategy is introduced to construct a parallel discrete unit individual (DUI) based CFD strategy (DUI-CFD), which solves the problem of low computational efficiency in single-threaded DUI-CFD coupling simulation technology. The proposed method has been shown to accurately simulate the separation process of tobacco stem shreds in an air separator and achieve higher simulation calculation speeds, as demonstrated by the experimental results.