bluuebunny/crossref_metadata_2025_split huggingface dataset:
From data to design: AI practice in design decisions
Authors: Du Wei 
Published: May 2024

Abstract
Facing the increasingly fierce market competition, enterprises need to make correct marketing decisions. Based on the decision support system, cloud server, and SOA framework, the article establishes an enterprise intelligent marketing decision-making system by combining the TCP/IP communication protocol and designing a data warehouse to store the marketing decision-making data. The Apriori algorithm in association rules is used to generate marketing rules to assist marketing decision-making, the marketing data is classified using the random forest algorithm, and the sparrow search algorithm optimizes the parameters of the random forest model. In practice, simulation experiments were designed to analyze the performance of the random forest model and the marketing decision-making system, and they were applied to the marketing decision-making example of the e-commerce platform. It was found that the AUC value obtained when the number of binary trees of the random forest model was 75 was 0.836, and the number of conflicts per second of the system was only 0.41 when the number of concurrent users was 5*104. The use of association rules resulted in eight marketing decisions, with the highest probability of user purchase prediction reaching 98.54%. Based on the intelligent marketing decision system, it can help decision-makers better analyze market changes and provide decision support for enterprises to develop scientific and reasonable marketing strategies.
Mining Text Value in Japanese Translation Teaching Based on KH Coder Text Data
Authors: Zhang Xiaoke 
Published: May 2024

Abstract
Vocabulary serves as the cornerstone of Japanese translation instruction, with the identification of high-frequency terms within educational texts yielding significant pedagogical insights. This study employs the KH-Coder software to extract feature words frequently used in Japanese translation teaching materials. Through a combination of covariate network analysis, sentiment analysis, and hierarchical clustering, the paper delves into the intrinsic textual value of these educational resources. Furthermore, it integrates both generative and discriminative approaches to conduct dependency parsing of Japanese translation. By incorporating probabilistic functions, the methodology enhances contextual understanding, ensuring that each annotation unit within a sentence is optimally tagged. Analysis of the CGTT-35 corpus through KH-Coder reveals a list of the top 50 high-frequency words in Japanese translation teaching, each appearing over 100 times. This enables students to use these frequent words and sentence structures as cues to master common phrases and familiarize themselves with core content. The approach has proven effective in enhancing students’ receptivity to Japanese translation instruction and their comprehension capabilities, offering valuable implications for teaching strategies.
Construction of a digital library of vocal music resources based on second-order data decomposition algorithm
Authors: Wang Chao , Guo Anni , Pan Yu , Shi Wei 
Published: May 2024

Abstract
In this paper, in order to solve the modal aliasing problem of the EMD decomposition algorithm and EEMD decomposition algorithm and optimize the vocal audio data decomposition on the basis of the adaptive VMD algorithm, the EEMD-VMD second-order data decomposition algorithm is proposed to decompose the digitized time series of vocal music resources, and to update the construction of the digital library of vocal music resources. Combined with the decomposition steps of the second-order data decomposition algorithm in the vocal resources digitized library, the overall framework of the vocal resources digitized library is designed and constructed with the main line of vocal resource types and the secondary line of content categories. Design the experimental environment, preprocess the vocal audio signal features, explore the modal number K value size of the EEMD-VMD second-order data decomposition algorithm, analyze the vocal audio denoising performance of the algorithm, and compare the correlation coefficients of the IMF components of the decomposition algorithms with the original audio signals. Explore the second-order data decomposition algorithm’s emotional classification of vocal resources and the performance of vocal signal enhancement, add noise sources, and use subjective and objective evaluation methods to assess the quality of vocal PESQ and STOI after decomposition processing. The EEMD-VMD second-order data decomposition algorithm performs the most prominently in street noise environments. The enhancement results in the case of signal-to-noise ratios of -5, -10, and -15 are 3.59, respectively, 4.36, 4.29, and the mean value of the enhancement performance reaches 4.08. The second-order data decomposition algorithm’s precise processing of vocal resources provides better quality digital resources for the construction of a digital library of vocal resources.
Exploring the Path of Village Protection and Renewal Strategy Based on the Maximum Information Entropy Model in the Context of Rural Revitalisation
Authors: Zhao Yufeng , Zhang Wenjun 
Published: May 2024

Abstract
A comprehensive and systematic view and solution to the protection and renewal of traditional villages can help actively promote and implement the strategy of rural revitalization. This paper constructs a village protection and renewal evaluation system based on the maximum information entropy model, utilizes the entropy weight method to build the index weight evaluation matrix, and introduces the confidence factor to correct the index weights, realizing the combination of the system. Then, based on the linear weighting method to carry out a comprehensive assessment of village protection and renewal development, and based on the assessment results to formulate a personalized village protection and renewal strategy, and the feasibility analysis of the strategy with the village of T city. The results show that village protection and renewal in T city villages generally indicate an upward trend from 2016 to 2023, and the comprehensive evaluation index reached a peak of 0.3227 in 2023. In the case study, the linear regression equations fitted to the scattering points of the uptown residential area villages and the entire T city villages’ axes intersect with a difference in slopes of 14.5123. The angle of the regression line continues to increase in comparison with 2016, indicating that the role of traditional village protection planning is significant. Village protection planning plays an important role in verifying the effectiveness of the formulated village protection and renewal strategy, which can promote the development of village regional characteristics for the good.
The Role and Impact of Social Media Data Analysis in Art Event Planning
Authors: Chen Jiahui 
Published: May 2024

Abstract
The proliferation of rich social data sources in the big data era offers a valuable opportunity for studying the planning of art events. In this study, we harvested data on art activity planning from social media via microblogging API calls, converting and analyzing this data through a novel methodological framework. Specifically, we employed the Sentiment-Enhanced Deep Graph Convolutional Network (SEDGCN) model to extract and identify sentiment features associated with art activity planning from social media datasets. Sentiments were categorized using the softmax function. Subsequently, our analysis integrated these findings into the art activity planning process. By conducting a correlation analysis between positive and negative sentiments on social media and various elements of art activity planning, we found a significant correlation (p < 0.005) with all six examined elements of art planning. Furthermore, an effectiveness analysis conducted post-implementation of the planned art events revealed predominantly positive emotional responses among attendees. Notably, 325 art professionals reported a sense of healing as a result of their participation. The methodology proposed in this paper for analyzing social media data effectively captures audience emotions, thereby assisting planners in crafting art events that resonate with and fulfill the emotional needs of the audience.
Application and Performance Evaluation of Superelastic Shape Memory Alloys in Building Vibration Isolation Systems
Authors: Chen Xiaoqin , Zheng Haibin 
Published: May 2024

Abstract
In this study, the intrinsic model of Shape Memory Alloys (SMA) is employed to facilitate a comprehensive analysis of the phase transition process, encapsulating the evolution of stress and strain across varying temperatures. The martensite volume fraction is quantitatively described using a cosine function, culminating in the formulation of a cosine-type SMA phase transition equation. This model enables the simulation of superelasticity, shape memory effects, and the elastic-thermal behavior of SMA by varying the loading conditions. This approach allows for an assessment of how different material parameters influence SMA properties. Notably, the results highlight that the heating temperature significantly affects the hyperelastic energy dissipation properties of SMA. The energy dissipation coefficient increased by 15.3% when the temperature was increased from 350 to 550 and decreased by 36.3% when the temperature was increased from 550 to 650. The peak values of top acceleration and interstorey displacement of the SMA-isolated structure were 0.826 m/s² and 0.641 mm for EL-centro waves at 7+ seismic intensities. The values of non-isolated were 1.151 m/s², 0.856 mm. 10 ground shaking, the SMA braced structure relative to the steel frame structure on the maximum peak inter-story displacement angle and the structure of the top layer of the permanent displacement, have different degrees of reduction. Therefore, the SMA material possesses good damping performance in the seismic isolation system.
Intelligent Detection of Robotic Arm Roller Wear Based on Combined DWAE and GRUNN Models
Authors: Dong Yan , Yuan Zheng 
Published: May 2024

Abstract
Long time and high intensity work makes the wear of the roller of the robotic arm increase gradually, which will affect the performance and service life if not regularly overhauled. In this paper, the sensor is used to obtain roller data from the mechanical arm, and the roller wear characteristics are extracted by combining them with the LSTM model. Based on the autoencoder, the wavelet function is introduced to establish a deep wavelet autoencoder, and the DWAE-GRUNN model is established by combining the gated recurrent unit neural network, which is used for the intelligent detection of the wear of the roller of the robotic arm. The model’s classification performance can be improved by using the CTC loss function, and the parameters can be optimized using the sparrow search algorithm. For the application of the DWAE-GRUNN model in the intelligent detection of roller wear of mechanical arms, this paper validates the model based on the aspects of performance, coefficient selection, and detection results. It is found that the average correct detection rate of the model in this paper is 95.97%, and the optimal accuracy is obtained when the weight attenuation coefficient of the DWAE structure is 0.005. The friction force changes inversely with the degree of smoothness after 3.1h of the detection time of the robotic arm roller, and the stiffness, cumulative large abrasive grains, and cumulative small abrasive grains also show significant changes. Using the DWAE-GRUNN model, changes in the wear of the robotic arm roller can be obtained, providing data support for timely maintenance.
A Perspective on the Current Situation of Children’s Education and Teachers’ Moral Cultivation Combined with Decision Tree Algorithm
Authors: Li Juan 
Published: May 2024

Abstract
The enhancement of children’s education quality necessitates a high level of teacher moral literacy. This paper employs data mining techniques to elaborate on the Classification and Regression Tree (CART) model within logistic regression and decision tree algorithms. Data pertinent to elementary school education were collected via questionnaires, followed by data cleaning and segmentation. The parameters of the CART model were optimized using a Bayesian algorithm, and its efficacy was validated through a dataset to support the exploration of factors influencing the developmental level of children’s education. Additionally, data regarding teachers’ moral literacy were gathered and analyzed using binary logistic regression within the logistic regression framework. The analysis revealed that the accuracy of the CART decision tree model reached 90%, with the error converging to zero at 50 trees. Key determinants such as willpower and communication abilities in children’s education were influenced by exercise duration, time spent in interest classes, gender, and parents’ educational levels. The mean score for teachers’ moral literacy was 4.349±0.465. Notably, teachers with low salary satisfaction exhibited a moral literacy level that was only 0.517 times that of their counterparts with high salary satisfaction. Establishing a scientifically sound and reasonable salary management system is crucial. Such a system can ignite teachers’ enthusiasm for teaching, substantially enhancing their moral literacy, which in turn positively impacts the level of children’s educational development.
Intercultural education and social innovation approaches as answers to societal challenges of migration
Authors: Spulber Diana , Nesterova Marja 
Published: May 2024

Abstract
Social reality is always in the process of changing. Globalisation has made these changes more abrupt with a more powerful impact. Migrations break one equilibrium and then create another. As a result, social reality is constantly facing new challenges. With ever-increasing immigration, social reality does not have time to settle an equilibrium that has to cope with significant changes. These situations can lead to social unrest. Both social innovations and intercultural education are constructive responses to these challenges. The manuscript aims to analyse how intercultural education and social innovation can be an opportunity to contribute to making societies more sustainable and cohesive.
Gender freedom through picture news. A visual - socio graphic analysis
Authors: Buoncompagni Giacomo 
Published: May 2024

Abstract
For two years now, the Taliban have regained control of the “new” Afghanistan. The images broadcast by Al-Jazeera of Islamic fighters inside the government building, of women fleeing, of violence at Kabul airport made this even clearer. The apparent openness to the press soon proved to be a fleeting veneer of democracy, and a sunset period for human rights began.
With the advent of the new Taliban government, the figure of the woman was relegated to the stereotype of wife and mother, while freedom of the press began to clash with radical Islamic thought. The panorama for Afghan women remains uncertain, and it remains to be understood to what extent their capacities, on the one hand, and the external actions of the international community, on the other, can influence the protection of rights and the improvement of conditions for women.
The work presented here traces the main critical aspects of the relationship between the media, women journalists, and gender equality in Afghanistan from two perspectives: the socio-historical and the socio-visual. Historical facts and international journalistic images accompany the analysis...
The Power of Small Talk Discourse as Mitigating Conflict in Different Religious Communities in Ntaram
Authors: Robot Marselus 
Published: May 2024

Objective: This research analyzes explicitly the tiny talk (fatik) discourse used by the Ntaram (Manggarai) Flores community as a verbal force to mitigate conflict in plural communities (different religions) in Ntaram, Manggarai-Flores.

Method: This research chooses qualitative (interpretive) because the data collected and analyzed is in words, phrases, clauses, or sentences. Data was collected through in-depth interviews with informants, which were determined purposively. In addition, the observation method is used to observe the daily communication of the plural community in Ntaram. Data were validated through (1) data source triangulation and method triangulation. (2) Checking validity through Focus Group Discussions involving key sources.

Results and Discussion: Small talk (fatik) in communicating between people of different religions in Ntaram: (1) Small talk in the form of greetings. Ntaram people call "ite" which means we (first person plural personal pronoun). The word addresses the speech partner (second person personal pronoun). (2) Small talk in the context of greetings, such as nia ngaok, which means "noisy." These pleasantries explain sociologically that the social behavior of the Ntaram people is cheerful and happy to accept anyone. (3) Typical terms of respect related to religion are ata sili mai wae and ata le mai tana golo. Ata silimai wae means people who come from the coast or riverbanks. (4) Ethics of Interrupting Conversations. Ntaram people have small talk about interrupting conversations ethically through small talk such as eta ulu keta ite and no ramping dite. Eta ulu keta means that I uphold your opinion above my head. These four types of pleasantries are most productively used in the context of building brotherhood amidst religious and ethnic differences in Ntaram.

Recommendations: The research findings recommend that (1) it is necessary to revitalize the small talk discourse in Ntaram in the form of content taught in schools. Thus, endemic inheritance is carried out well. (2) further research is needed regarding the antecedent factors that influence the harmony of multiethnic society in Ntaram. (3) Research in other areas must reveal how multicultural societies mitigate social conflict through small talk.
Challenges of Access to Treatments: The Case Of Laron Syndrome and the Fight For Social Inclusion
Authors: Vasco-Toapanta Gabriel Alejandro , Guanoluisa-Vasco Alisson Mayerly , Ochoa-Núñez Gabriela Alejandra , Vasco-Toapanta Cristhian Santiago 
Published: May 2024

Objective: To identify and disseminate the challenges faced by patients with Laron syndrome in accessing Mecasermin treatment in Ecuador.

Theoretical Framework: Laron syndrome is a rare genetic disease characterised by metabolic disorders such as hypoglycemia and severe growth retardation. Treatment with Mecasermin improves growth and thus quality of life for those affected. Ecuador has the largest Laron syndrome population in the world, extensively studied contributing to understanding the peculiarities and needs of these patients.

Method: Official documents, letters, news articles from national and international press, and legal and medical databases were reviewed. Legal and medical advice was sought for this study.

Results and Discussion: Over approximately ten years, a group of parents pursued national and international legal action to provide their children with the only scientifically validated treatment for this syndrome. However, authorities denied these requests without justification. It was only after the Inter-American Commission on Human Rights report the admissibility of this case that Ecuador began administering medication to children with Laron syndrome.

Research Implications: Increase public awareness of this rare disease and barriers faced by those affected, fostering empathy, and understanding of patients' needs.

Originality/Value: Identification of specific barriers to accessing treatment, while the quality of life of patients and their families is affected.
Total Quality Management in the Service Sector: A Case Study in a Water Supply Company
Authors: Souza Warton da Silva , Silva Mizael de Sousa , Santos Carla Daniele dos 
Published: May 2024

Objective: Analyze the benefits of adopting total quality in a water supply company, aiming to improve service quality and customer satisfaction.

Theoretical Framework: A literature review was conducted as a basis for understanding the key concepts of TQM, the dimensions of service quality, and the essential elements for the successful implementation of TQM in the context of the analyzed company.

Method: The research is classified as a case study with an applied qualitative approach. To achieve the proposed objectives, techniques such as documentary research, literature review, semi-structured interviews, and direct observation were used.

Results: The analysis of the results demonstrated that the water supply company faces significant challenges regarding service quality. From the TQM approach, opportunities for improvement were identified in different areas of the organization, both in the reliability of the services' outcomes, including the water treatment process and maintenance of the distribution network, and in customer service.

Research Implications: The research suggests that the water supply company should adopt TQM as a strategy to improve service quality, promote customer satisfaction, address internal challenges, and seek constant improvement.

Originality/Value: The study explores the application of TQM in a public service context, providing practical guidance and insights to improve service quality in a water supply company, with implications that may extend to similar organizations seeking to enhance their services and processes.
Effects of Climate Change and Global Warming on Enzymes
Authors: Agom Oshama , Gbadebo Adedeji 
Published: May 2024

Objective: The continuous rise in climate change has become a major cause of concern following the accelerated increase in temperature and its eventual consequences on the ecosystem. This study investigates the effects of global warming on Enzymes, with the aim of reviewing the relationship between climate change and enzymes.

Method: The methodology adopted for this research comprises of expository discussion. We explore the literature and carried out thorough theoretical discussion on the various impacts of climate change on enzyme-producing organisms, soil ecosystem, aquatic ecosystem as well as the role of enzymes in mitigating the consequences of climate change.

Results and Discussion: We find that temperature plays a crucial role in the activity of enzymes, which in turn has a significant impact on the entire organism. Any changes in temperature can disrupt the relationships between enzyme-producing microorganisms and the surrounding microbial communities. This disruption can have consequences for the overall ecosystem of microorganisms and affect the dynamics of enzyme production. When the temperature increases by 10°C, the rate of enzyme-controlled reactions doubles.

Implications: The practical and theoretical implications of this research are discussed. We show that temperature plays a crucial role in the activity of enzymes which in turn has a significant impact on the entire organism. The implication of our finding is that the relationship between global warming, climate change, and enzymes is complex and multifaceted.

Originality/Value: This study contributes to the literature by highlighting the interconnectedness of environmental factors with biological processes. The relevance and value of the paper are evidenced by the findings that Enzymes function within specific temperature ranges, and any shifts in temperature can affect their efficiency and their activity.