bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Key Technologies of Smart Breeding Platform Based on 5G
Authors: Yang Wen 
Published: March 2024

Abstract
In modern animal husbandry, the application of 5G technology opens a new era of farming management, especially in intelligent farming. The high-speed and low-latency communication characteristics make remote monitoring, data transmission, and thoughtful decision-making possible, significantly improving breeding efficiency and management. It has great potential for monitoring animal health, preventing and controlling diseases, and improving production efficiency. This paper explores the application of 5G technology in an intelligent farming management platform and its key technologies. By analyzing the needs of smart farming, we clarify the key application areas of 5G technology. To identify sick pigs, measure their weight accurately using binocular vision technology, and combine with machine learning algorithms, the YOLO v3 algorithm is utilized. The accuracy of sick pig identification based on YOLO v3 reaches 98%, the error of pig weight measurement is controlled within ±2%, and the real-time data transmission and processing realized by 5G technology significantly improves the efficiency of disease prevention and control.5G technology can effectively support the efficient operation of the intelligent farming platform, which is of great significance to enhance the level of farming management and promote the sustainable development of the animal husbandry industry.
Research on Online Course Design and Application of SPOC-based Moral Education Course
Authors: Zhang Yingshuai , Zhang Tongshuai , Jing Junmiao 
Published: March 2024

Abstract
Small Private Online Courses (SPOC) represent a significant stride in online education, merging personalization with flexibility to revolutionize moral education. Our research investigates the efficacy of SPOC for ethical education, leveraging advanced analytics like Pearson correlation and cosine similarity, alongside 3D convolutional neural network-based student behavior analysis, to develop a tailored teaching recommendation system. In a comparative 20-week trial involving traditional and SPOC methodologies, students engaged with SPOC demonstrated superior cognitive, emotional, and behavioral performance, outscoring their peers by 4.011 points in moral education. These findings underscore the transformative potential of SPOC in enhancing the quality and effectiveness of moral education online.
The Chinese Integration and Application of Marxism in the Context of Digital Intelligence
Authors: Xuan Lu 
Published: March 2024

Abstract
This paper aims to explore the integration of Marxism and Chinese-style modernization and its practical application in the context of the digital intelligence era. Through theoretical Analysis and empirical research, a system for assessing development of Marxist Chinese-style modernization has been established. The study finds that Marxism’s multiple characteristics, such as political, scientific, people’s, practical, developmental, and revolutionary, provide theoretical support for Chinese-style modernization. This paper uses grey correlation analysis and multiple linear regression models to evaluate the modernization development of 31 provinces, municipalities, and autonomous regions in China during 2010-2019. The study results show that the Marxist Chinese-style modernization index has grown from 0.164 in 2010 to 0.731 in 2020, with an average annual growth rate of 34.57%. The index significantly impacts the quality of the regional economy, cultural industry, and ecological environment. The study shows that the application of Marxism in China accelerates economic development and promotes the governance of cultural industry and ecological environment, which provides impetus for the construction of socialist modernization with Chinese characteristics.
Regression analysis of factors affecting college students’ employment motivation: college students’ willingness to receive career guidance
Authors: Zhang Rui , Jen Tsao Hsueh 
Published: March 2024

Abstract
This study analyzes the factors affecting college students’ employment motivation, especially the influence of college students’ acceptance of employment guidance, to propose effective strategies to improve employment motivation. This paper discusses the factors that affect college students’ employment motivation, with particular attention to their willingness to accept employment guidance. The research methodology included regression analyses of student data, significant data, and career guidance data for undergraduate students at University A between 2018 and 2022. The results showed that factors such as career guidance acceptance, professional knowledge, and interpersonal communication ability significantly affected students’ motivation to find employment. Specifically, students who received career guidance increased their motivation by an average of 15 per cent, while those with professional solid knowledge increased their motivation by 20 per cent. In addition, we found that gender, type of specialization and place of origin significantly affected motivation, and that comprehensive career guidance and targeted educational strategies are essential for improving college students’ motivation.
Research on Piano Curriculum Education and Its Performance Ecosystem Based on Network Flow Optimization
Authors: Wang Huang 
Published: March 2024

Abstract
This paper investigates music education, where an efficient and accurate performance evaluation system in the piano teaching and performance ecosystem is increasingly becoming an essential tool for improving teaching quality and performance level. The objective evaluation of students’ performance skills can be achieved by carefully analyzing piano performances using the network flow optimization technique. This technique optimizes the performance evaluation system’s audio recognition ability by analyzing the piano audio signal and solving the multi-constraint nonlinear optimization problem in a limited time domain. This paper establishes a network flow optimization model, applies the multi-constraint nonlinear optimization technique, and combines the non-negative matrix decomposition and dynamic time regularization algorithm to analyze the piano performance for experiments. After optimization processing, hundreds of piano audio samples were collected, and the audio recognition accuracy was improved by 20%. By optimizing and processing the audio signals from the network stream, the evaluation system could detect polyphony more accurately and track the musical score effectively, improving accuracy and efficiency. Using the non-negative matrix decomposition algorithm, the accuracy of detecting polyphony can reach 85%, while the dynamic temporal regularization algorithm can match the position of the musical score with 95% accuracy. The accuracy of piano performance evaluation is optimized by this network flow optimization method, providing new technical means for music education, and promoting the quality of teaching and performance.
Analysis of Construction Quality Control Measures of Building Decoration Engineering Based on Big Data Technology
Authors: Hong Ying , Xie Minjing 
Published: March 2024

Abstract
In the field of architectural decoration engineering, construction quality control is the main issue, which has a significant impact on project safety, cost and schedule. Under the background of the increasing maturity of big data technology, its application in the quality control of architectural decoration engineering has become a new trend in the industry, which is expected to improve quality management through technological innovation. This study analyzes the construction quality control measures of architectural decoration projects using big data technology to improve the efficiency and effectiveness of project quality management. The study utilizes PDCA and SDCA quality control theories, BIM technology, and extensive data analysis to fully monitor and assess the construction process of building decoration projects. The construction quality control mode using big data technology performs significantly better in improving project quality than traditional mode. The project’s second phase adopts the new model, and its construction quality score is higher than that of the first phase by more than 5 points on average, and the frequency of quality problems is reduced by 23%. A multi-layer fuzzy comprehensive evaluation model evaluates the quality control effect, and the construction quality control effect is rated as “excellent” with an affiliation value of 62.1%. The introduction of data technology significantly improves the efficiency and effectiveness of construction quality control in architectural decoration projects, and provides an effective management model for the industry.
Research on Long-term Mechanism of School-Enterprise Cooperation for Civic and Political Education Professional Talent Cultivation in Colleges and Universities under Big Data Technology
Authors: Shi Yaping 
Published: March 2024

Abstract
In the era of big data, establishing a sustainable school-enterprise collaboration framework for cultivating Civic and Political Education talents in higher education is crucial. This study employs the DEMATEL model and Structural Equation Modeling (SEM) to dissect this collaboration’s dynamics. Through DEMATEL, we unravel the complex interrelations among these factors, constructing a direct influence matrix and quantifying the centrality and causality indices. SEM further elucidates the causal interplays, underscoring the profound impact of university infrastructure, corporate culture, and governmental roles on the collaboration’s efficacy. Notably, the engagement of enterprise entities, academic institutions, and equitable benefit mechanisms emerge as pivotal, with path regression coefficients of 0.961, 0.943, and 0.925, respectively. The study highlights the indispensability of balanced benefit distribution, resource sharing, and strategic improvements in organizational management, pedagogical innovation, dual-expertise faculty development, and fostering industry-academia-research synergies. Offering theoretical insights and actionable strategies, this research advances the optimization of school-enterprise partnerships, ensuring the adept nurturing of Civic and Political Education professionals.
Exploration of Innovative Development and Talent Digital Cultivation Path of Computer Specialties in Colleges and Universities
Authors: Zou Hailin , Wu Qinlan 
Published: March 2024

Abstract
In the face of globalization and the rapid evolution of information technology, higher education, particularly in computer science, encounters both challenges and opportunities. This paper investigates strategies for fostering innovation and digital competency among university computer science students. Through an analysis of teaching methodologies across various institutions, student development, and industry collaborations, we propose a comprehensive educational framework. We evaluate and refine our student innovation ability assessment system by employing both quantitative and qualitative approaches, including the entropy weight method and gray correlation analysis. By updating curriculum content, prioritizing hands-on learning, and enhancing industry partnerships, we demonstrate a marked improvement in students’ programming and practical skills—showing 20% and 25% increases, respectively. Our findings advocate for a holistic revamp of teaching approaches, course material, and university-enterprise collaborations, aligning computer science education with the demands of the digital age.
Practice and Analysis of Rural Planning and Design for the Integration of Agriculture, Culture and Tourism in the Context of Big Data
Authors: Zhang Chao 
Published: March 2024

Abstract
In the contemporary society of globalization and rapid information technology development, rural areas face unprecedented challenges and opportunities. Rural planning and design are essential for regional economic development, cultural heritage, and ecological protection. As an innovative development model, integrating agriculture, culture, and tourism provides new ideas for rural revitalization. Big data technology can help analyze the countryside’s development potential more accurately and allocate resources more efficiently to promote the science and refinement of rural planning and design. This study establishes a GIS management system supported by geographic information data, uses Oracle database to manage spatial information and attribute information, and utilizes vector slicing technology and WebGL graphic rendering to achieve rapid rendering and diverse expression of maps. In creating an agricultural, cultural, and tourism integration index system, the entropy index method is used to assign weights to each index, and the coupling coordination degree model is set up. The coupling degree of Tibet’s agricultural, cultural, and tourism industry from 2011-2021 has increased from 0.219 to 0.769, and the coupling coordination degree has increased from 0.158 to 0.778, which shows an excellent upward trend. The study shows that big data technology can effectively improve the quality and efficiency of rural planning and design, and promote the development of agricultural, cultural, and tourism integration.
Factors Predicting Singers’ Work Efficiency and Singers’ Singing Peak
Authors: Huang Xuejie , Ang Mei Foong 
Published: March 2024

Abstract
The research focusses on understanding the controls and predicting singers’ work efficiency, which is measured by rework times (RwT) in the recording studios. We conducted a comprehensive literature synthesis to identify a set of nine critical factors combining advancements in both acoustic field and recording practice. We measured each of these potential variables while 10 individual singers performed the same original song independently. The pieces of music sentences (n = 380) were analyzed by the multiple linear regression method. We found that:

In the recording process, the RwT of a singer are predicted mainly by intensity, singing duration (SinD) and rhythm consistency.

SinD mediates the connection between intensity and RwT.

A singing peak exists in the performance.
A comparative study on characteristics of retracted publications across different open access levels
Authors: Zheng Er-Te , Fu Hui-Zhen 
Published: March 2024

Abstract

Purpose
Recently, global science has shown an increasing open trend, however, the characteristics of research integrity of open access (OA) publications have rarely been studied. The aim of this study is to compare the characteristics of retracted articles across different OA levels and discover whether OA level influences the characteristics of retracted articles.

Design/methodology/approach
The research conducted an analysis of 6,005 retracted publications between 2001 and 2020 from the Web of Science and Retraction Watch databases. These publications were categorized based on their OA levels, including Gold OA, Green OA, and non-OA. The study explored retraction rates, time lags and reasons within these categories.

Findings
The findings of this research revealed distinct patterns in retraction rates among different OA levels. Publications with Gold OA demonstrated the highest retraction rate, followed by Green OA and non-OA. A comparison of retraction reasons between Gold OA and non-OA categories indicated similar proportions, while Green OA exhibited a higher proportion due to falsification and manipulation issues, along with a lower occurrence of plagiarism and authorship issues. The retraction time lag was shortest for Gold OA, followed by non-OA, and longest for Green OA. The prolonged retraction time for Green OA could be attributed to an atypical distribution of retraction reasons.

Research limitations
There is no exploration of a wider range of OA levels, such as Hybrid OA and Bronze OA.

Practical implications
The outcomes of this study suggest the need for increased attention to research integrity within the OA publications. The occurrences of falsification, manipulation, and ethical concerns within Green OA publications warrant attention from the scientific community.

Originality/value
This study contributes to the understanding of research integrity in the realm of OA publications, shedding light on retraction patterns and reasons across different OA levels.
Challenges of Academic Ethos: The Scientific Community’s Response to the Ostracism of Russian Scientists Following the Invasion of Ukraine
Authors: Dziedzic Justyna , Sułkowski Łukasz 
Published: March 2024

Abstract

Objective
The primary aim of this article is to understand how contemporary scientists from the Polish academic community perceive the scientific ethos in the context of ostracism within the scientific community, which emerged following Russia’s invasion of Ukraine. The article focuses on analyzing the epistemological and ethical implications of this ostracism in the academic context, considering Russia’s invasion of Ukraine.

Methodology
For this purpose, in-depth interviews were conducted within the Polish scientific community (11 participants), with respondents with degrees (full professors, Ph. D’s, associate professors, assistant professors, and professor emeritus), and literature review was carried out.

Findings
Based on the discussion, the research findings illuminate diverse approaches within the Polish academic community regarding the ostracism of Russian scientists following Ukraine’s invasion, shedding light on the intricate interplay between personal beliefs, scientific ethos, and educational values while also highlighting the multifaceted ethical challenges faced by scientific research, especially within military and political contexts.

Value Added
The study suggests the necessity for academic institutions to establish clear protocols for knowledge dissemination and crisis management that respect the ethos of scientific work while being adaptable to the shifting geopolitical landscape. It is also recommended that there should be a concerted effort to create forums for international scholarly dialogue to ensure that ostracism does not stifle academic collaboration and knowledge advancement.

Recommendations
This article contributes to the existing literature by providing empirical insights into how the academic community navigates the ethical dilemmas posed by geopolitical conflicts. Moreover, it underscores the importance of maintaining the integrity of the scientific discourse amidst external pressures, offering a nuanced understanding of the interplay between political events and academic practices.
Analytical and Experimental Investigation of Asymmetric Floating Phenomena of Uniform Bodies
Authors: Gu Jian , Fernandes Antonio Carlos , Chai Wei , Bu Shu Xia , Han Xiangxi 
Published: March 2024

Abstract
Uniform symmetric bodies can be observed floating asymmetrically under certain circumstances. Previous explanations of this are mostly abstract and lack experimental verification, making their understanding and application difficult. This article presents in detail alternative insights into the floating equilibria of uniform prisms and parabolic cylinders. The intrinsic characteristics of the equilibrium curves are investigated, and several equilibria different from those in the literature are found. The inflection points in the equilibrium curves are analyzed quantitatively due to their significance for floating states. Furthermore, experiments have been conducted for the square prism which validate the derived equilibrium curve, and provide a practical impression of the asymmetric floating phenomenon of symmetric bodies. These results have the potential to be applied in naval and ocean engineering, such as in the design of vessels and floating offshore structures.
Analysis and Experimental Verification of Improving the EEDI of a Ship using a Thruster Supplied by a Hybrid Power System
Authors: Mindykowski Janusz , Wierzbicki Łukasz , Górniak Mariusz , Piłat Andrzej 
Published: March 2024

Abstract
In this study, the authors present a theoretical analysis and experimentally verified methods to improve the Energy Efficiency Design Index (EEDI) of ships. The improvements were studied via the application of an innovative solution of a thruster supplied by a hybrid power system on board a passenger-car ferry. The authors performed sea trials of a ship’s electrical power system supplied by battery packs with diesel generating set power units. The experimental study focused on energy balance and management, which were considered together with related power quality issues. The authors found that the application of an energy storage system to the ferry, such as batteries, with the simultaneous adaption of the operation modes of the electrical power system for current exploitation, significantly improved energy efficiency. Fuel consumption and CO2 emission were reduced, while adequate parameters of electrical power quality were maintained to meet classification standards.
Re-Identifying Naval Vessels Using Novel Convolutional Dynamic Alignment Networks Algorithm
Authors: Roy Sudipta , Jana Dipak Kumar , Long Nguyen 
Published: March 2024

Abstract
Technological innovation for re-identifying maritime vessels plays a crucial role in both smart shipping technologies and the pictorial observation tasks necessary for marine recon- naissance. Vessels are vulnerable to varying gradations of engaging in the marine environment, which is complicated and dynamic compared to the conditions on land. Fewer picture samples along with considerable similarity are characteristics of warships as a class of ship, making it more challenging to recover the identities of warships at sea. Consequently, a convolutional dynamic alignment network (CoDA-Net) re-identification framework is proposed in this research. To help the network understand the warships within the desired domain and increase its ability to identify warships, a variety of ships are employed as origin information. Simulating and testing the winning of war vessels at sea helps to increase the network’s ability to recognize complexity so that users can better handle the effects of challenging maritime environments. The impact of various types of ships as transfer items is also highlighted. The research results demonstrate that the enhanced algorithm increases the overall first hit rate (Rank1) by approximately 5.9%; it also increases the mean average accuracy (mAP) by approximately 10.7% and the correlation coefficient by 0.997%.