bluuebunny/crossref_metadata_2025 huggingface dataset:
РОЗВИТОК СУЧАСНИХ ТЕХНОЛОГІЙ: ВИКЛИКИ ДЛЯ НАЦІОНАЛЬНОЇ БЕЗПЕКИ ПОЛЬЩІ
Authors:   Інститут соціальних наук Академії Пьотрковської (м. Пьотркув-Трибунальський, Польща), Фуззі Ян
Published: October 2024

The main purpose of the article is to analyze national security challenges related to the development of modern technologies. The impact of this phenomenon on many aspects of safety in cyberspace is presented. The relationship between modern technologies with the military security of the state is also presented. There is also a cross-discussion of the struggle of state entities with terrorist threats directly related to dynamic technological progress. The possibilities of cybersecurity education at universities, within the framework of postgraduate education, courses and trainings are analyzed. The study shows that modern technologies have a significant impact on Poland's national security. Rapid technological development poses a serious threat to national security for any country, including Poland. They directly influence national security aspects as the fight against terrorism, ensuring the security of state institutions in cyberspace and guaranteeing permanent military development necessary to counteract both common and hybrid threats. The functioning of state entities and their citizens requires constant adaptation to an environment that changes dynamically in the international arena. Poland, like any other country, should be in constant readiness to resist the above mentioned challenges to defend their own national interests. To do this, you need to use the opportunities and soften the threats associated with the constant inter -sectoral development of technology. Modern information technologies offer advanced means and capabilities of cybersecurity. However, it also increases the potential for cyberattacks, which requires constant improvement and adaptation of cybersecurity policy. The development of military technologies, including artificial intelligence, nanotechnology, or cybercribe, changes the face of national defense. Poland needs to be effectively investing in modern defense technologies in order to maintain their defense capability at a proper level. Modern technologies influence the protection of critical infrastructure from potential terrorist attacks. Integrated IT systems can increase efficiency, but at the same time increase the risk of cyberattacks that can have serious consequences for the country's functioning. It is also necessary to strengthen international cooperation to exchange advanced experiences and work together to protect against modern technological threats. Key words: technology, military safety, terrorism, cyberspace, cybersecurity, higher education, Poland.
Performance of indicators used in regular risk assessments for COVID-19 in association with contextual factors
Authors: Hong Sujin , Oh Jiyoung , Lee Jia , Kim Yongmoon , Kim Bryan Inho , Lee Min Jei , Kim Hyunjung , Tak Sangwoo
Published: October 2024

Objectives: This study aimed to summarize the results of coronavirus disease 2019 (COVID-19) risk assessments and to examine the associations between risk levels and various indicators, including COVID-19 incidence, risk perception, community mobility, and government policy.Methods: The results of the risk assessment and the indicators utilized were summarized. From November 2021 to May 2022, the COVID-19 risk level was evaluated on a weekly basis, and its correlation with these indicators was analyzed. Data were obtained from press releases by the Korea Disease Control and Prevention Agency, regular surveys conducted by Hankook Research, and information available on the Google and Oxford websites.Results: Weekly risk assessments were conducted for 30 weeks, using different indices depending on the phases. Correlation analysis revealed the strongest positive correlation between risk level and risk perception (r=0.841). The risk level from “1-week lead” demonstrated a strong positive correlation with the time-varying reproduction number (Rt). Similarly, the risk level from “week lagged value” showed a strong positive correlation with the number of severe cases in the hospital.Conclusion: At the time of risk assessment, the Rt precedes the risk level, while severe cases in hospitals follow. Therefore, the assessed risk level functioned as an early warning system. Risk perception demonstrated the strongest correlation with the risk level, suggesting consistency throughout the assessment period. Contextual indicators (e.g., risk perception) that consider time lags and implementation scales, could improve the evaluation of future risk assessment results, particularly when there are challenges in reflecting specific situations in coordinated emergency response.
Traditional Craft Meets Contemporary: Exploring the Potential of Kelarai Bertam Weaving Technique in Modern Furniture Construction
Authors:   College of Creative Arts, Universiti Teknologi MARA Cawangan Kedah, Merbok, Kedah, Malaysia, Ahmad Zamri Ahmad Fazlan , Hasan Asrol ,   College of Creative Arts, Universiti Teknologi MARA Cawangan Kedah, Merbok, Kedah, Malaysia, Said Nurul Syafiqa
Published: October 2024

Kelarai Bertam is a traditional weaving method that has been used for ages to make comprehensive weaves for usage both indoors and outdoors in Malaysian homes. This traditional practice, however, is being explored as an innovative method to build modern furniture in response to the increasing need for unique and environmentally friendly designs. Using this detailed weaving technique, designers construct patterns and motifs that combine aesthetic appeal with practicality out of organic materials like rattan, bamboo, and pandan leaves. When applied to contemporary furniture, the outcome's combination of traditional craftsmanship and modern style is fascinating. This combination provides an opportunity to preserve and acknowledge traditional techniques while also emphasising the strength of Malaysian innovation in the present era.
Assessing cognitive flexibility in adaptive learning technologies for special education
Authors: Khasawneh Mohmmad Ahmad Saleem
Published: October 2024

This study used quantitative methods to examine the correlation between adaptive learning technology and cognitive flexibility in kids receiving special education. The study included a cohort of 120 kids, ages 8–12, who were diagnosed with particular learning difficulties, ADHD, or autism spectrum disorder. Cognitive flexibility was evaluated using the Wisconsin Card Sorting Test (WCST), while the utilization of adaptive learning technologies was quantified using self–report questionnaires. The data was analyzed using several statistical methods, such as independent samples t-tests, regression, Pearson correlation coefficients, ANOVA, and ANCOVA. The findings revealed a noteworthy and favorable correlation between the utilization of adaptive technology and the scores of cognitive flexibilities. This correlation remained significant even after accounting for demographic characteristics. Moreover, it was shown that the diagnostic status had a moderating effect on the correlation between the utilization of adaptive technology and cognitive flexibility. The results emphasize the capacity of adaptive learning technologies to improve cognitive flexibility abilities in kids with special needs, offering significant knowledge for educators, legislators, and technology developers.
Nexus between board characteristics and financial performance: Evidence from developing economy
Authors: Abdullah Shamsul Nahar , Chowdhury Kanta , Khan Maksudur Momin , Rahaman Mohammed Ashiqur , Masum Mofijul Hoq
Published: October 2024

Corporate performance is the key indicator of availing the economic performances in all economies. Especially for the emerging economy, it is the oxygen for smooth economic operations. The study aims to investigate the influence of board characteristics on the corporate performance of the listed pharmaceuticals and chemicals sector from a developing country, namely Bangladesh. This empirical study examines eight attributes of the board and four financial performance indicators of the businesses. Here, the annual reports of the DSE-listed pharmaceutical and chemicals companies are considered to examine the impact of board attributes on corporate performance. Based on panel data analysis, this empirical study concludes that the fixed effect regression model is suitable for all four models. Except board size, the results demonstrate that all board attributes are generally statistically significant. Furthermore, it confirms that all the significant characteristics of the board are positively associated with corporate performance, except for board independence. The research offers valuable insights for policymakers, investors, organizations, and scholars, promoting optimal board structures, innovative solutions, and an enhanced understanding of corporate governance matters. This research explores the challenges in board attributes, which enhances our understanding of corporate governance matters and their impact over the last decade in the listed pharmaceutical and chemicals sectors in Bangladesh.
Robotic assistants for the rehabilitation of communication disorders in children: A proposal based on MTO manufacturing for developing countries
Authors: Velásquez-Angamarca Verónica , Robles-Bykbaev Vladimir , León-Pesántez Adriana , Gómez-Galán Gabriela , Krupke David , Campos-Sarmiento Nataly
Published: October 2024

Language is fundamental to human communication, allowing individuals to express and exchange ideas, thoughts, and emotions. In early childhood, some children experience communication disorders that impede their ability to articulate words correctly, posing significant challenges to their learning and development. This issue is exacerbated in developing countries, where limited resources and a lack of technological tools hinder access to effective speech therapy. Traditional speech therapy remains vital, but the latest technological advancements have introduced robotic assistants to enhance therapy for communication disorders. Despite their potential, these technologies are often inaccessible in developing regions due to high production costs and a lack of sustainable manufacturing models. For these reasons, this paper presents “FONA,” a robotic assistant that employs rule-based expert systems to provide tactile, auditory, and visual stimuli. FONA supports children aged 3 to 6 in speech therapy by delivering exercises such as syllable production, word formation, and pictographic storytelling of various phonemes. Notably, FONA was successfully tested on children with cochlear implants, reducing the number of sessions required to produce isolated phonemes. The paper also introduces an innovative analysis of the Make To Order (MTO) manufacturing system for producing FONA in developing countries. This analysis explores two key perspectives: collaborative networks and entrepreneurship, offering a sustainable production model. In a pilot experiment, FONA significantly improved children’s attention spans, increasing the period by 17 min. Furthermore, the economic analysis demonstrates that producing FONA through collaborative networks can significantly reduce costs, making it more accessible to institutions in developing countries. The findings suggest that the project is viable for a five-year period, providing a sustainable and effective solution for addressing communication disorders in children.
Analysis of tourist flow prediction model of rural tourism on the edge of big cities in China
Authors: Yin Na , Sutunyarak Chonlavit
Published: October 2024

Introduction: With the adoption of the rural rehabilitation strategy in recent years, China’s rural tourist industry has entered a golden age of growth. Due to the lack of management and decision-support systems, many rural tourist attractions in China experience a “tourist overload” problem during minor holidays or Golden Week, an extended vacation of seven or more consecutive days in mainland China formed by transferring holidays during a specific holiday period. This poses a severe challenge to tourist attractions and relevant management departments. Objective: This study aims to summarize the elements influencing passenger flow by examining the features of rural tourist attractions outside China’s largest cities. Additionally, the study will investigate the variations in the flow of tourists. Method: Grey Model (1,1) is a first-order, single-variable differential equation model used for forecasting trends in data with exponential growth or decline, particularly when dealing with small and incomplete datasets. Four prediction algorithms—the conventional GM(1,1) model, residual time series GM(1,1) model, single-element input BP neural network model, and multi-element input BP network model—were used to anticipate and assess the passenger flow of scenic sites. Result: The multi-input BP neural network model and residual time series GM(1,1) model have significantly higher prediction accuracy than the conventional GM(1,1) model and unit-input BP neural network model. A multi-input BP neural network model and the residual time series GM(1,1) model were used in tandem to develop a short-term passenger flow warning model for rural tourism in China’s outskirts. Conclusion: This model can guide tourists to staggered trips and alleviate the problem of uneven allocation of tourism resources.
Analysis of the results-based budget and its effect on the quality of public expenditure of the national penitentiary institute, Peru
Authors: Ticona-Carrizales Lucio , Condori Sara Copari , Segales Betty Campos , Saico Cristóbal Rufino Yapuchura , Campos Varanny Nelyda Ticona , Apaza-Panca Cynthia Milagros
Published: October 2024

Since 2007, Peru has implemented results-based budgeting in order to ensure the quality of public spending in State entities and that the population receives goods and services in a timely manner; However, the demands of the current legal and regulatory context require a progressive application to budget processes such as that of the National Penitentiary Institute, which is basically focused on the allocation of resources by the central government, the collections it receives for penitentiary work. and the TUPA; Likewise, it requires strategic programming based on results, refining the procedures for programming, formulation, execution and evaluation of the budget. The objective of this research work is to describe the relationship between results-based budget management and the quality of spending in the Altiplano-Puno Regional Directorate of the National Penitentiary Institute in the period 2019. To achieve the objective, the descriptive explanatory method was used; in addition, the questionnaire and documentary analysis were used as a data collection instrument to determine the relationship between the study variables. Finally, it is concluded that the results-based budget is significantly related to the quality of spending, which means that the entity managed to apply the results-based budgeting methodology efficiently, obtaining an improvement in the quality of spending, consequently focusing on the optimization of the use of financial resources to achieve the strategic objectives of the penitentiary administration in this region. This approach seeks not only to guarantee the correct execution of spending, but also to maximize its positive impact on the management and conditions of penitentiary centers. In this way, a results-based budget approach must be implemented and ensuring the quality of public spending will allow the Office Regional Altiplano Puno of the INPE use its resources more effectively, achieving the objectives of prison security and rehabilitation and improving conditions in penitentiary centers. The adoption of efficient and transparent management practices will contribute significantly to a more responsible and results-oriented public administration.
Entrepreneurship education and digital transformation, opportunities and challenges in Indonesia
Authors: Rauf Rusdiaman , Raheni Cahyaning , Tovan Tovan , Mardia Mardia , Setiawan Lukman , Rodliyatun Mushbihah
Published: October 2024

This article explores the landscape of entrepreneurship education in Indonesia amid the wave of digital transformation. The research method uses Systematic Literature Review (SLR) to review research results sourced from journals indexed in Sinta or nationally accredited journals in Indonesia which can be accessed on Google Scholar. The conclusion, (i) Digital transformation-based entrepreneurship education creates a new learning model in colleges with the aim of developing entrepreneurial attitudes and values among young people, especially students, so as to produce entrepreneurial intentions. (ii) Higher education as an entrepreneur education provider must follow the progress of digital transformation in the teaching process of entrepreneurship education so that digital literacy among lecturers and students is getting better. (iii) The participation of stakeholders, the Government, college and the business world, is expected to provide support in policy making, especially curriculum changes in accordance with current circumstances in creating new business actors or entrepreneurial intentions.
How proficient are tertiary education providers in engaging with open-learning environments? A comparative study in the post-COVID-19 transition
Authors: Alimova Aziza , Turner Jason , Falahat Mohammad , Dana Kamilla
Published: October 2024

Purpose: This research paper aims to assess the proficiency of tertiary education providers in engaging with online learning environments, especially in the context of the post-COVID-19 transition. The COVID-19 pandemic accelerated the adoption of online learning platforms, it is essential to understand how educational institutions have adapted and evolved in their approach to virtual education. The central research question explores how Continuous Professional Development (CPD), Technological Infrastructure (TI), and Support Systems (SS) collectively influence educators’ proficiency in online teaching (POT). Study design/methodology/approach: A comparative study was performed, comparing data collected during the COVID-19 pandemic with post-pandemic data from higher education institutions in Uzbekistan. In-depth interviews were conducted with 15 education facilitators representing both public and international educational institutions. This purposive sampling approach allows for a holistic exploration of the experiences, challenges, strategies, and preparedness of these facilitators during the transition to online learning. Manual qualitative data classification and content analysis were employed to understand themes in respondent experiences and identified actions. Findings: The study reveals the significant role of CPD, robust TI, and effective SS in enhancing the Proficiency of tertiary education providers in engaging with Online Teaching. These elements were found to be significant determinants of how well institutions and educators adapted to the shift to virtual education. The research offers valuable insights for educators, policymakers, and students, aiding in decision-making processes within academia and guiding the development and implementation of effective online teaching strategies. Originality/value: This study contributes to the existing literature by providing an in-depth understanding of the adjustments education facilitators make in response to the pandemic. It emphasizes the importance of ongoing preparation for online learning and highlights the role of digital workplace capabilities in ensuring successful interaction in virtual educational environments.
The production systems green development: Waste logistics and data-driven waste management
Authors: Shinkevich Aleksei , Ershova Irina , Malysheva Tatyana
Published: October 2024

Increasing the environmental friendliness of production systems is largely dependent on the effective organization of waste logistics within a single enterprise or a system of interconnected market participants. The purpose of this article is to develop and test a methodology for evaluating a data-based waste logistics model, followed by solutions to reduce the level of waste in production. The methodology is based on the principle of balance between the generation and beneficial use of waste. The information base is data from mandatory state reporting, which determines the applicability of the methodology at the level of enterprises and management departments. The methodology is presented step by step, indicating data processing algorithms, their convolution into waste turnover efficiency coefficients, classification of coefficient values and subsequent interpretation, typology of waste logistics models with access to targeted solutions to improve the environmental sustainability of production. The practical implementation results of the proposed approach are presented using the production example of chemical products. Plastics production in primary forms has been determined, characterized by the interorganizational use of waste and the return of waste to the production cycle. Production of finished plastic products, characterized by a priority for the sale of waste to other enterprises. The proposed methodology can be used by enterprises to diagnose existing models for organizing waste circulation and design their own economically feasible model of waste processing and disposal.
Commutativity criteria for prime and semi-prime rings with semi-involution
Authors: Idrissi Moulay Abdallah
Published: October 2024

In this article, we study the concept of semi-involution on rings, which in general, is neither a usual involution nor a Jordan involution. Furthermore, we describe the structure of rings that satisfy certain differential identities on rings with semi-involution.
Research on National Cross-border E-commerce Trade Innovation and Development Strategy in the Context of Digital Economy
Authors: Liu Jiangwei , Liu Fei , Xie Min
Published: October 2024

Cross-border e-commerce is divided into export cross-border e-commerce and import cross-border e-commerce. Based on the fact that the development of China’s export cross-border e-commerce trade is dominant at present, this paper takes the diamond model and the theory of platform economics as the basis of model construction and selects the trade demand, human resources, cross-border platforms, cross-border payment and cross-border logistics to constitute the influencing factors of cross-border e-commerce system variables. Among them, for the influence mechanism of e-commerce development level on cross-border e-commerce trade, a cross-border e-commerce development level measurement index system has been established. Utilizing the entropy value method and comprehensive index method, the measurement value of the cross-border e-commerce development level is obtained. The order of importance of each influencing factor is determined using principal component analysis. The trade gravity model is introduced, combined with cross-border e-commerce export monitoring data, to carry out the model smoothness test and regression model solving. From the regression results, the P-values of the t-test statistics of independent variables InGDP
c
InR
i are 0.162 and 0.806 (>0.05), respectively, indicating that the influence of these two independent variables on the dependent variable is not significant. That is, China’s GDP and whether to join the “The Belt and Road Initiative” have no significant impact on the scale of China’s cross-border e-commerce trade. According to the regression results of the model, GDP, the coefficient of population size and the number of Internet users are highly positively correlated with the scale of cross-border e-commerce trade of the country, and the innovation of cross-border e-commerce trade can be based on the coefficient of GDP, the coefficient of population size, the number of Internet users and other aspects.
Big Data Knowledge Graph of Charging Safety Influencing Factors and Database Construction Method of Safety Features
Authors: Bai Shaofeng , Song Heng , Liu Zhibin , Chen Qian , Huang Wei , Yan Xinwei , Geng Deji
Published: October 2024

In this paper, we utilize big data to screen relevant data on charging safety influencing factors and perform data cleaning to constitute a charging safety influencing factors dataset. BERT is selected as the baseline model for the named entity recognition task, together with the CRF model, to exclude irrelevant features, resulting in an effective model for entity recognition in line with the knowledge graph. Introducing a security database, a graph attention network model that simultaneously obtains the structural features and textual description features of the security knowledge graph is proposed to improve the performance of knowledge graph relationship extraction. The dataset of high-frequency charging security composition, as well as the random dataset, are used as experimental samples, respectively, to compare and analyze the performance of the BERT-CRF named entity recognition model in terms of each index. The link prediction evaluation task is evaluated using the structure- and text-based graph attention network model, and experimental analysis is carried out using three benchmark models. From the overall results of the test, it can be seen that the BERT-CRF model learns 90% of the lexicon’s knowledge and passes the model test by keeping each evaluation metric in the range of 0.9 to 1.0 under the large data volume experimental environment. The proposed graph attention network model, which uses structure and text, has a better link prediction performance than other models and performs better in the FB15K-237 dataset.
Research on the Innovative Application of Artificial Intelligence in Cultural Heritage Services of Libraries
Authors: Chen Wei , Sun Cong
Published: October 2024

This paper applies artificial intelligence technology to libraries to promote service innovation in information resource construction, intelligent push and information analysis. Starting from college libraries, we collect relevant news reports and activity message texts from their libraries as textual materials for analysis and utilize the LDA subject model to reveal the current development status of the application of cultural inheritance in smart college libraries. A questionnaire was used to explore the tendency of teachers and students to promote cultural resources through RSS in smart college libraries. The results indicate that in smart libraries’ cultural heritage work, online services and knowledge resource services are the primary areas of focus, with their thematic strengths being 0.13874 and 0.12912, respectively. As time goes by, the intensity of the cultural theme of red gradually increases. The trend of RSS pushing resources in red culture, morality, philosophy, art, and religion is more than 60%.
Research on the Construction of Intelligent Evaluation System of State-owned Asset Management Performance in Higher Vocational Colleges and Universities Based on Data-Driven Approach
Authors: Chen Xiuchen
Published: October 2024

State-owned assets are an important guarantee for the daily teaching and research activities of higher vocational colleges and universities and serve an important role in ensuring the long-term development of higher vocational colleges and universities while also serving as an important task for talent cultivation and discipline development. In this paper, the construction process of the state-owned assets management performance assessment system is studied in depth, and the state-owned assets management level of higher vocational colleges and universities is analyzed by combining the hierarchical analysis method with the comprehensive fuzzy evaluation method. By constructing the index system and judgment matrix, the weights of “asset security level”, “asset management capacity”, “asset operation efficiency” and “asset management effect” are determined. The weights of “asset security level”, “asset management capacity”, “asset operation efficiency” and “asset management effect” are 0.41, 0.19, 0.18 and 0.22, respectively, and the judgment matrix satisfies the consistency test. The constructed index system is used to assess the management of state-owned assets of a higher vocational college, and the quantitative results show that its fuzzy comprehensive evaluation score is 66.6, reflecting the good level of comprehensive management of the school. The scores of specific level 1 indicators show that the school performs well in “asset management capacity” (70.08 points) but in “asset protection level” (66.72 points), “operational efficiency” (63 points) and “asset management capacity” (63 points), the school’s overall management level is good. However, there is still much room for improvement in “asset security level” (66.72 points), “operational efficiency” (63 points) and “management effectiveness” (66.32 points).
A real-time early warning method for electric vehicle fast charging safety based on multiple time scales
Authors: Song Heng , Huang Wei , Liu Zhibin , Li Lei , Luan Zhongfei , Liu Zhenyang , Sun Yuke
Published: October 2024

This paper puts forward the support technology of fast charging supply and demand matching in charging stations and analyzes the common large-capacity electrochemical energy storage technical parameters in charging stations. For the safety of electric vehicle charging, the thermal reaction and thermal runaway processes of power batteries are introduced. Design the electric vehicle charging state monitoring and safety warning methods, and select the multi-timescale ARIMA algorithm to build the electric vehicle charging safety warning model. The sliding window method is used to process the residual mean and residual standard deviation of electric vehicle charging data to improve prediction data and decrease the chance of misjudging pre- and alarms. Combined with the evaluation standard of the safety early warning model, set reasonable pre- and alarm thresholds using the residual analysis method. The safety warning model designed in this paper is verified by different charging fault warnings. Different charging fault warning examples show that the ARIMA-based charging safety early warning model proposed in this paper can be good for the charging facility’s output voltage, output current, and charging module temperature faults for early warning to ensure that the warning is carried out before the alarm of the actual fault information, to protect the charging safety of electric vehicles.
Research on the Strategy of Artificial Intelligence Technology in Enhancing the Quality of Students’ Civic and Political Education in Colleges and Universities
Authors: Wang Xia , Wu Meng
Published: October 2024

This study utilizes clustering algorithms, based on subject knowledge mapping, to construct a learning community that can support the comprehensive development of group wisdom, taking into account the learner portrait, initial learning community, and the learning path. In order to verify the validity of the E-GPPE-C model of wisdom learning, University X was selected to conduct a one-semester quasi-experimental study. Attitude data and outcome data from the pre- and post-teaching portraits were collected to analyze the effectiveness of teaching based on the amount of change and significance test. Using the E-GPPE-C model of smart learning proposed in this study, the number of learning achievers before and after teaching increased to 8, which can improve the learners’ academic performance in civics and politics (P<0.05) and their’ satisfaction with the learning environment. Many students believed that smart teaching had changed their ideal beliefs and knowledge base in civics and politics.
Study on the correlation between treatment outcome and quality of life of adolescent scoliosis based on big data analysis
Authors: Wei Qionge , Li Yongmei , Jin Lihua , Dong Juchuan , Wang Chuanhai
Published: October 2024

To evaluate the correlation between changes in spinal balance parameters and healthy quality of life after treatment of adolescent idiopathic scoliosis. The current study concentrated on the imbalance of the shoulder and pelvis in the coronal plane, along with the changes in thoracic and lumbar curvature and pelvic positional morphology in the sagittal plane in adolescent AIS patients. The aim was to summarize the characteristics of the morphological imbalance in the coronal and sagittal planes of AIS patients, and to investigate the mechanism of the influence between scoliosis deformity and the localized or overall morphological imbalance of the torso. Observe the changes in coronal and sagittal morphology indexes before and after rehabilitation treatment and analyze the effect of rehabilitation treatment on AIS. Based on the inclusion criteria, the Spine Disease Big Data Platform selected fifty patients with AIS and took pre-intervention full spine radiographs. The Cobb angle, clavicular angle, coronal pelvic tilt angle, and coronal sacral tilt angle were measured on the orthopantomographs, and the coronal torso offset was recorded. Pearson’s correlation coefficient was used to analyze the correlation between radiological parameters and quality of life score values. The mean value of ODI in the patients was 38.12±15.35 preoperatively and 19.11±10.43 after rehabilitation treatment, and the difference between preoperative and postoperative was statistically significant (p<0.05). The mean value of the patient’s Cobb angle decreased from 36.12±17.25° before rehabilitation therapy to 11.61±8.72° after rehabilitation therapy. The maximum isometric muscle strength of the subjects was measured in the standing position, prone position, and sitting position, respectively, and the strength of the low back muscles of the AIS patients who had undergone systematic treatment, compared with the observation group, was significantly improved (p<0.05). Improving spinal balance parameters alone does not indicate an improvement in quality of life after treatment in patients with AIS. It is more common for adolescent scoliosis patients to exhibit a high pelvic tilt angle and a low sacral incidence angle, and systematic treatment can effectively increase the sacral tilt and decrease the pelvic tilt angle, correcting spinal-pelvic imbalance in scoliosis patients. In AIS patients, the maximum isometric muscle strength of the low back muscles in a standing position significantly correlated negatively with dysfunction scores and positively with the patients’ health-related quality of life. The correlation was most significant with the dimensions of physiologic function and physiologic function, which are sensitive indicators of quality of life in patients with AIS.
Model Construction of the Impact of Digital Transformation of Non-Heritage Cultural Assets on Rural Revitalization in the Framework of Quantum Computing
Authors: Gao Xiaomei
Published: October 2024

In the new journey of building a socialist modernized country, how to empower rural revitalization in ethnic areas with non-heritage cultural assets is an important topic that requires in-depth thinking. In this paper, the development level of rural revitalization and the degree of digital transformation of non-heritage cultural assets are taken as explanatory variables and explanatory variables, and the gray correlation between them is calculated using the gray correlation analysis method. Then, based on the differential evolution operator and the improved quantum particle swarm algorithm with weighted coefficients as a framework, the impact prediction model of digital transformation of non-heritage cultural assets on rural revitalization is constructed. The study shows that the grey correlation between X2 “reliability”, X4 “quality” and X7 “diversity” and the development level of the rural revitalization of the three variables of digital transformation of non-heritage cultural assets exceeds 0.8 percent. The grey correlation between X2 “reliability”, X4 “quality” and X7 “diversity” and the development level of rural revitalization among the three variables is more than 0.850, and the grey correlation of the other variables is above 0.70, which indicates that the digital transformation of NRM cultural assets is a possible way out of rural revitalization. In addition, the MAE value of the impact prediction model constructed in this paper is 1.63%, which is much lower than other comparative models, indicating that it can accurately predict the impact of digital transformation of non-heritage cultural assets on rural revitalization. This paper studies the impact mechanism of digital transformation of non-heritage cultural assets to drive the development of regional high-rural revitalization. It is of great significance for other ethnic regions and even backward regions.
Research on the Application of Deep Learning Algorithm of Artificial Intelligence to 3D Clothing Design in Computerized Virtual Reality Environment
Authors: Hu Lingling
Published: October 2024

In this paper, point cloud data is used to construct a human body model, which in turn forms the transformation process of the human body. The corner point detection method is used to decompose the user-input two-dimensional garment shape contour lines, resulting in two types of data lines: shape lines and cross lines. Furthermore, the stereo configuration of the three-dimensional virtual garment is automatically generated using the void volume modeling method and displayed in real-time. The real graphic effect of 3D style is also studied by applying lighting and material processing methods. And take the actual case as the starting point to complete research on the use of 3D clothing design. After analysis, it can be seen that the standard deviation of point cloud data measuring human body parts is small, and the average errors of thickness, circumference, and volume are 1.21%, 2.64%, and 0.053%, respectively. The experimental study designed four garment models with the highest chest fit in terms of T-shirt styles’ fit measurement.
Study and Modeling of Nonlinear Dynamic Characteristics of DC-DC Converters with Amnesia Loads
Authors: Li Rong , Zhou Ling , Pan Haijun
Published: October 2024

The chaos phenomenon is a seemingly random irregular motion occurring in a deterministic system, which is an inherent characteristic and prevalent phenomenon of amnesia-loaded DC-DC converter nonlinear systems. Nonlinear dynamics and chaos theory guide the text, and we create an amnesia-loaded DC-DC converter system model using an amnesia resistor. We analyze the stability of the system using Filippov theory, and analyze the nonlinear dynamic characteristic behavior of the amnesia-loaded DC-DC converter using the time-domain waveform diagram, bifurcation diagram, and phase-track diagram. This paper talks about the slope compensation method and the parametric resonance perturbation method for control analysis. These methods are used to stop the chaotic behavior that happens in the amnesia-loaded DCDC converter. The system maintains a stable state when the reference current is less than 4.732A and the supply voltage exceeds about 17.966V, maintaining an amplitude of the maximum eigenvalue below 1. When the load resistance is 50Ω, the capacitance is 43 uF, the inductance is 2.8 mH, and the reference voltage is 2.05 volts, the amnesia-loaded DC-DC converter suffers from obvious chaos. To restore the system to a steady state by applying the ramp compensation method, the slope of the ramp signal will need to increase as the reference current increases. Loading amnesia onto the DC-DC converter achieves a stable cycle 1 state when the perturbation phase’s fluctuation range falls between 4.35 and 6.15. A nonlinear dynamic analysis of the amnesia-loaded DC-DC converter helps find the stable parameters of the amnesia-loaded DC-DC converter and improve the design of the converter.
Research on Real-Time Semantic Understanding and Dynamic Evaluation of Artificial Intelligence Techniques in Multilingual Environments
Authors: Li Wenyi , Li Gang
Published: October 2024

NPMI is used to describe the local co-occurrence properties of words, and the collected text data is constructed into a homogeneous graph composed of words. A word-granularity graph convolutional neural network (VGCN) is used as a graph encoder to achieve parallel training of graph convolutions. The output of the VGCN is used as a kind of embedding vector for BERT, and the VGCN is fused with other embedding using a transformer for feature fusion. The reprojection layer converts the model output to semantic representation vectors, and the post-projection layer converts the semantic representation vectors to vectors for loss computation. NT-Xent is chosen as the loss function of the model, while the real-time semantic understanding effect of the model is evaluated using the Spearman correlation coefficient in statistics. The CBOW model provided by Word2vec is learned from the training set and constantly updated for each parameter to calculate semantic similarity between words. The LDA model is used to extract topic keywords from each document and calculate the probability, which finally completes the dynamic assessment of the credibility of text content based on semantic understanding. The ROUGE-L index and BLEU-4 index of the VGCN-CL model in this paper are 66.47% and 63.86%, respectively, which are 23.20% higher than the baseline model ROUGE and 25.14% higher than BLEU-4. When the content assessment results are true, the accuracy and other metrics of this paper’s model are 90.36%, 89.87%, and 90.09%, respectively, which are the best performance among all models.
Research on the Integration and Innovation of Artificial Intelligence Technology in Modern Brand Design
Authors: Liu Xuelin
Published: October 2024

In the context of the artificial intelligence era, the application of artificial intelligence technology in modern brand design is increasingly widespread and is profoundly changing the design creation in this field. The purpose of this paper is to propose an intelligent image acquisition and automated brand design technology that utilizes AI technology to assist with brand design. The image acquisition and retrieval process of the online CBIR system is established, the average precision mean is used as the evaluation index of image retrieval, and the BoF model is constructed to realize RootSIFT feature extraction and image acquisition. Meanwhile, MultiStyleLogo GAN, a multi-style generative adversarial network, is designed to intelligently automate random output and generate brand design solutions through input sketches and style semantic descriptions to improve designers’ design efficiency. This paper utilizes technology to redesign the brand of A green plum wine in a province in China. Except for the pattern and font indicators, the average value of the newly designed brand image in each evaluation index of aesthetic design is greater than 4. The average values of the image aesthetics, cultural connotation, and emotional resonance indicators in the evaluation of brand narrative reach 4.25, 4.24, and 4.15, respectively, which achieve a high consumer satisfaction level.
Research on Cloud Computing-based Music Resource Sharing Platform Technology and Its Promotion of Employment and Entrepreneurship
Authors: Wei Wei , Du Yuelin , Li Wei , Wang Yan
Published: October 2024

Music resource-sharing platforms can increase students’ employment paths and enhance their employment ability. Load prediction and resource scheduling algorithms are designed in this paper to construct a music resource-sharing platform based on cloud computing technology. The mean predictor’s predictions are combined with the GRU-CNN model’s predictions, and the weighted average is calculated to enhance the accuracy and stability of the predictions. Then, the integrated migration scheduling method is designed to make the load of the cloud environment more balanced and the resource utilization more reasonable by the four processes of migration triggering, container selection, node selection, and container migration in a coarse-grained dynamic scheduling approach with nodes as objects. Following the completion of the construction, the algorithm that was designed is evaluated for load prediction and resource scheduling, and regression analysis is performed to examine the role of music resource-sharing platforms in promoting employment and entrepreneurship. It is found that after the resource scheduling by the algorithm in this paper, the node operation tension is greatly alleviated, and the CPU resource utilization and memory resource utilization of node Node1 are reduced from 80.96% and 62.69% to 58.03% and 43.36%, respectively. The resources of the low-load node Node4 are effectively utilized, the memory resource usage rate has increased from 6.86% to 49.52%, and the resource usage of each node in the cluster is more balanced and reasonable. At a statistical level of 1%, the impact of music resource-sharing platform development on employment quality is 0.194. In contrast, the industrial structure does not significantly contribute to the quality of employment, indicating that under the current economic situation, emerging economic forms such as music resource-sharing platforms are the main driving force to improve the quality of employment and the development of music resource sharing platforms generally improves the quality of labor force employment.
Research on the Informatization Strategy and Practical Effect of Chinese Traditional Culture Education
Authors: Wei Zhan'gang , Ma Xueying
Published: October 2024

The development of curriculum culture is a profound reflection on the evolution of school curriculum in the present era. The article proposes a Retina Student network to detect students’ classroom behaviors and then incorporates the implementation of a classroom behavior coding system using computer vision. Based on this, we established a student detection dataset for the classroom attention recognition task, utilizing the Retina Studen student detection algorithm to achieve optimal recognition accuracy of 0.92 and 0.93, and recall of 0.91 and 0.94 for both gaze and non-gaze states. Then, the visualization information of students’ learning behaviors was targeted, and the classroom status was discussed. The experimental results demonstrate that this paper’s algorithm outperforms other algorithms in identifying student learning behaviors. Finally, through the coding analysis of the teaching video of the cultural education smart classroom, we found that students’ behaviors in the calligraphy, painting, and opera smart classroom are rich, and the traditional way of “explaining-questioning-answering-feedback” is still the main behavior in the classroom.
The Construction of Digital Management Platform for Civic and Political Education for Future College Education and Its Intelligent Teaching Practice
Authors: Wu Juan , Ma Fei
Published: October 2024

Civic education in colleges and universities is facing the transformation of digital management mode, and this paper proposes to build a whole-process autonomous multi-dimensional fusion platform for the implementation and management of civic education in colleges and universities. The platform takes the big data analysis layer, object application layer and service management layer as the overall structure, builds the dynamic database of the Civic and Political Education program, and superimposes the tripartite comprehensive evaluation database. This paper improves the Apriori algorithm for association rules and applies the improved algorithm to the management platform for information mining. Intelligent teaching practices are designed based on the digital management platform, and their teaching effectiveness is analyzed. The performance of the Apriori algorithm before and after optimization is compared, and with the optimized algorithm, the execution efficiency is improved by about 10% to 15%. Students using the Civics education platform showed significant differences at the 1% level in all three dimensions of cognitive load, learning motivation, and mind-flow experience compared to students in the traditional teaching mode.