bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring Contemporary Calligraphic Creation and Aesthetic Characteristics Using Topological Data Analysis Methods
Authors: Shen Mingjie 
Published: February 2024

Abstract
In the process of digitization in today's society, the organic combination of technological means and traditional arts, such as calligraphy culture, is a topic that China is facing. The topological data analysis method is used in this paper to conduct an in-depth study on the creation and aesthetic characteristics of contemporary calligraphy, taking into account the situation above. In this paper, the topological data analysis method is first utilized to calculate the position of the critical points in the vector field and draw the topological structure of the vector field. The Jacobi matrix is computed, and the numerical solutions of the eigenvalues and eigenvectors in the matrix are used to pinpoint critical points. The TDA algorithm allows for the visualization and modeling of aesthetic features in contemporary calligraphy creation using the data required for the acquired bulk body model. The aesthetic features of calligraphy creation are analyzed through simulation experiments in the end. The results of simulation experiments show that the TDA algorithm completes the convergence before 500 iterations under a 4-fold filter, the nodes are mainly concentrated in the range of [500, 1000], and the convergence speed is the fastest among the five algorithms. Testing the topological data analysis algorithm for the recognition performance of aesthetic features of calligraphy creation, the recognition rate of TDA is as high as 98.30%, which has a good recognition effect.
Corpus Microtext Analysis and English Teaching Model Innovation in Cloud Computing Background
Authors: Huang Chunying 
Published: February 2024

Abstract
The rapid development of cloud computing technology makes the English teaching corpus an excellent choice for innovative English teaching mode. This paper constructs a corpus of English teaching resources and English O2O teaching mode based on MOOC education platform, combines the probabilistic semantic analysis (PLSA) model with the potential semantic indexing to carry out microtext analysis of the English teaching corpus, and solves the PLSA model by using the expectation (EM) algorithm. For the English teaching corpus and English O2O teaching model constructed in this paper, a validation analysis was conducted in three aspects: micro text analysis, text lexical ability and teaching satisfaction. The results show that the PLSA model is able to obtain complete sentence expressions in the microtexture of the corpus when the weight coefficient of the lexical items is set to 0.3. The text vocabulary ability of students in English O2O teaching mode shows a significant difference level at 1% level, and the correlation coefficient of in-class to pre-class reaches 0.889. The English teaching corpus relying on MOOC platform and O2O teaching mode can effectively enhance students’ deep understanding of English sentences, improve students’ satisfaction with English teaching, and enhance students’ interest in learning English.
The Practice and Application of Philosophical Thought of Music Education in the Information Age in the Education of College Music Curriculum
Authors: Feng Jinghua 
Published: February 2024

Abstract
Taking the philosophical view of music education as an entry point, this paper investigates the relevance of music education and philosophical thought from three aspects, focusing on the compatible philosophical view of music. Based on the random forest algorithm under machine learning, the music data samples are classified, and the algorithm is chosen to be optimized and improved when the dimension of music features is high. Using the extreme gradient boosting algorithm, the model is penalized to avoid the phenomenon of overfitting during the operation process. The RF-XGBoost hybrid music recommendation algorithm is proposed to help students learn personalized music by combining the two models mentioned above. Utilize ICT integration technology to combine music education and information technology in order to create the M-ICTPACK model. Create music simulation experiments to evaluate the impact of the music recommendation model proposed in this paper. Based on the idea of music education and philosophy, design music teaching content that meets the needs of students in colleges and universities and analyze its impact. The results show that in the music simulation recommendation effect, the smallest gap between the recommended musicians and the type of interest of the students is only 0.00001. The same student scores differently in music skills in different periods of music learning, and after 9 months of learning, except for the learning interest score of 79.365, the scores of all other aspects are more than 80. This paper proposes more effective philosophical ideas for music education in music curriculum education.
Research on Efficient English Teaching Model Combining Corpus Microtext Analysis
Authors: Tang Yong , Chen Hongping 
Published: February 2024

Abstract
Aiming at the goal of improving the quality of English teaching and combining the characteristics of English teaching, this paper constructs an efficient English discursive literacy teaching based on corpus micro-text analysis. Utilizing the unique advantages of online corpus to assist English teaching, it proposes the targeted teaching of English metaphorical vocabulary and combines the Word2Vec word embedding model and the cosine similarity algorithm to propose a model for analyzing the quality of English text coherence. Based on the characteristics of writing vocabulary in microtexts of the corpus, the analysis integrates the dimensional features of English writing vocabulary teaching. The effectiveness of the corpus-based efficient teaching model for English literacy teaching is verified through teaching practice, specifically utilizing the average values of pre- and post-tested vocabulary, sentences, and chapters of the two classes as comparison data. The results proved that the average value of the pre-test scores of all students in the experimental class is 7.78, and the average value of the post-test is 10.72, which is 2.94 higher than the pre-test. The English teaching model in colleges and universities based on corpus micro-text analysis can significantly improve the English writing level of students and achieve efficient English teaching.
A study of the multipoint boundary value problem for nonlinear differential equations of arbitrary fractional order based on the fixed point theorem for composite nonlinear operators
Authors: Luo Jiongxing 
Published: February 2024

Abstract
The existence and distinctiveness of solutions, as well as the iterative approximations of the distinctive answer to the initial boundary value issue of nonlinear differential equations, may be solved with the help of the theory of nonlinear operators, which offers a strong theoretical guarantee and a fundamental tool. In this work, we examine the fixed point theory for composites nonlinear operators, which may offer a fresh approach to solving linear differential equations having arbitrary order fractional multipoint boundary value problems. The existing result of the boundary value issue’s solution is confirmed by the fixed point theorem for composites nonlinear operators, and the four-point boundary value problem for fractional-order linear equations of the Riemann-Liouville type is examined. A group of fractional-order nonlinear differential equations with deviating quantities are examined to examine the presence of an unusual positive solution for this boundary value problem. The existence of this unique positive solution is determined by the use of both the mixed monotone operator and the combined nonlinear operator fixed point theorem. Ultimately, the nonlinear Bagley-Torvik equation with a fractional order variable coefficient four-point boundary value problem is converted into a Fredholm-Hammerstein integral the formula of the second type with weakly singular or continuous kernels, and the fixed point principle is used to demonstrate the uniqueness of the solution in the space of continuous functions. Approximate solutions are provided for the second class of nonlinear Fredholm-Hammerstein integral equations with weakly singular kernels. The outcomes demonstrate the applicability and validity of the fixed point theorem to composite nonlinear operators, offering a fresh approach to solving the multipoint boundary value issue for nonlinear differential equations of any fractional order.
Research on the Construction of Intelligent Robot Path Recognition System Supported by Deep Learning Network Algorithm
Authors: Ni Kan , Cao Yu , Jiang Xiongwen , Zhang Haolan , Seiji Hashimoto , Ni Qiyu 
Published: February 2024

Abstract
In this paper, a new intelligent robot path recognition system LADDPG, is constructed by extending the DDPG algorithm with the support of the deep learning network algorithm. The path recognition system is optimized by using the memory system and the decision module guided by the attention mechanism, which solves the problems of the existing DRL intelligent robot path recognition method that cannot store long-time memory and the training time is too long. The system in this paper is validated by conducting path recognition experiments under different road conditions and conducting dynamic obstacle avoidance test experiments. The system can maintain excellent noise immunity and a short path recognition time of 51 ms under the conditions of missing road conditions, circuitous road conditions and large curvature, and in the presence of multiple dynamic obstacles, the system can maintain a collision rate close to 0 while maintaining a very high success rate of 0.98, and the required path recognition time is much lower than that of other methods, with an average reward value of 0.4151. This paper’s system is highly accurate in recognizing intelligent robot paths and has high application value and capability.
Development path of college labor education based on big data platform in the context of health psychology
Authors: Li Congcong , Wang Xuehui 
Published: February 2024

Abstract
Labor education is an important content of quality education, and the promotion of higher education cannot be separated from the implementation and practice of labor education. The labor education platform and labor education resource base in colleges and universities are established using the big data platform, which combines Hadoop technology and the HBase database. In order to help students obtain labor education teaching resources more efficiently on the labor education platform, reinforcement learning is combined with a deep neural network to optimize the scheduling of teaching resources, and α -the dispersion recommendation algorithm is used to realize personalized recommendations of teaching resources. With regard to the effectiveness of the labor education platform, load testing and application effects were carried out, and the influencing factors of labor behavior and craftsmanship cultivation of college labor education students were analyzed in depth. The labor education platform’s transaction response time increases by 22.5 seconds when the number of users reaches 5000, according to the results. The personal motivation for craftsmanship in the process of labor education will be affected by the campus culture, and its correlation coefficient is 0.565, and the student’s satisfaction with the platform of labor education reaches 0.825. The innovation and development of labor education in colleges and universities need to fully rely on the big data platform to promote the optimization and sharing of labor education resources and to promote the development of labor education resources. The cultivation of student labor creation and craftsmanship can be ensured through the optimization and sharing of educational resources.
Portfolio Optimization Strategy Based on Risk Diffusion Model in Emerging Industry Development
Authors: Ni Shuangqin , Wang Shen 
Published: February 2024

Abstract
In this paper, we first sort out the formula of the premium principle and the algorithm of the diffusion model and then study the strategy problem about optimal investment consumption and insurance purchase when investors invest in new developing industries under the risk diffusion model. In real financial markets, there are two types of uncertainty regarding asset prices: normal fluctuations and abnormal shocks. The risk diffusion model is used to plan the optimal investment strategy based on this basis. In the end, three tests are executed, including two numerical simulations and one investment analysis that determines the investor’s age. The computational results show that the optimal strategy in the first set of simulations is the 56% increase in investment volume A(x) at the parameter σ = 0.1. The standard deviation of the investor’s objective in the second set of simulations is 9.287%, and the investor’s assets invested in risky securities should be 1.071. In the third set of tests, as the investor’s age increases, the value of the investor’s investment in risky assets continues to decline from 2.0 after 30 years, and by the time it reaches 40 years, it is already close to 0.25, and there is a continued decline, converging to 0. Investors can invest in providing effective reference data by investing in the portfolio optimization strategy in this paper, which predicts stock market volatility and vibration.
Data-Driven Unsteady Aerodynamic Modeling for Fluid–Structure Interaction
Authors: Fellows David W. , Bodony Daniel J. 
Published: February 2024

The piston theory class of simplified aerodynamic models that link body deformation to localized pressure fluctuation with respect to a mean steady state is attractive for modeling purposes as they constitute a computationally efficient model to calculate the unsteady pressure response on deforming bodies. However, as piston theories are valid for flow regimes where [Formula: see text], they are inaccurate for modeling the aerodynamic response associated with aeroelastic phenomena in subsonic or low-supersonic flow regimes. Unsteady computational fluid dynamics (CFD) simulations are used to learn the unsteady pressure response, and dynamic mode decomposition (DMD) is applied to the error between the CFD-computed pressure fluctuation and the piston-theory-predicted pressure fluctuation. This process is performed on two-dimensional and three-dimensional flow domains over various flow regimes. For both scenarios, the DMD analysis learns dominant spatial modes in the error that constitute low-order models, which may be used to improve the pressure response and are confirmed to be physically relevant. A method for computing aeroelastic stability with these leading modes is discussed and applied to fluid–structural beam and panel configurations. The results are compared against prior numerical and experimental investigations to quantify the improvement in prediction obtained by the DMD-augmented piston theory.
Effectiveness of IMPUTE ADT-1 mobile application in children with autism spectrum disorder: An interim analysis of an ongoing randomized controlled trial
Authors: Panda Prateek Kumar , Elwadhi Aman , Gupta Diksha , Palayullakandi Achanya , Tomar Apurva , Singh Mayank , Vyas Antara , Kumar Deepak , Sharawat Indar Kumar 
Published: February 2024

Objectives:
IMPUTE Inc., a software firm dedicated to healthcare technology, has developed a mobile medical application known as IMPUTE ADT-1 for children with autism spectrum disorder (ASD) based on the principle of applied behavior analysis.

Materials and Methods:
The primary objective of this trial was to compare the efficacy of add-on treatment with IMPUTE ADT-1 in children with ASD aged two to six years as compared to standard care alone for 12 weeks (in terms of change in Autism Diagnostic Observation Schedule [ADOS-2] scores). The secondary objective of the study was to assess the compliance with IMPUTE ADT-1 among participants and also to evaluate the feedback of parents regarding IMPUTE ADT-1 at the end of 12 weeks. The application provides personalized programs tailored to each user’s needs, and the program evolves based on the user’s progress. It also utilizes face tracking, eye tracking, and body tracking to gather behavior-related information for each child and apply it in reinforcement learning employing artificial intelligence-based algorithms.

Results:
Till the time of interim analysis, 37 and 33 children had completed 12-week follow-up in IMPUTE ADT-1 and control arm. At 12 weeks, as compared to baseline, change in social affect domain, repetitive ritualistic behavior domain, total ADOS-2 score, and ADOS-2 comparison score was better in the intervention group as compared to the control group (P < 0.001 for all). A total of 30 (81%), 28 (75%), and 29 (78%) caregivers in the IMPUTE ADT-1 group believed that the ADT-1 app improved their child’s verbal skills, social skills, and reduced repetitive behavior, respectively.

Conclusion:
IMPUTE ADT-1 mobile application has the efficacy to improve the severity of autism symptoms in children. Parents of these children also feel that the application is beneficial for improving the socialization and verbal communication of their children.
Dindarlık düzeyinin partiye yönelik tutum üzerindeki etkisinde lider imajının aracılık rolü
Authors: SESLİ Mutlu , KÖROĞLU Ali 
Published: February 2024

İnsan, toplumla iletişim kuran, sosyal ilişkilere giren ve o toplumun kurumları ile var olan siyasal bir varlıktır. Bu anlamda toplumda yaşayan herkes, insanların ortak yaşam alanını ve geleceğini etkileyen siyasetten bir şekilde etkilenmektedir. Fakat toplumdaki her bireyin siyaset hakkında bilgi düzeyi ve siyasetle ilgi düzeyi birbirinden farklıdır. Bireyleri siyasi davranışta bulunmaya iten pek çok nedenin yanında onların siyasi tercihlerini etkileyen pek çok faktör bulunmaktadır. Bu faktörler seçmenin yaşadığı bölgeye, yaşına, cinsiyetine, arkadaş grubuna, eğitim ve gelir düzeyine göre farklılaşabildiği gibi, seçmenin dindarlık düzeyi, laiklik tutumu ve seçime giren partinin liderinin kişisel özelliklerine göre de farklılaşabilmektedir. Bunun yanında ülkenin içinde bulunduğu ekonomik durum, uluslararası politika vs. gibi pek çok etken bireylerin siyasi tercihlerini etkilemektedir.
Çalışmanın amacı Tokat ilinde yaşayan katılımcıların dindarlık düzeylerinin partilere yönelik tutumu üzerindeki etkisinde lider imajının aracılık rolünün incelenmesidir. Çalışmada anket aracılığıyla toplanan verilerin analizi yapılmıştır. Çalışmada katılımcıların (N= 420) dindarlık düzeylerinin çalışma kapsamındaki partilere yönelik tutumları üzerindeki etkisinde parti liderlerinin imajının aracılık rolü bulunduğu sonucuna ulaşılmıştır. Ayrıca dindarlığın partiye yönelik tutum üzerindeki etkisi partilere göre de farklılık göstermektedir. Çalışma değişkenler arası ilişkileri araştırmasından dolayı literatüre katkı sunacağı değerlendirilmektedir.
Psychological Well Being and Family Supportive Supervision Behaviors with Work Life Balance in Working Women
Authors: Sari Rini Eka , Nugroho Andhi Dwi 
Published: February 2024

Abstract
Background: Women working is no longer a rare thing because of the era progresses. For a woman, it is very important to balance her life at work and at home because a balanced work life allows working women to maximize their potential, considering the importance of work life balance for working women. Objective: This research aims to determine work life balance in working women in terms of psychological well-being and family supportive supervision behavior. Method: The data collection method in this research uses three scales, namely the Work life balance scake, Psychological well being scale, and Family support supervision behaviors scale. Data analysis this research uses regression analysis. Results: The results show that psychological well being and family supportive supervision behaviors influence work life balance in women who work either together or separately for the two psychological well being and family supportive variables. Conclusion: The work life balance felt by working women occurs when working women feel psychological well being and family supportive supervision behaviors in the work and family environment.

Abstrak
Latar Belakang: Perempuan bekerja bukan lagi hal yang langka seiring dengan kemajuan jaman. Bagi seorang perempuan, sangat penting untuk menyeimbangkan kehidupannya di tempat kerja dan di rumah karena kehidupan kerja yang seimbang memungkinkan perempuan bekerja untuk memaksimalkan potensi yang dimilikinya, mengingat pentingnya keseimbangan kehidupan kerja bagi perempuan bekerja. Tujuan: Penelitian ini bertujuan untuk mengetahui keseimbangan kehidupan kerja pada wanita bekerja ditinjau dari kesejahteraan psikologis dan perilaku supervisi suportif keluarga. Metode: Metode pengumpulan data dalam penelitian ini menggunakan tiga skala, yaitu skala Work life balance, skala Psychological wellbeing, dan skala Family support supervision behaviors. Analisis data penelitian ini menggunakan analisis regresi. Hasil: Hasil penelitian menunjukkan bahwa perilaku kesejahteraan psikologis dan pengawasan suportif keluarga berpengaruh terhadap keseimbangan kehidupan kerja pada wanita yang bekerja baik secara bersama-sama maupun terpisah untuk kedua variabel kesejahteraan psikologis dan dukungan keluarga. Simpulan: Keseimbangan kehidupan kerja yang dirasakan wanita bekerja terjadi ketika wanita bekerja merasakan kesejahteraan psikologis dan perilaku pengawasan yang suportif dari keluarga di lingkungan kerja dan keluarga.
Prevalence of Metabolic Disease among Adults in Indonesia: A Cross-Sectional Population-Based Survey
Authors: Fatimah Meliya Husnatul , Ismail Aem 
Published: February 2024

Introduction: Metabolic diseases were the leading cause of morbidity and mortality in the world. the World Health Organization, the effective delivery of public health messages has become increasingly complicated due to CKD as a complication of cardiovascular disease and diabetes. Studies have prevalence of metabolic disease among adults in Indonesia. These study aims were to determine the prevalence of kidney, cardiovascular, diabetes.
Method: This study uses a cross-sectional study design used from Indonesia Family Life Survey Wave 5 (IFLS-5) organized by Rand Corporation conducted in 2014-2015. A statistical analysis is a descriptive observational study. The total number of respondents un this study was 27,718.
Result: Respondents with adult criteria in Indonesia were 52.67% women aged 38.20(±13.64), 78.48% married, 32.94%elementary, and 59.89% urban residents. The prevalence of chronic kidney disease among adults in Indonesia was 1.43% (95% CI: 00.01 – 0.02). The prevalence of cardiovascular disease among adults in Indonesia was 1.64% (95% CI: 00.01 – 0.02). The prevalence of diabetes among adults in Indonesia was 2.33% (95% CI: 00.02 – 0.03).
Conclusion: The prevalence of chronic kidney disease, cardiovascular disease, and diabetes in Indonesia is strongly by age and show a relationship between sufferers of these three diseases.