bluuebunny/crossref_metadata_2025 huggingface dataset:
PENGARUH TIPOLOGI KELUARGA DAN LINGKUNGAN RAMAH KELUARGA TERHADAP RESILIENSI DEWASA AWAL PADA MASA PANDEMI COVID-19
Authors: Salamah Ammi , Sunarti Euis , Eva Riany Yulina
Published: January 2024

Keluarga dan lingkungan keluarga yang mendukung dalam menghadapi berbagai kesulitan dan krisis dibutuhkan dewasa awal agar memiliki resiliensi yang tinggi. Penelitian ini bertujuan untuk menganalisis pengaruh tipologi keluarga regeneratif, tipologi keluarga ritmik, dan lingkungan ramah keluarga terhadap resiliensi dewasa awal. Sebanyak 520 dewasa awal dilibatkan dalam penelitian melalui teknik simple random sampling yang terdiri dari 200 laki-laki (38,5%) dan 320 perempuan (61,5%). Hasil analisis Structural Equation Modelling menunjukkan bahwa semakin tinggi tipologi keluarga regeneratif, tipologi keluarga ritmik, dan lingkungan ramah keluarga maka secara signifikan akan meningkatkan resiliensi dewasa awal. Berdasarkan hasil penelitian, diperoleh indikator-indikator yang menunjukkan aktivitas yang paling berkontribusi dalam meningkatkan tipologi keluarga, lingkungan ramah keluarga, dan resiliensi. Aktivitas yang meningkatkan keimanan, rasa hormat, kepedulian, interaksi, dan toleransi merupakan prediktor utama yang mampu meningkatkan tipologi keluarga, lingkungan ramah keluarga, dan resiliensi. Hasil ini dapat menjadi referensi bagi individu khususnya dewasa awal, keluarga, serta pemerintah dan lembaga yang bergerak dalam program ketahanan, kesejahteraan, dan kualitas keluarga. Referensi ini berguna untuk meningkatkan kemampuan keluarga dalam mengantisipasi kesulitan dan krisis keluarga di masa mendatang.
PERAN KELUARGA DAN TOLERANSI AMBIGUITAS PADA EFIKASI DIRI PENGAMBILAN KEPUTUSAN KARIER MAHASISWA
Authors: Djudiyah Djudiyah , Uningowati Dwi Wahyuni , Syakarofath Nandy Agustin
Published: January 2024

Pengaruh keluarga serta toleransi ambiguitas berperan dalam membentuk keyakinan diri mahasiswa dalam pengambilan keputusan karier. Penelitian ini bertujuan mengetahui peran keluarga dan toleransi ambiguitas pada keyakinan diri mahasiswa dalam memutuskan karier. Penelitian ini merupakan penelitian cross sectional. Subjek penelitian berjumlah 157 mahasiswa Fakultas Psikologi Universitas Muhammadiyah Malang yang diambil dengan teknik sampling accidental. Pengambilan data dilakukan menggunakan kuesioner. Analisis data dilakukan dengan uji regresi. Hasil analisis menemukan bahwa peran keluarga dan toleransi ambiguitas berpengaruh terhadap keyakinan diri penentuan pilihan karier mahasiswa. Toleransi ambiguitas berpengaruh lebih besar terhadap keyakinan diri dalam memutuskan karier mahasiswa dibanding peran keluarga. Implikasi penelitian ini yaitu mahasiswa dapat berpikir positif dalam menilai perubahan dunia kerja saat ini, menerima perubahan, mencari kejelasan hal-hal yang ambigu, memantau permintaan pasar tenaga kerja, dan mengembangkan kompetensi diri sesuai dengan demand pasar. Orang tua dapat membantu mahasiswa dengan cara berbagi informasi tentang perkerjaan dan memberikan dukungan emosional dan finansial dalam pengembangan diri mahasiswa.
ANALISIS RIWAYAT PENGASUHAN PADA TINGKAT POSTTRAUMATIC GROWTH BERBEDA PADA DEWASA MUDA SETELAH TERINFEKSI COVID-19
Authors: Mustamin Syarifa Nadhrah , Dwi Hastuti  , Yulina Eva Riany
Published: January 2024

Pandemi Covid-19 memberikan ancaman serius bagi kondisi kesehatan mental pada kelompok dewasa muda, dalam hal ini riwayat pengasuhan diyakini mampu menjelaskan apakah seseorang jadi terpuruk atau justru bertumbuh menjadi pribadi lebih baik, setelah menghadapi situasi krisis. Penelitian ini bertujuan untuk menganalisis riwayat pengasuhan ditinjau dari tingkat posttraumatic growth (PTG) pada dewasa muda setelah terinfeksi Covid-19. Desain mixed method digunakan dengan melakukan pengisian kuisioner Posttraumatic Growth Inventory (PTGI) α=0,971 dan wawancara semi terstruktur terkait riwayat pengasuhan. Diperoleh 204 responden yang berpartisipasi mengisi kuisioner, untuk selanjutnya dipilih masing-masing 4 responden dengan skor PTG relatif tinggi dan rendah untuk diwawancarai lebih lanjut. Hasil analisis deskriptif menemukan bahwa responden rata-rata memiliki skor total PTG yang tinggi (M = 77,02; SD = 15,87). Dari lima dimensi PTG, apresiasi hidup menunjukkan skor paling tinggi (M = 81,09; SD = 17,05) dialami oleh para responden setelah terinfeksi Covid-19 dibandingkan dimensi lainnya. Hasil analisis data kualitatif menggunakan Nvivo-12 mengindikasikan bahwa terdapat pola riwayat pengasuhan yang cenderung berbeda dihayati oleh kelompok responden dengan PTG tinggi dan rendah. Temuan ini dapat menjadi rujukan dalam praktek pengasuhan anak untuk menciptakan individu yang lebih tangguh di masa dewasa.
ANALISIS RISIKO BAHAYA PADA STASIUN LOADING RAMP DAN PEREBUSAN PADA INDUSTRI PENGOLAHAN KELAPA SAWIT DENGAN METODE JOB SAFETY ANALYSIS (JSA)
Authors: Sudarma Ahmad , Suastiyanti Dwita
Published: January 2024

The oil palm plantation industry in Southeast Asia, including PT. Kelapa Sawit plays an important economic role by creating jobs for thousands of people. This research employs the Job Safety Analysis (JSA) approach to recognize potential incidents and suggest the use of suitable personal protective gear (PPE/APD). Accidents on the production floor, such as falls, pinches, or contact with hazardous materials, pose a serious threat to employee safety. In order to achieve this goal, oil palm plantation companies need to continuously improve awareness of K3, identify existing risks, involve workers in safety improvements, and provide the necessary training and support
The effect of the pseudostem extract of ambon banana on the number of lymphocytes and fibroblasts in gingivitis : an experimental study
Authors: Andriani Ika , Medawati Ana , Lestra Citra , Salsabila Millati , Khairunnisa Putri Nabilla
Published: January 2024

ABSTRACTIntroduction: Gingivitis is an inflammation of the soft tissue that supports the teeth. Chemical treatment in the form of mouthwash, such as chlorhexidine, is often recommended. However, long-term use of chlorhexidine mouthwash will cause side effects, such as allergies, irritation of the oral cavity, and discoloration of the oral mucosa and teeth. Therefore, natural alternative materials containing flavonoids, saponins, and tannins that can cure gingivitis are needed. These ingredients are found in the pseudo stem of the Ambon banana. This research aims to analyze the effect of applying the pseudostem extract of Ambon banana on the number of lymphocytes and fibroblasts in treating gingivitis. Methods: This study was an in vivo laboratory experimental study with a post-test control group. The study used 45 Sprague Dawley rats which were divided into 3 groups, namely the positive control group (chlorhexidine gel), negative control (gel base), and treatment (Ambon Banana pseudostem extract gel). The gingiva on the mandibular incisor of the rat was ligated, then the gel was applied to the gingiva. Decapitation of rats was carried out on days 1, 3, 5, 7, and 9, and then made histological preparations with HE. Staining and observations were later made. Data analyzed using Kruskal-Wallis test. Results: The results showed that Ambon banana false stem extract gel reduced the number of lymphocyte cells with a significant difference of p=0.016 (p<0.05) and increased fibroblasts at p=0.85 (p>0.05). Conclusion: The pseudostem extract gel of Ambon banana reduced the number of lymphocyte cells and increased fibroblasts in gingivitis treatment.Keywords: fibroblasts, gingivitis, lymphocytes, pseudostem of ambon banana
Comparison of distribution and frequency of impacted teeth before and during COVID-19 pandemic in dental hospital: a descriptive study
Authors: Syafin Haura , Reksoprodjo Muhammad Ramaditto , Julia Vera , Heriasti Maudina Dwi , Ariawan Dwi , Sulistyani Lilies Dwi , Utomo Yudy Ardilla , Ratman Muhammad Farid
Published: January 2024

ABSTRACTIntroduction: The occurrence of the COVID-19 pandemic may affect the prevalence of patients with complaints of impacted teeth in dental hospital Faculty of Dentistry University of Indonesia (FKG UI), and there is no recent research on the distribution and frequency of impacted teeth based on age, gender, and teeth type in this hospital during the COVID-19 pandemic. This study aims to determine the distribution and frequency of impacted teeth during the COVID-19 pandemic in dental hospitals. Methods: A descriptive study uses the secondary data on impacted teeth patient's medical records. Utilizing purposive sampling, we selected participants for the research by carefully examining medical records to identify individuals that had undergone impacted tooth removal. The study used secondary data from the medical records of oral surgery patients at dental hospital FKG UI from June 2019 to June 2021, including complete patient identity, clinical diagnosis, and panoramic radiograph of the impacted teeth in June 2019 to June 2021. Diagnosis was determined through screening of medical records and panoramic radiographs. Data were analyzed using the statistical analysis software (SPSS version 21, IBM Corp.) Results: From 3,225 medical records of oral surgery patients at dental hospital FKG UI before and during COVID-19 pandemic, A total of 1292 patients were included in the study and 1496 impacted teeth cases were found. The frequency of impacted teeth cases before the pandemic was 825 (55.1%) cases; there were 671 (44.9%) cases during the pandemic. Conclusion: COVID-19 has caused a decrease in the distribution and frequency of impacted teeth cases, mostly in the middle aged patients, while more female as compared to male. The most common occurrence was in the third molars and the lowest was in the second molar tooth. Keyword : tooth, impacted, COVID-19, retrospective studies, wisdom tooth
Presença da Mãe D´Água
Authors: Paz Daniel Juracy Mellado
Published: January 2024

O presente trabalho aborda a localização das antigas hierofanias das divindades das águas os cultos de matriz africana, em especial aquelas relacionadas sob o nome Mãe d´Água, em Salvador (Bahia). O registro desses locais, para além do interesse nos aspectos da cultura afro-‑brasileira, pode iluminar a história urbana da cidade e essa relação mais própria da heortologiaurbana, do estudo das festas e eventos, em uma escala mais ampla. A vida na cidade – osvalores e crenças de seus habitantes, as movimentações em procissões, a consagração de lugares naturais ou edifícios, o seu calendário com o cotidiano e os momentos de efusão festiva – auxiliam na compreensão da cidade em sua fisicidade e esta, assim como suas transformações, ajuda a situar e compreender essa dinâmica da vida urbana.
Mycobacterium Abscessus – Diagnostic and Therapeutic Frontiers in Infection Management
Authors: Masiarova Simona , Dohal Matus , Porvaznik Igor , Solovic Ivan , Mokry Juraj
Published: January 2024

Mycobacterium (M.) abscessus, a highly pathogenic non-tuberculous mycobacterium, is responsible for several clinical manifestations. A very frequent occurrence is proven in patient with various lung diseases. Furthermore, it can result in complications such as skin and soft tissue diseases, central nervous system infections, bacteremia, eye infections, and others. M. abscessus is a clinical contraindication in cystic fibrosis patients awaiting a lung transplant, as it can exacerbate disease progression. Its pathogenicity and the emergence of resistance are influenced by factors including the composition of the cell envelope, rough and smooth M. abscessus morphotypes, efflux pumps, antibiotic-modifying/inactivating enzymes, and genetic polymorphisms in target genes. Management of the infection requires multicomponent therapy due to the high level of resistance. The following antibiotics are recommended according to the guidelines from the year 2017: amikacin, tigecycline, and imipenem with a macrolide. In order to properly manage patients with M. abscessus infection, correct identification of the subspecies as well as determination of resistance is essential. To achieve this goal, molecular-genetic techniques, such as whole-genome sequencing, are becoming increasingly favored in modern clinical practice. In this review, we provide up-to-date information on the issue of infections caused by non-tuberculous M. abscessus. We focus on its characteristics, possible infectious diseases, cystic fibrosis, and resistance, as well as the benefits of whole-genome sequencing.
Iron Citrate (Synthesit) Supplementation During Pancreas Cancer Showed Surprising Results – Case Study
Authors: Kusnir Patrik
Published: January 2024

Iron is a crucial mineral for our organism and its deficiency can cause serious health problems such as anaemia, fatigue, and impaired physical fitness. It has been shown that anaemia or iron deficiency is very common in patients with cancer. These patients benefit from iron supplementation either in intravenous or oral form. Our patient is a 67-year-old Russian woman with pancreatic cancer diagnosed in 2019. She fought off lymphocytic leukaemia in 2015. She refused treatment for her pancreatic cancer. The specific type of pancreatic cancer was not specified as the patient chose not to undergo targeted testing. Between March 2020 and February 2023, she took the dietary supplement Synthesit for three cycles (1 cycle lasted about a month).

After taking the dietary supplement, a total percentage of neutrophils became in the reference range. Subjectively, the patient started to feel better after taking Synthesit and her quality of life and well-being has improved as well. It might be supposed that the dietary supplement could have some effect on her well-being and various blood parameters such as white cells count.

Even though the dietary supplement is not supposed to be used for treatment of diseases, it can change some blood parameters and improve the immune system.

This short case study presents the patient with pancreatic cancer who started to take the dietary supplement Synthesit which contains iron in the form of citrate salt in a dosage of 800 μg per capsule, 1 capsule per day. The dietary supplement was administered over three treatment cycles (1 cycle took about a month) from March 2020 to February 2023. It describes a difference in blood test results before taking Synthesit and after the administration of Synthesit.
Multiple Chord Coding in China’s Minority Dance Music
Authors: Wu Xiaowen , Shang Ke
Published: January 2024

In this paper, we first use CNNS to collect rich samples of folk dance music, establish a model framework and a functional system framework, and conduct a comprehensive process analysis of the music. Then, the instrumental features, frequency features, and timbre features are extracted to obtain the spectral information. In the stage of chord analysis and encoding, a multivariate chord encoding model is established based on the acquired spectral information, including two parts: chord representation preprocessing and chord encoding. By utilizing this model, the chord structure of music was successfully and accurately encoded, allowing for analysis with up to 98% accuracy. Furthermore, significant recall results were achieved, reaching over 0.9, which suggests that the extracted chord features are highly reliable and accurate in recognizing musical chord information.
Exploration of Labor Education into Ideological and Political Education Based on the VAR Model
Authors: Cheng Chun
Published: January 2024

This paper is based on the VAR model, a regression analysis of the correlation between labor education and ideological and political education. Firstly, the LDA algorithm is used to speculate about the document to obtain the probability distribution of the subject, and this is used as the current subject feature. Then use the gray correlation algorithm to measure the distribution characteristics of each different indicator from the object dimension, and measure the correlation size and positive and negative by extracting the relative difference between indicators. Finally, the TF-IDF algorithm is used to determine the word weights, and text clustering is invoked to merge texts with the same theme. After the teaching of the VAR model, the significance of the learning motivation of the students in the experimental group is 0.009, the passing rate of the final grades is around 76%, and the significance of the dimensions of the learning effect is less than 0.05. It shows that the integration of labor education with ideological and political education can lead students to strengthen their concepts of labor so as to realize students’ comprehensive development.
Virtual Speech System Based on Sensing Technology and Teaching Management in Universities
Authors: Niu Yan
Published: January 2024

In this paper, digital speech is compressed using discrete Fourier transform, discrete cosine transform, and improved discrete cosine transform, and compressed sensing technology is proposed. Based on the compressed sensing technology, the frequency domain parameter compression algorithm and the speech coding and decoding algorithm are designed, and the interactive 3D virtual speech system design is completed through the pre-processing of the speech system, the extraction of speech features and the design of speech control commands. The virtual voice system designed in this paper is introduced in the teaching management mode of colleges and universities, and the main functions of the system include four major sections: notification management, online Q&A, virtual voice system interaction, and teaching resource management. The virtual voice system built using sensing technology is simulated and tested, and the practical application effect of the system is studied through empirical analysis. The experimental results show that the amplitude of the sound recorded by the compression sensor in the voice sensing experiment is more concentrated, the range is concentrated between [-0.025,0.025], and the detected voice is smaller and more effective than the amplitude recorded by the cell phone. Students were mainly satisfied and very satisfied with the four system functions designed in this paper, and in terms of the online Q&A function, only one student expressed great dissatisfaction and the total number of satisfied people was 119, and the students were highly satisfied with the teaching management of the system designed in this study.
Optimization of Innovative Talent Cultivation Mode of Tourism Management Major Combined with Multiple Intelligences Theory
Authors: Tong Guanglu
Published: January 2024

This paper first proposes the talent cultivation model of industry-academia integration on the basis of multiple intelligence theory and constructs the mathematical model of knowledge base expansion based on the three dimensions of coupling compatibility, interaction intensity and interaction time. Secondly, based on the knowledge transformation theory, it constructs the information and knowledge transformation model of industry-academia organizations and conducts the existence test of the Matthew effect. Finally, the tourism management major of University J as a research object is selected to analyze the operational development trend of the industry-academia integration talent cultivation model combined with multiple intelligences by analyzing the role relationship between system variables derived from the data. The results show that in 100 simulations, the coupling compatibility of the industry-academia fusion system of tourism management majors rises by 1.286 gradients for every 1.286 gradients, and the Matthew effect of the incremental knowledge of colleges and universities rises by one grade, indicating that the model, which has a more significant effect on the success rate of innovative talent cultivation in tourism management majors, has a more significant effect on the enhancement of the success rate of innovative talent cultivation.
Research on Distributed Virtual Reality Technology Based on VIRTOOLS in the Context of Big Data
Authors: Shi Minli
Published: January 2024

In this paper, virtual reality development software Virtools is used as the main tool for scene rendering in distributed virtual reality systems. The nearest distance-based control strategy is designed to achieve synchronous interaction between nodes by utilizing consistency control and prediction algorithms for nodes in the same cluster. Optimize the virtual scene by using texture mapping, detail level, and dynamic loading techniques. Propose a distributed parallel drawing method based on image plane segmentation to accelerate image drawing. The analysis and testing of the multiuser virtual reality roaming system in this paper is completed from four aspects: offline training model evaluation amount roaming test, lock performance test, and operation sequence error correction test. Among the analyzed data, the average lock time overhead is 123us, which has no obvious connection with the number of nodes, the number of locking times, and the execution of operations. According to each lock overhead of 123us, the number of concurrencies allowed per second is 8563, which fully meets the requirements of the system at this stage.
Research on the Synergistic Development and Operation Mechanism of Vocational Education and Innovative Development Concepts in the Context of Deep Learning
Authors: Xiao Qingshan
Published: January 2024

This paper proposes that the synergistic mechanism promotes the vocational education innovation system to transition from the primitive low-level, ordered and relatively balanced stage to the high-level, ordered and fully synergistic stage. By analyzing the dynamic evolution process of the order parameter, a complex system with self-evolution capability is built, and the vocational education collaborative innovation model is constructed at three levels: macro, meso and micro. Finally, in carrying out the benefit distribution and arithmetic example analysis, the spillover effect of the synergistic subject is explored, and the optimal value is taken using the optimization model of synergistic development of higher vocational colleges and universities. The results show that when the quadratic term coefficient of innovation output is 0.086, the stabilization strategy is (0,1) or (1,0), and the multi-body innovation resources realize interaction stabilization without spillover or feedback effects. This study proposes the optimal path of innovation integration mechanism from the aspects of mechanism, mode and content, which can provide new ideas for the collaborative development of vocational education and enterprises.
Research on the synergistic nurturing mechanism of ideological work and student management in colleges and universities under the binary structure
Authors: Du Zhenhua
Published: January 2024

This paper takes the synergy between ideological work and student management in colleges and universities as an entry point, analyzes the intrinsic mechanism between the two, and gives the synergistic effect of parenting after the integration of the two. The synergistic mechanism between student management and ideological work is explored by mining students’ daily behavioral data, and after analyzing students’ daily behavioral data based on density-optimized clustering algorithm, risk warning detection of students’ academic situation is carried out by combining the improved LSTM model. The GCN network model is utilized to detect students’ psychological disorders. In order to verify the effectiveness of the method given in this paper for exploring the synergistic cultivation of ideological work and student management, quantitative analysis was carried out through the data of college students’ one-card. The results show that the movement data of college students are divided into 4 classes, of which the largest proportion of students is class cluster 4 is 44.59%, the risk prediction accuracy of the improved LSTM academic warning model is 0.731, and the GCN network model has a model loss value of about 0.25% after about 50 iterations when the threshold value is 0. Colleges and universities under the binary structure can narrow the value differences between students through data mining technology, and can help students remove psychological barriers, prompting the generation of a collaborative parenting mechanism between ideological work and student management in colleges and universities.
A Study on the Construction of Cultivating High-Quality Farmers in Higher Vocational Colleges and Universities under the OBE-PDCA Approach
Authors: Han Jing , Zhou Jianshan
Published: January 2024

Rural revitalization, talent first, from the high-quality farmer’s cultivation policy as well as vocational education characteristics research, to achieve high-quality farmers’ talent cultivation. This paper analyzes the status quo of the cultivation of high-quality farmers, constructs the cultivation model of high-quality farmers through the OBE-PDCA method, and constructs the cultivation effect evaluation model of high-quality farmers based on the BP-PCA method by combining BP neural network and principal component analysis. On this basis, the cultivation path of management-type high-quality farmers is taken as an example to explore the effect of OBE-PDCA in constructing the cultivation model of high-quality farmers as well as the cultivation effect of high-quality farmers. The results show that the averages of the cultivation of provincial higher vocational colleges and universities in the four dimensions of PDCA are 16.07, 10.51, 13.48, and 22.58, and the F-values of the overall test are 2.4, 7.8, 4.5, and 4.1, with the correlation coefficients of 0.46, 0.45, and 0.59, respectively. The resulting difference in the weight scores of Δ ≥ 10 is 1 item, 5 ≤ Δ ＜ 10 is 6 items, 0≤ Δ ＜ 5 is 1 item, with good cultivation effects. Item, there is a good cultivation effect. The method constructed in this paper can effectively enhance the cultivation effect of high-quality farmers and promote rural revitalization.
Research on English Translation of Intangible Cultural Heritage in the Age of AIGC
Authors: Sun Wulin
Published: January 2024

Cultural dissemination and display methods with the progress of science and technology requirements continue to improve, especially in the AIGC era. The traditional cultural dissemination methods are no longer applicable, and “non-legacy digitization” needs to become more and more urgent. This paper analyzes the neural machine translation method and constructs a back-translation model by synthesizing a corpus and generating parameters. BLEU and other evaluation indexes are used to optimize the factors that affect the computation of synthetic data. An enhanced synthetic corpus is created using the kNN algorithm to construct a monolingual translation memory. Using the semantic information-sharing strategy, generate the parameters of the embedding layer of the non-legacy translation model while introducing the encoding layer to complete the overall construction of the non-legacy translation model. Comparative experiments and empirical analyses are set up to study the heterogeneity of the quality and dissemination effect of English translation of NRLs, and the experiments show that in the first set of translation tasks, the BLEU scores of the model proposed in this paper are 1 and 1.4 higher than those of the wait-k model when the value of k is 5 and 7, and the translation quality of the model proposed in this paper is better. The values of primary and secondary term coefficients of the English translation of non-legacy are 14.974 and -3.071, respectively, in the case of not establishing samples, showing an inverted U-shaped linear relationship.
Application of Big Data-based Information Technology in Business English Courses in Colleges and Universities
Authors: Kang Chunjie , Kang Bo
Published: January 2024

In this paper, after using Cool Edit Pro2.1 software to complete the speech signal acquisition work, the DTW method is used to pre-emphasize the speech signal. Due to the small continuous correlation between adjacent frames, the use of windowing and frame-splitting operation makes the amplitude change of the speech signal smooth and obtains the spectral envelope of the speech signal. The negative impact of MFCC feature parameter extraction is optimized by parameterizing the volume intensity and fundamental trajectory, and the application of the English scoring mechanism in business English education is explored. According to the current situation of business English teaching in colleges and universities, research problems and sampling objects are identified, and statistical analysis is applied to analyze the teaching effect of business English informatization by example. The results show that the speech evaluation system of spoken business English based on DTW does not differ much from the similar results of the scoring of the master’s degree of English majors in our university, and its difference value always stays between 1 and 10. In terms of the simple correlation coefficient and significance level (0.01), the simple correlation coefficient between teaching effectiveness and the use of technological media is 0.385 (P=0.00), which means that there is a significant correlation between both teaching effectiveness and the use of technological media. This study improves the standardization of English pronunciation among students, which is important for the development of business English in colleges and universities.
Research on Economic Trade and Cultural Value of the China-Russia Ten Thousand Mile Tea Route by Integrating Probabilistic Assessment Models
Authors: Ma Lankun
Published: January 2024

According to the relationship between the economy and trade of the tea ceremony in foreign markets, this paper establishes the economic output model of tea in the tea ceremony in China and Russia, and at the same time, considering the spring tea frost disaster, combined with the probability model, the economic loss rate of tea frost is quantitatively evaluated. Through the analysis of social network and semantic network diagram, the semantic related high-frequency words were classified into the concept of tea culture, and the correlation between high-frequency words about tea culture was obtained. According to the comprehensive influence of domestic factors and foreign factors, the index system of influencing factors of tea export value was determined, and the prediction model of China’s tea export value based on CNN-BSO-LSTM algorithm was constructed by using big data technology, and the tea economy and culture from the perspective of Sino-Russian tea ceremony were studied and analyzed. The results showed that the three indexes of CNNBSO-LSTM were 0.9431, 8850212 and 4.112, respectively, which performed better than other models. The CNN-BSOLSTM model predicts that China’s tea exports will reach around RMB 3.5 billion in 2025, up significantly from RMB 2.3 billion in 2022. This study promotes the economic and cultural exchanges between China and Russia, and is of great significance for promoting the rise and development of urban belts along the Belt and Road.
Sustainable Management of Decorative Patterns of Shanghai Shikumen Architectural Houses Based on ROI Optimization
Authors: Sun Zhongping
Published: January 2024

The decorative patterns of Shikumen architectural dwellings in Shanghai are of great investment value, and their cultural benefits can be fully utilized through sustainable operation and management. In this paper, after analyzing the traditional pattern generation method, we combine the semantic generation method with the design of the loss function and network structure of the generative adversarial network and construct the generation algorithm of architectural residential decoration pattern based on semantic perception. The constructed pattern generation algorithm is used to manage the sustainability of architectural residential decoration patterns and optimize the rate of return on the investment of sustainability management through fuzzy theory. The results show that the color similarity, pattern similarity, and organization form similarity are (0.62, 0.91), (0.58,0.89), and (0.59,0.88), respectively, and the return efficiency of the investment in the architectural residential decoration of Shanghai Shikumen architecture before and after the optimization fluctuates between (-0.26, 0.30) and (-0.18, 0.26). The ROI of sustainable business management of decorative patterns in Shanghai Shikumen architectural dwellings in this study can develop stably.
Internet Data-based Media Resource Mining Method for Artistic Talent Cultivation
Authors: Wang Lina
Published: January 2024

The cultivation of innovative artistic talents is the top priority of art education, making full use of Internet media resources to provide talents with high artistic literacy for art development. This paper begins with the integration of media resources in Internet data and builds a framework for the dimensions and processes of media resource knowledge integration. The BERT model combined with the multi-head self-attention mechanism is used for feature extraction of media text resources in Internet data, the signal decomposition of audio media resources is realized through the matching tracking algorithm, and the recommendation of video resources for art talent development is carried out based on the temporal hierarchical attention model. To verify the effectiveness of the algorithms given in this paper, a verification analysis of each algorithm is performed. The results show that when the IR value of audio signal decomposition increases from 1.49 to 10.36, the ROC-AUC value of art cultivation media audio decreases from 0.95±0.02 to 0.93±0.04. After 200 iterations, the video resource recommendation algorithm’s time fluctuation is between 0.21ms and 9.81ms, depending on the users’ behavior sequence. Making full use of technology to deeply mine Internet data can enable the diversification of media resources for art talent training and improve the quality of art talent training.
Exploration of cross-border e-commerce and its logistics supply chain innovation and development path for agricultural exports based on deep learning
Authors: Jin Lijing
Published: January 2024

This paper studies the cross-border e-commerce of agricultural products and its logistics supply chain collaborative management approach, the overall transaction mode and basic content, and proposes a cross-border e-commerce supply chain conceptual model. Aiming at the problems of agricultural product supply chains, a method for predicting agricultural product export prices is proposed. The Prophet algorithm under deep learning is utilized to construct the Prophet agricultural product price prediction model for trend, cycle, and holiday terms. Over the introduction of RNN algorithms and LSEM algorithms to optimize the prediction performance of the model, as well as the gradient explosion. On this basis, GRU neural networks are proposed as an improved model of RNN-LSTM. Prediction comparison experiments are designed to empirically analyze agricultural export price prediction and supply chain logistics risk control, and the results of the empirical analysis show that the vegetable export price predicted by using Prophet algorithm during the period of date 2013/4-2013/9 is 2.975, which differs from the actual price by 0.009 yuan, and the margin of error is in the interval of [-0.091,0.014], which is the smallest variation among the three algorithms, which shows that Prophet model has the best performance. After optimizing the FAPSC risk control coefficient, the risk value of supply chain logistics and transportation was successfully reduced from 0.364 to 0.296, and FAPSC effectively minimized the risk.
Research on the Innovative Path of College English Teaching Based on Deep Reinforcement Learning
Authors: Zhang Yumei , Cheng Hongmei
Published: January 2024

College English is a very flexible and important subject that needs to be constantly innovated. For the shortcomings of traditional teaching methods, this paper constructs a teaching behavior tree based on reinforcement learning. By analyzing the direction of the behavior tree, using the path planning algorithm to propose better teaching strategies, combined with the Q learning algorithm, the teaching theme and the environment of the information are timely updated in the Q value table to update the teaching behavior selection strategy, and ultimately obtain the teaching behavior tree. The reinforcement learning algorithm based on Q -function interacts with the environment to directly train the method of generating the behavior tree to check whether the teaching behavior tree reaches the optimal standard. Combine reinforcement deep learning with English teaching to introduce a new approach to teaching English. The results show that on the diversified evaluation behavior, teachers of 985 colleges scored significantly higher than teachers of 211 colleges, with a score of 3.05 for teachers of 985 colleges and 2.68 for teachers of 211 colleges. Among the two teaching factors, the F-value of the diversified evaluation is 4.601, and the F-value of the personalized teaching is 3.596, which indicates that both of them have a greater influence on the students and they are able to improve the English proficiency of the students. This study provides a new reference direction for college English teaching, which can effectively improve students’ practical skills.
Teaching Integration of Piano and Traditional Music Elements in Colleges and Universities Based on Network Flow Optimization
Authors: Dai Yufei
Published: January 2024

In this paper, from the basis of piano music theory, pitch and twelve equal temperaments are studied, and due to the characteristics of the piano’s construction, there are different timbres and harmonic structures. In order to realize the digitization of music signals for piano teaching, the collected analog signals are converted into digital signals by Fourier transform, the samples are inputted into the neural network model to get the output results, and the loss function based on Markov’s music language model in piano teaching is used to find the partial derivatives of the parameters to realize the maximization of the efficiency of the piano pitch and note recognition. According to the multi-task learning in neural networks and the envelope curve of notes, we construct the automatic music transcription model in piano teaching based on CNN-HMM and use the simulation experiment analysis to empirically analyze the piano teaching based on CNNHMM. The results show that the dual-channel audio results are improved by 2.68% in F1 value, 3.18% in accuracy and 2.61% in recall than the mono audio results. That is, dual-channel audio has richer information than mono audio, which enables the CNN-HNN network to learn richer features and thus improve the pitch and note recognition results. In this paper, the reliability of the teaching quality evaluation results of the CNN-HMM-based quantitative assessment model for facilitating the combination of electronic organ and piano teaching concepts ranges from 78.1% to 85.4%. This study provides guiding value for the development of digital piano teaching, which is of great significance for the innovative reform of piano teaching in colleges and universities.
Research on the Design and Practice of Civics Teaching in College Physical Education Courses Based on VAR Modeling
Authors: Fan Jun , Wang Bing , Wang Yueying
Published: January 2024

In this paper, a penalty function is added in the construction of the VAR model to control the accuracy of the model prediction, and considering the nature of the correlation between the variables, a weight fusion with Laplace penalty is introduced to generate a sparse solution to complete the construction of the vector autoregressive model. The basic types of vector autoregressive models under panel data are divided, the number of parameters to be estimated is determined, the parameters of the vector autoregressive model are estimated by the generalized method of moments estimation, and the parameter fitting effect of the model is improved by the great likelihood parameter estimation method, and the vector autoregressive model for panel data is constructed. Based on the VAR model, we propose a design scheme for the teaching of Civics in college sports courses and analyze the development of sports + Civics and the teaching effect of the courses through simulation and empirical analysis. The results of the study showed that OSI and OPCI rejected the original hypothesis at the significance level of 5% after second-order differencing, at which time both p-values were less than 0.1, and the series was smooth. The elasticity coefficient of the starting value of the sports response path is 0.0342, and the error interval is [0.0564, 0.06], indicating that the future development of the scale of “Sports + Civics” is stable.
Innovative Practice of Physical Education Teaching in Colleges and Universities in the Context of “Digital” Education
Authors: Zheng Lihong , Chen Kesheng
Published: January 2024

This paper takes the experimental design of the flipped classroom teaching mode under digital information technology as the entry point, chooses the appropriate research object and method, and designs the experimental program of flipped classroom teaching in college sports. Since the teaching effect of the flipped classroom teaching mode needs to be supported by students’ movement data, this paper utilizes the least squares distance to match and retrieve the data of students’ movement postures and then combines it with the ANN model to deeply mine the students’ movement data. For the teaching effect of the flipped classroom teaching mode, innovative practices are carried out for physical education teaching in colleges and universities. The results show that when the linear correlation coefficient of the ANN model is 1, the lowest value of validation loss is 2.1*10−4. The flipped classroom teaching mode can effectively enhance students’ physical fitness. The mean value of students in the experimental group in the learning motivation dimension has been improved by 5.44 points compared with the preexperimentation period. The results of the T-test of the sports concern and learning satisfaction are all significant differences at the 1% level. The combination of flipped classrooms and college physical education teaching in a digital environment can improve the effectiveness of physical education teaching and increase students’ interest in physical education learning.
Application of BIM technology in construction project cost refinement control and construction energy consumption control
Authors: Cao Hongmei
Published: January 2024

In order to solve the problem of accurate cost control management in the process of engineering construction, this paper applies BIM technology to the whole process of cost management, covering the whole life cycle of the project. Through efficient sharing of information on the BIM collaborative platform, it carries out unimpeded process work and achieves refined management. Aiming at the complexity of the information characteristics that affect the cost and uncertainty of information transmission, an algorithm fusion scheme based on NCM-FPN has been designed. The TOPSIS method is used to integrate the case feature attributes into the cost case information database. By combining the clustering algorithm with practical management experience, the knowledge base of engineering cost control strategies can be established, and the logical relationship of strategy matching can be determined. The inverse cloud algorithm is used to establish the feature cloud, determine the fuzzy Petri network structure based on generative rules and design the inference algorithm to establish an intelligent model for strategy matching so as to realize the accurate mapping and rapid response from the target case features to the control strategies. Through the analysis of construction energy consumption, it is concluded that the construction energy consumption of different structure buildings is not the same; the construction energy consumption per unit area of brick structure, steel structure residence and frame office building is 0.1659GJ/m2, 0.2706GJ/m2 and 0.3104GJ/m2 respectively, and the largest is the shear-wall structure residence is 0.3381GJ/m2 for the 2.04 times of the brick structure. Based on BIM technology, the cost of dynamic control engineering for construction projects was reduced by 5.4 million. Therefore, BIM is an important technical means to promote the whole process control of project cost, from empirical control to informationization, standardization, and intelligent control.
Integration of Instrumental Elements and Vocal Teaching Based on Music Core Literacy
Authors: Li Hua , Zhang Qingru , Liu Yuhe , Feng Fan
Published: January 2024

The current lack of music core literacy in vocal music teaching needs to be solved, and this paper aims to improve this problem. In the paper, a hybrid attention module is added to the multi-channel of MFCC to extract the acoustic elements of the musical instruments, and after characterizing the musical instruments as a multi-view sequence, visual features and temporal features are fused, and a graph convolution module is added to extract the visual elements of the musical instruments, and the two are fused. After extracting the elements of musical instruments, the development of vocal fusion teaching of the two was analyzed by combining the gray correlation analysis method, and experiments were designed on the basis of which to investigate the extraction effect of the elements of musical instruments as well as the development of vocal fusion pedagogy. The results show that the average accuracy of instrumental elements of the multimodal extraction model is 0.919, which is improved by 0.17 compared with the Baseline classification accuracy, and the extraction accuracy can reach more than 90% for flute, percussion instrument, plucked instrument, wind instrument, suona, xiao, sheng, wind instrument, pipa, and erhu. The gray correlation of the fourth grade ranged from 0.75 to 0.88, with a high improvement in the same grade, and the gray correlation of different grades all ranged from 0.3 to 1.0, and the higher the grade, the better the development.
Exploration of financial tax system in the context of big data
Authors: Ji Ning
Published: January 2024

The financial tax system is related to the actual effectiveness of a country’s modernized economic development and has a close relationship with the country’s economic enhancement. To examine the causal effects between potential variables in the tax system, this paper constructs a measurement model of financial tax system variables using Bayesian structural equations. Parameter estimation for SEM is completed by adding prior information to the sample data and calculating the posterior distribution of relevant parameters using Bayes’ theorem. The correlation between financial taxation and economic development is calculated to indicate whether there is consistency in financial taxation on economic efficiency. Cronbach’s coefficient is used to measure the degree of consistency and stability of each part of the financial tax index system. The results show that the impact value of personal tax is 0.71, 0.37 and 4.18 in provinces C, A and B. Promoting economic development in provinces and municipalities with a better degree of economic development is aided by the current personal income tax sharing ratio. Reducing the proportion of indirect taxes while keeping the macro tax burden unchanged results in a gradual increase of the proportion of personal income tax in total tax revenue from 8.7% to 18.7%. The research in this paper further improves the financial tax system and provides an effective method to improve economic efficiency.