bluuebunny/crossref_metadata_2025_split huggingface dataset:
TRACING AMERICAN SPIRIT IN INDONESIA’S INDEPENDENCE: A HISTORICAL-COMPARATIVE STUDY
Authors: Pasha Nariza Ayu 
Published: October 2024

The US and Indonesia, two countries that fought for freedom, are fascinating subjects to delve more into, despite their great distance from one another and their distant times of conflict. This research used a Transnational American Studies perspective and comparative-historical analysis. By using comparative historical analysis, this research aimed to explore the similarities and differences that exist in the journey of American independence and Indonesian independence. The results of this research showed that even though the independence movements in the US and Indonesia occurred several centuries apart, they had the same goal, namely opposing colonialism. Both showed the same enthusiasm to fight colonial power and the desire to determine the fate of their nation without interference from other parties. Thomas Paine and Bung Tomo through their writings and speeches led the spirit of independence in the US and Indonesia. Even though they use different communication styles, both have an impact in forming the spirit of resistance and unity of their nation. Additionally, by looking at the history of the struggle of the Indonesian people, it can be seen the spirit of freedom that the US promoted.
Charles-Joseph Tanret: natural principles
Authors: Wisniak Jaime 
Published: October 2024

Charles Tanret (1847-1917) was a French chemist and pharmacist who devoted most of his life to the isolation of new alkaloids and the chemistry of sugars. To his credit we owe the preparation of crystalline digitalis, the isolation of ergotinin, cornutin, and ergosterol from rye ergot, vincetoxin from the root of Asclepias, isohesperidin, hesperidin, etc. from the peel of bitter orange, quebrachitol from the bark of white quebracho, levosine from ripe rye, wheat, and barley, the glucoside picein from the leaves of spruce fir, and its derivative piceol, the synthesis of levoglucosan from piceol, and the synthesis of artificial alkaloids by the reaction between ammonia and glucose.

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The Role Of Company Size As A Moderating Variable Against Financial Statement Fraud: The Beneish Model Perspective
Authors: Biduri Sarwenda , Hermawan Sigit , Hariyanto Wiwit , Sriyono Sriyono , Ardianti Cintya Devi Retno 
Published: October 2024

Purpose: This study aims to prove the influence of External Pressure, Ineffective Monitoring, Quality of External Auditors, Changes in Auditors and Frequency of CEO Depictions and Company Size as a moderation of Fraud in a company's Financial Statements.
Methodology/approach: In this study, researchers used a type of quantitative research. Purposive sampling was used as a technique in determining the sample for this study. The data used are company annual reports and the population in this study are companies engaged in the textile and garment manufacturing sub-sector for the 2017-2021 period with a total sample of 55.
Findings: This study states that the variables Quality of External Auditors and Frequency of CEO Descriptions have an effect on fraudulent acts in reports financial statements, while the variables of Ineffective Oversight, External Pressure and Change of Auditor have no effect on fraudulent acts in financial statements. For the moderating variable in this study, company size is not able to moderate the relationship between ineffective monitoring and fraud in financial statements.
Practical implication: The theoretical implication of this research is to increase academic knowledge about the factors that cause fraudulent financial statements.
Leveraging Full Count Census Data through Record Linkage
Authors: Fitch Catherine A. , Udalova Victoria , Antonie Luiza 
Published: October 2024

Academic researchers in the U.S. and Canada have partnered with genealogical organizations and statistical agencies to create massive new scientific data collections from census enumerations. These data are creating new opportunities for research across the social and health sciences. By linking individuals and families across censuses, analysts can create national longitudinal panels that trace the characteristics of individuals over their lives and families over multiple generations.
IPUMS disseminates full count census enumerations for ten U.S. census years from 1850 to 1950. These full count data cover almost 800 million individual records and the IPUMS Multigenerational Longitudinal Panel (MLP) project links individuals' records across censuses. IPUMS data can be combined with data from the U.S. Census Bureau’s data linkage infrastructure to link historical records to numerous recent censuses, surveys and administrative data that measure social, economic and health outcomes.
The Canadian Peoples (TCP) is a comprehensive public research database of 40 million coded and georeferenced records found in Canadian censuses from the middle of the nineteenth century until after the First World War. The data include personal, family and household characteristics of every individual enumerated in each census from 1852 to 1921. TCP investigators are exploring record linkage technology to solve challenges presented with these historical records.
The workshop included one presentation from each organization, with these objectives: introduce the data collections, explain the challenges and opportunities of census linkage, describe the linking strategies, and provide an overview on how to access the data.
Penerapan Model Pembelajaran Problem Based Learning (PBL) Dipadu Two Stay Two Stray (TSTS) untuk Meningkatkan Motivasi Belajar Siswa Kelas X SMA
Authors: Rohmatulloh A. Farid , Susilo Herawati , Ruslina Elya 
Published: October 2024

Pembelajaran biologi di kelas X-2 SMAN 9 Malang kurang melibatkan partisipasi siswa secara aktif. Berdasarkan hasil observasi, motivasi belajar siswa tergolong rendah. Indikator rendahnya motivasi meliputi siswa kurang terlibat dalam pembelajaran, siswa berbicara sendiri di luar materi pelajaran, siswa tidak memperhatikan saat guru menjelaskan, sulit mengaitkan materi dengan kehidupan sehari-hari, kurang antusias serta kurang percaya diri. Solusi yang tepat adalah implementasi model Problem Based Learning (PBL) Dipadu dengan Two Stay Two Stray (TSTS). Penelitian ini bertujuan untuk meningkatkan motivasi belajar. Penelitian ini termasuk Penelitian Tindakan Kelas (PTK) dengan pendekatan penelitian deskriptif kualitatif. Subjek penelitian adalah siswa kelas X-2. Penelitian ini dilaksanakan dalam dua siklus yaitu siklus I dan siklus II. Hasil penelitian menunjukkan bahwa keterlaksanaan sintaks pembelajaran model PBL dipadu TSTS pada siklus I sebesar 95,45% dan meningkat pada siklus II sebesar 100%. Implementasi model PBL dipadu TSTS dapat meningkatkan motivasi belajar siswa dari aspek attention, relevance, confidence, satisfaction. Berdasarkan angket, terjadi peningkatan persentase attention 5%, relevance 4,26%, confidence 3,83%, satisfaction 4,9%. Berdasarkan lembar observasi dari siklus I ke siklus II yakni sebesar 32,32 %.
Penyebaran Daerah Rawan Banjir di Kelurahan Anggrung Kecamatan Medan Polonia Kota Medan
Authors: Asrul Asrul , Simanungkalit Nahor M. 
Published: October 2024

Penelitian ini dilaksanakan di Kelurahan Anggrung Kecamatan Medan Polonia, bertujuan untuk mengetahui persebaran daerah rawan banjir yang meliputi ;karakteristik banjir dan penyebaran daerah rawan banjir. Populasi dalam penelitian iniadalah seluruh daerah Kelurahan Anggrug dan populasi sekaligus dijadikan sampel (area sampling).Teknik pengumpulan data dilakukan dengan observasi, wawancara dan studi dokumentasi. Metode analisis data yang digunakan dalam penelitian adalah teknik analisis deskriptif kualitatif, karena penelitian ini menggunakan data kualitatif. Hasil penelitian menunjukan bahwa daerah yang rawan terkena banjir di Kelurahan Anggrung Kecamatan Medan Polonia umumnya berada di sekitar bantaran sungai Babura (banjir kiriman) dan di jalan-jalan raya (banjir lokal). Dengan luas banjir 32.21% dari luas Kelurahan Anggrung, kedalaman banjir berkisar antara 0,1-2 m, lama genangan 1-24 jam dan priode ulang banjir 13,3 kali dalam 4 tahun.Kata Kunci : Banjir, rawan banjir
Study on the role of “pre-incubators” in a high-quality vocational education system based on an information diffusion model
Authors: Li Zhibin 
Published: October 2024

Abstract
From the perspective of integrating social resources, the pre-incubator provides specialized training for college talents through in-depth cooperation between enterprises or governments and colleges and universities and guides the high-quality development of the vocational education system. This paper puts forward the basic model of information diffusion, based on the construction of an incubator network, combined with the role of incubator network nodes, and puts forward the information diffusion model of a “pre-incubator” network based on information content. The network structure of “pre-incubator” knowledge diffusion is analyzed with respect to the interest-matching degree of information content. Combined with the intrinsic connection between “pre-incubator” and a high-quality education system, we analyze the functional positioning of “pre-incubator” in higher vocational education. Combined with the descriptive statistics, analyze the role of “pre-incubator” on university-enterprise cooperation and innovation quality. The statistics show that the mean value of the number of patents of higher vocational institutions is 2.954, and the number of joint invention patents of university-enterprise is 0.721, and the estimation results show that, compared with the universities without higher vocational “pre-incubator”, the quality of innovation of the universities relying on the higher vocational “pre-incubator” is significantly improved after the establishment of the higher vocational “pre-incubator”. The results show that the quality of innovation of the universities based on the higher vocational “pre-incubator” is significantly improved after the establishment of the higher vocational “pre-incubator” compared with that of the universities without it.
Research on Talent Cultivation Strategies for Art and Design Majors Facing the Background of Informatization
Authors: Zhang Qinge 
Published: October 2024

Abstract
Under the implementation of new talent cultivation goals, the gaps in art design teaching are gradually revealed, and various teaching shortcomings have become stumbling blocks on the road of professional education development, which need to be improved in time. Combined with information technology, this paper proposes three curriculum integration strategies: enhancing audio-visual sensory effects, applying microteaching, and expanding the sharing channels of the art design resource library. A teaching resource application platform has been constructed for the art and design resource sharing strategy, which combines user-based and project-based collaborative filtering algorithms and is applied to the resource recommendation module. The performance of the system is evaluated through algorithmic comparison, and a satisfaction survey is conducted on the three dimensions of perceived usefulness, perceived ease of use, and intention to use for art and design students who use the system. The average satisfaction values in the three dimensions were 76.99%, 78.35%, and 79.5%, respectively, indicating that the art design students were more satisfied with the teaching resource application platform designed in this paper.
Research on the Innovation Path and Enterprise Adaptation of Green Finance in the Development of Low-Carbon Economy-Strategy Analysis Based on Neural Network Modeling
Authors: Fu Lin 
Published: October 2024

Abstract
Green finance is an economic form formed by the organic combination of finance and environmental awareness, and the long-term development of a low-carbon economy needs to be strongly supported by green finance. Based on the generalized regression neural network model, this paper measures the level of green finance development in a low-carbon economy by constructing a green finance evaluation system. The evaluation system for enterprise adaptability level under green finance is constructed from three dimensions: enterprise green development ability, enterprise green innovation ability, and enterprise green management ability. The entropy weight method is used to empower the indicators in the rating system, and the set-pair theory is used to portray the data of the empowered indicators, while the Markov chain combined with the set-pair linkage is introduced to portray the dynamic trend of the development of enterprise adaptability level. The generalized regression neural network model’s prediction accuracy for green finance development in Guangdong Province is above 85% after the study. Year-on-year, the level of green finance development in Guangdong Province increased by around 57.78%, creating a significant growth trend in the context of a low-carbon economy between 2010 and 2017. The level of business adaptability also leaps from “poor” to “excellent”, with the linkage value changing from −0.8574 in 2018 to 0.8031 in 2022. This paper’s research provides the perfect data support for choosing a green financial innovation path only in a low carbon economy.
Research on the design and precise monitoring technology of intelligent early warning system for power tower settlement based on multi-dimensional information fusion technology
Authors: Wang Youqing , Gao Xi , Du Mingjing , Ma Pengfei , Chen Fei 
Published: October 2024

Abstract
Multi-dimensional information fusion technology helps to realize the synergy and complementarity between the information, which provides a guarantee for the settlement monitoring and early warning of electric power pole towers. The settlement monitoring algorithm for electric power pole towers is improved by this paper based on this technology and a settlement warning model is proposed. The traditional PDA algorithm can be enhanced by enhancing the pole tower image acquisition capacity with the wavelet transform algorithm and achieving the fusion and evaluation of multidimensional information through an isolated forest algorithm. The relationship functions of tilt angle, settlement wind speed size and other indicators are established, and the system of super-definite equations is used to solve the correlation coefficients, and the early warning system of pole tower settlement is constructed. The analysis results show that the monitoring results of the monitoring algorithm are fluctuating and stable; the absolute value of the error in the horizontal direction is not more than 9 mm, and the absolute value of the error in the vertical direction is not more than 14 mm. The predicted values of the maximum displacement and stress R
2 are close to 1, and the MAPE is 0.436% and 1.123%, respectively. It indicates that the improved power pole tower settlement monitoring algorithm and early warning system in this paper have satisfactory performance.
An investigation on the application of deep reinforcement learning in piano playing technique training
Authors: Ji Chen , Wang Dan , Wang Huan 
Published: October 2024

Abstract
The article applies the knowledge of the physiological structure of finger movement in piano playing and the DH parameter method to construct a kinematic model of finger keystroke in piano playing. The Leap Motion-based gesture recognition algorithm is used for piano playing gesture movement extraction, gesture movement sub-framing, and velocity direction encoding, and the judgment HMM algorithm and the Viterbi improvement algorithm based on the a priori knowledge of fingering are utilized to automatically standardize piano fingering. After comparing the recognition performance of the piano playing training model in this paper, it is discussed how it can be used and how it can improve the user’s piano playing skills. In comparison to other piano gesture recognition models, the recognition accuracy and gesture dynamic information description of this paper’s training model demonstrate optimal performance. After the actual playing training experiments, the experimental group achieved significant improvements, while the control group experienced negligible improvements. After the experiment, the difference between the two groups increased, and the experimental group was superior to the control group in all aspects of piano playing. The training model for piano playing in this paper is effective in enhancing the user’s piano playing level.
Exploring Semantic Understanding and Generative Modeling in Speech-Text Multimodal Data Fusion
Authors: Yu Haitao , Wang Xuqiang , Sun Yifan , Yang Yifan , Sun Yan 
Published: October 2024

Abstract
Accurate semantic understanding is crucial in the field of human-computer interaction, and it can also greatly improve the comfort of users. In this paper, we use semantic emotion recognition as the research object, collect speech datasets from multiple domains, and extract their semantic features from natural language information. The natural language is digitized using word embedding technology, and then machine learning methods are used to understand the text’s semantics. The attention mechanism is included in the construction of a multimodal Attention-BiLSTM model. The model presented in this paper convergence is achieved in around 20 epochs of training, and the training time and effectiveness are better than those of the other two models. The model in this paper has the highest recognition accuracy. Compared to the S-CBLA model, the recognition accuracy of five semantic emotions, namely happy, angry, sad, sarcastic, and fear, has improved by 24.89%, 15.75%, 1.99%, 2.5%, and 8.5%, respectively. In addition, the probability of correctly recognizing the semantic emotion “Pleasure” in the S-CBLA model is 0.5, while the probability of being recognized as “Angry” is 0.25, which makes it easy to misclassify pleasure as anger. The model in this paper, on the other hand, is capable of distinguishing most semantic emotion types. To conclude, the above experiments confirm the superiority of this paper’s model. This paper’s model improves the accuracy of recognizing semantic emotions and is practical for human-computer interaction.
Using Data Mining Techniques to Explore the Compositional Characteristics of Mozart’s Piano Concertos
Authors: Wang Dan , Ji Chen , Cao Hongzhen 
Published: October 2024

Abstract
The piano concerto is the most important area of Mozart’s musical creation, except opera and throughout Mozart’s life. In this project, the original audio files of Mozart’s piano concertos were collected and preprocessed using data mining techniques. Then, the fast Fourier transform algorithm was used to extract the audio features, which was combined with the multimodal music emotion classification of audio and lyrics, to complete the fusion of multiple different music features. Finally, based on Thayer’s emotion model, the support vector machine algorithm is used to effectively classify music emotion and music frequency to deeply explore the creative characteristics of Mozart’s piano concerto. The results show that the algorithm in this paper identifies 52 samples that are biased towards calm emotion, which is 2.5 times more than the samples that are biased towards happy emotion, indicating that the style of Mozart’s music creation is biased towards calmness and elegance, and 80% of the Mozart’s music samples are biased towards high frequency above 4000 HZ, indicating that Mozart mainly creates high-frequency music. The algorithm in this paper accurately accomplishes the task of exploring the characteristics of Mozart’s piano concerto composition.
Analysis of Land Use and Occupation in a Neighborhood of the City of Manaus-AM Using Geotechnologies
Authors: Costa Géssica Maciel , Reis Raquel Freitas , Souza Maryana Antônia Braga Batalha de , Reis Vanderson de Lima , Pietzsch Madalena da Rocha , Lima Newton Silva de 
Published: October 2024

Objective: The objective of this study is to analyze the land use and occupation that occurred between 1999 and 2021 in the Tarumã neighborhood located in the city of Manaus-AM, with the aim of carrying out, through remote sensing techniques, the investigation of the environmental impacts that occurred, considering the classes of soil, vegetation and hydrography.

Theoretical Framework: The accelerated population expansion and the lack of environmental planning contribute to the increasing degradation of natural resources. The disorderly distribution of the territory represents one of the main problems in Manaus.

Method: Land use and occupation mapping was obtained from the supervised classification of Landsat 7 and Landsat 8 satellite images, RGB bands, through the United States Geological Survey – USGS (Earth Explore). Data comparisons were made based on the temporal analysis of the images and shapefile.

Results and Discussion: The results obtained identified the class transformations that occurred in the last 22 years, which corresponds to 41.71% of primary vegetation, 8.98% of secondary vegetation, 17.70% of exposed soil. In the urban area, there was interference of 30.16%, with a 1.74% decrease in the water class, including the Environmental Preservation Area

Research Implications: The practical and theoretical implications of this study favor the understanding, measurement and prediction of environmental impacts caused by the ordered and disordered urban occupation of cities.

Originality/Value: This study contributes to the monitoring of occupations in the Tarumâ neighborhood, contributing to decision-making in preservation areas.
Influences of Irreversibility in Transport of Peristaltic of Hybrid Nanomaterial through a Porous Medium in an Inclined Channel
Authors: Salih Alaa Waleed , Abdulhadi Ahmed M. 
Published: October 2024

The purpose of this work is to determine transferred heat features and irreversible transport peristaltic of nanomaterial fluid through a porous medium with an inclined symmetric channel. Expression of the basic velocity, pressure gradient, temperature, and stream function profiles within the boundary layer are plotted and discussed in detail via various values of the distinct parameters. Nanoparticles of hybrid nanomaterial impacts are also used. In the present article, water is used as a base liquid while nanoparticle contain polystyrene and graphene oxide. Over time, it is observed that there are distinct factors and effects such as magnetic field and porosity parameters. Mathematica software is used for estimating the exact solutions of axial velocity and temperature profiles. Additionally, the resolution of equations are considered under the small Reynolds number and large wavelength approximation. Results with plotting graph access via MATHEMATICA (11) are listed.