bluuebunny/crossref_metadata_2025_split huggingface dataset:
STUDI ETNOBOTANI PADA PROSES RITUAL ADAT MASYARAKAT BALI KECAMATAN LABUHAN MARINGGAI SEBAGAI SUMBER BELAJAR BIOLOGI
Authors: Safitri Safitri , Mufahroyin Mufahroyin , Santoso Handoko 
Published: September 2023

Abstrak: Etnobotani penting untuk dipelajari oleh masyarakat Indonesia karena pemanfaatan tumbuhan secara tradisional masih banyak yang belum diketahui. Rendahnya pengetahuan masyarakat akan ritual adat dan sedikit masyarakat yang memahami tentang ilmu etnobotani menyebabkan terjadinya degradasi budaya. Penelitian ini bertujuan untuk mengetahui pemanfaatan tumbuhan dalam ritual adat ritual lingkup keluarga yang mencakup pernikahan, kehamilan,melahirkan, kematian, ritual kemasyarakatan yang mencakup nebar beih, membangun rumah, memotong gigi, ritual peribadahan galungan, kuningan, nyepi, purnama, yajna, tri sadyana, saraswati oleh masyarakat Bali Kecamatan Labuhan Maringgai Kabupaten Lampung Timur. Metode yang digunakan dalam penelitian ini adalah gabungan antara metode kualitatif dan kuantitatif. Sampel diambil menggunakan teknik snowball sampling dan purposive sampling. Wawancara dilakukan pada 24 narasumber yang merupakan 4 tokoh adat dan 2 masyarakat Bali. Dari hasil wawancara di dapatkan hasil tumbuhan yang digunakan dalam ritual adat masyarakat Bali yang mencakup 4 Banten, yaitu banten pejati, banten daksine, banten kewangen, banten canang, banten sagehan. Terdapat tiga faktor yang menyebabkan terjadinya degradasi yaitu faktor internal, eksternal, dan etnobotani.
Abstract: Ethnobotany is important for the people of Indonesia to learn because the traditional use of plants is still unknown. The low level of public knowledge of traditional rituals and few people who understand ethnobotany have caused cultural degradation. This study aims to determine the use of plants in traditional rituals within the family which includes marriage, pregnancy, childbirth, death, social rituals which include nebar beih, building a house, cutting teeth, rituals of Galungan worship, brass, Nyepi, full moon, yajna, tri sadyana , saraswati by the people of Bali, Labuhan Maringgai District, East Lampung Regency. The method used in this study is a combination of qualitative and quantitative methods. Samples were taken using snowball sampling and purposive sampling techniques. Interviews were conducted with 24 informants who were 4 traditional leaders and 2 Balinese people. From the results of the interviews, it was obtained plant products used in Balinese traditional rituals which cover 4 Banten, namely Pejati Banten, Daksine Banten, Kewangen Banten, Canang Banten, Sagehan Banten. There are three factors that cause degradation, namely internal, external, and ethnobotanical factors.
KEANEKARAGAMAN JENIS CAPUNG DI LANSKAP PERTANIAN GOALPARA-PERBAWATI KABUPATEN SUKABUMI PROVINSI JAWA BARAT
Authors: Ibnusivva Caesar Adhitya , Kurnia Insan 
Published: September 2023

Capung merupakan serangga yang berperan penting secara ekologi sebagai predator terutama bagi serangga hama baik di habitat perairan maupun habitat terestrial. Lanskap pertanian Goalpara-Perbawati Kabupaten Sukabumi memiliki sejarah panjang pemanfaatannya sebagai lahan budidaya, sehingga penelitian ini bertujuan untuk menganalisis keanekaragaman jenis capung di lanskap pertanian Goalpara-Perbawati. Penelitian dilaksanakan pada Bulan Februari-Mei 2022 di lima habitat yaitu kebun teh, kebun kopi, kebun Bunnga, Kebun Sayur, dan Danau. Data capung diambil dengan metode transek berukuran 100x20 meter selama 10 menit setiap transek. Data habitat mencakup deskripsi vegetasi dominan, suhu udara, kelembaban udara, dan kecepatan angin. Data dianalisis dengan nilai indeks keanekaragaman jenis (H’) dan kemerataan jenis (E). Kekayaan jenis capung yang dijumpai sebanyak 16 jenis dari dua sub-ordo dan lima famili. Capung paling banyak dijumpai di habitat danau (13 jenis). Jenis Orthetrum sabina dapat dijumpai di seluruh tipe habitat, sementara jenis lain hanya dijumpai di satu sampai empat habitat. Secara keseluruhan diperoleh nilai H’ sebesar 1,82 dan nilai E sebesar 0,66. Nilai H’ tertinggi yaitu habitat danau (H’=2,07) sedangkan yang terendah yaitu habitat kebun teh (H’=0,85). Sementara nilai E yang tertinggi yaitu habitat danau (E=0,81) sedangkan yang terendah yaitu habitat kebun bunga serta kebun kopi sebesar E=0,71.
Pengaruh Discovery Learning Berbasis Augmented Reality terhadap Hasil Belajar Siswa
Authors: Indriyani Dian , Muhfahroyin Muhfahroyin , Santoso Handoko 
Published: September 2023

Abstrak: : Tujuan penelitian ini untuk mengetahui pengaruh model pembelajaran discovery learning berbasis augmented reality terhadap hasil belajar kognitif materi sistem ekskresi manusia pada siswa Kelas VIII SMPN 2 Raman Utara. Jenis penelitian ini adalah eksperimen semu dengan menggunakan Posttest Only Control Design, peneliti menggunakan instrument berupa butir soal tes uraian (essay) yang digunakan peneliti untuk mengukur kemampuan peserta didik setelah melakukan proses belajar dengan menggunakan model pembelajaran Discovey Learning Berbasis Augmented Reality. Penelitian ini menggunakan 2 kelas yaitu kelas kontrol dengan menggunakan model pembelajaran konvensional dan kelas eksperimen menggunakan model pembelajaran Discovery Learning Berbasis Augmented Reality. Data penelitian diuji hipotesis dengan Independent Sampel t-test. Hasil uji dengan uji normalitas menunjukan Sig > daripada α=0,05 yaitu 0,908 > 0,05, dan untuk uji homogenitas didapatkan nilai 0,715 yang berarti terima H0 kedua populasi mempunyai varians yang homogen (sama), kemudian pada uji Independent Sample t-test didapatkan nilai sig < dari ( = 5%) yaitu 0,001 < 0,05 Sehingga ada pengaruh model pembelajaran discovery learning berbasis augmented reality terhadap hasil belajar kognitif materi sistem ekskresi manusia pada siswa Kelas VIII SMPN 2 Raman Utara.

Kata kunci: model Discovery Learning, hasil belajar siswa
Abstract: The purpose of this study was to determine the effect of the augmented reality-based discovery learning model on cognitive learning outcomes of the human excretory system material in Class VIII students of SMPN 2 Raman Utara. This type of research is a quasi-experimental using the Posttest Only Control Design, the researcher uses an instrument in the form of essay test items used by researchers to measure the ability of students after carrying out the learning process using the Augmented Reality Based Discovery Learning learning model. This study used 2 classes, namely the control class using conventional learning models and the experimental class using the Augmented Reality Based Discovery Learning model. The research data was tested by the hypothesis with the Independent Sample t-test. The test results with the normality test show Sig > than α = 0.05, namely 0.908 > 0.05, and for the homogeneity test a value of 0.715 is obtained, which means that accept H0, the two populations have homogeneous (same) variance, then test the Independent Sample t-test obtained a sig value < of (α = 5%), namely 0.001 <0.05 So that there is an influence of the augmented reality-based discovery learning model on cognitive learning outcomes of human excretory system material in Class VIII students of SMPN 2 Raman Utara.
Research on the identification and integration of folk dance creation elements based on big data technology
Authors: Li Chang 
Published: September 2023

Abstract
In order to identify the elements of folk dance creation, two methods of continuous folk dance movement recognition are proposed in this paper. By considering the dance movement patterns as a whole and the templates as incomplete patterns, OE-DTW is applied to match them to segment and recognize each movement pattern one by one. To enhance the performance, a global restriction K-Repetition and endpoint detection condition are proposed to match with OE-DTW, and a penalty-based layer matching algorithm is proposed by using the layer structure feature of SegSVD so that the endpoint of the input movement pattern can be determined by the top layer matching of the latter when matching with the template pattern. Meanwhile, the similarity between two patterns based on this algorithm can also be calculated by the local results obtained from the weighted cumulative layer matching. Experiments show that the average recognition rate of OE-DTW is 0.891, SegSVD is 0.86, and CDP is 0.828. Both methods can effectively deal with the continuous action recognition problem, and they have better recognition results compared with CDP.
Analysis of energy storage capacity optimization of distribution network based on quadratic planning algorithm under large scale DG access
Authors: Song Xinfu , Li Changling , Yi Geng , Zhong Rui , Wang Wei 
Published: September 2023

Abstract
The intermittent, random and uncontrollable characteristics of renewable energy generation bring many challenges to the actual operation of distribution grid (DG) energy storage. This paper firstly establishes a whole life cycle model applicable to the distribution grid energy storage system, which fully considers the various types of costs of VSC converter stations. Secondly, for comprehensive reactive power optimization, a sequential quadratic programming algorithm is used, and inequality constraints are added to the objective function in the form of penalty functions to optimize the state of on-load transformers and capacitors. Finally, the effectiveness of its distribution grid energy storage configuration optimization is verified by applying the distribution grid energy storage optimization based on the quadratic programming algorithm to electric vehicle charging piles. The results show that after two stages of optimization, the configuration capacity of distribution grid energy storage is increased by 53.14Kw/h compared with that before optimization, which is a substantial increase. The average annual cost of battery 0’ access decreases by 0.275, and battery 2’ access decreases by 0.581. This shows that the energy storage capacity optimization strategy based on the sequential quadratic programming algorithm proposed in this paper can improve the efficiency of energy storage utilization. It provides the basis for the user to select the energy storage capacity.
Civic education reform based on deep reinforcement learning model
Authors: Peng Dan 
Published: September 2023

Abstract
The integration of artificial intelligence technology into education is an inevitable trend of scientific progress and educational reform, and how to use artificial intelligence technology and ideological and political education reform is called a key research direction in the education sector. Aiming at the problems of cold start in personalized recommendation system, lack of interpretability of recommendation results, and ignoring the implicit features of the course for better acceptance of recommendation results by learners, the BPRMF model based on deep learning is proposed to be applied to the problem of recommendation of Civics and Political Science course, which not only models learners’ preferences and combines with course attribute features to generate recommendation rating ranking list and provide personalized recommendation service. Then the study of Civics education reform is conducted, mainly analyzing the change in teaching methods based on big data, machine learning, and deep learning technologies to promote secondary school students. The performance of the BPRMF model is evaluated in comparison with the BPRMF model under different k values. It is concluded that the accuracy rate of the BPRMF model is 8.9%~12.01% higher than UBCF and 8.07%~10.26% higher than IBCF, but with the increase of k value, the recall rate will gradually pull away from other models and optimize the recommendation system to some extent. This study is beneficial to ideological education in the implementation process to better utilize the opportunities, meet the challenges, and develop efficiently.
Research on the cultivation path of craftsmanship in university education based on fuzzy hierarchical analysis
Authors: Ma Xin 
Published: September 2023

Abstract
This paper firstly explores the evaluation method of the level of cultivation of craftsmanship in colleges and universities and decomposes the problem to be analyzed into each component element that affects its goal by using the fuzzy hierarchical evaluation method. The hierarchical structure analysis model is established, and the upper influence factors of each layer are used as the basic criteria to compare each influence factor of the program layer and the criterion layer with each other, and the fuzzy consistency matrix is constructed to determine the relative weights of each divided influence factor. Then, the current situation of the level of cultivation of craftsmanship in college education and the problems of the cultivation mechanism of craftsmanship in colleges and universities were analyzed, and suggestions for improvement were put forward. In terms of the existing problems, 70% of them think that the atmosphere of attaching importance to craftsmanship spirit is insufficient, 80% of them think that the teaching method of craftsmanship spirit is in a single way, and 86% of them think that the excavation of craftsmanship spirit is not deep. In terms of the recognition of craftsmanship spirit, “respecting teachers and respecting morality”, “being willing to devote”, “being rigorous and meticulous”, “inheriting tradition “ and “innovation and creation” are all around 60%, while “excellence”, “love for work”, and “endurance of loneliness” are all around 60%. The approval rate of the artisan spirit of “enduring loneliness” is between 70% and 75%. The research of this paper is of great significance to the cultivation of craftsmanship in universities.
Analysis of the fusion development of traditional culture concept and interior art design based on 3D scene analysis
Authors: Zhu Shuhua 
Published: September 2023

Abstract
In this paper, by collecting a large number of 3D scenes with traditional cultural styles, after pre-processing, the style analysis task of 3D scenes is realized through two stages of model style element discovery and scene style pattern mining. In the style pattern mining stage, the maximum frequent pattern mining algorithm is used to get the style pattern of the final scene, and the part is visualized. To reduce the user’s selection time, a 3D interior layout recommendation system based on style rule mining is designed using collaborative filtering. Based on the previous work on scene style pattern mining, the style association rules are further mined, and the user is provided with candidate layouts and furniture dynamically and in real-time by introducing user interaction. Comparing the text-improved recommendation algorithm with the traditional recommendation algorithm, the accuracy rate of the traditional algorithm starts to saturate to 65% after TopN>20, while the algorithm in this paper is higher than 80%. In the analysis of traditional cultural contexts of interior art, in terms of the aesthetic acquisition, the highest proportion of aesthetic association is 63.7%. In terms of emotional expression, the proportion of symbolization of emotion is 73.1%. In terms of object comparison, the highest proportion of plurality and flexibility of combinations was 57.5%. Therefore, this paper provides good research ideas for how to better integrate traditional culture into interior design.
Exploration and Practice of College English Reading Teaching Reform in the Context of Deep Learning
Authors: Chen Xiaoxia , Ye Bangxiang 
Published: September 2023

Abstract
To improve the quality and effectiveness of learners’ English reading learning, this paper proposes a fuzzy hierarchical analysis method incorporating deviance entropy (DE-FAHP), which improves the differentiation quality of the fuzzy judgment matrix and enhances the accuracy of weight calculation of each influencing factor by introducing deviance entropy model. Finally, the comprehensive difficulty quantification model of English reading comprehension objective questions is determined to provide an efficient and accurate method for calculating the parameters of the subsequent English reading comprehension standardized question bank. Finally, this paper proposes a hybrid testing method that combines CAT’s online grouping technology with MST’s staged presentation of test questions to construct the English reading comprehension adaptive testing system ca-MST. Through system validity testing, students in the experimental class improved more significantly, with only question 20 in the experimental class scoring below 4.0, while most of the scores in the control class were below 4.0. The mean reading score of the experimental class was 76.31, with a standard deviation of 11.16, while the mean reading score of the control class was 69, with a standard deviation of 18.76. The comparison showed that the reading scores of the experimental class taught with the reading comprehension adaptive testing system were higher than those of the control class taught with the traditional model, and the differences within the class were smaller.
Analysis of the evolution of modern Chinese history based on data mining
Authors: Wang Yue 
Published: September 2023

Abstract
In this paper, data mining is proposed to study the evolution of China’s modern history by addressing the problem of incomplete content of the evolution process. The data mining technique mainly preprocesses the data set of Chinese modern history by logistic regression algorithm, and its purpose is to detect the accuracy of the data so as to provide accurate and high-quality data for the data mining process. The process of visualization using information related to the evolution of modern Chinese history and the influence of modern Chinese historical events is applied to the visualization analysis, and the final influence of the evolutionary development of modern Chinese history is obtained and saved to the database by weighting and summing the influence factors of modern Chinese historical figures. The logistic regression algorithm uses modern historical persons and things as input data, and the weights of modern historical persons and things are the predictions carried out by classification. The results show that the highest accuracy is 0.67 when the threshold value is set to 1. The logistic classification model predicts better for the case of weight type 2 of modern Chinese history people and weight type 6 of modern history things. This study makes a certain contribution to the study of modern history so that the study of modern history can gradually move toward completeness and objectivity.
Analysis and Evaluation of Ecotourism Resources in China Based on RIAM Model
Authors: Li Jingke 
Published: September 2023

Abstract
A comprehensive assessment of ecotourism resources is needed for the sustainable development of ecotourism in China. In this paper, based on the scientific classification of ecological resources, the RIAM model for the environmental impact assessment of ecotourism resources is established, and the indicator sets are obtained based on a fast matrix calculation combining semi-quantitative and qualitative. Then, the hierarchical analysis method is used to calculate the weights of different indicators for the established indicator sets. Finally, an empirical analysis of the resources of Huangtengxia Ecotourism Area was conducted based on the comprehensive assessment model. It was found that the bio-ecological impact index of Huangtengxia was [6,8,-2,15,7], and the economic return impact index was [4,7,10,-5,8]. Taken together, the overall evaluation of ecological tourism resources in Huangtengxia has a total score of 72, which belongs to the middle to the upper level of similar tourism resource regions in China. This study establishes a scientific evaluation system of ecotourism resources in Huangtengxia, which provides a valuable reference template for the evaluation of ecotourism resources in China.
Research on fault feature extraction and early warning of rolling bearing vibration signal of generator set
Authors: Ma Yan , Si Jun , Yan Qiuzhen , Wang Jun 
Published: September 2023

Abstract
The study of fault feature extraction and early warning of rolling bearing vibration signal of generator sets is beneficial for the timely diagnosis of bearing faults, thus improving the service life of generators. In this paper, a combined EEMD-GRU-MC prediction method is adopted to predict the model based on GRU through the data decomposition of EEMD, and the predicted model residuals are corrected using MC. The analysis and diagnosis of the algorithmic model are used to determine the fault characteristics of the generator’s vibration signals for diagnosis, and the analysis and diagnosis of the characteristics are verified using experiments with publicly available data sets from the Bearing Data Center at the Paderborn University School of Mechanical Engineering in Paderborn, Germany. Diagnosis can be performed with an accuracy of 99.6% under condition load K
0 and 99.9% close to 100% under condition load K
3 . The accuracy is the highest at this point, while the diagnostic accuracy at conditional load K
1 is only 99.8%, the lowest at this point. However, the accuracy under condition load K
2 is also 99.5%. Therefore, the diagnostic accuracy with EEMD-GRU-MC is around 99%. In this study, the EEMD-GRU-MC model can be used to extract the fault characteristics and early warning of the rolling bearing vibration signal of generator sets.
Construction of customer-aware grid interactive service system based on neural network model
Authors: Zhou Baowei , Ling Yongxiang , Cao Sheng , Su Hongbang , Qi Xiaoxuan , Zhang Yaling 
Published: September 2023

Abstract
Neural network models have advantages in spatial and temporal information processing, which provide new ideas for the construction of customer-aware grid interactive service system. In this paper, firstly, the spatio-temporal fusion deep neural network model based on the attention mechanism is used to extract spatial and temporal information by convolutional neural network and gated recurrent neural network, respectively. The attention mechanism is also introduced to assign weights to various types of features to improve prediction accuracy. Secondly, the global information of the attention mechanism of the channel on the feature map is fully utilized to solve the problem of inadequate extraction of feature information from a single model, and then the grid interactive service system is constructed. The results show that the model proposed in this paper has higher prediction accuracy with root mean square error, coefficient of determination, and prediction accuracy of 0.972, 1.742, and 0.935, respectively. To verify the performance of the cache-based curve service in handling customer-perceived grid interactions, minute samples are created, where the maximum number of minute sample records is 3.5 million. Thus, it is shown that by introducing the attention mechanism can effectively improve the computational efficiency of the model, get better prediction results, and meet the demand for efficient and stable customer-aware interactive service system.