bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impacts of climate change on hydrological hazards: mechanisms, predictions and coping strategies
Authors: Lu Yan 
Published: March 2024

Abstract
Climate change is triggering more frequent and intense hydrological disasters, which significantly impact society and economy. This paper discusses the specific impacts of these changes on hydrological hazards. It analyzes the early warning mechanism, risk assessment, and coping strategies to provide a scientific basis for effective response. This paper aims to explore the impact of climate change on hydrological disasters and develop effective prediction and response strategies. The effects of climate change on the mechanisms of hydrological disasters, risk assessment theory, influencing factors, and early warning mechanisms is studied through a comprehensive analysis method. According to the study, climate change significantly impacts the frequency and intensity of hydrological disasters. In a particular region, there has been a 30% increase in the frequency of floods caused by heavy rainfall over the past 20 years, leading to a 40% increase in economic losses. In addition, climate model-based risk assessment methods effectively predicted the potential impacts of these disasters. The study revealed that enhancing early warning systems and raising public awareness can reduce catastrophe risk. Climate change significantly impacts hydrological hazards, and more systematic and integrated management strategies are needed to reduce their impacts.
Research on Substation Network Security Situational Awareness Strategy and Equipment Remote Operation and Maintenance
Authors: Bai Jing , Jiao Jianlin , Han Meng , Zhou Xianfei , Liu Chao 
Published: March 2024

Abstract
Substation network security is the key to maintaining the stable operation of power systems. In the face of growing threats of network attacks, traditional security protection measures have been brutal to meet the needs of modern power systems. Research on substation network security, situational awareness strategies, and remote operation and maintenance of equipment is essential to improve network defense capability and ensure the continuity and reliability of power supply. This study explores effective security situational awareness methods and remote operation and maintenance techniques to provide new solutions for substation network security. This paper builds an efficient network attack detection model by introducing linear discriminant analysis (LDA) and radial basis function (RBF) neural networks. The experiment uses the KDD Cup99 dataset, which is preprocessed to provide the model training and testing data. The LDA-RBF model in this paper outperforms the traditional RNF neural and BP neural networks regarding recognition rate. Specifically, the recognition rate reaches 90.2% for the Smurf attack and 100% for the Ipsweep attack. The proposed model of the study also performs well in terms of leakage and false alarm rates, with an overall recognition rate of 97.00%. This study proposes a network security situational awareness strategy and equipment remote operation and maintenance method that can effectively enhance substation networks’ security and operation and maintenance efficiency.
Deep Learning Model Based Behavioural Recognition Technology for Electricity Operators and Its Safety Guardianship Analysis
Authors: Ye Ligang , Xu Guohui , Zhu Jiyang , Wu Shengli , Qiu Kaiyi , Li Jingya , Zhang Zhengchao 
Published: March 2024

Abstract
This study leverages the Openpose system to capture skeletal key points of electric power operators, simplifying network complexity by sharing convolutional layers during the ReLU activation phase. We introduce a graph convolutional network (GCN) to model these skeletal sequences, creating a spatio-temporal deep learning approach for behavior recognition. Tested on a relevant dataset, our Openpose-GCN network demonstrates stability with a training loss of 0.11 after 700 iterations, achieves over 90% accuracy in recognizing operator actions and behaviors, and maintains a recognition error below 0.003 for operations with varying risk levels. These findings underscore the potential of our approach to enhance electric power operation safety through real-time risk warning and control.
Applying Deep Learning Algorithms for Automatic Recognition and Transcription of Texts in Oracle Bones and Golden Texts
Authors: Qiao Yingjie , Xing Lizhi 
Published: March 2024

Abstract
This paper explores applying deep learning techniques for automatically recognizing and transcribing oracle bone and gold texts. We significantly enhance model recognition efficiency by leveraging the power of Generative Adversarial Networks (GANs) for image data enhancement and the Pix2Pix model for text repair. Our approach integrates the ResNet50 model for robust feature extraction with unsupervised domain adaptation, utilizing multiple pseudo labels to achieve efficient text recognition and transcription. We improve the model’s repair capabilities by generating hard-to-distinguish sample data through GANs and employing a U-Net-based text repair model enhanced with dense connectivity and spectral normalization. Further, combining ResNet50 for feature extraction and advanced domain adaptation techniques strengthens the model’s generalization. Our results on the Oracle dataset show an increase in recognition accuracy from 82% to 94.5%, highlighting the effectiveness of our image enhancement strategies. The ResNet50 extractor outperforms others across various Intersection over Union (IoU) metrics, establishing its feature extraction superiority. In real-world scenarios, testing with a combined Oracle and Jinwen dataset yields a recognition accuracy above 80%, demonstrating our model’s ability to effectively fulfill the recognition task. This research underscores the potential of deep learning algorithms in automating the recognition and transcription of ancient texts, offering a novel solution that significantly boosts recognition accuracy through a synergistic blend of image enhancement, feature extraction, and domain adaptation techniques.
Research on the integration and development of public management strategies and rural e-commerce based on the integration model
Authors: Li Xiaoxiao , Zhuo Pan , Zhang Hua 
Published: March 2024

Abstract
This paper focuses on the symbiotic development of rural e-commerce and logistics by exploring the intersection of fusion modeling with public management. By leveraging data fusion and logistics optimization, we address the burgeoning needs of rural e-commerce, presenting a deep learning approach that incorporates Deep Belief Networks (DBNs) and weight-sharing to achieve a 40% data compression rate. This advancement significantly lowers storage and energy costs while enhancing computational efficiency. Furthermore, we devise a rural e-commerce logistics and distribution model optimized through an ant colony algorithm to maximize profits and demand coverage. The application of this Model has led to a 20% increase in profits and a surge in demand coverage to 90%, showcasing the efficacy of fusion models in streamlining rural e-commerce logistics. These insights contribute to the broader discourse on innovative public management strategies.
CiteSpace-based Visualization and Analysis of Knowledge Graph in International Supply Chain Domain
Authors: Yang Xiaopeng 
Published: March 2024

Abstract
Along with globalization and technological advances, the complexity and dynamics of international supply chains are increasing. Using CiteSpace to visualize and analyze the knowledge map of the global supply chain helps to deeply understand the industry’s development trends and essential elements. The knowledge map of the international supply chain field is visualized and analyzed using CiteSpace software in this paper, which uncovers the key components and development trends in the field. The study involves collecting and analyzing relevant literature from 2009 to 2021, and applying techniques such as word frequency analysis, co-occurrence network construction, and spectral clustering algorithms to map the knowledge map. Supply chain management, supply chain resilience and risk management are the most popular topics in the supply chain field, in which the word “supply chain management” has a co-occurrence frequency of 485 times, with a centrality of 0.457. Using the spectral clustering algorithm, we identify several key research clusters and find that “supply chain security” has become a recent research topic. Security” has become a hot research topic recently. Research in the field of supply chain is gradually focusing on improving chain flexibility and reducing risks. There is increasing interest in the trend of supply chain futurization and intelligence.
Knowledge Mapping Applied to the Construction of a Theoretical Resource Base for Teaching English at the University Level
Authors: Xie Xia 
Published: March 2024

Abstract
In the evolving field of educational technology, knowledge mapping has emerged as a pivotal tool for university English education. This study examines its role in building a theoretical resource base to enhance the efficiency of organizing, accessing, and utilizing teaching materials. This research constructs a knowledge graph for English teaching resources by employing a seven-step process to create a domain ontology and an enhanced TF-IDF algorithm for keyword extraction. Results show the knowledge graph significantly boosts information retrieval accuracy and user satisfaction. The experimental group reported a 25% increase in learning efficiency, a 30% enhancement in the quality of learning outcomes, and a 12.63% rise in average grades, outperforming the control group. The findings suggest knowledge mapping substantially benefits the development of a theoretical resource base for university English teaching, improving teaching and learning quality.
Research on the Path of Improving Physical Education Teaching in Colleges and Universities Based on Deep Learning
Authors: Yang Hui , Xu Xiaoqin , Shu Bichao 
Published: March 2024

Abstract
This research investigates the application of deep learning to college physical education, proposing an innovative teaching methodology that significantly improves outcomes by fostering students’ practical skills and innovation. We introduce a structured deep learning model encompassing four stages and twelve instructional steps, employing an “independent-cooperative-inquiry” modality in real-world teaching scenarios. Through empirical assessment in various T colleges, notable enhancements were observed in student attitudes toward physical education, collaborative spirit, and physical health, culminating in a 92% satisfaction rate with the teaching approach and an 85% boost in learning effectiveness. Adopting a deep learning-based pedagogy in physical education elevates teaching quality and enriches students’ comprehensive abilities, charting a new course for the pedagogical advancement in this field.
A study of the impact of the two-child welfare policy on the investment cost of urban families’ children’s education--an empirical test based on the HOV model
Authors: Wang Jing 
Published: March 2024

Abstract
In recent years, the aging of the population and the tightening of the labor market have made the relaxation of the two-child policy a pivotal measure to promote population growth. As an essential part of socio-economic development, urban families’ changes in the cost of their children’s education investment under the two-child policy are significant in understanding the policy effect and optimizing the demographic structure. This paper analyzes the impact of the two-child welfare policy on urban families’ education investment costs using the HOV model to provide data support and decision-making reference for policy formulation. The research methods include analyzing the distribution of educational resources, predicting the impact of the two-child policy on the cost of educational investment using the HOV model. The cost of educational investment for urban families increased significantly after the two-child policy was implemented. The average price of educational investment increased by 15%, and the impact was more noticeable for low-income families. The two-child policy is beneficial for population growth but also increases urban families’ educational burden. It is recommended that the Government optimize the relevant welfare policies to reduce the burden on families, and at the same time improve the allocation efficiency of educational resources to ensure the sustainability and fairness of the policy.
Synergistic emulsification of polyetheramine/nanofluid system as a novel viscosity reducer of acidic crude oil
Authors: Cao Yang , Guo Yanlin , Wu Tao , Sun Dejun 
Published: March 2024

Abstract
Oil is a critical raw material for energy and industry, the depletion of conventional oil reserves necessitates efficient extraction and production of unconventional resources like acidic crude oil. However, its high viscosity poses significant challenges for transportation and processing. To address these challenges, this study developed a novel emulsion viscosity reducer. We designed a nanofluid based on a synergistic polyetheramine/nanofluid system consisting of alkyl ethoxy polyglycosides (AEG) as a green surfactant, SiO2 nanoparticles, and an organic alkali polyetheramine. The mixture was evaluated for its viscosity reduction and emulsification performance with acidic crude oi obtained from Qinghe oil production plant in Shengli Oilfield. The results showed that the optimized viscosity reducer achieved a remarkable reduction rate of 98.1% at 50◦C in crude oil viscosity from 6862 mPa·s to 129 mPa·s. This demonstrated the reducer effectively transformed acidic crude oil into a low viscosity oil-in-water (O/W) emulsion with high stability. Furthermore, the core imbibition simulation tests demonstrated that the viscosity reducer could improve the recovery of acidic crude oil from 29.6% to 49.4%, indicating the potential application of the optimized viscosity reducer in the exploitation of acidic crude oil. In conclusion, this study developed a novel emulsion viscosity reducer, which can reduce the viscosity and improve recovery of acidic crude oil by emulsifying into O/W emulsion. The optimized formula has potential for practical application in the exploitation of acidic crude oil.
Alat Permainan Edukatif untuk Meningkatkan Perkembangan Nilai Agama dan Moral Anak Usia Dini
Authors: Hasibuan Afrah Nadhilah 
Published: March 2024

Tujuan dari penelitian ini adalah untuk meningkatkan alat permainan edukatifdalam pendidikan moral dan agama pada anak usia dini. Penelitian ini menggunakan pendekatan Classroom Action Research (CAR) untuk membantu pendidik anak usia dini dalam menanamkan nilai moral dan agama pada siswanya. Penelitian ini dilakukan di bidang pendidikan anak usia dini di TK Mentari School. Kemajuan signifikan dalam hasil pembelajaran teramati selama siklus I dan II. Rata-rata nilai anak pada pertemuan pertama siklus adalah 52, dengan tingkat kelengkapan sebesar 25%. Nilai rata-rata meningkat menjadi 61 setelah pertemuan kedua, menunjukkan tingkat kelengkapan sebesar 42%. Pada pertemuan ketiga, perkembangan semakin baik dengan tingkat kelengkapan sebesar 50% dan nilai rata-rata 63. Siklus II menunjukkan lebih banyak kemajuan, dengan pertemuan pertama mencatat rata-rata nilai anak sebesar 67 dan tingkat kelengkapan 58%. Pertemuan kedua menunjukkan kemajuan lebih lanjut, dengan nilai rata-rata 75 dan kelengkapan mencapai 75%. Dengan tingkat kelengkapan mencapai 91% dan nilai rata-rata 88, pertemuan terakhir siklus II menunjukkan kemajuan yang mencolok dan menunjukkan efektivitas intervensi pendidikan.
Tahapan pengembangan koleksi dalam perspektif G. Edward Evans di Perpustakaan STIKES Tri Mandiri Sakti Bengkulu
Authors: Indriyani Meyza , Zulaikha Sri Rohyanti 
Published: March 2024

This article discusses the stages of collection development in the perspective of G. Edward Evans at the STIKES Tri Mandiri Sakti Library in Bengkulu. The purpose and benefits of this research are to help and make it easier for librarians to carry out collection development activities. The research method uses field research with a qualitative approach. Data collection methods through observation and interviews. Data analysis through data reduction, data presentation, and conclusions. The results showed, a) user analysis: students, lecturers, and employee staff, b) collection development policies: cooperation between libraries, budgets from the Foundation, procurement of collection types according to the health sector, c) collection selection: collection types, collection criteria, selection tools, and selection methods, d) collection procurement: purchases, donations or gifts, exchanges, and self-publications, e) collection weeding: damaged collections, not worth using, and the publication of the final project or thesis under the last 5 years, f) evaluation once in 4 years.
Peran Adat Dalihan Natolu dalam Kegiatan Moderasi Beragama di Tapanuli Bagian Selatan
Authors: Kamaluddin Kamaluddin 
Published: March 2024

Secara gelobal saat ini, kehidupan antar ummat beragama sedang mengalami konflik, yaitu antara ummat Islam dengan Yahudi di Yerussalem, antara ummat Islam dengan ummat Hindu di India dan ummat Islam dengan China di Rohingya.Tujuan penelitian ini untuk melihat hubungan antar ummat Islam dan Kristen (moderasi beragama) dan bagaimana peran adat Dalihan Natolu dalam pesta pernikahan (Siriaon) dan kemalangan (Siluluton). Peneiltian ini dilaksanakan di wilayah Tapanuli Bagian Selatan, yakni di Kota Padangsidimpuan, Kabupaten Tapanuli Selatan, Kabupaten Padang Lawas Utara dan di Kabupaten Mandailing Natal. Di daerah ini toleransi antar ummat beragama berjalan sangat baik dan belum pernah terjadi konflik, padahal jumlah ummat Islam 85 % sedangkan Kristen hanya 15 %. Dengan pendekatan antropologi, sosiologi dan agama, data dikumpulkan dan disajikan secara deskriptif kualitatif. Sumber data primer adalah tokoh agama Islam dan Kristen, sumber data sekunder adalah Kepala desa, lurah serta masyarakat. Melalui observasi dan wawancara menunjukkan hasil bahwa faktor-faktor yang membentuk moderasi beragama antara lain ialah faktor konversi agama, pernikahan silang, faktor adat Dalihan Natolu dan faktor agama, sehingga masyarakat hidup toleran, kerja sama, musyawarah, gotong royong, membenci kekerasan, berkeadilan dan melaksanakan adat Dalihan Natolu. Dalihan Natolu berperan aktif dalam pelaksanaan adat-istadat. Kahanggi, Anak Boru dan Mora tidak dibeda-bedakan dalam pelaksanaan adat siriaon (pernikahan) dan di kemalangan (siluluton). Jika pesta di rumah muslim, maka makanan tidak ada masalah, sedangkan apabila pesta di rumah kristen, kambing atau kerbau dipotong oleh muslim dan dimasak oleh muslim. Sedangkan bagi ummat kristen yang menggunakan adat Toba, mereka memasak sendiri untuk kristen, sedangkan untuk umat Islam dibeli di rumah makan dalam bentuk nasi kotak. Kahanggi berperan sebagai pendukung utama bagi suhut dalam suatu pesta, Anak boru juga berperan sebagai penanggung jawab dalam kesuksesan pesta, dan mora berperan sebagai pembimbing dan pemberi dukungan dalam pesta. Dalihan Natolu mengamalkan nila-nilai adat- istiadat Angkola seperti “Itte disiriaon, tangi disiluluton.” Salaklak sasikkoru, sasanggar saria-ria, saanak jana saboru, suang songon namarsada ina”. “Songon siala sampagul, rap tuginjang raptu toru, muda malamun saulak lalu muda madabu rap margulu”. ”Salumpat Saindege, sapangambe sapanaili, sahaccit sapakkilala”.(Kehidupan yang penuh kasih sayang dan saling menghormati dan kerjasama dalam hidup bermasyarakat serta seiya sekata dalam musyawarah).
REKLAMASI LAHAN BEKAS PENAMBANGAN BATU PASIR
Authors: Kusdarini Esthi , Mabuat Imelda Srilestari , Redanto Putri Fairus Atika 
Published: March 2024

Â AbstrakCV. BS melakukan penambangan batu pasir yang menyisakan lahan tidak rata dan tandus. Penelitian ini bertujuan: 1) mendapatkan rona awal lahan pertambangan: peruntukan lahan, kelandaian topografi, elevasi, 2) Â menentukan rona akhir lahan penambangan: bentuk lahan pasca penambangan, 3) rancangan teknis reklamasi: luas lahan reklamasi, waktu reklamasi, penatagunaan lahan, bentuk penampang dan dimensi saluran drainase, revegetasi, pemeliharaan. Metode yang digunakan adalah pengamatan, wawancara, pengumpulan data sekunder dan perhitungan matematis dengan bantuan tools software. Hasil penelitian menunjukkan bahwa: 1) rona awal area pertambangan berupa pertanian lahan kering dengan vegetasi: rumput liar, kelandaian topografi: 10o â€“ 20o,dan ketinggian elevasi: 41 â€“ 61 mdpl, 2) rona akhir area pertambangan berupa lahan dengan satu jenjang dengan ketinggian 8 m dan kemiringan 60o, 3) luas area reklamasi sebesar 4,42 Ha; penimbunan lahan untuk membentuk teras bangku, selanjutnya dilakukan penebaran tanah pucuk setebal 40 cm atau 17.680 m3, penampang saluran drainase berbentuk trapesium dengan kedalaman (h) 0,5 m, lebar bawah (B) 0,3 m, koefisien dinding saluran (n) 0,03, dan sudut kemiringan (ÆŸ) 60o; revegetasi membutuhkan bibit Â pohon sengon: 1770 buah dan kacang ruji: 13,26 kg; pemeliharaan membutuhkan pupuk urea: 354 kg dan pupuk kandang: 885 kg.Kata kunci: batu pasir, reklamasi, sengon.AbstractCV. BS carries out sandstone mining which leaves uneven and barren land. This research aims to: 1) obtain the initial baseline of mining land: land use, topographic slope, elevation, 2) determine the final baseline of mining land: post-mining land form, 3) reclamation technical design: area of reclaimed land, reclamation time, land use, shape cross-section and dimensions of drainage channels, revegetation, maintenance. The methods used are observation, interviews, secondary data collection and mathematical calculations with the help of software tools. The research results show that: 1) the initial baseline of the mining area is dry land farming with vegetation: wild grass, topographic slope: 10o â€“ 20o, and elevation height: 41 â€“ 61 meters above sea level, 2) the final baseline of the mining area is land with one level of elevation. 8 m and a slope of 60o, 3) the reclamation area is 4.42 Ha; filling the land to form a bench terrace, then spreading top soil 40 cm thick or 17,680 m3, the cross-section of the drainage channel is trapezoidal with a depth (h) of 0.5 m, bottom width (B) 0.3 m, channel wall coefficient (n) 0.03, and tilt angle (ÆŸ) 60o; revegetation requires sengon tree seeds: 1770 fruits and ruji nuts: 13.26 kg; maintenance requires urea fertilizer: 354 kg and manure: 885 kg.Keywords: sandstone, reclamation, sengon.
Peranan Orang Tua di Rumah Dalam Pembelajaran Online SD Negeri 220 Cinnong Kecamatan Sibulue Kabupaten Bone
Authors: Satriani DH Satriani DH , Adnan, K Adnan, K , Sahriani Sahriani 
Published: March 2024

Penelitian ini memiliki tujuan tentang gambaran peran orang tua dalam membimbing siswa di rumah beserta hambatan yang dihadapi orangtua selama pembelajaran online UPT SD Negeri 220 Kabupaten Bone. Penelitian ini menggunakan metode kualitatif deksriptif di UPT SD Negeri 220 Cinnong Kecamatan Sibulue Kabupaten Bone. Subjek penelitian orang tua siswa SDN 220 Cinnong Kecamatan Sibulue Kabupaten Bone berjumlah 6 orang. Teknik pengumpulan data wawancara, kuisoner. Analisis data reduksi data, penyajian data dan grafik kesimpulan / validasi. Hasil orang tua juga berperan sebagai seorang fasilitator yang menyediakan fasilitas yang digunakan anak untuk belajar seperti handphone dan kota internet sebagai bantuk dukungan mereka kepada anak untuk tetap mengikuti pembelajaran dengan baik. Hambatan yang dialami orang tua adalah mereka tidak bisa selalu menemani anak mereka elajar di rumah, anak harus mengikuti pembelajaran dengan sendiri tanpa pendampingan dari orang tuanya. Tak jarang juga ada beberapa orang yang tidak memahami materi pelajaran yang diberikan.Kata kunci : Pembelajaran Online, Peran Orangtua, Hambatan yang dialami.