bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accurate retinal vessel segmentation in OCT-A images based on MsTCG-Net
Authors: Qi Sumin , Cui Baoyu , Zhang Mengqi , Meng Jing , Qi Bangqiang 
Published: December 2024

Optical coherence tomography angiography (OCT-A) is a non-invasive visualization imaging technology with high-resolution that can more clearly image tiny blood vessels. Using OCT-A imaging technology, certain ophthalmic diseases can be better diagnosed by the morphological changes of retinal blood vessels. However, the task of segmenting retinal vessels is still very challenging due to the large variation in vessel size and shape and the presence of noise. In this paper, by introducing a transformer with a self-attention mechanism, we propose a novel multi-scale transformer-based channel and global attention network (MsTCG-Net) for segmentation of blood vessels in retinal OCT-A images. In MsTCG-Net, transformer-based channel joint attention (TC) block and transformer-based global joint attention (TG) block are proposed to capture multi-semantic features from spatial and channel dimension and fuse global contextual semantic features from different layers of encoder. Experimental results show that our proposed method achieves better segmentation performance than other state-of-the-art U-Net-based methods.
Research on Minimum Unstick Speed Flight Test Method for Civil Aircraft
Authors: Wang Lei 
Published: December 2024

The minimum unstick speed (VMU) is defined as the calibrated airspeed at which an aircraft can safely lift off and continue its takeoff without any difficulties. The VMU flight test, characterized by low-speed and high angle of attack under the influence of ground effect, poses significant challenges and high risks, making it one of the most hazardous flight test subjects in civil aircraft flight test. The research on VMU flight test methods for civil aircraft is of utmost importance in strengthening the foundation of flight test technology, improving flight test efficiency, and ensuring flight test safety.
Research on Airworthiness Certification and Risk Control of Minimum Unstick Speed for Civil Aircraft
Authors: Dong Mingjia , Zhang Chao , Pan Ting 
Published: December 2024

VMU is the minimum speed at and above which the aircraft can safely lift off the ground and continue the takeoff, expressed in terms of calibrated airspeed, and is the basis for formulating other takeoff speeds of the aircraft. As a typical high risk flight test subject, the VMU test is a key concern of the Administrator during airworthiness certification. Based on the takeoff speeds section of CCAR25.107, combined with relevant Advisory Circular, this paper analyzes the requirements of the airworthiness clause of the VMU, analyzes the characteristics of the VMU, gives the airworthiness certification concerns, systematically analyzes the risk and the risk reduction measure of the VMU for civil aircraft. It can provide reference for verifying the airworthiness compliance of the VMU section of civil aircraft.
A positioning method for AUV based on guiding light source
Authors: Wang Kai , Ren Wenyuan , Duan Yaoquan , Du Hongwei 
Published: December 2024

This paper proposes a method for determining the position of underwater vehicles using light vision guidance. In order to solve the problem of limited perception distance and unclear underwater images, the illumination device is installed on the recovery platform as a light source to enhance the feature information of the recovery platform. The collected underwater light source images are enhanced by the dark channel prior defogging algorithm, and then the YOLOv5 algorithm is used to recognize the targets. Through experiments, it is verified that the image enhancement algorithm and target recognition algorithm are effective. Using the recognition results, the positioning accuracy of the binocular camera ranging algorithm is verified, and the results indicate that the proposed method can accurately determine the distance of the AUV relative to the recovery platform.
Power forecast of hydro–wind–photovoltaic hybrid system dual-driven by physics and data
Authors: Xu Weifeng , Chen Xi , Wang Han , Zhang Ze , Bai Haonan 
Published: December 2024

Short-term power forecast is an important way to guide operation of renewable energy stations and hybrid energy system (HES). The current studies focus on power forecast of single renewable energy station. However, the universality and applicability of power forecast model for HES is not clear. This study proposes a physics and data dual-driven day-ahead power forecast model for hydro–wind–photovoltaic HES. The WRF model and Xinanjiang model are used to drive meteorological and hydrological forecasts respectively. The hybrid variational mode decomposition - principal component analysis method is applied to further extract the features hidden in the meteorology or hydrology factors. The long short-term memory network is used to drive power forecast. China’s Guandi hydro–wind–PV HES is considered as a case study. Results show that the forecast root mean square error of dual-driven model decreases by 4.2% ~ 12.0% compared to single-driven model.
TRFSA-HQS: Transformer-based MRI Compressed Sensing Network with Frequency Domain Self-Attention
Authors: Mo Taiping , Zheng Mingfeng , Sun Peng , Li Jiangtao 
Published: December 2024

Compressive sensing (CS) can reconstruct undersampled magnetic resonance images, but its iterative optimization process tends to be computationally intensive and time-consuming. Convolutional neural networks (CNNs) have demonstrated impressive reconstruction performance through non-linear feature extraction and mapping capabilities. However, CNNs often struggle to effectively learn and capture global dependencies in the data. Therefore, constructing a MRI reconstruction method that meets clinical real-time imaging and captures dynamic global correlation is crucial in fast and high-precision MRI tasks. We propose a deep unfolding network (TRFSA-HQS) for fast and accurate CS reconstruction, which combines frequency domain self-attention (FSA) based Transformer and half-quadratic splitting (HQS) iterative optimization scheme. TRFSA-HQS adopts an iterative scheme based on HQS to effectively decouple and update optimization problems. The decoupled data subproblems are updated by minimizing the objective function with competitive terms, while the regularization subproblems are updated using the TRFSA deep prior network. The TRFSA module employs an asymmetric UNet architecture, where the encoder and decoder utilize a frequency-domain discriminative feedforward network (DFFN) and FSA. The DFFN selectively extracts deep features from different frequency components, while the FSA captures global dependencies in the frequency domain. The experiment demonstrate that the proposed model achieves an average reconstruction PSNR of 35.11dB on a 0.2 sampling rate test set on FastMRI knee joint data, with an inference time of 0.74s. It has good reconstruction performance and noise robustness, meeting the clinical real-time imaging requirements.
On the solution of seven-precision-point path synthesis of planar four-bar linkages based on the solution region methodology
Authors: Zhao Song , Liu Wupeng , Liu Guangzheng , Zhao Yanhui Zhao , Guo Xiaoyan , Zhou Jiajin , Wang Yan 
Published: December 2024

This paper makes further research on the application of the solution region synthesis methodology (SRSM) in path synthesis of planar four-bar linkages. Detailed process of establishing the solution region for seven precision-point path synthesis is illustrated. In order to obtain the solution region where one point corresponds to one linkage and the feasible solution region where linkages distributes different zones according to curve types, this paper compares four different solution region schemes and finally establishes the solution region with B1 as the reference. Compared with the eight-point case, the range of the solution region in this paper is larger and the statistics on the feasible solutions is more than twice of that in the case with eight points. Moreover, the feasible solutions obtained in this case have more curve types.
Research on the approximate equation inversion method for the physical properties parameters of OA media with decoupling of stress and fracture effects
Authors: Fan Zihang , Zong Zhaoyun 
Published: December 2024

Pre-stack seismic inversion is an effective method for predicting reservoir physical parameters. At the same time, azimuth seismic data is a reliable source of information for predicting underground reservoir elastic parameters, fracture parameters, and interface parameters and has rich underground information. However, it is difficult to determine whether the anisotropy of the reservoir is caused by stress or the original fractures. Therefore, distinguishing the influence of fractures and initial stress in the reservoir from azimuth seismic data is the key to predicting reservoir parameters. Because of the problem of insufficient consideration of the influence of stress and fracture weakness in OA media, based on Born's first-order scattering theory and Bayesian inversion framework, an approximate equation for the reflection coefficient decoupling fracture anisotropy and stress-induced anisotropy was constructed, and a linear inversion method based on the approximate equation was developed, realizing the exploration of methods for predicting fracture weakness and stress action parameters. Model testing and actual work area application have verified the feasibility and practicability of predicting underground medium parameters from seismic response characteristics.
Simulation Study of Dual Source Heat Exchange Evaporator
Authors: Wang Dan , Zhao Qi , Gu Shijie , Ma Shuang , Jin Hongwen , Chang Huinan 
Published: December 2024

This article proposes a dual source heat exchange (DSHE) evaporator, which adopts a sleeve type heat exchanger design with external fins.A dual source heat exchange evaporator was simulated using Fluent software under different inlet velocity and temperature parameters,Analyzed the simulation results under typical working conditions,The temperature difference between the inlet and outlet of antifreeze is 1.93℃~4.28℃,The temperature difference between the inlet and outlet of the refrigerant is 6.39℃~12.53℃,The temperature difference between the inlet and outlet of air is 0.66℃~1.7℃.
Discriminating Homecoming Visitors Using Mobile Signaling Data
Authors: Tang Yonggang , Lin Huijie , Lin Huijie , Mo Mingjian 
Published: December 2024

This study utilizes mobile signal data as an emerging data source, aiming to construct a framework that can efficiently distinguish homecoming visitors from other types of tourists. The rich behavioral features contained in mobile signal data are deeply analyzed. A two-stage clustering method based on machine learning, which integrates multiple aspects such as feature engineering, model construction, and performance evaluation is designed to ensure the accuracy and generalization ability of classification results. The main data source is the signaling data of the three major telecommunications operators in China. Using the signaling data from China's three major telecommunications carriers as the primary data source, this study verified the number of tourists in the Guangxi, as well as in Nanning, Guilin, and Yulin cities during the 2019 National Day Golden Week. The results indicate that the method presented in this paper offers a viable new approach for the statistical analysis and data mining of large-scale tourism figures.
Case report and literature review of DYNC1H1 gene in Chinese literature
Authors: Peng Qingsong , Yuan Hui 
Published: December 2024

This paper presents an analysis of 15 cases (families) of Dync1h1-related genetic disorders reported in Chinese literature. The study focuses on the clinical manifestations, genetic mutations, and potential mechanisms underlying these diseases. Through a comprehensive review of the cited literature, they aim to provide insights into the spectrum of Dync1h1 gene disorders and their impact on patient health. The analysis highlights the importance of accurate genetic diagnosis in guiding clinical management and genetic counseling for affected individuals and their families.
Assessment of land use efficiency under carbon emission constraint: An empirical study of Pearl River Delta, China
Authors: Zeng Jinrong , Rong Qiangqiang , Hong Wuyang , We Fan 
Published: December 2024

Land use efficiency (LUE) is the comprehensive reflection of the input and output in the process of land resource utilization. However, carbon emission during this process will lead to a decrease in LUE. It is necessary to evaluate LUE under carbon emission constraint for urban sustainable development. Although the carbon emission and efficiency of land use have been extensively studied, few researches considered the uncertainties in carbon emissions when evaluating LUE. In this study, a comprehensive assessment model of LUE was proposed. Interval parameter is introduced to a super efficiency slack-based measurement (SBM) model, leading to an assessment method of interval LUE, which can analyze the impact of carbon emission on LUE. A case study in Pearl River Delta (PRD) was conducted from 2005 ~2020. Results revealed that the overall carbon emissions of land use in the PRD increased significantly during the study period. Particularly, Zhuhai and Huizhou had a relatively larger increase. In terms of the total amount of carbon emission, it was relatively higher in Guangzhou and Shenzhen than the other cities in the region. Taking the carbon emission into account, the LUE of PRD still improved, especially in Shenzhen, Guangzhou, Foshan, and Jiangmen. However, an opposite trend was found for the LUE of Huizhou and Zhaoqing, changing from effective to ineffective. The LUE of Zhuhai and Zhongshan was always effective, while that of Dongguan was ineffective during the study period. In conclusion, the assessment method of LUE considering carbon emissions should be used to promote the efficient use of land resource. The results of the case study in this research can also provide decision-making reference for PRD and other urban agglomerations to improve LUE.
Optimal allocation of low-impact development facilities for urban runoff reduction
Authors: Wen Fan , Rong Qiangqiang , Gu Zhihui , Zeng Jinrong 
Published: December 2024

In the context of global climate change and urbanization development, the intensity and frequency of extreme rainfall events have increased significantly, while the proportion of impermeable surfaces in cities has been increasing. These changes have led to frequent urban flooding, which seriously affects the safety of people's lives and properties and restricts the high-quality development of urbanization. Low-impact development (LID) is an important way to effectively mitigate urban flooding. How to obtain the optimal runoff control effect through the deployment of LID facilities in the construction of sponge cities is an urgent problem to be solved. This study proposed a novel implementation framework for LID optimization based on SCS-CN model and used data from Shenzhen to verify the effects. The results shows that the optimization of LID facilities proves to be effective in flooding mitigation. The results of this study can support decision-making for urban flood mitigation and sponge city construction.
Implementasi pendidikan karakter untuk mencapai mutu pendidikan di SMP N 4 Satu Atap Pakis Kabupaten Magelang
Authors: Suhada Imam , Supriyoko Supriyoko 
Published: December 2024

The purpose of this study is to describe the implementation of caharacter education curricullum in the context of achieving quality education which includes implementation strategies, the relationship of character education with the quality of education and the role of pricipals and the teachers in student character building in Primary school Satu Atap Pakis Magelang. This research was a descriptive qualitative study. Data sources were obtained from in-depth interviews with 4 informants and 5 additional informants. Source of supporting data obtained from observation and documentation. Data collection techniques by interviewing, observing and documenting. Data from interviews, observations and documentation were analyzed descriptively. The data analysis technique in this study used by reducing data, displaying data and verifying research data. As for the test of the validity of the data of this study, namely the extension of observation, increasing perseverance, triangulation and member check.The results of the study indicated that the character education implementation strategy includes the integration of building character values in all subjects and teaching and learning activities both intra-extracurricular, character education through routine habituation, stakeholder involvement and the existence of building character values ( religious values, honesty, love for peace, hard work, creative, respect for achievement, communicative, fond of reading, environmental care, discipline, tolerance, responsibility, democratic, independent, national spirit, self-confidence and social care) in school. There was a close relationship between character education and quality of education as evidenced by the achievements obtained by students both academically and non-academically. The role of principals and teachers includes policy makers, motivators, and role models. There needs to be an increase in stakeholder involvement and communication in building character education values. In addition, there is need to improve the quality of the implementation of integration of activities in character education at SMPN 4 satu atap Pakis Magelang.
Analisis profesionalitas guru berdasarkan pengalaman mengajar, motivasi berprestasi, dan ketersediaan sarpras
Authors: Istinuryanti Istinuryanti 
Published: December 2024

This study aims to determine : 1)how much influence the teaching experience, achievement motivation, availability of infrastructure on the professionalism of elementary school teachers in Paliyan District; 2) how much influence does the teaching experience have on the professionalism of elementary school teachers in Paliyan District; 3) how much influence does achievement motivation have on the professionalism of elementary school teachers in Paliyan District; 4) how much influence does the availability of infrastructure facilities on the professionalism of elementary school teachers in Paliyan District. This research is quantitative approach. The respondents are 176teachers of elementary school teachers in Paliyan Districtwhich spread in twenty elementary schools. The amount sample is 110 teachers determined by proposional random propotional sampling technique. Data are collected using questionnaires. Data analysis includes multiple regression analysis using SPSS 24 which coundcts normality test, , linierity test, and multicolinierity test as the pre requeisite. From the data analysis and some discussions, it is concluded that : 1) The teaching experience, achievement motivation, and availability of infrastructure contribute positively and significantly to the professionalism of the teacher which means having a long teaching experience, strong achievement motivation and the availability of supporting infrastructure, the teacher's professionalism will increase; 2) There is a positive and significant contribution of teaching experience to teacher professionalism, meaning that the longer the teaching experience possessed by the teacher, the more professional the teacher will be; 3) There is a positive and significant contribution of achievement motivation towards teacher professionalism, meaning that the stronger the achievement motivation possessed by the teacher, the more professional the teacher will be; 4) There is a positive and significant contribution to the availability of available infrastructure, so that the professionalism of teachers will increase.
Penerapan Algoritma C4.5 Untuk Prediksi Faktor Risiko Obesitas Pada Penduduk Dewasa
Authors: Yamantri Arief Bayu , Rifa’i Aris Ahmad 
Published: December 2024

Obesitas merupakan masalah kesehatan yang terus meningkat dan mempengaruhi kualitas hidup jutaan orang di seluruh dunia. Tujuan dari penelitian ini adalah untuk mengidentifikasi faktor-faktor risiko yang berkontribusi terhadap obesitas pada penduduk dewasa di Indonesia dengan menggunakan algoritma C4.5. Algoritma C4.5 adalah metode pembelajaran mesin yang menghasilkan pohon keputusan berdasarkan atribut-atribut yang relevan. Dalam penelitian ini, data demografis, gaya hidup, dan faktor kesehatan dikumpulkan dari 1000 responden dewasa melalui survei dan pemeriksaan kesehatan. Atribut yang dianalisis meliputi usia, jenis kelamin, indeks massa tubuh (IMT), tingkat aktivitas fisik, pola makan, dan riwayat kesehatan keluarga. Setelah proses pelatihan dan pengujian model, pohon keputusan yang dihasilkan menunjukkan bahwa pola makan yang buruk dan rendahnya tingkat aktivitas fisik merupakan faktor utama yang berkontribusi terhadap obesitas. Selain itu, faktor-faktor seperti usia dan riwayat kesehatan keluarga juga memiliki pengaruh signifikan. Model C4.5 yang dihasilkan memiliki akurasi prediksi sebesar 85%, menunjukkan potensi algoritma ini dalam mengidentifikasi individu yang berisiko tinggi mengalami obesitas. Hasil penelitian ini diharapkan dapat memberikan wawasan bagi pembuat kebijakan dan tenaga kesehatan untuk merancang intervensi yang lebih efektif dalam pencegahan dan penanganan obesitas. Penelitian ini juga menyarankan penerapan lebih lanjut pada populasi yang lebih luas untuk meningkatkan generalisasi hasil.

Obesity is a health problem that continues to increase and affects the quality of life of millions of people around the world. The aim of this research is to identify risk factors that contribute to obesity in the adult population in Indonesia using the C4.5 algorithm. The C4.5 algorithm is a machine learning method that produces a decision tree based on relevant attributes. In this study, demographic data, lifestyle and health factors were collected from 1000 adult respondents through surveys and health examinations. Attributes analyzed include age, gender, body mass index (BMI), physical activity level, diet, and family health history. After the process of training and testing the model, the resulting decision tree shows that poor diet and low levels of physical activity are the main factors contributing to obesity. Additionally, factors such as age and family health history also have a significant influence. The resulting C4.5 model had a prediction accuracy of 85%, demonstrating the potential of this algorithm in identifying individuals at high risk of obesity. It is hoped that the results of this research will provide insight for policy makers and health workers to design more effective interventions in preventing and treating obesity. This study also suggests further application to broader populations to increase the generalizability of the results.