bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fatigue Driving Detection Based on Facial Multi-Information Feature Fusion
Authors: Qu Wenjing , Wang Zhongsheng 
Published: October 2024

Abstract
Driver fatigue driving risk detection is one of the important areas of road traffic safety research in China. According to statistics, more than 40% of China’s traffic accidents every year are related to driver fatigue. In order to reduce this risk, this paper proposes a new method based on facial multi-information feature fusion to realize real-time fatigue driving detection. The method includes using the camera to capture the driver’s face image in real time, combining the face recognition in Dlib library and the detection of 68 key points, and implementing the face detection through OpenCV. Further, the opening and closing states of eyes and mouth were analyzed based on EAR and MAR algorithms, and a reasonable threshold was set to judge fatigue behavior. The HPE head pose estimation method is used to judge the fatigue state by considering the pitch Angle and roll Angle information. Finally, the improved rough set theory comprehensive evaluation method is used to carry out decision fusion processing on the feature results, and intuitively display the system detection results, which is convenient to evaluate the fatigue state of the current driver. The experimental results show that the multi-feature fusion detection method has good real-time performance, the accuracy rate is 94.55%, and the fatigue state can be detected quickly and accurately under various driving attitudes.
UAV Vehicle Detection System Based on YOLOv8
Authors: Chang Hao , Wang Zhongsheng 
Published: October 2024

Abstract
To utilize the drone vehicle detection technology to observe the road traffic conditions in real-time, thereby improving the operational effectiveness and safety of the traffic system, this paper adopts a vehicle target detection algorithm based on YOLOv8. YOLOv8 is the latest iteration developed by Ultralytics, which has further improvements and enhancements compared to YOLOv5. In the backbone network, YOLOv8 employs a C2f structure with richer gradient flow, boosting feature selection capabilities, and enhancing target detection performance and accuracy; In the detection head, YOLOv8 utilizes a Decoupled Head design and uses an improved Anchor-Free method to reduce computational complexity while improving detection efficiency; In terms of loss function, YOLOv8 utilizes the The Task-Aligned Assigner positive sample allocation strategy, and adds the Distribution Focal Loss to improve the model’s generalization ability. This paper divides the vehicles data set into 5 types, trains it using a pre-training model, and optimizes the network parameters through multiple iterations to achieve better detection performance. The experimental results indicate that YOLOv8 reaches the mAP of over 97% on the experimental data set, which is an improvement of approximately 8% compared to YOLOv5, and achieves a good detection performance, and is highly practical.
Research on Image Colorization Based on Deep Learning
Authors: Li Ao , Wang Zhongsheng 
Published: October 2024

Abstract
Gray scale picture colorization, a research hotspot in the domain of computer vision, seeks to assign reasonable colours to every single pixel of a grayscale picture, enriching the visual information of the coloured picture. Neural networks take grayscale images as input and output colorized images. From a psychological perspective, colours can provide observers with a more pleasant perceptual experience. Old photos can also be coloured, which are important documentary resources for recording real history and restoring the social landscape of the time. Additionally, due to the limitations of imaging mechanisms, most medical images are grayscale. Therefore, research on grayscale image colorization is a task of significant importance. However, existing automatic image colorization systems have issues such as “blurry boundaries”, “colour overflow”, “inappropriate colour choices” and “incorrect colour regions”. This paper proposes a model combining adversarial neural networks and U-Net networks, optimizing them by incorporating global feature fusion modules, Pathway emphasis mechanisms and spatial focus mechanisms. The idea of Markov discriminator was added to the discriminator, and the loss function was optimized. The ultimate investigative conclusions demonstrate that the PSNR and SSIM of the suggested system are 24.45 and 0.941, accordingly, in relation to the preceding protocol, which are 3% and 5% higher than the previous algorithm, and the example has been ameliorated to some degree. And the loss function is modified, and the final algorithm can improve the effect of picture colouring, which encompasses a broad spectrum of application prospects.
Research on Pseudo-Label Improvement Based on Probabilistic Uncertainty
Authors: Yang Chuanyuan , Zhao Shifeng , Fu Yanfang 
Published: October 2024

Abstract
The pedestrian re-identification task explored in this study has strong application scenarios in real life. Generally, in actual scenarios, the pedestrian samples taken by the camera are unlabeled, so pseudo-labeling is used. However, low-quality image feature extraction and imperfect clustering will produce low-quality and incorrect clustering results, which will have a negative impact on the re-identification performance. This article proposes a dual extraction method (PLR). The core idea of this study is to explore the distribution differences and similarities between two data sets through the pseudo-label method, so that the model can learn the distribution in one data set and apply it to another data set and accurately identify the target person to be found. Therefore, this article proposes a dual refinement method based on probability uncertainty. PLR first removes unqualified clustering results through probability uncertainty, and then continues to refine the remaining ones. Experiments have shown that compared to newer methods, PLR is approximately 1% higher in most tasks.
Global Indoor Localization Method for AGV Based on Ultrasonic Asynchronous Distance Measurement
Authors: Yang Xin’gang , Song Xianchen , Du Runtian , Shu Botong , Yang Shuo , Han Xuzhao 
Published: October 2024

Abstract
In order to realize free path indoor navigation and meet requirements of low cost, an integrated kinematics model of AGV and orienting mechanism of ultrasonic transmitter is established, and a global localization scheme based on three times asynchronous correlated ultrasonic distance measurement and with small number of end-nodes is given. The experiments showed that maximum localization error is just only 67 mm when the AGV travelled at a speed of 0.5 m/s and performed distance measurement at long time intervals of 1 s, which can meet the positioning requirements of most workshop operations.
Three-Frame Random Phase-Shifting Algorithm Based on VU Decomposition Method and Ellipse Fitting
Authors: Li Ziwen , Du Hubing , Feng Leijie 
Published: October 2024

Abstract
To enhance the precision and robustness of the three-frame phase shift technique, a new three-frame random phase-shifting fringe pattern phase demodulation method that combines VU decomposition and ellipse fitting techniques without the need for pre-filtering is proposed. The proposed method first performs VU decomposition on the interferograms to establish two orthogonal components of the fringe pattern. Then, the ellipse fitting method is used to obtain the relevant ellipse coefficients, thereby achieving precise phase demodulation. This method does not require an accurate phase-shifting process, thereby relaxing the stringent requirements on the phase shifter. Compared with traditional algorithms, the proposed method performs better under conditions of non-uniform background intensity and modulation amplitude. Numerical simulation experiments demonstrate that the proposed method maintains good stability across 20 repeated tests. Within the SNR range of 30 to 50 dB, the RMSE of the suggested approach is approximately 0.006 rad. This proves the effectiveness of the algorithm and provides a new approach for the development of three-frame phase-shifting technology.
Multi-Stage Wiener Process Based Remaining Useful Life Prediction for Load Cells
Authors: Lu Huanrong , Wang Chu , Li Houxin , Yan Zhipeng , Wang Peng , He Chuchao 
Published: October 2024

Abstract
Nowadays, sensor technology is used in a wide range of fields, and the demand for its reliability continues to increase. Accurate estimation of the remaining useful life of sensors is critical. Since the performance degradation of sensors involves multiple stages, the single-stage Wiener degradation model is difficult to accurately characterize. To resolve this issue, a multi-stage Wiener process degradation model is established. The model utilizes the cumulative sum algorithm to identify change points among stages. Then, the performance of the multi-stage Wiener model for characterizing degradation trends is validated with load cell accelerated aging test data. Furthermore, the results of experiment demonstrate that the proposed method provides a more accurate remaining useful life estimation compared to the single-stage Wiener model, and the relative error is reduced by 18.82%.
Illumination Correction and Enhancement Algorithm for Defective Powder Spreading Images in Selective Laser Sintering
Authors: Zhang Yikang , Guo Quanmin , Qian Yaxin 
Published: October 2024

Abstract
Based on the uneven illumination distribution and low defect contrast in the powder spreading images acquired during the selective laser sintering manufacturing process, which affects subsequent defect detection, an adaptive nonlinear illumination correction and enhancement algorithm is proposed. Local illumination correction is performed using gray valueitting curves and is combined with global gamma correction to improve correction capability in overly dark areas. A nonlinear enhancement function is constructed to boost the contrast of the image’s illumination component. Finally, a gradient-based L0 norm minimization algorithm is used to smooth non-defect areas. Experimental results show that the proposed algorithm signi icantly improves correction and enhancement, outperforming comparison algorithms overall. Compared to the original images, the coef icient of variation decreases by an average of 0.179, and the standard deviation increases by an average of 26.7%, demonstrating the effectiveness of the proposed algorithm.
An Adaptive Strong Tracking Volume Kalman Filter Algorithm
Authors: Xue Meng , Liu Baolong 
Published: October 2024

Abstract
Based on dental implant technology, this paper studies the position and posture tracking of surgical tools during the treatment of patients. A strong tracking adaptive volume Kalman filter (STF-ACKF) algorithm is proposed to meet the requirements of high accuracy, low time delay and strong robustness due to the complexity of the oral space and the narrow motion environment, to improve the measurement accuracy and reduce the noise interference. The adaptive module is added to the algorithm, and the real-time correction of process noise variance is realized by using MAP estimator [1-3]. The variance of the measured noise [4-5] was estimated using the variational Bayes (VB) method. Finally, the theoretical analysis and simulation results show that the mean error of STF-ACKF on X-axis, Y-axis and yaw angle is reduced by 1.17 mm, 0.76 mm and 0.62 ° respectively, the estimation accuracy and stability are improved significantly.
Fault Line Selection of Small Current Grounding System Research Based on Zero Sequence Circuit Current Phase
Authors: Wenjun Gong , Heng Wang , Ying Zhang 
Published: October 2024

Abstract
This paper investigates fault line selection in small current grounding systems, focusing on the zero sequence current phase characteristics. Small current grounding systems, prevalent in medium voltage distribution networks, face challenges in fault detection due to minimal fault currents during single status phase grounding faults. Traditional methods relying on manual line switching and zero sequence voltage monitoring are inefficient and can induce overvoltage. This study categorizes fault line selection techniques into three approaches: steady-state fault information, transient information, and modern signal processing technology. The analysis of zero sequence currents in non-grounded systems reveals that fault line zero sequence currents equal the sum of system capacitive currents, flowing opposite to those in non-fault lines. Additionally, transient signal analysis shows that these signals provide more robust information for fault detection. MATLAB simulations validate the theoretical models, demonstrating that zero sequence current direction and amplitude effectively identify fault lines. The results confirm the efficacy of combining steady-state and transient signal analyses for accurate fault line selection, contributing to enhanced safety and reliability in power distribution networks. This research offers practical insights and tools for engineers, improving fault management and reducing potential economic losses in small current grounding systems.
The Inter-channel Interference Cancellation Algorithm for Wireless Magnetic Induction MIMO Communication System Based on Zero-forcing Precoding
Authors: Zhang Yufang , Lu Xinhang , Ge Jiahao , Wang Peng , Chen Chen , Wang Bin , Li Xiaoyan , Xu Yuntao 
Published: October 2024

Abstract
The wireless magnetic induction MIMO system can enhance the data transmission rate in near-field magnetic induction communication, but it also suffers from severe inter-channel interference issues. This paper introduces precoding techniques into the wireless magnetic induction MIMO system, employing the zero-forcing precoding algorithm to eliminate interference between different channels. Firstly, leveraging the characteristic that the channel state of magnetic induction transmit-receive coils is determined solely by the physical parameters of the coils, channel estimation is performed to obtain the channel gain matrix for wireless magnetic induction communication. Subsequently, the obtained channel matrix is subjected to zero-forcing precoding to eliminate interference caused by coupling between different channels. Simulation results indicate that the data transmission rate of the wireless magnetic induction MIMO system is significantly higher after applying zero-forcing precoding compared to the rate without it. Additionally, the system’s data transmission rate decreases as the distance between the transmitting and receiving coils increases.
Core-winding of Sodium Cold Fast Reactor Based on CFD Method Numerical Study of Flow Characteristics
Authors: Liu Qi , Wang Ying , Wang Chuan’gao , Yan Qiang , Zhang Haitao , Chen Ling 
Published: October 2024

Abstract
Liquid metal cooled fast reactor often uses spiral winding wire as the positioning component of fuel rod bundle. Besides fixing, spiral winding has the functions of strengthening subchannel mixing and heat transfer. These characteristics have a very important impact on the internal flow temperature characteristics of the fuel assembly and the safety of the core system, so it is necessary to conduct in-depth research on the flow field distribution of the fuel rod bundle channel with wire wound, the transverse and axial flow characteristics of the edge channel and its internal channel, the flow characteristics of the circulation and eddy current, the local temperature field, and the outlet temperature distribution characteristics. In the actual research, there are some problems such as high cost, difficulty and high risk to carry out thermal hydraulic characteristic experiment directly. This paper uses CFD fine simulation technology to study 7 rod bundles with wire winding, uses Fluent meshing to partition high-quality polyhedral unstructured mesh, uses ANSYS Fluent to conduct numerical simulation, studies the influence of the presence of rod bundles with wire winding on the distribution of flow field and local temperature field, and forms a mature and reliable simulation experiment scheme. The temperature change curve and lateral mixing phenomenon obtained by CFD simulation were investigated. The outlet temperature differences of side channel, inner channel and corner channel were investigated, and the convective heat transfer characteristics between channels were investigated due to the existence of wire winding.
High-Pressure Study of Hydrogen-Bonded Energetic Material 3,5-Dimethyl-4-Nitropyrazole
Authors: Li Han , Xi Dongyang , Yan Tingting , Jiang Ran , Zhang Dandan , Xu Yifei 
Published: October 2024

Abstract
This article focused on 3,5-dimethyl-4-nitropyrazole (C5H7N3O2) as the subject of research for hydrogen-bonded energetic materials. It examined the characteristics and properties of this organic crystal under high pressure using a diamond anvil cell (DAC) and Raman spectroscopy. High-pressure Raman spectroscopy studies indicate that 3,5-dimethyl-4-nitropyrazole does not undergo a phase transition at pressures up to 9.9 GPa, confirming the structural stability of this compound. Analyzing the Hirshfeld surface energy, fingerprint plots, and intermolecular interactions reveals that this stability is attributed to its unique screw structure.
High-Pressure Behavior of NdF3: Structural and Photoluminescence Properties
Authors: Zhang Dandan , Yan Tingting , Qiu Lixin , Jin Yingying 
Published: October 2024

Abstract
This paper investigates the pressure-induced photoluminescence properties and structural phase transitions of functional material NdF3 at room temperature using diamond anvil cell (DAC), in-situ photoluminescence technology, and simulation calculations. Under hydrostatic experimental pressure and simulated pressure up to 20 GPa, the photoluminescence spectra, lattice parameters, and bond lengths of NdF3 were obtained, showing their variations with pressure. Experimental results show that a new emission line, corresponding to the 4F3/2→4I9/2 transition of Nd3+ ions, appears around 12 GPa and persists up to the highest pressure of the experiment. Upon decompression, the new emission line disappears, indicating a reversible phase transition. Notably, from 0 to 12 GPa, the emission intensity of NdF3 decreases significantly under pressure, which may be attributed to the increased energy of lattice phonons in the compressed crystal (shorter Nd-F bonds), leading to enhanced phonon-assisted non-radiative relaxation.
Preparation, Modification and Property Characterization of Nano-TiO2
Authors: Wang Xiaodan , Fan Zhaorong , Liu Yang 
Published: October 2024

Abstract
In view of the strong polarity and easy agglomeration of nano TiO2 in practical applications, its excellent performance cannot be fully exerted. In this paper, nano titanium dioxide was prepared by liquid phase hydrolysis method using TiCl4 and oxalic acid as raw materials, and then the surface modification of nano TiO2 was carried out with sodium dodecylbenzenesulfonate(SDS). The optimal modification process conditions were obtained through single-factor experiment and orthogonal experiment. The products before and after modification were characterized by scanning electron microscopy, infrared spectroscopy, particle size analysis. The results indicated that the modified nano titanium dioxide adsorbed a certain amount of modifier on the surface, with small and uniform particles that are not easily agglomerated. This greatly improved its dispersibility and stability in media, providing better guarantee for its application in various fields.
A Novel Microwave Dielectric Ceramic LiSrVO4 for LTCC
Authors: Cheng Zelai , Wang Xi , Su Hua 
Published: October 2024

Abstract
LiSrVO4 (LSV) ceramics were prepared using the solid-state synthesis method, and their phase structure, morphology, sintering characteristics, and microwave dielectric properties were investigated. The LSV ceramics could be densified by sintering at 875–925 °C for 4 hours. XRD indicated that LSV ceramics sintered at 875–925 °C for 4 hours were singlephase ceramics with a monoclinic structure. With the increase in sintering temperature, the dielectric constant and quality factor of LSV ceramics first increased and then decreased, while the temperature coefficient of the resonant frequency gradually decreased. LSV ceramics sintered at 900 °C for 4 hours exhibited a εr
of 10.92, a Q×f value of 21115 GHz, and a τf
of -4 ppm/°C. LSV ceramics demonstrated good chemical compatibility with silver, showing promising potential in the field of Low-Temperature Co-fired Ceramics.
Reproductive Performance of Beef Cattle (SIMPO, LIMPO, and Angus Grade-Black) and Socio-Economic Profile of Farmers in Sragen Regency, Indonesia
Authors: Riyanto J , Pramono A , Yanti Y , Cahyadi M , Wati A K , Pawestri W , Ananda R , Adinata Y , Krishna N H 
Published: October 2024

Abstract
This research aimed to obtain information regarding reproductive performance of three types of beef cattle in smallholder farm in Sragen Regency, Indonesia. Data was collected using survey with purposive sampling technique. The cattle samples included SIMPO, LIMPO, and Angus grade-black cattle. In addition, this research focused on some main reproductive performance indicators, namely postpartum estrus (PPE), postpartum mating (PPM), days open (DO), service per conception (S/C), and calving interval (CI). Following this process, farmers’ characteristics considered included age, highest level of education attained, length of farming experience, and daily income. All these characteristics were used as a support system to help achieve optimal productive performance of animals. Among the three types of cattle studied, Angus grade-black had better DO, S/C, and CI compared to SIMPO and LIMPO. This signified that Angus grade-black was more adaptive to tropical conditions of Sragen.
Commercial Trade and Conservation: DNA Barcoding of Wild Reticulated Python (Malayopython reticulatus) (Schneider, 1801) for Sustainable Management
Authors: Haris Hidayah , Ngadi Ehwan 
Published: October 2024

Abstract
The reticulated python, scientifically known as Malayopython reticulatus, is a prominent member of the Pythonidae family, exhibiting a wide geographic distribution across Southeast Asia. Like most python species, it is listed on Appendix II of CITES, allowing for regulated harvest and commercial export. However, inadequate monitoring of snakeskin origins within Malaysia has facilitated illegal trade, exacerbating concerns over population declines. Thus, this study aims to document the DNA barcoding of M. reticulatus in Pantai Penyabong, Johor, utilizing the COI gene marker of mitochondrial DNA (mtDNA). Observations revealed 11 reticulated pythons, with two successfully captured for blood sample extraction and amplification. Sequences obtained exhibited a high identity percentage in the NCBI GenBank database, supported by similar topologies in phylogenetic trees. These findings demonstrate the efficacy of molecular identification techniques in combating illegal wildlife trade. Governments and law enforcement agencies can enforce conservation laws and protect wild populations by verifying mislabeled python species. This study highlights the crucial role of DNA barcoding in wildlife forensics and conservation management, offering a rapid and reliable method for species identification and monitoring in the face of escalating threats.