bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of flexural oscillations of the shaft of saw cylinder on the elastic bearing supports of the fiber cleaner
Authors: Dzhuraev A A , Maksudov R Kh , Holdorov Sh S , Tukhliev A 
Published: December 2022

Abstract
The results of analysis of flexural oscillations of the shaft of saw cylinder on the elastic bearing supports of the fiber cleaner are presented in the article. A design diagram, a mathematical model of flexural oscillations of the shaft of saw cylinder on the elastic bearing supports of the fiber cleaner are given. Analytical and numerical solutions of the problem of oscillations of the saw cylinder shaft are given. The main parameters of the system are substantiated.
Study of the effect of the speed of the receiving drum of the carding machine on the properties of the thread
Authors: Mardonov S E , Toshpulotov L I , Muminov Q M 
Published: December 2022

Abstract
The purpose of the study of scientific work is to study the possibilities of improving the quality of the combined tape and the performance of the carding machine, determining the effect of the receiving drum on the quality of the thread. The speed (rotating frequency) of the take-up drum, acting on the properties of the fibers, directly leads to a change in the properties of the tape and thread.
Hydrodynamic model of motion control of pulsiting flow of two-phase media in a pipe
Authors: Abidov Kamildjan , Ergashev Bakhtiyor 
Published: December 2022

Abstract
The scientific research illustrates that theoretically investigates the issues of optimization of the process of controlling the movement of two-phase media in a pipe based on the theory of interpenetrating media. The optimal parameters of the flow in the process of pulp transportation have been determined.
Simulation of radio-frequency heating and fast-ion generation in Wendelstein 7-X
Authors: Slaby C. , Machielsen M. , Lazerson S. , Graves J.P. 
Published: December 2022

Abstract
The next scientific operation phase of Wendelstein 7-X (W7-X) is scheduled to begin in late autumn of 2022 and will, for the first time, include experiments in which the ICRH (ion-cyclotron-resonance heating) antenna will be used.
In addition to heating the plasma, this system will generate fast ions and thus offers a new way to assess fast-ion confinement in a stellarator such as W7-X. The first plasmas that will be used for the upcoming ICRH operation will be Helium-4 plasmas with a small Hydrogen minority on the order of about 10%. In tokamaks such plasmas typically offer good power absorption and are thus considered a safe way for gaining first experiences with the new antenna in W7-X.
This assessment is confirmed by the SCENIC simulations carried out in this contribution that use profiles foreseen for the upcoming campaign as input. The simulations are carried out in the standard configuration of W7-X in low-beta (0.3% ≲ 〈β〉 ≲ 1%) plasmas. However, also scans over minority concentration and background-plasma density are performed. We find that the power absorbed by the Hydrogen minority directly from the radio-frequency wave is typically (provided that the minority concentration is not too high) on the order of about 90% with the rest going to the electrons. Very little power goes to the Helium-4 ions. Under the present simulation conditions only fast-ion energies up to about E ≈ 50 keV can be reached.
Combining SCENIC and ASCOT simulations enables us to track lost particles through the scrape-off-layer to the 3D wall of W7-X and to compute wall loads caused by ICRH. The results show that the wall loads that can be expected from ICRH under the first operating conditions are benign.
Gyrokinetic Stability Analysis of JET Pedestal Top Plasmas with Small-ELMs
Authors: Dicorato M. , Muraglia M. , Camenen Y. , Garcia J. , Garbet X. , Frigione D. , Garzotti L. , Lomas P. , Rimini F. , Sozzi C. , Van Eester D. 
Published: December 2022

Abstract
In recent years, a strong effort has been dedicated to the development of tokamak plasma regimes alternative to the standard high confinement mode (H-mode) with type-I edge localized mode (ELM), i.e. ELM-free and small-ELM regimes, given the associated hardly sustainable energy and particle fluxes on plasma facing components.
In this work, we will focus on new H-mode regimes with small-ELMs, the so-called baseline small-ELMs (BSE), characterized by high thermal confinement and low core impurity accumulation, which have been recently found at JET. In order to characterize the micro-turbulence at play at the top of the pedestal, an extensive local linear gyrokinetic analysis with the GKW code has been carried out. In particular, a comparison between a reference type-I ELM (#97395) and two BSE plasmas (#96994 and #94442) has been performed.
The ion-scale (0.1 ≤ k

θ

ρ

i
≤ 2) micro-turbulence is found to have different characteristics in the two regimes. Indeed, kinetic-ballooning modes (KBM) are destabilized in the type-I ELM regime at k

θ

ρ

i
∼ 0.1, while they are stable in BSE regimes. In addition, negative (i.e. electron-diamagnetic-direction) frequency modes, identified as electron-temperature-gradient (ETG) modes, are destabilized at k

θ

ρ

i
∼ 1.5 in the type-I ELM regime while BSE regimes are characterized by positive (i.e. ion-diamagnetic-direction) frequency modes. Meanwhile, at electron-scale (10 ≤ k

θ

ρ

i
≤ 700) ETG modes are the dominant micro-instabilities in both regimes. Then, since BSE regimes are characterized by a higher impurity concentration at the pedestal, particular attention has been given to the role played by them. We found that impurities represent a critical player in the linear dynamics, strongly affecting the nature of micro-instabilities at ion-scale.
Kinematic viscosity estimates in reversed-field pinch fusion plasmas
Authors: Vivenzi N , Spizzo G , Veranda M , Bonfiglio D , Cappello S 
Published: December 2022

Abstract
This paper concerns the kinematic viscosity in reversed-field pinch fusion plasmas, including both the study of numerical magneto-hydrodynamics (MHD) simulations and the analysis of RFX-mod experimental data.
In the first part, we study the role of non-uniform time-constant radial viscosity profiles in 3D non-linear visco-resistive MHD simulations. The new profiles induce a moderate damp (for the velocity field) and a correspondent enhancement (for the magnetic field) of the spectral components resonating in the regions where the viscosity is higher.
In the second part, we evaluate the kinematic viscosity coefficient on a wide database of RFX-mod shots according to the transport theories of Braginskii (considering parallel, perpendicular and gyro viscosity coefficients), considering the action on viscosity of ITG modes (ion temperature gradient) and according to the transport theory of Finn. We then exploit the comparison with the visco-resistive MHD simulations (where the visco-resistive dissipation rules the MHD activity) to show that the classical Braginskii perpendicular viscosity produces the best agreement between simulations and data, followed by the Braginskii gyro-viscosity.
Statistics of Transport in the Vicinity of Lagrangian Coherent Structures
Authors: Dubuit N. , Agullo O. , Muraglia M. 
Published: December 2022

Abstract
Abstract. Transport properties of magnetic fluctuations, in particular the role of Lagrangian Coherent Structures, are investigated from a statistical point of view in a sheared magnetic field. It is shown that field lines escape a tube (jet) over a finite length which is independent of tube size. However this escape length is not uniform in a chaotic sea, and in particular is minimum (indicating maximal transport) in the vicinity of Lagrangian Coherent Structures. Combined with the fact that LCS are not fixed but vary in time and with the velocities of particles, this could reduce their effectiveness as transport barriers in cases where other transport processes exist.
Terrestrial Gamma-Ray Flashes at the Pierre Auger Observatory
Authors: Schimassek Martin 
Published: December 2022

Abstract
The Pierre Auger Observatory is designed to measure the highest energy cosmic rays. However, the surface detector, covering 3000 km2, is also sensitive to events associated with atmospheric electricity. These events can be distinguished from normal cosmic-ray events in both temporal and spatial structure. With signals lasting around 10 μs, they are about an order of magnitude longer than cosmic-ray events. Their circular footprints on the ground are also different and larger than those of typical cosmic-ray showers. Due to their association with thunderstorms and topology, these events are candidates for downward-going terrestrial gamma-ray flashes (TGFs). We show a detailed analysis of the effects that the data-taking system has on recording of TGF candidate events. Furthermore, we present a recently implemented special trigger algorithm aimed at increasing the data-taking efficiency for TGF candidates.
Transient Enhanced Mode design based on DC-DC Buck-Boost converter
Authors: Qiu Ziyi , Guo Zhongjie , Li Mengli , Shi Hao 
Published: December 2022

Abstract
With the rapid development of electronic products, a system may suddenly start operating from a dormant state. In order to provide a stable supply voltage to a system with a rapidly changing load and to improve the transient response of the DC-DC, a Buck-Boost type DC-DC with a Transient Enhancement Mode is proposed, which improves the transient response during load switching and reduces the overshoot/undershoot voltage and recovery time. The oscillator part can respond to different load transients and output different frequency clock signals to finally achieve fast charging and slow discharging of the inductor. The specific circuit design and physical implementation of the proposed method are verified based on a 0.18μm high-voltage BCD process. The test results show that the minimum overshoot/undershoot voltage can reach 40mV and the fastest recovery time can reach 14μs, and the transient voltage and recovery time are reduced by 66% and 88% respectively compared with the DC-DC design without a fast Transient Enhancement Mode.
Vehicle Real-time Condition Monitoring Based on CAN Bus
Authors: Wang Yuehao , Xu Jian 
Published: December 2022

Abstract
Because the automobile in the driving process there will be some hidden dangers, once the hidden dangers occur is likely to have a safety accident, then the driver’s safety will be endangered. In order to avoid this situation, this paper introduces multi-sensor communication under the CAN bus, using the CAN interface of STM32F103 MCU to transmit data with multi-sensor in real time. The high performance and reliability of CAN have been recognized, and it has been widely used in the field of automobile communication. It provides powerful technical support for the real-time and reliable data exchange of distributed control systems among nodes. Displaying the final result on the display when communicating with multiple sensors allows the driver to monitor the status of the car in real time and process it in the first place, providing a safety guide for driving.
YOLO-infrared: Enhancing YOLOX for Infrared Scene
Authors: Zhang Yao , Shen Ke Jiong , He Zhen Fang , Pan Zhi Song 
Published: December 2022

Abstract
Draw a bead on the specialty of infrared scenes and tackling the disequilibrium between positive and negative samples in object detectors, this paper introduces an object detection model for infrared scenes named YOLO-infrared based on YOLOX. This paper first analyses the shortcomings of the object detection model designed for the visible domain when applied to the infrared domain by visualizing the feature heat map of the YOLOX neck network. Considering the blurred edges of the target in the infrared image, which almost blends with the background in terms of colour and texture, with little distinction between pixel points at close distances, this paper first employs an attention module to extract the position relationship between distant pixels, which enhances the feature abstracting capacity of YOLOX. Finally, DR Loss is utilized to address the issue of positive and negative sample imbalance in the object detection process. The model YOLO-infrared proposed in this paper achieves 38.2% and 38.6% on the FLIR and KAIST datasets, respectively, which is at least 0.5% higher than the current SOAT detector.
Smart Home Environment Monitoring System Based on Microcontroller
Authors: Hu Chunzheng , Miao Fushuai , Ding Zeyu , Gong Wei 
Published: December 2022

Abstract
More than 90% of a person’s lifetime is spent indoors in a variety of activities, thus the parameters of the home environment affect human physical and mental health. With the development of Internet of things technology, people put forward new and higher requirements for the smart home. Based on the microcontroller, in this paper, we use multiple sensor systems to monitor various indoor environmental parameters, that is, to collect and display the environmental temperature, humidity, light intensity, CO concentration, and smoke concentration accurately and in real time. In the process of monitoring, the limits of various environmental parameters can be set artificially. Different types of alarms will be activated when one or several parameters are detected to exceed the limits. The microcontroller transmits the monitoring data to mobile terminals such as smartphones and others through Bluetooth modules, and the display interface is clear and intuitive. After testing, the system has the advantages of accurate measurement results, stable performance, and simple operation, which has a certain promotion and use value in smart home environment monitoring.
Automatic Depth Image Generation for Unseen Object Amodal Instance Segmentation
Authors: Wang Dongyu 
Published: December 2022

Abstract
This research proposes an automatic instance-wise depth image estimation method for Unseen Object Amodal Instance Segmentation (UOAIS), which predicts depth images automatically by sharing features of other prediction branches. The depth images can provide valuable information for amodal mask generation. To achieve good performance, the model estimates the depth images in two steps by adding two extra depth branches to the original UOAIS model. A new feature fusion scheme incorporating these two branches is also designed to facilitate information sharing between tasks. The new model is evaluated on OCID and UOAIS-Sim evaluation datasets. Compared with the performance of the original model with pure RGB input, the AP50 of the new model increases by 0.685% on the UOAIS-Sim evaluation dataset, and the overlap and boundary F measures increase by 2.3% and 1.6% respectively on the OCID dataset. Consequently, the model achieves similar performance to those which need RGB-D images as input. It has the potential to serve as a compromise plan for UOAIS if the collection of real scene-depth images is difficult or unavailable.
Deep Learning-based and Machine Learning-based Application in Skin Cancer Image Classification
Authors: Wang Xikun 
Published: December 2022

Abstract
Skin cancer arises from the skin and is capable of invading other parts of the body. The earlier detection of malignant skin lesions effectively helps cure skin disease and prevents fatal skin cancer. As part of AI, machine learning and deep learning can learn the characteristics of input datasets and perform classifications with high accuracy. In this paper, the CNN, KNN, and SVM models are implemented and tested based on the datasets collected from ISIC. The idea of the implementation is to classify the images of skin lesions into benign and malignant. The information of GANs based model is gathered. The results display the accuracy of using these models to classify different types of lesions. And the discussion of the results focuses on the efficiency to implement the machine learning and deep learning models and the accuracy of using them. The goal of the study is to figure out which method is more useful in skin cancer identification. And some of the possible practices are also discussed as future expectations.
rPPG Signal Measurement Based on Time-do-main Attention Network
Authors: Ding Wangyi , Chen Hao 
Published: December 2022

Abstract
The measurement of heart rate without touching the object being measured is referred to as “non-contact heart rate estimation.” Telemedicine, education, and a variety of other fields can all benefit from this approach, which is capable of achieving continuous heart rate measurement under certain conditions. The video segmentation network and the backbone network are cascaded in this paper’s cascaded heart rate estimation model. Adding temporal attention based on the existing 3D convolutional network model, the video segmentation network divides the video into multiple segments and fuses the relevant temporal features. It then sends the fusion results to the backbone network with the temporal attention mechanism. Mechanisms and modules like spatiotemporal convolution to make heart rate measurement more reliable and use a custom joint loss function to cut out other kinds of periodic signals’ influence. The trial results show the way that the proposed calculation can successfully lessen movement ancient rarity and light change clamor.Additionally, the dataset UBFC-rPPG demonstrates the model’s efficacy.
Research on Health Diagnosis Technology of Key Equipment in Coal Mine Power Grid
Authors: Li Zhong-kui , Wu Wen-zhen , Zhang Zi-Liang , Hua Dong 
Published: December 2022

Abstract
Aiming at the problem that the traditional fault monitoring method of mine power supply equipment is single and can not effectively reflect the real-time working state of equipment and cables, this project studies a comprehensive intelligent fault diagnosis and monitoring early warning technology method. Through the research of two key technologies, power quality analysis technology based on harmonic method and insulation condition monitoring technology of electrical equipment, an intelligent diagnosis system for the health condition of mine power supply equipment is designed and formed. Through real-time monitoring of power grid harmonic parameters, power grid operation parameters, insulation parameters, and temperature parameters, the system can comprehensively analyze and judge the working status of various equipment and connecting cables in the underground power grid to comprehensively judge the faults of high explosive switches, transformers, and connecting cables, and achieve the purpose of fault location and early warning.
Design and Prototyping of an Underactuated Index Finger Exoskeleton
Authors: Bo Jiacheng 
Published: December 2022

Abstract
At present, the rehabilitation treatment methods for hand dysfunction caused by stroke are mainly to reconstruct or improve the hand motor function of stroke patients through motor learning. To realize smooth motion without the interference of the underactuated hand exoskeleton system, this paper designs and manufactures an exoskeleton system in which a single motor drives the index finger MCP and PIP to rotate. The simulation results show that the system can realize 0-90° motion of MCP and 0-110° motion of PIP, and the motion is smooth and without interference. The system is prototyping by 3D printing. By testing the prototype, the actual movement range of the prototype is slightly smaller than the design index, and it can achieve the 0-90° movement of the MCP, but the PIP can only achieve the 0-90° movement. Through further research and analysis, it is determined that this phenomenon is caused by unreasonable motion coupling between MCP and PIP, inaccurate axial positioning, and offset of the rotation center of each joint. The system will be used as the basis for follow-up research and will continue to be optimized in combination with the problems shown in the actual wearing, and finally design and manufacture a complete set of underactuated hand exoskeleton systems that can move smoothly without interference.
Station-keeping of Stratospheric Aerostat with Receding Horizon Tree Search Planning Method
Authors: Xie Mengshan , Long Yuan , Deng Xiaolong , Yang Xixiang 
Published: December 2022

Abstract
The station-keeping property of stratospheric aerostat is significant for practical applications. In this work, we established the dynamics model of aerostat, then divided the wind fields into various layers according to the wind direction variation, which converted the data that wind speed continuously varies with height into a set of discrete wind layer sequences. After that, in order to realize station-keeping, the receding horizon tree search strategy was implemented to select the candidate wind layers. Finally, the station-keeping trajectory of the aerostat in dynamic wind fields was simulated. The results have shown that the proposed method could make the selection of the perpetual altitude more reasonable, and greatly reduce the computational complexity, effectively achieving the purpose of keeping the aerostat in a certain area.
Identification of Burned Areas Based on Texture Features of Different Windows
Authors: Wu Jinwen , Zhang Yushu , Sun Longyu , Ji Ruipeng , Yu Wenying , Feng Rui 
Published: December 2022

Abstract
It is vital to choose appropriate pixel spacing as the window size determines the distribution of texture features in a gray-level co-occurrence matrix (GLCM). The window size ranged from 9×9 to 15×15 to keep the richness of texture image information. In this study, the importance evaluation method based on the Gini index was used to determine the appropriate window for the identification of burned areas, and burned areas were identified with the random forest classification method based on texture features. The results showed that 15×15 was the most appropriate texture window size for the identification of burned areas, and the best texture features for the identification of burned areas were the contrast of the visible blue light band and the texture mean of the near-infrared band; burned areas could be fully identified with the random forest classification method based on texture features, with an overall classification accuracy of 83.87%, but there would be interference pixels in reservoirs, pits, ponds, marshes and irrigated dry fields.
Gram-Schmidt Remote Sensing Image Fusion Algorithm Based on Matrix Elementary Transformation
Authors: Zhang Shuang , Han Yifei , Wang Hua , Hou Daishuang 
Published: December 2022

Abstract
In the application of the Internet of vehicles, it is difficult for a single remote sensing image to have accurate spatial information and spectral information at the same time, so engineers must use image fusion to improve the utilization of remote sensing image information. Aiming at the shortcomings of low spectral resolution and relatively complex programming of traditional fusion algorithms, this paper proposes a Gram-Schmidt remote sensing image fusion algorithm based on matrix elementary transformation, which aims to improve the spatial resolution of multispectral images by using panchromatic images with high spatial resolution. The orthogonalization process of the algorithm in this paper uses the elementary matrix transformation, which is simple and easy to perform. The experimental results show that it can effectively improve the spatial resolution of the original image and has good spectral retention.