bluuebunny/crossref_metadata_2025_split huggingface dataset:
Observation of the Cumbre Vieja volcano plume above the Observatorio del Roque de los Muchachos with the Barcelona Raman LIDAR
Authors: Živec M , Ballester O , Blanch O , Boix J , Calisse P G , Campoy Ordaz A , Doro M , Font L , Garcia R , Gaug M , Grau R , Martinez M , Roman D , Stanič S , Ubach Ramirez S , Zavrtanik M 
Published: December 2022

Abstract
The Cherenkov Telescope Array Observatory (CTAO), currently under construction, is the next-generation very-high-energy gamma-ray observatory, providing the coverage for photons in the energy range 20GeV to 300TeV. CTAO will increase detection sensitivity in the 100 GeV to 10TeV range by a factor of 5 — 10 with respect to present experiments. CTAO retrieves the properties of very-high-energy gamma-rays by measuring Cherenkov light emitted by atmospheric showers of secondary particles that incident gamma rays produce in upper layers of the atmosphere. The key for reaching the required energy measurement accuracy is a precise knowledge of the atmospheric transmittance for Cherenkov light, which can be obtained using a dedicated Raman LIDAR. The device should operate at 355nm (near the maximum of Cherenkov light spectrum) and have the capability of taking data at specific azimuth and zenith angles up to distances of 30 km, so that atmospheric transmission along all possible air-shower directions can be determined. The Barcelona Raman LIDAR (BRL) is the official CTAO Pathfinder prototype, developed for atmospheric characterization of the Northern CTAO Site at the Observatorio del Roque de los Muchachos (ORM) on the Canary island of La Palma. BRL was deployed at ORM for extensive on-field tests between February 2021 and May 2022. We report on the commissioning results, including the remote operation capabilities of the system and its contribution to the understanding of atmospheric phenomena during its deployment period. In particular, we report on the properties of the volcanic plume from the eruption of the Cumbre Vieja volcano on 22 September 2021.
Site environment characterization for Southern Wide-field Gamma-ray Observatory
Authors: Jílek Vlastimil , Bakalová Alena , Chytka Ladislav , Mandát Dušan , Novotný Vladimír , Staník Daniel , Vícha Jakub , Moraes Arthur , Santander Marcos 
Published: December 2022

Abstract
The Southern Wide-field Gamma-ray Observatory (SWGO) is a proposed gamma-ray observatory based on the ground-level particle detection technique, with close to 100% duty cycle and an order of steradian field of view. SWGO will be located in South America at a latitude between 10 and 30 degrees South and an altitude of 4.4 km or higher, covering an energy range from hundreds of GeV to PeV. The SWGO Site Working Group is gathering, among other information, relevant environmental data to characterize the proposed sites using the AEROSITE instrument. Also atmospheric transparency is monitored to allow for potential enhancement of SWGO with a Cherenkov telescope. This contribution describes our activities in the study of the atmospheric conditions of selected candidate sites using instruments located onsite or installed at nearby stations.
Potential for atmospheric monitoring using FAST telescopes
Authors: Jilek Vlastimil , Mandat Dusan , Salamida Francesco , Svozilikova Zuzana 
Published: December 2022

Abstract
The Fluorescence detector Array of Single-pixel Telescopes (FAST) is a design for a next-generation ground-based ultra-high energy cosmic ray observatory, addressing the requirements for a large-area, low-cost detector suitable for measuring the properties of the highest energy cosmic rays with an unprecedented aperture. Three telescope prototypes are installed nearby the fluorescence telescopes of Telescope Array and one prototype is located at the Pierre Auger Observatory. Apart from detecting cosmic ray showers, the FAST prototypes offer the possibility of detecting laser pulses from atmospheric facilities such as CLF. The first part of the contribution describes the theoretical modeling of the photon scattering processes for different atmospheric models, and the raytracing of photons from the laser shot to and inside the FAST telescope. Simulations will be performed for different types of scattering conditions dependent on e.g. the size of the scattering centers or other parameters such as humidity. The ultimate goal is to create a software tool simulating the measured signals in the FAST telescopes from distant laser shots with proper treatment of light propagation trough the atmosphere and trough the detector. Such simulation toolkit for FAST prototypes at the Pierre Auger Observatory will benefit from existing attempts done for the Telescope Array site. Another part of the contribution will concern the real data of the observed CLF shots by the FAST prototypes both at the Pierre Auger Observatory and Telescope Array. Moreover, we can focus on the comparison of measured CLF shots by FAST prototype with the available data recorded by the full-scale fluorescence telescopes of the Pierre Auger Observatory.
Elastic LIDAR Monitoring of the Night-sky Brightness over Roque de los Muchachos Observatory
Authors: Pavletić Lovro , Gaug Markus , Fruck Christian , Hahn Alexander , Acciari Victor , Besenrieder Jürgen , Prester Dijana Dominis , Dorner Daniela , Fink David , Font Lluís , Mićanović Saša , Mirzoyan Razmik , Müller Dominik , Schmuckermaier Felix , Will Martin 
Published: December 2022

Abstract
Every large world-class observatory must operate in a very dark environment that is as free as possible of anthropogenic sources of light pollution, which can degrade the quality of ground-based astronomical observations. A LIDAR is able to measure, and subtract from its laser return signals, a corresponding contribution from the night-sky brightness. Our elastic LIDAR system is operated in semi-continuous mode at night, very closely following the observation schedule of the MAGIC Telescopes on Canary island La Palma, Spain. For the monitoring of the night-sky brightness, median LIDAR background rates at different atmospheric conditions and sky illuminations have been used. In this talk, results from data taken with the MAGIC LIDAR over seven years, from March 2013 until March 2020, will be presented and discussed.
Measuring Cloud Base Height and Cloud Coverage using Elastic Multiangle Lidars at Pierre Auger Observatory
Authors: Mussa R , Pallotta J 
Published: December 2022

Abstract
Cloud features above the Pierre Auger Observatory (Mendoza Province, Argentina) significantly affect the reconstruction of Extensive Air Showers. In this work, we present seasonal variations of cloud-base height, cloud coverage, and correlation between different sites using the information of elastic multiangle lidar data. This system locates the presence of clouds by measuring the spikes in the backscattered photons detected in the direction of the sweep performed during each lidar scan, outside the field of view (FOV) of the fluorescence detectors. Horizontal homogeneity should be assumed to translate these results to the full array. This ansatz is verified by a set of dedicated horizontal lidar shots performed for a few seconds every hour inside the FOV of the fluorescence detectors. Here we present the results for the period 2007 to 2016, using all the continuous lidar scans available in the lidar database. The analysis algorithm used for cloud retrieval has been upgraded and is based on a different concept than the previous one. How cloud parameters vary across seasons is investigated, and conclusions about cloud homogeneity across the Pierre Auger array are given.
Improved Point Spread Function Correction for Aerosol Measurements Using Wide-field Stellar Photometry
Authors: Negi Shefali , Ebr Jan , Karpov Sergey , Eliášek Jiří 
Published: December 2022

Abstract
When using wide-field stellar photometry to measure Vertical Aerosol Optical Depth (VAOD), we model the dependence of measured stellar fluxes on the star color and position within the field of view of the imaging system in order to control systematic uncertainties introduced through those dependencies. In wide-field imagers, the Point Spread Function (PSF) varies significantly across the instrument’s field of view (FOV) as the deformation of star images increases with the distance from the center of the FOV. While such dependence may be compensated using a synthetic flat-field correction created through the simultaneous analysis of many images, such an approach fails to account for the image-to-image changes in this correction due to minute changes in focus over time. This effect is believed to be the main reason for fluctuations in the conversion factor between measured photometric flux and actual star brightness (also known as zero-point) as determined by self-calibration scans, which is the dominant source of uncertainty for single-image VAOD measurements. We study the possibilities and limitations of using the PSFEx (PSF Extractor) code to extract the precise model of the PSF from wide-field images and compare the modeled PSF with the actual star shapes and search for optimal choices of global PSF extraction methods, including dividing the frame into smaller segments, across which the PSF is more stable.
A hexagonal high-performance transformer balun based on TSV technology for W-band application
Authors: Wang Fengjuan , Zhang Dingxi , Yu Ningmei , Yang Yuan 
Published: December 2022

Abstract
Balun has been widely used for microwave circuits for its balance properties. The development of highly integrated RF systems has put forward higher requirements for superior performance and miniaturization of the balun. A compact broadband millimeter wave (MMW) transformer balun based on through silicon via (TSV) technology is proposed in this letter. Compared with the traditional balun, the proposed balun impedance ratio is 4:1, and the use of hexagonal coil winding significantly reduces its area and improves its performance. It is shown that the proposed balun has a magnitude imbalance of 0.64dB and a phase imbalance of 2.5° at 81.5-93GHz. A return loss of greater than 15dB is obtained for the frequency band ranges from 82.1-88.6 GHz. Furthermore, the area of balun is only 0.201×0.29mm2 (0.2×0.29λg2).
First-order Bandgap Reference Source Design with High Power Supply Rejection Ratio
Authors: Kang Yunxin , Xu Ling 
Published: December 2022

Abstract
In this paper, a first-order bandgap reference source with a high power supply rejection ratio (PSRR) is designed. To obtain a low-temperature coefficient, a first-order bandgap temperature coefficient compensation method is used by adjusting the resistor resistance of the positive and negative temperature coefficients, and the gate-source voltage of the current mirror transistor is kept constant to increase the PSRR value in the low-frequency band. A self-start circuit is added to make the circuit start up quickly out of the simple bias point. The simulation results show that the bandgap reference voltage source has a constant 1.25V reference voltage with a temperature coefficient of 8.55ppm/°C in the temperature range of -40 to 125°C. The circuit is simulated using Cadence software. The circuit can be applied to OLED constant current source circuits and power management circuits.
Rasterize the Lidar Point Cloud on The Ground Out Method Optimization Analysis
Authors: Liu Chang , Gan Haiyun , Li Jialin , Zhu Boqing 
Published: December 2022

Abstract
This paper is mainly aimed at the over-segmentation or under-segmentation phenomenon of the ground point cloud in the moving scene of the unmanned platform to identify the target. This paper proposes an optimized rasterization method to remove the ground point clouds appropriately. First, the partitioned data by quadrant is processed based on the asymmetric distribution of front-to-back and left-to-right point cloud data. Then, the ground estimation of the lowest point is carried out by drilling into the laser layer data, and the connection between the estimated points and the ground detection point cloud data is segmented using the road reflection intensity correction. Next, the ground point cloud detection filtering is optimized using the raster elevation difference. Finally, an obstacle continuum hypothesis model is used to improve the under-segmentation phenomenon that occurs inside the raster. The overall ground point cloud detection filtering effect, the algorithm has a certain degree of universality and ideal ground detection filtering effect within the road, the overall achieve the desired goal.
Research on the Commissioning Method of a Current-controlled Oscillator
Authors: Huo Xianjie , Tian Lixue , Ma Wenzhe , Zhang Zhishuai , Li Yingtao 
Published: December 2022

Abstract
In this paper, the commissioning method of the current-controlled oscillator (ICO) is researched, making the ICO work under the required amplitude and frequency and exploring the best phase noise performance of ICO under the constraints of power dissipation and area. Through the theoretical analysis and simulation experiments, the commissioning process of ICO is clarified, which can meet the basic indexes of ICO, especially the amplitude and frequency, and optimize the phase noise performance of ICO.
Research on Marine Garbage Detection Based on Improved Yolov5 Model
Authors: Cai Chengtao , Gu Shenming 
Published: December 2022

Abstract
The tidal movement of the ocean carries garbage to the shore. The garbage needs to be dealt with in time, otherwise, the pollution of the garbage to the environment will become increasingly serious. According to statistics, plastic garbage accounts for a substantial proportion of marine garbage. This study developed a target detection model for some plastic garbage to help achieve automatic marine garbage capture. Firstly, according to the principle of balanced label distribution, multi-background, and multi-angle, we created an image dataset based on artificial synthesis to solve the problem of insufficient data. Secondly, the CBAM attention module was used for the target detection algorithm Yolov5 to improve the ability of target feature extraction and model generalization. Furthermore, the loss function of bounding box regression CIoU was replaced with SIoU to solve the problems of slow convergence speed and low training efficiency. Finally, the effectiveness of the Yolov5 model was discussed with the analysis of experimental results.
Ultra-wideband Vivaldi Antenna Loaded with Multi-layer Radar Absorbing Material
Authors: Li Zhengqi 
Published: December 2022

Abstract
In this paper, the radiation and scattering characteristics of a broadband miniaturized Vivaldi antenna are simulated. The proposed antenna operates at 3.6GHz-15.6GHz. Through calculation, the multi-layer absorbing material with the best broadband absorption loss is obtained, and the RCS reduction is effectively realized by loading RAM on the antenna metal floor. The simulated results between the reference antenna and the antenna loaded with RAM show that the RCS reduction of more than 10 dB under the incident angle of nearly ±70° in the xoz plane is realized, while the radiation performance of the antenna with RAM is well preserved, which proves the significance of absorbing material loading for antenna RCS reduction.
Underwater biological detection based on improved YOLOX
Authors: Zhu Aoqi , Wang Chen , Chen Shuai 
Published: December 2022

Abstract
China has abundant Marine resources. Underwater biological detection is important for the development of underwater resources in China. The detection accuracy of underwater biological detection is not high due to poor underwater visibility and the dense existence of biological and complex background information. This paper proposes an improved algorithm of underwater biological detection based on the YOLOX algorithm. CBAM attention mechanism is integrated into the CSPDarkNet of YOLOX, the background and object are distinguished by weighting object information. Considering the detection accuracy and positioning accuracy, the bounding box loss IoU is replaced by DIoU. In the present underwater biological data set, experimental findings demonstrate that the improved algorithm’s detection accuracy reaches 84.76%, which is increased by 2.22%.
FPGA-based Object Detection Acceleration Architecture Design
Authors: Li Wenhao , Hu Huaixiang 
Published: December 2022

Abstract
To solve the problems of insufficient acceleration capability and high power consumption of the existing embedded terminal target detection, a multi-strategy optimization hardware accelerator based on the YOLOv2 model is designed by taking advantage of the high concurrency characteristics of the CPU+FPGA structure. The accelerator improves its parallelism and real-time performance while reducing power consumption and resource consumption through floating-point quantization, adder optimization, and various HLS optimization strategies. Tested on Xilinx’s PYNQ-Z2 platform, the overall computing power of the accelerator reaches 27.1GOP/s, the average detection accuracy is 80.6%, and the overall power consumption is 2.609W. Compared with CPU and GPU, the obtained accuracy only loses 2%, but the power consumption is greatly reduced. It has strong practical significance in edge target detection that requires high real-time performance and low power consumption.
Task Scheduling Strategy for Industrial Control Network based on Cloud-Edge-End Fusion Framework
Authors: Liang Lei , Lu Jun , Tang Ran , Peng Jiakai , Zhang Wei , Zhao Min 
Published: December 2022

Abstract
Industrial tasks with traditional cloud architecture have many disadvantages, which are mainly longer delay of data transmission and difficulty in software deployment. In view of the above disadvantages, this paper used containers to solve the problems for industrial software deployment and upgrade. This paper uses a cloud-edge-end framework to deploy tasks with high delay on the edge of the network or even on the device side, so as to reduce the delay of data transmission and computing pressure. At the same time, the task scheduling strategy based on the particle swarm optimization algorithm is used to search for the node with the minimum task delay among multiple nodes to realize the task allocation optimization. Finally, through the comparison experiment, it is concluded that the task scheduling strategy for industrial control networks based on a cloud-edge-end fusion framework can better reduce the task execution delay and reduce the difficulty of software deployment.
Skin Disease Classification Using Mobilenet-RseSK Network
Authors: Hu Jihong , Qi Yongfeng , Wang Jiaying 
Published: December 2022

Abstract
The traditional deep learning method has a large amount of calculation, long time training and complex network structure, which is not easy to be applied to embedded or mobile devices. To solve the these problems, we proposed an improved lightweight mobile network named as Mobilenet-RseSK for skin disease classification. Firstly, a new attention mechanism seSK module is proposed, and seSK module is used to replace the position of SE in the original network. This module can better perform feature extraction and improve network performance than the original network attention module. Secondly, using RBN normalization, RBN maintains the advantages of BN, and strengthens the representation of specific features, which strengthens the degree of accuracy of skin disease identification. We compare the Mobilenet-RseSK network with MobilenetV3, Ghost and other advanced networks on the HAM10000 dataset. The proposed network promotes the accuracy of skin disease classification by 1.7% compared with the original network. Compared with advanced mobilenet network, our method achieves 85% accuracy on the test set. This network has certain practical value in skin disease classification, and is an effective lightweight skin disease classification algorithm.
Remaining Useful Life Prediction of Rolling Bearings Based on PCA and GSACO-SVR Model
Authors: Jiang You-liang , You Zhen-nan , Cao Zi-cong , Wang Yan 
Published: December 2022

Abstract
The prediction of the remaining useful life (RUL) of rolling bearings facilitates the better development of maintenance programs. It is very important to improve prediction accuracy. We proposed an improved optimized support vector regression (GSACO-SVR) model to accurately predict the RUL of bearings, which is based on a new golden sine ant colony algorithm (GSACO) aiming to optimize the support vector regression (SVR) parameters. Compared with SVR, fruit fly algorithm, and ant colony algorithm under different working conditions by experiments, the GSACO-SVR model has more accurate prediction results and better bearing life degradation trend.
Digital SI Cancellation Based on LSTM for Co-frequency Co-time Full Duplex Communication Systems
Authors: Wang Yuhan , Chen Yuanxiang , Hu Cong , Li Yanjiang , Wang Shuo , Yu Jianguo , Lu Fan , Fan Zhanchun , Du Hailong , Ma Chao 
Published: December 2022

Abstract
To address the high self-interference (SI) in co-frequency co-time full duplex (CCFD) communication systems, a digital SI suppression method based on deep learning is proposed. A memory polynomial is firstly utilized to simulate the SI channel. Then a long short-term memory network (LSTM) is used to reconstruct the SI signal. The clean signal after interference suppression can be achieved by subtracting the SI signal at the receiver. To better reflect the changes of the SI signals after being transmitted through the multiple channels and reduce dependence on data volume, feature preprocessing and feature reconstruction are performed at the input of the LSTM. We use the multi-segment delayed transmitted signal as the multiple features and utilize the brainstorm optimization (BSO) technique to estimate the ideal time delay. We verify the proposed SI suppression scheme in the OFDM transmission system. The experimental results show that compared with the traditional least squares estimation (LS) and adaptive filter least mean square (LMS) algorithms, the proposed scheme has a significant performance boost. A SI signal suppression capability of 47.19 dB is achieved.
Fast Recognition and Pose Estimation Algorithm for Space Cooperative Target via Mono-vision
Authors: Guo Meishan , Chen Yanjiang , Liang Binyan , Wang Yanbo , Huang Kui , Luo Zhiwen , Jiang Shan 
Published: December 2022

Abstract
Visual guidance based on cooperative target is one of the most commonly used approaches in the field of space in-orbit service, such as spacecraft rendezvous and docking and satellite maintenance. Considering the limited space hardware resources, it is necessary to design an embedded image processing algorithm to meet the special needs of space recognition, such as small memory consumption and fast recognition speed. Therefore, aiming at the classic three-point cooperative target, recognition, and pose estimation algorithm is designed in this paper based on mono-vision. In this method, a fast inflection point detection method is designed, and the contour is divided into several edges with a single feature, which improves the accuracy of circle recognition. Finally, the relative pose of the target coordinate system can be obtained quickly and accurately by P3P. The algorithm has low complexity and can realize fast recognition with small memory, even with limited space-grade hardware resources. The effectiveness of the proposed method is verified by experiments.