bluuebunny/crossref_metadata_2025 huggingface dataset:
Triangularity effects on global flux-driven gyrokinetic simulations
Authors: Giannatale Giovanni Di , Donnel Peter , Villard Laurent , Bottino Alberto , Brunner Stephan , Lanti Emmanuel , McMillan Ben F. , Mishchenko Alexey , Murugappan Moahan , Hayward-Schneider Thomas
Published: December 2022

On the road to fusion energy production, many alternative scenarios have been investigated in order to address certain well-known problems of tokamak devices; among which, anomalous transport, ELMs and disruptions. The studies on plasma shaping fall into this effort.

In particular, it has been experimentally observed that when operating in L mode, negative triangularity (NT) features better confinement properties than positive triangularity (PT). However, even though the trend is quite clear, a complete and satisfying theoretical explanation for this experimental findings is still lacking.

With the aim of understanding and describing these improvements starting from first principles, we present the first comparison between PT and NT with global flux-driven gyrokinetic simulations performed with the ORB5 code.

The numerical setup includes: electrostatic turbulence, kinetic trapped electrons, non-linear collisional operator, ECRH source, limiter and wall as boundary conditions. The simulations have been performed on ideal MHD equilibria and kinetic profiles inspired by TCV experiments, in a mixed ITG-TEM regime.

First analysis reveal a strong reduction of transport in NT; while at the edge PT shows superdiffusivity, NT does not. The limiter plays an important role that has to be further clarified.
Gyrokinetic modelling of the Alfvén mode and EGAM activity in ASDEX Upgrade
Authors: Vannini F. , Biancalani A. , Bottino A. , Hayward-Schneider T. , Lauber P. , Mishchenko A. , Poli E. , Rettino B. , Vlad G. , Wang X.
Published: December 2022

Energetic particles present in tokamak machines can drive through resonant wave-particle interaction different plasma instabilities, e.g Alfvén modes and energetic particle-driven geodesic acoustic modes (EGAMs). While the former are potentially detrimental as they can enhance the energetic particle transport and damage the machine wall, the latter are axisymmetric, possibly benign modes that can act to regulate turbulence. A unique scenario, the so-called NLED-AUG case, has been developed in ASDEX Upgrade by tuning the plasma parameters so that the energetic particle kinetic energy is 100 times higher than that of the background plasma, like in ITER. An intense energetic particle-driven activity is observed, most prominently various Alfvén mode bursts triggering chirping EGAMs. The present work reports studies on the Alfvén mode and EGAM dynamics showing, for the first time, many toroidal mode gyrokinetic simulations with ORB5 where the NLED-AUG case scenario is considered. We study the mode dynamics modelling the energetic particles with different equilibrium distribution functions, such as: isotropic slowing-down, double-bump-on-tail and equivalent Maxwellian. We retain, at the beginning, the nonlinearities only in the energetic particle dynamics. Later, also the background plasma species nonlinearities are taken into account.
On cubic non-linearities in fluid and kinetic models
Authors: Villa D , Garbet X , Dubuit N , Agullo O
Published: December 2022

The kinetic origin of the cubic terms found in electromagnetic reduced fluid models of magnetized plasmas is identified and analyzed. The transition from cartesian to guiding center variables in kinetic systems is responsible for the introduction of such cubic terms, and the derivation of a set of such terms is explicitly shown. The role of these terms in fluid simulations, and their importance for energy conservation of cubic terms in both frameworks is discussed
Investigation of the effectiveness of ‘multi-harmonic’ electron cyclotron current drive in the non inductive EXL-50 ST
Authors: Banerjee Debabrata , Song Shaodong , Xie Huasheng , Liu Bing , Wang Mingyuan , Liu Wenjun , Chen Bin , Han Lei , Luo Di , Song Yunyang , Song Xianming , Liu Minsheng , Shi Yuejiang , Martin Peng Y. K. , Petrov Yu. V. , Harvey R. W.
Published: December 2022

The fully non-inductive spherical tokamak EXL-50, built and operated by the ENN private limited company, has routinely achieved high current drive efficiency of ∼ 1 A/W in only ECRH powered experiments. We have numerically investigated the effectiveness of multiple electron cyclotron resonance (ECR) harmonics in generating such a high efficiency of electron cyclotron current drive (ECCD) in non-inductive plasma start-up. The Fokker-Planck equation is numerically solved to obtain the electron distribution function, under the steady state of relativistic nonlinear Coulomb collision and quasi-linear diffusion operators, for calculating plasma current driven by the injected EC waves. Multi-pass absorption simulations, done with the CQL3D code for extra-ordinary EC waves, demonstrate over 1 A/W efficiency in current for a relatively low density (∼ 2 × 1018
m
−3), and low temperature (∼ 100 eV) plasma, consistent with the experimental results observed on EXL-50. Systematic scanning of different ECR harmonics in simulation has revealed that the multi-harmonic resonance interaction in EXL-50 plays a pivotal role in generating the energetic electron tail responsible for the current.
Long-wavelength closures for collisional and neutral interaction terms in gyro-fluid models
Authors: Wiesenberger M. , Held M.
Published: December 2022

A collisional gyro-fluid model is presented. The goal of the model is edge and scrape-off layer turbulence. The emphasize in the model derivation heavily lies on ”implementability” with today’s numerical methods. This translates to an avoidance of infinite sums, strongly coupled equations in time and intricate elliptic operator functions. The resulting model contains the four moments density, parallel momentum, perpendicular pressure and parallel energy and is closed by a polarisation equation and parallel Ampere law. The central ingredient is a collisional long-wavelength closure that relies on a drift-fluid gyro-fluid correspondence principle. In this way the extensive literature on fluid collisions can be incorporated into the model including sources, plasma-neutral interactions and scattering collisions. Even though this disregards the characteristic finite Larmor radius terms in the collisional terms the resulting model is at least as accurate as the corresponding drift-fluid model in these terms. Furthermore, the model does enjoy the benefits of an underlying variational principle in an energy-momentum theorem and an inherent symmetry in moment equations with regards to multiple ion species. Consistent particle drifts as well as finite Larmor radius corrections and high amplitude effects in the advection and polarization terms are further characteristics of the model. Extensions and improvements like short-wavelength expressions, a trans-collisional closure scheme for the low-collisionality regime or zeroth order potential must be added at a later stage.
Axisymmetric modes, fast ions and X-point effects in tokamak plasmas
Authors: Barberis T. , Porcelli F. , Fitzpatrick R. , Yolbarsop A.
Published: December 2022

Recent progress on the understanding of axisymmetric pertubations in tokamak plasmas is presented, with particular attention on Vertical Displacement Oscillatory Modes (VDOM) that can be driven unstable by their resonance with fast ion orbits, and on the impact of divertor X-points on the stability of vertical displacements.
Sinergy of extra-terrestrial particle accelerators and accelerators operated in the terrestrial atmosphere
Authors: Chilingarian A , Hovsepyan G , Zazyan M
Published: December 2022

We performed simulations of the EAS particle transport initiated by ultra-high-energy gamma rays entering the terrestrial atmosphere. During thunderstorms, the electric fields above the LHAASO array efficiently modulate EAS particles. Because of this modulation, the possible bias on the energy estimation for primary energies up to 100 TeV can be up to ten-fold. Moreover, for the higher primary energies (≈1 PeV), the electric field modulation enlarges “genuine” primary gamma ray energy 2.5-3 times. This result is very important because observation of PEVatrons by LHAASO is based on rather small statistics, and the highest energy events can occasionally coincide with thunderstorms. We also demonstrate the existence of a threshold effect on the intracloud E-field strength needed to trigger the startup of a runaway process that exponentially multiplies the free electrons entering a strong atmospheric electric field.
Atmospheric Electrical Activity in central Argentina and its relationship with phenomena observed at the Auger Observatory
Authors: Nicora M G , Baissac D M , Villagran C I , Velazquez Y , Solari F I , Barle M F , Pini L , Bertone F
Published: December 2022

Thunderstorms in Argentina have great spatial variability explained by various mechanisms on different spatio-temporal scales, associated with the meridional extension and orography of the region. The Pierre Auger Observatory is located in Mendoza Province in central-western Argentina where the unique meteorological and geographical conditions result in a high spacial density of convective storms.Atmospheric electrical activity (AEA)produces Transient Luminous Events (TLEs) of which ELVES are the most prominent members of the extraordinary family that includes halos, jetstorms, and sprites. Northern Argentina and Southern Brazil are prolific producers of TLEs, which can be observed at the Pierre Auger Observatory by the Fluorescence Detector (FD) 24 UV telescope. In this work, we present the characterization of the AEA in the study region and the most important meteorological characteristics to aid in understanding which of the dynamical or microphysical processes could act in the formation of TLEs.
Atmospheric Gamma-ray Observations at the Telescope Array Detector
Authors: Abbasi R.
Published: December 2022

Previously in AtmoHead-2018, we reported joint observations by Telescope Array Surface Detector (TASD), Lightning Mapping Array (LMA), sferic sensor and broadband interferometer of particle showers coincident with lightning. These consisted of energetic showers of approximately less than 10 microsecond duration with footprints on the ground of 3-6 kilometers in diameter, originating in the first one to two milliseconds of downward lightning leaders and coincident with high-current processes within the leaders. Scintillator waveform and simulation studies confirmed that these showers must consist primarily of gamma radiation.

On September 11, 2021, atmospheric discharges emitting gamma rays were, for the first time, recorded by a high-speed camera and by lightning detectors on the ground simultaneously. The events were detected by the Telescope Array located in the Utah desert and were filmed by the Phantom v2012 camera, set at an acquisition rate of 40,000 frames per second (fps) in conjunction with the Lightning Mapping Array (LMA), an interferometer, a fast antenna, and the National Lightning Detection Network (NLDN). Results from this study reported the new observation of several events of significantly longer duration and higher uence, bridging the gap between the TASD and satellite-based detections. These events further demonstrate the similarity between the upward and downward TGF varieties and the likelihood of a common origin for their production.
Aerosol measurements at sub-percent precision using wide-field stellar photometry
Authors: Ebr Jan , Karpov Sergey , Eliášek Jiří , Blažek Jiří , Cunniffe Ronan , Ebrová Ivana , Janeček Petr , Jelínek Martin , Juryšek Jakub , Mandát Dušan , Mašek Martin , Pech Miroslav , Prouza Michael , Trávníček Petr
Published: December 2022

Wide-field stellar photometry – the process of simultaneous comparison of apparent and catalog brightness of a large number of stars – has long been a promising method of atmospheric monitoring, as it can provide atmospheric transparency measurements with high temporal and spatial resolution without any artificial illumination of the sky which would disturb nearby optical experiments. However, only recently have we developed methods of data analysis that allow an overall uncertainty in the Vertical Aerosol Optical Depth (VAOD) better than 0.01 optical depths. Such a feat requires precise laboratory measurements of spectral and signal responses of the instruments as well as careful analysis of all systematic effects that can appear during the extraction of stellar signals from the images. We will present a summary of the method with emphasis on the reliability of the estimates of uncertainties. Furthermore, we will discuss various possible applications of the method in different modes of operation, a comparison with other methods of aerosol measurement, and a selection of open questions and areas for further improvement.
The influence of reduced atmospheric transmission on the CTA-North performance
Authors: Pecimotika Mario , Prester Dijana Dominis , Hrupec Dario , Mićanović Saša , Pavletić Lovro , Sitarek Julian
Published: December 2022

Cherenkov Telescope Array (CTA) is the next generation ground-based observatory for gamma-ray astronomy at very-high energies which will consist of the northern (CTA-N, La Palma, Spain) and southern (CTA-S, Paranal, Chile) arrays. The atmosphere, as an integral part of the Cherenkov telescope detector, has a great impact on the observed data, especially in means of reduced sensitivity. One of the main contributions to the systematic uncertainties arises from the presence of clouds. To minimize these systematic uncertainties a calibration of the detector response is of great importance. Here, the influence of cloud altitude and transmission on the CTA-N performance degradation using detailed Monte Carlo simulations has been investigated for the case that no measures are taken to characterize clouds and correct their effects. The degradation effect of the presence of clouds is primarily observed at low and middle energies but spans across the entire energy range.
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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Machine Learning Amplified Control System for HASEL Actuator Soft Robot System
Authors: Dong Yuheng
Published: December 2022

The HASEL actuator is a cutting-edge soft robot compound that is well suited for tasks in unstructured, dynamic environments and has the penitential for superiorly comfortable and smooth human-robot Interaction. However, the nonlinear relation between the input voltage, output strain of the actuators, and the difficulty of analytical modelling makes it hard to design its control software due to the various source of kinematic noises. Machine learning technics, however, which are invented to study the implicit relations in multiparameter problems that do not require pre-existing knowledge, are well suited for HASEL actuators. Traditionally, researchers consider the behavior of this time-dependent system as a sequence of consecutive statuses and use machine learning to enhance conventional algorithms that consume previous and current status and target and adjust the system using varying control input. However, HASEL actuators’ unique propriety of self-stable and negligible lag in response to input changing makes it possible to consider the spatial path of the structure as a whole and control it based on pattern matching. Introducing Recurrent Neural Networks (RNN) and multilayer perceptron (MLP), this paper presents a pattern-matching-based predictive control algorithm for the HASEL actuator system with acceptable size and high accuracy.
A Fast Automatic Charging Method for Robots Based on Optic Position and Navigation
Authors: Tang Ran , Lu Jun , Liang Lei , Peng Jiakai , Zhao Min , Zhang Wei
Published: December 2022

Automatic charging is one of the important functions of a robot. Traditional automatic charging is generally based on multiple sensors working with each other. With the development of vision technology, the application of robots’ first vision and third vision is becoming more and more widespread. In this paper, an automatic robot charging system based on optical position and navigation is presented based on third vision. The system design is simplified by positioning the robot and the charging stand based on the optic. After the experimental test, it shows that the robot and the charging stand are docked with high accuracy and the docking is completed well.
Research on Target Simulation Technology Based on Stokes Vector
Authors: Wu Gang , Zhao Haili , Cai Lianlian
Published: December 2022

With the development of polarization optical technology, polarization detection technology plays a more and more important role in the military and other fields. Existing research demonstrates that the degree of polarization of reflected light from natural objects can often be ignored, while the degree of polarization of artificial objects is relatively large. If the target tracker can identify and track the target with this optical characteristic, the tracking efficiency can be greatly improved. However, at present, there is a lack of testing devices for relevant trackers, and the cost of physical testing is much too high. Therefore, given the lack of an available polarization target simulator, the polarization target simulator based on the Stokes vector is designed. The results show that the polarized target simulator can simulate the polarization target with specific linear polarization information, and the linear polarization degree image and polarization angle image can be obtained by the graphic calculation software.
Improved Particle Swarm Localization Algorithm Based on Evolutionary Mechanism
Authors: Pan Yang , Yu Xiuwu , Liu Yong
Published: December 2022

Aiming at the problem of low localization accuracy and poor robustness when conventional localization algorithms are used for the localization of WSN nodes, an improved particle swarm localization algorithm based on an evolutionary mechanism is proposed. To reduce the ranging error in a complex environment, the anchor box algorithm is improved by using ranging information, and the search area is reduced by the improved algorithm to determine the possible region where unknown nodes exist. Then the objective function is established to transform the localization problem into a bounded optimization problem. The conventional particle swarm optimization algorithm is improved and genetic operators such as crossover and mutation are introduced to improve the search accuracy and global optimization ability of the algorithm. The simulation results show that, compared with the conventional positioning algorithm, the proposed algorithm has smaller positioning errors and stronger robustness.
Fingerprint Matching Method Based on Ant Colony Algorithm
Authors: Qiao Weigao , Zhang Jianzhong , Yuan Fei
Published: December 2022

Based on previous research, this paper proposes a model and implementation of large-scale fingerprint image retrieval. In the retrieval, the C-means clustering method is used to quickly retrieve fingerprint images, and the shortest path algorithm is used to achieve effective matching fingerprints, and finally, the fingerprints with a higher matching rate are obtained, thereby realizing rapid retrieval and matching of fingerprint IDs. The matching fingerprint minutiae features are analyzed, a retrieval method that can be used for fast fingerprint retrieval is given, and the principle of the method is expounded. The algorithm is used to filter and remove the pseudo-feature points of all fingerprints and is used to calculate the similarity between all minutiae operators. Then the operator with the highest similarity is selected, and the corresponding minutiae pair is used as the registration point pair to complete the two minutiae registration transformation of the point set. And finally, the pairing relationship of minutiae points is established. After that, the time complexity and space complexity of the selected retrieval method is analyzed. All fingerprint pairs with the “identical” relationship provided in the data file are used as query images to verify the retrieval method in the fingerprint dataset. The shortcomings and deficiencies of this method are pointed out, and other ways to solve this problem are introduced.
Foreign object detection algorithm for high voltage transmission lines incorporating atrous convolution
Authors: Hu Shuang , Li Yu
Published: December 2022

There are problems of complex background, serious occlusion, and low accuracy of foreign object detection on high-voltage transmission lines. In this paper, we propose an algorithm incorporating atrous convolution for the detection of four types of foreign objects that are more likely to appear on high-voltage transmission lines: bird nests, balloons, kites, and rubbish. The algorithm is based on the original YOLOv4 model, replacing the original SPP structure with an ASPP structure. By using the atrous convolution instead of the original pooling operation, the network is able to have a larger field of perception during feature extraction, while the resolution of the feature map is not degraded too much to avoid losing too much information. The experimental results show that the accuracy of this method reaches 93.73% on the transmission line dataset used, which is a significant improvement over the original YOLOv4 model and improves the detection capability of foreign object targets that are obscured in complex environments.
Skin Cancer Classification Based on Convolutional Neural Networks and Vision Transformers
Authors: Zhao Zhenhao
Published: December 2022

Skin cancer is one of the most prevalent illnesses in the globe, and early diagnosis is the most effective method for preventing the disease and reducing mortality. Nowadays, the most prevalent way of detecting skin cancer is a visual diagnosis by specialists using dermoscopy images. Nevertheless, the similarity of the appearance between skin cancer lesions and the complexity of dermoscopic images pose a great challenge for the detection and classification of skin cancer. To solve these problems, this paper compares the current start-of-the-art deep learning methods, Convolutional Neural Networks (CNN), and transformers, to verify which method is more suitable for automatic skin cancer lesion classification. First, we assign different weights to individual lesions to address the problem of imbalance of the dataset. Secondly, we crop the images in the dataset and utilize the method of data augmentation to enhance the sample size. Thirdly, we select and construct the corresponding methods of CNN and transformers. The methods selected for CNN are VGGNet and ResNet. The methods selected for transformers are Vision Transformers (ViT) and DeepViT. Finally, we analyze these methods in terms of the loss, accuracy, and confusion matrix on the related HAM10000 dataset. The experimental results demonstrate that both CNN methods and transformers methods can achieve good performance on the skin cancer lesion classification task, but the CNN methods perform better than the transformers methods.
Network Information Data Security Transmission Method Based on the DES Algorithm
Authors: Shi Lipeng , Chang Jie , Liu Shuo , Zuo Xiaojun
Published: December 2022

In view of the current network information data security transmission method in the process of data transmission, the abnormal data detection performance is poor and the attack rate is high in the process of data transmission. This paper proposes a network information data security transmission method based on the DES algorithm. The 3DES algorithm is used to complete the data encryption process, and the RSA encryption algorithm is used to encrypt the key to get the final data transmission object. The network model is constructed. The LOF algorithm is used to eliminate the abnormal data nodes, and the reliable network nodes are used to complete the data transmission. The experimental results show that this method can effectively reduce the missing rate of abnormal data, further improve the data resistance to attack, and promote the development of network data transmission technology.