bluuebunny/crossref_metadata_2025_split huggingface dataset:
A dark matter telescope probing
the 6 to 60 GHz band
Authors: De Miguel Javier 
Published: April 2021

Abstract
In this article we present the Dark-photons&Axion-Like particles Interferometer (DALI),
a novel experiment designed for the detection of photon-mixing cold dark matter in the microwave
band between 6 and 60 GHz. DALI is a haloscope for the simultaneous search for axions, axion-like particles and dark
photons, with a number of novelties that make it unique. First, it is a dark matter telescope, with a
capacity for pointing, tracking and rastering objects and areas in the sky. This potentially
allows one to detect relativistic dark matter particles, substructures and flows, without
compromising the simultaneous scanning for dark matter relic particles present in the laboratory. Second, it has been designed using commercial technology. This will allow feasible manufacture
at a reasonable cost, thereby mitigating the need for R&D and facilitating maintenance. Finally,
it benefits from a high sensitivity over a broad band of frequencies with only minimal reconfiguration.
Warm-assisted natural inflation
Authors: Reyimuaji Yakefu , Zhang Xinyi 
Published: April 2021

Abstract
We consider natural inflation in a warm inflation framework with a temperature-dependent dissipative coefficient Γ∝ T3. Natural inflation can be compatible with the Planck 2018 results with such warm assistance. With no a priori assumptions on the dissipative effect's magnitude, we find that the Planck results prefer a weak dissipative regime for our benchmark scale f=5 Mpl, which lies outside the 2σ region in the cold case. The inflation starts in the cold regime and evolves with a growing thermal fluctuation that dominates over quantum fluctuation before the end of the inflation. The observed spectral tilt puts stringent constraints on the model's parameter space. We find that f< 1 M_ pl is excluded. A possible origin of such dissipative coefficient from axion-like coupling to gauge fields and tests of the model are also discussed.
Comparative investigation of 5-aminolevulinic acid and hexyl aminolevulinate-mediated photodynamic diagnostics and therapy of cervical dysplasia and vulvar leukoplakia
Authors: Efendiev K T , Alekseeva P M , Bikmukhametova I R , Piterskova L S , Orudzhova K F , Agabekova U D , Slovokhodov E K , Loschenov V B 
Published: April 2021

Abstract
This study aims to conduct a comparative analysis of aminolevulinic acid and its hexyl aminolevulinate (HAL) for photodynamic diagnostics and therapy of cervical dysplasia and vulvar leukoplakia in continuous and pulsed laser irradiation mode. The fluorescence intensity of protoporphyrin IX (PpIX) in the cervix epithelium was five times higher after the application of HAL compared with the application of aminolevulinic acid. Increased intensity of fluorescence of PpIX in vulvar tissues complicated by leukoplakia was not observed with 5-aminolevulinic acid and its HAL. Intraepithelial changes in patients with cervical dysplasia were absent after photodynamic therapy (PDT) in continuous irradiation mode. Repeated PDT was prescribed to several patients with vulvar leukoplakia after pulsed light irradiation. Pulse irradiation made it possible to avoid the use of various types of anesthesia in patients. In the regime of continuous irradiation, pain sensations of varying degrees from a burning sensation to sharp pains were observed in patients in the zone of photodynamic exposure. The results presented in this paper will help to optimize the PDT process of cervical dysplasia and leukoplakia using 5-aminolevulinic acid or HAL.
Electromagnetic Compatibility Simulation Analysis of Helicopter Engine Irradiated by EMP
Authors: Haoyang Chen , Yutang Fan 
Published: April 2021

Abstract
Due to the rapid development of battlefield complex electromagnetic environment research in recent years, electromagnetic pulse (EMP) environment has gradually stepped onto the stage of information war. To make low altitude flying electronic equipment engine plays its normal combat performance in the EMP radiation environment and ensure the integrity of electronic equipment, it is urgent to research in this field. In this paper, according to GJB-1389A and other standards, CST simulation software is used for simulation analysis. Through simulation, field strength and cable coupling with the airborne engine of an armed helicopter under EMP irradiation are predicted. The conclusions have a certain guiding significance of the further study of the protection against the complex electromagnetic environment of the engine.
Research on power exchange flexibility optimization of urban AC/DC distribution network
Authors: Sun Ke , Ye Gangjin , Yang Xuan , Weng Hua , Wang Xiran , Chen Zhiyuan 
Published: April 2021

Abstract
After large-scale access to distributed generation of new energy generation in urban AC/DC distribution network, its own randomness and uncertainty affect the supply-demand balance mechanism of distribution network. Therefore, this paper studies the power exchange flexibility optimization method of urban AC/DC distribution network to provide reference for the operation and scheduling of distribution network and main network. First, the active power exchange model of distribution network is established, the extreme value of power exchange of distribution network is obtained, and the flexible range of exchange power is calculated. Next, the flexibility evaluation index is established, and the operation characteristics of energy storage are transformed to complete the research on power exchange flexibility optimization of urban AC/DC distribution network. Through the actual example analysis, the results show that after the optimization of the design method, the net load curve is smoother, the effect of reducing the peak valley difference is more significant, and the overall curve is relatively smooth, which shows that the design method has certain effectiveness.
Analysis and Suppression Strategy of Transient Frequency Deviation by Soft Guide Vane Control in Hydro Turbine
Authors: Cai Weijiang , Shi Xinlei , Shi Haidong , Rong Hong , Zhao Yong , Wang Yongtan , Zhang Meijun 
Published: April 2021

Abstract
The hydro-dominant characteristic is notable after the asynchronous operation in Southwest China Power Grid which brings worse transient frequency deviation caused by water hammer effect. To prevent the possible cascading failure due to the worse transient frequency deviation in the secondary frequency regulation, the soft guide vane control law is proposed to suppress the water hammer effect in the transient regulation process based on the detailed turbine-penstock model. The discrete state space expression of the turbine-penstock model is built to simulate the regulation effect in the time domain and the PSO (Particle Swarm Optimization) algorithm is applied to optimize the soft guide vane control adjustment factor considering multi-object. Finally, the emergency AGC (Automatic Generation Control) adjustment in the single machine with load transmission system is conducted to verify the effect of transient frequency deviation suppression by optimized soft guide vane control.
Research on Attack Penetration Prevention Techniques of Power Terminal Network
Authors: Zhou Xiaojun , Wang Liming , Cai Yupeng , Ren Shuai , Li Tong , Yuan Yidong , Li Qi 
Published: April 2021

Abstract
After the power terminal network is attacked, it is necessary to adopt effective security strategies to block the attack in time to prevent further expansion of the attack damage. At this time, not only the availability of the system must be considered, but also the impact of the attack must be minimized. Traditional network isolation methods may cause excessive protection problems such as excessive isolation range and high isolation strength, and affect the continuity of power system business. Therefore, this paper conducts research on the attack penetration prevention techniques of power terminal network, under the condition of minimally affecting the real-time business continuity of the power grid, blocking low-risk terminals’ control commands and/or isolating high-risk terminals’ communication to realize accurate attack penetration prevention.
Research on shell magnetic shielding based on finite element method
Authors: Li Jiaqi , Jin Shilong 
Published: April 2021

Abstract
In this paper, several different magnetic shielding schemes are proposed, the finite element static magnetic field analysis method is introduced, and the finite element method is used to simulate these methods. According to the calculation results, we analysed different magnetic shielding schemes, the results show that the opening will significantly reduce the magnetic shielding efficiency; under the same materials, the multi-layer magnetic shielding effect is significantly improved; when the opening is parallel to the direction of the magnetic induction intensity, the magnetic shielding has a better effect; when the direction of the magnetic field is unknown, the two-layer magnetic shielding opening direction can be orthogonal to improve the magnetic shielding effect.
On the Adaptive Damper System of the Electric Reactor Based on Magnetorheological Fluid
Authors: Tian Tian , Zhou Yuan , Yang Qiong , Wang Jingang , Xu Changjian 
Published: April 2021

Abstract
The electric reactor will generate irregular electromagnetic vibration during the onsite operation of substation. If so for a long time, it will cause problems such as broken indoor floor and loose connecting parts, endanger the building structure or damage to the building, thus leading to waste of land resources in indoor substation. In order to effectively suppress the irregular electromagnetic vibration of the electric reactor, this paper proposed an adaptive damper system of the electric reactor based on magnetorheological fluid to realize the all-around vibration suppression of reactor field vibration. This system placed the homemade damper in the center of each surface of the reactor, and used external filter circuit and signal amplification circuit to process the vibration signal and transform it into electrical signal, which controlled the single-chip microcomputer to regulate the damper to output the damping force, forming an adaptive damper system based on the magnetorheological fluid. Then, the good performance of vibration reduction of the system was verified by the onsite vibration reduction test of the reactor. And the adaptive regulate ability of the system is superior and is of good engineering application value.
Modeling and Simulation of Solid Oxide Fuel Cell Based On Neural Network
Authors: Wang Qianru , Wang Caixia 
Published: April 2021

Abstract
In order to study the effects of hydrogen input molar flow, oxygen input molar flow, water vapor input molar flow and real-time temperature on the output voltage of solid oxide fuel cell (SOFC), this paper proposes a method to model SOFC using a BP neural network optimized by immunogenetic algorithm (IA). MATLAB simulation results show that the SOFC model established in this paper can more accurately reflect the actual SOFC input and output characteristics. And the model has a high fit to the real data.
Research on Energy Storage Development Adapting to Large-scale Access to renewable Energy
Authors: Qing Ran Wang 
Published: April 2021

Abstract
Energy storage is the key technology for large-scale renewable energy access and energy Internet construction. Among the numerous energy storage technologies, the pumped storage and electrochemical energy storage are the fastest developing. In the paper, the present application status of the pumped storage and electrochemical energy storage is introduced. In this paper, the development prospect of energy storage and its impact on power system are analyzed, and the overall strategies and ideas to deal with the development of energy storage are put forward.
LiveEar: An Efficient and Easy-to-use Liveness Detection System for Voice Assistants
Authors: Yue Ling , Cao Chenhong , Li Yufeng , Li Jiangtao , Liu Qi 
Published: April 2021

Abstract
Voice assistants, such as Amazon Alexa, Apple Siri and Tmall Genie, using voice biometrics for the identity authentication, are becoming pervasive in our daily lives. However, voice assistants are vulnerable to reply attack due to the open nature of voice-input channels. An attacker can record the voice commands of victims and replay them to spoof voice assistants. Existing liveness detection approaches are mostly based on machine learning methods, which are expensive and complex. Recently, several approaches are proposed to leverage the human specific voice features or the distinctness of voice played by loudspeaker. However, they require the users and the voice assistant to be in a fixed position and at a very close distance, which is not user-friendly in practice. This paper proposes LiveEar, an efficient and easy-to-use liveness detection system for voice assistant. LiveEar utilizes the differences in phoneme positions between live-human voices and voices replayed through loudspeakers. Specifically, it calculates the time-difference-of-arrival (TDoA) in a sequence of phoneme sounds to the microphone on the voice assistant. Then, an SVM-based classification model is trained with the extracted TDoA features. This paper implements a prototype of LiveEar and evaluates its performance using real-world data. Results show that LiveEar achieves high detection accuracy in various flexible positions, with negligible runtime overhead.
A Robust Watermarking Scheme based on Delaunay Image Reconstruction Robust to Affine Transformation
Authors: Feng Liu , Gong Daofu , Wang Wenbing 
Published: April 2021

Abstract
This paper proposes a sub-channel image reconstruction algorithm based on Delaunay triangle. First, according to the different sensitivity of the human eye to the three color channels, different channels are used to avoid the influence of watermark embedding on pixels around the feature points. Then, feature points should be selected on the selected channel to make them have sufficient robustness. At this time, the location of the feature points extracted on the corresponding channel can be used as the watermark embedding position. Finally, considering the influence of geometric attacks such as affine transformation, this paper proposes a reconstruction algorithm based on Delaunay triangle, which uses feature point information to reconstruct the image before the watermark extraction, and extract the watermark on the reconstructed image. The effect of watermark extraction has been improved.
Design of Fast Locking and Locking Detection System of Frequency Synthesizer
Authors: Ge Yili , Jin Lingling , Shen Fei 
Published: April 2021

Abstract
In some electronic reconnaissance fields, fast frequency switching is required. A radio frequency signal generator with fast lock and accurate lock time appears to be of great significance. Traditional detection requires additional equipment, which is expensive and cumbersome to operate without portability. This paper designs a simple, portable and easy-to-operate lock detection method, uses a timer to monitor the LD pin of the phase lock chip in real time, optimizes the algorithm for capturing signal edge transitions, and calculates the frequency switching time. The ADF4351 fast lock mode is combined with lock detection to improve the topology of the loop filter and speed up the lock time. With the keyboard and LCD module, a radio frequency signal source system capable of self-checking and locking time is constructed. Simulation and actual results verify that after changing the filter structure to achieve quick lock, the lock time is optimized by 16%, which verifies the effectiveness of quick lock and the accuracy of lock detection, and realizes efficient and convenient lock time detection.
Transmission line image mosaic based on improved SIFT-LATCH
Authors: Dong Shilin , Lu Li 
Published: April 2021

Abstract
In the transmission line inspection, in order to obtain wide-view and large-scale images, it is necessary to stitch images taken by drones. This article proposes an improved SIFT-LATCH-based UAV aerial transmission line image stitching algorithm. First, the image is processed in parallel through multi-threading. The SIFT algorithm is used to extract the feature points in the image, and the LATCH descriptor is used to describe the feature points. The sampling consensus algorithm is used to purify the feature points, and finally the translational homography matrix is used to solve the problem of black lines in the stitched image. Experiments show that the algorithm proposed in the article has the advantages of good real-time and high accuracy in splicing UAV aerial pictures of transmission lines.
Phase Object Tomography Reconstruction Based on high-order Transport of Intensity Equation
Authors: Cheng Hong , Zhang Xiaolong , Wang Tianxiang , Zhu Xiaotian 
Published: April 2021

Abstract
The phase of the object contains the depth, shape, refractive index and other information of the object surface, which is more important than the intensity. As a classical phase retrieval algorithm, the Transport of Intensity Equation(TIE) can directly obtain the phase calculated from the known intensity. In this paper, a new algorithm is proposed to reconstruct the three-dimensional phase information of an object by tomography. The algorithm obtains high-precision phase input through the high-order TIE, and then reconstructs the three-dimensional phase information of the object by using Fourier slice theorem backprojection tomography. The experimental results show that the algorithm can solve the problem of low phase accuracy caused by intensity differential approximation constraints, and can obtain high-precision 3D phase reconstruction results of objects.
Design and Implementation of Convolutional Neural Network Accelerator Based on RISCV
Authors: He Yangyang 
Published: April 2021

Abstract
Internet of Things devices are faced with ever-increasing amounts of data, and they can no longer only do data collection as they did in the past, and hand over computing tasks to servers on the cloud. The growing computing requirements in the field of Internet of Things and the diversity of its scenarios put forward configurable and flexible customization requirements for customized processors. This paper conducts in-depth analysis and research on configurable customized processors, and analyzes related work in the field of RISC-V chips and deep convolutional neural networks in the field of device-side optimization at home and abroad. Based on this, this paper proposes an instruction and hardware design of a customizable deep convolutional neural network accelerator attached to Rocket-Chip Generator based on the RISC-V modular instruction set.
An Automatic Recognition Method of Fruits and Vegetables Based on Depthwise Separable Convolution Neural Network
Authors: Yuhui Zhan , Mengyao Chen , Yuefen Chen , Zhaoqian Luo , Yao Luo , Kedi Li 
Published: April 2021

Abstract
Traditional fruit and vegetable classification is mostly based on manual operation, which is inefficient. Deep convolution neural network shows excellent performance in feature learning and expression. In this paper, an automatic recognition system of fruits and vegetables based on deep convolution neural network is designed. By using depthwise separable convolution instead of the traditional standard convolution, a neural network is constructed with less parameters, which is suitable for equipment with limited resources. A small data set including 12 kinds of common fruits and 8 kinds of common vegetables is established for training and testing through network download and physical shooting. The experimental results show that the recognition accuracy reaches 95.67%.
Influence of different wavelet bases and threshold estimation on noise reduction of substation fault signals under different SNR
Authors: Zhang Na , Zhang Chenwei’ , Gao Xian 
Published: April 2021

Abstract
With the rapid development of power industry, the number of substations is also increasing, and the voltage level is also higher and higher, and the types of equipment are diverse. The detection of equipment fault signal in substation is an important part to ensure the normal operation of electric power. Only timely detection of fault signal and corresponding processing can ensure the overall operation of substation. But the fault signal often contains a lot of white noise, which will interfere with our judgment of the fault point. How to extract the effective signal from the noisy signal becomes particularly important, but under different signal-to-noise ratio, the selection of different wavelet basis and threshold estimation also have a great impact on the noise reduction effect. In this paper, we choose different wavelet bases and threshold estimation under several different signal-to-noise ratios to study their influence on the effect of signal denoising.
Design of Prescribed Performance Controller for Load Disturbance Interconnected Power System Based on Fuzzy Adaptive Backstepping
Authors: Lanzheng Chen , Guopeng Zhou , Xin Xia , Danping Sun 
Published: April 2021

Abstract
The complex structure of interconnected power system and the existence of external load disturbance make it difficult to establish accurate system model and realize stability control with preset performance. In this paper, a fuzzy adaptive controller design method with preset performance is proposed for uncertain interconnected power systems. Firstly, the system approximation model is obtained by using the fuzzy approximation principle, then the preset performance control strategy is introduced to transform the steady-state preset performance of the system into an error performance function. Finally, the adaptive controller design with preset performance is realized based on the Backstepping method. For the validity of the algorithm, the Simulink simulation is carried out. The results show that the controller can make the output of the system uniformly bounded, that is, the tracking error can always be controlled within the specified performance range.
Grasping points detection of garments based on deep learning
Authors: Shan Chunhua , Xie Yongping 
Published: April 2021

Abstract
Robotic manipulation for rigid objects is a relatively easy task, while grasping highly deformable objects, such as garments, is still a big challenge for robots. This research detects the grasping points of hanging garment using deep learning to facilitate robot manipulation. A neural network is proposed to predict the cartesian coordinates and visibility of predefined grasping points. In order to reduce the impact of different clothing colors, depth images are used for the input of the model. It is inaccurate and unrealistic to label data manually because of complex dynamics of clothes; therefore, synthetic dataset is leveraged to train the neural network. This paper makes use of generative adversarial network (GAN) to translate synthetic data to real data. A real dataset is acquired taken by Azure Kinect sensor as the test dataset. The experimental results indicate that our method can provide accurate prediction of the grasping points and can be applied to real scenarios.
Design and Test of a Multifunctional Mobile Manipulator Control System on an Experimental Platform
Authors: Ling Chen , Xing Xiaoyue , Li Zhe , Liu Liwu , Li Xiaolong , Guo Jie 
Published: April 2021

Abstract
Mobile manipulators (MMs) performing the tasks of autonomous navigation, object grasp and transportation are widely used in industrial production and other domains. This paper presents a control system with multiple functions and good extendibility for a commonly configured MM, which controls the multi-degrees of freedom (DOF) movement of the MM while navigating, positioning, pose estimating and object grasp. This system has shown desirable control performance on an experimental platform.