bluuebunny/crossref_metadata_2025_split huggingface dataset:
Searching for γ-ray emission from LOTAAS pulsars
Authors: Lu Qi-Wei , Wang Zhong-Xiang , Xing Yi 
Published: April 2021

Abstract
The LOw-Frequency ARray (LOFAR) has recently conducted a survey (LOFAR Tied-Array Allsky Survey; LOTAAS) for pulsars in the Northern hemisphere that resulted in discoveries of 73 new pulsars. For the purpose of studying the properties of these pulsars, we search for their γ-ray counterparts using the all-sky survey data obtained with the Large Area Telescope (LAT) onboard the Fermi Gamma-Ray Space Telescope (Fermi). We analyze the LAT data for 70 LOTAAS pulsars (excluding two millisecond pulsars and one with the longest known spin period of 23.5 s). We find one candidate counterpart to PSR J1017+30, which should be searched for the γ-ray pulsation signal once its timing solution is available. For other LOTAAS pulsars, we derive their 0.3–500 GeV flux upper limits. In order to compare the LOTAAS pulsars with the known γ-ray pulsars, we also derive the 0.3–500 GeV γ-ray fluxes for 112 of the latter contained in the Fermi LAT fourth source catalog. Based on the properties of the γ-ray pulsars, we derive upper limits on the spin-down luminosities of the LOTAAS pulsars. The upper limits are not very constraining but help suggest that most of the LOTAAS pulsars probably have < 1033 erg s−1 spin-down luminosities and are not expected to be detectable with Fermi LAT.
Research on the HIP 18856 binary system
Authors: Efremova Polina , Mitrofanova Arina , Dyachenko Vladimir , Beskakotov Anatoly , Maksimov Alexander , Rastegaev Denis , Balega Yury , Komarinsky Sergey 
Published: April 2021

Abstract
The results of a study on the binary HIP 18856 and construction of its orbit are presented. New observational data were obtained at the BTA of SAO RAS in 2007-2019. Earlier, Cvetković et al. constructed the orbit for this system. However, it is based on six measurements, which cover a small part of the orbit. The positional parameters of the ESA astrometric satellite Hipparcos published speckle interferometric data (Mason et al., Balega et al., Horch et al.) and new ones were used in this study. Based on the new orbital parameters, the mass sum was calculated and the physical parameters of the components were found. The obtained orbital and fundamental parameters were compared with the data from the study by Cvetković et al.. The comparison shows that the new orbital solution is better than the old one, since it fits new observational data accurately. Also based on a qualitative evaluation performed by Worley & Heintz, the new orbit was classified as “reliable”, which means data cover more than half of the orbit with sufficient quantities of residuals of measurements.
Automatic detection and correction algorithms for magnetic saturation in the SMFT/HSOS longitudinal magnetograms
Authors: Xu Hai-Qing , Liu Suo , Su Jiang-Tao , Deng Yuan-Yong , Plotnikov Andrei , Bai Xian-Yong , Chen Jie , Yang Xiao , Guo Jing-Jing , Wang Xiao-Fan , Song Yong-Liang 
Published: April 2021

Abstract
A longitudinal magnetic field often suffers the saturation effect in a strong magnetic field region when the measurement is performed at a single-wavelength point and linear calibration is adopted. In this study, we develop a method that can judge the threshold of saturation in Stokes V/I observed by the Solar Magnetic Field Telescope (SMFT) and correct it automatically. The procedure is to first perform the second-order polynomial fit to the Stokes V/I vs. I/Im
(Im
is the maximum value of Stokes I) curve to estimate the threshold of saturation, then reconstruct Stokes V/I in a strong field region to correct for saturation. The algorithm is demonstrated to be effective by comparing with the magnetograms obtained by the Helioseismic and Magnetic Imager (HMI). The accuracy rate of detection and correction for saturation is ∼99.4% and ∼88% respectively among 175 active regions. The advantages and disadvantages of the algorithm are discussed.
On the torque exerted by a warped, magnetically threaded accretion disk
Authors: Liu Chang , Li Xiang-Dong 
Published: April 2021

Abstract
Most astrophysical accretion disks are likely to be warped. In X-ray binaries, the spin evolution of an accreting neutron star is critically dependent on the interaction between the neutron star magnetic field and the accretion disk. There have been extensive investigations on the accretion torque exerted by a coplanar disk that is magnetically threaded by the magnetic field lines from the neutron stars, but relevant works on warped/tilted accretion disks are still lacking. In this paper we develop a simplified two-component model, in which the disk is comprised of an inner coplanar part and an outer, tilted part. Based on standard assumption on the formation and evolution of the toroidal magnetic field component, we derive the dimensionless torque and show that a warped/titled disk is more likely to spin up the neutron star compared with a coplanar disk. We also discuss the possible influence of various initial parameters on the torque.
Chaos-induced resistivity in different magnetic configurations
Authors: Wang Zhen , Wu De-Jin , Chen Ling , Hao Yu-Fei 
Published: April 2021

Abstract
It is widely believed that magnetic reconnection plays an important role in various eruptive phenomena of space and astrophysical plasmas. The mechanism of anomalous resistivity, however, has been an open and unsolved problem. The chaos-induced resistivity proposed by Yoshida et al. is one of possible mechanisms for anomalous resistivity. By use of the test particle simulation, the present work studies the chaos-induced resistivity for different configurations of reconnection magnetic fields and its distribution in different chaos regions of reconnection current sheets. The results show that the chaos-induced resistivity can be 6 – 7 orders of magnitude higher than the classical Spitzer resistivity in the X-type chaos regions and 5 orders of magnitude in the O-type chaos regions. Moreover, in the X-type chaos regions the chaos-induced resistivity of the magnetized case is higher by a factor of 2 to 3 times than that of the unmagnetized case, but in the O-type chaos regions the chaos-induced resistivity of the magnetized case is close to or lower than that of the unmagnetized case. The present work is helpful to the understanding of the dynamics of reconnection current sheets, especially of the generation mechanism of the anomalous resistivity of collisionless reconnection regions.
A Brief Analysis of Intelligent Voice Technology for China’s Mainstream Media Content Production and Distribution Implications —— Take the Application of IFLYTEK Series Products in Mainstream Media as an Example
Authors: Song B X 
Published: April 2021

Abstract
Intelligent speech technology including speech recognition (ASR) and speech synthesis technology (TTS), it is in China’s mainstream media plays an important role in technological innovation, appropriate use of this technology can improve the efficiency of the mainstream media content production and distribution of precision, while fully give play to the role of the mainstream media propaganda, to give the mainstream media fresh vitality, so as to promote China’s mainstream media communication effect. IFLYTEK, as a leader in the field of intelligent voice technology, has close cooperative relations with many mainstream media. By analyzing the application of IFLYTEK series products in mainstream media from the perspective of technology, we can better understand the impact of intelligent voice technology on the production and distribution of mainstream media content in China.
Research on Modified Wavelet Threshold Denoising Algorithm Based around SEMG Signal
Authors: Wang Meng , Deng Keyong , Gao Leilei , Wang Hao , Li Zhijun 
Published: April 2021

Abstract
The surface electromyography (SEMG) signal of the lower limbs is collected by attaching electrodes to the surface of the muscles of the lower limbs, so it is non-invasive and simple to operate. Selected the threshold and the threshold function is very important when used the wavelet threshold denoising method to process some non-linear SEMG signals. But the traditional threshold is a fixed value, which is not conducive to the improvement of the denoising effect. Present paper discusses the previous wave threshold denoising means aiming at their shortcomings, to this end, an improved threshold method is proposed in present paper, which can change the threshold with the number of decomposition layers. In the meantime, the shortcomings of the previous threshold functions can be overcome by the modified threshold function. The SNR and MSE is selected as the parameters to evaluate the denoising performance and comparing the modified wavelet threshold denoising arithmetic with the traditional threshold arithmetic, the experiment results indicated that the denoising impact of the modified arithmetic is better than the previous arithmetic and it has certain practical value.
Dynamic Scene Deblurring of Multi-Scale Progressive Attention Network
Authors: Huang Wenzhuo , Deng Yueming , Liu Yiming , Wu Jun , Li Xiaojun 
Published: April 2021

Abstract
In order to enhance the attention to the image foreground targets in dynamic scenes and better suppress the generation of image edge artifacts, a multi-scale progressive attention network (MSPA) deblurring algorithm is proposed, MSPA is based on the GAN structure. In the feature extraction stage, MSPA designs multi-scale width perception and pyramid perception residual blocks to help our skeleton network better extract multi-scale local features and reduce the difficulty of network training, and In order to better obtain the semantic information of the image, the channel attention mechanism is used to correct the deep features of the blurred image; in the feature fusion stage, the progressive channel and spatial attention network (PCSA) is designed to enhance the receptive field, and selectively integrate multiple levels semantic information and enhance the non-local connection between features in progressive method. A large number of experiments show that the MSPA algorithm is superior to many advanced algorithms on the GoPro and Kohler datasets.
High-Resolution Virtual Try-On Network with Coarse-to-Fine Strategy
Authors: Lyu Qi , Wang Qiu-Feng , Huang Kaizhu 
Published: April 2021

Abstract
In this paper, we propose a high-resolution virtual try-on network model based on 2D images, which can seamlessly put on given clothing to a target person with any pose. Under the coarse-to-fine strategy, we firstly transform the given normal clothes to warped clothes to well match the pose of the person by a clothing matching module, then these two generated images are combined to generate one fitting image of the person put on the given clothes by a try-on module, lastly utilize a Very Deep Super Resolution (VDSR) module to refine the generated fitting image. Compared to the 3D based methods that are computationally prohibitive, our method only needs 2D images, which is much faster. We evaluate our proposed model both quantitatively (i.e., in terms of SSIM) and qualitatively on a public virtual try-on dataset (i.e, Zalando). The experimental results demonstrate the effectiveness of the proposed method: generating visually better quality of images, our new method can improve the SSIM by 1.5%.
Research on Intelligent Damage Assessment System for Time-sharing Rental Vehicles Based on Image Recognition
Authors: Zhu Qianqian , Liu Yingnan , Shen Ying , Zhao Zihao 
Published: April 2021

Abstract
With the popularity of the concept of sharing, car sharing has become a new hot spot. Currently, there are more than 100 brands operating car sharing in the market. The group composition of car rental is relatively complex, and most of them are novices in driving technology. Some minor scratches and other injuries are easy to occur during the driving of rental vehicles, which poses new challenges to the car-sharing operation platform. Therefore, in the operation of car-sharing business, it is very important to realize the automatic determination of vehicle damage in the process of each use. This paper presents a method and system for automatic damage determination of vehicles based on the shared vehicle four-corner images. By comparing the damage information before and after renting each vehicle, this scheme can effectively save labor cost, realize rapid damage recognition, clear responsibility definition, and improve user experience and damage treatment efficiency.
Freehand Sketching Portrait Recognition with Least Square CycleGAN
Authors: Gou Xiaosa , Liu Bingguo , Liu Guodong , Lu Binghui , Gan Yu , Chen Fengdong 
Published: April 2021

Abstract
Freehand sketching portrait recognition refers to the recognition of sketched portraits and face photos drawn by artists. Existing research mainly involves inputting a given real portrait and converting it into a similar sketch portrait, and then matching the face with the sketch portrait in the real portrait database. This paper starts from the idea of inputting a sketch image to identify the real portrait in the database, focuses on the research based on the method of portrait synthesis, and introduces the existing methods of sketch portrait identification. We use the CycleGAN improved by least squares to achieve the translation from sketch to portrait, and finally PCA was used to complete face matching. The results show that LS_CycleGAN has certain advantages. Compared with other methods, its synthesis results are most close to the portrait. The average score of SSIM and PSNR is 0.844 and 17.331, and the average success rate of recognition is 88.2% for Rank10.
Diversity Regularized StarGAN for Multi-style Fonts Generation of Chinese Characters
Authors: Zeng Jinshan , Chen Qi , Wang Mingwen 
Published: April 2021

Abstract
The generation of stylish Chinese fonts plays a central role in many applications such as the design of art fonts and Chinese calligraphy generation. Most of existing methods focus on the generation of a single-style Chinese font, while few works focus on the multi-style font generation. In this paper, we exploit the star generative adversarial networks (StarGAN), a very popular generative adversarial networks (GAN) model recently developed in the literature, to realize the generation of multi-style Chinese fonts via a single model. Furthermore, in order to tackle the generation issue of Chinese characters having similar strokes for StarGAN, i.e., generating the same mode for these different but similar Chinese characters, we introduce a diversity regularizer such that the generator can generate high-quality characters with better diversity. A series of experiments are conducted on a handwritten Chinese character dataset called CASIA-HWDB1.1 and three standard printing font datasets to show the effectiveness of the proposed method. The experiment results show that the proposed method can effectively tackle the generation issue of Chinese characters having similar strokes in terms of the quality and diversity of generated results, via comparing to the baseline StarGAN, and is scalable to the multi-font generation via comparing to existing methods for the single-style font generation.
ResNet-50 based Method for Cholangiocarcinoma Identification from Microscopic Hyperspectral Pathology Images
Authors: Deng Yingjiao , Yin Jintao , Wang Yan , Chen Jiangang , Sun Li , Li Qingli 
Published: April 2021

Abstract
As the second most common primary liver tumour, the early detection of cholangiocarcinoma is very important. Computer-aided diagnosis based on deep learning using pathological tissue images is often used in cancer diagnosis. Compared with traditional RGB pathological images, hyperspectral image has more advantages in deep learning based automatic pathological diagnosis because it contains spectral dimension information. In this paper, a ResNet-50 based method is used to identify cholangiocarcinoma from microscopy hyperspectral images. The microscope hyperspectral choledoch tissue images are captured by our microscopy hyperspectral imaging system (MHIS) and annotated by experienced pathologists manually. After pre-processing and data argumentation, we split them in to training set (6800 images) and testing set (210 images) and choose ResNet-50 structure to train the classification model. The classification model can automatically classify the choledich tissue images into cancerous and non-cancerous regions. Our experimental results show that the accuracy of proposed method is 82.4% in case of ResNet-50 structure.
Design Innovation Driven by Artificial Intelligence AI Multifunctional Wheelchair Design Based on the Needs of Patients with ALS
Authors: Liyao Rong 
Published: April 2021

Abstract
With the maturity of artificial intelligence technology, the integration of artificial intelligence and the medical and health fields has become more and more closely. The improvement of technology has played an important role in the development of the medical and health industry and has provided more possibilities for the treatment and rehabilitation of rare diseases. In mechanical design, integrated and innovative design methods can better discover the needs of patients, better reflect the advantages of technology and solve practical problems. Under the guidance of design thinking and inclusive design, this article will study the life needs of patients with amyotrophic lateral sclerosis (ALS) and the nursing needs of nursing staff, and integrate artificial intelligence technology to propose innovative solutions to users Solution-Design an AI multifunctional wheelchair dedicated to ALS patients to provide intelligent methods and paths for the rehabilitation and care of ALS patients.
Construction and Application of Comprehensive Evaluation Model of “Golden Classroom”
Authors: Zhang Deran , Chen Rui , Yuan Yunyun 
Published: April 2021

Abstract
The survey shows that the intensity of learners’ interest in courses is the strong positive energy for the construction of “Golden Lessons”, and the optimization of classroom teaching is the primary factor among many factors in the construction of “Golden Lessons”. The director who constructs the “golden lesson” is the teacher, the main body is the student, and the measurement of the “golden content” is the classroom teaching. Therefore, the continuous “Golden Classroom” is an inevitable move to build a “Golden Lessons”, it is imperative to find the evaluation standard of “Golden Classroom” scientifically and reasonably. Based on this, through the combination of qualitative and quantitative, using the principle of fuzzy mathematics, a comprehensive evaluation model of “Golden Classroom” is constructed, and the standard score of the final evaluation result is used to give the threshold of “Golden Classroom”. For the objective determination of “Golden Classroom”, building “Golden Lessons” has certain theoretical enlightenment and application value.
Optimization of E-Commerce Logistics System Based on Artificial Intelligence Technology
Authors: Lv Jian 
Published: April 2021

Abstract
With the improvement of China’s social and economic development level, the requirements for logistics efficiency are becoming more and more stringent. Artificial intelligence technology is the current direction of vigorous development. With the development of the Chinese era, in order to better promote the development of China’s urbanization, this technology has been widely used in various fields in our country and occupies an important position in various fields. With the continuous innovation of artificial intelligence technology, various industries are undergoing industrial upgrading and format conversion. E-commerce logistics bear the brunt. This article mainly discusses the application of artificial intelligence in the e-commerce logistics system, and applies it to the e-commerce logistics industry. With the help of artificial intelligence algorithms, it is used to accurately calculate the supply and demand relationship of goods and the optimal path of actual logistics distribution. The selection provides algorithm-level support. The use of artificial intelligence can not only accurately predict inventory, but also play a role in optimizing inventory measures. With this technology, the automation level of the logistics sorting period can be effectively improved, highlighting the application value of artificial intelligence technology and promoting China the development process of modern e-commerce logistics industry makes it possible to develop in the direction of intelligence and automation. The experimental results show that the e-commerce logistics industry has great convenience for the sales and transportation of goods under the condition of combining artificial intelligence technology, and it has higher efficiency than traditional e-commerce logistics.
Analysis on the Application of Cause Intelligence Financial Management System Based on Artificial Intelligence Environment
Authors: Zhu Xiangping 
Published: April 2021

Abstract
In recent years, artificial intelligence has made great progress in the field of science and technology, and has played a substantial role in the development of real life. At present, China’s financial management system is still in the basic stage, mainly relying on manual work, financial software informatization has achieved results, but the promotion of intelligence is relatively slow, cannot provide good prediction and decision-making scheme for people. This paper analyzes the current situation of the application of artificial intelligence technology in intelligent financial management system, and puts forward the application analysis of the cause intelligent financial management system based on the artificial intelligence environment. In this paper, through the investigation and analysis of 220 financial personnel and system R & D personnel, as well as the comparative analysis of the specialization, rationalization and intellectualization of the financial management system after the application of artificial intelligence, and the discussion and analysis of the results, put forward the application advantages of artificial intelligence in the financial management system, which provides guarantee for the development of intelligent financial management system. The research in this paper is of great significance to the further integration and development of the two, to find problems and to put forward constructive suggestions on the application of artificial intelligence technology in the cause intelligent financial management system.
The Influence of 5g on the Development of Electronic Information Engineering
Authors: An Na , Wang Lei , He Zhenquan 
Published: April 2021

Abstract
With the rapid development of the times, our quality of life is also rising rapidly. At present, our technology has undergone a round of rapid development and achieved certain results. The era of artificial intelligence based on computer technology has come, and our life begins to embrace and contain this new technology, so modern life is the era of artificial intelligence. So, the new technology has brought many changes. For example, in Information Engineering, we can replace manual operation with preset programming to increase efficiency and reduce error rate. So, how to program is a difficult problem. Therefore, this paper studies the influence of 5g on the development of electronic information engineering. In order to better carry out the experiment, we first set the general direction and overall tone of the experiment we need to do after consulting a large number of literatures. Then we borrowed a period of time from the laboratory to conduct real experiments. But before that, we also carried out simulation experiments to reduce errors, and then conducted real experiments (in this case, we used interactive system to model and calculate the number) According to the rationality, the experimental results are obtained. The experimental results show that after the improvement of artificial intelligence, 5g can increase the reliability of NC programming and the simulation of machining process.