bluuebunny/crossref_metadata_2025_split huggingface dataset:
Urology during COVID-19 Pandemic Crisis: A Systematic Review
Authors: Thapa Bikash Bikram , Shrestha Dhan , Bista Sanjeeb , Thapa Suresh , Niranjan Vikram 
Published: January 2021

AbstractBackground Coronavirus disease 2019 (COVID-19) has evolved as a pandemic of unimaginable magnitude. The health care system is facing a tremendous challenge to provide ethical and quality care. The transformation of the patient-based care to population-based care during the COVID-19 pandemic has raised ethical dilemma among urologists. Our objective is to explore the consensus in modified standard urology care, that can be adopted and applied during COVID-19 and similar pandemic.Methods We adopted an exploratory study design using secondary data. The data were extracted from a web-based medical library using keywords “COVID-19,” “severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2),” and “urology.” We identify and extrapolate (screening, eligibility, and inclusion) the data using PRISMA protocol, and summarize pandemic standard urology care under four main themes: (1) general urology care, (2) choice of surgical modality, (3) triage, and (4) urology training.Result We identified 63 academic papers related to our research question. The majority are expert opinions and perspectives on urology care. The common consensus is triage-based urology care and surgeries. Life or organ threatening conditions need immediate attention. Universal protective measures (personal protective equipment, safe operative environment) and protocol-based patient care are necessary to prevent and control SARS-CoV-2 infection. Conservation of the resources and its rational distribution provide an ethical basis for population-based health care during a pandemic. Informed decision making serves best to patients, families, and society during the public health crisis.Conclusion COVID-19 pandemic tends to transform standard urology practice into crisis standard population-based care. The consensus in crisis is drawn from evolving pieces of medical evidence and public health ethics. The provision of urology care during a pandemic is based on the availability of resources; severity of the disease, consequences of deferment of service, and dynamics of the pandemic.
2.12 Asymmetric Catalysis of Radical Reactions
Authors: Subramaniann H. , Sibi M. P. 
Published: January 2021

AbstractSynthetic methodologies based on radical chemistry are efficient and powerful tools for the construction of carbon–carbon and carbon–heteroatom bonds. This chapter highlights the significance of asymmetric catalysis in free-radical reactions. Several asymmetric catalytic principles, ranging from early chiral Lewis acid and organocatalytic activation to recent photoredox and transition-metal-based asymmetric catalytic systems, are discussed.
Chinese description generation of dual attention images based on multi-modal fusion
Authors: Lv Xiyun 
Published: January 2021

Abstract
In view of the lack of attention to image features in most of the current research on image Chinese description generation, the low quality of image details, and the low accuracy of generated language description, a multi-modal fusion dual attention image description generation model is proposed. The model uses the pre-trained VGG19 network to extract image features, LSTM extracts key information features of text, and combines image features and text features through attention stitching to obtain the attention weight of each spatial position of the image, and then input it into the LSTM language model Generate descriptive sentences. In the AI Challenger 2017 test set, the BLEU-1 and CIDEr scores of this algorithm can reach 71.2 and 106.1 respectively, which are better than baseline models based on a single attention structure, such as NIC, and perform manual observation and comparison of the effects of several models. The model can generate natural language descriptions that can better represent the details of the picture.
An Improved Quasi-Resonant Controller for Grid-Connected Inverter with LCL Filter
Authors: Huang Yuhe , Zheng Shousen , Qi Xinmei , He Laipei 
Published: January 2021

Abstract
Aiming at the problem of insufficient response speed of traditional quasi-resonant controllers in the application of grid-connected inverters with LCL filter, a novel hybrid controller which combines a quasi-proportional resonant controller and an integrator is proposed in this paper. Base on this controller, the stability, the parameter design and the digital time delay compensation of the system are analyzed and designed in detail. Finally, its effectiveness is experimentally verified at Matlab/Simulink. By comparing with the traditional control method, it leads to a conclusion that the novel hybrid controller can maintain the control accuracy while allowing the system have good dynamic performance.
The SEIR model of COVID-19 forecasting rates of infections in New York City
Authors: Zha Jiajing , Liu Xiangdong , Sui Minggang 
Published: January 2021

Abstract
We used SEIR mathematical models to simulate the spread of COVID-19 in New York City, selecting a period of time to estimate the total number of infections and to predict the date of the highest number of infections. We found that the cumulative number of people infected or infected and the proportion of those infected increased with the increase in infectivity; The peak of infectious diseases is brought forward with the decrease of infectiousness; The number of people, Ir
+ Iu
(prevalence), and the estimated peak of the disease occurred on April 25. At R_0, the regeneration number is much higher than 1, which is proportional to the infection rate. Since the infectiousness of unreported cases is not known, we can predict the outbreak under three different scenarios and get reasonable results.
Studies on the evaluation of college classroom teaching quality based on SVM multiclass classification algorithm
Authors: Wu Xinghui , Zhou Yuping , Xing Haihua 
Published: January 2021

Abstract
In order to improve the evaluation accuracy and efficiency of the quality of classroom teaching in colleges and universities, combined with the teaching process and evaluation system of colleges and universities, a multi-class classification algorithm is proposed, namely, the Distance binary tree support vector machine based on Euclidean distance (DBT-SVM) algorithm, and the algorithm is used to predict the quality evaluation of classroom teaching in colleges and universities. The algorithm uses the Euclidean distance of the center of the two nearest sample classes to influence the classification, so that the first isolated classes can be separated first. Experimentally, the algorithm can improve the efficiency and accuracy of classification and solve the problem of multi-class classification.
A New Way to Evaluate Products with Reviews: A Case Study of A Hair Dryer on Amazon Platform
Authors: Jin Xiting , Liu Xiangdong , Xiangsheng Zhan 
Published: January 2021

Abstract
The era of big data is coming. How to make effective use of users’ feedback information data is the key to success in various online industries. In order to help target enterprise enter the market, we build a comprehensive rating evaluation model that can evaluate the sales status, future development and contain comprehensive indicators. We firstly study the one-dimensional index. We adopt the method of correlation analysis to find the ripple effect of star rating. Then we use SPSS to draw scatter plots to analysis correlation between specific quality description and star rating level. We found through the research that “star rating”, “comment validity”, “positive and negative indicator in comments” and “member effect” are all informative for target enterprise to track, and will determine the market development of the product to a certain extent. We take advantage of the machine learning to turn the information in the text into quantifiable metrics and get polarity and subjectivity. Use NLTK for sentiment analysis of each comment to get negative, positive, neutral and compound value. Then use AHP to assign weight to the indicators wisely. With the comprehensive rating evaluation model that we build, we calculate the comprehensive rating value of all products in this industry and take the median as the benchmark value, then the products with the comprehensive rating value higher than the benchmark value can be regarded as successful products. We provide an accurate assessment. In order to effectively evaluate and predict the future sales trend of new products after their launch and effectively measure the increase and decrease of product market reputation, we establish a time-based measurement and prediction model based on Grey model theory. We can use the model to make comprehensive evaluation and effective prediction of the target company’s products. After inspection, our model can be effectively applied to different sales fields, which has great practical significance.
Analysis of Massive MIMO&NOMA of 5G and Future Prospects
Authors: Liu Yincheng 
Published: January 2021

Abstract
Since the 1970s, mobile communication has evolved from analog voice communication to a technology that can provide high-quality mobile broadband services today. The data rate of end users has reached several megabits per second, and the user experience has been continuously improved. In addition, with the increase of new mobile devices, the continuous growth of communication services and the continuous increase of network traffic, the existing wireless technology can no longer meet the needs of future communications. The 5th generation mobile communication system (5G) came into being, and its technological development is still in the exploratory stage. This article discusses the key technologies of 5G, massive MIMO (Multiple input multiple output) and NOMA (Non-orthogonal multiple access), briefly introduces their principles, and analyzes the advantages and potential research directions. Finally, this article looks forward to the development trend of 5G technology.
HelpCloud: Hierarchy Health Evaluation for Private Cloud
Authors: Liu Yiming , Xu Peng , Lin Yajian , Yu Qihang 
Published: January 2021

Abstract
Although the private cloud technology is developing rapidly, the operation and maintenance of private cloud are still too complicated for many non-IT enterprises. System health evaluation for private clouds is beneficial to reduce operation and maintenance complexity and workload. This paper aims to provide an easy-to-use method to evaluate a private cloud's system health. Firstly, we propose the Private Cloud Management Object Model (PCMOM). PCMOM uses a hierarchical architecture to organize a variety of entities in the private cloud. Secondly, based on PCMOM, Hierarchy health evaluation for the private Cloud (HelpCloud) Model is generated using the Analytic Hierarchy Process and D-S evidence theory. In the end, a set of tests verified the effectiveness of the HelpCloud model. Moreover, the management portal for the private cloud which integrates the HelpCloud model is designed and implemented. After several enterprises' trials, these enterprises recognized that using the HelpCloud model could simplify the private cloud's operation and maintenance.
Research on Dynamic Content Control Method in Virtual Projection
Authors: Xiu Yulin , Zhang Yue 
Published: January 2021

Abstract
With the rapid development of virtual projection technology, it has been widely used in art, stage design, cultural communication and other industries due to its unique characteristics of combining virtual with reality and its advantages of strong interactive immersion. In traditional stage design, the projection position and coordinates of virtual projection are fixed in advance, and actors must remember the projected coordinates of virtual image during performance, so as to accurately match the projection. This imposes great limitations on the performance of actors, and due to the complexity of the stage, it is difficult to achieve good interaction effects. Starting from the novel "dynamic" control technology in the virtual projection, this topic studies the intelligent control method of dynamic content in the projection. In the video projection process, FBX model is loaded dynamically, and the animation on the model is loaded and called dynamically.
The Independent Set Polynomials of a class of Graphs
Authors: Liu Man , Cai Jin , Zhuo-mo AN , Tian Shuang-liang 
Published: January 2021

Abstract
In this paper, a special graph is defined. According to the structural characteristics of the special graph

C

1
,
d

1
,
n

, the independent set polynomial of a special graph

I

(

C

1
,
d

1
,
n

;
x

)

is derived by using the properties and lemma of independent set polynomial of simple graph. The Merrifield-Simmons index of this kind of special graph

C

1
,
d

1
,
n

can be obtained.
Performance Optimization Of Micro-Power Wireless Transmission Based On Hardware Test
Authors: Gui Jie Hui , Zheng LI , Zhang Xu Dong , Chen YongLi , Fei LI 
Published: January 2021

Abstract
Wireless communication system is more unstable than wired transmission due to the influence of transmission media. However, the micro-power transmission technology applied in the power system, the hardware parameter is more susceptible to various factors, resulting in unstable communication performance. By testing the RF parameter of transmitting and receiving signals of communication products in the laboratory, it can guide to optimize the hardware circuit and improve the communication performance of wireless transmission of micro-power, which has important reference value for hardware design
Characteristic Analysis of Monobit Signal
Authors: Ji Pengfei , Yang Xiao , Xia Chenglong , Lv Huan 
Published: January 2021

Abstract
This paper analyzes the characters of monobit signals and gives the reason why the spurious free dynamic ranges (SFDR) of monobit signals is much lower than those of multi-bit signals. According to our analysis and simulation, if the third harmonic of a monobit signal can be filtered, the SFDR of it can be improved well. Therefore, we give the way to obtain the desired band, which do not contain any third harmonics, and the simulation results are in agreement with our design. Such way can be used to improve the performance of monobit digital receivers in engineering.
A New Modulation Recognition Method Based on Wavelet Transform and High-order Cumulants
Authors: Chen Wenxuan , Jiang Yuan , Zhang Lin , Zhang Yang 
Published: January 2021

Abstract
In order to improve the recognition performance of digital modulated signals under low signal-to-noise ratio, this paper proposes a new method that combines high-order cumulants and wavelet transform to extract transient features, and the recognition of six kinds of modulation signals is realized through the neural network classifier. Simulation results show that the proposed algorithm can achieve good performance under low signal-to-noise ratio. In addition, only three key features are selected in this method, which greatly reduces the complexity of the algorithm. Furthermore, the effects of sample rate, carrier frequency and symbol rate on recognition performance are analyzed and simulated for the sake of better recognition performance.
On Star Coloring of Several Corona Graphs
Authors: Cai Jin , Tian Shuangliang , An Zhuomo 
Published: January 2021

Abstract
Let G be a simple graph with vertex set V(G) and edge set E(G). A vertex coloring of G is called a star coloring of G if any of the paths of 4 order are bicolored. The minimum number of colors required for a star coloring of G is denoted by χs
(G). The corona product of simple graphs G of order m and H of order n is graph G ∘ H with vertex set V(G ∘ H) = {vi
|i = 1,2,⋯m}∪{vij
|i = 1,2,⋯m, j = 1,2,⋯n}, in which vi
is adjacent to every vertex of Hi
if and only if, vi
∈ V(G), vij
∈ V(Hi
). According to the existing graph dyeing literature, it has become a very important technical means to study the graph dyeing problem by using the graph structure operation. Therefore, it is of great significance to study the star coloring of graphs for studying the acyclic coloring and distance coloring of graphs, the study has strong application background and great theoretical value for computing graphs. In this paper, we find the upper bound of χs
(G ∘ H) and the exact values of χs
(G ∘ H) of the corona product G ∘ H of two graphs G and H as: χs
(G ∘ H) ≤ χs
(G) + χs
(H); χs
(Pm
∘ H) = χs
(H) + 2; χs
(K
1,m
∘ H) = χs
(H) + 2; χs
(Cn
∘ H) = χs
(H) + 2, where n ≠ 5.
Modeling and analysis of pixel quantization error of binocular vision system with unequal focal length
Authors: Lin Danlan , Wang Zhenwei , Shi Hongsheng , Chen Hong 
Published: January 2021

Abstract
Current Analysis of pixel quantization error has following problems in the binocular vision system. Most literatures are based on the ideal binocular vision system with equal focal length. Moreover, the precision of pixel quantization is relatively low. In order to solve above problems, an analysis method of pixel quantization error for binocular vision system with unequal focal length is proposed. Firstly, a pixel quantization error model is established and a mathematical expression is presented to characterize the pixel quantization error model. Secondly, in the case of equal and unequal focal lengths, measurement error of object point is discussed respectively. Finally, simulation experiments were conducted and the effect of some parameters on measurement error was analyzed. Reasonability and efficiency of proposed methods are verified.
An ambiguity function transformation characteristic for Radar signal sorting
Authors: Han Jun , Hu Yang , Tang Tang , Zhao Xin , Li Mingwei 
Published: January 2021

Abstract
The sorting rate of current methods is not high and too sensitive to the signal noise ratio (SNR). In order to solve this problem, a novel characteristic for sorting radar emitter signal is proposed. The ambiguity function Radon curve of received signal is extracted, and then a rectangle pulse sequence and a triangle pulse sequence are constructed. Furthermore, resemblance coefficients of the ambiguity function Radon curve with two pulse sequences are extracted, and are used as the sorting parameters. The advantage of this new characteristic is validated by simulation result, and the lowest sorting rate is 90%at SNR=10dB.
A Hazy Image Restoration Algorithm via JND Based Histogram Equalization and Weighted DCP Transmission Factor
Authors: Zhu Zhu , Hu Jibao , Jiang Julang , Zhang Xiaoguo 
Published: January 2021

Abstract
This paper proposed a three-step hazy image restoration method. Firstly, in HSI color space, we proposed a novel histogram equalization algorithm based on just noticeable difference (JND) to enhance the hazy image. Secondly, we apply the dark channel prior (DCP) to remove the image haze and compute the weighted transmission factor map. Finally, we integrated the enhancement results and dehazing results by the weighted transmission factor maps adaptively, and then the restoration result is obtained. Since the proposed method takes account of visual perception, and well balance image enhancement and image dehazing. Therefore, it results in a more natural haze-free scene for the human visual system (HVS). Experiment results demonstrate that our method achieves better restorations compared with some other state-of-the-art approaches.
Application of m-ldpc codes in multipath Rayleigh fading channels
Authors: Zhou Hui , Wang Rui , Zhao Hairu , An Zhenzhou 
Published: January 2021

Abstract
The fifth generation mobile communication (5G) network has been commercialized on a large scale in the world in 2020, but the wireless communication channel as an important component is a complex and changeable environment. The signal is easy to be affected by the fast time-varying channel, serious multipath interference and Doppler frequency shift, resulting in large ISI and delay. Therefore, it is necessary to process the signal before transmission. In this paper, LDPC code is used as channel coding method to study the performance of m-ldpc code in 5G wireless channel. The simulation results show that the m-ldpc code can avoid the influence of multipath channel on the signal in 5G wireless channel.
Drone Presence Detection by the Drone’s RF Communication
Authors: Lv Huan , Liu Fang , Yuan NaiChang 
Published: January 2021

Abstract
Unmanned aerial vehicles (UAVs), also known as drones, are expected to play an essential role in future life. However, if drone technology is misused, it will bring unpredictable harm. For example, the use of drones to engage in illegal, criminal, and terrorist activities has brought new challenges to confidentiality, security, and counter-terrorism. The demand for anti-drone systems from all walks of life is rising. These systems can detect and prevent the activities of illegal drones, so that the technology of drones can be used well. This article introduces the current mainstream methods of UAV detection, and then uses the radio frequency (RF) control and map transmission signal exchanged between the drone and its remote controller to achieve a way of passive radio detection of drones.
Research on Multi-robot Scheduling Algorithm in Intelligent Storage System
Authors: Zhu Weikang , Liu Jicheng 
Published: January 2021

Abstract
As an indispensable core part of modern industrial system, intelligent storage system is developing from mechanical automation to robot intelligence. Intelligent storage system is widely used with multi robots, which can replace the picker to work efficiently and realize the effective connection of operation links. How to play the cooperative operation ability of multi robot is the key research content in this field. Based on the improved genetic algorithm, this paper designs a multi robot scheduling algorithm in intelligent storage system. The simulation results show that the scheduling efficiency of this method is improved by about 10% compared with the common genetic algorithm, and it has good stability. The multi robot scheduling algorithm in intelligent warehouse system based on improved genetic algorithm has good generalization.
Implementation of Detection System of Grassland Degradation Indicator Grass Species Based on YOLOv3-SPP Algorithm
Authors: Dong Shuo , Ma Yihan , Li Chunmei 
Published: January 2021

Abstract
Due to climate change and human factors, grasslands in the Sanjiangyuan area have degraded. At present, most grassland workers use manual methods such as visual inspection, measurement and remote sensing technology or neural networks to conduct macro evaluation of grassland. However, the emergence of grassland degradation indicator grass is an important sign for grassland degradation. Therefore, it is simpler and more convenient to provide early warning of grassland degradation through the detection technology of degradation indicator grass species. In this paper, the degradation indicator grass species Stellera chamaejasme was used as an example, and the YOLOv3-SPP algorithm was used to detect the degradation indicator grass species. First of all, collect and process data on the spot, and establish a data set of Stellera chamaejasme for deep learning; secondly, use YOLOv3-SPP algorithm to train and test the data set. By continuously improving the quality of the data set, the accuracy of model detection is improved. Then through the test of the verification set, the accuracy rate reaches 95% and the recall rate reaches 98%. It is proved that the model can be used to detect grassland degradation indicator grass species under complex grassland background. Finally, the detection system of Stellera chamaejasme with uploading and detecting functions is realized.