bluuebunny/crossref_metadata_2025_split huggingface dataset:
Long-wave infrared InAs0.6Sb0.4 photodiodes grown onto n-InAs substrates
Authors: Klimov A A , Kunkov R E , Lavrov A A , Lebedeva N M , Lukhmyrina T C , Matveev B A , Remennyi M A 
Published: April 2021

Abstract
The results of a study of multilayer photodiodes based on InAs1-

x
Sb
x
solid solutions (0.3 < x <0.4), with a long-wavelength cut-off of λ

0.1
≈ 11 μm at room temperature are presented. The current-voltage and spectral characteristics of photosensitivity and electroluminescence were analyzed in the temperature range of 80 ÷ 300 K. Experimental samples of photodetectors are characterized by a quantum efficiency of 0.23 at 150 K and a diffusion mechanism of current flow at least in the 200-300 K range. The detectivity of the immersion lens PD at the maximum has values of at least D*8 µm = 8·108 and D*
5.5 µm = 1010 cm·Hz1/2W-1 at 300 and 150 K, respectively.
A comprehensive study of impulse pumping of Ti:Sapphire by AlInGaN LEDs
Authors: Ivanov A E , Aladov A V , Chernyakov A E , Talnishnikh N A , Zakgeim A L 
Published: April 2021

Abstract
LEDs operating under high pulsed current density, which excludes self-heating, are of great interest for different applications, in particular, for pumping lasers with a short time of activator relaxation, such as Ti:Sapphire. The current dependences of the efficiency emission spectra as well as the rise and fall times of high-power blue and green LEDs were investigated under extremely high pulse current density up to 7 kA/cm2 and a pulse duration of 100 ns to 3 μs. An analysis of the pulse behaviour of the LEDs reveals that the main droop in efficiency and a change in the spectrum occur up to the current densities ∼ 1 kA/cm2 and seem to be non-thermal. The energy and spectral pulse characteristics of the radiation were studied with simultaneous recording the excited Ti:Sapphire photoluminescence in order to determine the optimal pumping conditions.
Electro- and magnetotransport properties of a WTe2 single crystal
Authors: Domozhirova A N , Naumov S V , Podgornykh S M , Marchenkova E B , Chistyakov V V , Semiannikova A A , Huang J C A , Marchenkov V V 
Published: April 2021

Abstract
A single crystal of a topological Weyl semimetal WTe2 was grown and its electrical resistivity and galvanomagnetic properties (magnetoresistivity and the Hall effect) were investigated in detail in the temperature range from 1.8 K to 300 K and in magnetic fields of up to 9 T.
Human Resource Management Mode Based on Big Data
Authors: Wang Zhou 
Published: April 2021

Abstract
With the rapid development of Big Data(BD), more and more scholars of human resource management pay attention to its huge business opportunities and information value, so they begin to study and explore the innovation and reform of the company’s human resource management mode, in order to break through the difficulties in the traditional human resource management mode. In the process of motivating knowledge-based staff in Colleges and universities, university managers are based on BD platform to provide support for improving the competitiveness of the University, promoting the overall development and long-term progress of the University, and realizing the modernization of management. Based on this background, this paper analyzes the reform of BD into enterprise human resource management mode Sever database as an example, by calculating the efficiency of two kinds of human resource management and investigating the satisfaction of the company’s employees, this paper shows the role of two kinds of human resource management modes for enterprises and employees with practical data, reflects the advantages of human resource management mode based on BD platform, and discusses the specific reform and application of BD in human resource management mode.
Chinese and Western Art History Based on Big Data
Authors: Wang Jing 
Published: April 2021

Abstract
After entering the era of big data, artificial intelligence has developed rapidly, and the contradiction between technology and humanities has become increasingly prominent. World culture, technology, and art are all facing new conflicts and challenges. This article mainly studies the development and experience of Chinese and Western art history based on big data. This experiment uses an ordinary computer to build a Spark cluster environment by setting up 6 virtual hosts. Chinese artists are always more inclined to subjective creation, while the traditional Western realistic painting in the Renaissance period paid more attention to the three-dimensional painting color while achieving the harmony of the picture. Then sample the fingerprint at the reference point of the sparse density distribution to cluster the indoor area into a specific number of sub-regions, and use the sampling data of each sub-region to predict the fingerprints at other unmeasured reference points to reconstruct the complete Fingerprint database. The data shows that in the experimental cluster environment, when the processing data size is 50MB or far greater than 50MB, choosing parallel algorithms can save data processing time and improve data processing efficiency. The results show that both Chinese painting and Western modernist painting pursue the spontaneity, randomness and contingency of painting in terms of aesthetic effects. This is the common ground of the pursuit of expressiveness in Chinese and Western paintings.
Aesthetic Differences Between Chinese and Western Cultures Based on Big Data Analysis
Authors: Zhang Qi 
Published: April 2021

Abstract
With the development of the times, the gradual integration of Chinese and foreign civilizations and the continuous expansion of people’s living circles, the aesthetic consciousness of the interior space design of Chinese and Western residential buildings is also changing. The purpose of this article is to analyze the aesthetic differences between Chinese and Western cultures based on big data, analyze the clustering algorithms for aesthetic differences between Chinese and Western cultures, and conclude that different clustering algorithms have their own blind spots and misunderstandings for different data calculation processes. Aiming at the spatial distribution characteristics of aesthetic difference data between Chinese and Western cultures, an improved spectral clustering algorithm is proposed to better solve the problem of clustering and mining of aesthetic difference data between Chinese and Western cultures. The experimental results show that the fast clustering algorithm suitable for the aesthetic difference data sets of Chinese and Western cultures, the improved algorithm reduces the time of the traditional spectral clustering algorithm by 2%.
RETRACTED: Oil Painting Material Collection System Based on Artificial Intelligence
Authors: Peng Jianzhong 
Published: April 2021

Abstract
In recent years, with the rapid development of computer technology and artificial intelligence technology, the traditional oil painting creation field has also had a lot of influence. The most typical way to collect and manage materials in the future is to collect and manage materials through the Internet. Therefore, this paper puts forward the research of oil painting material collection system based on artificial intelligence. In this paper, the artificial intelligence technology and oil painting material collection work are deeply studied. The analysis shows that the traditional oil painting material collection work has obvious problems such as low efficiency, high cost and low accuracy. And through artificial intelligence technology, we can better solve these problems. According to the characteristics of oil painting material collection, combined with the latest artificial intelligence information collection technology, this paper establishes an intelligent system suitable for oil painting material collection. In order to further verify the actual effect of the collection system in this paper, the corresponding comparative experiments are established. The experimental data show that the highest accuracy rate of the artificial intelligence material collection system in this paper is as high as 99.6%, which is significantly improved compared with the 87.6% accuracy rate of the traditional artificial material collection method. Moreover, while ensuring the accuracy rate, the number of collected materials has been greatly improved. Analysis shows that this system effectively improves the efficiency of oil painting material collection.
RETRACTED: Jilin Province’s All-for-one Tourism Based on Artificial Intelligence and Synergy Theory
Authors: Li Jun 
Published: April 2021

Abstract
In modern society, the all-for-one economy is booming, and the economic level of the general public is also improving. After people have met their material needs, their spiritual needs are constantly increasing. Therefore, the tourism industry has achieved good development. As one of the important branches of system science, synergy theory is a discipline that studies the mechanism and law of orderly structure formed by open systems through the synergy between internal subsystems. It is the theoretical basis for constructing various systems and a method to solve complex system problems. Introducing synergy theory into all-for-one tourism research and studying all-for-one tourism development issues from a systematic point of view is of practical significance for solving various comprehensive and complex issues that have always occurred in the development of tourism. As the current hotspot of high-tech and new technology development, artificial intelligence technology has gradually been widely used in all aspects of social production and life, especially for the development and promotion of all-for-one tourism. Therefore, in the development of the global domain, increasing the application of artificial intelligence technology also has positive practical significance. Artificial intelligence technology can promote the development of all-for-one tourism to improve quality and efficiency, and bring tourists a brand new travel experience. This article discusses the application of artificial intelligence and synergy theory in the all-for-one tourism of Jilin Province, and explores a scientific, effective and sustainable tourism model. The experimental results show that all-for-one tourism with the introduction of artificial intelligence and synergy theory is more in line with the current pace of life and living habits of young people, which is bound to be positive and beneficial to promote the development of all-for-one tourism in Jilin Province.
Research on Image Deblurring Processing Technology Based on Genetic Algorithm
Authors: Xi Erhui , Zhang Jiali 
Published: April 2021

Abstract
Image deblurring, which is an important branch of digital image processing, is one of the difficulties in digital image processing. The main goal of image deblurring is to improve the quality of the given image, and to reconstruct or restore the original image using the relevant prior knowledge. Genetic algorithm (GA) is a global optimization search algorithm, which can quickly and effectively calculate complex multidimensional data area and indirectly. Now,genetic algorithm is slowly showing its excellent performance in the field of image processing. Therefore, based on the fuzzy features of the image, this paper uses the image enhancement algorithm to realize the image deblurring by capturing the gray value of the pixels in the image, and the improved genetic algorithm is used to better select the image threshold. The experimental results show that the new algorithm obtains higher definition than the traditional image deblurring method, and the improved genetic operator algorithm improves the degree of noise reduction.
The Design and Implementation of a Noise Reduction System for a Microcomputer Cooling Fan
Authors: Gong Jianhu 
Published: April 2021

Abstract
In view of the noise caused by the CPU inside the mainframe box, and the cooling fan of power unit, this paper comes up with a noise reduction device, comprising a polyurethane sound-insulating cotton layer, a wood-wool sound-absorbing board, a temperature detector and a cooling fan, etc. and illustrates its implementation method.
RETRACTED: Research on the Reform of Ideological and Political Theory Courses in Colleges and Universities in the Big Data Era
Authors: Guan Yong 
Published: April 2021

Abstract
The continuous progress of information technology provides favourable conditions for colleges and universities to innovate teaching methods and develop new teaching systems. Colleges and universities are important places for the generation of network information, and many of the contents contained in these network information are of great value to the teaching of ideological and political courses and campus management in universities. How to collect college campus network information, analyse and manage this information, and find hot topics from it, has a profound impact on the reform of college ideological and political courses. Based on this, this article attempts to design a system program that can be used to analyse hot topics in colleges and universities, and introduces the design from several aspects such as design goals, demand analysis, functional architecture, and module design. It can provide a certain reference for college ideological and political courses.
Research on Unmanned Ship Control System Based on Fuzzy PID
Authors: Huo Huwei 
Published: April 2021

Abstract
Unmanned ship is one of the typical representatives of unmanned intelligent equipment on water, which has been highly concerned by scholars all over the world. Since unmanned ship is unmanned in the process of surface operation, it must have the corresponding autonomous intelligence, which requires the stability of its autonomous control to be studied. This paper presents a control system of unmanned ship based on Fuzzy PID. The anti-jamming control system of unmanned ship is built. According to the power demand of unmanned ship control system, the hardware circuit is designed and the software code is written. Then the simulation experiment of the interference model in complex environment is carried out. Under the regulation of the control system, the unmanned ship can meet the requirements of fast response and high reliability.
MRI Image Reconstruction Based on Artificial Intelligence
Authors: Liang NaNa 
Published: April 2021

Abstract
Artificial intelligence is a new high and new technology, which has powerful functional advantages in processing big data, complex and non-deterministic data, and in-depth mining of hidden information behind the data. Magnetic resonance is a common diagnosis and treatment technology in medical clinics. The use of magnetic resonance imaging technology to construct medical images has a great auxiliary effect for doctors to make accurate medical diagnosis. This article proposes to combine artificial intelligence and magnetic resonance technology to construct magnetic resonance images based on artificial intelligence, in order to reconstruct high-quality magnetic resonance images, thereby improving the efficiency of doctors’ diagnosis and treatment and reducing misdiagnosis. This paper uses the deep learning algorithm of artificial intelligence to compare the analytic dictionary method, the synthetic dictionary method and the deep dictionary method based on convolutional neural network, and obtain the peak-to-noise ratio of the image reconstructed by the three algorithms under the same sampling rate. They are 42.56, 44.17 and 45.55 respectively; the structural similarity is 0.9387, 0.9536 and 0.9867, respectively. The study concluded that the deep dictionary method based on convolutional neural network has more advantages in reconstructing MRI images, and the effect is more obvious.
Geological Disaster Early Warning Model Based on Big Data
Authors: Liu Pengcheng 
Published: April 2021

Abstract
As a country with high frequency of geological disasters, China still faces many problems in dealing with geological disasters and reducing economic losses. In recent years, with the deepening of the research on geological disaster early warning, as well as exchanges with various institutions and learning experience, we have made some achievements in how to carry out geological disaster early warning, which has become a major driving force for social development. Nowadays, people mostly deal with geological disasters with certain human intervention. This paper relies on the “big data analysis” and mathematical conventional statistical analysis in recent years, and carries out a series of experiments to establish the early warning model, and carry out corresponding analysis on the multiple attributes of the model, so as to explore the usability of the early warning model in the future geological disasters. In this paper, the corresponding exploration of geological disasters in recent years is carried out. Correlation analysis and statistical analysis are carried out in the aspects of year, disaster frequency, loss and early warning, and the prediction model is established. It is found that with the development of time, the occurrence times of geological disasters are uncertain, and people pay more attention to the early warning of geological disasters and face the loss caused by geological disasters It will decrease gradually.
RETRACTED: Research on Personalized Healthy Diet Recommendation Based on Artificial Intelligence
Authors: Tang Xiaoxuan 
Published: April 2021

Abstract
With the development of the Internet, China’s good data mining technology in e-commerce has achieved development, and the recommendation service has gradually become popular and has been adopted by the majority of citizens. In order to facilitate people to quickly find what they need from a large number of commodities and save consumers’ time, the recommendation system pays more and more attention to the user experience. This paper constructs a healthy diet recommendation model based on improved Apriori. When judging the user’s dietary preferences, the improved Apriori algorithm is used to recommend the diet. The original algorithm and the improved algorithm are compared to the same example. The results show that the improved algorithm has advantages in mining association rules and can better realize personalized healthy diet recommendations.
Enterprise Financial Shared Service Platform Based on Big Data
Authors: Xiong Lilan 
Published: April 2021

Abstract
With the advent of the era of big data, the market economy continues to develop in depth, and the social division of labor is becoming more and more refined. The financial sharing platform service center can realize the transformation of financial management functions from financial accounting to management accounting according to the strategic needs of enterprises. Prevent financial risks in a timely manner, provide strong endogenous vitality and back-up support for corporate management, and promote the development of corporate economies of scale. The purpose of this paper is to study the corporate financial shared service platform based on big data. This article compares and analyzes the difference between the traditional “financial management mode” and the “shared service mode”, and at the same time proposes the impact of information technology on the financial sharing platform services in the era of big data, and then conducts the construction process and operation management status of the company’s financial sharing platform service center Describe, analyze and discuss its implementation results, existing problems, opportunities and challenges at this stage, and propose measures to be improved in response to existing problems, and put forward suggestions for optimization of the company’s financial sharing center based on the background of the big data era. The company was selected as a case study to explore its motivations for implementing the financial sharing platform service, to explain its construction plan in detail, and to analyze the benefits from different aspects. Research shows that more than 80% of the company’s accounting business vouchers are automatically generated by the business-driven system. Compared with traditional accounting methods, both the timeliness and accuracy of accounting treatment have undergone a qualitative leap.
Innovative Research on German Education Teaching Mode in Colleges and Universities from the Perspective of BD
Authors: Yan Chengcheng 
Published: April 2021

Abstract
With the needs of economic development, many colleges and universities offer German courses. However, because German course has just started in domestic universities, its teaching method is more simply to apply the ordinary German teaching mode, without too much consideration of the characteristics of higher education, and its teaching effect is not satisfactory. Therefore, the purpose of this paper is to make innovative research on German teaching mode in colleges and universities from the perspective of big data(BD). Firstly, this paper discusses the current situation of German teaching mode construction and resources in Chinese universities, and summarizes the main problems existing in contemporary German teaching mode in Chinese universities. The new teaching mode of German in colleges and universities puts the feelings of college students in the main position, guides students to learn actively through behavior guidance, and pays more attention to students’ communicative competence. This teaching mode also utilizes the storage architecture of data warehouse, combined with BD and other related technologies, and realizes the storage and update of various German teaching resources, which meets the innovative needs of universities for German teaching mode. Finally, this treatise compares the innovative modes of teaching German in universities with traditional modes of teaching. Experimental results show that the innovative mode of teaching German in college is recognized and loved by students, and their love for German has increased by about 30%, which plays a significant role in improving students’ enthusiasm for learning German and provides an important reference for the innovative research of German teaching mode in colleges and universities.
The Design of the Network Remote Interactive Livestock and Poultry Feed Formula System
Authors: Zhang YingYing , Ji MeiNan , Zhang KaiZhe , Zhang Yuge 
Published: April 2021

Abstract
In response to the current scientific requirements for livestock and poultry feeding, combined with current network technology, a remote livestock and poultry feed formulation system is proposed. In this system, the requirements of the system are analyzed first, and then the overall system architecture is constructed according to the requirements. Based on the construction of the overall structure, the main feed formula of the system is optimized by algorithm. Finally, the result of feed formula optimization is given.