bluuebunny/crossref_metadata_2025_split huggingface dataset:
Possible Implementations of Oracles in Quantum Algorithms
Authors: Zhao Jiahao 
Published: December 2022

Abstract
Quantum computing is an inspiring technic on solving complicate problems, which shows the superiority over the classical computing. Contemporarily, the quantum-based algorithms were invented in many purposes on solving those problems. The thing is some of the algorithms were composed with oracles, which can be treated as a black box. It can be worked out/analyzed in theoretical mathematical expressions, but it can never fall in the ground without those actual implementations. Therefore, this paper will illustrate the idea and possible implementations on some quantum algorithm. Among various algorithms, this research will choose those relatively famous quantum algorithms, i.e., Deutsch-Jozsa Algorithm, Shor’s Algorithm, and Grover’s Algorithm. Different algorithms have the different intrinsic logics, which means there is no general description for all solution in this problem, but all of those can achieve the goal according to the same framework. Since those oracles are black boxes that can only be analyzed by its behavior with different cases, and then based on the behaviors and cases, and in IBM quantum platform, one can fill out the oracle by manipulate with different quantum operators. Lastly, the figures of some the possible implementation of those oracles with the three quantum algorithms will be shown in the IBM quantum platform, as well as the histograms of probability distributions that can justify the correctness of the implementations. These results shed light on guiding further exploration of the design and analysis on quantum algorithms.
An Overview of the ITER Project
Authors: Geng Shuaibo 
Published: December 2022

Abstract
ITER (initially the International Thermonuclear Experimental Reactor) is the most perspective project to achieve fusion energy. In this article, the origin of the ITER project, fundamental members and how the design of Tokamak provides the demand or suitable conditions for ITER to achieve its scientific or experimental goals will be discussed. In addition, the technological improvements in several different aspects and how it can function under different situations will be introduced. The principle of nuclear fusion and nuclear reactor and how the energy is created and conserved in the whole process will also be explained. This will lead to the significant problem that is considered the relationship between the ITER project and new energy resource form. The future prospects of this type of future energy resources and comparison with other present energy recourses will be discussed as well.
Analysis Concerning the Problem of the Optimal Delivery in Three Towns
Authors: Gong Yuxin , Xiang Jianxin , Yao Jiawei 
Published: December 2022

Abstract
The aim intimately pertinent to this research program is to use constructive mathematical notions to analyze how constructive real numbers and rational numbers are likely to have an influence on the outcomes involving economic problems. Researchers endeavor to find a computer program to determine the optimal location of a production plant and to find out that provided that the distances from the production plant to the sales location are rational numbers, then the problem is algorithmically solvable, though, if the distances are constructive real numbers, then the existence of the computer program that solves all such problems will not be possible.
Integer Solution for a Class of Indeterminate Equations
Authors: Zong Qi 
Published: December 2022

Abstract
The mathematical discipline of number theory has a long history. It originated in the ancient Greek period in natural mathematics and geometry. With the progress of science and technology, people began to recognize the importance of “number,” which led to the rapid development of number theory and gradually becoming an independent discipline. Indeterminate equations are one of the most important branches of number theory and have always received a lot of attention from the mathematical community. The problem of integer solutions of indeterminate equations was also called the Diophantus equation because of the profound study of these equations by Diophantus in the early third century. However, there is no unified method for solving the Diophantus equation today, so the investigation of its integer solution often needs to be combined with previous studies. This paper focuses on the application of Gaussian rings of integers and congruence theory to the study of integer solution problems for indeterminate equations of the form x^2+4^k=4y^n (k=1,2 n=3,5..). The study generalizes the understanding of the local distribution rules in specific situations, which helps to simplify the discussion of the classification of this category of problems and provides alternative ideas for subsequent more in-depth studies by others. This paper concludes that every such indeterminate equation can be discussed in x ≡ 1 (mod 2) and x ≡ 0 (mod 2). A template for discussion is provided for the first scenario, and only when 2k-1=n can there exist only an integer solution (x,y)=(±2^k,3) for the second scenario.
The Scope of Application of Letter Frequency Analysis in Substitution Cipher
Authors: Pan Yining 
Published: December 2022

Abstract
Since its inception, substitution ciphers have been a popular type of cipher, and over time, academics have studied them in an effort to discover patterns that will allow them to be broken. They created it because substitution ciphers are a reasonably simple type of cipher. Through a survey of the literature, this paper investigates the encryption and decryption of three sub-types of monoalphabetic ciphers: shift cipher, affine cipher, and random substitution cipher. Letter frequency analysis is the foundation of the primary decryption technique. After that, two sub-kinds of monoalphabetic ciphers, Hill cipher and Playfair cipher, which are resistant to this decryption method because the letters encrypted hardly keep the original frequency, will be introduced. The paper shows that statistical analysis of letter frequency is only useful for deciphering single-table substitution ciphers.
Applications of Advanced Mathematics in The Field of Economics
Authors: Sun Yibing 
Published: December 2022

Abstract
The application of mathematics permeates different fields, especially in the field of economics. The connection between economics and mathematics is indispensable. It can also be said that the problems and research in the economic field are inseparable from the support of mathematics. This paper explores the connection between advanced mathematics and economics and its application in economics through the literature review method. Through example studies, the paper finds that only by choosing appropriate mathematical methods for different economic problems can economic problems be solved effectively.
Different Algorithms to Solve a Rubik’s Cube
Authors: Chen Juntao 
Published: December 2022

Abstract
This essay introduces and compares four methods to solve a Rubik’s cube which are Korf’s algorithm, Thistlethwaite’s algorithm, Kociemba’s algorithm and machine learning method. Rubik’s cube is a rather complicated problem to solve, investigation on the algorithms to solve a Rubik’s cube can provide some valuable enlightenment which can be applied to other complex areas. Through comparing the efficiency of the four methods, this essay indicates that Korf’s algorithm is the most efficient algorithm to solve this problem, while Kociemba’s algorithm is the second. On the other hand, machine learning method will be the future prevalent algorithm to be investigated. Although it appears to be less efficient in solving this problem, it has more potential than the other three algorithms.
The Principles, Algorithms and State-of-Art Applications of Quantum Computing
Authors: Duan Hongyu 
Published: December 2022

Abstract
Contemporarily, quantum computing has become a popular topic, which is a new approach that is different from classic computing. To be specific, it can deal with information by using mathematical modeling that used to represent quantum mechanics, including superposition, interference, and entanglement. In quantum Computing, information is storage in ‘qubit’, whereas classic computer use bit to store information. This article aims to introduce the principles and some algorithms of quantum computing, and then discuss some up-to-date important development. There are two important algorithms are mentioned in this article, Grover’s algorithms and Shor’s algorithms. According to the analysis, Grover’s algorithms is potentially faster than classic algorithms. However, it requires millions of qubits to make it. Besides, Shor’s algorithms have challenged classic encryption (RSA encryption). Two quantum computer Google Sycamore and Jiuzhang are also mentioned here. The interesting thing is, for some specific question, Jiuzhang performed better than classic computers. Finally, it is found out that the quantum computing is generally slower that classic computer now, due to the restriction of qubit numbers. However, quantum computing still has an advantage in some specific question. These results shed light on guiding further exploration of quantum computer designing.
RETRACTED: Application of Convolutional Neural Network in Modern Technology Field and Improvement by Time-space Version
Authors: Hung Shengyu 
Published: December 2022

Abstract
Based on the basic principle of convolutional neural networks, this paper gradually introduces the development of convolutional neural networks and its related application fields. We also analyze and compare the iterations and developments of convolutional neural networks in three most commonly used areas: medical treatment, face recognition and transportation. A large number of articles have been written to understand the variations and differences of convolutional neural networks in these three areas, such as the use of different training methods or different structures, such as the time-space convolutional neural networks that will be mentioned in the article. And the last part is the summary.
Attention-based Dual-channel Deep Neural Network For Aero-engine RUL Prediction Under Time-varying Operating Conditions
Authors: Zhao Zijian , Zou Pengyuan 
Published: December 2022

Abstract
For complex systems such as aerospace, remaining useful life (RUL) prediction is a general technique that provides information for decision-making in predictive maintenance. In the industrial field, RUL prediction under time-varying operating conditions is a challenging task. In this paper, an attention-based dual-channel deep neural network is proposed to fuse the time-varying operating conditions, with both prediction channels using long short-term memory (LSTM) neural networks. First, the features are extracted by a one-dimensional convolutional neural network (CNN). The operating conditions and sensor data are put into the dual-channel LSTM neural networks separately for prediction. The obtained results are combined with the attention mechanism to assign weights and finally put into the fully connected network for linear mapping to get the final RUL prediction results. This study is based on the N-CMAPSS dataset published by NASA. Compared with traditional methods, this method demonstrates its superiority and effectiveness.
Research Progress of Atmospheric CO2Monitoring by Satellite Remote Sensing
Authors: Gao Ruiyang 
Published: December 2022

AbstractCarbon peaking and carbon neutrality are gaining popularity in the international community. As a result, there is a growing demand for high-accuracy quantification of carbon sources and sinks. Global carbon dioxide (CO2) concentrations measured by satellite are essential evidence for accurate CO2 emissions estimation. And advances in infrared hyper-spectral technologies have enhanced satellite-derived CO2 estimation. This paper reviews the development of space-borne instruments, such as the infrared hypersoectral sounder and lidar, from the 1950s. The two types of infrared hyperspectral sounders, including sounders for observing atmospheric profiles, such as AIRS, IASI, CrIS, and HIRAS, and special instruments for observing atmospheric composition, such as GOSAT, OCO, GAS, and ACGS/TanSAT. The precision of total volume CO2 concentration products has improved. It therefore encourages satellite observation based researches into carbon sources and sinks, as well as emissions inventories. And rising of related publication is well corresponding to the launch of new instruments. And in the future, the rapid development of lidar observation will further improve accuracy of CO2 monitoring.
A Study of the Use of Euler Totient Function in RSA Cryptosystem and the Future of RSA Cryptosystem
Authors: Wang Shuodong 
Published: December 2022

Abstract
At the end of the last century, an innovative two-key cryptosystem called RSA was created due to booming demand for secure remote communication. The core for this encryption system is a mathematical function called the Euler totient function (Euler φ function), introduced by Leonhard Euler. This article will first deduce four theorems related to Euler φ function, and then illustrate the correctness of the RSA cryptosystem using Euler’s φ function. The study then starts with well-known RSA attacks such as the Coppersmith attack, assesses some of RSA’s vulnerabilities, and measures the impact of quantum technologies on RSA. Finally, this study provides projections and recommendations for the future development of RSA based on all evaluation studies completed during the entire research program.
Reframe the Field of Aerospace Engineering Via Machine Learning: Application and Comparison
Authors: Ni Zhehan 
Published: December 2022

AbstractMachine learning (ML) shows its significant efficiency and excellent performance of computing while handling various complex issues in different areas since the term ‘Big Data’ emerged in the early 1990s. Big data analysis and ML that are effective at resolving various multi-objective as well as limited optimization issues that emerge in spacecraft design and manufacture, are positioned to benefit the aerospace industry. This research paper demonstrates a radical analysis of the use of ML in aerospace engineering. Spacecraft section focuses on anomaly detection, collision avoidance and attitude control. Artificial satellite part is categorized in satellite communication and default diagnosis while thermoacoustic instabilities detection and lunar landing are the main concentration on rockets. The vast application of machine learning in aerospace engineering certainly boosts the growth of the modern aerospace industry as each collected data contributes to a better trained system for attitude control, navigation and default diagnosis which significantly increase the success rate of future space exploration missions.
The Analysis of EEG after Mild Traumatic Brain Injury(mTBI) Using CWT and CNN
Authors: Ma Detao , Wang Chang Le , Zhang Lanxi , Zhou Xuanyi 
Published: December 2022

Abstract
Electroencephalography (EEG) is a bio-signal used in various approaches such as clinical diagnosis. The analysis aims to investigate the validity of EEG signal detection after mTBI which refers to mild traumatic brain injury. Although EEG does not directly present features that could be found within mTBI, by utilizing the processing method of CWT (Continuous Wavelet Transform) and CNN deep learning which will be mentioned, the resulted accuracy reached 91.29%. This study indicates that the proposed CWT-CNN method may have a potential usage in the identification, classification, and monitoring of mTBI patients.
How Machine Learning Applied in Covid-19 Prevention & Control
Authors: Fang Ruiqi , Guo Jiajun , Xian Bolong 
Published: December 2022

Abstract
Since the outbreak in the beginning of 2020, the COVID-19 pandemic has spread out to all around the world and brought severe lost to lots of aspects of the society. To prevent and control the epidemic situation, models based on machine learning have been widely applied in many medical domains. Despite the abundant researches and works, there are few academic reports make review on them. This study is aimed to fill this gap by providing an systematic review of the machine learning technology applied in dealing with covid-19, including clinical diagnosis, transmission prediction and drug and vaccine invention. This will provide advantage for further research into the application of machine learning in medical and public hygiene area and give instructions for medical workers related to epidemic prevention and control in the future.
Experiments of Mutual Information Maximization on Deep Infomax
Authors: Han Zihao , Lin Zichao 
Published: December 2022

Abstract
Image search and photo search at the current level of science and technology have become increasingly mature, and the underlying logic of these is the clustering of pictures. Mutual information(MI) is widely used in machine learning and deep learning, its value cannot be computed directly. Therefore, there are several methods to estimate MI, such as Deep VIB, MINE, and MoCo. Deep Infomax(DIM) technique is applied to maximize the MI based on Jensen-Shannon divergence. The paper derives the mathematical formula of Deep Infomax first. If two images have the maximum MI, it could be concluded that they are similar images. In the experiment, this technique is applied in clustering of datasets that are cifar10, celeba. In the experiment, the results of cifar10 and celeba are close to expectations and can be considered to have achieved good results. In cifar10, it clusters images of similar colors. In celeba, it clusters together faces of the same skin tone and even expressions. This paper and experiment could conclude that Deep Infomax is an effective way to cluster the images and maximize the mutual information.
The Research and Analysis of Different Face Recognition Algorithms
Authors: Xiang Wang 
Published: December 2022

Abstract
With the background of fast developing artificial intelligence and Internet technology, face recognition, one of the product technologies under the theory of machine learning, has become widely applied on safety tests, identity confirmation, public security photos, and access control system. Based on the trend of its development speed, this technology will have well developed circumstances and the field of application will expand. One of the most essential reasons why it has become so popular is that the algorithms used for face recognition are advanced. In this paper, the author mainly researches five algorithms to realize face recognition based on relevant literature. They are separately CNN, PCA, SVM, MTCNN, and Facenet. After comparison and analysis, it can be found that CNN is one of the most suitable algorithms to recognize human faces, and PCA and SVM have problems of calculating speed. The use of complex neural networks can intensify the accuracy of face recognition just like MTCNN and Facenet. If combining different algorithms together and using their advantages in face recognition in different steps, the prediction of the algorithms will be better.
Basic GAN Models and the Application In Medical Image Field
Authors: Li Kangning 
Published: December 2022

Abstract
Generative adversarial networks (GANs) have shown its prominent performance to the world and be exploited in many areas. For example, generating human face image, translating image between different domain, generating supplementary data for tasks which lacks training and labeled data. Specially, GANs also shows its potential in medical image analysis. It can tackle the problems in medical image analysis such as medical image translation, segmentation, reconstruction, detection and image classification. Being capable of generating images at amazing level of realisim, GANs gives the opportunity to resolve the problem that labeled data for those rare diseases cannot meet the need for medical field. In this paper, we give an overview of GANs and its application in medical image analysis. Defects and advantages of those GANs methods are also thoroughly reviewed. We also discuss its potential improvement in future. We review those most frequently methods published until now. And essential details about papers we discussed in this paper and access to that paper is attached at the endpage.
Comparison of Decision Tree, Random Forest and Linear Discriminant Analysis Models in Breast Cancer Prediction
Authors: Wang Rui 
Published: December 2022

Abstract
Breast cancer is one of the illnesses that has become a leading cause of female death worldwide, and early diagnosis of these diseases is a difficult and important undertaking. The intention of this paper is to design prediction models based on Decision Tree, Random Forest and Linear Discriminant Analysis respectively to forecast the breast cancer occurrence at an early stage. The design is focused on analyzing the minimum set of attributes from the clinical data set that have been chosen by experts, and then compare the performances of the models to find their advantages in each model. Breast Cancer Wisconsin Data Set is used in this paper to construct the expected prediction models. Classification accuracy which is determined by comparing real values with predicted values, and generalization ability which is reflected by Receiver Operating Characteristic curve, are used to gauge the performance of the models. The results confirm that the Random Forest model can achieve the highest accuracy to 99.4% and the best generalization ability. However, the Linear Discriminant Analysis model can keep better stability in prediction accuracy and has the fastest running speed.
A Study on the Development of the Rocking Structures in Past 20 Years
Authors: Xu Yutong 
Published: December 2022

AbstractPendulum structure refers to release the rotational freedom of the structure and the foundation, so that the structure and component can lift, swing with descending manner or rotate with fixed center under the action of external forces, so as to control the intraformational deformation distribution mode of the structure. Because the building structure is inevitably damaged to a certain extent under the action of strong earthquake, the purpose of “repairable” will be achieved if the damaged part and degree of the structure can be effectively controlled. In this case, Housner found out in the 1960s that the upward lifting of buildings could protect the structure itself, which became the initial discussion of modern pendulum shock absorption system. Currently, pendulum structures have developed into a variety of branches and damping forms. This article classifies and summarizes the new developments of pendulum structures in the past 20 years from three directions, namely pendulum walls, pendulum columns and pendulum frames. It gives its own views and prospects on the future development of pendulum structures.
Research on Drip Irrigation System Based on Self-Controlled System
Authors: Chen Ruimeng 
Published: December 2022

Abstract
With the increasing demand of efficient drip irrigation systems worldwide, there are many of them which contain feedback system to control drip speed based on factors like temperature, plant types and soil moisture. This paper is about the design of a self-controlled drip irrigation system based on the ideas of feedback systems and early designs of irrigation systems. Based on the exploration on metal-core indicator, a PID control system is designed which can make drip irrigation works accurately. Some further conditions are considered.