The black hole has been a mystery and a source of detection motivation for the human race ever since our quest of the discovery and research of other space. In general, the black hole can be defined as a special time-space structure where the gravity is strong enough to trap the photons, i.e., the light will be unable to penetrate or escape from it. In this paper, the current theorem and state-of-art detection paradigms are discussed in detail. Primarily, the categories of the black holes are demonstrated. The four different types of black holes all present their unique features. the quest for black hole exploration has never ceased. It has achieved stunning breakthrough with the first ever photo taken of the black hole by NASA in 2019. The future analysis of black hole excavation and research has been brought a bright future, as technology and outer space exploration plans continue to evolve. These results shed light on guiding further exploration of cosmology as well as the astrophysics.

Autonomous driving is a very hot development direction in the future. With the application of electricity and the development of technology, autonomous driving technology will also be widely adopted. This study discusses the ethical issues of autonomous driving in society from the perspectives of social exclusion and private issues. The results demonstrate that although automatic driving is an excellent technology, it still needs more time to improve the whole systems and hardware facility to provide the best experience for people.

With the increasing degree of informatization in today's society, the presentation of problems has become more complex, which puts forward higher requirements for people's ability to solve problems. Python is a popular language recently, and it is very popular among developers because of the many mature libraries that are encapsulated in it. People can use related libraries in Python and use open-source related libraries for algorithm research. The main purpose of this paper is to study the optimization platform of the model based on Python. This paper mainly analyzes the characteristics of the Python language and the structure of Python programming, and uses the relevant database of Python to realize the modeling work. The experiment shows that the accuracy of the decision tree model is 96.94 %, the accuracy of the KNN classification model is 89.05%.

The most fundamental way to comprehend mathematics is through its history. It is becoming more widely acknowledged that studying and teaching mathematics history has important epistemological implications. However, learning about the history of mathematics is also a good way to get a liberal education. This paper, through a method of literature review, introduces the functions of mathematics history education and provides several suggestions for mathematics history education.

The Enigma machine is a kind of advanced mechanical encryption system used by the Nazi German military during World War II, with the rotor structure as the main structure. Cryptographic machines generally take the form of a boxed structure. When encrypting a string of characters, the user enters the information into a machine or system and gets ciphertext. The original information can be obtained by reverse operation of the ciphertext. As the operator enters the message to be encrypted, a sequence of plain-length passwords can be recorded based on the sequence of letters lit up on the lamp board. This article will focus on the simple structure of the Enigma machine and the mathematics behind it, thus illustrating its importance and security in the history of human encryption. Then, to further explore the working principle of the Enigma machine and help to better understand its internal nature, the essay has provided a simple code that can realize the simple function of the Enigma, and also shows a simply equipped Enigma machine.

Artificial intelligence has emerged with big data technologies in natural language processing and been applied to creative solutions for overload information especially around the time of the COVID-19 epidemic. This paper provides a comprehensive review of research dedicated to applications of artificial intelligence in misinformation detection. This work organizes the necessary background material for COVID-19-related misinformation detection in NLP, concentrating on the transfer learning technique. Database, data preparation, and modeling make up the major body of information. In the part of modeling, it will merge the attributes of the pre-trained model with the specifical task scenario to explain and present pertinent comments on the future model's improvement under the task scenario. This research will benefit the decision-making and information screen for people's inability to distinguish truth from fiction during the COVID-19 pandemic.

With the explosion of the MetaVerse concept and the burgeoning of VR (Virtual Reality) technology, VR has been applied in diverse scenarios，for example，social networking, games, education, online retail, house inspections, exhibition tours, training, virtual concerts and so on. Learning in the 3D environment of virtual reality can bring people an immersive interactive experience, which can improve the learners’ efficiency and deepen understanding. Music learning mainly includes the cultivation of rhythm (or sense of music, also including intonation), mainly relying on ears, followed by muscle memory, and the immersion of VR games is an optimal solution for music learning. This work proposes a VR-based drum learning game to solve several troubling problems such that when drummers practice real drums at home, the sound gets too loud, and the real drums occupy a large space, going out to practice drums will take much time. But to play drums in VR game, just put on a portable VR glass and pick up the touch controllers, drum players can practice at anytime, anywhere. What's more, it's very easy for novice to get started quickly. Another conspicuous advantage of VR is it provides an immersive experience for users，including a 360-degree panoramic screen, spatial audio, and authentic atmosphere.

This paper mainly introduces the basic structure and the function of each part of servomotor. At first, it talks about what is servomotor and where does it used for. Three parts are introduced in the article, the integration part, the addition part, and the feedback part. In each part, the article talks what the electronic components that are used in each part and how do these electronic components make the arithmetic come true. At last, the paper will discuss the advantage of the feedback part.

In order for investors to maximize their benefit by having better forecasts of the complex dynamics of the stock market, there are many factors that affect the stock market, from a company's financial ratios to investor sentiment and reactions to financial news. This project aims to collect UK business news from the Guardian and uses NLP techniques to transform unstructured text data into usable structured sentiment data to predict the movement of the FTSE100 index. The program uses two different libraries TEXTBLOB and VADER to extract sentiments from both the headlines and main bodies of the business news articles. Four machine learning algorithms including Logistic Regression, Naive Bayes, K-Nearest Neighbours and Support Vector Machines and a voting classifier were used to predict FTSE100 index movement given the business news sentiments of the previous day.

In this paper, we describe a content-based movie recommendation system and provide an overview of the movie recommendation systems in today's market. Our findings show 1): Summary-Based and Feature-Based movie recommendation systems will provide different recommendation results. 2) Combined recommendation system’s result is consistent with the Summary-Based recommendation system but different from the Feature-Based recommendation system. Based on our recommendation system, we also made some innovations and fusion and conducted several control tests to improve the quality of our recommendations.

We notice the situation that when applicants are qualified and have the willingness to seek a job, the appraises of employees already in the company will have a large impact on applicants’ decisions of whether to become a member of this company or not. We believe that positive appraises will encourage the applicants to enter while negative appraises will discourage applicants. On the basis of this fact, in this paper we propose a compartmental model including the applicants population, the employed population and the resignation population. Several differential equations are set up and disease-free equilibrium is calculated. After the calculation of R_0, we complete sensitivity analysis which leads to the conclusion. The conclusion suggests that either decreasing the progression rate from applicants to employees who have negative appraises or increasing the progression rate from employees with negative appraises to employees with positive appraises can decrease the population of negative states.

In the field of astrophysics and cosmology, astronomical telescopes are the main and key tool for observing and capturing information of celestial bodies. Generally, there are two types of telescopes, i.e., terrestrial telescopes and space telescopes. This study will be mainly focused on the differences and similarities between the two types mentioned above. According to the analysis, the ground telescope is larger and collect data with processing instead of real picture. The space telescope, on the other hand, is smaller but hard to repair, which is able to send back the real pictures of the space. The research aims of this investigation are helping the further researchers to have better understanding to the two different types of telescopes and offering a guideline for them to choose the more appropriate resources to use for the future research. These results shed light on guiding further exploration of different types of telescopes and pave a path for the future inventions of the telescopes.

In this research, researchers aim to find the existence of possible new exoplanets within the various red dwarf systems with masses of 0.1 M/Me 0.3 within 15 parsecs of the Earth. In the sample size of 600, the Team Hypothesized the existence of at least 3-5 previously undiscovered exoplanets due to the red dwarf's properties mentioned above combined with technological advancement, allowing for a more effective analysis method of the existing data. The Researchers intended to use python to access Jupyter labs through which the codes analyze to measure the relative flux graph and with the aid of other programs such as NumPy, lightkurve, BLS, and Doppler shift method. The researchers classified all flux patterns into four different types: Ordinary(there’s no worth-noticing feature) flux pattern; Wave pattern, for which the flux distribution in the graph is an approximate adjustment to the sinusoidal mathematical trend with few minimal variations; Transit patterns, graphs which got flux pattern at some specific period ,when researchers find this pattern, they will zoom in the special flux area and employ BLS method to determine whether there exists at least one exo-planet.; Flare patterns, which have a feature of windfall, they have steep and rapid changes in flux as well as patterns. Researchers recorded the fourth type in paper to offer reference materials for later researchers who may be interested in flares. Through analyzing, we found 1 case of unresearched flare and 2 cases of worth-noting patterns, but no new exoplanets were found.

In this paper, the stress and deformation of a manipulator structure are analyzed, and the structural optimization design is carried out. The initial configuration is a cantilever beam structure with rectangular section, which is fixed at one end and bears a load of 1 ton at the other end. After stress and deformation analysis with ABAQUS software and SolidWorks software, three optimizations were carried out. Geometric configuration optimization, topology optimization and material optimization. After optimization, the overall quality of the structure is reduced by 80%, and there is no great loss of strength and safety.

Intelligent dialogue systems, as a subfield of artificial intelligence, have very important research significance and application value. Today’s AI dialogue systems are still in a relatively early stage, but they are developing very rapidly. In recent years, intelligent dialogue systems have been applied in many fields, such as intelligent customer service in online transactions, intelligent voice assistants in smartphones, and virtual chatbots. This paper introduces the background of intelligent dialogue systems and the current research status of key technologies and discusses some challenges in this field and some recent research to improve the system. Most of the current intelligent dialogue systems can perform effective human-computer interaction and respond accordingly. But for the next generation of intelligent dialogue system, more human characteristics are needed so that it can better understand and express human language, have its own personality, and maintain the consistency and logic of dialogue.

Bitcoin is known to the world from its birth to the present, and it only took 13 years. In the past 13 years, countless virtual currencies have flourished. In the rapid development of virtual currencies, many problems have been revealed. This article will mainly discuss (1) energy consumption, (2) miner consolidation, (3) encryption security and finally (4) miner income volatility through different types of virtual currency data. And use Android virtual currency as a case to look forward to virtual currency The direction of development. Readers can learn more about the main challenges faced by virtual currencies through this article, and explore the future development model of virtual currencies.

The credit assessment system is an essential part of modern financial institutions, and most of them have adopted different models to perform the task according to their specific needs. Support Vector Machine has been widespread and proved an efficient classifier, especially for relatively small datasets in recent years. When using SVM, data processing, choosing an appropriate kernel function, and tuning parameters can largely affect its performance. The most popular kernel function of SVM is the Radial basis function (RBF), and its main parameters are the regularization parameter, C, and the kernel coefficient, γ. Our study based on the South German credit dataset demonstrates that parameter optimization and an appropriate ratio of the size of the training dataset to the size of the testing dataset could significantly improve the performance of SVM.

Encryption is an important factor during online communication. It is useful to protect users’ privacy and prevent eavesdroppers listening. RSA encryption and quantum encryption are two mainstream encryption methods applied nowadays. This paper focuses on the evaluation and comparison between these two encryptions. It adopts the basic theory of RSA encryption and quantum encryption and provides an analysis of the benefits and shortcomings of these encryptions. It can be concluded that RSA (a type of mathematical encryption) is more popular than quantum encryption (a kind of physical encryption), but is less secure.

This document explains and explores the basics of the jet engine, from basic physical knowledge to the inner workings of the engine, as well as the maintenance aspect. It touches on the mechanical properties that allow the jet engine to function, the design considerations, the mechanisms within the engine, and finally the maintenance of the engine.

Traditional robots are mainly rigid structures. They are complex in structure but limited in flexibility, and have poor security and adaptability. At that time, many bio-inspired robots were created to overcome the traditional robotic challenges. Creatures gave us the inspiration to use a soft body to complete task, and then soft robotics were invented. This paper evaluated the future difficulties faced by this area, and listed the deficiencies that still need to be improved for soft robots that should be overcome in future projects as well. First of all, the first difficulty is that most soft robots rely on software drivers to complete tasks, and because of this, the driving functions of soft robots cannot be perfectly performed, and the action tasks are not diverse. Secondly, if the action moving is over flexible, it will be hard to control. The precision for missions cannot be satisfied. Thirdly, the choice of drivers’ type becomes another problem. For example, the memory alloy drive has the advantages of large driving force, controllable stiffness, good elasticity, etc., but it also has disadvantages such as easy aging and slow response speed. Although the pneumatic drive has a fast response rate, there is a risk that the fluid may leak, and the environment cannot be guaranteed to be airtight. Obviously, there is no ideal solution to work out actuation difficulties.