# The Application of Mental Health Teaching Method and Special Teaching Method in College Chinese Teaching under the Network Environment

Authors: Wei Zhang
Journal: Journal of Environmental and Public Health
 (2022)

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## Abstract

In order to improve the quality of College Chinese teaching, innovate the teaching mode, enrich the teaching content, and fundamentally improve the application and practice ability of college students so as to promote the reform of College Chinese teaching, this article briefly describes the research background of this subject, introduces the special teaching mode under the network environment, and briefly describes the basic content and practice of the special teaching method. This article mainly explores the construction of a network environment based on blockchain technology, including the construction of a blockchain framework and the application of the blockchain system. This article briefly analyzes the functional requirements of the network environment, explores the application practice of the mental health teaching method and the special subject teaching method based on the network environment, and finally studies the creation and implementation of the network environment conditions of the special subject teaching method. By creating a high-quality network environment, it provides a technical guarantee for the application and realization of special teaching method, effectively meets the needs of College Chinese teaching, and cultivates students’ interest. Under the joint action of the above algorithms, the BTP congestion control system is verified by the laboratory simulation environment: it has more than 40% random packet loss resistance, the bandwidth is still available as low as 300 kbps, and the network jitter is 1200 ms. It has been proved that the mental health teaching method, the special subject teaching method, and the network environment have remarkable application effects in College Chinese teaching and are worthy of wide application and promotion.


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## Body

## 1. Introduction

As the rapid development of modern computer network technology, the university provides new opportunities for Chinese education and training, integrates high-quality education, provides new training methods for students, attracts students’ attention, and encourages students’ interest in learning [1]. Based on the network environment, the introduction of specialized Chinese language instruction in colleges has improved classroom quality, improved classroom relationships, engaged with students' education, promoted the development of good Chinese classes, and developed fine arts skills. Therefore, relevant colleges and universities must change the concept of Chinese teaching and continuously accumulate practical experience of special subject teaching methods in College Chinese teaching. Based on the Internet + environment, the educational informatization teaching goal has been realized and the blockchain platform education mode built. At present, based on the network environment, blockchain is widely used in public network services to promote the normal operation of the Internet [2]. For the network system, it is safe, reliable, and low in cost. The DNS system based on the blockchain ensures the accuracy of query results and provides stable and efficient network services. It is applied in university education and teaching, optimizes the curriculum, realizes the sharing of high-quality educational resources, and improves teaching efficiency. At the same time, with the support of the application of blockchain technology, a university student learning information database has been established to record the performance of students in school, including academic achievements, awards, and transcripts, so as to provide a guarantee for the formulation of university talent training plan and reference basis for university employment units [3]. Employers can obtain university talent information through the blockchain platform and select the best candidates according to their employment standards. Based on the network environment constructed by blockchain technology, the infrastructure system is established. The system application layer, perception layer, and control layer all play different functions, guaranteeing the implementation of a special teaching method. The consensus algorithm and network equipment in the blockchain system are complete, creating a good network environment. The sequence approval algorithm in the time window is called the “approval mechanism” and usually includes pow, POS, dpos, pool, and pbft. There are some differences between the advantages and disadvantages of each consensus mechanism. For example, the use of a blockchain makes it difficult for a pow-approved mechanism to obtain the same power for its own security; Although the software code has been changed in the network agreement, it is not possible to access the network without permission, which greatly improves the security of the network environment [4]. The blockchain infrastructure system is shown in Figure 1.Figure 1
Blockchain infrastructure.


## 2. Introduction of Special Subject Teaching Mode under Network Environment

### 2.1. Special Teaching and Network Environment

The special subject teaching method adopts the form of special subject for systematic teaching, pays attention to the combination of theory and practice, trains students’ creative thinking, and improves students’ Chinese self-cultivation and humanistic quality by cultivating students’ ability to observe, analyze, and explore problems [5]. Thematic training is an open course that combines the principles of teaching and teaching and learning aids, including heuristic learning, teaching procedures, instructional questions, and teaching various, which guarantee the application and use of thematic instructions. It integrates a variety of teaching and learning methods. At the same time, the thematic curriculum honors the student management system in the classroom, focuses on developing students' knowledge of information, and allows students to express and learn model instruction. Scientists believe that specific teaching comes from environmental connections. In the area of networked technology, the advent of microclass technology, multimedia technology, and other forms of modern education is a necessity for learning [6]. The procedure for applying a special method is shown in Figure 2.Figure 2
Implementation flowchart of special subject teaching method under Network Environment.Blockchain integrates cryptography, networking technology, consensus algorithm, smart contract, and other technologies. With the continuous maturity and development of blockchain technology, various industries in society pay extensive attention to the practical application scenarios of this technology and try to apply it in college education and teaching to give full play to the advantages of blockchain technology [7]. The network environment created based on the blockchain consensus algorithm ensures the accuracy of data recording nodes and can provide data to all nodes in the network to ensure data information sharing. The average time of the block generated based on bitcoin is 10 min. Therefore, in order to maintain the current speed and adjust the target value in combination with the current computing power of the whole network, the relationship between the difficulty of all nodes in the block and the target value is as follows:(1)C=2224D.At this time, the number of hashes to be calculated for finding a new block is as follows:(2)2256C=222D.Then it is concluded that the relationship between difficulty, computational power technology, and time is as follows:(3)P=222⋅DT.If an organization has enough computing power, it can launch an attack against the bitcoin network. When the attacker has enough computing power, they can calculate the latest block first so as to master the longest chain [8]. The PoW consensus algorithm in the blockchain system mentioned above can specifically calculate the attacker's computing power and the probability of attack success and then obtain the relationship between the malicious node's attack success rate and computing power as follows:(4)P=1−∑kn=0λek−λk1−qpn−k,where q is the proportion of the computing power mastered by the malicious node in the total computing power, P = 1-Q is the proportion of the computing power mastered by the honest node in the total computing power, n is the number of blocks until the message is confirmed, and λ=nq/p is the relationship between the attacker's computing power and the attack success probability under different values of n. It can be seen that when the attackers have the same computing power, more blocks will be added to a block [9]. Therefore, the lower the probability of the block being attacked so as to ensure the data and information security of each node. Based on this, building a network environment based on blockchain technology is safe and reliable, which can create a network environment with higher safety factors for the development of special teaching methods. In order to ensure the reliable application of the network environment, the VRF consensus algorithm (verifiable random function) in the blockchain system is combined to further increase the network communication nodes, improve the performance of the blockchain system, ensure the stability of the network environment, and provide support for the implementation of the special teaching method. VRF consensus algorithm can use RSA or elliptic curve to construct random numbers, which can ensure the accuracy of the generated random numbers. The specific verification process is as follows:When generating the key, A produces the public-private key pair (sk, pk) locally; when calculating value, A takes the private key sk and messagem as inputs, and the calculation results are as follows:Value = VPFvat (sk,m);Verify value: B verifies the received value and proof. The verified value can be calculated by proof:Value = VPFproof2value (proof):Verify proof: B verifies the received proof, which can be calculated by A's private keys SK and M:Ture/False = VPFvalue (proof,sk,m)


### 2.2. The Mental Health Teaching Method

Action orientation is a kind of teaching method; it can also be said to be a kind of teaching guiding ideology and teaching plan design. This teaching method pays attention to the subjectivity, initiative, and creativity of students’ learning while also paying attention to the interaction in the learning process. The interaction shapes students’ personalities. We try to use the action-oriented teaching method in the mental health course for college students to build a course teaching system based on the task. In the interaction of the learning process, students can improve their training of mental health ability, improve psychological function, cultivate good psychological quality, and uild a healthy personality.


#### 2.2.1. Understanding the Basic Situation of Students’ Mental Health

Understanding the basic situation of students’ mental health is the basis for designing curriculum teaching. In order to better use the ”action-oriented teaching method,” we need to understand the psychological characteristics of students of all ages, understand the basic situation of their native families, use psychological measurement methods to understand the students’ mental health, and use questionnaires to understand the students’ experiences in the process of growing up. Various psychological problems can be clearly the teaching objectives of the course.


#### 2.2.2. Improving the Quality of Students' Mental Health as the Teaching Goal

When designing the teaching objectives of the course, we should focus on the learning process of students and pay attention to the relationship between knowledge and skills. The teaching goals of this course are to enhance self-consciousness of mental healthcare and psychological crisis prevention, master and apply mental health knowledge, cultivate the self-cognitive ability, interpersonal communication ability, and self-regulation ability, effectively improve psychological quality, and promote students’ all-round development.


#### 2.2.3. Setting the Course Content According to the Teaching Objectives

According to the requirements of action-oriented teaching, improving the psychological quality is the basis for the selection of course teaching content. The teaching content of college students’ mental health course is to understand the psychological development characteristics and abnormal performance of college students at the knowledge level and master the basic knowledge of self-adjustment; at the skill level, they can master self-exploration skills, psychological adjustment skills, and psychological development skills, such as environmental adaptation skills, stress management skills, communication skills, problem-solving skills, self-management skills, and interpersonal skills; at the level of self-awareness, they can correctly understand themselves, adapt to the society, and find a living state that suits them.


#### 2.2.4. Carefully Designing the Teaching Situation According to the Teaching Content

Select one or more action-oriented teaching methods to implement classroom teaching. In the design of teaching situations, attention should be paid to students' inner emotional experiences and the establishment of attitudes and values. For the teaching content of professional skills such as self-cognition, self-management, self-regulation, and interpersonal communication, theory and practice should be combined. For example, when teaching self-cognition analysis, in addition to letting students understand self-analysis methods, teachers also need to let students know themselves according to self-analysis methods. In the beginning, write no less than 20 sentences about me on paper, and then summarize according to the physical self, psychological self, and social self, so as to achieve the effect of self-cognition.


### 2.3. Multimedia Technology

Based on the development and progress of the new generation of information technology, multimedia technology is widely used in special teaching to realize the innovation of education and teaching mode in colleges and universities. Compared with traditional education methods, it has high technical content, attaches importance to students' visual impact and visual communication effect, enhances students' learning experience, and fundamentally stimulates students' interest in learning [10]. With the support of the application of multimedia technology, the transformation of abstract learning content is realized, which becomes easier to understand, reduces the difficulty of students' understanding, and ensures the effect of classroom teaching. The application of multimedia technology in special subject teaching can achieve the teaching goal of both pictures and texts, display vivid teaching scenes, and dynamically demonstrate specific conceptual knowledge, which is highly intuitive. Therefore, it is widely used in special subject teaching. Multimedia technology refers to computer application technology that deals with graphics, images, video, audio, and animation in computer programs [11]. It is now a medium for storing data such as ROM, RAM, tape, magnetic disk, and optical disk. The main information is CD-ROM, VCD, web page, and so on. Multimedia is a recent update. The development of multimedia technology has transformed the field of computing, transforming computers from offices and specialized laboratories into devices of the information community. It is widely used in production management and school education. For special education, it covers e-learning plans, video tutorials, interactive simulation techniques, and network multimedia techniques [12]. Multimedia video technology is focused on computer operations by converting analog video images into digital signals, analog-to-digital conversion, and color space so that the computer can display and make video signals. There are now two types of models: Y: U: V4: 1 : 1 and Y: U: V4: 2 : 2. The first is the simple approval form for early products. Y: u: v4: 2 : 2 format doubles the standard chrome signal and enhances the color, sharpness, and stability of digital video to provide multimedia video. See Figure 3 for the multimedia technology framework [13].Figure 3
Multimedia technology framework.


## 2.1. Special Teaching and Network Environment

The special subject teaching method adopts the form of special subject for systematic teaching, pays attention to the combination of theory and practice, trains students’ creative thinking, and improves students’ Chinese self-cultivation and humanistic quality by cultivating students’ ability to observe, analyze, and explore problems [5]. Thematic training is an open course that combines the principles of teaching and teaching and learning aids, including heuristic learning, teaching procedures, instructional questions, and teaching various, which guarantee the application and use of thematic instructions. It integrates a variety of teaching and learning methods. At the same time, the thematic curriculum honors the student management system in the classroom, focuses on developing students' knowledge of information, and allows students to express and learn model instruction. Scientists believe that specific teaching comes from environmental connections. In the area of networked technology, the advent of microclass technology, multimedia technology, and other forms of modern education is a necessity for learning [6]. The procedure for applying a special method is shown in Figure 2.Figure 2
Implementation flowchart of special subject teaching method under Network Environment.Blockchain integrates cryptography, networking technology, consensus algorithm, smart contract, and other technologies. With the continuous maturity and development of blockchain technology, various industries in society pay extensive attention to the practical application scenarios of this technology and try to apply it in college education and teaching to give full play to the advantages of blockchain technology [7]. The network environment created based on the blockchain consensus algorithm ensures the accuracy of data recording nodes and can provide data to all nodes in the network to ensure data information sharing. The average time of the block generated based on bitcoin is 10 min. Therefore, in order to maintain the current speed and adjust the target value in combination with the current computing power of the whole network, the relationship between the difficulty of all nodes in the block and the target value is as follows:(1)C=2224D.At this time, the number of hashes to be calculated for finding a new block is as follows:(2)2256C=222D.Then it is concluded that the relationship between difficulty, computational power technology, and time is as follows:(3)P=222⋅DT.If an organization has enough computing power, it can launch an attack against the bitcoin network. When the attacker has enough computing power, they can calculate the latest block first so as to master the longest chain [8]. The PoW consensus algorithm in the blockchain system mentioned above can specifically calculate the attacker's computing power and the probability of attack success and then obtain the relationship between the malicious node's attack success rate and computing power as follows:(4)P=1−∑kn=0λek−λk1−qpn−k,where q is the proportion of the computing power mastered by the malicious node in the total computing power, P = 1-Q is the proportion of the computing power mastered by the honest node in the total computing power, n is the number of blocks until the message is confirmed, and λ=nq/p is the relationship between the attacker's computing power and the attack success probability under different values of n. It can be seen that when the attackers have the same computing power, more blocks will be added to a block [9]. Therefore, the lower the probability of the block being attacked so as to ensure the data and information security of each node. Based on this, building a network environment based on blockchain technology is safe and reliable, which can create a network environment with higher safety factors for the development of special teaching methods. In order to ensure the reliable application of the network environment, the VRF consensus algorithm (verifiable random function) in the blockchain system is combined to further increase the network communication nodes, improve the performance of the blockchain system, ensure the stability of the network environment, and provide support for the implementation of the special teaching method. VRF consensus algorithm can use RSA or elliptic curve to construct random numbers, which can ensure the accuracy of the generated random numbers. The specific verification process is as follows:When generating the key, A produces the public-private key pair (sk, pk) locally; when calculating value, A takes the private key sk and messagem as inputs, and the calculation results are as follows:Value = VPFvat (sk,m);Verify value: B verifies the received value and proof. The verified value can be calculated by proof:Value = VPFproof2value (proof):Verify proof: B verifies the received proof, which can be calculated by A's private keys SK and M:Ture/False = VPFvalue (proof,sk,m)


## 2.2. The Mental Health Teaching Method

Action orientation is a kind of teaching method; it can also be said to be a kind of teaching guiding ideology and teaching plan design. This teaching method pays attention to the subjectivity, initiative, and creativity of students’ learning while also paying attention to the interaction in the learning process. The interaction shapes students’ personalities. We try to use the action-oriented teaching method in the mental health course for college students to build a course teaching system based on the task. In the interaction of the learning process, students can improve their training of mental health ability, improve psychological function, cultivate good psychological quality, and uild a healthy personality.


### 2.2.1. Understanding the Basic Situation of Students’ Mental Health

Understanding the basic situation of students’ mental health is the basis for designing curriculum teaching. In order to better use the ”action-oriented teaching method,” we need to understand the psychological characteristics of students of all ages, understand the basic situation of their native families, use psychological measurement methods to understand the students’ mental health, and use questionnaires to understand the students’ experiences in the process of growing up. Various psychological problems can be clearly the teaching objectives of the course.


### 2.2.2. Improving the Quality of Students' Mental Health as the Teaching Goal

When designing the teaching objectives of the course, we should focus on the learning process of students and pay attention to the relationship between knowledge and skills. The teaching goals of this course are to enhance self-consciousness of mental healthcare and psychological crisis prevention, master and apply mental health knowledge, cultivate the self-cognitive ability, interpersonal communication ability, and self-regulation ability, effectively improve psychological quality, and promote students’ all-round development.


### 2.2.3. Setting the Course Content According to the Teaching Objectives

According to the requirements of action-oriented teaching, improving the psychological quality is the basis for the selection of course teaching content. The teaching content of college students’ mental health course is to understand the psychological development characteristics and abnormal performance of college students at the knowledge level and master the basic knowledge of self-adjustment; at the skill level, they can master self-exploration skills, psychological adjustment skills, and psychological development skills, such as environmental adaptation skills, stress management skills, communication skills, problem-solving skills, self-management skills, and interpersonal skills; at the level of self-awareness, they can correctly understand themselves, adapt to the society, and find a living state that suits them.


### 2.2.4. Carefully Designing the Teaching Situation According to the Teaching Content

Select one or more action-oriented teaching methods to implement classroom teaching. In the design of teaching situations, attention should be paid to students' inner emotional experiences and the establishment of attitudes and values. For the teaching content of professional skills such as self-cognition, self-management, self-regulation, and interpersonal communication, theory and practice should be combined. For example, when teaching self-cognition analysis, in addition to letting students understand self-analysis methods, teachers also need to let students know themselves according to self-analysis methods. In the beginning, write no less than 20 sentences about me on paper, and then summarize according to the physical self, psychological self, and social self, so as to achieve the effect of self-cognition.


## 2.2.1. Understanding the Basic Situation of Students’ Mental Health

Understanding the basic situation of students’ mental health is the basis for designing curriculum teaching. In order to better use the ”action-oriented teaching method,” we need to understand the psychological characteristics of students of all ages, understand the basic situation of their native families, use psychological measurement methods to understand the students’ mental health, and use questionnaires to understand the students’ experiences in the process of growing up. Various psychological problems can be clearly the teaching objectives of the course.


## 2.2.2. Improving the Quality of Students' Mental Health as the Teaching Goal

When designing the teaching objectives of the course, we should focus on the learning process of students and pay attention to the relationship between knowledge and skills. The teaching goals of this course are to enhance self-consciousness of mental healthcare and psychological crisis prevention, master and apply mental health knowledge, cultivate the self-cognitive ability, interpersonal communication ability, and self-regulation ability, effectively improve psychological quality, and promote students’ all-round development.


## 2.2.3. Setting the Course Content According to the Teaching Objectives

According to the requirements of action-oriented teaching, improving the psychological quality is the basis for the selection of course teaching content. The teaching content of college students’ mental health course is to understand the psychological development characteristics and abnormal performance of college students at the knowledge level and master the basic knowledge of self-adjustment; at the skill level, they can master self-exploration skills, psychological adjustment skills, and psychological development skills, such as environmental adaptation skills, stress management skills, communication skills, problem-solving skills, self-management skills, and interpersonal skills; at the level of self-awareness, they can correctly understand themselves, adapt to the society, and find a living state that suits them.


## 2.2.4. Carefully Designing the Teaching Situation According to the Teaching Content

Select one or more action-oriented teaching methods to implement classroom teaching. In the design of teaching situations, attention should be paid to students' inner emotional experiences and the establishment of attitudes and values. For the teaching content of professional skills such as self-cognition, self-management, self-regulation, and interpersonal communication, theory and practice should be combined. For example, when teaching self-cognition analysis, in addition to letting students understand self-analysis methods, teachers also need to let students know themselves according to self-analysis methods. In the beginning, write no less than 20 sentences about me on paper, and then summarize according to the physical self, psychological self, and social self, so as to achieve the effect of self-cognition.


## 2.3. Multimedia Technology

Based on the development and progress of the new generation of information technology, multimedia technology is widely used in special teaching to realize the innovation of education and teaching mode in colleges and universities. Compared with traditional education methods, it has high technical content, attaches importance to students' visual impact and visual communication effect, enhances students' learning experience, and fundamentally stimulates students' interest in learning [10]. With the support of the application of multimedia technology, the transformation of abstract learning content is realized, which becomes easier to understand, reduces the difficulty of students' understanding, and ensures the effect of classroom teaching. The application of multimedia technology in special subject teaching can achieve the teaching goal of both pictures and texts, display vivid teaching scenes, and dynamically demonstrate specific conceptual knowledge, which is highly intuitive. Therefore, it is widely used in special subject teaching. Multimedia technology refers to computer application technology that deals with graphics, images, video, audio, and animation in computer programs [11]. It is now a medium for storing data such as ROM, RAM, tape, magnetic disk, and optical disk. The main information is CD-ROM, VCD, web page, and so on. Multimedia is a recent update. The development of multimedia technology has transformed the field of computing, transforming computers from offices and specialized laboratories into devices of the information community. It is widely used in production management and school education. For special education, it covers e-learning plans, video tutorials, interactive simulation techniques, and network multimedia techniques [12]. Multimedia video technology is focused on computer operations by converting analog video images into digital signals, analog-to-digital conversion, and color space so that the computer can display and make video signals. There are now two types of models: Y: U: V4: 1 : 1 and Y: U: V4: 2 : 2. The first is the simple approval form for early products. Y: u: v4: 2 : 2 format doubles the standard chrome signal and enhances the color, sharpness, and stability of digital video to provide multimedia video. See Figure 3 for the multimedia technology framework [13].Figure 3
Multimedia technology framework.


## 3. Functional Requirements Analysis of Network Environment

For the special teaching method based on the network environment, we need to focus on the stability of the application of network technology, ensure that the technology is handled properly, including audio processing and image processing, and ensure that the display interface of special teaching is clear. At the same time, students’ sense of learning experience should be considered. In the process of creating the network environment, we give full play to the technical advantages of blockchain and use the consensus algorithm to calculate the parameter values of each module so as to reduce the difficulty of operation and maintenance of the computer network system in the later stage as much as possible [14]. We fully rely on the software equipment and hardware equipment in the blockchain system to create a network environment, ensure the feasibility of various educational technology applications, effectively provide technical support for special teaching, better create a good teaching atmosphere, enhance students' learning experience in the network environment, and improve students' learning enthusiasm.


## 4. Application Practice of Special Subject Teaching Method Based on Network Environment

### 4.1. Realization of Special Teaching

Professional teaching based on the network environment mainly relies on the blockchain technology carrier to create the network environment and then create a complete blockchain system to provide a guarantee for the implementation of the special teaching method [15]. With the application support of the blockchain system, the application purpose of multimedia technology in special teaching is realized, and the expected teaching effect is achieved. Multimedia technology in short video content creation platform, combined with audio technology, has accumulated rich technical experience, is widely used in major live broadcasting platforms, and achieved remarkable results. Based on the complex and diverse terminal distribution and network environment in the world, we gradually expand the core technology business, create a diversified technology scene, and further optimize the audio technology. The core capabilities of the overall solution of audio and video technology include the following: (a) it has a super large service scale [16]. The duration of audio and video services in a single month is more than 10000000000 minutes, one of the best in the world. (b) It supports a large number of users online at the same time. It provides real-time video interactive services for tens of millions of people online at the same time. (c) It has a high-quality service capability. It provides industry-leading high-quality audio and video services in QoE/QoS in the global complex network environment. (d) Its performance is costly. Under the same service conditions, the average cost is only 50% of the general level in the industry. Next, the analysis will be carried out from the technical level, in order to provide technical support for the application of the thematic teaching method [17].


### 4.2. Application of Audio Technology

#### 4.2.1. Self-Coding Technology

Based on the requirements of multimedia teaching video image quality and sound quality, and based on the network environment, we actively study a lower bit rate and faster network transmission rate to ensure the definition and resolution of image quality. Compared with the previous generation encoder x264, HEVC open source encoder can save 40+% bit rate and greatly improve the basic video experience under the same coding speed and image quality [18]. The coding performance of x265 does not give full play to the compression extreme of the HEVC standard. Compared with the very slow file of x265, it can save a 15% bit rate on average under the condition of 5x acceleration. The compressibility of the x265 encoder can be seen in Table 1.Table 1
Compression performance of x265 encoder.
PSNR@CRF256 slowVsPSNRSSEIMSpeedVP9GOOD−35.56%−44.42%1X264veryslow−40.54%−46.63%2.5Svt-av1 preset8−34.57%−29.98%1.3Average−37%−40.34%1.6The performance of the x265 encoder is evaluated under the test conditions of MSU encoder competition, which meets the standard of MSU encoder competition. In the specific test, it includes different resolutions and content complexity, covering a variety of video scenes. Among them, Likee is the relevant video on the service side, JCTVC is the official test set of HM, and MSU is the complex mixed test set provided by Moscow University [19]. Moreover, 265 has great advantages in the coding effect of various test videos; the evaluation and test results are shown in Figure 4.Figure 4
Performance evaluation curve of x265 encoder.


#### 4.2.2. Adaptive Coding Technology

Traditional transcoding services use fixed coding parameters for transcoding, which cannot adaptively select the best coding parameters according to the complexity of video content, resulting in a waste of code rate of simple videos and insufficient quality of the complex video. X265 encodere is committed to automatically identifying the complexity of video content so as to select a reasonable coding strategy to achieve the best balance between quality and bit rate, save bit rate, and balance image quality globally [20]. The coding prediction accuracy within the range of the target vmaf score [−2, +2] can reach 93%+. On the 3000 test sets covering multiple resolutions and frame rates, the quality variance is significantly improved, the low-quality cases are reduced, and the average bit rate is saved by 40% +. See Table 2.Table 2
Performance of adaptive coding technology.
Coding resolutionVmaf meanvmaf_stdAverage bitrateRate saving720PFixed crf95.6831882.435618−41.83%CAE90.0327851.547586540PFixed crf95.7494352.195823−41.90%CAE89.9450441.26428360PFixed crf96.1221291.900628−45.16%CAE89.9690490.941953CAE content adaptive transcoding strategy is based on x265 encoder, which integrates content analysis (migration learning, coding feature analysis, etc.), AI coding parameter prediction, fine-grained rate control (frame level code control, ROI code control), and other technologies to achieve the purpose of stable quality and code rate saving. The content analysis adopts coding features and transfer learning features. Transfer learning adopts the classical image classification network, uses the trained image classification network for CV application, and extracts the FC layer before classification as the input feature of AI coding prediction. In order to accelerate the prediction speed and meet the real-time needs of business, AI coding prediction adopts a simple shallow neural network [21].


#### 4.2.3. Network Transmission Congestion Control Technology

If you imagine the Internet as a highway system, every Internet path is like a highway. When too much data enters the network, it will be blocked due to the insufficient transportation capacity of some nodes in the highway system. This kind of data congestion is usually called link congestion. Congestion control has been studied for more than 30 years, and many congestion control algorithms have emerged, including some representative algorithms; see Figure5.Figure 5
Congestion control algorithm.In order to improve the definition of video pictures, a complete congestion control scheme has been accumulated—the BTP congestion control system. Aiming at the characteristics of live broadcast jamming, sensitivity to the definition, and relatively insensitive to delay, the average zero jamming rate is more than 94%, 720p accounts for more than 30%, and the average delay time is less than 2S [22]. In order to solve the problem of the random packet loss scenario, a random packet loss filter is preinstalled, which can accurately filter the random packet loss under the speed limit network mixed with various random packet loss distributions (such as 10% random packet loss subject to Gaussian distribution + 800 kbps speed limit) and retain the congestion loss as the congestion control signal. High delay in small bandwidth scenario: for small bandwidth networks below 600 kbps, its typical feature is that the routing buffer queue is long. When packet loss congestion is detected, the waiting time of data accumulated in the buffer can be more than 10s, which seriously affects the live broadcast experience. At the same time, the auxiliary algorithm slops are introduced, which is a delay-based congestion control algorithm that can accurately infer the delay type and network state to implement the corresponding congestion control output [23]. Under the joint action of the above algorithms, the BTP congestion control system is verified by the laboratory simulation environment: it has more than 40% random packet loss resistance, the bandwidth is still available as low as 300 kbps, and the network jitter is 1200 ms. The scenario architecture of the BTP congestion control system is shown in Figure 6.Figure 6
BTP congestion control system architecture.


#### 4.2.4. Adaptive Rate Playback Control Technology

According to the summary of viewing code rate, transcoding and distribution on demand in the cloud can achieve the goal of saving transcoding computing resources and network transmission resources (Table3). Adaptive rate control of live/video on demand in live and video on demand scenarios, an adaptive rate algorithm based on MPC model prediction, is developed and implemented. By analyzing user characteristics and preferences, predicting download bandwidth information and cache length change state, the selection resolution/code rate problem is modeled as a dynamic optimization problem. The optimization goal is the user's viewing experience index QoE (quality of experience). It not only improves users' viewing satisfaction but also saves the bandwidth consumption of the server.Table 3
Optimization benefits of adaptive rate algorithm.
IndexPer capita WRetainedPer capita playback timeAverage flowCaton rateSecond output rateExperience group+0.78%+0.32%+0.71%−11.0%−10.13%+0.5%


#### 4.2.5. Access Routing Strategy Optimization Technology

Based on the complex and diverse network environment, strengthening the construction of network infrastructure can improve the service level of audio technology, accumulate technical experience, create specific audio scenes, comprehensively ensure the quality of network access and the effect of audio communication, and then provide high-quality network technical conditions for the development of special teaching method [24]. The access network is optimized to further improve the audio playback effect, as shown in Figure 7.Figure 7
Structure diagram of the optimized access network.


#### 4.2.6. Audio and Video Transmission Technology

It is very important for audio and video products to build an industrial audio and video transmission technology with high availability, high versatility, and high-quality assurance, and the optimization focus of transmission technology varies greatly in different business scenarios. In addition, the network characteristics of different countries and regions are very different; there are also great differences in routing, link quality, and charging methods across countries and continents. Different network types have their own behavior patterns and pipeline characteristics, which need to adapt to different transmission control strategies. Users in the same region have great differences in network access types and methods, and users have different preferences for network traffic costs. Therefore, in the process of formulating the transmission strategy, it is necessary to comprehensively consider and optimize the multidimensional situation, such as the focus of the business scenario, the network characteristics of different countries and regions, and the user's experience quality and network payment preference. In the face of the above key challenges of audio and video transmission, BIGO audio and video transmission technology has built a complete basic system of transmission technology through continuous evolution from the beginning of design to the actual implementation, including the following four key technical directions; see Figure8.Figure 8
Technical direction diagram.


### 4.3. Creation and Realization of Network Environment Conditions of Special Subject Teaching Method

#### 4.3.1. Construction of E-Learning Platform

We build a network platform based on the blockchain system, carry out overall construction and planning, set up a teacher login system, and create a course website and course module. In the course website, we enter relevant information, including the description of the course website, applicable courses, and website name; then select the course template and add relevant application functions in combination with the implementation needs of the special teaching method; in addition, set up external network display website, delete the website and other setting modes. We make full use of the distributed advantages of blockchain to collect access user data and divide the information according to departments, teachers, visits, and course categories. When students log in to the system, they can be guided to quickly enter the corresponding course website.


#### 4.3.2. Blockchain System Implementation

A blockchain system is a distributed database system. Compared with traditional databases, it has the characteristics of atomicity, consistency, isolation, and persistence. The first is to obtain the packaging right of block data through competition, package the transaction data in the memory pool (the transaction data sent in the network but not confirmed into the block belongs to the transaction data to be confirmed) into the block, and broadcast it to other nodes. The second is to accept the digital currency reward of the system for packaging behavior so that the system can complete the issuance of new currency through this reward mechanism. Among the front-end tools, the most obvious is the wallet tool, which provides users with the ability to manage their account address and balance. The browser is used to view the data in the blockchain network, such as the latest block height, the number of transactions in the memory pool, and the network processing capacity per unit time. Both the PRC client and the command line interface are used to access the functions of the node. At this time, the core node is equivalent to a server, which provides a function call interface through the PRC service.There are three main types of popular information. Stable information: every reader can continuously read the results of past writing, for example, multitopic information, in a shared environment. All functions can be returned from time to time; the system can be used at any time. Network distribution tolerance, reliability: in the case of a network partition (such as disconnecting the network), a separate system will operate normally. The most important feature of the blockchain is the use of computational and storage divisions to reduce or even eliminate intermediate objects or regulatory agencies. In a blockchain, the rights and responsibilities of a node are equal, and the data blocks in the system are jointly protected by the nodes with the maintenance function of the whole system. Once the data are checked and added to the blockchain, they will be stored permanently. Data exchange at an incorrect point: therefore, the security and reliability of blockchain data are very high. The structure of the blockchain database is shown in Figure9.Figure 9
Blockchain database framework.The blockchain system is distributed, while big data focuses on large-scale and quantifiable data; the blockchain system is anonymous and private, while big data cares about personalization; The blockchain system is secure and the information is relatively independent, while big data cares about the integration and analysis of information. The blockchain system itself is a database, and what we call big data refers to the in-depth analysis and mining of data; that is, data analysis and mining need to be built on the blockchain system to give full play to the value of data. The function of the consensus module in the blockchain database is to make all data nodes in the system consistent. If a new transaction is added to a node's blockchain, all other nodes in the database will add the same transaction to their respective blockchains. The consensus algorithm is reached in Ethereum and bitcoin blockchain through proof of work (PoW) or proof of entitlement (POS), while IBM hyperledger and other blockchain systems that want to improve efficiency adopt PBFT (practical Byzantine fault tolerance) protocol. The efficiency of the latter will be much higher, but the data transmitted by the network will increase exponentially according to the increase in the number of nodes.With the support of the blockchain consensus algorithm, the combination of VRF and POS algorithm is realized. All new nodes in the network must execute PoW first. The existing nodes in the network verify the pow of the new node and authorize it to join the consensus algorithm VBFT designed by the network blockchain project ontology, which combines VRF, POS, and BFT algorithms. VRF randomly selects consensus nodes among many candidate nodes and determines the arrangement order of consensus nodes, which can reduce the impact of malicious bifurcation on the blockchain system and ensure the fairness and randomness of the algorithm. Combining POS and VRF, nodes can become candidate nodes in the form of a token pledge, then select some nodes through the noninteractive VRF algorithm to form a consensus committee, and then these nodes execute a pbft consensus algorithm to be responsible for the rapid verification of transactions. Algorand can ensure the normal operation of the system when the nodes are honest nodes. Each participating node generates a pair of public-private key pairs (ski, pki) and calculates a random number m through the previous round of block information. The information for calculating the random number comes from the chain, and all nodes will calculate the same random number. The node uses its own private key and the calculated random number M. The calculation results and proof are as follows:(5)hash=VRFvalskm,(6)π=VREskm.The node substitutes the calculated result hash according to the above formula to obtain:d=hash/2hashlen, where hashlen is the number of bits of the calculated result hash. Where P = t/w is the probability in the word lottery, t is the number of consensus nodes expected to be selected, and W=∑wi is the total weight of all consensus nodes after pledging tokens:(7)B=k;w;p=kwPk1−pw−k.In constructorfJ=∑0jBk;w;p, each formula node tries to calculate from 0 to W, when d < hash, π, j > 0. After other nodes accept the lottery result, they can confirm the correctness of the VRF calculation through the formula and query the weight wi of the node according to the parameters provided by the node and the chain to verify the correctness of the lottery:(8)π=VRFproofpk,m,(9)Hash=VRFproof2valeπ.


## 4.1. Realization of Special Teaching

Professional teaching based on the network environment mainly relies on the blockchain technology carrier to create the network environment and then create a complete blockchain system to provide a guarantee for the implementation of the special teaching method [15]. With the application support of the blockchain system, the application purpose of multimedia technology in special teaching is realized, and the expected teaching effect is achieved. Multimedia technology in short video content creation platform, combined with audio technology, has accumulated rich technical experience, is widely used in major live broadcasting platforms, and achieved remarkable results. Based on the complex and diverse terminal distribution and network environment in the world, we gradually expand the core technology business, create a diversified technology scene, and further optimize the audio technology. The core capabilities of the overall solution of audio and video technology include the following: (a) it has a super large service scale [16]. The duration of audio and video services in a single month is more than 10000000000 minutes, one of the best in the world. (b) It supports a large number of users online at the same time. It provides real-time video interactive services for tens of millions of people online at the same time. (c) It has a high-quality service capability. It provides industry-leading high-quality audio and video services in QoE/QoS in the global complex network environment. (d) Its performance is costly. Under the same service conditions, the average cost is only 50% of the general level in the industry. Next, the analysis will be carried out from the technical level, in order to provide technical support for the application of the thematic teaching method [17].


## 4.2. Application of Audio Technology

### 4.2.1. Self-Coding Technology

Based on the requirements of multimedia teaching video image quality and sound quality, and based on the network environment, we actively study a lower bit rate and faster network transmission rate to ensure the definition and resolution of image quality. Compared with the previous generation encoder x264, HEVC open source encoder can save 40+% bit rate and greatly improve the basic video experience under the same coding speed and image quality [18]. The coding performance of x265 does not give full play to the compression extreme of the HEVC standard. Compared with the very slow file of x265, it can save a 15% bit rate on average under the condition of 5x acceleration. The compressibility of the x265 encoder can be seen in Table 1.Table 1
Compression performance of x265 encoder.
PSNR@CRF256 slowVsPSNRSSEIMSpeedVP9GOOD−35.56%−44.42%1X264veryslow−40.54%−46.63%2.5Svt-av1 preset8−34.57%−29.98%1.3Average−37%−40.34%1.6The performance of the x265 encoder is evaluated under the test conditions of MSU encoder competition, which meets the standard of MSU encoder competition. In the specific test, it includes different resolutions and content complexity, covering a variety of video scenes. Among them, Likee is the relevant video on the service side, JCTVC is the official test set of HM, and MSU is the complex mixed test set provided by Moscow University [19]. Moreover, 265 has great advantages in the coding effect of various test videos; the evaluation and test results are shown in Figure 4.Figure 4
Performance evaluation curve of x265 encoder.


### 4.2.2. Adaptive Coding Technology

Traditional transcoding services use fixed coding parameters for transcoding, which cannot adaptively select the best coding parameters according to the complexity of video content, resulting in a waste of code rate of simple videos and insufficient quality of the complex video. X265 encodere is committed to automatically identifying the complexity of video content so as to select a reasonable coding strategy to achieve the best balance between quality and bit rate, save bit rate, and balance image quality globally [20]. The coding prediction accuracy within the range of the target vmaf score [−2, +2] can reach 93%+. On the 3000 test sets covering multiple resolutions and frame rates, the quality variance is significantly improved, the low-quality cases are reduced, and the average bit rate is saved by 40% +. See Table 2.Table 2
Performance of adaptive coding technology.
Coding resolutionVmaf meanvmaf_stdAverage bitrateRate saving720PFixed crf95.6831882.435618−41.83%CAE90.0327851.547586540PFixed crf95.7494352.195823−41.90%CAE89.9450441.26428360PFixed crf96.1221291.900628−45.16%CAE89.9690490.941953CAE content adaptive transcoding strategy is based on x265 encoder, which integrates content analysis (migration learning, coding feature analysis, etc.), AI coding parameter prediction, fine-grained rate control (frame level code control, ROI code control), and other technologies to achieve the purpose of stable quality and code rate saving. The content analysis adopts coding features and transfer learning features. Transfer learning adopts the classical image classification network, uses the trained image classification network for CV application, and extracts the FC layer before classification as the input feature of AI coding prediction. In order to accelerate the prediction speed and meet the real-time needs of business, AI coding prediction adopts a simple shallow neural network [21].


### 4.2.3. Network Transmission Congestion Control Technology

If you imagine the Internet as a highway system, every Internet path is like a highway. When too much data enters the network, it will be blocked due to the insufficient transportation capacity of some nodes in the highway system. This kind of data congestion is usually called link congestion. Congestion control has been studied for more than 30 years, and many congestion control algorithms have emerged, including some representative algorithms; see Figure5.Figure 5
Congestion control algorithm.In order to improve the definition of video pictures, a complete congestion control scheme has been accumulated—the BTP congestion control system. Aiming at the characteristics of live broadcast jamming, sensitivity to the definition, and relatively insensitive to delay, the average zero jamming rate is more than 94%, 720p accounts for more than 30%, and the average delay time is less than 2S [22]. In order to solve the problem of the random packet loss scenario, a random packet loss filter is preinstalled, which can accurately filter the random packet loss under the speed limit network mixed with various random packet loss distributions (such as 10% random packet loss subject to Gaussian distribution + 800 kbps speed limit) and retain the congestion loss as the congestion control signal. High delay in small bandwidth scenario: for small bandwidth networks below 600 kbps, its typical feature is that the routing buffer queue is long. When packet loss congestion is detected, the waiting time of data accumulated in the buffer can be more than 10s, which seriously affects the live broadcast experience. At the same time, the auxiliary algorithm slops are introduced, which is a delay-based congestion control algorithm that can accurately infer the delay type and network state to implement the corresponding congestion control output [23]. Under the joint action of the above algorithms, the BTP congestion control system is verified by the laboratory simulation environment: it has more than 40% random packet loss resistance, the bandwidth is still available as low as 300 kbps, and the network jitter is 1200 ms. The scenario architecture of the BTP congestion control system is shown in Figure 6.Figure 6
BTP congestion control system architecture.


### 4.2.4. Adaptive Rate Playback Control Technology

According to the summary of viewing code rate, transcoding and distribution on demand in the cloud can achieve the goal of saving transcoding computing resources and network transmission resources (Table3). Adaptive rate control of live/video on demand in live and video on demand scenarios, an adaptive rate algorithm based on MPC model prediction, is developed and implemented. By analyzing user characteristics and preferences, predicting download bandwidth information and cache length change state, the selection resolution/code rate problem is modeled as a dynamic optimization problem. The optimization goal is the user's viewing experience index QoE (quality of experience). It not only improves users' viewing satisfaction but also saves the bandwidth consumption of the server.Table 3
Optimization benefits of adaptive rate algorithm.
IndexPer capita WRetainedPer capita playback timeAverage flowCaton rateSecond output rateExperience group+0.78%+0.32%+0.71%−11.0%−10.13%+0.5%


### 4.2.5. Access Routing Strategy Optimization Technology

Based on the complex and diverse network environment, strengthening the construction of network infrastructure can improve the service level of audio technology, accumulate technical experience, create specific audio scenes, comprehensively ensure the quality of network access and the effect of audio communication, and then provide high-quality network technical conditions for the development of special teaching method [24]. The access network is optimized to further improve the audio playback effect, as shown in Figure 7.Figure 7
Structure diagram of the optimized access network.


### 4.2.6. Audio and Video Transmission Technology

It is very important for audio and video products to build an industrial audio and video transmission technology with high availability, high versatility, and high-quality assurance, and the optimization focus of transmission technology varies greatly in different business scenarios. In addition, the network characteristics of different countries and regions are very different; there are also great differences in routing, link quality, and charging methods across countries and continents. Different network types have their own behavior patterns and pipeline characteristics, which need to adapt to different transmission control strategies. Users in the same region have great differences in network access types and methods, and users have different preferences for network traffic costs. Therefore, in the process of formulating the transmission strategy, it is necessary to comprehensively consider and optimize the multidimensional situation, such as the focus of the business scenario, the network characteristics of different countries and regions, and the user's experience quality and network payment preference. In the face of the above key challenges of audio and video transmission, BIGO audio and video transmission technology has built a complete basic system of transmission technology through continuous evolution from the beginning of design to the actual implementation, including the following four key technical directions; see Figure8.Figure 8
Technical direction diagram.


## 4.2.1. Self-Coding Technology

Based on the requirements of multimedia teaching video image quality and sound quality, and based on the network environment, we actively study a lower bit rate and faster network transmission rate to ensure the definition and resolution of image quality. Compared with the previous generation encoder x264, HEVC open source encoder can save 40+% bit rate and greatly improve the basic video experience under the same coding speed and image quality [18]. The coding performance of x265 does not give full play to the compression extreme of the HEVC standard. Compared with the very slow file of x265, it can save a 15% bit rate on average under the condition of 5x acceleration. The compressibility of the x265 encoder can be seen in Table 1.Table 1
Compression performance of x265 encoder.
PSNR@CRF256 slowVsPSNRSSEIMSpeedVP9GOOD−35.56%−44.42%1X264veryslow−40.54%−46.63%2.5Svt-av1 preset8−34.57%−29.98%1.3Average−37%−40.34%1.6The performance of the x265 encoder is evaluated under the test conditions of MSU encoder competition, which meets the standard of MSU encoder competition. In the specific test, it includes different resolutions and content complexity, covering a variety of video scenes. Among them, Likee is the relevant video on the service side, JCTVC is the official test set of HM, and MSU is the complex mixed test set provided by Moscow University [19]. Moreover, 265 has great advantages in the coding effect of various test videos; the evaluation and test results are shown in Figure 4.Figure 4
Performance evaluation curve of x265 encoder.


## 4.2.2. Adaptive Coding Technology

Traditional transcoding services use fixed coding parameters for transcoding, which cannot adaptively select the best coding parameters according to the complexity of video content, resulting in a waste of code rate of simple videos and insufficient quality of the complex video. X265 encodere is committed to automatically identifying the complexity of video content so as to select a reasonable coding strategy to achieve the best balance between quality and bit rate, save bit rate, and balance image quality globally [20]. The coding prediction accuracy within the range of the target vmaf score [−2, +2] can reach 93%+. On the 3000 test sets covering multiple resolutions and frame rates, the quality variance is significantly improved, the low-quality cases are reduced, and the average bit rate is saved by 40% +. See Table 2.Table 2
Performance of adaptive coding technology.
Coding resolutionVmaf meanvmaf_stdAverage bitrateRate saving720PFixed crf95.6831882.435618−41.83%CAE90.0327851.547586540PFixed crf95.7494352.195823−41.90%CAE89.9450441.26428360PFixed crf96.1221291.900628−45.16%CAE89.9690490.941953CAE content adaptive transcoding strategy is based on x265 encoder, which integrates content analysis (migration learning, coding feature analysis, etc.), AI coding parameter prediction, fine-grained rate control (frame level code control, ROI code control), and other technologies to achieve the purpose of stable quality and code rate saving. The content analysis adopts coding features and transfer learning features. Transfer learning adopts the classical image classification network, uses the trained image classification network for CV application, and extracts the FC layer before classification as the input feature of AI coding prediction. In order to accelerate the prediction speed and meet the real-time needs of business, AI coding prediction adopts a simple shallow neural network [21].


## 4.2.3. Network Transmission Congestion Control Technology

If you imagine the Internet as a highway system, every Internet path is like a highway. When too much data enters the network, it will be blocked due to the insufficient transportation capacity of some nodes in the highway system. This kind of data congestion is usually called link congestion. Congestion control has been studied for more than 30 years, and many congestion control algorithms have emerged, including some representative algorithms; see Figure5.Figure 5
Congestion control algorithm.In order to improve the definition of video pictures, a complete congestion control scheme has been accumulated—the BTP congestion control system. Aiming at the characteristics of live broadcast jamming, sensitivity to the definition, and relatively insensitive to delay, the average zero jamming rate is more than 94%, 720p accounts for more than 30%, and the average delay time is less than 2S [22]. In order to solve the problem of the random packet loss scenario, a random packet loss filter is preinstalled, which can accurately filter the random packet loss under the speed limit network mixed with various random packet loss distributions (such as 10% random packet loss subject to Gaussian distribution + 800 kbps speed limit) and retain the congestion loss as the congestion control signal. High delay in small bandwidth scenario: for small bandwidth networks below 600 kbps, its typical feature is that the routing buffer queue is long. When packet loss congestion is detected, the waiting time of data accumulated in the buffer can be more than 10s, which seriously affects the live broadcast experience. At the same time, the auxiliary algorithm slops are introduced, which is a delay-based congestion control algorithm that can accurately infer the delay type and network state to implement the corresponding congestion control output [23]. Under the joint action of the above algorithms, the BTP congestion control system is verified by the laboratory simulation environment: it has more than 40% random packet loss resistance, the bandwidth is still available as low as 300 kbps, and the network jitter is 1200 ms. The scenario architecture of the BTP congestion control system is shown in Figure 6.Figure 6
BTP congestion control system architecture.


## 4.2.4. Adaptive Rate Playback Control Technology

According to the summary of viewing code rate, transcoding and distribution on demand in the cloud can achieve the goal of saving transcoding computing resources and network transmission resources (Table3). Adaptive rate control of live/video on demand in live and video on demand scenarios, an adaptive rate algorithm based on MPC model prediction, is developed and implemented. By analyzing user characteristics and preferences, predicting download bandwidth information and cache length change state, the selection resolution/code rate problem is modeled as a dynamic optimization problem. The optimization goal is the user's viewing experience index QoE (quality of experience). It not only improves users' viewing satisfaction but also saves the bandwidth consumption of the server.Table 3
Optimization benefits of adaptive rate algorithm.
IndexPer capita WRetainedPer capita playback timeAverage flowCaton rateSecond output rateExperience group+0.78%+0.32%+0.71%−11.0%−10.13%+0.5%


## 4.2.5. Access Routing Strategy Optimization Technology

Based on the complex and diverse network environment, strengthening the construction of network infrastructure can improve the service level of audio technology, accumulate technical experience, create specific audio scenes, comprehensively ensure the quality of network access and the effect of audio communication, and then provide high-quality network technical conditions for the development of special teaching method [24]. The access network is optimized to further improve the audio playback effect, as shown in Figure 7.Figure 7
Structure diagram of the optimized access network.


## 4.2.6. Audio and Video Transmission Technology

It is very important for audio and video products to build an industrial audio and video transmission technology with high availability, high versatility, and high-quality assurance, and the optimization focus of transmission technology varies greatly in different business scenarios. In addition, the network characteristics of different countries and regions are very different; there are also great differences in routing, link quality, and charging methods across countries and continents. Different network types have their own behavior patterns and pipeline characteristics, which need to adapt to different transmission control strategies. Users in the same region have great differences in network access types and methods, and users have different preferences for network traffic costs. Therefore, in the process of formulating the transmission strategy, it is necessary to comprehensively consider and optimize the multidimensional situation, such as the focus of the business scenario, the network characteristics of different countries and regions, and the user's experience quality and network payment preference. In the face of the above key challenges of audio and video transmission, BIGO audio and video transmission technology has built a complete basic system of transmission technology through continuous evolution from the beginning of design to the actual implementation, including the following four key technical directions; see Figure8.Figure 8
Technical direction diagram.


## 4.3. Creation and Realization of Network Environment Conditions of Special Subject Teaching Method

### 4.3.1. Construction of E-Learning Platform

We build a network platform based on the blockchain system, carry out overall construction and planning, set up a teacher login system, and create a course website and course module. In the course website, we enter relevant information, including the description of the course website, applicable courses, and website name; then select the course template and add relevant application functions in combination with the implementation needs of the special teaching method; in addition, set up external network display website, delete the website and other setting modes. We make full use of the distributed advantages of blockchain to collect access user data and divide the information according to departments, teachers, visits, and course categories. When students log in to the system, they can be guided to quickly enter the corresponding course website.


### 4.3.2. Blockchain System Implementation

A blockchain system is a distributed database system. Compared with traditional databases, it has the characteristics of atomicity, consistency, isolation, and persistence. The first is to obtain the packaging right of block data through competition, package the transaction data in the memory pool (the transaction data sent in the network but not confirmed into the block belongs to the transaction data to be confirmed) into the block, and broadcast it to other nodes. The second is to accept the digital currency reward of the system for packaging behavior so that the system can complete the issuance of new currency through this reward mechanism. Among the front-end tools, the most obvious is the wallet tool, which provides users with the ability to manage their account address and balance. The browser is used to view the data in the blockchain network, such as the latest block height, the number of transactions in the memory pool, and the network processing capacity per unit time. Both the PRC client and the command line interface are used to access the functions of the node. At this time, the core node is equivalent to a server, which provides a function call interface through the PRC service.There are three main types of popular information. Stable information: every reader can continuously read the results of past writing, for example, multitopic information, in a shared environment. All functions can be returned from time to time; the system can be used at any time. Network distribution tolerance, reliability: in the case of a network partition (such as disconnecting the network), a separate system will operate normally. The most important feature of the blockchain is the use of computational and storage divisions to reduce or even eliminate intermediate objects or regulatory agencies. In a blockchain, the rights and responsibilities of a node are equal, and the data blocks in the system are jointly protected by the nodes with the maintenance function of the whole system. Once the data are checked and added to the blockchain, they will be stored permanently. Data exchange at an incorrect point: therefore, the security and reliability of blockchain data are very high. The structure of the blockchain database is shown in Figure9.Figure 9
Blockchain database framework.The blockchain system is distributed, while big data focuses on large-scale and quantifiable data; the blockchain system is anonymous and private, while big data cares about personalization; The blockchain system is secure and the information is relatively independent, while big data cares about the integration and analysis of information. The blockchain system itself is a database, and what we call big data refers to the in-depth analysis and mining of data; that is, data analysis and mining need to be built on the blockchain system to give full play to the value of data. The function of the consensus module in the blockchain database is to make all data nodes in the system consistent. If a new transaction is added to a node's blockchain, all other nodes in the database will add the same transaction to their respective blockchains. The consensus algorithm is reached in Ethereum and bitcoin blockchain through proof of work (PoW) or proof of entitlement (POS), while IBM hyperledger and other blockchain systems that want to improve efficiency adopt PBFT (practical Byzantine fault tolerance) protocol. The efficiency of the latter will be much higher, but the data transmitted by the network will increase exponentially according to the increase in the number of nodes.With the support of the blockchain consensus algorithm, the combination of VRF and POS algorithm is realized. All new nodes in the network must execute PoW first. The existing nodes in the network verify the pow of the new node and authorize it to join the consensus algorithm VBFT designed by the network blockchain project ontology, which combines VRF, POS, and BFT algorithms. VRF randomly selects consensus nodes among many candidate nodes and determines the arrangement order of consensus nodes, which can reduce the impact of malicious bifurcation on the blockchain system and ensure the fairness and randomness of the algorithm. Combining POS and VRF, nodes can become candidate nodes in the form of a token pledge, then select some nodes through the noninteractive VRF algorithm to form a consensus committee, and then these nodes execute a pbft consensus algorithm to be responsible for the rapid verification of transactions. Algorand can ensure the normal operation of the system when the nodes are honest nodes. Each participating node generates a pair of public-private key pairs (ski, pki) and calculates a random number m through the previous round of block information. The information for calculating the random number comes from the chain, and all nodes will calculate the same random number. The node uses its own private key and the calculated random number M. The calculation results and proof are as follows:(5)hash=VRFvalskm,(6)π=VREskm.The node substitutes the calculated result hash according to the above formula to obtain:d=hash/2hashlen, where hashlen is the number of bits of the calculated result hash. Where P = t/w is the probability in the word lottery, t is the number of consensus nodes expected to be selected, and W=∑wi is the total weight of all consensus nodes after pledging tokens:(7)B=k;w;p=kwPk1−pw−k.In constructorfJ=∑0jBk;w;p, each formula node tries to calculate from 0 to W, when d < hash, π, j > 0. After other nodes accept the lottery result, they can confirm the correctness of the VRF calculation through the formula and query the weight wi of the node according to the parameters provided by the node and the chain to verify the correctness of the lottery:(8)π=VRFproofpk,m,(9)Hash=VRFproof2valeπ.


## 4.3.1. Construction of E-Learning Platform

We build a network platform based on the blockchain system, carry out overall construction and planning, set up a teacher login system, and create a course website and course module. In the course website, we enter relevant information, including the description of the course website, applicable courses, and website name; then select the course template and add relevant application functions in combination with the implementation needs of the special teaching method; in addition, set up external network display website, delete the website and other setting modes. We make full use of the distributed advantages of blockchain to collect access user data and divide the information according to departments, teachers, visits, and course categories. When students log in to the system, they can be guided to quickly enter the corresponding course website.


## 4.3.2. Blockchain System Implementation

A blockchain system is a distributed database system. Compared with traditional databases, it has the characteristics of atomicity, consistency, isolation, and persistence. The first is to obtain the packaging right of block data through competition, package the transaction data in the memory pool (the transaction data sent in the network but not confirmed into the block belongs to the transaction data to be confirmed) into the block, and broadcast it to other nodes. The second is to accept the digital currency reward of the system for packaging behavior so that the system can complete the issuance of new currency through this reward mechanism. Among the front-end tools, the most obvious is the wallet tool, which provides users with the ability to manage their account address and balance. The browser is used to view the data in the blockchain network, such as the latest block height, the number of transactions in the memory pool, and the network processing capacity per unit time. Both the PRC client and the command line interface are used to access the functions of the node. At this time, the core node is equivalent to a server, which provides a function call interface through the PRC service.There are three main types of popular information. Stable information: every reader can continuously read the results of past writing, for example, multitopic information, in a shared environment. All functions can be returned from time to time; the system can be used at any time. Network distribution tolerance, reliability: in the case of a network partition (such as disconnecting the network), a separate system will operate normally. The most important feature of the blockchain is the use of computational and storage divisions to reduce or even eliminate intermediate objects or regulatory agencies. In a blockchain, the rights and responsibilities of a node are equal, and the data blocks in the system are jointly protected by the nodes with the maintenance function of the whole system. Once the data are checked and added to the blockchain, they will be stored permanently. Data exchange at an incorrect point: therefore, the security and reliability of blockchain data are very high. The structure of the blockchain database is shown in Figure9.Figure 9
Blockchain database framework.The blockchain system is distributed, while big data focuses on large-scale and quantifiable data; the blockchain system is anonymous and private, while big data cares about personalization; The blockchain system is secure and the information is relatively independent, while big data cares about the integration and analysis of information. The blockchain system itself is a database, and what we call big data refers to the in-depth analysis and mining of data; that is, data analysis and mining need to be built on the blockchain system to give full play to the value of data. The function of the consensus module in the blockchain database is to make all data nodes in the system consistent. If a new transaction is added to a node's blockchain, all other nodes in the database will add the same transaction to their respective blockchains. The consensus algorithm is reached in Ethereum and bitcoin blockchain through proof of work (PoW) or proof of entitlement (POS), while IBM hyperledger and other blockchain systems that want to improve efficiency adopt PBFT (practical Byzantine fault tolerance) protocol. The efficiency of the latter will be much higher, but the data transmitted by the network will increase exponentially according to the increase in the number of nodes.With the support of the blockchain consensus algorithm, the combination of VRF and POS algorithm is realized. All new nodes in the network must execute PoW first. The existing nodes in the network verify the pow of the new node and authorize it to join the consensus algorithm VBFT designed by the network blockchain project ontology, which combines VRF, POS, and BFT algorithms. VRF randomly selects consensus nodes among many candidate nodes and determines the arrangement order of consensus nodes, which can reduce the impact of malicious bifurcation on the blockchain system and ensure the fairness and randomness of the algorithm. Combining POS and VRF, nodes can become candidate nodes in the form of a token pledge, then select some nodes through the noninteractive VRF algorithm to form a consensus committee, and then these nodes execute a pbft consensus algorithm to be responsible for the rapid verification of transactions. Algorand can ensure the normal operation of the system when the nodes are honest nodes. Each participating node generates a pair of public-private key pairs (ski, pki) and calculates a random number m through the previous round of block information. The information for calculating the random number comes from the chain, and all nodes will calculate the same random number. The node uses its own private key and the calculated random number M. The calculation results and proof are as follows:(5)hash=VRFvalskm,(6)π=VREskm.The node substitutes the calculated result hash according to the above formula to obtain:d=hash/2hashlen, where hashlen is the number of bits of the calculated result hash. Where P = t/w is the probability in the word lottery, t is the number of consensus nodes expected to be selected, and W=∑wi is the total weight of all consensus nodes after pledging tokens:(7)B=k;w;p=kwPk1−pw−k.In constructorfJ=∑0jBk;w;p, each formula node tries to calculate from 0 to W, when d < hash, π, j > 0. After other nodes accept the lottery result, they can confirm the correctness of the VRF calculation through the formula and query the weight wi of the node according to the parameters provided by the node and the chain to verify the correctness of the lottery:(8)π=VRFproofpk,m,(9)Hash=VRFproof2valeπ.


## 5. Conclusion

To sum up, this article has completed the research and discussion of this topic. The special teaching method and the mental health teaching method based on the network environment have been technically guaranteed. Through the technical support of blockchain, it has created a network environment with high communication demand, effectively optimized the multimedia technology teaching mode in special teaching and the mental health teaching method, and provided a guarantee for the realization of modern educational technology. At the same time, with the support of audio technology, the teaching experience is enhanced, and through in-depth exploration of the connotation and essence of audio technology, the application of technical algorithms is understood so as to provide support for the realization of audio technology. In the future, facing the complex and diverse network environment, we still need to give further play to the advantages of new generation information technology such as big data technology, cloud computing technology, and Internet of things technology, innovate the university education and teaching environment, and create environmental conditions for the realization of diversified teaching methods and teaching modes. In short, the reform direction of College Chinese teaching is clear. In the network environment, it is urgent to further study the application of network technology in teaching, realize the deep integration with the special teaching method, and improve the education quality of colleges and universities to the greatest extent.



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*Source: 8371421-2022-08-22.xml*