Dissemination Path Research Articles

A Modern Communication Path for Traditional Chinese Cultural Design Concepts Based on AdaBoost Model

Abstract Clarifying the integration and communication path of Chinese traditional cultural design concepts and modern art design is beneficial to inherit Chinese traditional culture and innovate modern art design. This paper proposes an SD-AdaBoost classification model based on the AdaBoost algorithm, optimizes the algorithm’s design using the sample density method, and conducts a comparative performance analysis for the model. The SD-AdaBoost classification model is used to mine two research items, application path, and dissemination mode, for the fusion of Chinese traditional cultural concepts and modern art design communication, and relevant data analysis is presented. As far as the application carriers are concerned, they embody different values, but all reflect traditional Chinese cultural ideas. Regarding dissemination methods, social media, recommendation engines, and advertising are better ways to disseminate traditional Chinese cultural ideas and modern art design, accounting for 46.96%, 47.92%, and 45.47%, respectively. Based on the AdaBoost model, we can analyze the current dissemination path of Chinese traditional culture design ideas and grasp how we can better integrate and develop Chinese traditional culture and modern art and design ideas.

Research on the English Dissemination Path of Yongjia Kunqu: A Chinese Intangible Cultural Heritage

As an outstanding branch of Kunqu Opera, Yongjia Kunqu is rooted in Wenzhou and exhibits distinct local characteristics in its singing and performance styles. It embodies the regional customs and folk culture of Wenzhou, displaying a down-to-earth quality and a charm of everyday life. Based on the current situation of Yongjia Kunqu, this study analyzes the challenges it faces in inheritance and development. It explores the use of English as a medium to connect Kunqu troupes, universities, and online platforms, aiming to protect and inherit this excellent art form and promote its further development.

An investigation into the causes of science fiction animation influencing young people’s awareness of science and technology based on the DIMT model - Love, Death and Robots as an example

As a medium, science fiction animation has a special significance for the construction of science and technology awareness among youth. As the science fiction animation market is booming and popular among young people, it is more and more urgent to explore ways to improve the impact of science fiction animation. This research report analyzes the science fiction symbolic landscape presented by the animation through the questionnaire analysis and interviews of Love, Death and Robots, and explores the meaning construction of the science fiction symbols in the animation and the dissemination path of the scientific spirit kernel, in order to explore the law of its construction of science and technology consciousness for young people, with a view to providing some reference for the innovative development of science fiction animation in China in the future.

News Hotspot Event Diffusion Mechanism Based on Complex Network

The wide range of social hot news events on the Internet has made the Internet have a great impact on the public. However, there are few studies on Internet information. In order to improve the efficiency of user network information dissemination of Internet information based on complex network theory and model simulation, this paper makes a more in-depth study on information dissemination on the Internet, constructs a complex network of Internet information dissemination, and analyzes the static topology and dynamic evolution process of the network. Using the attention relationship between Internet users, the Internet information dissemination network, degree, and path were used to select multiple indicators. The static topology of the network is analyzed by using the complex network theory. The study found that the complex network of Internet information is different from other complex networks. The influencing factors of network dynamic evolution are studied from three aspects: overall structure, local structure, and time constraints. The evolution trend of different forms and overall network nodes in the evolution process was explored, and the network dynamic evolution process model was constructed. Practice shows that the model can better describe the evolution process of network information dissemination in complex networks. The degree values of the two networks are positively correlated with the corresponding average clustering coefficients, and the networks have a significant hierarchy. The correlation between news hot events and network nodes is not as good as users’ attention to the network.

Analysis of News Dissemination Path and Impact of Big Data Technology in Public Health Emergencies.

Throughout the past public health early warning work, there is still a lack of early warning. Therefore, starting from the reform of the public health early warning mechanism, this paper sorts out the design and development of our country's public health early warning mechanism and its legal framework and further analyzes the unresolved problems that exist in early warning work. At this stage, our country's public health departments have put forward targeted suggestions for improving the early warning mechanism for emergencies and stabilizing public order. In this context, the following data are obtained: (1) The timeliness under the big data model is 73.81%, the prudence is 84.25%, the sustainability is 96.28%; the timeliness under the data mining model is 61.98%, prudence is 77.58%, sustainability is 83.24%; and the timeliness of the intelligent computing model is 53.44%, prudence is 65.58%, and sustainability is 96.28%. (2) During public health emergencies, the path of news dissemination includes 54 people for radio and television communication, accounting for 13%; 98 people for digital communication, accounting for 24%; 73 people for digital TV communication, accounting for 19%; the number of public relations companies was 63 people, accounting for 16%; the number of people who reprinted and spread was 52 people, accounting for 12%; the number of people who searched and spread was 73 people, accounting for 19%; the number of people who spread mobile phone messages was 32 people, accounting for 9%. At this stage, according to the characteristics of public health emergencies, the problems existing in the early warning work are analyzed, and specific suggestions for improving the early warning mechanism of public health emergencies in our country are put forward to stabilize the “public order.” Research in this area is ongoing.

Deep Learning Prediction Model for NiCrAlY Diffusion Barrier Thickness for燭ungsten Wires

In the last decades, technology has used Copper for IC interconnect and it has been the best material used in the wire downsizing. However, Copper is now showing inefficiency as downscaling is getting deeper. Recent research starts to show Tungsten (W) as a possible replacement, for its better downsizing characteristic. The scaling-down of interconnects dimension has to be augmented with thin diffusion layers. It is crucial to subdue tungsten diffusion in the nickel-based thermal spray Flexicord (NiCrAlY) coating layers. Inappropriately, diffusion barriers with thicknesses less than 4.3 nm do not to execute well. With the introduction of two dimensional layers, hexagonal boron has been recommended as a substitute for Tungsten diffusion barrier layers with thicknesses less than 1.5 Nano meters (nm). Nevertheless, vacancies flaws may develop into a Tungsten dissemination path, which is a problematic issue in the manufacturing of diffusion barriers. The energy layer density, of Tungsten atom diffusion via a di-vacancy in NiCrAlY, is computed by density functions 3D. NiCrAlY has complex energy barrier which is thicker than other materials such as Graphene. This is due to the sturdier contact and charge variance of NI and Cr in NiCrAlY. Also, we utilize the energy barriers of several vacancy constructions and produce a dataset to be employed in the proposed 3-imensional deep learning model (3D-DNN). Our trained deep learning neural model can predict the energy barrier of Tungsten diffusion through arbitrarily configured NiCrAlY with accuracy greater than 98.4% in 5 × 5 cell. Prediction results generate directors on selecting barriers through energy computation.

Analysis on the media presentation and dissemination path of cultural variety shows

Chinese traditional culture and history have always been titled as "treasures standing in the East" in the world. Inheriting excellent traditional culture is a long-term process, characterized by timeliness and diversity, which requires continuous injection of vitality, continuous promotion and development as well as continuous innovation and publicity. The inheritance of excellent traditional culture includes the subject and object of inheritance, as well as multiple elements such as media, content, and environment. From 2016 to 2022, cultural variety shows undoubtedly have always been maintaining a "unique" status in this project. With the continuous breakthrough and improvement of radio and television, the integration of various media and the diversification of communication methods, many of these "new ideas" have attracted more young people's attention to such "cultural popular" programs. Under the exposure and influence of such cultural variety shows, the youth of today will become more firm in cultural identity and cultural self-confidence.

Public Opinion Analysis on Novel Coronavirus Pneumonia and Interaction With Event Evolution in Real World

During the novel coronavirus pneumonia, the underlying comments and news of the epidemic had bombed on the Internet media and social networks, reflecting the views and attitudes of the governments, society, and individuals to the epidemic situation. Those comments are closely related to people's lives and blend with each other. Novel coronavirus pneumonia affects people's lives, and they publish comments on social networks and media, and the underlying information from social networks and Internet media in turn affects people's attitude to the epidemic and the measures, and strategies taken to fight coronavirus in life. We collect the comments from various social network platforms and network media such as Weibo, WeChat, Chinanews, Sina News, NetEase News, Sohu News, and analyze the overall situation of public opinion on the novel coronavirus pneumonia. We explore the interaction between online public opinion and real life using a variety of algorithms in different stages of the epidemic. We can obtain public attention and key nodes in the dissemination of public opinion by detecting hot events and calculating user's influence. The analysis of information dissemination path is conducive to the rapid propagation of healthy comments, curbing the spread of bad information. Event-specific details and topics are mined from large amounts of comments by thematic clustering and association relationship detecting, which helps to provide technical support for government response measures. The emotional analysis of Internet users' groups helps to guide the direction of public opinion. The situation analysis shows the deep blending and mutual influence between the online public opinion and the real world.

Progression of Watermelon Bud Necrosis Virus Infection in Its Vector, Thrips palmi.

Thrips are important pests of agricultural, horticultural, and forest crops worldwide. In addition to direct damages caused by feeding, several thrips species can transmit diverse tospoviruses. The present understanding of thrips–tospovirus relationships is largely based on studies of tomato spotted wilt virus (TSWV) and Western flower thrips (Frankliniella occidentalis). Little is known about other predominant tospoviruses and their thrips vectors. In this study, we report the progression of watermelon bud necrosis virus (WBNV) infection in its vector, melon thrips (Thrips palmi). Virus infection was visualized in different life stages of thrips using WBNV-nucleocapsid protein antibodies detected with FITC-conjugated secondary antibodies. The anterior midgut was the first to be infected with WBNV in the first instar larvae. The midgut of T. palmi was connected to the principal salivary glands (PSG) via ligaments and the tubular salivary glands (TSG). The infection progressed to the PSG primarily through the connecting ligaments during early larval instars. The TSG may also have an ancillary role in disseminating WBNV from the midgut to PSG in older instars of T. palmi. Infection of WBNV was also spread to the Malpighian tubules, hindgut, and posterior portion of the foregut during the adult stage. Maximum virus-specific fluorescence in the anterior midgut and PSG indicated the primary sites for WBNV replication. These findings will help to better understand the thrips–tospovirus molecular relationships and identify novel potential targets for their management. To our knowledge, this is the first report of the WBNV dissemination path in its vector, T. palmi.

Prediction of information cascades via content and structure proximity preserved graph level embedding

Understanding the mechanisms how one message acquires more popularity than another and modeling how it gains popularity dynamically are of tremendous interest to related AI-based decision support systems. The information cascade prediction begins benefiting from the development of deep learning on graphs. However, recent studies are generally learning the representation of nodes in the graph, which may be not suitable as cascades contain all nodes in the dissemination path as a whole. Thus, we investigate whether the whole graph of cascade could be directly embedded in low dimension and how it would be effective for predicting the future popularity. Rather than learning the representation of all nodes in the cascade, we design a framework to learn the low dimension representation of each cascade graph by constructing the content and structure proximity-based high-order graph where each node refers to each cascade. By random walk and a semi-supervised language model, the embedding of the whole cascade graph can be obtained. Our results show that the proposed method can reduce the prediction error by at least 10.29%, 22.89% and 20.01% (measured by RMSPE) respectively on three real datasets over baselines. Moreover, the running time of the model training is much less than baselines.

Research on the Dissemination Path of the Red Boat Spirit in China in the New Era

As the successors of the Chinese nation, college students’ ideological and moral cultivation is related to the future and destiny of the country. The red cultural gene contained in the Red Boat spirit can lead college students to shoulder the great mission of the Chinese nation, and its value of the times has a very important inheritance role. . However, it is currently found that with regard to the Red Boat spirit, university survival is low in recognition, interest, value, and behavioral recognition. This paper combines quantitative and qualitative analysis, and according to the relevant situation of the survey results, gives the inheritance subject, Countermeasures and suggestions with practical effects on the content and carrier.

Research on the Translation and Dissemination Path of Compendium of Materia Medica under “the Belt and Road” Initiative

Research on the Translation and Dissemination Path of Compendium of Materia Medica under “the Belt and Road” Initiative

Energy Efficient Two-Tier Data Dissemination Based on Q-Learning for Wireless Sensor Networks

Green communication for different kinds of wireless networks has begun to receive significant research attention recently. Green communication focuses mainly on the issue of improving energy efficiency substantially. A wireless sensor network (WSN) consists of a large number of randomly and widely deployed sensor nodes, and these nodes themselves have the ability to wireless communicate, detect and process data. Sensor nodes can thus detect their surrounding environment, and transmit related data to a sink via wireless communication. This study proposes two two-tier data dissemination schemes based on Q-learning for wireless sensor networks. In the proposed schemes, a source node uses Q-learning to find the most energy efficient data dissemination path from the source node to the sink. The first scheme is called TTDD-QL, and the second scheme is called TTDD-QL-A which is an advanced version of TTDD-QL. In TTDD-QL, the reward is determined by the distance between the current dissemination node and the sink. In each iteration, the proposed scheme will update the Q values. After multiple learning iterations, the Q values are converged, and the data dissemination path is found according to the Q values. In TTDD-QL-A, the reward is determined not only by the distance between the current dissemination node and the sink but also by the remaining energy of the current dissemination node. Simulation results show that TTDD-QL and TTDD-QL-A can reduce sensor node energy consumption and extend the lifetime of the WSN.

Brand Spreading Path of City Convention and Exhibition Under New Media—Take Guiyang “Big Data Expo” as an Example

With the rapid development of domestic exhibition industry, many cities are actively building their local exhibition brand and establishing a core competitive position. At the same time, the development of new media technology also provides a broad space for exhibition brand promotion. This paper is based on the relevant concepts and theories of new media communication, starting with the characteristics of new media communication, analyzing the dissemination path requirements of exhibition brand under new media, propose using big data, brand website and virtual community as effective ways of brand communication of exhibition, and taking Guiyang Big Data Expo as an example, the dissemination path of exhibition brand in the new media era is explored.

Information Dissemination Analysis Using a Time-Weight Null Model: A Case Study of Sina Micro-Blog

Information dissemination in a social network is constrained by the underlying structure of the network and interaction between the users, and different dissemination patterns are exhibited over time. In this paper, first, information dissemination trees (IDTs) are constructed by tracking the Sina micro-blog information dissemination path (i.e., message forwarding and @), and an empirical analysis of their time characteristics is conducted. Second, the time-weight shuffle null model is established based on the null model in statistics, including the equal time-weight edge shuffle null model and the node time-weight shuffle null model, which are utilized to analyze the temporal properties and the corresponding information dissemination pattern. Thus, we further analyze the dynamics of the IDTs, which contain the burstiness of the information dissemination, the dissemination scale, and the effect of the network structure on the information dissemination. Finally, the experimental results indicate that the information dissemination in Sina micro-blog has a 5-h-effect and the network structure has a positive effect on the dissemination of information. The latter contrasts sharply with the scenarios of the European mobile phone network and e-mail communication network, and the burstiness of the information dissemination is suppressed while the network structure is destroyed.

Research on the Dissemination Path of Virtual Reality Book Publications

Based on the summary of the dissemination and management status of virtual reality book publications, this article builds a dissemination industry ecosystem of the virtual reality book publications with the core of IP operation, and also expounds the relationship among stakeholders in the ecosystem. Finally, this article discusses the dissemination path of virtual reality book publications in details from three aspects of marketing integration, IP operation and organization integration.

The data-driven null models for information dissemination tree in social networks

For the purpose of detecting relatedness and co-occurrence between users, as well as the distribution features of nodes in spreading path of a social network, this paper explores topological characteristics of information dissemination trees (IDT) that can be employed indirectly to probe the information dissemination laws within social networks. Hence, three different null models of IDT are presented in this article, including the statistical-constrained 0-order IDT null model, the random-rewire-broken-edge 0-order IDT null model and the random-rewire-broken-edge 2-order IDT null model. These null models firstly generate the corresponding randomized copy of an actual IDT; then the extended significance profile, which is developed by adding the cascade ratio of information dissemination path, is exploited not only to evaluate degree correlation of two nodes associated with an edge, but also to assess the cascade ratio of different length of information dissemination paths. The experimental correspondences of the empirical analysis for several SinaWeibo IDTs and Twitter IDTs indicate that the IDT null models presented in this paper perform well in terms of degree correlation of nodes and dissemination path cascade ratio, which can be better to reveal the features of information dissemination and to fit the situation of real social networks.

Using Web Crawler Technology for Geo-Events Analysis: A Case Study of the Huangyan Island Incident

Social networking and network socialization provide abundant text information and social relationships into our daily lives. Making full use of these data in the big data era is of great significance for us to better understand the changing world and the information-based society. Though politics have been integrally involved in the hyperlinked world issues since the 1990s, the text analysis and data visualization of geo-events faced the bottleneck of traditional manual analysis. Though automatic assembly of different geospatial web and distributed geospatial information systems utilizing service chaining have been explored and built recently, the data mining and information collection are not comprehensive enough because of the sensibility, complexity, relativity, timeliness, and unexpected characteristics of political events. Based on the framework of Heritrix and the analysis of web-based text, word frequency, sentiment tendency, and dissemination path of the Huangyan Island incident were studied by using web crawler technology and the text analysis. The results indicate that tag cloud, frequency map, attitudes pie, individual mention ratios, and dissemination flow graph, based on the crawled information and data processing not only highlight the characteristics of geo-event itself, but also implicate many interesting phenomenon and deep-seated problems behind it, such as related topics, theme vocabularies, subject contents, hot countries, event bodies, opinion leaders, high-frequency vocabularies, information sources, semantic structure, propagation paths, distribution of different attitudes, and regional difference of net citizens’ response in the Huangyan Island incident. Furthermore, the text analysis of network information with the help of focused web crawler is able to express the time-space relationship of crawled information and the information characteristic of semantic network to the geo-events. Therefore, it is a useful tool to collect information for understanding the formation and diffusion of web-based public opinions in political events.

Using Web Crawler Technology for Text Analysis of Geo-Events: A Case Study of the Huangyan Island Incident

Abstract. With the social networking and network socialisation have brought more text information and social relationships into our daily lives, the question of whether big data can be fully used to study the phenomenon and discipline of natural sciences has prompted many specialists and scholars to innovate their research. Though politics were integrally involved in the hyperlinked word issues since 1990s, automatic assembly of different geospatial web and distributed geospatial information systems utilizing service chaining have explored and built recently, the information collection and data visualisation of geo-events have always faced the bottleneck of traditional manual analysis because of the sensibility, complexity, relativity, timeliness and unexpected characteristics of political events. Based on the framework of Heritrix and the analysis of web-based text, word frequency, sentiment tendency and dissemination path of the Huangyan Island incident is studied here by combining web crawler technology and the text analysis method. The results indicate that tag cloud, frequency map, attitudes pie, individual mention ratios and dissemination flow graph based on the data collection and processing not only highlight the subject and theme vocabularies of related topics but also certain issues and problems behind it. Being able to express the time-space relationship of text information and to disseminate the information regarding geo-events, the text analysis of network information based on focused web crawler technology can be a tool for understanding the formation and diffusion of web-based public opinions in political events.

Safety Information Dissemination Path Prediction in High-Density Vehicular Wireless Networks

Many safety applications needed safety warning information to be disseminated to all vehicles in an area quickly. A path prediction model was built from the fused evidences by evidence theory, in which the basic probability assignment function of the local load and the old path load could be achieved using fuzzy set. And the loads became the evidences of the dissemination path prediction respectively. The prediction result with the maximal confidence was regarded as the quasi-real-time dissemination path load. Simulations show that the average end-to-end delay of safety information under heavy load with path prediction is less than the half of the delay without path prediction. However, the average packets loss rate of two schemes is almost the same.