Multimedia Fusion Research Articles

A study of the role of new feature fusion based on multimedia analysis on accounting investment decision methods in economic models

Accounting investing analysis has been expanding at a steady clip, and some of the findings suggest that investors' restricted reasoning and self-psychological sentiments may not always lead them to make their negative emotions influence their financial decisions, leading to a loss. Digital multimedia fusion and display are made possible, and numerous terminals may now communicate with one another in a seamless, real-time manner thanks to the growth of e-commerce and multimedia. This paper proposes a Multimedia Analysis (MA) feature fusion method for understanding the psychological emotions associated with accounting investments in the online retail environment, which can then be used to guide the development of an investment strategy that is both appropriate and successful for the target demographic. The primary goal of this study is to show how multimedia information retrieval tasks may benefit from combining text pre-filtering with image sorting. For this investigation; they used information from the reliable China Stock Market and Accounting Research (CSMAR) Database. The information fusion technology that supports this paper's investigation is used to dissect experiment outcomes, examine issues with the emotional effect of financial investment clients, and assess the paper's intended study topic. In experiments, we found a 97% accuracy rate in terms of accuracy.

Retracted: The Development Strategy of the Multimedia Fusion Mode of Big Data Technology in Japanese Translation Teaching

Retracted: The Development Strategy of the Multimedia Fusion Mode of Big Data Technology in Japanese Translation Teaching

A high performance computing technology powered multimedia fusion model in university English translation.

Various forms of materials, such as pictures, videos and texts, have rapidly brought the college English translation teaching model into the era of multimedia integration. This makes it difficult for English teachers to improve college English translation by using unique materials, so as to form their own unique teaching style. In view of this, a multimedia comprehensive English translation framework based on the combination of big data technology and multimedia teaching mode is proposed. At the same time, the idea of building the framework is introduced from two perspectives: the integration of big data technology and multimedia, and the integration of multimedia and English teaching process. Then, a recursive neural network algorithm based on ant colony optimization algorithm is proposed and tested. Finally, the simulation results show that the proposed method has significantly improved the accuracy and retention rate, indicating the effectiveness of the framework.

The Development Strategy of the Multimedia Fusion Mode of Big Data Technology in Japanese Translation Teaching

With the in-depth development of economic globalization, the connection and communication between China and other countries in the world are increasingly deepened, so the task of cultivating translation talents in various languages is particularly important. In the teaching process, teachers mainly focus on explaining theoretical knowledge and lack of classroom interaction, resulting in a boring and dull classroom atmosphere. At the same time, it does not pay attention to the practice of translation after class and often pays attention to interpretation and neglects written translation, which leads many students to think that Japanese translation is difficult and boring, which greatly reduces students’ enthusiasm for learning. In view of this situation, the application of multimedia technology in Japanese translation teaching proposes that the application of multimedia technology in Japanese teaching can improve the interest of students in Japanese learning and improve the teaching effect of Japanese teaching. Firstly, this paper constructs a logistic semantic ontology model based on automatic calibration of Japanese translation, extracts Japanese semantic features through this model, and performs relational mapping on the extracted Japanese semantic features. Starting from each aspect, optimize the automatic calibration algorithm of Japanese translation, find the best semantic relevance feature in each sentence, and realize automatic optimization, thereby improving the automatic calibration of Japanese translation machines and the registration of subject words.

Multimedia Fusion Privacy Protection Algorithm Based on IoT Data Security under Network Regulations.

This study provides an in-depth analysis and research on multimedia fusion privacy protection algorithms based on IoT data security in a network regulation environment. Aiming at the problem of collusion and conspiracy to deceive users in the process of outsourced computing and outsourced verification, a safe, reliable, and collusion-resistant scheme based on blockchain is studied for IoT outsourced data computing and public verification, with the help of distributed storage methods, where smart devices encrypt the collected data and upload them to the DHT for storage along with the results of this data given by the cloud server. After testing, the constructed model has a privacy-preserving budget value of 0.6 and the smallest information leakage ratio of multimedia fusion data based on IoT data security when the decision tree depth is 6. After using this model under this condition, the maximum value of the information leakage ratio of multimedia fusion data based on IoT data security is reduced from 0.0865 to 0.003, and the data security is significantly improved. In the consensus verification process, to reduce the consensus time and ensure the operating efficiency of the system, a consensus node selection algorithm is proposed, thereby reducing the time complexity of the consensus. Based on the smart grid application scenario, the security and performance of the proposed model are analyzed. This study proves the correctness of this scheme by using BAN logic and proves the security of this scheme under the stochastic prediction machine model. Finally, this study compares the security aspects and performance aspects of the scheme with some existing similar schemes and shows that the scheme is feasible under IoT.

Design and implementation of multimedia video fusion system

With the rapid development of computer network application technology, various video products and video systems are changing with each passing day. The daily internal communication, training and exchange activities mainly use video conference, paperless conference, projection display, large screen splicing display and other video systems for interaction. These systems are developed and run independently and lack system linkage. In addition, due to the disunity of platforms, the system is prone to multiple devices, complex operation and low resource utilization, which increases the operation and maintenance cost. To solve the above problems, a set of multimedia video fusion system is designed to integrate various video systems to achieve unified control of video conference, paperless conference, projection display, large screen display and other systems, effectively support the use of various business scenarios, and achieve the purpose of improving efficiency and reducing costs.

Analysis of College Students' Mental Health Education Model Based on Media Integration.

At present, the mental health problems of college students in China are on the rise. Many incentives lead to college students becoming a psychological vulnerable group, lacking the minimum “decompression ability” in the face of pressure. With the emergence of new media and the increasingly obvious fusion of new media and traditional media, the recognition algorithm of media fusion begins to enter people's vision, and multimedia fusion has gradually formed an irresistible development trend. Based on the media fusion recognition algorithm under the background of media fusion, this paper studies the model of college students' mental health education. In the process of comparing the accuracy of college students' mental health, the accuracy of this method is the highest, up to 99.25%, followed by the decision tree algorithm, up to 80.53%, and finally the ant colony algorithm, up to 75.25%. Therefore, this method is more conducive to the study of college students' mental health. Under the media fusion recognition algorithm, colleges and universities should give full play to the advantages of media fusion, broaden the path of mental health education, enhance the effectiveness of mental health education, improve the quality and efficiency of education, and guide the mental health growth of college students.

Research on the Blended Teaching Mode Reform of University Physical Education Curriculum Based on the Integration of 5G Cloud Computing and Multimedia

With the advent of the Internet+ era, the fifth generation of mobile communication technology (5G) will bring about new opportunities for the development of sports wisdom teaching and promote the new direction of sports wisdom teaching from offline teaching to multimedia integration of online and offline teaching. Students are more enthusiastic about multimedia than the course. Therefore, while catering to students’ interests and needs, we proposed a mixed teaching reform experiment of multimedia integration based on 5G cloud computing communication technology to observe the differences in students’ physical exercise behavior and body composition before and after the teaching reform. The methods of literature, questionnaire, teaching experiment, measurement, and quantitative statistics were adopted. The results show that the experimental results of multimedia fusion and mixed teaching reform based on 5G cloud computing communication technology show that the teaching reform experiment can effectively increase the number of college students’ sports population and promote the change of students’ body composition. The experimental results of mixed teaching reform with multimedia integration show that the experiment of teaching reform can effectively increase the number of college students’ sports population and promote the change of students’ body composition. The conclusions show that the increase in the sports population chiefly mirrors the stability of students’ physical exercise behavior and the betterment of sports participation, which effectively promotes the formation of students’ physical exercise habits. The changes of body composition showed significant changes in the basal metabolism (BM), body mass index (BMI), body fat mass (BFM), visceral fat index (VFI), and other components, which indicated that the reform of teaching experiment could effectively promote students’ participation in sports, promote students to shape a healthy body, and promote students’ good physical health. At the same time, the experiment showed the difference between male and female. The muscle of male students began to increase significantly, while that of female students was still in the stage of decreasing water content and not increasing muscle significantly. It shows that girls need more time to exercise to bolster their body composition and achieve the effect of promoting physical health level effectively. China has entered a new era of 5G cloud computing, college students are relatively quick to accept new things, and the traditional teaching mode cannot fully stimulate students’ interest in physical exercise. Therefore, the multimedia integrated teaching mode based on 5G cloud computing communication technology is an inevitable trend of PE curriculum reform. It can not only deeply promote students’ physical exercise habits but also promote students’ physical health to a certain extent. Thereby, it boosts Chinese great strategy of health as well.

RETRACTED ARTICLE: Game analysis of the equity investment exit mechanism of university schools and enterprises under the background of internet multimedia convergence

In today’s highly developed information, multimedia involves no longer just the traditional teaching and media industry, but a broader and more comprehensive process. The game analysis of using the Internet multimedia to carry out the investment exit mechanism of colleges and universities can greatly improve Management efficiency. This paper analyses the game form of the equity investment exit mechanism of colleges and universities in the context of Internet multimedia fusion, and analyses its existence and significance to enhance the equity exit mechanism of schools and enterprises, and analyses and discusses them. This paper establishes a game analysis on the exit method and exit timing of college-enterprise equity investment, which has certain reference value. The perfect exit mechanism is an inevitable requirement for the development of equity investment in colleges and universities, and it is an inseparable part of the equity investment system of colleges and universities. This will enable China’s colleges and universities to have a relatively good and standardized operating environment for equity investment, which will drive China’s economic connotation growth. This has related to the construction of many external environments such as capital markets, policies, and regulations. Therefore, it is necessary to improve the multi-level capital market as soon as possible and accelerate the construction of external systems such as policies and regulations.

Game Engine Conventions and Games that Challenge them: Subverting Conventions as Metacommentary

Consumer-grade game engines such as Multimedia Fusion and RPG Maker have dramatically extended the reach of digital games as a medium. They have also spawned online communities, where conventions and canons of using these tools have evolved. These partly stem from the functional constraints of the game engines themselves and are institutionalized through manuals, examples, tutorials, and games made with them. However, some members of game engine communities actively seek to challenge these conventions by experimenting with the engines and finding ingenious ways to put them to unexpected uses. Such experiments can be regarded as a form of metacommentary on the engines’ capabilities and limitations. While arguably impractical and inefficient, they enrich the scope of what can be done with the engine and can contribute to its further development.

Survey on Modeling and Detection Events in Georeferenced Multimedia Fusion

Survey on Modeling and Detection Events in Georeferenced Multimedia Fusion

Survey on modeling and detection events in georeferenced multimedia fusion

Survey on modeling and detection events in georeferenced multimedia fusion

Multi-INT Query Language for DDDAS Designs

Abstract Context understanding is established from coordination of content, analysis, and interaction between users and machines. In this manuscript, a live-video computing (LVC) approach is presented for access to data, comprehension of context, and analysis for context assessment. Context assessment includes multimedia fusion of query-based text, images, and exploited tracks, which are utilized for information retrieval. We explore developments in database systems which enable context to be extracted by user-based queries. Using a common image processing data set, we demonstrate activity analysis with context, privacy, and semantic-awareness in a Dynamic Data-Driven Applications System (DDDAS).

Dynamic Data-driven Application System (DDDAS) for Video Surveillance User Support

Human-machine interaction mixed initiatives require a pragmatic coordination between different systems. Context understanding is established from the content, analysis, and guidance from query-based coordination between users and machines. Inspired by Level 5 Information Fusion ‘user refinement’, a live-video computing (LVC) structure is presented for user-based query access of a data-base management of information. Information access includes multimedia fusion of query-based text, images, and exploited tracks which can be utilized for context assessment, content-based information retrieval (CBIR), and situation awareness. In this paper, we explore new developments in dynamic data-driven application systems (DDDAS) of context analysis for user support. Using a common image processing data set, a system-level time savings is demonstrated using a query-based approach in a context, control, and semantic-aware information fusion design.

Content-oriented multimedia document understanding through cross-media correlation

This paper presents a novel method for multimedia document content analysis through modeling multimodal data correlations. We hypothesize that the correlation of different modalities from the same data source can help achieve better multimedia content understanding results than one which explores a single modality. We turn this task into two parts: multimedia data fusion and multimodal correlation propagation. During the first stage, we re-organize the training multimedia data into Modality semAntic Documents (MADs) after extracting quantized multimodal features, and then use multivariate Gaussian distributions to characterize the continuous quantity by latent topic modeling. Model parameters are asymmetrically learned to initialize multimodal correlations in the latent topic space. Accordingly, during the second stage, we construct a Multimodal Correlation Network (MCN) based on the initialized multimodal correlations, and a new mechanism of propagating inter-modality correlations and intra-modality similarities in MCN is further proposed to take the complementary from cross-modalities to facilitate multimedia content analysis. The experimental results of image-audio data retrieval on a 10-categories dataset and content-oriented web page recommendation on the USTODAY dataset show the effectiveness of our method.

Multimedia Fusion for Public Security in Heterogeneous Sensor Networks

Public security is a widespread disastrous phenomenon that constitutes a grave threat. Although information fusion of video sensor networks for public security has been studied extensively, multimedia fusion in heterogeneous sensor networks or its application in public security remains a challenge and central goal in the field of information fusion. In this study, to realize the detection, monitoring, and intelligent alarm of such hazards, we develop a graph-based real-time schema for studying the dynamic structure of heterogeneous sensors for public security. In the proposed schema, data fusion algorithms based on data-driven aspects of fusion are explored to locate the optimal sensing ranges of sensor nodes in a network with heterogeneous targets. In addition, we propose a framework incorporating useful contextual and temporal cues for public security alarm, explore its conceptualizations, benefits, and challenges, and analyze the correlations of the target motion elements in the multimedia sensor stream. The experimental results show that the new method offers a better way of intelligent alarm that cannot be achieved by existing schemes.

Query-Document-Dependent Fusion: A Case Study of Multimodal Music Retrieval

In recent years, multimodal fusion has emerged as a promising technology for effective multimedia retrieval. Developing the optimal fusion strategy for different modalities (e.g., content, metadata) has been the subject of intensive research. Given a query, existing methods derive a unified fusion strategy for all documents with the underlying assumption that the relative significance of a modality remains the same across all documents. However, this assumption is often invalid. We thus propose a general multimodal fusion framework, query-document-dependent fusion (QDDF), which derives the optimal fusion strategy for each query-document pair via intelligent content analysis of both queries and documents. By investigating multimodal fusion strategies adaptive to both queries and documents, we demonstrate that existing multimodal fusion approaches are special cases of QDDF and propose two QDDF approaches to derive fusion strategies. The dual-phase QDDF explicitly derives and fuses query- and document-dependent weights, and the regression-based QDDF determines the fusion weight for a query-document pair via a regression model derived from training data. To evaluate the proposed approaches, comprehensive experiments have been conducted using a multimedia data set with around 17 K full songs and over 236 K social queries. Results indicate that the regression-based QDDF is superior in handling single-dimension queries. In comparison, the dual-phase QDDF outperforms existing approaches for most query types. We found that document-dependent weights are instrumental in enhancing multimedia fusion performance. In addition, efficiency analysis demonstrates the scalability of QDDF over large data sets.

Multimedia Data Fusion

Multimedia data is widely used in the world such as image, video, text, and audio. For obtaining better sensing performance, research on multimedia data fusion (MDF) is active and extensive around the world. In medical systems, a body part could be imagedwith different sensors such as computed tomography and magnetic resonance imaging. In video surveillance, the interest is in the identification, recognition, and tracking of people by numerous cameras. All of these cases illustrate the importance of MDF in real-life applications. A number of mathematical methods have been researched in MDF such as statistics, fuzzy mathematical, stochastic differential theory, and computational methods. As a special issue, we aim to reflect on the current and future theory and application of MDF in the following aspects: sensor fusion in multimedia medical data, sensor registration in 3D multimedia data, sensor selection for optimal sensor fusion, performance evaluation of the data fusion algorithms, joint data registration and fusion algorithms and the application of multimedia data fusion.

Multimedia Fusion With Mean-Covariance Analysis

The number of multimedia applications has been increasing over the past two decades. Multimedia information fusion has therefore attracted significant attention with many techniques having been proposed. However, the uncertainty and correlation among different information sources have not been fully considered in the existing fusion methods. In general, the predictions of individual information source have uncertainty. Furthermore, many information sources in the multimedia systems are correlated with each other. In this paper, we propose a novel multimedia fusion method based on the portfolio theory. Portfolio theory is a widely used financial investment theory dealing with how to allocate funds across securities. The key idea is to maximize the performance of the allocated portfolio while minimize the risk in returns. We adapt this approach to multimedia fusion to derive optimal weights that can achieve good fusion results. The optimization is formulated as a quadratic programming problem. Experimental results with both simulation and real data confirm the theoretical insights and show promising results.

Multimedia Fusion Era Editorial Role

Abstract With digital technology, the rapid development of new technology, digital media era has arrived, a variety of media have emerged a new trend of convergence. Then, edit the Multimedia Fusion should be the role of? The thesis that edit roles should highlight three areas: one is the more prominent editorial guidance function; the second is more focused on editorial planning function; the third is the more prominent editing creativity.