The essential purpose of this research study is to determine the public perceptions of nanotechnology research, describe the risks and benefits also trust between them. This research study was also conducted in Chine to determine the perception of nanotechnology. This research study depends upon primary data analysis to describe theoretical concepts related to the risk, benefits, and trust of nanotechnology. This research study also depends upon the observation of research participants about nanotechnology. For this purpose, develop different research questions and fulfill these questions from local participants who know about nanotechnology. Smart PLS software was utilized to measure the research study's findings. It produced informative results that included the R square, Total effects, significant analysis, and descriptions of the path coefficient analysis and the combined effects of graphical analysis between them. The result found that some public perception is positive thinking about nanotechnology and some negative also that nanotechnology plays a vital role in every field of industries.
The teaching of solid geometry plays an essential role in cultivating students' spatial imagination ability. In the traditional teaching method, teachers often operate by themselves to avoid the damage of teaching tools. Students can only observe passively, which is easy to produce a sense of boredom to study. Moreover, abstract geometric features and phenomena are not intuitive enough for students to form a correct cognition of solid geometry. In this paper, we designed an inquiry geometry learning environment by using virtual reality technology. Students can interact with the virtual geometry model to promote immersive, interactive, and inquiry learning to improve students' understanding of geometric structures and features. To study the influence and application effects of virtual geometry learning environment on students ' learning knowledge level, we recruited 60 seventh grade students (aged 13-14 years) and randomly divided them into VR teaching group (N=30) and control group (N=30). Students in the VR teaching group conducted gesture-based inquiry learning in the virtual geometry learning environment, while students in the control group used traditional methods to learn. The test of geometry knowledge before and after the experiment indicates that the virtual geometry learning environment positively impacts students' acquisition of geometry knowledge. The questionnaire survey results show that the students' subjective perception of usability and willingness to use score high. Virtual reality and gesture interaction techniques can help students visualize geometric abstractions and facilitate their understanding, and students have shown a strong desire to continue learning using related technologies.
The continuous expansion of technological innovation and big data technology to various fields has brought great challenges to the reform of high school education. This work intends to improve the teaching effect of classical poetry in high school Chinese teaching, change the traditional teaching method, improve students' subjective initiative and practical ability, and improve the teaching effect of classical poetry under the traditional philosophy. The Outcome-based Education (OBE) teaching philosophy and the personalized recommendation algorithm of teaching resources based on Convolutional Neural Network (CNN) are applied to the teaching of classical poetry in high school. The teaching objectives, teaching process and teaching activity evaluation are designed. The model design is applied to the teaching of the experimental class, and the results of the application of the design model are comprehensively evaluated through comparison. The result shows: (1) Through the evaluation and analysis of teaching strategies, the satisfaction of pre-class preparation strategy, classroom teaching implementation strategy and after-class teaching evaluation strategy design mode is higher than that of traditional teaching mode. In particular, the satisfaction of teaching results in class 1 and class 2 are 95.1 % and 93.3 %, respectively, while that in the control class is only 62.6 %. (2) The teaching implementation process is evaluated. Comparisons are made from the exploration of teaching activities, the interaction between teachers and students in the classroom, and the recommendation of teaching resources. (3) The application effect of the design model is evaluated. The satisfaction degree of the experimental class is higher than that of the control class in terms of learning attitude, learning ability and academic performance. (4) The satisfaction of the design model is higher than other teaching models in terms of student recognition, goal achievement and teaching effect. It aims to innovate the teaching methods of high school poetry appreciation, provide some reference for teaching reform, and provide some ideas for the subsequent application curriculum.
In order to solve the teaching problems such as the single form of traditional teaching mode and the unsatisfactory effect of classroom teaching, this paper proposes a new teaching mode based on the fusion of multimodal multimedia information. The main research contents are: Firstly, the concept of modal and multi-modality is expounded in detail, and the representation form of modal carrier multimedia is described in detail. Secondly, the problems existing in traditional teaching are analyzed. Finally, in Solutions Statistical Package for the Social Sciences (SPSS), the normal equation is solved by using the least square method, and the statistical data is saved in the data file to realize the nonlinear analysis of the data to realize the change of multimodal information technology in preschool education by using nonlinear analysis technology. The results show that in the traditional preschool education mode, the number of students with good learning status in the class is always kept at 20%, and the number of students with poor learning and ordinary learning is almost the same. In the multi-modal teaching mode, the number of outstanding students is increasing by 12% every week, accounting for 60% in the last week, which is more than half of the number of normal classes. It clearly shows that students feel the innovation and interest of multi-modal technology integration teaching, and have a high interest in learning. After the integration of multimodal information technology, the teaching classroom of preschool education has become rich and the students' practical ability has been improved. The research in this paper provides a theoretical basis for the integration of multimodal information technology in college teaching, which is helpful for more research on improving the quality and effect of classroom teaching in colleges and universities in the future.
In recent years, frequent occurrence of major emergencies in our country not only endangers social stability, causes loss of life and property, but also has a huge impact on psychology of audience. crisis. In order to minimize psychological impact of sudden public crises on audience, it is necessary to conduct in-depth research on group psychological service process under sudden public crises. According to characteristics of sudden public crisis events and psychological services, this paper analyzes reasons for psychological service reactions of individuals, mainly from external and internal aspects, and proposes that psychological service process mainly includes three stages: psychological service The formation, development and termination of psychological service in three stages are described in detail, and feasibility of Agent modeling of group psychological service is analyzed. And put forward intervention measures of psychological service, mainly starting from social support and crowd environment, respectively changing intensity of social support and size of crowd environment to intervene in psychological service process of group, which is beneficial to emergency management of sudden public crisis events in our country. policy recommendations.
Under the "Belt and Road" project and China's Intangible Cultural Heritage (ICH) program, embroidery culture has gained significance. Yet, a comparative assessment of the current state of embroidery research in China and other nations is limited. Using CNKI, WoS, and CiteSpace, a knowledge graph analysis tool, we determined the state and trends of embroidery research from 2010 to 2022. China, the United States, and the United Kingdom perform the most embroidery research, according to the findings. Recently, there has been a trend among Chinese researchers toward interdisciplinarity, and they have begun to publish actively abroad. Chinese research focuses on the craft techniques of embroidery, the artistic characteristics of embroidered fabrics, the design and application of needlework, as well as conducting study on national cultural connotations and innovative embroidery design under the category of ICH. The focus of international research is on embroidery fabric materials, machine embroidery, recognition and image analysis of embroidery weaves, with the promotion of machine embroidery, the conductivity of intelligent fabrics, and ancient weaves serving as the central themes. Future Chinese researchers can compare cutting-edge international research in three dimensions: (1) inter-disciplinary embroidery research; (2) innovative design and application of embroidery; (3) system development and standardisation of folk embroidery.
The principles of protection relay architectures for use inside a Brilliant Matrix and depict the results of a hypothetical turn of events. The whole structure that must be considered for protective operation inside Brilliant Network is laid out in this article, along with the assessment methods that were applied in both blamed and regular scenarios. Shikoku Electric Power CO., INC created a 66kV framework, and the results of a field experiment show that this framework is capable of managing, coordinating check, and improving setting values while being able to completely evaluate power framework characteristics continuously. Power framework protection is arguably the most challenging area of electrical engineering because it requires not only a thorough understanding of the various components of a power system and how they interact but also a thorough understanding of the unusual circumstances and failures that can occur in any one of them. Distance relays are affected by shortfall blockage in how they operate, which causes them to estimate impedance incorrectly and lead to under-arrived conditions. The trip report of the shortage occurrence on the Alaoji-Afam 330kV line served as evidence of the impact of the blockage issue on the relay operation. This research intends to change the defined safe zone in order to improve distance relay performance on the Alaoji-Afam 330kV transmission line in terms of dependability, speed, and selectivity when a significant obstacle is present. The distance relay employed in this investigation is displayed and emulated using NEPLAN software.
In order to make full use of flight data, combined with the development of machine learning algorithm under big data technology, flight data is applied to aero engine fault diagnosis and prediction technology. Through the accumulation of flight data, combined with the classification and prediction functions of advanced algorithms, the comprehensive processing of flight data can identify aero engine failure modes and predict potential risks, providing a scientific basis for aero engine health monitoring and management. The research is of great significance to ensure flight safety and improve economic benefits.
The age of self-media means that every consumer user can publish production information and influence others. Therefore, the interaction between consumer users and companies on self-media platforms is far more effective than before, and the way of purchasing decisions has been transformed. This paper takes the characteristics of consumer users as the starting point, integrates the three consumption processes and analyzes the consumption characteristics of consumer users by analyzing the changes in the interaction characteristics of consumer users and companies and the way of transaction shopping decision in the era of self-media; soundly estimates the characteristics of consumer users of companies on the self -media platform in a way that provides reference for the marketing activities and practical activities of companies; through the inevitability of interactive communication between companies and consumer users on the self-media platform analysis, build the value model of consumer user characteristics based on the current dilemma encountered by consumer users in the era of self-media; explore the influence of consumer user characteristics on corporate marketing activities, analyze the necessity of self-media platforms, show the connection between self-media and consumer users, broaden sales channels by grasping consumer user characteristics, and finally constitute a positive feedback system.
Violin concerto is of great significance to the development of the whole classical music. Polyphonic music is one of the important essence of violin concerto. The intelligent recognition and analysis of violin concerto polyphony is of great significance to the development and intelligent creation of violin music. This paper analyzes the possibility of applying depth learning to violin concerto polyphony recognition and analysis, constructs a violin microphone array polyphony source extraction system using intelligent sensors, and establishes a violin concerto polyphony melody extraction and analysis model based on depth learning CNN-CRF algorithm. Subsequently, the actual experimental simulation was carried out. The results show that the violin concerto polyphony extraction model based on convolutional neural network is improved by 2.1% and 0.1% respectively compared with other models. According to the extracted and analyzed data, the electronic reproduction process of the violin concerto polyphonic music is simulated. It has laid a certain foundation for the following violin concerto music theory intelligent analysis and artificial intelligence creation.
With the development of online interactive information, multimedia e-commerce platforms have been seen everywhere. Digital painting technology can well optimize the deficiency of online display function of business platform. In this paper, firstly, we study a commodity image saliency information autonomous classification system based on digital painting technology. The autonomous classification system includes image preprocessing module, salient information feature extraction module and convolutional neural network classification module. The high-quality images after independent classification are used for online platform display. Based on virtual touch, this paper studies the impact of digital painting technology and online interactive function optimization of online display products on consumers' purchase actions. The results show that: the training classification model used in this paper has an accuracy rate of more than 99% for independent classification of digital painting commodity images; Digital painting image technology and online interaction take virtual contact as an incomplete intermediate variable, which has a direct and indirect impact on consumers' impulse purchase desire.
A classification method for health-related questions in Chinese combining multi-channel attentional convolution and syntactic analysis is proposed to address the characteristics of sparse and noisy Chinese health interrogative sentences, as well as the shortcomings of traditional neural networks feature extraction which ignores the syntactic relationship of text. In this study, our method first used the BERT pre-trained language model to generate word vectors to alleviate the problem of semantic sparsity caused by short texts. Then, multiple layers of convolutional kernels at different scales were used to extract semantic features of interrogative sentences at different granularities to solve the problem of noisy public health interrogatives, which was also combined with multi-scale feature attention mechanisms to suppress irrelevant semantic information to highlight deeper features of the text. Next, our method stitched the extracted interrogative features to obtain multi-level interrogative feature information. Meanwhile, we also constructed syntactic dependency graphs through syntactic analysis, and used graph attention networks to capture syntactic dependencies within the text. Finally, the probabilities of the input text in each category were obtained by the full concatenation and Softmax classifier thereby to achieve the final classification purpose. Experiments demonstrated that the precision, recall and F_1 value of our method were 87.9%, 88.1% and 88.0%, respectively, on the Chinese health care question dataset, suggesting our method can effectively improve the semantic representation and classification for questions about health issues in Chinese.
Sustainable development stands as a paramount strategic objective for the Chinese government, along with being a crucial research subject within the realm of China's sports industry. This industry has transformed into a pivotal element and a significant domain in the construction of China's athletic dominance, emerging as a dynamic catalyst for the nation's high-quality economic advancement. Regrettably, the exploration of sustainable development within China's sports industry has not received the requisite attention and profound investigation it deserves. The purpose of the study is to analyze the internal and external development environment of China's sports industry from four aspects with the help of SWOT-PEST model: Political, Economic, Social and Technological, and make an exploratory study on the strategic choices for the sustainable development of China's sports industry, suggesting: Strengthen the leading role of the Chinese government in the sports industry, increase policy support and financial investment; reduce the tax burden of sports enterprises and encourage sports enterprises to expand their scale; innovate sports products and services to promote the development of sports and health industry; Continue to strengthen the intelligent construction of sports infrastructure to improve operational efficiency and sports experience; strengthen international cooperation and exchanges, and learn from the experience and technology of other countries to improve international competitiveness; and utilize the digital economy to promote the development of the sports industry by organizing online tournaments and virtual spectator experiences, and other specific development strategies.
with the advent of the Internet era, the frequency and proportion of job seekers using the Internet to access recruitment information have been increasing. Consequently, the volume of human re-source information, including talent profiles and job postings, has experienced an unprecedented growth, posing challenges of information overload to human resource services. Recommender systems, however, can proactively address this issue by helping users navigate through the over-whelming information and delivering content that aligns with their interests, thereby becoming a primary tool for tackling information overload in the Internet era. Meanwhile, in recent years, deep learning has achieved remarkable success in various domains such as computer vision, nat-ural language processing, and semantic recognition. However, the application of deep learning in the field of recommender systems, particularly in the context of human resources, remains limited. Current research efforts in the development of human resource recommender systems mainly rely on traditional collaborative filtering or content-based filtering algorithms, with few explorations and investigations into novel recommendation approaches. To enhance the performance of hu-man resource recommender systems, this paper proposes a deep learning-based approach. This method involves transforming human resource data into normalized images and employing im-age processing techniques for learning and training on the human resource database. By doing so, this approach effectively addresses major issues encountered in traditional collaborative filtering algorithms, such as data sparsity and cold-start problems, thereby achieving higher recommendation performance.
Wool fiber, a ubiquitous natural fiber, carries numerous beneficial characteristics making it and its derived fabrics a popular choice in the commercial arena. However, the felting induced by the fiber's structural traits adversely affects its wear ability. This manuscript presents a comprehensive review of the merits and drawbacks associated with various wool processing techniques, the origin of enzyme extraction, the influence of diverse enzymes on different wool structures, and the additional utilities of enzymes.
In the age of informatization, the development of enterprises is affected by internal and external factors such as themselves and external competition, and the risks they face are gradually increasing. Therefore, it is urgent to establish an active, effective, targeted, sustainable, and effective early warning system. This paper analyzes the enterprise financial risk and its formation reasons, and studies in depth the factors affecting the enterprise financial risk early warning. On this basis, based on the Z3 model, it selects the financial risk early warning index with high comprehensiveness and conducts a comprehensive evaluation of the enterprise's financial risk from the enterprise's development situation and the industry's development prospect. Finally, relevant early warning measures are proposed, which are important for the early warning of corporate financial risk.
Chemical laboratory hazardous chemical management is a crucial component of laboratory management, as poor management can lead to serious accidents and losses. However, research on the HAZOP (Hazard and Operability Study) method in the field of chemical laboratory hazardous chemical management is relatively limited. This study aims to conduct an in-depth investigation into chemical laboratory hazardous chemical management based on the HAZOP method, in order to fill the research gap in this field. Firstly, we provide an overview of the HAZOP method, which is a commonly used hazard and operability analysis approach that identifies potential risks and safety vulnerabilities in hazardous chemical management. Subsequently, this study applies the HAZOP method to various aspects of chemical laboratory hazardous chemical management. Using this method, we identify factors that may give rise to risks such as fire, explosion, leakage, and poisoning in the storage, use, handling, and disposal of hazardous chemicals, and propose corresponding preventive measures and emergency response plans. The research findings demonstrate that applying the HAZOP method can enhance the efficiency and safety of hazardous chemical management, reduce the probability of accidents, and strengthen the safety awareness of laboratory personnel. This study provides laboratory managers and practitioners with a feasible approach for identifying and managing risks associated with hazardous chemicals, thereby ensuring the safe operation of the laboratory.
With the development of Internet and Big data technology, Internet music services have become an important channel for people to access music. However, existing internet music services often face issues such as inaccurate personalized recommendations and incomplete data management. To address these issues, this study designs a new internet music service prototype based on the idea of data grids. After utilizing data grid technology, we established a large and rich music data grid, slicing and storing music information in different dimensions. By utilizing this emerging approach, we can efficiently manage and access music data, and improve service performance and response speed. And we adopted a personalized recommendation algorithm based on user preferences and music features. By analyzing users' historical behavior and preferences, combined with the corresponding styles, emotions, and other characteristics of music, we can accurately recommend music content that suits their interests. After Big data computing and in-depth discussion of the principles of the Internet of Things, the new music service using data grid has great advantages in personalized recommendation and data management. Users can more conveniently access their favorite music while saving storage and processing resources on the server. The contribution of this study is to combine data grids with traditional internet music and demonstrate its advantages in personalized recommendations and data management through experiments. This prototype provides an important reference for the improvement and development of internet music services and provides users with a more efficient and personalized music experience.
In order to effectively ensure the effect of the three-dimensional hovering control of the tunnel inspection robot, enhance the anti-interference ability of the three-dimensional hovering control of the tunnel inspection robot, and shorten the three-dimensional hovering control time of the tunnel inspection robot. A 3D hovering control algorithm for tunnel inspection robot based on robust inverse sliding mode control is proposed. Analyze the basic principle of inversion method, design sliding mode variable structure control, and study adaptive inversion sliding mode control. The three-dimensional physical model, kinematic model and motion control model of the tunnel inspection robot are established. Through the design of fuzzy adaptive estimation, the robust inversion sliding mode control method is adopted to realize the three-dimensional hovering control of the tunnel inspection robot. The experimental results show that the control accuracy of the proposed algorithm reaches 50 cm and the error is less than 2 cm. When the three-dimensional hovering depth reaches 50cm, the control time is 9.7s. It is proved that the proposed algorithm can effectively enhance the anti-interference ability of the three-dimensional hovering control of the tunnel detection robot, shorten the three-dimensional hovering control time of the tunnel detection robot, and ensure the safety and stability of the detection when detecting the diversion tunnel of the hydropower station.
The security of cryptographic products not only relies on the mathematical security of cryptographic algorithms, but is also affected by the physical security of cryptographic implementations. Side-channel attacks utilize side-channel information such as power consumption, electromagnetic radiation, and operation time generated during encryption and decryption of cryptographic products, which may lead to key leakage and pose a serious threat to the security of cryptographic products. However, there are some problems in the existing evaluation methods of side-channel attacks, such as the inability to accurately find the key leakage location, low accuracy and efficiency. In order to solve these problems, this paper proposes a side channel leakage assessment framework based on digital twin technology, which utilizes digital twin technology to generate a simulation model of cryptographic devices to simulate the side channel information generated during the encryption process of cryptographic devices, and by testing and analyzing the simulation model, the relevant side channel information and leakage locations can be accurately measured. The study also proposes a measurement algorithm, which utilizes the simulation model generated by digital twin technology for measurement. By testing different encrypted plaintexts, the measurement algorithm can accurately determine whether there is any side channel leakage of the cryptographic device and determine the key leakage location. The experimental results show that the evaluation method based on digital twin technology has higher accuracy and efficiency compared with the traditional method, and this study is of great significance for the security evaluation and improvement of cryptographic products
