With the development of network service integration, in order to obtain a better quality of service (QoS) guarantee, aiming at the characteristics of integrated network service composition and correlation, this paper proposes a QoS correlation-based service composition (QCSC) approximate algorithm based on multi-constraint optimal path selection (MCOPS). It analyses the QoS correlation criteria, correlation ratios, and Skyline algorithms to calculate the optimal path by dynamic programming, record the path nodes, and obtain the optimal service composition path that meets the user's demand. Simulation results demonstrate the good performance of the proposed algorithm in both the average calculation time and the solution path quality. Accordingly, it can meet the QCSC requirements in the cloud environment.
Objectives: To discuss the construction of hybrid teaching mode of nursing under new situation and evaluate its effect. Methods: Using information technology to build a blended teaching mode, nursing students in Class 2 Grade 2017 were randomly selected as the observation group, and students in the other class as the control group. The hybrid teaching mode was used in the observation group, and the traditional teaching method was used in the control group. Observe and compare the teaching effect. Results: The observation group got higher marks in theoretical knowledge mastery, course preference degree, critical thinking ability and self-learning ability, which had statistically significant differences from the control group. Conclusion: Under the epidemic prevention and control situation, the blended teaching based on information technology not only improves the teaching quality and teaching efficiency, but also can mobilize students' enthusiasm for learning and promote the improvement of students' communication ability.
In order to improve the programming ability of students, teachers are actively seeking various new methods for research and practice. Based on the “Data Structure and Program Design” course, we have carried out the exploration and practice of blended teaching, formulated instructional design based on OBE theory, constructed the teaching mode of online preview before class, offline class + online test in class, and online test after class. Practice shows that these measures improve the students' ability to analyze, express and solve problems.
In recent years, China has been paying attention to the cultivation of international talents. This paper aims to cultivate international talents with international vision. Take the combination of information technology and international teaching as the path, formulate an international talent cultivating program in line with the needs of social development, and take the school of economics and economics of Shandong University of finance as the pilot object. The results show that the integration of international teaching and information technology has significantly improved the proportion of international courses and the scale of teachers.
In recent years, with the rapid development of the Internet and communication technology, online learning has become an important means and way for college students to acquire knowledge, but the quality and effect of online learning are not satisfactory. By exploring the reasons why college students are willing to invest time and energy in online learning, more targeted online courses can be developed to further promote the overall knowledge literacy of college students. This article adopts a data-driven approach, starting from the emotional dimension, by studying the comments and barrage data of some courses in bilibili, China University MOOC, and Tencent classrooms, after data cleaning, use topic analysis, word cloud graphs and data visualization to analyze the emotional state of college students in the process of learning online classes. Combined with the interactive mode, manipulation method, and auxiliary functions of the online course, leads to the reasons why college students are willing to invest time and energy in online learning. Through the research results, we found that online teaching videos with advanced marking of the difficulty of the course, humorous teaching style, and high degree of interaction are more popular among college students. Therefore, this research suggests that teachers can carry out gradient teaching when recording online courses, breaking down the difficulties from simple to deep, from easy to difficult, and at the same time increase teacher-student interaction in the teaching process to increase students' participation, thereby increasing the emotional investment in online learning level. Applying the findings of this survey to online teaching platforms and online teaching arrangements for colleges and universities will better increase the degree of college students' online learning investment, and improve the sustainability of college students' online learning investment as a whole.
With the development of information technology, informatization plays an increasingly important role in medical vocational education. It has a broad prospect to improve the quality of medical vocational education with information as the starting point. This paper analyzes from the aspects of informatization to improve the level of internal governance, leading the implementation of the reform of the three education, and enhancing the synergy of medical education. It focuses on the construction of internal control system of medical vocational colleges, decision-making assistance system of medical vocational colleges, and intelligent management system of medical vocational colleges. Informatization leads the reform of teachers, teaching materials and teaching methods, the collaborative platform of education resources and medical education, and the collaborative platform of job skills and medical education, etc. Combining with the characteristics of medical education itself, it is of practical significance to use information measures to assist the construction of high quality medical education.
This paper makes a brief introduction of the design and application of Blind Chess education system based on speech recognition. We put forward a new online system for Blind Chess education on the basis of speech recognition. Our system enables users to move pieces by virtue of voice messages when they are not looking at the chessboard so as to make Blind Chess training more effective. Meanwhile, it also removes site restrictions and save much manpower. The paper proposes a Chinese Chess terminology analysis algorithm based on the rule base. The algorithm can use existing, well-established Chinese Chess terminologies as voice input, into texts through speech recognition techniques, and extract the initial and end positions of pieces after querying the rule base. The experiments on the application of our Blind Chess education system have been carried out using the computer to improve the recognition accuracy of some common words and make the system more humanized. Practical operations have proved that the Blind Chess education system can provide better experiences for users, effectively promote traditional cultures and help develop user's intelligence and thinking ability.
The quality of dissertations is an important reference for evaluating the quality of graduate degree-awarding. Most of the methods evaluate the quality of the dissertation from four types of dimentions, topic and review, innovation and paper value, scientific research ability and basic knowledge, and the standard expression of the paper. However, the experts' comments often have great value for evaluating the quality of the dissertations. Thus, this paper proposes an innovative method of quality evaluation of the dissertations, which integrates the experts' comments and four types of evaluation criteria mentioned above. The results show that the deviation of the dissertations' score becomes larger. So, it is easier to distinguish between excellent papers and problematic papers, as the score of low-level papers decrease, while the score of high-level papers increase. And, our proposed method has a strong generalization ability for all levels of the paper. Finally, the paper compares the indicators and comments of the eliminated papers and excellent papers in the engineering discipline, analyzes the typical characteristics of the two kinds, and gives corresponding suggestions on how to write high-level dissertations.
Engineering mechanics is a fundamental major course for engineering majors in application-oriented universities. Based on reviewing current situation of classroom teaching of engineering mechanics, the paper puts forward the countermeasures for reforming classroom teaching in the student-centered principle, including making the innovation of teaching pattern, integrating theoretical knowledge with engineering practice and introducing curriculum ideological and political education, in order to achieve the cultivation of comprehensive and all-round applied-type talents. The research can provide reference for the education of fundamental mechanics courses.
Steiner minimal tree construction is a key step in the physical design of Very Large Scale Integration (VLSI). Further considering X-architecture with better wirelength optimization and allowing wires to pass through obstacles to a certain extent before signal distortion, a novel X-architecture Steiner Minimal Tree with Limited Routing Length inside Obstacle (XSMT-LRLO) problem is formed. Therefore, the XSMT-LRLO based on Discrete Particle Swarm Optimization algorithm (XSMT-LRLO-DPSO) is proposed. Firstly, in order to significantly reduce the times of evaluations, a preprocessing strategy based on a lookup table is proposed. Secondly, XSMT-LRLO-DPSO is effectively en-coded by adopting the edge-point pairs encoding method adapted to an evolutionary iterative process. Then, aiming at the XSMT-LRLO problem, which is a discrete problem, a discrete update strategy based on mutation operation and crossover operation is proposed. Finally, adjustment and refinement strategies are introduced to respectively improve the obstacles bypassing ability and wirelength optimization ability of the proposed algorithm. The experimental results show that the proposed algorithm makes full use of the routing resources within the obstacles, and effectively saves routing resources. Compared with similar algorithms, the proposed algorithm has the strongest wirelength optimization ability.
This paper studies learning engagement measurement in SPOC. Based on the existing literature and the analysis of SPOC learning engagement process, a learning engagement evaluation index system is proposed that integrates offline and online data. It realizes the quantitative study of learning engagement based on data.
SiamRPN++ has achieved excellent performance on thermal infrared object tracking. However, it directly fuses multi-layer features using weighted summation, which has the problem of insufficient feature fusion. In this paper, we propose an adaptive feature fusion module. It can fuse the features of different layers by adaptively allocating channel weights. Meanwhile, CIoU loss is used to make the regression of the bounding box more accurate. Experimental results show that the proposed method improves the baseline algorithm effectively and achieves excellent tracking accuracy and efficiency. The proposed method has strong robustness, effectively dealing with some challenges such as interference and occlusion. Therefore, the proposed method is valuable in practical application.
Respiratory diseases have a significant impact on the health and social economy of the population, and there are currently limited ways to detect respiratory diseases in hospitals. To this end, we proposed a cascade neural network model based on multi-features fusion to classify respiratory diseases. Meanwhile, we also used two different pre-processings to input respiratory sounds into three diffe...
Secondary vocational education is an important component in modern education. Recently, the research on teaching methods in secondary vocational education has attracted great attention and achieved remarkable results. However, there are still some problems such as the lack of initiative in students. In this paper, the visualization software of CiteSpace is used to analyze the teaching methods in secondary vocational school in China in recent ten years. The analysis results show that the task-driven method and micro-class teaching are two hot teaching methods in secondary vocational school. Therefore, these two methods are applied to the actual teaching of computer basic course in secondary vocational school. The practice results show that the hybrid learning method of task-driven method and micro-class teaching method significantly improves the teaching effect and raises students' learning enthusiasm.
During the epidemic period, in response to the national education policy of “continuous suspension of classes”, the teaching work of universities was carried out online with the help of various online teaching platforms such as Superplatform, rain classroom, smart tree, university MODC, school-based platform smart classroom, as well as well as software with the function of teaching live broadcast. In order to improve the teaching effect, build students ‘cognitive system, cultivate students’ ability of independent learning and collaborative learning, and help students to achieve the knowledge objectives, skills objectives and quality objectives required by the curriculum. The author from the current situation of the post-epidemic era, combined with hunan automobile engineering vocational college online mixed teaching reality, with research results at home and abroad as the theoretical support, develop granular micro class video, system design orderly teaching link, in the actual practice of offline teaching mode, and reversed transmission teachers, teaching materials, teaching method reform.
In recent years, with the development of artificial intelligence and information technology, we are gradually stepping into the era of big data, in which education-related data has developed sufficiently in terms of quantity and content. To be able to use machine learning techniques to assist educators to help improve the current quality of education and teaching, more and more researchers have started to data-mine educational data. In this paper, various algorithms of machine learning are applied to the field of education to process the data of students' teaching performance and then model it using various algorithms of machine learning to predict the students' performance and provide some suggestions to the teachers to improve the students' performance. The main contributions of this paper are as follows: Firstly, this paper carries out necessary preprocessing operations on the original data to remove some dirty data or missing data. Then, a variety of machine learning algorithms are used to model students' academic performance. By comparing the prediction accuracy, recall rate, and F1 score of the model, the Gradient Boosting Decision Tree Classifier is finally obtained as the optimal model. We then integrated the three best machine learning models as the base models and proposed a new Stacking learning method with better results. Finally, this paper analyzes the interpretability of the Gradient Boosting Decision Tree Classifier, evaluates the importance of different characteristics, and finally concludes that “Visited resources”, “Raised hand”, “Student Absence Days”, and “Viewing announcements” are the most important factors affecting students' performance. This model has an advanced effect and good interpretability.
With the rapid development of science and technology, the drawbacks of talent training based on traditional industries gradually emerge. Due to the slow development of the profession, it often leads to low professional identity, which brings new challenges to the cultivation of talents in universities. The new generation of information technology brings new vitality to the development of traditional industries, and the traditional production modes are transformed to intelligent production to improve the market competitiveness of products and industries. In this paper, the traditional leather industry is the object of study, and the current situation of leather talents training in colleges and universities in recent years is investigated. The impact of information technology on the leather industry and the development of the direction of leather professional higher education are analyzed. Finally, the reform strategy of leather professional talent training under the opportunity of new generation of information technology is proposed.
With the advent of big data, the construction of new engineering in higher education is urgently required, and the requirements of information management and information system specialty(IMIS for short) in big data analysis and application are also increased. The integration between industry and education is an effective way for IMIS to cultivate new engineering talents needed by the society. It firstly analyzed the current situation of integration between industry, education for IMIS. On this basis, the cultivation mode of big data talents for IMIS based on the deep integration between industry and education is discussed, which are include the construction of application-oriented and innovative talents cultivation system, the curriculum practice system of big data course, and the policy of government financial support.
From the perspective of data-driven technology, this paper analyzed the practical challenges faced by colleges and universities in the process of realizing the modernization of educational governance, and summarized the implementation path and technical framework from practice, So as to provide a useful reference for colleges and universities to realize the governance modernization. Through research and summary, the implementation path mainly consist of three important components: selecting a reasonable platform architecture, improving data governance services and continuously promoting data governance operations. Finally,take Shandong Youth College of Political Science as an example to carry out practical research and display the case results of data driven governance modernization. It's proved that the implementation path of data driven university governance modernization proposed in this paper is effective.
Taking the creative design professional group of the Art College of Dalian University of technology as an example, based on the background of the integration of industry and education, according to the group logic of the professional group docking with the industrial cluster, this paper discusses the construction path of the talent training mode of “two pairs, 335 stages studio system” of the professional group, expounds the effectiveness of the reform of the talent training mode, and Teaching reform provides theoretical reference and practical guidance for future development.
