School of the Art Institute of Chicago
  • Chicago, IL, United States
Recent publications
With the continuous advancement of higher education reform, talent classification evaluation has become a new trend in the management and development of teachers in colleges and universities. As an important foundation for the development of teachers in colleges and universities, talent evaluation not only plays the role of the baton but also promotes the process of educational reform in colleges and universities. As the difficulty and key point of the reform of the personnel system in colleges and universities, the implementation of the classification and evaluation of talents in colleges and universities is conducive to mobilizing their enthusiasm and creativity and is an inevitable trend in the reform and development of higher education. However, at present, teaching, scientific research, and social services are mainly used as the important basis for teacher evaluation in college talent evaluation. The evaluation mechanism is not perfect, the evaluation standard is single, the evaluation methods are convergent, and evaluation mechanism of the academic circles on evaluation, etc. The research on the problem is still very weak, and the development of college teachers is increasingly affected. It is urgent to build a set of accurate classification and evaluation systems for college talents. In view of the many problems existing in the above-mentioned talent classification and evaluation mechanism in colleges and universities, this paper adopts AHP and fuzzy evaluation method, adopts this method to evaluate talents in the stage of talent introduction in colleges and universities, classifies talents according to the evaluation results, and finally uses the classification results as it is tested in practice to verify the effectiveness of the method constructed in this paper.
Aiming at the high requirements of cloud service-based virtual reality in AIoT for data transmission rate and delay sensitivity, a cloud VR system scheme based on MEC (Mobile Edge Computing) is proposed, which mainly incorporates viewpoint-based VR video data processing and hybrid digital-to-analog (HDA) transmission optimization and can be served for AIoT transmission filed. Firstly, a learning-driven multiaccess MEC offloading strategy is designed, in which the VR terminal automatically selects the optimal MEC server for task offloading, thereby effectively improving network efficiency and reducing service delay. Secondly, the progressive transmission of the VR data is realized through viewpoint-aware dynamic streaming based on RoI (region of interest) and the priorities of different objects. The transmission priority of each object in the scene is determined through the ROI layering, which effectively solves the contradiction between the large data volume in the VR scenes and the network bandwidth limitation when applied in AIoT domain, and further improves the real-time performance of the system. Then, the HDA (hybrid digital-analog) technique is introduced to optimize the transmission. Finally, the base station protocol stack is modified on the basis of the LTE (Long-Term Evolution) system, and the MEC technology is integrated to realize a complete cloud VR system in AIoT. The experimental results show that compared with other advanced schemes, the proposed scheme can achieve more robust and efficient data transmission performance and provide better VR user experience.
There are some problems in the creation process of public health visual art works, such as low accuracy and poor content quality. In order to further improve the accuracy and quality of artistic creation, based on artificial intelligence technology, a neural network model and an error backpropagation algorithm are used to analyze artistic creation, so as to obtain the corresponding optimization model. This model can analyze the application of public health visual art creation concepts in the Venice Biennale, so as to obtain the corresponding model calculation results under different indicators. Finally, data comparison is used to verify the accuracy of the model. Relevant studies show that activation values have different trends in connection weights under the action of different factors. The fluctuation of the curve is obvious in the initial state, but when the factor is high, the corresponding connection weight tends to be stable gradually. The range of learning rate in the initial state is relatively small, and the connection weights show a V-shaped change at higher factors. It can be seen from the curve corresponding to the ω learning method that the increase in learning speed will lead to further compression of calculation time, and the curve shows a trend of fluctuation. The corresponding learning error decreases gradually with the increase in factors, which indicates that higher factors will promote the accuracy of connection weights. Artificial intelligence-based visual models of art can calculate public health. It can be seen from the calculation results that the curve corresponding to artistic connotation has the largest range of variation and the highest influence on the model. The theme, form, and style of art all show a linear trend of improvement with the increase in time, while the content of art shows a downward trend. This research can provide support for the application of artificial intelligence theory in the field of public health.
As the basic concept of higher education, the three comprehensive education is a reliable guarantee for strengthening and improving moral work in higher education, which is a complex of talents meeting the requirements of the times, and “universal education” is a comprehensive training for students to improve their cultural and spiritual moral level to meet the requirements of future social consumption. In order to study the comprehensive reform and development of moral education in universities, this paper reviews and standardizes the formation and development of comprehensive reform in universities, which is closely related to the development of comprehensive reform: strengthening the interconnection of systems in the process of training all employees, strengthening the effective interaction between cultures in the whole process, and ensuring the complete organic integration of cultures. The authors propose a solution for the comprehensive reform of “three-completion education” in universities. The authors offer some reasonable suggestions for the development of moral education in colleges and universities.
Main melody extraction and multi-pitch estimation are two important research topics in the MIR field. In this article, the SVM algorithm is used to analyze and discuss music melody extraction and multi-pitch estimation. In the part of multi-fundamental frequency extraction, this article first filters the song signal with equal loudness and weakens the energy of the high-frequency and low-frequency parts of the song signal. Thereafter, the multi-resolution short-time Fourier transform suitable for processing song signals is introduced. In addition, in order to avoid the sharp jump of the estimated melody pitch in the same note duration range, this article proposes a main melody extraction method combining the SVM algorithm with dynamic programming. In this article, more features are used to distinguish the pitch contour of vocal fundamental frequency from that of the nonvocal fundamental frequency, which does not only depend on energy or a certain feature. The experimental results show that the lowest octave error of this method is 1.46. Meanwhile, the recall rate of the algorithm can reach about 95%. This method not only improves the recall rate of the fundamental frequency of the human voice but also improves the recall rate and pitch accuracy rate of the whole main melody extraction system.
Nowadays, we have entered the golden age of economic development, and the Internet of Things (IoT) has also ushered in the opportunity of development, and the rapid development of IoT is also beneficial to drive the economy forward continuously. Therefore, the research on IoT is very meaningful and meets the contemporary development needs and greatly facilitates people’s daily life through the interconnection of all things. In today’s era of massive data, all kinds of data are complicated and messy, and if the large amount of data obtained is not properly classified and processed, the major problem will be that a pile of disordered and messy data is generated, and it is impossible to find the corresponding useful, engineering value, and regular data among them, and then, such data can only be discarded. Such a simple and brutal way of data processing is not only a waste of data resources but also may inadvertently throw away important, confidential, and private data information. If such data is carelessly discarded, the consequences will be incalculable, because such data information is likely to be used, processed, and disseminated by unscrupulous elements, which will eventually result in the following consequences: for individuals, it is equivalent to making their privacy public, which will seriously affect all aspects of life; for enterprises, if confidential data information is disseminated, then it will bring unpredictable losses to the enterprise. The adaptive data processing method for edge node sensing in ubiquitous NB-IoT can make the data generated from NB-IoT modules in ubiquitous IoT have practical engineering application value after processing, so the data source of this paper is the IoT data generated from NB-IoT communication modules in ubiquitous network (called NB-IoT dataset in this paper). The experimental results show that the accuracy of the adaptive data classification achieved by these two algorithms reaches about 75%, which provides some help to improve the efficiency of data utilization.
A Pareto-based genetic algorithm (PGA) product design decision model is proposed in this work to improve the efficiency of product design decisions and avoid the instability of individual decision differences. Based on the product modeling design decision constraint space, decision variables, and other factors, the model utilizes the PGA optimization algorithm to make an objective decision on a design scheme. Using the analytic hierarchy process, the design expectations, objectives, variables, and schemes are constructed into a hierarchical structure. The design decision problems are then mapped to a mathematical model, and a simulation of the design scheme decision process is performed. Finally, the feasibility of the proposed model is analyzed and verified by evaluating the design decisions of a brand electric scooter product to guide designers in making innovative design decisions.
At present, artificial intelligence algorithms based on deep learning have achieved good results in image classification, biometric recognition, medical diagnosis, and other fields. However, in practice, many times researchers are unable to obtain a large number of samples due to many limitations or high sampling costs. Therefore, image sorting zero-sampling order research algorithms have become the central engine of intelligent processing and a hot spot for current research. Because of the need for the development of deep learning prediction capability, coupled with the emergence of time and technical-level drawbacks, the advantages of zero-sample and small-sample are gradually emerging, so this paper chooses to fuse the learning methods of both for image recognition research. This paper mainly introduces the current situation of zero-sample and small-sample learning and summarizes the learning of zero-sample and small-sample. And the meaning of zero-sample learning and small-sample learning and the classification of the main learning methods are introduced and compared and outlined, respectively. Finally, the methods of zero-sample and small-sample learning are fused, the design is introduced and analyzed, and the future research directions are prospected according to the current research problems.
The key identification element of the smart factory is the interconnection between devices, which solves the production method and development dilemma of the factory under Industry 3.0 and previous models. The new article published by Xinhua News Agency on January 16, 2022, advocates the idea of industry+ Internet, and its main goal is to realize intelligent production. At present, smart factories have become the main development direction of industrial enterprises in the world. 5G technology has been rapidly deployed with the development of mobile communication, and its performance has also been greatly improved compared to previous communication technologies. After China put forward the smart manufacturing 2025 plan, although a large number of enterprises are still lingering in the process of research, learning, and exploration, the idea of Industry 4.0 has taken root in various intelligent manufacturing enterprises, and the development route of Chinese manufacturing enterprises in the future has been ahead of schedule. Direction. Based on the basic theory of Industry 4.0, 5G wireless communication, Internet of Things, and smart factories, this paper firstly distributed questionnaires to 20 enterprises with smart factories by means of network and interview and reanalyzed the collected questionnaires by regression analysis method and then used the questionnaire scale analysis method to analyze the reliability and validity of the questionnaire and combined with the results of the questionnaire analysis to analyze the problems existing in the current smart factory. Finally, based on the background of Industry 4.0 and 5G communication technology, combined with the Internet of Things technology, the development layout of the smart factory is designed; that is, based on the elliptic curve encryption algorithm, the signature mechanism of mutual trust of all electronic devices in the IoT smart factory is set to improve the smart factory.
Artificial intelligence (AI) and the Internet of Things (IoT) make it urgent to push the frontier of AI to the network edge and release the potential of edge big data. The model’s accuracy in data acquisition and music genre classification (MGC) is further improved based on theater music data acquisition. First, machine learning and AI algorithms are used to collect data on various devices and automatically identify music genres. The data collected by edge devices are safe and private, which shortens the time delay of data processing and response. In addition, the deep belief network (DBN)-based MGC algorithm has better overall recognition and classification effect on music genres. The MGC accuracy of the proposed improved DBN algorithm is nearly 80%, compared to 30%–40% of the traditional algorithms. The DBN algorithm is more accurate than the traditional classical algorithm in MGC. The research has an important reference value for developing Internet technology and establishing a music recognition model.
At present, with the rapid development of the Internet and its close connection with our life, more and more educators apply the Internet to teaching. However, there is little research on the application of the Internet in solfeggio teaching, and there are some problems in the teaching process, such as nonstandard use methods, inability to highlight teaching objectives, and mismatch with students’ professional level. On the premise of fully understanding the teaching objectives of solfeggio in China, this paper designs an experiential teaching system of solfeggio in normal universities based on machine learning algorithm, studies the application of digital technology in solfeggio, including Internet technology, multimedia digital technology, and the use of music software, and analyzes the auxiliary role of digital technology in solfeggio teaching by combining the specific teaching contents of online solfeggio teaching during the epidemic period. In this experiment, the average classification accuracy of WNB algorithm is 0.767, while that of BP algorithm is 0.683. Experimental results show that WNB algorithm outperforms BP algorithm in classification. At the same time, in terms of time efficiency, the average time consumption of WNB algorithm in this experiment is about 0.026 s, while that of BP algorithm is about 0.45 s. Compared with WNB algorithm, the time consumption of WNB algorithm is less. Through concrete practice, it is proved that the combination of solfeggio teaching and digital technology is of great significance to both teachers’ teaching and students’ learning.
Folk vocal music is an important part of music majors in colleges and universities (CaU), and the core of music education is AE. Therefore, in vocal music teaching, students should be guided to understand the beauty of music and to use vocal performance as an aesthetic experience so as to cultivate their aesthetic appreciation ability. As one of the national musical instruments, Chinese Zither has a unique musical charm. Its traditional aesthetic value is high, which can bring people beautiful music enjoyment. This paper takes Chinese Zither as an example to study the aesthetic teaching methods in college national instrumental music teaching. In the process of research, we use a combination of a variety of research methods to study two classes of music major in our school. This paper first uses the literature analysis method to elaborate the AE and then uses the questionnaire survey method to study the college students’ understanding and views on the national instrumental music. Then, through the case analysis method, it analyzes the achievements and interest changes of the students after the introduction of aesthetic teaching in Chinese Zither teaching. At the same time, through expert interviews, it summarizes the teaching of national instrumental music in the CaU aesthetic teaching strategy and the use of mathematical analysis on the relevant data processing. This study found that before the introduction of aesthetic teaching in Chinese Zither teaching, the good rate of class 2 students was only 33.33%, and after the introduction of aesthetic teaching in Chinese Zither teaching, the good rate of students in class 2 reached 86.67%. Therefore, the introduction of aesthetic teaching in Chinese Zither teaching can effectively improve students’ learning level. This also shows that in the teaching of ethnic music, the introduction of aesthetic teaching and the combination of aesthetic art and music art can effectively improve the learning level of students.
The blockchain is a distributed storage system of digital assets. This decentralized, non-copyable technology stems from universal standard password algorithm and the consensus mechanism of the game theory. The development of quantum computing poses threat to traditional algorithms of blockchain encryption, including symmetric encryption and hash encryption. Focusing on the traditional blockchain consensus mechanism, this paper designs a new blockchain consensus mechanism, based on the stochasticity, irreversibility, and uncertainty of quantum measurement. In the proposed consensus mechanism, complex calculations and intractability mathematical problems are abandoned. In this way, a huge amount of computing resources is saved, less energy is consumed, the time delay is shortened, and the throughput is increased. The proposed quantum consensus mechanism can withstand 51% attacks.
People are becoming more and more aware of the value of design throughout a product’s entire life cycle as a result of the fierce competition for industrial products that exists today. The life of a product involves its design, manufacture, sale, and use, and how well these links are managed determines the product’s positioning in terms of value in the eyes of consumers. The key to the functional integration of the design is monitoring the entire process and applying the user’s emotional needs. A useful tool for assessing users’ emotional needs is the perceptual image of a product. An artificial intelligence-driven method for product perceptual design is proposed, and its efficacy is demonstrated by the design of an optometer. This method addresses the issues of incomplete measurement and insufficient sample collection in the traditional users’ perceptual cognition measurement. The findings demonstrate that extracting users’ perceptual cognition through text mining can assist designers in better understanding users’ perceptual needs, resulting in designed products that are more likely to meet users’ expectations for satisfaction. A design approach that can increase users’ psychological acceptance of products and boost their competitiveness is the perceptual design method, which combines human and artificial intelligence.
In recent years, with the improvement of economic level, music art has become a major focus of extracurricular teaching. Students of all ages are included. However, the high cost of piano teaching and the unique one-to-one teaching method of teachers and students lead to the lack of piano education resources. Learning piano has become a luxury activity. Therefore, using computer multimedia software to teach piano has become a feasible way to alleviate the current contradiction. For piano teaching, the main difficulties are the differences between teachers and students (i.e., the data change at both ends due to the network), the instability of the network system, and the neural network algorithm can solve these difficulties. Based on this point, this work aims to introduce neural network algorithm into piano teaching intelligent system. This paper first introduces the theoretical basis of the neural network algorithm, then expounds the algorithm flow and general framework of the algorithm in speech recognition, and explains the split explanation in combination with five aspects: preprocessing, character extraction, acoustic model, linguistic model, and decoding. Then, it introduces the system design of intelligent piano teaching and describes the general system requirements and product architecture. Finally, the intelligent piano teaching system is tested and applied to prove the effectiveness of the system. I hope this intelligent piano teaching system can provide more convenience for piano teaching.
Jingdezhen ceramic heritage is the largest existing ceramic cultural heritage in China, with the richest connotation and the most complete system. It has the characteristics of strong systematization, complicated preservation, and diversified use. With the vigorous development of cultural industry, Jingdezhen’s ceramic heritage has a broad application prospect, but at the same time, it faces the problem of being destroyed or improperly developed. With the progress of science and technology and the development of machinery, the traditional hand-made porcelain technology of Jingdezhen ceramics is gradually being eliminated. The value and distinctive feature of Jingdezhen ceramic heritage is the importance and necessity of its protection, and the protection of Jingdezhen ceramic heritage has become an urgent problem to be solved. In order to solve this problem, this paper takes the protection of Jingdezhen ceramic heritage as the research object, analyzes the characteristics and protection status of Jingdezhen ceramic heritage, and applies blockchain technology to the protection of Jingdezhen ceramic heritage, which promotes the protection of ceramic heritage. The decentralized, traceable, and open characteristics of blockchain technology provide innovative technical support for the digital construction of ceramic heritage and strong technical support for the protection of ceramic heritage. The results show that by analyzing the current situation of Jingdezhen ceramic heritage protection and construction, the digital model of Jingdezhen ceramic heritage based on blockchain technology is established by combining blockchain technology with digital construction of ceramic heritage, and a digital identity is built for Jingdezhen ceramics. The collected Jingdezhen ceramic information is attached to the blockchain, which ensures its unique and effective identity information, realizes the integration of Jingdezhen ceramic information, and actively promotes the informatization and standardization of ceramic heritage protection. The research results provide new ideas for Jingdezhen ceramic heritage protection and theoretical support for heritage protection and inheritance.
People’s research on nanocrystals is getting more in-depth with the development of science and technology, and the patterned arrangement of nanocrystals can greatly improve the performance of our equipment in related fields, allowing people to control the patterning of nanocrystals. Research on thermal transfer is also increasing. Glass materials doped with patterned metal nanocrystals have great application potential, and the search for a simple and efficient patterned preparation method has attracted great attention of many researchers. Using the directional induced migration effect of the high temperature and high voltage DC electric field, combined with the subsequent heat treatment process, the distribution of silver nanocrystals corresponding to the surface silver film pattern can be formed in the silicate glass substrate, to realize the electric field-induced thermal transfer of the nanocrystal pattern print. This article aims to study the patterned thermal transfer of silver ions and nanocrystals on the glass substrate by applying an electric field to induce and analyze the ink absorption layer structure and printing performance. On this basis, an electron beam-induced thermal transfer method and Maxwell’s equation are proposed to investigate and calculate the structure of the ink absorption layer. The experimental structure shows that using this method increases the success rate of the preparation of silver ions and nanocrystal patterns on the glass substrate by 30%, which improves the ink absorption layer and printing performance to different degrees.
With the emergence of new tourism trends such as popularized and individualized tourism, the traditional development model can no longer meet the development requirements of the new era. Therefore, the construction of tourism informatization is imperative. This work aims to enhance the promotion of tourism resources in Zhejiang Province and explore the effective promotion forms and strategies of tourism resources in Zhejiang network media. The construction of smart tourism city (STC) is taken as the research object. First, the evaluation index system and evaluation model of the construction level of STC are constructed. Besides, an empirical evaluation is conducted with the pilot project of smart tourism city construction determined by the National Tourism Administration as a case. Then, the concept of strength, weakness, opportunity, and threat (SWOT) is used to analyze the advantages, disadvantages, opportunities, and threats of Zhoushan Town’s tourism development. Finally, the model proposed here is tested. The results show that the comprehensive level of STC in 18 cities is quite different. The current average level of STC in China is 0.2791. Except for the support level of smart tourism environment that is lower than Suzhou, the rest levels of Beijing are in the first place, and the comprehensive level of STC construction is in the first place. The comprehensive level of STC construction in Suzhou ranks second, with an average level of 0.1521. Nevertheless, there is a big gap between Suzhou with Beijing. The overall evaluation satisfaction of Zhoushan Town’s tourism is in a moderate state. The analysis results of the SWOT intelligent model demonstrate that Zhoushan Town tourism should choose a growth marketing strategy. The research reported here provides a particular reference for realizing the seamless connection between the intelligent cultural tourism industry and consumers.
The development and construction of cities and villages are a complex process jointly promoted by multiple subjects such as government, residents, enterprises, planners, and community elites. Through the summary and analysis of the practice of art rural construction at home and abroad, it is found that its events show three main paradigms in the development process. The environmental creation paradigm reconstructs the environmental semantics of the countryside through the creation of environmental art works, showing the remarkable characteristics of “the presence of works.” The cultural revival paradigm maintains the local culture through cooperation with residents in art and has the characteristics of “de-artization ” and “de-heritage.” The industrial development paradigm adjusts the industrial structure through the production of commodity art to achieve the improvement of the rural economic foundation. Under the new development trend, the three paradigms are gradually converging.
In order to solve the problem that the automobile sales management becomes more and more complicated, this paper proposes a sales system software platform based on a computer network. The automobile sales management system based on the MVVM framework, with Java as the development language and MySQL as the database, is implemented by the progressive framework Vue in the front end and developed by the Spring Boot framework in the back end. Starting with the design and implementation of the system, the technical framework, functional modules, and implementation processes used to develop the system are studied. The experimental results show that the function tests are normal, the response time of the system client is generally 1-2 seconds, the processing speed is fast, and the influence ability is good. The system improves the comprehensive management ability and promotes the rapid development of automobile industry.
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1,165 members
Elizabeth D. Freeland
  • Department of Liberal Arts
Jisoo Woo
  • Department of Architecture, Interior Architecture and Designed Objects
Savneet Talwar
  • Department of Art Therapy
Eva Marxen
  • Department of Art Therapy
Andrew S Yang
  • Department of Liberal Arts
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