Analysis of Intelligent Campus Construction in 2.0 Era of Educational Informatization

The construction of university informatization in China has already entered the 2.0 era. It requires universities to explore a new way of thinking when strengthening campus construction. At present, colleges and universities have found a new construction direction of “smart campus construction”. On the basis of drawing lessons from the construction experience of “smart campus” pilot schools, they are gradually improving the construction method of smart campus. The achievements of some colleges and universities are not ideal. This affects the actual quality of smart campus construction. Therefore, colleges and universities should take educational informationization 2.0 as the basic guidance when embarking on the innovative development path of intelligent education. The bright future of the smart campus construction will be revealed by exploring the smart campus construction methods that meet the requirements of The Times. This provides sufficient practical reference for the innovation and development of intelligent education in colleges and universities

Analysis of University Network Security Management and Countermeasures

With the development and progress of science and technology, the Internet is widely used in every aspect of people’s life. Chinese universities have gradually begun to apply the Internet. This facilitates the work and life of teachers and students. But the dual nature of campus network brings a series of threats to teachers and students. This paper states the problems and threats of network security management in colleges and universities. By putting forward the corresponding solutions and discussion, it provides theoretical support for jointly promoting the progress and development of network security construction in colleges and universities

Research on Application of Cloud Computing Based University Education Informationization

With the development of information age and technological means, people’s production and life, way of thinking and working concept are gradually changing. Cloud computing has become one of the hottest topics in the world. Cloud computing based on efficient computing power, scalable storage capacity and high security has become a new favorite in all walks of life. Chinese university information construction should also seize the opportunity to fully combine the advantages of cloud computing technology to strengthen the university campus network construction, enhance the integration of educational resources and promote information sharing. By combining cloud computing technology to expand network cloud service platform, Chinese universities education has greater space for development. Thus, it is an inevitable trend to apply cloud computing technology to Chinese university informationization construction. Based on the above purpose, this paper will start from the technical summary behind cloud computing technology, in-depth analysis and computing technology definition and characteristics. By exploring the application and existing problems of cloud computing technology in university information construction, this paper provides new ideas for university information construction development. This improves the overall development level of education industry, colleges and universities’ social influence and credibility

Research on the Application of Big Data in the Informatization of University Education

With the continuous development of information technology revolution, cloud computing, Internet of things, Internet and other information technologies appear. They have infiltrated every corner of society. As a result, the numbers are exploding. It is difficult to estimate the value and information of these data. Education has become an important front in social life in the era of big data. This paper mainly analyzes the data characteristics and data sources. In the era of big data, the application of big data in the informatization of college education is discussed

CCD photometric study of the W UMa-type binary II CMa in the field of Berkeley 33

The CCD photometric data of the EW-type binary, II CMa, which is a contact star in the field of the middle-aged open cluster Berkeley 33, are presented. The complete R light curve was obtained. In the present paper, using the five CCD epochs of light minimum (three of them are calculated from Mazur et al. (1993)'s data and two from our new data), the orbital period P was revised to 0.22919704 days. The complete R light curve was analyzed by using the 2003 version of W-D (Wilson-Devinney) program. It is found that this is a contact system with a mass ratio $q=0.9$ and a contact factor $f=4.1$. The high mass ratio ($q=0.9$) and the low contact factor ($f=4.1$) indicate that the system just evolved into the marginal contact stage

Optical Heritage Museum: An Interactive Touch

Optical Heritage Museum (OHM) was established in 1983 with the aim to preserve, promote and display historical artifacts of the optics industry and educate all of its vital role optics has played in societal development. Over the years, the museum has grown in its physical space along with exhibit development to engage audiences in innovative, effective methods. Clark University’s School of Professional Studies department and curator of Optical Heritage Museum, Mr. Whitney’s Whitney, have establish a collaboration that has spanned over two semesters with the goal to support and aid in improving OHM. Our capstone group was assigned the task of improving marketing strategies for OHM, which altered its focus on developing strategies and knowledge on improving the museum’s interactivity amongst its exhibits

Some variational recipes for quantum field theories

Rapid developments of quantum information technology show promising opportunities for simulating quantum field theory in near-term quantum devices. In this work, we formulate the theory of (time-dependent) variational quantum simulation of the 1+1 dimensional $\lambda \phi^4$ quantum field theory including encoding, state preparation, and time evolution, with several numerical simulation results. These algorithms could be understood as near-term variational analogs of the Jordan-Lee-Preskill algorithm, the basic algorithm for simulating quantum field theory using universal quantum devices. Besides, we highlight the advantages of encoding with harmonic oscillator basis based on the LSZ reduction formula and several computational efficiency such as when implementing a bosonic version of the unitary coupled cluster ansatz to prepare initial states. We also discuss how to circumvent the "spectral crowding" problem in the quantum field theory simulation and appraise our algorithm by both state and subspace fidelities.Comment: 28 pages, many figures. v2: modified style, add references, clear typos. v3: significant change, authors adde

Application and Evaluation of Meta-Model Assisted Optimisation Strategies for Gripper-Assisted Fabric Draping in Composite Manufacturing

With respect to their extraordinary weight-specific mechanical properties, continuous Fibre Reinforced Plastics (CoFRP) have drawn increasing attention for use in load bearing structures. Contrasting metals, manufacturing of CoFRPs components requires multiple steps, often including a draping process of textiles. To predict and optimise the manufacturing process, Finite-Element (FE) simulation methods are being developed along virtual process chains. For maximum part quality, draping process parameters need to be optimised, which requires numerous computationally expensive iterations. While efforts have been made for time-efficient process optimisation in metal forming, composite draping optimisation has is a comparably young discipline and still lacks time-efficient optimisation strategies. In this work, modelling strategies for time-efficient optimisation using computationally inexpensive meta-models are examined, which are used to guide the search for optima in the parameter space. The meta-models are trained by observations of FE-based draping simulations of an automotive part, thereby learning the relationship between variable gripper forces (input) and the resulting shear angles (output). Parametric model functions are compared against deep neural networks (DNN) as non-parametric models with respect to prediction accuracy. Best results are achieved using a DNN that predicts the shear angles of more than 24 000 fabric shell elements