Reviewerly/exHarmony huggingface dataset:
Design and Implementation of Learning Management System Based on User Behavior Dynamic Recommendation Algorithm

This paper studies the design and implementation of the learning management system of user behavior dynamic recommendation algorithm. With the rapid development of the Internet and the increasing number of information, the learning and thinking methods of college teachers and students have changed greatly, and the traditional education model has been unable to meet the requirements of teachers and students. In class, the teacher explains the knowledge step by step, and the teacher can’t get the feedback from the students in time, which may cause the students to not understand the knowledge and feel great pressure. The existing resources can not be effectively shared, nor can they provide interactive learning. At the same time, it is impossible to provide personalized recommendations based on users’ behavior. When more and more students join the classroom, their learning space is not only limited, but also can not meet the basic needs of personalized learning. Learning management system is the product of the perfect combination of traditional education and the Internet. Through the existing classroom teaching means, teaching activities can transfer knowledge to students more conveniently and effectively. The system provides personalized services such as search, recommendation and resource reuse, which not only simplifies the workload of college teachers, but also provides the function of statistical analysis. Combined with the actual situation, the system uses a unique recommendation model to analyze the user’s behavior, and then provides users with personalized recommendation content.
Design and Implementation of Teaching Assessment System in Higher Vocational Colleges Based on Association Rule Algorithm

The systematic assessment of teachers’ classroom work is to adjust teachers’ behavior, improve classroom quality, and then manage them well. This paper expounds the problems existing in the assessment of Higher Vocational Colleges in China; Taking the teaching management of higher vocational colleges as the background and teaching assessment as the research object, this paper discusses the design and implementation method of teaching assessment system under the environment of data warehouse. This paper attempts to build a decision support system for teaching management in Universities under the environment of data warehouse, which can first promote the improvement of teachers’ personal teaching level, and then improve the overall teaching quality of the school. This paper discusses the design and implementation of teaching assessment system in Higher Vocational Colleges Based on association rule algorithm. In connection with the present condition and development requirements of assessment, and further combine their own situation, design a practical teaching assessment system with the participation of students, teachers, supervisors, educational administration managers, branch (workstation) teaching managers and experts, which can comprehensively and objectively evaluate the teaching situation of teachers, So as to promote the improvement of teaching quality.
Course Recommendation Method and System of Education Platform Based on Deep Learning

Course recommendation is a service mode that recommends personalized learning resources to users according to their historical behavior information. Traditional recommendation methods can not effectively use auxiliary information and its potential relationship, resulting in problems such as cold start and sparse data. With the growth of data and the progress of computing power, the combination of deep learning and course Recommendation provides a new idea to solve the above problems. The research on in-depth learning methods for education platform curriculum recommendation has become a research hotspot in the field of education. In view of the challenges faced by the current curriculum recommendation, this paper studies the curriculum recommendation method and system of the education platform based on deep learning.
Detection of Anomalies in Traffic Flows with Large Amounts of Missing Data

Anomaly detection plays an important role in traffic operations and control. Missingness in spatial-temporal datasets prohibits anomaly detection algorithms from learning characteristic rules and patterns due to the lack of large amounts of data. This paper proposes an anomaly detection scheme for the 2021 Algorithms for Threat Detection (ATD) challenge based on Gaussian process models that generate features used in a logistic regression model which leads to high prediction accuracy for sparse traffic flow data with a large proportion of missingness. The dataset is provided by the National Science Foundation (NSF) in conjunction with the National Geospatial-Intelligence Agency (NGA), and it consists of thousands of labeled traffic flow records for 400 sensors from 2011 to 2020. Each sensor is purposely downsampled by NSF and NGA in order to simulate missing completely at random, and the missing rates are 99%, 98%, 95%, and 90%. Hence, it is challenging to detect anomalies from the sparse traffic flow data. The proposed scheme makes use of traffic patterns at different times of day and on different days of week to recover the complete data. The proposed anomaly detection scheme is computationally efficient by allowing parallel computation on different sensors. The proposed method is one of the two top performing algorithms in the 2021 ATD challenge.
An Intelligent Piano Teaching System and Method Based on a Cloud Platform

With the progressive development of the ‘Internet+’ trend and the elevation of artificial intelligence to a national strategy, the use of new Internet cloud technologies and hardware and software technologies such as computers to serve music dissemination and music education has become an inevitable trend. In this wave, a large number of software and hardware systems and new teaching platforms have emerged over the years for piano education, which is an important area of popular music education. In the whole platform of intelligent piano teaching, the main aspects include hardware construction methods, software design methods, music presentation forms, teaching methods, etc. Based on the currently available technologies and theories, different methods have different characteristics in the whole teaching. This paper is based on a study of intelligent piano teaching systems on a cloud platform, and in this regard hopes to make such approaches better for new models of music education and to provide references for the transformation of other music disciplines on the Internet.
Design and Implementation of English Grammar Error Correction System Based on Deep Learning

The purpose of this project is to develop an English grammar error correction system based on deep learning. The system will be able to recognize grammatical errors and automatically correct them using machine learning technology. The main goal of the project is to build an efficient and accurate grammar error detection tool, which can detect and correct the errors made by users when inputting in English, Chinese and other languages. Grammar error detection system using deep learning technology: grammar correction is a technology that can identify and correct written English grammar errors. The system uses deep learning techniques to identify grammatical errors and correct them. It is used in conjunction with an algorithm for identifying errors and then generates a corrected sentence from which you can learn how to write correctly. The system also learns your writing style by observing how your writing changes over time, so it will be able to detect more errors. When using this tool, you don’t have to remember any rules or patterns, because it will automatically detect problems and suggest corrections based on your knowledge of English grammar rules.
Exploring the Practical Teaching of a Specialized Interim Course in Electronic Information Engineering Under the Background of Artificial Intelligence

Electronic information technology in China is rapidly developing. With the submission of the idea of artificial intelligence, higher education corresponded to the growth rate of the industrial revolution and the new economic environment. Artificial intelligence meets the progress logic of the Department and provides breakthroughs for education facing under the new environment. In this paper, we analyze the needs of human resources in the insertion system, knowledge system, internal core and processor linear. On the other hand, the author explained the selection of the contents content integration experiment platform and the practical program design of the “insertion system” practice education of the electronic information engineering.
The Influence of Computer Aided System Teaching on Vocabulary Learning

Computer assisted instruction (CAI) has been widely used in the practice of vocabulary learning in classroom teaching. The methods of vocabulary learning in teaching and the modes of vocabulary learning in teaching have diversified Aiming at the main links of vocabulary learning in college classroom teaching, this paper puts forward the design idea of a practical computer-aided system TCAS for vocabulary learning in college teaching, and uses vfp9 0 to reduce teachers’ repeated work and improve the quality of vocabulary learning in teaching. The database design adopts the classic case tool set Sybase PowerDesigner, and gives the main data table structure The experimental results show that when TCAS is used in the actual teaching of operating system and other courses, only a small amount of key information needs to be input or imported into each teaching link of vocabulary learning; At the same time, TCAS has a convenient user interface. In terms of the relationship between vocabulary richness and writing quality, vocabulary variability, vocabulary complexity and vocabulary density are significantly positively correlated with writing quality, and vocabulary errors are significantly negatively correlated with writing quality. TCAS can better meet the needs of College Teaching for vocabulary learning.
The Reform of Accounting Education in Colleges and Universities Based on Cloud Computing in the Era of Big Data

With the rapid development of China’s economy, accounting education in Colleges and universities has also achieved long-term development, with the continuous expansion of education scale, the continuous improvement of teaching system and the increasing improvement of teaching quality. Accounting education has played an important role in promoting national economic construction. However, with the development of economic globalization, accounting education presents many problems that are inappropriate to social development. Accounting education must be reformed. Starting from changing the concept of accounting education in Colleges and universities, this paper makes a preliminary discussion on how to give full play to the advantages of cloud computing, build a cloud accounting education platform and change the accounting education mode in Colleges and Universities under the background of the big data era.
Addressing Complexity in the Pandemic Context: How Systems Thinking Can Facilitate Understanding of Design Aspects for Preventive Technologies

The COVID-19 pandemic constitutes a wicked problem that is defined by rapidly evolving and dynamic conditions, where the physical world changes (e.g., pathogens mutate) and, in parallel, our understanding and knowledge rapidly progress. Various preventive measures have been developed or proposed to manage the situation, including digital preventive technologies to support contact tracing or physical distancing. The complexity of the pandemic and the rapidly evolving nature of the situation pose challenges for the design of effective preventive technologies. The aim of this conceptual paper is to apply a systems thinking model, DSRP (distinctions, systems, relations, perspectives) to explain the underlying assumptions, patterns, and connections of the pandemic domain, as well as to identify potential leverage points for design of preventive technologies. Two different design approaches, contact tracing and nudging for distance, are compared, focusing on how their design and preventive logic are related to system complexity. The analysis explains why a contact tracing technology involves more complexity, which can challenge both implementation and user understanding. A system utilizing nudges can operate using a more distinct system boundary, which can benefit understanding and implementation. However, frequent nudges might pose challenges for user experience. This further implies that these technologies have different contextual requirements and are useful at different levels in society. The main contribution of this work is to show how systems thinking can organize our understanding and guide the design of preventive technologies in the context of epidemics and pandemics.
Classification of Colon and Lung Cancer Through Analysis of Histopathology Images Using Deep Learning Models

In the last four decades, medicine and healthcare have made revolutionary advances. During this time, the true causes of many diseases were discovered and new diagnostic procedures were devised and new remedies were invented. Globally, cancer is one of the serious diseases, which has become a widespread medical issue. A credible and early finding is especially important to reduce the risk of death. In any way, it is a difficult task that relies on the expertise of histopathologists. If a histologist is unprepared, a patient’s life may be put in danger. Deep learning has gotten a lot of attention recently and is being used in medical imaging analysis. Artificial Intelligence (AI) can be used to automate cancer detection. To better classify and for quality improvement of histopathology images, visualization techniques GradCam and SmoothGard are applied. This objective can be achieved by evaluating histopathological images of five types of colon and lung tissues using MobileNetV2 and InceptionResnetV2 models. These proposed models have accurately identified cancer tissues to a maximum of 99.95%. These models will assist medical professionals in the advancement of an automated and authentic system for detecting different types of colon and lung cancers.
Research on English Teaching in Higher Vocational Colleges Based on Big Data Analysis

Big data analysis is an important part of English Teaching in higher vocational colleges. Because of its huge database, complex theoretical knowledge and wide simulation range, it is difficult to carry out and implement English Teaching in Higher Vocational Colleges Based on big data analysis. The teaching research and scientific research of Higher Vocational and technical education have always been weak, and the English teaching methods are still relatively lagging behind. English multimedia teaching is basically the broadcasting of voice lessons and PPT electronic manuscripts, ignoring the valuable resource of network data analysis. Carry out the teaching and learning interaction of the course on this network data platform, gradually optimize the interactive environment through multiple rounds of action reflection in the teaching process, learn the methods of theoretical analysis, and master the ability to use professional knowledge, so as to cultivate students’ scientific research ability and comprehensive quality.
Multi-objective Hardware-aware Neural Architecture Search with Pareto Rank-preserving Surrogate Models

Deep learning (DL) models such as convolutional neural networks (ConvNets) are being deployed to solve various computer vision and natural language processing tasks at the edge. It is a challenge to find the right DL architecture that simultaneously meets the accuracy, power, and performance budgets of such resource-constrained devices. Hardware-aware Neural Architecture Search (HW-NAS) has recently gained steam by automating the design of efficient DL models for a variety of target hardware platforms. However, such algorithms require excessive computational resources. Thousands of GPU days are required to evaluate and explore an architecture search space such as FBNet [ 45 ]. State-of-the-art approaches propose using surrogate models to predict architecture accuracy and hardware performance to speed up HW-NAS. Existing approaches use independent surrogate models to estimate each objective, resulting in non-optimal Pareto fronts. In this article, HW-PR-NAS, 1 a novel Pareto rank-preserving surrogate model for edge computing platforms, is presented. Our model integrates a new loss function that ranks the architectures according to their Pareto rank, regardless of the actual values of the various objectives. We employ a simple yet effective surrogate model architecture that can be generalized to any standard DL model. We then present an optimized evolutionary algorithm that uses and validates our surrogate model. Our approach has been evaluated on seven edge hardware platforms from various classes, including ASIC, FPGA, GPU, and multi-core CPU. The evaluation results show that HW-PR-NAS achieves up to 2.5× speedup compared to state-of-the-art methods while achieving 98% near the actual Pareto front.
Research on Enterprise Financial risk Prediction Method Based on Regression Analysis

The prediction and control of enterprise financial risk is an important research topic in the financial field. Over the years, the financial risks of enterprises have seriously affected the healthy development of enterprises, credit institutions, securities investors and even the whole country. However, from the current practice and theoretical research of enterprises, how to effectively evaluate and control the financial risk of Chinese enterprises is still very scarce. Therefore, this paper conducts detailed analysis on the prediction and control of financial risk based on regression analysis to better identify the financial risks of enterprises.
Skill retention after desktop and head-mounted-display virtual reality training

Abstract Virtual reality (VR) is increasingly used in learning and can be experienced with a head-mounted display as a 3D immersive version (immersive virtual reality [IVR]) or with a PC (or another computer) as a 2D desktop-based version (desktop virtual reality [DVR]). A research gap is the effect of IVR and DVR on learners’ skill retention. To address this gap, we designed an experiment in which learners were trained and tested for the assembly of a procedural industrial task. We found nonsignificant differences in the number of errors, the time to completion, satisfaction, self-efficacy, and motivation. The results support the view that DVR and IVR are similarly useful for learning retention. These insights may help researchers and practitioners to decide which form of VR they should use.
Secure Data Processing Technology of Distribution Network OPGW Line with Edge Computing

Promoted by information technology and scalable information systems, the network design and communication method of optical fiber composite overhead ground wire (OPGW) have been in great progress recently. As the overhead transmission line has strict requirements on the outer diameter and weight of OPGW, it is of vital importance to perform the physical-layer secure data processing for the distribution network OPGW line with edge computing. To this end, we examine a physical-layer secure distribution network OPGW with edge computing in this article, where there exists one transmitter S, one receiver D, one authorized legitimate monitor LM, and an interfering node I. To better analyze the system performance, we firstly give the definition of the system outage probability, based on the secure data rate. Then, we evaluate the system performance for the distribution network OPGW, by deriving analytical outage probability of secure data processing, to facilitate the system performance evaluation of secure data processing in the entire SNR regime. Finally, we demonstrate some simulation results to validate the analytical results on the physical-layer secure distribution network OPGW line with edge computing.
Construction of Maker Education Resource Sharing Platform Based on Web Technology

At present, what maker education lacks is not a certain software or hardware, but a system. This platform should connect students, teachers and education authorities in series. This series is not a series of products, but a series of data. Now the exam oriented education industry is very concerned about the construction of three links and two platforms, and the same is true of maker education. Considering the practicability and economy, building a network teaching platform based on Web technology is an important task and development direction of the current construction of educational resource sharing platform. The summary of the construction of maker education platform may have some enlightenment.
Photon-pair generation in a lossy waveguide

Abstract An on-chip quantum light source based on spontaneous four-wave mixing is an essential element for developing quantum photonic integrated circuit technology, which has the advantage of no connection loss owing to the integration of the source into photonic circuits. The waveguide-based quantum light source inevitably causes propagation loss owing to imperfections in the fabrication process, but the propagation loss effects on photon-pair generation have not been extensively studied. In this study, propagation loss effects were examined using theoretical and experimental methods. In theory, the performance of quantum light sources, such as brightness, heralding efficiency, and coincidence-to-accidental ratio, strongly depend on propagation loss. We fabricate several waveguides with a moderate propagation loss of 2.2 dB/cm to investigate the loss dependence and ascertain that the brightness, heralding efficiency, and coincidence-to-accident ratio strongly correlate with the length of the optical waveguide. The maximum coincidence-count brightness occurred at an optimization length of 1/ α , where α is the absorption coefficient. In contrast, the single-count brightness shows slightly different waveguide length dependence owing to loss-induced one-photon states. We expect that the results obtained in this study will greatly assist in determining the proper waveguide length for photon-pair generation according to the source’s application fields. The results will be helpful in the development of a quantum light source suitable for practical and quantum optical integrated circuits and will lead to the development of high-fidelity quantum technologies.
Research on the Influencing Factors of the Endangered Inheritance of Folk Intangible Cultural Heritage and the Educational Protection Based on Big Data Technology

The traditional mode of intangible cultural heritage communication is mainly offline activities, such as market fairs, temple fairs, sacrificial activities or physical or text and picture display of scenic area museums. With the popularity of the Internet and mobile terminal devices, the traditional offline display methods obviously can not meet the needs of the audience. Communication through digital technology can truly realize the "living communication" of intangible cultural heritage. In the era of rapid development of mobile Internet, video and video have become popular communication methods for the audience. Intangible cultural heritage uses digital means to achieve more detailed and diversified communication, and substitutes the audience into its scene to have all-round contact with intangible cultural heritage. With the rapid development of economic construction, the construction of social spiritual civilization has also accelerated its own pace. We need to use big data technology to give modern attributes to the traditional intangible cultural heritage and make these unfamiliar information full of vitality. Therefore, this paper studies the influencing factors and protection of folk intangible cultural heritage endangered inheritance based on big data technology.