Reviewerly/exHarmony huggingface dataset:
Investigation and Research on the Status Quo of Social Piano Education Based on BP Neural Network

In the context of general education, people generally begin to improve students' comprehensive quality. Among them, social piano education, as a kind of music education, plays an important role in shaping and promoting students' cultural literacy, music perception and creativity. Therefore, allowing students to receive social piano education can make students improve their comprehensive quality faster. Taking general education as the background, this paper establishes a survey model for the current situation of social piano education based on BP neural network, then collects data through questionnaire survey, and tests the results of the questionnaire survey by reliability test and regression analysis, so as to ensure the accuracy of the survey results of the current situation of social piano education.
Research on the Construction of Capability Evaluation Index System Based on IEO Model

The development of general education is not only conducive to the realization of higher education objectives, but also conducive to improving the training quality of professional talents in Colleges and universities. Therefore, it is of great practical significance to apply general education to nursing specialty in Colleges and universities. In order to effectively evaluate the level of general education of nursing specialty in Colleges and universities, it is necessary to construct the ability evaluation index system based on IEO model. Through the construction of the ability evaluation index system, the education quality and education effect of general education of nursing specialty in Colleges and universities can be presented in the form of data, which is convenient for the continuous improvement of general education of nursing specialty in Colleges and universities.
On the construction of employee performance management system of smart tourism hotel under P-O model

research-article On the construction of employee performance management system of smart tourism hotel under P-O model Share on Author: Liu Jingjiang Nanchang Institute Technology, China Nanchang Institute Technology, ChinaSearch about this author Authors Info & Claims AICSconf '21: 2021 2nd Artificial Intelligence and Complex Systems ConferenceOctober 2021 Pages 123–127https://doi.org/10.1145/3516529.3516553Online:05 April 2022Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Research on Key Technologies of Medical Data Processing and Protection Based on Cloud Computing and Blockchain Technology

With the popularization and development of universal medical care, the medical system has produced a large amount of data and information, and the processing and storage of these massive amounts of data has become the focus of research by many experts in the era of big data. This article is based on cloud computing and blockchain technology to process and protect data and information, and provide users with efficient, safe, and reliable cloud computing services.
The Research on information recommendation model based on an improved deep learning Model

In recent years, information recommendation system has been widely used in various fields. Deep learning is increasingly combined with information recommendation system to capture user preference or item interaction evolution over time. In this paper, we improve the deep learning model applied to information recommendation system, and use LDA (Linear Discriminant Analysis) classifier instead of the Softmax. Experimental results show that our method has better accuracy, recall rate and F1-Score. It has certain significance for the development of recommendation information service for follow-up research.
Research on the Quality Evaluation of General Education Piano Course Based on Analytic Hierarchy Process

The emergence of MOOCs in the Internet age has attracted a large number of students, and as people's awareness of MOOCs deepens, the quality of MOOCs has become higher and higher. In order to improve the comprehensive artistic literacy of college students, many domestic colleges and universities have begun to try to build general education piano MOOCs, so that more students can understand the knowledge of piano music theory and master piano performance skills. Therefore, based on the development of general education construction as the research background, this article explores the construction quality of general education piano MOOC, constructs a hierarchy analysis evaluation model, determines the quality evaluation index weights and conducts consistency tests, determines the quality evaluation level, and finally obtains The quality evaluation result of the general education piano MOOC is to clarify the future development trend of the general education piano MOOC.
Opera by Lev Kolodub "The Poet" as a Vector of the Director's Actualization of the Kobzar’s Image in Modern Ukrainian Realities

Creative and ideological prerequisites of the director's appeals to L. Kolodub's opera "The Poet" are considered. The reasons for the need for a new scientific and creative understanding of opera in the sociocultural realities of a modern Ukraine are clarified. The scientific novelty of the research is determined, which consists of the original conceptual vision of updating the performance in accordance with the requirements of the present on the basis of synthesis of achievements of scientific thought and creative heritage of iconic figures of Ukraine and abroad. The purpose of the research is the need for new readings of the opera "The Poet" by Lev Kolodub as an ideological and integral work, devoid of the narrative of the Soviet era and the pathos of canonization of Kobzar as a "Superman", which is not characterized by human and romantic experiences, the research methods chosen: to determine the influence of world socio-cultural processes on the musical theater of Ukraine – system-analytical; to consider the creative heritage of L. Kolodub - biographical; to analyze the musical drama of the work — genre stylistic; to analyze the director's embodiments of the Opera — interpretative; to create your own concept of a creative art project — experimental modeling. The main results and conclusions of the study are obtained, which are as follows: a long break between the time of writing the opera "The Poet" by L. Kolodub (1984-1988) and its first stage reading (2001) is associated with subjective reasons due to the inconsistency of actions between musical theaters of Ukraine. The opera "The Poet" from the point of view of the composer's idea is definitely a new look at the image of Taras Shevchenko. In fact, Levko Kolodub invented a new genre of musical theater with this work — "biographical opera". Its versatility can be regarded as an attempt by the composer himself to "revive the classics" and bring them closer to the audience's perception. In this vein, this work provides a wide range of opportunities for director's reading and can live an active repertoire, ideologically true life at opera venues in Ukraine and diasporas. A comparative analysis of the Opera implementations in the Lysenko Kharkiv National Academic Opera and Ballet Theatre and the National Philharmonic of Ukraine allowed us to determine the difference between the director's approaches to solving mise en scene due to traditional (theater stage in Kharkiv) and non — traditional (concert hall in Kyiv, in the past-a room for balls of the merchant's House) locations. The post-graduate student predicted her own conceptual vision of the creative art project - the opera "The Poet" by L. Kolodub, which provides for the use of the latest achievements of scientific thought and original creative findings of leading figures of musical theater in Ukraine and abroad.
The Concept of Training a Doctor of Art from Music Directing

The relevance of the research is due to need to train highly qualified professionals in today's sociocultural challenges, able to generate creative ideas in the implementation of creative projects, able to respond quickly to changes in the market of theater services, to be competitive in the fleeting space. Scientific novelty - outlining the concept of formation of professional competencies of the artist in the synthesis of domestic traditions and foreign innovations, taking into account the specifics of the mental perception of works by the Ukrainian audience. Main objectives of the research is the process of preparing a doctor of art in music directing in the context of Ukraine's integration into the European educational and artistic space and to determine the specifics of the integrative educational and creative training of the doctor of art in musical directing in the context of world tendencies of musical theater development. The methodology of the research is the application of a comprehensive intersectoral approach based on the synthesis of systems analysis (the concept of modern directing in a new paradigm of musical theater) and the structural-functional method (algorithm of integrative training of doctors of art in creative graduate school). Findings and conclusion of the research is the influence of globalization and integration processes has affected the paradigm shift of musical and theatrical art in a positive sense - the information exchange of experience; professional growth of artists; application of art technologies; joint solution of urgent problems; in the negative - the dominance of foreign repertoire over domestic with the priority of foreign language content; commercialization of the theater; changes in value orientations; hedonistic orientation of interpretations of works. Factors influencing modern musical directing are the need to find means of expression for adequate perception of the Ukrainian audience of a foreign text; combining the aesthetic and value aspect with the financial and economic content of the play; inadmissibility of vulgarized interpretations of works; mastering the techniques of artistic reconstruction, authentic, modern, art-technological solution of performances; mastering the specifics of dancers, international and festival projects. The concept of training a doctor of art in music directing involves a creative rethinking of global innovative directing practices on domestic soil, taking into account the peculiarities of the Ukrainian mentality, cultural traditions, and achievements of national educational and art schools with gradual integration into Europe.
Perspectives of Blockchain in Digital Health in Brazil

In Brazil, the Public Health System was established in 1988 by the Federal Constitution, and it is currently known as the Sistema Único de Saúde (Unified Health System), better known by the acronym SUS. In 2015, a survey by the Ministry of Health carried out in partnership with the Brazilian Institute of Geography and Statistics (IBGE) found that 71.1% of the Brazilian population sought public health facilities to be served. Moreover, according to the SUS computer department, in 2016, about 76% of basic health units used the patient’s history on paper. With this scenario, the need for computerization of patient data management processes arose, and, with this, several tools were developed. One of these tools is the Electronic Patient Record (EHR). Considering the barriers brought by the operability of digital health concerning data security in an EHR, the present study aims to address the solution of the blockchain applicability to solve some systemic problems of data privacy. In this way, a study was carried out on blockchain and its applicability within health, highlighting Ethereum and Hyperledger Fabric. With this, it was possible to propose a domain model for the EHR with the blockchain within the scope of the Brazilian health system, contributing to the first steps of developing a tool using blockchain for digital health. This study provided the first theoretical contact in an academic context for implementing a blockchain system for digital transformation involving mainly EHR.
Automatic Voice Query Service for Multi-Accented Mandarin Speech

Automatic Voice Query Service can extremely reduce the artificial cost, which can improve the response efficiency for users. The automatic speech recognition (ASR) is one of the important component in AVQS. However, many dialect areas in China make the AVQS have to response the multi-accented Mandarin users by single acoustic model in ASR. This problem severely limits the accuracy of ASR for multi-accented speech in the AVQS. In this paper, a new framework for AVQS is proposed to improve the accuracy of response. Firstly, the fusion feature including iVector and filterbank acoustic features is used to train the Transformer-CTC model. Secondly, the transformer-CTC model is used to construct the end-to-end ASR. Finally, keywords matching algorithm for AVQS based on fuzzy mathematic theory is proposed to further improve the accuracy of response. The results show that the final accuracy in our proposed framework for AVQS arrives at 91.5%. The proposed framework for AVQS can satisfy the service requirement of different areas in mainland of China. This research has a great significance for exploring the application value of artificial intelligence in the real scene.
Multi-task Command and Control System based on Cloud Architecture

This paper designs a multi-task command and control system based on cloud architecture. It can greatly facilitate the deployment of multiple command and control tasks. The cloud architecture in this system includes virtualized cloud, container cloud, and desktop cloud. The management nodes in the container cloud and the underlying virtual machines in the desktop cloud are deployed on the virtualized cloud. In order to make full use of and ensure the reliability of data, the data of virtualized cloud, container cloud, and desktop cloud are all stored on distributed storage systems. The system can greatly reduce the operational complexity of operation and maintenance personnel through introducing unified cloud management and comprehensive operation and maintenance.
End-to-end Speech Recognition Based on BGRU-CTC

In recent years, the end-to-end speech recognition model has gradually become the development trend of large-scale continuous speech recognition because of its simplicity and easy training characteristics. In this paper, we use the good performance of bidirectional gated recurrent unit (BGRU), a variant of long short term memory (LSTM), in the field of speech recognition. At the same time, we use connectionist temporal classification (CTC) algorithm to train the model, build an end-to-end speech recognition system, and carry out speech recognition experiments on TIMIT. The results show that, compared with the traditional recognition model, the accuracy of the improved end-to-end model is improved by about 2.4%.
Research on Image Dimensionality Reduction Algorithms

This paper summarizes the principle of the Scale Invariant Feature (SIFT), Principal Component Analysis (PCA), and PCANet. Also, the paper uses IPython to realize the similarity comparison using SIFT and handwriting recognization using PCANet, then calculate the precision and recall of the result. The main thing of the SIFT is to find the key point descriptor through the Scale-space, Gaussian Pyramid, and Difference of Gaussian Pyramid (DoG), while the primary purpose of PCA is to find the eigenvalue and eigenvector through calculating the covariance. The combination of the PCA and neuro network, PCANet is divided into three stages.
DeepLab Network for Meteorological Trough Line Recognition

A meteorological trough line recognition method is proposed in this paper, in which a DeepLab network that adopts an encoder-decoder architecture is utilized to classify each point in the meteorological grid data into two categories: trough point or not, and then the trough area with the strongest horizontal convergence in the low-pressure area will be identified. The meteorological elements data related to the formation of trough includes the air pressure, the wind velocity and the temperature on 500hp, while the labels are marked with trough lines manually, they are used to train the network model. The proposed method first uses the Deeplab model to recognize the trough area from the meteorological elements data and then extracts the trough line from the trough area by skeleton line extraction algorithm. To evaluate our proposed method, the quantitative experiments were conducted and the results show us that the precission rate of proposed method performances better than the traditional method.
Generic Demosaicking Method for Multispectral Filter Arrays Based on Adaptive Frequency Domain Filtering

Multispectral filter arrays (MSFAs) are widely applied to achieve snapshot multispectral imaging on a single image sensor, which causes incomplete data of each channel in the original captured image, and thus a process of estimating missing data named “demosaicking” is needed for high spatial resolution imaging. In a multispectral imaging system equipped with MSFA, as the number of spectral channels increases, the lack of data in the original captured image becomes severer, which brings great challenges to the demosaicking process, and thus classical demosaicking methods for MSFAs often fail to satisfy both reconstructed image quality and computational efficiency. In this paper, we propose a generic demosaicking method for MSFAs based on adaptive frequency domain filtering (AFDF) which achieves high quality of reconstructed images with little computational cost. Experimental results demonstrate that our proposed demosaicking method outperforms the state-of-the-art methods in terms of both quality of reconstructed images and processing time.
An Optical Tracking System with Defaced Marker Detection

Optical tracking systems (OTSs) have been widely used in clinical practice to fulfill the high precision needs of contemporary surgery. The markers that are defaced in the production or surgery reduce the accuracy and tracking range of OTS. This effect was not considered in current products from either industry or academia. In this paper, we propose an OTS which can detect the defaced markers automatically. A stereo camera module is set to track surgical instruments by locating the markers affixed to them. An adaptive threshold approach is suggested to locate the markers. The typical fiducial localization error of our OTS reaches 0.28 mm, which is totally comparable to commercial devices. A defaced marker detection method based on the luminous energy model of OTS is proposed and can be used to recognize the defaced markers regardless of their relative positions to the OTS.
Data Augmentation Framework for Smart Sensor System Development Using the Sensor-in-the-Loop Prototyping Platform

Sensor subsystems are becoming more complex as they increasingly take on various tasks, from signal processing to pattern recognition. This off-loading of continuous processes can decrease power consumption of the entire system, as the application processor of e.g. a smartwatch can spend more time in low-power modes. The design and validation of these sensor subsystems are thus becoming more difficult and time-consuming. This development process relies heavily on the availability of suitable sensor signals for testing. We propose a modular component-based framework to generate a multitude of tests using either prerecorded sensor signals or artificial signals to allow for a faster and more thorough development process and prototyping.Using the recently proposed Sensor-in-the-Loop architecture, the work at hand demonstrates not only the ability to test and develop the software offline in a simulation, but to also use the augmented sensor signal data directly on the hardware prototype at run-time. The framework can be used in various testing- and development setups to simulate sensor characteristics, processing steps and errors. We show, based on three comprehensive examples, that the proposed framework is able to simulate the common errors found in inertial MEMS sensors, generate signal traces to develop, train, and evaluate gesture recognition algorithms, and simulate pre-processing steps in order to evaluate their feasibility before they are implemented in the sensor firmware.
Project-Based Learning Using Remote-Controlled Plane for Students in Mechatronics Course

The Ministry of Education, Culture, Sports, Science and Technology, Japan recommended educational institutions in Japan to carry out educational reforms by building active-learning courses. This paper explains the practice of project-based learning for sophomores in the mechatronics course, Tokyo University of Technology. We designed a project to teach simple principles of aeronautics, plant modeling, and mechatronics. Students are required to assemble radio-controlled planes. It tries to gain the motivation in learning mechatronics and the ability of teamwork and communication. We explained how we designed the project and the practical results. Statistics show that this project stimulated students' curiosity about mechatronics.
Measurement of Utility in User Access of COVID-19 Literature via AI-powered Chatbot

The advent of COVID-19 has resulted in a data deluge in the medical literature archives and there is a need for publication analytics services to augment the clinical workflow of medical users (e.g., clinicians, researchers, medical students) for literature search. Publication analytics services such as KnowCOVID-19 science gateway with a chatbot interface viz., Vidura Advisor have been developed to mine relevant literature from archives such as e.g., CORD-19 open-source dataset. In this paper, we present a novel utility measurement framework that uses a statistical technique for z-score calculation to measure the utility in user access of COVID-19 literature with publi-cation analytics services. Our framework approach builds on a usability study of the KnowCOVID-19 science gateway to identify challenges of user adoption of publication analytics at the individual level through the assessment of user performance and perception of factors such as user interface design, functionality, and derived information insights. In addition, we detail the soft-ware features (e.g., domain-specific topic filtering, data reports in terms of drugs/genes) within KnowCOVID-19 that support our measurement framework assessments. We evaluate our proposed framework through experiments on user performance and perception by comparing KnowCOVID-19 assisted by Vidura Advisor with a standard search engine i.e., Google Scholar over a set of clinical literature search tasks. The results from our usability study for assessing user performance using a single usability metric (z-score) show a 47% higher score in application utility with KnowCOVID-19 compared to Google Scholar.