Reviewerly/exHarmony huggingface dataset:
Statistical analysis of several factors in predicting student performance

Education has always been a key factor in a country's development. Improving student performance is a common goal of students, parents and teachers. Studying the factors that influence student performance can help students focus on their weak points to improve their final grades more effectively. In this paper, random forest algorithm is used to extract the four most important independent variables, which are second-period grade (G2), first-period grade (G1), number of school absences (absences) and number of past class failures (failures) from a dataset on student performance. Then a multiple linear regression model is then established to study the relationship between the dependent variable final grade (G3) and them. After the evaluation of the model fitting accuracy and residual test, a linear model (<i>y</i> = -1.76483 + 0.97847 <i>X</i><sub>1</sub> + 0.14374 <i>X</i><sub>2</sub> + 0.03759 <i>X</i><sub>3</sub> - 0.25720 <i>X</i><sub>4</sub>) is built. It simplifies the model and can predict student performance with great accuracy
Post-Tonal Primer

A <italic>pitch</italic> is a specific point on the continuum of audible sound (the eighty-eight keys of the piano keyboard, for example, correspond to eighty-eight different pitches). A <italic>pitch class</italic> is group of pitches related by octave, and thus with the same (or enharmonic) name. There are twelve pitch classes, which can be visualized on the ...
FroggyHand: A Gesture Based Control System for Omni-Directional Projections

We would like to introduce FroggyHand, a novel interactive display which projects images onto a webbed skin between the user’s fingers. Applications connected to these images are then activated via hand tracking and gesture recognition. We present the implementation steps as well as small, prototype applications and discuss future plans.
Expressiveness of Shallow Networks

In this chapter, it is proved that the set of multivariate functions generated by shallow networks is dense in the space of continuous functions on a compact set if and only if the activation function is not a polynomial. For the specific choice of the ReLU activation function, a two-sided estimate of the approximation rate of Lipschitz functions by shallow networks is also provided. The argument for the lower estimate makes use of an upper estimate on the VC-dimension of shallow ReLU networks.
The library is one of the main social areas of information services

The concept of continuous education covers the progress of science and technology, the widespread use of advanced production technologies in practice, the mastery of knowledge by a person, the method of fruitful activity and personal qualities that will serve him all his life in the future. Continuing education is the basis of the competitive personnel training system, covers all types of education, state educational standards, and personnel training systems, and create conditions for its activities. Continuous education makes it possible to create the necessary conditions for the formation of a creative, socially active, spiritually rich and highly educated person. In the provision of library and information services, it is necessary to take into account the leading importance of education, the democratization of education, the humanity of education, the social significance of education, the national orientation of education, the close relationship between education and upbringing, the identification of talented youth, and the creation of conditions for obtaining fundamental and specialized knowledge.
Indoor Tracking of Dementia Patients without GPS

Dementia is one of the most common conditions that can be seen in elderly people. Often patients suffering from dementia lose their way home or wander in the streets. The caretakers find it difficult to keep track of the patient&#x0027;s movements. The Real-time locating systems (RTLS) is a technology that is used to track and locate objects or people. RTLS can be used in the hospital to track the movements of the patients. This research work proposes an RTLS based method to track the movements of the patients suffering from dementia to stop them from getting out of the house or care centers. So that they would not get lost in the streets. The proposed system uses a NodeMCU based wearable device that helps in tracking patient. The necessary counter actions are deployed if the patient tries to leave the care center. This proposed system enables the caretaker to monitor and track the movements of the patient. The unique aspect of the proposed system is that it does not use GPS (global pointing system) and the NodeMCUs can be networked locally so that external factors like internet outrage will not affect the system. The Internet can be used if needed.
Cloud computing security challenges and their solutions

Cloud computing is an internet-based technology that is becoming an emerging trend. It provides on-demand cloud-based services. Although it has many advantages, cloud computing poses a much more complicated situation in terms of key management, data security, data privacy, anomaly detection, cloud computing security and sharing, and vendor lock-in. Due to these issues, cloud computing adoptions are becoming difficult nowadays. Additionally, data integrity, privacy, and security are the biggest issue. Many scholars have conducted several surveys and published several papers related to the security of cloud computing. However, there was still a gap between cloud computing issues and their solutions because some researchers have discussed data security issues, and the rest have discussed virtualization issues. But we tried to make an effort to outline all the security issues, and we have been delivered a proper and clear way. We have discussed many challenges and security threats regarding cloud computing and suggested possible solutions in our paper. We extracted the most common challenges and explain those and also compare them in a tabular form.
Digital Trade Negotiation in Korea-China-Japan FTA: Minimax Strategy in the Process of Making Consensus

Purpose &#8211; The purpose of this paper is to apply the minimax procedures of the negotiation model to digital trade negotiation in the KCJ FTA to predict possible negotiation outcomes, as well as sensitive issues, for each country. Design/Methodology/Approach &#8211; Based on the negotiation model of the minimax procedures, this paper first derives top preferences for each country in negotiating the KCJ FTA. It then conducts a sectional analysis of issues and derives possible negotiation outcomes in terms of both majority voting (MV) outcomes and minimax outcomes (FBn). It finally predicts sensitive issues in the voting process and outcome rankings for each section of issues. Findings &#8211; For the first section of issues, the minimax outcome will prevail, while the MV outcome will be the first in ranking for the last section of issues. In terms of sensitivity during the negotiation process for voting, China is predicted to be the most reluctant to agree on binding rules on non-discrimination. As Japan is not as sensitive as the other two countries in each issue of digital trade agreement, both Korea and China are predicted to be the most hesitative in agreeing on binding rules on source code. Research Implications &#8211; Under the minimax procedures, negotiation positions as well as the dynamics of the voting process for each issue can be systematically predicted ex ante. The negotiation outcomes derived from the model can be viewed as win-win that would not produce any left-out countries, since each country minimizes the deviation from the initial top preference to the agreed deal.
Tan Dun, Intercourse of Fire and Water for solo cello (1996)

The three small phrases that comprise this passage are highly contrasting, in ways that are suggestive of the title of the work: one is slow, wavy, and watery; the other two are fiery and furious, loud and agitated. Both the watery and fiery music are based on pentatonic scales, organized as RI-chains, and with frequent reference to inversional symmetry. An underlying contrast between the natural hexachord and the complementary sharp hexachord further shapes the musical rhetoric. The progress of the piece can be traced on a space that consists of the traditional circle of fifths.
Security algorithms for secure cloud environment

The most emerging internet technology of this era is Cloud Computing. Its services are available in shared distributive manners. These services are provided to the users in reusable manners. Cloud users are increasing day by day because of its effectiveness and reliability. Cloud Computing provides the facility of backing up files. Cost-saving is the second feature. The third feature is that there is no time restriction in the Cloud environment. Users can gain access to its services anytime as user required. A large amount of data of many organizations, is transferred on a cloud environment for securing it. The main aspect of any organization is to transmit data in a secured and timely manner. Day by day, many security and privacy issues are increasing in the cloud environment. Security algorithms are used to protect the cloud’s data so that data remains safe and secure. Security algorithms secure data by different methods known as Encryption and decryption. In this study, an exhausted survey is carried about Cloud Computing and all the security algorithms. A comparison table is also drawn that defines the comparative study between security algorithms.
Tender Document inviting submissions for Literacy Editorship for the period November 2022 to November 2025

LiteracyVolume 56, Issue 2 p. 186-187 Announcement Tender Document inviting submissions for Literacy Editorship for the period November 2022 to November 2025 Diane R. Collier, Corresponding Author Diane R. Collier dcollier@brocku.ca Faculty of Education, Brock University, St. Catharines, Ontario, Canada Correspondence: Diane R. Collier, Associate Professor, Faculty of Education, Brock University, St. Catharines, Ontario, Canada. email: dcollier@brocku.caSearch for more papers by this authorNatalia Kucirkova, Natalia Kucirkova Norwegian Center for Learning Environment and Behavioural Research, University of Stavanger, Stavanger, NorwaySearch for more papers by this author Diane R. Collier, Corresponding Author Diane R. Collier dcollier@brocku.ca Faculty of Education, Brock University, St. Catharines, Ontario, Canada Correspondence: Diane R. Collier, Associate Professor, Faculty of Education, Brock University, St. Catharines, Ontario, Canada. email: dcollier@brocku.caSearch for more papers by this authorNatalia Kucirkova, Natalia Kucirkova Norwegian Center for Learning Environment and Behavioural Research, University of Stavanger, Stavanger, NorwaySearch for more papers by this author First published: 18 April 2022 https://doi.org/10.1111/lit.12285 The deadline for receipt of proposals is 31 May 2022 with interviews scheduled for July 2022. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume56, Issue2May 2022Pages 186-187 RelatedInformation
Integration of PSO and Clustering algorithms for privacy preserving data mining

Privacy Preserving Data Mining (PPDM) currently has become an important research area. There are some issues and problems related to PPDM have been identified. Information loss occurs when the original of data is modified to keep the privacy of those data. Effects of PPDM also cause the level of data quality to become lower. The aim of this research is to minimize information loss and increase the accuracy of mining result while maintaining the privacy level of data. A randomization approach based on optimization and clustering algorithms is proposed in order to minimize the information loss and improve the accuracy of data clustering quality for PPDM results. There are three main objectives for this research which is to perform data pre-processing on data through the normalization process and k-Anonymity algorithm. The second objective is to minimize data loss and increase the accuracy of data mining result using Particle Swarm Optimization and clustering algorithms. The third objective is to evaluate and benchmark the performance measurement based privacy level and data quality of enhanced PPDM. Diabetes dataset is used in this research and all instances are a numerical value. The outcome of this research is the privacy level of the dataset was increased while the information loss is minimized. The experimental results also show that the accuracy of data clustering quality can be preserved with using PSO algorithm.
A quantitative approach to the competence of trainees based on the cyber security skills framework

The continuous development of cyber security industry has brought about a new change in employment requirements, and the job requirements for the ability of employees show the characteristics of "customized" professional skills. The existing cyber security training effectiveness assessment method mainly from the point of view of task completion, based on the assessment results of task training effectiveness to subjectively evaluate the training personnel's ability, lack of training personnel in different aspects of professional skills and objective evaluation of the training personnel's ability, resulting in the assessment results can not determine whether the training personnel's ability can match the needs of the job. In response to the above problems, we propose a quantitative method of the trainee's ability based on the cyber security skills framework, which achieves a quantitative assessment of the trainees' abilities in cyber security training from the perspective of cyber security skills. The experimental results show that compared with the evaluation method of focusing on the completion of training tasks, the method proposed in this paper can realize the objective quantification of the trainee's ability, and provide the information of the trainee's mastery of different skills, and provide reference for guiding the cyber security employment.
General Introduction

This book considers the extent to which, if at all, legislatures and social media platforms should ban or place restrictions on the spread false and misleading electoral and political information. The key distinction, around which the arguments of the book revolve, is a distinction between electoral participation disinformation and political viewpoint disinformation. I argue that whilst it is legitimate to ban or restrict the spread of disinformation about how to participate in elections, it is not acceptable to ban or restrict the spread of false or misleading political viewpoint disinformation as such. Someone denied their vote, or deterred from voting by false information about the voting procedure, has suffered a rights violation (just like someone who is the victim of hate speech). By contrast, someone who is simply persuaded to accept false political claims (about a particular candidate, or a party, for example) has not suffered such a violation, even if the latter’s acceptance of the claims leads them, say, to vote in a way that they might not otherwise have done. The spread of false and misleading political information is strongly associated with highly partisan and emotionally charged forms of politics. Accordingly, to accept that engaging in this kind of politics is legitimate—and it is—entails adopting a tolerant attitude to the spread of political viewpoint disinformation. However, such a tolerant attitude is inappropriate in the case of electoral participation disinformation, disinformation that undermines a key non-partisan feature of the democratic state.
Computational Linguistics for Subjectivity Preslav Nakov

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MODERN APPROACHES TO TEACHING SCHOOLCHILDREN IN A PANDEMIC

Annotation: The review analyzes the results of studies that justify the introduction of blended learning in the school system. For more than a decade, modern universities have been gradually introducing additional technologies into their educational programs, including the use of distance learning. Schools until 2019 provided traditional face-to-face education, but the ongoing COVID-19 pandemic has made adjustments, which has spurred the active adoption of distance learning. Despite the uncertainty about how long this pandemic will persist and the possibility of a new pandemic in the future, it is necessary to rethink current approaches in educational practice, as well as re-evaluate distance learning as an alternative to the traditional approach in education.
A Study on General Characteristics in Korean-Spanish Machine Translation

This paper aims to analyze the general characteristics of Korean-Spanish machine translation and vice versa. In spite of recent developments in artificial intelligence, there still are numerous errors in lexical and syntactic structure in machine translation. One of the most important reasons for these errors in machine translation is word-for-word translation without considering the linguistic differences of Korean and Spanish. For the purpose of our analysis, we focused on two grammatical categories, noun phrases and verbal phrases in the 100 cases. In the analysis of noun phrases, we investigated the problems on plurality and definiteness in Koean and Spanish. In our analysis of verb phrases in context, we find that the mood and tense cause some problems in machine translation.. We believe that this paper can contribute to a comparative analysis of human and machine translation in the near future. We insist that we must find some feedback system to improve the quality of machine translation through systematic and coherent research cooperation.
Formal Representation and Extraction of Perspectives Aldo Gangemi and Valentina Presutti

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Using Results of Subject and Methodological Competencies of Teacher in Formation of Natural Scientific Literacy of Students

The article is devoted to one of the important problems of the modern education system ‒ the formation of functional literacy of students, which allows ensuring the competitiveness of Russian schoolchildren in the market of educational services by ensuring the accessibility and quality of education. The article focuses on the relevance of the formation of functional literacy of students in the field of the regional system for assessing the quality of education; The main approaches to developing tools for assessing functional literacy are being considered. The results of monitoring the assessment of the natural science literacy of students in the 6th, 7th grades of general education organizations of the Stavropol Territory, carried out as part of the innovation project of the Ministry of Education of the Russian Federation "Monitoring the formation of functional literacy," as well as the results of a study of the professional competencies of teachers of the natural science cycle, which will determine the main directions for further improving the regional system for assessing the quality of education.
Electrical project cluster model based on text similarity algorithm in machine learning

At present, text similarity calculation technology is widely used in text data mining, text classification, information retrieval, information filtering, machine translation, text checking and other fields, but it is rarely used in project association. Among them, the cluster analysis of electrical projects is a cluster correlation analysis based on the text similarity of the electrical projects in the database. This study studies the related technology of text similarity calculation, and focuses on the problem that the traditional vector space model cannot reflect the special text performance ability of feature projects in different positions in the text similarity calculation, and studies its improved model: text segment vector space model, the calculation efficiency of text similarity of electrical projects is improved, and problems such as duplication of construction are effectively avoided.
Sparse Recovery from Linear Observations

This chapter introduces the standard compressive sensing problem, where one tries to recover sparse vectors from few linear observations. The problem is proved to be solvable using ?1-minimization as a recovery map if and only if the observation matrix satisfies the so-called null space property. This property is then shown to be a consequence of an atypical restricted isometry property from ?2 to ?1, which holds with high probability for Gaussian matrices.
Natural Language Processing Tasks for the Extraction of Perspectives Chantal van Son, Roser Morante, and Piek Vossen

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Trusted blockchain of ring signature in TEE environment

Traditional blockchain system has two problems: poor privacy protection and scalability. The public chain discloses all information, which can be seen by every node. The code of smart contract is clear-text, and the data is also clear-text. Every node in the public chain is untrustworthy, so it is necessary to design a complex consistency protocol, which often leads to poor performance (low TPS), waste of power, or lower overall credibility. TEE can construct a trusted execution environment Enclave (safe house), which is similar to a black box, the outside cannot access the inside, and it can allow the outside to authenticate the inside reliably through remote authentication. This paper focuses on how to integrate Intel SGX and ring signature algorithm into traditional blockchain to realize privacy calculation and transaction. To protect the anonymity of traders and to process trusted privacy calculation under the chain. Through the cooperation between on the chain and off the chain, "calculation" and "settlement" are completely decoupled, thus solving the performance bottleneck and privacy problems of traditional smart contracts.