Reviewerly/exHarmony huggingface dataset:
MUSIC TEACHER AND PRIMARY SCHOOL TEACHER TRAINING WITHIN ONE EDUCATIONAL PROGRAM

The article reveals the legal and substantive components of music teacher and primary school teacher training, which is within one educational and professional program «Secondary Education (Music). Primary education». Its characteristic features are analyzed. The combination of general and professional competencies, and program results of training, which are formed by its educational components are defined.
Case Study on Data Collection of Kreol Morisien, a Low-Resourced Creole Language

This case study focuses on laying down the foundations for the development of Kreol Morisien NLP (KreMoN) which is a series of Natural Language Processing tools to be used to process Mauritian Creole. While most of the works done so far focuses on detailing the Machine Learning algorithms, this work focuses on the first steps needed for any low resourced language which is the collection of data. We present a process currently being used to collect audio and textual data for a low resourced language like Mauritian Creole. This data will be used to develop a speech-to-text system as well as an Information Extractor for Mauritian Creole. As part of the case study, we detail some of the works made using existing textual data in Non standardized Mauritian Creole where an NLP pre-processing pipeline adapted for low resourced languages have been developed.
A Circular Detection Driven Adaptive Birth Density for Multi-Object Tracking with Sets of Trajectories

Multi-object tracking filters require a birth density to detect new objects from measurement data. If the initial positions of new objects are unknown, it may be useful to choose an adaptive birth density. In this paper, a circular birth density is proposed, which is placed like a band around the surveillance area. This allows for 360° coverage. The birth density is described in polar coordinates and considers all point-symmetric quantities such as radius, radial velocity and tangential velocity of objects entering the surveillance area. Since it is assumed that these quantities are unknown and may vary between different targets, detected trajectories, and in particular their initial states, are used to estimate the distribution of initial states. The adapted birth density is approximated as a Gaussian mixture, so that it can be used for filters operating on Cartesian coordinates.
Socio-Cultural Project as the Implementation of an Active Method in the Process of Professional Competence Formation among Future Buryat Language and Literature Teachers

The aim of the study is to substantiate the effectiveness of using the project method in the process of professional competence formation among students during the implementation of the socio-cultural project “The Interactive Platform”. The paper describes the implementation of the project method in extracurricular activities of students in the training programme “Pedagogical Education with Two Training Programme Specialisations: Native Language and Literature, Russian Language and Literature” at Buryat State University. The study is novel in that it proposes the idea of using the project method as one of the active teaching methods to increase students’ internal motivation, which is a condition for professional competence formation in extracurricular activities of teacher trainees. As a result of the study, it has been found that project work allowed students to realise the social significance of their future profession, greatly increased their motivation to carry out their future professional activities and contributed to professional competence formation.
Professional Difficulties of Young Teachers (by the Example of Amur Region Universities)

The study aims to identify negative factors accompanying young teachers’ professional activities at higher education organisations. The paper considers the main trends that have a negative impact on modern teachers under the age of 35 and the specificity of their manifestation at Amur Region universities. Scientific novelty of the work lies in the fact that based on the research relevant to the subject of the paper that was conducted at Amur Region universities among the teaching staff aged 22 to 68, it has been found that young teachers are less stable psychologically than middle-aged teachers, less self-confident, they are characterised by the emerging foundations of emotional burnout. In addition, young teachers are in a less stable position than more experienced employees due to the influence of a whole range of factors, which accounts for the increased turnover among young staff. As a result, the researchers have determined the place of a young teacher in a modern university, have identified the main factors contributing to the decline in the quality and effectiveness of teachers’ professional activities at higher education organisations, have noted regional specifics.
BYOD (“Bring Your Own Device”) Technologies in Elective Physics Course for Engineering Classes

The study aims to introduce the BYOD (“Bring Your Own Device”) concept and BYOD technologies into the organisation of design and research activities of schoolchildren attending an elective physics course of a technical university for engineering classes. The paper considers the features of organisation of an elective physics course for engineering classes of lyceums by a technical university, describes the process of implementing the BYOD concept and adapted BYOD technologies when organising design and research activities of students of engineering classes in an elective physics course, presents an assessment of the results of introducing BYOD technologies in an elective physics course for students of engineering classes at Novosibirsk State Technical University. Scientific novelty of the study lies in developing a methodology for adapting and applying BYOD technologies in the organisation of design and research activities of students of engineering classes attending an elective physics course of a technical university. Adapted mobile BYOD technologies make it possible to organise the learning process that contributes to more effective mastery of fundamental activities of modelling and experimentation by schoolchildren. At the same time, the use of mobile technologies forms the basic components of information competence among schoolchildren, serves as a source of acquiring and improving digital skills. As a result, it has been proved that it is not only possible, but also necessary to apply the BYOD concept and BYOD technologies when organising schoolchildren’s design and research activities in an elective physics course for engineering classes. Students’ own smartphones and tablets are characterised as having sets of various sensors and applications. Therefore, mobile devices can serve as a basis for more diverse and effective design and research activities of schoolchildren in an elective physics course. This includes using electronic sensors and mobile applications to perform and process measurements, creating video reports when designing installations and conducting experiments, mathematical processing of experimental results on video recordings, keeping electronic diaries, participating in video conferences, preparing and recording performances. The analysis of the results of introducing adapted BYOD technologies into an elective physics course has demonstrated a significant increase in schoolchildren’s interest in project research using mobile devices. A more effective organisation of students’ own activities and teamwork has been registered. It is noted that schoolchildren master measurement methods, ways of video recording and processing of experimental results using mobile devices rather quickly. Undoubtedly, the use of BYOD technologies by schoolchildren should be accompanied by control over their work with mobile devices within the scope of the set tasks of project research.
Usability of Paper Audit Trails in Electronic Voting Machines

Electronic voting machines (EVM) can improve the efficiency of elections. However, due to the possibility of errors in electronic voting machines, user trust in them is an issue. To improve user trust, one mechanism used by EVMs is the inclusion of a paper audit trail, which shows users a paper receipt of their vote for 7-seconds and asks them to verify their vote. While paper audit trails can theoretically improve user trust, their usability has not yet been explored, which can affect user trust. In this paper, we evaluate the usability of paper audit trails by creating two UI prototypes and testing them with users through a user study. The design of the first prototype reflected existing audit trail systems, whereas the second prototype was created using HCI design principles. Results showed that the second prototype improved error recognition rates compared to the first prototype. Post-test interviews showed that the second prototype also reduced users’ stress and anxiety of the voting process. Our work highlights the importance of exploring the human aspect in the design of electronic voting machines, and their associated components such as paper audit trails. It also provides insights into users’ overall perceptions of electronic voting.
Memory-based Collaborative Filtering on Twitter Using Support Vector Machine Classification

Nowadays, watching films at home is one of people's entertainment. Netflix is a service provider for watching films and provides many types of film genres. However, of the many films available, it makes users confused to choose which film to watch first. The solution to the problem is a system that provides recommendations for the best films to watch based on user ratings. Twitter is still people's favorite social media to express their feelings, thoughts, and criticisms. In this system, tweets serve as input data that will be processed into data with rating values. This research implemented a recommendation system based on user ratings from tweets using collaborative filtering combined with Support Vector Machine (SVM) classification and implemented it on user-based and item-based. The test results in this study show that Collaborative Filtering gets the best RMSE value results on item-based 0.5911 and 0.8162 on user-based. The Support Vector Machine (SVM) classification algorithm using hyperparameter tuning produces item-based values with a precision of 85.03% and recall of 90.71%, while user-based values with a precision of 87.75% and recall of 88.95%.
Implementasi push notification dalam rancang bangun sistem informasi manajemen evaluasi pembelajaran di perguruan tinggi

The Student Academic Administration Agency (BAAK) STIE PGRI Dewantara Jombang experienced inefficient evaluation (exam) administration problems. Such as: 1) BAAK has difficulty dividing exam supervisors so that schedules do not clash, 2) Study Programs have difficulty in making evaluation schedules so that there are no clashing schedules, and 3) Lecturers forget or are late in collecting questions and evaluation scores. In this study, it is proposed to create a web-based learning evaluation management information system equipped with a push notification feature to overcome these problems. The software development method used is waterfall, programming language using PHP and HTML5 with CodeIgniter Framework technology and Apache Cordova, notifications using Firebase Cloud, database management system (DBMS) using MySQL, and interface design using Balsamic. Based on the results of testing using blackbox testing, it is concluded that the system can be used to divide supervisors, make scheduling without conflicting times or places, and send notifications to remind when to collect exam questions.
Retraction: Evolved Fuzzy NN Control for Discrete-Time Nonlinear Systems

Journal of Circuits, Systems and ComputersVol. 31, No. 15, 2293001 (2022) RetractionFree AccessRetraction: Evolved Fuzzy NN Control for Discrete-Time Nonlinear SystemsOriginal articleEvolved Fuzzy NN Control for Discrete-Time Nonlinear SystemsTim Chen, A. Babanin, Assim Muhammad, B. Chapron, and C. Y. J. ChenTim ChenFaculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam, A. BabaninDepartment of Engineering, College of Engineering and Computer Science, Australian National University, 95 Daley Road, Canberra, ACT 2601, Australia, Assim MuhammadFaculty of Industrial Engineering, King Saud University, P. O. Box 2454, Riyadh 11451, Saudi Arabia, B. ChapronLe Laboratoire Interdisciplinaire des Energies, Paris Diderot University — Paris 7, 5 Rue Thomas Mann, 75013 Paris, France, and C. Y. J. ChenElectronic Automatic Engineering Centre, Industrial Technology Research Institute, Chutung, Hsinchu 31057, Taiwan, R. O. ChinaApplied Physics Research Centre, The Papua New Guinea University of Technology, Lae 411 Morobe, Papua New Guineahttps://doi.org/10.1142/S021812662293001XCited by:0 Previous AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail [J. Circuits Syst. Comput., Vol. 29, No. 1 (2020) 2050015] DOI:10.1142/S0218126620500152 FiguresReferencesRelatedDetailsRelated articlesEvolved Fuzzy NN Control for Discrete-Time Nonlinear Systems10 Apr 2019Journal of Circuits, Systems and Computers Recommended Vol. 31, No. 15 Metrics History Published: 29 August 2022 PDF download
Truncation point estimation of truncated normal samples and its applications

&lt;abstract&gt;&lt;p&gt;The moment estimates and maximum likelihood estimates of the truncation points in the truncated normal distribution are given, as well as the interval estimates for large samples. The estimation method of truncation point is applied to the assembly of DNA sequencing data, and moment estimation, maximum likelihood estimation and interval estimation of gap length are obtained. Monte Carlo simulations show that the experimental results are very close to the theoretical estimates. When the estimation method given in this paper is applied to a real DNA sequencing dataset, ideal estimation results are also obtained.&lt;/p&gt;&lt;/abstract&gt;
Humanistic and Socio-Cultural Key In Linguistic Education

The article argues that the most effective foreign language is given in the activity, and, consequently, mainly in the process of self-education. At the same time, linguistic education is based primarily on understanding, and not on the system of knowledge. Mastering a foreign language is impossible without mastering culture. Both are perceived as interpenetrations of native and foreign cultures, native and foreign languages, their mutual enrichment.
Campus Cart - A Campus Trading Mobile Application

Sharing is an act that is equal to caring. This is very true in how people build and function within our social relationships. In everyday life, people have items that they no longer use and that can be perfectly shareable with someone who needs it. When people share the things that they have with others, it showcases a sense of humility and empathy for those in need. Campus Cart is an android-based application exclusively for college campuses. Through this project, customers are able to connect with each other and trade the product. With this proposed system a community is built that encourages reducing the wastage of products and improving resource utilization.
Investigating the Effect of Concept Teaching Strategy on Academic Success

This study examined the effect of concept teaching on students’ learning level of concepts through concept teaching strategy; hence, a quasi-experimental design with pretest–posttest measurements and experimental and control groups was employed. An achievement test was created by the researcher to determine the experimental and control groups; this test was administered to 129 students studying in Grade 3, and the KR20 reliability coefficient was found to be .846. The pretest data were analyzed by independent groups’ t-test. As a result of the analysis, two groups that were identical to each other were randomly assigned as experimental and control groups. While the concepts such as governor, district governor, mayor, and headman, which are the concepts determined from the life science curriculum, were taught to the experimental group with the help of concept teaching strategy, a program-based teaching was conducted for the control group. After 5 weeks of application, a posttest was administered to the experimental and control groups. As a result of the dependent group t-test, a significant increase in the posttest scores of the experimental and control groups was observed. As a result of the independent groups’ t-test, a significant difference was noticed in favor of the posttest scores of the experimental group.
Decision Tree-Based Classification of sEMG and Accelerometer Data of Sign Language

Sign language is a worldwide gesture-based technique for communication in mute and hearing-impaired communities. It is rich in its own vocabulary and grammar. The ideas, emotions and information are conveyed only through physical and non-physical gestures of hands, facial muscular movements, and eye’s movement. Sign language recognition is broadly classified as vision-based and sensor-based techniques. However, vision-based technique is having issues like low illumination, bad camera setting, etc. We prefer here sensor-based technique for sign word prediction by using decision tree algorithm. In this study, we are using surface electromyography and accelerometer data of both fore arms of subject for classification and prediction of isolated sign words; this database is freely available. We have used decision tree classifier and found accuracy of 95% with k-fold validation. Sign language recognition will have grate impact on hearing-impaired community for expressing their views, emotions, thoughts with hearing individuals.
An Attention-Guided Visual Semantic Fusion Method for Remote Sensing Image Captioning

As a multi-modal task, remote sensing image captioning (RSIC) plays an essential role in image understanding. However, most current RSIC methods ignore sufficient utilization of image features. we propose an improved image description method with improved attention mechanism, named attention-guided visual semantic fusion (AVSF) method for RSIC, based on the encoder-decoder framework. Attention mechanism contributes to obtaining the relationship between global and local image, as well as the relationship between image region and corresponding text, which is more conducive to the generation of description. Firstly, convolutional neural network VGG16 is introduced as the main network to construct the encoder and extract the features for remote sensing images. Secondly, image features are fused with text features, and attention mechanism is introduced to enhance the attention to vision features. Then, long short-term memory is used to build a decoder for learning the mapping relationships between image visual features and text semantic features. The experiments show that evaluation metrics have been improved on the UCM and Sydney datasets.
A Real-time Visualization of Global Sentiment Analysis on Declaration of Pandemic

The paper's objective is to carry out a real-time visualization of pandemic sentiment at the very first instance.The paper shows multilevel visualization of sentiment analysis conducted on the covid19 dataset acquired from Twitter.The visualization tools used for real-time data are Google data studio, Python matplotlib, Carto, and Tableau.On Mar 11, 2020, Covid19 was declared a global pandemic, and stage wise lockdown protocols were implemented.The covid19 virus has spread worldwide and consumed millions of people.The impact of the virus is affected not only on the physical body but also on mental health and results in increased distress, depression, anxiety, fear, and panic simultaneously.The data was downloaded using twitter's official API on Mar 11, 2020.Vader sentiment analysis is performed on 3,27,717 tweets downloaded from 200 Megacities globally.The study achieved 50.95% negative and 58.72% positive sentiment and neutral values ranging between 0 to 1 polarity.
Cryptocurrencies in India : A Perspective

Cryptocurrencies came into existence in last one decade, and have gained a lot of attention from investors’ community. Legendary investors like Warren Buffett are not in favour of these currencies due to non-existence of intrinsic value. Concepts such as ‘Internet of Value’, ‘decentralization of finance’, and ‘application of blockchain technology’ have contributed to the emergence of this new phenomenon. This chapter is about Cryptocurrency market in India. It covers underlying objectives behind emergence of cryptocurrencies across the world and in India, their use, controversies associated with their use, trading platforms for their trading in India, and risks associated with cryptocurrencies. Suggestive framework for appropriate development in the domain, i.e., cryptocurrencies in India has been proposed at the end.
Sentiment Analysis of China-Related News in The Star Online Newspaper

As China and Malaysia approach their 47th year of diplomatic relationships, cooperation and trust between the two countries have deepened in aspects ranging from politics to economy. Despite this mutual reliance, the relationship between Malaysia and China is not without its conflicts and these conflicts are often manifested in media reports. How China is presented in Malaysia news is a field that has been scarcely explored. As part of the research on media sentiment towards China, this research investigates the general sentiment of China-related news in Malaysian media through sentiment analysis of some selected news coverages. Selecting China-related news in The Star Online from 2012 to 2021 as the data for investigation,the Excel Add-in tool Azure Machine Learning was used to generate polarity of these news reports automatically and corpus tool Wordsmith was used for the analysis of news discourse. A total of 137,475 pieces of news have been collected as the research sample. The finding reveals that: 1) despite the large proportion of news with negative sentiment in China-related news in The Star Online , the monthly trend of sentiment shows a slight increase of positiveness over time; 2) an investigation into the keyword lists of three months with highest proportion of negativeness and collocates of the top keywords, however, shows that negative sentiment of the news may be due to a global conflict at that particular time and does not necessarily indicate negative sentiment towards China. A combination of sentiment analysis and corpus approach on the study of China-related news in Malaysian media enriches the study of news discourse from the perspective of corpus linguistics.
Adversarial examples for poisoning attacks against federated learning

为了解决传统的机器学习中数据孤岛和数据隐私问题, 联邦学习技术应运而生. 现有的联邦学习方法采用多个不共享私有数据的参与方联合训练得到了更优的全局模型. 然而研究表明, 联邦学习仍然存在很多安全问题. 典型地如在训练阶段受到恶意参与方的攻击, 导致联邦学习全局模型失效和参与方隐私泄露. 本文通过研究对抗样本在训练阶段对联邦学习系统进行投毒攻击的有效性, 以发现联邦学习系统的潜在安全问题. 尽管对抗样本常用于在测试阶段对机器学习模型进行攻击, 但本文中, 恶意参与方将对抗样本用于本地模型训练, 旨在使得本地模型学习混乱的样本分类特征, 从而生成恶意的本地模型参数. 为了让恶意参与方主导联邦学习训练过程, 本文进一步使用了`` 学习率放大"的策略. 实验表明, 相比于Fed-Deepconfuse攻击方法，本文的攻击在CIFAR10数据集和MNIST数据集上均获得了更优的攻击性能.
Towards Syntactic Epistemic Logic

Traditionally, Epistemic Logic represents epistemic scenarios using a single model. This, however, covers only complete descriptions that specify truth values of all assertions. Indeed, many—and perhaps most—epistemic descriptions are not complete. Syntactic Epistemic Logic, SEL, suggests viewing an epistemic situation as a set of syntactic conditions rather than as a model. This allows us to naturally capture incomplete descriptions; we discuss a case study in which our proposal is successful. In Epistemic Game Theory, this closes the conceptual and technical gap, identified by R. Aumann, between the syntactic character of game-descriptions and semantic representations of games.