Reviewerly/exHarmony huggingface dataset:
IMPROVING THE STUDENTS' READING COMPREHENSION THROUGH THE USE OF SUGGESTOPEDIA METHOD

The objective of the research was to get empirical evidenceof the improving students’ reading comprehension of narrative text through suggestopedia method. The method of this research was classroom action research which was conducted in two cycles. The subject of this research was the Second Grade Students of SMA Pesantren Pancasila Bengkulu at Academic Year 2017/2018 with total number of students 18. The research instruments were the observation sheet, interview guidelines, questionnaire and test form. Based on the results of data analysis of pre-test and post-test shown the significant improvement. The average score of pre-test was 54,05. It means two students’ score could pass the KKM. It was 11,11% passed the learning outcome . The average score of post-test 1 was 72,94. It proved that 44,44% students passed KKM. The average score of post-test 2 was 82,77. Then, it was obtained that the percentage of students who could get the score above the KKM in post-test 2 was 100%. Based on the learning activities which have occurred the enhancing from the first to second cycle. From this research findings, it showed that suggestopedia method could improve the students’ reading comprehension of narrative text.
Reform of Talent Training Mode in Computer Major Under the Background of Artificial Intelligence

The development of artificial intelligence technology promotes industrial transformation and upgrading, and the demand for artificial intelligence talents is also increasing.Local applied universities should give full play to their functions, cultivate talents urgently needed by society, and promote the rapid development of the regional economy.This article introduces the ideas and practices of the computer major of Xijing University in the training of artificial intelligence talents.Firstly, it clarifies the necessity of the reform of the talent training mode.Secondly, the current status of talent cultivation for computer majors is analysed according to the requirements of engineering education professional accreditation, and the problems that need to be solved in the training of artificial intelligence talents are identified.Finally, reform ideas and methods are put forward to provide reference for the reformation of artificial intelligence talent training mode in similar colleges.
Life-Based Learning Approach on Massage Course in College Students

This research aimed at developing a learning method product using the blended learning model integrated with e-learning at State University of Malang (UM).The research method used was Research and Development method (R&D), with the following research steps (1) Needs analysis, (2) Early product development and expert assessment in the form of massage video learning, massage E-book, and UM e-learning integrated form of learning method.The results showed that it could be applied to small group with respect to 86.4% and 90% for the large group.The product made was a blended learning model integrated with UM e-learning in the form of learning videos.
Phonological study of the Sonaha language

The Sonaha is a language which is spoken in Bardiya, Kailali and Kanchanpur districts in Nepal. Sonaha language, henceforth Sonaha, was not identified by the government before the Census 2011. In spite of having its own linguistic features and originality, Sonaha is badly affected by the influence of other neighboring languages. Keeping this in mind, this study mainly aims to explore and present the inventory of the phoneme, syllable structures and vowel sequence or, in short, to highlight the phonological system of Sonaha language. Sonaha 3404 native words were collected from fifty native speakers of Rajapur Municipality and Geruwa Rural Municipality of Bardiya district, Ghodaghodi Municipality of Kailali and Bhimdutt Municipality of Kanchanpur district. The data were presented and analyzed based on minimal pairs to verify phonemes. This study explored six vowels, twenty nine consonants, six types of syllable structures and seven vowel sequences in Sonaha.
汉语学习者依存句法树库构建(Construction of a Treebank of Learner Chinese)

汉语学习者依存句法树库为非母语者语料提供依存句法分析,可以支持第二语言教学与研究,也对面向第二语言的句法分析、语法改错等相关研究具有重要意义。然而,现有的汉语学习者依存句法树库数量较少,且在标注方面仍存在一些问题。为此,本文改进依存句法标注规范,搭建在线标注平台,并开展汉语学习者依存句法标注。本文重点介绍了数据选取、标注流程等问题,并对标注结果进行质量分析,探索二语偏误对标注质量与句法分析的影响。
Analysis from a Dualist Perspective: “Frühling” from Richard Strauss’s Vier Letzte Lieder

The paper presents an analysis of Richard Strauss’s “Frühling”, the first of his Last Four Songs composed in 1948. I adopt the harmonic dualism of Moritz Hauptmann and Hugo Riemann—a theoretical perspective which reflects the ideals of German Romanticism. I contrast this approach with Schenkerian and Neo-Riemannian analyses of the song by Richard Kaplan and Richard Cohn. Two features central to my analysis are: 1) the rejection of enharmonic equivalence, and 2) the function of a special type of augmented sixth, a “Frühling sixth”, which propels the music forward and gives the song its characteristic chromatic sound. Using Riemann’s Schritt/Wechsel system, I chart the large-scale harmonic moves of the piece on a ‘Klangnetz’, showing how the various harmonic transformations articulate certain key areas and reflect the meaning of the song’s text.
A Simple Approach to Learning Unsupervised Multilingual Embeddings

Recent progress on unsupervised cross-lingual embeddings in the bilingual setting has given the impetus to learning a shared embedding space for several languages.A popular framework to solve the latter problem is to solve the following two sub-problems jointly: 1) learning unsupervised word alignment between several language pairs, and 2) learning how to map the monolingual embeddings of every language to shared multilingual space.In contrast, we propose a simple approach by decoupling the above two sub-problems and solving them separately, one after another, using existing techniques.We show that this proposed approach obtains surprisingly good performance in tasks such as bilingual lexicon induction, cross-lingual word similarity, multilingual document classification, and multilingual dependency parsing.When distant languages are involved, the proposed approach shows robust behavior and outperforms existing unsupervised multilingual word embedding approaches.
Correction To: Clustering in the Three and Four Color Cyclic Particle Systems in One Dimension

There is an error in the proof of Lemma 4.1.
Integration of Legalization Information System Web-Based using Shipping API and Telegram API

Education is a right for every citizen. Quality education makes people more intelligent. Educational outcomes documented in a file called a diploma. A diploma is a necessary file for doing things related to work or other administrative matters. Generally, the diploma file submitted is in the form of a photocopy of a certificate that has been legalized for administrative requirements. The process of legalizing diplomas is often a hindrance because the time required is quite long and especially if someone is in an area far from where to take care of legalization. In the industrial era 4.0, information technology can be utilized to facilitate public access to services in the world of education, for example, using technology to implement an online legalization system. Application of technology in the legalization process is not just online but can be integrated with API (Application Programming Interface). It can attract millennial access to the application easily. There are two APIs used, namely the Shipping API and the Social Messaging API. Shipping API makes it easy to check shipping costs based on alumni location. Social messaging API with assistant features so that it can be easier to serve alumni accessing application features via Telegram. This study aims to facilitate the alumni in legalizing online to make time-efficient and affordable—implementation of information systems with the integrated website media Telegram API and Rajaongkir or shipping cost API. Based on testing the usability testing results obtained a value of 4.56 on a scale of 5. These results indicate that the application can function following the needs of users of information systems.
HLTRI at W-NUT 2020 Shared Task-3: COVID-19 Event Extraction from Twitter Using Multi-Task Hopfield Pooling

Extracting structured knowledge involving self-reported events related to the COVID-19 pandemic from Twitter has the potential to inform surveillance systems that play a critical role in public health.The event extraction challenge presented by the W-NUT 2020 Shared Task 3 focused on the identification of five types of events relevant to the COVID-19 pandemic and their respective set of pre-defined slots encoding demographic, epidemiological, clinical as well as spatial, temporal or subjective knowledge.Our participation in the challenge led to the design of a neural architecture for jointly identifying all Event Slots expressed in a tweet relevant to an event of interest.This architecture uses COVID-Twitter-BERT as the pre-trained language model.In addition, to learn text span embeddings for each Event Slot, we relied on a special case of Hopfield Networks, namely Hopfield pooling.The results of the shared task evaluation indicate that our system performs best when it is trained on a larger dataset, while it remains competitive when training on smaller datasets.
PERBANDINGAN KINERJA VARIASI NAÏVE BAYES MULTIVARIATE BERNOULLI DAN NAÏVE BAYES MULTINOMIAL DALAM PENGKLASIFIKASIAN DOKUMEN TEKS

Classification of text documents with large amounts will be a job that requires a lot of time, effort and cost of having to read text documents and then categorize them manually, therefore the automatic classification of text documents is needed. The algorithm developed is K-Nearest-Neighbor (KNN), Naïve Bayes, Support Vector Machine (SVM), Decision Tree (DT), Neural Network (NN) and Maximum Entropy. The algorithm used as the object of research is a variation of the Naïve Bayes algorithm, the Naïve Bayes Multivariate Bernoulli and the Naïve Bayes Multinomial. This study discusses whether there are differences between the Algorithms. The Naïve Bayes Multivariate Bernoulli algorithm and the Naïve Bayes Multinomial can be seen from the value of the agreement and the speed of the process of classifying text documents, as well as more information about the process of processing requests that are getting more and more requested. While the highest value using the non-stemming Naïve Bayes Bernoulli method is 71.33%, and the fastest processing time is required using the non-stemming Naïve Bayes method which requires 0.12 seconds processing time.
Training of undergraduates in modern art and pedagogical education

The article describes the essence of master’s education, actualizes the problems of master’s training of artists and teachers in modern Russia. It is suggested that the lack of qualification of the previous level of specialized education for master’s students violates the specifics of training in higher art education. The purpose of the article is to update the problems of master’s training of specialists who do not have a diploma in art and pedagogical education. Methodology. The study is built on the basis of a contextual approach, which made it possible to identify a problem relevant to the current state of art education related to the master’s training of an artist-teacher. The theoretical method was chosen as the main research method (analysis of regulatory documents and literature on the research problem, analysis and synthesis, comparison, generalization and interpretation of data). Research result. The analysis of the state of implementation of the master’s training of the artist-teacher in Russian education made it possible to identify a problem that must be addressed at the legislative level. Artistic and pedagogical education has its own specifics, which must be taken into account when organizing recruitment for a master’s degree in the field of “Art Education”. The lack of thought of innovations has a negative impact on the quality of training of graduates who do not have a previous level of specialized education. Conclusion. In conclusion, the authors argue that applicants with a non-core education experience difficulties in a master’s program in art education, since they do not have a list of competencies required by the master’s training of an artist-teacher.
AN ABSTRACT MODEL OF SEARCH INDEX QUERY IN THE RUSSIAN NATIONAL CORPUS

The paper discusses the so-called “bag problem,” which affects the search accuracy in the Russian National Corpus (RNC). Solving the problem requires a change of the search index data scheme used in RNC, which in its turn requires a significant refactoring of the RNC program code. The basis of such a refactoring is proposed to be an abstract model of the search index query, which allows us to separate the query formation from the query implementation. An experiment was carried out in which one of the RNC system program modules was decomposed, which confirmed sufficient expressiveness of the constructed model. Directions of further work are determined.
Using the Generative Adversarial Network to Generate Recommendations

Widely used recommendation systems do not meet all industry requirements, so the search for more advanced methods for creating recommendations continues. The proposed new methods based on Generative Adversarial Networks (GAN) have a theoretical comparison with other recommendation algorithms; however, real-world comparisons are needed to introduce new methods in the industry. In our work, we compare recommendations from the Generative Adversarial Network with recommendation from the Deep Semantic Similarity Model (DSSM) on real-world case of airflight tickets. We found a way to train the GAN so that users receive appropriate recommendations, and during A/B testing, we noted that the GAN-based recommendation system can successfully compete with other neural networks in generating recommendations. One of the advantages of the proposed approach is that the GAN training process avoids a negative sampling, which causes a number of distortions in the final ratings of recommendations. Due to the ability of the GAN to generate new objects from the distribution of the training set, we assume that the Conditional GAN is able to solve the cold start problem.
An Algebraic Approach for Action Based Default Reasoning

Often, we assume that an action is permitted simply because it is not explicitly forbidden; or, similarly, that an action is forbidden simply because it is not explicitly permitted.This kind of assumptions appear, e.g., in autonomous computing systems where decisions must be taken in the presence of an incomplete set of norms regulating a particular scenario.Combining default and deontic reasoning over actions allows us to formally reason about such assumptions.With this in mind, we propose a logical formalism for default reasoning over a deontic action logic.The novelty of our approach is twofold.First, our formalism for default reasoning deals with actions and action operators, and it is based on the deontic action logic originally proposed by Segerberg in [27].Second, inspired by Segerberg's approach, we use tools coming from the theory of Boolean Algebra.These tools allow us to extend Segerberg's algebraic completeness result to the setting of Default Logics.
THE IMPACT OF INFORMATION TECHNOLOGY ON STUDENT’S ACHIEVEMENT AT THE UNIVERSITY OF FLORES IN THE CONTEXT OF SOCIO-CULTURAL RESILIENCE

This research aims to know the impacts between moral behavior, interaction with the community, and the impact of technology on Education which is the achievement index in Flores University especially in the study program of Accountant, management, Development Economics, and Information System. This research used the survey research approach with 95 respondents of the research sample. The method of analyzing data in this research was the correlation of Pearson Product Moment. To test the relation of some variables that used SPSS. The results of this research were: (1) The variable impact of Information systems on education had a positive impact on the achievement variable. (2) The interaction variable with the community did not have any impacts or influences on the achievement variable. (3) The moral behavior variable did not impact the achievement variable. It means that the use of good and right information technology will increase the students learning achievements, meanwhile the interaction with the community, and the moral behavior as the complement to support the students' success in gaining the good achievements in the University of Flores.
An Overview of Research on the Model of Teaching Chinese as a Foreign Language Over the Past Twenty Years-Based on the Analysis With Visualization Graphs

In a context that the comprehensive national strength constantly increases and the undertaking of teaching Chinese as a foreign language continuously develops, how to improve teaching efficiency and choose the right teaching model become the question worth studying.Taking the 241 research papers on the models of teaching Chinese as a foreign language included from 2000 to this day as the object of study, using the visualization document analysis software SATI as the analytical tool, through arranging the time of publication, the authors of papers, the institutes of publishing papers, the high-frequency keywords and other aspects, this article analyses the research hotspots and trends of the Chinese teaching models, and argues that the models of teaching Chinese as a foreign language can be further expanded and deeply studied in the aspects such as the skill separation teaching, element separation teaching, establishment of language database, composite teaching based on internet.
Business Environment and Their Readiness to Implement the Teleworking: A Field Study on the Application of the Egyptian Private Commercial Banks

The study aimed to determine the readiness of the business environment in the commercial banks of the Arab Republic of Egypt, to apply the method of teleworking, where a range of dimensions affecting the application of teleworking was studied, which is: information and communication technology, training, organizational culture, support to senior management, staff skills, and nature of jobs (flexibility).To achieve the goal of the study, the researcher followed the quantitative approach method through which the researcher relied on the questionnaire as tools to collect data from the study sample, which consisted of 322 workers at the private commercial banks of the study in Alexandria, and collected data and analysis by the statistical analysis program (SPSS version, 25).The researcher reached several important results, including the following: 1) There is an awareness among the vocabulary of the study sample of the readiness of the business environment to apply the teleworking to the private commercial banks operating in the governorate of Alexandria under study.2) There is an awareness among the vocabulary of the study sample to adopt the method of teleworking at the private commercial banks operating in the governorate of Alexandria under study.3) There is a positive effect on the dimensions (communication and information technology, organizational culture, employee skills, nature of jobs), while dimensions (training, support to senior management) negatively affect the application of teleworking in private commercial banks.The study also recommended the need to increase support for senior management in private commercial banks for the implementation of teleworking.In addition, providing the necessary training for managers and workers in banks, and at the end of the study, the researcher presented a guide for private commercial banks to implement the recommendations of the study.
PELATIHAN SOFTWARE R UNTUK ANALISIS STATISTIK1

R is a very useful software in statistical analysis. Its open-source nature makes it easy for users to download and use it freely. Its relatively small size allows R to be installed and used on a laptop because it doesn't use much laptop memory. Users are also facilitated to learn statistical analysis using R because there are many learning resources available which are also easily accessible. But the existence and ease of this has not been widely known by users of statistical analysis. To further introduce R to the public using statistical analysis, R training was conducted through the community service program (PPM) of Sriwijaya University. In this training, the introduction of R along with its potential use and development was carried out in statistical analysis. Participants were guided while practicing. The material studied included downloading and installing R, adding packages, calling data, naming and determining variable values, as well as some simple statistical analyzes. Statistical analysis studied descriptive, regression, and ANOVA. During training, participants can already download, install, and use R in accordance with the training material. For further use according to the needs of the participants, they are given some reference materials contained in a flash disk. In addition participants were also shown how to search for the required syntax via the internet.
TESTING PSEUDORANDOM NUMBER SENSORS BUILT IN SMART CARDS

This article explores randomness and how general purpose computers generate it. It also discusses the security requirements that a pseudo-random number generator must satisfy for use in cryptographic applications. And also special attention is paid to the known and new methods of testing random bit sequences. Analyzing the effectiveness of pseudo-random sequence generators is a pressing problem for smart cards when using more advanced methods of encryption and information protection. The available methods show low flexibility and versatility in the means of finding hidden patterns in data. To solve this problem, it is proposed to use algorithms based on multivariate statistics. These algorithms combine all the advantages of statistical methods and are the only alternative for analyzing short and medium-length sequences. The paper considers the scheme of operation of pseudo-random number generators in limited devices. The main requirements for modern smart cards are highlighted. A criterion for checking the randomness of bit sequences of small length (up to 100 bits) is proposed. This approach is appropriate for testing a lightweight pseudo-random number generator in devices with certain resource constraints. The paper presents the compatible distributions of the number of 2-strings and the number of 3-strings of a fixed form of a random bit sequence, which make it possible to carry out a statistical analysis of local sections of this sequence. A possible application of the obtained formulas can be to test the hypothesis of the randomness of the arrangement of zeros and ones in a (0, 1) -sequence of finite length. Research has shown that even with limited resources and a limited entropy environment like a smart card, good quality pseudo-random sequences can be created that can satisfy all the requirements for pseudo-random number generators, even those used for general purpose computers. In the work, the set of statistical tests was expanded to include other tests that are not included in the statistical set of NIST tests, and to analyze the work of the proposed algorithms. The paper presents algorithms for testing a pseudo-random sequence using multivariate statistics to illustrate their possible application in a smart card environment.