Reviewerly/exHarmony huggingface dataset:
ACTIVE METHODS IN TEACHING MEASUREMENT UNCERTAINTY

The article considers the problem of activation of students’ cognitive activity and efficient use of study time while studying by them of the definition of measurement uncertainty and its calculation. Survey of 56 students studying in specialty “Metrology and information and measurement system” demonstrated that 80% among them assumed this topic to be the most difficult in the course “Principles of metrology”, and 60% answered that they required more time to digest it than provided in the discipline plan. To eliminate this discrepancy, students were proposed with the methods of working with educational materials for independent study with further practice in classroom: supporting signals and blitz games. Such pedagogical methods are focused on gaining a better understanding of theory for the same period. At the second stage the authors asked the students to evaluate those skills they have gained. The survey demonstrated that 30% of students interviewed found it difficult to calculate measurement uncertainty during classroom and graduation project, as well as when solving application tasks requiring for calculation of uncertainty, when studying interdependent disciplines. 18% asked that they could not make a budget of uncertainty by themselves. 70% noted that they wanted to receive more practical examples of solving such tasks. The authors chose the “case study” method, one its prominent feature is the creation of problem situation based on facts of real life or professional activity. The results demonstrated that, subject to static essentiality and compared to the control group, successfulness of learning measurement uncertainty increased by 16 %, and quality – by 12 %.
Comparison of Data MigrationTechniques from SQL Databaseto NoSQL Database

With rapid and multi-dimensional growth of data, Relational Database Management System (RDBMS) having Structured Query Language (SQL) support is facing difficulties in managing huge data due to lack of dynamic data model, performance and scalability issues etc. NoSQL database addresses these issues by providing the features that SQL database lacks. So, many organizations are migrating from SQL to NoSQL. RDBMS database deals with structured data and NoSQL database with structured, unstructured and semi-structured data. As the continuous development of applications is taking place, a huge volume of data collected has already been taken for architectural migration from SQL database to NoSQL database. Since NoSQL is emerging and evolving technology in the field of database management and because of increased maturity of NoSQL database technology, many applications have already switched to NoSQL so that extracting information from big data. This study discusses, analyzes and compares 7 (seven) different techniques of data migration from SQL database to NoSQL database. The migration is performed by using appropriated tools / frameworks available for each technique and the results are evaluated, analyzed and validated using a system tool called SysGauge. The parameters used for the analysis and the comparison are Speed, Execution Time, Maximum CPU Usage and Maximum Memory Usage. At the end of the entire work, the most efficient techniques have been recommended.
Compressing LSTM Networks by Matrix Product Operators

Long Short Term Memory(LSTM) models are the building blocks of many state-of-the-art natural language processing(NLP) and speech enhancement(SE) algorithms. However, there are a large number of parameters in an LSTM model. This usually consumes a large number of resources to train the LSTM model. Also, LSTM models suffer from computational inefficiency in the inference phase. Existing model compression methods (e.g., model pruning) can only discriminate based on the magnitude of model parameters, ignoring the issue of importance distribution based on the model information. Here we introduce the MPO decomposition, which describes the local correlation of quantum states in quantum many-body physics and is used to represent the large model parameter matrix in a neural network, which can compress the neural network by truncating the unimportant information in the weight matrix. In this paper, we propose a matrix product operator(MPO) based neural network architecture to replace the LSTM model. The effective representation of neural networks by MPO can effectively reduce the computational consumption of training LSTM models on the one hand, and speed up the computation in the inference phase of the model on the other hand. We compare the MPO-LSTM model-based compression model with the traditional LSTM model with pruning methods on sequence classification, sequence prediction, and speech enhancement tasks in our experiments. The experimental results show that our proposed neural network architecture based on the MPO approach significantly outperforms the pruning approach.
Investigating sets of linguistic features for two sentiment analysis tasks in Brazilian Portuguese web reviews

Identifying subjective sentences and classifying the polarity of subjective sentences are two important tasks in sentiment analysis. Besides being a hot topic, there is still a lack of resources to perform the mentioned sentiment analysis tasks in the Portuguese language, with its syntactic specificities. This paper describes the identified challenges and next steps in an initial study regarding the classification of subjectivity and polarity of sentences with a small set of syntactic features extracted directly from the text. Our approach reached satisfying results in experiments with two classic machine learning models in four datasets consisting of user reviews from different domains.
Museums in Building Social Capital

The article analyzes the role of museums in the formation of social capital in society, presents the possibilities of museum-type institutions in this context for Ukrainian society. The advantages of societies with a high level of social capital are highlighted; the urgency of this problem for our country is substantiated.&#x0D; Museums are a separate group of exceptional social institutions, the meaning of existence and the true nature of which was revealed and manifested only in the XXI century. Today, museums have gone far beyond their vision of decades past - in developed economies, they are becoming agents of social change, transforming social practices, helping to reduce antisocial phenomena and bringing significant benefits to local communities. We can compare how drastically the interpretation of the museum's mission and the vector of its activity in the era of globalization have changed in just some 20-30 years.&#x0D; Over the last decade, museums in Ukraine have responded more confidently to social and political problems in society, participated more actively in the consolidation of society, and generated new practices of cooperation with the local groups. The intensity of the media environment, the rapid development of IT technologies help individual museums to more openly broadcast their communicative mission.&#x0D; At the present stage society is slowly but surely changing. Post-communist transformation, unpredictability of the political future, economic problems and military aggression in the east of the country have led to problems of adaptation of the population to new socio-economic conditions and test the resilience of our communities. All this changes everyday life and requires adaptation to new conditions. In this direction, provided a well-thought-out strategy and appropriate regulatory framework, museums have significant positive potential.
PEMODELAN APLIKASI PENDUKUNG KEPUTUSAN MAKANAN PENDAMPING AIR SUSU IBU (MPASI) BERBASIS ANDROID

Complementary foods breast milk (MPASI) is a very important thing for growth and development in a baby, to achieve optimal growth and development process, balanced nutrition is needed, even nowadays babies are often stunted or have malnutrition. Good parents, of course, do not just provide complementary foods to their babies but will pay attention to whether or not the MPASI nutrition is given. By modeling an MPASI guide application, it can help parents determine the right nutrition to give to their babies and parents can make the right decisions and find out the nutritional status of their babies. Modeling this application using Unifield Modeling Language (UML) and implemented into the application using Android Studio. From the resulting application model, it can help and provide references to parents in providing balanced nutrition for their babies.
Accurate Word Representations with Universal Visual Guidance

Word representation is a fundamental component in neural language understanding models. Recently, pre-trained language models (PrLMs) offer a new performant method of contextualized word representations by leveraging the sequence-level context for modeling. Although the PrLMs generally give more accurate contextualized word representations than non-contextualized models do, they are still subject to a sequence of text contexts without diverse hints for word representation from multimodality. This paper thus proposes a visual representation method to explicitly enhance conventional word embedding with multiple-aspect senses from visual guidance. In detail, we build a small-scale word-image dictionary from a multimodal seed dataset where each word corresponds to diverse related images. The texts and paired images are encoded in parallel, followed by an attention layer to integrate the multimodal representations. We show that the method substantially improves the accuracy of disambiguation. Experiments on 12 natural language understanding and machine translation tasks further verify the effectiveness and the generalization capability of the proposed approach.
LibGuides: The Fourth Industrial Revolution: 3D Printing

Professor Klaus Schwab is convinced that we are at ‘the beginning of a revolution that is fundamentally changing the way we live, work and relate to one another.’ He calls this revolution the Fourth Industrial Revolution.
Evolution of Alexander Zhurbin’s Musical Theatre: From “Orpheus and Eurydice” to “Love’s Metamorphoses”

In his 40 years of creative search in musical theatre, the composer Alexander Zhurbin has worked his way from zong/rock operas and musicals to grand operas of academic variety. The purpose of the study is to characterise evolution of creative work, the author’s aesthetics in the context of philosophical consideration of culturological shifts, to identify its stages. The work focuses on studying the very first musical-theatrical opus of the composer and his latest work, which shows qualitative changes in the method and aesthetics. Scientific novelty of the study lies in the fact that for the first time in scientific literature, twelve works created by A. Zhurbin for musical theatre are considered, their genre is determined according to the composer himself and also taking into account theatre practice. As a result, six definitive operas and six opuses falling between genres and combining features of opera and different types of musical are identified.
EKSISTENSI MEDIA DALAM PEMBELAJARAN MELALUI MEDIA SOSIAL DAN MEDIA AUDIOVISUAL DI FAKULTAS KEGURUAN DAN ILMU PENDIDIKAN (FKIP) UNIVERSITAS PRIMA INDONESIA

This study aims to identify learning outcomes through the media used by students, focus student knowledge to determine the contribution of media in their learning, improve student expertise / knowledge, and provide opportunities for students to become innovative teachers. This research method applies descriptive qualitative data analysis and comparative quantitative. The research data was measured through test and non-test instruments. The research sample was FKIP students majoring in Indonesian and English through 2 general subjects, namely learning media and educational statistics. The results of the study have shown that the learning outcomes of the two majors do not show a significant difference. Furthermore, 24 questionnaire items showed that social media contributed more to student learning activities than audiovisual media. On the other hand, the observations show that students are more likely to behave negatively during research activities. Students feel uncomfortable if learning activities are dominated by media. Plus the imposition of online learning which requires virtual learning activities. So this research concludes that the existence of the media will be increasingly felt if it is collaborated with other relevant learning methods. Keywords: Media, Learning, Existence, FKIP Students
Improving Self-Learning for Deaf Students in SMPLB Through Use of BISINDO Video in Heat and Temperature

Deaf students have limitations on the sense of hearing, so to grow self-learning requires special processes and training. The results of the observations at the especialy needs secondary school (Sekolah menengah pertama luar biasa negeri/SMPLB-N-in Indosesia) found that one of the goals of the SMPLB-N Ungaran was to produce graduates who were independent and could live in community life. This study aims to improve the learning independence of SMPLB-N Ungaran students by using BISINDO-based videos. This video is equipped with sign language that makes it easy for students to understand the material being studied. The method used is an experiment with the design of single subject A-B patterns. A is baseline dan B is Intervention. The data analysis technique uses descriptive percentages. BISINDO-based video-assisted learning helps students improve self-learning. The increase in the learning independence of deaf students from the baseline phase to the intervention phase was 2.29 in the high category. The average increase in studentsâ€™ self-learning is 46.1% for the personal aspects of attributes, 52.4% for the aspect process, and 10.2% for the learning context aspect.
Cognitive Computing in Data-centric Paradigm

Knowledge is the most precious asset of humankind. People extract the experience from the data that provide for us the reality through the feelings. Generally speaking, it is possible to see the analogy of knowledge elaboration between humankind's way and the artificial system's way. Digital data are the "feelings" of an artificial system, and it needs to invent a method of extraction of knowledge from the Universe of data. The cognitive computing paradigm implies that a system should be able to extract the knowledge from raw data without any human-made algorithm. The first step of the paradigm is analysis of raw data streams through the discovery of repeatable patterns of data. The knowledge of relationships among the patterns provides a way to see the structures and to generalize the concepts with the goal to synthesize new statements. The cognitive computing paradigm is capable of mimicking the human's ability to generalize the notions. It is possible to say that the generalization step provides the basis for discovering the abstract notions, revealing the abstract relations of patterns and general rules of structure synthesis. If anyone continues the process of structure generalization, then it is possible to build the multi-level hierarchy of abstract notions. Moreover, discovering the generalized classes of notions is the first step towards a paradigm of artificial analytical thinking. The most critical possible responsibility of cognitive computing could be the classification of data and recognition of input data stream's states. The synthesis of new statements creates the foundation for the foreseeing the possible data states and elaboration of knowledge about new data classes by employing synthesis and checking the hypothesis.
Inovasi Pelayanan Perputakaan di Taman Bacaan Masyarakat Lingkaran Cahaya selama Pandemi Covid-19

The Covid-19 pandemic has had a tremendous impact on all sectors of society, including information institutions such as libraries and Community Reading Park which have been affected. Community Reading Park has also innovated to survive during a pandemic by developing collections, reference services, and circulation services at Community Reading Park The purpose of this study was to determine the innovation of the Circle of Light Community Reading Park during the Covid-19 pandemic. This study used a descriptive qualitative research method, in which the researcher conducted interviews and observations on the managers of the Circle of Light Community Reading Park. The innovation at Community Reading Park involves several aspects and services such as management, collection development, and services such as reference services and circulation services. This innovation is expected to attract people to carry out the function of Community Reading Park to increase reading interest during the Covid-19 pandemic.
Quantum Collision Attacks on AES-like Hashing with Low Quantum Random Access Memories.

At EUROCRYPT 2020, Hosoyamada and Sasaki proposed the first dedicated quantum attack on hash functions—a quantum version of the rebound attack exploiting differentials whose probabilities are too low to be useful in the classical setting. This work opens up a new perspective toward the security of hash functions against quantum attacks. In particular, it tells us that the search for differentials should not stop at the classical birthday bound. Despite these interesting and promising implications, the concrete attacks described by Hosoyamada and Sasaki make use of large quantum random access memories (qRAMs), a resource whose availability in the foreseeable future is controversial even in the quantum computation community. Without large qRAMs, these attacks incur significant increases in time complexities. In this work, we reduce or even avoid the use of qRAMs by performing a quantum rebound attack based on differentials with non-full-active super S-boxes. Along the way, an MILP-based method is proposed to systematically explore the search space of useful truncated differentials with respect to rebound attacks. As a result, we obtain improved attacks on AES-MMO, AES-MP, and the first classical collision attacks on 4- and 5-round Grostl-512. Interestingly, the use of non-full-active super S-box differentials in the analysis of AES-MMO gives rise to new difficulties in collecting enough starting points. To overcome this issue, we consider attacks involving two message blocks to gain more degrees of freedom, and we successfully compress the qRAM demand of the collision attacks on AES-MMO and AES-MP (EUROCRYPT 2020) from \(2^{48}\) to a range from \(2^{16}\) to 0, while still maintaining a comparable time complexity. To the best of our knowledge, these are the first dedicated quantum attacks on hash functions that slightly outperform Chailloux, Naya-Plasencia, and Schrottenloher’s generic quantum collision attack (ASIACRYPT 2017) in a model where large qRAMs are not available. This work demonstrates again how a clever combination of classical cryptanalytic technique and quantum computation leads to improved attacks, and shows that the direction pointed out by Hosoyamada and Sasaki deserves further investigation.
Training of postgraduate students – future teachers to pedagogical activities

The article analyzes the focus of modern pedagogical education on the development of a professional teacher capable of updating personal and creative potential. The author uses the following methods: analysis and synthesis of thematic scientific information, results of research by specialists in the area under consideration; synthesis and systematization of facts and provisions; pedagogical observation. Also, it substantiates the main conditions for the professional formation of a graduate student-future teacher: the development of professional self-consciousness, the formation of frustration tolerance, communicative competence, the need to develop personal and professional competencies. Experience of introduction of practical-oriented system of training aimed at formation of pedagogical orientation, development of professional pedagogical thinking, social-perceptual and communicative skills of graduate students-future teachers is presented. The article proves the need for a value and meaning orientation of professional training in psychological and pedagogical education, which leads to semantic search and semantic construction in pedagogical activity. Training forms and methods that conducive to the development of personal and professional competencies are described: pedagogical studio, art-therapeutic workshop, communication training; conflict method, analysis of pedagogical situations, analysis of artistic and pedagogical works, mastering of partnership interaction techniques. Awareness of a postgraduate student a future teacher of his potential, prospects for personal and professional growth encourages him to constantly experiment in the course of his professional activity, search, creativity and choice. The sooner the directed personal and professional development of the teacher begins, the more it is possible to predict his psychological well-being and personal growth
Analysis of the Countermeasures of Dealing with the Network Public Opinions on Emergencies of Colleges in Gansu Province

The popularity of the Internet and the rise of self-media have built a diversified, convenient and instant platform for colleges and universities to do a good job in education, teaching, propaganda and ideology, but at the same time it also brings challenges and problems of college network security and campus stability. Most emergencies in colleges and universities are caused by trivial incidents and are largely unpredictable. If they are put online through online channels, they will attract the attention of the majority of netizens in a short period of time and attract online public attention. Once it is not handled in a timely manner, it will affect the normal education and teaching of colleges and universities and the safety and stability of campuses, and it is likely to form major public opinion on a larger scale, affecting the harmony and stability of the local society. This article adopts the characteristics of the network public opinion of colleges and universities in Gansu Province. It analyzes the current situation and focuses on the countermeasures to deal with network public opinion caused by emergencies in colleges and universities, hoping to provide a reference for further promoting the level and effectiveness of network public opinion in response to emergencies in Gansu Province.
DEEPYANG at SemEval-2020 Task 4: Using the Hidden Layer State of BERT Model for Differentiating Common Sense

Introducing common sense to natural language understanding systems has received increasing research attention.To facilitate the researches on common sense reasoning, the SemEval-2020 Task 4 Commonsense Validation and Explanation(ComVE) is proposed.We participate in sub-task A and try various methods including traditional machine learning methods, deep learning methods, and also recent pre-trained language models.Finally, we concatenate the original output of BERT and the output vector of BERT hidden layer state to obtain more abundant semantic information features, and obtain competitive results.Our model achieves an accuracy of 0.8510 in the final test data and ranks 25th among all the teams.