Reviewerly/exHarmony huggingface dataset:
Expedition as an effective form of student research

The article considers school research expedition as one of the effective forms of research activity of students. Features of creation of scientific research expeditions in the Republic of Sakha (Yakutia) in the conditions of introduction of the federal state educational standard (FSES) of the second generation in general educational institutions are described. In connection with this, research expeditions have been organized in Yakutia in recent years to improve the quality of education and upbringing of the next generation. In research expeditions, students receive practical research skills. Research expedition is an effective form of research activity of students in preparation and selection of future profession, increase the quality of performance of educational programs, promotes intellectual self-development of young people.
Municipal management team in the system of methodological support of schools with low educational results

The article explores the possibilities of interaction between municipal and school management teams in solving topical issues of improving the quality of school education by the example of the implementation of regional and federal projects to overcome low educational results. Based on risk factors, a number of indicators were developed for the first time to monitor the effectiveness of project implementation. The principle of harmonization of management systems, the implementation of measures by the municipal team at all stages of the full management cycle, correlation and mutual complementation of the activities of management teams to improve educational results are defined as conditions for the achievement by the municipal education system of performance indicators enshrined in strategic and conceptual documents. The result of the study is the introduction of changes in the methodology and technology for the implementation of federal and regional projects for the transfer of schools in the Ryazan region to an effective mode of operation, taking into account changes in the implementation of relevant concepts and development programs.
Automatic Generation and Analysis of Role Relation Network from Emergency Plans

In order to improve the efficiency of emergency response and optimize the utilization of emergency resources, domain experts actively create role network of emergency response. Creating emergency role network manually is a time-consuming and labor-intensive task. An approach to extracting role networks from emergency plans is proposed, and then the extracted role relation network is made a quantitative analysis in this paper. First, role relation network is generated from emergency plan, which includes the emergency department and personnel are identified through a Bi-LSTM-CRF network, coreference resolution is implemented based on RoBERTa-E2E-Coref model, role relation is extracted based on the RoBRETa-CasRel model, and role relation network of emergency response is generated based on identified roles and their relationship. Second, role relation network from emergency plan with different levels were analyzed quantitatively by using the complex network analysis methods. Finally, experiment evaluation and a case study are given based on the real data sets, and the results show that the proposed approach can be used to assist emergency decision-makers to create role relation networks of emergency response. In addition, through the analysis of the extracted role relationship network, the quality of the emergency plan can be indirectly reflected.
NU HLT at CMCL 2022 Shared Task: Multilingual and Crosslingual Prediction of Human Reading Behavior in Universal Language Space

In this paper, we present a unified model that works for both multilingual and crosslingual prediction of reading times of words in various languages.The secret behind the success of this model is in the preprocessing step where all words are transformed to their universal language representation via the International Phonetic Alphabet (IPA).To the best of our knowledge, this is the first study to favorably exploit this phonological property of language for the two tasks.Various feature types were extracted covering basic frequencies, n-grams, information theoretic, and psycholinguisticallymotivated predictors for model training.A finetuned Random Forest model obtained best performance for both tasks with 3.8031 and 3.9065 MAE scores for mean first fixation duration (FFDAvg) and mean total reading time (TRTAvg) respectively 1 .
Formation of professional subjective activity of future teachers in the field of upbringing

The increased attention of the state and society to education as an integral part of the educational process at all levels of education actualizes the problem of the readiness of future teachers to implement educational tasks. To determine the prospects of this activity, the provisions of the modern theory of education have a significant place, which is the methodological basis for considering the role and place of the teacher and his subjectivity in the process of preparing for educational activities. In order to achieve a high degree of readiness for professional activity, it is necessary to have a certain personal, intellectual and activity potential, which means that personal and professional changes are an integral attribute of the development of professionally significant personality traits that should be included in the logic of the organization of the process of professional education in the academic and extracurricular components. The success of the educational activity of a novice teacher in the future largely depends on the student's activity in professional self-development during the period of study at the university. The readiness of teachers for educational activities is largely determined by the formation of professional subjective activity of the individual. Professional subjective activity is considered as the activity of a personality that develops and implements its subjectivity in the space of professional activity. Its main characteristics are uniqueness, activity, independence, responsibility, authorship of one's own life and one's own history, value relations, the ability to master one's own behavior and generate one's own behavior. For their formation, it is necessary to create special conditions in a pedagogical university: the organization of horizontal and vertical subjectsubject interaction; development of the mentoring system; development of the institute's life activity as a professional educational organization that creates a space for the accumulation of individual professional style and operational repertoire for solving professional tasks.
YouTube as a Learning Media for Music Creation

The development of information and communication technology in the generation of the industrial revolution 4.0 brings new challenges and possibilities in the world of education.One in every of them is the possibility for teachers to integrate generation into the studying method, in order that mastering effects can be more effective.The internet is part of the development of information and communication technology.Internet users in Indonesia mostly use the YouTube platform.In the world of education, YouTube is used as a learning to support the success of the learning process, the creative process of students in learning music.This article describes how YouTube can be a complementary and supporting media in learning to channel their interests and talents as an encouragement for students to create music.The purpose of writing this article is to describe the use of YouTube as a learning for music creation.The method used in this research is descriptive qualitative.The research subjects were students of class X MA Persis 31 Banjaran.The data obtained from this research is by interview, observation, and documentation.The results of the study reveal that learning music creation through YouTube is not only for learning in the form of learning videos but also as a forum to motivate students to practice and make or upload a music that we didn't expect that every student has a many good creations in distance learning.
Sketching a Linguistically-Driven Reasoning Dialog Model for Social Talk

The capability of holding social talk (or casual conversation) and making sense of conversational content requires context-sensitive natural language understanding and reasoning, which cannot be handled efficiently by the current popular open-domain dialog systems and chatbots.Heavily relying on corpus-based machine learning techniques to encode and decode context-sensitive meanings, these systems focus on fitting a particular training dataset, but not tracking what is actually happening in a conversation, and therefore easily derail in a new context.This work sketches out a more linguistically-informed architecture to handle social talk in English, in which corpus-based methods form the backbone of the relatively context-insensitive components (e.g.part-ofspeech tagging, approximation of lexical meaning and constituent chunking), while symbolic modeling is used for reasoning out the contextsensitive components, which do not have any consistent mapping to linguistic forms.All components are fitted into a Bayesian gametheoretic model to address the interactive and rational aspects of conversation. 1
Deep Neural Representations for Multiword Expressions Detection

Effective methods for multiword expressions detection are important for many technologies related to Natural Language Processing.Most contemporary methods are based on the sequence labeling scheme applied to an annotated corpus, while traditional methods use statistical measures.In our approach, we want to integrate the concepts of those two approaches.We present a novel weakly supervised multiword expressions extraction method which focuses on their behaviour in various contexts.Our method uses a lexicon of English multiword lexical units acquired from The Oxford Dictionary of English as a reference knowledge base and leverages neural language modelling with deep learning architectures.In our approach, we do not need a corpus annotated specifically for the task.The only required components are: a lexicon of multiword units, a large corpus, and a general contextual embeddings model.We propose a method for building a silver dataset by spotting multiword expression occurrences and acquiring statistical collocations as negative samples.Sample representation has been inspired by representations used in Natural Language Inference and relation recognition.Very good results (F1=0.8)were obtained with CNN network applied to individual occurrences followed by weighted voting used to combine results from the whole corpus.The proposed method can be quite easily applied to other languages.
PROJECT APPROACH AS A MODERN METHOD OF MANAGING THE SPHERE OF CULTURE IN THE CONDITIONS OF TRANSFORMATION OF RUSSIAN SOCIETY

The sphere of culture needs to be rethought, because everything is changing in connection with the development of information systems and the creation of a unified economic and socio-cultural system. Culture acts as a single resource in the development of socio-economic activity and human abilities. In the context of the transformation of Russian society, the preservation of cultural heritage and its development is possible within the framework of a well-thought-out cultural policy that has strategic goals for the long term, while culture is a factor in the development of both moral and spiritual potential and contributes to stability in the field of social, economic, political and social activities. In recent years, many cultural projects have been put into practice in Russia, which confirms the importance of the project approach, which contributes to the development of culture. With the active development of cultural activities, there is a lag in the development of the project base, there are shortcomings: there is not enough necessary information and scientific projects, research to train project managers.
A Study on Entity Linking Across Domains”:" Which Data is Best for Fine-Tuning?

Entity linking disambiguates mentions by mapping them to entities in a knowledge graph (KG).One important question in today's research is how to extend neural entity linking systems to new domains.In this paper, we aim at a system that enables linking mentions to entities from a general-domain KG and a domainspecific KG at the same time.In particular, we represent the entities of different KGs in a joint vector space and address the questions of which data is best suited for creating and fine-tuning that space, and whether fine-tuning harms performance on the general domain.We find that a combination of data from both the general and the special domain is most helpful.The first is especially necessary for avoiding performance loss on the general domain.While additional supervision on entities that appear in both KGs performs best in an intrinsic evaluation of the vector space, it has less impact on the downstream task of entity linking.
Importance of Software Support in Crisis Situations Decision-Making

The COVID-19 pandemic caused by the Sars-Cov2 coronavirus has affected all spheres of business like no crisis before, forcing business systems to adapt their business processes to the newly emerged business conditions.Rapid development in the field of information technologies has given rise to the development of new intelligent solutions that strongly support real-time monitoring, and decision-making based on accurate and timely information.The importance of fast data collection and their processing in real time is becoming increasingly important in modern business, as a factor that contributes to a timely response to changes in the business environment.In crisis situations, such as the global COVID-19 pandemic, the application of software tools, based on modern intelligent technological solutions, to support decision-making is an imperative.The aim of this paper is to show the importance and role of software support in crisis situations decision-making with emphasis on the COVID-19 pandemic.The paper is structured as follows: the first chapter discussed the importance of business decision-making, importance of software support in such decision-making, and the characteristics of decision support systems.The paper will also present the analysis of emergency situations and examples of information systems in different emergency systems.
Dual Discriminators Generative Adversarial Networks for Unsupervised Infrared Super-Resolution

The breakthrough of sensor resolution has always been focused on the computer vision area, which is an urgent need when infrared sensor technology progresses slowly. We propose a novel unsupervised infrared super-resolution (UISR) without high resolution ground truth and establish a fully unpaired generative adversarial framework to enrich the image details and improve the visual perception of human eyes aiming at the photoelectric characteristics of infrared images. In the process of SR, UISR corrects the abnormal pixel values, blurred edges, and mosaic effect by maintaining the image style uniformity and mining the texture distribution characteristics in the image domain. Specifically, the dual discriminator module is designed to enhance both global structures and local textures. The style discriminator captures the natural structure characteristics of large image patches to control the authenticity. In contrast, the texture discriminator captures the texture characteristics of small image patches to improve the detail generation performance. Besides, the content constraint module is designed to maintain the basic content of the image. Experiments show that, compared to the supervised algorithm, the proposed UISR presents more real SR infrared images and is simpler to generalize in higher scales beyond sensor resolution.
Optimized Squeezing Operation for Phase-Shift Keying Quantum State Discrimination

Many receiver designs have been studied in the past to discriminate Phase-Shift Keying (PSK) quantum states that are used to encode information before transmitting over the communication channel. Among many types of quantum states, there has been significant work on the use of coherent states for encoding information. Previous work has sought to improve the communication performance in terms of various metrics such as error probability of state discrimination and capacities by employing more complex quantum states such as squeezed-displaced states. One of the simplest receivers for state discrimination is the displacement receiver. However, our calculation demonstrates that when we use optimal parameters for a displacement receiver, squeezed-displaced states might not be necessary, and merely using coherent states suffice. We see no performance improvement in terms of probability of error of state discrimination as well as mutual information using displacement receivers when optimal squeezing parameters are used with squeezing operation on the transmitter side for BPSK and QPSK. In addition, we also study the receiver design scheme for QPSK modulation where squeezing is employed at the receiver side. We find that using squeezing operation on the receiver side just before detection provides an advantage in terms of increased mutual information for the low-photon regime compared to when no squeezing is used. For all other cases, squeezing offers no additional advantage.
Gender classification in classical fiction: A computational analysis of 1113 fictions

&lt;abstract&gt; &lt;p&gt;Recent decades have witnessed the rapid development of literary studies on gender and writing style. One of the common limitations of previous studies is that they analyze only a few texts, which some researchers have already pointed out. In this study, we attempt to find the features that best facilitate the classification of texts by authorial gender. Based on a corpus of 1113 classical fictions from the early 19&lt;sup&gt;th&lt;/sup&gt; century to the early 20&lt;sup&gt;th&lt;/sup&gt; century. Eight algorithms, including SVM, random forest, decision tree, AdaBoost, logistic regression, K-nearest neighbors, gradient boosting and XGBoost, are used to automatically select the features that are most useful for properly categorizing a text. We find that word frequency is the most important predictor for identifying authorial gender in classical fictions, achieving an accuracy rate of 92%. We also find that nationhood is not particularly impactful when dealing with authorial gender differences in classical fictions, as genderlectal variation is 'universal' in the English-speaking world.&lt;/p&gt; &lt;/abstract&gt;
The effect of Time Token Arends as cooperative learning types on the students’ speaking skills at eleventh grade of SMAN 1 Bandar Lampung

This research was aimed to find out the effect of Time Token Arends to students speaking skills aspects. This research applied qualitative and quantitative research by using the cooperative learning method. In taking the sample, the researcher used the purposive sampling technique. The number of the sample is 36 students at XI MIPA 1 SMAN 1 Bandar Lampung. The instrument of this research was an observation sheets, documentation and speaking test. There were 2 lesson plans and worksheets for the speaking test. The finding showed that there was a significant difference of students after being taught by using Time Token Arends strategy. Mean score of Pre-test was 58.7 and mean score of first Post-test was 69.1 and second Post-test was 76.1. Accent aspect increased 4.00, vocabulary aspect increased 3.33, comprehension aspect increased 3.34, fluency aspect increased 2.80, and grammar aspect increased 1.73.; it assumed that this technique has positive effect toward students speaking ability.
Controlling Formality in Low-Resource NMT with Domain Adaptation and Re-Ranking: SLT-CDT-UoS at IWSLT2022

This paper describes the SLT-CDT-UoS group's submission to the first Special Task on Formality Control for Spoken Language Translation, part of the IWSLT 2022 Evaluation Campaign.Our efforts were split between two fronts: data engineering and altering the objective function for best hypothesis selection.We used language-independent methods to extract formal and informal sentence pairs from the provided corpora; using English as a pivot language, we propagated formality annotations to languages treated as zero-shot in the task; we also further improved formality controlling with a hypothesis re-ranking approach.On the test sets for English-to-German and Englishto-Spanish, we achieved an average accuracy of .935within the constrained setting and .995within unconstrained setting.In a zero-shot setting for English-to-Russian and English-to-Italian, we scored average accuracy of .590for constrained setting and .659for unconstrained.
A SURVEY OF RETRIEVAL ALGORITHMS AND THEIR PARALLELIZATION IN LARGE-SCALE SYSTEMS

This article presented a survey of two well-known algorithms, TF-IDF and BM-25 methods, for document ranking on a single CPU and parallel processes via HPC. An amazon review dataset with more than two million reviews was measured to measure the rank parameters. We set up the number of workers for the parallel processing during the experiment, which we selected as one and three. Four benchmarks evaluated the preprocess and reading time, vectorization time, TF-IDF transformation time, and overall time. Results metrics have shown a significant difference in speed.
Difference Poetry Reading Skills Using Interactive Video Learning Media and Power Point Teaching Materials in Grade IV Elementary School Students

In this study, a problem was found, namely in Indonesian language learning where the poetry reading skills of fourth grade students at SD Negeri Gebangsari 01 were classified as low both in terms of rhythm, articulation. volume, expression, and kinesics or body movements. This research is a quantitative research that includes a true experimental design with a posttest only control group design type. This study aims to determine differences in poetry reading skills using interactive video learning media and power point teaching materials for fourth grade students at SD Negeri Gebangsari 01. The results of data analysis Independent Sample T-Test hypothesis test proves that there is a difference in terms of Lower and Upper respectively. negative values, namely lower -22.388 and upper -12,128. while Sig (2-tailed) is worth 0.000.
Post EraMethod in Teaching Indonesian Language and Literature in Elementary School

This study aims to explain the Post Method era in teaching language and literature in elementary school. This study uses a qualitative approach with library study methods or Library Research. Library studies as a data collection technique by conducting study studies on books, literature-literature, records, and reports that have to do with problems solved. This study utilizes journals, materials and relevant information to be collected, read and studied, recorded as guidelines or reference sources. The literature study method in this study can be used as data and data sources regarding the topic of problems. In the post-method era, language teaching is done not only based on certain methods. Language teaching can adopt several different methods and techniques at the same time. So, we can say that even though there are still methods in the post-method era, but we don't depend on certain methods. The first post-method era is not an era where no method is used in Indonesian language and literary teaching. Second, the method used in language teaching can be a combination of several methods in accordance with the teaching needs of Indonesian language and literature.