Reviewerly/exHarmony huggingface dataset:
‘가장, 더, 덜’의 코퍼스 분석과 어휘 교육 방안 연구

The purpose of this study is to investigate on usage for 'Kajang, Deo, Deol' of degree adverbs and extract a list of co occurrent words with 'Kajang, Deo, Deol by the part of speech presented in Korean University textbooks for Korean learners. For this study, the corpus was analyzed through classifying 59 Korean university textbooks to extract co occurrent words named predicates by the part of speech at different level of textbooks. The result shows that 'Kajang' and ‘Deo’ has a higher frequency of cooccurrence with gradable antonym adjectives in each level. In contrast, ‘Deol’ has rare cooccurrence with adjectives. In the aspect of usage with verbs of ‘Kajang’ and ‘Deol’ is highly collocated with ‘like’ in every level. Especially, ‘Kajang’ is collocated with some psychological verbs. ‘Deo’ is highly collocated with some kind of action verbs intermediate and advanced level. In the aspect of usage with adverbs, ‘Kajang’ is collocated with ‘a lot(mani)’, ‘Deo’ is collocated with ‘a little(jom)’ in beginning and ‘jeomjeom, jogeum, holshin’ in intermediate and advanced. In the aspect of usage with nouns ‘Kajang’, ‘Deol’ is collocated with ‘static noun’ but ‘Deol’ has rare frequencey of ‘noun’. Noteworthy results are that ‘Deo’ and ‘Deol’ has some marked meaning when collocated with special action verbs. Deo has a marked meaning of ‘ strengthening’ and 'Deol' have a marked meaning of 'incompletion'. In hence, I will also present some possibility of application for Korean Language Education for Korean learners based on Corpus analysis. Eventually I expect that the results of this study will be applied to teaching methods of the degree adverbs 'Kajang', 'deo', 'deol' for Korean learners, and construction of Korean textbooks.
Regularized Submodular Maximization at Scale

In this paper, we propose scalable methods for maximizing a regularized submodular function $f = g - \ell$ expressed as the difference between a monotone submodular function $g$ and a modular function $\ell$. Indeed, submodularity is inherently related to the notions of diversity, coverage, and representativeness. In particular, finding the mode of many popular probabilistic models of diversity, such as determinantal point processes, submodular probabilistic models, and strongly log-concave distributions, involves maximization of (regularized) submodular functions. Since a regularized function $f$ can potentially take on negative values, the classic theory of submodular maximization, which heavily relies on the non-negativity assumption of submodular functions, may not be applicable. To circumvent this challenge, we develop the first one-pass streaming algorithm for maximizing a regularized submodular function subject to a $k$-cardinality constraint. It returns a solution $S$ with the guarantee that $f(S)\geq(\phi^{-2}-\epsilon) \cdot g(OPT)-\ell (OPT)$, where $\phi$ is the golden ratio. Furthermore, we develop the first distributed algorithm that returns a solution $S$ with the guarantee that $\mathbb{E}[f(S)] \geq (1-\epsilon) [(1-e^{-1}) \cdot g(OPT)-\ell(OPT)]$ in $O(1/ \epsilon)$ rounds of MapReduce computation, without keeping multiple copies of the entire dataset in each round (as it is usually done). We should highlight that our result, even for the unregularized case where the modular term $\ell$ is zero, improves the memory and communication complexity of the existing work by a factor of $O(1/ \epsilon)$ while arguably provides a simpler distributed algorithm and a unifying analysis. We also empirically study the performance of our scalable methods on a set of real-life applications, including finding the mode of distributions, data summarization, and product recommendation.
Development of research competence: a task approach

In the article the relevance of the development of the student's research competence in the context of the requirements of current federal state educational and professional standards is proved. The purpose of the article is to prove the possibility of developing research competence by solving research problems. Methods of systematic, competent and person-oriented approaches applicable to development of trainees’ research competence are used for analysis. The concept of research competence is considered, the list of research skills as its constituent elements is defined, the levels of skills formation are described. The article considers various approaches to the definition of the concept «research task» provides an overview of the main scientific ideas about this type of task. Essential distinctive characteristics of research tasks are presented. Species and level classifications of research tasks are considered. Being based on the analysis, the following distinctive features of research problems are highlighted: the problematic nature, the development of the researcher's resources, the subjective and objective difficulty of solving the problem, the presence of normative and real complexity of the problem, the need for a deep study of the solution of the problem, the novelty of the solution, the variability of the solution, the insignificant dependence of the development of research skills on the number of solved problems. The article describes the stages and algorithms for solving research problems. The pedagogical practice of learning the skill of solving research problems at a university has been generalized. The author focuses on the possibility of using research tasks to develop research competence in all forms of educational activity in higher school (theoretical and practical training, performing qualification work at different stages of training). It was concluded about the role of research tasks in the development of students’ research competence and the assumption that the use of multi-level research tasks will create conditions for the effective development of research competence.
A Natural Logic for Artificial Intelligence, and its Risks and Benefits

This paper is a multidisciplinary project proposal, submitted in the hopes that it may garner enough interest to launch it with members of the AI research community along with linguists and philosophers of mind and language interested in constructing a semantics for a natural logic for AI. The paper outlines some of the major hurdles in the way of “semantics-driven” natural language processing based on standard predicate logic and sketches out the steps to be taken toward a “natural logic”, a semantic system explicitly defined on a well-regimented (but indefinitely expandable) fragment of a natural language that can, therefore, be “intelligently” processed by computers, using the semantic representations of the phrases of the fragment.
A Knowledge-Enhanced Pretraining Model for Commonsense Story Generation

Story generation, namely generating a reasonable story from a leading context, is an important but challenging task. In spite of the success in modeling ﬂuency and local coherence, existing neural language generation models (e.g., GPT-2) still suffer from repetition, logic conﬂicts, and lack of long-range coherence in generated stories. We conjecture that this is because of the difﬁculty of associating relevant commonsense knowledge, understanding the causal relationships, and planning entities and events with proper temporal order. In this paper, we devise a knowledge-enhanced pretraining model for commonsense story generation. We propose to utilize commonsense knowledge from external knowledge bases to generate reasonable stories. To further capture the causal and temporal dependencies between the sentences in a reasonable story, we employ multi-task learning which combines a discriminative objective to distinguish true and fake stories during ﬁne-tuning. Automatic and manual evaluation shows that our model can generate more reasonable stories than state-of-the-art baselines, particularly in terms of logic and global coherence.
Addictive Parameter In Ensemble Technique & Implementation Using Flask Server

Exceeding use of screen has completely switched the teens routine life who are addicted with social media and other electronic accessories, which results in psychological disorder like anger, stress, depression, anxiety etc., The addiction data set  applied with some algorithm like Random forest, decision tree and so on. The Ensemble Technique bagging and voting classifier are used for better prediction. The bagging classifier which combines the decision tree and random forest, the voting classifier which compares the bagging classifier and gradient booster. Among the two classifier bagging classifier gives the best prediction result. Implementation proceeded with webpage, Flask server and python model using logistic regression model. In future the app can be used as a standalone system, which now works in local server.
An efficient deep learning based fog removal model for multimedia applications

In the present era of technology, several applications such as surveillances systems, security and object recognitions mainly depend on the contents of an image. In this context, the hazy/foggy environment and/or other adverse climatic conditions degrade the image contents that severely influences the result of related applications. The effective haze removal from a single image decides the reliability of these systems. The convolutional neural network (CNN) based techniques are widely used among the available image dehazing methods. However, in CNN based image dehazing techniques, the robustness and accuracy of the learning models are based on the improvement of transmission estimation without giving much concern to the atmospheric light. Therefore, in this paper, the accurate and efficient deep CNN based image dehazing model, which take care the minute information elements during the learning of feature map, is proposed. Besides, the proposed model handles the hallo, blocking artifacts, retainment of fine edges, white region handling, and color fidelity problems, which are primarily responsible for image sharpening and structural stability. For the evaluation of proposed method, the extensive experiments on synthetic and real world images are performed using existing and proposed techniques. The qualitative and quantitative analysis of experimental result shows that the proposed model is more efficient over the existing prior-based and learning-based methods.
COMPETENCE BASED APPROACH AND KEY COMPETENCIES IN THE MODERN FOREIGN LANGUAGE EDUCATIO

The modern era of educational development faces large-scale problems that are emerging in society. This fact affects the state of education, which cannot at the moment be limited to the transmission of sociocultural norms. The current education system needs to develop the individual’s capacity to find and fill socio-economic and socio-psychological niches. This ability can enable individuals to successfully realize themselves, be ready to cater for the demands based on positive communication and the principle of social responsibility. The competence based approach is proved to be an effective solution to all the abovementioned issues. The article considers the competence based approach in modern education, the definitions of competence based approach, competences and competencies presented by foreign, Russian and domestic scientists. Classifications of key competences put forward by various scholars in the field of education are also described.
PENERAPAN TINGKAT MINAT BACA SISWA SD INPRES 037145 MENGGUNAKAN K-MEANS

Grouping students' reading interest based on the criteria for books read, books borrowed, and also considering the number of books available can help in the process of adding to the existing book collection in the library. One way to manage this data is by using data mining by utilizing the K-Means method. Book data are grouped into 3 clusters, namely priority, consideration, and not prioritization in planning for additional book collections. The result of this research is that the cluster with the largest value in the final centroid is the recommended cluster in planning to add to the book collection.
간접 복수 표지의 의미적 기능에 대한 고찰

This study investigates the semantic functions of Korean extrinsic plural marker(EPM) -tul and the factors that can influence its distributivity in the sentence interpretation. There has been a consensus that EPM -tul distributes the element it is attached to over each of the agents denoted by subject plural nouns, however, which factors can affect its semantic functions such as distributivity and exhaustivity and which interpretation can be evoked in accordance with them have been no paid attention.To validate the relevant previous analyses and speculate the semantic functions based on them, the study analyzed how -tul that appears in various positions within a sentence works in the sentence interpretation. The result showed that the positions(verb, direct object, indirect object, adverb) where -tul is located and the features of the elements it is attached to (countable nouns and non-countable nouns) varied the way -tul evokes distributivity in the sentence interpretation. As a result of analyzing possible factors that can influence the functions of EPM, firstly, it was found that world knowledge related to distributed elements can weaken distributivity. Secondly, agents constrained by contexts or a small number of the agents can evoke exhaustivity. Lastly, the distributive relation between plural agents and the elements -tul is attached to is influenced by contextual information. The definiteness of distributed elements was also observed to facilitate the meaning of event plurality. The results showed Korean EPM -tul is context-dependent and can be affected by linguistic or non-linguistic information.
Deep Learning Model Based on Mobile-Net with Haar like Algorithm for Masked Face Recognition at Nuclear Facilities

During the spread of the COVID-I9 pandemic in early 2020, the WHO organization advised all people in the world to wear face-mask to limit the spread of COVID-19. Many facilities required that their employees wear face-mask. For the safety of the facility, it was mandatory to recognize the identity of the individual wearing the mask. Hence, face recognition of the masked individuals was required. In this research, a novel technique is proposed based on a mobile-net and Haar-like algorithm for detecting and recognizing the masked face. Firstly, recognize the authorized person that enters the nuclear facility in case of wearing the masked-face using mobile-net. Secondly, applying Haar-like features to detect the retina of the person to extract the boundary box around the retina compares this with the dataset of the person without the mask for recognition. The results of the proposed modal, which was tested on a dataset from Kaggle, yielded 0.99 accuracies, a loss of 0.08, F1.score 0.98.
International comparative analysis of national state electronic educational platforms for schoolchildren

Developing electronic educational platforms for organizing the education of schoolchildren in different countries are considered. The purpose of the study was to conduct a comparative analysis of national electronic educational platforms by parameters: the organizational structure of electronic educational platforms, the functionality of user interfaces, educational data analytics programs, the possibilities and directions of using the results of educational data analysis. The paper actualizes the issues of the need to develop a new field of pedagogical knowledge – “Pedagogy based on data”. The new field of knowledge is aimed at the development of methodology and technologies for the analysis of educational data, which is accumulated in the form of students’ “digital traces” on electronic educational platforms.
MODERN APPROACHES IN ANDROID DEVELOPMENT ON THE EXAMPLE OF THE TO-DO APP

The article discusses modern approaches and technologies in the development of android applications. These approaches have the following advantages: the ability to unit test the application, support a large project for a long time without rewriting the old code base. And they also provide the readability of the entire code and the extensibility of the project, with the ability to add new modules to it.
Scientific and Methodological Support for Modern Educational Technology Introduction into the Educational Process

In the article the authors consider opportunities for scientific and methodological support of contemporary education digitization. The purpose of the article is to identify scientific and methodological support resources for developing specific recommendations to teachers on tackling education-related problems in the digital educational environment. When designing scientific and methodological support tools meant to facilitate introduction of modern educational technologies into the advanced teacher training process, the authors were basing on the principles of globalization and regionalization, technology continuity and discreteness, flexibility and availability. Consideration of the above mentioned principles permits to: introduce technologies applied in the global educational space, taking into account regional potential and student needs; select and combine individual factors of pedagogical technologies being based on assessment of their didactic efficiency under the conditions of a concrete educational process; adapt the technologies to teaching conditions, student cohort, budget, time and other circumstances in a timely and mobile manner. The article is meant for the academic teaching staff of institutes of supplementary teacher education, postgraduate and external PhD students, teachers and all those who take interest in problems of contemporary education.
Serverless Apps: A Google-drive-based Sacco Management System

This paper describes a cloud-based SACCO Management Application System. It provides the design parameters, the programming features and the deployment process of the system. The motivation is to avoid server-based applications which require heavy investments and instead ride on the secure google cloud-based services for the development and deployment of the system. Google Drive was chosen as the hosting web server, where the Google Sheets, Docs, and Forms were customized to provide safe on-site data and templates for data capture and processing. While the system is entirely dependent on google cloud apps, the user is provided with a mobile App which directly connects to the google sheets for individualized reports and formatted member information. The user only needs to use a device which senses gmail login in order to provide SACCO information at a click of a button. Both data capturing and visualization processes are managed in a single web interface, bringing easy-to-use benefits to end users. The concept has been implemented with an existing SACCO and has provided adequate level of automation to the SACCO management. The SACCO management board is now able to track in real time the activities of the SACCO and retrieve ready-made reports at a click of a button. The system developed in this research has potential applications in helping upcoming SACCOs implement secure Information Systems for Data capturing, client management and instant provision of reports without being worried about server space and domain name costs.
The Security System For Web-Based Lontar Images in JPG Format Using The Rivest Shamir Adleman

The Security System For Web-Based Lontar Images in JPG Format Using the Rivest Shamir Adleman Method is a system that is basically used to secure an image in JPG format, which after the encryption process will be converted into txt. Where the system functions to secure lontar by using an encryption process using a cryptographic technique, namely Rivest Shamir Adleman (RSA) which is expected to help the public to maintain information or documentation and evidence of important events that occurred in the past.
Unchiku Generation with Moving Illustration Using Kabuki Knowledge

We developed an explanation-generation system based on narratology.We also developed an unchiku generation system as an application.After creating a prototype, we then considered a new system that would combine the unchiku generation system with an animation system.We implemented the animation system in our kabuki study.This paper considers the possibilities of the unchiku generation system.
UoB at ProfNER 2021: Data Augmentation for Classification Using Machine Translation

This paper describes the participation of the UoB-NLP team in the ProfNER-ST shared subtask 7a.The task was aimed at detecting the mention of professions in social media text.Our team experimented with two methods of improving the performance of pretrained models: Specifically, we experimented with data augmentation through translation and the merging of multiple language inputs to meet the objective of the task.While the best performing model on the test data consisted of mBERT fine-tuned on augmented data using back-translation, the improvement is minor possibly because multi-lingual pre-trained models such as mBERT already have access to the kind of information provided through backtranslation and bilingual data.
Usare RDA per gli authority record nel catalogo dell’Associazione IRIS

The essay intends to examine the approach to the use of RDA (Resource Description and Access) on a selection of authority record from the catalogue of IRIS - Associazione di biblioteche storico-artistiche e umanistiche dell’area fiorentina. From this application, we highlight the enrichment, the enhancement and the enlargement of the data of the authority record. The RDA-MARC 21 Authority mapping and the example will explain the process that determined the particular application choices.
Multi-Component Liquid Analyzer During Steady-State and Dynamic CO2 Capture Operations: Near Real-Time Feedback in Industrialized Environment

ION implemented an online liquid monitoring system for real-time analysis of solvent, water and carbon dioxide composition. ION’s Multicomponent Liquid Analyzers (MLA) were installed on both rich and lean solvent lines at TCM in Norway and transmitted data at near-real- time. When compared with lab analysis, the MLA was within 1.5% during steady-state as well as dynamic operations. With these promising results in the initial pilot release, ION believes the MLA is a useful and important tool for both safe monitoring liquid compositions as well as providing a mechanism to automate and optimize the control of the process. Overall, the fast-tracked development from lab to the installation of the MLAs at the industrialized TCM-site adjacent to Statoil’s largest refinery has been remarkably successful.
Metadata Term Extraction for Research Data Management and Sharing

This article set out to design metadata management model and metadata terms and controlled vocabulary for successful management, sharing, and reuse of research data. We suggest three-layer metadata model for research data and repository management, and design metadata terms for each layer accordingly. For collections, items and files, we mostly use terms from DCMI and DataCite schema; for the repository itself, we use RIF-CI and re3data.org schemas. The results of this study can help researchers and organizations take a system approach to establish a metadata schema for data storage and reuse. It can further be applied to integrated management and sharing of research data.