Reviewerly/exHarmony huggingface dataset:
Optimizing The Implementation Of University Digitalization Practices

The process of university digitalization at the present stage includes an information educational environment, electronic office management, financial reporting, various information systems and communication tools.The optimization of university digitalization processes involves the use of the single digital platform for all information processes and university's departments, which provides direct document exchange between the systems.The linking element of digital space formation is, in our opinion, electronic document management.The purpose of the study is to analyze the practice of introducing information systems and technologies into the work of universities, identifying legal and organizational problems arising in this regard, determining the optimal conditions for the introduction of electronic document management.The study analyses the experience of implementation of different electronic document interchange systems (EDMS) as well as the comparison of approaches devoted to electronic document management implementation in other universities.Therefore, EDMS has been chosen.The modeling of the system for the main divisions of the university was carried out using the example of several groups of documents.Experimental approbation of electronic document management in university is implemented.The result of the study is the reasoning of need to develop mutually integrated systems, which model the work of university divisions, branches.The study found that important problems of optimizing the implementation of digitalization practices in universities lie in the legal framework.The argument was made for the internal regulation developing, which, if possible, exclude the duplication of paper and electronic document interchange and parallel maintenance of several information systems.
Folklore and It’s Effect on Student’s Ability In Reading Narrative Text: a Systematic Literature Review

This study describes the improvement of narrative text reading skills using folklore. The method used is a systematic literature review (SLR). This article provides a systematic review of journals discussing folklore in reading narrative texts. Search using Google Scholar, Science Direct.com, and JSTOR for ten years (2011-2021). After being selected, observation found ten articles to be eligible for analysis. The results showed that folklore could significantly improve students' ability to read narrative texts. Penelitian ini bertujuan untuk mendeskripsikan peningkatan keterampilan membaca teks narasi dengan menggunakan cerita rakyat. Metode yang digunakan adalah systematic literature review (SLR). Artikel ini memberikan tinjauan sistematis terhadap jurnal yang membahas penggunaan cerita rakyat dalam membaca teks naratif. Pencarian menggunakan Google Scholar, Science Direct.com, dan JSTOR selama sepuluh tahun (2011-2021). Setelah diseleksi, sepuluh artikel yang ditemukan memenuhi syarat untuk dianalisis. Hasil penelitian menunjukkan bahwa penggunaan cerita rakyat secara signifikan dapat meningkatkan kemampuan siswa dalam membaca teks naratif.
Transfer Learning with Social Media Content in the Ride-Hailing Domain by Using a Hybrid Machine Learning Architecture

The analysis of the content of posts written on social media has established an important line of research in recent years. The study of these texts, as well as their relationship with each other and their dependence on the platform on which they are written, enables the behavior analysis of users and their opinions with respect to different domains. In this work, a hybrid machine learning-based system has been developed to classify texts using topic modeling techniques and different word-vector representations, as well as traditional text representations. The system has been trained with ride-hailing posts extracted from Reddit, showing promising performance. Then, the generated models have been tested with data extracted from other sources such as Twitter and Google Play, classifying these texts without retraining any models and thus performing Transfer Learning. The obtained results show that our proposed architecture is effective when performing Transfer Learning from data-rich domains and applying them to other sources.
Domain Semirings United

Domain operations on semirings have been axiomatised in two different ways: by a map from an additively idempotent semiring into a boolean subalgebra of the semiring bounded by the additive and multiplicative unit of the semiring, or by an endofunction on a semiring that induces a distributive lattice bounded by the two units as its image. This note presents classes of semirings where these approaches coincide.
Teaching Methods for Modeling the Image of Territory in a Media Text: The Problem of Meaning Formation

The purpose of the article is to summarize the methodological experience of work on the value-semantic component of modeling the media image of territory in the process of creating a media text of different genres and designs, to characterize the pedagogical technologies of teaching text construction using conceptual representations of society, its cultural memory.The article presents the characteristics of methodological materials on the formation of the competence of the media text author working with the territory's media image used in the ours of training "Journalism", "Advertising and Public Relations" -the bachelor's degree, the master's degree.Cognitive means of a media text addressed to the sociocode of culture have been highlighted.Using them, the textured material is percepted and processed in modeling the media image of a country or a region.Active and interactive teaching methods focused on reflection and conscious use of these tools in the media text author's creative activity have been structured.The authors propose several tasks for active, problem-based learning and articulate the culturological model of education in forming professional competencies in modeling a media image, which replenishes the educational environment with sociocultural meanings characteristic of a person's territory.
The Force of Habit: Examining the Status Quo Bias for Using Mixed Reality in Patient Education

Using mixed reality (MR) glasses for preoperative patient education (PPE) can help patients understand the purpose and risks of surgical procedures through informative visualizations.However, patients tend to be critical regarding the use of MR glasses in healthcare and often prefer the status quo of healthcare services provided.This study explores the resistance to MR technologies in PPE through the lens of the status quo bias theory by surveying n = 171 participants.We conducted a fuzzy set qualitative comparative analysis revealing configurations that provide a typological understanding of patient resistance.This allows healthcare stakeholders to take more targeted interventions to promote MR adoption.Notably, the results indicate that healthcare providers need to be transparent in communicating the benefits and drawbacks of using MR, as uncertainty costs are the main driver of resistance to MR glasses in PPE.
THE USE OF CLOUD TECHNOLOGIES IN EDUCATIONAL PROCESS OF PEDAGOGICAL UNIVERSITIES

The article deals with the use of cloud technologies in the organization of independent activities of University students. This problem is particularly relevant at present due to the significant increase in the hours allocated for independent work of students at universities in Ukraine. There are many technological tools for effective organization of independent activities of students, one of which can be considered cloud technologies, as the most popular in the modern world, due to its advantages: they can be applied in the educational process not only for the organization of independent work (or distance learning) – versatility; ability to work anywhere (where there is Internet access) and at any time-versatility; reduced financial costs for training – cost-effectiveness; reach a large number of trainees-progress in learning; allow you to use a wide variety of forms of learning and types of control; allow you to release creative thinking (Sway, DropBox Paper). The use of cloud-based data storage helps each student create their own personal cloud-oriented learning environment during the learning process (personal cloud-oriented learning environment). Therefore, it is important to teach students how to use cloud services correctly at the initial stages of University education, as well as to familiarize them with the diverse functionality of modern cloud software products. The modern labor market places high demands on the level of training of modern personnel. As statistics show, one of the most popular specialists are specialists in the field of cloud technologies. If we want our graduates to be competitive in today's society, we need to train them in the latest technologies and the ability to use these skills in their future professional activities. Thus, the main task of a modern school of higher education is to cultivate a highly qualified, competitive specialist who is able to improve their professional level and update their knowledge and skills. Using the latest digital technologies in the educational process, you should not underestimate the role of the teacher in the educational process. Therefore, it is obvious that the future of the education system is in the use of a combined approach (Blended learning) to learning.
RTI metoda jako způsob digitalizace kulturního dědictví

Current technological developments offer an inexhaustible number of procedures for digitization. However, technological equipment intended for teams in professional laboratories reaches price levels that cultural institutions often do not have enough finances. Procedures and methods using equipment, which institutions often already own or are not so expensive to acquire, come to the fore. One of them is the RTI (Reflectance Transformation Imaging) method, which creates a spatial relief composed of a sequence of images with visible lighting. The RTI method is very successful in depicting illegible or wiped details and is already widely used in archaeology.
Towards Non-Linear Social Recommendation Using Gaussian Process

Recent research on recommender systems has proved that by leveraging social network information, the quality of recommendations can be evidently improved. Traditional social recommendation models typically <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">linearly</i> combine social network information. For instance, matrix factorization based models linearly combine latent factors of relevant users and items. However, in practice, the multifaceted social relations are so complex that simple linear combination may not be able to reasonably organize such information for accurate social recommendation. On the other hand, existing deep learning based non-linear methods lack systematic modeling of user-item-friend relations. To handle these issues, we propose a novel, non-linear latent factor model for social recommendations leveraging Gaussian process. By introducing a social-aware covariance function, we organize individual users’ past feedback, as well as the associated social information (e.g., friends’ feedback to the same items) into a covariance matrix, which non-linearly and systematically learns the complex interactions among users, their interacted items and their friends’ opinions. A stochastic gradient descent based optimization algorithm is developed to fit the model. Extensive experiments conducted on three real-world datasets demonstrate that the proposed model outperforms the state-of-the-art social recommendation models and Gaussian process based models.
The Organization’s Sustainable Work Stress and Maladjustment Management Plan by Predicting Early Retirement through Big Data Analysis: Focused on the Case of South Korea

The purpose of this study is to verify the predictive model of early retirees’ responses to work stress and maladjustment to the company by utilizing big data analytics and to extract the reasons for early retirement from the personnel information. Company A’s personnel information of employees working in the company for 10 years was used, K-Nearest Neighbor (K-NN) algorithm was used to verify the predictive model of early retirees, and Decision Tree Analysis algorithm was used to extract the causing factors. According to the analysis results, first, the verification of the predictive model of early retirees based on the personnel information data showed 98% accuracy. Second, among the personnel information items, the ranking of items with high relevance for early retirement was the distance between the company and the residence (first place), the recent promotion history (second place), and whether or not to have the license (third place) out of a total of 18 items. The results of the analysis conducted in this study suggest that HRD intervention is required in the provision of problem-solving solutions involved in the HRM field, which is expected to be effective as a basic diagnostic tool for HR diagnosis involving HRD and HRM. In addition, this study may provide a detailed analysis of early retirement due to work stress and maladjustment of young people.
Classification of $ \mathbf{(3 \!\mod 5)} $ arcs in $ \mathbf{ \operatorname{PG}(3,5)} $

The proof of the non-existence of Griesmer $[104, 4, 82]_5$-codes is just one of many examples where extendability results are used. In a series of papers Landjev and Rousseva have introduced the concept of $(t\operatorname{mod} q)$-arcs as a general framework for extendability results for codes and arcs. Here we complete the known partial classification of $(3 \operatorname{mod} 5)$-arcs in $\operatorname{PG}(3,5)$ and uncover two missing, rather exceptional, examples disproving a conjecture of Landjev and Rousseva. As also the original non-existence proof of Griesmer $[104, 4, 82]_5$-codes is affected, we present an extended proof to fill this gap.
THE EFFECTIVENESS OF MAKE A MATCH METHOD IN IMPROVING STUDENTS’ WRITING SKILLS

This research aimed to explain how the use of “Make a Match Method” was able to improve the students’ writing descriptive text view from content aspect and explain how the use of “Make a Match Method” was able to improve the students’ writing descriptive text view from grammar aspect. The researcher used a pre-experimental design with one group pre-test and post-test design. The population was the seventh-grade students of one of junior high schools in Gowa which consisted of one class. The sample was taken by total sampling technique and the total number of samples was 28 students. It employed six meetings which writing test as the instrument. The research findings indicated that the use of “Make a Match Method” could improve the students’ writing skill view from content aspect and grammar aspect. It was proven by the students’ mean score in post-test (75.36) improved 25.6% from the pre-test mean score (60) with t-test 25.545 and t-table 2.052 where (25.545 &gt; 2.052). It was improved because the t-test was higher than t-table. It meant that there was significant difference of the students’ writing descriptive text before and after being taught through Make a Match Method.
Nanosyntactic Analysis of Turkish Case System

This paper takes two challenging characteristics of the Turkish case system and shows that a nanosyntactic analysis can cover both. The first puzzle is that some cases, namely ACC and GEN, in Turkish show alternations between specific and non-specific forms, while other cases like DAT and INS do not. The second puzzle concerns containment relations in morphology. Caha (2009) proposes that cases stand in a containment relation. In some languages like Estonian, Tocharian, and Vlax Romani, the ACC form serves as the foundation of the oblique cases. The puzzle is that in Turkish, the morphological containment holds only for ACC and GEN, but not for ACC and the other obliques. The comparison leads us to expect that the INS in Turkish could be *adam-ı-la, with the ACC marker to the left of -la. Interestingly, this expectation fails precisely in those cases which do not distinguish specific and non-specific forms. We propose a solution to both of these puzzles within the Nanosyntactic framework. The main idea is that Turkish nouns and cases can be composed of smaller, sub-morphemic features. These features allow specificity information to be encapsulated within the noun itself, rather than the case as previously suggested by Öztürk (2005).
Mineralogical and geochemical specificity of carbonaceous rocks from the area of Ust'-Kara astrobleme (Pay-Khoy)

We studied Upper Paleozoic (P1pt-ng) carbonaceous shales and siltstones from the area of the Ust'-Kara astrobleme (PayKhoy). We analyzed mineralogical and geochemical features of carbonaceous rocks of the target in the vicinity of the Ust'-Kara astrobleme event using a complex of modern methods to identify possible mobilization, redeposition and concentration of ore substance under intensive post-impact hydrothermal activity. Geochemical features of carbon deposits, altered by post-impact hydrothermal processes in the vicinity of the Ust'-Kara impact structure, have been determined. We found anomalous contents of Ti, Mn, Cr, Zr, Ni, Li, Co, Sc and REE. Inherent rare metal and rare earth minerals (monazite, florensite), sulfides (pyrite, chalcopyrite, marcasite, sphalerite), apatite, barite, anatase, chrome spinels were diagnosed.
Determining the Number of Topics to Retain using Tools from Factor Analysis

Abstract Determining the optimal number of topics to retain in the conduct of topic modeling (TM) has received much attention over the last decade. Despite this work, issues remain regarding the best methods to use for making such determinations. Approaches involving the use of relatively simple statistics, most notably perplexity, have proven to be somewhat inconsistent. Recently, researchers have suggested the use of change in perplexity scores as a useful heuristic for determining the optimal number of topics to retain. The current study builds on this earlier work by assessing the utility of several methods borrowed from factor analysis and applied to statistics commonly used in topic modeling, including perplexity and Alpha. These new approaches are applied to several textual datasets and compared with more traditional methods for determining the number of topics to retain. Results of these analyses demonstrate that application of these methods borrowed from factor analysis does appear to be effective for identifying the number of topics to retain.
Immersive Technologies in 5G-Enabled Applications: Some Technical Challenges of the Novel Usage Models

5G next-generation networking paradigm with its envisioned capacity, coverage, and data transfer rates provide a developmental field for novel applications scenarios. Virtual, Mixed, and Augmented Reality will play a key role as visualization, interaction, and information delivery platforms. The recent hardware and software developments in immersive technologies including AR, VR and MR in terms of the commercial availability of advanced headsets equipped with XR-accelerated processing units and Software Development Kits (SDKs) are significantly increasing the penetration of such devices for entertainment, corporate and industrial use. This trend creates next-generation usage models which rise serious technical challenges within all networking and software architecture levels to support the immersive digital transformation. The focus of this paper is to detect, discuss and propose system development approaches and architectures for successful integration of the immersive technologies in the future information and communication concepts like Tactile Internet and Internet of Skills.
Real-Time Face Mask Detection to Prevent COVID-19 in Confined Spaces

In this pandemic, it is getting more and more challenging to keep track of people wearing masks regularly.We cannot solely depend on human efforts to take care of this task.Therefore we need to develop software that can automatically detect whether any given person is wearing a mask or not.In this time of Covid-19 pandemic, it is of utmost importance that we all use masks regularly.But there are always exceptions, and only manual human efforts are meaningless to track who are not wearing masks.Therefore there is a need to develop software that can detect if a person is wearing a mask or not automatically.Currently, face recognition field has seen many challenges and has evolved much.New and more accurate algorithms are being derived by using convolutional architectures.Convolutional architecture also has the benefit of its ability to extract pixel details.Fully convolutional architecture is used for training so that faces are segmented out of the image semantically.We can find whether a person is using a mask not or adequately by feature detection and feature extraction.For accurate model creation, a dataset of morphed images with veneers can be used by the face mask detector.Thus, the created model will be computationally efficient.This will also be easily deployable because it will use MobileNetV2 architecture (Google coral, Raspberry Pi, etc.).Due to Covid-19 pandemic, face mask detection is required, and this framework can be used for that in real-time applications.This project can be used at public places like airports, schools, train stations, workplaces and bus stops by merging with embedded applications.This will lead to a safer environment in pandemic times.This identification process will help us classify individuals by reducing the number of manpower required.
A Research Synthesis on L2 Simplified Chinese Reading among Adults: Research and Pedagogical Implications

Even though there is still a dearth of scholarship in L2 simplified Chinese reading among adults, a growing body of research has contributed to this area to examine L2 Chinese reading process and performance.Due to this advancement in current literature, it is imperative to reflect on what has been researched in L2 Chinese reading in recent years and shed light on potential future research directions and pedagogical practices.To fill this gap, a qualitative analytic method was adopted to synthesize 25 selected studies (2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018) in L2 simplified Chinese reading among adult learners.Using analytic coding to identify emergent patterns regarding the research questions, methodologies, findings, and research implications, this study proposes that scholars interested in adult L2 Chinese reading conduct research looking at L2 Chinese reading processes embedded in learners' social and cultural environment, adopting diverse methodological approaches that uncover readers' voices, advancing understanding in social factors that impact L2 Chinese reading acquisition in classrooms, and attending to different processing levels and various forms of characters/ words/ sentences/ texts.Pedagogical implications were also discussed.