Reviewerly/exHarmony huggingface dataset:
A Mathematical Model of Distributing New Information in Society

Diversification of any new idea or concept in the society often begins with the emergence in the mass media of information that can win the attention of particular social groups or individuals. The author analyzes and interprets the results obtained by the means of constructing and studying a basic mathematical model of distribution of new information. The article describes factors and regularities that make the basis for the model, comments on all the relators that form the structure of the model, and describes the parameters of this structure. The proposed model is represented by a system of four ordinary differential equations. The stationary points of the system are found, and their conceptual meaning is described. The stationary points have cardinally different properties, depending on different relators. This provides for several possible scenarios of distributing new information in the society, whose description and geometric interpretation is given in the article.
COMPUTER MEDIATED COMMUNICATION (CMC) DALAM PEMBELAJARAN BAHASA INGGRIS

The Industrial Revolution 4.0 has produced many breakthroughs especially the appearance of communication platforms that gave colour to English learning in Indonesia. Therefore computers are very useful in language class, although basically computers are only tools for mediating student’s communication in English learning. This paper describes Computer Mediated Communication (CMC) in English learning.
Localization and discrete probability function of Szegedy’s quantum search one-dimensional cycle with self-loops

We study the localization and the discrete probability function of a quantum search on the one-dimensional (1D) cycle with self-loops for n vertices and m marked vertices. First, unmarked vertices have no localization since the quantum search on unmarked vertices behaves like the 1D three-state quantum walk (3QW) and localization does not occur with nonlocal initial states on a 3QW, according to residue calculations and the Riemann-Lebesgue theorem. Second, we show that localization does occur on the marked vertices and derive an analytic expression for localization by the degenerate 1-eigenvalues contributing to marked vertices. Therefore localization can contribute to a quantum search. Furthermore, we emphasize that localization comes from the self-loops. Third, using the localization of a quantum search, the asymptotic average probability distribution (AAPD) and the discrete probability function (DPF) of a quantum search are obtained. The DPF shows that Szegedy’s quantum search on the 1D cycle with self-loops spreads ballistically.
Typical Features of Politeness Strategy Performed by Anregurutta (Religious Leader in Pappandangan Maros District of South Sulawesi)

Politeness has been considered as a core dimension of social interaction regardless of culture and ethnicity and is a predictor of good etique to prevent offensive reactions from the other interlocutor. The main purpose of this study is to address the politeness strategy use in Buginese Language with special reference to Anregurutta Pappandangan Maros of South Sulawesi. The present research has been set up to account for an ethnographic research and as such research instruments were strictly employed to comply with the nature of resarch design. These include field notes, direct observation, idepth interviews, and recordings. Data were mostly gathered from Anregurutta and the rest from the local people mostly by means of recording and interviews. Greater proportion of the recorded data were from Anregurutta whose daily language of interactional conversation is in Buginese. The recorded conversations were analyzed by means of descriptive analysis and interpretative paradigm.The analysis came up with a series of findings that partly confirm the validity of previous politeness framework, such as Brown and Levinson (1978), and Yassi (1996) with reference to Kinship (K), Distance (D) and Power (P). The finding deviates from the universality of politeness pattern that confirm use of bald-on strategy in non-kinship relation. It appears from the study, bald-on strategy was consistently used in kinship pattern, such as Anregurutta and his wife and daughter. (4.1.5 and 4.1.8). This research gap is most probably due to changes in interactional paradigm as a reult of religious values that has affected the way kindship family interacts. The second finding that has been neglected in the study of poliness of which contributes as the research gap is in reference to metalinguistic of politeness that count spritualism and Islamic suphism as generating motives of having to be polite to other people. The finding may contribute the the development of pragmatics with special reference to politeness strategy in non-european context since these aspects have been neglected in previous studies.
Certified and fast computations with shallow covariance kernels

Many techniques for data science and uncertainty quantification demand efficient tools to handle Gaussian random fields, which are defined in terms of their mean functions and covariance operators. Recently, parameterized Gaussian random fields have gained increased attention, due to their higher degree of flexibility. However, especially if the random field is parameterized through its covariance operator, classical random field discretization techniques fail or become inefficient. In this work we introduce and analyze a new and certified algorithm for the low-rank approximation of a parameterized family of covariance operators which represents an extension of the adaptive cross approximation method for symmetric positive definite matrices. The algorithm relies on an affine linear expansion of the covariance operator with respect to the parameters, which needs to be computed in a preprocessing step using, e.g., the empirical interpolation method. We discuss and test our new approach for isotropic covariance kernels, such as Matérn kernels. The numerical results demonstrate the advantages of our approach in terms of computational time and confirm that the proposed algorithm provides the basis of a fast sampling procedure for parameter dependent Gaussian random fields.
UI design development for informative mobile game about light pollution

Light pollution has been an environmental concern in Jakarta and surrounding cities. Despite the negative consequences, Jakarta residents have low to non-existent awareness about light pollution. To raise awareness, the development of an informative mobile game with the title MA’LAM is proposed. As one means to develop an ideal gaming experience, User Interface (UI) needs to be developed with usability and aesthetic approach. To implement UI design successfully, a suitable user-centric design method is required. Therefore, Design Thinking was used to develop MA’LAM’s UI design as part of User Experience (UX) development process. With a usable and aesthetically pleasing UI, message and information about light pollution could be conveyed through a positive gameplay interaction.
Dampak Penerapan E-Money bagi Proses Administrasi Keuangan di Sekolah Dasar Muhammadiyah 1 Ketelan Surakarta

This is reason the researchers to explore more about the impact of e-money on the administrative process at Muhammadiyah 1 Ketelan Surakarta Elementary School. This study aims to describe: 1) The process of financial administration at Muhammadiyah 1 Elementary School Surakarta. 2) Implementation of e-money at Muhammadiyah 1 Elementary School in Surakarta. 3) Impact of e-money for the administrative process at Muhammadiyah 1 Ketelan Surakarta Elementary School. This research is a descriptive qualitative study. Informants in this study were principals, treasurers, BUMS officers, parents and students. The technique of collecting data is by interview, observation and documentation. Data techniques were analyzed by interactive analysis. Check the validity of the data using triangulation of sources and techniques. The results of this study indicate that 1) The process of administration of school finance is managed by treasurers and BUMS officers who have tasks in the form of planning, recording, implementation, accountability, and reporting. Then there needs to be supervision carried out by the head of school and the Council of Dikdasmen PDM Kota Surakarta. 2) The application of e-money at the Muhammadiyah 1 Ketelan Surakarta Elementary School because has several reasons including the school has been appointed by the Ministry of Education and Culture to implement digital literacy, the school canteen has won healthy canteens, and concerns of parents who still don't buy unhealthy snacks outside school environment. Some of the advantages include the following: a) transactions become more efficient, b) the means to implement digital literacy, c) applying a line culture to students, d) audit financial data easier, e) e-money cards are equipped with student data, f. students easily check the balance. 3) Impact of e-money for the administration of the Muhammadiyah Surakarta elementary school is e-money used by students to transact in canteens and school cooperatives. So that e-money has an impact on financial administration managed by BUMS officers.
Readability Level of Arabic Texts for Upper Primary Pupils at Al-Amin Islamic Primary School (SRI)

Textbook has become one of the primary materials in the teaching of Arabic language in Malaysia. Studies among scholars shown that the proficiency of Arabic language among non-native students is still at a low level due to many factors including the ineffectiveness of textbooks’ contents. Evaluation of a reading material takes into consideration of many aspects including the readability level, which is the difficulty level of a reading material. A quality textbook is a reading material that is easy to understand. This study discusses the readability of Arabic texts among the upper primary pupils in Al-Amin Islamic Primary School (SRI), Nilai, Negeri Sembilan. This study of readability has a role for documentation to facilitates the Ministry of Education, teachers, policymakers, textbook writers, and the related people in other fields.
Explainable AI for Workflow Verification in VIPLE

Teaching students the concepts behind computational thinking is a difficult task, often gated by the inherent difficulty of programming languages. In the classroom, teaching assistants may be required to interact with students to help them learn the material. Time spent in grading and offering feedback on assignments removes from this time to help students directly. As such, we offer a framework for developing an explainable Artificial Intelligence that performs automated analysis of student code while offering feedback and partial credit. The creation of this system is dependent on three core components. Those components are a knowledge base, a set of conditions to be analyzed, and a formal set of inference rules. In this paper, we develop such a system for our own language by employing Pi-Calculus and Hoare Logic. Our detailed system can also perform self-learning of rules. Given solution files, the system is able to extract the important aspects of the program and develop feedback that explicitly details the errors students make when they veer away from these aspects. The level of detail and expected precision can be easily modified through parameter tuning and variety in sample solutions.
Comparative analysis of the technology used to create multi-platform applications on the example of NW.js and Electron

The article presents an analysis of the performance of frameworks that enable the creation of multi-platform desktop applications. Electron and NW.js were selected for comparison. The study was conducted using a test desktop application with social media functionality. The test application was developed on both compared platforms. The presented research results allowed to conclude that the NW.js framework is more efficient than the Electron framework.
International Conference "Historical Research in the Context of Data Science: Information Resources, Analytical Methods and Digital Technologies"

The word "data" has recently become one of the key words in the semantic field of modern science. This happened due to a sharp increase in information flows in the economy and social sphere and the ongoing breakthrough in the development of methods and technologies for processing and analyzing data in the context of large-scale digitalization and the need to work with big data. This has led to the rapid development of data science. Historical science has been affected by these processes as well. The article discusses the course and results of the 17th international conference of the interregional association "History and Computer" held under the title "Historical Research in the Context of Data Science: Information Resources, Analytical Methods and Digital Technologies". Researchers from 7 countries took part in the conference held on-line. The article characterized the structure of the conference in details and the most interesting speeches of its participants. There were two plenary meetings, two round tales and 9 sections. The conference results show that historical computer science has entered a new stage of its development and has ceased to be perceived as a kind of "niche" area of historical science. New researchers are being involved in its development, the geography of scientific centers of historical computer science is expanding, their studies touch upon the most important issues of Russian and foreign history.
Product Recommendation using Object Detection from Video, Based on Facial Emotions

In today’s world, with the increasing demand of products and their growing productivity from producers, customers sometimes failed to decide whether they are interested in buying a particular product or not. So author, here proposed a framework which deals with the buying of only items of interest, for a consumer. In our feature-set, whenever any consumer tends to watch any video from YouTube, it results in breakdown into several frames (frames per second), and from there we use object detection technique to detect each and every object in a particular frame, and then to find whether our consumer is interested in that particular object or not, we use facial emotion detector to check whether our user is happy, surprised, neutral or any other emotion. After viewing those products which are present in a frame of a video. Merging only those items of interest which were tend to fall for consumer’s positive choices (emotions), we then used Amazon online marketing technique to recommend products selected by our framework.
Pointing to Subwords for Generating Function Names in Source Code

We tackle the task of automatically generating a function name from source code.Existing generators face difficulties in generating low-frequency or out-of-vocabulary subwords.In this paper, we propose two strategies for copying low-frequency or out-of-vocabulary subwords in inputs.Our best performing model showed an improvement over the conventional method in terms of our modified F1 and accuracy on the Java-small and Java-large datasets.
Learning stereometry in a secondary school within GeoGebra’s Augmented Reality app

Abstract GeoGebra dynamic mathematics system has earned a public acceptance as a software product to support educational and even scientific activities in the field of mathematics. Since 2017, GeoGebra developers have provided users of this program with a new feature for creating and using AR. In this article a series of tasks for modeling of real objects using GeoGebra AR is presented. They assigned to different levels of secondary geometric education: basic, specialized, and advanced. Setting such tasks for students contributes to the formation of visual thinking and skills of using of stereometry knowledge for solving practical problems.
Virtual and Augmented Reality Technologies in Training Architecture and Civil Engineering Specialists

This paper discusses the aspects of training architecture and civil engineering specialists using virtual and augmented reality technologies. It also addresses the issues of training specialists in software development for visualization of buildings and structures information models. The paper deals with the selection of optimal hardware and software for the most effective learning process and provides an overview of the most relevant areas of scientific research in this field.
Technology: COVID-19 and the ‘New-Normal’ Lifestyle vs. Security Challenges

Abstract In the last period, especially during the COVID-19 pandemics, individuals as well as institutions globally and in North Macedonia particularly, have failed to correctly respond to the new challenges related to cyber security, online attacks, and fake news. Being that in a state of isolation and quarantine most governmental institutions have heavily relied on online tools to communicate among each other and with the public, it is quite evident that they have not been well prepared to adopt new technologies. This paper aims to bridge together the needs for technology during the COVID-19 pandemics versus the security challenges that many forget to mention. The primary focus of this paper is to elaborate on the security challenges associated with technology with several examples from incidents around the world and from North Macedonia. As such, it represents a perspective paper with focus on current and emerging advances on IT security for running the “new normal” world.
New Method for Optimal Feature Set Reduction

A problem of searching a minimum-size feature set to use in distribution of multidimensional objects in classes, for instance with the help of classifying trees, is considered. It has an important value in developing high speed and accuracy classifying systems. A short comparative review of existing approaches is given. Formally, the problem is formulated as finding a minimum-size (minimum weighted sum) covering set of discriminating 0,1-matrix, which is used to represent capabilities of the features to distinguish between each pair of objects belonging to different classes. There is given a way to build a discriminating 0,1-matrix. On the basis of the common solving principle, called the group resolution principle, the following problems are formulated and solved: finding an exact minimum-size feature set; finding a feature set with minimum total weight among all the minimum-size feature sets (the feature weights may be defined by the known methods, e.g. the RELIEF method and its modifications); finding an optimal feature set with respect to fuzzy data and discriminating matrix elements belonging to diapason [0,1]; finding statistically optimal solution especially in the case of big data. Statistically optimal algorithm makes it possible to restrict computational time by a polynomial of the problem sizes and density of units in discriminating matrix and provides a probability of finding an exact solution close to 1.&#x0D; Thus, the paper suggests a common approach to finding a minimum-size feature set with peculiarities in problem formulation, which differs it from the known approaches. The paper contains a lot of illustrations for clarification aims. Some theoretical statements given in the paper are based on the previously published works.&#x0D; In the concluding part, the results of the experiments are presented, as well as the information on dimensionality reduction for the coverage problem for big datasets. Some promising directions of the outlined approach are noted, including working with incomplete and categorical data, integrating the control model into the data classification system.
Comparison of Two Objects Classification Techniques using Hidden Markov Models and Convolutional Neural Networks

This paper presents a comparison between discrete Hidden Markov Models and Convolutional Neural Networks for the image classification task. By fragmenting an image into sections, it is feasible to obtain vectors that represent visual features locally, but if a spatial sequence is established in a fixed way, it is possible to represent an image as a sequence of vectors. Using clustering techniques, we obtain an alphabet from said vectors and then symbol sequences are constructed to obtain a statistical model that represents a class of images. Hidden Markov Models, combined with quantization methods, can treat noise and distortions in observations for computer vision problems such as the classification of images with lighting and perspective changes.We have tested architectures based on three, six and nine hidden states favoring the detection speed and low memory usage. Also, two types of ensemble models were tested. We evaluated the precision of the proposed methods using a public domain data set, obtaining competitive results with respect to fine-tuned Convolutional Neural Networks, but using significantly less computing resources. This is of interest in the development of mobile robots with computers with limited battery life, but requiring the ability to detect and add new objects to their classification systems.
Bibliotecas argentinas: reflexiones, acciones y propuestas en tiempos de pandemia. La experiencia de la BCN, BNM, BNMM y CONABIP

From the Association of Graduate Librarians of the Argentine Republic we want to record the importance of the actions of libraries in times of the COVID-19 pandemic. On this occasion, we present the contributions of the Argentine national libraries, the National Library of Congress, the National Teacher Library, the Mariano Moreno National Library and the National Commission of Popular Libraries (CONABIP) in the face of this highly uncertain panorama, forming a guide to everything to come It is clear that in this context of uncertainty, libraries have readjusted their functions and activities, in general to the virtual, demonstrating a great capacity to adapt to these circumstances. The following documents will contain reflections on the actions and proposals in times of pandemic based on the following thematic lines: ● Learning for the library that the pandemic is leaving it Strategies for reopening ● Librarian teleworking ● Pre and post-covid transformations of the library ● Protocols ● Benefits and disadvantages of the library in the ASPO ● Issues that the library will need to rethink after COVID-19. The questions we asked them were: How is the teleworking staff being supported and supported? What strategies are being designed for the reopening? How do you envision the library of the post-covid-19 future?
Communication effectiveness in social networks of leading universities

The article presents the results of communication effectiveness analysis in social networks of leading universities with strong economic departments. The study was carried out using the textual information analysis i.e. content, links, posts, comments, tags, etc.; multimedia i.e. photos, videos, audio, etc., and the ontology method, which estimated the social networks parameters like the number of subscribers, average path length, etc. The study showed that the main platform for international higher education institutions is Facebook; Instagram is actively developing, and then comes YouTube. The number of publications does not directly affect the number of subscribers, in contrast to the number of students. The high frequency of posts does not lead to subscribers increase. There is no single strategy for universities social network development. The use of informal communication, which encourages action, significantly increases the audience and its involvement; but is not used by all universities, because it might contradict with the university’s image. It should be noted that good design, the use of professional photos and videos,has its impact on potential audience.