Reviewerly/exHarmony huggingface dataset:
Directory of Open-Access External Electronic Resources on the Research Topics of the Ural Branch of the Russian Academy of Sciences

The article presents the results of compiling the External Electronic Resources directory based on the online platform “Web-office of a Scientist” (http://i.uran.ru/webcab/) of the Central Scientific Library of the Ural Branch of the Russian Academy of Sciences. The directory includes electronic libraries and collections, repositories, and journal platforms on the research subjects of the Ural Branch of the Russian Academy of Sciences. To select resources data from the universal repository registration system called Directory of Open Access Repositories (OpenDOAR) as well as scientific organizations’ websites in Russian Federation and abroad were used. The External Electronic Resources Directory contains 130 information sources on humanities, medicine, biology, physics, engineering science, chemistry, economics, mathematics, mechanics, computer science, agriculture, and Earth sciences. These information sources provide access to full-text documents, as well as multimedia and audiovisual materials, bibliographic and research data in English, Russian, French, German, Czech, Polish, Latin, and other languages. The search engine of the directory gives an opportunity to select electronic resource by tytle, link, country, subject, type, and a substring of the given resource description. There is a possibility of statistical accounting of queries to electronic resources from the Directory page on the online platform “Web-office of a Scientist”. The directory has practical importance for the research support and information servicing of scientists of the Ural Branch of the Russian Academy of Sciences. The use analysis of this Directory will be beneficial for the development of a search methodology as well as technologies to provide the scientific library with remote electronic resources.
A Countermeasure Against Adversarial Attacks on Power Allocation in a Massive MIMO Network

Deep learning has been emerging as a powerful design tool for the current and future generations of wireless networks. Among many other successful applications, deep learning has been shown to reduce computational complexity in power allocation problems in massive multiple-input and multiple-output (MIMO) networks. Despite its advantages over conventional power allocations, a recent study demonstrated that an imperceptible yet carefully designed feature perturbation named as adversarial examples may drastically degrade the performance of the power allocation system based on deep learning. Hence, in this paper, a defence system called noise-augmented neural network is investigated to mitigate the effect of adversarial attacks, and its performance against white-box fast gradient sign attacks and projected gradient descent attacks is evaluated. It is shown that the proposed noise-augmented neural network could protect power allocation system from the damaging effect of the adversarial perturbations with much greater accuracy as compared to the undefended deep neural network.
Implementasi Pembelajaran Dalam Jaringan (Daring) Menggunakan Aplikasi Ispring Suite 8 di Taman Kanak-Kanak

The weakness of the world of education in Indonesia is the problem of the learning process. In this process students are less motivated to develop thinking skills and skills. For early childhood children at a certain age are not given the opportunity to develop their abilities, both by teachers and parents, it seems that there are still many children who are shy, not independent and not confident.In its implementation, the online learning system during the Covid-19 pandemic encountered several obstacles, including not all students understood internet technology and the need for preparation from the school in such a way. One solution that can be taken by implementing online learning is to use the Ispring suite 8 application which is a tool for creating presentational learning media that can be used in the learning process which includes aspects of audio, visual, audio visual, and audio visual media. various types of evaluations have been carried out. Provided. The Ispring suite 8 application is an application that is run on a computer for use in making learning media either directly, through online learning or a combination of both. the results of this study indicate that the application of online learning using the ispring suite 8 application can increase the creativity of children aged 5-6 years.
Scaling Subgraph Matching by Improving Ullmann Algorithm

Graphs are widely used to model complicated data semantics in many application domains. Subgraph isomorphism checking (an NP-complete problem) is a regular operation with this kind of data. In this paper, we propose an improvement of Ullmann algorithm, a well-known subgraph isomorphism checker. Our new algorithm is called Ullmann-ONL. It utilizes a new search ordering and L-levels of vertex neighborhoods (NL) to confine the search space of Ullmann algorithm. Our performance study shows that Ullmann-ONL outperforms previously proposed algorithms with a wide margin.
Technology-Enabled Co-Regulation for Blockchain Implementation

Blockchain technology has great potential to reshape the financial industry.However, the existing policy and regulatory regimes fail to provide a supportive environment for blockchain technology to fulfill its potential.In this Article, I propose technology-enabled co-regulation as a new approach to blockchain implementation, especially in the financial markets.This approach has two distinctive elements: a collaborative environment and a technology-enabled mechanism.A collaborative environment consists of regulatory and industry sandboxes in which regulators and industry representatives can experiment with novel ideas.A technology-enabled mechanism is empowered by regulatory technologies ("RegTech") and supervisory technologies ("SupTech") that support compliance with regulatory and reporting requirements and facilitate supervisory obligations.This technology-enabled co-regulation can help to achieve policy and regulatory goals: a fair and efficient market, financial stability, consumer and investor protection, law enforcement efficiency, and, most importantly, technology innovation.Technology-enabled co-regulation is preferable to traditional commandand-control regulation and self-regulation.Its collaborative and technological elements are also more advanced than a simple co-regulation is.To reach this conclusion, this Article conducts an impact assessment of proposed regulatory options.The impact assessment consists of five analytic steps, asking the following questions: (1) what problems have emerged from existing policies and regulations?(2) what are the objectives of the proposed regulations?(3) what are the regulatory options?(4) what are the possible impacts?(5) how do the options compare?
Internet of Things (IoT) Based Free Fall Motion Instructions in Physics Subjects for Class X Students

Physics subjects are one of the most difficult materials for students to understand. According to the research that has been done, props are one of the answers to make it easier for students to understand physics lessons. Since most physical materials are directly related to everyday life, props serve as a practical medium to facilitate the learning process. Learning physics concepts is easier to understand by using props which we simulate based on real events. One of the materials in physics class is free-fall motion. In this material, when an object falls from a height and has no initial velocity, its falling velocity is calculated. In this study, we apply the Internet of Things (IoT) to the props of free fall material and by adding Ambrose's concepts namely practice and feedback, so that students can better understand the material of free-fall motion. By implementing IoT, the system can read, record, and evaluate the experimental activities performed by users, and users who already have an account can access it online through the website. The system was evaluated based on system functionality and accuracy generated by the system. Based on the test results, it was found that all functions included in the system were 100% working. Based on the three tests performed, the system achieved an average accuracy of 80%.
Software process improvement programs

While many organizations successfully embrace and experience software process improvement (SPI) benefits, others abandon the effort before realizing the total potential result of an SPI initiative. Therefore, researchers' interest in understanding the reasons why software organizations that have a successful start in adopting SPI abandon improvement initiatives after evaluation has increased. Thus, this work aims to investigate how the abandonment of SPI programs based on maturity models occurs after the evaluation. The multiple case study method was used with eight organizations. Data were analyzed using Grounded Theory open and axial coding procedures. The results show that SPI initiatives failed because of internal factors (people, SPI project management, organizational aspects, and processes) and external factors to the organizational context (country economic crisis, outsourcing, governmental political influence, and external pressure from the client). As a contribution, we highlight the identification of these factors that organizations can use to learn about their initiatives and avoid pitfalls that can lead to the abandonment of SPI.
Implementation of Learning Using Interactive Multimedia Based on Android On Theme 9 be Class V SD

The problem in the thematic learning of class V Elementary School is caused by conventional teaching methods and does not use engaging learning media so that students feel bored to take part in learning activities. This research is a follow-up to the results of the validity test and practicality test of interactive multimedia developed using the Android Operating System. This study aims to analyze the effectiveness of android-based interactive multimedia. The method used to collect data is observation, interviews, and tests. The instrument used to collect data is a test question. Data were analyzed using a t-test. In previous studies, the validity of android-based interactive multimedia was tested through expert validity tests and practicality tests through individual trials. The effectiveness of using Android-based interactive multimedia was tested by giving a pretest-posttest in the form of an objective test consisting of 20 questions with 12 students. The effectiveness test results of student learning outcomes from the pretest and post-test data showed an increase from the average before using android-based interactive learning media. Based on these data, it can be said that interactive multimedia based on android thematic learning to improve student learning outcomes in students is valid, practical and effective for use in the learning process. Thus, it can be said that the Android-based interactive multimedia developed effectively improves the learning outcomes of fifth-grade elementary school students.
Estimating the Deployment Time for Containerized Application Using Novel Microsoft Azure Based Docker Container over Google Cloud Platform Based Docker Container

Aim:The aim of the study is to estimate the deployment time of Containerized application using Novel Microsoft Azure based Docker Container over Google cloud platform based docker container.Materials and Methods: Sample groups that are considered in the project can be classified into two each has 20 samples, one for Google cloud platform and other for Novel Microsoft Azure based docker container, which are tested using 0.80 for Gpower to determine the sample size and for t-test analysis.20 applications have been used in each group for estimating deployment time.Results: The Novel Microsoft Azure based Docker container with efficient accuracy of 77%, which by far seems to be better than the Google cloud platform based docker container which gives around 70.00%.As a result, the study group has a statistically negligible difference.The significance is around 0.0477 (p<0.05) and therefore there is a statistical insignificant difference among the study group. Conclusion:The deployment time of Containerized application in the Novel Microsoft Azure based Docker container is better compared to Google cloud platform based docker container.
Pelatihan Desain Grafis bagi Siswa SMK Global Persada Mandiri Bekasi

Graphic design is a communication process using visual elements, such as typography, photography, and illustrations that are intended to create a perception of a message being conveyed. This field involves the process of visual communication and communication design and is very much needed by today's society, including students at SMK Global Persada Mandiri Bekasi. The material provided in this graphic design training is an introduction to graphic design, the benefits of graphic design, types of graphic design, and the practice of making graphic designs, in the form of logos, banners, and flyers. This graphic design training in the form of logo creation training provides tremendous benefits for students. Students can design any logo so that their soft skills increase and can be used in everyday life.&#x0D; &#x0D; Keywords— Graphic design, logo, soft skills
Image Encryption Using Homomorphic Transform

As more and more information is stored and sent electronically, the subject of cryptography has recently gotten a lot of attention. Cryptography is the practice of converting the original data into unreadable from intruders. The process of image encryption follows the image conversion in frequency and from frequency to an 8x8 matrix. The homomorphic transform is used to translate the target image into an 8x8 matrix which further follows simple mathematical calculations to convert the image into encrypted data. In the reverse process from getting the original image, back from the encrypted image. Image cryptographic schemes are to be considered best if they retrieve the original data without causing any loss to the original information. The proposed encryption algorithm is appropriate for applications that demand safe data transfer.
Residual Information Flow for Neural Machine Translation

Automatic machine translation plays an important role in reducing language barriers between people speaking different languages. Deep neural networks (DNN) have attained major success in diverse research fields such as computer vision, information retrieval, language modelling, and recently machine translation. Neural sequence-to-sequence networks have accomplished noteworthy progress for machine translation. Inspired by the success achieved by residual connections in different applications, in this work, we introduce a novel NMT model that adopts residual connections to achieve better performing automatic translation. Evaluation of the proposed model has shown an improvement in translation accuracy by 0.3 BLEU compared to the original model, using an ensemble of 5 LSTMs. Regarding training time complexity, the proposed model saves about 33% of the time needed by the original model to train datasets of short sentences. Deeper neural networks of the proposed model have shown a good performance in dealing with the vanishing/exploding problems. All experiments have been performed over NVIDIA Tesla V100 32G Passive GPU and using the WMT14 English-German translation task.
Digital pedagogy

The article is dedicated to possible changes in the modern paradigm of education that presupposes a traditional model of activity in solving pedagogical problems. The main focus of the article is on two areas of scientific research: the disclosure of the deep meanings of “digital pedagogy” and the formulation of its main problems. The article presents the results of the study of psychological and pedagogical literature, which explains the interpretation of the new concept of “digital pedagogy” by modern Russian researchers. The article also analyzes the scientific literature explaining the problems of digital pedagogy identified on a variety of grounds, including the issues of insufficient quantity or poor quality of learning indicators, the need for the development of a teacher's digital culture, difficulties in the implementation of digital learning into the higher education system etc. The authors investigate the problems of digital pedagogy to define the essence of the concept and formulate its principles.
Distilled Model for Russian News Clustering: much lighter and faster, still accurate

This paper explores abilities of knowledge distillation for the purposes of News clustering which also can be generalized as an event detection task. We used a BERT-based clustering model as a teacher and tested various student networks based on different architectures (RNN, FFN, convolutional and Transformer-based networks) in order to get a faster lightweight analogue that is more likely to be deployed in real products. We tried two distillation strategies: the first one combined an original loss function from the initial model with a distillation objective, for the second one we used only a specific distillation loss. This approach turned out to be more successful. It let us extend training and validation datasets and gave significantly better results. One of our distilled models scored about 1% lower than the teacher network, but is more than 20 times smaller and 5 times faster by inference.
Pedagogic Meaning-Making in Spherical Video-Based Virtual Reality – a Case Study from the EFL Classroom

This article explores relevant conceptual frameworks and design principles for the planning and implementation of a virtual reality (VR) learning environment in English as a foreign language (EFL) contexts. The primary focus is on what knowledge teachers need to acquire when designing and implementing a spherical video-based training world that allows English learners to experience the different phases of an oral examination in English. Therefore, the paper introduces the educational potential and affordances of spherical videos and describes structural and contextual aspects of oral examinations in English. Employing a prototype learning environment, we expand on major learning theories in spherical video-based learning and suggest best practices for the design and implementation of immersive learning experiences in EFL contexts.
PENGEMBANGAN MEDIA GAME SCRATCH PADA PEMBELAJARAN IPA KELAS V MATERI ALAT PERNAPASAN PADA HEWAN

This research was motivated by the results of observations at SDN Mrican 1 class V science subjects on respiratory equipment in animals which showed that 60% of fifth grade students still had difficulty understanding the material. One of the reasons is that teachers tend to use existing media so that students are less enthusiastic in participating in learning. To overcome this problem, it is necessary to develop innovative learning media according to the material. This research is a Research and Development (R&amp;D) research using the ADDIE development model. This development model has 5 stages, namely: Analysis (Analysis), Design (Design), Develompent (Development), Implementation (Implementation), Evaluation (Evaluation). The data collection instrument in this study used a questionnaire and a test. Questionnaires are used to determine the assessment given by media experts, material experts, classroom teachers to the developed media. While the test is used to measure the initial ability and final ability of students after using the media that has been developed. The results of this study are Game Scratch media is declared valid based on the results of expert validation and the material obtained is 88% and 89% is included in the very valid category. While the practicality questionnaire given by the teacher obtained 92% results categorized as very practical. In a limited trial, the result was 87.5%, so it was categorized as very effective.Based on the conclusions of this study, it is stated that the development of this media can help teachers to create a pleasant learning atmosphere and can arouse students' enthusiasm in participating in learning
Hand gesture recognition using deep learning

The aim of our project is to design system which will be elementary and useful to obtain human-computer interconnection and will provide support to those in necessity by confirming social importance also Deaf & Dumb people could easily communicate with community. The Classical methods have crashed to obtain compatible image descriptors for hand gesture recognition in the present framework because of many challenging elements. Recently come up Deep learning algorithms and developments in CNN exceeds the traditional address towards the hand gesture recognition as it keeps away the standard preprocessing and segmentation steps and automatizes the operation of feature extraction.
Food Sustainability, Cyber-Biosecurity, Emerging Technologies, and Cybersecurity Risks in the Agriculture and Food Industries

The United Nations forecasts that by 2050, the world's population will reach 9.8 billion and 11.2 billion in 2100. An ever-growing global population threatens food security, accompanied by an increasing food shortage and relentless cybersecurity attacks. Agriculture 4.0, smart farming, and precision farming are essential to provide the technological breakthroughs to increase agricultural production while simultaneously expanding cybersecurity risks in the agriculture and food industries. With a global cybersecurity talent shortage and increasing cyber-attacks on the agriculture and food industries, there is a dire need to address cybersecurity solutions for the agriculture and food industries. A developing area in agriculture is cyberbiosecurity, an integrated concept of biosecurity and cybersecurity underline the need to safeguard systems, humans, animals, and plants from biological mischiefs, such as bioterrorism, environmental terrorism, infections, plagues, and pandemics. This paper explores these complex dynamics through an exploration of current and emerging literature.
Penerapan Algoritma Naïve Bayes Untuk Pengelompokkan Predikat Peserta Uji Kemahiran Berbahasa Indonesia

Indonesian Language Proficiency Test is a proficiency test to measure a person's language proficiency in communicating using Indonesian, both Indonesian speakers and foreign speakers. The UKBI rating has 7 rating categories consisting of special, very excellent, excellent, intermediate, poor, marginal, and limited. The number of participants who take UKBI at the Riau Province Language Center has more than 1000 but no one has managed the data into new knowledge. One of the efforts that can be done with the data is classification. The Naïve Bayes Classification Algorithm is a classification algorithm that is very effective (getting the right results) and efficient (the reasoning process is carried out by utilizing existing inputs in a relatively fast way). In order to obtain good accuracy results, the Naive Bayes Algorithm is combined with the Adaboost feature selection with a 70:30 and 80:20 test scheme. The results of the research carried out resulted in the highest accuracy value, namely 89% which combined the Naive Bayes algorithm with the Adaboost feature selection with 70:30 data splitting