Reviewerly/exHarmony huggingface dataset:
Prospects for modernization of the electronic educational environment “Cross-Platform Project” format in the context of blended and distant learning

Problem and goal. The relevance of this study is emphasized by the increasing need and importance of distance education in the modern world in connection with the pandemic, as well as the increased demand of teachers and students of different levels for the tools of the virtual classroom. The purpose of this work is to introduce teachers to the tools of the Internet, to present a classification of these tools, resources and existing electronic educational environments for working in distance learning. Methodology. The use of the Langteach-online cross-platform learning environment during the COVID-19 pandemic, and the experience of working with LMS Moodle and LMS Canvas related to the construction of online courses are analyzed. A comparative analysis of online services and the use of QR technology for educational purposes for the modernization of the developed format of the electronic educational environment is carried out. Results. The experience of modernizing the format under study to expand the range of disciplines and forms of education in the field of which it can be applied at the levels of secondary and higher education in the Russian Federation is presented. The working conditions of the environment, its functionality and requirements for the teacher as the organizer of the educational environment of this format are described. Conclusion. The presented format expands the effective tools of the teacher, integrates mobile technologies into the educational process, forms multifunctional online libraries of various-format educational materials.
Expert System to Diagnose Appendicitis with the Certainty Factor Method

Health is the main key to human life, for that the author also needs health in writing a thesis entitled appendicitis so that readers can understand and recognize appendicitis more quickly. According to Kusrini, S.Kom (2006:11). An expert system is a computer-based system that uses knowledge, facts and reasoning techniques in solving problems that can usually only be solved by an expert in the field. Basically expert systems are applied to support problem solving activities. According to (T. Sujoto, Edy Mulyanto, Dr. Vincen Suhartono, 2011: 125) the Certainty Factor (CF) theory is to accommodate the inexact reasoning of an expert proposed by Shortliffe and Buchanan in 1975. Here the author will discuss on the Expert System for Diagnosing Appendicitis, Certainty Factor Method is one of the Expert System Methods for diagnosing appendicitis. To make the application the author uses Microsoft Visual Studio 2010.
Improving information architecture by documenting domain knowledge in conceptual models: How software creation can benefit from leveraging conceptual models

In the last decade, Agile has become the default software development process. This paper questions if parts of the traditional system analysis process could still be valuable in the context of an Agile process. This paper is focused on conceptual models which can share domain knowledge, by documenting in text or a visual representation. The aim of this thesis is to find out if a conceptual model brings value in the software development process, or that it is an avoidable effort? The research question that was formulated: Does the usage of conceptual models with domain knowledge lead to a better understanding of the subject domain? An experiment has been conducted which included two groups that had a limited amount of time to study a significant amount of domain knowledge. One of the groups received a conceptual model and a text to explain the domain, while the other groups just received the text. The groups of participants that were included in the experiment did not have significant differences in properties amongst them. The result of the experiment was that there was no significant difference for either of the categories of questions, as well in the overall results.
ANALISIS KESALAHAN BERBAHASA DIKAJI BERDASARKAN TATARAN MORFOLOGI PADA JUDUL YOUTUBE DI CHANNEL RANS ENTERTAINMENT

The background of the problem in this study is the language error in the field of morphology contained in the Youtube title on Channel Rans Entertainment. The purpose of this study was to research and analyze language errors in morphology in Youtube titles on Channel Rans Entertainment. This study used descriptive qualitative method. The data collection techniques used in this study were observation, documentation, note-taking, and data analysis techniques. The results of this study describe language errors in the morphological field of Youtube titles on Channel Rans Entertainment, especially errors in the use of affixation. These errors include: omitting the prefix {ber-}, writing errors in the prefix {di-}, removing the prefix {me-}, removing the prefix {meng-}, removing the confix {me-kan}, removing the confix {di-kan}, removing the prefix {meN-}, removing the confix {ke-an}, removing the confix {meng-i} and removing the suffix {-kan}.
Challenges and Opportunities of the Education Industry in the Post-Epidemic Era

The outbreak of the epidemic, we face new challenges, the epidemic actually triggered people’s reflection on education, objectively promoted the progress and innovation of education, and brought new development opportunities. With regard to the importance of life education, we pay more attention to educational issues such as family education and parent-child relationships, and we are more aware of the important role of technology in the field of education. In the past, we often thought that schools were classrooms for imparting knowledge to students, but now that technology provides more ways to learn knowledge, schools must become a place for students to truly achieve all-round growth, and to cultivate students’ practical application of knowledge. From the perspective of education reforms, artificial intelligence and big data analysis will be widely used in the education field. In the future, pure online and offline education will continue to exist, but the online and offline integration model may become the mainstream. With the help of AI, 5G, and block-chain technology, future education evaluation methods will also change from a single result evaluation to a process and result multi-dimensional evaluation, and the definition of students' abilities will be fairer.
STUDENT MICRO LOAN MANAGEMENT SYSTEM

In the daily transmuting scenarios of the financial world, lenders and students are searching for new, modern and digital techniques to manage their loans through an automated management system that can ease their effort. The need of this system is to make the process flexible, scalable, agile and fast while being more affordable and reliable. Student Micro Loan Management System is an application which will provide users information with different types of loan available for students. This application gains the headway of an understudy and moneylender simple in giving the confirmed data about student micro loan. This project provides the information about various details of Student micro (Tuition and facilities) loans which are allocated for students. This task accumulates all the data of the advances. This project provides the information about various details of education loans and makes it available to users in user-friendly website/app.
Development of Novel Algorithm for Data Hiding on Mobile Application

We can easily observe that in the current era of communication, Computers, mobile phones, and the Internet are widely used mediums.In such an environment, information security is an important issue.The most common techniques used for information security are Cryptography and Steganography.Many research works have been done on image Steganography.These images have different kinds of formats like BMP, GIF, and PNG.Several compression methods are available which applied to the images having the format BMP, GIF, and PNG is comparatively less effective than the JPEG image.JPEG compression steganography method is complex to implement even then some algorithms have been developed for it.They provide single-level or two-level information securities.This paper presents a method in which is the combination of Cryptography and Steganography is used over android mobile phones.Here we are performing encryption two times on data to be hidden and then that encrypted data hidden both in text and image.We are using the Advanced Encryption Standard (AES) algorithm to hide text within a text, Discrete Cosine transform (DCT) for image steganography, and Data Encryption Standard (DES) for encryption of text.This paper gives the idea of threelevel information security over the android environment.
Factors Affecting Awareness of Phishing Among Generation Y

The purpose of this study was to determine the factors affecting awareness of phishing among Generation Y in Malaysia. Specifically, this study identified three factors that may influence awareness of phishing by applying the Theory of Technology Threat Avoidance. The factors are social engineering, anti-phishing knowledge, and security concern. Data was collected through a questionnaire survey. This study found that all the factors significantly influenced awareness of phishing among Generation Y in Malaysia. The findings of this study provide a further understanding of the factors that affect awareness of phishing. This study would benefit the public, especially Generation Y, the government, and all types of businesses, including financial institutions, by raising awareness of phishing and reducing phishing attacks. Keywords: phishing, Generation Y, social engineering, anti-phishing knowledge, security concern
Classification of hand gestures from forearm electromyogram signatures from support vector machine

&lt;p&gt;Robotic prosthetics is increasingly adopted as an enabling technology for amputees. These are vital not only for activities of daily living but to display expression and affection. A vital element to this system is an intelligent model that can identify signatures from the remaining limb that can be mapped to specific effector movements. Therefore, the study proposes the use of forearm electromyogram to classify between different types of hand gestures; fingers spread, wave out, wave in, fist, double tap, and relaxed state. Data are acquired from 32 subjects using Myo armband. Initially, a total of 248 time-and frequency-domain features are extracted from the eightchannel device. Neighborhood component analysis has reduced them to a total of fourteen features. A hand gesture classification model based on electromyogram signal has been successfully developed using support vector machine with overall accuracy of 97.4% for training, and 88.0% for testing.&lt;/p&gt;
Effective Resource Management in Cloud based Service Models

Cloud Computing is the utilization of computing assets (Hardware and Software) that are conveyed as a help over a system (ordinarily the web) to the clients. It plans to share huge scale supplies and assets for calculation, stockpiling, data and information for logical inquires about [1]. Cloud computing offers three sorts of administration models in particular (i) Software as a Service (SaaS), wherein the end-client application is conveyed as an assistance, (ii) Platform as a Service (PaaS), wherein the application stage is given onto which custom applications and administrations can be sent and (iii) Infrastructure as a Service (IaaS), wherein purchasers control and deal with the assets as far as processors, memory, stockpiling, and system availability. There is a need to deal with the accessible assets in an advanced manner to such an extent that both the cloud specialist organization and cloud client work inside the acknowledged SLA as far as cost the executives and vitality the board. Asset Management systems relevant at SaaS layer are managed from two perspectives to be specific benefit boost and giving decency to cloud clients. In this paper projected for foreseeing the CPU use dependent on which the over provisioning and under provisioning of assets can be maintained a strategic distance from. Understanding the idea of the application, accessible stage and CPU usage fundamentally makes an improvement in successful asset provisioning on the cloud.
Analysis of Elementary School Students’ Leisure Time during the Covid-19 Pandemic

Unforeseen circumstances in the form of the COVID- 19 disease outbreak have brought urgent changes to various sectors. The government's recommendation to stay at home and physical and social distancing must be followed by a change in the face-to-face learning mode to online so that a lot of free time is left at home. The purpose of this study was to analyse the planning of activities carried out in free time for elementary school students’ during the covid-19 pandemic. The study used a quantitative approach using a pre-experimental method in the form of a one-group pre-test - post-test design. The results of the research show that the average post-test score of students’ is 84.7%, greater than the average pre-test score of 69.3% which has a difference of 15.4%. Therefore, it is hoped that students’ can plan positive activities to fill their spare time during the COVID-19 pandemic.
Sistem Informasi Berbasis Website Adol Investor (Ayo Dagang Online) Sebagai Front End Web

The impact of Covid-19 has indeed made the economy sink. This can be felt by the traveling sellers in marketing their trade. However, along with the development of information technology, activities that were manual turned into automatic. Apart from being effective in terms of time, these technological developments are also able to adapt to the business world. One of them is looking for investors for the ADOL application (Ayo Dagang Online). With this investor website, it is hoped that it can help traveling traders in finding funding to develop their business, providing information on how to invest in ADOL and what benefits will be obtained when investing in ADOL. This ADOL application is based on a website built using several software such as Framewok laravel, XAMPP, Visual studio code, MySQL, PHP. The data collection technique was carried out by discussing with the field supervisor to explain the concept of this website. Keywords: XAMPP, PHP, MySQL, Laravel framework, Information System, real time.
Similarity Measure Algorithm for Text Document Clustering, Using Singular Value Decomposition

We examined a similarity measure between text documents clustering. Data mining is a challenging field with more research and application areas. Text document clustering, which is a subset of data mining helps groups and organizes a large quantity of unstructured text documents into a small number of meaningful clusters. An algorithm which works better by calculating the degree of closeness of documents using their document matrix was used to query the terms/words in each document. We also determined whether a given set of text documents are similar/different to the other when these terms are queried. We found that, the ability to rank and approximate documents using matrix allows the use of Singular Value Decomposition (SVD) as an enhanced text data mining algorithm. Also, applying SVD to a matrix of a high dimension results in matrix of a lower dimension, to expose the relationships in the original matrix by ordering it from the most variant to the lowest.
Semantic Perturbations with Normalizing Flows for Improved Generalization

Data augmentation is a widely adopted technique for avoiding overfitting when training deep neural networks. However, this approach requires domain-specific knowledge and is often limited to a fixed set of hard-coded transformations. Recently, several works proposed to use generative models for generating semantically meaningful perturbations to train a classifier. However, because accurate encoding and decoding are critical, these methods, which use architectures that approximate the latent-variable inference, remained limited to pilot studies on small datasets. Exploiting the exactly reversible encoder-decoder structure of normalizing flows, we perform on-manifold perturbations in the latent space to define fully unsupervised data augmentations. We demonstrate that such perturbations match the performance of advanced data augmentation techniques -- reaching 96.6% test accuracy for CIFAR-10 using ResNet-18 and outperform existing methods, particularly in low data regimes -- yielding 10--25% relative improvement of test accuracy from classical training. We find that our latent adversarial perturbations adaptive to the classifier throughout its training are most effective, yielding the first test accuracy improvement results on real-world datasets -- CIFAR-10/100 -- via latent-space perturbations.
RANCANG BANGUN AUTOMATIC CLOSE-TRANSITION TRANSFER SWITCH (ACTS) DENGAN SISTEM BACK-UP CATU DAYA UPS

RANCANG BANGUN AUTOMATIC CLOSE-TRANSITION TRANSFER SWITCH (ACTS) DENGAN SISTEM BACK-UP CATU DAYA UPS
IMPROVING THE STUDENTS’ VOCABULARY MASTERY THROUGH WORD SQUARE GAME AT THE EIGHTH GRADE OF SMP DWIJENDRA DENPASAR IN THE ACADEMIC YEAR 2019/2020

The aim of this research was to know the process of improve the students’ vocabulary mastery through word square game for eighth grade stuxdents of SMP Dwijendra Denpasar in the academic year 2019/2020. The subject was the students of VIII D in the academic year 2019/2020. This class consists of 30 students. In collecting the data, the researcher used test. The test were given in pre-test, post-test 1 and post-test 2. The researcher analyzed the mean score of each test to find out the improvement of students’ vocabulary mastery after the action was conducted. The researcher conducted the action the students’ vocabulary mastery increased optimally. It could be seen from the score that pre-test was 61,55, post-test 1 was 71,03, and post-test 2 was 80. After apply the action the researcher was able to solve the problem in improve vocabulary mastery. The students were able to take the word meaning based on the context. The use of word square game in teaching vocabulary, students could easly understand and memorize new vocabulary. In the teaching process, when the teacher used word square game, the students were enthusiastic and enjoy during teaching learning process.
A Comparison of Sentence-Weighting Techniques for NMT.

Sentence weighting is a simple and powerful domain adaptation technique. We carry out domain classification for computing sentence weights with 1) language model cross entropy difference 2) a convolutional neural network 3) a Recursive Neural Tensor Network. We compare these approaches with regard to domain classification accuracy and and study the posterior probability distributions. Then we carry out NMT experiments in the scenario where we have no in-domain parallel corpora and and only very limited in-domain monolingual corpora. Here and we use the domain classifier to reweight the sentences of our out-of-domain training corpus. This leads to improvements of up to 2.1 BLEU for German to English translation.
Nearest Neighbour Few-Shot Learning for Cross-lingual Classification

Even though large pre-trained multilingual models (e.g.mBERT, XLM-R) have led to significant performance gains on a wide range of cross-lingual NLP tasks, success on many downstream tasks still relies on the availability of sufficient annotated data.Traditional fine-tuning of pre-trained models using only a few target samples can cause over-fitting.This can be quite limiting as most languages in the world are under-resourced.In this work, we investigate cross-lingual adaptation using a simple nearest neighbor few-shot (< 15 samples) inference technique for classification tasks.We experiment using a total of 16 distinct languages across two NLP tasks-XNLI and PAWS-X.Our approach consistently improves traditional fine-tuning using only a handful of labeled samples in target locales.We also demonstrate its generalization capability across tasks.* Work done while Saiful was interning at Amazon AI 1 We loosely use the term LM to describe unsupervised pretrained models including Masked-LMs and Causal-LMs
Assessing the effects of the modular approach in math learning on independent creativity of university students

Numerous teachers and researchers are studying the issue of improving the effectiveness of university education and offer innovative technologies to address this challenge. Modular learning is among the most relevant and productive teaching techniques. The paper examines how the modular approach in math learning contributes to the development of independent creativity of university students. The testing was performed at Tyumen Industrial University (Russia) among students of the Applied Geology program numbering 28 individuals in the control group and 27 individuals in the experimental group. The students were given a series of lectures to present new material that was later assimilated and reinforced during practical sessions through blocks and chains of preparatory and auxiliary tasks. To demonstrate their knowledge and grasping of the material, the students passed individual tests and exams. Statistical data were processed using Pearson’s chi-squared test and the Wilcoxon signed-rank test. Based on the decision-making rule, the research confirms the hypothesis that the modular approach is more effective in forming students’ independent creativity in math learning if compared with conventional education. The research results demonstrate that 92% of students in the experimental group set about solving advanced math problems, while in the control group this share was 61%. The share of students in the experimental group who prepared research projects increased from 52% to 89%, while in the control group their number decreased from 56% to 43%. Among the avenues for further research is an attempt to implement applied research projects not only in math learning, but also in applied subjects of study throughout the entire training period. The development of independent creativity of university students is expected to have a positive effect on their ability to absorb the material of other courses.
CLASSIFICATION OF PARTIAL DISCHARGE FAULTS BASED ON SIGNAL PEAKS AND LOCATIONS

Diagnosis of the partial discharge (PD) faults protects the insulation of the high voltage equipment from the breakdown issues.Many techniques are used to capture and analyse the PD signals that emit in the case of PD faults.In this work, a new application of the peak-finder algorithm is employed to classify among the PD faults that result from different PD sources.The artificial defects are made in different types of high voltage insulation such as mica and the cross-linked polyethylene (XLPE) insulation of the power cable in the laboratory to capture PD data using Portable PD Analyzing System (LDS-6).The high accuracy is obtained for the classification of the PD signals that developed from different PD sources, which is 93.34% of mica insulation and 86.67% for XLPE insulation for power cable.The results of the PD type classification accuracies refer to the high performance of the proposed technique to extinguish among the different sources of PD.
Використання інформаційно-комунікаційних технологій на заняттях з іноземної мови

International scientific and practical conference «Pedagogy, psychology and teaching methods: international experience» : conference proceedings, July 16–17, 2021. Riga, Latvia : «Baltija Publishing», 2021. 295 pages.