Reviewerly/exHarmony huggingface dataset:
The Educational Impact of Distance Learning during the COVID-19 Pandemic on Students' Interaction in the Educational Process

Due to the widespread impact of the Covid 19 pandemic, teachers and students were driven to relocate their teaching learning practices to the safety of their own homes. The goal of this research was to learn how Saudi students felt about distance learning online during the lockout of the College of Science and Humanities at Sulail, Prince Sattam Bin Abdullah University. Multiple methods were used to complete the study. Researchers collected data from 152 degree students of Management,Computer Science, English, Islamic Studies, Arabic department to rate their satisfaction with online learning settings using a Likert scale ranging from one to five points. A mixed research strategy was chosen for the study's purposes, with descriptive analysis used for the quantitative data analysis and content analysis used for the qualitative data analysis. Although some respondents expressed enthusiasm for online distance learning, the vast majority reported difficulties with the format and stated a preference for traditional in-person classes. Some students have expressed enthusiasm for this form of distance education. The study concluded that the findings can help policymakers and professors construct effective or efficient teaching ways to overcome difficult situations or pandemics, which is a summary of the study's main points.
Peculiarities of Bulgarian universities' digitalization during the Covid-19 pandemic

The COVID-19 pandemic forced the education system to transform quickly from a straightforward traditional process to an online one.Both schools and universities, including their management and administration) were challenged to maintain the quality of the educational service they provided, but this time under completely different conditions and in a new and unfamiliar online environment.In Bulgaria, due to the rules of the systems and the academic autonomy, each university had the opportunity to decide how to deal with these force major circumstances.Along with the technical challenges, professors have to overcome the difficulties related to the motivation and engagement of the students in such a mediated environment.The main objective of the current article is to evaluate the results of the online learning process during the COVID-19 pandemic in Bulgaria.The results from empirical research (N = 140) clearly show that most Bulgarian lecturers prefer face-to-face learning.At the same time, they admit the necessity of specific training for technical skills improvement and different approaches for students' attention and engagement in online learning.According to the professors, the overall assessment for the level of satisfaction from online learning during the COVID-19 pandemic is in the golden mean -3 on a scale of 1 -"not at all effective" to 5 -"it is effective".
PENDAMPINGAN PESERTA DIDIK DALAM UPAYA MENINGKATKAN KREATIVITAS SISWA SERTA PENAMBAHAN WAWASAN PUBLIK SPEAKING DI UPT SDN 42 GRESIK

Abstract&#x0D; This study aims to understand in an effort to increase student creativity and increase public speaking insight at UPT SDN 42 Gresik. This research is motivated by the lack of teacher approach and assistance to students so that student creativity is still minimally formed. This research is a qualitative research that directly provides assistance to students. The subjects in this study were students at UPT SDN 42 Gresik. Data collection techniques in this study used oral and practical tests. The data analysis technique used descriptive analysis and cycle results. The descriptive results explain that the students' ability in creativity is very high, and the ability of public speaking is also very good. Judging from the results of the cycle table that cycle 1 before mentoring the average student is 34% in creativity and explaining lessons in front of his friends, and the average student in cycle 2 is 48% in creativity and explaining lessons in front of friends - friends, while after mentoring the average student in cycles 1 and 2 was 69% and 85% in creativity and explaining lessons in front of their friends.&#x0D; &#x0D; Keywords : Mentoring, Student Creativity, Adding Public Speaking Insights.
(Non-)specificity across languages: constancy, variation, v-variation

Indefinites are known to give rise to different scopal (specific vs non-specific) and epistemic (known vs unknown) uses. Farkas &amp; Brasoveanu (2020) explained these specificity distinctions in terms of stability vs. variability in value assignments of the variable introduced by the indefinite. Typological research (Haspelmath 1997) showed that indefinites have different functional distributions with respect to these uses. In this work, we present a formal framework where Farkas &amp; Brasoveanu (2020)’s ideas are rigorously formalized. We develop a two-sorted team semantics which integrates both scope and epistemic effects. We apply the framework to explain typological variety of indefinites, their restricted distribution and licensing conditions, and some diachronic developments of indefinite forms.
Educational and Professional Programme “Online Journalism and Blogging”: Interdisciplinary Content of the Speciality “Information, Library and Archival Management”

The aim of the study is to identify and substantiate the list of competencies required by a specialist within the interdisciplinary major “Online Journalism and Blogging” in the field of study “Information, Library, and Archival Management”. The research methodology is based on the use of a set of general scientific and special methods: analysis and synthesis, the method of comparative analysis for comparing the standards of higher education, which form the subject field of activity of a future specialist majoring in “Online Journalism and Blogging” in the field of study “Information, Library, and Archival Management”; the method of content analysis in the study of texts and documents; a hypothetical method for justifying the need for online journalism in the activities of institutions and the infrastructure of the document and information sphere. The scientific novelty consists in identifying the list of competencies required by a specialist within the interdisciplinary major “Online Journalism and Blogging” in the field of study “Information, Library and Archival Management” and substantiating the main focus of the educational programme, which is outlined as the formation and development of professional competence in providing press strategies in various forms of their implementation in the digital social and information environment as an integrative activity that includes information (document)-communicative and journalistic components. Conclusions. Increasing the competitiveness of modern specialists is normalised today by the introduction of interdisciplinary educational programmes into the educational process. The offer of the educational and professional programme “Online Journalism and Blogging” in the field of study “Information, Library and Archival Management” provides for mastering the knowledge related to the programme subject areas 061 Journalism and 029 Information, library and archival management, which determine its subject area, and the integration of educational content in these fields. The projected activity of the future specialist in the educational and professional programme “Online Journalism and Blogging” is within the framework of such basic concepts as “information resource” – “social communications” – “information product” in their interconnection and mediation by the use of digital technologies. The main focus of the educational programme and major is the formation and development of professional competence in providing press strategies in various forms of their implementation in the digital social and information environment as an integrative activity that includes information (document)-communicative and journalistic components.
INTERACTION AS A CRITERION OF MATERIALITY AND THE BASIS FOR OPERATIONAL DEFINITION OF MATTER

Проанализированы имеющиеся определения материи (П. Гольбаха, Г.В. Плеханова и В.И. Ленина). Сделан вывод о том, что для этих однотипных определений характерен сенсуализм. Кроме того, сформулирован вывод о том, что не движение, как полагал Ф. Энгельс, а взаимодействие является основным атрибутом, признаком материи, критерием материальности. Взаимодействие данного объекта с другими материальными телами, включая физические приборы и органы чувств человека, положено в основу предложенного нами определения материи. Analyzing the existing definitions of matter (P. Holbach, G.V. Plekhanov and V.I. Lenin), we made a conclusion that sensualism inherent to these similar definitions may be considered as their main drawback. In addition, it was concluded that not motion, as F. Engels believed, but interaction is the main attribute, a signature of matter, a criterion of materiality. The interaction of an object with other material bodies, including physical instruments and the human sense organs, is the basis of our operational definition of matter. Concepts of the energy and mass, considered as basic characteristics of material bodies and material physical fields, are also discussed.
Monetary Conditions Index and Economic Activity in Dollarized Zimbabwe

Purpose: Zimbabwe has experienced a chronic inflationary crisis whose roots can be traced back to 1997. Various macroeconomic instruments have been suggested to stabilize the country’s prices and foster economic growth but evidence on how they interplay to influence policy is lacking. This study developed a monetary conditions index (MCI) for Zimbabwe during the 10-year dollarization period, 2009 to 2018, and measured its correlation with economic activity. The aim of the MCI is to inform monetary policy making in Zimbabwe. Design/methodology/approach: Using monthly time series data, the MCI series from 2009 to 2018 was calculated using real interest rates and exchange rates. The relationship between the MCI, GDP, inflation, money supply and private sector credit was analysed using the Auto Regressive Distributed Lag (ARDL) model for the long-term relationship and Granger causality for the short term. Findings: Results showed MCI weights of 1:1.54 implying that exchange rates dominate the interest rate in Zimbabwe’s monetary policy. A long run relationship between the MCI and economic variables was statistically significant while short term relationships were established for private sector credit, GDP, and foreign interest rates. Research implications: The study concludes that the MCI is a useful indicator of the central bank’s monetary policy positionfor economic analysts while the central bank can also adopt it for inflation and growth targeting. Originality/value: Unlike previous research which has proffered monetary solutions based on specific variables, this study took into consideration the interplay between interest rates and exchange rates in determining economic activity in Zimbabwe. The constructed MCI captured the interplay between these two key variables and the study established its relationship with economic activity. On this basis, the study recommends the adoption of the MCI in guiding monetary policy in Zimbabwe.
A Neural Network-Based Algorithm for Weak Signal Enhancement in Low Illumination Images

There is noise interference in low-illumination images, which makes it difficult to extract weak signals.For this reason, this paper proposes a low-illumination image weak signal enhancement algorithm based on neural network.Multi-scale normalization is performed on low-light images, and multi-scale Retinex is used to enhance weak signals in low-light images.On this basis, the GAN artificial neural network is used to detect the weak signal of the weak signal in the image, the normalization of the weak signal of the low-illumination image is completed based on the residual network, the self-encoding parameters of the depth residual are generated, and the weak signal enhancement result of the low-illumination image is output.The experimental results show that the method in this paper has better enhancement effect on low-illumination images and better image denoising effect.When the scale value is large, the low-contrast area of the low-illumination image has a better enhancement effect.The saturated area of the low-light image has a better enhancement effect.
An Adaptive Texture Enhancement Algorithm for AR Live Screen Based on Approximate Matching

In order to improve the visual effect of AR live video detail texture, an adaptive enhancement algorithm based on approximate matching is proposed.According to the local self-similarity of the original image, the best matching block of the initial super-resolution image block is obtained.After extracting its high-frequency information, the improved singular value decomposition (SVD) is used to embed the watermark into the original super-resolution gray image; And through the watermark extraction and reconstruction matrix, the effective high-frequency detail texture information is obtained, then the final super-resolution image is obtained, and the AR live video detail texture enhancement is completed.The experimental results show that the peak signal-to-noise ratio, structure similarity and feature similarity of the algorithm are high, and the reconstruction effect is good; After detail texture enhancement, the detail texture clarity and edge sharpness of AR live picture are better, and the best visual effect is achieved.
Research on the Application of Virtual Technology-based Posture Detection Device in Swimming Teaching

With the socio-economic development, the national demand for playing leisure sports has increased, and swimming is one of the popular choices.To help swimming beginners understand the correct swimming posture more quickly and directly, hybrid neural network algorithms based on sliding window detection and deep residual networks are designed in this study, and two corresponding virtual image classification models of swimmer's posture are designed based on these algorithms.In order to reduce the noise of the input data and reduce the cost of data collection, the virtual reality technology is used to convert the swimmer's swimming pose image into the image model in the virtual reality space as the input data of the algorithm.The performance test experimental results show that the classification accuracy of the swimmer pose recognition models based on PTP-CNN algorithm and SW-CNN algorithm designed in this research are 97.48% and 96.72% respectively on the test set, which are much higher than other comparison models, and the model built based on PTP-CNN algorithm has the fastest computation speed.The results of this research can be applied to assist participants in swimming pose recognition in teaching beginner swimmers.
Synthetic aperture radar image despeckling using convolutional neural networks in wavelet domain

Abstract It is difficult for a convolutional neural network (CNN) to capture the detailed features of synthetic aperture radar (SAR) images when increasing the network depth. To capture sufficient information for reconstructing image details, the authors propose a multidirectional and multiscale convolutional neural network (MMCNN) in which the wavelet subband is input into each independent subnetwork to be trained. Each subnetwork has few convolution layers and a loss function. When the loss function reaches its optimal value, all subbands are integrated to produce the despeckled SAR image through the inverse Wavelet transform. The proposed MMCNN consisting of multiple subnetworks extracts the detailed features and suppresses speckle noise from different directions and scales; thus, its performance is improved by broadening the network width rather than increasing the depth. Experimental results on synthetic and real SAR images show that the proposed method shows superior performance over the state‐of‐the‐art methods in terms of both quantitative assessments and subjective visual quality, especially for strong speckle noise.
HYBRID LOAD BALANCING POLICY TO OPTIMIZE RESOURCE DISTRIBUTION AND RESPONSE TIME IN CLOUD ENVIRONMENT

Load balancing and task scheduling are the main challenges in Cloud Computing. Existing load balancing algorithms have a drawback in considering the capacity of virtual machines while distributing loads among them. The proposed algorithm works toward solving existing issues, such as fair load distribution, avoiding underloading and overloading, and improving response time. It implements best practices of Throttled load balancing algorithm and Equally Shared Current Execution algorithm. Virtual machines are selected based on the ratio of their bandwidth and load allocation count. Requests are sent to a Virtual Machine with higher bandwidth and lower load allocation count. Proposed algorithm checks for the availability of VM based on their capacity. This process is performed by selecting two VMs and comparing their vmWeight capacity. The one with the least vmWeight is selected. CloudAnalyst is used for simulation, response time evaluation, and resource utilization evaluation. The simulation result of the proposed algorithm is compared with three well-known load-balancing algorithms. These are Round Robin, Throttled Load balancing algorithm, and Enhanced Active Monitoring. Load-balancing Proposed Algorithm selects VMs based on their Algorithm. The proposed algorithm has improved over other algorithms in load distribution, response time, and resource utilization. All virtual machines in the data centers are loaded with a relatively equal number of tasks according to their capacity. This resulted in fair resource sharing and load distribution.
Pembelajaran E-Learning Berbasis Google Clasroom Berbantuan Vidio Youtube pada Materi Statistika untuk Meningkatkan Motivasi Belajar Siswa Kelas XII-IPS 4 SMAN 3 Selong

This Classroom Action Research aims to increase the motivation to study statistics for class XII IPS-4 SMAN 3 Selong through Google Classroom-based E-learning learning assisted by YouTube videos and describe the increase in learning motivation for class XII IPS-4 SMAN 3 Selong through Google-based E-Learning Classroom assisted by youtube videos. The condition of the Covid-19 pandemic requires implementing physical distancing so that face-to-face learning cannot be carried out and learning is forced to be carried out online (online) and student motivation is still low in learning mathematics. This research was conducted in two cycles of 30 students. Data collection techniques through observation and motivational questionnaires. The implementation of Google Classroom-based E-Learning assisted by YouTube videos is stated in very good, good, quite good, not good, and not good categories, while the motivation to learn mathematics is expressed in very high, high, medium, low and very low categories. Based on the results of the research conducted, it can be concluded as follows: 1) the implementation of Google Classroom-based E-Learning assisted by YouTube videos in cycle I was in the fairly good category and in cycle II in the good category. 2) Motivation to learn statistics material for class XII IPS-4 SMA Negeri 3 Selong in cycle I was low, cycle two was moderate, namely in cycle I the average motivation to learn mathematics was 66.3% while in cycle II it rose to 72.4% .
A New Method of Galaxy Classification Using Optimal Convolution Neural Network

A galaxy classification system using Optimal Convolution Neural Network has been designed and developed. Broadly there are five different types of galaxies. They are elliptical, spiral, disk, lenticular and irregular. We have proposed an Optimal Deep Convolution Neural Network which learns the features of the different types of galaxies in the form of a set of filters and after the learning is over recognizes the type of the unknown galaxies. With this, the optimal point with data size as well as number of filters of neither overshooting nor undershooting is found out to get the optimal network complexity – which highly improves the performance evaluation. The performance evaluation of the CNN architecture used for galaxy classification in terms of its accuracy, precision, recall and f-score is quite satisfactory. Also the training and testing time is affordable.
Understanding KlimaDAO Use and Value: Insights from an Empirical Analysis

Blockchain technologies have demonstrated the potential to build decentralized finance (DeFi) protocols that are composable and interoperable. One of the envisioned applications of blockchains is that of becoming a platform for markets of greenhouse-gas emissions. KlimaDAO is one of the recently launched protocols that attempts to bridge existing voluntary carbon markets to DeFi by means of building incentive mechanisms on top of tokenized carbon assets. That approach may eventually bring benefits to carbon markets in terms of liquidity and transparency and address a wider audience. Here we report the analysis of the early status of that initiative in an attempt to get insights in its actual functioning and value, and on the extent to which they are currently addressing the original goals and potential benefits of this kind of protocols.
Integrating A Dialogue Tree Based Turkish Chatbot into an Open Source Python Coding Editor

In this study, a dialogue tree-based Turkish chatbot has been developed and integreted into the Pynar Python code editor in order to help the users with the questions they may ask while learning the python language. The Pynar Python Code editor is developed as a TÜBİTAK supported open source project. The architecture we propose has been developed in such a way that it can respond to users' questions and give emotional feedback through dialogs and emojis. It also runs completely offline, without being connected to any internet site or web service. The chatbot is coded using Python language and a Turkish NLP library and Qt GUI library. Considering the age and education levels of the target user group of the Pynar editor, our chatbot will provide great convenience to those who are trying to learn Python programming on their own, with the possibility of asking questions and getting answers in their native language.
Discussion on the Construction and Innovation of the Reader Service System of University Library Under the Network Environment

Based on the development of university library service in China, this paper analyzes the significance of university library service innovation and transformation under the "Internet plus" environment, puts forward the problems existing in the current university library service, first expounds the necessity of university library adapting to the new technological environment to build an innovative service system under the network environment, and then from the concept, management, resources The construction of innovative service system is discussed from five aspects of technology and service. This paper focuses on the analysis of the construction of the intelligent service mode of university libraries from the perspective of innovation and puts forward reasonable suggestions in order to improve the service ability of intelligent libraries and provide reference for people who pay attention to such topics.
LEKSIKON DAN GRAFEM BERDASARKAN VISUALISASI GAMBAR: KAJIAN PSIKOLINGUISTIK

There are two lexical problems in children, one of which is lexical mastery itself. The purpose of this research is to photograph the lexical picture possessed by children based on the visualization of images and conversations that are carried out during interactions. The research method uses a qualitative approach with observation and recording techniques. The subjects in this study were seven children located in three different locations. The results of lexical recording in general, children can pronounce correctly according to the meaning, although in some children it is still not in accordance with the meaning or the pronunciation. This is caused by environmental conditions and different children's lexical mastery