Reviewerly/exHarmony huggingface dataset:
Covid-19 Sentiment Analysis Using Deep Learning and Machine Learning

As we see in later days the covid-19 is spreading broadly. In this the individuals from diverse places within the world discussing about this widespread in numerous ways. So In this respect here we are employing a estimation examination to classify each and each survey of the individuals. What estimation examination will do is it’ll qualify and measure the comes about agreeing to the voice of client so for this individuals reaction is taken from online platform such as twitter stack the information and store this information in shape of datasets after that we got to do investigation on information utilizing conclusion mining. In this venture we got to take the covid-19 tweets information from twitter, based on the information we need to made the investigation of the information by utilizing the opinion analysis. In this venture we have long shortterm memory(LSTM), Näıve Bayes and Calculated Regression. Then we discover the exactness’s of each calculations based on that we’ll conclude that which calculation will be great in arrange to execute assumption investigation.
Modified British Parliamentary Debate Technique in Teaching Speaking to Indonesian EFL Learners

For English language learners, speaking is an essential skill that should be achieved. By practicing continuously, they can become trained and skilled. To support their proficiencies and competencies, they also should master the language subskills: pronunciation, structure, and vocabulary. The teachers, therefore, should facilitate their students by applying appropriate techniques of language learning in the classroom so that their students can speak English quickly. Through this study, the researchers managed an effective teaching technique for speaking class by implementing a modified British Parliamentary Debate to train the students' speaking skills. This study, therefore, projected to find out whether or not the use of the Modified British Parliamentary Debate technique in teaching speaking can increase their speaking skill. This study also aims to determine whether or not the students are interested in learning to speak through the modified British parliamentary debate. The study applied the quasi-experimental method with a nonequivalent control group design. The subjects of the study were students of Madrasah Aliyah Negeri Enrekang, Indonesia. The population of the research was 64 students. The researchers grouped the students into two groups. There were 32 students in group one and 32 students in group two. The researchers assigned both groups to the same activities in pretest and posttests but different treatments of teaching techniques. The researchers gave a modified British parliamentary debate model for the experimental group and a small group discussion for the control one. The instruments of the research were an oral speaking test and a questionnaire. The results of data analysis exhibited a significant improvement in the students' speaking skills after the treatments. The result of hypothesis testing showed that the t-test value (2.087) was higher than the t-table value (2.000) at the level of significance 0.05 and the degree of freedom 62. Moreover, based on the questionnaire, this study found that the students were interested in learning the speaking skill through modified British Parliamentary debate. In short, implementing the modified British parliamentary debate in teaching speaking can develop the students' speaking skills and encourage the students to learn speaking ability.
University contribution to the development of the region: ecosystem approach

Problem and purpose. Assessment of the contribution of universities to the socio-economic development of regions, technological and innovative progress of industry are topical issues of the modern agenda for the modernization of higher education in the Russian Federation. The authors propose a methodology for assessing the contribution of universities to regional development from the standpoint of the ecosystem approach, which makes it possible to reconfigure the development programs of the actors of the regional ecosystem "Education – Science – Industry" in order to achieve the tasks of technological progress and socio-economic development of the region. Research methods. When determining indicators using the ecosystem concept, it was taken into account that the initial components for the work of each actor of the regional ecosystem "Education – Science – Industry" are the results of the activity of one of these components. When using the system theory in determining the groups of indicators, the process, environmental and design components of the regional ecosystem "Education – Science – Industry" were identified. Results. Eight blocks of subsystems of indicators of the university's contribution to regional development have been formed: in integration, investment processes and technological development of the region, innovative development of the region, demographic development of the region, labor market of the region, social development of the region, intellectual potential of the region, infrastructure of the region, economy of the region. The indicators of the efficiency (effectiveness) of the university ("internal" efficiency of the university) and the indicators of the university's contribution to the development of the region are distinguished. The indicators are divided into short-term (allowing to evaluate the university's contribution as the effect of the university's activities, which manifests itself within 1-2 years) and long-term (allowing to evaluate the university's contribution as the effect from the university's activities, which manifests itself in 5-7 years). The indicators are differentiated by groups (priority 1, priority 2, priority 3) taking into account the close relationship between the indicator and the indicator of the university's contribution to regional development. In the conclusion, the possibilities of practical use of the methodology for analyzing the performance of the university in the region and adjusting the programs for the development of universities in the regional ecosystem, including when assessing the effectiveness of the implementation of the Priority 2030 program, are shown.
Аспект виховання під час лекції у контексті виховання у вищій школі і глобальних питань формування особистості

International scientific conference «Modern European psychological and pedagogical education. The development of a creative learning environment» : conference proceedings, October 8–9, 2021. Łódź, the Republic of Poland : “Baltija Publishing”, 2021. 162 pages.
A Hierarchical Entity Graph Convolutional Network for Relation Extraction across Documents

Distantly supervised datasets for relation extraction mostly focus on sentence-level extraction, and they cover very few relations.In this work, we propose cross-document relation extraction, where the two entities of a relation tuple appear in two different documents that are connected via a chain of common entities.Following this idea, we create a dataset for two-hop relation extraction, where each chain contains exactly two documents.Our proposed dataset covers a higher number of relations than the publicly available sentencelevel datasets.We also propose a hierarchical entity graph convolutional network (HEGCN) model for this task that improves performance by 1.1% F1 score on our two-hop relation extraction dataset, compared to some strong neural baselines.
A FRAMEWORK BASED ON BLOCKCHAIN FOR ELECTORAL VOTING SYSTEM

Electoral voting system is the pillar to maintain the democratic freedom of any country. The fair and transparent organization of election is the basic need of the country. Many countries are basically using one of two ways to conduct election either using ballot paper or using electronic voting machines. Each one has its own pros and cons. The fast, trust and e-voting is the need of future. In recent years, blockchain technology is rapidly adopted in various fields by various organizations. The Decentralized and cryptographic algorithms are the major reason behind this. Considering the increasing issue of security, trust in the traditional Voting System and future requirements, this paper proposes a framework for E-Voting system based on blockchain technology. This paper discusses the network architecture for blockchain technology, framing the processing casting votes and counting of votes. The analysis of various issues and challenges in electoral system is carried out in context of the proposed framework. This framework may improve the security and decreases the cost of hosting nationwide elections
Tertiary study on the application of augmented reality in education

The aim of this work is to carry out a tertiary study on the use of Augmented Reality (AR) in education, based on a set of five research questions. This review will greatly benefit researchers who wish to conduct research on the topic for the first time. In addition, this study extends to new researchers due to the compilation of important information that was collected through Systematic Literature Reviews RSL. It was concluded that the research questions were answered based on the findings and it is also possible to observe the expansion of technologies, AR research fields and target audience by each author.
PENGEMBANGAN SIMIPA BERBASIS ANDROID MENGGUNAKAN METODE SCRUM PADA MODUL MAHASISWA

Academic activities are a learning process that is carried out based on the curriculum in university to produce quality graduate students. Good academic activities can be supported by having a system that helps academic activities at a university. FMIPA University of Lampung currently has a web-based MIPA information system (SIMIPA) which is used as a system that can support the administrative service process for FMIPA University Lampung students. Information technology that is currently developing rapidly shows that there is a need for development to be done on the SIMIPA as an effort to increase the benefits of SIMIPA. Development of an android-based student module SIMIPA application is one of the systems developed to improve services for FMIPA students at the University of Lampung. This application development will use the Scrum method. The scrum method is a software development framework from implementing Agile Development method for software projects. Development of this application is based on the product backlog which is divided into 8 sprints. The result of this research is the successful development of the SIMIPA application module for academic students using Scrum method. This is evidenced by testing using black box testing which shows the overall functional needs of the student module SIMIPA application as expected.
SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization

Multilayer-perceptrons (MLP) are known to struggle with learning functions of high-frequencies, and in particular cases with wide frequency bands. We present a spatially adaptive progressive encoding (SAPE) scheme for input signals of MLP networks, which enables them to better fit a wide range of frequencies without sacrificing training stability or requiring any domain specific preprocessing. SAPE gradually unmasks signal components with increasing frequencies as a function of time and space. The progressive exposure of frequencies is monitored by a feedback loop throughout the neural optimization process, allowing changes to propagate at different rates among local spatial portions of the signal space. We demonstrate the advantage of SAPE on a variety of domains and applications, including regression of low dimensional signals and images, representation learning of occupancy networks, and a geometric task of mesh transfer between 3D shapes.
Credit scoring development in the light of the new Brazilian General Data Protection Law

With the advent of the new Brazilian General Data Protection Law (LGPD) which determines the right to the explanation of automated decisions, the use of non-interpretable models for human beings, known as black boxes, for the purposes of credit risk assessment may remain unfeasible. Thus, three different methods commonly applied to credit scoring – logistic regression, decision tree, and support vector machine (SVM) – were adjusted to an anonymized sample of a consumer credit portfolio from a credit union. Their results were compared and the adequacy of the explanation achieved for each classifier was assessed. Particularly for the SVM, which generated a black box model, a local interpretation method – the SHapley Additive exPlanation (SHAP) – was incorporated, enabling this machine learning classifier to fulfill the requirements imposed by the new LGPD, in equivalence to the inherent comprehensibility of the white box models.
The Development and Value of Blockchain Technology + Higher Education under the Background of China's Higher Education Reform and Innovation

With the popularization of higher education in China, promoting the development of higher education informatization is an important subject to realize the connotative development of higher education. In May 2018, dozens of colleges and universities across the country jointly established the blockchain alliance, named Youth Education Chain , initiated by x-lab of tsinghua university and announced the launch of Youth Education Chain . This is the first blockchain-based public education chain jointly built by universities in the world. By taking the establishment of Youth Education Chain platform as the entry point, this paper holds that the university enrollment based on Youth Education Chain will be of great value to the reform and innovation of China's higher education in the aspects of constructing the Shared education ecology, changing the traditional teaching mode and improving the efficiency of school management.
Low-Cost Machine Learning for Effective and Efficient Bad Smells Detection

Bad smells are characteristics of software that indicate a code or design problem which can make information system hard to understand, evolve, and maintain. To address this problem, different approaches, manual and automated, have been proposed over the years, including more recently machine learning alternatives. However, despite the advances achieved, some machine learning techniques have not yet been effectively explored, such as the use of feature selection techniques. Moreover, it is not clear to what extent the use of numerous source-code features are necessary for reasonable bad smell detection success. Therefore, in this work we propose an approach using low-cost machine learning for effective and efficient detection of bad smells, through explicit feature selection. Our results showed that the selection allowed to statistically improve the effectiveness of the models. For some cases, the models achieved statistical equivalence, but relying on a highly reduced set of features. Indeed, by using explicit feature selection, simpler models such as Naive Bayes became statistically equivalent to robust models such as Random Forest. Therefore, the selection of features allowed keeping competitive or even superior effectiveness while also improving the efficiency of the models, demanding less computational resources for source-code preprocessing, model training and bad smell detection.
Forecasting of solar irradiance and ramp events with all-sky imagers

&amp;lt;p&amp;gt;Cloud cameras (all sky imagers/ASIs) can be used for short-term (next 20 min) forecasts of solar irradiance. For this reason, several experimental and operational solutions emerged in the last decade with different approaches in terms of instrument types and forecast algorithms. Moreover, few commercial and semi-prototype systems are already available or being investigated. So far, the uncertainty of the predictions cannot be fully compared, as previously published tests were carried out during different periods and at different locations. In this study, the results from a benchmark exercise are presented in order to qualify the current ASI-based short-term forecasting solutions and examine their accuracy. This first comparative measurement campaign carried out as part of the IEA PVPS Task 16 (https://iea-pvps.org/research-tasks/solar-resource-for-high-penetration-and-large-scale-applications/). A 3-month observation campaign (from August to December 2019) took place at Plataforma Solar de Almeria of the Spanish research center CIEMAT including five different ASI systems and a network of high-quality measurements of solar irradiance and other atmospheric parameters. Forecasted time-series of global horizontal irradiance are compared with ground-based measurements and two persistence models to identify strengths and weaknesses of each approach and define best practices of ASI-based forecasts. The statistical analysis is divided into seven cloud classes to interpret the different cloud type effect on ASIs forecast accuracy. For every cloud cluster, at least three ASIs outperform persistence models, in terms of forecast error, highlighting their performance capabilities. The feasibility of ASIs on ramp event detection is also investigated, applying different approaches of ramp event prediction. The revealed findings are promising in terms of overall performance of ASIs as well as their forecasting capabilities in ramp detection. &amp;amp;#160;&amp;lt;/p&amp;gt;
PERANCANGAN MOTION GRAPHIC PENGENALAN DESAIN KOMUNIKASI VISUAL UNTUK SISWA SMA-SMK

This study focuses on making motion graphics for the introduction of visual communication design (VCD) for high schools in Tegal and surrounding areas with the aim of being a promotional medium for the D-III VCD study program at the Harapan Bersama Polytechnic. Motion graphics have advantages when used in advertising, which are cost-effective and time-consuming, with educative and communicative animations that make it easy for the target audience to understand the images and ideas that are presented in a simple and attractive way in an animation, the audience in this case is high school and vocational high school students. more interested in watching a video than reading text, this makes the content shareable across social media networks. Motion graphics are made using techniques and in several stages including initial concepts, script or narration writing, storyboarding, sound (voiceover, music and sound effects) and animation. As well as information on the introduction of VCD that was conveyed in the form of the definition of VCD, the scope of the VCD field of science, the role and application of VCD, VCD universities and the advantages of the D-III VCD study program at the Harapan Bersama Polytechnic. Through this research, it is hoped that it can become a benchmark for the development of animation and visual advertising communication in the D-III VCD study program and in addition to being a promotional media for this research, it is also a learning medium for students in motion graphics courses. So that students can understand the flow, concepts and techniques or stages in making motion graphic advertising videos. Keywords : Introduction VCD, Motion Graphic, R&amp;D, Promotion, Video Profil
IMPLEMENTING MICROSOFT OFFICE 365 FOR INNOVATION ELT PRACTICES FACING COVID 19

ABSTRACT: This study deals with teaching English by using Microsoft office 365 for innovation ELT Practices in Students in Junior High School in facing Corona 19. As one of the communicative skills, reading should be achieved by the student to be able understand English. Unfortunately, some students have difficulties to study English at school when Covid 19 spreads in Indonesia. Students have to stay at home to stay safe. Therefore, implementing Microsoft Office 365 for innovation ELT practices facing Covid 19 of students in eight grade of Junior High School are expected to increase students ‘ability to understand English about general truth. The objective of this study are to find out how the teacher implement Microsoft Office 365 and how the students’ ability to understand general truth by using Microsoft Office 365. The assessment of implementing Microsoft Office 365 for innovation ELT Practices in Students of Junior High School was analyzed by using Microsoft Office 365‘s scoring rubric which consists of analysis students’ answer. The results of this research can be formulated as follows: 1) Students can answer questions of general truth well based on Microsoft Office responses from students.2) Students’ scoring analysis to answer general truth is described Microsoft Office 365 that most students achieve 90 when they answered general truth questions that can be found in Microsoft Office 365 of students ‘response.
Дистанційне навчання в контексті розвитку правової компетентності педагогічних працівників економічних коледжів

International scientific conference «Modern European psychological and pedagogical education. The development of a creative learning environment» : conference proceedings, October 8–9, 2021. Łódź, the Republic of Poland : “Baltija Publishing”, 2021. 162 pages.
Використання сучасних цифрових ресурсів для розвитку іншомовної компетентності військових фахівців

International scientific conference «Modern European psychological and pedagogical education. The development of a creative learning environment» : conference proceedings, October 8–9, 2021. Łódź, the Republic of Poland : “Baltija Publishing”, 2021. 162 pages.
Dye Amount Estimation in a Papanicolaou-stained specimen using Multispectral Imaging

Papanicolaou stain is mainly used in cytological diagnosis such as gynecological diseases.In the image analysis of stained histopathology specimens, color unmixing technique, which estimates the dye abundance map, is useful.In this paper, we apply the dye amount estimation method based on color unmixing to Papanicolaou-stained specimen.In the proposed method, we capture the Papanicolaou-stained samples using a multispectral microscope, and then we estimate the amount of dyes from the observation and practically measured the spectral characteristics of the stain.Besides, we construct an application depicting the amount of stain and the bar-graph plot.In the experiments, we verify the feasibility of the proposed method and analyze a precancerous lesion of the uterine cervix using the proposed method.
THE PERFORMANCE ANALYSIS OF HEALTH, SAFETY, ENVIRONMENT, AND ENERGY INTEGRATED MANAGEMENT SYSTEM (HSEE-IMS) USING FUZZY COGNITIVE MAPPING METHOD

The performance assessment of strategic levels of an integrated management system (IMS) is critical to policy making phase of executive organizations.Because, the integrity of objectives and strategies in the overall system performance insures the integrity of activities and performance in the subsidiary departments and units.Unfortunately, this approach of assessment has been rarely focused.Here, the Fuzzy Cognitive Mapping-Relative Degree Analysis (FCM-RDA) technique was chosen to assess the performance trend of the health, safety, environment, and energy (HSEE)-IMS in a ministry during 2014-2019.There were 12 HSEE-IMS strategic sub-elements and 6 system sub-performances.The Gephi0.9.2 software was applied to simulate the FCM model.Accordingly, the sub-performance of policy and leadership was placed at the first priority.The development of HSEE management, and review (of policies and programs) were two HSEE-IMS sub-elements, categorized in the second priority.The results showed an ascending trend of the system performance during 2014-2018 and a descending trend during 2018-2019.It was found that the poor performance of HSEE-IMS sub-elements in the strategic and tactical levels resulted in the poor performance of system at the operational levels.There was found a strong relationship between the HSEE-IMS sub-elements and system sub-performances.