Reviewerly/exHarmony huggingface dataset:
Errors in the Russian Web Corpus

The explosion of the Web leads to the production of large amounts of texts and inevitably influences their quality. Errors that tend to occur more often can distort results, especially when texts are used for scientific purposes, in language teaching or learning. Hence, there is a need to examine the existing corpora based on web texts and to clean up the data, which may contain such “noisy” fragments. In our study, we turn to the problem of errors and analyze the Aranea Russicum Maximum corpus. Among such errors, we can name, above all, encoding errors, incorrect font types, as well as segments written in other languages. These phenomena result in incorrect morphological analysis and lemmatization, frequency distortion, as well as the fact that lexical units cannot be found and therefore displayed to corpus users. The paper focuses on the errors, describe their types and outline possible ways to eliminate them.
Modeling Multioutput Response Uses Ridge Regression and MLP Neural Network with Tuning Hyperparameter through Cross Validation

The multiple regression model is very popular among researchers in both field of social and science because it is easy to interpret and have a well-established theoretical framework.However, the multioutput multiple regression model is actually widely applied in the engineering field because in the industrial world there are many systems with multiple outputs.The ridge regression model and the Multi-Layer Perceptron (MLP) neural network model are representations of the predictive linear regression model and predictive non-linear regression model that are widely applied in the world of practice.This study aims to build multi-output models of a ridge regression model and an MLP neural network whose hyperparameters are determined by a grid search algorithm through the cross-validation method.The hyperparameter that produces the smallest RMSE value in the validation data is chosen as the hyperparameter to train both models on the training data.The hyperparameter in question is a combination of learning algorithms and alpha values (ridge regression), a combination of the number of hidden nodes and gamma values (MLP neural network).In the ridge regression model for alpha in the range between 0.1 and 0.7, the smallest RMSE is obtained for all learning algorithms used.While the MLP neural network model specifically obtained a combination of the number of nodes = 18 and gamma = 0.1 which produces the smallest RMSE.The ridge regression model with selected hyperparameters has better performance (in the RMSE and R2 value) than the MLP neural network model with selected hyperparameters, both on training and testing data.
USoil: Development of USCS-Based Soil Classifier Using Digital Image Processing and Convolutional Neural Network

The purpose of this study is to demonstrate how image processing and convolutional neural networks may be utilized to efficiently classify a soil sample using the Unified Soil Classification System (USCS).The system is composed of five sections: jar testing, picture capture, image processing, Convolutional Neural Network (CNN) training system, and outcome.The convolutional neural network is a type of machine learning that enables quicker image processing while still providing accurate evaluation and output.The system will be based on picture data collected from soil samples using the camera included in the hardware component.As the default neural network tool through Google Colab, the breakdown will be 70% for training, 15% for testing, and another 15% for validation.The application will then display the projected amount and proportion of each soil type -silt, sand, gravel, and clay -in a given sample, before categorizing it according to the conditions specified for each classification.In all, this study classified soils and was found to be 92.4% accurate.
Pengembangan Sistem Informasi Terpadu Industri Pariwisata Kota Batam Menerapkan User Centered Design Berbasis Website

The Integrated Tourism Industry System in Batam City is a system designed to make it easier for tourists to find tourism information in the city of Batam. Batam City is one of the cities with leading tourist destinations that are in great demand by domestic and foreign tourists. However, the lack of promotion and tourism information in Batam City is an obstacle for tourists to get this information. This integrated tourism information system is equipped with a cost estimation feature that makes it easier for tourists to check the estimated cost to be issued and what destinations are available in each tourist destination. Coupled with the event calendar menu, tourists can see what activities will be held in the city of Batam, and on the main page of the tourism website tourists can see a description of the city of Batam as well as a gallery containing pictures of Batam city tourism. This Integrated Tourism Industry System in Batam City is based on a website using the CodeIgniter framework, php as the basis for the programming language, and for data storage using mysql, and xampp is used as the server. This system is expected in the future to become the main media for tourism promotion in the city of Batam, so that tourism in the city of Batam is able to compete with tours in other cities, this will have an impact on both the industrial and business sectors because they have utilized and followed the development of information technology.
Restrictions on Formal Education Due to the COVID-19 Pandemic and Their Effects on Growing Marginalisation in Argentina

The chapter focuses on the multiple effects that the policies of social isolation and distancing, implemented to prevent the spread of the COVID-19 pandemic, have had in Argentina, particularly in the field of education. It considers the specific restrictions and their profound consequences on school access for millions of children and young people. The transformation from face-to-face to virtual education has crudely exposed a very disparate socio-economic, cultural and technological situation that has particularly affected the marginalised population, limiting their opportunities to achieve better social integration, both present and future. The problem is framed within the sequence of government measures to reduce activities linked to the temporal evolution of the pandemic in Argentina and its consequences, such as the sharp increase in poverty levels that affect children even more severely. A case study concerning schools close to marginal neighbourhoods allows a concrete and close-up view of the daily experience of teachers and pupils. In these two years, educational disparities have significantly widened inequality among children, delaying the development of some and hindering their social integration. The marginality of today and tomorrow has increased in Argentine society.
School Operational Assistance Management to Lighten School Burden: A Literature Review

This paper aims to discuss the management of school operational funds in an effort to ease the school's burden. This study uses a literature review method with narrative analysis to deepen knowledge about the management of school operational funds. The data was obtained through the process of collecting written documents regarding the management of educational operational assistance from previous researchers and writers as well as documents of applicable laws and regulations. The results of this study can be drawn several conclusions: (1) school financial receipts and expenditures must be reported and accounted for regularly in accordance with applicable regulations. Budget reporting and accountability from parents and the community are carried out in detail and transparently according to the source of funds; (2) School Operational Assistance in practice is very helpful in realizing the quality of education. Nevertheless, the operational assistance must be appropriately managed and closely monitored by various parties so that its usefulness is in accordance with its primary duties and functions; (3) the preparation of school budgets and expenditures is a barometer in the financial managerial process in schools. Recommendations that can be given are to the manager of the school operational assistance program to further maximize the school active assistance program because this is one of the government programs that can assist the community in getting better educational services so that in its implementation in the field, more optimal management is needed so that the objectives and the benefits that can be obtained from this application can be channeled more optimally as well.
How Infrastructures, Social and Ethical issues and Governments are Affecting the Expansion of Autonomous Vehicles?

Autonomous Vehicles (AVs) are expected to considerably reduce pollution, energy consumption as well as car accidents in the very near future. In spite of all these promising perspectives, the expansion of such technology is encountering significant obstacles going beyond the simple technical difficulties. In this paper the issues dealing with car insurance, regulations, cybersecurity, real world poorly regular environments and technical limitations are treated aiming at giving an overview about such revolutionary technology.
Central Zone Size Dependence of Peripheral Dimming Technique Under Wide Field of View Environment

Peripheral dimming technique based on gaze tracking was proposed to reduce the power consumption of emissive displays adopted in headset. This technique divides an image into two zones: a central zone which is a circular area centered on the gaze point, and a peripheral zone which is the outer area of the central zone. This technique achieves power savings by gradually reducing the brightness in the peripheral zone while maintaining the brightness of the central zone. This paper investigates effects of central zone size (CZS) on the technique under a wide field of view (FoV) environment. Psychophysical experiments are conducted to determine the threshold dimming conditions for the CZSs of 10°, 25°, and 40°. The results showed that the individual variations and the mean value of threshold dimming condition increased in proportion to CZS. Interestingly, in contrast, the power-saving efficiency depending on the CZS was not significantly different. The technique can reduce power consumption of display panel by approximately 12% on average, up to 15%. It is demonstrated that the technique is feasible even in a wide FoV environment, and the CZS can be flexibly determined depending on the application or image content.
Didactics of Education Digitalization: the Aspect of Cadets’ Patriotic Education

Progressive technologies open up limitless possibilities of using digital resources, the use of adaptive mechanisms and digital environments, contribute to the expansion of the space for creativity, promote the development of interest in the process of patriotic education. Fostering sustainable patriotism among cadets is an important task facing the teaching staff of the cadet military corps. The purpose of this article is to study the peculiarities of the organization of patriotic activities by teachers in the digital environment. The urgency of the problem of digitalization of the process of patriotic education in the cadet military corps is due to the need for teachers to ensure its effectiveness in accordance with the needs of modern society. The article substantiates the importance of teachers&amp;apos; readiness for the transformation of patriotic activities and their mastery of digital competence. Access to various information and communication materials allows teachers not only to select the necessary ones, but also to make changes to them, to develop their own digital resources to improve the effectiveness of solving specific patriotic tasks. This paper analyzes the important factors that teachers need to take into account in the conditions of digitalization of patriotic education of cadets.
Integrating Apps for English Teaching and Learning

Learners of today are more technologically advanced than ever before.They live their lives with technology at their fingertips.Not only do today's young people own multiple technology devices, they use them constantly in their dayto-day lives.The task for teachers today is a stronger focus on successfully integrating technology into the curriculum, but this has posed a number of challenges, not only because some teachers are not technologically competent, but also because the focus has remained on technology and not on pedagogy.One of the aims of the South African curriculum for English is for learners to achieve communicative competence and produce grammatically correct and contextually appropriate sentences in different situations.Moreover, learners should also become technologically proficient in line with the changing needs of society.This article reports on research conducted with the aim of sourcing and evaluating Android Apps for use in the English classroom.It offers a narrative of the process undertaken and explores the benefits of using Apps in the English classroom to promote communicative competence.The qualitative research was framed within the social constructivist theory and based on the principles of Participatory Research and Action (PRA) and the Technological Pedagogical Content Knowledge (TPACK) framework.Fourteen ( 14) preservice teachers studying English Methodology were purposively selected to source and evaluate Apps for teaching and learning in the English classroom.The participants collaborated online to sift through applicable Apps and develop interactive lessons using these Apps.Data from pre-and post-intervention workshops and focus group interviews were thematically and inductively analysed and mapped against the four components of communicative Lizette de Jager 210 competence, namely grammatical, strategic, socio-linguistic and discourse competence.This was done to determine participants' perceptions and experiences when integrating technology in lessons and the extent to which communicative competence was achieved through these Apps.The outcomes will help pre-service teachers develop and improve their own teaching practices by experiencing integrating technology into the teaching of English, but more importantly to improve their own communicative competence and that of their learners.
Trapped in Texture Bias? A Large Scale Comparison of Deep Instance Segmentation

Do deep learning models for instance segmentation generalize to novel objects in a systematic way? For classification, such behavior has been questioned. In this study, we aim to understand if certain design decisions such as framework, architecture or pre-training contribute to the semantic understanding of instance segmentation. To answer this question, we consider a special case of robustness and compare pre-trained models on a challenging benchmark for object-centric, out-of-distribution texture. We do not introduce another method in this work. Instead, we take a step back and evaluate a broad range of existing literature. This includes Cascade and Mask R-CNN, Swin Transformer, BMask, YOLACT(++), DETR, BCNet, SOTR and SOLOv2. We find that YOLACT++, SOTR and SOLOv2 are significantly more robust to out-of-distribution texture than other frameworks. In addition, we show that deeper and dynamic architectures improve robustness whereas training schedules, data augmentation and pre-training have only a minor impact. In summary we evaluate 68 models on 61 versions of MS COCO for a total of 4148 evaluations.
Financial revolution of payment methods toward energy efficiency growth: Which one is the most sustainable?

Environmental issues have been a crucial concern in every global sector. One sector that might cause environmental problems is the financial sector. Surrounding issues come from various factors such as the usage of fossil fuels that lead to global warming and climate change which slowly assassinate human beings. This article will focus on efficiency comparison between using paper money, plastic cards and cryptocurrency. The main goal is to prove which of the three financial payments is the most energy-efficient in the past, present, and future. The parameters used in this study are electricity usage and CO2 emissions. The whole analysis is based on a quantitative-descriptive method which provides in depth analysis of electricity usage and CO2 emissions level among financial equates from every generation. Even though plastic cards have the highest efficiency level initially, over time, cryptocurrency is going revolutionary, making them more efficient than paper money and plastic cards. This proves that cryptocurrency could be the most energy-efficient payment method in the future.
Coffee Shop as a Space for Learning English Speaking Skills for Underprivileged Students

Take a look at from the current situation, drinking a cup of coffee in a coffee shop becomes a living style trend in society. Not only teenagers experience enjoyable and comfort there, but also adult people feel the same too. This phenomenon are happening right now. Seeing this situation, it would be better if the activity of drinking coffee that was liked by the general public could be a way to overcome boredom in learning English, especially in speaking skills. However, not all students can get these facilities due to economic factors. They are called "Underprivileged Students". So, with this activity, it is hoped that it can help disadvantaged students so that they can get additional English education. The ranking shows that the English ability of the people in Indonesia is in the very low category. Without exception, teenagers or students in Surabaya. Especially those who experience this problem are underprivileged students, because they only get education through formal schools which are only carried out in class or online so they are less effective. As stated in the sub-chapter description of partner problems, there are solutions to overcome problems with partners. One of the creative ideas that can be done is to learn English at the Coffee Shop. This activity will take place through 4 stages, the first is pre-activity, the second is the general stage which includes the inauguration of the activity, the third is the core of the activity, and the fourth is the evaluation of the activity.
Analysis of the use of video media on the learning interest of BI Class Students in Elementary School Teacher Education at the Universitas Terbuka

This study aims to analyze the use of video media on the learning interest of elementary school teacher education students. The population used in this study were all students of the BI Service Center class at the Universitas Terbuka Purwodadi-Grobogan Campus 1 Pancasila Vocational School for the 2022.2 academic year. Meanwhile, the sample in this study were some students of the BI Service Center class at the Universitas Terbuka Purwodadi-Grobogan Campus 1 Pancasila Vocational School for the 2022.2 academic year. Data collection techniques used were interviews, observation, documentation, and literature study. The data analysis techniques used in this study are data reduction, data presentation, and drawing conclusions. The results of the analysis show that there is a significant increase in student learning interest when learning activities use video media. This research can be used as input material in developing innovative learning media according to student characteristics.
Machine Learning and Cloud Enabled Fall Detection System using Data from Wearable Devices: Deployment and Evaluation

In recent years, the popularization of devices to monitor people in combination with Machine Learning (ML) in the context of Internet of Things (IoT) has grown significantly. Then, the number of applications to solve many health issues that require data collection and processing has increased. One of the common concerns by Health institutions is human falls, which can lead to severe health damages or death. Thus, it is crucial to detect quickly when a fall occurs, to reduce the possible sequels. One way to identify potential falls is using data collected from wearable devices as input of an IoT system using ML models, which is the solution proposed in this work using Cloud computing. Thus, we present this solution and its deployment and evaluation that consists of three modules: data acquisition and transfer, intelligent cloud application, and notification service. The best result of the ML models presented is 94.4% of accuracy, considering a low rate of false negatives of 4.3%.
Online Tools in Teaching Literature in Times of Troubles

Bearing in mind the fact that the number of research papers dealing with the ways in which literature can be most efficiently taught in the digital era and the ways in which the existing online educational tools can be applied to teaching literature online is rather limited, we set out to conduct a modest research aimed at tackling these issues and providing the literature teachers with more information regarding the use of digital tools specially designed to meet the needs of literature courses. The first part of the paper offers a glimpse into literature review, in which the history of using modern technologies in literature teaching is briefly presented, the second part of the paper examines the list of online tools that can be the most effectively and easily adapted to literature classes, while the third part of the paper sums up the main ideas presented and opens questions that point to the need for further research into this field.
The Undergraduate Students’ Difficulties in Writing Thesis Proposal

The purposes of this research were to find out the students’ difficulties in developing a paragraph and to understand the students’ difficulties in implementing the writing elements in writing their undergraduate thesis proposals. This research used the descriptive qualitative method. The instrument used in this research were interviews, documentation, and Oshima &amp; Hogue’s Paragraph Rubric. The research subject was 7 eighth-semester students of UINSI Samarinda. The data were collected from the background of the study of the student’s undergraduate thesis proposals and analyzed with the Miles and Huberman Model. The result showed that the difficulties in developing a paragraph experienced by the students were related to too specific and too general topic sentences, poor supporting sentences, the absence of concluding sentences, inconsistent topic discussion, and inharmonic sentences. At the same time, the students’ difficulties shown in implementing the writing elements were found in the organization (the failure to run the sentences smoothly), vocabulary (informal phrases, redundancy, unclear word), grammar (singular and plural error, wrong word choice errors, missing word error, article error, subject-verb agreement error, fragment error, conjunction error, wrong word form error, wrong word order error, and preposition error), and mechanics (capitalization error, punctuation error, and spelling error). The causes of these problems were the interference of students’ native language and the lack of knowledge about the rules of the development of paragraph and writing elements.
Mengukur Kinerja Layanan Internet Indihome dari Opini Masyarakat Menggunakan Sentimen Analisis Twitter Dengan Metode Naïve Byes

In 2019, 73.7% of Indonesians said that their purpose for using the internet was to access social media. One of the social media used is Twitter. With many tweets that have been published through Twitter, these tweets can contain user opinions on a particular thing, it can be like an event in the surrounding Indihome. Through Twitter, users can discuss their complaints or satisfaction with the Indihome service. For that reason, a method is needed, namely sentiment analysis to find out whether the data contains negative or positive opinions. The author uses the Naïve Bayes method in conducting sentiment analysis on the opinions or opinions of Indihome service users on Twitter, to know how accurate the Naïve Bayes method is applied to sentiment analysis. After testing using the Naïve Bayes method, the results obtained are 82% accuracy, 78% precision, 84% recall, and 81% f1-score.