Reviewerly/exHarmony huggingface dataset:
Online Learning Behavior During COVID-19 Pandemic toward Students' Digital Literacy Skills

COVID-19 pandemic changes the learning pattern is everywhere, including in Indonesia. This change raises problems in elementary school. This study analyzed online learning behavior in elementary school and the digital literacy skills of students during the Covid-19 pandemic in Indonesia. The descriptive qualitative research method with survey techniques toward 60 respondents was employed to investigate online learning behavior and digital literacy skills. The finding and data on digital literacy indicators show that the students have 8 elements of digital literacy, there are functional skills, creativity, critical thinking and evaluation, cultural and social understanding, collaboration, the ability to find and select information, effective communication, and e-safety. According to the data, the result shows that online learning behavior affects students' digital literacy skills.
Using the Moodle Distance Learning System in the Educational Process

Educational process of modern times is undergoing significant changes due to various reasons such as active development of Internet resources, diverse e-learning platforms application, new objectives of education and evolved requirements for the up-to-date specialists. Modern educational process needs to fall outside the limits of the traditional practices of a chalkboard inside the four walls of a classroom and apply new technological advancements capable of enriching the teaching-learning process and propel it to the next, more complicated and advanced level. Moreover, students of the modern generation are capable of getting, studying and learning digital information and partaking in engaging interactive activities within the contemporary digital world.
METHODS OF STUDYING STRUCTURE AND FUNCTIONS OF LIVING ORGANISMS AND USING THEM IN BIOLOGY CLASSES

Knowledge and use of advanced techniques in biology lessons is very effective. By combining updated and analyzed technologies for conducting various lessons, you can achieve better results in learning the material. In the course of research, it has been proven that it helps students easily master the curriculum and shows good results in the process of learning in biology lessons. To do this, it is necessary to apply effective methods used in other developed countries, since today the priority in the classroom belongs to the student, not the teacher. Also, modern teaching methods, such as: communicative, project-based, intensive, activity-based, distance learning technologies are very effective and in the process of use allow you to quickly learn the lesson material, which is important for both teachers and students.
Online Meeting of the Forum of Rectors of Humanities Universities and Deans of Humanities Faculties of the CIS Member States

The article presents an overview of the online meeting of the Forum of Rectors of Humanities Universities and Deans of Humanities Faculties of the CIS member States, held on December 4, 2020. The Forum has established itself as one of the most popular and effective mechanisms of interaction between the university community of our country and other CIS countries, and representatives of leading universities and faculties of the humanities regularly take part in its work. An important role in the work of the Forum is played by the participation of heads and representatives of relevant state authorities of the Russian Federation, foundations, public and international organizations. This time, the participants focused on digital technologies in humanitarian education and their role in the integration cooperation of the CIS countries in the context of the fight against COVID-19 and countering other modern challenges, humanitarian education and strengthening cultural and humanitarian ties in the Commonwealth, the state and prospects of scientific cooperation between universities in the CIS countries. During the online meeting, the participants expressed a consolidated position that the new challenges they face dictate the need to form common approaches to educational technologies, as well as a willingness to expand cooperation in solving specific tasks that are of key importance for public policy.
Жизнь интересных людей: кардиохирург Рустам Нагуманов о медицине, хирургии и жизни вне больницы

Cardiac surgery - field of surgery and cardiology, eliminating feature pathologies cardiovascular system systems. Heart it is a motor our body, and related diseases with him, always carry for themselves sad and the inescapable consequences. And doctors who are engaged in prevention problems and their solutions treatment, can feel free to wear it title of heroes. The purpose of this policy articles: find out about the company a cardiac surgeon, his understanding its importance professions.
OPTIMASI MESIN PENCARI BUKU FIKSI BERDASARKAN PADA SEMANTIK IMPRESI

Fiction books are one of the most popular types of books in Indonesia. There are five most popular genres in fiction books, namely fantasy, mystery, romance, sci-fi, and thriller. Each genre gives a different impression and special interest for readers. It has become a common habit when people choose a fiction book based on the title, author, or publisher of the book. However, it does not provide precise search results. In this final project, an application system was developed to find out fiction books based on semantic impressions on the cover of the fiction book. The impression on each book cover is obtained through a survey of fiction book lovers in Indonesia. To get the results of the closeness between the user search and the impression survey data obtained through text mining, as well as the cosine similarity algorithm to calculate the most precise proximity value to the impression the user expects. The results of this system display a fiction book that has a closeness value with an error rate of 3.93% based on the impression expected by the user.
LibGuides: Online Streaming Video: Current Kanopy Licenses

Online streaming video available via the CSU Stanislaus Library. Kanopy videos with Stan State licenses expiring after summer 2021.
Fast qubit initialization in a superconducting circuit*

We demonstrate an active reset protocol in a superconducting quantum circuit. The thermal population on the excited state of a transmon qubit is reduced through driving the transitions between the qubit and an ancillary qubit. Furthermore, we investigate the efficiency of this approach at different temperatures. The result shows that population in the first excited state can be dropped from 7% to 2.55% in 27 ns at 30 mK. The efficiency improves as the temperature increases. Compared to other schemes, our proposal alleviates the requirements for measurement procedure and equipment. With the increase of qubit integration, the fast reset technique holds the promise of improving the fidelity of quantum control.
ПОВЫШЕНИЕ МОТИВАЦИИ К ИЗУЧЕНИЮ ХИМИИ В ПРОФИЛЬНОМ ОБРАЗОВАНИИ

This paper presents the results of pedagogical research with the introduction of the educational process of the elective course Chemistry in our life. The aim of the study is to increase motivation to study chemistry and academic performance, help in choosing a future profession. During the study the goal of the training experiment was achieved: an elective course for the interest of students of the 8th grade was developed and tested. The use of elective courses in the learning process promotes a school motivation by developing cognitive and self-realization motives. A high level of motivation of educational and research activities needed to achieve in learning outcomes and in overall academic excellences of the student. This is confirmed by the fact that students engaged in elective courses take an active part during the lessons. The level of formation of students's motivation is revealed.
Local Areas and Localism

In the current (third) lockdown,attention has once again been focused on what we’ve been instructed that we should, and should not do, in terms of essential daily activities. One issue that’s come to the fore is exercise and the ‘requirement’ we should stay within our local area.Two cases immediately come to mind.
Experiences Deploying Multi-Vantage-Point Domain Validation at Let’s Encrypt

An attacker can obtain a valid TLS certificate for a domain by hijacking communication between a certificate authority (CA) and a victim domain. Performing domain validation from multiple vantage points can defend against these attacks. We explore the design space of multi-vantage-point domain validation to achieve (1) security via sufficiently diverse vantage points, (2) performance by ensuring low latency and overhead in certificate issuance, (3) manageability by complying with CA/Browser forum requirements, and requiring minimal changes to CA operations, and (4) a low benign failure rate for legitimate requests. Our opensource implementation was deployed by the Let's Encrypt CA in February 2020, and has since secured the issuance of more than half a billion certificates during the first year of its deployment. Using real-world operational data from Let's Encrypt, we show that our approach has negligible latency and communication overhead, and a benign failure rate comparable to conventional designs with one vantage point. Finally, we evaluate the security improvements using a combination of ethically conducted real-world BGP hijacks, Internet-scale traceroute experiments, and a novel BGP simulation framework. We show that multi-vantage-point domain validation can thwart the vast majority of BGP attacks. Our work motivates the deployment of multi-vantage-point domain validation across the CA ecosystem to strengthen TLS certificate issuance and user privacy.
AS A PEDAGOGICAL PROCESS IN THE ORGANIZATION OF PRESCHOOL EDUCATION, THE EDUCATOR ORGANIZES AND DIRECTS THE DEVELOPMENT CENTERS ON THE BASIS OF THE STATE PROGRAM "FIRST STEP"

Issues to be taken into account by educators working in preschool educational institutions in the organization of educational activities in development centers on the basis of the state program First Step, to guide and control the activities of children curiosity, individual capabilities).
HUBUNGAN KETRAMPILAN SELF-REGULATED LEARNING DENGAN HASIL BELAJAR SISWA (STUDI META ANALISIS)

The Self-regulated learning Relator to How Students Manage Their Own Learning Time, Thereby Improving Their Learning Result. There have been innumerable studies regarding the effectiveness of strategies in improving students’ performance, however most of them only looked at and emphasized on the students’ characters rather than the learning results. This study was aimed to find out how strong the correlation between the self-regulated learning and the learning result is. Meta analysis was used here. Data was collected by documenting articles of study results from various sources obtained through google.com search engine. Those articles have been published since 2010 up to 2019, and mostly related the self-regulated learning and learning performance. This study used an analysis design of fixed effect model with corrected effect size. The analysis was conducted with the help of JASP software by counting the correlation, drawing the forest plot, as well as the publication bias. The analysis results showed that there was a significant correlation between the self-regulated learning and the learning result.
The Use of CIRC Strategy on Students’ Reading Comprehension Skill

Reading is the most and useful skill for people. It is an activity that can update any information or knowledge. This research aims to know the effect of CIRC strategy on students' reading comprehension skills in the description text. This study used a quasi-experimental in which design involves two groups, namely the experimental group and the control group. The research was conducted in the experimental class consists of 20 students, and the control class consists of 20 students. The results show that The minimum score of pre-tests in the experiment class was 44, and the maximum was 84. While the minimum score of pre-tests in the control class was 44and, the ceiling was 78.  On the other side, the mean of each group was different. The mean score of the pre-test experiment was 68,00, and the mean score of pre-test control was 61,50, and The minimum score of post-tests in the experiment class was 80, and the maximum was 92. While the minimum score of post-tests in the control class was 68, and the maximum was 84. On the other side, the mean of each group was different. The mean score of the post-test experiment was 85,00, and the mean score of post-test control was 75,30.
Experimental Disproof of a Manga Character Construction Model

In prior works, the impression of elements of virtual agents/manga character and the overall impression of virtual agents/manga character were considered completely symmetric. In this work, we conducted a preliminary experiment to develop a system that creates designs of virtual agents depending on a text. In this experiment, the participants read the text and chose the image of an agent and social group that resembled their mental image. We introduced the lattice derived by the rough set induction method to suggest the model to analyze the mental image. In this model, we constructed the lattice from two interpretations to evaluate the complexity of the mental image generation process. As a result, the lattices derived by social groups and appearance were non-Boolean; however, those derived by two kinds of design features were not non-Boolean. This result shows that the mental appearance and social images cannot be combined voluntarily. This result showed that it is not symmetric between each element of virtual agents/manga character and overall virtual agents/manga character.
Penggunaan Metode Discovery Learning Pada Pembelajaran PAI Untuk Meningkatkan Hasil Belajar Siswa Kelas VII SMP Negeri 10 Seluma

The objective of this study aimed at developing learning methods in teaching PAI subject at secondary school level. The research method used is classroom action research, which is carried out in II sycle which consist of four steps. The subject of the reaseach was the students of the first year at SMPN 10 Seluma Regency. Based on the results, the data shows there was improvement on the students’ achievement in understanding the goal of teaching related to the given topics. The data indicated that in each sycle increased significantly from 62% at first cycle become 85% at the secondary sycle. Then the data also show that there was improvement on students’attitude, motivation during the class activity. In conclusion, discovery learning method is effective used at SMPN 10 Seluma.
Affine Transform for Skew Correction Based on Generative Adversarial Network Method for Multi-Camera Person Re-Identification

In intelligent video surveillance system, person re-identification is a key technology. In order to address the problem, the decrease in performance of person Re-Id lead by the skew pedestrian images, this paper proposes the affine transform for skew correction based on generative adversarial network (GAN) method for multi-camera person re-identification (Re-Id). Firstly, an effective GAN is proposed to guide the spatial transformer network (STN) to learn affine transform parameters for skew correction in an adversarial way, and STN is adopted as the preprocessing model for Re-Id to reduce influence of variations in person posture. Then, features are extracted by a deep convolutional neural network from input images which are corrected by STN, and finally results can be obtained by measuring similarity between features. Besides, in the proposed GAN, a classification model and related loss functions are introduced to reduce the damage to the key features of pedestrian during skew correction. The effectiveness of the proposed method is verified by experiments conducted on the skew pedestrian dataset.
A Fast Clustering Method for Large Data Sets

In this paper a deterministic clustering method based on the Katsavounidis, Kuo & Zhang (KKZ) seed procedure, is proposed. This approach has a lower computational complexity than the prominent k-means algorithm. We compared our method with a related deterministic clustering method: KKZ_ k-means (k-means initialized by KKZ). Performance evaluation demonstrates its effectiveness in term of average Silhouette index in various benchmark datasets.
Building Competence Professional Self-Development For University Students As A Pedagogical Problem

Currently, there is a sufficient variety of different ideas for building a system of continuous professional education, however, most authors agree that the current situation requires constant development and self-development of a person as a subject of his own life.
ИНТЕРПРЕТАЦИЯ КРЕОЛИЗОВАННОГО ТЕКСТА КАК ПРИЁМ КОНСТРУИРОВАНИЯ ПЕДАГОГИЧЕСКОЙ РЕАЛЬНОСТИ

The article content reflects the product of a scientific and methodological search in updating the forms and means of training a Russian language teacher. The purpose of experimental research is to define the limits of applicability of creolized texts in the professional training of a student of Philology. The article highlights the aspects of using creolized texts in classes as the method of teaching the Russian language. The significance of the research results lies in the development of linguodidactic theory as a component of the strategy of linguistic education of schoolchildren in the modern language situation. Interpretation of creolized texts in the process of training a Russian language teacher is regarded as a didactic method of constructing pedagogical reality.Key words: pedagogical reality, methods of teaching the Russian language, linguistic and methodological competence, creolized text.DOI 10.18522/1995-0640-2020-4-203-214
Identity Crime in the Digital Age: Malaysian and Mauritanian Legal Frameworks

Legally speaking, a crime is an action or omission punishable by law and it takes many forms, e.g., crimes against people, property and so forth. Identity crime is one of those crimes that could affect financial institutions, individuals or even the whole society. Identity crime impacts include, inter alia, emotional and psychological, financial and security ones. In its basic meaning, identity crime is a term used to refer to all forms of unlawful activities (stealing, fraudulently using, modifying, etc.,) done under the identity of persons (names, passports, bank accounts, etc.). The term ‘identity’ includes all information relating to persons (natural or legal) such as name, address, email, phone number, bank account, uniform and such like. These types of crimes are not new but there is no doubt that the availability of information and data in the virtual world flourishes identity related-crimes and makes them easier to be committed. Like other countries in the world, Malaysia and Mauritania have general and specific provisions for combatting identity related-crimes and bringing offenders to justice. This paper discussed the concept of identity crime, then analysed and examined laws related to the matter in the legal systems of the two countries and assessed the efficiency and capability of those laws to combat this serious crime. Moreover, it made a comparison between the two systems and suggested some steps to be taken to improve the existing laws governing identity crime in the countries. This research is a doctrinal research depending on both primary and secondary related sources. It is argued and believed that a study such this will positively contribute to the field of legal studies as it is examining an aggravated crime (identity crime) from a comparative perspective.
IDENTIFYING OBJECT IN AN IMAGE AND GENERATING CAPTION FOR GIVEN IMAGE

Automatically generating the textual description for an image from an artificial system is known as image captioning. It uses each tongue process and computer vision to get the captions. It is a challenging artificial problem since it requires computer vision to understand the content of the image and a language model from the field of natural language processing to turn the understandings of the image into words. Many techniques proposed to solve this problem. Current approaches or techniques mainly focus on generating captions that are general about image contents.Describing images at a human level and applicable in real life environments is a challenging issue. In this paper, we would implement a neural network based method for image captioning and make it generate the captions for images at a human level by using image captioning, well grounded by the elements of images.
Research on Physical Fitness Test Data Mining and Analysis Based on Apriori Algorithm

Abstract Based on the analysis of the characteristics of Apriori algorithm, this paper uses the iterative method of layer by layer search to find out the relationship of item sets in the students’ body measurement database to form the mining model of association rules. The model maximizes the generation of candidate sets, reduces the size of frequent sets, and achieves good performance. At the same time, the average GM (1,1) model is constructed by the accumulation of the original sequence and the least square estimation of the parameters, as well as the whitening differential equation form, to predict the trend of College Students’ physique change in the future, and the research shows that the error of the model is small and the precision is high.
Application of Artificial Intelligence to Assist in Mapping for Flood-Prone Areas in the Bantul Regency, Yogyakarta

Flooding is one of the natural disasters that poses a serious threat to people who live near watersheds and coastal areas. Floods may affect various sectors of socioeconomic life of a society, such as sectors of the economy, agriculture, and education. This led to the need for an accurate method for predicting flood-prone areas so the public and the government can prevent and minimize the negative impacts and able to assist the recovery process in the sectors affected by the floods more optimal. In the Industrial Revolution 4.0 era, science and technology develop very quickly, one example is the development of Artificial Intelligence (AI) where the system adopts the way of human thinking, such as planning, learning, reasoning, and self-correction which is then manifested in a mathematical form so it can be applied for solving real problems. Therefore, this study used the AI ​​system in the process of prediction and mapping of disaster-prone areas. The data used in this study are rainfall, land altitude, watersheds, river depth, and distance of the settlement to the seashore or river. These data were then processed using the method of deep learning for prediction function and Fuzzy C-Means (FCM) for mapping function which is a technique in AI systems. The final results of this study were obtained three criteria for disaster vulnerability, namely low, medium, and high, which can be used to predict the mapping of flood-prone areas until the coming years in the Bantul Regency area.