Reviewerly/exHarmony huggingface dataset:
Creativity Of Teacher In Conditions Of Digital Transformation Of Education

In modern educational system teachers are increasingly required who know their subject well, comprehend the specifics of using new methods and forms of education, master teaching techniques and understand their purpose.Important aspects of an effective educational process have become creativity, personal qualities, and abilities of a teacher.The ability to creatively rethink, transform the reality, find a variety of decisions for the same problem, use knowledge in a non-standard setting allows a personality to find a way out of any situation, as well as become successful, realize their potential under changing conditions of modern life.One more tendency has become a full or partial transition to digital educational resources.Today, on the Internet, there are a lot of educational portals and digital materials that require systematization and targeted use in the educational process.In this article, the authors reveal the role of digital educational resources in the formation of the personality of a creative teacher, as well as the role of creativity in the development and self-development of a teacher.Also, the authors give certain recommendations to create technologies of digital learning based on a creative approach.
Evaluation of Distance Learning Resilience During COVID-19 Pandemic using ANFIS

Given the growing usage of e-learning systems during COVID-19 epidemic and expansion of internet-based infrastructure, a resilient approach for e-learning systems is highly required.This paper proposes an Adaptive Neuro-Fuzzy Inference System (ANFIS) to evaluate e-learning resilience.In the ANFIS model, five substantial factors including individual, technology, content, agility, and assessment/support factors are considered as fuzzy inputs, while e-learning resilience is considered as a single output.The proposed ANFIS model has been successfully implemented for e-learning resilience measurement during COVID-19 epidemic in virtual Iranian university.Statistical analysis demonstrated that there was no meaningful difference between experts' opinions and our proposed procedure for e-learning resilience measurement.Sensitivity analysis via the proposed model on changing the different factors showed significant sensitivity to changes in the agility factor.The proposed model can be used in all educational institutions to evaluate the improvement of resilience in e-learning systems.To implement the model for an organization, the values of the designed ANFIS model should be defined specifically for the organization and the corresponding model need to be simulated by examining the involved components and relationships.
Mythology Of Information-Digital Space Of Historical Reality Picture

The proposed article considers the problem of determining the basis of mythologemization of information about the existence of socio-historical phenomena represented in digital space.History, reflected in the picture of socio-historical, unfolds as a form of expression of an information project, which determines the vision of a historical event in the parameters necessary for the subject.The formation of the information model of history in practice is accompanied by the leveling of objective and actualization of subjective components.Providing society with a historical tool for justifying one's own being is an objective factor in social reproduction, despite the fact that the filling of existential paradigms of social being with a certain content has an obvious subjective format.The question of human mastering the information space of history involves an appeal to its socio-cultural meanings.The information resource involved in the complex of organizing the content of the picture of socio-historical reality inevitably loses its own ontological independence and becomes part of the socio-cultural and epistemological system of organizing the subject.The interpretation of information sets the angles of perception of a historical phenomenon, its "visibility" and the level of mastery.The parameters of the historical model are due to the movement of information flows, the vector aspiration of which depends on the coordinates of the gnoseological system and the axiological imperatives of the cultural matrix of the subject.
Development of Learning Media for Google Classroom Session in Madrasa

This research aims to develop teaching materials for google classroom sessions at MTs and MA Nizhamiyah Ploso Jombang. Data collection techniques using questionnaires, validation sheets, and pretest-posttest questions. Therefore, researchers used the R&amp;D method to process questionnaires and the Pairet Sample Test to determine student learning outcomes and meaningful treatment in researching each variable. The research was conducted on 30 7th grade students of Islamic Cultural History subject MTs Nizhamiyah and 30 11th grade students of MA Nizhamiyah Fiqh subject. The results of the research conducted state that: (1) From the average of all the aspects asked in class 7 SKI subject is 69.6% and in class 11 Fiqh subject is 75%, both of which mean feasible It is concluded that learning using Google Classroom learning media at MTs and MA Nizhamiyah Ploso is said to be feasible. (2) The mean score of the pretest class 7 subject to SKI was 52.8, while the posttest score was 68.5 and the mean score of the pretest class 11 Subject Fiqh was 48.1, while the posttest score was 68.1. Based on the table of paired samples test, the significance value is &lt;0.05, indicating that there is a significant influence on the differences in treatment given during the pretest and posttest in Islamic Cultural History subjects MTs Nizhamiyyah and Fiqih MA Nizhamiyyah Ploso Jombang.
The importance of teaching equipment in geography classrooms

The main aim of the research was to determine teachers? opinion on the importance of teaching equipment in geography classroom. The research was conducted during the school year 2020/2021. A total of 134 geography teachers from different districts in Serbia took part in the survey. In general, 57.5% of the participants stated that their school buildings have a specialized and separate geography classroom, while in other schools a classroom is shared between related subjects. It is interesting that 84.3% of the participants stated that in their classrooms they have internet at their disposal. Further, it was concluded that there is no statistically significant correlation between the availability of internet connection and the location of school (rural and urban). On the other hand, one of the biggest problems that 38.8% of the participants highlighted is that maps, which are essential for geography teaching, are approximately 20 years old. On average, the best grade for equipment is awarded to schools in the City of Belgrade (3.47) while the lowest grade is awarded to geography classrooms in Kosovo and Metohija province (2.00). On average, participants graded that their classroom equipment is ?good? (3.02) while the importance of classroom equipment was graded with ?very good? (4.49).
Parallel Deep Learning Framework for Video Surveillance System

In today’s world, the security of every individual has become an important aspect. There is a need for constant monitoring in public places. A Manual operating camera system is an unreliable and very basic and poor method for this purpose. Intelligent Video Surveillance is an approach where multiple CCTVs constantly record the scenes and proper algorithms are deployed in order to detect and monitor activities. Deep Learning frameworks and algorithms like Kera’s, YOLO, Convolutional Neural Networks or backbones for image detection like VGG16, Mobile net, Resnet101 have been used for human and weapon detection. The paper focuses on deep learning techniques and threading to collectively develop a Parallel Deep Learning Framework for Video Surveillance that aims at striking the right balance between accuracy and system performance or stability. Threading is used in terms of implementation of a uniquely proposed Dynamic Selection Algorithm that uses two backbones for object detection and switches between them based on the queue status for achieving system stability. A uniquely designed logistic regression filter is also implemented that boosts the system performance.
Disguise of Steganography Behaviour: Steganography Using Image Processing with Generative Adversarial Network

The deep learning based image steganalysis is becoming a serious threat to modification-based image steganography in recent years. Generation-based steganography directly produces stego images with secret data and can resist the advanced steganalysis algorithms. This paper proposes a novel generation-based steganography method by disguising the stego images into the kinds of images processed by normal operations (e.g., histogram equalization and sharpening). Firstly, an image processing model is trained using DCGAN and WGAN-GP, which is used to generate the images processed by normal operations. Then, the noise mapped by secret data is inputted into the trained model, and the obtained stego image is indistinguishable from the processed image. In this way, the steganographic process can be covered by the process of image processing, leaving little embedding trace in the process of steganography. As a result, the security of steganography is guaranteed. Experimental results show that the proposed scheme has better security performance than the existing steganographic methods when checked by state-of-the-art steganalytic tools, and the superiority and applicability of the proposed work are shown.
Fostering Students’ Cognitive Achievement Through Employing Virtual Reality Laboratory (VRL)

Titration was one of the chemistry concepts that require practicum in the learning process. But, many obstacles in the real laboratory such as lack of material, tools, and times made the real laboratory less optimal. These lacks could be solved by used Virtual Reality (VR) technology. VR made a big contribution to the education sector. One of them was implementing it in the development virtual laboratory. Virtual laboratory plays an important role in the learning process. It was possible to manipulate 2D (virtual world) objects similar to 3D (real world) objects. This study developed Virtual Reality Laboratory (VRL) to analyze its characteristics, quality, and impact on students' cognitive achievement. A research and development (R&amp;D) method with a post-test design was used in this study. The subjects of this study were 102 high school students in class XI. The samples were divided into 3 classes, namely CC (real laboratory); EC-1 (VRL); and EC-2 (real laboratory and VRL). The results of students' cognitive achievement were analyzed using ANOVA and it was found that there were significant differences in students' cognitive achievement in the three classes. Students who used VRL had higher cognitive achievement than students who used real laboratory. VRL also received excellent grades from chemistry educators. Thus VRL is very useful as a supplement in the teaching and learning process.
Expert System for Early Diagnosis of Tropical Malaria and Tertiana Malaria using Certainty Factor

Twano Health Center is one of the technical implementing units of the Jayapura City Health Office which organizes Health Efforts, but the constraints regarding the facilities and infrastructure of the Puskesmas are not yet adequate in supporting health services. Based on observations, the increase in the level of malaria sufferers in the Jayapura area is caused by parasites (protozoa) of the genus Plasmodium and the mode of transmission is through the bite of a female Anopheles mosquito. There are two types of malaria that are often experienced by Jayapura residents, namely Tropical Malaria (Plasmodium falciparum) and Tertiana (Plasmodium vivax). The purpose of this study is to create an expert system that can diagnose early diseases such as an expert or doctor using the Certainty Factor method which expresses belief in an event (fact or hypothesis) based on evidence or expert judgment in early diagnosis of Tropical Malaria and Tertiana. The research subjects taken were 5 patients who had symptoms of Malaria and 1 doctor to determine the symptoms of the disease) The expert system using the Certainty Factor method was used because this method was suitable in determining the disease, and the result was a percentage which was the level of accuracy in determining the patient's disease. Determination of the percentage is influenced by the MB value (a measure of the increase in confidence) and the MD value (a measure of the increase in distrust) obtained from the assessment of an expert. For data modeling using data flow diagrams (DFD) and website-based. Total accurate patient recapitulation results are 80% of the Expert System for Early Diagnosis of Tropical Malaria and Tertiana using Certainty Factor
Analysis and Design of Advance Scalable QoS Based Resource Provisioning Framework

In today’s growing cloud world, where users are continuously demanding a large number of services or resources at the same time, cloud providers aim to meet their needs while maintaining service quality, an ideal QoS-based resource provisioning is required. In the consideration of the quality-of-service parameters, it is essential to place a greater emphasis on the scalability attribute, which aids in the design of complex resource provisioning frameworks. This study aims to determine how much work is done in light of scalability as the most important QoS attribute. We first conducted a detailed survey on similar QoS-based resource provisioning proposed frameworks/techniques in this article, which discusses QoS parameters with increasingly growing cloud usage expectations. Second, this paper focuses on scalability as the main QOS characteristic, with types, issues, review questions and research gaps discussed in detail, revealing that less work has been performed thus far. We will try to address scalability and resource provisioning problems with our proposed advance scalable QoS-based resource provisioning framework by integrating new modules resource scheduler, load balancer, resource tracker, and cloud user budget tracker in the resource provisioning process. Cloud providers can easily achieve scalability of resources while performing resource provisioning by integrating the working specialty of these sub modules.
Bilingual Text Classification in English and Indonesian via Transfer Learning using XLM-RoBERTa

With the large amount of text information circulating on the internet, there is a need of a solution that can help processing data in the form of text for various purposes. In Indonesia, text information circulating on the internet generally uses 2 languages, English and Indonesian. This research focuses in building a model that is able to classify text in more than one language, or also commonly known as multilingual text classification. The multilingual text classification will use the XLM-RoBERTa model in its implementation. This study applied the transfer learning concept used by XLM-RoBERTa to build a classification model for texts in Indonesian using only the English News Dataset as a training dataset with Matthew Correlation Coefficient value of 42.2%. The results of this study also have the highest accuracy value when tested on a large English News Dataset (37,886) with Matthew Correlation Coefficient value of 90.8%, accuracy of 93.3%, precision of 93.4%, recall of 93.3%, and F1 of 93.3% and the accuracy value when tested on a large Indonesian News Dataset (70,304) with Matthew Correlation Coefficient value of 86.4%, accuracy, precision, recall, and F1 values of 90.2% using the large size Mixed News Dataset (108,190) in the model training process. Keywords: Multilingual Text Classification, Natural Language Processing, News Dataset, Transfer Learning, XLM-RoBERTa
Recent Advances in Arabic Automatic Text Summarization

Recently, the volume of the Arabic texts and documents on the internet had increased rabidly and generated a rich and valuable content on the www. Several parties had contributed to this content, this includes researchers, companies, governmental agencies, educational institutions, etc. With this big content it became difficult to search and extract useful information using only mankind skills and search engines. This motivated researchers to propose automated methodologies to extract summaries or useful information from those documents. A lot of research has been proposed for the automatic extraction of summaries for the English language and other languages. Unfortunately, the research for the Arabic automatic text summarization is still humble and needs more attention. This study presents a critical review and analysis of recent studies in Arabic automatic text summarization. The review includes all recent studies used the different text summarization approaches which include statistical-based, graph-based, evolutionary-based, and machine learning-based approaches. The selection criteria of the literature are based on the venue of publication and year of publication; back to five years. All review papers in Arabic ATS are excluded from the review since the study considers the recent methodologies in Arabic ATS. As a conclusion of this research, we recommend researchers in Arabic text summarization to investigate the use of machine learning on abstractive approach for text summarization due to the lack of research in this area. Keywords: Automatic Text Summarization, The Arabic Language, Machine Learning, Natural Language Processing, Text Processing, Computational Linguistics.
Mobile Data-Mule Optimal Path Planning for Wireless Sensor Networks

This article is concerned with collecting stored sensor data from a static Wireless Sensor Network utilizing a group of mobile robots that act as data mules. In this scenario, the static sensor nodes’ locations are known a priori, and the overall optimization problem is formulated as a variation of the Traveling Salesman Subset-tour Problem (TSSP). The constraints that are taken into account include: (a) the pairwise distance between static nodes, (b) the maximum time interval between consecutive visits of each static node, (c) the service time that is required for the collection of the sensor data from the mobile element that visits this sensor node, and (d) the energy efficiency for the mobile nodes. The optimal mobile robot paths are computed using an enhanced Mobile Element Scheduling scheme. This scheme extracts the sequential paths of the mobile elements in an attempt to eliminate any sensor data loss.
Russia And Russian Culture In English-Language Internet Space Memes

Considering the memes as a carrier of cultural code and means as well as the results of intercultural communication, the article studies whether the Internet memes in the English-language segment of the Internet are a way of promoting Russian culture or only the jokes that reflect stereotypes about Russia and Russians.The article proposes the set of criteria for memes search and selection, and, therefore, the basis for further analysis.The sample under the review includes 107 memes taken from the Know Your Meme site and refers to Russia and various aspects of Russian culture.The data examined indicate a wide range of aspects of Russian culture and subculture and stereotypes represented in memes.Analysis of memes' spreading paths shows that memes of both Russian and foreign origin develop and change, effortlessly moving between English-language and Russian-language segments of the Internet.Russians and foreigners use memes about Russia to promote their online shops and accounts on social networks, regardless of whether the image of Russia presented in these memes is appealing.Russians also use memes to increase interest in the Russian language and culture.Thus, the Internet memes can be regarded not only as a carrier of stereotype but also as a way of promoting a peculiar image of Russian culture and a basis for intercultural exchange.
Pengolahan Limbah Cair Rumah Sakit dengan Metode Lahan Basah Buatan (Constructed Wetland) dan Tanaman Air Typha latifolia

&lt;p&gt;Utilization of the aquatic plant Typha latifolia, in the treatment of hospital wastewater with the method of an artificial wetland system (constructed wetland), is expected to be able to treat the liquid waste of health care facilities. This study aims to determine the ability of the aquatic plant Typha latifolia in degrading the parameters contained in the wastewater of health facilities using the Artificial Wetland Method. Quasi-experimental research design. The measurement of liquid waste parameters (BOD, COD, TSS, Fatty Oil, and Ammonia) is carried out by taking samples at the inlet and outlet of each pot, then analyzed in the laboratory. The study reported an average influent BOD level of 66.2mg/L, an average effluent in a circular cross-sectional pot increased by 99.6mg/L, an influent COD level of 190.8mg/L, an effluent in a rectangular pot four decreased by an average of 31.6mg/L, the influent TSS parameter was 106mg/L, the average effluent in a circular cross-sectional pot was 283.6mg/L, the influent Oil &amp;amp; Fat parameter averaged 1.2mg/L, average effluent 1.2mg/L, ammonia influent parameter 12mg/L, effluent 2.62mg/L. The rectangular cross-section has a good ability compared to other cross-sections in reducing hospital waste, namely; BOD=64%, COD=40%, TSS=48%, Ammonia=67%, Oil and Fat parameters did not decrease because the influent parameter levels were already below the Liquid Waste quality standard. The researcher concluded that the rectangular cross-sectional pot planted with Typha latifolia could reduce the wastewater parameters better than other cross-sectional types. &lt;/p&gt;
Financial Security Analysis of E-Commerce Platform Based on Supply Chain for Heterogeneous Network Location Verification

The development of supply chain finance, its pricing strategy for bilateral business cooperation between e-commerce, banking institutions, and fourth-party logistics services providers has gained the attention of researchers. This paper combines the heterogeneous network location verification technology, starting from information asymmetry and Rubens bargaining game ideas, and combines it with game theory methods to provide a reference for bilateral cooperation decision-making on e-commerce platforms. The experiment results indicated the pricing decisions of e-commerce platforms which are affected by the efforts of the other party and the ability of bargaining. The quoted price increases with the decrease of the bank’s ability and the increase of the service provider’s ability. The pricing decisions of banks and service providers are only affected by the direct proportion of their respective business costs. When considering the introduction of incentive mechanism conditions, it is found that appropriate incentive conditions can increase the quotation of the e-commerce platform. The price quoted by the e-commerce platform that chooses to bargain with the bank is higher than the price quoted by the bank after negotiating with the service provider, which will help to better realize the benefits. Finally, the paper numerically analyzes the results of the bargaining game between e-commerce platforms and banks and fourth-party logistics service providers, and the numerical results verify the better performance.