Reviewerly/exHarmony huggingface dataset:
The Role of a Personally-focused Approach in Learning

This article examines the role and importance of personality-oriented learning in the formation of a creative, independent, creative, active personality with leadership qualities. The development of the theoretical foundations of innovation in student-centered learning, the development of new learning models have become innovative directions in the system of teacher education. Revision of the role of the teacher and the student is the main idea of the position of the student-centered approach in education. With the personal-activity approach, the action of both the teacher and the student changes. Modern pedagogical education technologies are aimed at organizing joint activities with students. The use of new pedagogical technologies, approaches contributes to the formation of activity, creative abilities of students, assists them in their striving to become the best professional in their chosen future profession. The individuality of the student, the creation of all kinds of pedagogical conditions on the part of the educational institution for its formation, development are the fundamental principles of the personality-oriented approach in the educational process.
Few Shots Learning: Caricature to Image Recognition Using Improved Relation Network

Inspired by the human ability to learn instance-label associations given only a handful of examples, few-shots learning is gaining increased attention from the researchers. In this direction, we have proposed a modified relation network to perform few shots caricature to image recognition. Since caricature and real images come from different modalities, we have extended the relation network to contain separate feature extracting networks for the two modalities in the embedding module. This extension was necessitated by the fact that since caricature and real images come from different modalities and hence different distributions, a single feature extracting network in the embedding module may not learn cross-modal features. Experiment results on caricature recognition dataset and subsequent comparison of our proposed network against the baseline model quantitatively substantiates our hypothesis. While comparing the performance of our modified network against the baseline, we were able to improve the recognition accuracy by $$26.3\%$$ for $$5-way, 1-shot$$ setting and by $$25.5\%$$ for $$5-way, 5-shot$$ setting.
Benefits of HyFlex learning in creating a positive students’ experience

During the COVID-19 pandemic HyFlex teaching/learning has increasingly grown into a crucial feature of education. My strong conviction is the integration of information technology in education will be further accelerated and online education has eventually become an integral component of the present-day education. Despite the drawbacks, there are some obvious benefits to leveraging a HyFlex course model. It allows students more flexibility than ever before, meaning they can adjust and adapt as needed to accommodate their schedules (in our case, being in Ukraine or abroad). It also gives students access to a greater breadth of learning materials than they would otherwise receive. It is worth mentioning that after Covid-19 the world and education has changed dramatically, with the distinctive rise of e-learning, whereby teaching is undertaken remotely and on digital platforms. This resulted in the largest “online movement” in the history of education. Importantly, research suggests that online learning has been shown to increase retention of information and less time-consuming, means the changes Coronavirus have caused will be here to stay.
The Functions of Evidentiality in English News Corpus from the Perspective of Transitivity based on the Data Mining

Due to the social attributes of news reports, the language in news corpus, however, is influenced by the ideology and attitude of journalists in one way or another. By analyzing the Evidentiality in news texts from the perspective of transitivity based on the Data Mining, the functions of evidentiality are: 1. Evidentiality is about the speaker's expression of source of information and his commitment to the reliability of information. 2. Evidentiality Plays the Dynamic Function between the Reporter and the Reader.
Knowledge Graph Embedding with Relation Constraint

Knowledge graph (KG) is structure representations of the real-world facts by triples, and embedding entities and relations of a KG into continuous vector spaces is proven to be effective in many applications. Schema-based KG also has rich prior information about entities and relations, such as entity constraints for relations which define the semantic role of relations. In this paper, we propose TransRC (Translation model with Relation Constraint) model, which use relation constraint as a part of score function to extend the TransE. Experimental results from multiple benchmarks knowledge graph datasets show that the TransRC benefits from relation constraint information, and it is better than other methods on link prediction and triple classification.
교육부 고시 한국어(KSL) 교육과정의 내용 체계와 언어 재료

This study examines the content system of the KSL curriculum which is a public education curriculum, and explains how the language materials of the KSL curriculum were established.The language materials of the KSL curriculum were presented mainly for two areas of Korean language education, that is education of Korean language as a communication tool and education of Korean language as a learning tool. Grammars and vocabularies corresponding to each area were made into a list after expert evaluation. In the case of vocabulary of communication area, a list of school life vocabulary was added, and in the case of vocabulary of learning tool area, classroom vocabulary, thinking tool vocabulary, and general knowledge vocabulary are included. As for the language materials for the subject- adapted Korean language education area, the vocabulary of each subject was presented simply by classifying them according to the priority and importance of learning.The establishment of language materials for the KSL curriculum is specially meaningful in that it has been materialized by clearly revealing the process of its construction. Meanwhile, some language materials need to be presented separately, taking into account the characteristics of each area a little more, and for the area of subject-adapted Korean language education, it would be good if a specific sentence pattern for each subject was presented.
Performance Analysis of Different Models for Twitter Sentiment

Sentiment analysis is the classification of emotions (such as positive negative and neutral) in the textual data. It helps companies to know the sentiments of customers regarding their products and services that they provide. Today many customers express their reviews on particular product on social media sites. If we analyze those reviews using sentiment analysis, we could know whether customers are happy or not with certain products. Twitter represents the largest and most dynamic datasets for data mining and sentiment analysis. Therefore, Twitter Sentiment Analysis plays an important role in the research area with significant applications in industry and academics. The purpose of this paper is to provide an optimal algorithm for Twitter sentiment analysis by comparing the accuracy of various machine learning models. In this context, nine well-known learning-based classifiers have been evaluated based on confusion matrices.
Android-based 3D Digital Story Telling development for learning batik

Abstract This study aims to design an android-based 3D Digital Story Telling application that is used to introduce the philosophical value of batik motifs. This application development integrates 3D technology with marker-based Augmented Reality (AR). This marker will later act as a detection tool to display visual objects in 3D or video. The design of the 3D Digital Story Telling application can provide more real and more complete information about the philosophical value of batik which is depicted in the batik motif which is the object of visualization. This application can provide a more complete picture of the various local wisdom values of Indonesian Batik.
Perancangan Website Dengan Usability Pada Toko Cek Hijab Baturaja Kabupaten Ogan Komering Ulu

Computer technology today is a means of communication that brings a lot of change to the world of education, business, government agencies, and private sector.  One form of technological development that is currently trending is website.  Website is one of the applications on the internet in the form of Hypertext information, where Hypertext can read and browse the information virtually without being related to certain media. With the website is expected to help market products or services, promote a company, and others online. This website application helps users, in this case business owners both goods and services and internet connoisseurs in this case are consumers which with the existence of the website will cause a sense of comfort and provide convenience to the komsumen to be able to choose the goods according to the wishes. With an attractive look, and easy to understand website is expected to help business owners in increasing sales. Based on this thought, a website is created using the Usability method with the results in the form of an attractive website appearance for consumers.
Reversals of Fortune

The outstanding issue with reversals concerned the fidelity of the spreading ocean crust as a magnetic tape recorder: some geologists asked themselves if the reversals could have occurred spontaneously in the rocks sampled. This conundrum could be resolved by obtaining accurate dates of formation for groups of rocks with normal and reversed polarity, and so determining whether the rock magnetism reversed in sync or not. In the 1950s, uranium–lead (U–Pb) radiometric dating was not accurate enough for younger rocks because the half-life of uranium is so long, which meant the quantity of lead was insufficient for analysis by the technology then available. By the end of the 1950s, two groups of geochemists, one at the United States Geological Survey (USGS), Menlo Park, California, and the other at Australian National University, had developed the techniques of potassium–argon (K–Ar) dating to the stage where it could be used on young rocks, such as lava flows, with ages of hundreds of thousands to a few million years.
Computer language and linguistics

Language is the ability to use complex communication systems and a set of signals used to encode and decode information. Mathematics and linguistics deal with the representation of thought through symbolic language under a guiding structure of language functioning. Computer language is formal, symbolic, and depends on linguistic principles of natural language. Computing regulates the behavior of the machine in the execution of specific tasks and, for that, generative models were developed. The underlying structure of the latter would be adequate to incorporate complex and high-dimensional data in a latent space with a supposed ability to replicate the original data. The distribution in probabilistic terms, however, does not reflect reality. We suggest the logical-axiomatic principle of natural language as an algorithmic core of computational methods capable of generalizing the execution of a set of factors.
Research on Dynamic target Detection and Precise Positioning Based on PIXEL CODE YOLOv3 Deep Learning

At this stage, research on Dynamic target detection has become more and more heated. This paper starts from utilize Pixel code Technology in SSD deep learning algorithm. Through training the model from multiple angles, a Dynamic target detector based on the SSD method is finally obtained. To verify the final performance and overall effect of DynChang Shamic target detection, we conduct rigorous experiments on the data set. By analyzing the results of the experiment, we conclude that the SSD-based Dynamic target detection algorithm simplifies the re-sampling process, reduces the time complexity of the operation, and compresses the detection time of the system, thereby improving the detection efficiency.
Design of school development information system in the district

Abstract The development of primary schools in a district needs to be monitored to make it easier for the education office to manage primary school resources effectively. This monitoring can be done through a system that provides information about the profiles of principals, teachers, and students in each elementary school in the district area. Documents containing primary school data are sometimes so numerous that a paper-free computerized information system can be chosen to overcome them. Based on these problems, the purpose of this study is to build an information system for elementary school development in web-based districts. This information system is designed using the Unified Approach method which consists of stages of object-oriented analysis, design and programming. The results of the study are systems that can store school data, school principals, teachers and students to make school progress reports per school year. The resulting system can be studied by users in the education office in about two hours with an absorption rate of 87%. The benefit gained is that it is known that the development of elementary school conditions in all districts is used to plan further development of primary schools.
Implementation of the fuzzy logic for measuring instrument evaluation results in Information Security Index

Abstract Information security in an organization is very important and should be a major concern. The government designed and made an application of security standards for the application of information security in Indonesia. This Information Security Index is an application that is used as a tool to analyze and evaluate the level of readiness, completeness and maturity of the application of information security in an organization in accordance with the criteria in SNI ISO / IEC 27001 and COBIT. Fill in the index instrument is expected to be easier and faster in using the application. In its development, there is a method that will be applied to this application, namely fuzzy logic. Fuzzy logic is implemented in the Information Security index application in this case serves to predict the final result. In this study, the prediction results using the Mamdani fuzzy method get the percentage of MAPE error 19.17%, so that the accuracy of the implementation of the Mamdani fuzzy method in the security index application is 80.83%.
A Novel Method for Hostility Management

With the rise of social networking websites, there is a wave of user opinions expressed in text, image or different content. Different words and images are used to express one’s personal feeling, but sometimes words and sentences are not used properly which results in an offensive or inappropriate language. Therefore, there is a need to look into the problem. There are many techniques to mine the sentiment from the most well-known social media, Twitter, where users post real-time reactions and opinions relating to everything. This is done by first analyzing the words properly by semantic analysis technique. Throughout this paper, we’ve a tendency to create a hybrid approach to exploitation of every word primarily based and lexicon-based types in which to figure out the linguistics orientation of the opinion words in tweets. Our aim is to optimize the classification of sentiments and prevent increasing hostility on social media platforms. Here, we used the machine learning technique to classify the text. Hostility management is finding out if a text is hostile or not. It can occur anytime or at any place. For cleaning text, we use lemmatization and stemming. To extract the features, we have different techniques in consideration that are bag of words, tfidfvectorizer, Word2Vec, Doc2vec and TF-IDF. We have developed an original technique that mixes existing approaches, providing the simplest coverage results and competitive agreement.
Uso del procesamiento digital de imágenes para la extracción de datos de medidas experimentales publicados en formato gráfico

In this article, we propose a method as an alternative to obtain experimental measurement data, in the absence of laboratory equipment to perform tests, in a suitable format to perform mathematical operations in order to use them as information to validate: hypotheses, models constitutive and / or research theories focused on technological development. The proposed method uses as a main tool the image segmentation technique by region growth by pixel grouping and the normalization of the coordinates of the positions of the pixels extracted to the axis scale in the corresponding figure. The segmentation of the image separates the coordinates of the pixels that form the axes and the curves, the coordinates of the pixels of the curves are normalized to the scale of the axes. The method is tested with images of the result of experimental tests of stress-strain behavior recovered from [1]. The results of the data extraction are plotted and the averages of each curve extracted as well as the standard deviation are obtained. It is verified that the data obtained can be used to corroborate or support hypotheses in a wide range of investigations.
Battering Review Spam Through Ensemble Learning in Imbalanced Datasets

Abstract Nowadays, people’s buying or availing services decisions are subject to online available reviews/opinions. The authenticity of these reviews/opinions is dubious, as there exist many fake reviews posted to attain monetary benefits by promoting their own or demoting the competitor’s products or services known as review spam. Although the number of spam is relatively less than that of normal reviews in real-life, this class imbalance is a critical concern in review spam detection. The performance degrades when the classifier skew towards the majority class. Moreover, efficient feature selection is essentially needed for this issue. The purpose of this study is to develop a framework based on different effective feature selection along with data balancing techniques. Validation results show that our proposed framework commendably copes up with the review spam issue and a higher precision on the real-life dataset. Further, we tested the sensitivity of our proposed framework using both parametric and non-parametric tests and found it significant.
A Model of Intelligent Recommender System with Explicit Feedback Mechanism for Performance Improvement

Recommender Systems are intelligent applications designed to assist the user in a decision-making process whereby user wants to choose one item amongst the potentially overwhelming set of alternative products or services. This work focused on using usersâ€™bank statements that explicitly shows inflow and outflow of funds. The dataset used is real and reliable because the use of non-reliable data in a recommender system causes users lack of trust in the system. However, the data collected were anonymized for privacy reasons. The recommender system was developed as aweb application using Java programming language. Unlike other recommender systems, the graph-oriented database management system was used.In Google news, 38% of the total views are the result of recommendations; similarly, 60% of the rented movies from Netflix come from recommendations and more than that Amazon sales percentage due to recommendations are 35%. Successful integration of recommendation system by online companies like Amazon, eBay, Flipkart amongst others impelled the research community to avail similar benefits in Financial domain to recommend product and services [26]. Therefore, recommendation systems are considered an expedient factor in business nowadays. The aim of all recommender systems is to provide recommendation that will be favourably evaluated and accepted by its users.
Development of Standard Hill Technology for Image Encryption over a 256-element Body

This document traces the new technologies development based on a deep classical Hill method improvement.Based on the chaos, this improvement begins with the 256 element body construction, which is to replace the classic ring used by all encryption systems.In order to facilitate the application of algebraic operators on the pixels, two substitution tables will be created, the first represents the discrete logarithm, while the second represents the discrete exponential.At the same time, a large invertible matrix whose structure will be explained in detail will be the subject of the advanced classical Hill technique improvement.To eliminate any linearity, this matrix will be accompanied by dynamic vectors to install an affine transformation.The simulation of a large number of images of different sizes and formats checked by our algorithm ensures the robustness of our method.
An Efficient Authentication Scheme for Mobile Cloud Computing Using a Key Server

In today's world, mobile devices and smartphones are used heavily and have become one of the essential requisites of everyday life. The development of several applications feasible for those devices has revealed that there is a huge demand for applications of mobile. A technology which aroused in the IT sector provides an opportunity to solve those issues, namely mobile computing and cloud computing. The modern mobile architecture integrates cloud computing and mobile technology to produce Mobile Cloud Computing (MCC). Processing, data storage, and computation accompanied by the applications are moved off the mobile device to be a robust centralized platform of computing that resides in the cloud. The significant risk of mobile cloud computing is securing remote applications and data from illegal access. There is a possibility of unauthorized access, which is accessed by third parties. Therefore the issue of security in mobile cloud computing becomes one of the major research areas. It is necessary to implement strict authentication controls in MCC. The proposed research work is an attempt for secure authentication in a mobile cloud by using a key server and AES-256 algorithm for cryptographic purposes.
Artistic Media Stylization and Identification Using Convolution Neural Networks

This paper explores the usage of different convolutional neural network-based methods for artistic style transfer on images. Style transfer is an interesting domain of Computer Vision as it combines both aspects of style and content recognition in images. In this paper, methods are discussed to transfer mixed or unseen artistic styles to images in real time. Two approaches are implemented, which can achieve multiple and mixed style transfer, building on and inspired by Johnson’s fast style transfer algorithm. A custom baseline CNN architecture and a fine-tuned ResNet-18 are trained using transfer learning. The problem of artist identification of fine art paintings is also explored as this is a challenging problem handled by art historians who have vast experience and training and will use for digitizing large swathes of artwork.