Reviewerly/exHarmony huggingface dataset:
FORMATION OF READING INDEPENDENCE OF SCHOOLCHILDREN BY MEANS OF A CHILDRENʼS ART BOOK

The article raises an important problem ‒ the formation of reading independence of junior schoolchildren, since the level of formation of the skills of independent work with a book is an important prerequisite for the intellectual, creative and spiritual development of the individual.The author analyzes the objective and subjective reasons for the decline in interest in reading fiction among younger schoolchildren; reveals the content aspect of the concept of “reader independence”; outlines the range of literary works for extracurricular reading lessons that would contribute to the expansion of reading interests and the development of reading culture; outlines the range of literary concepts necessary for junior schoolchildren to understand; determines the psychological and pedagogical conditions that contribute to the effective formation of reading independence of junior schoolchildren.The article focuses attention on the principles of material selection for textbooks on literary reading: thematic and genre, which involves the selection of works that meet the needs, interests and cognitive abilities of children of primary school age and at the same time allow them to familiarize themselves with various genre forms; artistic-aesthetic – a selection of works that are marked by artistic perfection, and their content affirms moral-ethical and patriotic values, contributes to the aesthetic and speech development of students; literary ‒ formation of initial knowledge of literary studies.&#x0D; Keywords: reading independence; reading activity; reading culture; junior schoolchildren; fiction; literary concepts; reading interest; psychological and pedagogical conditions; literary genres; extracurricular reading lesson.
DESIGNING A WEB-BASED APPLICATION OF MATERIAL AND INVENTORY MANAGEMENT FOR GARMENT WORKSHOP

Inventory management must be implemented properly so that the flow of goods can be controlled easily. A large number of small sized tools and materials in the workshop of Garment Engineering major require a well-managed inventory. Moreover, the rapid circulation of their inflow and outflow also needs to be addressed well. The garment workshop managers currently only record the material flow manually in the logbook, so it is necessary to design an application that can help them achieving more effective and efficient records. This designed application contains information about the amount of workshop material inflow, outflow and their availability. There are other features which considers the number of materials needed based on the available stock. Barcode system is also utilized to ease the data input process. Usability test was then performed to the application using System Usability Scale (SUS) questionnaire, resulting in average of 63,75 from all of the respondents. That value shows that this application has a low level of usability. Where it is actually understandable since this is the first prototype for the next application developments. All of the application menu and features can be successfully running and the application also helps the garment workshop managers a lot, thus in accordance with the purpose of making this application
Credit Card Fraud Detection Using State-of-the-Art Machine Learning and Deep Learning Algorithms

This research study aims to detect credit card frauds, such as accessibility of public data, high-class imbalance data, changes in fraud nature, and high rates of false alarm. Machine learning and deep learning algorithms have been used to detect frauds, but there is still a need to apply state-of-the-art deep learning algorithms to reduce fraud losses. Comparative analysis of both machine learning and deep learning algorithms was performed to find efficient outcomes. The European card benchmark dataset was used to evaluate the proposed model, which outperformed the state-of-the-art machine learning and deep learning algorithms.
Farmers E-Digital Marketing

The role of the project is to develop a webpage for admin (farmer) to add the farmer items from field for online shopping. The item is added under four different categories such as vegetables, fruits, grains and spinach. The items are added under any one of the category. The user will be provided with android application to view all the added items where shopping can be carried out. The user can view all the items or search the needed items as per the category. The needed items will be added to cart where order can be placed. As soon as the order placed, the admin will get the notification regarding the order placing. The admin can view the overall order and as per the request, the confirmation will be fixed. The user will be provided with android application to view all the added items where shopping can be carried out. The user can view all the items or search the needed items as per the category. The needed items will be added to cart where order can be placed. As soon as the order placed, the admin will get the notification regarding the order placing. The admin can view the overall order and as per the request, the confirmation will be fixed.
Loan Prediction Using Machine Learning Algorithms

Loans are a major prerequisite in the present-day world. By this, as it were, Banks get a major portion of the entire benefit. It is advantageous for understudies to oversee their instruction and living costs, and for individuals to purchase any kind of extravagance like houses, cars, etc. But when it comes to choosing whether the applicant's profile is pertinent to be allowed a credit or not. Banks must see many aspects. Giving credit is the most commerce of banks. A noteworthy parcel of the bank's income comes straightforwardly from benefits from credits. Indeed, on the off chance that the bank favors the advance after the confirmation and certification relapses prepare, it cannot be beyond any doubt that the chosen candidate is the genuine candidate. Doing this handle physically requires unused time. Able to anticipate whether. a specific candidate is secure, and the whole confirmation handle is automatized with the machine. fashion. After the presentation of innovation to the world everything began to be automatized. With the introduction of machine learning, the world has seen a modern side of innovation. When the diversion of the forecast is played, machine learning gives a few of the most excellent. models to test the information for the exactness of the result. A few of them are broadly utilized. Machine learning calculations are Decision trees, support vector machine, logistic regression, random forest, etc.
Big Data Analysis in Commercial Social Networks: Analysis of Twitter Reviews for Marketing Decision Making

Content generated by users on commercial social networks about products and brands generates large volumes of data that can be transformed into relevant and useful recommendations for marketing decisions. Every day, consumers post their opinions online on social networks about products they have purchased and used, and companies are increasingly interested in tracking this information in real time for better decision making. The main problem is to extract key information from consumers' textual comments and use it automatically to measure the quality of products or brands. In this work, we propose a hybrid approach to automatically analyze these reviews, assigning a quantitative score to negative and positive user content. The analysis of online consumer sentiment has increased significantly in recent years, being crucial to determine the success of businesses in a wide range of sectors, tourism, hospitality and e-commerce. In the same context, this work proposes a framework for analyzing the sentiment of reviews posted on the Twitter network towards products and brands. The first step is the construction of a dataset by collecting a set of reviews posted online on Twitter, processing and cleaning the textual data for better accuracy, and then developing a hybrid approach for product evaluation and polarities creation using lexicon-based methods and machine learning-based analysis techniques.
The failure of Wigner function negativity to detect quantum dissonance in an open bipartite system

We study the dynamics of Wigner function, quantum discord, entanglement and quantum dissonance for bipartite Bell-diagonal states independently interacting with dephasing reservoirs. We analyze comparatively their behavior under the decoherence effect. Our main goal is to test the ability of Wigner function negativity to measure all kinds of quantum correlations in such system. Particularly, we find that this negativity can only capture entanglement and discord. Of course it succeeded in predicting the behavior of quantum dissonance, but nevertheless, it failed to detect its presence. As a matter of fact, we conclude that Wigner function negativity cannot be used as measure of quantum dissonance in the two qubit open system.
Human Action Recognition and Posture Prediction

Human action recognition and posture prediction aim to recognize and predict respectively the action and postures of persons in videos. They are both active research topics in computer vision community, which have attracted considerable attention from academia and industry. They are also the precondition for intelligent interaction and human-computer cooperation, and they help the machine perceive the external environment. In the past decade, tremendous progress has been made in the field, especially after the emergence of deep learning technologies. Hence, it is necessary to make a comprehensive review of recent developments. In this paper, firstly, we attempt to present the background, and then discuss research progresses.
SELF-PRESENTATION OF YOUNG PEOPLE IN VIRTUAL REALITY: PSYCHOLOGICAL ASPECT

Introduction. Modern Dictionary of Ukrainiandefines self-identification as identification of a person or a group of people with other, certain patterns and images, definition of self and own orientation affecting behavior, decisions, and emotions [1]. It is clear that teenagers and young people look for role models of personalities or groups in the virtual world, because the Internet is not only a source of information, but also one of the main factors in the formation of new generation of young people. Virtual reality is an interactive environment created with the help of computer, which has graphic, acoustic, plastic and other properties, in which the user immerses himself or herself as viewer or creator, thus forming such a structure as virtual consciousness [2]. It is on its basis that the process of self-presentation of the individual in the information space takes place.
Design of Dashboard Administration of the Public Sector

This research discusses the design of a public service administration system which is expected to facilitate the processing of public service administration data, the method of implementing activities carried out to achieve the success of the objectives of this activity through mapping indicators and data elements, field surveys, dashboard designs. The results of the design of a public service administration system with the waterfall model stages have resulted in a new system analysis UML modeling approach to systematic and sequential software development starting from the level and progress of the system in analysis, design, code, testing and maintenance of the system, with this system can maximize time and easily find data again.
VISUAL ANALYSIS OF TIME-VARYING MULTIDIMENSIONAL DATA SETS

Abstract. This paper contains a description of computational experiments on the application of elastic maps to the analysis of time-varying volumes of textual information. Elastic maps are considered as a tool to provide analytical work with textual information and large information arrays of data. This paper presents the results of numerical experiments on the study of data volumes consisting of frequencies of joint use of words from different parts of speech, for instance “noun + verb” or “adjective + noun”. We consider text collections in Russian for experiments. Previously, static information arrays were mostly considered. It is for them methods of data analysis and methods of visual analytics were developed. Nevertheless, data comes in all the time in various areas of human activity. And in practice it is necessary to know how the cluster picture of multidimensional data volume changes over time. The paper describes the numerical experiments for real time-varying multidimensional data sets. Such experiments allows to analyze the evolution of cluster structure for multidimensional data and to trace the evolution for separate cluster.
USING GOOGLE JAMBOARD IN TEACHING SOCIO-GEOGRAPHIC DISCIPLINES TO FUTURE GEOGRAPHY TEACHERS

The article highlights the problems of using the Google Jamboard board in the educational process of higher education students on the example of social and geographical disciplines of OPP Secondary education (Geography. Biology and human health). It is noted that globalization, the transition to scientific and information technologies, the formation of a “knowledge society” significantly affect the nature of education, in particular, the perception of its quality. Information technologies in training make it possible to achieve the main goals of the modernization of education: to improve the quality of education and training, to ensure the formation of a harmoniously developed personality, ideally positioned in the information space. During the COVID-19 pandemic, the Russian-Ukrainian war, when online learning is a challenge of our time, informatization of education is especially relevant. The results of a questionnaire survey applicants for higher education. The attraction to the use of Jamboard in the process of teaching social and geographical disciplines has been determined. It is noted that thanks to the use of Google Jamboard in teaching social and geographical disciplines of future geography teachers, several important tasks are solved at once. Applicants for education form a steady interest in the process of acquiring knowledge, ability to search, process and analyze information from a variety of sources, to work confidently and critically using information society technologies and communication, the ability to work in a team, to communicate on professional issues.&#x0D; Keywords: innovation; informatization of education; information technology of training; interactive whiteboard; Google Jamboard; information society; computerized learning; technical means of training.
Classification of Breast Masses Using Ultrasound Images by Approaching GAN, Transfer Learning and Deep Learning Techniques

Breast cancer is a common cause of death among women worldwide. Ultrasonic imaging is a valuable diagnostic tool in breast cancer detection. However, the accuracy of computer-aided diagnosis systems for breast cancer classification is limited due to the lack of well-annotated datasets. This study proposes a deep learning-based framework for breast mass classification using ultrasound images, which incorporates a novel data augmentation technique, Generative Adversarial Network (GAN), and Transfer Learning (TL). Automating early tumor identification and classification in breast cancer diagnosis can save lives by improving the accuracy of diagnoses and reducing the need for invasive procedures. However, the limited availability of well-annotated datasets for ultrasound images of breast cancer has hampered the development of accurate computer-aided diagnosis systems. The accuracy of breast mass classification using ultrasound images is limited due to the lack of well-annotated datasets. Conventional data augmentation techniques have limitations in applications with strict guidelines, such as medical datasets. Therefore, there is a need to develop a novel data augmentation technique to improve the accuracy of breast mass classification using ultrasound images. The proposed framework can be extended to other medical imaging applications, where the availability of well-annotated datasets is limited. The GAN-based data augmentation technique and TL-based feature extraction can be used to improve the accuracy of classification models in other medical imaging applications. Additionally, the proposed framework can be used to develop accurate computer-aided diagnosis systems for breast cancer detection in clinical settings. The proposed framework incorporates a deep learning-based approach for breast mass classification using ultrasound images. The framework includes a GAN-based data augmentation technique and TL for feature extraction. The dataset used for training and testing the model is the Breast Ultrasound Images (BUSI) dataset, which includes 1311 images with normal and abnormal breast masses. The proposed framework achieved an accuracy of 99.6% for breast mass classification using ultrasound images, which outperformed existing methods. The GAN-based data augmentation technique and TL-based feature extraction improved the accuracy of the classification model. The results suggest that deep learning algorithms can be effectively applied for breast ultrasound categorization. The proposed framework presents a novel approach for breast mass classification using ultrasound images, which incorporates a GAN-based data augmentation technique and TL-based feature extraction. The results demonstrate that the proposed framework outperforms existing methods and achieves high accuracy in breast mass classification using ultrasound images. This framework can be useful for developing accurate computer-aided diagnosis systems for breast cancer detection.
Teaching programming for students remotely during social isolation due to the COVID-19 pandemic

Due to the Pandemic caused by Covid-19, schools had to quickly adapt teaching to students. Faced with this situation, teachers had to overcome the challenges during this experienced period, and students had to learn to assimilate the contents remotely. Despite the difficulties and challenges faced by the professors, it was also an opportunity to learn how to use new technologies to assist in teaching and learning. The work had as a data collection instrument an online questionnaire produced in Google Forms, a questionnaire answered in person with the students, and an interview with two programming teachers of the school, anonymous and voluntary, being sent to the José Pacifico School of Moorish. It is noteworthy that we are going through moments of transformation and adaptation, in which we continue to learn and create new forms of teaching strategies. In this sense, technology becomes a positive strategy and contributes to student learning in remote learning, providing new ways to teach and learn.
Web Authentication Biometric 3D Animated CAPTCHA System Using Artificial Intelligence and Machine Learning Approach

The internet and web security are integral aspects of our daily lives. Many commercial firms provide clients with internet services. For web access, it is assumed that only the genuine user, who is a human, will register. Yet automated hacking programs can also do registrations with fake data that consume a lot of bandwidth, slowing down or occasionally even shutting down websites, leading to Distributed denial-of-service (DDOS) attacks. Completely Automated Public Turing test to tell Computers and Human Apart (CAPTCHA) is the solution. Complex CAPTCHA is challenging for humans to recognize, but simple CAPTCHA is simple for AI to decipher. With the developments in neural networks and machine learning bots are mimicking humans and it is becoming difficult to distinguish humans and bots apart. This generated a need to think of some more innovative and novel CAPTCHA. Now, utilizing the same AIML approach to increase the efficacy of CAPTCHA and make it stronger against the bot attack. Biometric 3D Animated (B3DA) Algorithm proposed in this research is a novel approach based on the Face Detection AI algorithm along with handwritten 3D animated characters selected randomly to create a string which makes CAPTCHA simple that humans can identify but very difficult for bots. The test results have proven this to be a very robust CAPTCHA. The machine learning algorithm employed will keep on increasing the efficacy of this CAPTCHA each time the bot tries to break this.
Policy Analysis for Prevention of the Danger of Drugs Abuse for Young Generation

The possibilities and challenges of youth development nowadays are followed by serious drug misuse problems among the younger generation, which continue to endanger the existence of youth as the holder of the leadership baton in attaining the nation's objectives. It has been demonstrated that drug misuse and illegal trafficking harm the nation's future. Therefore, the purpose of this study is to develop alternative strategies and policy recommendations that are acceptable and successful in preventing the dangers of teenage drug misuse. Using the analytical technique of Strategic Assumption Surfacing and Testing, the outcomes were analyzed (SAST). The data utilized are both primary and secondary and pertain to teenage drug addiction. This research focuses on five districts and cities in West Java and DKI Jakarta. The findings indicate that the prevalence of substance misuse in Indonesia remains relatively high. Therefore, efforts have been made at both the central and regional levels to combat the hazards of drug usage. There are five aspects of prevention that must be considered. Coordinate and synergize the implementation of an action plan program that can describe the model and form of anti-drug cadre training beginning with planning, implementing, monitoring, and evaluating, as well as integrating with other programs at the central and regional levels, is required to address these issues. regions as well as a defined road map for post-training anti-drug cadres as sustainable P4GN agents of change.
On Discerning Between Mixtures of Linearly Polarized Photons using the Hong-Ou-Mandel Effect and Heralding Photon

Abstract The Hong, Ou, and Mandel (HOM) effect allows to assess the similarity between the polarization of two (otherwise identical) photons that enter a beam-splitter from two different ports at the same time, without obtaining information regarding the absolute polarization. This report presents new methods that utilize the HOM effect with three photons to discern between mixtures of polarized photons. When one photon is detected in one port of the beam splitter, it heralds that the two other photons are likely to be identical. The resulted polarization statistics can be utilized to discern between mixed states of polarized photons that cannot be discerned by previous methods.
Kesalahan Berbahasa Tataran Semantik Dalam Unggahan Akun Instragram

There are a lot of language errors on social media, especially Instagram. One of the language errors that are also often found is language errors in semantics. This study aims to find out the language errors at the semantic level contained in Instagram information posters uploaded by @infobandungbarat. @infobandungbarat is the place to provide information throughout West Bandung district with slogan info in the area. The research method used in this study is a descriptive qualitative method with the final result in the form of a narrative. Data collection techniques in this study consisted of: 1) reading techniques, 2) note-taking techniques, and 3) documentation techniques. Data validation in research uses validity and triangulation of data sources. So from the results of this study it can be concluded that there are ten data obtained and analyzed. Errors contained in the data consist of word errors, word shortages, or inappropriate word placement, causing semantic language errors. The results of the analysis show that: 1) there are 5 data placement errors, 2) there are 4 word errors in the missing data, and 3) there are 1 data word errors.&#x0D; &#x0D; &#x0D;