Reviewerly/exHarmony huggingface dataset:
REPRODUCTIVE HEALTH SOCIALIZATION FOR ADOLESCENTS USING A COMBINATION OF CROSSWORDS AND LECTURE METHODS

The human reproductive system begins to become active at the age of adolescence. Therefore, they are expected to understand how to maintain the cleanliness and health of their reproductive organs to reduce the risk of unwanted pregnancy and the transmission of HIV/AIDS. With this urgency, the following activities were carried out to provide education about reproductive health to adolescents in Sekaran Village, Balen District, Bojonegoro Regency. This activity was carried out to 47 students in grades 7, 8, and 9 of MTs Manba'ul Huda, Bojonegoro Regency. The activities were chosen using the methods of lecture and playing crossword, as the presence of games can enhance students' interest in engaging with the presented material. The data was collected using a questionnaire in the form of pre-test and post-test given to the students. Then statistical analysis was performed using the Wilcoxon test to measure the difference between the pre-test and post-test scores. From these two values, it was found that there was an average increase from the results of the pre-test (32.34 ± 20.664) to the post-test (58.30 ± 26.826). From the results of data analysis that has been carried out, it can be concluded that the method of playing crossword and lecture is effective for increasing the knowledge of MTs Manba'ul Huda students about adolescent reproductive health.
Counting in Visual Question Answering: Methods, Datasets, and Future Work

Visual Question Answering (VQA) is a language-based method for analyzing images, which is highly helpful in assisting people with visual impairment. The VQA system requires a demonstrated holistic image understanding and conducts basic reasoning tasks concerning the image in contrast to the specific task-oriented models that simply classifies object into categories. Thus, VQA systems contribute to the growth of Artificial Intelligence (AI) technology by answering open-ended, arbitrary questions about a given image. In addition, VQA is also used to assess the system’s ability by conducting Visual Turing Test (VTT). However, because of the inability to generate the essential datasets and being incapable of evaluating the systems due to flawlessness and bias, the VQA system is incapable of assessing the system’s overall efficiency. This is seen as a possible and significant limitation of the VQA system. This, in turn, has a negative impact on the progress of performance observed in VQA algorithms. Currently, the research on the VQA system is dealing with more specific sub-problems, which include counting in VQA systems. The counting sub-problem of VQA is a more sophisticated one, riddling with several challenging questions, especially when it comes to complex counting questions such as those that demand object identifications along with detection of objects attributes and positional reasoning. The pooling operation that is considered to perform an attention mechanism in VQA is found to degrade the counting performance. A number of algorithms have been developed to address this issue. In this paper, we provide a comprehensive survey of counting techniques in the VQA system that is developed especially for answering questions such as “How many?”. However, the performance progress achieved by this system is still not satisfactory due to bias that occurs in the datasets from the way we phrase the questions and because of weak evaluation metrics. In the future, fully-fledged architecture, wide-size datasets with complex counting questions and a detailed breakdown in categories, and strong evaluation metrics for evaluating the ability of the system to answer complex counting questions, such as positional and comparative reasoning will be executed.
MODIFIKASI HILL CIPHER DENGAN MENGGUNAKAN MATRIKS KUNCI ORTHOGONAL DAN TRANSPOSITION SUBSTITUTION LEFT RIGHT SHIFT (TSLRS)

Matrix is a collection of components arranged in rows and columns, concept of a matrix can be used in solving a problem related to cryptography. A mathematician named Lester Hill created a polyalphabetic cryptographic system called the Hill Cipher. Hill cipher is an algorithm that in its process uses a matrix with size (a × a) as the key matrix. The classic Hill Cipher has the disadvantage that the operation used is not complicated. In this study, the classic Hill Cipher will be modified by using an orthogonal matrix as the key matrix, as well as adding several other operations such as transposition, substitution, and bit shift. This study compares the performance of the traditional Hill Cipher and the modified Hill Cipher in terms of cryptographic techniques on data(text). This research was conducted by encrypting and decrypting the classic Hill Cipher and modified Hill Cipher using similar data (text). Furthermore, a simulation will be carried out using Matlab so that it can use data (text) with a larger size. The results obtained are Hill Cipher which has been modified using an asymmetric cryptographic system, that is in left-right shift process so that the matrix keys will be different when use for encryption and decryption. Because it uses a different key in the encryption and decryption process, thus increasing the level of difficulty in decoding the message.
Poverty Level Prediction Based on E-Commerce Data Using Naïve Bayes Algorithm and Similarity-Based Feature Selection

The poverty rate is an important measure of any country because it indicates how well the economy develops and how well the economic prosperity distributes among citizens. The Central Statistics Agency, or BPS, measures the poverty rates in Indonesia using the concept of the ability to meet demands (basic needs approach). Using this approach, spending becomes a measure of poverty, defined as an economic incapacity to satisfy food and non-food requirements. Thus, the poor are individuals whose monthly per capita spending is less than the poverty threshold. In this study, the machine learning method using Naive Bayes with similarity-based feature selection and e-commerce data has been proposed to predict the poverty level in Indonesia. We proposed the method to be used as a complement to the results of the costly surveys and censuses conducted by BPS. Our experiments show that the classifier shows little relevance between the predicted and the original values or actual poverty prediction based on BPS data. A limited number of features does not necessarily result in poor accuracy, however great accuracy is not always achieved if a lot of features are being used.
POLA KESALAHAN PENGERJAAN SOAL CERITA MATEMATIKA SISWA SEKOLAH DASAR BERBASIS GENDER

Errors in the work on fractional material metamatics are still commonly found in elementary schools but no one has made a pattern of errors that are often experienced by male students and female students in grade IV elementary schools, therefore the purpose of this study is to find out the pattern of miswork on fractional material stories in elementary schools. grade IV elementary school students by gender. The error analysis pattern uses Newman's theory with five types of errors namely reading errors, comprehention errors, transformation errors , process skill errors , and errors in writing the final answer conclusion (Endcoding Errors). The subjects in this study amounted to 48 grade IV elementary school students with 24 male students and 24 female students. Qualitative case studies were used in this study using data collection techniques in the form of documentation of question work and interviews. The transkrip results of documentation analysis and transkrip interviews were then used to make patterns of miswork on grade IV students based on gender using the help of the Nvivo 12 plus application by codifying to make project map outputs in order to obtain patterns of errors in working on questions based on gender, namely the pattern of male students and students Women who produce patterns of more differences in error patterns than the similarity of patterns of work errors between male students and female students in grade IV elementary schools.
Innovative development of Russian universities in the context of accelerated growth of the world market of higher education services

the article presents the results of a study of the processes of innovative development of Russian universities in the context of accelerated growth of the world market of higher education services. The volume of the market of higher education services in the Russian Federation in 2016-2021 is analyzed. The prerequisites for accelerated growth of the world market of educational services and its on–line segment are determined.
The Impact of Images in Enhancing the ESL Vocabulary Breadth of Malaysian Year 4 Students

The role of ESL vocabulary plays in language competence and literacy development is increasingly prevalent in language acquisition studies, especially so within the domain of second language acquisition research. In Malaysia, generally, the young learners face difficulties in their learning is due to their scarce vocabulary knowledge. This quasi-experimental study scrutinizes how the employment of images in Malaysian primary school level ESL classrooms via the adapted Picture Word Inductive Model (PWIM) effects on students’ ESL vocabulary breadth development. Both the experimental group (n=35) and control group (n=35) consisted of Malaysian national primary school Year 4 pupils. The vocabulary recall and retention of the two intact groups were collated. The data of the two groups were collected from pre-tests, post-tests, and delayed post-tests. These collected data were statistically analysed and assessed. The analysis shown that the Experimental group demonstrated higher recall and retention implying the efficacy of PWIM in enhancing the ESL vocabulary breadth knowledge recall and retention among Malaysian young learners. This study and its findings are of significance to shed light on the development of the ESL vocabulary research. Besides, there is a dearth of thorough study pertinent to the use of images for language learning, especially for the Malaysian primary level 2.
Automated Creation of a Repository for Learning Words in the Area of Computer Science by Keyword Extraction Methods and Text Classification

In this work, it is presented an innovative approach towards the automated creation of a repository for word learning in the area of computer science. In the vast expanse of technical terminology, learners often find it difficult to understand the complex lexicon used in the field of computer science. To fill this gap, we present an intelligent system that combines the use of keyword extraction methods, text classification, word2vec, KeyBERT and Scrapy. Keyword extraction is performed using Key BERT, a minimal and high-performance keyphrase extraction model, which allows us to isolate the most relevant terms from the computer literature. Scrapy, a fast, open-source web crawling framework, is used to collect large volumes of computer-related data from various online resources. We then employ text classification algorithms to sort and categorize the extracted terms based on their context and usage. In addition, we take advantage of the Word2Vec model, a two-layer neural network, to transform these textual inputs into numerical form. This model not only simplifies data handling, but also facilitates the understanding of semantic relationships between terms by creating a vector space in which words with similar meanings are placed close to each other. It generates a large dataset of computer-related words and presents them in a contextualized way. The automated process not only facilitates the learning and understanding of complex terminologies for both students and professionals, but also promotes consistency in the use of technical jargon across the field. This innovative approach streamlines the process of learning new computer terms and concepts, as the system is able to provide context-based learning of words and terminologies. The keywords are then stored in an easily accessible repository, in addition to an accurate translation of each keyword in the Spanish language and its respective definition, using the ChatGPT API tool, in order to provide more optimal support and improved understanding. The quantitative results of the study show that this automated system significantly improves the efficiency of the computer terminology learning process.
SentiDariPers: Sentiment Analysis of Dari-Persian Tweets Based on People’s Views and Opinion

In the research area of sentiment analysis, there is a noticeable gap when it comes to the Dari-Persian dialect. To bridge this gap, our research aimed to curate a comprehensive dataset encompassing people’s opinions in this specific language variant. This paper presents the development of a benchmark sentiment annotated dataset for the Dari dialect of Persian, which serves as an official language of Afghanistan. The dataset, named “SentiDariPers”, comprises 43,089 tweets posted between August 2021 and April 2023. It has been manually annotated with four sentiment classes: Negative, Positive, Neutral, and Mixed. We applied a range of models, such as Support Vector Machine (SVM), Long Short-Term Memory (LSTM), Bi-directional Long Short-Term Memory (Bi-LSTM), Gated Recurrent Unit (GRU), and Convolutional Neural Network (CNN). Additionally, we develop an ensemble model that combines different sets of sentiment classes for each system. We present a detailed comparative analysis of the results obtained from these models. Experimental findings demonstrate that the ensemble model achieves the highest accuracy 91%. We provide insights into the data collection and annotation process, offer relevant dataset statistics, discuss the experimental results, and provide further analysis of the data.
On the issue of using RFID technologies in the activities of production units of the penal system

The article describes the possibility of using radio frequency identification of objects (RFID) technology in the practical activities of an economic entity. The principle of operation of RFID technology in practical conditions is described. The analysis of digital technologies used at Russian enterprises is given, indicating that this technology is in fifth place in terms of distribution. The industries where the use of this technology has yielded tangible results are given. The main advantages of this system in comparison with barcodes and QR codes are listed. The possible directions of application of this technology in production units are highlighted.
Blockchain and its Potential in the Digitization of Land and Real Estate Property Records

A blockchain, is a decentralized digital ledger that is distributed across multiple computers, recording transactions in a way that cannot be altered without the consent of the network and the alteration of all subsequent blocks. In the context of land and real estate property records, a blockchain could be used to securely and transparently track the ownership and transfer of properties. Using a blockchain to digitize land and real estate records can have several benefits. For example, it can help reduce the risk of fraud, as all transactions are recorded on a secure and tamper-proof ledger. It can also make the process of transferring ownership more efficient, as it can automate many of the steps involved and reduce the need for intermediaries. Additionally, a blockchain can increase the transparency of the property market, as all records will be publicly available on the ledger. In this work, we examine the current situation and the related problems in registering land and real estate property records, especially in developing countries, and we state the challenges and opportunities of the application of blockchain technology in this field. We investigate whether blockchain has the potential to bring a positive change and play a significant role in the real estate market in the future and what are the prerequisites to achieve that.
Projection of Socio-Linguistic markers in a semantic context and its application to online social networks

Relevant socio-psychological processes can be detected in social networks thanks to an analysis of linguistic markers that sheds light on the characteristics and dynamics of the social discourse. Usually, linguistic markers comprise a list of words representative of a given construct; however, this approach does not account for contextual interdependencies of words, which can amplify or diminish the relevance of a particular word. In this paper, we present and leverage a scalable method called PageRank-like marker projection (PLMP) that addresses this problem. Its rationale, inspired by PageRank, is meant to fully exploit the interdependencies in a semantic network to project markers from a social discourse level (tweets) to its semantic elements (words). We show how PLMP is able to associate markers with specific words from their semantic context, which allows for an even richer interpretation of the online sentiment. We demonstrate the effectiveness of PLMP in practice by considering specific instances of social discourse on Twitter for three exemplary calls to collective action.
Tecnologias de fala e a variação de pronúncia do russo no contexto de VoiceInteraction

This article aims to describe the work conducted at VoiceInteraction, a company specialized in speech processing solutions, with a particular focus on automatic transcription using a Hybrid Automatic Speech Recognizer (ASR). The primary objective revolved around studying the phonetic characteristics of the Russian language, encompassing four main tasks: describing the phonetic-phonological inventory, validating news transcriptions, validating a previously created lexicon, and integrating filled pauses into the ASR. This work contributed to the Artificial Intelligence and Advanced Data Analysis for Authority Agencies (AIDA) project, funded by the European Commission under the Horizon 2020 program, by transcribing the data in the Russian language.
Blockchain Application Using NFT Marketplace

The emergence of Non-Fungible Tokens (NFTs) has revolutionized the digital ownership landscape, offering a secure and transparent way to represent ownership and provenance of digital assets. NFT marketplaces have risen as essential platforms, facilitating the creation, exchange, and trade of these unique digital assets. This research paper presents a rigorous investigation into the intricate process of designing and implementing a fully functional NFT marketplace, akin to industry leaders such as Opensea. By harnessing the capabilities of blockchain technology and smart contracts, this study explores the profound implications, technical intricacies, and market dynamics that underlie the development of a cutting-edge NFT marketplace. The research paper's foundation is a meticulous literature review that synthesizes insights from a curated selection of seminal works. These sources provide a robust theoretical framework, which informs the study's understanding of blockchain technology, NFTs, and digital marketplaces. The methodology section of this research outlines the step-by-step process for building an NFT marketplace. It delves into the selection of blockchain technology, the development tools, and the use of smart contracts. The paramount objectives are to ensure the security and unique representation of NFTs, facilitating trust in this innovative digital ecosystem. The architecture of the NFT marketplace is expounded upon, encompassing its various components, layers, and functionalities. This encompasses the creation, buying, selling, and management of NFTs, coupled with robust security measures, ensuring the integrity of the platform and the safety of its users. A comprehensive case study is presented to provide a real-world illustration of the NFT marketplace's operation. Through the utilization of actual data and statistics, this case study offers insights into the marketplace's performance, user experience, and economic impact, further substantiating the platform's practical viability. Results and discussion critically analyze the case study findings, while concurrently addressing the challenges encountered during development, including innovative solutions. A comparative analysis with existing NFT marketplaces underscores the unique value proposition of the platform and potential areas for further improvement. This research paper underscores the significance of NFT marketplaces in the digital economy. By offering a roadmap for the development of a secure, user-friendly, and functional NFT marketplace, this study contributes to the ongoing discourse on blockchain applications and digital asset management. The research paper presents significant scholarly and economic potential, laying the groundwork for further research in this dynamic and transformative field.
Improving the Professionally Significant Gualities of the Personality of Specialists in the System of Advanced Training of Personnel

The article reveals the problem of the formation and development of professionally significant qualities of the personality of specialists in the context of the tasks of the system of advanced training of personnel. This task in the studies of modern scientists (S.N. Begizhova, G.V. Koloshina, O.A. Mosina, Yu.V. Sorokopud, etc.) is presented as important in the context of continuous professional development and self-development of representatives of different professions. Its solution within the framework of the personnel development system is justified as socially and personally significant; provided with a psychological and pedagogical theoretical and methodological basis for certain groups of qualities; methodologically and technologically presented in rare studies that consider this issue in relation to specific organizational forms of advanced training. The aim of the work was to determine the set of organizational and pedagogical conditions for improving the professionally significant qualities of the personality of specialists in the system of advanced training of personnel, taking into account the organizational and content variability of this system. To achieve it, methods of theoretical analysis, generalization and modeling were used, which made it possible to systematize and concretize information regarding the structure of professionally significant personality traits of specialists and the conditions for their improvement. The works of modern scientists in the field of the essence, structure, composition of professionally significant personality traits among representatives of different professions (on the example of professions of the “man-man” type) made it possible to single out two structural elements - characterological and motivational qualities, and confirmed the expediency and possibility of their conjugated formation and development . Researches of scientists in the field of principles and methods of development of personal qualities, abilities, motives and value orientations, as well as in the field of organizational features and targets of various forms of advanced training of personnel determined the structure of organizational and pedagogical conditions for improving professionally significant qualities of the personality of specialists, including groups of invariant (mainly , methodological) and variable (mainly organizational and methodological) conditions.