Reviewerly/exHarmony huggingface dataset:
Image Security using Steganography and Cryptography

Cryptography and Steganography could be used to provide data security, each of them has a problem. Cryptography problem is that, the cipher text looks meaningless, so the attacker will interrupt the transmission or make more careful checks on the data from the sender to the receiver. Steganography problem is that once the presence of hidden information is revealed or even suspected, the message is become known . According to my proposed work in which both steganography and cryptography are combine and give good security for data. Firstly, the encrypted images has been hidden using image steganography method. Secondly, the Hash function algorithm has been modified and used to encrypt the stego image by using 128 digit hexa-key. Therefore, two levels of security have been provided using the proposed technique. In addition, the proposed technique provides high embedding capacity and better quality stego images.
PENGGUNAAN MEDIA PEMBELAJARAN SEBAGAI UPAYA MENCIPTAKAN PEMBELAJARAN AKTIF DI KELAS

Learning media is a learning tool or device that can be used by teachers to assist them in conveying learning messages. This study aims to determine how the influence of learning media in creating active learning. This research was conducted using descriptive qualitative method. Data collection techniques in this study used interview and observation techniques. Based on the research that has been done, the implementation of learning at SDN Kebon Jahe, especially in class V, has used learning media that makes learning run active.
Klasifikasi Komentar Instagram untuk Identifikasi Keluhan Pelanggan Jasa Pengiriman Barang dengan Metode SVM dan Naïve Bayes Berbasis Teknik Smote

Customer satisfaction is one of the things expected by a company when the product produced has been marketed, both in the form of goods and services. How to complain through customer service is very diverse, lately not only by telephone, customers submit their suggestions or complaints. Customers can submit their suggestions or complaints via e-mail or e-mail or forums in the virtual world that are made by product-producing companies to accommodate a variety of complaints, suggestions, and direct criticism from consumers, especially social media, who are free to express their opinions on shipping services. they use. Instagram is a social media that is more inclined to images and on the other hand has text captions and comments, from the above problems trying to make a research for customer complaints of users of goods delivery services on an Instagram account shipping service company. From the background of the problem, the researchers tried to solve the problem for text mining classifiers by using the Support Vector Machine (SVM) and Naïve Bayes methods and using the SMOTE technique with the usual processes for text mining so that they could produce 69.68% accuracy for Support Vector Machine (SVM) and Naïve Bayes with an accuracy of 88.54%, using the Instagram comment text dataset of 776 records that have been done with preprocessing text.
THE EFFECT OF HUMAN CAPITAL ON ECONOMIC GROWTH IN SOME SUB SAHARA AFRICAN COUNTRIES (SSA)

Purpose: This research looked into debate on the possible impact of human capital on economic growth in Sub-Saharan Africa (SSA) and considers two alternative measures of human capital: health and education.&#x0D; Methodology: The research used a dynamic model based on the system generalized method of moments (SGMM) and analysed a balanced panel data covering 35 countries from 1986–2018. The research used Microsoft excel to record all the data gotten from the world indicator data base from world bank, penn world table data base and CANA database. The analysis was presented in a tabular form.&#x0D; Findings: This study found that human capital has an overall positive and statistically significant impact on economic growth in the SSA region, although, democracy has a negative and statistically significant impact on economic growth in the region. This finding shows the importance of both measures of human capital and aligns with the argument in the literature that neither education nor health is a perfect substitute for the other as a measure of human capital.&#x0D; Unique contribution to theory, practice and policy:Generally, the finding emphasised that both education and health measures of human capital are important, and that policymakers must consider the level of economic development while formulating policies that can enhance the impact of human capital on economic growth in the Sub-Saharan Africa region.
Exploratory Study of Ecuadorian Teachers’ Understanding of Social Emotional Learning: An Examination of Primary School Teachers

Direct instruction of Social Emotional Learning (SEL) has been suggested for improving academic performance and reducing behavioral issues in classrooms (CASEL, 2020). This exploratory study provides insight into how a group of Ecuadorian elementary school teachers define and understand SEL. It examined changes in teachers’ perspectives and beliefs about their role in SEL integration in elementary school classrooms, after a full-day workshop focused on SEL integration. Quantitative and qualitative data collected before, during and after the SEL workshop indicated a positive change in the teachers’ foundational knowledge of SEL after participation in the workshop; however, there was no observed change in the teachers’ perceptions of their role in the actual implementation of SEL. Challenges and future implications for an effective integration of SEL are discussed in this research article.
Exploring Non-Autoregressive Text Style Transfer

In this paper, we explore Non-AutoRegressive (NAR) decoding for unsupervised text style transfer.We first propose a base NAR model by directly adapting the common training scheme from its AutoRegressive (AR) counterpart.Despite the faster inference speed over the AR model, this NAR model sacrifices its transfer performance due to the lack of conditional dependence between output tokens.To this end, we investigate three techniques, i.e., knowledge distillation, contrastive learning, and iterative decoding, for performance enhancement.Experimental results on two benchmark datasets suggest that, although the base NAR model is generally inferior to AR decoding, their performance gap can be clearly narrowed when empowering NAR decoding with knowledge distillation, contrastive learning, and iterative decoding.
La ciencia de la información y su objeto de estudio: problemas históricos y conceptuales

A historical review of information science in the second half of the 20thcentury is carried out. It is identified that, historically, there has been an attempt to specify what is its objectof study. The objective is to make explicit that it has been accepted as valid to determine an object for the discipline as an essential element for its scientificity. A bibliographic analysis is carried out, which allows us to examine the history of the discipline and study various theoretical contributions. It is observed that several of the discussions respond to the need to establish limits with respect to the different areas. The characteristics of Thomas Kuhn's philosophy are exposed, which offer another perspective regarding disciplinary consolidation which do not refer to the search for an object of study. It is concluded that the search for an object of study does not contribute or impact on the improvement of its scientific claims.
PUBLIC’S SENTIMENT ANALYSIS ON SHOPEE-FOOD SERVICE USING LEXICON-BASED AND SUPPORT VECTOR MACHINE

Technology field following how era keep evolving. Social media already on everyone’s daily life and being a place for writing their opinion, either review or response for product and service that already being used. Twitter are one of popular social media on Indonesia, according to Statista data it reach 17.55 million users. For online business sector, knowing sentiment score are really important to stepping up their business. The use of machine learning, NLP (Natural Processing Language), and text mining for knowing the real meaning of opinion words given by customer called sentiment analysis. Two methods are using for data testing, the first is Lexicon Based and the second is Support Vector Machine (SVM). Data source that used for sentiment analyst are from keyword ‘ShopeeFood’ and ‘syopifud’. The result of analysis giving accuracy score 87%, precision score 81%, recall score 75%, and f1-score 78%.
Structured Learning Based Turkish Sentiment Analysis

Sentiment analysis is highly popular topic to identify people's opinions through the social media, forums and other websites. There are an abundance of opinions on internet and analysing those opinions would have many benefits for both private and public sectors. Research has evolved looking on tweets for mining opinions and for the classification of the tweets as positive, negative or neutral in its sentiment. In this research, Turkish tweets are used for sentiment extraction where a two layer neural network is used as the pattern recognition system. The supervised training of this system is based on structured learning. As a conclusion, structured learning seems to be helpful in pattern recognition to classify tweets and mining the opinions. However, it is evident that further research in data processing and training methodology is necessary to obtain reliable sentiment analysis results.
New Constructions of Extended Sonar Sequences From Sidon Sets

A <inline-formula> <tex-math notation="LaTeX">$(m,n)$ </tex-math></inline-formula> sonar sequence is an <inline-formula> <tex-math notation="LaTeX">$m\times n$ </tex-math></inline-formula> array with exactly one dot in each column and where all lines connecting two dots in the array are distinct as vectors. These arrays are known to have many applications such as sonar and radar detection and these are studied as a particular case of Golomb rectangles or two-dimensional Sidon sets. The main open problem for sonar sequences is: for fixed <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>, find the largest <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> for which there is an <inline-formula> <tex-math notation="LaTeX">$(m,n)$ </tex-math></inline-formula> sonar sequence, these sequences are called the best sonar sequences. The extended sonar sequences are generalizations of sonar sequences where each column has at most one dot, the motivation to study these arrays are the best results obtained when applied to radar and sonar detection. In this paper, we give the best sonar sequences with <inline-formula> <tex-math notation="LaTeX">$m\leq 100$ </tex-math></inline-formula> obtained from an exhaustive computational search based on the Caicedo, Ruiz and Trujillo constructions and we present new constructions of extended sonar sequences that use Sidon sets.
Implementation of Dijkstra Algorithm with React Native to Determine Covid-19 Distribution

Since Covid-19 was declared a global pandemic because it has spread throughout the world, every effort has been made to help prevent and tackle the transmission of Covid-19, including information technology. Information technology developed to determine the shortest distance for Covid-19 cases around us needs to be developed. This research implements Dijkstra's Algorithm written in the React Native programming language to build a Covid-19 tracking application. The system can display the closest distance with a radius of at least one meter, and the test results can map the nearest radius of 41 meters and the most immediate radius of 147 meters. This system is built for the compatibility of Android OS and iOS applications with React Native programming.
Comparing Text Representations: A Theory-Driven Approach

Much of the progress in contemporary NLP has come from learning representations, such as masked language model (MLM) contextual embeddings, that turn challenging problems into simple classification tasks.But how do we quantify and explain this effect?We adapt general tools from computational learning theory to fit the specific characteristics of text datasets and present a method to evaluate the compatibility between representations and tasks.Even though many tasks can be easily solved with simple bag-of-words (BOW) representations, BOW does poorly on hard natural language inference tasks.For one such task we find that BOW cannot distinguish between real and randomized labelings, while pre-trained MLM representations show 72x greater distinction between real and random labelings than BOW.This method provides a calibrated, quantitative measure of the difficulty of a classificationbased NLP task, enabling comparisons between representations without requiring empirical evaluations that may be sensitive to initializations and hyperparameters.The method provides a fresh perspective on the patterns in a dataset and the alignment of those patterns with specific labels.
Signature Verification using Edge Detection and Oc-Svm

There are many researches going on in the field of Image processing to find an accurate model for detection of forged signatures. It is compulsory to select appropriate algorithm for achieving best results. Many have implemented the available algorithms like LBP, HOG, geometric features and some have designed their own extraction techniques like Histogram of template and mixture of many complex algorithms to detect the forgeries. In our model we extracted edge features of the image using canny edge detection and then extracted features using HOG and then we calculated area, standard deviation, centroid, kurtosis etc. for the edge image which give a feature vector of length 262. There is little research towards one class SVM or outlier detection. We trained our model with different kernels of SVM to find which kernel gives best result. This OC-SVM will be very helpful than a multi class SVM as we will be having only original signatures of the users and not forged so it will be best to use though it is very sensitive it can be used even in the real world.
Impact of Advantageous Campaigns on Customer-Brand Relationship Building Through Social Media Marketing

Marketing has been paying close attention to social media engagement because of its potential to influence consumer behaviour. A key component of marketing communication in Oman is the use of social media. In this research paper, we aim to identify the dynamics of the influence of social-media marketing elements (e.g., valuable campaigns, relevant content, frequent updates, popular content, and brand appearances on different platforms) on consumer perceptions of customer-brand relationship building. Researchers collected data on 209 respondents by using purposive sampling in a field survey conducted in Muscat, Oman. Adapted from prior research, the data collection instrument contains items measured on a Likert scale. Results of the study revealed that the predictors (advantageous campaigns, relevant content, frequent updates, popular content, and appearance of brand on various platforms) significantly impact customer-brand relationships. Consequently, this study adds to the growing body of work on social media marketing (SMM) by exploring the role of SMM in enhancing important branding goals, including customer loyalty. This study extends the benefits of social media marketing to management by providing insight on how to engage customers and increase sales.
Implementasi Metode Unsupervised Learning Pada Sistem Keamanan Dengan Optimalisasi Penyimpanan Kamera IP

Security monitoring systems using face recognition can be applied to CCTV or IP cameras. This is intended to improve the security system and make it easier for users to track criminals is theft. The experiment was carried out by detecting human faces for 24 hours using different cameras, namely an HD camera that was active during the day and a Night Vision camera that was active at night. The application of Unsupervised Learning method with the concept of an image cluster, aims to distinguish the faces of known or unknown people according to the dataset built in the Raspberry Pi 4. The user interface media of this system is a web-based application built with Python Flask and Python MySQL. This application can be accessed using the domain provided by the IP Forwarding device which can be accessed anywhere. According to the test results on optimization of storage, the system is able to save files only when a face is detected with an average file size of ± 2.28 MB for 1x24 hours of streaming. So that this storage process becomes more efficient and economical compared to the storage process for CCTV or IP cameras in general.
Subword Mapping and Anchoring across Languages

State-of-the-art multilingual systems rely on shared vocabularies that sufficiently cover all considered languages.To this end, a simple and frequently used approach makes use of subword vocabularies constructed jointly over several languages.We hypothesize that such vocabularies are suboptimal due to false positives (identical subwords with different meanings across languages) and false negatives (different subwords with similar meanings).To address these issues, we propose Subword Mapping and Anchoring across Languages (SMALA), a method to construct bilingual subword vocabularies.SMALA extracts subword alignments using an unsupervised stateof-the-art mapping technique and uses them to create cross-lingual anchors based on subword similarities.We demonstrate the benefits of SMALA for cross-lingual natural language inference (XNLI), where it improves zero-shot transfer to an unseen language without taskspecific data, but only by sharing subword embeddings.Moreover, in neural machine translation, we show that joint subword vocabularies obtained with SMALA lead to higher BLEU scores on sentences that contain many false positives and false negatives.
PENGEMBANGAN E-MODUL BERBASIS DISCOVERY LEARNING PADA PEMBELAJARAN TEMATIK TEMA 6 SUBTEMA 1 HEWAN DI SEKITAR KU SD KELAS II

This study aims to produce an E-Module based on discovery learning in thematic learning of theme 6 sub-theme 1 for class II SD which is valid and practical and to determine the potential effects of development. This research is included in research and development, referring to the development of ADDIE. The research took place at SDN 199 Palembang. The research subjects were 24 second grade elementary school students. Data collection was carried out by means of a media and language expert validation questionnaire, material expert, mathematics teacher questionnaire, student response questionnaire, and student test result data. The data were analyzed quantitatively and qualitatively. The results showed that the validation of the validators got an average validation score of 88.66% with a valid category. The results of student responses based on trials got an average score of 91.58% in the practical category. The results of the test questions distributed to 24 students contained 21 students who completed and 3 students did not complete, the average student score was 84.50% in the very good category or had a potential effect on student learning outcomes. Keywords: E-Module, ADDIE, Discovery Learning, Thematic Theme 6 Sub-theme 1
K-MEANS CLUSTERING FOR GROUPING INDONESIA UNDERDEVELOPED REGIONS IN 2020 BASED ON POVERTY INDICATORS

Poverty is still a problem in Indonesia, especially in underdeveloped areas. Underdeveloped areas are areas where the region and its people are less developed than other regions on a national scale. The classification of disadvantaged areas is determined by the president in the Presidential Regulation of the Republic of Indonesia Number 63 of 2020 concerning the Determination of Underdeveloped Regions of 2020-2024. Various policies need to be set by the government to overcome poverty in underdeveloped areas. Program planning strategies may be different for each region. Therefore, in order to achieve an optimal implementation of poverty alleviation programs, it is necessary to group the districts covered in underdeveloped areas in Indonesia based on poverty indicators. The data used is macro data from the characteristics of each region in disadvantaged areas obtained from regional publications in the figures for each district. From the results of the analysis of k means clustering formed three groups with different characteristics in each cluster. In cluster one, the focus of government policies is on employment and sanitation aspects, cluster two is on health, education, and employment aspects, cluster three is on all aspects because cluster three is the area with the highest percentage of poor people compared to the other two clusters. The high percentage of poor people is also followed by other poor aspects.
Herramientas digitales para recolección, procesamiento y presentación de datos de campo como instrumento para afrontar la contingencia COVID-19

In March of 2020, the COVID-19 outbreak forced people to lock themselves inside their homes and begin the process of transitioning from face-to-face activities at work, schools and universities to a 100 % virtual method. Even when Communication Technologies (ICT) and online platforms have seen growth over the past two decades, including various virtual libraries developed by database publishers or web-based training programs that appear to shorten the learning curve (Lee, Hong y Nian, 2002), many people were unprepared for this transition and all of them are now dedicated to entering the new reality. In this order of ideas, the activities that have traditionally required the assistance of the staff have had to adapt with the use of new tools, which meet daily needs. A clear example is the field work collection tasks. In this group, there are different types such as surveys, photographs, reviews or on-site inspections. The current work presents the use of tools for collecting, validating, analysing and presenting data remotely and in real time. All of them based on the ArcGIS Online platform.
Cloud Computing-Based Information System as an Effort for Developing Tourism Village

Cloud computing-based information system is an effective way for regional development.By utilizing the existing potential dan supported by good management, the area can be used as the development of surrounding resources.Information management based on Cloud Computing can be used as a promotional medium that can improve various sectors of the region.This study aims to explain an information system based on Cloud Computing as an effort to develop a tourist village.This research is literature study.Data collection is done by reviewing and also exploring several journals, articles, data sources, as well as various information that is considered relevant to the research.The results of this study indicate that Cloud Computing in tourist villages makes the data owned can be stored on a centralized server and also has a high security guarantee.Cloud Computing is able to store data virtually, making it easier for users without having to provide storage devices such as hard drives.In addition, the tourism potential owned by the village can be better known by the wider community by the existence of the Cloud Computing-based information system.Therefore, it can be said that Cloud Computing in tourist villages is an effective, efficient and innovative step to introduce the potential of the village to the wider community.Cloud computing is very easy for tourists, because media information about village tourism can be accessed anytime and anywhere.