Reviewerly/exHarmony huggingface dataset:
ZNAČAJ DIGITALIZACIJE I DIGITALNIH BIBLIOTEKA U VRIJEME PANDEMIJE COVID-19 NA PRIMJERU GAZI HUSREV-BEGOVE BIBLIOTEKE U SARAJEVU / THE IMPORTANCE OF DIGITIZATION AND DIGITAL LIBRARIES AT THE TIME OF THE PANDEMIC COVID-19 IN THE EXAMPLE OF GAZI HUSREV-BEY LIBRARY IN SARAJEVO

The subject of this paper is the analysis of the importance of digital libraries for pupils, students, professors, librarians and researchers in Bosnia and Herzegovina, but also around the world during the COVID-19 pandemic and frequent closures of cultural, information and heritage institutions. In 2017, the Gazi Husrev-bey Library established digital library, and its importance and importance of other digital libraries and repositories from around the world was best seen in the extraordinary conditions in which libraries were forced to continue their operations. In all of this, it is extremely important to mention the role of librarians and information experts, thanks to whom the educational processes and access to the necessary literature could be successfully continued. The importance of digitization is even greater if you take into account its role for international cooperation and the development of good relations between related institutions, especially in the Balkans. The aim of the paper is to present the importance of digital libraries, so that more users would learn about their existence, and at the same time encourage other institutions to start this type of activity. The analytical method will lead to basic conclusions related to the use and expediency of digital libraries, taking into account the forced closure of library buildings and the transition to digital or digitized content in all information and heritage institutions around the world through the example of Gazi Husrev-bey's library in Sarajevo.
Development of Pop-up Book Learning Media to Improve Student Language Skills

Learning media has a big impact on the success of the teaching and learning process. This study aims to develop innovative and interactive pop-up book learning media, as well as knowing the practicality of the learning media of energy changes in energy. This study uses the Research and Development (R&amp;D) approach using the ADDIE development model (Analysis, Design, Development, Implementation, and Evaluation). The sample of this study was all students of Class III SD Negeri 169 Purba Julu, Kec Puncak Sorik Merapi with research instruments in the form of validation sheets of material, language, and design experts. The results showed that the pop-up book learning media developed energy changes had met the validators' criteria based on validator assessment with material validity value of 4.6 with a very feasible category, for the value of language validity of 4.7 with a very feasible category, and for values Design validity of 4.6 with a very decent category. Pop-up Book Learning Media Changes developed have met practicality criteria through: a) Teacher response questionnaire results to interactive teaching materials show practical values of 4.6 with a very practical category; b) The results of student response questionnaires to interactive teaching materials show a practical value of 4 with a very practical category.
PERBANDINGAN METODE CART DAN NAÏVE BAYES UNTUK KLASIFIKASI CUSTOMER CHURN

Classification is the process of identifying and grouping an object into the same group or category Classification can be used to group a large-sized dataset, and some commonly used classification methods are CART (Classification And Regression Tree) and Naïve Bayes. This study discusses the comparison of CART and Naïve Bayes methods by measuring accuracy, precision, recall, and f1-score values with 3 scenarios of training and testing dataset distribution. Accuracy, precision, recall, and f1-score measurements are performed using a confusion matrix. The scenarios for training and testing dataset division are 70%, 80%, and 90% of the training dataset. From the results of the study, CART has the highest average accuracy and f1-score of 79.616% and 57.636% respectively, while the highest average accuracy and f1-score of Naïve Bayes are 75.104% and 62.004% respectively.
Retainer cekat sebagai metode retensi Pasca perawatan ortodonti (scoping review)

Background: Cases of relapse after orthodontic treatment are often reported with a prevalence that tends to be high. The retention method using a fixed retainer is commonly used to obtain long-term stability of orthodontic treatment results. Objective: To determine the effectiveness of fixed retainers post orthodontic treatment. Methods: This research was conducted using the scoping review method based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines in the period of September 2022-December 2022. Article researches were adjusted to the inclusion and exclusion criteria, as well as the established PCC concept using Google Scholar and PubMed databases. Results: After using the correct keywords and Boolean terminology, 319 articles were identified in the database and further selection was then made. A total of 12 articles met the inclusion criteria, in which the effectiveness of the fixed retainers was described based on the clinical parameters listed in each article. Conclusion: The use of fixed retainers is effective in maintaining the stability of anterior teeth alignment after orthodontic treatment.
Survei jenis bahan cetak gigi tiruan cekat di jakarta

Background: Fixed prosthodontics final impression is heavily influenced by the impression material selection. Purpose: To find out the impression materials used by dentists in for fixed prosthodontics impression in Jakarta. Methods: Descriptive observational research with a cross-sectional design involving 96 respondents. Data collected using a questionnaire distributed to dentists in Jakarta through google form. Results: The usage percentage of polyvinyl siloxane is higher than alginate and polyether for fixed prosthodontics final impression. Conclusion: The percentage of never using alginate impression material was (57%), The very often frequency of using polyvinyl siloxane shows a percentage of (56%). The results of this study indicate that the use of polyvinyl siloxane is more widely used by dentists in Jakarta.
Correction: Mushtaq et al. Super Resolution for Noisy Images Using Convolutional Neural Networks. Mathematics 2022, 10, 777

In the original publication [...]
Deep Learning Model Compression Techniques: Advances, Opportunities, and Perspective

Recently, deep learning (DL) models have excelled in a wide range of fields. All of these successes are built on intricate DL models. The hundreds of millions or even billions of parameters and high-performance computing graphical processing units or tensor processing units are largely responsible for their achievement. DL model integration into real-time devices with tight latency limitations, limited memory, and power-constrained requirements is the key driving force behind investigation of DL model compression techniques. Also, there is an increase in data availability that encourages multimodal fusion in DL models to boost the models' predictive accuracy. In order to create compact DL models for deployment that is memory- and computationally efficient, the data included in the network parameters is compressed as much as possible, leaving only the bits necessary to carry out the task. A better trade-off between compression rate and accuracy loss should be established to take model acceleration and compression into consideration without severely reducing the model's performance. In this paper, we examine various DL model compression techniques used for both single- modality and multi-modal deep learning tasks. We explore over numerous DL model compression methods that have advanced in a number of applications. We then come up with the benefits and drawbacks of various compression and acceleration methods such as ineffectiveness in compressing more complicated networks with dimensionality-dependent complex structures, and, ultimately, the field's future prospects are given.
Perbedaan Hasil Belajar Menggunakan Model Pembelajaran Discovery Learning Berbantu Aplikasi Quizizz dengan Pembelajaran Konvensional

This study aim to compare learning outcomes in Class XI SMAN 1 Pantai Cermin using the Quizizz Aplication-assisted Discovery Learning learning model versus the Conventional learning model. A quasi-experimental design, purposive sampling technique, instrument testing, gain score, validity, reliability, different test questions, and level of difficulty were all used in the study. Data collection and documentation, as well as learning outcomes tests This study's population was class XI IPS SMA N 1 Pantai Cermin, with samples XI IPS 3 for the experimental class and XI IPS 2 for the control class. The paired sample t-test and independent sample t-test analysis methods were used. The study found that there are differences in student learning outcomes when using the Quizizz Aplication assisted Discovery Learning learning model versus traditional methods.
Facilitating EFL Students’ Learning Listening Subject through English Songs: The Audio-Lingual Method Perspectives

Listening skill is considered to be a challenging activity for English as a Foreign Language (EFL) learners in the context of English language learning. The present article aims at discussing the utilization of English songs as one of the learning sources for learning listening skills for EFL learners from the perspective of the Audio-Lingual Method (ALM). A qualitative descriptive research design was applied to scrutinize how English songs benefit for EFL learners to facilitate their listening subject. The data were obtained from previous related research findings and documentation studies. Furthermore, it discusses the relationship between song and listening, song as media to facilitate listening skills, the reasons for why using the songs as the learning media, the implication of using the songs to improve listening skills, and the benefits of using English song as a learning media. Review literature shows that the utilization of English songs may improve students’ listening skills and pronunciation over time. The ALM may assist learners in systematically learning the language by playing audio files. Students can comprehend brief and easy sentences when music is played in the background. English songs may assist learners in improving their listening skills and can be used for a variety of learning objectives. From the perspective of the ALM, English songs allow students to better understand the language being taught because it needs a high level of concentration as purposed by the ALM teaching and learning characteristics. In conclusion, from the perspective of ALM, English songs may bring positive contribution to the development of EFL students’ listening skills for some reasons.
Topic Modelling, Classification and Characterization of Critical Information

The misinformation, spread on the social media sites such as Twitter, overshadows the utility of such platforms, especially during times of crisis.Fake content is spread to popularize unauthorized treatments or downgrade the efficacy of preventative measures and treatments, resulting in spread of anxiety, depression and chaos amongst society.It is need of the hour, therefore, to apply the technologies like deep learning, natural language programming, and data mining, to develop automated systems that can discern false information from the real information, characterize it for better understanding, and mine it to derive actionable knowledge, that helps to check the spread of misinformation.This work proposes an automated framework that uses a combination of NLP & descriptive and predictive machine learning techniques.COVID-19 related messages on the social media sites are classified as appropriate or misleading using a deep learning model.With an accuracy of 86% BERT classifier was used to classify 3777 tweets.The model tagged 2350 tweets as real and 1427 tweets as fake.The classified social media information is characterized based on its sentimental valence, sentimental intensity and emotional acceptance in public, for better understanding.It was found by the framework that the polarity and intensity of negative fake tweets is much higher than the intensity of positive real tweets.It was found by the framework that the sentiment polarity and intensity of negative fake tweets is much higher than the intensity of positive real tweets.The emotional analysis re-enforced that the fear and negativity of the fake tweets far surpass the fear and negativity spread by real tweets.In fact, conclusions could be drawn that established that the real tweets generated more positivity, joy, trust, and lead to more anticipation.Critical information is retrieved from the authentic information, analyzed for better comprehension, and put in an actionable form, ready to be leveraged.The popular fake information, such as myths or rumors, also equally important to be identified are retrieved and understood, in order to develop counter-strategies for curbing their spread.Results demonstrate that the framework developed in this paper is able to successfully classify information as fake or real; sentimentally and emotionally characterize it, and churn out novel, actionable and interesting knowledge, crucial for the policymakers, to curb the spread of misinformation.
PENGGUNAAN MEDIA SEARCH ENGINE DALAM MENINGKATKAN CIVIC INTELLEGENCE SISWA PADA MATA PELAJARAN PKN

This study aims to explore the benefits of using search engine media in improving students' civic intelligence in Civic Education (Civics). Media search engines, such as online search engines, provide easy and quick access to various sources of information relevant to Civics Education materials. This study involved high school student participants who were involved in the use of search engines as a learning tool in Civics class. The results showed that the use of search engines has significant benefits in improving students' civic intelligence. The students reported that they were able to access extensive and diverse information, deepen their understanding of Civics concepts, and develop digital literacy skills. The use of search engines also provided opportunities for students to actively participate in class discussions, presentations and Civics projects.
Generalized structured component analysis (GSCA) method in evaluating service satisfaction at FMIPA Syiah Kuala University

This research focuses on the Generalized Structured Component Analysis (GSCA) method in evaluating service satisfaction at FMIPA Syiah Kuala University (USK). FMIPA USK is expected to have good service quality to satisfy stakeholders with the services provided. FMIPA USK needs to know the factors that affect service satisfaction. An internal survey of the integrity zone is one way to determine the quality and satisfaction of the services provided by FMIPA USK. However, this survey uses indirect variables, so the structural equation model (SEM) can be used. The SEM method used in this study is component-based SEM, namely Generalized Structured Component Analysis (GSCA). GSCA is used because questionnaires do not fulfill existing assumptions in general research, and the GSCA method does not require many assumptions. This research aims to form a model, determine the relationship between indicators and latent variables, and know the relationship between latent variables and the factors significantly affecting student satisfaction with services at FMIPA USK. The results of this study show that the indicators used are valid and reliable. Reliability, assurance, empathy, and tangibles is a factor that affects service satisfaction. Models formed in this study have a GFI value of 0.962 and SRMR of 0.365, so the model used is suitable.
Analysis of The Effect of Population Density, Unemployment, Minimum Wage, and Human Development Index (IPM) on Criminality in North Sumatra

The study aims to analyze the effect of population density, unemployment, minimum wage, inequality and human development index on crime in North Sumatra province. The type of research used in this study was descriptive research using quantitative research methods. The type of data used in this research is secondary data. In this study, Microsoft Excel Home and Student 2021 and Eviews 12 Student were used for data processing and hypothesis testing. The result of this study is that population density and Human Development Index has a positive and significant effect on crime. Unemployment has a positive and insignificant effect on crime. The Minimum Wage have a negative and insignificant effect on crime, and then Population Density, Unemployment, Minimum Wage, and Human Development Index together have an effect on crime in North Sumatra Province.
Nexus of Government Support, Product Innovation Capability, and Organizational Performance of Manufacturing SMES in Ghana

The study is premised on unveiling the role of government support, innovation capability, and firm performance.This study aimed at examining the relevance of government financial and non-financial support and SME performance.The moderating role of innovation capability was also examined in the study.The data was gathered through convenience sampling method.Using a self-administered questionnaire, 400 SME operators in five major business cities in the Eastern Region of Ghana were understudied.Using PLS Structural Modelling, analyses were conducted.It was revealed that both governments financial and nonfinancial support is significantly linked to organizational performance, while product innovation capability is strongly linked to organizational performance.Meanwhile, product innovation capability exhibited a mixed result for its mediating role in the relationship between government financial support and non-financial support and organizational performance.The study thus reveals the relevance of government support and innovation capability on SME organizational performance.
Web Portal for Academic Libraries in India

This paper is focused on library web portal for online information services.The Library web portal contains the different types of web based services.The library information professionals and researcher are taking interest to use of library web portal as a central component of their integrated online library information system constructions. In this regard, the FOSS-based library web portal has drawn a considerable attention amongst library and information professionals and researchers in the field of integrated online library and information services throughinternet.There is a need of library web portal which is easy to design, implement and maintain by the library and information professionals.
Review on Video Super Resolution: Methods and Metrics

Video Super Resolution (VSR) is a wide area in image processing, where numerous research works are going on. Super Resolution (SR) means the upstaging of Low Resolution (LR) frames to High Resolution (HR) frames with minimal loss in image quality. The goal of this paper is to give the comprehensive review of various VSR methods like Convolutional Neural Network (CNN), Generative Adversarial Network (GAN), Gated Recurrent Unit (GRU), Spatial Temporal Transformer (STT), Fractional-Sine Cosine Algorithm (F-SCA), Recurrent Back-Projection Network (RBPN), Temporally-Deformable Alignment Network (TDAN). Finally, the readers will get more ideas about VSR based methods and metrics.
Deep Learning Architectures Based Sentiment Analysis Systematic Literature Review

Recently, sentiment analysis has attracted a good deal of interest from researchers. Each day, FB, Twitter, Weibo, and other social media, in addition to huge e-trade websites, generate big feedback, which can be used to investigate humans' critiques or emotions. Sentiment analysis will correctly analyze subjective records from this information. Deep learning becomes an effective machine learning approach which learns from a couple of layers of representations or features of the records and outputs a cutting-edge prediction effect. Deep learning overcomes all other machine learning techniques for sentiment analysis as well as offers different architectures for sentiment evaluation. Recently, RNN abbreviated as Recurrent Neural Networks as well as CNN abbreviated as Convolutional Neural Networks has been replaced with Transformer Language models in deep learning architecture.This survey deals with contemporary architectures and challenges in that are in Sentiment Analysis as well as Natural Language Processing.
PENGEMBANGAN MEDIA POP UP BOOK PADA TEMA 6 ENERGI DAN PERUBAHANNYA SUBTEMA SUMBER ENERGI DI KELAS III SDN 014684 DADIMULYO TAHUN AJARAN 2019/2020

This study aims to develop pop-up book learning media, to analyze the feasibility of the pop-up book learning media being developed, and to determine the response of students and educators to the developed pop-up book learning media. The type of research used is R&amp;D with research and development procedural from Borg and Gall which has been modified by Sugiyono with development steps, namely; (1) the potential and problem stage by observing, (2) the data collection stage by conducting research activities, (3) media design, (4) media validation, (5) media revision stage I, (6) testing, and ( 7) revision of stage II media. Researchers took five steps in this process due to the current Covid-19 virus pandemic. This pop-up book learning media is validated by media expert validators and material expert validators. Assessment of media feasibility uses a Likert scale. Based on the data analysis, the media expert's assessment at stage I obtained a percentage of the feasibility results of 78.3% including the criteria of "Good". The results of the second stage media validation assessment obtained a score of 69 with the percentage of eligibility results was 83.3%. The pop up book is included in the "Very Good" category, the material expert's assessment at stage I obtained a percentage of the eligibility results of 89.5% including the criteria "Very Good" and in stage II obtained a percentage of eligibility results of 94.5% included in the criteria "Very Good. Good". &#x0D; Keywords: Learning Media, Energy and Change, Pop-up Book, SDN 014684 Dadimulyo
Mapping Vocabulary: A corpus-based comparison of Indonesian fourth-grade students' writing and English language textbooks

This study compares the vocabulary used by Indonesian fourth-grade students in their free writing with that taught in their English language textbooks to assist language teachers in developing relevant learning materials for young learners. To achieve this, the researchers employed the corpus linguistic method and analyzed the writings of 369 students from 19 public elementary schools in Malang, East Java, Indonesia, along with five selected English textbooks. The University of Adelaide Text Analysis Tool program, AdTAT, was used to analyze the corpus. The program generated word lists consisting of the top 100 words most frequently used by students and the top 100 words used in English textbooks. The findings of the study revealed a 45% match between the top 100 words most frequently used by students and the top 100 words used in English textbooks. This suggests that there is a significant overlap between the vocabulary used in free writing and that taught in textbooks. The implication of this study is that language teachers need to recognize the basic words students acquire before learning new vocabulary to achieve successful learning of the target language. The study suggests that language teachers should incorporate more culturally relevant vocabulary into their teaching materials to better engage and motivate their students. The findings of this study can also assist language curriculum developers in designing more effective and culturally relevant teaching materials for young learners.