Reviewerly/exHarmony huggingface dataset:
The Current State of Ukrainian Bibliography: Prospects for Overcoming the Crisis Situation

The relevance of the research. Experts ascertain the crisis state of modern book study. We consider it necessary to understand the essence of the crisis as a phenomenon and to understand whether it really is fraught with danger, or vice versa, it can breathe new life into book study in the context of the transformation of book industries in the digital environment.&#x0D; The purpose of our scientific research is to analyze the state of modern book study in Ukraine and outline ways out of the crisis.&#x0D; The methodology. The study was conducted using the method of analyzing.&#x0D; The results. The status of modern as a scientific and educational discipline is considered. The following activities are proposed: revision of the object of bibliography, expansion of the scope of scientific research of bibliography due to the “return” of the figures of the author and reader, consideration of book communication and the processes taking place in it in a new communicative reality in integrity and interconnection, without breaking it into separate branches, parallel use as synchrony and diachrony in the analysis of the processes taking place in the book industry, the active involvement of comparative methods of analysis, as well as the productive involvement of the methodological apparatus of other sciences, the return to the socio-communicative approach as the main one in bibliography, the unification of the efforts of all those who in one way or another are involved in book industry, regardless of how they pose themselves in the scientific community.&#x0D; The scientific topicality. An analysis of the current state of bibliography and the outlined prospects for overcoming the crisis can become a methodological basis for the further transformation of bibliography in the context of digital reality.&#x0D; The practical significance. The results of the study can be used in the formation of a strategy for the development of bibliography.
LIBRARY RESOURCES OF THE NETWORK AND MU-SIC INFORMATION: MODERNITY THROUGH TRADI-TIONS

The article briefly describes the current condition of music libraries as a deposi-tory of specific documents and also the peculiarities of working with the book selectors and catalogers in this segment of library activity. The article assesses the experience of library communication from the part of the main consumers of music library services and explains the reasons of the emergence of the al-ternative network initiatives of musicians that can have a significant influence on the conception of organizing library servicing.
Meningkatkan Kemampuan Kognitif Dengan Penerapan Metode Pembelajaran Berbasis Proyek Kegiatan Mengelompokkan Buah Jeruk

The learning proses in kindergarten is still very conventional in nature, This is shown is teaching an learning activites in kindergarden Taman Kanak kanak Bersemi kepenuhan jaya Rokan Hulu.in traducing the number of teacher skill using the lecture method and memorizing.To count number children still write in the book given by their teacher.The research is currenty doing is to improve numeracy skill in children aged 5-6 year with interesting activities for children by providing learning methods need for children .This research method uses classroom action research..The research subjects were 13 student.corsiiting 0f 5 bays and 8 girls.The data method can improve numeracy skill.Pre cycle of 55 % with is in the ceritena of not Developing.in the first cycle the action taken trough the project based learning (PJBL) method tho 65 % in the criretia of developing in accordanc with ecpectatino , and increased in the second cycle to 85 % on criteria ocorrding to expextation an very good development.Based on the results of this study ,it show that on increase in numeracy the skill of children aged 5-6 years with PJBL methods.&#x0D; Keywords: Cognitive Skills, Classifying citrus fruits, Classroom Action Research
Pengembangan Kemampuan Kognitif Anak Dengan Menggunakan Media Papan Pintar Angka

This background of this research is the low ability of children to understand concept of numbers, one of the alternatives offered by researchers is the introduction of understand of numbers by . The research method used was classroom action research conducted in 2 cycles. Data collection methods used are observation, assignment and documentation. The results showed that the children's cognitive abilities in recognizing number symbols which developed very well in each indicator showed a good increase after the action was carried out in cycle II, where children could recognize number symbols 1-10 with a percentage of 90%, children could show number symbols 1-10 in sequence with a percentage of 90%, children paired symbol numbers 1-10 with picture media with a percentage of 90%, and children could name symbols of numbers 1-10 in sequence with a percentage of 90%.&#x0D; Keywords: Cognitive Abilities, Smartboard number, Demonstration Learning Method
Meningkatkan Kecerdasan Logika Matematika Anak Usia 5-6 Tahun Melalui Media Game Edukasi di TK Aisyiyah Bustanul Afthal VII Pekanbaru

The purpose of this study was to improve the mathematical logic intelligence of children aged 5-6 years through educational game media at Aisyiyah Bustanul Afthal VII Kindergarten Pekanbaru. The method used in this research is class action research (Classroom Action Research) with the number of research subjects as many as 20 children consisting of 10 boys and 10 girls. Data collection techniques in this study were observation and documentation. The data analysis technique used in this research is the percentage technique. The results showed that the application of educational game media implemented in Aisyiyah Pekanbaru Kindergarten was carried out in two cycles where each cycle consisted of 3 meetings. The implementation and application of educational game media that researchers do with the help of an observer, namely one of the teachers at Aisyiyah VII Kindergarten Pekanbaru. Shows the results in accordance with what is expected where this educational game media has a positive impact on children's mathematical logic intelligence. in cycle I obtained an average score of 34.9 (43.6%) with the criteria starting to develop. There was an increase in the increase in mathematical logic intelligence in children at Aisyiyah Bustanul Afthal VII Kindergarten Pekanbaru in cycle II with an average score of 65.1 (81.3%) with very good developing criteria (BSB). From the research data above, it can be said that the increase in mathematical logic intelligence in each child has increased from before the research action compared to after the research action with educational game media at Aisyiyah Bustanul Afthal VII Kindergarten Pekanbaru.&#x0D; Keywords: math logic intelligence, educational games, classroom Action Research
Digital Transformation Governance at the Organization Using IT Infrastructure Library Framework

Nowadays, most of our daily activities are assisted electronically due to not only time effectiveness but also activity efficiency. Processes that once could only be completed at the office are now able to be done anywhere and anytime, as long as there is internet access. One obvious example is the COVID-19 pandemic which leads to the work-from-home system. Therefore, this spurred the author on to innovation by adapting to the current phenomenon. Most of our daily activities are currently converted to digital, in which these digital users can reap abundant results. This manual-to-digital conversion is known as ‘digital transformation’. The purpose of digitalization in this organization is to transform the disposition distribution of the leaders from manual to digital. The result of the study is the adoption of e-Disposisi application (paperless office) in the organization, which causes the business processes to be more effective and more efficient concerning time, human resources, document storage, and paper use. This implementation results in changes in the business processes, the reduction of time needed to distribute documents, the lower purchase of paper and tint, and the minimized employment of human resources. Generally, the research contributes to the more effortless business processes in the organization, allowing operations to continue without direct contact. Data collection was done through various methods, namely observation, interview, questionnaire, focus group discussion (FGD), and literature. The methodologies used were Soft System Management, qualitative and quantitative referring to the IT Information Library framework. Doi: 10.28991/ESJ-2023-07-06-07 Full Text: PDF
Analysis of Readiness to Use the Metaverse Platform in Learning Activities

Metaverse technology is one of the many technological breakthroughs in education, notably in the teaching and learning process in the classroom, especially since the COVID-19 epidemic. This study aims to investigate, model, and assess the potential adoption of metaverse technology from the viewpoint of BINUS University students. The study methodology that is employed is quantitative descriptive analysis. This research used Mozilla Hub's SPOKE to create the classroom simulation. Students are asked to use a laptop web browser and a Virtual Reality (VR) headset to replicate two scenarios from the metaverse realm. The variables used are comfort, convenience, compatibility, interest, and efficacy. The findings of this research indicate that a more significant number of participants, as much as 80% than fewer respondents (20%) were interested in employing VR (the Metaverse) for online teaching and learning using headsets. The novelty in this research is that academics can find out student behavior that they prefer to study using a VR headset compared to a regular laptop by opening a web browser. This can be a special note that the use of VR headsets in learning can increase interest in learning so that it is more effective in providing teaching material. Future work for this study is the application of this metaverse technology, which still requires work and development, as it still necessitates careful planning and consideration of a few factors, including security, infrastructure availability, and user comfort. Doi: 10.28991/ESJ-2023-07-06-016 Full Text: PDF
Developing a Linked Open Data Platform for Folktales in the Greater Mekong Subregion

This research paper presents the development of a linked open data (LOD) platform that aims to organize and facilitate access to valuable knowledge about folktales and ethnic groups in the Greater Mekong Subregion countries. The study’s methodology involved the creation of a linked open data platform, structuring folktales’ knowledge, and evaluating its performance through expert assessment. The LOD platform was constructed through Google OpenRefine to establish connections with external data sources, and the RDF files (N-Triples) were deployed on Fuseki Server (Apache Jena) to serve as the SPARQL endpoint for querying the linked open data. The Pubby web app was chosen for further development to provide a user-friendly interface, which customized with the Bootstrap framework, featuring an intuitive homepage and a search box function for simplified data retrieval. For the expert evaluation, the study confirmed that the platform performs a high suitability in terms of congruence, reliability, integrity, understandability, collaboration, accessibility, and connectedness. The developed LOD platform exhibits significant potential for expanding its application to various content domains, offering a valuable resource for accessing and exploring the rich cultural heritage of folktales in the Greater Mekong Subregion countries. Doi: 10.28991/ESJ-2023-07-06-06 Full Text: PDF
The Mechanisms of Applying Open Book ‎Management Approach at Shaqra University ‎in the Kingdom of Saudi Arabia

The study aimed to identify the reality of applying the open-‎book management approach at Shaqra University, determine ‎whether there are statistically significant differences for ‎variables (gender-type of work); and define the difficulties of ‎applying the open-book management approach at Shaqra ‎University to develop proposed mechanisms for applying the ‎open-book management approach based on the results of the ‎study. The researcher used the descriptive survey approach and ‎the questionnaire as the tool for data collection. The study ‎population included the college's deans and deputies of the ‎university who are (51). The study mainly revealed the ‎following results: the reality of applying the open-book ‎management approach at Shaqra University is moderate as ‎follows (education and training - organizational environment - ‎support and motivation), and there are no statistically significant ‎differences in the gender and type of work.. The most ‎prominent difficulties limiting the application of the open-book ‎management approach at Shaqra University are: bureaucracy in ‎work performance and the ambiguity of the criteria for ‎nominating leadership selection. In addition, the study ‎concluded with the development of the most important ‎measures that help to apply the open-book management ‎approach at Shaqra University, including creating a favorable ‎environment for spreading out the open-book management ‎approach and empowering employees by delegating greater ‎powers to the middle and lower levels according to the abilities ‎and skills of workers.‎ ‎(Keywords: Application Mechanisms, Open-book ‎Management, Shaqra University)‎
Predicting Dementia Using Deep Learning Methods

Dementia, a progressive neurodegenerative disorder, poses a growing global health challenge. Early diagnosis is crucial for effective intervention and management. Deep learning, a subset of artificial intelligence, has shown promise in aiding early dementia prediction through the analysis of various data modalities, including neuroimaging, genetic markers, and cognitive assessments. The predictive models is built upon extensive datasets comprising a diverse range of demographic, genetic, and neuroimaging data, often collected through longitudinal studies. Preprocessing techniques are applied to handle data irregularities, while various deep learning architectures, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and hybrid models, are employed to capture intricate patterns within the data.Training and evaluation of these models are conducted rigorously, with a focus on optimizing hyperparameters and mitigating overfitting. Performance metrics such as accuracy, precision, recall, and ROC-AUC are used to assess model efficacy, with interpretability methods providing insights into the influential factors behind predictions.
CoBiAt: A Sentiment ClassificatiCobiat: A Sentiment Classification Model Using Hybrid Convnet- Dual-lstm with Attention Mechanismon Model using Hybrid ConvNet- Dual-LSTM with Attention Mechanism

The exponential growth of social reviews of various services has encouraged many researchers to focus on emotion analysis in recent times. The availability of such huge information helps in analyzing the behavior of end-users for improving the QoS. Text categorization is a major language processing research topic that organizes disorganized text into useful categories. LSTM and CNN models are employed in several natural language processing (NLP) applications for text-based classification and that offer reliable results. CNN models extract top-level features with help of convolutions and maximum pooling-based layers, whereas LSTM based models acquire long-term relationships between text sequences and therefore more suited to text categorization. In this research, an optimized attention-oriented model combined with BiLSTM with ConvNet is proposed. Model is trained by utilizing two distinct datasets for performance validation of the model. Comparison of the proposed model is performed with other deep learning techniques and the proposed attention-based model has shown a significant performance improvement. The proposed model produces more accuracy in results in comparison to other classic machine learning models.
Machine Learning for the Exposure of Malicious URLs

In today's era, as per the statistics for world-wide internet users or digital population as on April 2023, there are 5.18 billion internet users worldwide, which goes to 64.6 percent of global population. Of this total, 4.8 billion, or 59.9 percent of the world's population are social media users. [statistica.com/statistics617136/digital-population-worldwide]. Enhancement in technology and internet usage increases the scope for cyber-criminal activities. As the connectivity and the number of users grow, there is a proportional increase in attackers. Vindictive sites or URLs become one of the significant dangers for network protection. Malevolent URLs are most risky danger prompting phishing assault, malware dissemination, Drive-by Downloads, Program Exploits, Data fraud in this computerized world. It's critical to remain cautious and safeguard us on the web. It is vital to be sufficiently mindful and have the option to identify and act against these dangers by not visiting such destinations or giving any private data. In this work we will focus on attacks through malicious URLS, working, preventions and machine learning algorithms used to detect malicious URLs.
Spam Sentinel: Revolutionizing Email Protection Using Machine Learning Techniques

The rapid growth of email usage has brought about an unprecedented increase in spam emails, posing serious challenges to users and businesses alike. To tackle this issue, this study presents an enhanced spam email detection system leveraging the power of machine learning techniques. The objective is to create a robust and efficient model capable of accurately differentiating between legitimate emails and spam messages. Various features are extracted from the email content, including text-based characteristics, header information, and metadata, to create comprehensive representations of the emails. Machine learning algorithms, such as KNeighbors, Support Vector Classifier, Multinomial NB, Logistic Regression, Random Forest, Extra Trees Classifier, AdaBoost, Bagging, XGB Classifier, Decision Tree, Gradient Boosting, Gaussian NB (Naïve Bayes), Multinomial NB, Bernoulli NB (Naïve Bayes) and ensemble model are employed to develop and compare different spam detection models. The experimental results demonstrate the efficacy of the proposed enhanced spam email detection system. The combination of machine learning techniques leads to significant improvements in accuracy and efficiency, enabling effective identification and classification of spam emails. Bernoulli achieved better accuracy of 99%.
Analyzing the Sentiments Of Filipino Commuters: An Application of Data Science Techniques through the Use of Machine Learning Algorithms

Living in the 21st century, the rise of science and technology has brought upon various developments that help improve the quality of life for all humans. Diverse innovations are slowly being developed into better ideas, thus causing people to think outside the box. Various computer-related techniques are being applied in order to make life easier. This study is an application of data science techniques with regard to analyzing the Twitter sentiments of Filipino commuters. Moreover, this study also determines and compares which data science model obtained the most accurate result with regard to the prediction and analysis of Twitter sentiments. The algorithms used in this study are the Naïve-Bayes, Support Vector Machine, and Deep Learning (Artificial Neural Network) containing English and Filipino language datasets.
Infrared Face Detection Based on Data Enhancement and Its Application

With the rise of artificial intelligence, face recognition technology is also developing rapidly. At present, most face recognition methods are based on visible spectrum images, but the complex background environment, lighting conditions and diverse facial expressions hinder the progress of face recognition technology. In order to solve the above problems, this paper proposes an infrared face recognition algorithm based on the YOLOv5 model. In the data processing stage, this paper expands the sample data set using data enhancement techniques, and then trains it based on the YOLOv5 model. Finally, it is tested on infrared face images. The experimental results show that infrared faces can be recognized quickly and correctly by this algorithm.
Upaya Meningkatkan Kemampuan Mengenal Lambang Bilangan Melalui Kegiatan Mencocokkan Tulisan Dengan Lambang Bilangan

The background of this research is the low ability of the children group B of Harapan Bangsa Kindergarten in recognizing number symbols 1-10. Some children have not been able to match numbers with their number symbols. One of the solutions offered by researchers is to try the activity of matching writing with number symbols to improve understanding of number symbols in children group B of Harapan Bangsa Kindergarten. The type of research applied is Classroom Action Research (CAR). Data collection techniques used were observation techniques and documentation techniques, while data analysis techniques used in this research were quantitative data analysis techniques and qualitative data analysis techniques. The research results obtained were the BB value in the pre-action 7 children or 41.18% In the first cycle it became 2 children or 11.76% and in the second cycle it became 0 children or 0%, the MB value in the pre-action was 6 children or 35.209% , in cycle 1 there were 5 children or 29.41% then in cycle II there was 1 child or 5.88%, the BSH value in the pre-action there were 2 children or 11.76% In cycle 1 there were 6 children or 35.29% then in cycle II there were 5 children or 29.41%, the final value of BSB in pre-action activities there were 2 children or 11.76% in cycle 1 there were 4 children or 23.53% and at the end of cycle II there were 11 children or 64.71% of these results show a very significant improvement. Thus it can be concluded that the activity of matching writing with number symbols can improve the ability to recognize number symbols in children. It is also suggested to teachers to make this activity an alternative activity to improve children's cognitive abilities in recognizing number symbols&#x0D; Keywords: number symbol, matching activity, class actionroom research