Reviewerly/exHarmony huggingface dataset:
Challenges and computer-aided reading strategies in vocabulary enhancement

Early literacy development depends significantly on developing a vocabulary, and computer-aided reading techniques have the potential to improve this process. To maximize their efficacy, grade 1 teachers might encounter particular difficulties when implementing these tactics into their lesson plans. In light of this, the goal of this study is to determine the difficulties that Grade 1 instructors encounter when instructing vocabulary and investigate the possibility of using computer-aided reading procedures to help with these difficulties. The primary goal of the qualitative research for this study was to interview grade 1 teachers about their experiences and anecdotes. Six professional teachers—four from private and four from public schools— participated in the study's interviews. According to the results, the most challenges that first-grade teachers encounter when trying to expand their students' vocabulary include the transition from their native tongue to English, word pronunciation and spelling mistakes, and students' reluctance to learn new vocabulary. The twenty experienced educators use a range of techniques to help students with their vocabulary. These include using the Marungko Method in a multimedia presentation to introduce letter names and sounds, watching phonics and phonemic movies, pronouncing words using YouTube videos and audio-visual presentations, interactive slides, digital flashcards, recordings of the alphabet, and rereading while playing interactive language games to help with retention. The study's outcomes will contribute to the existing literature on vocabulary instruction and computer-aided learning, highlighting the potential of technology in addressing the challenges faced by Grade 1 teachers.
Concepts of Money Laundering Resulting Destroy the Structure of Financial Policy

Money laundering is the technique used to make significant sums of money earned illegally through drug trafficking, terrorism, or other major crimes that appear to have come from legitimate sources. Money laundering has a negative influence on the nation's economic and political stability, hence it must be strictly prohibited. As one of the most significant components of the financial system, it serves as the backbone of the money market and plays a vital role in raising funds for beneficial investments that advance economic growth in a nation. An effective and stable financial system is a requirement for the nation's overall growth.
A Framework for Mobile Forensic Readiness in Yemen

One of the most important inventions of the 20th century is the mobile phone. In addition to making and receiving phone calls, a mobile phone can be used for texting, gaming, taking photos, recording movies, and accessing the internet, among many other things. This paper develops a framework for mobile forensic readiness in Yemen. In addition, mobile forensic readiness (MFR) aims to know the level of readiness for mobile forensic in Yemen, the level of mobile forensic factors in Yemen, and factors that affect the readiness for mobile forensic in Yemen. The main goal of forensic preparedness is to maximize an organization's capacity for establishing the viability of conducting forensic investigations and for accessing digital evidence at the lowest possible cost of an inquiry. Fundamentally, the primary goal of forensic preparation is to guarantee that the evidence is pertinent and comprehensive enough for the forensic investigation. The research is descriptive and collects indicators of MFR from literature review and 110 questionnaire that given to the Yemeni criminal investigation bureau employees, technology users, public prosecutor office employees. Furthermore, through the interviews were done with the police station managers and their employees. However, the returned questionnaires were 101. Statistical Package for the Social Sciences (SPSS) was used to analyze and test the data through mean, standard deviation, and one sample T- test. Moreover, SPSS AMOS was used to design the framework. All mentioned hypotheses were tested using regression, T- Value, Beta, P- value, and R-square. Therefore, the results show that all hypotheses were supported. This paper develops a framework for mobile forensic which reveals if we have a suitable infrastructure for mobile forensic and increase the awareness of mobile forensic which assists the experts to recover and analyze data. Furthermore, this research increases the potential use of digital evidence and increases the trust in the mobile forensic process.
Hubungan antara minat baca dengan kemampuan berpikir kritis dalam pembelajaran IPS di sekolah dasar

The research purpose was determined the correlation of reading interest and critical thinking ability in social studies learning at &lt;span&gt;elementary school&lt;/span&gt;. This research type is a quantitative approach with correlational research design. The research sample was fifth grade students at SDN Laban 01, SDN Wirun 04, SDN Laban 02, and SDN Plumbon 02, Mojolaban District, Sukoharjo Regency. The sampling technique applies the probability sampling technique of cluster random sampling type. Data collection techniques for reading interest and critical thinking ability are in the form of tests and questionnaires. Analysis prerequisite test using normality and linearity tests. Hypothesis testing using simple correlation analysis by applying Pearson Product Moment correlation and multiple correlation analysis with the help of the SPSS 21 program. The results showed that reading interest affect critical thinking ability in fifth grade students of SD in Mojolaban District.
Faktor kesulitan membaca pemahaman teks cerita bahasa jawa peserta didik kelas V Sekolah Dasar

&lt;p&gt;This research is motivated by observation and interview data which indicate there are problems at school regarding the low reading comprehension skills of fifth grade students at SDN Tegalayu Surakarta in the 2022/2023 academic year. To overcome these problems, the researcher conducted a qualitative study with the aims of: (1) To describe the difficulties in understanding Javanese texts (2)to explain the factors that cause difficulties in understanding Javanese texts.This research was conducted on teachers and students of class V SDN Tegalayu Surakarta. In this research, a qualitative descriptive approach was used, and observation, interviews, and documentation studies were used to collect data.Source triangulation and triangulation techniques are used to test the validity of the data.From the research, data were obtained in the form of difficulties experienced by students, namely difficulties in interpreting words, difficulties in making new sentences using words in the text of the story and difficulty answering questions according to the contents of the story. While the factors that affect the difficulty of reading comprehension skills are intellectual factors, psychological factors, environmental factors and physiological factors.&lt;/p&gt;&lt;p&gt; &lt;/p&gt;
Kendala implementasi P5 dengan tema bhinneka tunggal ika di sekolah dasar

&lt;p class="Abstract"&gt;&lt;em&gt;This research was conducted to examine the obstacles to implementing P5 with the topic Bhinneka Tunggal Ika at SDN Bumi 1 No. 67 Surakarta starting from the planning stage, implementation, to assessment and efforts made to overcome it. This research uses a qualitative descriptive method approach. The obstacles encountered in the implementation of P5 are due to internal factors and external factors. The obstacles caused by internal factors are the absence of training regarding P5 for teachers, P5 is not well documented due to lack of teacher understanding, and differences in perception between teachers and school principals. Meanwhile, obstacles are caused by external factors such as limited learning media, the lack of role of teachers and school principals in establishing collaboration, and the lack of involvement of committees and supervisors. The solution to overcome these obstacles are to encourage the strengthening of teacher capacity through training to be able to implement P5 in accordance with the guidelines, to equalize perceptions and build communication between teachers and the school principals, to work with the parents of pupils in providing adequate learning media and to optimize the role of the head, teacher, committee, and supervisor to support a collaborative school ecosystem.&lt;/em&gt;&lt;/p&gt;
Pengaruh media audiobook cerita keberagaman sosial budaya di indonesia terhadap keterampilan menyimak peserta didik kelas V SD se-kecamatan banjarsari

&lt;p class="Abstract"&gt;&lt;em&gt;The aim of this research is to examine how audiobook media stories about social diversity in Indonesia influence the listening skills of grade V students in elementary schools in Surakarta's Banjarsari District. The design of this research is experimental. Methods of data collection include tests and observations. According to the research's findings, the use of audiobook media stories of socio-cultural diversity in Indonesia impacts the listening skills of students in Banjarsari District, Surakarta's grade V elementary schools. The paired sample t-test on the hypothesis test, which examines the post-test values of the experimental and control groups. The hypothesis test findings show significant values of 0.009 &amp;lt; 0.05. The average post-test score in the experimental group was 81.3 &amp;gt; 72.2, which was higher than the pre-test score. It was also discovered that the experimental group's average post-test score was higher than the control group's, with 81.3 &amp;gt; 70.7. Students with this attitude are those who quickly focus on listening to the teacher's explanation and are able to reply to the story.&lt;/em&gt;&lt;em&gt;&lt;/em&gt;&lt;/p&gt;
Total Factor Productivity and Financial Development

The main objective of this study is to explore the relationship between total factor productivity and financial development for a group of Latin American countries consisting of Brazil, Colombia, Costa Rica and Mexico covering the period from 1996 to 2019. Total factor productivity, which is considered as one of the main drivers of sustainable economic growth, especially for emerging economies, is the measure of productive efficiency given by the ratio of aggregate output to aggregate inputs. Financial development refers to the development of financial institutions and financial markets. Latin American countries exhibit different levels of both total factor productivity and financial development mainly due to the emerging nature of their economies, which explains the motivation of choosing four of these countries as the sample to analyze the association between total factor productivity and financial development. Data for total factor productivity is taken from the Penn World Table while the Financial Development Index Database provided by the IMF is used in order to examine financial development. The results of this study indicate that countries with higher levels of total factor productivity also have higher levels of financial development. This finding can be interpreted as the outcome of the fact that there are macroeconomic and financial factors determining or similarly influencing both total factor productivity and financial development. Significant policy implications for emerging countries can be inferred from this close connection between total factor productivity and financial development, which constitutes the major contribution of this study to the literature.
Comparison of Naive Bayes and Support Vector Machine (SVM) Algorithms Regarding The Popularity of Presidential Candidates In The Upcoming 2024 Presidential Election

This study aims to compare the effectiveness of two classification algorithms, Naive Bayes and Support Vector Machine (SVM), in analyzing the popularity of presidential candidates for the 2024 Presidential Election (Pilpres). The popularity of presidential candidates plays a crucial role in campaign strategies and political decision-making in the modern political era. This research utilizes data from social media, encompassing public sentiment towards presidential candidates and related political issues. The research results indicate that SVM achieves an accuracy rate of 97%, while Naive Bayes achieves 95%, demonstrating the superiority of SVM in predicting the popularity of presidential candidates. In conclusion, the selection of the appropriate algorithm for analyzing complex political data has a significant impact, and the high accuracy rates of both algorithms provide valuable guidance for political decision-makers and campaign teams in preparation for the upcoming 2024 Pilpres.
GUARANTEES OF FREEDOM OF SCIENTIFIC CREATIVITY IN THE NORMS OF INTERNATIONAL LAW

The article examines the consolidation and development in the law "On Science and Scientific activity" of the internationally recognized human right to freedom of scientific research. The article analyzes the normative content of freedom of science and its reflection in legislation of Uzbekistan. Much attention is paid to the issue of the correlation of freedom of science with a number of civil, social and economic human rights, the beneficiaries of which are also scientists and scientific and technical workers. It is concluded that it is necessary to establish a balance between freedom of scientific research and human rights due to the increasing risky nature of modern scientific and technological progress.
METHODS OF DOCUMENT FORGERY AND THEIR DETECTION PROBLEMS

In this article, the types of forgery of documents, the methods and tools used in forgery are analyzed, and the mechanism of appearance of traces and signs of forgery of documents is researched. Also, the elements that can be changed in the text of the document are divided into separate categories and analyzed. The second part of the article is directly devoted to the problems of identifying the elements of forgery, in which the methods and tools used to identify the signs of forgery are analyzed from a criminalistic and technical point of view.
Inaugural Editorial: Editorial about the Founding of Medinformatics

The convergence of biology and artificial intelligence represents a paradigm shift in scientific exploration. The integration of AI into the study of omics—genomics, proteomics, transcriptomics, metabolomics, and beyond—has revolutionized our ability to decipher the complexities of biological systems. From predictive modeling of gene structures to the elucidation of protein interactions, from the analysis of transcriptomic profiles to the exploration of epigenetic landscapes, AI has become an indispensable tool in the biologist's toolkit. In this journal that focuses on the integration of information and life medicine, we embark on countless journeys of artificial intelligence applications in biomedical fields, focusing on the application of omics analysis in analyzing biological processes or disease occurrence and development. In addition, this journal also focuses on the forefront of interdisciplinary research, with a particular focus on the knowledge and methods of artificial intelligence, mathematics, physics, and other disciplines to solve biomedical problems, enhancing our rational understanding of life and disease. As we founded this magazine, we invited researchers, scholars, and practitioners from different backgrounds to publish cutting-edge biomedical informatics research or join our editorial board. Let us explore the frontiers of knowledge, push the boundaries of innovation, and together, forge a brighter future for biomedical science.
Patient Admission Projection Using Facebook Prophet

Healthcare facilities face the continual challenge of managing patient admissions efficiently while maintaining high standards of care. Accurate forecasting of patient admissions is crucial for optimizing resource allocation, ensuring adequate staffing, and enhancing overall operational efficiency. To address this challenge, this research paper explores the application of Facebook Prophet, an advanced time series forecasting tool, in predicting patient admissions within healthcare facilities. Facebook Prophet, a specialized time series forecasting model developed by Facebook's Core Data Science team, is then employed to model and predict patient admissions. Facebook Prophet is particularly well-suited for handling time series data characterized by seasonality, trends, and special events. The model's flexibility and ease of use make it an ideal choice for healthcare providers seeking to leverage advanced analytics techniques for predictive purposes. In the implementation of Facebook Prophet, the model is meticulously trained and validated using the pre-processed historical admission data. The model's ability to capture complex temporal patterns, including seasonality and special events such as holidays or outbreaks, is thoroughly evaluated. By incorporating these patterns into the forecasting process, the model can provide accurate predictions of future patient admissions. By accurately predicting patient admissions, healthcare facilities can optimize resource allocation, streamline operations, and ensure adequate staffing levels to meet patient demand. Additionally, the model enables healthcare providers to proactively plan for special events or seasonal fluctuations in admission rates, further enhancing operational efficiency. The application of Facebook Prophet holds significant promise for improving patient care delivery and operational outcomes in healthcare facilities.
Cyber Security from a Business Perspective

In today’s era of Information Technology, we have encountered drastic changes in computing methodologies due to a tremendous increase in ONLINE communication traffic both in terms of the number of users and data communication. The COVID–19 pandemic has brought the entire world online. Cyber Security plays an important role in the field of information technology. In order to secure information, one can face many challenges. Nowadays, governments and other organisations are following various measures to prevent vivid cybercrimes. In this chapter, we have raised concern over the drastic increment in an ONLINE communication system, which urges the need for the development and deployment of Cyber Security in a business environment.
Region-based convolutional neural networks for occluded person re-identification

In a variety of applications, including intelligent surveillance systems, targeted tracking, and assistive human-following robots, the ability to accurately identify individuals even when they are partially obscured is imperative. Such Continuous person tracking is complicated by the close similarity between the appearance of people and target occlusions. This study addresses this significant challenge by proposing a two-step, detection-first approach that uses a region-based convolutional neural network (R-CNN) as the re-identification (re-ID)solution. The model is specifically trained to detect occluded persons at different levels of occlusion before forwarding the image for the re-ID process. Three occluded-specific datasets are selected to evaluate the model's effectiveness in detecting occluded people. There are 379 distinct people in total, and each has five images obstructed from different angles. A sample of the data is taken to simulate various environment settings, and new data points are generated with different degrees of occlusion to assess how well the model performs under varying levels of obstruction. The findings demonstrate that the proposed person re-ID model is reliable in most circumstances, correctly re-identifying at 74% (Rank-1) and 90% (Rank-5). Although there is a decrease in accuracy as the number of distinctive people in the dataset increases, this does not significantly impact the tracking performance in various applications, which are expected to recognize a single person or a small group of individuals. Future works will explore refining similarity matching algorithms by delving into robust image comparison techniques, thereby addressing the challenges presented by occlusions. A critical aspect is to assess the model under diverse lighting conditions and investigate scenarios with multiple individuals in a frame. It is also beneficial to exploit high-resolution datasets, such as DukeMTMC-reID, and integrate finer contextual details, like clothing or carried objects. These collective efforts are essential for optimizing the model’s efficacy in practical applications and advancing person re-ID technologies.
Development of the support strategy for Videoconferencing Discussion Class Using Facial Expression Analysis Data

Objectives In order to develop the design principles for online discussion in videoconferencing instruction, this study develops the design principles by using learning analysis data analyzed with facial expression analysis tool and confirms the user's reaction.&#x0D; Methods Using the design and development research method, the initial design principles was developed by analyzing previous research and problems of videoconferencing classroom field. They were modified and developed through expert validation tests for three times. A prototype of facial expression analysis tool was developed to evaluate usability, and the final design principles were developed.&#x0D; Results The final support strategy consists of 9 support strategies and 26 detailed guidelines, tailored to the pre-debate, during the debate, and post-debate stages. In this regard, it has been confirmed by users that the strategy enables to simultaneously perceive non-verbal elements and to provide timely feedback. However, it was also observed that the intervention of instructors can function both as a strength and as a disruptive factor to discussions.&#x0D; Conclusions The above design principles are significant in that it suggested the prescription using learning analysis data what is facial expressions. It showed a new possibility to apply artificial intelligence technology at learning analysis by using facial expression analysis tool that automatically analyzes present a result value.&#x0D;
Exploring The Intention of Using Mobile Learning in Flipped Classroom Approach for Arts and Design Students

The flipped classroom is a pedagogical approach that encourages active learning experience activities in the classroom. The students will receive information and materials before class learning using mobile technology both inside and outside of the classroom to allow for more dynamic, interactive, and advanced learning activities that involve the application of knowledge with higher-order thinking. Studies have shown, students who use the Mobile learning or M-learning platform in a flipped learning method can provide an interactive, engaging, and cost-effective way for graduates to broaden their employability skills. Although research on mobile learning in the flipped classroom approach has been extensive, research on M-learning has been limited. The study's objective is to examine the effectiveness of mobile learning adoption in relation to students' perceptions and responses under the UTAUT2 (unified theory of acceptance and use of technology) model in the undergraduate arts and design students and to review the pilot study model in development for larger-scale future research. Through a quantitative research approach, the pilot study used questionnaires to gather data from 50 undergraduate arts and design in multimedia design programme students of first-year from a local higher education institution. The findings showed that every composite reliability value in this study exceeded the 0.70 threshold value, indicating strong indicator reliability of the factors. Moreover, flipped classrooms increase student involvement, learning motivation, achievements and both at the same time improving educators' knowledge of how to use the flipped learning model in ways that are most advantageous for their own students.