Reviewerly/exHarmony huggingface dataset:
Financial Development and Integration, Exchange Rate Regimes, and Economic Growth: New Evidence from African Economies

This paper examines empirically the extent to which financial development, financial integration and exchange rate regime (ERR) altogether influence positively economic growth in Africa. To achieve this, we build two baseline panel data samples of African countries and new expanded datasets spanning 1980-2015 using a small sample adjusted Generalized Method of Moments (GMM) estimator. To check the robustness of our results, we build two other panel samples by adding on the two previous panel data samples, data from emerging and developed countries and repeat the analysis. The results from the estimations suggest that financial development and financial integration influence positively and significantly economic growth, whereas exchange rate regime has no significant effect on economic performance, controlling for the usual growth- regression variables like trade openness, human capital, investment, governance and the lagged value of per capita GDP.
Flutter Based Android Application for Smart Waste Management System

This abstract introduces a Flutter-based Android application designed for efficient waste management through QR-based dustbin location tracking and alerting. The application aims to revolutionize waste disposal by leveraging QR codes to identify and monitor dustbin locations. Users can scan QR codes placed on designated bins, enabling real-time tracking and status updates. The system generates alerts when bins reach capacity, notifying authorities for timely cleaning interventions. Additionally, the application integrates a unique feature for waste material sales, connecting users with recyclers. This Recycler Management System promotes sustainability by streamlining the recycling process and fostering collaboration between waste producers and recyclers. Overall, the Flutter Android application provides a comprehensive solution for smart waste management, incorporating tracking, alerts, and a marketplace for waste material transactions. In summary, the proposed Flutter-based application addresses key challenges in waste management through an innovative approach. By combining QR technology, real-time tracking, and a marketplace for waste material, the system not only facilitates efficient cleaning operations but also contributes to sustainable practices by promoting recycling. This holistic approach aligns with contemporary environmental priorities, offering a user-friendly and integrated solution for optimizing waste disposal processes
Experimental Investigation of Protection Method for Detection of Cloning Attack on Paper Certificates

A method of paper certificate protection against a cloning attack is investigated, that was proposed recently theoretically in a paper of the same author. This method is based on the use of digital watermarks. In order to extend watermark approach to a protection against cloning attacks, it has been suggested to execute estimation of the noise power which appear during the image scanning and printing. Algorithms of embedding and extraction of watermarks out of the images are presented along with a method of detecting of the cloning attack after scanning and printing by an attacker. Numerical results of the experiments for the error probabilities of a cloning missing and a false alarm are also presented and are in agreement with theoretical results obtained before.
School Administrators’ Possession of Digital Skills and Digital Literacy Content for Implementation of Digital Literacy Program in Public Primary Schools in Kitui County-Kenya

Purpose: The purpose of this study was to find out school administrators’ possession of digital skills and digital literacy content impact on the implementation of digital literacy program in public primary schools in Kitui county-Kenya.&#x0D; Methodology: Descriptive survey research design was used to describe the characteristics of the respondents. Review of related literature was done in line with the objectives of the study. The target population comprised of 3280 school administrators, who comprised of both head teachers and deputy head teachers and 328 classroom teachers making a total of 3608 respondents. A sample of 10% of the total population was taken making a sample size of 361 respondents, comprising of 328 school administrators and 33 classroom teachers. Self-administered questionnaires were used for data collection. A test- retest was carried out in four public primary schools to establish the reliability of the research instrument. Data collected were analyzed descriptively with help of Statistical Packages of Social Sciences (SPSS) version 28.&#x0D; Findings: The study established that school administrators’ skills and competencies in digital technology were a good predictor of a smooth digital literacy implementation. On the overall the study found out that schools’ administrators’ possession and use of digital literacy skills was below average. The study further established that 145(88.48%) respondents could access digital literacy content in their school while 19(11.52%) could not access the content in school.&#x0D; Unique Contribution to Theory, Policy and Practice: The findings of the study will guide the leadership in effective delivery of flagship programs like the digital literacy program through multi-agency approaches
Overview on Efficient Resource Provisioning Approach Using Cloud Computing Environment

Abstract: The goal of this study is to examine the importance of effective resource management across different fields and the critical role that cloud computing apps have in accomplishing this effectiveness. To show how these various approaches and strategies can be used in real-world scenarios, the article looks at case studies and application usage. Optimizing resource utilization and performance in cloud computing requires effective scheduling, resource allocation, and other algorithms Using Cloud Simulation (cloud sim) Tool and other cloud environment tools. By adjusting to changing workloads, these algorithms improve fault tolerance, cost effectiveness, and load balancing. Furthermore, maintaining cloud service integrity depends heavily on algorithms for data processing, network optimization, and fault tolerance. Sufficient research in this area is essential to fully utilize cloud computing.
Pelatihan Membuat Soal Matematika Secara Daring Menggunakan Aplikasi Kahoot

In the world of education, it is currently commonly known as learning media that can be used as teaching aids for teachers to make it easier for students to understand the material being taught. Learning media can clarify the presentation of messages and information from teachers to students so that they can facilitate and improve learning processes and outcomes. Learning media can also overcome the limitations of the senses, space and time. One form of media is Kahoot. Kahoot is a game-based learning platform that uses educational technology in schools and other educational institutions. Kahoot is in the form of a multiple choice quiz game application or a survey of opinions and opinions of students or members of public institutions conducted online via a browser. learning through Kahoot is very easy to implement. Kahoot can be played through different browsers to browsers installed on student gadgets. The Kahoot application is very interesting, because the teacher can create quizzes by inserting pictures or videos in the problem so that it can attract students' attention. Kahoot is because the question is equipped with an image or video. Even using short expressions, accompanied by music that is appropriate for their age. Not only that, kahoot can be a form of online interactive media.
The role of Calligraphy in Confirming Identity and Cultural Belonging

This study deals with the relationship of language with general culture, represented by handwriting in language. It is clear that there is a link between language in all its manifestations and culture; Hence, the alphabets became an important part of culture in its spread and decline. This study aims to confirm the importance of calligraphy and indicate its connection to culture. This is done through practical models in which the connection of calligraphy with culture was clearly shown. Using the descriptive analytical approach, the study concluded with some results, the most important of which is that the alphabets acquire a cultural load over time, thus becoming a symbol of general culture, and that replacing or changing the form of the alphabet leads to breaking the connection with heritage and consequently its loss, and hence the interest of Western countries in the Latin alphabet and the attempts to spread it, It emphasizes the great importance of the form of the alphabet and its role in achieving cultural hegemony.
Language acquisition between I-language and E-language

When we talk about I-language and E-language, we are talking about confronting rationality and environment, or about innateness or originality, language acquisition, and learning, or about the evolution of man as a unique creature at its peak. In terms of I-language and E- language, there are many facts and scientific efforts, and several schools and scientific movements have emerged, Structuralism appeared, then came the behavioral theory, and then the generative theory came to confront it later. On this basis, several theories of language acquisition have been developed, and these theories will be discussed in this paper.
The Impact of Technology Identity on Student‘s Adoption of Social Media in Online Learning

This study examined the impact of social media identity on online learning through social media. Smart-PLS 3.3 was run to test the relationship between social media identity, self-efficacy, and social influence on online learning through social media. The Moderation effect of social influence and self-efficacy on the relation between social media identity and behavioral intention to use social media for online learning was examined. Questionnaires were distributed online and 362 valid responses received. Results showed significant positive impact of social media identity, self-efficacy and social influence on behavioral intention to use social media in online learning courses. The moderating effect of self-efficacy and social influence was affirmed. High self-efficacy led to the negative impact of social media identity on the use of the use of social media in online learning. The high social influence led to the positive impact of social media identity on social media use in online learning. The study recommends developing guidelines for integrating social media effectively in education, creating user-friendly platforms, and enhancing students’ self-efficacy through engaging projects. Additionally, promoting communication and considering emotional participation, self-efficacy, and social influence are essential. Further research could explore performance expectancy and academic achievement for deeper insights.
The Impact of Language User Interfaces on Finding Scholarly Repositories

In the winding world of academic research, the quest for an appropriate repository to store and share scholarly data has been akin to a modern-day odyssey. Traditionally, this journey involved wading through static pages and search indexes, a process both time-consuming and fraught with uncertainty.
Students with Reading Disorders: Their Characteristics and Affected Skill Areas

Some children appear to grow normally until they face the academic demands of school. These learners cannot make their way continue compensating for the added content-learning demands. Their performance problems are sometimes rooted in reading disorders. Reading disorder is a specific learning disability described by disorders with correct and /or fluent word recognition, and poor spelling and decoding abilities. This study aims to highlight the characteristic features of reading disorder and the skill area affected by students suffering from reading so that they can be used as a basis for identifying this disorder among learners. The study concludes that the main characteristics of reading disorder could be found in the following areas 'reading, writing and the general aspect of learner's life'. Besides, the skill area affected by students with a reading disorder is realized by a deficit in the main components of being a good reader, that is: (reading decoding, word recognition, reading fluency, and reading comprehension). A deficit in one of these components could result in a reading disability by learners.
Identify technologies and applications in the university digital transformation journey

University digital transformation is no longer an option and has become a top priority for most universities in the world and in Vietnam. In digital transformation, there are three important aspects to consider: people, process and technology. While research in Vietnam focuses a lot on the aspect of change management, from raising human awareness or developing processes, it seems that identifying digital technologies - the potential for digital transformation has not been mentioned much. The article focuses on analyzing and clarifying where and how platform and disruptive technologies are applied in digital university activities. From there, the vision of a complete digital university- the destination of the digital transformation journey- is outlined more specifically.
Demystifying explainable artificial intelligence (EAI)

Today, artificial intelligence (AI) permeates nearly every aspect of our personal and professional life. It is the most extensive information base and common-sense reasoning system. When examining a dataset, the era of automated decision-making, such as profiling, necessitates the correct knowledge and skills. Modern systems frequently suffer from a lack of transparency and interpretability. Due to these problems, explainable AI (EAI) has become a hot topic in academia. The term "explainable AI" (EAI), also known as "interpretable AI," is a term used to describe machine learning and deep learning methods that can justify decisions that people can understand. In this work, we demonstrate how our EAI technique can be used to analyze the model&apos;s real-time decisions, identify trends in the model&apos;s overall behavior, and aid in the identification of potential flaws in the model&apos;s evolution. Furthermore, in order to ensure that the explanations are reliable and useful, we objectively test their consistency across a wide range of EAI metrics. EAI strives to demystify the reasoning that underlies an algorithm&apos;s output.
Breaking the Cubic Barrier for (Unweighted) Tree Edit Distance

The (unweighted) tree edit distance problem for node trees asks to compute a measure of dissimilarity between two rooted trees with node labels. The current best algorithm from more than a decade ago runs in time [Demaine et al., Automata, Languages and Programming, Springer, Berlin, 2007, pp. 146–157]. The same paper also showed that is the best possible running time for any algorithm using the so-called decomposition strategy, which underlies almost all the known algorithms for this problem. These algorithms would also work for the weighted tree edit distance problem, which cannot be solved in truly subcubic time under the All-Pairs Shortest Paths conjecture [Bringmann et al., ACM Trans. Algorithms, 16 (2020), pp. 48:1–48:22]. In this paper, we break the cubic barrier by showing an time algorithm for the unweighted tree edit distance problem. We consider an equivalent maximization problem and use a dynamic programming scheme involving matrices with many special properties. By using a decomposition scheme as well as several combinatorial techniques, we reduce tree edit distance to the max-plus product of bounded-difference matrices, which can be solved in truly subcubic time [Bringmann et al., Proceedings of the IEEE 57th Annual Symposium on Foundations of Computer Science, 2016, pp. 375–384].
Heterogeneous graph attention networks for passage retrieval

This paper presents an exploration of the usage of Heterogeneous Graph Attention Networks, or HGATs, for the task of Passage Retrieval. More precisely, we study how these models perform to alleviate the problem of passage contextualization, that is incorporating information about the context of a passage (its containing document, neighbouring passages, etc.) in its relevance estimation. We first propose several configurations to compute contextualized passage representations, including a document graph representation composed of contextualizing signals and judiciously modified HGAT architectures. We then present how we integrate these configurations in a neural passage ranking model. We evaluate our approach on a Passage Retrieval task on patent documents: CLEF-IP2013, as these documents possess several different contextualizing signals fully exploited in our models. Our results show that some HGAT architecture modifications allow for a better context representation leading to improved performances and stability.
A Novel Method for Utilizing Electronic Health Record Data in Condition-specific Research

<h3>Context:</h3> Large sets of Electronic Health Record (EHR) data are a practical tool to gain insights into cross sectional or longitudinal trends of conditions or diseases that affect millions of people. However, EHR data tends to be notoriously messy and unstandardized from one system to another, making it unpopular with many researchers. EHR repositories can standardize the data from multiple systems using models such as the Observational Medical Outcomes Partnership Common Data Model v6 (OMOP CDM v6). Utilizing one such repository, the study team defined questions and proxies related to Opioid Use Disorder (OUD) and implemented a way to organize packets of information into value sets. <h3>Objective:</h3> Design a methodology to approach using EHR data to study a specific condition of interest to data-focused researchers. <h3>Study Design and Analysis:</h3> Mixed methods study including literature reviews, analysis of EHR data, and value set creation. <h3>Setting or Dataset:</h3> American Academy of Family Physicians (AAFP) National Research Network. <h3>Population Studied:</h3> Secondary data analysis. <h3>Instrument:</h3> The open-source application for data and analytics, ATLAS, was used to obtain codes of the conditions, measurements, observations, medications, or procedures related to the topic being researched. <h3>Outcome Measures:</h3> A novel mixed methods approach to effectively conduct analyses on a condition or disease utilizing EHR repository data. <h3>Results:</h3> The study team applied the mixed methodology to conduct analyses of diagnosis and treatments for OUD in a dataset of four million patient records from 2010 to 2020. The first step was to conduct a literature search on best practices for diagnosing and treating OUD, common comorbidities, and the medications and/or behavioral therapy associated with treatment, along with other necessary proxies. The next search was for interactions between opioids and other drugs or diseases, and potential contraindications. Lastly, value sets were created to contain ICD9, ICD10, SNOMED, LOINC, HCPCS, CPT, and RxNorm codes, and these were used to identify patients diagnosed with OUD and describe the accompanying follow-up care. <h3>Conclusions:</h3> The study team developed the mixed methodology to efficiently analyze longitudinal patterns of care in patients with OUD. Because EHR data includes demographic information, further analysis can be done to distinguish differences in personal characteristics, such as gender, race, age, and geographic region.
Information technology infrastructure in digital transformation at Banking Academy of Vietnam

The Covid -19 pandemic broke out and caused negative impacts on all aspects of socio-economic life, but it is also a factor that promotes the process of digital transformation of education to happen faster. During the period of quarantine due to the epidemic, educational institutions have actively applied information technology in teaching, learning and evaluation to complete the school year plan. Reality has proven that one of the most important foundations of digital transformation in education is ensuring the conditions for digital infrastructure to apply information technology. By summarizing data and observing trends, the article evaluates the current situations of digital infrastructure, information system security and software systems serving digital transformation at the Banking Academy of Vietnam (BAV). From that, the authors point out shortcomings, difficulties and infrastructure challenges for the digital transformation process at BAV in the current period.
Digital transformation journey at the Banking Academy of Vietnam- Current status and Solutions

After 62 years of formation and development, the Banking Academy of Vietnam (BAV) is facing new challenges in terms of development orientation in the context of a rapidly changing digital economy and digital society. The strengths of BAV in the past have been promoted and brought BAV’s position today as a convenient location in the center of Hanoi, a school affiliated with the banking industry, with a long history of training and a team of committed and enthusiastic lecturers. However, in the new context of the digital age, many advantages may have reached their limit and besides, many factors have revealed weaknesses that need to be overcome, leaving little room for development. BAV’s campus is always overloaded, library space is becoming more and more cramped, the management of lecture halls and facilities is becoming increasingly inadequate, the need for learner experience is increasing, especially for digital services, etc. Digital transformation (DT) is considered the key to help BAV overcome the above weaknesses, helping to increase effectiveness and efficiency in management and administration activities and improve competitiveness in the context of integration. This study was conducted with the goal of determining the current status and solutions to effectively implement DT activities at BAV in the period 2022-2025, vision 2030
MENINGKATKAN EFISIENSI PENGENDALIAN SUHU BOILER PADA PLTSa BURANGKENG MELALUI ANALISIS KOMPREHENSIF BERBASIS MACHINE LEARNING

Waste management has become an urgent issue in many regions, prompting the need for sustainable solutions in its treatment. Waste-to-Energy (WtE) power plants have emerged as a promising option, but manual control issues within them have raised some serious challenges. Temperature variations in the boiler pose a threat to efficiency and productivity, resulting in significant economic losses and adverse environmental impacts. To address this problem, this research aims to apply Machine Learning to optimize boiler temperature control. Operational data is collected and used to train a Machine Learning model capable of accurately predicting temperature. This model is then implemented into the boiler control system. The research results indicate a significant improvement in temperature stability and a reduction in operational costs. The utilization of Machine Learning technology has paved the way for more efficient and sustainable operations. With the successful implementation of Machine Learning in boiler control, this research emphasizes the crucial role of advanced technology in the development of sustainable energy industries. In conclusion, the application of Machine Learning can provide an effective solution to temperature control issues, significantly optimizing efficiency and productivity. Therefore, this research makes a valuable contribution to more efficient waste management, has a positive impact on the environment, and supports the achievement of cleaner and more sustainable renewable energy goals.