Reviewerly/exHarmony huggingface dataset:
Automation in e-procurement system with auction module

The article focuses on design and development around automation processes in complex e-procurement system with auction module. The complex system was built based on microservices architecture using latest server-side and client-side technologies. Data synchronization and integration amongst system’s various modules was implemented in real time via Web Socket protocol and database triggers. Web client notification methods involved SignalR technology. Data was stored in a distributed database and cached to dramatically improve query execution time. Authentication and authorization for users, modules, and subsystems was designed according to OAuth 2.0 standard with a proprietary implementation of the Proof Key Code Exchange algorithm and Backend for Frontend approach. The web client was built as a single page application using a strongly typed managed language to simplify development and debugging process. The client application was optimized with the help of lazy-loading algorithms for key modules, among them supplier, buyer, and common module. The system was composed into a Docker container to be ready to publish on cloud services or physical servers and support any operating system. A set of unit, integration, and system tests was created for each subsystem and module. Monitoring of the complex includes a technology stack to log, store, and visualize request statuses, latency, uptime, and overall health of the system. Existing automation flows for build and deployment were improved to accommodate the needs of the complex e procurement system. The system was designed and built for key stakeholders such as private enterprises acting as buyers and people or companies acting as suppliers.
THE EFFECT OF LETTER CARD MEDIA ON LEARNING OUTCOMES IN ELEMENTARY LEARNING

This study aims to determine the effect of Letter Card Media on the Theme of Living in Harmony and the Sub-themes of Living in Harmony at Home to Improve Student Learning Outcomes in Class II SD Negeri 095191 Lihas. The research design used was a quantitative approach with an experimental method in the form of a one group pretest posttest design without any comparison group. The population in this study were all second grade students at SD Negeri 095191 Lihas and the sample used was 30 students at SD Negeri 095191 Lihas. The sample technique used is random sampling with two research variables, namely the dependent variable in the form of student learning outcomes, and the independent variable in the form of letter card media. The data collection technique is the test technique. The results of testing the hypothesis using the t test technique paired sample t test with the help of the SPSS Version 21 program, based on the calculation results that the significant value is 0.000 &lt;0.05, so that ho is rejected and ha is accepted or by slamming tcount &gt; ttable with df = (n- 1) namely tcount = 14.68 &gt; ttable = 2.04. So it can be concluded that there is an effect of using letter card media on the theme of living in harmony, sub-theme of living in harmony at home, to improve student learning outcomes in class II SD Negeri 095191 Lihas
EFFORTS TO IMPROVE THE ABILITY OF WRITING SIMPLE PARAGRAPH IN INDONESIAN SUBJECTS USING STUDENT IMAGE SERIES CLASS III MIS AL QUBA MEDAN

In an effort to realize an increase in students' writing, teachers are expected to be able to choose and apply instructional media that can convey learning objectives well to students. The formulation of the problem in this study is whether the application of serial picture media can improve the ability to write simple paragraphs in Indonesian class III students, for example. Al Quba Medan. The purpose of this study was to find out and describe the learning outcomes in the form of the ability to write simple paragraphs using picture series media in Indonesian language learning class III III Mis. Al Quba Medan. This study uses Classroom Action Research (CAR). The data obtained from qualitative data and quantitative data. Data collection techniques through student observation to determine the increase in student learning activities, tests to determine student learning outcomes and documentation. The method of data analysis in this study uses qualitative and quantitative analysis. Based on the results of data analysis it is known that after the picture series media is applied the students' writing ability has increased, this can be seen from the average student learning activity in cycle I of 63.1% and cycle II of 82%. Experiencing an increase from cycle I to cycle II of 18.9%. Students' writing ability has increased after applying serial picture media in the learning process. This can be seen from the increase in student completeness in cycle I of 68.2% and cycle II of 84.21%. Experiencing an increase from cycle I to cycle II by 20%.
Enhancing Employee Productivity in Multinational Logistics Through Big Data Analysis: Investigating the Impact of Flexible Work Arrangements, Location, And Amenities

In today’s working environment, various organizations confront the significant challenges of productivity and performance. However, higher education institutes (HEIs) are also not free from this massive issue. Therefore, the present study investigates employee productivity and performance through work engagement (WEE) and organizational factors. The modes of study are quantitative and based on cross-sectional data. The study collects the response from academic and administrative staff from public and private HEIs of Saudi Arabia. The study applies convenience sampling and successfully proceeds 254 valid cases to conclude the findings. The applied structural equation model (SEM) path analysis demonstrates a positive and significant effect of WEE comprising vigour, dedication, and absorption factors on employee productivity (EPD). In addition, employee performance (EP) is predicted through organizational factors such as management support (MS), learning culture (LC), work environment (WE) and organizational commitment (OC). Finally, the study finds a significant and positive effect of EPD on EP among the employees of HEIs. The study findings would be guidelines for policymakers and the top management of higher education commissions to advance the knowledge and skills of EPD and EP of the organizations. The study would support achieving job tasks and goals through developing WEE and organizational factors for productivity and performance. Lastly, the findings will augment the literature and provide empirical evidence from Middle East countries. The study provides a vigorous model which connects the WEE theory and organizational factors towards EPD and EP in an integrated way.
A study on the current situation of classroom common problem behaviors of lower primary school students in Ningxiang City

The problem behavior of primary and secondary school students in the classroom directly affects the quality of classroom teaching. Studies have shown that the classroom problem behavior of primary school students will bring many adverse effects on teachers' classroom teaching and student development, which not only disrupts teachers' teaching, wastes students' learning time, but also reduces students' learning motivation and enthusiasm, forms a stressful classroom atmosphere, and destroys the trust and cooperative relationship between teachers and students. As a teacher, managing students' classroom problem behaviors is one of the trickiest things to do and a major source of professional stress. Therefore, the author adopts questionnaire survey method, observation method and literature research method to investigate from multiple dimensions to study the current situation of common classroom behavior of primary school students in a primary school in Ningxiang.
Rainfall Prediction with Support Vector Machines: A Case Study in Tanjungpinang City, Indonesia

Rainfall forecasting is becoming more challenging due to extreme climate change. Especially for the archipelago which has a unique geography compared to the mainland. The aim of this study is to test the performance of the support vector machine in predicting rainfall in Tanjungpinang, Kepulauan Riau, Indonesia. The variables used to predict are temperature, humidity, wind speed, and rainfall. The results obtained is a precision value of 82% for rain, with a ROC curve evaluation score of 0.74. These results show that the model built has a fairly good ability to separate between positive and negative results in predicting rainfall.
Various Skew Correction Techniques: Kannada Handwritten Script

In a handwritten text document, before identifying the character it is essential to pre-process. During the pre-processing stage, identifying the skewed angle and correcting the text document is a significant step. A few effective algorithms are used in later stages to extract the features and identify the characters. In this paper, Fourier Transform, Hough Transform, and Horizontal Projection Profile Techniques are described in steps. These are implemented forskew detection, and correcting techniquesin a Kannada handwritten document. Comparison analysis is also undertaken in this study, to get unambiguousness about the suitable algorithm to use on different documents for effectual results.
Word Lengths in Classical and Post-Classical Greek

The purpose of this dataset is to collate average word lengths in Greek in the Classical period (using a sample from the 5th century BCE) and the average word lengths in the Post-classical period (using a sample from the 1st century CE). This dataset, which is stored as a CSV file in the Harvard Dataverse, has been used to demonstrate that the average length of words in Greek increased significantly between the Classical and Post-classical periods. It comprises two word lists and corresponding word lengths for each sample; a table of the average word lengths (for nouns, adjectives, verbs, adverbs, and total) of each sample and the statistical t-test results showing the significance of the difference in word lengths between Classical and Post-classical Greek. This dataset has a reuse potential for linguists investigating diachronic change in word lengths as well as for historical linguists looking at the evolution of Classical and Post-classical Greek.
Unveiling the Digital Equation Through Innovative Approaches for Teaching Discrete Mathematics to Future Computer Science Educators

Aim/Purpose: This study seeks to present a learning model of discrete mathematics elements, elucidate the content of teaching, and validate the effectiveness of this learning in a digital education context. Background: Teaching discrete mathematics in the realm of digital education poses challenges, particularly in crafting the optimal model, content, tools, and methods tailored for aspiring computer science teachers. The study draws from both a comprehensive review of relevant literature and the synthesis of the authors’ pedagogical experiences. Methodology: The research utilized a system-activity approach and aligned with the State Educational Standard. It further integrated the theory of continuous education as its psychological and pedagogical foundation. Contribution: A unique model for instructing discrete mathematics elements to future computer science educators has been proposed. This model is underpinned by informative, technological, and personal competencies, intertwined with the mathematical bedrock of computer science. Findings: The study revealed the importance of holistic teaching of discrete mathematics elements for computer science teacher aspirants in line with the Informatics educational programs. An elective course, “Elements of Discrete Mathematics in Computer Science”, comprising three modules, was outlined. Practical examples spotlighting elements of mathematical logic and graph theory of discrete mathematics in programming and computer science were showcased. Recommendations for Practitioners: Future computer science educators should deeply integrate discrete mathematics elements in their teaching methodologies, especially when aligning with professional disciplines of the Informatics educational program. Recommendation for Researchers: Further exploration is recommended on the seamless integration of discrete mathematics elements in diverse computer science curricula, optimizing for varied learning outcomes and student profiles. Impact on Society: Enhancing the quality of teaching discrete mathematics to future computer science teachers can lead to better-educated professionals, driving advancements in the tech industry and contributing to societal progress. Future Research: There is scope to explore the wider applications of the discrete mathematics elements model in varied computer science sub-disciplines, and its adaptability across different educational frameworks.
EFFECTIVE COMPARATIVE EVALUATION OF SENTIMENT ANALYSIS USING PAIRED T-TEST: A PERFORMANCE STUDY OF SUPERVISED METHODS

This article introduces a comprehensive investigation into the evolution of sentiment analysis, a field dedicated to extracting and comprehending human language expressions of opinions and emotions. The authors address a pivotal question: how has sentiment analysis progressed over the past two decades, and what are the principal challenges and advancements shaping this discipline? In pursuit of this inquiry, this article presents a systematic literature review of sentiment analysis research conducted using supervised machine learning techniques over the last twenty years. This review encapsulates the major discoveries, obstacles, and developments that have shaped the field. The authors provide an overview of various supervised machine learning methodologies employed in sentiment analysis, offering performance comparisons and highlighting the temporal evolution of these approaches. Additionally, the assessment relies on accuracy as the primary metric for technique comparison, which is fortified by the application of paired t-tests. This rigorous methodology ensures a precise and reliable evaluation, confirming that observed performance disparities are not merely a result of happenstance but reflect genuine methodological advantages. The decision to focus on supervised machine learning methods for sentiment analysis is grounded in their prevalence in the literature and their proven efficacy in handling extensive textual datasets. The specific techniques emphasized in this review were carefully selected on the basis of their enduring relevance in contemporary research and their substantial influence on sentiment analysis throughout the past two decades. While supervised techniques have exhibited promising outcomes, their effectiveness is often contingent on the quality and scale of annotated datasets at their disposal. These methods may encounter challenges when dealing with subtly conveyed sentiments or languages that lack substantial annotated resources, primarily because of the absence of extensive labeled data. This comprehensive examination sheds light on the dynamic landscape of sentiment analysis, illuminating its historical trajectory and highlighting key advancements and challenges. Furthermore, it underscores the importance of supervised machine learning in this domain, offering insights that can inform future research and practical applications. Keywords: Sentiment Analysis, Supervised Machine Learning, Comparative Analysis, Accuracy, Paired T-Test DOI： https://doi.org/10.35741/issn.0258-2724.58.5.28
IMPACT OF SOCIAL MEDIA LANGUAGE USE ON LANGUAGE VARIATION AND CHANGE: A STUDY OF TWITTER DISCOURSE

This investigation explores the effects of social media language use on linguistic variation and modification in the context of Twitter discourse. Using a quantitative methodology, we investigate commonly occurring linguistic characteristics, connections with user demographic information, and correlations with metrics related to user engagement. The examination of linguistic characteristics reveals the prevalent use of hashtags, abbreviations, emojis, and linguistic novelties in Twitter communication. Hashtags aid in the classification of content and promote participation in wider discussions, whereas abbreviations and emojis enable succinct and expressive communication. The manifestation of novel linguistic features indicates the fluid and progressive character of language in the context of digital domains. The correlation between linguistic variation and user demographics underscores the impact of societal factors. Gender-specific linguistic norms and preferences are discerned, suggesting the existence of gender-specific language patterns. Linguistic variations that are distinct across various age groups and geographical locations indicate the sociocultural factors that impact language usage. Keywords: Language Use, Language Variation, Social Media DOI： https://doi.org/10.35741/issn.0258-2724.58.5.47
FROM TEXT TO TECH: INVESTIGATING CHATBOTS' ROLE IN ENHANCING ORAL PROFICIENCY IN SECOND LANGUAGE LEARNERS

This study examines the profound influence that chariots exert on the cultivation of oral proficiency among individuals engaged in the acquisition of a second language. Employing a rigorous quantitative approach, the present study employed a pre-test/post-test experimental design to investigate the impact of a language-focused chatbot intervention on the enhancement of oral proficiency. The participants were divided into two cohorts: an experimental group, which was subjected to the interactive chatbot, and a control group, which employed conventional language learning methodologies. This study presents compelling findings that support the efficacy of chatbots in enhancing speech proficiency. By offering interactive practice, immediate feedback, and personalized learning paths, chatbots have demonstrated a significant impact on improving language skills. The juxtaposition between chatbots and traditional methodologies highlights the superior efficacy of chatbots in fostering the advancement of oral communication skills. This research endeavor significantly enriches the scholarly domain by effectively bridging prevailing research lacunae, augmenting our understanding of the efficacy of chatbots in the realm of language acquisition, and furnishing pragmatic ramifications for practitioners in the spheres of education, curriculum design, and technological advancement. Keywords: Chatbots, Oral Proficiency, Second Language Learners, Technology-Enhanced Education, Traditional Language Learning Methods DOI： https://doi.org/10.35741/issn.0258-2724.58.5.45
EXPLORING THE INTEGRATION OF COMPUTER PROGRAMMING INTO EARLY CHILDHOOD EDUCATION

This study examines the pedagogical approaches employed in teaching computer programming to children in Jordan and Saudi Arabia. The objective of this study is to gain a deeper understanding of the challenges that educators encounter, the resultant impact on students’ levels of engagement and drive, and the role of parental participation in this context. The data were compiled through interviews with teachers and observations of classroom coding activities. The findings indicate that educators encounter challenges such as inadequate coding proficiency and self-efficacy and limited resources and antiquated technology. The incorporation of computer programming has been observed to enhance students’ interest and enthusiasm, stimulate their inquisitiveness, and promote collaborative efforts. The effectiveness of integration is enhanced by the involvement and awareness of parents regarding their child’s academic progress. The research emphasizes the necessity of providing opportunities for professional development, appropriate resources, and family involvement to effectively integrate computer programming into early childhood education. Keywords: Computer Programming, Early Childhood Education, Student Engagement DOI： https://doi.org/10.35741/issn.0258-2724.58.5.46
INTEGRATING AI-BASED VIRTUAL CONVERSATION PARTNERS IN ENHANCING SPEAKING SKILLS IN FOREIGN LANGUAGES: INSIGHTS FROM UNIVERSITY STUDENTS

Speaking skills in a foreign language has been the benchmark for rating proficiency and level of development in the foreign language. As such, any attempt to critically evaluate tools that can enhance the speaking skills of foreign language learners usually attracts considerable attention. This study explored how AI-powered virtual conversation partners (VCPs) can help foreign language undergraduates improve their speaking ability. A total of 597 undergraduates in the penultimate and final years at various universities. The study community is mainly university undergraduates in foreign language education. A questionnaire was used to collect data from the participants, and analysis was conducted using relevant statistical tools. The analysis indicates that a greater percentage of the study population (82%) uses Linguino as the main virtual conversation partner for enhancing their foreign language speaking ability. The data further indicated that the most ineffective tools were Speaking AI (58.96%) and Poliglo Pa (51.09%). The results also indicated that the students have a positive attitude toward the use of these VCPs, and they perceive these tools as important in enhancing their speaking skills in the foreign language because the tools are easy and user-friendly. Thus, from the learners’ perspective, these VCP tools are very effective in enhancing their foreign language speaking skills. There is also an increase in the number of foreign language learners who use VCPs to improve their foreign language speaking skills. Further studies are recommended to offer insights into how these VCPs can be integrated into foreign language education. Keywords: Speaking Skills, Artificial Intelligence, Foreign Language, Virtual Conversation Partners DOI： https://doi.org/10.35741/issn.0258-2724.58.5.43
Banking on the Cloud: Insights into Security and Smooth Operations‎

Cloud computing facilitates the online provisioning of IT resources, and banks are progressively adopting it to enhance operational efficiency. Despite its usefulness, combining cloud services is not without its difficulties. This study examines the pros and cons of using cloud services in banking, focusing on data security, infrastructure stability, and ongoing business functions. For the purpose of this study, we interviewed a number of leaders in the field, such as officials from a major cloud provider and an Omani bank. The importance of addressing environmental considerations, personnel training, data privacy, security, and system integration was highlighted through key insights. It was concluded that, in order to make a smooth shift to the cloud, financial institution employees must have a thorough understanding of its features. The findings of this research add to the ongoing discussion about banking’s embrace of the cloud and provide useful pointers for working with the cloud.
Teaching through Educational Apps: The Effect of Using Smart Books on Enriching the Oral Communicative Ability of the Learners

The appropriate use of new technologies and educational applications is undoubtedly very important in facilitating English language learners’ communicative competence. One of these technological devices used in education is the smartbook. Accordingly, the present study has tried to investigate the effectiveness of the use of smartbooks in the process of teaching English to learners and, consequently, the improvement of their communicative ability. In order to collect data for the study, 40 high school students learning English, including one experimental group and one control group, participated in this study. A pre-post test and teacher-made tests were designed for the learners. The One-way ANCOVA results indicated that the learners participating in the experimental group were more successful than those participating in the control group. This shows that the use of smartbooks has a significant effect on improving the oral communicative ability of English language learners. Implications for L2 researchers and practitioners were finally discussed.