Reviewerly/exHarmony huggingface dataset:
A THEORETICAL REVIEW OF VOCABULARY ACQUISITION LEVEL AND ITS INFLUENCE ON STUDENTS READING COMPREHENSION

Reading is a creative way to actively and positively acquire information and to develop students' ability to perceive and access information visually through writing. At the same time, vocabulary is a foundation for reading. The relationship between English vocabulary level and reading comprehension ability are studied by different scholars, especially the relationship between these two variables. Supported by different findings, most of these researchers have found that there is a high correlation between English vocabulary level and reading comprehension ability. An indication is that English language learners' reading comprehension is generally influenced by how much vocabulary they know. The implication is that, as vocabulary contributes to students' understanding of what they read, reading must be part of their learning to improve their vocabulary and one of the essential components of language learning that could lead to their overall language proficiency.&#x0D;
Research on Anchoring Effect

A psychological phenomena is the anchoring effect. It alludes to the idea of a persons judgment or choice being influenced by an otherwise unrelated reference point or anchor. Once the anchors value is determined in numerical anchoring, the persons following arguments, estimates, etc., may differ from what they would have been without the anchor. Traditional economics holds that people make rational decisions and are not distracted by meaningless numbers. The anchoring effect discovered by Daniel-Kahneman-and-Amos-Tversky is a very typical psychological bias, and it is a rejection of the assumption of a rational person. The anchoring effect refers to the fact that when people need to evaluate an event, they will use some specific value as an initial reference value, and this initial reference value is like an anchor that restricts the evaluation result.
Price of Ethereum Token Effect on the Non-Fungible Token User Trading Activities in the 2020s

This research investigates the relationship between the price of the Ethereum token and Non-Fungible Token (NFT) trading activities on the Ethereum blockchain in the 2020s. Through regression analysis and t-tests, the study explores how changes in Ethereum's price and price volatility influence NFT trading behaviors. The regression analysis reveals significant positive correlations between Ethereum's price and various NFT trading variables, indicating that an increase in Ethereum's price positively impacts sales volume, unique sellers, unique buyers, and average sales of NFTs. Conversely, Ethereum's price volatility demonstrates significant negative associations with NFT trading activities, suggesting that market uncertainty and risk aversion influence investor decisions. The findings provide valuable insights for practitioners, investors, and traders in the NFT market, offering guidance for decision-making strategies and market trends; however, the study also acknowledges limitations in establishing causal relationships and suggests future research directions. Understanding the dynamics between Ethereum's price and NFT trading activities is crucial in navigating the evolving landscape of blockchain-based assets and decentralized markets.
Assessing the Suitability of Rooftop Solar Photovoltaic Systems for Sustainable Electricity Generation

The adoption of solar energy as a sustainable solution is gaining momentum in Malaysia. Universities, as prominent stakeholders, are at the forefront of implementing energy efficiency and renewable generation objectives. This study aimed to evaluate the suitability of photovoltaic systems for electricity generation by assessing the solar radiation potential of the Universiti Kebangsaan Malaysia (UKM) campus in Bangi. Geospatial data and GIS approaches were utilized to characterize solar potential across the 1096-hectare campus. Unmanned aerial vehicle (UAV) images were processed to derive digital surface models, enabling the calculation of slope and aspect. By considering slope, aspect, shadow, area, and total solar radiation, suitable buildings for photovoltaic installation were identified. Out of the 546 buildings assessed, two were highly suitable, seven were suitable, 32 were moderately suitable, 134 were unsuitable, and 367 were highly unsuitable. The selected rooftops have the potential to generate 69,975 MWh annually, representing about 17% of the total electricity consumption from the grid. These findings highlight the viability of rooftop solar arrays for UKM and suggest an estimated energy production ranging from 9,949 MWh/year. The methods employed in this study, leveraging high-resolution UAV images, can be adapted to comprehensively assess solar potential in other institutions across Malaysia, contributing towards meeting campus energy goals and advancing sustainable practices. Keywords : Renewable energy, Energy Consumption, urban, Unmanned aerial vehicle, photovoltaic
The Impact of External Factor on Cryptocurrency: Explicit and Implicit Policy

In recent years, the view of economists and issuers of cryptocurrencies has changed a lot, from the original price of cryptocurrencies is unpredictable, to the view that cryptocurrencies are affected by several key factors. Confidence is one of the key factors, and it is thought to be controllable. However, many economists and cryptocurrency issuers have acknowledged that the support for confidence in the cryptocurrency market is complex and volatile. The goal of this paper is to propose ways to stabilize confidence in cryptocurrencies based on these studies. Explicit and implicit policies are one of the important factors affecting cryptocurrencies. The purpose of this article is to illustrate the close connection between cryptocurrencies and information, and to analyze how explicit and implicit policies affect cryptocurrency information and markets. The impact of explicit and implicit policies on the price of cryptocurrencies is unpredictable, but it still has regularity in the impact on the price of cryptocurrencies. This article analyzes several notable cryptocurrency explicit and implicit policy events to illustrate the differences and characteristics between the two types of policies. The influence of explicit policy is not positively correlated with its propaganda intensity in the short term but will be maintained and stable in the long term. Stealth policies tend to show dramatic changes in a short period of time and are highly correlated with popularity. While hidden policies can cause sudden fluctuations, issuers of cryptocurrencies should pay more attention to the effects of explicit policies because they are more durable.
Discuss the Motivations and Risks Behind Microsofts Acquisition of Activision Blizzard

With the rapid growth of the gaming sector and advancements in technology, the global gaming market has reached unprecedented heights, capturing the attention of millions worldwide. Simultaneously, the concept of metaverse has become a topic of intense discussion, holding the promise of transforming virtual experiences. This paper study thoroughly examines Microsoft's strategic move to acquire Activision Blizzard, scrutinizing its multifaceted impact from various perspectives. Motivated by the pursuit of synergy effects, market expansion, and preparation for the metaverse, Microsoft aims to harness the potential of Activision Blizzard's intellectual properties and fortify its gaming portfolio, potentially positioning itself ahead of Sony in the fiercely competitive gaming console market. Nevertheless, the integration of diverse corporate cultures and the ever-present specter of antitrust scrutiny pose significant challenges on the horizon. This compelling case study offers invaluable insights into the decision-making processes of major corporations, shedding light on the intricacies of the dynamic gaming industry and the unfolding metaverse landscape. As the gaming realm and technology continue to thrive, this landmark acquisition becomes a pivotal example in understanding and navigating strategic business decisions in the rapidly evolving digital era.
On Frontier Portfolio in Shanghai Stock Exchange Based on Mean Variance Model

In security markets, how to achieve optimal allocation of asset has become the focus of investors. The mean-variance model is a method to achieve revenue maximization and risk minimization on investing stock portfolio. This paper will research on investment problem in Shanghai Stock Exchange. It involves research result about mean variance model since 1952. To take the experiment, 10 stocks are chosen from Shanghai Stock Exchange. Organizing rates of return for 360 days and using the average daily rate of return as the expected rate of return. Applying mean variance model, selecting data, the curve of frontier portfolio is obtained by experiment. Based on the result, the investment advice is given. It shows that higher expected rate of return accompanies by higher risk. To achieve higher returns, investor could analyse the variation of each asset along with the rise of the expected rate of change. When negative weight appears, there exists short selling. If short selling is not allowed, investor could shrink the interval of the expected rate of return.
Detection of Buffer Overflow Attacks with Memoization-based Rule Set

Different abnormalities are commonly encountered in computer network systems. These types of abnormalities can lead to critical data losses or unauthorized access in the systems. Buffer overflow anomaly is a prominent issue among these abnormalities, posing a serious threat to network security. The primary objective of this study is to identify the potential risks of buffer overflow that can be caused by functions frequently used in the PHP programming language and to provide solutions to minimize these risks. Static code analyzers are used to detect security vulnerabilities, among which SonarQube stands out with its extensive library, flexible customization options, and reliability in the industry. In this context, a customized rule set aimed at automatically detecting buffer overflows has been developed on the SonarQube platform. The memoization optimization technique used while creating the customized rule set enhances the speed and efficiency of the code analysis process. As a result, the code analysis process is not repeatedly run for code snippets that have been analyzed before, significantly reducing processing time and resource utilization. In this study, a memoization-based rule set was utilized to detect critical security vulnerabilities that could lead to buffer overflow in source codes written in the PHP programming language. Thus, the analysis process is not repeatedly run for code snippets that have been analyzed before, leading to a significant reduction in processing time and resource utilization. In a case study conducted to assess the effectiveness of this method, a significant decrease in the source code analysis time was observed.
Insights into B2C E-Commerce Quality Using ISO 25010

This paper introduces an innovative Software Quality Assurance framework tailored for B2C e-commerce systems, seamlessly integrating software quality with business objectives. Drawing from elements of the ISO 25000 series and ISO 20000 standards, this framework specifically addresses challenges inherent to e-commerce. By establishing business-relevant KPIs, the framework ensures that ongoing improvement initiatives resonate with the company’s strategic goals. Additionally, the paper presents a Dynamic Bayesian Network model as a hands-on tool for implementing the framework within e-commerce organisations.
Theoretical Principles of Measuring and Interpreting Levels of Attention, Involvement and Organizing Feedback of Students to the Educational Process Using Automated Software Products

The article highlights the theoretical foundations of measuring and interpreting student attention levels, engagement, and feedback, an attempt is made to characterize the possibilities of using automated software products for this purpose. The article identifies the psychological characteristics of students of the Zoomers generation, which affect the educational process and cause the revision of educational technologies. A comparative analysis of traditional and distance learning was carried out. Based on the characteristics and interpretation of visual markers for measuring the attention and involvement of the acquirers, the requirements for the software product for determining the degree of involvement and the degree of information perception are described. The article discusses the main AI-based tools that allow you to assess the level of audience attention in real time during online conferences (EmotionCues, HEADROOM and MeetingPulse) from the standpoint of the effectiveness of the analysis of the emotional component and the possibility of integration with online conference services. The theoretical analysis is the basis for further research on the measurement and interpretation of students’ attention, engagement and feedback.
Enhancing Performance Evaluation Through Augmented Reality Smart Glasses for Industrial Operators

Monitoring operator compliance with work instructions is critical to ensuring that product quality is maintained, safety requirements are fulfilled, rules are followed, efficiency is enhanced, and suitable training is provided. Various industries employ different tools to manage operator performance, such as Standard Operating Procedures, Checklists, Performance metrics, Audits or Inspections. Due to the requirements for infrastructure, manpower, training, maintenance, integration, and privacy issues, the process of monitoring operators’ performance can be costly for industry. On the other hand, the advantages of a well-designed monitoring system can offset these cost expenses by increasing productivity, quality, and safety, resulting in long-term cost savings and better competitiveness. This paper reports a research project that transferred Hololens 2 with Microsoft Dynamics Guide to a tool that simultaneously guides and monitors operators’ real-time performance. The new technology can assist industry in identifying areas where operators may require more training or support and optimising workflow to increase overall efficiency. Furthermore, the data gathered by this technology may be utilised to enhance future trainings and modify ongoing production processes.
Empowering Worldwide EFL Learners' Reading Learning Dynamics in the Support of the Jigsaw Technique

The significant impediments frequently hampering globalized EFL learners from continuing their reading learning enterprises are a higher sense of competitiveness among learning community members, satiation to read plenty of challenging reading texts, and constant perturbing of encountering adverse reading learning situations. These inevitable reading learning obstructions can be better mitigated with the continuous support of the jigsaw technique wherein EFL learners willingly, supportively, and collaboratively address insistent reading learning supports to achieve more gratifying reading learning outcomes as solid teammates. This current small-scale library study is a further attempt by the researcher to exhaustively investigate the influence and crucial role of the jigsaw technique in empowering worldwide EFL reading learning dynamics. To that end, the researchers utilized a thematic analysis approach in reviewing specifically attained research results derived from 20 jigsaw techniques in reading study techniques more trustworthy, robust, and representative findings. The 20 chosen journal articles ranged from 2018 until 2022 to ascertain the validity and reliability of the reviewed research results toward existing EFL reading learning contexts. The thematically categorized research results revealed that the jigsaw technique did not solely make EFL learners more proficient but also avid readers. Therefore, it is vitally essential for worldwide second language educators to commence their daily-based reading learning activities with the endorsement of the jigsaw technique. Keywords: Jigsaw technique; EFL reading; thematic analysis; library study
Comparison of HSV, LAB and YCrCb Color Feature Extraction Results in the SVM Algorithm for Bird Species Classification

The classification of bird species is a problem often faced by ornithologists, and has been considered scientific research since antiquity. This study aims to evaluate the results of color feature extraction including HSV, LAB and YCrCb against the results of the SVM classification. In addition, the results of this study are useful to determine the performance of color feature extraction that is suitable for bird species classification. The dataset used was 22,617 bird species images. Based on experimental results, the effect of HSV on the SVM classification caused a decrease in accuracy by -0.33% while LAB and YCrCb on the SVM classification caused an increase in accuracy of 0.44% and 0.21%. However, the accuracy of the SVM classification does not yet have good performance so that further research will be carried out using other classifications, including convolutional neural networks and others.
Pemanfaatan Excel Dalam Penyusunan Laporan Keuangan Sederhana Pada Usaha Sablon Di Desa Santong Kecamatan Kayangan Kabupaten Lombok Utara

Financial reports have a very important role in the sustainability of an agency or organization. There is a lack of insight and understanding regarding modernization in financial reporting at the Makmur Abadi Printing Business and Langit Biru Printing, so direction and knowledge must be given to operate Microsoft Excel software in preparing simple financial reports. That way, service partners can make financial reports easily and practically. Not only that, to make it easier to remember the composition of financial reports, a simple financial report format was created that is concise and easy to understand so that what was originally recorded manually can be summarized more effectively and efficiently. This service activity is urgently carried out as a solution to this problem. This type of service activity is helping the printing business in Santong Village prepare simple financial reports using Microsoft Excel. The implementation method for this service activity is carried out using a simulation method to provide direct experience to the owners of the Makmur Abadi Printing Business and other screen printing entrepreneurs in Santong Village in recording financial reports. Apart from that, the question-and-answer method and mentoring are used during the process of preparing financial statements. The result of this service is the design of an accounting system using Microsoft Excel. Service Partners can use examples of monthly profit and loss calculations resulting from the output of this service to be applied in preparing financial reports for the following months.
Analyzing the Impacts of Artificial Intelligence on Education

Artificial Intelligence (AI) is a rapidly growing field that encompasses various disciplines, including mathematics, engineering, computer science, philosophy, and linguistics. It has significantly impacted various sectors, including education, by addressing issues such as content accessibility and teacher deficiency. AI implementation and adoption are inevitable in the education sector, and it includes technologies such as smart learning, tutoring systems, social robots, virtual facilitators, online learning environments, learning management systems, and learning analytics. As machines gain learning abilities, they may soon become super-intelligent. AI researchers and government authorities should promote further research to improve the pace and rate of human intelligence development through education, ensuring that individuals do not feel inferior or obsolete in the face of AI research and technology advancements. This will prevent individuals from feeling inferior, irrelevant, or obsolete in the face of AI advancements. Keywords: Effects, Artificial Intelligence, Education, Administration, Learning
Development of an Android-based Machine Learning Student Problem Identification Tool Application at YPT Banjarmasin VHS

The era of the 5.0 Industrial Revolution demands that we develop automation and digitalization technologies in various aspects of life, including education. Even Guidance and Counseling teachers who manually analyze counseling instrument items need assistance in swiftly and accurately analyzing instruments for hundreds of students. This research aims to support counselors in analyzing the Student Problem Identification Tool Instrument, which consists of 225 items, through student’s Android devices, thereby enabling the prompt resolution of student issues. Through the stages of Research and Development (R&amp;D), the Student Problem Identification Tool Application is developed using the Multinomial Logistic Regression method within Machine Learning. This is achieved by replicating the capabilities of counselors based on analysis data from various previous instances of the Student Problem Identification Tool Instrument. Research outcomes reveal that the application achieves an accuracy rate of 100% when compared to manual analysis by counselors and application-based analysis for 30 students. The average performance test result is 85.00%, and the feasibility test result is 96.30%, categorizing it as "Highly Feasible." In conclusion, Machine Learning facilitates the effective and efficient analysis of extensive data when supported by quality training data and the appropriate method selection for problem-solving
English Teacher's Strategy in Teaching Writing

One of the English language skills needed by junior high school students to master is writing. The objective of this research is to find out the English teacher’s teaching strategies for teaching writing to seventh graders in SMP Miftahul Ulum Melirang and to describe the responses of students toward the strategy of writing skill of the seventh graders at SMP Miftahul Ulum. The design of the research is qualitative research. The population and sample of this study are English teachers at SMP Miftahul Ulum Melirang. The data collection methods for this study are observation and questioning Based on observation there were four meetings for learning to write, all teaching processes in class used PowerPoint and video as learning media to make the students easier to learn writing. English teachers used strategy in teaching writing by Cox theory (2012). This strategy made students more enthusiastic in learning; there were many good responses from the students. The material taught by the teacher is regarding Descriptive Text (people) and lyrics song; while the media used by the teacher are handbooks, lesson plans, PowerPoint, and videos. Furthermore, the activities in teaching writing consist of opening activities, core activities, and closing activities
The Use of Communication Strategies in The Context of English Teaching

In the context of English teaching and learning, teachers can employ communication strategies to facilitate students' comprehension of the study material. The aim of this study is to outline the categories of communication strategies used by an English teacher at SDN 2 Jatiluwih. This investigation takes a descriptive qualitative approach, focusing on an English teacher within the SDN 2 Jatiluwih setting. During the observations in the 6th grade English class in SDN 2 Jatiluwih, the teacher not only use simple English but also employed body language. Moreover, the students there were quite unique because they tended to use the Indonesian language. Therefore, the teacher, in this case, it was required to use various communication strategies in teaching. The theoretical framework for this study relies on Dornyei's communication strategies theory. The research outcomes reveal that the teacher employed five distinct communication strategies in the classroom to support student learning, namely stalling or time-gaining strategies (1.724%), literal translation (1.724%), prefabricated patterns (5.17%), non-linguistic signals (12.07%), and code-switching (79.31%).