Reviewerly/exHarmony huggingface dataset:
How the EndNote Gives Accurate In-Text Citations in Academic Writing

End Note is a reference management software programme among many others—such as Mendeley, Ref Works, and Zotero—for storing, managing, retrieving, and using sources for citation in an academic writing. This phenomenological study deals with how the use of the software gives accurate in-text citations of all types of references, such as, books, book sections, theses, journal articles, WebPages, and newspaper articles with reference to APA 7th style of academic writing. For this, I draw reflections on my own direct experience of using End Note for the purpose of citation as a practitioner, tutor, and trainer during the last four years. I categorize the in-text citations into themes on the basis of the way they can be accurately managed in MS (Microsoft) word file, and describe how to enter the input so that the resultant output gives accurate in-text citation with special reference to APA 7th. Drawing on the findings, I have concluded that the use of End Note helps to accurately and systematically manage the citation with very little manual adjustment, and thereby to accelerate and systematize the academic writing as a whole.
Pengembangan Bahan Ajar Berbasis E-Book Menggunakan Flip Pdf Professional pada Mata Pelajaran Sejarah Kebudayaan Islam

This research is motivated by the importance of developing E-book-based teaching materials in SKI lessons, because these lessons make students bored and less interesting. This study aims to determine the application of E-book teaching materials using Flip PDF Professional in Islamic cultural history subjects, and the effectiveness of E-book teaching materials using Flip PDF Professional in Islamic cultural history subjects. This research uses research and development. The sample in this study was using class X students at MAN 1 Trenggalek with a non-probability sampling technique. Data collection techniques and instruments used tests, distribution of e-book products, questionnaires or questionnaires, interviews, and documentation. Data analysis used the effectiveness test through the normality test and the assumption test using the paired t test and two independent samples (parametric). The results showed that the development of Flip PDF Professional teaching materials was carried out with reference to the development and research of ADDIE Analysis, Design, Development, Implementation, evaluation. Material development shows that the student learning outcomes for the experimental class posttest and the control class posttest have significant differences, thus the e-book teaching materials using Flip PDF Professional are effective in the subject of Islamic cultural history.&#x0D; Keywords: Development, E-book Based Teaching Materials, Flip Pdf Professional, Islamic Cultural History Subject.
Investigation of the Earth’s Albedo Using Meteorological Parameters over Maiduguri, Nigeria

The present study estimate and investigate the variation of albedo for Maiduguri situated in the Sahelian region of Nigeria, using meteorological data of global solar radiation obtained from the National Aeronautics and Space Administration (NASA) extending for a period between 1984 to 2021. Investigation was carried out on the variation of albedo with surface temperature, maximum wavelength, clearness index, global solar radiation, relative humidity and mean temperature. The study found that the estimated surface albedo exhibited a direct opposite relationship with the clearness index, an inverse relationship with the emitting Earth’s surface temperature and a direct relationship with the wavelength for the location. The highest value of 0.5125 and lowest value of 0.3344 were found in August and November respectively. The emitting Earth surface temperature ranged between 232.8674 K in August and 251.7177 K in November. This is in agreement with the standard emitting Earth surface temperature (255.0000 K). The values of the maximum emitting wavelength were found to be &gt; 4 indicating longwave radiation which is within the infrared region of the electromagnetic spectrum. The results from this study will be useful for the design of solar energy collectors and researches on atmospheric radiative transfer.
New Cryptocurrency Regulation in Lithuania and the European Union

The paper examines the major threats and related legal challenges posed by activities based on blockchain technology, such as cryptocurrencies, smart contracts, Decentralised Autonomous Organisations (DAOs), the Decentralised Finance System (DeFi), and Non-Fungible Tokens (NFTs). In the light of practical findings, the provisions of the Lithuanian Law on prevention of money laundering and terrorist financing and MiCA regulation are being analysed. The paper arrives at the conclusion that the new national law should effectively contribute to the prevention of cybercrimes, money laundering, terrorist financing, and violation of international sanctions. Nevertheless, a number of other issues typical for cryptocurrencies and other forms of utilisation of the blockchain technology remain unaddressed. Certain loopholes will be partly filled in by MiCA regulation. However, it will not create the required scope of legal certainty for other than cryptocurrencies forms of technology utilisation. On the basis of these findings, the paper puts forward proposals for the further development of the regulation of activities based on the blockchain technology.
Privacy-preserving Vertical Federated Broad Learning System for Artificial Intelligence Generated Image Content

Abstract Artificial intelligence generated image content generates desired image content according to given instructions. It is widely applied in digital marketing, video game design, and movie production. Efficiently detecting the quality of generated images is one of the key problems. A broad learning system is a feasible solution because it requires no complex parameter calculation and depth expansion. However, the broad learning system is built by centralized learning, so it may not take advantage of isolated feature data, which prevents broad learning systems from detecting isolated AL-generated image content. To address the above problem, this paper proposes a privacy-preserving vertical federated broad learning system for artificial intelligence generated image content (PVF-BLS). In PVF-BLS, the vertical federated architecture is introduced into the broad learning system to utilize isolated feature data and interactive data is masked by matrix masks for security. To further improve the security of PVF-BLS, this paper proposes a secure incremental learning algorithm based on matrix masks (ILA-MM) to update PVF-BLS. In ILA-MM, the interaction data is processed by matrix masks, which makes PVF-BLS more secure. Experimental results show that PVF-BLS outperforms traditional broad learning systems when the data is isolated.
Optimizing Immersion: Analyzing Graphics and Performance Considerations in Unity3D VR Development

Aims: Virtual reality (VR) is a new approach that gives users an immersive experience. VR applications frequently experience performance bottlenecks due to the high processing cost of displaying real-time animations multiple times (for both eyes) and the limited resources of wearable devices, performance optimization serves a significant part in VR application development. The goal of this paper is to investigate approaches and techniques available in Unity3D to improve the immersion of VR in virtual reality. This entails studying visuals and performance elements to design more fluid and engaging VR apps.&#x0D; Study Design: Quantitative analysis.&#x0D; Methodology: Systematic literature reviews, Consensus on the design space for VR-based education would greatly benefit future advances. To do this, we use a systematic mapping technique to the literature, extracting essential data from papers indexed in four academic online databases.&#x0D; Results: VR applications include extra aspects like graphics rendering and actual time animation, performance improvements for VR apps might differ significantly from those for standard software. Fully immersive virtual environments vary from standard virtual reality environments in that they can record entire body movements. This skill enables users to engage with other avatars, computer-controlled entities, and artifacts in the virtual world using their complete range of physical activities. VR performance optimization, in essence, relates to the methods, tactics, and procedures used to ensure that VR experiences function as smoothly as feasible.&#x0D; Conclusion: This optimization might be performed on different kinds of technology, particularly low-end devices, without sacrificing visual fidelity or immersive experience. VR is well-known for. It is critical to optimize visuals as well as performance in Unity3D VR apps to produce immersive and engaging experiences. Balancing great aesthetics with seamless performance necessitates a thorough grasp of Unity's features as well as a dedication to constant optimization.
Designing a Blockchain-Based Customer Loyalty Programme using Design Science Research Method

Loyalty programmes are crucial marketing tools for businesses to increase customer engagement and retention. These programmes, sponsored by enterprises, offer rewards, discounts, and other incentives to attract and retain customers. However, the lack of interoperability among loyalty programmes of different organisations can limit the customer’s ability to maximise the value of their loyalty points. In this study, we proposed the design and implementation of a blockchain-based platform using the design science research (DSR) method as a candidate solution to overcome the limitations of conventional loyalty programmes. Using smart contracts, the design enables organisations to embed all necessary attributes for their desired customer loyalty programmes in accordance with their policies. The designed platform provides a decentralised, transparent, and secure environment for the exchange of loyalty tokens between various organisations and customers. Using expert opinion methodology, we discussed the technical considerations and implementation of the blockchain-based loyalty programme platform, as well as its potential impact on the customer experience. Our findings suggest that the proposed platform can improve the interoperability of loyalty programmes using a universal token that creates more value for businesses and customers. The research contributes to the field of loyalty programmes and blockchain technology by proposing a platform that enable businesses to develop more effective and data-driven loyalty strategies, while providing customers with better value for their loyalty points.
Mass Media Perception And Utilization For Accessing Agricultural Information Among Farmers In Ogoja Agricultural Zone, Cross River State, Nigeria

The study focused on mass media perception and utilization for accessing agricultural information among farmers in Ogoja agricultural zone, Cross River State, Nigeria. The study specifically identified agricultural information needs of the farmers, ascertained the mass media available in the area, determined the extent of utilization of mass media by farmers, and established the relationship between mass media perception and utilization by farmers in the area. The study was conducted in Ogoja agricultural zone, the population consisted of all the registered farmers in the area, and the 3 extension blocks used, namely Ogoja, Obudu and Yala were randomly selected. The sample comprised 200 randomly selected respondents. Data were collected using a structured questionnaire and analyzed using percentages, mean, standard deviation, ranking and chi square statistics. The results revealed that farmers needs information on herbicides/pesticides (ranked = 1st), transportation (ranked = 2nd) and credit facilities (ranked = 3rd) etc. The predominant mass media available were mobile phone (ranked = 1st), television (ranked 2nd) and radio (ranked = 3rd) were the most extensively utilized in the area. The study found a significant relationship between mass media perception and utilization by the farmers. A comprehensive internet network coverage in the area and ICT training were recommended among others, to enhance mass media utilization.&#x0D;
Unveiling the Role of Explicit Metadiscourse Instruction, Language Proficiency, and Content Familiarity in EFL Reading Comprehension: A Comprehensive Review

This review comprehensively explores the integral role of explicit metadiscourse instruction and language proficiency and content familiarity in the context of reading comprehension among learners of English as a Foreign Language (EFL). Drawing upon a wide-ranging analysis of empirical studies spanning two decades (2003-2023), the review illuminates the intricate dynamics between these key components. It underscores how metadiscourse markers, as vital linguistic devices, significantly impact the learners' processing, comprehension, and retention of information. The importance of language proficiency emerges as a decisive factor, shaping the degree to which EFL learners can effectively utilize metadiscourse markers to enhance their reading comprehension skills. Moreover, the review accentuates the critical synergistic relationship between content familiarity and the efficacy of metadiscourse instruction, shedding light on how prior knowledge can optimize learning outcomes. It identifies significant gaps in existing research, emphasizing the need for a more integrated approach that simultaneously considers metadiscourse instruction, language proficiency, and content familiarity. The review concludes by advocating for greater emphasis on explicit metadiscourse instruction in EFL pedagogy, positioning this work as a synthesis of current knowledge and a guidepost for future research and instructional innovation in EFL reading comprehension.
Establishing a framework for the ethical and legal use of web scrapers by cybercrime and cybersecurity researchers: learnings from a systematic review of Australian research

Abstract The Internet has become an increasingly attractive location for collecting data about cyber threats, driven by the abundance of quality data available and accessible online. As such, researchers and practitioners have turned to automated data collection technologies (ADCT), including ‘web crawlers’ and ‘web scrapers’, to study these threats. The rapid proliferation of ADCT has meant directions for their ethical and legal operation have been slow to adapt, with no clear guidelines regulating their use for research. This article identifies the relevant ethical and legal frameworks guiding the deployment of ADCT in Australia for cybersecurity research. This is accomplished through a systematic review of research within this context, coupled with ethical and jurisprudential analysis. We argue that the use of ADCT can be both ethical and legal, but only where mitigating measures are implemented. We provide a series of practical directions to guide researchers and practitioners when navigating this novel terrain.
PENGARUH MEDIA GAMBAR DAN MOTIVASI TERHADAP HASIL BELAJAR IPA SISWA KELAS V SD NEGERI KECAMATAN TAPIAN DOLOK

Learning models and student characteristics are components that influence better student learning outcomes. This research aims to find out how the use of image media significantly affects the natural sciences learning achievement of students with high learning motivation compared to students with low learning motivation. The research will also investigate the relationship between the use of image media and learning motivation on Natural Sciences learning outcomes. This study was conducted at SDN 095557 and SDN 091608 Sinaksak in Tapian Dolok District in the 2021/2022 academic year, and the subjects were fifth-grade elementary school students. Descriptive experiments were conducted using a quantitative approach with a 2x2 factorial design. Researchers used a random sample of forty people for the research. The data analysis used was Analysis of Variance (ANOVA), followed by the t-test. The results of this research indicate that the use of learning image media significantly influences students' science learning outcomes. The sciencelearning outcomes of students with high learning motivation differ from those with low learning motivation. With a calculated result of sig = 0.00 &lt; sig = 0.05, the research results show that using learning image media and learning motivation impacts the science learning outcomes of class V students at SDN 095557 Sinaksak. This research concludes that learning image media and learningmotivation impact their science learning outcomes.
Classification Of Population Data On Status In The Family Based On Last Education And Work Using The Clustering Method (Case Study: Sei Prison Village Office)

Population data is structured individual or individual data through population registration, civil registration and population census activities. It is important to know population data because in making policies and planning regional or state development, population data is needed to describe the condition of an area. Population data include births, deaths, transfers or migration, population composition, population density and so on. This grouping is done so that population data that is already in the archives will be input into an application that will be designed to make it easier for parties who need data without having to look at the data that is still manual. The problems that exist are such as the increase in the number of residents in a city, village or even a district which is increasing while the population that has been recorded still does not have a job, such as status in the family, namely the head of the family is still there who does not work in terms of recent education can still be considered to get a job that matches the last type of education. From the research process conducted on 20 data, 3 groups were obtained, Cluster 1 contained 16 data, Cluster 2 contained 1 data, and Cluster 3 contained 3 data. And the most group obtained is cluster 1, there is education last high school, has a type of work that has not worked and status in the family of the head of the family.
Use of Case Based Reasoning (CBR) Methods to Diagnosis Diseases in Pregnancy

Diseases in pregnant women are diseases that many people need to pay attention to, because diseases that occur in pregnant women will not only endanger one life, but more than that. Hypertension currently occupies the 2nd position as a type of disease that threatens the lives of many pregnant women. The application of Case Based Reasoning (CBR) in diagnosing diseases that occur during pregnancy is motivated by the difficulty of consulting an obstetrician due to costs, time or even the limited number of doctors in a hospital. The use of CBR aims to solve new problems by adapting solutions to problems that occurred before. The expert system itself is one of the solutions to solve problems faced by users in the health sector, this system can minimize costs incurred to consult about diseases in pregnancy to specialist doctors. "Use of Case Base Reasoning (CBR) to Diagnose Diseases in Pregnancy" is expected to help the general public, especially pregnant women, make a simple diagnosis of symptoms and diseases in pregnancy.
The Grouping Of Types Of Tax Revenue In Binjai City Uses The K-Means Clustering Method Algorithm

Taxes are a major source of state revenue. Without taxes, most activities of the country are difficult to implement. The use of tax money includes ranging from employee shopping to financing various development projects. Public utilities such as roads, Bridges, schools, hospitals/center facilities, police stations are financed with tax returns. Tax money is also used for financing to provide a sense of security for all levels of society. Every citizen from birth to death enjoys facilities or government services all funded with tax money.
Clustering Disease on Settlements Inhabitant In place seedy With Use Clustering Method

Residents living in slum areas often face serious problems related to public health, where the prevalence of disease tends to be high and its spread is difficult to control. The impact of the formation of slums for the community is that safety is threatened, health deteriorates, and social conditions worsen, causing many diseases for people living in slums. Therefore, this study aims to identify patterns and clusters of diseases that exist in residential areas in slums Binjai city using clustering method. The K-Means Algorithm clustering method was chosen because it is able to group data based on similar characteristics, so that it can help identify diseases in a more focused and efficient manner, using the MATLAB application is also very appropriate in this problem so that it can produce output from data mining that can be used in decision making. future decisions. By utilizing the data mining process using the clustering method, clustering can be a problem of grouping diseases in slum settlements. Based on the results of trials with 20 sample data conducted with MATLAB obtained in cluster 1 DHF cases with high slums, Cluster 2 cases of vomiting with moderate slums and cluster 3 cases of diarrhea with moderate slums. The results of this study are expected to provide in-depth insight into disease patterns and clusters in residential areas in slums.
Diagnosing a Paper Dryer Malfunction in PT.Bamindo Agrapersada Using the Method DecisionTree

PT. BAMINDO AGRAPERSADA is a private company that processes bamboo into paper and sells it to consumers. In an industrial field, problems often occur to overcome damage to paper drying machines because mechanics are difficult to find and sometimes time is not possible so that operations are hampered while production targets must be completed immediately. Decision Tree which is a tree that is used as a reasoning procedure to get answers to the problems entered. Decision trees provide a way to present algorithms with conditional control statements that include branches in decision-making steps that lead to a favorable outcome. With the Decission Tree, it can minimize damage to the paper drying machine and help solve problems in the PT. BAMINDO AGRAPERSADA industry.
ANALISIS KESALAHAN MENULIS TANDA BACA PADA KARANGAN DESKRIPSI KELAS IV MI HUDAATUL UMAM KABUPATEN TANGERANG

This study aims to determine punctuation writing mistakes that are often made by students in writing description essays at MI Hudaatul Umam. The method used in this study is a descriptive qualitative method, which is a method that involves researchers directly observing the object being studied. The results of this study were found in writing capital letters, with a percentage of 56.32%. The error is seen at the beginning of sentences, both the beginning of the sentence and the turn of the sentence. This indication often occurs due to the familiarity of the students themselves, also students are not trained to write capital letters at the beginning of words. In punctuation, the most errors are in the error of omitting periods at the end of sentences that are not question or exclamation sentences with a percentage of 42.78%. The indication that causes this error to occur is the lack of accuracy of students in placing periods at the end of sentences, also students do not understand the rules of punctuation placement.