Reviewerly/exHarmony huggingface dataset:
Analysis of Factors that Inhibit Early Reading Learning in Elementary School Students in MIS Al-Afkari Deliserdang

The purpose of this study was to describe the forms of difficulties faced by Class I students at MIS AL-Afkari Deliserdang that hindered early reading. This research is an observational study. Data collection techniques, using observation, interviews, and documentation. The data obtained were analyzed descriptively after being reduced (data reduction), and tested for validity through a data credibility test. The results showed that the types of difficulties faced by Class I students at MIS AL-Afkari Deliserdang that could potentially hinder learning to read the beginning were as follows: 1) students had difficulty reading the alphabet with proper pronunciation, students had difficulty showing and mentioning vowels, students had difficulty showing and mentioning consonants, students find it difficult to name some combined sounds of vowels and consonants, students find it difficult to spell the syllables that are instructed, 2) the factors that hinder students in Beginning Reading Difficulties in Class I students at MIS AL-Afkari Deliserdang are intellectual factors, factors physiological, environmental factors including parents, and psychological factors. The solution is that parents must really accompany their children when learning and teachers innovate in learning such as using suitable media and methods for learning to read early.
Remote Sensing Image Super-Resolution Using Texture Enhancing Generative Adversarial Network

&lt;p&gt;Single image super-resolution (SISR) brings excellent improvement in remote sensing applications, which has been widely studied in recent years. A method named TFSRGAN of remote sensing single image super-resolution based on generative adversarial network is proposed in this paper to address the problems of poor reconstruction visual quality and smooth details in traditional algorithms. In the proposed framework, s dense residual connection method is proposed to fuse the deep features from each residual block based on the SRGAN network, and the channel attention mechanism is added into the residual block to combinate the channel information. In addition, the network employs an edge extractor to divide the low-resolution image into low-frequency image and high-frequency image as the input of generator to improve the effect of texture reconstruction. Extensive comparison experiments were performed using AID, UCAS_AOD and China Gaofen-1 datasets, the SR results demonstrate that the proposed TFSRGAN framework outperforms the state-of-the-art algorithms including VDSR, SRGAN and ESRGAN in terms of objective evaluation metrics and subjective visual perception. The ground targets detection experiments represent that the proposed TFSRGAN can significantly improve the effect in remote sensing super-resolution application.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
Interval Methods in Knowledge Representation

International Journal of Uncertainty, Fuzziness and Knowledge-Based SystemsVol. 31, No. 05, pp. 889-890 (2023) No AccessInterval Methods in Knowledge RepresentationVladik KreinovichVladik KreinovichDepartment of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USAhttps://doi.org/10.1142/S021848852397005XCited by:0 (Source: Crossref) Previous AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail Remember to check out the Most Cited Articles! Check out our titles on Fuzzy Logic & Z-Numbers With a wide range of areas, you're bound to find something you like. FiguresReferencesRelatedDetails Recommended Vol. 31, No. 05 Metrics History PDF download
Improving national security through accountability

The cyber security of an organisation starts with the software it uses. And that places a responsibility on software vendors to ensure that the code they ship is intrinsically secure. And that security can't be added as an afterthought – it needs to be integrated deep into the development process.
Embracing an outcome-based approach to cyber security

Cyber security is often seen as an activity separate from an organisation's main business processes. It is something that only comes to the fore when an incident occurs – which may be too late. And this can create a gap between the true security needs of the organisation and its security posture. In contrast, outcome-based security creates direct links between business goals and security requirements.
Incident response: are alert levels now unmanageable?

Computer Fraud & SecurityVol. 2023, No. 10 The SandboxIncident response: are alert levels now unmanageable?Brian MartinBrian MartinIntegrity360Search for more papers by this authorBrian MartinPublished Online:31 Oct 2023https://doi.org/10.12968/S1361-3723(23)70050-XAboutSectionsView articleView Full TextView EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article References 1. Coutinho, S et al.. ‘Cyber security skills in the UK labour market 2023’. Department for Science, Innovation and Technology (DSIT). Accessed Oct 2023. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1173325/Cyber_security_skills_in_the_UK_labour_market_2023.pdf Google Scholar2. ‘Global Incident Response Threat Report’. VMware, 2022. Accessed Oct 2023. www.vmware.com/content/dam/learn/en/amer/fy23/pdf/1553238_Global_Incident_Response_Threat_Report_Weathering_The_Storm.pdf. Google Scholar3. ‘Gartner predicts nearly half of cyber security leaders will change jobs by 2025’. Gartner, 22 Feb 2023. Accessed Oct 2023. www.gartner.com/en/newsroom/press-releases/2023-02-22-gartner-predicts-nearly-half-of-cyber security-leaders-will-change-jobs-by-2025. Google Scholar FiguresReferencesRelatedDetails 1 October 2023Volume 2023Issue 10ISSN (print): 1361-3723ISSN (online): 1873-7056 Metrics History Published online 31 October 2023 Published in print 1 October 2023 Information© MA Business Ltd.
The challenges of data sovereignty

Any companies still adopting a tech-first strategy for cyber security are entirely misunderstanding the intentions of global data protection regulation – and as a result are leaving both individuals and the business dangerously exposed. There are broader issues of data governance, including data sovereignty, that involve the whole of the organisation's management team.
Digital identity – creating a unified system

Network SecurityVol. 2023, No. 10 FeaturesDigital identity – creating a unified systemFrederik MennesFrederik MennesOneSpanSearch for more papers by this authorFrederik MennesPublished Online:31 Oct 2023https://doi.org/10.12968/S1353-4858(23)70049-4AboutSectionsView articleView Full TextView EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article References 1. ‘New legislation set to make digital identities more trustworthy and secure’. Department for Digital, Culture, Media & Sport (DCMS), 10 Mar 2022. Accessed Oct 2023. www.gov.uk/government/news/new-legislation-set-to-make-digital-identities-more-trustworthy-and-secure. Google Scholar2. ‘Tony Blair and William Hague call for digital ID cards for all’. BBC News, 22 Feb 2023. Accessed Oct 2023. www.bbc.com/news/uk-politics-64729442. Google Scholar3. ‘British businesses to save billions under new UK version of GDPR’. Department for Science, Innovation and Technology (DSIT), 8 Mar 2023. Accessed Oct 2023. www.gov.uk/government/news/british-businesses-to-save-billions-under-new-uk-version-of-gdpr. Google Scholar FiguresReferencesRelatedDetails 1 October 2023Volume 2023Issue 10ISSN (print): 1353-4858ISSN (online): 1872-9371 Metrics History Published online 31 October 2023 Published in print 1 October 2023 Information© MA Business Ltd.
HUBUNGAN POLA ASUH ORANG TUA TERHADAP MOTIVASI BELAJAR SISWA

The reason for this research is to; (1). Knowing the causes of decreased student motivation; (2). Knowing the implications of parenting patterns on students' learning motivation, and (3). Analyzing the urgency of parenting parents to student learning motivation. This study uses qualitative methods and descriptive analysis research types. Sources of data were obtained from literature studies by citing theories from various scientific journals, printed books, and e-books. Research Results Show (1). Parenting style is divided into three; authoritarian, permissive, authoritative (2). The application of each parenting pattern has a positive and negative impact on student learning motivation (3). Student motivation is further increased in the application of authoritative parenting
Weight based Approach for virtual machine migration in Cloud Architecture

The cloud computing is the architecture which is used to execute the cloudlets on the virtual machines. The most applicable virtual machines are selected on the basis of execution time and failure rate. Due to virtual machine overloading execution time and energy consumption is increased at steady rate. In this paper, weight based technique is applied in which weight of each virtual machine is calculated and virtual machine which has maximum weight is selected on which cloudlet is migrated. The performance of proposed weight based is tested on cloudsim. It is analyzed that weight based algorithm performs well as compared to check pointing algorithm.
Implementation of Cyber Security in Corporate Sector of Pakistan

We live in a time when knowledge is easily accessible and people are connected throughout the world. The technological improvements that modern states use to advance include streamlined online bill payments, improved healthcare systems, sophisticated transportation networks, the use of artificial intelligence, cutting-edge communication systems, and technological warfare. Despite the fact that technology has made it possible to break down geographical borders, the widespread use of technology has led to the emergence of new challenges and concerns. Hacking, bank fraud, money laundering, data breaches, unauthorized acquisition of state secrets, and targeted attacks on critical infrastructure are just a few of the criminal activities and threats that plague the digital world today. These crimes have all emerged as major facets of modern cyber warfare. Such threats can affect both wealthy and developing countries, creating a challenging situation for national security. Among these countries, Pakistan and other emerging nations are particularly at risk. The nation has a sizable population of business users who are unfamiliar with information technology, which makes it more difficult for governmental and legislative authorities to regulate the nation's digital environment. Recent catastrophic cyberattacks on Pakistani institutions' most essential websites have successfully breached significant digital installations. Legislators in Pakistan have responded by introducing cyber legislation, but it doesn't seem like they fully address the variety of online threats. This study paper is focused on creating a framework for the adoption of cyber security in Pakistan's corporate sector and investigating workable solutions to serious cybersecurity issues. In order to generate findings, a qualitative research methodology was used, gathering information from both primary and secondary sources. Finally, the study makes a number of suggestions on how Pakistan's corporate sector may implement cyber security.
The effects of structural reforms on economic growth

This study investigates the effects of structural reforms in fiscal, financial, trade, and real sectors on economic growth for 56 countries within the IMF-Supported Program over the 2002-19 period. Using a novel database (IMF Monitoring of Fund Arrangements-MONA), it constructs new structural reform indexes for each sector employing the Z-score approach. The present study highlights that all structural reforms except for real sector reforms in all models, constructed based on the extended Cobb-Douglas production function, have a positive and statistically significant impact on economic growth. The robustness of the models is confirmed by using two different structural reform indexes for each sector and two different estimators considering cross-sectional dependence. Empirical findings point to the structural reforms being potentially key factors that provide strong long-term growth performance for countries. Hence, along with the relevant traditional policies and sufficiently developed institutions, policymakers should extend the structural reforms to lift potential growth and provide lasting economic recovery.
Introduction

We start this chapter with a few words about the need for this book. Almost 20 years ago, I started doing Windows software diagnostics full time as a member of the technical support and escalation team at a large global software vendor. In addition to crash and hang dump analysis, the job required analysis of software traces similar to that of Process Monitor log format with messages from hundreds of processes and thousands of threads totaling millions of lines (Figure 1-1). Gradually I became aware that we need a similar pattern-driven system as I devised for memory dump analysis. However, after a few patterns, such as Periodic Error, I was stuck devising more. At this time, through my voracious independent reading, I accidentally became acquainted with narratology, a discipline that studies narration and narrative stories. So this became the foundation for what I later named Software Narratology, a new approach to the study of software narrative, stories of computation. Viewing software traces as narratives helped devise general analysis patterns to structure trace and log analysis independent of OS and products. Although this book teaches some analysis patterns in a Windows context, you can apply them to your specific environment and product domain problems. Some examples are illustrated with Process Monitor and Event Tracing for Windows because they are widely used and not tied to specific products. In addition to native logging, Linux has LTTng tracing. All these tracing frameworks produce trace and log files with conceptually similar formats.
Preduzetničke kompetencije vaspitača u kontekstu profesionalnog osposobljavanja

Whether entrepreneurship competences are considered as competences of the entrepreneur's professional action (career determination) or general transferable competences necessary for the action of every person (competence components of functional action), their development has its basis in childhood. Therefore, supporting the development of entrepreneurship characteristics in children during preschool education is necessary. The first systematic education of preschool children is realized by preschool teachers. The importance of preschool educators for the development of entrepreneurship competencies in preschool children is discussed in the paper. The specifics of the entrepreneurship competence of preschool educators, who should act as models to develop the entrepreneurship competencies of their preschool pupils/children, are also presented. A holistic approach to the entrepreneurship training of educators is proposed to develop their entrepreneurship competencies and to develop methods and approaches for the entrepreneurship education of preschool children.
Forensic Analysis of Contents in Thumbnails Using Transfer Learning

Thumbnails accelerate the concise description of a collection of images that iterate through large datasets till it trains our deep learning model to capture the text-whitened thumbnails. Many court cases and forensic investigations have involved thumbnail pictures within laptops or mobile devices. Millions of thumbnails are often ready for digital forensics experts to export. Machine learning can quickly help identify an investigation’s targets. Text or objective recognition is a primary study solution for document digitization and forensic analysis. Inspired by the recent success of Transformer in many applications, in this paper, we adopt design transfer learning as an effective method of achieving excellent performance with a noisy training of dataset of thumbnails. This deep learning model aims to investigate the pre-trained model in the Torch Vision package employing tensors and Cuda-GPU parallel computing to emphasize the OCR (Optical Character Recognition) system engine. We report the preliminary results of our methods to help digital forensics experts to identify their targets robustly and efficiently.
STEM Activities in Working with Children of Early Ages

Education is a vital part of any society, and it plays a critical role in shaping the future of young learners. Because traditional teaching methods are not always effective in engaging and motivating students, especially in an increasingly digital and fast-paced world, teachers should develop and implement new, innovative teaching strategies that promote and involve active learning. The STE(A)M concept is also part of the modern teaching paradigm and represents the fusion of science, technology, mathematics, engineering and art. At the same time, STEM is much more than any individual subject. It is the culture we should be building with children. At the core of this concept are active practical work, children’s engagement and exploratory learning, based on experimental or project engagement and work. STEAM is not only an introduction to science, scientific phenomena and concepts, but also children’s attitude towards creativity, challenges, solving challenges and ways of reaching (finding) solutions. In this paper, we present the essence and specifics of organizing STEAM activities with children of early ages, the importance and necessity of applying such a way of working in early childhood and the possibilities of organizing STEAM activities with children in preschools.
Credit Card Fraud Detection on Original European Credit Card Holder Dataset Using Ensemble Machine Learning Technique

The proliferation of digital payment methods facilitated by various online platforms and applications has led to a surge in financial fraud, particularly in credit card transactions. Advanced technologies such as machine learning have been widely employed to enhance the early detection and prevention of losses arising from potentially fraudulent activities. However, a prevalent approach in existing literature involves the use of extensive data sampling and feature selection algorithms as a precursor to subsequent investigations. While sampling techniques can significantly reduce computational time, the resulting dataset relies on generated data and the accuracy of the pre-processing machine learning models employed. Such datasets often lack true representativeness of real-world data, potentially introducing secondary issues that affect the precision of the results. For instance, under-sampling may result in the loss of critical information, while over-sampling can lead to overfitting machine learning models. In this paper, we proposed a classification study of credit card fraud using fundamental machine learning models without the application of any sampling techniques on all the features present in the original dataset. The results indicate that Support Vector Machine (SVM) consistently achieves classification performance exceeding 90% across various evaluation metrics. This discovery serves as a valuable reference for future research, encouraging comparative studies on original dataset without the reliance on sampling techniques. Furthermore, we explore hybrid machine learning techniques, such as ensemble learning constructed based on SVM, K-Nearest Neighbor (KNN) and decision tree, highlighting their potential advancements in the field. The study demonstrates that the proposed machine learning models yield promising results, suggesting that pre-processing the dataset with sampling algorithm or additional machine learning technique may not always be necessary. This research contributes to the field of credit card fraud detection by emphasizing the potential of employing machine learning models directly on original datasets, thereby simplifying the workflow and potentially improving the accuracy and efficiency of fraud detection systems.
MENINGKATKAN KEAKTIFAN BELAJAR PENDIDIKAN AGAMA KATOLIK MELALUI METODE KOOPERATIF TIPE KANCING GEMERINCING BAGI SISWA KELAS X SOSIAL 1 SMAN 1 MALAKA TIMUR TAHUN AJARAN 2022/2021

This research was conducted to determine the quality of the process of implementing the rattling button type cooperative method which can increase learning activity in Class This research includes classroom action research (PTK) which consists of cycle I and cycle II, each of which has four stages, namely: planning stage, implementation stage, observation stage and reflection stage. The techniques used in data collection are observation, tests and research documentation. The results of the research show that the application of the rattling button type cooperative method can increase learning activity in Catholic religious education, where in cycle I student activity was 75.53% with fairly good criteria, and in cycle II student activity increased 95.92% with very good criteria. Based on the research results obtained, the researchers concluded that through the cooperative method of the jingling button type can increase the learning activity of Class X Social 1 students at SMAN 1 East Malaka for the 2022/2023 academic year.
Analysis of Writing in General-Purpose Korean Textbooks: Focusing on the Current Status of Writing Genre Education

This study selected three Korean textbooks for general-purpose learners to analyze the current status of writing genre education by analyzing the writing syllabus, genre knowledge, and genre type by proficiency in these Korean textbooks. The results are as follows. The current status of writing genre education in textbooks A, B, and C was very different, and the information on writing genre provided in these textbooks was inadequate. However, the genre types in Korean textbooks in current use were more diverse than reported by Lee Mi-hye (2013). Moreover, genre types such as Internet bulletin boards, blogs, and text messages that are widely used in contemporary everyday life have also been presented in textbooks. Nevertheless, it was confirmed that the genre types were not systematically implemented in Korean textbooks according to proficiency. As a future task, deep discussions of how to present writing syllabus and genre knowledge in textbooks and arrange writing genre types by proficiency should be made first so that genre-oriented writing education can be effectively implemented in Korean textbooks for general-purpose learners.
On General Language Understanding

Natural Language Processing prides itself to be an empirically-minded, if not outright empiricist field, and yet lately it seems to get itself into essentialist debates on issues of meaning and measurement ("Do Large Language Models Understand Language, And If So, How Much?"). This is not by accident: Here, as everywhere, the evidence underspecifies the understanding. As a remedy, this paper sketches the outlines of a model of understanding, which can ground questions of the adequacy of current methods of measurement of model quality. The paper makes three claims: A) That different language use situation types have different characteristics, B) That language understanding is a multifaceted phenomenon, bringing together individualistic and social processes, and C) That the choice of Understanding Indicator marks the limits of benchmarking, and the beginnings of considerations of the ethics of NLP use.