Reviewerly/exHarmony huggingface dataset:
Analisis Kesalahan Numerasi Siswa Kelas 3 MI dalam Penulisan Lambang Bilangan Ribuan

The concept of recognizing number symbols is very important to understand because it is a basic concept in mathematics. Mathematical concepts that need to be introduced to early childhood are the concepts of numbers, calculation patterns, measurements, geometry, strategies in problem solving games. Numeral serves to concretize the concept of numbers that are still abstract. This research is a type of qualitative research with research subjects as many as 5 third grade students. In elementary school,, there are students who cannot pronounce and write number symbols correctly. This may be an indicator of a student having difficulty in numeracy.
IOT BASED EARLY FLOOD DETECTION AND ALERT

Natural calamities are increasing day by day everywhere in the world it is affecting the economy of the country.Economy and the growth of the country depends upon the agriculture of the country by the natural calamities like flood which is mainly affecting the agriculture and which in turn resulting in the financial stability of the farmers as well as the country's economy.Many regions are continuously affecting every year so to control these or to take precautions before it happens we need the help of the new technology.This project proposes a very much utilized for monitoring the water level, flow variations in the river using sensors and it can be used in the dams and reservoirs.We can prevent natural disaster caused by the flood, with the aid of an IOT based early flood related parameter monitoring and detection system.First the hardware is placed in the flood prone areas, if the water level rises it gives alert messages immediately.In summary, it will help in the community in taking quick decisions and planning against the disaster.
Devloping and applying a set of criteria for monitoring experiential and career guidance activities according to the 2018 General Education Program

Research results on organizational management of experiential and career guidance activities in high schools has evidently demonstrated the role of supervising these educational activities. Through theoretical and practical research, related concepts have been presented and analyzed in order to clarify the viewpoints and duties of supervision in the management and organization of experiential and career guidance activities for high school students. Since then, a set of criteria for monitoring experiential and career guidance activities in high schools has been developed and proposed to be applied in practice. This set of criteria will contribute to improving the management efficiency of the organization of experience and career guidance activities, meeting the requirements of comprehensive education, forming the quality and capacity for students under the 2018 General Education Program. The development and application of a set of criteria to monitor experiential and career guidance activities is affected by many factors and is still quite new to Vietnamese education today
Validation of Problem Solving and Problem Finding Creativity Test based on Remote Association Theory

The purpose of this research is to develop a ‘Problem Solving and Problem Finding Creativity Test based on Remote Association Theory’ and to verify its reliability and validity. It was the application of two Mednick (1962) remote associative theories and problem finding, which were most importantly considered in the development of new and different creativity test. For this reason, after conducting inspections on 327 elementary school students in the 5th and 6th grades, 9 questions (8 problem-solving types and 1 problem-finding type) developed based on the analysis of previous research and the opinions of experts were conducted. , Various analyzes have shown the proper reliability. Correlation analysis with KEDI, TTCT, and K-RAT was conducted to verify the concurrent validity and discrimination validity of the creativity test, and as a result, the possibility as a test tool with differentiation from the conventional test tool was confirmed. Also, it was developed by deriving that there is a significant difference between a group of students of the same age and teachers nominated as highly creative and a general group, and a group of gifted students and a group of general students. We verified the predictive validity of the creativity test. It is expected that the findings of this research will be useful in many upcoming creativity-related researches, qualitatively creative human resource development, and educational settings for gifted student identification.
An Empirical Study on the Impacts of UTAUT2 in Online Learning Platform

In recent years, due to the rapid development of information technology, online learning platforms are attracting many people's attention. The purpose of this study is to conduct empirical research on the factors affecting the use intention the online learning platform. To this end, data related to the online learning platform were reviewed and analyzed, and theoretical backgrounds and hypotheses were established by analyzing the expanded technology acceptance and integration theory and research models of previous studies. Through the expanded integrated technology acceptance model (UTAUT2), it is intended to analyze the relationship between performance expectancy, effort expectancy, social influence, and price value on use intention and use behavior. In addition, the effect relationship of perceived risk on use behavior was also analyzed. In this study, SPSS 23.0 was used for basic statistical analysis, and the Smart PLS 4.0 statistical package was used for hypothesis verification. A survey was conducted on 260 people using online learning platforms. As a result of confirming the relationship between performance expectancy, effort expectancy, social influence, price value, perceived risk, use intention, and use behavior, performance expectancy, effort expectancy, social influence, and price value had a positive effect on use intention. Perceived risk had a negative effect on use behavior, and use intention had a positive effect on use behavior.
Knowledge Graph: A Survey

This survey discusses the concept of knowledge graphs, including their construction, extraction, and applications. Various tools such as Zotero, Web of Science, Google Scholar, EndNote, and VosViewer are used to analyze and visualize collected data. A Boolean query mechanism ensures the gathered material is relevant to the study. The discussion includes studies on relation extraction using graph neural networks, the application of knowledge graphs in biomedical research, and the use of knowledge graph embedding in healthcare. These studies highlight the growing importance of knowledge graphs in managing and representing complex information. Notable studies discussed include the role of knowledge graphs in connecting related medical information, the application of knowledge graph technology in healthcare, and the potential benefits and limitations of using knowledge graph embedding in biomedical data analysis. This survey paper provides valuable insights into the growing importance of knowledge graphs in managing and representing complex information and how they can help provide new insights into various fields. It suggests potential future directions for research in this area, highlighting the importance of continued exploration and innovation to realize the potential of knowledge graphs fully
A dataset of dairy cow diseases for knowledge graph construction in China

As a key area of China’s animal husbandry development, dairy farming plays a pivotal role in promoting agricultural structural adjustment and driving social and economic development. The occurrence of dairy cow disease not only brings great economic losses to animal husbandry, but also seriously threatens food safety and human health. The task of disease prevention and control is important and arduous. The construction of dairy cow disease knowledge graph is the basis of disease prevention and control, which is of great significance to the development of animal husbandry. In the dataset of dairy cow diseases in China for knowledge graph construction, based on books and websites of dairy cow disease types, we carried out data collecting, cleansing, organizing and merging to obtain 261 data of 5 types of dairy cow disease, including 42 infectious diseases, 16 kinds of parasitic diseases, 111 kinds of internal diseases, 54 kinds of surgical diseases, and 38 kinds of obstetric diseases. This dataset can be used to construct a knowledge graph of dairy cow diseases, and provide basic data support for the construction of dairy cow disease prevention and control in China.
DIGITAL CURRENCY, THE FINANCIAL INCLUSION, BENEFITS, AND CHALLENGES IN THE IMPLEMENTATION OF ENAIRA

Financial inclusion makes sure that all people and enterprises have access to formal financial services that are both accessible and useful for enhancing welfare.Since digital money is domiciled with the CBN, the expectation is that it will help to contain inflation and make transactions easier without requiring the use of cash or trips to the bank.Nigeria, which has been labeled as immature because of its ongoing electrical crisis, corruption, and issues with internet accessibility, is likely to experience difficulties while using virtual wallets for digital currency that are registered under the CBN.Researchers are now wondering the feasibility, the benefits, and the challenges of the eNaira.The paper, therefore, examined digital currency, the financial inclusion, benefits, and challenges in the implementation of the eNaira.The scope of literature examines in this review include journal article and web document covering a period of 2015 -2023.It the study concludes that eNaira presents opportunities and challenges for the Nigerian government, the CBN, the financial sectors, individuals, and other stakeholders.It equally recommends amongst other things that financial education needs to be given attention, particularly in the area of using digital currencies, since this will promote inclusion among rural people.
PENGARUH PENGGUNAAN MEDIA E-BOOKLET TERHADAP HASIL BELAJAR SISWA SEKOLAH DASAR

Abstract: This study aims to determine the effect of using e-booklet media on student learning outcomes in theme 6 sub-theme 2 class III SD Negeri 104201 Kolam T.A 2022/2023. This type of research uses a quasi-experimental method. Data was collected using multiple choice instruments. The data analysis technique was a two-sample T-test assisted by the SPSS 22 application. The results of the study using a two-sample T-test obtained a significant value (2 tailed) 0.000 &lt;0.05 with a significant level (2 tailed) &lt; 0.05, proving that Ha is accepted and Ho rejected, meaning that there is an effect of using e-booklet media on student learning outcomes in theme 6 sub-theme 2 class III SDN 104201 Kolam. Keyword: Media E-booklet, Learning Outcomes, Thematic.Abstrak: Penelitian ini bertujuan untuk mengetahui pengaruh penggunaan media e-booklet terhadap hasil belajar siswa pada tema 6 subtema 2 kelas III SD Negeri 104201 Kolam T.A 2022/2023. Jenis penelitian menggunakan metode quasi experiment. Data dikumpulkan menggunakan instrumen pilihan ganda. Teknik analisis data dengan uji T dua sampel berbantuan aplikasi SPSS 22. Hasil penelitian menggunakan uji T dua sampel diperoleh nilai signifikan (2 tailed) 0,000 &lt; 0,05 dengan taraf signifikan (2 tailed) &lt; 0,05, membuktikan bahwa Ha diterima dan Ho ditolak, artinya terdapat pengaruh penggunaan media e-booklet terhadap hasil belajar siswa pada tema 6 subtema 2 kelas III SDN 104201 Kolam.Kata Kunci: Media E-booklet, Hasil Belajar, Tematik
Development of Blended Learning-Based Science Module on Sound Material to Improve Learning Outcomes of Fourth-grade Elementary School Students

This research is motivated by the lack of learning resources that can support learning during the learning process, both face-to-face and independently, which causes a decline in student learning outcomes. This study aims to design and analyzing the effectiveness of blended learning-based science learning modules on sound material to improve learning outcomes of fourth-grade elementary school students. This study is a research and development (R D) by Borg and Gall, with an operational test design using a pretest-posttest control group design. There are 33 students in an experimental class and 31 students in a control class in grade IV. The results showed the module is valid and effective with good criteria, for the experimental class with pretest results of 53.5 and posttest of 71.5 with n-gain of 0.47 medium criteria. Meanwhile, in the control class, pretest results were obtained of 53.1 and posttest of 61.8 with n gains of 0.19 low criteria. Compared to the control group, the experimental group saw a greater improvement in learning outcomes in the test of the materials' efficacy. The blended learning module created for this research can be used as a resource for both students and educators to help them reach their educational goals.
Implementation of White Hat SEO-Based Digital Incubator Platform

Advances in information technology are developing rapidly in various areas of life. The Internet is one of the most influential information and communication technologies. A website, one of the Internet technologies, is not only a medium of information, but also a process that supports a company's business. No effect. SEO (Search Engine Optimization) is one of the advertising methods using search engine optimization so that the website created by our company will be displayed on the top of the search engine page or on the first page (first page). This research was initially conducted on the Business Incubator website, which did not follow his SEO techniques. Then some steps were also taken by implementing on-page SEO techniques such as title tag, content, meta keywords, keyword optimization for meta description and sharing on social media. This point. A test as a benchmark for successful implementation of SEO techniques. As a result of implementing SEO techniques, his website's SERP (Search Engine Results Pages) on search engines increased and in the second month he successfully landed on Google's second page and was indexed by Google Search. The first page was not successful in March.
Quality Assessment of Digital Resources in Education

The use of new information and communication technologies (ICT) in the field of training, where the ability to self-train, inform, and communicate via different technologies, is now becoming an essential condition for adapting to the programs taught.Moreover, the use of technologies for learning is currently a key skill to enable pedagogical actors to be more successful in an educational context.The problem that arises is how to ensure good management of the credibility of the digital resources used by learners, given the absence of central evaluation processes that constitute a risk for the reliability, credibility, and pedagogical value of the content used for teaching and learning.It is in this perspective that our article proposes an evaluation grid for digital training content that can be used by teachers and students.The proposed evaluation criteria have been inspired by a set of experiences and works of some authors who have worked on models of evaluation of the pedagogical quality of digital sources.
A Path Signature Approach for Speech-based Dementia Detection

People who have dementia show a decline in their speech abilities. In speech-based dementia detection, the difficulty has remained the representation of an individual's sequential temporal variation of speech is related to dementia symptoms with fix-length features. In this paper, a novel feature extrac- tion method is proposed for extracting fix-length features from unfixed-length audio recordings for dementia detection. When diagnosing dementia, an automatic speech recognition (ASR) system is necessary for extracting linguistic information when constructing an automatic dementia detection system. This paper uses wav2vec2.0, a self-supervised end-to-end ASR system, to achieve such a goal. Similar to the pipeline ASR system, which has been used for extracting the sequential speak-and-pause patterns related to dementia using estimated time alignment information, we propose using character-level transcripts to extract speak-and-pause patterns. Path signature technology, which can represent a sequential feature with a trajectory in the un-parameterised path space, is proposed to describe speak- and-pause patterns embedded in character-level transcripts into character path signatures. Similarly, the variable-length embed- ding matrices extracted from wav2vec2.0's contextual layers are also represented with their acoustic path signatures. The exper- iments are designed based on three publicly available datasets: DementiaBank, ADReSS and ADReSSo. The results show that: (1). The distinguished information embedded in the character path signature is visualised for dementia detection; (2). The acoustic path signature and character path signature individually can show superior performance on all three publicly available datasets. (3). Combining the character path signature with the acoustic path signature can considerably increase performance over the ADReSSo dataset.
Geometric Deep Neural Network Using Rigid and Non-rigid Transformations for Landmark-based Human Behavior Analysis

Deep learning architectures, albeit successful in most computer vision tasks, were designed for data with an underlying Euclidean structure, which is not usually fulfilled since pre-processed data may lie on a non-linear space. In this paper, we propose a geometric deep learning approach using rigid and non-rigid transformations, named KShapenet, for 2D and 3D landmark-based human motion analysis. Landmark configuration sequences are first modeled as trajectories on Kendall's shape space and then mapped to a linear tangent space. The resulting structured data are then input to a deep learning architecture, which includes a layer that optimizes over rigid and non-rigid transformations of landmark configurations, followed by a CNN-LSTM network. We apply KShapenet to 3D human landmark sequences for action and gait recognition, and 2D facial landmark sequences for expression recognition, and demonstrate the competitiveness of the proposed approach with respect to state-of-the-art.
Application of Proof by Contradiction in Solving Junior High School Mathematics Competition Questions

Mathematics competition is an important platform to improve students' thinking and ability, so the questions of mathematics competition are more difficult and more comprehensive than ordinary questions.The examination of proof by contradiction in junior high school mathematics competitions can improve students' thinking and ability in many aspects and has an educational value that cannot be ignored.The author gives examples to explore the specific application of proof by contradiction in solving junior high school mathematics competition questions.Analyze its investigation value in the competition.
Distributed Multi-Modal Classification Approach for Breast Cancer Prediction Based on WBCD Through Machine Learning Paradigms

Cancer death is one of the main challenges that the mankind is facing in developing countries.Although there are many strategies to prevent cancer in the first place, some types of cancer remain incurable.Breast cancer is one of the most common types of cancer and its early detection is crucial for its treatment.One of the most crucial aspects of breast cancer treatment is the accurate diagnosis.Numerous studies have been published in the literature to predict the type of breast cancer.Data on breast cancer tumors from Dr. William H. Wahlberg of the Hospital of the University of Wisconsin was used to predict breast tumor type in this study.This dataset was subjected to data visualization and machine learning techniques, such as Distributed logistic regression, Distributed k-nearest neighbors, and distributed naive Bayesian.The aim of this study was to perform a comparative study of breast cancer detection and diagnosis using data visualization and machine learning tools.The results obtained using the Distributed logistic regression model with all features included show the best classification accuracy, and the proposed approach reveals an improvement in accuracy.To achieve this, machine learning classification methods have been used to tune a function that can predict the discrete class of new entries, and modern technologies with new hybrid frameworks and models have been introduced for higher accuracy and to store large amounts of data and security.
IIoT Supporting Technologies: Evolution, Concepts, and Challenges

“Necessity is the mother of invention” is a saying that very much applies to the evolution of technologies.
Utilizing Block chain in the Internet of Things for an Effective Security Sharing Scheme

Organizations and other institutions have recently started using cloud service providers to store and share information in light of the Internet of Things (IoT).The major issues with this storage are preventing unauthorized access and data theft from outside parties.The Block chain based Security Sharing scheme with Data Access Control (BSSDAC) was implemented to improve access control and secure data transaction operations.The goal of this research is to strengthen Data Access Control (DAC) and security in IoT applications.To improve the security of personal data, cypher text-Policy Attribute-Based Encryption (CP-ABE) can be developed.The Aquila Optimization Algorithm (AOA) generates keys in the CP-ABE.DAC based on a block chain can be created to maintain the owner's security.The block chain based CP-ABE was developed to maintain secures data storage to sharing.With block chain technology, the data owner is enhancing data security and access management.Finally, a block chain-based solution can be used to secure data and restrict who has access to it.Performance of the suggested method is evaluated after it has been implemented in MATLAB.To compare the proposed method with current practices, Rivest-Shamir-Adleman (RSA) and Elliptic Curve Cryptography (ECC) are both used.
Analysis of the impact of artificial intelligence on college students and countermeasures based on the perspective of comprehensive development

In order to investigate the various impact of artificial intelligence on college students, this paper analyzed 248 questionnaires to obtain the real opinions of college students.The results of the questionnaires show that: in terms of learning and education, the era of AI has increased the opportunities for college students to contact with AI and their enthusiasm for learning; in terms of employment and career, the era of AI has brought employment anxiety to college students and increased their awareness of crisis; in terms of life and communication, the era of AI has facilitated the life of college students, but it has also put them in a conflict between realistic feelings and "intelligent feelings".In terms of ethics and morality, the era of AI has increased the transparency of college students and their awareness of AI ethics is lacking; in terms of expectation and confidence, college students have self-fulfillment expectation and optimism in the face of the coming era of AI.