Reviewerly/exHarmony huggingface dataset:
Research on Experiences of Teachers and Children through Childcare Curriculum Consulting

Authors:
raw_author_name: Sung-Hee Kang
raw_author_name: Hyun-Joo Kim

Abstract: The purpose of this research is to explore changes and progress observed in both teachers and children during customized childcare curriculum consulting sessions developed based implementation of self-examination. The research was carried out among 6 teachers of childcare centers. This research was conducted in conjunction with the childcare curriculum consulting project of “A” Childcare Support Center as part of the 4th Standardized Childcare Curriculum implementation. The following were collected: in-depth qualitative interviews, journals kept by research participants, pictures of playtime, video clips, and researcher notes. The collected materials were transcribed and coded with coded responses grouped based on themes as needed. The results were the followings. First, teachers observed with care when children were playing and supported children to find purpose and lead their play time. Second, children became more independent during their playtime and proactively created their own plays. The childcare curriculum consulting supported teachers to implement goals of play-centered and child centered childcare curriculum through implementation of selfexamination.
Decentralized Energy Trading for Grids Using Blockchain for Sustainable Smart Cities

Authors:
raw_author_name: None Gururaja H S
raw_affiliation_string: Assistant Professor, Dept. of ISE, B.M.S. College of Engineering, Bengaluru, India

Abstract: Blockchain technology can be used to create a decentralized energy trading system for grids that rely on renewable energy sources. This system would allow individuals and organizations that generate renewable energy, such as solar or wind power, to sell excess energy to others on the grid through a peer-to-peer network. Blockchain has smart contracts that facilitate the transactions and ensure that the energy is exchanged securely and transparently. This type of system can increase the efficiency and flexibility of the grid, and help to improve the acquisition of sustainable energy resources. The system allows organizations and smart homes that generate sustainable energy to trade excess energy to others on the grid through a peer-to-peer network, facilitated by smart contracts. The use of blockchain in this manner can increase the efficiency and flexibility of grids and promote the adoption of renewable energy sources. Blockchain technology possesses the potential to transform the energy trading system by creating a decentralized, secure, and transparent P2P energy trading facility for grids that rely on renewable energy sources. This facility allows the trading of energy that is produced in excess by any entity through smart contracts. By using blockchain technology, the energy trading process is more efficient, secure, and transparent, and it can facilitate the adoption of sustainable energy sources. The implementation of such a system, however, requires collaboration between various stakeholders and compliance with existing regulations and standards of the energy sector. Despite the challenges, the potential benefits of a blockchain-based smart decentralized energy trading system make it a promising solution for the future of the energy sector.
A Comparative Study on Machine Learning Approaches for Sentiment Analysis

Authors:
raw_author_name: None Dr. T. Kumaresan
raw_affiliation_string: Associate Professor, Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Erode, Tamilnadu, India.

Abstract: Sentiment analysis plays a pivotal role in the operations of online product companies. User reviews are taken into account by others when they search for products, forming the cornerstone for delivering the right product based on user sentiments through sentiment analysis. Sentiment analysis involves the process of collecting, analyzing, and recommending reviews, which are often extensive and contain multiple paragraphs of content. This paper presents a comparative analysis of various machine learning models used to conduct sentiment analysis on customer reviews of Amazon products within the Electronics category. The initial models under scrutiny for our analysis include Logistic Regression, Decision Tree, Naive Bayes Classifier, Random Forest, Support Vector Machines, and BERT Model. The experimental result show that BERT classifier achieves higher accuracy when compare with other machine learning models.
The meaning of picture book reading activities for infants and toddlers to pre-service early childhood teachers

Authors:
raw_author_name: Se-Ru Kim

Abstract: This study sought to examine the meaning that the experience of reading picture books in the infant class gave to pre-service early childhood teachers. The subjects of this study are two public daycare centers located in Nam-gu, G Metropolitan City, and classes for 1-2 year olds. The study participants were 10 first to third grade students attending the Department of Early Childhood Education at G University. Data analysis was conducted through the process of data integration, domain analysis, data classification, and interpretation of classified content based on the collected journals of pre-service early childhood teachers. As a result of the study, the meaning of the experience of pre-service early childhood teachers' picture book reading activities for infants was categorized into ‘the joy of novelty and challenge in the role of teacher’, ‘gift-like interaction time with infants’, ‘growth and development’, and ‘confidence through self-reflection’. In this way, activities linked to the early childhood education field provide prospective early childhood teachers with the ability to understand infants and recognize their value. In the process of preparing and executing the activity, infant development and developmental characteristics related to the activity are connected and analyzed after the activity. This can be an experience that supports the improvement of one's teaching abilities and allows one to develop into a better teacher. In this context, field-linked activities can be said to be an effective means that can have an effective and positive impact on the teacher training process and foster teachers with practical capabilities.
Learning Effects of Aviation Cabin Service Practice by Applying the PBL Teaching Model: For Aviation Service Departments

Authors:
raw_author_name: Eun-Hee Lee

Abstract: This study applied the problem-based learning (PBL) teaching model to the aviation cabin service practical course offered in the Department of Aviation Service to train airline cabin crew and analyzed its learning effects. For this purpose, the PBL teaching model was applied to 61 students in the Department of Aviation Service in Jeollanam-do for a total of 12 weeks out of 15 weeks of class for 3 credits in the aviation cabin service practical course. The application of the PBL teaching model was conducted in a total of two modules based on the National Competency Standards (NCS). In the self-evaluation of participation in airline cabin service practical classes using the PBL teaching model, learners faithfully presented the learning outcomes of problem-solving activities. In the self-evaluation of the training results, the learners said that they learned a lot about communication problems during team activities and that the overall class activities were helpful in terms of training satisfaction. Through the application of the PBL teaching model, students faithfully presented the learning results of problem-solving activities, became aware of many communication problem situations during team activities, and found that overall class activities were helpful.
Factors Influencing the Improvement of Elementary Students' Basic Reading Skills: A Mixed-Methods Approach from the Teachers' Perspective

Authors:
raw_author_name: Jeong-suk Jang

Abstract: This study analyzed factors influencing elementary students' basic reading skills enhancement from teachers' perspectives, focusing on the impact of digital environment changes and diverse learning methods. Employing a mixed-methods approach, the research unfolded in two phases: analysis of students' Korean language scores and a teacher survey on reading skill improvement factors, followed by teacher interviews based on survey outcomes. Teachers identified three main factors contributing to the improvement of students' basic reading skills: strengthening teamwork through regular learning, lesson planning, and mutual support among teachers; sharing students' incremental achievement assessment results within the grade to identify areas of growth; and setting continuous improvement of reading skills and literacy enhancement as a primary goal at the school level. These findings indicate that teachers prioritize team-based learning and collaboration. Enhancing basic reading skills requires strengthening teacher collaboration, sharing achievement insights to identify growth areas, and establishing literacy improvement as a school-wide goal, necessitating specific educational strategies and policies.
The Influence of Chinese Students' Motivation to Study Abroad on Educational Service Quality and Adaptation to University Life: The Moderated Mediating Effect of Korean Language Proficiency

Authors:
raw_author_name: Xiao tong Li

Abstract: The purpose of this study was to investigate the mediating effect of educational service quality and the moderated mediating effect of Korean language level in the relationship between motivation to study abroad and adaptation to college life of Chinese students majoring in dance. Reliability analysis, descriptive statistical analysis, frequency analysis, correlation analysis, and structural model analysis were conducted using SPSS and Process Macro program. As a result of analyzing the mediating effect of education service quality in the relationship between motivation to study abroad and adaptation to college life, education service quality had a significant effect. It was confirmed that there was a moderating effect of Korean language level and a moderated mediating effect in the relationship between education service quality and college life adaptation.
Leveraging the Jetson Nano AI Kit for Machine Learning in Quantifying Gender Bias in Image Captioning

Authors:
raw_author_name: None Gururaja H S
raw_affiliation_string: Assistant Professor, Dept. of ISE, B.M.S. College of Engineering, Bengaluru, India.

Abstract: In an era where artificial intelligence intertwines with ethical concerns, this paper delves into the practical deployment of the Jetson Nano AI kit to assess gender bias in image captioning. As the AI landscape evolves, the Jetson Nano stands out as an effective tool for environments with limited resources, leveraging its edge computing capabilities to reshape AI research. The paper examines the foundational concepts of gender bias quantification and its real-world application using the Jetson Nano, highlighting its versatility in constrained environments. Throughout the exploration, the seamless integration of the Jetson Nano into machine learning processes is detailed, shedding light on crucial optimizations and adjustments. Challenges encountered are also analyzed, offering insights for researchers undertaking similar projects. Ultimately, the research underscores not just Jetson Nano's role in edge computing but also the imperative of confronting gender bias in AI-generated image descriptions. By melding ethical considerations with edge computing, this paper paves the way for a more balanced and effective AI future.
Synchronization of Complex System by Designing a Controller

Authors:
raw_author_name: None Komal
raw_affiliation_string: PG, Mathematics, Geeta University, Panipat, Haryana, India.

Abstract: Synchronization of two complex identical systems using nonlinear control is presented by this paper. For emphasis on the chaos behavior, initial conditions sensitivity and Lyapunov exponent is calculated. For the synchronization of the complex master and slave system, the nonlinear control method is proposed effectively.
Prediksi Beban Daya Listrik (W) Menggunakan Metode Support Vector Machine (SVM) Pada Listrik Token Rumah Tangga

Authors:
raw_author_name: Sri Anardani
raw_affiliation_string: Universitas PGRI Madiun
raw_author_name: Yoga Prisma Yuda
raw_affiliation_string: Universitas PGRI Madiun

Abstract: Electricity is an essential need that cannot be separated from daily human life, especially in the modern era where many devices require electrical energy. The demand for electrical energy is increasing over time, thus the electricity providers must have sufficient capacity to meet the demand. However, there is still a lot of wasted energy due to the mismatch between the demand and the supplied amount of electricity, leading to significant electricity wastage. In this regard, appropriate calculations are needed to determine the amount of electrical power required, hence the need for a prediction method to determine the required power in real-time. The Support Vector Machine method is expected to predict the electrical load accurately, enabling users to determine the required load for the next period. It is hoped that this prediction will achieve an accuracy rate above 85%.
Institutional quality, information and communication technologies and gender inclusion nexus: global comparative evidence

Authors:
raw_author_name: Elvis Achuo
raw_author_name: Bruno Emmanuel Ongo Nkoa

Abstract: Purpose Despite the longstanding male dominance in the socio-politico-economic spheres, recent decades have witnessed remarkable improvements in gender inclusion. Although the issue of gender inclusion has been widely documented, answers to the question of whether institutional arrangements and information technology shape gender inclusion remain contentious. This study, therefore, empirically examines the effects of institutional quality and ICT penetration on gender inclusion on a global scale. Design/methodology/approach To control for the endogeneity of modeled variables and cross-sectional dependence inherent with large panel datasets, the study employs the Driscoll-Kraay Fixed Effects (DKFE) and the system Generalised Method of Moments (GMM) estimators for a panel of 142 countries from 1996 to 2020. Findings The empirical findings from the DKFE and system GMM estimators reveal that strong institutions significantly enhance gender inclusion. Moreover, by disaggregating institutional quality into various governance indicators, we show that besides corruption control, which has a positive but insignificant effect on women’s empowerment, other governance indicators significantly enhance gender inclusion. Furthermore, there is evidence that various ICT measures promote gender inclusion. Practical implications The study results suggest that policymakers in developing countries should implement stringent measures to curb corruption. Moreover, policymakers in low-income countries should create avenues to facilitate women’s access to ICTs. Hence, policymakers in low-income countries should create and equip ICT training centers and render them accessible to all categories of women. Furthermore, developed countries with high-tech knowledge could help developing countries by organizing free training workshops and sensitization campaigns concerning the use of ICTs vis-à-vis women empowerment in various fields of life. Originality/value The present study fills a significant research gap by comprehensively exploring the nexuses between governance, ICT penetration, and the socio-politico-economic dimensions of gender inclusion from a global perspective. Besides the paucity of studies in this regard, the few existing studies have either been focused on region and country-specific case studies in developed or developing economies. Moreover, this study is timely, given the importance placed on gender inclusion (SDG5), quality of institutions (SDG16), and ICT penetration (SDG9) in the 2015–2030 global development agenda.
INKLUZIVNA DIMENZIJA CJELOŽIVOTNOG UČENJA

Authors:
raw_author_name: Tihomir Žiljak

Abstract: The article analyses the relationship between lifelong learning and inclusive policies for persons with disabilities. The first part analyses the concept of inclusiveness in lifelong learning and the application of this concept in educational policies. The emphasis is on the educational obstacles faced by persons with disabilities and the opportunities that the concept of lifelong learning provides for their inclusion in various forms of education and learning. In doing so, dispositional, situational and institutional obstacles for persons with disabilities and different dimensions of inclusivity are distinguished. The second part of the article analyses the validity of this conceptual framework for describing the educational inclusion of persons with disabilities in Croatia. The difficulties in ensuring the coherence of the policy towards persons with disabilities and the importance of the time dimension in the implementation of these policies are described. Special attention is paid to the final results of inclusive policies. This refers to the lower inclusion of persons with disabilities, their earlier school leaving, and lower overall educational achievements compared to the general population. The analysis is based on data from research on the education of persons with disabilities on obstacles to the inclusion of persons with disabilities in the process of lifelong learning, which were conducted as part of the Academic Network of European Disability Experts and within the thematic network Lifelong education available to all.
Semiautomatic assessment of immunofluorescence microscopy on blood smears in inherited platelet disorders using artificial intelligence: a proof of concept.

Authors:
raw_author_name: C. E. Sigel
raw_affiliation_string: Medical Faculty Carl Gustav Carus of Technical University Dresden, Dresden, Germany; Universitätsmedizin Greifswald, Institut für Transfusionsmedizin, Greifswald, Germany
raw_author_name: L. Kaderali
raw_affiliation_string: Universität Greifswald Zentrum, Institut für Bioinformatik, Greifswald, Germany

Abstract: Introduction Inherited platelet disorders (IPD) are a group of rare diseases caused by mutations in more than 70 genes. Despite advances in molecular diagnosis, platelet phenotyping still represents a cornerstone in the diagnostic workup of IPD. Immunofluorescence microscopy on the blood smear, combined with light microscopy, has been established as a screening tool for IPD and validated as sensitive and specific for 9 of the most frequent IPD [1]. A major drawback of the method lies in the subjective nature of morphological evaluation. Recent advances in computer vision and artificial intelligence tools offer improved performance and increasing accessibility of these technologies even for diagnostic laboratories.
Do Democracy and Government Capacity Positively Contribute to Technological Innovation?

Authors:
raw_author_name: Young-Soo Lee
raw_author_name: Jong-Il Choe

Abstract: Purpose: In this study, we analyze the f ollowing two points based on these existing studies. F irst, we examine the c orrelation between democracy and technological innovation, using cross-national data.We examine whether more democratized countries have an advantage over less democratic c ountries in t erms o f technological i nnovation, and whether d emocratic countries have an advantage over non-democratic countries in terms of innovation performance. we examine how government capabilities affect technological innovation by dividing them into democratic and non-democratic countries. We aim to analyze whether government capacity is important for technological innovation not only in democratic countries but also in non-democratic countries.&#x0D; Research design, data, and methodology: This paper analyzed how political systems, especially democracy and government capacity, affect technological innovation for the period 1997-2017 in 101 countries using data extracted from the World Bank’s World Development Indicators. The relationship between political systems and technological innovation was examined using the Negative Binomial Regression Model (NBRM), which is commonly used to analyze count data with the characteristic of over-dispersion.&#x0D; Results: The findings indicate that as democratization progresses, there is a corresponding increase in innovation performance. Additionally, democratic nations demonstrate higher levels of innovation compared to non-democratic countries. Furthermore, the research reveals that countries with robust government capacity, as measured by factors such as the effectiveness of public officials, provision of public services, regulation and support of the private sector, and corruption control, tend to achieve superior innovation performance.&#x0D; Implications: These f indings support t he a rgument put forth b y Acemoglu a nd R obinson, s uggesting that i n order to a ttain s ustained economic development and innovation, countries require a certain level of government capacity associated with the operation of exploitative economic institutions. The escalating power struggle between the United States and China has now evolved into a technological competition between market democracies and s tate capitalism. Consequently, there i s a f ervent debate regarding which political systems and forms of capitalism have a positive influence on innovation. This study is expected to offer valuable insights and serve as a crucial reference point for this ongoing discourse.
Real-Time Sign Language Recognition and Translation Using Deep Learning Techniques

Authors:
raw_author_name: None Tazyeen Fathima
raw_author_name: None Ashif Alam
raw_author_name: None Prof. Ramya K

Abstract: Sign Language Recognition (SLR) recognizes hand gestures and produces the corresponding text or speech. Despite advances in deep learning, the SLR still faces challenges in terms of accuracy and visual quality. Sign Language Translation (SLT) aims to translate sign language images or videos into spoken language, which is hampered by limited language comprehension datasets. This paper presents an innovative approach for sign language recognition and conversion to text using a custom dataset containing 15 different classes, each class containing 70-75 different images. The proposed solution uses the YOLOv5 architecture, a state-of-the-art Convolutional Neural Network (CNN) to achieve robust and accurate sign language recognition. With careful training and optimization, the model achieves impressive mAP values (average accuracy) of 92% to 99% for each of the 15 classes. An extensive dataset combined with the YOLOv5 model provides effective real-time sign language interpretation, showing the potential to improve accessibility and communication for the hearing impaired. This application lays the groundwork for further advances in sign language recognition systems with implications for inclusive technology applications.