Reviewerly/exHarmony huggingface dataset:
Evolution of Money from Stones to Digital Blocks: Transformation of Value

This study examines the evolutionary route of money and discusses its transformation with increasing digitalization. Although economic thought has focused on different topics and employed different analyses throughout history, concepts such as value and justice have always been part of the discussion. Approaches regarding the functions of money have also changed with digitalization and new possibilities have emerged regarding its impact on social structure. As central banks are also joining this journey, which started with bitcoin using blockchain technology, it is of great importance that the practices to be implemented eliminate concerns raised in the past and are functional in terms of equality and justice. This paper discusses the current framework, along with important themes in economic history and the development of decentralized technologies that aim to alter functions of money. The opportunities and potential risks are identified and possible scenarios for the future are discussed in conclusion.
An Analysis of Foreign Undergraduates&amp;apos; Perceptions of a Good Class in College Writing

This study aims to find out what constitutes a good class as seen by foreign undergraduates in liberal arts college writing courses. A survey on the perception of a good class was conducted for 211 foreign students taking the College Writing courses. As a result, the factors that constitute a good class according to the students were the following: first, the instructors, second, the class environment, third, the evaluation and the atmosphere, fourth, the contents of education, and lastly, the teaching method by category. The students judged whether the class was good or not, largely according to the instructors’ kindness, the degree of care he or she gave to the students, and the ability of the instructor to communicate. Next, the study found that there was a difference in the perception of a good class according to the level of students’ Korean proficiency. Compared to intermediate and advanced learners, beginner learners recognized writing courses involving the learners' participation as worse in terms of teaching method, evaluation, and atmosphere. If instructors in charge of university writing courses for foreign undergraduate students plan and operate classes with the results of this study in mind, it is expected that the educational effect and student satisfaction will be enhanced.
Health professors and students’ perception about Google Classroom in higher education

This research is carried out with the purpose of analyze Google Classroom through remote education from health professors and students' perception at a university in Cusco.From this perception, it is evident how the platform is applied, the interrelation between teachers and students, as well as the benefits and barriers that have arisen throughout their educational experiences.This study has a qualitative approach with a hermeneutic phenomenological design with the intervention of ten informants: 8 students and 2 teachers from a clinical area of health sciences.The results showed that Google Classroom constitutes a necessary alternative for remote education.Tutoring is not properly governed as in the face-to-face modality but monitoring by teachers is constant and permanent.They also specified that the Google Classroom has many benefits for distance education, especially for theoretical courses, but that it is not for practical clinical courses in the health area, since the healthcare part is essential, concluding that, due to its benefits, it facilitates the development of education and achieves theoretical skills, but not clinical skills.
Research on singular value decomposition denoising algorithm based on a genetic algorithm and FFT and its application

To address the impact of noise in spectral signals on gas detection accuracy and sensitivity, this paper carries out a study of a singular value decomposition denoising algorithm based on a genetic algorithm and fast Fourier transform. Aiming at the optimization problem of two key parameters (structure of Toeplitz matrix and effective singular value order) in the smooth filtering algorithm of singular value decomposition, this paper uses a genetic algorithm to optimize the number of rows of the reconstructed Toeplitz matrix and determines the effective singular value order by performing fast Fourier transform on the constructed differential spectral signal. To test the effectiveness of the self-established singular value decomposition denoising algorithm, a detailed filtering and noise reduction analysis study is carried out on the simulated spectrum and experimentally measured signals with the absorption spectrum of atmospheric oxygen molecules as the analysis object, and compared with the traditional S-G filtering algorithm, wavelet transform denoising and principal component analysis denoising algorithm. The results show that the singular value decomposition denoising algorithm established in this paper has obvious superiority in suppressing noise, which can more effectively improve the signal-to-noise ratio and reduce the root-mean-square error of the spectral signal, thus improving the gas detection accuracy and sensitivity of the spectral experimental system.
Vote Now Application

The E-voting system offers internet voting. To stop voter fraud, we use two different levels of security. As the first level of security, a web camera records the voter's face and uploads it to the database. After that, the person's face is compared to the face in the database to verify its authenticity. The two faces are compared with the help of the Local Binary Pattern algorithm. The plan's foundation is combining two images and assigning a value to a central pixel. Those central pixels will have values of either 0 or 1. If the value is less than a pixel, a histogram of the labels is calculated and used as a descriptor.
IS COMMUNICATING MATHEMATICS PART OF THE EASE OF ONLINE LEARNING FACTOR?

In this study, we focus on self-disclosure, communicating mathematics, and infrastructure support in determining the ease of online learning for students of mathematics education study programs. The sample in this study were students (n=465) who were asked voluntarily to fill out an online questionnaire. Participants consisted of 335 female students (72%) and 130 male students (28%) from various universities in Indonesia. The data were analyzed quantitatively using structural equation modeling. The results of the path analysis show that the ease of online learning is influenced by self-disclosure, communicating mathematics, and infrastructure support. The R square results show that these factors influence 47%. Each path analysis shows that self-disclosure (r = 0.556 p= 0.000) and infrastructure support (r = 0.243 p = 0.000) have a significant positive relationship with the ease of online learning. Meanwhile, communicating mathematics (r = -0.025 p =0.507) has an insignificant negative relationship to the ease of online learning. Further research is needed to see how the impact of mathematical application support communicating mathematics in online learning.
Comparing Image Captioning Techniques using Deep Learning Models

Websites today generate tremendous amounts of data and this data needs to be processed effectively by the creators. One such important factor is processing images on the website and generating effective data from it through techniques like Web Scraping. This process can be done through techniques like Image Captioning. Image captioning is a powerful process that involves generating descriptive image captions. The ability to generate detailed and accurate descriptions of images is extremely valuable in many different fields, particularly in machine learning-based applications and systems. Images often contain a wealth of information that can be difficult for machines to understand without the help of advanced algorithms. Image captioning is one way to extract and use this information for a variety of purposes. Image captioning can also be used in self-driving cars to help vehicles navigate the environment more effectively. It can also be used to develop software for blind people, providing them with descriptions of the images that they cannot see. To accomplish image captioning, we rely on models based on deep learning, specifically advancements in natural language processing. One approach to creating these models involves using pre-trained CNNs and recurrent neural networks (RNNs) like ResNet and LSTM. These pre-trained models can be combined with natural language processing techniques to generate captions for images. As deep learning continues to evolve, there will likely be even more advanced techniques and models that can be used to enhance the accuracy and efficiency of image captioning. Overall, image captioning is a valuable tool that can help us better understand and utilize the vast amount of information contained in images.
Breast Cancer Prediction using Machine Learning

Abstract: Breast cancer poses a serious threat to women, as it is highly morbid and lethal. Doctors find it challenging to develop a treatment plan that could increase patient survival time due to the lack of reliable prognosis models. Therefore, figuring out a method that outcome in the least amount of wrongdoings while improving productivity requires time. In the paper, SVM, Logistic Regression, Random Forest, XGBoost, AdaBoost, kNearest Neighbors, Naive Bayes and custom ensemble Classifiers. These algorithms that predict the outcome of breast cancer. The JUPYTER platform is used to conduct all experiments, which are carried out in a simulation environment.
Tree Learning: Towards Promoting Coordination in Scalable Multi-Client Training Acceleration

Iteration based collaborative learning (CL) paradigms, such as federated learning (FL) and split learning (SL), faces challenges in training neural models over the rapidly growing yet resource-constrained edge devices. Such devices have difficulty in accommodating a full-size large model for FL or affording an excessive waiting time for the mandatory synchronization step in SL. To deal with such challenge, we propose a novel CL framework which adopts an tree-aggregation structure with an adaptive partition and ensemble strategy to achieve optimal synchronization and fast convergence at scale. To find the optimal split point for heterogeneous clients, we also design a novel partitioning algorithm by minimizing the idleness during communication and achieving the optimal synchronization between clients. In addition, a parallelism paradigm is proposed to unleash the potential of optimum synchronization between the clients and server to boost the distributed training process without losing model accuracy for edge devices. Furthermore, we theoretically prove that our framework can achieve better convergence rate than state-of-the-art CL paradigms. We conduct extensive experiments and show that our framework is 4.6× in training speed as compared with the traditional methods, without compromising training accuracy.
ALJABAR UNTUK ANAK USIA DINI

This paper aims to describe the importance of teaching algebraic content and algebraic thinking skills for early childhood and how the learning strategies are at the early childhood education level. The research method uses library research to understand learning algebraic content and algebraic thinking for early childhood. The results obtained in this study include the application of learning mathematics for children through various creative activities and introducing the concept of arithmetic and geometric concepts. Both of these concepts in teaching early childhood are introduced to several objects in the environment around them so that these mathematical concepts can be understood and understood more deeply by early childhood.
Modeling of dengue hemorrhagic fever cases in AWS Hospital Samarinda using bi-responses nonparametric regression with estimator spline truncated

Research on innovations in the field of statistics implemented in the health sector. This research is the development of birespon nonparametric regression model with spline truncated approach. The purpose of this research is to model and determine the factors affecting the Dengue Hemorrhagic Fever Cases in AWS Hospital Samarinda using Bi-responses Nonparametric Regression with estimator Spline Truncated. The data used in this study were data on the platelet count of dengue fever patients when they first checked blood and after three days of treatment in 2022 as well as factors that were thought to have an effect. From the research results, the best model was biresponse nonparametric regression with three knot points where the minimum GCV value was 97.77 and R2 value of 89.88%. Based on the test results, the factors affecting the response variable were the number of hematocrit and the level of hemoglobin in DHF patients.
User-Centered Digital Instructional Design for the Hearing Disabilities

In attention to educational inclusion and the use of information and communication technologies, the instructional design focused on people with hearing disabilities is presented. Methodology: It is of an analytical-documentary type, composed of four phases carrying out the theoretical and methodological framework of instructional design and user-centered design. Results: The user-centered instructional design for people with hearing disabilities is presented, incorporating the three dimensions: pedagogical, technological, and user-centered. Conclusions: User-centered instructional design for people with hearing disabilities suggests incorporating sign language learning or translators into digital content, as well as text transcribers for audio or podcast and subtitling of videos with sound content.
Korean Buddhist Tales utilised Cultural Arts Education for Young Children and the Effect on Young Children’s Empathetic Ability from the Integrated Approach of Problem-Based Learning (PBL)

Objectives This study analysed Korean Buddhist Tales utilised cultural arts education for young children and the effect on young children’s empathetic ability from the integrated approach of problem-based learning (PBL). Methods Fifty Gwangju city based five years-old young children (twenty-five children for both experiment group and controlled group) were selected and the experiment were held for eight weeks (four times a week and thirty-two times in total). Five Korean Buddhist tales were selected to build a teaching-learning method that integrates cultural arts education for young children and PBL, and five stages of experiment were executed; stage 1: facing the problem; stage 2: identifying the topic; stage 3: discovery; stage 4: finding the solution; stage 5: presentation and assessment. The examination on the children’s empathetic ability was used to analyze, using SPSS (ver. 26), the difference among groups based on ANCOVA and MANCOVA. Results To sum, Korean Buddhist Tales utilised cultural arts education for young children and the integrated approach of PBL has positive impact on improvement of children’s empathetic ability. Among the sub-elements, communication empathy and cognitive empathy also showed positive impact on this while the other sub-elements that are social empathy and emotional empathy didn’t show a meaningful difference. Conclusions This proves that Korean Buddhist Tales utilised cultural arts education for young children and the integrated approach of PBL have a positive impact in increasing ‘communication empathy’ and ‘cognitive empathy’.
Development Case Study of Convergence Education Program for Enhancing Teaching-Learning Effect of Classical Literature Using Information Visualization Design

Objectives The empirical goal of this study is improving students’ academic ability through visualization of information. To achieve the goal, through case study, this study aims to find out what teaching-learning experience effect teachers and learners can have by developing and applying convergence education program using visualization design of classical literature which belongs to high school national curriculum. Methods For the investigation, this study developed a teaching model using organized information planning process. The participants for the teaching model was Korean teachers, art teachers and 24 students of middle ranked high school in Chungcheongbukdo Cheongju. To identify the effectiveness, this study conducted in-depth interview and before-after test strip which can evaluate affective and cognitive constructs. Teachers’ instructions were analyzed with integrative perspective of Curriculum-Class-Evaluation-Feedback. The results of students’ before-after test strip and individual interviews according to the achievement level were classified by visualization of information and learning effect. Then, students’ experiences were organized based on the results. Results As a result, systematically organized information planning and information visualization design made students learn classical novel more constructively. Also this teaching model encouraged the integration of Curriculum- Class-Evaluation-Feedback and student-centered collaborative learning. In addiction, this study suggests advantages and concerns for application of digital device in visualizing process. Conclusions Through this study, it was confirmed that both teachers and students have positive learning experience in the process of producing text information into visual information during the teaching-leaning process of classic novel. The findings of this study will become an alternative method to revive marginalized classic novel teaching. Also, it extended the availability of information visualization design in the teaching and learning.
The effectiveness of K-means clustering algorithm-based class in elementary social education

Objectives The purpose of this study is to check whether elementary social studies class is effective in cultivating learners' accountability and information utilization skill using the K-means clustering algorithm and to propose a new elementary social studies class model suitable for the era of the 4th Industrial Revolution. Methods Using various tools, the procedure of the K-means clustering algorithm was reconstructed into an unplugged class model, and the class was constructed by fusing it with the climate environment among the topics of elementary social studies education. In addition, the effectiveness was analyzed qualitatively and quantitatively by applying it to actual elementary school classroom. Results After executing the class applying the K-means clustering algorithm, it was found that accountability was cultivated by qualitative analysis of the learning material written by students. In addition, when quantitatively analyzing and comparing students' information utilization skill before and after class, it was found that the information utilization skill after class was further improved. Conclusions Through this study, the possibility of convergence of elementary social studies education and K-means clustering algorithm was confirmed, and the effectiveness of algorithm-based class in elementary schools was verified. In addition, a new elementary social studies class that can be used in the era of the 4th Industrial Revolution was proposed.
Comparative Analysis of the Guidelines for the Development of Subject Curriculum in the 2015 and 2022 Revision from the viewpoint of Coherence between General Guidelines and Subject Curriculum

Objectives The purpose of this study is to draw implications for the next curriculum revision by comparing and analyzing the 2015 Revised Curriculum and the 2022 Revised Curriculum in terms of coherence between general guidelines and subject curriculum in Korea. Methods The focus of analysis is on the guidelines for the development of subject curriculum of 2015 Revised Curriculum and 2022 Revised Curriculum. In particular, in the case of judgment on clarity, in addition to judgment on whether or not to present, it was analyzed with a focus on whether the guideline itself was sufficient to develop the subject curriculum without any more explanation from the standpoint of the subject curriculum development team. Results Although the problem of the 2015 revision guidelines that did not provide guidance on the meaning of competency education, curriculum design principles, and national and social requirements was resolved, it is found that the 2022 revision guidelines for development of subject curriculum are still insufficient in preparing guidelines considering the characteristics of each subject and guidance on development of achievement standards as performance standards. Conclusions Based on the results of this analysis, suggestions for the next curriculum revision are presented as follows. First, it is necessary to prepare clear directions and development guidelines related to the development of achievement standards. Second, it is necessary to prepare guidelines for developing subject curriculum in consideration of the characteristics of each subject. Third, Detailed discussions on how to reflect national and social requirements are needed. As a follow-up study, it is necessary to restructure the overall structure of the subject curriculum in connection with the general direction of core competency education.
Necessary factors and Prospects for Online Beauty Education Based on the Experience of Beauty-majors Professors After COVID-19

Objectives This study is to explore the experiences of high school teachers and university professors in online classes conducted after COVID-19, and to predict the future of online education in beauty majors, present directions for sustainable online education and contribute to the development of the field. Methods After COVID-19, data were collected based on the experiences of beauty high school teachers and university professors who had undergone full-fledged online education, and the operation method of online education was diagnosed, and the future was predicted. The analysis of the data focused on excluding the subjectivity of the researcher and revealing the meaning of the experience of the study participants using Giorgi's analysis method, a prominent phenomenological analysis method. Results In the question of the general experience of online classes, the study participants generally mentioned negative experiences. Participants in the study mentioned self-directed learning ability and digital device utilization ability as Student's necessary factors for sustainable online education, digital device utilization ability and class quality as Teacher's necessary factors, and resolution of difficulties in supporting and filming digital devices, and establishing accurate government guidelines and school programs as Technical necessary factors. In addition, regarding the prospect of online education for beauty majors, they said that online education has the advantage of time convenience and repetitive learning, and online beauty education will continue in the future. Conclusions Based on the experiences of teachers and professors who experienced online classes after COVID-19, this study found out the experiences of online education and the needs for sustainable online education, and presented the prospects of online beauty education, which is meaningful, but limited to some cases. Therefore, such research needs to lead to more verification of cases and opinions in the future, and more diverse opinions and solutions should be devised for sustainable online education.