Reviewerly/exHarmony huggingface dataset:
The Composition and Effects of a Young Children’s Environmental Education Program connecting to Family

The purpose of this study is to develop a young children’s environmental education program connecting to family and to investigate its effects. Researchers developed a young children’s environmental education program connecting to family according to 6-step process. The effects of the program were observed from thirty eight 5-year-old children (nineteen in experimental group, nineteen in comparative group) and their parents of S preschool in Gwangju metropolitan city. Experimental group participated in the young children’s environmental education program connecting. to family, and comparative group in daily activities according to the Nuri curriculum. The experiments were conducted ten times targeting to parents and twenty times targeting to children for ten weeks from the eighteenth of October to twenty-fourth of December in 2021. The results of this study were as follows. The young children’s environmental education program connecting to family was consisted of educational contents, teaching-learning methods, and evaluation to promote the environmental sensitivity and environmental preservation attitudes of children and parents. Also, the environmental sensitivity and environmental preservation attitudes of children and parents were increased meaningfully through the program. That is to say, the young children’s environmental education program connecting to family was effective to increase the environmental sensitivity and environmental preservation attitudes of children and parents. As a result, it is significant that this study suggests new model of a young children’s environmental education by showing the educational effects of the young children’s environmental education program connecting to family.
An Analysis of Using Chuchu TV Nursery Rhymes and Kids Songs YouTube Channel as Medium for Learning Early Childhood English Vocabulary

Many children who have not been able to master basic English vocabulary such as various colors, animals, fruits, and the alphabet Learning English must be done from an early age, one of the media that can be used to learn English is YouTube. YouTube is an interesting medium to use in the teaching and learning process of English. YouTube users are spread all over the world from various age groups, from early childhood to adults. One of the popular YouTube Channels among children is ChuChu TV. This study aims to analyze the use of ChuChu TV as a vocabulary-learning medium for early childhood. This research is a type of qualitative research with a case study method. Researchers used observation and interviews as data collection techniques. Participants in this study were children aged 5 to 6 years in Purwosari, North Metro District, Metro City. The research results show that the use of the ChuChu TV YouTube Channel can improve English vocabulary in some early childhood students.&#x0D; Keywords: English Vocabulary, YouTube Education, Early Childhood
Sistem Pendukung Keputusan Manajemen Pemilihan Aplikasi Jasa Transportasi Online Menerapkan Metode ROC dan WASPAS

Transportation in Indonesia has various types of vehicles, ranging from two-wheeled to six-wheeled, which are adjusted according to user needs. The ease of ordering transportation services is also increasing with the application that can be downloaded on a smartphone. This application provides convenience and security, as well as setting tariff rates according to the intended destination. Even though using an online transportation service ordering application has many advantages, such as convenience and security, there are some drawbacks that users often face. One of them is the discrepancy between the travel time stated in the application and reality, which can result in delays if there is an urgent need. In addition, sometimes the application also provides a longer travel route even though there is a road that is closer to the destination, so the driver must use an alternative road outside the specified route. Therefore, evaluation of the applications used needs to be done by comparing one application with another. This study aims to use a Decision Support System (SPK) to assist online transportation users in choosing the best application, taking into account factors such as the accuracy of travel time and the efficiency of the route taken by the application. There are many DSS methods that can be applied in the process of selecting or selecting the object under study, in this study the method used is the ROC method as a weighting of the level of importance of each criterion and the WASPAS method for the ranking process for each alternative. The final result obtained is that the Grab application (A3) is declared the best application in online transportation services with an acquisition value of 0.9331Decision Support System
Optimal Number Data Trains in Hoax News Detection of Indonesian using SVM and Word2Vec

Along with the development of the era of technological development also has an increase. Information dissemination occurs very quickly on social media, especially Twitter. On Twitter, only some news circulating is necessarily accurate information. Lots of information that is spread is hoax news that irresponsible individuals apply. In this research, the author will build a system to determine the optimal amount of data trained in the hoax news classification process. In this study, the authors will use the support vector machine and word2vec algorithms to classify hoax and non-hoax news on the system to be created. In this study, five experiments were carried out with the number of train data used as many as 5000, 10000, 15000, 20000, and 25000. 5000 data train results in an accuracy of 77.28%, 10000 data train produce an accuracy of 79.68%, data 15,000 trains produce an accuracy of 79.892%, 20,000 data trains produce an accuracy of 80,416%, and 25,000 data trains produce an accuracy of 81,184%, by using a combination of unigram with token full token selection. This research aims to build a hoax detection system that can determine the optimal amount of data training to use. Also, this research is used to see the performance of the Support Vector Machine algorithm with Word2Vec in detecting hoax news
FPGA implementation of QUasi-Affine TRansformation evolutionary algorithm

The QUasi-Affine TRansformation Evolutionary (QUATRE) algorithm, a new intelligence optimization algorithm, has been widely used in many optimization fields. In this paper, a hardware-based QUATRE algorithm is designed and implemented on a field-programmable gate array (FPGA). To facilitate the implementation of the QUATRE algorithm on hardware, this paper simplifies the co-evolutionary matrix generation process. Compared with the original QUATRE algorithm, the simplified QUATRE algorithm may reduce latency and resource occupation. The Vivado High-Level Synthesis (HLS) design tool is used to complete the IP core design of the QUATRE algorithm. Through the benchmark function test under different population sizes, compared with the QUATRE algorithm implemented by software, both the running speed and optimization performance of the QUATRE algorithm implemented by hardware are significantly better than the former. Compared with the GA, DE, and PSO algorithms implemented by hardware, the QUATRE algorithm also shows strong competitiveness.
HUBUNGAN MEDIA SOSIAL TERHADAP MOTIVASI BELAJAR DAN HASIL BELAJAR MATEMATIKA

Along with the development of technological advances, social media is increasingly diverse. Social media such as Instagram, Facebook, Youtube are widely used by all ages including elementary school students. Easy access and use make social media look attractive to use. Its use is not only to find learning materials, but can be used to communicate with anyone they meet from the platform. Researchers wanted to know how the influence of social media and learning motivation on the mathematics learning outcomes of grade VI students at SD XYZ. Researchers use a quantitative approach to process data obtained by correlative descriptive methods. The respondents who were the object of the study were grade VI students at SD XYZ as many as 30 students. Data collection techniques by filling out questionnaires on social media use and learning motivation through the Google Form application, while for learning outcomes researchers took data from several math task scores. The data obtained is processed with the SPSS v25 program. The results showed (1) there was no significant influence of social media use on mathematics learning outcomes, (2) there was no significant enough influence between learning motivation and mathematics learning outcomes, (3) there was no positive and significant relationship between social media use and learning motivation simultaneously with mathematics learning outcomes.
Detection of high-residual days of incoming shortwave radiation and its limitations

Forecasting the photovoltaic (PV) power produced by a plant implies large financial gains or losses for companies. The PV power forecasting skill mainly depends on solar radiation, one of the most challenging variables to predict due to its extreme temporal and spatial variability. For instance, two recurring weather phenomena in midlatitudes are spring-summertime convective thunderstorms and fog. The first are characterized by strong spatiotemporal variability: grid resolution of a forecasting model is thus often too coarse to resolve them, and parametrisation schemes are required. The second is of strong local nature, depending on soil type, orography, and soil water content, which, if not represented correctly in a model, may lead to strong overestimation of solar radiation forecast. The vertical resolution in NWP models does not allow to correctly predict the fog&amp;#8217;s upper limit while the horizontal resolution is typically incapable of fully resolving water bodies. Such weather events thus lead to large errors in day-ahead forecasts for solar radiation.&amp;#8239;&amp;#8239;In this study, the meteorological causes for particularly bad solar radiation forecasts - the so-called high residual days (HRDs) - have been investigated and a technique to detect them in advance with good reliability has been developed.&amp;#8239;&amp;#8239;The analysis was performed comparing one year (May 2021 - April 2022) of hourly values for incoming shortwave radiation at surface from a multi-model combination of NWP models (forecasts) and from SARAH solar radiation data retrieved from the EUMETSAT Climate Monitoring Satellite Application Facility (measurements). To identify which variables could reveal HRDs, five distinct locations in north-west Switzerland, corresponding to ground weather stations were selected, for which, imposing specific conditions, a set of HRDs was defined. For each set, various meteorological variables from multiple models, combinations, and measurements were investigated. We found that over 65 % of HRDs are associated with shifts or mistakes in precipitation forecasts. To identify HRDs forecast, we consequently selected two quantities based on the standard deviation of precipitation; specifically: (i) days with high spatial standard deviation &amp;#8211; at fixed forecasting model, spotting high variability between the examined and surrounding grid cells, and (ii) days with high standard deviation between different models within the same grid cell. Combining these two sets with a proper choice of parameters, 75% of HRDs were detected. A spatial investigation showed that this approach scores good in central Europe and even better in desertic and tropical areas. Although the standard-deviation-based approach does not determine the sign of the residuals, the prediction of HRDs is nonetheless advantageous: on HRDs, users should favour a multi-model over a single-model forecast, to be able to better assess the uncertainty and the possible range of solar radiation and PV power.&amp;#8239;&amp;#160;
Comparative Analysis of Community Sentiment Against the Implementation of Booster Vaccination in Indonesia Using the K-Nearest Neighbor and Naïve Bayes Classifier Methods

Sentiment analysis is a person's opinion or view of a particular object that produces positive, negative, or neutral sentiments. The government's effort during the COVID-19 pandemic is to call for the implementation of a booster vaccination program to the public. Based on this, it produces several public sentiments, some of which are uploaded on the Twitter social media platform, which generate positive and negative sentiments. To find out the classification of public sentiment, the researchers carried out calculations using the K-Nearest Neighbor and Naïve Bayes Classifier methods. Based on the calculation results, it was found that the public sentiment was positive at 98% and negative at 2%. This means that the community is enthusiastic and supports the booster vaccination program. Then the comparison based on the calculation results, namely the K-Nearest Neighbor method with a K value of 3 resulting in an accuracy calculation of 97.33% and using the Naïve Bayes Classifier method, an accuracy calculation of 97.35% can be generated. So it can be seen that using the Naïve Bayes Classifier method has a higher accuracy than the K-Nearest Neighbor method.
The Geometry of Curved Spaces

The mathematics required to analyse higher dimensional curved spaces and space-times is developed in this chapter. General coordinate transformations, tangent spaces, vectors and tensors are described. Lie derivatives and covariant derivatives are motivated and defined. The concepts of parallel transport and a connection is introduced and the relation between the Levi-Civita connection and geodesics is elucidated. Christoffel symbols the Riemann tensor are defined as well as the Ricci tensor, the Ricci scalar and the Einstein tensor, and their algebraic and differential properties are described (though technical details of the derivationa of the Rimeann tensor are let to an appendix).
Twitter Sentiment Analysis of Kanjuruhan Disaster using Word2Vec and Support Vector Machine

The Kanjuruhan disaster on 1 October 2022, gained the peoples attention. People share their thoughts on social media. Their posts contain a variety of perspectives. Sentiment analysis is possible to use on a dataset of people's posts. This final project applies the supervised learning Support Vector Machine (SVM) method with feature expansion using Word2Vec and TF-IDF as weighting. Three SVM kernels—rbf, linear, and polynomial—are applied. Three split data techniques and two different types of training data are used to train each kernel. Training data with oversampling and training data without oversampling are the two types of training data. The best result gained from using rbf kernel, split ratio 70:30, and oversampling. From it, oversampling trained model have relatively stable in every split rasio and kernel without having significant difference.
Application of growth model applying GAMM and PGM

Exploring a growth model in a longitudinal study is as important as verifying the effectiveness of variables related to growth. In this study, in identifying the growth model, the analysis was conducted using the generalized additive mixed model (GAMM) and the piecewise growth model (PGM) in longitudinal study. For empirical data, GAMM and PGM were used for identifying changes in students' academic achievement in mathematics through the Korean Education Longitudinal Study (KELS-2013) data. As a result, the exponent of the growth model function optimized in GAMM was calculated as 2.98, confirming that the growth model was most suitable for a cubic function. In addition, as a result of verifying the random effect by applying GAMM, a growth of 198.73 points was confirmed in the first year, the starting point of the survey, and it was confirmed that female students showed 2.97 points higher growth than male students in terms of growth in students' math achievement. On the other hand, as a result of applying PGM, the turning point appeared at 2.54, and it was confirmed that the greatest change was shown at the time of school grade change from elementary school to middle school. Such results as in this study show different approaches through GAMM and PGM to explore data-based growth models, and these results can be greatly expanded to analyze growth models such as data-based machine learning methods.
Comparative Study on the Curriculum of Elementary Social Studies in Korea and Taiwan of the Japanese colonial era : As the Structural-Functionalism of Parsons.T

[Purpose]This study finds that despite the historical similarities between Korea and Taiwan, which were under Japanese rule at a similar time, there is a difference in the majority's feelings toward Japan. The reason for this discrepancy was discovered in the composition of curricula and methods of textbook technology. Therefore, a study was conducted to examine the functional relationship between education and society through comparative analysis.&#x0D; [Methods]To achieve the objectives of this study, a literature review was conducted. As a theoretical framework for the analysis, the study examined the structural and functional aspects of both countries, taking into account their respective historical backgrounds. In addition, a comparative analysis was conducted to examine the relationships between social conditions, curriculum, textbooks, and classroom management.&#x0D; [Results] The main findings are as follows. First, the social-structural discourse influences the criteria for selecting educational content. Second, the difference in technology method of related content in textbook, according to historical and social context. Third, the emphasis on curriculum and technological methods may also vary depending on the changes in social discourse.&#x0D; [Conclusion]In summary, the comparative analysis of the historical backgrounds and contexts of the two countries, together with the study of the curricula, confirmed the complementary relationship between national and social discourse and the curriculum. Especially in Korea, where accredited social textbooks for 5th-6th grade will be introduced from 2023, this study is significant as it highlights the influence of curriculum and textbook presentation on students and social discourse. It also provides recommendations for improving curriculum and textbooks.
A study on Establishment of Stability Test and Biopharmaceutical Analysis Support Center

This study was undertaken to suggest the necessity of establishing stability test and biopharmaceutical analysis support center. Feasibility study on center establishment was performed as online survey to factory manager and person in charge in 39 pharmaceutical companies in Korea. More than seventy percent of 39 companies responded that they need to establish it. Eighty percent of respondents answered that they would entrust the entire test items of stability test and 71.8% of respondents answered that they would entrust biopharmaceutical cell bank and protein analysis. The construction cost of two centers with 2 stories and 1 basement floor and 3000m2 was 6.37 billion won. The stability test center need to 173 EA of 71 types of equipment and 4.086 billion won in budget for equipment purchases. The biopharmaceutical analysis support center need to 169 EA of 77 types of equipment and about 7.2 billion won in budget for equipment purchase. Total cost for construction and equipment purchase was 17.65 billion won. The establishment of two centers with expertise and efficiency would provide the competitiveness of the pharmaceutical industry in Korea.
Dynamics of causes and factors of obtaining secondary vocational education: the situation of «college at the university»

The article is devoted to the results of a sociological study of the causes and factors determining the educational trajectories of students of secondary vocational education. The trend of recent years in the field of vocational education has been a gradual increase in the number of school graduates entering secondary vocational education institutions, while at the same time reducing the number of graduates entering higher education programs. The above explains the relevance of studying the dynamics of the structure of causes and factors that determine professional and educational trajectories. The authors also substantiate the need to take into account the factors associated with conducting such studies of the characteristics of a particular category of secondary vocational education institutions, one of which includes colleges at universities. The authors conducted two rounds of a questionnaire survey in 2018 and 2023 of senior students of all specialties of the Baikal State University College. The monitoring nature of the survey made it possible to consider the dynamics of the structure of the reasons and factors of admission to the «ollege at the university» and to determine changes in the preferred professional and educational trajectories of students after they receive secondary vocational education. There are significant differences in the studied issues between students studying on the basis of basic and secondary general education. In general, there is a general decrease in the importance of the factor of the possibility of entering a university without passing a unified state exam after graduation from college. For students on the basis of 9th grades, the importance of factors related to the possibility of obtaining a profession and a workplace more quickly has increased. The analysis of the dynamics of educational intentions revealed a significant decrease in interest in further education at the university both in the near and long term, which is especially pronounced among those enrolled in college on the basis of basic general education. In general, the data obtained confirm the general trend of strengthening the importance of secondary vocational education as an independent educational level.
Proposed Secure Activity Diagram for Software Development

Unified Modeling Language (UML) activity diagrams are derived from use case diagrams.It becomes essential to incorporate security features and maintain consistency in the diagrams during analysis phase of Software Development Life Cycle (SDLC).As part of current software development practices, software security must be a constant effort.The activity diagrams are used to model business process.The detailed analysis of activity diagram is done.The challenge lies in viewing the main activity diagram from attacker's perspective and providing defense mechanism to mitigate the attacks.This paper presents an extension of the activity diagram named SecUML3Activity to provide security with Object Constraint Language (OCL) constraints using Five Primary Security Input Validation Attributes (FPSIVA) parameters for input validation.It also proposed three security color code notations and stereotypes in activity diagrams.White color is used to represent activity diagram in normal state.Red color in dotted line is used to represent attack activity components.Blue color with double line is used to represent the defensive activity components.The defense mechanism algorithm against SQL Injection (SQLI) attack, Cross Site Scripting (XSS) attack, DoS/ DDoS attack, access validation attack is provided.The mapping of Secure 3-Use Case diagram with SecUML3Activity diagram is done through mathematical modeling.