Reviewerly/exHarmony huggingface dataset:
A Learning Organization: Conditions for Success of the Excellent Schools in Hunan, China

This research aimed to study the conditions for the success of the three excellent schools and use the findings to design a model for the development of excellent schools in Hunan, China. The quantitative data were gathered from the sample group of 392 teachers of the three schools, who filled out the 45-item questionnaires, while the qualitative data were from in-depth interviews with the three school principles. Quantitative data were analyzed by factor analysis, and qualitative interview data were analyzed by Grounded Theory. The findings from the questionnaire data analysis identified eight aspects that shaped a learning organization: 1) School policies and goals 2) Supportive Environment 3) Professional development 4) Collaboration 5) Strategies to adapt to changes 6) Leadership 7) Sharing vision 8) Information Technology. From the three principals’ interviews, six themes emerged: 1) Changes in all areas affecting education and Change-facing strategies 2) Choices of curricula and pedagogies 3) Successful ways to teacher development 4) Student preparation for the Future 5) Cooperation of all school stakeholders and 6) Focus on Innovations. Based on the findings, a recommended model for the schools which aim to become excellent schools has been proposed.
Penggunaan Media Google Site untuk Meningkatkan Motivasi dan Hasil Belajar IPS pada Peserta Didik Kelas VII SMP

Motivation and social studies learning outcomes in class VII students are still low, one of which is because the learning media is less attractive. For this reason, teachers need to make interesting media so that it helps students in learning. Google Site is one of the alternative learning media that can be obtained for free and is easily accessible by students without the need for special applications, can be opened at any time and is not bound by space and time. This research is a type of classroom action research which is carried out in 2 cycles with the object of research being the seventh grade students of SMP. This study aims to improve learning outcomes through the Google Site media. Data collection techniques using test questions, questionnaires and observations. The expected result of this research is an increase in social studies learning outcomes through the Google Site media.
Diagnosa Penyakit Tulang Belakang Menggunakan Metode Forward Chaining dan Certainty Factor

In the field of medicine, especially orthopedics, there are several types of spinal diseases including scoliosis, lordosis, kyphosis, and spondylosis. Therefore, an expert system is needed to diagnose spinal diseases. Based on this problem, we performed an exponential comparison of the two hybrid methods. With the final value of the combined forward chaining &amp; naive bayes method of 8.89, and 9.40 the highest final value of the combined forward chaining method and certainty factor. So that in this research, forward chaining and certainty factor methods are used which are designed based on a website, using Sublime Text 3 programming tools and PHP and MySQL as databases. From the results of application testing and manual calculations with 30 sample data, it was concluded that 7 users or about 23% entered the level of confidence in the possibility of developing spinal disease and 23 users or 77% of the total testing stated at the level of confidence in the probability of developing spinal disease with a value of the highest confidence of 88.5% in spondylosis disease.
Disiplin Belajar, Lingkungan Kelas, Perhatian Orang Tua sebagai Upaya Meningkatkan Hasil Belajar IPS

This study aims to determine the positive influence student learning discipline, classroom environment on learning outcomes in subjects in class IV SDN Bratasena. The population in this study were all students of class IV SDN Bratasena 2021/2022 total as many as 188 students. Determination of the sample is done with purposive sampling technique; namely the sample is determined by the investigators. In this study, researchers took samples based classes with setting Tourism IV as samples, amounting to a total of 100 students.
FORMATION OF DIGITAL COMPETENCE OF FUTURE TEACHERS IN HIGHER EDUCATION INSTITUTIONS

The rapid development of society in recent years has forced higher education institutions to change the requirements for the training of future teachers. Digital technologies continue to be a challenge to the education system and are key to training future teachers in higher education.One of the main components of the professional competence of future teachers is digital competence. The formation and evolution of this type of competence relate to the tasks of each discipline studied in the curriculum of higher education institutions. The article identifies the main factors in the formation of digital competence of future teachers. Different approaches to the definition of digital competence of future professionals, the terminology used in the modern scientific literature to define the concept of digital competence are identified. One of the tasks of higher education is to achieve the level of awareness, the formation of a digital environment of information activity space, which ensures the implementation of educational programs, education of information culture and literacy in future teachers. The integration and globalization of social, economic and cultural processes taking place in the world, the prospects for the development of the Ukrainian state for the next two decades require a deep renewal of the education system and determine the advanced nature. Digital competence, which provides the formation of professional competence, is one of the main components of the model of a graduate of a pedagogical university.&#x0D; Keywords: digital competence; digital literacy; future teachers; information; information culture; information educational online environment; professional growth; applicants for higher education.
A Novel Under-sampling Method with Gaussian Mixture and Jensen-Shannon Divergence

Due to bias towards major class samples, the traditional classifier cannot obtain excellent performance in imbalanced data. The under-sampling approach is one of the effective methods in imbalance classification. Nowadays, most of the under-sampling methods do not consider the global and local distribution of samples and the intra-class imbalance problem simultaneously. In addition, the sampling quantity cannot be adjusted adaptively in the practical application. To handle the above problems, in this paper, we propose a novel under-sampling approach with the Gaussian mixture model and Jensen-Shannon divergence, called GD-US. Firstly, it utilizes a Gaussian mixture model to cluster the majority class samples. And then, it calculates the number of sampling in each cluster according to its sparsity. In addition, GD-US adopts the global and local distribution of samples to decide the probability of deleting samples. Eventually, the Jensen-Shannon divergence is used to control the number of sampling. The experimental results show that the proposal can help solve the imbalance problem and enhance the classification accuracy.
Hesitant Fuzzy Prime Ideal of Γ- ring

In this paper, we introduce the notions of hesitant fuzzy ideal, hesitant fuzzy prime ideal, hesitant fuzzy strongly prime ideal in gamma rings and hesitant 3-prime ideal. Also, we study the relation between the above concepts
The Internet of Things Based Healthcare (HIoT): Networks, Technologies, Applications, and Challenges

As the proportion of total generation by renewable sources compared to non-renewable sources increases, the relative inertial stability provided by large rotating generators in electricity grids is found to shrink and is not being replaced by sources such as photovoltaic and wind power, which are already known for their inherent variability.This leads to electricity generation systems being less stable, less flexible, and less adequate in applications with a high diversity factor, and literature shows that the penetration of renewable energy sources in distribution-generation/microgrid system frequently presents several technical and economic challenges in their usual applications.This work examines how increased renewable energy penetration impacts the distribution-generation system and suggests approaches and measures for tackling the challenges that are associated with it.
English-Assisted Teaching Evaluation System Based on Artificial Intelligence and Rasch Model

In order to improve the effect of English teaching in colleges and universities, this paper analyzes the English teaching process and combines the English teaching evaluation system and the Rasch model to construct an English teaching evaluation system. Moreover, this paper analyzes the needs of English teaching evaluation and uses the mixed Rasch model in the item reflection theoretical model to study the potential classification problems of teaching. At the same time as the optimal parameter estimation, the potential optimal classification ratio is found, and it is used as the basis for the classification of English teaching grades. In addition, this paper combines the Rasch model to construct the English-assisted teaching evaluation system and analyzes the system framework and workflow. The experimental research shows that the evaluation system of college English teaching process based on the Rasch model proposed in this paper has a good effect.
Comparison of onboard processors for real-time target identification in unmanned aircraft systems

The real-time identification of targets on small unmanned aircraft systems (UAS) is a challenging task. One approach to achieving this task is the use of image recognition in deep learning networks on embedded processors. While it has been well established that the use of deep learning networks can help increase the reliability of image recognition applications, less research has been performed on the requirements needed for selecting an appropriate embedded processor that can meet the speed and efficiency needs for real-time target identification. The embedded processor must fit within the size, weight, and power (SWaP) constraints of small UAS, while still meeting the computational and memory requirements of the detection algorithms. To determine whether embedded processors meet these form factor requirements and other performance considerations, we evaluated and compared several commercially available embedded processors based on their physical specifications, performance using lightweight benchmark machine learning models developed for commercial use, and performance using a Navy-developed deep convolutional neural network (CNN) used for identifying the California Least Tern. This evaluation will provide information on the necessary hardware and software requirements for performing complex computing tasks on a UAS in real-time using image recognition deep learning networks on embedded processors.
Code-Switching Used In Judges’ Utterances of Masterchef Indonesia Season 7 Grand Final Episodes

This study deals with the types and functions of code switching used in the speeches of the judges of MasterChef Indonesia Season 7 at the grand final episode,in line with that this research also analyzed the social aspects that affected code switching based on these utterances. The judges of MasterChef Indonesia Season 7 who had educational backgrounds abroad made them accustomed to using code switching in their speech. The aim of this research are (1) To analyze the types of code-switching used in judges’ utterances of MasterChef Indonesia Season 7 grand final episodes, (2) To analyze the functions of code-switching used in judges’ utterances of asterChef Indonesia Season 7 grand final episodes. The data source of this research was obtained by watching and listening to 12 video CDs from an online video sharing platform called YouTube. The researchers find three types of code-switching: 7 tag switching, 53 inter-sentential switching, and 17 intra-sentential switching. The functions of code-switching found in this research are only four functions, they are 25 referential functions, 8 directive functions, 28 expressive functions, and 6 phatic functions. The social aspect affecting code-switching in this research is social class and status.
Research on the Evaluation of Reformation and Revolution System for Universities Based on Neural Network

Accurately evaluating the working conditions of college revolution and reformation system personnel is currently a hot issue in the field of revolution and reformation system research. Based on the neural network architecture, this paper constructs a model for the system and obtains relevant quality evaluation indicators through simulation experiment analysis. According to the quality evaluation index framework of the revolution and reformation system, the experimental platform selects 7 universities in the region, 6 of which are samples, and 1 (S University) is the research target, and the scores of each index are calculated using MATLAB auxiliary software. The simulation process starts from the characteristics of the actual neural network model; selects 17 evaluation impact indicators, including 3 basic indicators and 14 technical indicators based on historical data; and uses the factor recursive method to improve the neural network and establish an evaluation model. Then use the collected specific data to train a BP neural network with a structure of 21 × 11 × 1, continuously adjust the weights and thresholds of the neural network until the standard error requirements are met, finally verify the scientificity of the evaluation model, and compare the actual output value with the expected output value for comparison. The experimental results show that the model input data redundancy rate is reduced to 0.136, and the network training time delay is reduced to 413 ms, which improves the computing power of the network model of the reformation and revolution system in colleges and universities. The use of neural network data to reduce dimensionality effectively promotes the reformation and revolution system in universities.
Extractive Text Summarization for Wolaita

Text summarization is the mechanism of summarizing a huge document comprising vast amount of information which is difficult to overcome and understand its message easily in any written documents for whatever languages without losing its entire message. A short and precise document which conveys intended information for the user in demand is expected in this information age. In addition to that, summarizing a document with vast amount of information is very difficult and time consuming specially for less resourced and technologically unfavored languages. Therefore in this study, the researcher proposed to address such problems for Wolaita by using graph based extractive text summarization approach. To attain the goal of this study the researcher prepared 92 documents for the study, explored extractive text summarization with graph-based approach to address the problems, performed text preprocessing tasks and finally developed text summarization model by using TextRank algorithms. The researcher used 92 documents, performed 92 various experiments, on documents and experimental results and findings were discussed in detail. To evaluate the model performance, three different expert summaries were collected for documents and computed system generated summaries with ROUGE evaluation metric. The researcher justified it with ROUGE evaluation metrics by comparing the system summaries with the expert summaries. The result obtained from the experiment shows promising result in summarization of Wolaita text. Finally, the experimental result of a 61.16% recall, 60.69% precision and 60.46% f-measures were obtained.
Analisa UI/UX Terhadap Perancangan Website Laundry dengan Metode Human Centered Design dan User Experience Questionnaire

The development of information technology today has developed very rapidly where in its development can help people from all walks of life in doing anything, one of which is in the laundry service business sector. My laundry is one of the businesses that offer Laundry services that provide kiloan washingservices. In My laundry In doing data collection or recording my laundry data still does manually. In solving the problems that occur in my laundry system the solution is to apply an information technology system that uses a website. In a design of user interface and user experience can be used as basic things in the creation of a website. In conducting analysis and design of user interface and user experience using the Human Centered Design (HCD) approach and user experience questionnaire (UEQ) method is expected to provide conveniencefor users of the website
DEVELOPMENT OF INDONESIAN LEARNING MEDIA BY USING MICROSOFT POWERPOINT FOR STUDENTS OF CLASS VII SMP NEGERI 2

Learning media has an influence in efforts to increase student learning achievement. The selection of traditional learning media has begun to shift to modern and up-to-date learning media that are more practical, attractive, interesting, creative and innovative. This research was conducted to produce the development of writing materials and learning media for Indonesian language learning using Microsoft PowerPoint for class VII semester 2 students of SMP Negeri 2 Pegajahan. This type of development research data is in the form of qualitative data and quantitative data. The research uses the research and development (R&amp;D) model of Borg and Gall. The purpose of this study is the compilation of a learning media product as an effort to develop writing materials. In connection with this goal, the researcher uses seven steps in developing learning media, namely analyzing the needs of teachers and students, product development with Microsoft PowerPoint, validation of media experts and material experts and language teachers Indonesia, the first phase of revision, field trials, and finally the final revision. The quality of learning media products can be known through the average obtained from the validation results from Indonesian language teachers of 95%. The average percentage of the assessment results is 87.18% with a very good category. In addition, the quality of development products can also be known through the results of excellent student feedback. The product of this research is learning materials and media designed for class VII SMP in the second semester. This product contains eight Competency Standards which are translated into seventeen Basic Competencies and contained in twelve lessons. The twelve lessons are structured and integrated with one main menu. Each media unit is arranged systematically including apperception, competency standards and basic competencies, indicators, materials, sample questions and competency tests in which there are various media that are arranged simultaneously including text, audio recordings, videos and animations. The results of this study are very relevant to the 2013 curriculum because it is in accordance with the standards of the interactive, inspiring, fun, creative, challenging and motivating learning process for students. Further research is needed to determine the effectiveness and influence of the use of this media on student achievement.
Application of Voice Recognition Interaction and Big Data Internet of Things in Urban Fire Fighting

With the continuous development of science and technology, especially computer technology, people need a more convenient and natural way to communicate with the machine. Language can provide people with convenient and efficient information, and speech recognition technology makes this convenience extended to the field of science and deep into human daily life. In this paper, based on human-computer speech recognition interaction system, using big data Internet of things as technical support, the contribution of intelligent social service robot to urban fire protection is studied. In this system, the user can control the action of the service robot through voice command, and the user can also realize voice interaction with the robot. Because of the continuous expansion of information technology and computer technology, human beings have entered the era of information overload, and big data technology has become a hot spot in people’s production and life. The integration of big data and Internet of things technology will make the intelligence of human society to a new level, and its development has unlimited possibilities in the future. In recent years, China’s urbanization process continues to accelerate, and the land price and house price of cities begin to rise rapidly. In order to meet people’s need, a large number of high-rise, super high-rise and underground buildings continue to increase, which not only provides us with convenience, but also makes fire safety a hot concern of the whole society. Fire fighting plays an increasingly important role in the life of urban residents. In order to greatly reduce the lack of fire safety monitoring ability, this paper uses speech recognition technology to design a city fire safety management service platform based on big data Internet of things.
CONVERSATION TEXT ON INDONESIAN LESSONS USING IMAGES IN CLASS V STATE ELEMENTARY SCHOOL 101938 ADOLINA, PERBAUNGAN DISTRICT

Many educators still use conventional teaching materials, namely teaching materials that are ready to use, just buy, instant, without the effort of planning, preparing, and compiling their own and less attracting children's attention in learning. So the image media is used as a development effort in learning Indonesian. This study aims to determine the quality of teaching materials based on the validation of material experts and media experts, to determine the attractiveness of teaching materials based on student responses, and to determine the average increase in student achievement based on pretest and posttest scores. This research was carried out at SDN 101938 Adolina, Perbaungan District, for the 2021-2022 academic year. This research is development research. The subjects of the study were the fifth grade students of SDN 101938 Adolina, Perbaungan District, for the academic year 2021-2022 with a total of 36 students. Data collection techniques used are tests, questionnaires, and documentation. The data analysis technique used is the percentage and the average. The results of the overall quality of teaching materials are good with a percentage of 78%. The results of the attractiveness of teaching materials based on student responses in the limited trial obtained a percentage of 87% with a very interesting category, while in the large group trial a percentage of 85% was obtained with a very attractive category. The average value of the pretest is 6.09, while the average value of the posttest is 8.44, so it can be concluded that there is an increase in the average student achievement.
Convolutional neural network for color images classification

Artificial intelligent and application of computer vision are an exciting topic in last few years, and its key for many real time applications like video summarization, image retrieval and image classifications. One of the most trend method in deep learning is a convolutional neural network, used for many applications of image processing and computer vision. In this work convolutional neural networks CNN model proposed for color image classification, the proposed model build using MATLAB tools of deep learning. In addition, the suggested model tested on three different datasets, with different size. The proposed model achieved highest result of accuracy, precision and sensitivity with the largest dataset and it was as following: accuracy is 0.9924, precision is 0.9947 and sensitivity is 0.9931, compare with other models.