Reviewerly/exHarmony huggingface dataset:
Extractive Text and Video Summarization using TF-IDF Algorithm

Abstract: Text summarization is a technique for extracting concise summaries from a large text without sacrificing any important information. It's a good way to extract crucial information from documents. The rapid rise of the internet has resulted in a substantial surge in data all across the world. It has become difficult for humans to manually summarise big documents. Automatic Text Summarization is an NLP technique that lowers the time and efforts required by a human to create a summary. Text summarising techniques are divided into two categories: extractive and abstractive. In the extractive approach, text summarising techniques choose sentences from documents based on a set of criteria. In the abstractive approach, text summarising techniques strive to improve sentence coherence by reducing redundancies and explaining the context of sentences. The extractive summarization approach is the subject of this paper. There are several methods for summarising data, including TF-IDF, Text Rank, PageRank, and Latent Dirichlet Allocation (LDA). This work examines Text Summarization using the TFIDF Algorithm, a numerical measure that ranks the value of a word in a document based on how frequently it appears in that document and a set of documents. The application of the TF-IDF Algorithm for text, document, article, and video summarization is described in this study. There are no repetitions in the results, and for some searches, they are nearly identical to the summary results provided by humans. This algorithm offers a sentence extraction technique that selects the most diverse top-ranked sentences. Keywords: Extractive Summarization, Term Frequency-Inverse Document Frequency (TF-IDF), Natural Language Processing (NLP), Text Summarization, Video Summarization
EFFORTS TO IMPROVE STUDENT'S READING ABILITY BY USING IMAGE STORY MEDIA IN INDONESIAN LESSON

The objectives of this study were: to determine whether pictorial story media in Indonesian subjects could improve the reading skills of fourth grade students of SD Negeri Pante Ceuremen. This research approach uses qualitative. Type pThis research is Classroom Action Research (PTK). When this research was conducted in August 2018. The subjects in this study areIV SDPante Ceuremen's country districts Pante Ceuremen West Aceh District as much 23 people consisting of 14 men and 9 women. Data collection techniques: tests, observation and documentation. The research instruments were test sheets, observation sheets and documentation sheets. Data analysis techniques aredataincreasing students' reading skills and statistical data for hypothesis testing. From the results of the study it was found that students' reading skills could be improved through pictorial story media in grade IV SD Negeri Pante Ceuremen in the 2018/2019 academic year. Based on the test in the initial conditions, it was found that 20 students scored less than 65. Only 3 students scored above 65. The average score for class 50 with a classification level of completeness was 13%. Based on the results of the Indonesian test on the beauty and cleanliness of the school environment, the reading ability in the first cycle, it was known that the class average was 1480, there were 13 students who had not completed because they got a score of 60 and there were 10 students who got a score of 70. Classical completeness was 43%. Based on the results of the second cycle test shows that the average value of the Indonesian language on the beauty and cleanliness of the school environment increases reading skills by 73.47. Classical completeness is 9.3%. Based on these results, it can be seen that the classical has been completed in cycle II
Determination of the influence of the choice of the pruning procedure parameters on the learning quality of a multilayer perceptron

Pruning connections in a fully connected neural network allows to remove redundancy in the structure of the neural network and thus reduce the computational complexity of its implementation while maintaining the resulting characteristics of the classification of images entering its input. However, the issues of choosing the parameters of the pruning procedure have not been sufficiently studied at the moment. The choice essentially depends on the configuration of the neural network. However, in any neural network configuration there is one or more multilayer perceptrons. For them, it is possible to develop universal recommendations for choosing the parameters of the pruning procedure. One of the most promising methods for practical implementation is considered – the iterative pruning method, which uses preprocessing of input signals to regularize the learning process of a neural network. For a specific configuration of a multilayer perceptron and the MNIST (Modified National Institute of Standards and Technology) dataset, a database of handwritten digit samples proposed by the US National Institute of Standards and Technology as a standard when comparing image recognition methods, dependences of the classification accuracy of handwritten digits and learning rate were obtained on the learning step, pruning interval, and the number of links removed at each pruning iteration. It is shown that the best set of parameters of the learning procedure with pruning provides an increase in the quality of classification by about 1 %, compared with the worst set in the studied range. The convex nature of these dependencies allows a constructive approach to finding a neural network configuration that provides the highest classification accuracy with the minimum amount of computational costs during implementation.
Lessons from machine-readable Chinese applied to managing retrieval of graphical and textual information

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Facial Recognition with Face Regions by Machine Learning: Review

Abstract: This paper proposes a comprehensive study of facial recognition method supported a unique facial decomposition. First, seven regions of interest (ROI), representing the most parts of a face (left eye, right eye, between eyebrows, left eyebrow, right eyebrow, mouth and nose), are extracted by using facial landmarks detected by the IntraFace algorithm. Then, proposes a study of completely different native descriptors, such as LTP, Dynamic LTP, LBP and CLBP are used to extract features. Keywords: Facial expression recognition, SVM, feature descriptor, Facial decomposition, facial landmarks
Pengembangan Mobile Learning Berbasis Android pada Materi Perkalian antara Dua Matriks bagi Siswa Kelas X di SMK Satya Bhakti 1 Jakarta

This study aims to develop Android-based mobile learning on the multiplication material between two matrices for class X students of SMK Satya Bhakti 1 Jakarta. Mobile learning is made as an alternative learning media that can be used when learning online. This is because pre-existing learning media are considered less attractive and this mobile learning can be used without quota. This research is development research. The procedures in this study consisted of analyzing the developed product, developing the initial product, and testing the product. The results showed that the Android-based mobile learning developed was feasible to use. The results of media validation were 75.90% and material and language validations were 77.36%. The results of the trials on teachers were 82.35%. The small-scale trial results were 84.77%. The results of large-scale trials were 83.19%. Based on these results, it was concluded that Android-based mobile learning on the multiplication material between two matrices for class X students of SMK Satya Bhakti 1 Jakarta was feasible.&#x0D;
Using Machine Learning to Analyze Sudanese Opinions for Political Decision Making

Sentiment Analysis (SA) is the application of text mining techniques for extraction and identification of subjective opinions from textual data.SA has many applications ranging from financial analysis to political decision-making domains.Although a lot of works have been made in SA of English tweets, very limited work focused on Arabic political colloquial tweets.In this paper, we focused on analyzing tweets during Sudanese revolution 2018 and leverage Term Frequency-Inverse Document Frequency and word embedding methods with machine learning classifiers to detect user's sentiments of colloquial Arabic political tweets instead of using modern standard Arabic.Experiments were conducted to evaluate our classifiers and the results showed superiority of the Ensemble learning model with an F-score of 83% compared to other machine learning classifiers.
Using DPLA and the Wikimedia Foundation to Increase Usage of Digitized Resources

The Digital Public Library of America has created a process by which rights-free or openly licensed resources that have already been harvested can be copied over into Wikimedia Commons, thus creating a simple path for including those digital collections materials into Wikipedia articles. By meeting internet users where they already are, rather than relying on them to navigate to individual digital libraries, the access and usage of digital assets is dramatically increased, in particular to user groups that might otherwise not have a reason to interact with such digitized resources.
Role of Nepali Army in Promotion and Preservation of Nepalese Art, Culture, and Traditions

The Nepali Army was founded initially as the Gorkha Army around 450 Years ago. Since its inception, the Nepali Army as the nation's largest organization has not only been ensuring our territorial integrity but has also been connecting multi-ethnic, multi-lingual, multi-religious, multi-cultural Nepalese society in a common thread by preserving its rich tangible and intangible cultural heritages along with the associated traditions. In this regard, this study predominantly illuminates the fact that modern-day Nepal has been shaped through the sacrifices of the Nepali Army and their histories are interwoven altogether. This research illustrates that the Nepali Army has been preserving and promoting Nepalese art, culture, and tradition for centuries both in times of peace and war. Despite socio-economic and political shifts in the nation's history over time, the Nepali Army has remained resolute in its spirit assimilating various cultural transplants within the organization promoting cultural relativism. Within this frame of reference, this study primarily aims to unfold major hurdles the Nepali Army is currently facing in the conundrum of operational and ceremonial duties along with the impacts of modern world issues, such as digitization and modernization. To fulfil objectives, this study follows a qualitative research methodology. It analyzes data collected from various primary and secondary sources and analyze it to draw out relevant inferences. I explore the military institution's roles to promote arts and cultures based on quantitative data with qualitative analysis.
Implementation of the Chua’s circuit and its applications

In this paper the Chua's circuit is investigated.This oscillator consists of a passive RLC 1 C 2 block coupled to an active nonlinear resistor (Chua's diode).Electronics Workbench (EW) simulation results showing the existence of chaos are given.The circuit implementation and experimental results referring to the double scroll attractor are reported.Applications of the Chua's circuit in the area of communication are discussed.
Random forest-based physical activities recognition by using wearable sensors

Physical activity recognition (PAR) is a topic worthy of attention. In order to improve the practicality of wearable sensors for recognition, in this study, we propose an approach to create a classifier of PAR based on the collected data. At first, we discuss how features extracted from the accelerometer and gyroscope contribute to distinguish different activities, including walking, walking upstairs, walking downstairs, sitting, standing, laying, and also provide an analytical method employed for this purpose. Then, a supervised machine learning method, random forest algorithm, is adopted to create a classifier to recognize physical activities based on the extracted features. Lastly, the performances of the constructed classifier are evaluated and compared with other methods. The performance evaluation shows the classifier trained by random forest algorithm are better than other algorithms, and its overall recognition rate reaches 93.75%. In addition, our approach also has strong potential for applications in smart textiles.
Perancangan Sistem Informasi Data Kependudukan Berbasis Web pada Kelurahan Lokoboko Kecamatan Ndona

The problem found in Lokoboko Village, Ndona sub-district is that village data input is still done manually and has not been regulated properly, therefore this community service program is very good for changes in village data management that has been carried out by village officials. With the design of this Web-based data information system, it is very easy for village officials to input and manage population data. The purpose of this service activity is to provide convenience to village officials in filling village data using the HTML website. The method used in this service activity is socialization, assistance and training to village officials in using HTML Web sites. The results obtained are that data taken from the community is inputted via a web created and the data is well organized so that it can be presented neatly.
The Development and Evaluation of Augmented Reality Learning Application in Geometry Topic

The application of technology should be applied by teachers and pupils to be prepared with knowledge and skills that can provide positive impact in teaching and learning.Hence, the Malaysia Education Blueprint 2013-2025 was developed by the Ministry of Education which emphasizes on the use of technology and innovation that can improve the achievement of students.Pupils in primary school face difficulties in basic concepts, reasoning and problem solving in geometry.Based on the global benchmarking of Trends in International Mathematics and Science Study (TIMSS) test report in 2019, the average score of mathematics achievement for Malaysian students is at a low level compared to other Southeast Asian countries like Singapore which are at the highest-level score in the world.Moreover, geometry domains also reported as low levels from 2007 to 2019.Most of teachers use drawings on whiteboards, static images in books and verbal explaining to describe threedimensional shapes to pupils.In this regard, the innovation of learning application utilizing Augmented Reality technology was developed for pupils.This study used ADDIE's instructional design model as a framework to develop the application.This study used three experts' interviews to confirm the need for developing this application and quasi experimental to evaluate the effectiveness of the application to 30 grade 2 pupils.This study is hoped that the AR technology applied can improve the effectiveness of learning, increase motivation and creative thinking skills of students in solving problems especially in geometry topic.
BETA CHI-SQUARE DISTRIBUTIONS PROPERTIES AND APPLICATIONS

In this paper we introduce the distribution of three parameters, called Beta Chi-square distribution (BCHI), is presented and contains the Chi-square distribution as a sub-model. Its density function can be expressed as a linear combination of Chi-square density function. Some structural properties of this distribution, how moments, and hazard function are presented. Estimates of the model parameters are performed using the Maximum Likelihood method. We obtain the observed information matrix and discuss inference methods. In order to demonstrate the utility of the distribution, a real data set is analyzed.
Transformations in Mexican Basic Education as a Result of the Social Distancing Forced by COVID-19

One year after that the forced social distancing due to the COVID-19 health emergency began, the deficiencies of the Mexican Education System came&nbsp;under the spotlight. The closure of educational institutions has implied the loss of school space as a privileged place for interaction,&nbsp;while&nbsp;pre-existing structural inequalities have been exacerbated. The purpose of this essay is to carry out a general description of the changes in basic education due to the forced distancing based on a general overview&nbsp;of the inequality crisis that our country has faced since the pandemic began,&nbsp;with the aim of reflecting on its future sequels.&nbsp
Development of Android-Based Interactive Media Learning Economics Capital Market Materials

This study aimed to produce an Android-based interactive media for economic learning in class X SMA/MA which was valid and practical. This type of research was Research and Development (R &amp; D). The research was conducted at SMA N 1 Salimpaung for the 2020/2021 academic year. The test subjects involved in the research were media, language, material and evaluation validators, economics teachers and students. The model in this development used a 4-D model, namely definition, design, development, and dissemination, but this research was limited to the develop stage. The results of study obtained a score of 86.65%, from the material validator with a very decent category. The media validator obtained a score of 87.3%, with a very decent category. The assessment of the language validator got a score of 83% with a very decent category. Meanwhile, the evaluation validator got a score of 92% with a very decent category. The practicality results of the teacher obtained a score of 92.78% and the assessment of the students was 94.9%. The results of both assessments were in the very practical category. This android-based interactive media was declared very feasible to be applied to economics learning material for capital markets.
Basic Study on the Use of XR Technology to Support Science Education

According to the results of a survey on science teaching in 2016, the percentage of students who answered that they like science is lower than other subjects.However, more than 80% of students said that they like experiments and observations.In addition, a 2019 survey on smartphone penetration showed that about 90% of students are familiar with the technology.Also, XR technology has made remarkable progress in recent years.Based on the above, I conducted this research because I thought that creating a simulation application using XR technology with smartphones would change the way we think about science classes.In this paper, we have developed a simulation application for science experiments.The subjects were asked to experience the created application and answer a questionnaire.As a result, the average score was 4 out of 5, which was not a bad result.At the same time, however, we found a problem.The problem was that since this was a simulation application, the user experience was not very good.So we wanted to make it a little easier to use.While improving the problems, I would like to create applications for other fields as well.
An Ensemble Kalman Filter for Estimating Future Slow Slip Events and Earthquakes on 1D, 2D and 3D Synthetic Experiments&amp;#160;

&amp;lt;p&amp;gt;Our ability to forecast future earthquakes is hampered by the very limited information on the fault slip that produce them. In particular the current state of stress, strength, and parameters governing the slip of the faults are highly uncertain. Ensemble data-assimilation methods provide a means to estimate these variables by combining physics-based models and observations while considering their uncertainties. Perfect model experiments with an Ensemble Kalman Filter (EnKF), connected with one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) earthquake cycle models, demonstrate the ability to estimate the state variables of shear stress, slip velocity, and state (&amp;amp;#952;) of a straight fault governed by rate-and-state friction surrounded by a homogeneous elastic medium. The models represent a direct-shear laboratory setup in one, two and three dimensions, with an array of shear-strain gauges and piezoelectric transducers located at a small distance to the fault. In this research, we compare the recurrence interval and earthquake occurrence of the EnKF across the different models to better understand the challenges associated with a space-time systems with increasing dimensions and increasingly complex earthquake sequences. The assimilation of synthetic shear-stress and slip-rate observations improves in particular the estimates of shear stress and slip rate on the fault, despite the very low accuracy of the observations. We get reasonable estimates when modelling long-duration earthquakes or slow slip events . Interestingly, we also obtain very good estimates when simulating earthquakes with fast slip rates (up to m/s). The large, nonlinear, changes in stress and velocitiy &amp;amp;#160;during the fast transition from the interseismic to the coseismic phase cause the distributions of the state variables to become bi-modal. The EnKF still provides a reasonable estimate of the time of occurrence of the earthquakes in the synthetic experiments, despite the inherent assumption on the Gaussianity of these distributions.&amp;lt;/p&amp;gt;
IDENTIFYING THE MAIN FACTOR OF STUDENTS’ ANXIETY IN LIMITED FACE-TO-FACE LEARNING ENGLISH SPEAKING DURING COVID-19

One of the obstacles, particularly speaking anxiety, has a significant impact on someone's ability to speak a foreign language. In fact, because to the Covid-19 pandemic, researchers discovered that students were anxious of speaking English in class in limited face-to-face learning. In light of this context, the purpose of this study was to look at the primary causes and sources of students' anxiety when learning to speak English in limited face-to-face learning due to pandemic Covid-19. A qualitative methodology and descriptive method were used to conduct the research. Six eighth-grade students from a public junior high school in Karawang took part in the study. Two low-level students, two middle-level students, and two high-level students were separated into three groups. Researchers used observation, interview, and documentation to gather data. The result showed that the primary causes of students' concern in learning English speaking, according to this research, were poor pronunciation and a lack of vocabulary. Meanwhile, students' anxiety in learning English speaking came from lack of confidence and nervousness. It implies that it is essential for teachers to be able to fulfill their roles as facilitators in order to minimize students' speaking anxiety in a foreign language classroom.