Reviewerly/exHarmony huggingface dataset:
The Effect of Project Based Learning Model in the Group Investigation in Learning Strategy on Social Attitude Student Subject in USI Pematangsiantar

This study analyzes the determine the effect of project based learning model in the Group Investigation and conventional of learning strategy on social attitude student subject in USI Pematangsiantar. Samples are taken by total sampling, namely all semester VI students. The total sample of 60 people are grouped into the experimental group with the project based learning model in the Group Investigation, the experimental group with the Group Investigation learning model, and the control group with the conventional learning model. The research instrument was in the form of an observation sheet on students' social attitudes. This research method is quasi-experimental with data analysis techniques using ANOVA test at a significant level α = 5% with the help of the SPSS 21.0 program. The result of this study found that: Social attitudes of students who are taught with project-based learning in the order of Group Investigation 83.10 ± 4.52 are significantly higher compared to Group Investigation learning 69.80 ± 4.56 and conventional learning 63.15 ± 8 , 20 with (Fcount = 57.005; P = 0.000). Thus, it can be concluded that the project based learning model in the Group Investigation order influences the social attitudes of USI Pematangsiantar students.
MAIN CHARACTER IN THE NOVEL DI BIBIRNYA ADA DUSTA BY MIRA WIJAYA LIES AND THEIR IMPLICATION FOR INDONESIA LEARNING

Abstract: This study aims to describe the main character in the novel Di Bibirnya Ada Dusta. The method used for research was descriptive qualitative method. To analyze the data, researchers used analytic and dramatic approaches, Semi (in Djojosuroto, 2009: 119). Analytic approach was an approach that describes the character or character by describing the character directly, while the dramatic approach was the approach used by the author in describing the character indirectly. The technique of collecting data in this research is first reading the novel carefully, then marking the parts related to the analytic and dramatic aspects of the main character, the focus of the research, namely the novel Di Bibirnya Ada Dusta by Mira Wijaya, while the became a research sub-focus related to the attitudes and actions of the main characters. After researching it can be concluded, the main character in this novel, namely Ray and Roy. Ray's attitude can be seen from an analytical aspect, which is serious and a liar, while the dramatic attitude depicts Ray's physical athletic, macho, handsome, handsome, and intelligent, while Roy has a physical similar to Ray's when viewed in dramatic terms, namely handsome, macho, intelligent, athletic, and imaginative, while the analytical aspects of Roy's attitude, namely boredom, imaginative, brave, and liar. The results of this study will be used to provide teaching in Indonesian language and literature. With the aim, so students can enhance appreciation, be able to appreciate, and be able to recognize the character of the character that the author has described. Keywords: Character, Novel, and Literature Learning.
Chinese Keyword Extraction Method Based on Context and Word Classification

The traditional keyword extraction algorithm TextRank increases the weight of the central word through the correlation between the words and the central word in the co-occurrence window, but the number of words in the co-occurrence window is limited, which will cause the poor expression of the semantic information of the word, and then affect accuracy of the keyword extraction results. In order to solve the limitation of word information in traditional keyword extraction methods and the problem of ignoring polysemy, this paper proposes a Chinese keyword extraction method based on context and semantic classification.
Social Media Used by Krishi Vigyan Kendra Scientists

The present study was undertaken in five southern states (Andhra Pradesh, Karnataka, Kerala, Tamil Nadu and Telangana) and two Union territories (Lakshadweep and Puducherry) of Southern India during 2019-2020 to find out the social media used by Krishi Vigyan Kendra scientists.One hundred and sixty one scientists working in 117 Krishi Vigyan Kendras were purposively selected as the sample of the study.The collected data was scored, tabulated and analysed using frequency, mean, standard deviation and multiple regression analysis.The results revealed that a majority of KVK scientists were very frequently using WhatsApp (91.93%) and Facebook (61.49%), while a majority of KVK scientists were not using Twitter (86.34%),Quora (72.67%),Telegram (68.94%),Instagram (66.46%) and Skype (51.55%).A little more than one-third of the KVK scientists were: very frequently using YouTube (45.34%), rarely using Messenger (36.02%) and not using ResearchGate (41.61%).It was found that more than three-fourth (79.51%) of the KVK scientists were belonging to low to medium category of overall extent of utilization of social media.The important five informations disseminate by KVK scientists to the farmers were integrated pest management, date and venue of trainings/ demonstration, integrated nutrient management, availability of agricultural inputs and subsidies and integrated disease management.The R 2 value indicated that all the 21 personal, socio-economic, psychological and communication characteristics of KVK scientists had contributed to the tune of 81.91 per cent of variation in using of social media by the KVK scientists.Poor internet connectivity in rural areas (86.34%), lack of scientific validity in messages spread via social media (80.75%), insufficiency of time to use social media for agricultural development (78.26%), technical problems while using social media (66.46%) and lack of privacy in social media (54.04%) were the constraints faced by majority of KVK scientists while using social media.
HOG and Zone Base Features for Handwritten Malayalam Character Classification

The recognition of handwritten characters remains one of challenging task in character recognition problems. The variations created by each person in writing the characters affect the character recognition result. Many studies have been performed to increase the performance of Malayalam character recognition. The efforts are to extract the best feature for classification or to get the best classifier for classification. In this study, HOG feature and zoning based feature is be used to classify Malayalam Characters. The performance of both features will be compared for classifying Malayalam character by using SVM classifier. The result showed that HOG feature is able to show higher accuracy as compared to the simple zone based feature. The best accuracy for HOG is achieved by using binary input. On the other hand, despite its simplicity zone based feature is able to achieve accuracy by using skeleton input. Considering that the zone based feature used in this research is simply the pixel count in each zone, future research may be performed to extract more statistical properties on each zone. Future works may also focus on rotation free feature extraction for Malayalam character classification.
Accelerating Natural Language Understanding in Task-Oriented Dialog

Task-oriented dialog models typically leverage complex neural architectures and large-scale, pre-trained Transformers to achieve state-ofthe-art performance on popular natural language understanding benchmarks.However, these models frequently have in excess of tens of millions of parameters, making them impossible to deploy on-device where resourceefficiency is a major concern.In this work, we show that a simple convolutional model compressed with structured pruning achieves largely comparable results to BERT (Devlin et al., 2019) on ATIS and Snips, with under 100K parameters.Moreover, we perform acceleration experiments on CPUs, where we observe our multi-task model predicts intents and slots nearly 63× faster than even DistilBERT (Sanh et al., 2019).
Pengembangan Bahan Ajar MOREL (Modul Elektronik) Berbasis APPS Android

The learning process of students at AMIK AKMI Baturaja still uses textbooks as a learning medium that has not yet led to the digital generation, namely the process of learning using smartphones and based on electronic documents. He problem faced is that the Digital Generation or Z cannot be separated anymore from a Smartphone so that if given a learning method using Textbook, it becomes bored. Besides students are already lazi reading modules in the form of text, the focus of the digital generation is Smartphone. To overcome these problems, it is needed an application development of Morel Teaching Materials (Electronic Modules) based on Android Apps in the hope that it will provide a lot of convenience for students as well as lecturers, as well as the achievement of learning objectives applied by every course on the AMIK AKMI campus in Baturaja. The research method used is the waterfall method while the data collection techniques used are observation, interview and documentation techniques. The results of this study are Morel applications (electronic modules) based on Android Apps. Analysis of the successful implementation of the application implementation development of Morel teaching materials (electronic modules) on AMIK AKMI Baturaja based on Android APPS using the HOT Fit Model method. From the results of the student and lecturer quisoners with 61 respondents the 53.22% results answered agree while 11, 40% answered strongly agree which means the implementation of the electronic module is good.
Automating Template Creation for Ranking-Based Dialogue Models

Dialogue response generation models that use template ranking rather than direct sequence generation allow model developers to limit generated responses to pre-approved messages.However, manually creating templates is timeconsuming and requires domain expertise.To alleviate this problem, we explore automating the process of creating dialogue templates by using unsupervised methods to cluster historical utterances and selecting representative utterances from each cluster.Specifically, we propose an end-to-end model called Deep Sentence Encoder Clustering (DSEC) that uses an auto-encoder structure to jointly learn the utterance representation and construct template clusters.We compare this method to a random baseline that randomly assigns templates to clusters as well as a strong baseline that performs the sentence encoding and the utterance clustering sequentially.To evaluate the performance of the proposed method, we perform an automatic evaluation with two annotated customer service datasets to assess clustering effectiveness, and a human-in-the-loop experiment using a live customer service application to measure the acceptance rate of the generated templates.DSEC performs best in the automatic evaluation, beats both the sequential and random baselines on most metrics in the human-in-theloop experiment, and shows promising results when compared to gold/manually created templates.
Improvisation for Technically-Oriented Peoples

Teaching “soft” skills to technical people is just as important as learning “hard” skills. Improvisation techniques can also be used in teaching technical concepts such as cyber-security, agile development, database design, programming concepts, and most importantly how to better one’s communication skills. In an age where rapid changes have become the norm, improvisation techniques can be used to help navigate the new challenges of the next generation careers, global interaction, and technologies. These techniques can easily be incorporated in other methodologies such as creative problem-solving and design thinking. There are clearly defined and flexible rules for improvising, which make it easier for technical persons to learn and use in their daily life and career.
ZONE OF PROXIMAL DEVELOPMENT AND SOCIAL CONSTRUCTIVISM BASED EDUCATION ACCORDING TO LEV SEMYONOVICH VYGOTSKY

This article is a theoretical study of Vygotsky's idea of zone of proximal development. Its aimed at finding out of its relevance to contemporary educational practices that are increasingly complex. Through the description of the background of the emergence of this idea the author concludes that the idea of zone of proximal development is still relevant in modern education, especially to support the educational practices that are friendly toward student’s individual differences at school. Vygotsky's criticism of the practice of levering in schooling is a warning for teachers and education practicioners to consider learning interventions based on individual students' backgrounds especially their mental development differences so that education can be an effective medium to help children's growth and development optimally.
English-to-Japanese Diverse Translation by Combining Forward and Backward Outputs

We introduce our TMU system that is submitted to The 4th Workshop on Neural Generation and Translation (WNGT2020) to Englishto-Japanese (En→Ja) track on Simultaneous Translation And Paraphrase for Language Education (STAPLE) shared task.In most cases machine translation systems generate a single output from the input sentence, however, in order to assist language learners in their journey with better and more diverse feedback, it is helpful to create a machine translation system that is able to produce diverse translations of each input sentence.However, creating such systems would require complex modifications in a model to ensure the diversity of outputs.In this paper, we investigated if it is possible to create such systems in a simple way and whether it can produce desired diverse outputs.In particular, we combined the outputs from forward and backward neural translation models (NMT).Our system achieved third place in En→Ja track, despite adopting only a simple approach.
Creative Ability of Students as a Precondition for the Successful Development of Children’s Musical Creativity in Teaching Music in Lower Grades of Primary School

The effectiveness of teaching music in lower grades of primary school depends on competences of pre-service and in-service teachers who have to teach the subject curriculum.During their formal education, student teachers at pedagogical faculties acquire elementary knowledge of the theory of music and didactic-methodical competencies, but the important factor of successful teaching has to be their musical-performing and creative abilities.In this paper we examine the musical and creative abilities of student teachers in the final year of their bachelor studies (N = 48), by analyzing their products within the course of the Methodological Practicum of Music Teaching.Descriptive method and procedure of qualitative analysis of obtained student teachers' products in the field of music creation were used.The results show that student teachers' musical and creative abilities and the quality of their creative products do not exceed the level of curriculum requirements for teaching music in the fourth grade of primary school.The aim of this paper is to determine the level of creativity aptitude of student teachers in order to improve it by adequate methodical procedures and training in order to achieve an optimal level sufficient for developing musical and creative activities in teaching young children in a regular school context.On the basis of the obtained results, it can be concluded that frequent neglect of work in the field of developing children's musical creativity in music teaching practice is connected with teachers' insecurity about their own creative abilities and competencies necessary for teaching music.
Teacher’s Strategies in Improving Student’s Reading Interest

Most of Indonesian students in university had low interest in reading. Thus, the strategies of the teacher were essential to be considered to build up students’ reading interest. The aim of this research was to investigate the teacher’s strategies in university in teaching reading and also tried to explore the students’ response toward the strategies. Therefore, this research used mix method to reveal the result. The participants involved in this research were 50 master degree students in English Education Department in certain University in Yogyakarta. To acquire the distribution of the students’ response toward the teachers’ strategies, this research used questionnaire. Furthermore, to collect the data deeper, this research used in-depth interviews. The finding showed that the teacher could boost students’ interest in reading if the teacher could provide transparent scoring system which could assist them to obtain a reflection. Therefore, indirectly, by using this strategy, the teacher forced the students to read to acquire good score in reading activity. Thus, the teacher could enhance the students’ reading interest if the teacher could combine transparent scoring system and force in reading class.
Professional Competencies of Teachers in the Field of Modern Educational and Information-Communication Technologies

Contemporary achievements of pedagogical science and the advancement of information communication technology (ICT), enable new organizational solutions to be applied in teaching, which makes the teaching process more interesting, dynamic and efficient.Modern society and education require an individual teacher who is able to follow changes in society and science.The main goal of this paper is to consider one of the primary question: What teacher competencies are needed and at at what level of application should they be for the modernization of teaching?The empirical part of the paper represents which didactic multimedia teachers use the most in teaching, and what teachers attitudes are towards ability to use educational software in teaching.This study used a descriptive method, and scaling technique with a Likert type assessment scale instrument.The survey involved 209 elementary and secondary school teachers in the region of Nis.In concluding observations, it is noted that classic classrooms are slowly turning towards the use of multimedia, but the current application of educational software is still not satisfactory.Also, the authors draw attention to the need for a wider and more intensive range of professional teacher training courses, primarily in the didactic-methodology field, as well as the field of modern education technology, because this is certainly one of the best ways to meet the necessity of reform of our education and the ever-increasing challenges of modern education for the 21st century.
Tests of Autoencoder Compression of Trigger Jets in the ATLAS Experiment

Limited data storage capability is a large obstacle for saving data in high energy particle physics. One method of partially circumventing these limitations, is trigger level analysis (TLA) as used by the ATLAS experiment. The efficiency of TLA can be further increased by doing effective data compression. One class of artificial neural networks are called autoencoders, which may be used for data compression. This thesis further tests the use of autoencoders for compression of TLA data, while showing that it may however be difficult to generalize between different datasets. The processing resources needed to compress TLA data in real time is shown to fit well within the computing constraints available, and that the memory usage is predictable. The use of different compression techniques used sequentially, by so called float truncation then followed by autoencoder compression is evaluated. It is shown that autoencoders show that same potential to be used on both uncompressed and float truncated data. Compression artifacts from float truncation, called double quantization, are also explained and analytically predicted.
Comparative Study of Bearing Vibration Estimation in Turning using Multiple Regression and GMDH

In modern manufacturing environments, machinery failures are predictable. Vibration monitoring is the most widely used technique. A performance study on the critical bearing vibration of a lathe was carried out. Estimation of bearing vibration was done by measuring bearing vibration along horizontal and vertical directions, flank wear (maximum and average) of the tool, machining time and tool tip temperature. From the experimental analysis it was observed that the vibration velocity depends on cutting conditions. For reliable estimate of bearing vibration, methods like multiple regression analysis and Group Method of Data Handling (GMDH) have been applied. It was observed that the multiple regression estimates give better results for higher speeds. For GMDH, three criterions were considered. Regularity and combined criterion gave better representation. The comparison studies on estimates of bearing vibration by multiple regression analysis and GMDH were made. It was found that at higher speeds, good correlation was obtained for both multiple regression and GMDH models. Among these, GMDH with regularity criterion gives better results.
Learning from evolving data streams

Ubiquitous data poses challenges on current machine learning systems to store, handle and analyze data at scale.Traditionally, this task is tackled by dividing the data into (large) batches.Models are trained on a data batch and then used to obtain predictions.As new data becomes available, new models are created which may contain previous data or not.This training-testing cycle is repeated continuously.Stream learning is an active field where the goal is to learn from infinite data streams.This gives rise to additional challenges to those found in the traditional batch setting: First, data is not stored (it is infinite), thus models are exposed only once to single samples of the data, and once processed those samples are not seen again.Models shall be ready to provide predictions at any time.Compute resources such as memory and time are limited, consequently, they shall be carefully managed.The data can drift over time and models shall be able to adapt accordingly.This is a key difference with respect to batch learning, where data is assumed static and models will fail in the presence of change.Model degradation is a side-effect of batch learning in many real-world applications requiring additional efforts to address it.This papers provides a brief overview of the core concepts of machine learning for data streams and describes scikit-multiflow, an open-source Python library specifically created for machine learning on data streams.scikit-multiflow is built to serve two main purposes: easy to design and run experiments, easy to extend and modify existing methods.
Teacher Competencies for Inclusive Education and Resources for Their Improvement

Knowing the importance of teachers' competencies for inclusive education and the fact that the vast majority of them have not had the opportunity to develop them in the initial [undergraduate] education, the aim of this work is to determine the competencies of teachers for inclusive education and to examine the possibilities for their improvement.For research requirements a questionnaire was created.The study was carried out in January 2018 and encompassed 70 teachers of primary and secondary schools in Kragujevac.The general findings that teachers have assessed their competencies for inclusive education as low and that they mapped the difficulties they face in inclusive practice, point to a conclusion about the generally developed awareness of the importance of competencies for inclusive education, the need for their improvement and the efforts made by them in that direction.Through suggestions of activities that represent significant resources for inclusive education empowerment, teachers emphasize the importance of exchanging experiences with colleagues and the occasional involvement of mentors in immediate school practice, while the greatest help in school is expected from professional associates.In this regard, the obtained findings, although on a small sample of teachers, which can be considered as a limitation of the research, suggest the importance of creating various programs of school support and developing the competencies of teachers for inclusive education that would be realized, both in the school context and in the wider community.