Reviewerly/exHarmony huggingface dataset:
Improving Students’ Vocabulary Mastery through Word Wall Method at Ninth Graders of SMPN 1 Mamuju

This research was a classroom action research (CAR). The objective of this research was to find out students’ vocabulary mastery especially its application in a correct sentence pattern by using Word Wall method to the ninth grade students of SMP Negeri 1 Mamuju. This research consisted of three cycles. There were 30 students in one class that followed this research. The result showed there was improvement of the students’ vocabulary. It could be seen on their average score in the first cycle improved by 49.25%, from the diagnostic test 34.83%. Then, it improved more in the second cycle by 60.8% and more in the third cycle that achieves 68.25%. However, despite getting the students’ average score improved, after applying the three cycles, it is still not success achieving the Minimum Completeness Criteria (MCC) of the subject that was 75.
Study of Fake News Dissemination Articles on Criminal Code Regulations, Law of Information and Electronic Technology, and also Law of Terrorism Criminal Act Eradication

Proceedings INTERNATIONAL CONFERENCE FAKE NEWS AND ELECTIONS IN ASIA, Bangkok, Thailand, 10-12 July 2019
Pengaruh Media Power Point Tematik-Integratif dan Motivasi Belajar Terhadap Hasil Belajar Siswa Kelas IV SD N Kleco 1 Surakarta

The aim of this study were to know: 1) To determine the effect of thematic integrative power point media on the fourth grade students’ achievement at Elementary School Kleco I Surakarta. 2) To determine the effect of the students’ learning motivation on the fourth grade students’achievement at Elementary School Kleco I Surakarta. 3) To determine the effect of thematic integrative power point media and students’learning motivation on the fourth grade students’ achievement at Elementary School Kleco I Surakarta. This study was a cualitative design with intact-group compariso design. In this design, there is one group that is used in the study but is divided into two was part of pre-experimental design. Questionnaire and test rest was used to collecting the data. Simple linier regresion and doble regresion were used to analyze the data. Base on the data analysis, there was no effect on the experiment class and contriol class. The point were 28,72% on the experimen class and 12,96% on the control class with the significant falue 5%. And in the thematic-integrative power point media to the learning achievemen, there was no effect. The point were 21,35% on the experiment class and 18,21% on the control class with significant falue 5%. Therefore in the learning motivation to the learning achievement there was no effect at 19,6% with the significant falue 5%. There was no effect on the learning motivation to the learning achievement in the conclusion, thematic-integrative power point media and learning motivation has no contribusion on the fourth grade student’s learning achievement at Elementary School Kleco I Surakarta.
Symmetric hidden state model for trust-less entanglement witness

We introduce a symmetric local hidden state $(slhs)$ model in a scenario, where two spacially separated parties receive quantum states from an unknown source. We derive an inequality based on the model. A completely new form of nonlocality emerges from the resource theoretic point of view. The inequality singles out a larger set of quantum correlated states in the higher dimensional scenarios $(d> 2 $ X $2)$ than what is predicted by the existing $lhs$ model, opening a new front for the experimentalists to test the accuracy of the prediction. We propose an experiment to show the experimental violation of the inequality in the two qubit scenario and perform the experiment on the IBM quantum computer. However, the experimental method adopted for the two-qubit scenario does not naturally generalize in the higher dimensional scenarios and leaves the experimental verification of the claim open. We also show that the maximal violation of the inequality can be used to self-test the Bell state and measurement bases, leading to complete device-independence.
Peningkatan keterampilan membaca puisi melalui penggunaan model pembelajaran cooperative script pada kelas IV sekolah dasar

The purpose of this research is to improve poetry reading skills through the use of cooperative script learning models. Data collection technique are using test, interview, observation,and documentation. Data validity test are using content validity, source trianggulation, and technique trianggulation. Data analysis technique used is the interactive analysis and descriptive comparative. The results showed the average value of pre-action class 61.80, cycle I 72.29, and in the second cycle 81.31. Pre-action classical completeness 27.78%, first cycle 55.56%, and in the second cycle 83.33%. The value of the pre-action pronunciation is 15.27, the first cycle is 18.19, and the second cycle is 19.58. The value of the pre-action intonation is 14.44, the first cycle was 16.94, and the second cycle was 19.02. The value of the pre-action expression is 15.83, the first cycle is 18.96, the second cycle is 21.64. The value of the pre-action appreciation is 16.25, the first cycle is 18.33, and the second cycle is 21.04. Based on the result of the research, it can be concluded that through the use of cooperative script learning models can improve the poetry reading skills for fourth grade students of SD N Kismantoro 2 Wonogiri in the academic year 2018/2019.
INFORMATION TECHNOLOGIES IN THE CONTEXT OF FORMING THE DIGITAL COMPETENCE OF FUTURE TEACHERS

The article analyzes information technologies as components of the formation of the digital competence of future primary school teachers, focuses on practically oriented online resources (Canva, Paint Kards, VivaVideo-Video Editor & Photo Movie, mozaBook, etc.). Modernization of all spheres of modern life results in changes in the educational environment. The integration of information technologies into the formation of the digital competence of future teachers at the lessons of the linguistic and literary direction is due to the problem of losing the interest of schoolchildren in the book and reading in general. Therefore, it is quite logical to use close to modern children new technologies, since the student of the XXI century needs not only the updating of technical support, but also teaching methods. Thus, a modern teacher of the primary school in the context of the formation of digital competence must have the full range of available innovative instruments. It has been highlighted that modern information technologies, combining various possibilities, being universal, can imitate educational toys and games, at the same time they act as an equal partner, able to respond subtly to relevant actions and inquiries. In this area, educational institutions are being increasingly provided with computers, projectors, interactive whiteboards, tablets, e-books, whiteboards of the new generation of ЕdPrо Tоuch and mozaBook software. All this requires a teacher to be a professional who can work in a team, creatively approach the organization of the educational process. DOI: https://doi.org/10.28925/2414-0325.2019 s36
Research Guides: Applied Geophysics - Spring 2019: Avoiding Plagiarism

This guide was created specifically for Dr. Kristina Keating's class - Spring 2019 (Note the sub-page: Citation Managers)
On Boosting Semantic Street Scene Segmentation with Weak Supervision.

Training convolutional networks for semantic segmentation requires per-pixel ground truth labels, which are very time consuming and hence costly to obtain. Therefore, in this work, we research and develop a hierarchical deep network architecture and the corresponding loss for semantic segmentation that can be trained from weak supervision, such as bounding boxes or image level labels, as well as from strong per-pixel supervision. We demonstrate that the hierarchical structure and the simultaneous training on strong (per-pixel) and weak (bounding boxes) labels, even from separate datasets, consistently increases the performance against per-pixel only training. Moreover, we explore the more challenging case of adding weak image-level labels. We collect street scene images and weak labels from the immense Open Images dataset to generate the OpenScapes dataset, and we use this novel dataset to increase segmentation performance on two established per-pixel labeled datasets, Cityscapes and Vistas. We report performance gains up to +13.2% mIoU on crucial street scene classes, and inference speed of 20 fps on a Titan V GPU for Cityscapes at $512 \times 1024$ resolution. Our network and OpenScapes dataset are shared with the research community.
Virtual Reality in the Product Development in the Fashion Industry : Application Areas, Opportunities, and Challenges of Virtual Reality in the Product Development

The purpose of this thesis is to examine how Virtual Reality can be applied in the product development in the fashion industry. Therefore, the research focuses on potential areas of application as ...
BUILDING THE YOUNG LEARNERS ENGLISH VOCABULARY BY USING THE SMART CARD AT MBS SANG SURYA

Abstract: Smart card  as a medium of teaching language is regarded as central elements of the approach because it can be used as media to attract the young learners interest in learning language especially English language. The writer try to adopt this media in the classroom, especially by using a smart card to make  the  lesson  more easier and  interesting for the young learners to build their vocabulary in english. In relation, the purpose of this research is to investigate does the use of smart card has effect in building vocabulary in english to MBS DayCare learners. The researcher applied true exprimental research design as the methodology with 20 young learners as the population and all of them taken as a sample by using rubric and t-test formula theory according Hughes. The researcher collect the data by using testing method. The result of this research showed that mean score of experimental group 8 and mean score of control group 7. Based on t-test, it showed that t- value 3,782 and after cosulting to t-table, the t-value was higher than t-table. The smart card in vocabulary learning process is more effective to enrich the learners’ vocabulary, this can be seen from the results of test score that the experimental class which was given treatment using smart card media got higher score than control class without taught by used smart card  media. The writer concluded that smart card has an effect in building vocabulary in english at Daycare learners in Muhammadiyah Boarding School (MBS) Sang Surya. Abstrak : Tujuan dari penelitian ini adalah untuk menyelidiki apakah penggunaan kartu pintar berpengaruh dalam membangun kosa kata dalam bahasa Inggris untuk pelajar MBS DayCare. Peneliti menerapkan desain penelitian exprimental sejati sebagai metodologi dengan populasi 20 siswa sebagai populasi dan semuanya diambil sebagai sampel dengan menggunakan teori rumus rubrik dan uji-t menurut Hughes. Peneliti mengumpulkan data dengan menggunakan metode test. Hasil penelitian ini menunjukkan bahwa skor rata-rata kelompok eksperimen adalah 8 dan skor rata-rata kelompok kontrol adalah 7. Berdasarkan uji-t, menunjukkan bahwa nilai t-hitung sebesar 3,782 dan setelah korelasikan dengan t-tabel, t-hitung lebih tinggi daripada t-tabel. Kartu pintar dalam proses pembelajaran kosakata lebih efektif untuk memperkaya kosakata peserta didik, hal ini dapat dilihat dari hasil skor tes bahwa kelas eksperimen yang diberi perlakuan menggunakan media kartu pintar mendapat skor lebih tinggi daripada kelas kontrol tanpa diajar dengan menggunakan media kartu pintar. Penulis menyimpulkan bahwa kartu pintar berpengaruh dalam membangun kosa kata dalam bahasa Inggris.
Practice and Research on the College English Teaching Reform under Network Multimedia Environment

As an international language and a key examination-oriented subject that throughout most of the educational experience, English accounts for a very high proportion in higher education and academic research. At the same time, as a popular course of university learning, English teaching reform under network multimedia environment in the new era is of great significance for the guidance of teaching, the accumulation of students' learning experience, the improvement of learning and academic research ability in the future.
An Interactive Visual Analytics Tool for Big Earth Observation Data Content Estimation

This paper introduces a tool designed to provide an innovative and insightful way of exploring Earth observation data content beyond visualization, by addressing a visual analytics process. The considered framework combines machine learning and visualization techniques, empowered through human interaction, to gain knowledge from the data. The proposed tool- eVADE leverages the methodologies developed in the fields of information retrieval, data mining and knowledge representation by the means of a visual analytics component. eVADE increases users capability to understand and extract meaningful semantic clusters together with quantitative measurements, presented in a suggestive visual way.
VIRTUAL REALITY AND OLDER ADULTS: A USABILITY STUDY

Abstract Within the past two years there has been a very small but growing number of scholarly articles that highlight the potential benefit of mobile Virtual Reality (VR) platforms among older adult populations. Yet, it is critical to assess older adult user needs and preferences, as well as ethical considerations, before utilizing VR in applied contexts. This pilot study investigated perceptions of VR use and its potential application by individually interviewing ten community-dwelling older adults (ages 63 to 89) both before and after trying the Samsung Gear VR and followed with two focus group discussions. Themes identified from the transcripts include 1) usability, 2) video subject matter preferences, and 3) implications with use. These themes highlighted both the challenges and opportunities of VR use among a wide range of older populations, and provided greater insight with its exploration and application in future studies, particularly with individuals with functional limitations.
KEEFEKTIFAN STRATEGI MENULIS TERBIMBING UNTUK MENINGKATKAN KETERAMPILAN MENGARANG NARASI DI KELAS IV SD NEGERI 003 TASIK JUANG

This research is motivated by the low learning outcomes of students' narrative writing skills at SDN 003 Tasik Juang. This research was conducted in class IV with a total of 25 students. The purpose of this study is to improve students' narrative writing skills by implementing guided writing strategies. This research is a class action research consisting of two cycles with stages of planning, action, observation and reflection. The results showed in learning 1 the number of students who completed as many as 19 people with a percentage of 76% and as many as 6 people who did not complete with a percentage of 24%. In learning 2 the number of students who completed as many as 21 people with a percentage of 84% and as many as 4 people who did not complete with a percentage of 16%. In learning 3 the number of students who completed as many as 22 people with a percentage of 88% and as many as 3 people who did not complete with a percentage of 12%. In the last study, the number of students who completed as many as 23 people with a percentage of 92% and as many as 2 people who did not complete with a percentage of 8%. Based on the results of this study it can be concluded that the implementation of the guided writing strategy has proven to be effective in improving the learning outcomes of narrative writing skills of the fourth grade students of SDN 003 Tasik Juang.
Gesture to Speech Conversion

Sign language is a primary mode of communication for people with language disabilities. This language uses a set of representation that is a sign of finger, expression or mixture of both to express their information among others. This system presents a new approach for translation based on mobile application of analysis of sign, recognition and generation of a textual description in Kannada language. We use two important steps of training and testing. In training, 50 different domains of video samples are collected, each domain contains 5 samples and assigns a class of words to each video sample and will be stored in the database. During the test, the sample is pre-processed using a median filter, a smart operator for edge detection, HOG (Histogram Oriented Gradients) is used for the extraction of features. SVM (Support Vector Machine) takes the input as a HOG feature and predicts the class label based on the trained SVM model. Finally, in the Kannada language, the text description will be produced. The average calculation time is minimal and with an acceptable recognition rate and validates the performance efficiency compared to the conventional model.
John J. McCarthy and Joe Pater (eds.): <i>Harmonic grammar and harmonic serialism</i>.

This volume contains chapters that explore and extend advances in formal investigations of grammar that employ violable constraints in the analysis of individual languages, the study of linguistic typology, and the learnability of grammars. Initial investigations in a generative framework that employs violable constraints took place in Optimality Theory (OT) (Prince & Smolensky, 1993/2004). It is worth noting that although “representational constraints had of course long existed as a means of formally expressing restrictions on linguistic structures, […] the notion that one constraint could compel the violation of another had never been given much attention before OT” (p. vii). The violable constraints in OT are strictly ranked with respect to one another, preventing the possibility of multiple violations of lower-ranked constraints accumulating and ‘ganging up’ on higher ranked ones. Harmonic Grammar (HG) is an alternative version of a grammar model that employs violable, ranked constraints (as is commonplace in OT) which uses weighted constraints in place of strictly ranked ones. Pater (this volume) highlights two potential advantages that an HG may have over an OT-model: Firstly, as initially noted by Prince (2003), there are asymmetric trade-offs on gang effects (based on the fact that the weighted constraint violations in HG can lead to gang effects of lower weighted constraints under certain circumstances), which are simply not possible in OT. Secondly, “the promise of weighted constraint theories of Universal Grammar derives from the ability of HG to generate attested patterns that fall out of the reach of OT using the same sets of constraints” (p. 2). Here Pater points to previous research (in particular, Flemming, 2001) that shows the difficulty that OT has in establishing compatibility with scalar constraints. This potential issue purportedly receives a more straightforward account in HG. The inclusion of weighted constraints permits new theories concerning which constraints (Con) exist. Initially, analyses in OT assumed a parallel theory of candidate generation and evaluation. There is no reason, however, that single iterative applications of the generation (Gen) and evaluation (Eval) of candidates cannot replace parallel evaluations. Harmonic Serialism (HS), see McCarthy (this volume) for a detailed introduction, combines the inclusion of weighted violable constraints in serial evaluation of candidates. The contributions in this volume consist of studies that show the advantages and challenges associated with current research within the HG and HS models.
Thermal to Visible Face Recognition Using Deep Autoencoders

Visible face recognition systems achieve nearly perfect recognition accuracies using deep learning. However, in lack of light, these systems perform poorly. A way to deal with this problem is thermal to visible cross-domain face matching. This is a desired technology because of its usefulness in night time surveillance. Nevertheless, due to differences between two domains, it is a very challenging face recognition problem. In this paper, we present a deep autoencoder based system to learn the mapping between visible and thermal face images. Also, we assess the impact of alignment in thermal to visible face recognition. For this purpose, we manually annotate the facial landmarks on the Carl and EURECOM datasets. The proposed approach is extensively tested on three publicly available datasets: Carl, UND-X1, and EURECOM. Experimental results show that the proposed approach improves the state-of-the-art significantly. We observe that alignment increases the performance by around 2%. Annotated facial landmark positions in this study can be downloaded from the following link: github.com/Alpkant/Thermal-to-Visible-Face-Recognition-Using-Deep-Autoencoders .
Use Case Prediction Using Product Reviews Text Classification

Research into sentiment analysis and its capabilities at analysing product reviews has increased tremendously in recent years. In this paper, we propose an approach to classify product reviews and identify use cases. Several iterations showing the application of natural language processing techniques and machine learning classifications are depicted. A number of machine learning classifiers are trained/tested in various iterations, their performance and accuracy at predicting the existence of use cases in product reviews is evaluated.
Verifying OpenJDK’s LinkedList using KeY

As a particular case study of the formal verification of state-of-the-art, real software, we discuss the specification and verification of a corrected version of the implementation of a linked list as provided by the Java Collection framework. Keywords: Java, standard library, deductive verification, KeY, Java Modeling Language, case study, bug
MBCAL: A Simple and Efficient Reinforcement Learning Method for Recommendation Systems

It has been widely regarded that only considering the immediate user feedbackis not sufficient for modern industrial recommendation systems. Many previousworks attempt to maximize the long term rewards with ReinforcementLearning(RL). However, model-free RL suffers from problems includingsignificant variance in gradient, long convergence period, and requirement ofsophisticated online infrastructures. While model-based RL provides asample-efficient choice, the cost of planning in an online system isunacceptable. To achieve high sample efficiency in practical situations, wepropose a novel model-based reinforcement learning method, namely themodel-based counterfactual advantage learning(MBCAL). In the proposed method, amasking item is introduced in the environment model learning. With the maskingitem and the environment model, we introduce the counterfactual futureadvantage, which eliminates most of the noises in long term rewards. Theproposed method selects through approximating the immediate reward and futureadvantage separately. It is easy to implement, yet it requires reasonable costin both training and inference processes. In the experiments, we compare ourmethods with several baselines, including supervised learning, model-free RL,and other model-based RL methods in carefully designed experiments. Resultsshow that our method transcends all the baselines in both sample efficiency andasymptotic performance.
Bulk Subscription to YANG Event Notification

This document defines a YANG data model and associated mechanism thatallows subscriber applications to bulk subscribe to publishers'event streams based on their requirements. And it also allows thepublishers to report multiple event streams or subscriptions into asingle notification message based on group identifier affiliation.
PAC-Bayesian Theory for Domain Adaptation

As recalled in section 1.2.3, the PAC–Bayesian theory offers tools to derive generalization bounds for models that take the form of a weighted majority vote over a set of functions that can be the hypothesis space. In this section, we recall the work done by Germain et al. on how the PAC–Bayesian theory can help to theoretically understand domain adaptation through the weighted majority vote learning point of view.