Reviewerly/exHarmony huggingface dataset:
GX@DravidianLangTech-EACL2021: Multilingual Neural Machine Translation and Back-translation

In this paper, we describe the GX system in the EACL2021 shared task on machine translation in Dravidian languages. Given the low amount of parallel training data, We adopt two methods to improve the overall performance: (1) multilingual translation, we use a shared encoder-decoder multilingual translation model handling multiple languages simultaneously to facilitate the translation performance of these languages; (2) back-translation, we collected other open-source parallel and monolingual data and apply back-translation to benefit from the monolingual data. The experimental results show that we can achieve satisfactory translation results in these Dravidian languages and rank first in English-Telugu and Tamil-Telugu translation.
Bus Tracking App for Universities Transportation

Shuttle buses have become an important means of transportation for students especially for those who rely on it to go to class. However, students often face difficulty knowing the current location of the bus and its estimated arrival time. Some of them are even unaware of the bus schedule provided by higher management. Consequently, they have to wait too long for their respective buses to arrive. Hence, for the convenience of those who want to plan their journey with shuttle buses, two applications are proposed. One application will track the location of the bus and the other application will be used by the students. Both proposed applications will be used along with an Android phone since it is mostly used by students. The main objectives of developing this application are to inform users regarding the current bus location and estimated arrival time. This application also provides users real-time forum so they can start conversations with others with the same application. Besides, the driver's profile is alsoincluded for the user's future reference.
Artwork Identification in a Museum Environment: A Quantitative Evaluation of Factors Affecting Identification Accuracy

The ability to identify the artworks that a museum visitor is looking at, using first-person images seamlessly captured by wearable cameras can be used as a means for invoking applications that provide information about the exhibits, and provide information about visitors’ activities. As part of our efforts to optimize the artwork recognition accuracy of an artwork identification system under development, an investigation aiming to determine the effect of different conditions on the artwork recognition accuracy in a gallery/exhibition environment is presented. Through the controlled introduction of different distractors in a virtual museum environment, it is feasible to assess the effect on the recognition performance of different conditions. The results of the experiment are important for improving the robustness of artwork recognition systems, and at the same time the conclusions of this work can provide specific guidelines to curators, museum professionals and visitors, that will enable the efficient identification of artworks, using images captured with wearable cameras in a museum environment.
Conoscenze e competenze nell’educazione linguistica

Knowledge (declarative and procedural; tacit and epistemological; implicit and explicit; acquired and learned, operational and pragmatic knowledge); knowledge by acquaintance or by description; knowledge as commodity; competence; competency, capacity, ability, skill, mastery: these are the terms used to define the aims of educational linguistics, that is, knowledge about the language and competence in the language: the analysis vs. use pendulum that has been swinging for the last 25 centuries. The article tries to bring some terminological (and epistemological) order into this cluster of terms.
Creating an Aligned Russian Text Simplification Dataset from Language Learner Data

Parallel language corpora where regular texts are aligned with their simplified versions can be used in both natural language processing and theoretical linguistic studies. They are essential for the task of automatic text simplification, but can also provide valuable insights into the characteristics that make texts more accessible and reveal strategies that human experts use to simplify texts. Today, there exist a few parallel datasets for English and Simple English, but many other languages lack such data. In this paper we describe our work on creating an aligned Russian-Simple Russian dataset composed of Russian literature texts adapted for learners of Russian as a foreign language. This will be the first parallel dataset in this domain, and one of the first Simple Russian datasets in general.
Post-crisis Slowdown in the Korean Economy and Long-term Outlook

The Korean economy grew at an annual average rate of 3% in 2011-2018, which appears to be a downward trend and not a temporary setback. A prolonged growth accounting reveals that the Korean economy will likely grow to a low-to-mid 2% (annual average) in the 2020s when productivity is expected to improve through continued innovation. Thus, the government should make concerted policy efforts to improve productivity and to keep a close eye on the causes of the slow economic growth.
An Analysis on the Students’ Indirect Learning Strategies in Writing Skill

Abstract The problem of this study was “what are the indirect learning strategies in writing skill applied by the eleventh grade students of State Senior High School 12 Palembang?” The objective of this study was to find out what the indirect learning strategies in writing skill are applied by the eleventh grade students of State Senior High School 12 Palembang. This study used qualitative descriptive method. The population of this study was 232 of the eleventh grade students of State Senior High School 12 Palembang in the academic year of 2016 / 2017. The class of XI IPA 1 that consisted of 38 students was chosen as the sample of this study. The data was collected through the SILL questionnaire and documentation. The data obtained was analyzed by using SPSS version 20. Based on the study, it showed that eventhough there was no learning strategy applied by the students in the high use, but according to the average use of the strategy, metacognitive strategies (Mean = 3.28) became the most frequently strategies applied by the students, then, followed by affective strategies (Mean = 2.65), and the last was social strategies (Mean = 2.46). In conclusion, all the indirect learning strategies in writing skill that are metacognitive, affective, and social strategies were applied by the eleventh grade students of State Senior High School 12 Palembang. Keywords: Analysis, Indirect Learning Strategies, and Writing Skill
Research on the cultivation of College Students’ intercultural communicative competence based on the technology of multimedia immersion in 5G Era

One belt, one road initiative, China needs comprehensive talents with international vision, international working background, international finance and international economic management. In order to improve college students’ intercultural communicative competence, China attaches importance to foreign cultural exchange and comprehensively improves the cultivation of foreign communicative competence. Students’ awareness of cross-cultural communication is weak and their communicative competence is lacking. In addition to enriching students’ cross-cultural communication ability, it is urgent to cultivate students’ comprehensive language competence. The rapid changes and development of economic globalization and information technology have promoted the frequent communication between different cultures. Such a development trend also puts forward higher requirements for the talent training of university teaching at this stage. The teaching of each university pays more attention to the application ability of language knowledge and the ability of international communication and communication in the future work and social communication. In the actual teaching process, due to the lack of practical communicative situations, most of the teaching still stay in the aspects of historical and cultural background, mode of thinking, pragmatic principles, values and social norms of different nationalities, and there are few opportunities to experience the coding and decoding in actual communication, and the related obstacles and misunderstandings in the process are even more difficult to understand. Therefore, cross-cultural practice should be placed on the same important position as the cognition of language and culture knowledge. Combined with the rapid development of network information technology, the creation of optimized teaching and practice integration paradigm has become the research and development trend of cultivating cross-cultural communication ability in today’s information society.
Corpus extraction tool LIST 1.2

The LIST corpus extraction tool is a Java program for extracting lists from text corpora on the levels of characters, word parts, words, and word sets. It supports VERT and TEI P5 XML formats and outputs .CSV files that can be imported into Microsoft Excel or similar statistical processing software.Version 1.2 adds support for Gigafida 2.0 in XML format and fixes a bug which disabled the extraction of character-level n-grams from normalized forms in the GOS 1.0 corpus.
Penerapan Metode PIECES pada Analisis Sistem Informasi Manajemen Apotek

Pharmacy is one of the first public health services. The Management Information Sistem at a pharmacy that is still using a conventional sistem is only recorded on paper for all data management processes for drug ordering, drug purchases, drug purchase returns, drug sales, drug sales returns and taking stock. So that the information generated is less accurate. The data needed is sometimes lost or damaged when it is stored because it is still written on paper. The conventional sistem of pharmacies does the writing of sales reports on sales books that are done after making a sales transaction, sometimes it takes time because of the large amount of drug data that must be written. This results in the sales transaction service process taking a long time and complaints from consumers due to the long service process. In this research, the sistem will be designed using the waterfall sistem development method with the Data Flow Diagram (DFD) modeling flow. Then a sistem analysis will be carried out using the framework of Performance, Information, Economics, Control, Efficiency, Service (PIECES). The sistem analysis resulted from this research is a sistem that can be used to manage drug ordering data, drug purchase data, drug purchase return data, drug sales data, drug sales return data and drug taking stock data so that pharmacies can improve services to consumers more effectively and efficient. The application of the PIECES method in sistem design results in a comparison of the sistem process between the running sistem and the sistem being developed.
Sentiment Analysis of Dravidian Code Mixed Data

This paper presents the methodologies implemented while classifying Dravidian code-mixed comments according to their polarity. With datasets of code-mixed Tamil and Malayalam available, three methods are proposed - a sub-word level model, a word embedding based model and a machine learning based architecture. The sub-word and word embedding based models utilized Long Short Term Memory (LSTM) network along with language-specific preprocessing while the machine learning model used term frequency–inverse document frequency (TF-IDF) vectorization along with a Logistic Regression model. The sub-word level model was submitted to the the track ‘Sentiment Analysis for Dravidian Languages in Code-Mixed Text’ proposed by Forum of Information Retrieval Evaluation in 2020 (FIRE 2020). Although it received a rank of 5 and 12 for the Tamil and Malayalam tasks respectively in the FIRE 2020 track, this paper improves upon the results by a margin to attain final weighted F1-scores of 0.65 for the Tamil task and 0.68 for the Malayalam task. The former score is equivalent to that attained by the highest ranked team of the Tamil track.
Multiset relations and multigroups under tn-norm

Multi Set Relations and Multi Groups under Tn-norm(ABSTRACT)In this paper , first we introduce the properties and theorems of the multi groups . After , we describe the results of the isomorphisms in multi groups , We show that how a multi group can be generated another non constant multi group under a proper binary operator, , call it t n norm . In fact, under an arbitrary t n norm to a multi group, we obtain the other multi group and examine their interactions . We use this process to generate a non constant multi group of a multi set relation under an arbitrary t n norm . We also present at the end an application of the concepts presented for generating usage encryption .K E Y W O R D S : Group , Multi set , Multi set relation , Multi group , T n norm .
IMPROVING STUDENTS’ READING COMPREHENSION THROUGH RECIPROCAL TECHNIQUE.

The objective of this research is to find out that Reciprocal technique can improve students’ reading comprehension of second year students of SMP Negeri 19 Palu. The researcher was conducted the research to the second years students at SMPN 19 Palu. This research applied quasi-experimental research design. The samples of this research were class VIII B as the experimental class that consist 19 students and class VIII D as control class that consist of 19 students. They were selected by using purposive sampling. The instrument of data collection in this research were tests that were divided into pre-test and post-test. There is significant different in pretest and posttest. It can be seen at the mean score of both tests’ results, the mean score of experimental group significantly increased from 40.18 to 68.95. The mean score of control group improved from 40.16 to 40.35. Based on the result of the pre-test and post-test, the researcher found that the value of t-counted is 3.98. By applying degree of freedom (df) 36 (19+19-2) and 0.05 level of significance, the researcher found that the value of t-table is 1.69 which shows that the value of t-counted (3.98) is higher than the value of t-table (1.69). Keywords: Improving, Reading Comprehension, Reciprocal Technique. Abstrak Tujuan dari penelitian ini adalah untuk mengetahui bahwa teknik Reciprocal dapat meningkatkan pemahaman membaca siswa kelas dua SMP Negeri 19 Palu. Peneliti melakukan penelitian terhadap siswa kelas dua di SMPN 19 Palu. Penelitian ini menggunakan desain penelitian eksperimen semu. Sampel penelitian ini adalah kelas B sebagai kelas eksperimen yang terdiri dari 19 siswa dan kelas VIII D sebagai kelas kontrol yang terdiri dari 19 siswa. Mereka dipilih dengan menggunakan purposive sampling. Instrumen pengumpulan data dalam penelitian ini adalah tes yang dibagi menjadi pre-test dan post-test. Ada perbedaan signifikan pada pretes dan postes. Hal ini dapat dilihat pada skor rata-rata dari kedua hasil tes, skor rata-rata kelompok eksperimen meningkat secara signifikan dari 40,18 menjadi 68,95. Skor rata-rata kelompok kontrol meningkat dari 40,16 menjadi 40,35. Berdasarkan hasil pre-test dan post-test, peneliti menemukan bahwa nilai t-hitung adalah 3,98. Dengan menerapkan derajat kebebasan (df) 36 (19 + 19-2) dan tingkat signifikansi 0,05, peneliti menemukan bahwa nilai t- tabel adalah 1,69 yang menunjukkan bahwa nilai t-hitung (3,98) lebih tinggi dari nilai t-tabel (1.69). Kata kunci: Peningkatan, Pemahaman Membaca, Teknik Reciprocal.
ThaiWritableGAN: Handwriting Generation under Given Information

For the local technique challenge, Thai has different symbols' vertical positions with no space between characters and words.Thai handwriting recognition has been a long time research problem.To join the edge between unsupervised Generative adversarial network (GAN) and Thai handwriting recognition, this paper introduces a novel Thai handwriting generation under given information (named "ThaiWritableGAN").ThaiWritableGAN is proposed to map textual information with real handwritten data to generate a new handwritten style (a.k.a.calligraphy).The proposed algorithm consists of generator (G), discriminator (D), and recognizer (R).The synthesized (or generated) handwritten sample is done by G which is proposed to fool D. D is assigned to discriminate an unknown handwritten image that it is real or generated.R is a convolutional neural network (pre-trained by real Thai handwritten images) that is additionally added to recognize the synthesized images (generated by G).For the scientific knowledge discovery, self-attention mechanism (introduced by Google AI) and R totally boost more realistic Thai handwriting generation as well as other languages.The gradient balancing argument should be set to 1.The word error rate (WER) can be relieved by computational reduction in R's gradient.But the reduction affects a little lower realistic quality of Thai handwriting, measured by Fréchet inception distance (FID).For the beyond following, Thai handwriting generation competition might be opened that the local researchers can submit their handwriting generation algorithms to the calligraphy contest.
Evaluation of Taxonomy Enrichment on Diachronic WordNet Versions

The vast majority of the existing approaches for taxonomy enrichment apply word embeddings as they have proven to accumulate contexts (in a broad sense) extracted from texts which are sufficient for attaching orphan words to the taxonomy. On the other hand, apart from being large lexical and semantic resources, taxonomies are graph structures. Combining word embeddings with graph structure of taxonomy could be of use for predicting taxonomic relations. In this paper we compare several approaches for attaching new words to the existing taxonomy which are based on the graph representations with the one that relies on fastText embeddings. We test all methods on Russian and English datasets, but they could be also applied to other wordnets and languages.
Automated Classification of Written Proficiency Levels on the CEFR-Scale through Complexity Contours and RNNs

Automatically predicting the level of second language (L2) learner proficiency is an emerging topic of interest and research based on machine learning approaches to language learning and development. The key to the present paper is the combined use of what we refer to as ‘complexity contours’, a series of measurements of indices of L2 proficiency obtained by a computational tool that implements a sliding window technique, and recurrent neural network (RNN) classifiers that adequately capture the sequential information in those contours. We used the EF-Cambridge Open Language Database (Geertzen et al. 2013) with its labelled Common European Framework of Reference (CEFR) levels (Council of Europe 2018) to predict six classes of L2 proficiency levels (A1, A2, B1, B2, C1, C2) in the assessment of writing skills. Our experiments demonstrate that an RNN classifier trained on complexity contours achieves higher classification accuracy than one trained on text-average complexity scores. In a secondary experiment, we determined the relative importance of features from four distinct categories through a sensitivity-based pruning technique. Our approach makes an important contribution to the field of automated identification of language proficiency levels, more specifically, to the increasing efforts towards the empirical validation of CEFR levels.
A Novel Approach to Store an Image in QR Code

: Quick Response Code is a machine-readable, two-dimensional barcode consisting of an array of black and white squares which can be scan quickly by any smartphone. It allows encoding over 4000 pulse characters in a two-dimensional barcode. It is used to store a small amount of information like web URL, item data, phone numbers and multimedia data. Due to restricted size in it, QR codes are presently limited in the extent to store the data. But the data in image format uses more space, if you want to store image data in QR code you must enlarge the storage capacity of QR code. In this paper, we propose a very simple form of lossy data compression, in which runs of data is dividing into blocks of equals size. The entire block is stored as a character rather than as the original run with generic HashMap which makes more robust and provides all sorts of security. Finally, our results are compared with other techniques to differentiate the optimality, efficiency of the new technique for producing optimal QR codes.
Privacy by Design by Regulation: The Case Study of Ontario

&lt;p&gt;A study of two cases in which Ontario organizations, the Toronto Transit Commission (TTC) and the Ontario Lottery and Gaming Commission (OLG), attempted, with the support of the Information and Privacy Commissioner at the time, Ann Cavoukian, to design privacy into their use of closed circuit surveillance cameras (CCTV). The study examines the role of the regulator in facilitating Privacy by Design (“PbD”) solutions. With the introduction of PbD into the European Union General Data Protection Regulation (GDPR), it is important to understand the conditions under which PbD can succeed and the role which regulators can play (if at all) in promoting such success. The findings are organized into three overarching themes: PbD-focused findings, leadership and organizational findings, and regulator-focused findings. The article argues that privacy continues to persist as an engineering problem despite PbD, that (related to that) there is growing recognition of privacy as an issue of organizational change and leadership, and consequently, that the role of the regulator must evolve if PbD is to become a meaningful regulatory tool, an evolution that carries with it both risks and opportunities for privacy.&lt;/p&gt;
OffTamil@DravideanLangTech-EASL2021: Offensive Language Identification in Tamil Text

In the last few decades, Code-Mixed Offensive texts are used penetratingly in social media posts. Social media platforms and online communities showed much interest on offensive text identification in recent years. Consequently, research community is also interested in identifying such content and also contributed to the development of corpora. Many publicly available corpora are there for research on identifying offensive text written in English language but rare for low resourced languages like Tamil. The first code-mixed offensive text for Dravidian languages are developed by shared task organizers which is used for this study. This study focused on offensive language identification on code-mixed low-resourced Dravidian language Tamil using four classifiers (Support Vector Machine, random forest, k- Nearest Neighbour and Naive Bayes) using chiˆ2 feature selection technique along with BoW and TF-IDF feature representation techniques using different combinations of n-grams. This proposed model achieved an accuracy of 76.96% while using linear SVM with TF-IDF feature representation technique.
Growing the Nigerian Economy

The Nigerian economy has witnessed persistent decline over time, as a result of fall in global oil prices. The external shock has had unintended consequences for the Nigerian economy: dwindling revenues, decrease in the economic growth, increase in youth restiveness and an increase in the levels of unemployment. Thus far, there has been no holistic government policy or initiatives targeted at addressing the challenges of the Nigerian youth. It is recommended that piecemeal approach by the Nigerian government should be addressed. A youthful development initiative that adopts a holistic approach should be designed to resolve the problems of the Nigerian youth. In doing so, the government should focus on strengthening existing institutions, enhancing human capital development, creating a platform and environment to enable young entrepreneurs build businesses and provide critical solutions to the many existing economic problems.
Best Headphones For Elementary School Computer Lab

It is almost impossible not to notice childrens excitement when they’re engaged in learning activities that they love, especially if the activity ...