Reviewerly/exHarmony huggingface dataset:
EnAsCorp1.0: English-Assamese Corpus

The corpus preparation is one of the important challenging task for the domain of machine translation especially in low resource language scenarios. Country like India where multiple languages exists, machine translation attempts to minimize the communication gap among people with different linguistic backgrounds. Although Google Translation covers automatic translation of various languages all over the world but it lags in some languages including Assamese. In this paper, we have developed EnAsCorp1.0, corpus of English-Assamese low resource pair where parallel and monolingual data are collected from various online sources. We have also implemented baseline systems with statistical machine translation and neural machine translation approaches for the same corpus.
다문화가정 학습자를 위한 국어교육 방안 연구

In 2018, the Ministry of Public Administration and Security reported that the number of foreigners staying in Korea stood at 1.86 million, or 3.6% of the total population. The 2018 Education, Statistics and Service data show that a total of 121,783 students from multicultural families are attending school education, accounting for 2.18% of the total number of students. 93,027 (3.43%), 18,068 middle school students (1.35%), and 10,688 high school students (0.6%).The language ability and difficulty in Korean language education of multicultural families are leading to difficulties in school life and the relationship between friends. Therefore, as a way to improve their language skills and Korean language education, it is suggested that multicultural families learn more by using children's literature and fairy tales.A learner-centered learning model using fairy tales was constructed to improve the language skills and Korean language education skills of multicultural families.The learning period consisted of 3 months, 12 weeks (12 time), 2 times a week, and 40 minutes of each class. Using this learning model, professor-learning will have beneficial meanings to improve the language skills and Korean language education of certain subjects such as multicultural families.(Kyungpook National University)
PEDAGOGICAL ASPECTS OF CHILDREN’S COOPERATION IN THE COURSE OF TEACHING NATURAL SCIENCE

The article is devoted to the formation and development in primary school children of the ability to work in a group (team) by means of creating pedagogical conditions for organizing and conducting a group form work. It presents methods and techniques, criteria for diagnosing the level of these skills. The article substantiates the importance of group work, identifies difficulties in the organization of joint activities of pupils and provides recommendations to overcome them. It uncovers effective methods and techniques of group work organization while studying natural science at primary school. Ggoup work requires a well-thought-out system of actions on the part of a teacher, both at the stage of developing group tasks, and at lessons themselves in the course of organizing them.
*Improving Natural Language Queries Search and Retrieval through Semantic Image Annotation Understanding

Retrieving images using detailed natural language queries remains a difficult challenge. Traditional annotation-based image retrieval systems using word matching techniques cannot efficiently support such query types. Significant improvements for this problem can be achieved with a semantic understanding for those query sentences and image annotations. This paper presents a two-stage semantic understanding approach for natural language query sentences. At the first stage, the Stanford parser and a designed rule-based relation extraction tool are used in triple extraction process to efficiently extract the objects attributes, instances and natural language annotations relationships involving these objects. The second stage integrates the extracted relations with external commonsense knowledge source in a mapping process to provide high-level semantic meanings to the extracted triples. Experiments are conducted for evaluating the benefit of the proposed semantic understanding against a testing set of natural language sentences from the Flickr8k dataset. The results show that the proposed approach succeeds to extract relational triples with average accuracy value of 97% for the different types of annotations relationships: attributes and instance relations, multiword dependence relations, and semantic relations.
A Blockchain Implemented Fast P2P Instant Messaging Application

Supervisor: Dr. Chan, Wing Kwong Ricky; First Reader: Dr. Lau, Rynson W H; Second Reader: Prof. Tan, Kay Chen
The Effect of Severity of Addiction and Abstinence Self-efficacy to Drug Craving in Narkotics Abusers

Drug craving is a subjective motivation where users feel they want to go back to using narcotics. Drug craving is closely related to relapse. Rehabilitation carried out will be in vain when the abuser has stopped using narcotics but then reuse (relapse), so it is important to know what factors can influence drug craving. This study aims to examine the effect of the severity of addiction and abstinence self efficacy on drug craving in drug abusers. In this study, there were 100 stimulant narcotics abusers who were running a rehabilitation program somewhere. Data were analyzed using multiple regression analysis. The results showed that there was a significant effect of addiction severity and abstinence of self efficacy on drug craving with a significant value of 0.000 (p <0.05).
무용 읽기 교수-학습의 구조

Education that determines individual culture styles and forms of life is demanding environments in which people can be free from limited worlds of knowledge in a society of particular times. In such contexts, the need for dance literacy education is being demanded as another form the awareness of worlds that broaden the horizons of our lives with cultural understanding.Therefore, this study was conducted to reveal the educational role of dance literacy along with the characteristics of learning in dance literacy education and the contents are as follows.Through interpretative attitudes in which records are examined and explored, dance literacy provides guidance so that universal commonness as human citizens and distinct characteristics in regional and cultural environments can be perceived.As the purpose of dance literacy education is in problem discovery rather than problem solving, dance literacy learning provides experience material and background knowledge and allows the relationships between certain things to be sensed through experiences, thus increasing understanding and the ability to interpret.A sense of understanding awakened through dance literacy learning discovers the relationships of the world and contributes to the formation of a cultural identity that reflects on its own existence within those relationships.All parts of dance literacy that make approaches towards cultural understanding and an understanding of media serve as grounds for the understanding of the spirituality of human nature and revelations were made of expansions of the mind, or in other words, the expansion of knowledge through processes in which records are examined and understood.The accessibility of dance literacy learning is individuality that understands and interprets everything from universal values of mankind to unique characters.
Social Media Analytics: The Next Big Thing?

The emergence of Internet and Social media has created huge opportunities for marketers to know their customers. User generated content and consumer generated media have brought social networking to a new altitude. People are eager to share what they think, what they prefer and companies are taking its advantage to the maximum. It is not only the one side of the coin which is being benefitted, consumers are also gaining in the form of improved information and opinion from users. For various companies, social media platforms have become primary source of personal information of users. Social media analytics help marketers to identify segments and know customer's appeal towards a particular brand. The present study focuses on the emergence of social media analytics and modelling. It has been observed that despite enormous benefits, companies in developing countries like India are unable to exploit the opportunity to the fullest. The present study is based on exploratory research design where extant review of literature has been carried out. It also focuses on the various methods used by marketers to derive decisions out of data available on the social media platforms. The study also includes a systematic arrangement of reviews and comments collected from a social media platform and a sentiment analysis is being conducted on the data collected. Finally this paper contributes to the area of SMA and induces marketers towards a wise use of social media analytics in their business.
Dampak Covid-19 Terhadap Kegiatan Pembelajaran Online Di Sd Negeri 157013 Sibabangun 5 Tapanuli Tengah

COVID-19 is an outbreak of disease originating from China which spread rapidly throughout the world. COVID-19 spread in Indonesia in early March 2020. This study aims to identify online learning activities at the homes of students as an effort to support government programs namely study from home during the covid 19 pandemic. The spread of this virus caused losses to several countries, especially in the field of economy. In the field of education, it also changed the learning model drastically; all learning activities are carried out online starting from elementary school level to university level. This research is a qualitative descriptive study describing online learning activities at a elementary school 157013 Sibabangun 5 after the stipulation of all learning activities carried out from home in online mode. Interview was used to collect the data from 2 students, 2 Teachers and 1 Student parents. Based on the interview results, online learning activities at this university have been effective by utilizing the Zoom, Google Classroom, Whatsapp applications. Constraint in implementing online learning mostly is internet connection problems that less supportive.
Leadership Styles and Corporate Social Performance: The Mediatory Role of CSR Based on Stakeholders Approach

Firms that we're able to develop competitive advantages in CSR using proactive environmental and social strategies, achieve superior social and economic performance. However, the big challenge is to recognize the factors that are shaping organizational strategies towards CSR. In particular, we attempt to answer, how leadership styles influences CSR based strategies, and how these strategies inurn affect social and environmental performance. For this, we proposed a theoretical framework that explained different leadership styles (Transformational, Ethical, and Servant) that have a different effect on corporate social and environmental performance through adopting CSR strategies targeted to different stakeholders. We also explored, which stakeholder targeted CSR leads to better social or environmental performance. For this, we modified Shaukat et. al. (2016) model to incorporate different leadership styles. We used Spiller's (2000) manifestation of Stakeholder theory to classify CSR into (i) community, (ii) environment, (iii) employees, (iv) customers, (v) suppliers, (vi) shareholders dimensions. Empirical validity was established by conducting a survey using a close-ended questionnaire. Data was collected from 289employees of various firms and analyzed using confirmatory factor analysis and structured equation modeling. The results suggested that Ethical and Transformational leadership have a significant and positive effect on Customers and Employees directed CSR. Ethical, Servant and Transformational leadership also seem to positively and significantly affect Environment, Shareholders, and Suppliers directed CSR respectively. However, Ethical and Servant leadership negatively and significantly affect Shareholders, and Customers directed CSR respectively. Among CSR activities, Community, Environment, Shareholders, and Suppliers directed CSR have a positive and significant effect on both social and Environmental Performance. Interestingly, Employees directed CSR have a significant negative effect on both social and Environmental Performance, moreover, customer directed CSR also inversely impact Environmental Performance.
LibGuides: ACC Library Research Guides: Get Help!

An overview of Subject Guides, Class Guides, Library (How To...) Guides, InformationPlus Guides, and Expert Librarian Profile Guides
Named-Entity Based Sentiment Analysis of Nepali News Media Texts

Due to the general availability, relative abundance and wide diversity of opinions, news Media texts are very good sources for sentiment analysis. However, the major challenge with such texts is the difficulty in aligning the expressed opinions to the concerned political leaders as this entails a non-trivial task of named-entity recognition and anaphora resolution. In this work, our primary focus is on developing a Natural Language Processing (NLP) pipeline involving a robust Named-Entity Recognition followed by Anaphora Resolution and then after alignment of the recognized and resolved named-entities, in this case, political leaders to the correct class of opinions as expressed in the texts. We visualize the popularity of the politicians via the time series graph of positive and negative sentiments as an outcome of the pipeline. We have achieved the performance metrics of the individual components of the pipeline as follows: Part of speech tagging – 93.06% (F1-score), Named-Entity Recognition – 86% (F1-score), Anaphora Resolution – 87.45% (Accuracy), Sentiment Analysis – 80.2% (F1-score).
Towards a Standardized Dataset on Indonesian Named Entity Recognition.

In recent years, named entity recognition (NER) tasks in the Indonesian language have undergone extensive development. There are only a few corpora for Indonesian NER; hence, recent Indonesian NER studies have used diverse datasets. Although an open dataset is available, it includes only approximately 2,000 sentences and contains inconsistent annotations, thereby preventing accurate training of NER models without reliance on pre-trained models. Therefore, we re-annotated the dataset and compared the two annotations’ performance using the Bidirectional Long Short-Term Memory and Conditional Random Field (BiLSTM-CRF) approach. Fixing the annotation yielded a more consistent result for the organization tag and improved the prediction score by a large margin. Moreover, to take full advantage of pre-trained models, we compared different feature embeddings to determine their impact on the NER task for the Indonesian language.
A new-one-time-pad stream cipher: new design, hardware implementation and its application in security of UAVs

UAVs are used in military and civilian fields. Security of UAV Data Link is still unsatisfactory especially if a strong adversary model is considered. This paper describes a new design of AENOTP, tested for security in UAVs Data Link. AENOTP algorithm combines NOTP with AE technique to ensure encryption and authentication along with data integrity. AE is a technique that ensures the security of the transported data. The design and analysis of AENOTP gives a fast and enhanced stream cipher AE architecture based on the unpredictability concept. Implementation of AENOTP measures encryption and decryption of any sent and received data. AENOTP shows high speed of generating the key stream bits of the OTP stream cipher and high speed of the proposed algorithm of 75 Mbits/sec. It achieves high level of security for any transmitted data. It can easily resist different attacks such as linear and differential attacks.
The Use of AI for Writing: What do We Have in Store?

Artificial intelligence (AI) fast-spreading use in EFL classrooms has received growing attention but unfortunately, as a relatively new area, published articles that inform the implementation and impact of AI are relatively scarce. Nevertheless, some works began to shed light on the use of AI based tools and bots in teaching and this paper will raise some concerns over the use of bots in EFL class in general and in writing class in particular. AI-based tool and bots that work on big data to provide its users an instant essay offers unlimited data search, automatic paraphrasing, grammar and spelling as well as plagiarism checkers. These AI-based tool usually brings a magical moment for its early users and this paper questions whether the use of such AI-based tools, including bots, in writing class beneficial. Using samples of students’ work, interview, and reflective observation, this paper attempts to open a discussion on what teachers have in store with the continuous and accelerated improvement of AI, particularly in EFL writing class.
A Theory of Self-Supervised Framework for Few-Shot Learning

Recently, self-supervised learning (SSL) algorithms have been applied to Few-shot learning(FSL). FSL aims at distilling transferable knowledge on existing classes with large-scale labeled data to cope with novel classes for which only a few labeled data are available. Due to the limited number of novel classes, the initial embedding network becomes an essential component and can largely affect the performance in practice. But almost no one analyzes why a pre-trained embedding network with self-supervised training can provide representation for downstream FSL tasks in theory. In this paper, we first summarized the supervised FSL methods and explained why SSL is suitable for FSL. Then we further analyzed the main difference between supervised training and self-supervised training on FSL and obtained the bound for the gap between self-supervised loss and supervised loss. Finally, we proposed potential ways to improve the test accuracy under the setting of self-supervised FSL.
The Predicament and Recognition of the Development of Modern School Physical Education

The research uses literature and logical induction to discuss the predicament faced by contemporary school physical education from a new perspective, and uses this as a starting point to re-examine the function and value of school physical education, so that people have a comprehensive and correct understanding of school physical education. Then better optimize the school sports work and achieve the school sports work goals.
Penerapan Pembelajaran Kooperatif Tipe Think Talk Write (TTW) untuk Meningkatkan Keterampilan Menulis Kembali Teks Narasi pada Peserta Didik Kelas IV Sekolah Dasar

This research aims are: 1) to improve writing skills again through the application of cooperative learning in the type of think talk write, and 2) to describe the results of the application of cooperative learning in the type of think talk write. This research is a class action research with two cycles. The subjects of this study were 4th grade students at Karangasem III Elementary School Surakarta in the academic year 2019/2020, totaling 31 students. This study uses data collection techniques in the form of interviews, observation, documentation analysis and tests with content validity data analysis, technical triangulation and source triangulation. Analysis of the data used is describing comparative analysis and Miles-Huberman interactive analysis models. The conclusion is that the writing skills of the 4th grade students at Karangasem III Elementary School in Surakarta in the academic year 2019/2020 can be improved through cooperative learning in the type of think talk write. The results of this study have contributed to the world of education as an alternative to solving the psychomotor domain, namely the ability to rewrite narrative texts
EER-ASSL: Combining Rollback Learning and Deep Learning for Rapid Adaptive Object Detection

We propose a rapid adaptive learning framework for streaming object detection, called EER-ASSL.The method combines the expected error reduction (EER) dependent rollback learning and the active semi-supervised learning (ASSL) for a rapid adaptive CNN detector.Most CNN object detectors are built on the assumption of static data distribution.However, images are often noisy and biased, and the data distribution is imbalanced in a real world environment.The proposed method consists of collaborative sampling and EER-ASSL.The EER-ASSL utilizes the active learning (AL) and rollback based semi-supervised learning (SSL).The AL allows us to select more informative and representative samples measuring uncertainty and diversity.The SSL divides the selected streaming image samples into the bins and each bin repeatedly transfers the discriminative knowledge of the EER and CNN models to the next bin until convergence and incorporation with the EER rollback learning algorithm is achieved.The EER models provide a rapid short-term myopic adaptation and the CNN models an incremental long-term performance improvement.EER-ASSL can overcome noisy and biased labels in varying data distribution.Extensive experiments shows that EER-ASSL obtained 70.9 mAP compared to state-of-the-art technology such as Faster RCNN, SSD300, and YOLOv2.
Bayesian Methods for Semi-supervised Text Annotation

Human annotations are an important source of information in the development of natural language understanding approaches. As under the pressure of productivity annotators can assign different labels to a given text, the quality of produced annotations frequently varies. This is especially the case if decisions are difficult, with high cognitive load, requires awareness of broader context, or careful consideration of background knowledge. To alleviate the problem, we propose two semi-supervised methods to guide the annotation process: a Bayesian deep learning model and a Bayesian ensemble method. Using a Bayesian deep learning method, we can discover annotations that cannot be trusted and might require reannotation. A recently proposed Bayesian ensemble method helps us to combine the annotators’ labels with predictions of trained models. According to the results obtained from three hate speech detection experiments, the proposed Bayesian methods can improve the annotations and prediction performance of BERT models.
Steganography Based Authenticated Data Sharing in Health Care

As per Health Insurance Portability and Accountability Act (HIPAA)the patient's protection and protection are significant in assurance of medical care protection. Simultaneously, the quantity of maturing populace is developing essentially. Purpose Of-care in medical clinics utilized generally around the globe. The Security Regulations are represented in order to provide data veracity, privacy, and accessibility. Consequently, patient’s ECG along with other physiological signals, for example, temperature, pulse, glucose reading, position, and so forth, were gathered by utilizing Body Sensor Networks (BSNs) and transmitted. At a similar cost, understanding protection is ensured against stalkers while information direct in vulnerable organization and placed in medical clinic workers. Likewise, the accompanying system was consolidated in this venture: (1) encryption and decryption for information classification and trustworthiness (2) ECG based Steganography to trade information. Our plan additionally guarantees security, efficiency, and scalability.