Reviewerly/exHarmony huggingface dataset:
Foundations of a Blockchain

A blockchain is a decentralized data structure with internal consistency maintained through consensus reached by all the users on the current state of the network. It is an enabling technology that resolved the Byzantine Generals Problem (described as a problem of establishing trust between three generals such that a coordinated strike can take down an enemy; more in Chapter 1 ) and opened a new horizon of possibilities for application development with trustless transactions and exchange of information. If the internet democratized the peer-to-peer exchange of information, then the blockchain has democratized the peer-to-peer exchange of value. We will begin this chapter by exploring how transactions work between users on the Bitcoin network. This will entail a technical discussion of the structures of a block and a transaction. Then, we will dive into the role of wallets and user addresses. After talking about wallets, we will shift our focus to Simple Payment Verification (SPV), which is implemented in the Bitcoin network. SPV will allow us to understand why blocks have a peculiar structure and, more important, how the Bitcoin network can retain efficiency despite the network’s scaling at a high rate. Finally, we will end our discussion by talking about hard and soft forks in the Blockchain. We will present the implications of forks in the context of forward compatibility for merchants and users involved in running the Bitcoin core code. Even though there are numerous variations of blockchain during this "Cambrian explosion" phase of tech development, the core principles remain the same.
Cross-lingual annotation: a road map for low-and no-resource languages

This paper presents a “road map” for the annotation of semantic categories in typologically diverse languages, with potentially few linguistic resources, and often no existing computational resources. Past semantic annotation efforts have focused largely on high-resource languages, or relatively low-resource languages with a large number of native speakers. However, there are certain typological traits, namely the synthesis of multiple concepts into a single word, that are more common in languages with a smaller speech community. For example, what is expressed as a sentence in a more analytic language like English, may be expressed as a single word in a more synthetic language like Arapaho. This paper proposes solutions for annotating analytic and synthetic languages in a comparable way based on existing typological research, and introduces a road map for the annotation of languages with a dearth of resources.
Aspectos subjetivos do jornalista na relação com a fonte de informação

It analyzes aspects related to the journalist's personality in relation to his source of information. The study is carried out through empirical research in a group of 16 journalists from Porto Alegre (RS), submitted to two analysis tools: sociological questionnaire and Big Five method (or Big Five Factors, BFF). Among the results, it was observed that the group is characterized by the “kindness” factor; most are indifferent to the preference of interviewing men or women; it usually obtains information about his sources through co-workers and in internet research; it has a preference for official sources; medium level of affective involvement with sources; the majority considers that it establishes a neutral negotiation process; and the level of command is high / balanced during an interview.
Information Assurance: Manpower Development—Indian Possibilities in International Perspective

Information Assurance is an emerging name in Information Security and Privacy and is falls under the Computing and Information Technology domain. Information Assurance deals with both the technology and policy and dedicated to the designing and development of secure and healthy information systems. This is an important fact that internationally there is a shortage of skilled manpower in the field of Information Security. Two important domains, Information Security and Information Assurance are closely related; but Management policies and principles are being used in Information Assurance for various purposes viz. formulation, design, implementation of information security related rules, regulation, and guidelines. Information Assurance also called as IA. Information Assurance and Security, Information Assurance and Cyber Security, IT Security and Information Assurance, etc are close words and nomenclature of Information Assurance field. Worldwide the nomenclature is gaining popularity in the IT industries, organizations, academics, companies apart from the government departments, ministries, and administration. Various universities internationally started programs in Information Assurance and allied fields and most of these are in western countries. Countries like India and other developing nations may start Information Assurance as well as allied programs. This chapter discusses the potentialities as well as challenges and opportunities of the Information Assurance field in Indian context based on international trend.
Current Tasks of Academies and Academia

The present article is written as an issue paper on academies for the GL-21 Project. It traces activities of academies and their associations in the present information-rich society. The state-of-the-art of the academic world is briefly described. This permits to focus on general trends in knowledge management in general and the role of academies. The successful strategies and interdependencies form the framework of activities, where one should also understand the possible obstacles. The impact of these activities together with ideas for more social responsibility and cooperation are examined. The unique position of WAAS in organizing a network for social progress is underlined.
Learning a Max-Margin Classifier for Cross-Domain Sentiment Analysis

Sentiment analysis is a costly yet necessary task for enterprises to study the opinions of their costumers to improve their products and services and to determine optimal marketing strategies. Due to existence of a wide range of domains across different products and services, cross-domain sentiment analysis methods have received significant attention in recent years. These methods mitigate the domain gap between different applications by training cross-domain generalizable classifiers which help to relax the need for individual data annotation per each domain. Most existing methods focus on learning domain-agnostic representations that are invariant with respect to both the source and the target domains. As a result, a classifier that is trained using annotated data in a source domain, would generalize well in a related target domain. In this work, we introduce a new domain adaptation method which induces large margins between different classes in an embedding space based on the notion of prototypical distribution. This embedding space is trained to be domain-agnostic by matching the data distributions across the domains. Large margins in the source domain help to reduce the effect of ``domain shift'' on the performance of a trained classifier in the target domain. Theoreticaland empirical analysis are provided to demonstrate that the method is effective.
AN ANALYSIS OF THE SIXTH SEMESTER STUDENT TRANSLATION SKILL AT MUHAMMADIYAH UNIVERSITY OF TANGERANG

This research aimed at analyzing translation accuray of student translation between the source language (SL) in Bahasa and target language (TL) in English and finding out the translation process used by student at Muhammadiyah University of Tangerang. The object of this research is 6th Grade Student at Muhammadiyah University of Tangerang. The researcher focuses on the accuracy of student translation results in range accurate, less accurate and inaccurate based on Accurate Translation Rate proposed by Nababan (2012). The researcher also analyzes the translation process based on Nida and Taber’s theory (1969). In conclusion, researcher found that the accuracy of translation is rated by a lecturer of English Education Study Program of Teachers Training and Education Faculty of Muhammadiyah Tangerang with the results 83,1% translations are accurate, 15,3% translations are less accurate and 1,6.% translation are inaccurate. While, the researcher found that most of translation process used by students is non sequentially process (71%), and the sequentially process is 29%.
Contextual Augmentation of Pretrained Language Models for Emotion Recognition in Conversations

Since language model pretraining to learn contextualized word representations has been proposed, pretrained language models have made success in many natural language processing tasks. That is because it is helpful to use individual contextualized representations of self-attention layers as to initialize parameters for downstream tasks. Yet, unfortunately, use of pretrained language models for emotion recognition in conversations has not been studied enough. We firstly use ELECTRA which is a state-of-the-art pretrained language model and validate the performance on emotion recognition in conversations. Furthermore, we propose contextual augmentation of pretrained language models for emotion recognition in conversations, which is to consider not only previous utterances, but also conversation-related information such as speakers, speech acts and topics. We classify information based on what the information is related to, and propose position of words corresponding to the information in the entire input sequence. To validate the proposed method, we conduct experiments on the DailyDialog dataset which contains abundant annotated information of conversations. The experiments show that the proposed method achieves state-of-the-art F1 scores on the dataset and significantly improves the performance.
Composing Byte-Pair Encodings for Morphological Sequence Classification

Byte-pair encodings is a method for splitting a word into sub-word tokens, a language model then assigns contextual representations separately to each of these tokens. In this paper, we evaluate four different methods of composing such sub-word representations into word representations. We evaluate the methods on morphological sequence classification, the task of predicting grammatical features of a word. Our experiments reveal that using an RNN to compute word representations is consistently more effective than the other methods tested across a sample of eight languages with different typology and varying numbers of byte-pair tokens per word.
SEMANTIC WEB TECHNOLOGIES: CHALLENGES AND APPLICATIONS -

This research paper focuses on different application of semantic web and challenges faced in utilizing thistechnology. The Semantic Web gives a typical structure that permits information and information to be sharedand reused across application, endeavour, and network limits. Through this paperwe will discuss in depth theimportance of semantic web and various challenges that are yet to overcome.
Crypto-Micropayments: Issues in Gaining Trustworthiness

Conducting businesses over Internet has now turned to necessity rather than just considering it as fashion and in the same context turns into an essential part of financial institutions serving as one of the trusted third parties to process electronic payments. Now a day, crypto-micropayments are playing major roles as world-shattering decentralized, trustless payment systems nevertheless used by many individual entities, as well as, business houses for the benefit of their own concerns. Logically, crypto-micropayments provide a digital alternative to government-issued fiat currencies, and thus, can be used in online marketplaces to buy everything from a needle to flight tickets. Although with the growing number of opponents, cryptocurrencies show fearless traversal over the internet against its challengers who are also gaining grip from such virtual currencies whose presence in this era foretell a matter of great distrust and concurrently all hastening to become the main teller for the upcoming future cashless world. Since, digital currencies are still in a state of flux, this paper tries to target the squashy curves associated with cryptocurrencies, as well as, its frailty in association with societal perspectives due to its anonymity and cross-border features. This paper also focuses on the need for radical overhauling of existing payment-related regulatory framework in India with special reference to crypto-micropayments.
An Improved Monarch Butterfly Optimization Algorithm based on RNA Computing

As a new natural heuristic algorithm, the MBO(monarch butterfly optimization) algorithm simulates the migration behavior of monarch butterfly. Meta heuristic algorithm has significant and effective performance when working on high-dimensional nonlinear problems. Aiming at the problems of the original monarch butterfly algorithm such as weak search ability and unable to jump out of local optimization, an ameliorated monarch butterfly optimization algorithm (RNA-MBO) established on RNA computing is proposed. Firstly, RNA operator is introduced to seize the equilibrium of the algorithm in local and global searching ability during the migration and cross calculation of the monarch butterfly; secondly, the top 1/4 population with the best ranking is selected to perform transposition, neck ring and replacement operation to increase disturbance force, It can replace the elite retention strategy in the standard MBO algorithm and improve its computational efficiency. Finally, the performance of three MBO and improved algorithms is tested and analyzed based on 23 test functions of 30 dimensions; RNA-MBO and two classical algorithms are tested and analyzed based on 8 test functions of 50 dimensions. The consequence of simulation reveal that their comprehensive performance of RNA-MBO algorithm is the best of all the other MBO optimization algorithms and classic algorithms, It has better stability and optimization ability, and has more advantages in solving complex multi-dimensional optimization problems.
Secure Transfer of Medical data to the cloud using cyclic watermarking and Encryption Technique

Cloud Computing is one of the valuable service in medical field. However, the differentchallenges need to be mange in the privacy and security of cloud in the medical field. To discuss in detail,the security is to maintain and to transmit the original data to the cloud manager and service providerbecame the major deal. To solve such problem different stages of security system is to be developed andfiltered the data at each level. In this paper, multi-level security technique is suggested in cloud computing.Thus improvising the security parameter regarding medical sensitive data. Thus, the AES-SHA combinationof algorithm and durable cyclic watermarking model used to send the data to the cloud manager. It offersbetter security performance, amplifies the organising of medical data and assures confidentiality.
Chinese Grammatical Errors Diagnosis System Based on BERT at NLPTEA-2020 CGED Shared Task

In the process of learning Chinese, second language learners may have various grammatical errors due to the negative transfer of native language. This paper describes our submission to the NLPTEA 2020 shared task on CGED. We present a hybrid system that utilizes both detection and correction stages. The detection stage is a sequential labelling model based on BiLSTM-CRF and BERT contextual word representation. The correction stage is a hybrid model based on the n-gram and Seq2Seq. Without adding additional features and external data, the BERT contextual word representation can effectively improve the performance metrics of Chinese grammatical error detection and correction.
EDUCATION – RETURN TO REALITY

The post-socialist transformation of general and vocational education system has led to the loss of many positive gains that were already achieved earlier. The polytechnic character of our school and its practice-oriented foundations, based on a reasonable combination of basic education and professional and applied training, were seriously undermined. Modern Russian secondary schools have become something like pre-revolutionary classical high schools, without taking into account the significant fact that in pre-Soviet Russia, along with high schools, there was a wide network of real schools. They focused students on further mastering technical professions and active participation in the production sector of the country. Today we are witnessing a global revolution in the spiritual sphere, aimed at changing the very essence of a man. Note that natural science education is valuable not only for its formal method, but also for providing the basis for a correct understanding of the world. It fosters independence of thought and distrust of other people’s words and authorities. This is the best protection of the human mind from all sorts of superstitions delusions and mysticism.
DIGITAL DIDACTICS AS A NEW MODEL IN THE THEORY OF EDUCATION

Rapid changes in society connected with the qualitative transformation of informational and educational environment provoke the study and development of a new tendency in pedagogics, in particular in the theory of education. The article explains the necessity of transition to a new digital model of didactics, suggests its structure and approaches to its realization. The author’s vision of new principles, methods, means and forms of organization of modern education are presented in the article. The study of the level of teachers’ awareness of digital didactics principles and their real readiness to work in the conditions of informational educational environment has shown a low level of the formation of corresponding competences among teachers. As teacher’s qualities are transformed due to the transition from teaching to engineering of educational activity, the article states the main e-teacher’s qualities: informational resources analyst, content designer and designer of education and evaluation methods. Their formation helps to realize e-didactics idea, in which educational resource is a system-forming element. Given e-didactics structure illustrates the way educational resource can serve as content, tasks for the formation of corresponding competences and means of control of education quality. Padagogy Wheel is considered to be a means of web-resources selection for any level of knowledge. Teachers’ questionnaire has shown that their knowledge, skills and will to use web-resources (for example, Padagogy Wheel) in the organization of educational activity is at 30 % mark that requires considerable attention of pedagogical community. One of the ways of solving this problem consists in the creation and extensive testing of open educational resources dedicated to implementation of digital didactics.
Teaching practice for pandemic times and the empowerment of audiovisual didactic sequences

Closed gates and students away from classrooms consist of scenarios with thou- sands of schools in different countries, showing all the zeal we must have with teaching, which was opened wide by the indirect relationship between Education and Coronavirus. It is a frightening and troubling panorama, not only in health but also in teaching impacts. The learning process can and should hap- pen outside the classroom, and the pandemic accelerated this understanding. Technology support is fundamental for this to happen, eliminating any physical or geographical barrier of communication and interaction. However, the technological tools go further. Educational technologies are the leading solution to our situation and have the most significant potential for teaching children and young people. It is an opportunity to reframe Education and think of more effective ways to develop new children and young people. However, there is no ready recipe. Several frameworks for creating can guide audiovisual didactic sequences are not entirely descriptive in practice, applicability, or evaluation. Therefore, this work has its starting point the instructional design to supply this development, with other frameworks within its phases, allowing a better understanding of the objectives and greater ease in developing the instructional material. The results show that students well accept this new proposal.
IMPROVING PHONETICS AWARENESS OF KINDERGARTEN TEACHERS TO ERADICATE ENGLISH LANGUAGE FOSSILIZATION AMONG KINDERGARTEN STUDENTS

Children's language development is largely determined by the surrounding environment. This is often associated with the opinion of experts who say that children at an early age have a 'golden period' to absorb and imitate what they hear. The abilities of absorbing and imitating need to be understood thoroughly both by parents at home and educators who deal directly with young children so that phonological fossilization does not occur. One way to reduce phonological fossilization is to increase teacher awareness about phonology because not all teachers who teach in kindergartens are graduates of English Education courses. In this community service program, the teacher is first given a pre-test to measure initial abilities. Furthermore, teachers were given knowledge and exercises related to phonology with several teaching techniques. At the end of the meeting, the teachers were given a post-test and the post test results showed a significant improvement of their phonetics awareness.
Towards a Task-Agnostic Model of Difficulty Estimation for Supervised Learning Tasks

Curriculum learning, a training strategy where training data are ordered based on their difficulty, has been shown to improve performance and reduce training time on various NLP tasks. While much work over the years has developed novel approaches for generating curricula, these strategies are typically only suited for the task they were designed for. This work explores developing a task-agnostic model for problem difficulty and applying it to the Stanford Natural Language Inference (SNLI) dataset. Using the human responses that come with the dev set of SNLI, we train both regression and classification models to predict how many annotators will answer a question correctly and then project the difficulty estimates onto the full SNLI train set to create the curriculum. We argue that our curriculum is effectively capturing difficulty for this task through various analyses of both the model and the predicted difficulty scores.
Web-Based Document Management System: A Management Tool for an Educational Institution

Document Management Systems (DMS) plays an important role in different organizations today.This paper presents an application of DMS in an educational institution. This system specifically aims tomobilize the recording, retrieving, tracking and efficient record distribution in an electronic manner. UnifiedProcess model was used to develop the system. All these phases are done sequentially, in which a projectmilestone had been achieved upon the completion of a phase and was used as an input for the succeedingphase. The average result for the User Acceptance Test (UAT) is 4.27 that is above than the target average.Based from the UAT results, the Office is satisfied and accepted the implementation of the system