Reviewerly/exHarmony huggingface dataset:
Named Entity Recognition as Graph Classification

Injecting real-world information (typically contained in Knowledge Graphs) and human expertise into an end-to-end training pipeline for Natural Language Processing models is an open challenge. In this preliminary work, we propose to approach the task of Named Entity Recognition, which is traditionally viewed as a Sequence Labeling problem, as a Graph Classification problem, where every word is represented as a node in a graph. This allows to embed contextual information as well as other external knowledge relevant to each token, such as gazetteer mentions, morphological form, and linguistic tags. We experiment with a variety of graph modeling techniques to represent words, their contexts, and external knowledge, and we evaluate our approach on the standard CoNLL-2003 dataset. We obtained promising results when integrating external knowledge through the use of graph representation in comparison to the dominant end-to-end training paradigm.
SOCIAL CRITICISM IN KONSPIRASI ALAM SEMESTA NOVEL BY FIERSA BESARI

Every litterateur makes existing issues or phenomena as inspiration in making literary works. In case with novelist, they convey criticism expressly or implicitly in their novel. Besides the love story, the Konspirasi Alam Semesta novel by Fiersa Besari, the author also criticizes the social conditions that exist in Indonesia. Social criticism in the novel will be the purpose of this research. Furthermore, this research focuses on analyzing the Konspirasi Alam Semesta novel using a sociological literary approach with social criticism. The research method is qualitative research methods with reading and note-taking techniques. The purpose of the research is to describe the problem of social criticism and the form of its presentation in the novel. The research result has obtained: (1) social criticism about politics such as discrimination against families of ex- political prisoner, government policies towards those who have made the country proud, Papua’s wealth and injustice in the development of remote areas, (2) moral criticism of corruption, (3) social criticism of humanity such as generalizations about a group, individual differences, violence against separatists and stigma about spinster, (4) social criticism about religion / belief about the creator. It can be concluded that the author implicitly conveyed his message and response through the Konspirasi Alam Semesta novel. It describes conditions that deviate from social conditions that must be criticized. This novel revives the people’s insights about social problems that exist in Indonesia. Furthermore, the author’s main topic of social criticism is political and humanitarian in Indonesia.
The participatory behaviour and the students’ adaptability in the online environment during the pandemic

Changing the relational environment from face-to-face to the online one led to new problems regarding the student classroom’s functionality, which led to the students’ difficulties in relation to the new situation and the adaptability process. In this new context brought by the pandemic, the relationship’s dynamic between student’s changes, as well as the one between students and teachers. The endeavour includes the analysis of a small group of students, who resorted to therapy throughout the lockdown, to remit the difficulties that emerged due to the teaching environment’s change from face-to-face to the online medium. The objectives’ focus highlighted the participatory behaviour’s optimization of the students in the new conditions, the enhancement of the students’ wellbeing’s, in order to optimally face the teaching process and finish the academic year.
Splitting EUD Graphs into Trees: A Quick and Clatty Approach

We present the system submission from the FASTPARSE team for the EUD Shared Task at IWPT 2021.We engaged in the task last year by focusing on efficiency.This year we have focused on experimenting with new ideas on a limited time budget.Our system is based on splitting the EUD graph into several trees, based on linguistic criteria.We predict these trees using a sequence-labelling parser and combine them into an EUD graph.The results were relatively poor, although not a total disaster and could probably be improved with some polishing of the system's rough edges.
Determining subject headings of documents using information retrieval models

&lt;p&gt;Subject heading is a controlled vocabulary that describes the topic of adocument, which is important to find and organize library resources. Assigning appropriate subject headings to a document, however, is a time-consuming process. We therefore conduct a novel study on the effectiveness of information retrieval models, i.e.,language model (LM) andvector spacemodel (VSM), to automatically generate a ranked list of relevant subject headings, with the aim to give a recommendation for librarians to determine the subject headings effectively and efficiently. Our results show that there are a high number of our queries (up to 61%) that have relevant subject headings in the ten top-ranked recommendations and on average, the first relevant subject heading is found at the early position (3rd rank). This indicates that document retrieval methods can help the subject heading assignment process. LM and VSM are shown to have comparable performance, except when the search unit is title, VSM is superior to LM by8-22%. Our further analysis exhibits three faculty pairs that are potential to have research collaboration as their students’ thesis often have overlap subject headings: i) economy and business-social and political sciences, ii) nursing-public health and iii) medicine-public health.&lt;/p&gt;
The Pedagogical Interaction In The Digital Learning Environment

Digital learning environment is an actual form of informatization in education.The purpose of our study is to identify and describe possible scenarios of interaction between the teacher and the student in this environment.Most authors consider scenarios of the interaction between the teacher and the student in the digital learning environment in the framework of the dichotomy, for example, synchronous and asynchronous scenarios.We consider it necessary, and this is confirmed in the results of the study, to distinguish the system from three main scenarios -Content Oriented, Subject Oriented and Interlocking.In line with the Content Oriented scenario, the interaction between the teacher and student is based on the educational material and various forms of its presentation and visualization, including educational maps.Within the framework of the Subject Oriented scenario, the interaction is based on the consideration and reflection of the personal attitudes of the student in the learning content and teaching methods.According to the Interlocking scenario, the teacher acts as an interface that connects the student, the learning group, educational material within the framework of various forms of educational activity.The system of scenarios of interaction between the teacher and the student that we have identified can serve as the basis for the design of digital learning environment and for the professional preparation of teachers for work within such environments.
Smart Contracts in Smart Cities: Application of Blockchain Technology

Over the recent years, blockchain has emerged as an area of great interest with its applications in multiple domains like financial, technology, security, education, and many more. In addition to these, it also has a great potential to be used in many other areas and it is accompanied by other modern technologies like IoT, cloud computing, etc. In this time of global urbanization, a huge influx of people could be seen in the urban settings in pursuit of better career opportunities, health and education services and better standard of living. This has also tremendously increased the resource demands managing which could be a herculean task. A smart city could be considered as a modern digitized city which integrates the latest ICTs along with existing infrastructure to maximize the optimization of resource utilization to provide better quality of living with security and transparency. This paper aims to explore the potential and contribution of blockchain technology in smart cities along with IoT and provide a novel solution for easy and automated consumer utility payments based on smart contracts.
Argument Extraction for Key Point Generation Using MMR-Based Methods

When people debate, they want to familiarize themselves with a whole range of arguments about a given topic in order to deepen their knowledge and inspire new claims.However, the amount of differently phrased arguments is humongous, making the process of processing them time-consuming.In spite of many works on using arguments (e.g.counter-argument generation), there is only a few studies on argument aggregation.To address this problem, we propose a new task in argument mining -Argument Extraction, which gathers similar arguments into key points, usually single sentences describing a set of arguments for a given debate topic.Such a short summary of related arguments has been manually created in previous research, while in our research key point generation becomes fully automatic, saving time and cost.As the first step of key point generation we explore existing similarity calculation methods, i.e.Sentence-BERT and MoverScore to investigate their performance.Next, we propose a combination of argument similarity and Maximal Marginal Relevance (MMR) for extracting key phrases to be utilized in our novel task of Argument Extraction.Experimental results show that MoverScore-based MMR outperforms strong baselines covering 72.5% of arguments when eleven or more arguments are extracted.This percentage is almost identical with the cover rate of human-made key points.
Classification and Analysis of Malicious Traffic with Multi-layer Perceptron Model

Traffic classification is very important field of computer science as it provides network management information. Classification of traffic become complicated due to emerging technologies and applications. It is used for Quality of Service (QoS) provisioning, security and detecting intrusion in a system. In the past used of port, inspecting packet, and machine learning algorithms have been used widely, but due to the sudden changes in the traffic, their accuracy was diminished. In this paper a Multi-Layer Perceptron model with 2 hidden layers is proposed for traffic classification and target traffic classify into different categories. The experimental results indicate that proposed classifier efficiently classifies traffic and achieves 99.28% accuracy without feature engineering.
Telepresence Robots: A Phenomenological Study of Perceptions of Graduate Students and Professors

The purpose of this phenomenological case study was to capture the perceptions of telepresence learning from three different perspectives: the graduate student using the telepresence robot, the graduate students in the physical learning environment with one of their peers utilizing the telepresence robot, and the instructor teaching in the learning environment where a telepresence robot is being utilized. This study was analyzed through the lens of Whiteside’s 2015 Social Presence Model, which synchronizes interactions between the instructor/professor, students, content, and technologies being utilized. While some challenges exist, the telepresence robots established a social and physical presence from a remote location.
Software Security: Role in SDLC

This research emphasizes mainly on the need for software security. Softwares are developing at a faster pace so it is required to impose security on them in order to secure them from cybercrimes. Softwares have been facing problems by the attackers who are constantly kept on breaching the Data. Therefore this survey comprises the phases that are an integral part of the SDLC from the security point of views such as Design and testing phase. Moreover, it quests upon the data related to threats and attacks. Not only this, but it also involves the prerequisites that have to be determined before developing the software like, what are the approaches that should be followed and what are the best suitable designs to secure the software?
An Evaluation of Tourism Attributes related to Satisfaction and Challenges by Foreign Tourists in Sultanate of Oman

Tourism economy has enhanced the employment opportunities in Oman and lot of new tourism projects are coming up throughout the country. The awareness among the Omani public has to improve to consider a future in the tourism industry. The study is attempted to understand the satisfaction level of international tourists in Oman, the factors that affects tourism and the challenges faced by the tourists. The responses were collected from 111 foreign tourists visited Oman. It was found that majority of the tourists are from France, Germany, Italy and Britain. International tourists are satisfied by the friendliness and openness of Omanis, culture and customs and have a safe feeling of security to travel in Oman. The challenges faced by foreign tourists include difficulty in language, GPS connection, lack of Wifi connectivity, problems in walking alone, more time at the airport to exit, time for visa processing, bad driving, expensive ticket charges, taxi and hotel charges, crowded and traffic jam and language difficulties.
Information Society And Digital Leadership In The Globalized Educational System: Political Approach

The article dwells on the changes that the information society has brought to all spheres of human life, education being one of them.A huge gap has appeared between the countries which produce and circulate knowledge, thus defining the dominant trends in different fields of science and technology, and economically less developed countries.At present, the notion of poverty acquires new meanings, since it is defined not only by the material conditions in which people live, but also by the existing opportunities to get access to new cultural and social meanings, to actively participate in new social practices.ICT can give people of different countries more possibilities to obtain key information necessary for understanding the dynamics of developments in different spheres of globalized and digital reality.Eleadership skills help make the best use of digital technologies within any type of organization and introduce digital innovations in both the public and private sectors.The article addresses the problem of the educational system response to the new scenarios against the background of the changes that new technologies dictate.The educational system leadership should consider the fact that today's teachers should be capable of making agreeable use of digital tools and be willing to introduce them into their classes on a daily basis.These skills and abilities have become even more relevant during the pandemic of COVID 19.Apart from theoretical insights, the article presents the results of a small-scale empirical research on the attitude to digitalization of educational leadership in Kazakhstan.
An Automated Stable Personalised Partner Selection for Collaborative Privacy Education

E-learning platforms have never been as in-demand as they are now since the recent pandemic making privacy education more important than ever. However, for the most part, these platforms are single-user learning environments and lack student-student interactions. To overcome this deficiency, we propose a collaborative e-learning platform for privacy education that matches students in a stable and automatic manner according to students’ preferences. Each student is represented by a vector profile that is created from behavioural skills and academic knowledge obtained from the platform. Once the preferences are determined, the residents-hospitals matching algorithm is applied to select students who will collaborate with one another. Experimental results show that the proposed model offers an effective way to create stable, thus satisfied, coalitions of students from two groups of arbitrary sizes. In addition, the automation allows students to skip the tedious process of manually selecting partners. Therefore, saving their time to collaborate on privacy education with their teammates helping them to increase their privacy awareness.
Geometric Authentication Mechanism for Enhancing Security in IoT Environment

In the Internet of things (IoT) environment, many applications access services through remote methods. In this paper, we designed a new geometric authentication mechanism to enhance security. The solution is based on geometric characteristics to achieve rapid authentication at low computational cost. In addition, we use the user’s biometrics to improve the security level of the system. Our solution meets the following security features: anonymity, resistance to forgery attacks and replay attacks, fast error detection, resistance to offline password guessing attacks, resistance to server overload attacks, mutual authentication, session key agreement, and flexibility in users choosing and changing their passwords easily.
A differentiable estimator of VMAF for Video

Modern Perceptual Visual Quality Metrics (PVQMs) for video are generally complex and non-differentiable. This makes them difficult to use as loss functions in restoration and compression tuning. Traditional metrics such as PSNR/MSE which are differentiable remain important but do not capture perceptual visual criteria. In this paper we present a DNN which models a popular perceptual video metric VMAF. In so doing, we introduce a differentiable loss function that closely matches the behaviour of a perceptual metric. Employing degradation generated with H.265 compression, our model achieves a 4.41% RMSE in predicting VMAF. This can now be deployed as a video based loss function in video enhancement and compression tasks.
The Effect of Communicative Approach towards Students’ Reading Comprehension on The Eighth Grade of SMP PGRI 3 South Jakarta

The research aims at finding out the effect of Communicative Approach’s learning model to the students’ reading ability. The research was conducted at SMP PGRI 3 South Jakarta. The method applied was experimental research. Samples were taken randomly and grouped in two classes of experiment and control consisting of 30 students of each group. The analysis of data for hypothesis test was by using t-test. Prior to the calculation of hypothesis test, it was preceded by the calculation of normality test by applying Lilliefors and homogenity test with F-test. Findings show that for experiment class, Lcount = 0.1097 and Ltabel = 0.161, even controll class it is obtained Lcount = 0.1214 and Ltable = 0.161. if Fcount= 1.32 and Ftable=1,84. It can be concluded that both research groups are normally distributed and the data is homogenous with α = 0.05. the hypothesis test with t-test statistic formula, it is obtained that tcount is 2.46 and ttable is 1.67. After being compared, tcount value is somewhat higher than ttable value (2.46 &gt; 1.67).
Improving the Tenth Grade Students’ Reading Comprehension Achievement of Narrative Text and Reading Interest by Using Guided Reading Strategy

This research aimed at improving the tenth-grade students' reading comprehension achievement of Narrative Text and reading interest by using Guided Reading Strategy at SMK Sentosa Bhakti in the academic year of 2020/2021.The method used in this research is classroom action research which consists of four steps, namely planning, implementation or action, observation, and reflection.The subject of this research is X TKJ 1 of SMK Sentosa Bhakti Baturaja consist of 28 students.In collecting the data, the researcher used a test to measure students' reading comprehension achievement, questionnaires to measure students' reading interest, and an observation sheet to know the teacher and students' participants.The result of this research showed that the tenth-grade students made improvements in reading comprehension achievement.It could be seen from the mean score on preliminary research (17,86 %), cycle I (60,71 %) and cycle 2 (85,71% )and for their interest in cycle I ( 60,71 % ) and cycle 2 (85,71%).This paper contibutes for teacher to improve their student's reading comprehension and reading interest by using guided reading strategy.
Linguistic Knowledge in Multilingual Grapheme-to-Phoneme Conversion

This paper documents the UBC Linguistics team's approach to the SIGMORPHON 2021 Grapheme-to-Phoneme Shared Task, concentrating on the low-resource setting.Our systems expand the baseline model with simple modifications informed by syllable structure and error analysis.In-depth investigation of test-set predictions shows that our best model rectifies a significant number of mistakes compared to the baseline prediction, besting all other submissions.Our results validate the view that careful error analysis in conjunction with linguistic knowledge can lead to more effective computational modeling.
Design and Development of Management Information System in Ma'had Huffadz Bilingual Darul Hikmah Malang Using Scrum Method

The scrum method is the most important thing in building software. The following research builds a management information system on Ma'had Huffadz Bilingual Darul Hikmah under Darus-Sa'adah Al Mardliyah Foundation. The institution, which is one of the Boarding Schools Tahfidzul Qur'an located in the city of Malang, East Java. The following research uses the Scrum framework. The implementation of the scrum method in the following research uses three sprints. The process of working on each sprint takes no more than a month. The software development in this research is web-based. Work on application programs using the Laravel framework using the PHP programming language. The results showed that the scrum method is very effective in building a boarding school management information system. Scrum is more dynamic, and the results of this scrum implementation can be seen from the system that has been developed. So that by implementing Scrum can produce a system that suits the requirements of the user.
Twitter Bots Detection Using Machine Learning Techniques

The social network, a crucial part of our life is plagued by online impersonation and fake accounts. Fake profiles are mostly used by the intruders to carry out malicious activities such as harming person , identity theft and privacy intrusion in Online Social Network(OSN). Hence identifying an account is genuine or fake is one of the critical problem in OSN .In this paper we proposed many classification algorithm like Support Vector Machine algorithm ,KNN, and Random Forest algorithm. It also studies the comparison of classification methods on Spam User dataset which is used to select the best.
The DCU-EPFL Enhanced Dependency Parser at the IWPT 2021 Shared Task

We describe the DCU-EPFL submission to the IWPT 2021 Parsing Shared Task: From Raw Text to Enhanced Universal Dependencies.The task involves parsing Enhanced UD graphs, which are an extension of the basic dependency trees designed to be more facilitative towards representing semantic structure.Evaluation is carried out on 29 treebanks in 17 languages and participants are required to parse the data from each language starting from raw strings.Our approach uses the Stanza pipeline to preprocess the text files, XLM-RoBERTa to obtain contextualized token representations, and an edge-scoring and labeling model to predict the enhanced graph.Finally, we run a post-processing script to ensure all of our outputs are valid Enhanced UD graphs.Our system places 6th out of 9 participants with a coarse Enhanced Labeled Attachment Score (ELAS) of 83.57.We carry out additional post-deadline experiments which include using Trankit for pre-processing, XLM-RoBERTa LARGE , treebank concatenation, and multitask learning between a basic and an enhanced dependency parser.All of these modifications improve our initial score and our final system has a coarse ELAS of 88.04.