Reviewerly/exHarmony huggingface dataset:
Dative as the unmarked unmarked case in Hungarian

Hungarian nominative and dative DPs alternate in particular constructions.We show standard theory, where cases are licensed by heads, is unable to cope with the data and present a different analysis of the distribution of these cases within Dependent Case theory in which nominative and dative are unmarked cases in different domains.The unmarked nominative domain is identified as the complement of a canonical final projection head (C, D and P) but the unmarked dative domain seems to lack a unifying property.We conclude that it is the elsewhere domain and dative is therefore the unmarked case of the unmarked domain.This has the advantage of giving a more explanatory account of the distribution of nominative and dative forms, including data with non-verbal predication.
TeLU: A New Activation Function for Deep Learning

The following topics are dealt with: power convertors; DC-DC power convertors; deep learning (artificial intelligence); computer aided instruction; feature extraction; learning (artificial intelligence); diseases; medical image processing; image classification; convolutional neural nets.
A Gaussian Process Latent Variable Model for Subspace Clustering

Effective feature representation is the key to success of machine learning applications. Recently, many feature learning models have been proposed. Among these models, the Gaussian process latent variable model (GPLVM) for nonlinear feature learning has received much attention because of its superior performance. However, most of the existing GPLVMs are mainly designed for classification and regression tasks, thus cannot be used in data clustering task. To address this issue and extend the application scope, this paper proposes a novel GPLVM for clustering (C-GPLVM). Specifically, by combining GPLVM with the subspace clustering method, our C-GPLVM can obtain more representative latent variable for clustering. Moreover, it can directly predict the new samples by introducing a back constraint in the model, thus being more suitable for big data learning tasks such as analysis of chaotic time series and so on. In the experiment, we compare it with the related GPLVMs and clustering algorithms. The experimental results show that the proposed model not only inherits the feature learning ability of GPLVM but also has superior clustering accuracy.
Students' Perception of English Learning through YouTube Application

As one of the most popular social media in this modern era, YouTube is also playing a role in education. Technology, which is part of student life, can offer useful feedback, especially in facilitating, increasing knowledge and English skills. An audio-visual model that can be accessed anywhere can make students feel more open about thoughts, opinions, questions, and be more comfortable and motivated in learning English. This article reports a qualitative study that finds out students' perceptions of English learning through YouTube are beneficial and help them learn English. 5 students who use the YouTube application as a media for learning English in SMK Negeri 17 participated in this study, and data were collected through interview-based on case study design.&#x0D; The results of this study find out all of the students have many benefits to improve their English skills, and very easy to access in almost every student's gadget and it can be used in every situation for help and motivated them to learn English. The students are only feeling the difficulty if the internet connection is not good. &#x0D; All of the students are given positive responses about the use of YouTube application in learning English.
Analysis of Audience Response to Public Service Advertisement about Covid-19 in Instagram

COVID-19 pandemic has taken place globally, especially in Indonesia, so the government has decided to prevent the spread of the corona virus.One of them is the Ministry of Health of Republic of Indonesia, as a government institution that has been recognized and accepted, and has certain impacts and interests.This is explained in Permenkes 64 of 2016, the 3rd clause which carries out functions, one of which is the implementation of policies in the field of public health, prevention and control of diseases.Through advertising that consists of visuals and texts in infographics, the Ministry of Health of Republic of Indonesia informs and persuades the audience in the early prevention of the corona virus in Instagram.The pre-research results with 56.5% of respondents who are generation Z shows 52.2% choosing visual and text as the most interesting advertising elements.In addition, 53.9% of respondents often see advertising through Instagram.The purpose of this descriptive quantitative research method is to analyze the audience response on public service advertisement (PSA) "JAGA DIRI, JAGA SESAMA DARI COVID-19" using the AISAS MODEL which consists of Attention, Interest, Search, Action, and Share dimensions.This research was conducted with survey data collection techniques to 108 respondents who had seen the PSA.The results of research indicate that the audience response on PSA has a high response for attention 83,7%, interest 77,7% and action 83,8%, while a low response for the search 61,5% and share 60,3%.In other words, the Indonesian Ministry of Health through advertising messages on Instagram succeeded in getting the audience to take precautions against COVID-19 based on the highest results compared to all dimensions of the AISAS model, 83.8%.
Pemanfaatan Augmented Reality Sebagai Media Pembelajaran Protozoa

One of the efforts to improve the quality of education is the use of technology as a medium of learning. The learning media used by XYZ SMA teachers to teach about protozoa in class X MIPA still use graphic images in books. Problems that occur students find it difficult to understand the form, name and function of protozoa animals. To see protozoan animals in real terms, a microscop tool is needed, but there are not many microscopes owned by XYZ SMA. The purpose of this research is to make learning media with Augmented Reality technology about Protists on mobile devices. This application will only display four 3D objects, namely Paramecium, Flagellata, Sporozoa, and Amoeba. The method used by MDLC consists of six stages, namely concept, desing, material collecting, assembly, testing, and distribution. The results of this study are in the form of an Augmented Reality application as a learning medium for the discussion of protozoa. After testing using the alpha test, all buttons / menus run according to their function. Then in testing using the beta test, respondents stated that the application is very good for use as a learning medium.
Red Dragon AI at TextGraphs 2020 Shared Task : LIT : LSTM-Interleaved Transformer for Multi-Hop Explanation Ranking

Explainable question answering for science questions is a challenging task that requires multihop inference over a large set of fact sentences.To counter the limitations of methods that view each query-document pair in isolation, we propose the LSTM-Interleaved Transformer which incorporates cross-document interactions for improved multi-hop ranking.The LIT architecture can leverage prior ranking positions in the re-ranking setting.Our model is competitive on the current leaderboard for the TextGraphs 2020 shared task, achieving a test-set MAP of 0.5607, and would have gained third place had we submitted before the competition deadline.
Reversible image authentication scheme based on prediction error expansion

&lt;span&gt;Reversible image authentication scheme is a technique that detects tampered areas in images and allows them to be reconstructed to their original version without any distortion. In this article, a new, reversible, image authentication scheme based on prediction error expansion is proposed for digital images. The proposed scheme classifies the host image into smooth blocks and complex blocks. Then, an authentication code that is created randomly with a seed is embedded adaptively into each image block. Experimental results showed that our proposed scheme achieves the high accuracy of tamper detection and preserved high image quality. Moreover, the proposed scheme achieved the reversibility, which is needed for some special applications, such as fine artwork, military images, and medical images. &lt;/span&gt;
Strategies to Motivate Children to Engage in Leisure Reading: Qualitative Insights from Nigerian Children

Some research done in the Western world indicates that children’s reading engagement is affected by certain factors and that children can be impacted in such a way that they will choose to engage in leisure reading. This paper, which arises from a study that explored the reading habits of a group of 9-12-year-olds in a book club in Nigeria, examines the factors that affected the reading engagement of the participants and suggests evidence-based strategies that could motivate children to engage in leisure reading. Through an interpretivist theoretical perspective, the study gathered data using the methods of collage making, observation, questionnaire, and interviews, and analysed them through inductive thematic analysis. Findings indicate that the participants read for pleasure, though their level of reading engagement differed. Findings also reveal that the reading engagement of all the participants may have been, in varying degrees, influenced by different factors such as the pedagogy of reading, access to reading materials, the reading environment, and the availability of social networks that support leisure reading. Insights from the study could guide on practices that strengthen children’s engagement in leisure reading.
University life during pandemic COVID-19: Attitudes of staff and students towards distance education

Research background: The analysis of the problem was carried out according to the standard scheme: collection of information - description of the received data - generalization of data - recommendations. All the information available on this subject was obtained by questioning teachers, administrative staff and students.
The Influence of Student Characteristics, Design Learning Features, and Learning Outcomes on Blended Learning Effectiveness (Case study: Higher Education in Indonesia)

Abstract: The purpose of this study is to determine the effect of student characteristics, design learning features, and learning outcomes on the effectiveness of blended learning. This research was conducted at a higher education institution in the city of Bandung, Indonesia. 376 The sampling method used was purposive sampling technique, in this case involving 376 students. The data analysis method used in this study was a multiple linear regression analysis. The findings of this study indicate that the design learning features and the learning outcomes can significantly influence the implementation of blended learning, while the student characteristics do not significantly influence. It shows that to increase the effectiveness of the implementation of blended learning, we need to maximize the design learning features. Besides, factors related to student motivation and satisfaction must also be considered. Thus, the effectiveness of implementing blended learning can be increased. Abstrak: Tujuan penelitian ini adalah untuk mengetahui pengaruh karakteristik siswa, desain fitur pembelajaran, dan hasil belajar terhadap keefektifan blended learning. Penelitian ini dilakukan di sebuah institusi pendidikan tinggi di kota Bandung, Indonesia. pengambilan 376 sampel yang digunakan dengan teknik purposive sampling, dalam hal ini melibatkan 376 mahasiswa. Metode analisis data yang digunakan dalam penelitian ini adalah analisis regresi linier berganda. Temuan penelitian ini menunjukkan bahwa desain fitur pembelajaran dan hasil belajar berpengaruh signifikan terhadap penerapan blended learning, sedangkan karakteristik siswa tidak berpengaruh signifikan. Hal tersebut menunjukkan bahwa untuk meningkatkan keefektifan penerapan blended learning di pendidikan tinggi perlu memaksimalkan desain fitur pembelajaran. Selain itu faktor yang berhubungan dengan motivasi dan kepuasan mahasiswa juga harus diperhatikan. Dengan demikian efektivitas penerapan blended learning dapat ditingkatkan.
Document-Level Neural TTS Using Curriculum Learning and Attention Masking

Speech synthesis has been developed to the level of natural human-level speech synthesized through an attention-based end-to-end text-to-speech synthesis (TTS) model. However, it is difficult to generate attention when synthesizing a text longer than the trained length or document-level text. In this paper, we propose a neural speech synthesis model that can synthesize more than 5 min of speech at once using training data comprising a short speech of less than 10 s. This model can be used for tasks that need to synthesize document-level speech at a time, such as a singing voice synthesis (SVS) system or a book reading system. First, through curriculum learning, our model automatically increases the length of the speech trained for each epoch, while reducing the batch size so that long sentences can be trained with a limited graphics processing unit (GPU) capacity. During synthesis, the document-level text is synthesized using only the necessary contexts of the current time step and masking the rest through an attention-masking mechanism. The Tacotron2-based speech synthesis model and duration predictor were used in the experiment, and the results showed that proposed method can synthesize document-level speech with overwhelmingly lower character error rate, and attention error rates, and higher quality than those obtained using the existing model.
COMPARING THE HIGH AND LOW ACHIEVER STUDENTS’ DIFFICULTIES IN LEARNING WRITING DURING REMOTE LEARNING

Writing in English is very important for every student who learns English as a foreign language (EFL). With good writing skills, information can be conveyed well to readers. Yet, EFL students often find difficulties in writing by using English as a target language, especially during the pandemic of COVID 19. This paper aims to investigate some problems faced by the students in their learning of writing during the pandemic of COVD 19. The design of the study is a case study. The instruments to obtain the data were interviews and documents. The subjects of the study were three high achiever students and three low achiever students who joined the writing course in the English Education Study Program in the University of PGRI Wiranegara. They were chosen based on their writing achievements. The finding shows that the high achiever students’ problems are more on the technical problems (the internet connection, bad signals, and family distractions during online learning). For them the technical problems would lead to other issues such as materials comprehension and task accomplishment. The low achievers have more problems in generating ideas for all type of writing. The study also reveals that the low achievers have more time management problems and more language problems. Interestingly, they share the same solutions. The solutions are 1) to read more sources to get ideas and to help them write; 2) to boost moods before writing by reading a lot, listening to music, and watching movies; 3) to ask friends and lecturers to help understand the materials and tasks; and 3) to use writing tools application to solve the writing problems particularly in vocabulary and grammar.
Medical Images Processing using Effectiveness of Walsh Function

This paper presents the new method for processing medical images using effectiveness Walsh function.The Block pulse functions is defined, and the coefficient function is developed for identifying fixations and boundary limitations.The algorithms developed for basic functions with respect individual blocks and simulating using MATLAB.Proposed scheme shows that the performance analysis is better than existing schemes.
Analysis of Naıve Bayes Algorithm for Email Spam Filtering

The upsurge in the volume of unwanted emails called spam has created an intense need for the development of more dependable and robust antispam filters. Machine learning methods of recent are being used to successfully detect and filter spam emails. We present a systematic review of some of the popular machine learning based email spam filtering approaches. Our review covers survey of the important concepts, attempts, efficiency, and the research trend in spam filtering. The preliminary discussion in the study background examines the applications of machine learning techniques to the email spam filtering process of the leading internet service providers (ISPs) like Gmail, Yahoo and Outlook emails spam filters. Discussion on general email spam filtering process, and the various efforts by different researchers in combating spam through the use machine learning techniques was done. Our review compares the strengths and drawbacks of existing machine learning approaches and the open research problems in spam filtering. We recommended deep learning and deep adversarial learning as the future techniques that can effectively handle the menace of spam emails
A Nexus among Institutions, Education and Economic Growth: An Analysis of Developing Countries

This study investigates linkages among institutions, education and economic growth empirically and theoretically and is based on panel data between 1996 and 2017. For the panel data, two-stage least squares (2SLS) regression analysis was used to estimate the results in developing countries. Rule of law, control of corruption, absence of violence and political stability were used as proxies for institution. We found that economic growth exerted positive and significant effects on education, control of corruption, absence of violence and political stability. Rule of law, absence of violence, political stability and control of corruption have positive and significant effects on education, and education has a negative and significant effect on absence of violence and political stability but a positive and significant effect on rule of law and economic growth. Hence, results show that institutions positively affect economic growth through education and a difference in institutional quality is the key to differences in education among countries.
THE DEVELOPMENT OF DIGITAL COMPETENCES. CURRENT CHALLENGES AND PERSPECTIVES

The current context determined by the social distancing has changed the way of carrying out the learning activities which are taught and evaluated at school; during this situation the Romanian and also the global education system faced an unprecedented challenge, namely the transfer of the whole school activity to the online environment. Given this situation, we analyzed data from national and international studies in order to have an overview of the characteristics of digitization and existing digital skills, especially in the Romanian education system. This analysis allowed the understanding of the structure on which this sudden digitization developed and the premises of public policies on which the process was built. The analysis was combined with the presentation of projects carried out during this period, in order to prepare the various school actors in the field of digital education in the form of recommendations to support the empowerment processes in training digital skills of teachers and students in the current context and on a long-term.
Digital Identity as a Phenomenon of Information Modernity

The paper is devoted to the philosophical under-standing of digital identity as a phenomenon of in-formation modernity. It is substantiated that the existence of a modern person is constituted in the real and virtual worlds, which contributes to the transformation of traditional anthropological attrib-utes and the introduction of a digital component into it. It is stated that in the virtual space, identifica-tion is carried out through virtual communication with network communities. It is concluded that the result of adaptation to life in hybrid reality is the formation of a virtual personality as a carrier of digi-tal attributes: а digital image, а digital profile, and a digital identity as an awareness of oneself as an integral part of information reality. Through the “re-al-virtual” dichotomy, the definition of digital identi-ty is formulated as the unity of “I-virtual” and “I-real”, the aggregate perception and experience of oneself in indissoluble unity with the real and virtual worlds.
Evaluating the User Experience of a Web-Based Child Health Record System

The aim for this research is to design , develop and evaluate a web - based child health record system with appointment notification. This system has the ability to record all the medical information about a child such as the heig ht, weight, treatments and medical conditions . It also has the ability to rec ord the visit s and immunization details, reminder for next visits and immunization appointments. A User Experience ( UX ) Test were conducted during the study to evaluate the system . User Experience Questionnaire (UEQ) is the instrument that is being utilized during the UX Testing to evaluate the user experience quality of a product. UEQ has been divided into six scales which are attractiveness, perspicuity, efficiency, dependability, stimulation and novelty . During the UX Testing, the users were given a chance to explore and evaluate the system. The result from the UX Testing indicates that most of the users agree that the system is attractive and has a good perspicuity, efficiency, dependability, stimulation and novelty. In conclusion, this research h as achieved the objectives which are to design, develop and evaluate a Web - Based Child Health Record System with Appointment Notifications.
The Architecture of the Common Digital Space of Scientific Knowledge

The architecture of the Common Digital Space of Scientific &#x0D; Knowledge (CDSSK) is determined by its functions and objectives. CDSSK includes a set of subspaces related to various scientific fields. The unity of subspaces is provided by unified principles for constructing subspaces and ontological connections between their objects. Each subspace includes digital objects, metadata containing facts related to objects, and subject onotologies that provide advanced searches and navigation through space. All &#x0D; information is reflected in the CDSSK according to the rules of the «semantic WEB». The content of each subspace includes a core (time-tested reliable 8 scientific results) and a superstructure — new scientific results that have passed preliminary examination.
Early results on deep unfolded conjugate gradient‐based large‐scale MIMO detection

Deep learning (DL) is attracting considerable attention in the design of communication systems. This paper derives a deep unfolded conjugate gradient (CG) architecture for large-scale multiple-input multiple-output detection. The proposed technique combines the advantages of a model-driven approach in readily incorporating domain knowledge and deep learning in effective parameters learning. The parameters are trained via backpropagation over a data flow graph inspired from the iterative conjugate gradient method. We derive the closed-form expressions for the gradients for parameters training and discuss early results on the performance in a statistically identical and independent distributed channel where the training overhead is considerably low. It is worth noting that the loss function is based on the residual error that is not an explicit function of the desired signal, which makes the proposed algorithm blind. As an initial framework, we will point to the inherent issues and future directions.