Reviewerly/exHarmony huggingface dataset:
Towards Deep Learning-Powered Chatbot for Translation Learning

As a consequence of the recent advances in artificial intelligence and educational technologies, the education sector is witnessing significant changes and transformations through massive use of intelligent systems with the goal to assist students in their learning experience and teachers in delivering academic knowledge in a better way while reducing burnout and stress. Communication, knowledge acquisition, and learning are now possible anytime and anywhere through modern technologies. However, learning translation is a process that requires continuous effort, enthusiasm, and motivation from both students and instructors. While some universities adopt traditional and outdated approaches to translation instruction, others use more innovative ways. Within this context and in order to foster a student-centered translation learning approach, our work focuses on taking advantage of recent advances in machine learning to develop a chatbot to help language learners, especially translators, develop their skills by having a conversation with a chatbot and getting the appropriate Arabic translations of English sentences under study. A general framework is proposed, and a first prototype is developed using a part of bilingual corpora. Another focus of this study is the preprocessing phase used to create a sentence-based paired dataset to train the machine learning model from bilingual corpora. The preliminary results are promising.
UX in the Arab World - Research Trends and Challenges for a Better Understanding and Collaboration

During the last decade, a considerable number of studies question how HCI is perceived and how the cultural differences are considered. However, very few focused on eliciting the cultural factors of UX and the underlying integration of UX research methods. In this paper, we overview the literature on UX research in the Arab world. Among others, our findings show that UX research focused on two main themes (1) elicitation of UX guidelines and UX patterns (best UX practices) to match the Arab culture (2) identification of the factors influencing UX in the Arab region. The findings also illustrate existing efforts to raise awareness of HCI and conclude with some research challenges that draw a road map for a better collaboration between Arab researchers and the international community.
Uncertainty Detection in Historical Databases

Historians analyze information from diverse and heterogeneous sources to verify hypotheses and/or to propose new ones. Central to any historical project is the concept of uncertainty, reflecting a lack of confidence. This may limit the scope of the hypotheses formulated. Uncertainty encompasses a variety of aspects including ambiguity, incompleteness, vagueness, randomness, and inconsistency. These aspects cannot be easily detected automatically in plain-text documents. The objective of this article is to propose a process for detecting uncertainty, combining dictionary-based approaches, and pattern identification. The process is validated through experiments conducted on a real historical data set.
Learning-Based Visual Acuity Test System with Pepper Robot for User Behavior Research

Hand pose estimation based on deep learning is widely used in Human-Computer Interaction (HCI) field. This paper combines state-of-the-art hand pose estimation to build a gesture recognition model based on Long Short-Term Memory (LSTM) for a visual acuity test system with the Pepper robot. The size of the optotype is updated according to the distance between a user and the robot and displayed on the table. Experimental results show that the system is robust for users to perform well with different fingers. In the future, the HRI system is good to design a questionnaire to investigate users’ preferences which include acceptances, a distance of visual acuity test, sit or stand, number of fingers.
Facial Expression Change Recognition on Neutral-Negative Axis Based on Siamese-Structure Deep Neural Network

Facial expressions are very crucial in everyday communication, since a person’s internal state of emotion swings can be assessed based on changes in expressions. Because there have been previous studies on positive expressions, and people with diseases are more inclined to show negative expressions, we focused our study on negative expressions. And we provided a new objective measure of facial expression that can be applied to dementia care, rehabilitation support, QOL assessment, etc. We analyzed the process of “change" in facial expressions for obtaining the degree of negative expressions, rather than the extreme facial expressions previously studied in various fields. Unfortunately, since there is no database on expression change picture sequences, we collected a small-scale database on our own in the experiment. We applied Siamese-structure deep neural network for classification of the pictures. The results show that the muscle parts affected by the change of facial expressions from neutral to negative, such as lip corners and forehead, can also be extracted accurately by the network, and a recognition accuracy of over $$92\%$$ is obtained.
Classifying Documents by Viewpoint Using Word2Vec and Support Vector Machines

Ensuring viewpoint diversity in mass media is a historical challenge and recent political events, and the ever-increased use of the Internet, have made it an increasingly critical and contentious issue. This research explores the relationship between semantic structures and viewpoint; demonstrating that the viewpoint diversity in a selection of documents can be increased by utilizing extracted semantic and sentiment features. Small portions of documents matching search terms were embedded in a semantic space using word vectors and sentiment scores. The resulting features were used to train a support vector machine to differentiate documents by viewpoint in a topically homogeneous corpus. When evaluating the top 10% most probable predictions for each viewpoint, this approach yielded a lift of between 1.26 and 2.04.
APPLICATION OF NEURAL NETWORKS IN CLASSIFICATION OF LOW-QUALITY SATELLITE IMAGERY

The article offers a solution to the problem of classification of low-quality images of aircraft using convolutional neural networks. To solve this problem with sufficient accuracy, an analysis of popular architectural neural networks was performed, and the process of preparing the selected algorithm at all stages was described: preprocessing test data, training the neural network, and processing the results obtained.
Cyber Security and Management

1. To make a secure cyber ecosystem in India, generate an ample amount of trust in IT systems and transactions in cyberspace and thereby enhance the adoption of IT in all sectors of the economy. 2. To create a convincing framework for developing security policies and enabling actions to abidance to global security standards. 3) To build up the Regulatory framework to ensure a Secure Cyberspace ecosystem. 4) To enhance and create National and Sectoral level mechanisms to obtain strategic policy regarding threats to ICT infrastructure. 5) To enhance the protection of the Nation's critical information infrastructure by operating a National Critical Information Infrastructure Protection Centre and mandating security practices related to the design, accession, evolution, use and operation of information resources. 6) For the growth of suitable indigenous security technologies, solution-oriented research, proof of concept, pilot development, transition, diffusion. 7) To develop the range of the integrity of ICT products and services by establishing infrastructure for testing &amp; validating the security of such products. 8) Create a workspace for 500,000 professionals skilled in cyber security in India within 5years 9) To provide monetary benefits to businesses to adopt standard security practices. 10) To enable security of information while during the process, storage &amp; transit to safeguard the privacy of citizen's data and for reducing financial losses due to cybercrime. 11) To create adequate safety, investigation and prosecution of cybercrime and development of law enforcement capabilities through appropriate legislative intervention.
Dynamic Topic-Noise Models for Social Media

Temporal topic models often cannot effectively approximate topics on social media data sets due to the noise levels inherent in these types of data. Topic-noise models are important for modeling the short, sparse, noisy posts that we see throughout social media platforms. We propose using topic-noise models for temporal topic modeling, specifically D-TND (dynamic topic-noise discriminator). It enables topic and noise distributions to be generated together, modeling both the relationships between words in documents and the evolution of words and noise. We also propose Dynamic Noiseless Latent Dirichlet Allocation (D-NLDA), which integrates D-TND’s time-dependent noise distribution with the topic distributions of Dynamic LDA, and show its propensity for improving dynamic topic models by effectively separating noise and topics on two large Twitter data sets.
Impact of performance: SSD vs YOLOV3 machine learning for mask detection and temperature sensing device

Since the advent of the COVID-19 pandemic, face mask detection has witnessed substantial advancements in the fields of image processing. This paper includes a performance comparison between two of the most popular one-stage object detectors, YOLOv3 and SSDMobileNetV2 for a custom mask detection model on the System on Chip SoC platforms. The comparison was held regarding their image classification performance, speed, loss graph, and transferability to portable platforms such as the raspberry pi. The results obtained from the comparison showed that the SSDMobileNetV2 was the optimal choice in terms of performance for mask detection for portable devices such as the raspberry pi.
THEORETICAL SUBSTANTIATION OF THE CONCEPT OF DEVELOPMENT OF CREATIVE POTENTIAL OF STUDENTS

The article discusses the issues of developing the concept of the development of the creative potential of future teach- ers of vocational training; substantiates its main provisions: the idea; patterns and principles of the development of the creative potential of future teachers of vocational training; content and semantic content, reflecting the target, content and procedural aspects of the preparation of the future teacher of vocational training in the modern creative educational environment of the university.
Strategies for sense reading in the process of learning to solve text problems in primary school

The article deals with the issue of the formation of semantic reading skills in mathematics lessons in elementary school in the process of analyzing and solving plot text problems. Attention is focused on the stages of analyzing the text of the task in accordance with the known types of semantic reading. For each of these stages, a brief description of the students' activities is given. The purpose of the study is to identify the features of the formation of semantic reading skills in younger schoolchildren when working with text tasks. As a result, strategies and techniques that contribute to the formation of the foundations of semantic reading in younger schoolchildren are described; examples of the use of some techniques in mathematics lessons are given.
Innovative technologies for the reproduction of the socio-cultural potential of young people through the prism of a project-oriented approach in a music college

The purpose of the study is to study and analyze innovative technologies for the reproduction of the socio-cultural potential of students in a music college. The scientific novelty of the research consists in identifying and substantiating the interrelations in the process of social reproduction, which provides innovative educational and educational activities in a music college. As a result, the authors have developed a technology of social audit of the process of reproduction of the socio-cultural potential of youth in a music college. The technologization of the process made it possible to develop a model for managing the reproductive processes of the socio-cultural potential of college youth based on the principles of a project-oriented approach.
Between Morphological Research and Social Criticism

Musical noises have existed in music from the past but are treated separately in one way or another. Avant-garde music likes complexity, with regards to both structures or compositional processes and sounds: in acoustic terms, noises are more complex sounds than the so-called ‘musical’ sounds. Before 1945, noise had already entered avant-garde music in several ways, closely combining morphological research and criticism. The avant-garde music of the immediate post-1945 era unmistakably has a ‘technocratic’ aspect. In instrumental music, dissonance, being so widespread, becomes commonplace: we can no longer consider it as a form of criticism. Much as the 1950s and 1960s were a period of faith in technocratic progress, the 1960s and 1970s were a period marked by protest. In avant-garde music, composers such as Iannis Xenakis, Luigi Nono or Helmut Lachenmann also use noises for purposes of protest.
National Education Policy-2020

Education is a building block for any individual as well as the nation. Today the field of education is undergoing rapid changes, with the advent of Industry 4.0 that emphasizes artificial intelligence, robotics, virtualization, augmented reality, big data, adaptive technology, and so on. The needs of the society are also changing rapidly. This calls for reforming the education system from traditional to Education 4.0, transforming the role of colleges and universities, and changing the strategies to prepare for this new world. At the backdrop of this scenario the National Education Policy-2020 (NEP-2020) has shifted its focus to refine the traditional education system by a new personalized, experience-based, and technology integrated education system. The NEP-2020 is a milestone in achieving the goals of Education 4.0, which not only aims at meeting the needs of the industry but also to ensure the best possible development of students. The proposed chapter aims at providing a platform to the stakeholders of higher education to explore strategies that will cater to the changing needs of the society. It intends to emphasize on the changing role of higher education as cited in the NEP-2020. Emphasis will be particularly given to the integration of new technology that includes artificial intelligence, machine learning, virtualization, robotics, block chain, and so on.
Techno-Pedagogical Concepts with Digital Skills

Dynamism and interactivity are the attributes of a techno-pedagogical innovative teaching–learning environment. The core foundations of this environment reside in digital skills and related competencies. It is, however, important to understand that integration of technology is not antagonistic to the traditional teaching setup. A balanced approach between technology and the innovative pedagogies can help in exploring and achieving excellence in teaching competencies as per the changing scenarios. The present pandemic has compelled every educator to shift into an online mode of education almost overnight. This has opened the door to various new opportunities and challenges. This chapter has been designed to assist stakeholders in exploring the digital skills and pedagogical experiences for catering to the needs of ‘digital natives’, more specifically, that of Generation Z. This chapter has four sections. The first section focuses on the meaning of pedagogy and technologically enabled pedagogy. The second section emphasizes digital literacy, along with the educational needs of digital natives and Generation Z. The third section throws light on the diverse digital pedagogical tools, and the concluding section highlights the role of teachers in a techno-pedagogical learning environment. A small insight is also provided toward assessment methodologies and some open digital resources for facilitating technology integration into pedagogical innovations.
Introduction

This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book offers a more nuanced interpretation of Shannon and Weaver and points out recent developments in cybernetics. It presents theoretical perspectives on noise and noise music from different disciplines. The book traces the interpretation of noise in communication theories from Claude Shannon and Warren Weaver to the more recent activities of the Cybernetic Cultures Research Unit. It looks at ‘hyperstitional’ aspects in punk and industrial music. The book argues that this ‘noise of the new’ in popular music is neither a purely sonic phenomenon nor a mere transgression of a dominant musical regime. It retraces how noise gained importance in avant-garde music. The book focuses on the analysis of non-score-based music. It argues for an approach in which the musician’s and listener’s perspectives interact. The book analyses a recording of a solo improvisation by the contemporary American drummer Chris Corsano.
Back to school for higher ed marketers

With classes starting year‐round for college students, you could say that it's always back‐to‐school season. Still, there's something about summer winding down that gets us in the spirit for restocking our stash of school supplies and navigating a new schedule.
Is There Noise in Helmut Lachenmann's Music?

Musical acoustics and psychoacoustics have informed us that in music there is hardly any sound without noise components – components that in many cases and respects are crucial for the characteristics of a particular instrumental or vocal timbre and make it so hard to produce ‘exact’ copies of such timbres through physical modelling. Twentieth-century music since Luigi Russolo, Erik Satie and Edgard Varese has explored two different functions of noise: its fundamental incompatibility with and its gradual approximation to pitched and tonal sounds. Lachenmann scholarship has largely followed the composer’s own scepticism concerning the term ‘noise’.The unsettling qualities of noise-permeated sounds in Lachenmann’s works assume a crucial function in disturbing such pacified areas. The fragmentary character referred to in the title of the work is particularly recognizable in the ‘interrupted exposition’ that introduces a large number of sound families, while in the further course long passages are reduced to only a few families or sounds.
Noise Annoys, Noise is the Future

This chapter argues that the ‘noise of the new’ in popular music is neither a purely sonic phenomenon nor a mere transgression of a dominant musical regime, but rather a kind of communicational noise that overwhelms the current limits and norms of social communication and ushers in an unanticipated future that extends beyond the purely musical or sonic. When Shannon and Weaver introduced their ‘mathematical model of communication’ in 1949, both communication and noise were seemingly considered an engineering issue, while at the same time presented in a highly generic and abstract form. The concept of noise as premonitory also resonates with the idea of hyperstition as developed by the Cybernetic Cultures Research Unit in the 1990s to account for the ways in which aesthetic works such as William Gibson’s Neuromancer could not only anticipate the future but engineer it.
Noise as Ground in Improvised Music

During the 1960s, several groups of composers, performers and artists gathered to protest against the established socio-political structures with a new non-idiomatic concept of music. The chapter outlines the state of the art of the analytical research on improvised music. It proposes to use the concept of noise as a constructive aesthetic phenomenon to gain a new perspective, and perhaps better understanding, of improvisations such as the ones by Chris Corsano. The chapter deals with a listening-informed analysis to examine the vertical density of sounds in the improvisation and identify the horizontal densities and rhythmic contours, in particular, the ways in which Corsano subverts the listener’s perception of rhythm over the course of the improvisation. Derek Bailey’s comment on the un-analysability of free improvisation is a testimony to the close relationship between noise music and free improvisation.
Multimodal interaction analysis of non-lexical vocalisations in low-verbal autistic children

This article analyses non-lexical vocalisations produced by low-verbal autistic children. Seven dyads of naturalistic interactions between non-autistic adults and low-verbal autistic children over five years old were analysed from a multimodal conversation analysis perspective. Data were extracted from an audio-visual corpus of interactions in institutional (school) and non-institutional settings (home). The data are in Brazilian Portuguese. The videos are visualised using the ELAN tool and transcribed. The analyses showed that in some cases participants did not reach a mutual understanding of the semantic meaning of non-lexical vocalisations, while in other cases, the meanings of vocalisations emerged between the participants in the multimodal process of sense-making in their embodied context. A microanalysis of where these vocalisations occurred and their multimodal aspects (linguistics, bodily, material, and spatial) suggests that: a) such occurrences are both initiated by the autistic child and responsive to the non-autistic interlocutor’s turn; b) some vocalisations play an important role in the sequential organisation of the interaction, promoting the maintenance of intersubjective of low verbal children; and c) non-autistic adult interlocutors perform a varied set of actions, recycling, incorporating, retaking, assigning meaning, and repairing the non-lexical vocalisations produced by autistic children. The indexical analysis shows how communicative ecologies create meaning. This study thus contributes to our understanding of the interactional behaviour of these children and their interlocutors.
Visual Question Answering

We propose the task of free-form and open- ended Visual Question Answering (VQA). Given an image and a natural language question about the image, the task is to provide an accurate natural language answer. Mirroring real-world scenarios, such as helping the visually impaired, both the questions and answers are open-ended. Visual questions selectively target different areas of an image, including background details and underlying context. As a result, a system that succeeds at VQA typically needs a more detailed understanding of the image and complex reasoning than a system producing generic image captions. Moreover, VQA is amenable to automatic evaluation, since many open- ended answers contain only a few words or a closed set of answers that can be provided in a multiple choice format. We provide a dataset containing ~0.25M images, ~0.76M questions, and ~10M answers and discuss the information it provides. Numerous baseline for VQA are provided and compared with human performance. In this model, we have exclusively introduced a feature of voice to text using Speech recognition, Google Text-to-Speech and pygame module.