Reviewerly/exHarmony huggingface dataset:
Assessment and Management of Language and Technology Literacy Barriers to access E-Learning Services in India

Language and technology literacy barriers to access E-learning services have been a topic of interest for the last two decades. The paper intends to explain how language and technology literacy are creating obstacles for students and teachers in India. The paper presents research aimed at overcoming obstruction to citizens’ capability to access the E-learning services. Especially in the context of a multi-lingual country like India, these issues must be researched well for better service delivery. Cost-effective and readily accessible technology and electronic devices have broadened the scope of facilities for the citizens of India. Several parameters like socio-economic conditions, economic status, and access to internet facilities have been considered to analyze the data. Lack of understanding of foreign language and technology has created huge differences among the students and generating misconceptions about the services. National Education Policy taken by GOI in 2020 has focused to remove the language and technology literacy barrier between students and educators by popularizing language education. Ways to manage the discriminating factors are the major objectives of this research. Implication of Natural language processing (NLP) advancements in other languages have become pertinent as technology benefits non-English speaking communities and businesses can develop localized applications to reach customers in their preferred languages. Educational applications are unable to reach the expectations of the students, teachers, and parents. Still many mobile applications have become popular as a learning medium. More research and government initiatives are required to implement online education across India.
Medical Students Perceptions towards Smart Devices and Their Relationship with Academic Performance

Background: Smart devices turned into a basic tool of medical students' academic life. Smart devices are utilized throughout the day for numerous reasons including learning, communication, productivity, entertainment, utilities, social networking and gaming. The objectives of the current study were to determine the use and perceptions of medical students at Majmaah University, Saudi Arabia towards smart devices and its relationship with academic performance.Methods: This was a cross-sectional study to determine the use and perceptions of medical students at Majmaah University, Saudi Arabia towards smart devices. The total enumeration of all eligible students was considered in this study. Data were collected by a questionnaire. Analysis was performed by SPSS.Results: All students (n=174, 100%) use smart devices and 37% use them more than 6 hours per day. 141 (81.0%) students preferred to study using smart devices. Most students utilize smartphones in studying lectures and preparing PBL/CDs 79.3% and 75.3% respectively. Eighty-seven (49.7%) have a good perception towards smart devices. Nine (47.4%) students with high academic performance study less than three hours/day with smart devices.Conclusion: Most students at the College of Medicine, Majmaah University use smart devices, mostly for more than six hours every day. Studying lectures constitute the most use of smart devices. Most students have good perception towards smart devices. There is a significant relation between the number of hours spent on smart devices and academic performance.
A significance of Identity Management as a Prerequisite for Enterprise AI on the Cloud

This paper provides a review on the significance of identity management for enterprise AI on the cloud. In addition to data security and authentication, identity management is continuously developing across key tasks such as synchronizing internal data, allowing consumer contact preference management, and fulfilling privacy compliance needs, to mention a few. Protection of corporate information systems from data breaches, hostile insiders, and fraud continues to be a key business concern, and this is fueling the need for better identity analytics that can dynamically identify abnormal user behavior. IT professionals' work is becoming somewhat simpler as identity and access management solutions grow more automated — but they can't fully delegate their responsibilities just yet. Many innovations in the identity and access management (IAM) sector have been driven by mobile technology in recent years, with suppliers being encouraged to enhance usability on mobile devices as a result. Identity and access management solutions are now being enhanced by the incorporation of advancements like artificial intelligence, machine learning, microservices, and cloud services, often with the idea of achieving them more smooth, accessible, and automated for both end-users and IT.
Atomizing E- Government Facilities using Big Data Analytic

During the last two decades, technical advancements in data bases and query processing have replaced hard copy maintenance in government sectors, resulting in an increase in the use of software applications to simplify human tasks in a matter of seconds. Any official task that has to be more efficient requires improvement and quick access.Collecting demographic information is also a major concern for government authorities. This article offers a method for gathering people's data and organising it as a hierarchy using a tree structure, which may be used to produce unique data and reduce redundant data. The Hadoop Map Reduction function can be used to complete this expected task.
Finally, which meta-heuristic algorithm is the best one

This paper is conducted to rank the six meta-heuristic algorithms such as the genetic, ant colony optimisation, tabu search, particle swarm optimisation, imperialist competitive, and simulated anne...
Функции экранов в современном российском театре в эпоху трансмедийности: от экранов малого формата к виртуальной реальности

This article explores the role of screen images in contemporary Russian theatre and describes the modifications the theatre faces during the Digital Turn. By examining the performances of such artists as Maxim Didenko, Danil Chaschin, Andrey Prikotenko, Mikhail Patlasov, Semen Alexandrovsky, etc. the author of this article reveals the transformation in the usage of displays on the stage resulting from the changing context and new dimensions. In the theatre space, a screen is increasingly being presented in modern modifications. Often a monitor that is used in performances represents a screen reality. A screen image in the theatre equals its real self. It happens for example when a performance includes smartphones that people can interact with. In that case, a gadget becomes a readymade, an image on the smartphone screen gains new meanings without changing its form. But a display on the stage can also refer to the layers of virtual reality that it is not associated with outside the theatre space. This happens, for example, when a screen is used to place the audience inside a computer game or when phone displays are shown to spectators on big monitors. Traditionally, displays were used in theatres to demonstrate what is happening behind the stage or to show the inner world of the characters: their dreams, memories, and fantasies. This approach has been adopted and developed by contemporary Russian artists and now it is applied to immerse the viewers into digital reality, in the world of social media and avatars or to show the 360-degree view of the world outside the stage during a performance.  A monitor in a theatre now is a window into other dimensions as well as a language component up to date enough to communicate with the audience today.
A Video Summarization Approach to Speed-up the Analysis of Child Sexual Exploitation Material

Identifying key content from a video is essential for many security applications such as motion/action detection, person re-identification and recognition. Moreover, summarizing the key information from Child Sexual Exploitation Materials, especially videos, which mainly contain distinctive scenes including people’s faces is crucial to speed-up the investigation of Law Enforcement Agencies. In this paper, we present a video summarization strategy that combines perceptual hashing and face detection algorithms to keep the most relevant frames of a video containing people’s faces that may correspond to victims or offenders. Due to legal constraints to access Child Sexual Abuse datasets, we evaluated the performance of the proposed strategy during the detection of adult pornography content with the NDPI-800 dataset. Also, we assessed the capability of our strategy to create video summaries preserving frames with distinctive faces from the original video using ten additional short videos manually labeled. Results showed that our approach can detect pornography content with an accuracy of 84.15% at a speed of 8.05 ms/frame making this appropriate for realtime applications.
Article 3—Text and Data Mining for the Purposes of Scientific Research

Abstract This chapter focuses on the laws about text and data mining for scientific researchstipulated under Article 3 of the Directive 2019/790 or copyright directive of the Digital Single Market in Europe. It examines the legislation that require Member States to provide an exception for reproductions and extractions made by research organisations and cultural heritage institutions on text and data mining of works or other subject matter for the purposes of scientific research. It also stresses that copies of works or other subject matter on text and data mining will be stored with an appropriate level of security and retained for the purposes of scientific research. The chapter talks about rightholders, which are allowed to apply measures to ensure the security and integrity of the networks and databases. It mentions Member States that encourage rightholders, research organisations, and cultural heritage institutions to define commonly agreed best practices concerning the application of the obligation and measures on text and data mining.
On the Limits of Minimal Pairs in Contrastive Evaluation

Minimal sentence pairs are frequently used to analyze the behavior of language models. It is often assumed that model behavior on contrastive pairs is predictive of model behavior at large. We argue that two conditions are necessary for this assumption to hold: First, a tested hypothesis should be well-motivated, since experiments show that contrastive evaluation can lead to false positives. Secondly, test data should be chosen such as to minimize distributional discrepancy between evaluation time and deployment time. For a good approximation of deployment-time decoding, we recommend that minimal pairs are created based on machine-generated text, as opposed to human-written references. We present a contrastive evaluation suite for English–German MT that implements this recommendation.
MM Adapted MH Methods

In this paper, we derive a novel MH proposal, inspired from Langevin dynamics, where the drift term is preconditioned by an adaptive matrix constructed through an MM strategy. We propose several variants of low-complexity curvature metrics applicable to large scale problems. The proposed method is shown to exhibit a good performance in an image recovery example.
Addressing the Challenges of Interoperability and Cultural Heritage Data

One of the ongoing challenges for effective utilization of heritage science data is the lack of access to well-organized and accessible extant data sets and the need to structure data in formats that allow interrogation and integration of related data. This need for data fusion expands to both subjective and objective measurements and descriptors, as well as a long-overdue need for established guidelines for metadata and shared terminologies, or more critically, ontologies. Research into this area has shown the need for Knowledge Organization Systems (KOS) that bridge and integrate multiple ontologies that address specific needs – for example the Getty Vocabularies for cultural heritage terms, the Linked Art model for a simplified core CIDOC-CRM, as well as the OBO Foundry and other scientific ontologies for measurements and heritage science terminology.[1]
MODEL FOR BUILDING STABLE MOTIVATION FOR STUDING THE MUSICAL INSTRUMENT

Studying the musical instrument is a longtime process aiming building technical and performing skills, cultivation of pupil’s musical taste and interest. But in the context of motivation it has a different aim- to influence on student’s motivation for achieving the above goals. There is a lack of the model which can help teachers to be aware of the process and have an influence on student’s motivation. This study strives to fill that gap presenting the model based on the Self Determination Theory for human’s motivation. The fundamental concepts of the theory are presented- basic psychological needs of autonomy, competence and relatedness, intrinsic and extrinsic motivation and their relation. On this basis the model for building stable motivation is suggested as an attempt to adapt the Self Determination Theory to the needs of studying the musical instrument. Some practical aspects of the model are presented. The model is applied among 7-14 years old pupils attending guitar course, but taking into account the age characteristics it might be successfully used with students and adults. We hope that this study can be useful for professionals teaching different musical instruments as well as to provoke the future research in that specific field.
The mediating role of organizational silence in the relationship between workplace ostracism and employees' creativity (Case Study: employee of Lorestan University)

Context: Employee creativity and the use of their opinions are the most important factors influencing the development of organizations and act as the antidote to laziness and weakness in the organization. Meanwhile, various factors affect employees' creativity, including workplace ostracism and organizational silence. Objective: The purpose of this study was to investigate the mediating role of organizational silence in the relationship between workplace ostracism and employees' creativity at Lorestan University. Research method: The present descriptive-exploratory research is applied in terms of purpose and is based on the deductive research and positivism paradigm in term of philosophy. The statistical population of the study was 440 employees of Lorestan University. Based on Morgan's table, a sample of 205 people was selected by stratified random sampling. In order to measure the variables of the research, the (Ferris et al’s, 2008) workplace ostracism Questionnaire, (Torrance’s, 2001), creativity Questionnaire and the (Bouradas and Maria’s, 2019) organizational silence Questionnaire were used and Their reliability was confirmed by Cronbach's alpha. For data analysis, structural equations modeling and PLS software have been used. Findings: Research findings show that workplace ostracism has a positive relationship with organizational silence and a negative relationship with employee's creativity. Conclusion: The overall results of the study show that workplace ostracism has a negative relationship with employee's creativity both directly and through organizational silence.
On recommender systems with big data

This chapter introduces taxonomy of recommender systems (RSs) in the context of big data and covers the traditional RSs, namely, collaborative filtering (CF)-based and content-based methods along with the state-of-the-art RSs. We also present a detailed study on (a) state of the art methodologies, (b) issues and challenges such as cold start, scalability and sparsity, (c) similarity measures and methodologies, (d) evaluation metrics and (e) popular experimental datasets. This survey explores the breadth in the field of RSs with a focus on big data to the extent possible and tries to summarize them.
Pemetaan Informasi Sebaran Bidang Ilmu Pada Skripsi Fakultas Matematika dan Ilmu Pengetahuan Alam Lulusan IPB University Tahun 2015 - 2019 Berdasarkan Universal Decimal Classification:

Preliminary. IPB-University, a leading university in Indonesia, always produces a lot of research and innovation. Academic writing in the form of a thesis is a real proof. However, there has been no study that has mapped the results of these studies. This research was conducted to determine: the distribution of research topics, create a map of the field of science based on the Universal Decimal Classification standard, and visualize a map of keywords, as well as the productivity of the supervisor in the thesis of the Faculty of Mathematics and Natural Sciences, IPB University.Research Methods. This research is a bibliometric study with quantitative research methods, in order to describe the mapping of information on the distribution of knowledge in the thesis of the Faculty of Mathematics and Natural Sciences, IPB University.Research Data Processing. The object of this research is the Faculty of Mathematics and Natural Sciences thesis data in the IPB University Library database. The data is processed using the M.S. Excel and grouped according to the Universal Decimal Classification standard. The keyword data was created in an RIS File and analyzed using the VosViewer-Visualizing Scientific Landscapes 1.6.1.5 program developed by Nees Jan Van Eck and Ludo Waltman.Research Result. Proving that the thesis research topics of Faculty of Mathematics and Natural Sciences, IPB University graduates in 2015-2019 are 3,550 titles. Map of fields of science based on UDC showing research topics at most grade 004: “Computer Science and Technology, Computing and Data Processing” 719 (20.25%) titles, research topics at least grade 590: “Zoology” 43 (1.21%) . Co-word analysis using Vosviewer 1.6.1.5 on the occurrence of a minimum of 5 keywords succeeded in visualizing 683 keywords in 12 clusters. The keyword that appears the most occurs is Computer Science and Technology 153 times. Network Visualization shows the trend of the most popular research topics: “Computer Science and Technology” is in cluster 5 with a total network link strength of 397. Overlay Visualization shows a tendency the year the research was conducted, which was between 2016-2018. Density Visualization shows the tendency for the density of research volumes for each of these keywords to vary. The highest productivity of the thesis supervisor as the main supervisor is Imas Sukaesih Sitanggang as many as 79 guidance, while as member supervisors are Ali Kusnanto and Budi Waryanto, the number of guidance is 42 and 8 thesis guidance, respectively
Expounding the Blockchain Architecture

Blockchain is being fervently presented as the future of business and the future is here. It is paramount and pertinent to review the key differentiators of the blockchain technology and how it gets synchronized with other pioneering technologies to enable businesses to visualize and realize next-generation competencies. Considering its powerful and promising nature, enterprises are keenly embracing the blockchain technology. There are unprecedented number of start-ups with the sole aim of producing viable products and services to enable businesses and individuals to leverage the blockchain technology in a simplified and streamlined manner. In this chapter, we would like to explain various contributing components of any blockchain system in detail. There are a few interesting technology components in forming and firming up blockchains. All those are being delineated to give a comprehensive architectural view to our esteemed readers.
Earthquake Resistance and Disaster Prevention of Engineering Structure Based on Improved Genetic Algorithm

The earthquake often sweeps to the human side without any sign, with the higher the magnitude, the greater the test degree of the seismic effect of the building structure. When the earthquake comes, the vibration wave generated by the earthquake is transmitted to the ground, releasing the energy that can cause structural damage, which extremely damages people's property and life safety. Structural optimization method is an important development field. With the advancement of science and technology, people have successively proposed several direct calculation methods that do not depend on the problem itself, such as evolutionary strategy method, genetic algorithm, and evolutionary calculation method. These new optimization algorithms solve problems that cannot be effectively solved by ordinary calculation methods, such as the unimodal problem of building structures, structural gradient information problems, and other building structure problems. This paper proposes the seismic and disaster prevention of engineering structures based on improved genetic algorithm, and analyzes its characteristics and difficulties. Then genetic algorithm is used to realize the intelligent optimization design of seismic structure.
Secure and Efficient Access of Cipher Text for Mobile Cloud Computing

With the fame of distributed computing, cell phones can stack/recover individual information from anyplace whenever. Thus, the information security issue in versatile cloud turns out to be increasingly serious and forestalls further advancement of portable cloud. To ensure information security, clients normally encode their touchy information before transferring to cloud servers, which renders the information usage to be troublesome. In any case, there is no solid examinations for getting to cipher texts in mobile cloud. In this paper, we propose a safe and proficient information get to technique for versatile distributed computing. Consolidating proficient Mobile distributed computing system dependent on CP-ABE and presenting characteristic sprout channel for quicker cipher text access in versatile cloud. This plan has straight intricacy and depends for the most part on proficient symmetric key tasks. At long last, security examination and effectiveness correlation show that the proposition is successful for the proficient access of scrambled information in distributed computing.
IDENTIFICATION OF KAWI-SONGGORITI GEOTHERMAL PROSPECTS BASED ON FAULT AND FRACTURE DENSITY (FFD)

The aim of this research is to identify the surface structures of geothermal area in Kawi-Songgoriti based on lineament density and surface manifestation. The lineament density is processed by using satellite image as the input data. The surface structures were analyzed through the density of lineaments on the surface with FFD method. The lineaments are assumed associated with fractures or faults found in geothermal areas those are generally covered by surface manifestation which are hard to be identified. These faults and fractures were assumed as weak line that act as fluid thermal movement, thereby it can be used as guidance for the location of permeable area or a reservoir.  As a result, the high lineament density can be found in Kawi thus assumed as the control of Songgoriti manifestation.
The concatenated structure of quasi-abelian codes

The decomposition of a quasi-abelian code into shorter linear codes over larger alphabets was given in Jitman and Ling (Des Codes Cryptogr 74:511–531, 2015), extending the analogous Chinese remainder decomposition of quasi-cyclic codes (Ling and Solé in IEEE Trans Inf Theory 47:2751–2760, 2001). We give a concatenated decomposition of quasi-abelian codes and show, as in the quasi-cyclic case, that the two decompositions are equivalent. The concatenated decomposition allows us to give a general minimum distance bound for quasi-abelian codes and to construct some optimal codes. Moreover, we show by examples that the minimum distance bound is sharp in some cases. In addition, examples of large strictly quasi-abelian codes of about a half rate are given. The concatenated structure also enables us to conclude that strictly quasi-abelian linear complementary dual codes over any finite field are asymptotically good.