Reviewerly/exHarmony huggingface dataset:
School performance: New multimedia resources versus traditional notes

With the increasing adoption of information and communication technologies among youngsters, it has become common for high school students to incorporate the use of multiple devices and digital platforms in their study habits. Although these digital resources support and motivate them to learn, these are also a source of continuous distraction. This research analyzes the impact of studying with handwritten notes, WhatsApp, YouTube and searching the Internet in academic performance, through a mixed method that combines 31 focus groups and a survey of 7,217 students from 12 to 18 years of age in Chile. The results of the focus groups show that the positive impact of technologies in learning would depend on the students’ motivation for learning, their ability to efficiently control and manage the available digital resources, and their capacity to search and evaluate information on the Internet. The survey concludes that those who study with their notes more frequently have better academic performance, whereas those who frequently study with YouTube and WhatsApp have a lower GPA, with no significant differences when it comes to internet browsing. These results reinforce the need raised by scholars to generate policies that promote digital literacy both inside and outside the school. Con la creciente masificación de las tecnologías de información y comunicación entre los jóvenes, es cada vez más común que los estudiantes de secundaria incorporen el uso de múltiples dispositivos y plataformas en sus hábitos de estudio, lo que sería una fuente de apoyo y motivación, pero también de constante distracción. Esta investigación compara el impacto que tiene estudiar con apuntes escritos a mano, WhatsApp, YouTube y navegando por Internet, en el rendimiento académico, a través de un método mixto que combina 31 grupos focales y una encuesta a 7.217 estudiantes de 12 a 18 años en Chile. El análisis de los grupos focales muestra que el buen uso de tecnologías al estudiar dependería de la capacidad de los estudiantes para controlar y hacer un uso eficiente de los recursos digitales disponibles, de sus motivaciones individuales y de la habilidad que tienen para buscar y evaluar la información en Internet. Por su parte, los resultados de la encuesta concluyen que aquellos jóvenes que estudian con mayor frecuencia con sus apuntes presentan un promedio de calificaciones más alto y los que estudian frecuentemente con YouTube y WhatsApp, un promedio de calificaciones más bajo, sin encontrar diferencias significativas en el caso de los navegadores de Internet. Esto reforzaría la necesidad observada por académicos de generar políticas que promuevan la alfabetización digital tanto dentro como fuera del colegio.
ENCRYPTION AND DECRYPTION OF AUDIO SIGNAL BASED ON RSA ALGORITHN

One of the most important methods to protect and verify information that are exchanged over public communication channels in the existence of third party called antagonists is encryption. The stored or transmitted message is transformed in the encryption process to unreadable or gibberish form. The reverse process in which the intendent recipient can reveal the encrypted message content is called decryption. The encryption and decryption processes are achieved using secret keys that are exclusively exchanged between the sender and recipient. This method can be applied to any form of message such as audio, video, image or text data. The current work applies the well-known RSA algorithm for audio signal encryption and decryption. The performance of the presented algorithm has been tested via experimental implementation which show that the Cpestral Distance Measure (CD), Linear Predicative Code Measure (LPC) and Segmental Spectral Signal to Noise Ratio (SSSNR) reach to 6.8781, 4.9614 and -21.5563 dB respectively using Matlab simulations. The results on the presented technique validated that it is secure, reliable and efficient to be applied in secure audio communications as well as it performed high intelligibility of the recovered audio signal.
Classification of Tumors in Breast Echography Using a SVM Algorithm

In this work tumor classification was performed using K-means and GLCM algorithms to segment ultrasound images. In order to apply Stavros criteria, a lineal support vector machine (SVM) algorithm was used to classify benign and malignant tumors. 94% of echographies were correctly classified.
A Deep Learning based Arabic Script Recognition System: Benchmark on KHAT

This paper presents a deep learning benchmark on a complex dataset known as KFUPM Handwritten Arabic TexT (KHATT). The KHATT data-set consists of complex patterns of handwritten Arabic text-lines. This paper contributes mainly in three aspects i.e., (1) pre-processing, (2) deep learning based approach, and (3) data-augmentation. The pre-processing step includes pruning of white extra spaces plus de-skewing the skewed text-lines. We deploy a deep learning approach based on Multi-Dimensional Long Short-Term Memory (MDLSTM) networks and Connectionist Temporal Classification (CTC). The MDLSTM has the advantage of scanning the Arabic text-lines in all directions (horizontal and vertical) to cover dots, diacritics, strokes and fine inflammation. The data-augmentation with a deep learning approach proves to achieve better and promising improvement in results by gaining 80.02% Character Recognition (CR) over 75.08% as baseline.
Virtual Reality Media: The Simulation of Relativity Theory on Smartphone

Learning physics science is ideally accomplished through the experiments, although the theory of special relativity is challenging to understand. It is difficult because this topic has not occurred in real experience, and no technology has launched at the speed of light. To understand this theory, Virtual Reality (VR) can potentially visualize the actual concept of relativity by presenting an artificial environment to the students. The aim of this research is to develop the virtual reality application as a learning media for special relativity. This Research and Development uses the Lee and Owens Model, which consists of analysis, design, development, implementation, and evaluation. The system development method used is black-box testing. The result of the development of this system is the creation of a VR application to explain the material of relativity. From the results of black-box testing, the test results show that the percentage of application system success is 83%, which indicates that the application is functioning correctly on smartphone usage so that this application can be used on the theory of relativity simulation users using virtual reality devices.
Modeling Network Architecture: A Cloud Case Study

The Internet s ability to support a wide range of services depends on the network architecture and theoretical and practical innovations necessary for future networks. Network architecture in this context refers to the structure of a computer network system as well as interactions among its physical components, their configuration, and communication protocols. Various descriptions of architecture have been developed over the years with an unusually large number of superficial icons and symbols. This situation has created a need for more coherent systematic representations of network architecture. This paper is intended to refine the design, analysis, and documentation of network architecture by adopting a conceptual model called a thinging (abstract) machine (TM), which views all components of a network in terms of a single notion: the flow of things in a TM. Since cloud computing has become increasingly popular in the last few years as a model for a shared pool of networks, servers, storage, and applications, we apply the TM to model a real case study of cloud networks. The resultant model introduces an integrated representation of computer networks.
CAiRE: An Empathetic Neural Chatbot

In this paper, we present an end-to-end empathetic conversation agent CAiRE. Our system adapts TransferTransfo (Wolf et al., 2019) learning approach that fine-tunes a large-scale pre-trained language model with multi-task objectives: response language modeling, response prediction and dialogue emotion detection. We evaluate our model on the recently proposed empathetic-dialogues dataset (Rashkin et al., 2019), the experiment results show that CAiRE achieves state-of-the-art performance on dialogue emotion detection and empathetic response generation.
Education quality as a factor of modern studentʼs social success

Rapidly growing educational space as well as increasing demands of the market to the modern specialist made the problem of social success a topical one. The paper focuses on sociological analysis of social success of students, its purpose is to study satisfaction with the quality of education obtained as a factor of their social success achieved in the educational process. Social success is regarded as integrated evaluation of student personality, which is based on analysis of the educational organization. In contrary, social unsuccess is connected with academic, professional and personal failure demonstrated in the process of studentʼs self-realization in educational environment. Among factors, influencing the quality of education and hence the social success of students one can note motivation, professional focus, activity, digital behavior, skills in adopting of digital educational environment. Researches in this sphere can focus on development of feedback mechanisms with students, which can form their analytical competencies and foster confidence between participants of educational process. This determines to put focus of the study on resilient educational environment, project and creative forms of academic activity and on looking for the best ways of further implementation of digital technologies.
Privacy Guidelines for Contact Tracing Applications

Contact tracing is a very powerful method to implement and enforce social distancing to avoid spreading of infectious diseases. The traditional approach of contact tracing is time consuming, manpower intensive, dangerous and prone to error due to fatigue or lack of skill. Due to this there is an emergence of mobile based applications for contact tracing. These applications primarily utilize a combination of GPS based absolute location and Bluetooth based relative location remitted from user's smartphone to infer various insights. These applications have eased the task of contact tracing; however, they also have severe implication on user's privacy, for example, mass surveillance, personal information leakage and additionally revealing the behavioral patterns of the user. This impact on user's privacy leads to trust deficit in these applications, and hence defeats their purpose. In this work we discuss the various scenarios which a contact tracing application should be able to handle. We highlight the privacy handling of some of the prominent contact tracing applications. Additionally, we describe the various threat actors who can disrupt its working, or misuse end user's data, or hamper its mass adoption. Finally, we present privacy guidelines for contact tracing applications from different stakeholder's perspective. To best of our knowledge, this is the first generic work which provides privacy guidelines for contact tracing applications.
Leveraging Blockchain for Sustainability and Open Innovation: A Cyber-Resilient Approach toward EU Green Deal and UN Sustainable Development Goals

In 2015, the United Nations (UN) member states identified 17 Sustainable Development Goals (SDGs) to be fulfilled by 2030. SDGs are an urgent global call for action to provide a blueprint for shared prosperity in a sustainable world. At a European level, in December 2019, the European Green Deal was presented, a roadmap to implement the UN 2030 agenda with a commitment to a growth strategy that will turn environmental challenges into opportunities across all policy areas. To achieve these SDGs, blockchain is one of the key enabling technologies that can help to create sustainable and secure solutions, since it is able to deliver accountability, transparency, traceability, and cyber-resilience, as well as to provide a higher operational efficiency in global partnerships. This chapter overviews the potential of blockchain to face sustainability challenges by describing several relevant applications. Finally, different open challenges and recommendations are enumerated with the aim of guiding all the stakeholders committed to the development of cyber-resilient and high-impact sustainable solutions.
The Book Transformations in the Context of Media Revolutions

The article is devoted to the analysis of book transformation as one of the oldest and the most influential types of media in the historical context of media revolutions. It characterizes the main attributes of media, underlining common features of the book and other types of media. The article explores the evolution and specific changes of oral, written and electronic information carriers and other types of media in the context of time and space. It analyses historical conditions and the modern tendency to reproduce a book in audio and electronic formats. The article also claims that such transformations make a significant impact on the classical relationship between all participants and stakeholders in book creation, production, distribution and usage. The authors emphasize the importance and further impact of large-scale changes in the nature of book in the context of media revolutions. The history of humankind has undergone four media revolutions. At present one can observe transforming the world and domestic book markets: new market segments are being formed and continue to develop. The most important trend is the transformation of the book as medium and the appearance of its new features and communication opportunities. The article considers the processes of mediatization that transform mental landmarks of contemporaries, and form new skills and techniques that are essential in modern communication. Mutual influence and modification of information channels and message itself, lead to the modification the perception of texts. All these processes require the development of new media authors’, text creators’, publishers’, editors’, readers/users’, media consumers’ competences, and ultimately change communication abilities and the priorities of all media consumers. The authors underline the necessity to create and use a new transdisciplinary medialogical approach to book research and its industry in space-time context.
Simulation of a Homomorphic Encryption System

Abstract Cryptology is defined as the science of making communication incomprehensible to third parties who have no right to read and understand the data or messages. Cryptology consists of two parts, namely, cryptography and cryptanalysis. Cryptography analyzes methods of encrypting messages, and cryptanalysis analyzes methods of decrypting encrypted messages. Encryption is the process of translating plaintext data into something that appears to be random and meaningless. Decryption is the process of converting this random text into plaintext. Cloud computing is the legal transfer of computing services over the Internet. Cloud services let individuals and businesses to use software and hardware resources at remote locations. Widespread use of cloud computing raises the question of whether it is possible to delegate the processing of data without giving access to it. However, homomorphic encryption allows performing computations on encrypted data without decryption. In homomorphic encryption, only the encrypted version of the data is given to the untrusted computer to process. The computer will perform the computation on this encrypted data, without knowing anything on its real value. Finally, it will send back the result, and whoever has the proper deciphering key can decrypt the cryptogram correctly. The decrypted result will be equal to the intended computed value. In this paper, homomorphic encryption and their types are reviewed. Also, a simulation of somewhat homomorphic encryption is examined.
Almost perfect transmission of multipartite entanglement through disordered and noisy spin chains

We show how to efficiently send an M-partite entangled state along a spin chain of arbitrary size. Specifically, we show how an entangled M-partite W sate can be almost flawlessly transmitted from one end (Alice) to the other end (Bob) of a spin-1/2 chain described by a slightly modified XX model. We achieve an almost perfect transmission without employing external magnetic fields or modulating the coupling constants among the spins of the chain, the two standard approaches used to achieve a good transmission efficiency. Moreover, the protocol here proposed can be used to transform an M-partite W state with Alice into an M˜-partite one with Bob (M≠M˜). We also investigate the proposed protocol's response to several types of disorder and noise and show that it is quite robust to small deviations about the coupling constants of the optimal ordered and noiseless case.
A New Player for Tackling Inequalities? Framing the Social Value and Impact of the Maker Movement

The Maker Movement has raised great expectations towards its potential for tackling social inequalities by mediating technology-related skills to everybody. Are maker spaces new players for social inclusion in digital societies? How can this potential impact be framed? While scientific discourse has so far identified broad value and impact dimensions of the Maker Movement, this article adds empirical insight into the potential for tackling social inequalities. The study is based on 39 interviews with makers and managers of maker initiatives and ten self-reporting surveys filled in by maker initiative managers throughout Europe, which have been analyzed qualitatively. We found four main domains in which makers address social inclusion: First, by mediating skills and competences not only in the field of digital technologies but in the broader sense of empowering people to “make” solutions for encountered problems. Second, we found that makers actively strive to provide democratized access to digital fabrication and the knowledge on how to use them. Third and fourth, we found different ambitions articulated by makers to change society and social practices towards a society providing better opportunities for individuals. As an entry point for further research and actions, we derived a maker typology that reflects the diverse and various types of relationships to be found in the maker community. This typology could be used for exploring further collaborations between social actors and the Maker Movement. We conclude with an outlook on potential trajectories of the Maker Movement and specify which could influence the inclusion of marginalized persons.
High-resolution and high-accuracy optical extensometer based on a reflective imaging technique

Optical extensometer is a popular device for strain measurement due to its merits of non-contact measurement over a wide range of strain values compared to conventional contact measurement devices. Telecentric lens is often implemented in optical extensometers to improve the measurement accuracy by alleviating the effect of out-of-plane motion. However, the accuracy of an optical extensometer is always limited by the gauge length, which is generally less than the resolution of a digital camera. In this study, we propose a reflective imaging technique to effectively enhance the gauge length by recording two isolated long-distance regions on the specimen using a telecentric lens. The corresponding reflective imaging device was integrated in a single apparatus in which the installation of telecentric lens was very convenient. Through precise calibration, the gauge length of proposed extensometer could be increased from 1700pixels to 7477.5pixels. The performance of the proposed extensometer is evaluated using self-heating and static tests. Furthermore, the feasibility, repeatability, and reliability of the extensometer are validated by uniaxial tensile tests on a stainless-steel specimen. Experimental results showed that the axial strains obtained using proposed method were in excellent agreement with those obtained using strain gauge, and the root mean square error of strain was below 5με in most cases. Therefore, the proposed extensometer is highly accurate and exhibits immense potential to replace mechanical extensometer and strain gauge for determining the mechanical properties of materials.
Factors affecting Chinese university students’ intention to continue using virtual and remote labs

Recently, virtual and remote labs (VRLs) have been developed to support students in conducting experiments in engineering and science education. However, little is known about the students’ intentions to continue using VRLs and their satisfaction with the experience. This study proposed an extended model embedded within the expectation confirmation model and two variables concerning flow experience (time distortion and focused attention) to predict Chinese university students’ satisfaction with and intention to continue using VRLs. A structural equation modelling technique based on covariance was conducted to evaluate survey questionnaire responses received from 238 students at a university located in central China. The results demonstrated that satisfaction was the most crucial determinant of the students’ intention to continue using VRLs, followed closely by perceived usefulness. Confirmation played an indirect role in predicting students’ intentions to continue using VRLs via satisfaction and perceived usefulness. Students’ flow experience while performing virtual experiments played a positive and direct role in confirming their expectations of VRLs.
Situational Awareness-based Augmented Reality Instructional (ARI) Module for Building Evacuation

Emergency response in indoor building evacuation is essential for effective rescue and safety management. First responders often lack the situational awareness capability to quickly assess the layout of a building upon initial entry. For occupants of the building, situational awareness becomes more important in cases of active shooter events or circumstances of fire and smoke. One of the challenges is to provide user-specific personalized evacuation routes in real-time. In multilevel building environments, the complexity of the architecture creates problems for both visual and mental representation of the 3D spaces. This paper presents three cutting edge Augmented Reality Instructional (ARI) modules that overcome the visual limitations associated with the traditional, static 2D methods of communicating evacuation plans for multilevel buildings. Using existing building features, the authors demonstrate how the three modules provide contextualized 3D visualizations that promote and support spatial knowledge acquisition and cognitive mapping thereby enhancing situational awareness. These ARI visualizations are developed for first responders and building occupants to help increase emergency preparedness and mitigate the evacuation related risks in multilevel building rescues and safety management. Specifically, the paper describes the design and implementation of the ARI modules and reports the results of the pilot studies conducted to evaluate their perceived usefulness, ease-of-use, and usability. The results suggest the desirability of further heuristic examination of three-dimensional situational awareness-based ARI application effectiveness in multilevel building evacuations.