Reviewerly/exHarmony huggingface dataset:
Digital Skills, An Attribute Of The Information Society

The most recent major event that has marked the whole of humanity, the COVID-19 pandemic, has meant a major change in lifestyle, from a digital perspective.The whole activity was based on the online environment, each person, depending on the basic activity, being forced to develop their digital skills in a short time.Thus, pupils, students, teachers, and employees in various sectors of activity, in the private sector or the budget, really gave the test of digital skills, in a context not of assessment of learning, but of assessment for learning.Each of us has been able to see our own level of digital skills and has taken action accordingly, all with the common denominator of improving digital skills and making the most of the digital devices available.What do digital skills entail?One of the eight key competencies, digital competence, aims, in general, at the efficient, creative and responsible use of information and communication technologies.The present study aims to draw a package of digital skills starting from the identification of the challenges of contemporary reality.
Shape optimization for transcranial ultrasound computed tomography

Using waveform-based inversion methods within transcranial ultrasound computed tomography is an attractive emerging reconstruction technique for imaging the human brain. However, such imaging approaches generally rely on possessing an accurate model of the skull in order to account for the complex interactions which occur when the ultrasound waves propagate between soft tissue and bone. In order to recover the shape of the skull within the context of full-waveform inversion, adjoint-based shape optimization is performed within this study. The gradients with respect to the acoustic properties of the tissues which are used in conventional full-waveform inversion act as a proxy for estimating the sensitivities to the shape of the skull. These shape derivatives can be utilized to update the interface between the interior brain tissue and the skull. This technique employs the spectral-element method for solving the wave equation and, thus, allows for the use of a convenient framework for representing the skull interfaces throughout the inversion. Adaptations of the Shepp-Logan phantom are used as a proof of concept to demonstrate this inversion strategy where both the shape of the skull as well as the interior brain tissue are imaged sequentially.
Current Trends In Preschool Leisure Management

Speaking of recreational and leisure activities, we first think about the fun of a sport.Baron Pierre de Coubertin, noted the danger of spreading sport and its Olympic principles to a servant of the elite, money and business, which is why he introduces the term Sport for all, explaining that "sport is not a way to spend luxury time, "An activity for the disadvantaged and not even a form of muscular compensation of brain activity."Managing time in such a way that we get free time proves a special ability on the part of the one who manages to do it in the conditions in which unforeseen events occur in our life preventing the real attempts to be good time managers.Like adults, children are often surprised by how fast time passes and how few things they have accomplished.Thus, the lesson on using leisure time in the most effective way can start as early as possible with notions of time management for children.Preschool and early school age are a key period for shaping the behavior of the future individual, outlining the basic mental processes.In the formation and development of the preschooler's personality, today the thesis is unanimously accepted that at birth the child is only "a candidate for humanity" and that this quality will be acquired through learning and education, through socialization, human potential being stimulated, developed and exploited under the influence of the environment.and education.
Contextual Curriculum: Perspective Of Correlating Educational And Professional Activities

The conceptualization of a contextual academic curriculum is generated by external factors, by the needs of the labor market with reference to the level of professional competences of higher education institutions' graduates.It is certified by the employers that the graduates' competences do not allow them to efficiently exercise their professional functions.At the same time, graduates affirm the existence of discrepancies between the content of academic activity and the content of professional activity.The key idea of the contextual academic curriculum is related to an interconnected approach to academic competences and professional competences as a teleological approach, to valorize on active, interactive and innovative didactic strategies.The key concept of the contextual curriculum relates to the holistic and integrative approach to the factors that influence and determine the content substance of this document.Importantly, guidelines were established for the interconnection between external contexts and internal contexts; academic skills and professional skills; curricular contents and types of professional activities.In a comparative plane is widely analysed the learning activity within the university and the professional activity in respective field on the dimensions: needs, motives, actions, subjects, outcomes.Examples of modelling contextual university curriculum are presented.
E-Learning In Higher Education – Pros And Cons

The pandemic has led to the generalization of e-learning in higher education and its transformation into a long-term process.For most students (and teaching staff), this transformation has been unexpected, difficult, challenging, and stressful.The study takes as its starting point this context, our observations during classes, and some informally collected student testimonies.This paper presents the results of a questionnaire-based study conducted at the "Vasile Alecsandri" University of Bacău, Romania.The aim of the study is to identify students' perceptions of the impact of e-learning on some important dimensions of the professional and personal training process.The objectives of the study are: O1. to identify students' perceptions regarding the correlation between some aspects of the online didactic activity (access to a device; type of device; time spent learning; degree of stress generated; interactive methods used) and its efficiency; O2.To identify students' perceptions regarding the impact of e-learning on their training and motivation; O3.On this basis, to systematize the main arguments pros and cons the use of e-learning in higher education.The data were collected by means of a questionnaire consisting of 11 closed items answered by 201 students.The obtained results made it possible to determine both the students' perception of the impact of e-learning on their professional and personal education and to formulate proposals for the use of e-learning at a higher level in higher education.
Efficacy of Virtual Reality Exposure Therapy in the Treatment of Specific Phobias: A Systematic Review

Specific phobia is defined as a notable and continuous fear of a certain object or a situation that particularly impairs daily life and functioning. It is also one of the most common psychological disorders. Exposure-based interventions are commonly used in the treatment of specific phobias. However, some limitations of the standard methods require the need for alternative approaches. In light of this, the use of virtual reality technology in psychotherapy has become increasingly widespread in recent years and is now integrated with exposure therapy. Virtual reality provides real-time interaction using the computer-generated three-dimensional environment via variety oftechnological tools. Applications of virtual reality in exposure therapy have proven to be an important intervention method, especially in the psychopathologies such as specific phobias. In this study, virtual reality exposure therapy for the treatment of specific phobias is systematically reviewed. Inclusion criteria were taken into account in the scanning performed in APA (PsycINFO), EBSCO, PubMed, Scopus, Web of Science, Science Direct, Ulakbim ve TRDizin databses following the PRISMA method. Following that, ten randomized controlled trials, which included adult participants meeting the diagnostic criteria for specific phobia, examined the efficacy of virtual reality and exposure therapy compared to the control group, and the ones with full text could be accessed, were included in this systematic review. The included studies were evaluated in terms of sample attributes, primary measurement tools, research design, characteristics of the intervention and its efficacy. In general, the findings indicate the efficacy of virtual reality exposure therapy in reducing specific phobia symptoms. Follow-up studies support the long-term maintenance of the results.
Using LSTM and GRU With a New Dataset for Named Entity Recognition in the Arabic Language

Named entity recognition (NER) is a natural language processing task (NLP), which aims to identify named entities and classify them like person, location, organization, etc. In the Arabic language, we can find a considerable size of unstructured data, and it needs to different preprocessing tool than languages like (English, Russian, German...). From this point, we can note the importance of building a new structured dataset to solve the lack of structured data. In this work, we use the BIOES format to tag the word, which allows us to handle the nested name entity that consists of more than one sentence and define the start and the end of the name. The dataset consists of more than thirty-six thousand records. In addition, this work proposes long short term memory (LSTM) units and Gated Recurrent Units (GRU) for building the named entity recognition model in the Arabic language. The models give an approximately good result (80%) because LSTM and GRU models can find the relationships between the words of the sentence. Also, use a new library from Google, which is Trax and platform Colab
Improving Adaptive Real-Time Video Communication Via Cross-layer Optimization

Effective Adaptive BitRate (ABR) algorithm or policy is of paramount importance for Real-Time Video Communication (RTVC) amid this pandemic to pursue uncompromised quality of experience (QoE). Existing ABR methods mainly separate the network bandwidth estimation and video encoder control, and fine-tune video bitrate towards estimated bandwidth, assuming the maximization of bandwidth utilization yields the optimal QoE. However, the QoE of a RTVC system is jointly determined by the quality of compressed video, fluency of video playback, and interaction delay. Solely maximizing the bandwidth utilization without comprehensively considering compound impacts incurred by both network and video application layers, does not assure the satisfactory QoE. And the decoupling of network and video layer further exacerbates the user experience due to network-codec incoordination. This work therefore proposes the Palette, a reinforcement learning based ABR scheme that unifies the processing of network and video application layers to directly maximize the QoE formulated as the weighted function of video quality, stalling rate and delay. To this aim, a cross-layer optimization is proposed to derive fine-grained compression factor of upcoming frame(s) using cross-layer observations like network conditions, video encoding parameters, and video content complexity. As a result, Palette manages to resolve the network-codec incoordination and to best catch up with the network fluctuation. Compared with state-of-the-art schemes in real-world tests, Palette not only reduces 3.1%-46.3% of the stalling rate, 20.2%-50.8% of the delay, but also improves 0.2%-7.2% of the video quality with comparable bandwidth consumption, under a variety of application scenarios.
Implementation of the Van Meter and Van Horn Zoning System Policies Model

This research is motivated by the phenomenon of the policy phenomenon of the New Student Admission Zoning System which causes pros and cons in society. Some people argue that this system is unfair for high achieving students but cannot enter the favorite school that was previously intended. On the other hand, the community argues that this system is beneficial for students who live in favorite schools.The approach used in this research is qualitative with descriptive analysis method. The purpose of this study is to see and describe the implementation of the Van Meter and Van Horn policy models. The results of this study are: 1) Implementation and communication activities between policy implementing organizations have been implemented, but the results have not been optimal, 2) The characters of SMAN 2 Bandung as implementers have understood the policy context well, are consistent with the goals and objectives and Policy objectives, implement prospective students firmly and strictly on policy rules, and supervise Zoning System policies in accordance with PPDB technical guidelines and SOPs but the results are optimal, 3) The disposition as policy implementers has not seen what to do, has the ability to do these policies and have the commitment to implement PPDB policies for optimal system zoning systems, 4) Social, economic and political conditions have influenced policy policies, 5) The zoning of system policy implementation has a positive impact on service policies and the quality of education services. The conclusion of this research is that SMAN 2 Bandung has implemented a zoning system policy but it has not been optimal.
Distance Learning in the Context of E-Learning: Trends of Postmodern Society

The article highlights the trends of the postmodern society developing in the context of a globally integrated world. The postmodern cultural trend is an exponent of the cultural and artistic aspect of the post-industrial world, including the educational aspect. Therefore, such a topic is relevant for research.&#x0D; The article analyzes the basic theoretical and methodological foundations of distance education as an effective technology of innovative e-learning. Based on the statements of scientists, it is determined that distance education in addition to effective learning technology is also a manifestation of postmodern cultural and artistic worldview.&#x0D; The article defines the essence of distance education in the context of technological process as a feature that forms the global trends of society development. The article also presents the postmodern paradigm as a defining feature of the current worldview of society, which has emerged as a result of innovation and information space.&#x0D; On the basis of the questionnaire it was determined that distance education as a technology is the most effective in the current postmodern view of the world. The study applied the integrative method of synthesis and analysis, as well as research, descriptive and scientific methods to determine the theoretical foundations of distance education. The questionnaire method was used to determine the effectiveness of distance education in e-learning as a manifestation of postmodernism. The results of the study became the basis for the definition of distance education as an effective learning technology.
Machine learning-enabled globally guaranteed evolutionary computation

Abstract Evolutionary computation, for example, particle swarm optimization, has impressive achievements in solving complex problems in science and industry; however, an important open problem in evolutionary computation is that there is no theoretical guarantee of reaching the global optimum and general reliability; this is due to the lack of a unified representation of diverse problem structures and a generic mechanism by which to avoid local optima. This unresolved challenge impairs trust in the applicability of evolutionary computation to a variety of problems. Here we report an evolutionary computation framework aided by machine learning, named EVOLER, which enables the theoretically guaranteed global optimization of a range of complex non-convex problems. This is achieved by: (1) learning a low-rank representation of a problem with limited samples, which helps to identify an attention subspace; and (2) exploring this small attention subspace via the evolutionary computation method, which helps to reliably avoid local optima. As validated on 20 challenging benchmarks, this method finds the global optimum with a probability approaching 1. We use EVOLER to tackle two important problems: power grid dispatch and the inverse design of nanophotonics devices. The method consistently reached optimal results that were challenging to achieve with previous state-of-the-art methods. EVOLER takes a leap forwards in globally guaranteed evolutionary computation, overcoming the uncertainty of data-driven black-box methods, and offering broad prospects for tackling complex real-world problems.
Development of Music Education in Postmodern Society

The article is devoted to the emergence of new contradictory trends in the school music education of postmodern society, how young postmodern youth perceives and uses music and attempts to methodically solve these problems. We explain the relevance of the topic by the fact that postmodern historical trends are still very strong in developing countries, and the industrialization of music art is increasingly distancing young people from academic and folk music achievements. Objective of the article is to identify the main trends, contradictions and problems of music education in postmodernism, and to simulate possible methodical ways of its decision. The general methodological approach is theoretical. We have chosen sociological, theoretical and analytical plus theoretical and methodological methods as the main ones for a data collection, information processing and modeling (modification) of educational conditions in music lessons in high school. As a result, the authors of the article presented main features of music education in postmodern society, the attitude of young people to music, and most importantly presented a thesis formulated 15 guidelines for optimizing school music education. The main conclusion is to avoid categoricalness in the hierarchy of educational process management; evaluation of musical content, to emphasize perceptual, reflexive and performative mechanisms of the development of musical heritage. The international significance of the article lies in the supplementation of numerous theoretical studies with specific methodological recommendations, as well as the use of the Ukrainian cultural context of the late postmodern era, which for some reason scholars pay little attention to.
Software Engineering for Responsible AI

The unique characteristics of artificial intelligence (AI) systems pose new challenges to traditional software engineering approaches. Thus, new software engineering approaches are required to develop AI systems in a responsible manner.
Fall Detection Among Elderly Using Deep Learning

As humans continue to grow older and weaker and are not able to keep themselves stable at all times, falls among said elderly keep growing in number with their age. If these falls remain constant it can lead to their body wearing down even faster than before when it was due to just old age along with other scenarios that can also occur such as a single fall alone causing immense damage to the elderly or even the youth. It is due to this reason that fall detection and prediction are starting to turn into necessities so that action can be taken immediately to help a person on detection or prediction with the help of vision surveillance or sensors.
21 Gbps Source-Independent Quantum Random Number Generator Based on Vacuum Fluctuations

We report an ultra-fast quantum random number generator based on detecting vacuum fluctuations without assuming input states. To elimate the effect of classical noise, Toeplitz hash extractor is employed to extract randomness. The final random number generation rate up to 21.28 Gbps is experimentally achieved.
Using Double Deep Q-Learning to learn Attitude Control of Fixed-Wing Aircraft

These last few years have been big for the field of Reinforcement Learning. While is was long thought to be impossible for Reinforcement Learning to master complex environments, recent research has seen Reinforcement Learning agent master highly complex tasks like Atari Games, Go, Dota 2, Autonomous transportation among many others. This has sparked a new wave of interest into Reinforcement Learning, with most of that focus directed towards Deep Reinforcement Learning algorithms. This paper will explore the realm of aviation and apply Deep Reinforcement learning to it. To be more specific, we will train an agent with Double Deep Q-Learning to learn how to control the planes attitude control. The QPlane toolkit will be used for this, and we will utilize both simulators provided. The methodology and results will be presented in this paper.
The Solution of Scalar Bimatrix Games in Preferred Pure Strategies

In the present work the task of finding Nash equi-librium situation or finding the most preffered pure strategies in finite scalar mn  bimatrix ) ,
Illumination Distillation Framework for Nighttime Person Re-Identification and a New Benchmark

Nighttime person Re-ID (person re-identification in the nighttime) is a very important and challenging task for visual surveillance but it has not been thoroughly investigated. Under the low illumination condition, the performance of person Re-ID methods usually sharply deteriorates. To address the low illumination challenge in nighttime person Re-ID, this paper proposes an Illumination Distillation Framework (IDF), which utilizes illumination enhancement and illumination distillation schemes to promote the learning of Re-ID models. Specifically, IDF consists of a master branch, an illumination enhancement branch, and an illumination distillation module. The master branch is used to extract the features from a nighttime image. The illumination enhancement branch first estimates an enhanced image from the nighttime image using a nonlinear curve mapping method and then extracts the enhanced features. However, nighttime and enhanced features usually contain data noise due to unstable lighting conditions and enhancement failures. To fully exploit the complementary benefits of nighttime and enhanced features while suppressing data noise, we propose an illumination distillation module. In particular, the illumination distillation module fuses the features from two branches through a bottleneck fusion model and then uses the fused features to guide the learning of both branches in a distillation manner. In addition, we build a real-world nighttime person Re-ID dataset, named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Night600</i> , which contains 600 identities captured from different viewpoints and nighttime illumination conditions under complex outdoor environments. Experimental results demonstrate that our IDF can achieve state-of-the-art performance on two nighttime person Re-ID datasets ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Night600</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Knight</i> ). We will release our code and dataset at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/Alexadlu/IDF</uri> .