Reviewerly/exHarmony huggingface dataset:
Evaluation of a teleoperated vehicle for educational purposes

espanolLa utilizacion de vehiculos roboticos en la educacion de ninos y adolescentes constituye una tendencia moderna de gran interes en Cuba, debido a la cantidad de conocimientos que provee y la variedad de disciplinas que integra. El presente trabajo tiene como objetivo evaluar el empleo de un vehiculo robotico teleoperado basado en Arduino, en la educacion de ninos y adolescentes cubanos. Contempla el estudio del estado del arte de la robotica educativa en el mundo y en Cuba, lo cual posibilito definir las principales actividades educativas que permiten los robots y los parametros a evaluar en el vehiculo de analisis. Posteriormente, se realiza una descripcion de las caracteristicas tecnica del dispositivo, las cuales influyen en los beneficios que se obtienen del empleo del vehiculo. Para finalizar, se realiza la evaluacion teniendo en cuenta los parametros definidos en el estudio del estado del arte. Se obtienen como conclusiones que seria muy provechoso el empleo del vehiculo con fines instructivos, a pesar de limitaciones minimas que no ponen directamente en riesgo la calidad de las actividades educativas. EnglishThe use of robotics vehicles in the education of children and teenagers constitutes a modern tendency of great interest in Cuba, due to the quantity of knowledge that provides and the variety of disciplines that it integrates. The present work has as objective to evaluate the use of a teleoperated and robotic vehicle based on Arduino, in the education of children and adolescents from Cuba. It includes the study of the state of the art about educational robotics in the world and in Cuba, who allows to define the main educational activities permitted by robots and the parameters to evaluate in the vehicle of analysis. Afterwards, it carries out a description of the technical specifications of the device, which influences in the benefits obtained by the use of the vehicle. Finally, it carries out the evaluation taking into account the defined parameters in the study of the state of the art. It obtains as conclusions that the use of the vehicle with educational purposes would be very fruitful, in spite of minimum limitations that do not put directly in risk the quality of educational activities.
Emoji in Online and Offline Interaction

No doubt that emoji has become a part of people’s daily communication whether inworkplace or private. It is true emoji eases the way how people communicate with each otherin virtual platforms. Over the internet, it has restraint the ability of people to identify, interpret,listen and reading due to the lack of nonverbal cues in communication. In this research, thismain purpose is to find out the interaction of male and female in online and offline by usingemoji whereby to get into a deeper exploration of the gender understanding on the meaning ofemoji, the effect of them expressing emotions in reality and the motives of them using emoji.In order to get the results of this research, a quantitative – online survey questionnaire andqualitative – focus group method have been conducted. A total of 152 responses from the onlinesurvey have gathered and have filtered out 12 participants – 6 males and females to conduct afocus group session. The theory of Social Information Processing theory (SIPT) and SocialPresence theory have applied in this research. Further discussion on the collected results are inthe following chapters.
The effect of scientific and technical mentality and innovation on the formation of modern spiritual and ethical factors in young people

This article analyzes the influence of spiritual and moral factors in the formation of scientific and technical thinking in young people. The role of scientific and technical literacy in the formation of innovative thinking of young people in modern times has been scientifically discussed.
Use of technological strategies as an educational policy of continuity in the university academic processUso de estrategias tecnológicas como política educativa de continuidad en el proceso académico universitario.

There is a need to know the basis of the use of technological strategies and to apply them in a particular case in the teaching of Mathematics; therefore, the general objective of the research is to explain the importance of the use of technological strategies as an educational policy of continuity in the university academic process. The study is based on the historical hermeneutic paradigm of mixed approach. The method used was logical inductive, and the research is explanatory. A careful tracking of documentary information was carried out in which the use of technological strategies as an educational policy of continuity is addressed. On the other hand, it had a pre-experimental design in the achievement of Mathematics skills using technological strategies, such as video tutorials. The fundamentals of the use of technological strategies are investigated, analyzing the use and benefits presented in the virtual modality in university education in the area of Mathematics. The results indicate that the use of technological strategies should be considered as an educational policy of continuity in the university educational process, since they contribute to the development and continuous improvement of education in the area of Mathematics in the country. The results also indicate that the evaluation of the contents of Mathematics and the opinion of the teachers were favorable to the use of the technological strategy in their teaching practice in the reality of the Pandemic COVID-19. The conclusions obtained report high predisposition of the participants to the use of the digital technological strategy, a high percentage of very favorable opinion of the teachers who conducted the subject of Mathematics through the use of appropriate technological strategies and this corroborates the foundations exposed by various authors consulted.
COGNITIVE APPROACHES FOR THE FORMATION OF INFORMATION AND COMMUNICATION COMPETENCE OF TEACHERS

This article examines the problem of the formation of information and communication competence of teachers in professional activities. Cognitive components of information and communication competence of teachers are highlighted. The stages of cognitive approaches aimed at the formation of information and communication competence of teachers are described.
Accurate whole-rock geochemistry analysis by combined ICP-OES and LA-ICP-MS instruments

ICP-OES and LA-ICP-MS instruments routinely used to assess the geochemical properties of the various natural and synthetic materials.In this contribution, the analytical routines and method development procedures of the ICP-OES and LA-ICP-MS facilities installed at the İstanbul University-Cerrahpaşa Geological Engineering Department, Geochronology and Geochemistry Laboratory have been evaluated using well-known international rock standards.Sample preparation techniques, method development, experimental setup and measurement conditions for the both ICP-OES and LA-ICP-MS instruments were discussed and specific analyze results of NIST SRM 614, BCR-2, AGV-2, BCR-2G and AGV-2G were evaluated.Flux-free USGS glass standards were produced by in-house techniques and flux-bearing glasses were produced by fusion of sample with the mixture of ultra-pure lithium-tetraborate, lithium metaborate and lithiumbromide were evaluated and compared with the well-known reference values in the literature.Relative standard deviation (RSD) values for the major oxide measurements for standards given range of 0.0 wt.% to 1.5 wt.%.RSD values for the trace and rare-earth-elements values were mainly lower than 10 wt.%.The results confirm that the both flux-bearing and flux-free glasses reasonably match with the worldwide inter-laboratory values for international standards samples.The combination of these two instruments can be used to conduct geochemistry of various solid earth materials.
Forecasting of Cloud Computing Services Workload using Machine Learning

This paper analyses and compares prediction accuracy of different machine learning algorithms intended to forecast the workloads of server logs.  The proposed prediction model conducts comparative study has been applied using Linear Regression (LR), K- Nearest Neighbors (KNN), Support Vector Machine (SVM), ARMA, ARIMA, and Support Vector Regression (SVR) for web applications to select the suitable algorithm as per workload features. The experiments have used real trace files to evaluate the best suitable method to predict the workloads. The experimental results describe that the ARIMA model shows significant improvement in QoS metrics and improve the cloud datacenter availability in a cloud environment and forecasting. Finally results presented and conclusions are drawn.
An Automated Mulitple-choice Question Generation Using Natural Language Processing Techniques

Automatic multiple-choice question generation (MCQG) is a useful yet challenging task in Natural Language Processing (NLP). It is the task of automatic generation of correct and relevant questions from textual data. Despite its usefulness, manually creating sizeable, meaningful and relevant questions is a time-consuming and challenging task for teachers. In this paper, we present an NLP-based system for automatic MCQG for Computer-Based Testing Examination (CBTE).We used NLP technique to extract keywords that are important words in a given lesson material. To validate that the system is not perverse, five lesson materials were used to check the effectiveness and efficiency of the system. The manually extracted keywords by the teacher were compared to the auto-generated keywords and the result shows that the system was capable of extracting keywords from lesson materials in setting examinable questions. This outcome is presented in a user-friendly interface for easy accessibility.
Face Mask Detection in Classroom using Deep Convolutional Neural Network

Wearing a mask has become mandatory to protect ourselves from infectious diseases caused by viruses. Today, we are facing a pandemic crisis due to COVID-19 virus. It worsens the lives of living things particularly human beings. The whole world felt stagnant from its normalcy. The educational institutions are particularly affected by this pandemic situation for not conducting the direct classes. To avoid this scenario, they are willing to conduct classes with some guidelines such as social distancing, wearing masks, and sanitizing the hands. We have considered wearing a mask is more important than the remaining two aspects. We are providing a solution with the help of the ResNet50 deep learning network to check whether the students have worn a mask in a classroom in order to prevent them from illness. Deep learning is an advancement of machine learning technique which gives more accurate results than the machine learning algorithms. The performance of our implemented deep learning based face mask detection system is discussed. The live video of the classroom is taken and analysed for recognizing the student’s face with and without mask and generating the name of the students without wearing a mask.
Tampering Detection using Resampling Features and Convolution Neural Networks

The increased usage of image editing tools has resulted in the ease of manipulating multimedia data such as images. These manipulations affect the truthfulness and legitimacy of images, resulting in misinterpretation and may affect social stability. The image forensic technique has been utilized for detecting whether an image is tampered with using certain attacks such as splicing, copy-move, etc.This paper presents an efficient tampering detection method using resampling features (RSF) and Convolution neural network (CNN). In RSF-CNN, during preprocessing the image is divided into homogenous patches. Then, within each patch resampling features are extracted by exploiting affine transformation and Laplacian operator. Then, features extracted are aggregated for constructing descriptors using Convolution neural network. Extensive analysis is carried out for evaluating tampering detection and tampered region segmentationaccuracies of proposed RSF-CNN based tampering detection methodologies considering various distortions and post-processing attacks such as joint photographic expert group (JPEG) compression, scaling, rotations, noise additions, and multiple manipulations. From the result achieved it can be seen the RSF-CNN based tampering detection model achieves much better accuracies than existing tampering detection methodologies.
Unsupervised Moving Object Segmentation using Region - Based Approach

Unsupervised moving object segmentation plays a crucial role in a very wide selection of applications from object identification to compression. However, quick motion, motion blur and occlusions cause important challenges. To deal with these challenges for unsupervised video segmentation, we tend to develop a unique Unsupervised Moving Object Segmentation using Region-Based Approach. During this the motion-based region classification provides a decent data format for object segmentation. The aim of segmentation i s to modify and alter the illustration of a picture into one thing that's additional significant, easier to research and simple to grasp. Image segmentation is employed to present the values of objects and limits of a particular image like lines, curves. Image segmentation is that the most vital field of image analysis and its process that is generally employed in medical field to research the illness. It's conjointly employed in several scientific fields together with, engineering and technology, face recognition and object. In this paper region-based segmentation technique is bestowed for decisive and locating the specified region properly. Simply, it combines the individual pixels in an input image to sets of pixels referred to as regions that may correspond to an object or a significant part of one. Tanuja and Subhangi came up with a system to segment tumors from the given imaging (Magnetic Resonance Imaging) supported the similarity among the pixels. The fundamental plan was to outline a seed pixel and move to neighboring pixels, grouping the pixels with the similar attributes. The experiments and analysis depict that this technique was quick and correct.
Socialization of personality in the context of competence approach

Introduction. In the context of the transition of modern Russia to civil society and civilized market, special emphasis in the process of modernization of education is placed on training graduates to function as full members of society and citizens of their country. Research methodology. Modern understanding of competence includes both the ability and skill to perform certain functions, and the presence of a number of mental qualities that allow acting independently and responsibly. Research results. The phenomenon of competence has a certain hierarchy, revealed on the grounds of scale, content and methods of formation. Ensuring the growth of competence is inextricably linked with the personal values system. Therefore, the identification of value orientations of the individual, helping him to understand them better, the resolution of value conflicts and evaluation of alternatives are the basis of any program in this direction. Discussion. Social competence of the person assumes that he, first of all: carries himself to members of society; owns the moral and ethical standards peculiar to society; realizes need of orientation of all activity for the benefit of society; assumes social responsibility for consequences of the acts; cooperates with other members of society; is capable to flexible change of a social role; is ready to changes and is capable to influence process of changes in the interpersonal relations; seeks and is able to cause in society interest to his professional and public activity; aspires to compliance of the professional and public status to individual and personal qualities. Conclusion. Personality is considered as a complex dynamic structural formation. The phenomenon of self-development can be identified as the main internal mechanism of personality development. The importance of personal self-development is determined by its regulatory function.
AutoSampling: Search for Effective Data Sampling Schedules.

Data sampling acts as a pivotal role in training deep learning models. However, an effective sampling schedule is difficult to learn due to the inherently high dimension of parameters in learning the sampling schedule. In this paper, we propose an AutoSampling method to automatically learn sampling schedules for model training, which consists of the multi-exploitation step aiming for optimal local sampling schedules and the exploration step for the ideal sampling distribution. More specifically, we achieve sampling schedule search with shortened exploitation cycle to provide enough supervision. In addition, we periodically estimate the sampling distribution from the learned sampling schedules and perturb it to search in the distribution space. The combination of two searches allows us to learn a robust sampling schedule. We apply our AutoSampling method to a variety of image classification tasks illustrating the effectiveness of the proposed method.
Pedagogical Basis of Professional Training of Future Teachers

This article discusses the pedagogical basis of professional training of future teachers and the content of their competency-based approach to their professional activities and provides methodological recommendations
The Hannover Coupler V2: Audiological outcomes of a round window coupler for vibrant soundbridge

Introduction The coupling of the Floating Mass Transducers (FMT) of the Vibrant Soundbridge (VSB) to the round window results in varying audiological outcomes due to the /undefinable forces between FMT and membrane. Hannover Coupler V2 was designed to stabilize and control the coupling forces. First audiological outcomes are available.
Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference

We propose a Multiscale Invertible Generative Network (MsIGN) and associated training algorithm that leverages multiscale structure to solve high-dimensional Bayesian inference. To address the curse of dimensionality, MsIGN exploits the low-dimensional nature of the posterior, and generates samples from coarse to fine scale (low to high dimension) by iteratively upsampling and refining samples. MsIGN is trained in a multi-stage manner to minimize the Jeffreys divergence, which avoids mode dropping in high-dimensional cases. On two high-dimensional Bayesian inverse problems, we show superior performance of MsIGN over previous approaches in posterior approximation and multiple mode capture. On the natural image synthesis task, MsIGN achieves superior performance in bits-per-dimension over baseline models and yields great interpret-ability of its neurons in intermediate layers.
Spatial distribution of clustered seismicity in Khibiny Montains

&amp;lt;p&amp;gt;Using long-term mining-induced earthquake statistics of the Khibiny Mountains (Kola Peninsula, Russia) we studied the spatial peculiarities of clustered seismicity. To declutter the earthquake catalog, we used the nearest neighbor method by Zaliapin and Ben-Zion, 2016, DOI: 10.1093/gji/ggw300. It was shown that the distribution of distances from triggering event to triggered earthquakes obeys a power law with a parameter independent of the trigger magnitude. This result is consistent with distribution of mainshock-aftershock distances obtained for tectonic seismicity by many researchers (e.g., Huc M., Main, DOI: 10.1029/2001JB001645; Felzer and Brodsky, DOI: 10.1785/0120030069; Richards-Dinger et al., DOI: 10.1038/nature09402). Combining the spatial power distribution and the law of earthquake productivity by Shebalin et al. 2020 (DOI: 10.1093/gji/ggaa252), confirmed for the seismicity of the Khibiny Mountains (Baranov et al., 2020, DOI: 10.1134/S1069351320030015) we derived a distribution of maximal distances from trigger to triggered earthquake.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Using this distribution, we suggest a probabilistic model of zone where triggered earthquakes are expected. The zone is a cylinder centered on the trigger hypocenter, its size (radius and height) depends on the probability of containing triggered earthquakes. The model validation was performed using Molchan&amp;amp;#8217;s error diagram. Applying the method of three strategies (Baranov and Shebalin, 2017, DOI: 10.1134/S1069351317020021) to the error diagram, we identified three limiting points on the error trajectory, corresponding to &amp;quot;soft,&amp;quot; &amp;quot;neutral,&amp;quot; and &amp;quot;hard&amp;quot; strategies. These strategies reflect the prediction importance.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The research was supported by Russian Foundation of Basic Research, Project No 19-05-00812.&amp;lt;/p&amp;gt;
El potencial transformador de la transdisciplinariedad y de la creatividad para la educación contemporánea

espanolLas discusiones contemporaneas a respeto del escenario educacional demandan la articulacion de las dimensiones de naturaleza ontologica, epistemologica y metodologica como condicion esencial para transitar de la fragmentacion para la conexion de los conocimientos y de estos con lo que esta entre ellos, mas alla y por medio de ellos. Con el objetivo de presentar una reflexion acerca de la perspectiva transdisciplinaria y las posibilidades que ofrece para la conexion de los conocimientos en el escenario educacional contemporaneo, presentando la propuesta de las Escuelas Creativas como un ejemplo practico, este estudio es constituido de una revision bibliografica, con el apoyo del enfoque cualitativo, priorizando el analisis de aportes de pensadores contemporaneos como Morin (2009, 2015), Nicolescu (2005, 2014) y Torre (2005, 2008, 2016). Los referenciales teoricos han senalado que, a partir de la transdisciplinariedad y de la creatividad, las perspectivas educacionales se abren a la conexion entre los diferentes tipos de conocimiento y su articulacion con la realidad, estimulando la superacion de la dicotomia entre el sujeto y el objeto y, consecuentemente, la consideracion del ser que conecta y trasciende las dimensiones de la realidad y los niveles de percepcion. Emerge, por lo tanto, la necesidad de revolucionar el modo de pensar de los educadores, como tambien un nuevo hacer pedagogico a partir de la conexion de saberes, vidas y seres, como partes interconectadas de una dimension planetaria. EnglishContemporary discussions regarding the educational scenario demand the articulation of the dimensions of an ontological, epistemological and methodological nature as an essential condition to move from fragmentation to the connection of knowledge and these with what is between them, beyond and through from them. With the aim of presenting a reflection on the transdisciplinary perspective and the possibilities it offers for the connection of knowledge in the contemporary educational scenario, presenting the proposal of the Creative Schools as a practical example, this study is constituted by a literature review, with the support of the qualitative approach, prioritizing the analysis of contributions of contemporary thinkers like Morin (2009, 2015), Nicolescu (2005, 2014) and Torre (2005, 2008, 2016). Theoretical references have indicated that, from transdisciplinarity and creativity, educational perspectives open to the connection between different types of knowledge and its articulation with reality, stimulating the overcoming of the dichotomy between the subject and the object and, consequently, the consideration of the being that connects and transcends the dimensions of reality and the levels of perception. The need therefore arises to revolutionize the way of thinking of educators, as well as a new pedagogical work based on the connection of knowledge, lives and beings, as interconnected parts of a planetary dimension.