Reviewerly/exHarmony huggingface dataset:
PLATFORM FOR HYBRID EDUCATION CONCEPT: INSIGHT INTO VIRTUAL TOOLS IMPACT TO ENGINEERING STUDENTS’ COMPETENCES GROWTH

Engineering education has been and will continue to be vital in everyday life of people around the real world, and students must have key competences to keep up with the speed of innovation in production sphere. The main aims of the paper are focused on setting up platform for Hybrid Education Concept, integration of virtual tools into didactic cycle, learning content and support the students learning experiences for an effective transfer of knowledge into the actual environment of the European labour market challenges. Even before COVID-19, there was growing demand among both faculty and students to create a more flexible and personalized learning experience in key competences development that enabled students to access learning content in a hybrid education concept. Based on the framework, a set of virtual tools and simulation-driven support that allow this hybrid education platform to run smoothly, were implemented. The implementation of a new Hybrid Education Concept (HEC) has proven an effective learning environment to work well as a method for elevating key career-ready engineering competences. The main benefit of the study is the new insight into students´ competences growth based engineering knowledge scaffold with significant findings and recommendations. The innovative hybrid concept is based on compatible hardware modules, virtual instrumentation software and simulation-driven innovation support with the new assessment to identify and reflect on the students´ competences outcomes of learning experiences during didactic cycle to examine the hybrid environment helpfulness of virtual tools and simulation driven learning and to explore how the concept enhances career-ready competences growth. This contribution discusses the findings and experiences gained from the hybrid education concept which was piloted with a producer of virtual instrumentation modules. The paper brings the results of the current national educational agency research project focused on effectiveness of hybrid education concept with virtual instrumentation technologies, small didactic forms and active learning methods in student-focused concept through the processing of instructors and students survey data of the electronics and autotronics study programs from the period of 2018 - 2020. The survey found that the use of hybrid education concept with the enhanced active learning techniques such as promoting interaction among students, getting students to work and collaborate together and pushing students to apply what they are learning, has a positive impact on how students use their learning experiences. Finally, the article brings a summary of the benefits and recommendations to expand the areas of utilization of project findings in wide educational applications and to form forecasts to improve the key competences of engineering faculty’s students through innovative hybrid educational environment support.
La visualización en la enseñanza de la matemática: su empleo mediante el uso del geogebra

The objective of the research is to evaluate the impact of a classroom intervention applied in the teaching-learning process of second grade curves developed in the course of Bachelor in Mathematics Education at the University of Holguin. In the intervention, visualization assumes the role of heuristic principle and the teaching-learning process of Mathematics is dynamized through the use of resources created with GeoGebra software. The intervention was carried out in five work sessions and a pre-test and apost-test were applied in order to verify the results of the intervention, both of which were validated by a Committee of Experts. As a result, a development of the necessary skills for the understanding of the concepts related to the curves of second degree by the students is observed. In addition, problems related to this content are solved by means of a dynamic approach supported by the use of Geogebra software.
Triage by Text: Home Monitoring of Patients with COVID-19 Using Automated Texts

Concerns about preventing infection — as well as other stresses on the health care system due to the COVID-19 pandemic — have prompted innovative
ANALYSIS OF LEARNERS' ATTITUDES DURING ONLINE COURSES: DEMONSTRATION OF THE NOTION OF RESILIENCE AND STRUCTURAL APPROACHES ON THE ROLE OF THE PLATFORM FOR THE NOTION OF RESILIENCE

Information about the paper titled "ANALYSIS OF LEARNERS' ATTITUDES DURING ONLINE COURSES: DEMONSTRATION OF THE NOTION OF RESILIENCE AND STRUCTURAL APPROACHES ON THE ROLE OF THE PLATFORM FOR THE NOTION OF RESILIENCE" at IATED Digital Library
Learning Invariant Representations with Missing Data.

Spurious correlations allow flexible models to predict well during training but poorly on related test populations. Recent work has shown that models that satisfy particular independencies involving correlation-inducing nuisance variables have guarantees on their test performance. Enforcing such independencies requires nuisances to be observed during training. However, nuisances, such as demographics or image background labels, are often missing. Enforcing independence on just the observed data does not imply independence on the entire population. Here we derive MMD estimators used for invariance objectives under missing nuisances. On simulations and clinical data, optimizing through these estimates achieves test performance similar to using estimators that make use of the full data.
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning

Existing 3D human pose estimation algorithms trained on distortion-free datasets suffer performance drop when applied to new scenarios with a specific camera distortion. In this paper, we propose a simple yet effective model for 3D human pose estimation in video that can quickly adapt to any distortion environment by utilizing MAML, a representative optimization-based meta-learning algorithm. We consider a sequence of 2D keypoints in a particular distortion as a single task of MAML. However, due to the absence of a large-scale dataset in a distorted environment, we propose an efficient method to generate synthetic distorted data from undistorted 2D keypoints. For the evaluation, we assume two practical testing situations depending on whether a motion capture sensor is available or not. In particular, we propose Inference Stage Optimization using bone-length symmetry and consistency. Extensive evaluation shows that our proposed method successfully adapts to various degrees of distortion in the testing phase and outperforms the existing state-of-the-art approaches. The proposed method is useful in practice because it does not require camera calibration and additional computations in a testing set-up.
ENT600: Smart adhesive board blueprint / Filzah Nur Fawati Rosli … [et al.]

'Smart Adhesive Board' uses electro-adhesive energy to stick paper on the bulletin board. It also comes with a phone application which make it easier for users to gain and deliver information. The purpose of the innovation is to enable users to stick paper on the board without using adhesive tools such as staplers. With a phone application, users will not miss out any information. This product will be test market in universities and other institutions that uses bulletin board, such as hospital. The team came up with the idea by observation. The observation is validated through interview.
Cycle Consistent Probability Divergences Across Different Spaces

Discrepancy measures between probability distributions are at the core of statistical inference and machine learning. In many applications, distributions of interest are supported on different spaces, and yet a meaningful correspondence between data points is desired. Motivated to explicitly encode consistent bidirectional maps into the discrepancy measure, this work proposes a novel unbalanced Monge optimal transport formulation for matching, up to isometries, distributions on different spaces. Our formulation arises as a principled relaxation of the Gromov-Haussdroff distance between metric spaces, and employs two cycle-consistent maps that push forward each distribution onto the other. We study structural properties of the proposed discrepancy and, in particular, show that it captures the popular cycle-consistent generative adversarial network (GAN) framework as a special case, thereby providing the theory to explain it. Motivated by computational efficiency, we then kernelize the discrepancy and restrict the mappings to parametric function classes. The resulting kernelized version is coined the generalized maximum mean discrepancy (GMMD). Convergence rates for empirical estimation of GMMD are studied and experiments to support our theory are provided.
Pengembangan Media Membaca dan Menulis Permulaan untuk Siswa Kelas I Sekolah Dasar

The results of the needs analysis on the implementation of the student’s ability test showed that there were still students who had difficulty reading and writing at the beginning. This is caused by several factors, one of which is the use of methods and media that tend to be monotonous during the implementation of distance learning and also the limited sources of teaching materials used by teachers. From this background, a solution is needed so that students can continue to learn and improve their early reading and writing skills outside of school. Android-based learning applications are one of the solutions and the researchers are trying to develop in this research. The research method used is research and development (R&D) with the ADDIE development model. The results of the study showed early reading and writing application had a feasibility percentage of 85% from material expert and 80% from media expert. After being declared eligible, this application is implemented to determine student responses as users. The results of the small-scale test showed that the application had a percentage of 82% (Very Feasible) and experienced an increase in the percentage in the large-scale test of 87% (Very Feasible).
Higher Education Curriculum Evaluation Method Based on Deep Learning Model

Higher education plays an important role in the improvement of people’s quality and the development of our country. Therefore, it is necessary to evaluate the higher education curriculum. This paper analyzes and constructs the deep network learning system and self-encoder and evaluates the Chongqing higher education curriculum based on the deep learning network selected by 50 universities in Chongqing. It is found that the numbers of test objects, indicators, and hidden layers have an impact on the evaluation results. At the same time, a classroom teaching model is designed to improve the quality of higher education and solve the problem of insufficient curriculum quality of higher education.
Big data jako nástroj pro determinaci temporálního a prostorového chování realitního trhu

This article explains efficient-market hypothesis in the context of real estate market, what impact has an insufficient knowledge about the real estate market and how this may fail for the market value determination.It points out there are not enough scientific resources focused on the economic behavior of the real estate market in the Czech Republic.Finally, it proposes big data approach for the deeper and more detailed research of the real estate market behavior.
Recognizing Scenes from Novel Viewpoints

Humans can perceive scenes in 3D from a handful of 2D views. For AI agents, the ability to recognize a scene from any viewpoint given only a few images enables them to efficiently interact with the scene and its objects. In this work, we attempt to endow machines with this ability. We propose a model which takes as input a few RGB images of a new scene and recognizes the scene from novel viewpoints by segmenting it into semantic categories. All this without access to the RGB images from those views. We pair 2D scene recognition with an implicit 3D representation and learn from multi-view 2D annotations of hundreds of scenes without any 3D supervision beyond camera poses. We experiment on challenging datasets and demonstrate our model's ability to jointly capture semantics and geometry of novel scenes with diverse layouts, object types and shapes.
PROSEDUR TERAPI RADIASI EKSTERNA PADA PASIEN KANKER KANDUNG KEMIH DENGAN METASTASIS ARTICULATIO COXAE

ABSTRACT&#x0D; Background: It has been conducted research about external radiation therapy technique of bladder cancer with articulatio coxae metastasis at Dr. Moewardi Hospital Surakarta in order to explain the procedure of external radiation therapy in bladder cancer with articulatio coxae metastasis and the purpose of asymmetric radiation field that used in external radiation therapy of bladder cancer with articulatio coxae metastasis.&#x0D; Methods: The type of research conducts is an observational research with case report approach conducted by using direct observation method, interview with radiation oncologist and radiation technologies as well as documenting the data about external radiation therapy of bladder cancer with articulatio coxae metastasis.&#x0D; Results: From the research result, it is obtained the data that external radiation therapy technique of bladder cancer patient with articulatio coxae metastasis is used asymmetric whole pelvic field where right border more wide than left border. The purpose of using asymmetric field is to reach articulatio coxae metastasis in radiation field, to decrease skin dose and time efficiency of radiation therapy.&#x0D; Conclusions: From a technical point of view, for time efficiency by considering many patients, there is only one plane therapy and the plane can be carried out in an asymmetrical field between the right and left. While the goal from a clinical perspective is to reach the articulatio coxae into the radiation field and reduce the dose received by the skin.
THE ECOLOGICAL SYSTEM OF PRINCIPALS' WORK AND THE PERSONAL EXPERIENCE OF INTERACTION WITH AND BETWEEN DIFFERENT ELEMENTS

M. Elomaa1, S. Eskelä-Haapanen1, E. Pakarinen1, L. Halttunen2, M.K. Lerkkanen1 1University of Jyväskylä, Department of Teacher Education (FINLAND) 2University of Jyväskylä, Department of Education (FINLAND)
Development of the computing node for processing satellite imagery and spatial data for earth sciences

The work is devoted to the development of a computing node for processing satellite and spatial data for earth sciences by the example of its implementation as part of the Information and Analytical Environment to support scientific research in geology of the Vernadsky State Geological Museum (SGM RAS). The prerequisites for the creation of such a computing node and the requirements for it to solve geological problems are given. An overview of cloud platforms for access to satellite and spatial data and its processing has been presented. Based on the overview a conceptual diagram of a computing node has been proposed and the list of modern technologies required for building it has been determined. The developed node provides tools for searching data from external cloud providers, processing them with various built-in and custom algorithms, as well as tools for visualizing the results. It is an independent web service, although it is part of the Computational and Analytical Geological Environment of SGM RAS and is integrated with its services. This allows a wide range of users to access data and processing algorithms provided by computing node, including integrating it into other information systems as a third-party application for processing satellite and spatial data.
Quantum-Resistant Cryptography.

Quantum-resistant cryptography is cryptography that aims to deliver cryptographic functions and protocols that remain secure even if large-scale fault-tolerant quantum computers are built. NIST will soon announce the first selected public-key cryptography algorithms in its Post-Quantum Cryptography (PQC) standardization which is the most important current effort in the field of quantum-resistant cryptography. This report provides an overview to security experts who do not yet have a deep understanding of quantum-resistant cryptography. It surveys the computational model of quantum computers; the quantum algorithms that affect cryptography the most; the risk of Cryptographically Relevant Quantum Computers (CRQCs) being built; the security of symmetric and public-key cryptography in the presence of CRQCs; the NIST PQC standardization effort; the migration to quantum-resistant public-key cryptography; the relevance of Quantum Key Distribution as a complement to conventional cryptography; and the relevance of Quantum Random Number Generators as a complement to current hardware Random Number Generators.
PECULIARITIES OF COMPETENCE DEVELOPMENT IN PRESCHOOL TEACHERS WHO WORK WITH CHILDREN WITH ATTENTION, EMOTIONAL, OR DEVELOPMENTAL DISORDERS

L. Dulksniene , G. Širvinskienė, D. Antinienė, A. Griciute, R. Kregzdyte, V. AsisiLithuanian University of Health Sciences (LITHUANIA)
Sign To Text Conversion- Helping Aid

The ancient way of sign language is most natural forms of communication. The recognition of sign is place a key role in research field. The development and improvement on this kind of work need more and more new techniques to analyze the accurate results. Many people don't know it and interpreters are hard to come by, we developed a real-time technique for finger spelling-based American Sign Language using neural networks. In our technique, the hand is first sent through a filter, and then it is passed through a classifier, which analyses the class of hand movements. For each alphabet the proposed model has a 96 percent accuracy rate. This model mainly implemented for Dumb and Deaf people for communication.
THE CULTURAL ENVIRONMENT OF A MODERN UNIVERSITY AS A FACTOR IN THE FORMATION OF PROFESSIONAL COMPETENCE OF A TEACHER-MUSICIAN

The article considers the ways of forming the professional competence of a teacher-musician in the cultural environment of a modern university. The characteristic of the phenomenon of the cultural environment of the university in the context of the formation of the spiritual and moral worldview of students-musicians is presented.
PyTorch Operations Based Approach for Computing Local Binary Patterns

Advances in machine learning frameworks like PyTorch provides users with various machine learning algorithms together with general purpose operations. PyTorch framework provides Numpy like functions and makes it practical to use computational resources for accelerating computations. Also users may define their custom layers or operations for feature extraction algorithms based on the tensor operations. In this paper, Local Binary Patterns (LBP) which is one of the important feature extraction approaches in computer vision were realized using tensor operations of PyTorch framework. The algorithm was written both using Python code with standard libraries and tensor operations of PyTorch in Python. According to experimental measurements which were realized for various batches of images, the algorithm based on tensor operations considerably reduced the computation time and provides significant accelerations over Python implementation with standard libraries.
The Pedagogical Basis for the Organization of Professional Self-Determination Among Junior Medical Students

Objective: to identify the main pedagogical techniques of the organization of an educational environment for indirect and purposeful management of the process of personal and professional development of specialists in a medical school. Material and methods. The following methods were applied: the methods of theoretical analysis including philosophical, psychological and educational, the method of methodological literature on the problem, problem analysis in existing practice; methods of observation and sociological methods. Results. In order to ensure successful professional selfdetermination of all year medical students, it is necessary: to specify important professional qualities of general practitioners and the requirements for their competitiveness; to develop a modular program of the development of the students` subjective position and the criterion basis for evaluation of the levels of their professional selfdetermination; to develop programs for personal and professional selfdetermination of students and their pedagogical assistance, to develop methodical recommendations for professors on how to create conditions for successful adaptation of students and their professional selfdetermination. Conclusion. The developing sociocultural and educational environment of a medical university favors the formation of professionally significant qualities of doctors to be, provided students constantly reconsider their roles in different social groups, their status in the educational process, positions in educational and professional and sociocultural situations, which is inherent from the necessity to communicate and interact with people.
VIRTUAL AND AUGMENTED REALITY TECHNOLOGY IN EDUCATIONAL PROCESS: ISSUES AND PERSPECTIVES

A. Nurutdinova 1, E. Dmitrieva 2, D. Shakirova 1, Z. Fazlyeva 1, E. Panfilova3 1Kazan Federal University (RUSSIAN FEDERATION) 2Kazan State Power Engineering University (RUSSIAN FEDERATION) 3ANCO CPE "International" Academic Centre for Language and Development", (RUSSIAN FEDERATION)
Penggunaan Layanan Aplikasi Google Classroom untuk Meningkatkan Hasil Belajar Fisika Mahasiswa Universitas Bina Insan

The Covid-19 pandemic that hit countries around the world, including Indonesia, resulted in learning to be done online. One type of online learning application that can be used in online learning is google classroom. Google classroom is a learning application that functions to connect teachers and students in teaching and learning activities such as distributing materials, learning videos and assessing assignments online. This study aims to determine the use of the google classroom application in improving student learning outcomes in the physics course at the Faculty of Agriculture, Bina Insan University. The research method used is a pre-experimental method with a one group pretest-posttest design research design. As samples in this study were all students of the first semester of agriculture faculty of Bina Insan University. Data collection techniques using tests. The results of the study showed that learning outcomes using e-learning learning methods using the Google Classroom application on Physics subjects can improve student learning outcomes (N-gain) in moderate criteria.
he nature and types of women's personal and professional behavioral styles

Introduction. The global transformation of the public life as well as social tension and the restructuring of gender stereotypes affect the role repertoire of women and their active inclusion in socio-economic life. This requires studying the nature and types of women's personal and professional behavioral styles.Aim. Based on the analysis of Ukrainian and foreign sources, to explore the content, types and significance of women's personal and professional behavioral styles.Results. The author has analyzed the contentof personal life scenarios and the nature, types and role of women's personal and professional behavioral styles.Conclusions. The findings can be helpful in givingpsychological support for women's professional activities, in particular in providingpsychological counseling and training programs.