Reviewerly/exHarmony huggingface dataset:
CONTINUOUS PROFESSIONAL DEVELOPMENT AS A LABOR FUNCTION OF A TEACHER

The article presents the results of theoretical (content and essence of the concept of “labour function”) and empirical research (survey of teachers in the format of focus groups). Analysis of the content of the concept of “continuous professional development” and the dynamics of its changes during the teacher’s professional life made it possible to identify the leading competencies that are included in the content of the labour function. Discussion of the content and essence of the labour function “continuous professional development” in focus groups demonstrated some difficulties that the respondents experience in determining the content of the main competencies. The survey also revealed the respondents’ assessments of the existence of certain risks that the norms of the professional standard will be interpreted exclusively as new requirements for the teacher and will not take into account the changes in the requirements for the employer, who is obliged to provide conditions for the implementation of this labour function. The conducted research has confirmed the relevance of the development of the professional standard for teachers and revealed the need for additional explanatory work in the professional environment. The respondents also pointed out that the introduction of this document into practice can become the basis for designing an individual professional educational trajectory for a teacher and creating plans for corporate training for teaching teams. Further research is required by the introduction of a draft professional standard, including a possible revision of the activities of the advanced training system.
Evaluation and Application of Surrounding Rock Stability Based on the Improved Weighting Multidimensional Cloud Model

Aiming at the uncertainty in the existing tunnel surrounding rock stability evaluation methods and the inability to make scientific explanations in the process of determining the weights of multiple evaluation indicators, this paper combines subjective weighting based on the nonlinear characteristics of the surrounding rock stability evaluation criteria. Based on the advantages of the method AHP and the objective weighting method CRITIC, a comprehensive weighting method with multiple evaluation indicators is proposed, which is integrated with the multidimensional normal cloud model to establish a surrounding rock stability evaluation method for the improved weighted multidimensional cloud model and accurately obtain the safety level of tunnel surrounding rock construction. The multidimensional cloud model based on improved weighting not only solves the two major problems of randomness and ambiguity in surrounding rock stability evaluation but also fully considers the influence of the information contained in each evaluation factor on the results. The surrounding rock stability evaluation method in this paper is applied to the tunnel construction of the Beijing-Shanghai Expressway and Jinan Expressway connecting line construction project, and the evaluation results have a scientific guiding role for construction risk control.
Features of Digital Education Mentors’ Innovations

Introduction. The strategy for the development of international education 20.30 stimulates the study of the issues in the implementation of digital education around the world. The article discusses current applied and practical issues of digital education that educational management specialists came across. Materials and Methods. The authors research management of digital education through mentoring, mentoring pedagogy and mentoring innovations in traditional learning environments and during the time of crisis. The study presents an applied comparative analysis of the questions of targeted intensities, digital footprint, the SELFIE portal usage features, objectives and technologies for training digital mentors. Results. The research findings show an underutilisation of informal education ideas and technologies in the in the process of training digital mentors. The predominance and stable efficiency in the use of informal education takes place at leading European universities. From the standpoint of a humanistic view, exactly informal education is able to balance and regulate the need for knowledge of technologies of an innovative digital economy and its own individual resource for preserving itself, basic life values, and form digital education informal mentors. Discussion and Conclusion. Why does the mentor of a targeted digital educational intensive have a psychological advantage? Can everyone become a mentor in network communication for the rest, and what are the digital education mentor’s competencies? What contribution can everyone make to the training of the others? The discussion these issues in the context of management strategies for the development of international education, and the implementation of the European plan for the quality of digital education will be useful to for heads of educational organizations, departments of continuing professional education and academic mobility of educators.
IoT Based an Efficient Image Processing Algorithm for Capture Image in Museum using Localization Service for User Involvement

The emergence of new technologies makes everything in today’s world to be smarter. The innovation focused toward IoT leads to the enhancement of the domestic environment. The smart environment provides advanced services to the user by allowing the environment address to user and user address to the world. The Museum is a place where work of art, scientific specimens or other object kept permanent and displayed. This paper, to design a smart museum that brings comfort to visitors through wearable device, interacting with IoT based smart environment to act as a museum guide. The localization service is provided by the Beacon device which is installed in the museum. The user has the wearable device, which capture the image of user interested artwork and the image processing algorithm analysis the captured image. Once the image is recognized, then the result is forwarded to the proceeding center along with this localization information. The proceeding center retrieves this content from outside world of the cloud and sent them to the user mobile devices. This system improves the experience of user by delivering the content to the user three times faster than the system not using localization service.
On the Interplay of Smells Large Class, Complex Class and Duplicate Code

Bad smells have been defined to describe potential problems in code, possibly pointing out refactoring opportunities. Several empirical studies have highlighted that smells have a negative impact on comprehension and maintainability. Consequently, several approaches have been proposed to detect and restructure them. However, studies on the inter-relationship of occurrence of different types of smells in source code are still lacking, especially those focused on the quantification of this inter-relationship. In this work, we aim at understand and quantify the possible the inter-relation of smells Large Class - LC, Complex Class - CC and Duplicate Code - DC. In particular, we investigate patterns of LC and CC regarding the presence or absence of duplicate code. We conduct a quantitative study on five open source projects, and also a qualitative analysis to measure and understand the association of specific smells. As one of the main results, we highlight that there are ”occurrence patterns” among these smells, for example: either in Complex Class or in the co-occurrence of Large Class and Complex Class, clones tend to be more prevalent in highly complex classes than less complex classes. The found patterns could be used to improve the performance of detection tools or even help in refactoring tasks.
Recommending Best Course of Treatment Based on Similarities of Prognostic Markers

With the advancement in the technology sector spanning over every field, a huge influx of information is inevitable. Among all the opportunities that the advancements in the technology have brought, one of them is to propose efficient solutions for data retrieval. This means that from an enormous pile of data, the retrieval methods should allow the users to fetch the relevant and recent data over time. In the field of entertainment and e-commerce, recommender systems have been functioning to provide the aforementioned. Employing the same systems in the medical domain could definitely prove to be useful in variety of ways. Following this context, the goal of this paper is to propose collaborative filtering based recommender system in the healthcare sector to recommend remedies based on the symptoms experienced by the patients. Furthermore, a new dataset is developed consisting of remedies concerning various diseases to address the limited availability of the data. The proposed recommender system accepts the prognostic markers of a patient as the input and generates the best remedy course. With several experimental trials, the proposed model achieved promising results in recommending the possible remedy for given prognostic markers.
Pedestrian Detection Method Based on Deep Convolution Neural Network

Abstract Compared with the traditional pedestrian detection technology, the pedestrian detection technology based on deep learning has achieved overwhelming advantages. However, due to the large scale of deep convolution network, the demand for dedicated processor limits the popularization of pedestrian detection system. To solve these problems, this paper proposes a deep convolution network model with moderate network scale, which improves the universality of the detection model on the premise of ensuring the detection accuracy. Based on the low dimensional shallow convolution neural network, the optimal network structure is found from three aspects of network layer number, sensor field size and characteristic graph, and the final network parameters are determined by guiding experimental evaluation. The pedestrian image to be detected is input into the above network model, and the pedestrian detection result is obtained. The pedestrian detection results on several popular pedestrian databases such as Daimler, MIT and INRIA show that the network structure designed in this paper not only has moderate network size, but also has good detection performance. Cross experiments also verify the robustness and generalization of the algorithm. The work of this article is funded by the undergraduate training program for innovation and entrepreneurship (202010373050, 202010373051, 202010373046).
Approximation Properties of Ridge Functions and Extreme Learning Machines

For a compact set $D\subset\mathbb{R}^{m}$ we consider the problem of approximating a function $f$ over $D$ by sums of ridge functions ${x}\mapsto\varphi({w}^{T}{x})$ with ${w}$ in a given set $\mathcal{W}$. While such sums are dense in $C(D)$ if $\mathcal{W}=\mathbb{R}^{m}$, to understand the effectiveness of these approximations we consider finite $\mathcal{W}$ and estimate the infimum of $\left\Vert f-g\right\Vert _{\infty}$ over $g\in V_{\mathcal{W}}:={span}\left\{ \,{x}\mapsto\varphi({w}^{T}{x})\mid\varphi\in C(\mathbb{R}),\,{w}\in\mathcal{W}\,\right\} $ in terms of the Lipschitz constant of $f$. In particular, we show lower bounds for the worst case approximation of functions of Lipschitz constant one by considering unapproximable functions $f$ ($\left\Vert f-g\right\Vert _{\infty}\geq\left\Vert f\right\Vert _{\infty}$ for any $g\in V_{\mathcal{W}}$) of Lipschitz constant one. Accurate approximations appear to require $\left|\mathcal{W}\right|=\Omega(m^{2})$ for $D$ a unit hypercube in $\mathbb{R}^{m}$: if $\left|\mathcal{W}\right|\leq\frac{1}{2}m(m-1)$ and $m\geq2$, then $\sup_{f}\inf_{g\in V_{\mathcal{W}}}\left\Vert f-g\right\Vert _{\infty}\geq1/\sqrt{m-1}$, where $f$ ranges over Lipschitz functions of Lipschitz constant one. Similar results hold for sums of products of pairs of ridge functions with weight vectors in $\mathcal{W}$.
Culture and education as a binding condition for harmonious personal development

The exclusive role of culture and education in the modern strategy of sustainable development is emphasized. For so many centuries, culture and education had a distinct flavor of luxury and were available, as a rule, to a select few. Currently, there is a widespread expansion of culture and education, and indicators of upbringing and training have become the primary condition for the sustainable existence of society and the individual. The question arises: what is the hidden primacy of culture and education today? The authors call the answer to it moral postulates and enlightenment, which affect not only the human mind, but feelings and soul, giving rise to desires and actions that obey the will. It is concluded that ideals, beliefs and other qualitative characteristics of a person are the main regulators of sustainable social life. Thus, the role of culture and education is to implement social harmony and ensure the quality of life of people.
Stereoscopic zoom for visual optimization based on grid deformation

Stereoscopic image zoom optimization is a popular basic research problem in the field of image processing and computer vision in recent years. The zoom visual enhancement technology of 3D images has attracted more and more attention. To this end, this paper proposes a method of stereoscopic zoom vision optimization based on grid deformation from the model of camera zoom shooting, and strives to improve the experience of 3D stereo-scopic vision. Firstly, use the digital zoom method to simulate the camera model to properly zoom in on the target area, and then establish the mapping relationship between the reference image and the target image according to the camera zoom distance. Secondly, extract the foreground target object and use the modified just noticeable depth difference (JNDiD) model to guide the adaptive depth adjustment of the target object. Finally, combined with the seven grid-optimized energy terms designed in this paper, the image grid is optimized to improve the visual perception of the target object and ensure a good visual experience for the entire stereoscopic image. Compared with the existing digital zoom method, the proposed method has better effects on the size control of the image target object and the depth adjustment of the target object.
What do users think of the UK’s three COVID-19 contact-tracing apps? A comparative analysis

Objectives Our goal was to gain insights into the user reviews of the three COVID-19 contact-tracing mobile apps, developed for the different regions of the UK: ‘NHS COVID-19’ for England and Wales, ‘StopCOVID NI’ for Northern Ireland and ‘Protect Scotland’ for Scotland. Our two research questions are (1) what are the users’ experience and satisfaction levels with the three apps? and (2) what are the main issues (problems) that users have reported about the apps? Methods We assess the popularity of the apps and end users’ perceptions based on user reviews in app stores. We conduct three types of analysis (data mining, sentiment analysis and topic modelling) to derive insights from the combined set of 25 583 user reviews of the aforementioned three apps (submitted by users until the end of 2020). Results Results show that end users have been generally dissatisfied with the apps under study, except the Scottish app. Some of the major issues that users have reported are high battery drainage and doubts on whether apps are really working. Discussion Towards the end of 2020, the much-awaited COVID-19 vaccines started to be available, but still, analysing the users’ feedback and technical issues of these apps, in retrospective, is valuable to learn the right lessons to be ready for similar circumstances in future. Conclusion Our results show that more work is needed by the stakeholders behind the apps (eg, apps’ software engineering teams, public-health experts and decision makers) to improve the software quality and, as a result, the public adoption of these apps. For example, they should be designed to be as simple as possible to operate (need for usability).
Information Distribution in Multi-Robot Systems: Generic, Utility-Aware Optimization Middleware

This work addresses the problem of what information is worth sending in a multi-robot system under generic constraints, e.g., limited throughput or energy. Our decision method is based on Monte Carlo Tree Search. It is designed as a transparent middleware that can be integrated into existing systems to optimize communication among robots. Furthermore, we introduce techniques to reduce the decision space of this problem to further improve the performance. We evaluate our approach using a simulation study and demonstrate its feasibility in a real-world environment by realizing a proof of concept in ROS 2 on mobile robots.
Features of career self-determination of regional university applicants in the context of the COVID-19 pandemic

The impact of the COVID-19 pandemic on the career plans of high school graduates in 2020 is examined in article. At the stage of graduating from high school and admission to university, career self-determination is considered in the context of professional self-determination, an indicator of the development of which is a conscious choice of a professional future. As a result of a survey and diagnostic of 127 first-year students of Smolensk State University, it was found that students who entered the university with formed professional plans have a higher level of development of personal competencies that are significant for career self-determination. Most of them implemented their university admission plans despite the limitations associated with the COVID-19 pandemics. At the same time, students who did not have formed career ideas at the time of admission experienced more difficulties in entering; their choice of the training program was due to external factors.
Fuzzy OWL-Boost: Learning fuzzy concept inclusions via real-valued boosting

OWL ontologies are nowadays a quite popular way to describe structured knowledge in terms of classes, relations among classes and class instances. In this paper, given an OWL ontology and a target class T, we address the problem of learning fuzzy concept inclusion axioms that describe sufficient conditions for being an individual instance of T (and to which degree). To do so, we present Fuzzy OWL-Boost that relies on the Real AdaBoost boosting algorithm adapted to the (fuzzy) OWL case. We illustrate its effectiveness by means of an experimentation with several ontologies.
Blockchain Impact on the Efficiency of Public Administration in the Sphere of State and Municipal Services

State and local governments have stepped up research on innovative approaches to the provision of basic public services. The purpose of this study is to determine the blockchain impact on the efficiency of public administration in the sphere of state (municipal) services.The study illustrates the advantages and problems of blockchain on the example of its application and implementation in government bodies at various levels with an analysis of international experience. According to international experience, new technologies can improve the efficiency of service delivery, therefore, this study appeals to the importance of supportive policies for improving the results of using blockchain in the sphere of public administration of state (municipal) services.In the end, the authors determined that the introduction of blockchain in the sector of state (municipal) services, on the one hand, has several advantages (cost reduction, immutability (minimization of the risk of losing documents), elimination of intermediaries (network decentralization), distribution of information storage (lack of a single center vulnerability), openness of transactions and demonstration of innovative potential), on the other hand, several problems (the problem of trust and security, invasion of privacy and violation of constitutional rights, inequality in access to technology, changing legislation in accordance with new technologies, slow and costly implementation process).
Treemap-Based Cluster Visualization and its Application to Text Data Analysis

This paper proposes Treemap-based visualization for supporting cluster analysis of multi-dimensional data. It is important to grasp data distribution in a target dataset for such tasks as machine learning and cluster analysis. When dealing with multi-dimensional data such as statistical data and document datasets, dimensionality reduction algorithms are usually applied to project original data to lower-dimensional space. However, dimensionality reduction tends to lose the characteristics of data in the original space. In particular, the border between different data groups could not be represented correctly in lower-dimensional space. To overcome this problem, the proposed visualization method applies Fuzzy c-Means to target data and visualizes the result on the basis of the highest and the second-highest membership values with Treemap. Visualizing the information about not only the closest clusters but also the second closest ones is expected to be useful for identifying objects around the border between different clusters, as well as for understanding the relationship between different clusters. A prototype interface is implemented, of which the effectiveness is investigated with a user experiment on a news articles dataset. As another kind of text data, a case study of applying it to a word embedding space is also shown.
Impact of social network addiction in adolescents. Review

The objective of this review is to analyze the impact of addiction to social networks in adolescents, which means a challenge to adapt to these changes but is currently becoming addictive by the COVID-19 pandemic that is being experienced, therefore, the requirement arises that everyone develop skills and abilities, In order to reduce and even eliminate the disorders caused by the misuse of social networks, some recommendations are offered, such as training in access to the network, application of codes of conduct and codes of good practices and patterns of use. Learning how to use the Internet correctly is one of them, as they are revealing of the individual's daily life, progressively and others in a practical way. Social networks have become in very few years an instrument of influence and communication in all age ranges, where adolescents remain the most vulnerable group because they lack strategies to defend themselves from certain aggressions of this medium.