Reviewerly/exHarmony huggingface dataset:
Automatically human action recognition (HAR) with view variation from skeleton means of adaptive transformer network

Human action recognition using skeletons has become increasingly appealing to a growing number of researchers in recent years. It is particularly challenging to recognize actions when they are captured from different angles because there are so many variations in their representations. This paper proposes an automatic strategy for determining virtual observation viewpoints that are based on learning and data driven to solve the problem of view variation throughout an act. Our VA-CNN and VA-RNN networks, which use convolutional and recurrent neural networks with long short-term memory, offer an alternative to the conventional method of reorienting skeletons according to a human-defined earlier benchmark. Using the unique view adaption module, each network first identifies the best observation perspectives and then transforms the skeletons for end-to-end detection with the main classification network based on those viewpoints. The suggested view adaptive models can provide significantly more consistent virtual viewpoints using the skeletons of different perspectives. By removing views, the models allow networks to learn action-specific properties more efficiently. Furthermore, we developed a two-stream scheme (referred to as VA-fusion) that integrates the performance of two networks to obtain an improved prediction. Random rotation of skeletal sequences is used to avoid overfitting during training and improve the reliability of view adaption models. An extensive experiment demonstrates that our proposed view adaptive networks outperform existing solutions on five challenging benchmarks.
Methodological support of professional self-determination of a future specialist using the tools of the national qualifications system (within the framework of the project “The National Qualifications System as a Career Designer”)

The study aims to substantiate the effectiveness of the approaches chosen for methodological support of students’ professional self-determination using the tools of the national qualifications system. The paper raises the problem of students’ professional self-determination in the process of professional education. The scientific novelty of the study lies in testing the tools of the national qualifications system and identifying the effectiveness of their application in the process of methodological support of students’ professional self-determination. As a result of analysing the data obtained, it has been revealed that the presented approaches of methodological support of professional self-determination promote the formation of a conscious professional intention, planning of one’s career development and successful employment.
Conceptual model for the process of professional training of a computer science teacher for instructional design in a digital educational environment

The study aims to build a conceptual model for the process of professional training of a future computer science teacher for the development and implementation of projects in a digital educational environment. The paper presents the general ideas of how to organise project activities in a digital educational environment. The scientific novelty lies in elaborating the basic requirements for the process of forming the skills of projects development and implementation of a future computer science teacher, taking into account the general theory of project management, digital technological capabilities, providing favourable conditions for the implementation of educational effects of project activities. The main results are represented by a list of proposals on the need for a set of measures designated as part of the components of the model for the process of professional training of a future computer science teacher for project activities in the context of education digitalisation.
Web-application “The Correct Solution” for organising a mathematical olympiad for 9th grade students

The aim of the research is to present an organisational-measuring and career guidance tool for organising a mathematical olympiad in the remote format to the pedagogical community. The scientific novelty of the research lies in implementing the idea of synthesising the career guidance and control-forming nature of the developed web resource. The paper focuses on a number of topics from the school mathematics course, the knowledge of which is the basis for the successful completion of test tasks. The technical tools underlying the creation of web application attributes have been described and the software requirements have been specified. Access to parts of the application has been determined depending on the user’s status. Detailed instructions to ensure correct operation of the application aimed at schoolchildren have been developed. The created web application allows conducting subject olympiads for schoolchildren and also suggests the possibility of further additions and modifications. As a result, the researchers have created a resource the functionality of which is aimed both at increasing schoolchildren’s motivation of studying mathematics and at attracting potential applicants to the main university training programmes.
Formation of motivation to study a second foreign language among students of language faculties using gamification elements (by the example of German language teaching)

The aim of the study is to substantiate the necessity and expediency of including gamification elements in the process of teaching a second foreign language to students of language faculties to increase their motivation. The paper focuses on the role of gamification in the formation of stable positive motivation of students to learn a foreign language. The scientific novelty of the study lies in developing a system to increase students’ internal motivation, which is based on the gamification method relying on the implementation of the following principles: the game orientation of the learning process, the use of a point-based system for assessing students’ results, the implementation of the “Feedback” strategy and the interactive nature of learning in the framework of teaching the discipline “Practical Course of a Second Foreign Language (German)”. As a result of the study, it has been revealed that students showed great interest in mastering a second foreign language during the implementation of fragments of classes using gamification elements.
Solving the issues of personnel training through science popularisation and early career guidance among schoolchildren in the spheres of agriculture and biology

The aim of the study is to summarise the experience of working with schoolchildren in the spheres of agriculture and biology, ranging from work of stations of young naturalists to scientific volunteering, using the example of the projects “Academic Class”, “Agricultural Classes”, “Volunteer Naturalist”, “Green Club” and other initiatives being developed in various regions of the Russian Federation. The paper presents the author’s experience in initiating and developing modern career guidance projects for schoolchildren on agricultural and general biological topics to address global issues of personnel training for the fields of plant breeding, biotechnology and the agro-industrial complex as a whole. The scientific novelty of the paper consists in providing insight into the features and summarising characteristics of the existing practices of pre-professional work with schoolchildren, in identifying problem blocks and possible ways to overcome them in order to accelerate the solution of the acute shortage of highly professional scientific personnel in applied areas of agricultural spheres. As a result, the author has substantiated the need to expand the coverage of career guidance and popularisation work among schoolchildren to form a positive image of such professions as agronomist, plant breeder, plant pathologist and others.
Guidelines for designing a working programme for character building in the context of updated federal state educational standards

The study aims to present the main theoretical and practice-oriented aspects of designing the character building system of modern secondary schools based on the identification of problematic aspects in the development of a working programme for character building at schools, including taking into account the requirements contained in the updated federal state educational standards of primary general and basic general education. The paper reveals the main practical difficulties that the management teams of secondary schools may face when developing and implementing working programmes for character building; based on regulatory legal acts, the authors’ vision of how to resolve these problems is presented. The scientific novelty lies in the identification and justification of the main directions of improving the character building system at schools through the refinement and improvement of working programmes for character building. As a result, the possible didactic potential of consolidation of educational institutions for improving educational, methodological and practical character building work has been revealed.
Using the methodology of project activity in the preparation of students of technical specialties in the humanities

The subject of this study is the teaching of humanities to students of technical specialties. The object of the research is the methodology of project activity in the higher education system aimed at expanding the professional competencies of engineering students. The authors consider in detail such aspects as interdisciplinary and personalized approaches in the higher education system and the key parameters of their relationship with project work. Special attention is paid in the article to the tasks that the project activity solves. Among them are the formation of knowledge, skills and abilities in key competencies, work in an interdisciplinary field, the formation of teamwork skills and the ability to evaluate it. The study provides a detailed description of the implemented projects at ITMO University. The scientific novelty lies in the presentation of the results of the approbation of projects of different scientific and pedagogical orientation. The main conclusions of the study convincingly demonstrate that the applied nature of projects is key for the development of skills in the historical and cultural field. At the same time, there is an adaptation of current knowledge about the current state of historical science. As a result, the focus on interdisciplinary and personalized approaches is directly reflected in the framework of project work by integrating historical knowledge with digital methods and research and tools of technical sciences.
An intuitionistic set-theoretical model of fully dependent CC

Abstract Werner’s set-theoretical model is one of the simplest models of CIC. It combines a functional view of predicative universes with a collapsed view of the impredicative sort “ ${\tt Prop}$ ”. However, this model of ${\tt Prop}$ is so coarse that the principle of excluded middle $P \lor \neg P$ holds. Following our previous work, we interpret ${\tt Prop}$ into a topological space (a special case of Heyting algebra) to make the model more intuitionistic without sacrificing simplicity. We improve on that work by providing a full interpretation of dependent product types, using Alexandroff spaces. We also extend our approach to inductive types by adding support for ${\mathsf{list}}$ s.
Privacy implications of blockchain systems: a data management perspective

Purpose Privacy scholars appear to struggle in conceptualizing blockchain from a privacy perspective: is it a privacy-enhancing mechanism like differential privacy, a privacy-intruding tool like third-party cookies or a technology orthogonal to the issue of privacy? Blockchain does not seem to neatly fit into any of these buckets that we traditionally use to gauge the privacy implications of information technologies. In this article, the authors argue that blockchain transcends the extant conceptualization of privacy because it modifies the nature of data flow upon which the modern concept of privacy is based. Design/methodology/approach The authors introduce a conceptualization of blockchain as a new mechanism for data management. Then, following this conceptualization, the authors present a functional review of blockchain, summarizing the features it provides for the data it manages. This review sets up the discussion of how blockchain redefines data flow by separating the power of collection, access and query of data to different entities. After illustrating how this change regrounds privacy concerns in a blockchain system, the authors conclude with a discussion of the recommendations for future privacy research on blockchain. Findings The authors demonstrate that blockchain, by design, separates three core data-centric operations that are assumed to be inextricably linked in the canonical conceptualization of privacy: the collection, access and query of data. Collection means to capture and then store the data; access means to modify or augment the data and query means the ability to test or verify certain properties of the data (e.g. whether a bank account has a zero balance). Traditionally, any entities that collect data can evidently read, modify or query the same data as they wish. With blockchain, however, an entity that stores the data may not be able to modify the data, yet an entity that cannot even read the data may be able to verify certain properties of the data. Originality/value Privacy scholars appear to struggle in conceptualizing blockchain from a privacy perspective: is it a privacy-enhancing mechanism like differential privacy, a privacy-intruding tool like third-party cookies or a technology orthogonal to the issue of privacy? In this article, the authors aim to respond to this important question.
Anonymous Homomorphic IBE with Application to Anonymous Aggregation

All anonymous identity-based encryption (IBE) schemes that are group homomorphic (to the best of our knowledge) require knowledge of the identity to compute the homomorphic operation. This paper is motivated by this open problem, namely to construct an anonymous group-homomorphic IBE scheme that does not sacrifice anonymity to perform homomorphic operations. Note that even when strong assumptions, such as indistinguishability obfuscation (iO), are permitted, no schemes are known. We succeed in solving this open problem by assuming iO and the hardness of the DBDH problem over rings (specifically, ZN2 for RSA modulus N). We then use the existence of such a scheme to construct an IBE scheme with re-randomizable anonymous encryption keys, which we prove to be IND-ID-RCCA secure. Finally, we use our results to construct identity-based anonymous aggregation protocols.
Earthquake perception data highlight natural frequency details of Italian buildings

As the distance from an earthquake increases, the percentage of people who do not feel it also increases. The average transition distance between “felt” and “not felt” reports is mainly determined by the magnitude and depth of the earthquake, but it also depends on the observation floor and building height. Buildings act as resonators and can amplify the shaking at specific frequencies. We analyzed over 286,000 crowdsourced reports to study the effect of floor and building height on earthquake perception. We found that, compared to average values, there is an increase in the percentage of “felt” reports on the highest floors and a decrease in the lowest floors of buildings of all heights. We determined the range within which an observer is likely to feel an earthquake (perception boundary) and examined how it varies with magnitude. We found that as the building height increases, people on higher floors perceive medium to high magnitude earthquakes progressively better than lower magnitude ones. We compared the perception boundary with a model of seismic response spectra to estimate the vibration frequency perceived by observers on each floor/building height combination. Our results show that the value of the fundamental period increases with building height for the top floor, and that higher vibration modes become more evident for buildings with more than 6 stories. In addition, we observed that the height of the building also affects the vibration of the basement, with the frequency tending to decrease as the building height increases. Concerning macroseismic intensity estimation, we show that in tall buildings, observations made on both the upper and lower floors must be considered outside the normal range, and that earthquake perception also changes as a function of magnitude and distance, pointing out the importance of collecting an adequate number of observations to sample different locations of observers.
Unsupervised Image Enhancement Method Based on Attention Map Network Guidance and Attention Mechanism

Low-light image enhancement is a crucial preprocessing task in complex vision tasks. It directly impacts object detection, image segmentation, and image recognition outcomes. In recent years, with the continuous development of deep learning techniques, an increasing number of image enhancement methods based on deep learning have emerged. However, due to the high cost of data collection and the limited content of supervised learning datasets, more and more scholars have shifted their focus to the field of unsupervised image enhancement. Unsupervised image enhancement methods do not require paired images of the same scene during the training process, which greatly reduces the threshold for network training. Nevertheless, current unsupervised methods still suffer from issues such as unstable enhancement effects and limited generalization ability. To address these problems, we propose an improved low-light image enhancement method. The proposed method employs the LSGAN as the training architecture and utilizes an attention map network to dynamically generate attention maps that best fit the network enhancement task, which can effectively improve the generalization ability and enhancement performance of the network. Additionally, we adopt an attention mechanism to enhance the subtle details of the image features. Regarding the network training, considering that the traditional convolutional neural network discriminator may not provide effective guidance to the generator in the early stages of training, we propose an improved discriminator structure. The experimental results demonstrate that our method can achieve good enhancement performance on different datasets and has practical value. Although our method has advantages in enhancing low-light images, it also has certain limitations, such as the network size not meeting the requirements for lightweight models and the potential for further improvement under extremely low-light conditions. We will strive to address these issues as comprehensively as possible in our future research.
Geometric Prior-Guided Self-Supervised Learning for Multi-View Stereo

Recently, self-supervised multi-view stereo (MVS) methods, which are dependent primarily on optimizing networks using photometric consistency, have made clear progress. However, the difference in lighting between different views and reflective objects in the scene can make photometric consistency unreliable. To address this issue, a geometric prior-guided multi-view stereo (GP-MVS) for self-supervised learning is proposed, which exploits the geometric prior from the input data to obtain high-quality depth pseudo-labels. Specifically, two types of pseudo-labels for self-supervised MVS are proposed, based on the structure-from-motion (SfM) and traditional MVS methods. One converts the sparse points of SfM into sparse depth maps and combines the depth maps with spatial smoothness constraints to obtain a sparse prior loss. The other generates initial depth maps for semi-dense depth pseudo-labels using the traditional MVS, and applies a geometric consistency check to filter the wrong depth in the initial depth maps. We conducted extensive experiments on the DTU and Tanks and Temples datasets, which demonstrate that our method achieves state-of-the-art performance compared to existing unsupervised/self-supervised approaches, and even performs on par with traditional and supervised approaches.
Solving Rehabilitation Scheduling Problems via a Two-Phase ASP Approach

Abstract A core part of the rehabilitation scheduling process consists of planning rehabilitation physiotherapy sessions for patients, by assigning proper operators to them in a certain time slot of a given day, taking into account several legal, medical, and ethical requirements and optimizations, for example, patient’s preferences and operator’s work balancing. Being able to efficiently solve such problem is of upmost importance, in particular after the COVID-19 pandemic that significantly increased rehabilitation’s needs. In this paper, we present a two-phase solution to rehabilitation scheduling based on Answer Set Programming, which proved to be an effective tool for solving practical scheduling problems. We first present a general encoding and then add domain-specific optimizations. Results of experiments performed on both synthetic and real benchmarks, the latter provided by ICS Maugeri, show the effectiveness of our solution as well as the impact of our domain-specific optimizations.
Investigating the Knowledge Management Model in the Primary Healthcare System of Tabriz in the Field of Suicide Prevention

Background. Knowledge management seeks to convert individual and organizational information and assets into scientific knowledge and teamwork skills. Success in knowledge management requires creating a new work environment where knowledge and experience can be easily shared. The current study aimed to investigate the pattern of knowledge management in the primary healthcare system of Tabriz, Iran in the field of suicide prevention. Methods. This study was a descriptive and cross-sectional research conducted in 2022. The study’s statistical population included all healthcare providers involved in suicide prevention in the primary healthcare system of Tabriz city, Iran. To collect the data, a demographic questionnaire based on age, occupation, gender, education, work experience, and workplace was prepared and used along with the main scale of Lawson Knowledge Management Questionnaire. Measures of variability and mean were used to describe data. Independent T-test, chi-square and ANOVA were used to compare the groups. Data were analyzed using SPSS v.21. Results. From the perspective of suicide care providers, the utilization of knowledge management in the primary healthcare system of Tabriz was about 46.5%. A statistically significant differences was found between men and women in this regard. A significant relationship was also observed among all aspects of knowledge management. Conclusion. The application of knowledge and inclusion of knowledge management in suicide prevention program was below the average. There were differences between healthcare providers and education levels. To apply knowledge management in the primary healthcare system in the field of suicide prevention, it was recommended that knowledge management should be integrated with the mission, vision, strategic plans, and work processes of this system as an important principle.