Reviewerly/exHarmony huggingface dataset:
Analysis of the Demand for Russian Literature in Shanghai Library

This research focuses on Shanghai Library users’ demand for Russian literature of different literary periods. Method of sampling and questionnaire were applied for the study. Analyzing the online circulation records of Chinese translations of Russian literature in the main collection of Shanghai Library from 2016 to 2019 and providing an overview of reader demographics are two major tasks. As a typical example, the circulation records of 2019 are thoroughly examined. The aim of the study is to identify the level of demand for Russian literature at various times and the factors influencing the changing trend of demand. The results obtained from the research show that despite the large total number of visitors and the frequency of use of the main collection, the demand for Russian literature was relatively low, especially when compared with other foreign authors. Russian literature from the 19th century and Soviet literature are in the highest demand. Readers didn’t show an obvious interest in contemporary Russian authors. The demand for these three types of authors is clearly uneven. Russian-American writers, as a special group, are also popular choice of readers. The largest reader group consists of middle-aged women. Male readers have a more steadfast and clear preference for one particular author than female readers do. The demand for Russian literature in the library is influenced by such factors, as age and gender, the spread of culture through mass media and social networks, and reading promotion practices by libraries. These factors interact with each other.
Personnel Potential of Libraries in Music and Art Schools: State and Prospects of Development

The article reflects the results of a local study of the human resources of libraries in music and art schools of St. Petersburg, conducted in 2020, assesses the current state of their human resources and suggests possible ways of its development. Libraries in children’s music and art schools (CMS/CAS) are an important participant in the system of additional pre-professional education of children, that’s why the quality of the work of specialists is an important factor in ensuring the quality of the educational process. It was found that the information about these libraries on the websites of the CMS/CAS, is given extremely rare, and it is not structured. Regulatory documents contain very little or no information at all about the tasks of the library, the functional responsibilities of librarians, let along their salaries. The staff is exclusively women; three-quarters of employees are over 50 years old; their work experience in libraries ranges from a minimum to several decades; only the third of employees have a higher library education, more than a half – the pedagogical one, that result in the quality of library activity. Only half of the employees is able to work on computer. Qualification categories to librarians are not assigned. All respondents need advanced training in basic library processes. In the current situation, the main way to develop the activities of the libraries in the CMS/CAS of St. Petersburg is to transform them into information and library centers for the arts similar to those created in school libraries, and to unite them into a network to overcome the disunity of the professional group of librarians of the CMS/CAS.
Region velocity estimation and visulization with seurat v1

Example pipeline of region velocity estimation and visulization of steady-state model and dynamical model using EM algorithm in R with Seurat to pretreat scRNA-seq data
A Novel Probabilistic Graphical Model-Based Click Model for Vertical Search

Modern search engines provide the result including not only the traditional web documents, but also the segments aggregated with specialized information such as images, videos, and news, called vertical, to the users. Most click models associated with vertical search were designed to reduce various biases caused by verticals in search engine result pages to evaluate user behavior of web documents. However, evaluation of verticals themselves has not been conducted. In this paper, we propose vertical click models to analyze user behavior associated with both verticals and documents. The proposed click models based on probabilistic graphical model framework directly reflect events occurred in verticals and documents, so that they allow to elaborately calculate and evaluate the preference of verticals felt by the user. The proposed models were evaluated with a click log dataset from the popular commercial search engine in Korea. The results demonstrated superiority of our model over existing models in terms of normalized discounted cumulative gain.
COVID-19 Pandemic and Contact Tracing

The coronavirus disease-2019 (COVID-19), which caused loss of massive lives and is still continuing to do so, was initially observed to cause severe illness and deaths in Wuhan (China) around December of 2019.The virus spread at a very fast pace all around the world extensively which made the World Health Organization (WHO) to declare a pandemic on March 11, 2020.Contract tracing is an effective method for containment of infectious like coronavirus disease.It is a method in which a lead case with confirmed COVID infection is enquired about the people he contacted during the period when he was possibly infective as the contacts were at a very high risk of obtaining infection from the lead case.The contacts are then traced and counseled about the risk of infection, quarantined, and tested if necessary as per the countries testing guidelines.Contact tracing is an efficacious method which can prevent the transmission of infection by identification of infected individuals, their isolation and care depending upon the severity of the disease (home isolation/hospitalization), and also investigation of the individuals which were exposed to them and isolating them for the required period if necessary so that virus transmission can be stopped.To conclude, contact tracing is definitely an important measure to control, prevention as well as the spread of coronavirus disease as respiratory droplets are the main form of spread of the virus.It is equally effective against all the strains of the virus irrespective of its virulence.
Penerapan Jaringan Syaraf Tiruan Backpropagation Dalam Memprediksi Jumlah Pertumbuhan Kendaraan Di Provinsi Sumatera Utara

Motorized vehicles are part of the need for transportation of vehicles that are derivatives due to economic, social, and other activities. The growth of vehicles is not proportional to the population in the province of North Sumatra. This causes various negative impacts, one of which is an increase in traffic congestion, air pollution from motorized vehicles which causes an increase in greenhouse gas emissions. Based on this problem, it is necessary to predict the number of vehicles in North Sumatra Province using the backpropagation algorithm artificial neural network. The results of trials carried out with MATLAB R2011b software, the best architectural model is the 2-2-1 model with an accuracy rate of 94% with MSE number 0.000208514, epoch value 789. It can be concluded that the Backpropagation method can be used as one of the predictive methods that make it easier to find predictions. Whatever.
Penerapan Metode K-Means Dalam Mengelompokkan Persebaran Lahan Kritis Di Indonesia Berdasarkan Provinsi

The study aims to group the distribution of critical land in Indonesia by province. To solve this problem, researchers applied the K-Means Algorithm method. Where the source of research data is collected based on documents - documents of Information on The Extent and Dissemination of Critical Land By Province produced by the Central Statistics Agency (BPS). The data used in the study was data from 2011, 2013 and 2018 consisting of 34 provinces. Data will be processed by clustering in 2 clusters, namely clusters of high critical land distribution rates and clusters of low critical land distribution rates. The high cluster amounted to 4 data, namely the provinces of North Sumatra, Jambi, East Java, and Central Kalimantan. With the conduct of research can contribute in improving the performance of Balai Pengelolaan Daerah Aliran Sungai dan Hutan Lindung (BPDASHL) on the process of fixing and tackling critical land in the provinces in Indonesia.
Digital competencies as the basis of professional competitiveness (on the example of training management specialists)

Introduction. The digitalization of the economy and the digitalization of society are occurring at a rapid pace. The Russian Federation has approved a strategy for the development of the information society for the period up to 2030. The implementation of this strategy provides for improving the quality of life, creating conditions for the development of knowledge, the use of digital technologies, increasing the degree of digital literacy, digital security, etc. The formation of a global digital environment has affected all spheres of life, and especially education. Currently, the digitalization of education is seen as a turning point in history and the formation of a new paradigm for it’s development. Purpose setting. The article studies and discusses the problem of the formation and development of digital competencies of management specialists. Methodology of the study. The methodology of the research includes a socio-philosophical analysis of current trends in the digitalization of education and the use of a sociological survey of students. Results. The paper presents the results of a study on the use of information technologies by students in education (the viewing and searching for information and digital content, evaluating and analyzing information and digital content, using the functionality of social networks in education, reading educational and scientific literature, professional development, working with a text editor, working with electronic tables, information visualization). According to the authors, management specialists should confidently use “smart” gadgets (smartphones, tablets, etc.). In the digital environment, management professionals need to be able to use data analysis programs such as Jupyter Notebook, JupyterLab, PyCharm, RStudio, Stata, SPSS, Microsoft Excel and others, and use Google Sheets. Also, in their professional activities, they must be able to use cloud technologies and programs for data analysis with the ability to simultaneously edit a document (Google Collaboratory, for example). Conclusion. The authors believe that digital literacy and digital competencies are necessary for the competitiveness of a future management specialists and for their success in the modern labor market.
Iterative Pruning-based Model Compression for Pose Estimation on Resource-constrained Devices

In this work, we propose a pruning-based model compression scheme, aiming at achieving an efficient model that has strength in both accuracy and inference time on an embedded device environment with limited resources. The proposed scheme consists of (1) pruning profiling and (2) iterative pruning via knowledge distillation. With the scheme, we develop a resource-efficient 2D pose estimation model using HRNet and evaluate the model on NVIDA JetsonNano with the Microsoft COCO keypoint dataset. Specifically, our compressed model obtains the fast pose estimation of 20.3 FPS on NVIDA JetsonNano, while maintaining a high accuracy of 74.1 AP. Compared to the conventional HRNet model without compression, the proposed compression technique achieves 33 % improvement in FPS with only 0.4 % degradation in AP.
Combined Cognitive Model for Forecasting University Activities

Purpose of the study . The purpose of the study is to develop a model for predicting university performance indicators based on a cognitive approach, which is based on the construction of a cognitive map that reflects the influence of a set of latent factors on the basic indicators and provides a solution to the problem of scenario forecasting. The degree of achievement of the required values of the basic indicators that determine the ranking of the university depends on the magnitude of the increment of the identified latent factors. The developed model makes it possible to choose the most preferable variant of scenario forecasting under the existing restrictions on the resources allocated for the increment of latent factors. Materials and methods. To achieve this goal, cognitive modeling methods based on gray fuzzy cognitive maps (FCM) were used in combination with methods of interval mathematics and causal algebra. The application of the considered approach made it possible to reduce the uncertainty of expert estimates of the strength of the relationship between the concepts of the cognitive map due to the use of special constructions in the form of interval estimates rather than point estimates when describing the relationships between the concepts, which ensured an increase in the reliability of the modeling results. The developed model is created based on an ensemble of gray FCMs, which, in turn, made it possible to increase the accuracy and reliability of the predictive model. The proposed approach to solving the problem of predicting the activities of the university made it possible to develop an adequate cognitive model. Results . The developed cognitive model of the university’s activities made it possible to analyze the dynamics of changes in factors and their influence on basic indicators, as well as the dynamics of the development of the system of indicators. The calculation made it possible to choose the most cost-effective scenario for incrementing the values of latent factors to obtain the required value of the university ranking in the framework of the QS international institutional ranking of universities. A comparative analysis of the results of scenario forecasting based on conventional FCM, gray FCM, and an ensemble of gray FCM was carried out, which showed the advantage of the proposed approach. Conclusion. During the study, a fuzzy cognitive model was developed for scenario forecasting of measures to achieve the required values of university performance targets in the QS international institutional ranking based on an ensemble of gray FCMs. The developed model provides, under the given constraints, obtaining the most acceptable scenario for planning the increment of basic indicators to target values by identifying the latent factors influencing them and calculating the required values of impulse effects on latent factors.
Inclusive model of education in the creation and implementation of educational trajectories

Introduction. The inclusive model of education introduces a number of important additions to the system of educational relations, including the idea that students with certain typical or individual characteristics can and should learn and be brought up together, albeit within the framework of personal educational trajectories. There are more of these trajectories, which differ from the trajectories of other students, the greater, the older they are, the more unique the situation of their development, the more developed the educational environment of the institution or the educational complex of institutions, etc. Problem statement. The idea of inclusion is the idea of systemic individualization of education: the creation of complex, ordered individual programs of (re)training that would meet the more or less specific capabilities and needs of a particular schoolchild or student, allowing education to be carried out at a qualitatively high productive and procedural level. Methodology of the study. The work contains a systematic theoretical understanding of modern problems of development and implementation of individual educational trajectories in the context of the model of inclusive education in the era of transition to a new technological and social order. Results. The inclusive model of education makes a number of important additions to the system of educational relations, draws the attention of practitioners and theorists of education to the importance of harmonizing educational trends towards standardization, universalization and individualization, towards solving the problems of a person’s realization of himself in the world, in a way that will be significant and necessary for him and the community. Conclusion. Inclusive education largely focuses on universal, common human values that reflect the eusocial nature of the human community. At the same time, it is important to take into account human characteristics in educational and other activities systematica lly.
Ukrainian E-Learning Platforms for Schools: Evaluation of Their Functionality

This article defines 27 criteria for evaluating the functionality of e-learning platforms, grouped into three macro groups: (a) learning management, (b) learning content management, and (c) communications and collaboration tools. The proposed criteria can be used to evaluate any e-learning platform’s functionality. They allow teachers and administrators to make conscious choices about the highest-quality e-learning platform for their schools and developers to improve e-learning platforms’ functionality. The developed criteria became the basis for rating the functionality of Ukrainian developers’ eight e-learning platforms' and determining the degree of support (in whole or partly) of e-learning components, categorized on the cognitive, social constructivist, motivation, and e-learning theories (CT, SCT, MT, and E-LT). The results indicate that the lack of communication and collaboration tools necessary to ensure quality distance learning is the main problem of Ukrainian e-leaning platforms. Comparative analysis of the functionality of e-learning platforms and components categorized on the learning theories helped determine that only three of the eight Ukrainian e-learning platforms (Accent [Mobischool], Class Assessment, My Class) fully follow the CT, SCT, and MT, but these platforms are all commercial products; therefore, they only partially support the E-LT. Solving this problem will be facilitated by developing e-learning platforms with open access, financed by the state budget in the context of the development of open and distance learning for Ukrainian students, as well as improving communication and collaboration tools in the context of conforming e-learning components to the social constructivist learning theory.
Popular Biobibliographic Essay (The Evolution of the Genre in RSL Publications)

The article examines the evolution of the modern genre of recommended bibliographic publications, which is clearly tracked in the publications of the Russian State Library (RSL). The author’s goal is to show how the signs that make the genre popular for modern cultural and educational activities have been formed and consolidated in the process of evolution. The relevance of the research is to identify the opportunities to use recommended bibliographic publications more effectively to promote a book to a reader. The popular biobibliographic essay has become an evolutionary pinnacle for two types of recommended bibliographic products. These are personal indexes, where information about a person is combined with information about literature (publications) plus a detailed review in the genre of «conversations about books». Both types of indexes go back to the list of recommended literature, with the creation of which in the 1920s the recommendation bibliographic activity of the RSL began. In the 1980s, in the RSL there appeared publications, which became the prototype of modern popular biobibliographic essays. The decisive influence on the formation of the genre of popular biobibliographic essay had «perestroika». The recommendation bibliography was actively engaged in navigation in the array of the most popular literature, And in parallel it turned to the little-known and hard-to-access literature. In both cases, new tasks appeared. Some authors had to be selected from the total number, while others, in fact, had to be introduced. A modern essay, accordingly, gives a comprehensive picture of life and work of the person to whom it is dedicated. It creates the image of a person, shows his (her) place in the cultural context, analyzes creativity in general, and characterizes specific book publications.
Automatic product region extraction based on colour similarity and saliency detection models

In this paper, product region extraction, which can classify the pixels of the product images as product and background regions, is proposed. The proposed method is based on the handcrafted algorithm using both the colour similarity and the saliency detection. Our experiment, which employed 180 product images, clarified that the proposed method increased all the metric for the extraction accuracy compared with conventional methods based on the handcrafted algorithm. The F-measure, which is the comprehensive metric, was significantly increased by 2.20% or more. Our discussion also found that the proposed method also overcame the shortcoming of the conventional method, because the F-measure for the dataset, the accuracy of which was decreased by the conventional method, was significantly improved. In addition, the F-measure was increased by 0.92% or more for each product category. Further comparison and discussion are included in this paper to provide more focused findings.
Quantum Computing for Power Flow Algorithms: Testing on real Quantum Computers

Quantum computing has the potential to solve many computational problems exponentially faster than classical computers. The high shares of renewables and the wide deployment of converter-interfaced resources require new tools that shall drastically accelerate power system computations, including optimization and security assessment, which can benefit from quantum computing. To the best of our knowledge, this is the first paper that goes beyond quantum computing simulations and performs an experimental application of Quantum Computing for power systems on a real quantum computer. We use five different quantum computers, apply the HHL quantum algorithm, and examine the impact of current noisy quantum hardware on the accuracy and speed of an AC power flow algorithm. We perform the same studies on a 3-bus and a 5-bus system with real quantum computers to identify challenges and open research questions related with the scalability of these algorithms.
Using 3D Shadows to Detect Object Hiding Attacks on Autonomous Vehicle Perception

Autonomous Vehicles (AVs) are mostly reliant on LiDAR sensors which enable spatial perception of their surroundings and help make driving decisions. Recent works demonstrated attacks that aim to hide objects from AV perception, which can result in severe consequences. 3D shadows, are regions void of measurements in 3D point clouds which arise from occlusions of objects in a scene. 3D shadows were proposed as a physical invariant valuable for detecting spoofed or fake objects. In this work, we leverage 3D shadows to locate obstacles that are hidden from object detectors. We achieve this by searching for void regions and locating the obstacles that cause these shadows. Our proposed methodology can be used to detect an object that has been hidden by an adversary as these objects, while hidden from 3D object detectors, still induce shadow artifacts in 3D point clouds, which we use for obstacle detection. We show that using 3D shadows for obstacle detection can achieve high accuracy in matching shadows to their object and provide precise prediction of an obstacle's distance from the ego-vehicle.