Reviewerly/exHarmony huggingface dataset:
Semiotic Approach in the Development of Interactive Visual Analytics Systems

Increasing information saturation in all spheres of life entails accumulation of large amounts of data that must be perceived, processed and decisions must be made on their basis. Therefore, the issues of interaction with data and of visual analytics require solutions at a new level. The authors investigate communication between the user and the data, highlight a number of negative trends that prevent effective use of visualization in solving practical problems, formulate aspects of subjective influence on the decision-making procedure, namely those leading to significant decrease in the efficiency of visual analytics systems. The paper proposes an approach to the problem of reasonable use of existing and potential visualization capabilities for solving data analysis problems and making control decisions. A significant factor hindering the development of visual analytics is a lack of a model for coordinated use of computational and subjective resources corresponding to the technical level of computer visualization capable of ensuring close communication between the researcher and the available data. The paper describes an approach based on the concept of visual communication, the properties of which are determined on the basis of a number of key concepts of semiotics and linguistics.
Management of Economics and State "Bottom"

The scientific problem of economics “Managing the quality of human life” is formulated on the basis of artificial intelligence, algebra of logic and logical-probabilistic calculus. Managing the quality of human life is represented by managing the processes of his treatment, training and decision making. Events in these processes and the corresponding logical variables relate to the behavior of a person, other persons and infrastructure. The processes of the quality of human life are modeled, analyzed and managed with the participation of the person himself. Scenarios and structural, logical and probabilistic models of managing the quality of human life are given. Special software for quality management is described. The relationship of human quality of life and the digital economy is examined. We consider the role of public opinion in the management of the “bottom” based on the synthesis of many studies on the management of the economics and the state. The bottom management is also feedback from the top management.
The Effects of Using a Fully Integrated Mobile Application to Access Learning Management Systems in Higher Education

The use of mobile devices in the classroom is increasingly frequent. However, the LMS are still not completely adapted to this format, preventing students from using all the LMS web-functionalities in their mobiles. Hence, we present and evaluate the use of a new mobile application fully integrated with Learning Management Systems (LMS). We examined access to LMS by 95 postgraduate university students, differentiating between the services accessed and the means used. Students belonged to four consecutive promotions. In the first two, access to the system was through the web, while in the third and fourth, an app fully integrated with the LMS was available. The results showed an overall increase in access to LMS, with a considerable reduction in access via the web in favor of access via the application. Significant differences were found in the access patterns to communication and assessment services depending on the students' age, gender, academic major and previous m-learning experience. Satisfaction with the LMS rose when the app was available, with greater growth within the academic major on IT and previous m-learning experience group. Finally, students with high performance accessed the system significantly more than those with low performance. In conclusion, the integration of the app with the system showed useful and efficient results. The app eased the use of the system, increased student satisfaction with LMS, and student performance improved with increased access.
Towards a Documents Processing Tool using Traceability Information Retrieval and Content Recognition Through Machine Learning in a Big Data Context

In 1980, an application was developed to track, manage and store documents in electronic format.Scan technology has enabled organizations to digitize papers for easier document storage and tracking.Document management tools have since developed by introducing new functionalities, related to security, users services, workflow and audit.Our research is part of the context of improving the efficiency of document processing by proposing an approach using information traceability retrieval and content recognition techniques through machine learning.In this sense, we started by proposing the exploitation and extraction of relationships between documents based on the traceability links and the calculation of similarity using information retrieval.Then, in order to improve the processing of documents, we proposed a contribution of the use of recognition of content techniques by machine learning approaches.Thus, the visualization of the results, according to user profiles, motivated us to offer recommendations dedicated to the document management system.A Big Data environment is proposed because of the exponential growth of data and also to our needs concerning the analysis and the distributed calculation of the voluminous masses of data.
Research on Detection and Recognition of Pointer Instrument Based on Lightweight Network

This article proposes an embedded platform automatic detection and recognition method for pointer instruments in substations and communication rooms. Firstly, YOLO network is selected for coarse positioning, and SSD network is used as the backbone network for fine positioning, and they are respectively lightweight for deployment in embedded devices. Secondly, perspective transformation is used to correct the deviation of the viewing angle between the dial and the camera for the positioned meters. Finally, for the obtained high-quality meter image, the final reading of the meter is recognized through the dial detection, pointer detection and scale correspondence. Experimental results show that the proposed method has good performance for rapid and effective detection and recognition of pointer instruments in substation and communication room environments.
THE SPECIFICS OF THE RUSSIAN PROJECT CULTURE

In conditions of economic, social and cultural glocalization (the interaction between local and global phenomena), it becomes especially important for a designer to realize his/her own mental habits that impede intercultural dialogue, despite identifying his/her projects and project communication. The object of the study is Russian project culture as an essential characteristic of the design thinking, allowing a designer to implement the value content of the culture he/she belongs to. &#x0D; The methodological basis of the study includes problem statement, generalization and interpretation of the term, comparative method, historical and cultural analysis. &#x0D; As a result of the study, the authors conclude that the specificity of Russian project culture lies in its "theurgic" nature (connection with inspired creativity). According to the authors, the awareness of the fundamental dissimilarity of Russian project culture with Western or Eastern project culture (the fundamental diversity of the design thinking types) opens up the prospect of a genuine intercultural dialogue within a holistic design culture.
Features of Signature Verification By a Person as a Primary Criteria for Developing an Artificial Intelligence System

The modern capabilities of computers have returned interest in artificial intelligence technologies. A particular area of application of these technologies is pattern recognition, which can be applied to the traditional forensic task – identification of signs of forgery (imitation) of a signature. The results of forgery are differentiated into three types: auto-forgery, simple and skilled forgeries. Only skilled forgeries are considered in this study. The online and offline approaches to the study of signatures and other handwriting material are described. The developed artificial intelligence system based on an artificial neural network refers to the offline type of signature recognition – that is, it is focused on working exclusively with the consequences of the signature – its graphic image. The content and principles of the formation of a hypothesis for the development of an artificial intelligence system are described with a combination of humanitarian (legal) knowledge and natural-technical knowledge. At the initial stage of the study, in order to develop an experimental-applied artificial intelligence system based on an artificial neural network focused on identifying forged signatures, 127 people were questioned in order to identify a person's ability to detect fake signatures. It was found that under experimental conditions the probability of a correct determination of the originality or forgery of the presented signature for the respondent is on average 69.29 %. Accordingly, this value can be used as a threshold for determining the effectiveness of the developed artificial intelligence system. In the process of preparing the dataset (an array for training and verification of its results) of the system in terms of fraudulent signatures, some forensically significant features were revealed, associated with the psychological and anatomical features of the person performing the forgery, both known to criminalistics and new ones. It is emphasized that the joint development of artificial intelligence systems by the methods of computer science and criminalistics can generate additional results that may be useful outside the scope of the research tasks.
Description and Findings of OPPO’s Machine Translation Systems for CCMT 2020

This paper demonstrates our machine translation systems for the CCMT 2020, which is composed of four parts. The last three parts report our results in the contest, each respectively focuses on English-Chinese bi-direction translation, Japanese-Chinese-English multi-lingual translation (patent domain), and Chinese minority languages to Mandarin Chinese translation. In each part, we will demonstrate our work on data pre-processing, model training as well as the application of general techniques, such as back-translation, ensemble and reranking. Besides, during our experiments, we surprisingly found that simply applying different Chinese word segmentation tools on low-resource corpora could bring obvious benefit across different tasks, and we will separate an independent section to discuss this finding. Among the 7 directions we participated in, we ranked the first in 6 tasks (For the corpus filtering task, we ranked first in the 500 million words sub-task) and the second for the rest.
Model of University's Career Guidance Activities within the Context of Lifelong Learning

In the 21st century, human capital has become the most important factor for the development of society. Human capital contributes to enhancing the position of Russia in global economy. Nowadays, education is an investment which provides the scale and quality of the economic growth, the prosperity of the country and every person in particular. Unfortunately, the formal educational potential of the Russian population is not used to its full. Therefore, the role of universities in our country is reconsidered; they are becoming the drivers of the growth in the economy and regional centers of innovations. At the same time, apart from education and science, the universities are responsible for the third social mission, a global trend with local characteristics. Having a huge intellectual potential, the University is able to influence individual regional processes. The authors consider the generation of relevant ideas for the development of continuing education as the most important and unique mission of higher education to shape the future of each child, create conditions for self-development of the individual, its career tracks that ensure continuity, identification and support of giftedness.
Evaluating the Socioenactive Experience with a Tangible Tabletop Installation: A Case Study

A multitude of methods for evaluating the interaction and experience exists, but there is a lack of discussion on methods that evaluate the experience in enactive and socioenactive scenarios. In this work, we investigate whether current evaluation methods are sufficient to evaluate the socioenactive experience that emerges of the coupling of three main elements (physical, digital, and social) as part of those scenarios. We conducted a case study to evaluate the experience resulting from the interaction with TangiTime, a tangible tabletop installation, using the AttrakDiff questionnaire as an evaluation method for the socioenactive experience. Based on findings from this case study, we provide insights on other design aspects to be covered in the evaluation of socioenactive scenarios.
Two-Stage Framework for Accurate and Differentially Private Network Information Publication

We propose a novel mechanism to release an accurate and differentially private estimate of the link set of social networks. Differential privacy is one of the most common notations to quantify the privacy level of information publication. Several methods have been proposed to publish edge set information, among which one of the notable mechanisms is based on stratified sampling. While it is very scalable, social network information can be significantly altered by this technique. In fact, when we use mechanism based on stratified sampling, a totally random network may get published even when the input network is sparse. We aim to overcome this drawback in our work. We provide an efficient two-stage mechanism to control the edge set size and quality independently. To confirm the practical utility of our proposal, we apply it to the maximum matching problem when the edge information is spread between two different bipartite networks. We validate through experiments that the error induced by our framework is at least 20 times smaller than that of the original stratified sampling based mechanism when privacy level is 5. In addition, the computation time of our framework is 3 times shorter than the original method.
Relative Study Between Technology to Perceive Hand Gestures

Interaction with each other helps human beings to share their intention, belief, understanding, and experience to individuals around them. This is not true in the case of people with hearing or speech disabilities. Communication for a hearing- or speech-impaired person is achieved through sign language. The main idea behind this problem is to develop a system for recognizing the signs, which would bridge out the communication gap between people with speech-impaired and normal people. The main goal of the paper is to track the region of interest (ROI) with the help of a camera and detect the target object by using object detection algorithms. Here, the target object is the hand and any gestures made by the hand are analyzed using different technologies.
Spin Doctoring in modern political discourse: linguistic aspect

In the article, the realization of verbal influence (also known as suggestion) phenomenon in political discourse is considered. This concept is defined as a whole combined image of the text itself and emotions of its recipient and addressee,including the peculiarities of perception, external and internal circumstances, its pragmatic and linguistic aspects, etc, and is aimed at a a political subject’s influencing a political object. Usually, political discourse and its immanent influential properties are researched from the standpoint of Psychology, Communicative Linguistics, Pragmalinguistics, Political Linguistics and other related sciences, but the author proposes to involve Neurolinguistic Programming as a modern science which deals with analyzing the peculiarities of perception, processing and generation of information and its transformations from deep thought structures to superficial speech; as well as Spin-Doctoring, an ultramodern complex discipline aimed at correcting the negative image of the event in the media after its has already happened or right before its manifestation, which is impossible without the involvement of language techniques to influence the recipient or a group of them. In order to fully research the political discourse, which in the network of this article is represented by the political speeches of the leaders of Ukraine, USA, France, Spain, Italy, Canada, Germany, the author involves both the basic Spin Doctoring techniques of political discourse correction ( negative information delay, ambiguous informing, focus switch, interspersing the artificial situations with elements of naturalness, and the technique of controlled information leaks and preparation for events expectations); and the NLP paradigm meta- and Milton-model analysis text having been utilized in order to isolate the actual linguistic influential patterns (markers of language metamodel processes, simple, complex and indirect inductions). The analysis details the available information on the peculiarities of implementing and enhancing the linguistic influence within the political discourse, as well as outlines the crucial next steps in the further researches on this topic, especially ones in the field of Ukraine’s state information security, which is a particularly important aspect of the state’s modern information during hybrid wars.
Tilt and Rotation Motion Control System for Solar Panel

This paper proposes a control system to enhance the performance of a solar panel. A two axes mechanism is developed that tilts and turns the solar panel to face the highest intensity of light. The system was designed in LabVIEW and implemented on the Arduino Mega 2560. The physical model of the system was built using servo motors and photoresistors. The pilot plant was tested by applying a source of light from various directions and monitoring its response. The solar panel was able to face towards the highest intensity of light with high level of precision.
Conditional GAN-based Remote Sensing Target Image Generation Method

Abstract In view of the uncontrollable process of traditional GAN generating remote sensing target images, the shortcomings of generated samples are similar, and lack diversity. This paper proposes a generative confrontation network model based on background conditions. First, the computer vision attention mechanism is introduced into the generative confrontation network. Choose a learning target model so that the GAN network only learns the target model during training, and ignores other non-target information. Reduce the dependence on the number of samples in the GAN training process; secondly, use the U-net network as a generator to restore other non-target information when generating the remote sensing image of the target as much as possible; again, distinguish by different colors of the conditional mask The category of the generated target; at the same time, the L1 regularization loss is added to the loss term of the generator model, and finally, the remote sensing target image is generated. The experimental results show that the peak signal-to-noise ratio (PSNR) of the remote sensing image generation algorithm proposed in this paper reached 18.512, and the structural similarity (SSIM) reached 88.47%, which is better than the comparison test model where the generator is an ordinary autoencoder.
“Manor libraries of the Tambov province of the late 18th – early 20th centuries”: a method of creating an information resource

The article analyzes the main approaches to creating an information resource “Estate libraries of the Tambov province of the late XVIII – early XX century. The author analyzes the source base, identifies ways to systematize book collections of Tambov nobles of the XVIII–XIX centuries in Russian, French, Greek, Latin, English and German, and their significance for the study of book culture in the region
Augmented Memory Replay in Reinforcement Learning With Continuous Control

Online reinforcement learning agents are currently able to process an increasing amount of data by converting it into a higher order value functions. This expansion of the information collected from the environment increases the agent's state space enabling it to scale up to a more complex problems but also increases the risk of forgetting by learning on redundant or conflicting data. To improve the approximation of a large amount of data, a random mini-batch of the past experiences that are stored in the replay memory buffer is often replayed at each learning step. The proposed work takes inspiration from a biological mechanism which act as a protective layer of human brain higher cognitive functions: active memory consolidation mitigates the effect of forgetting of previous memories by dynamically processing the new ones. The similar dynamics are implemented by a proposed augmented memory replay AMR capable of optimizing the replay of the experiences from the agent's memory structure by altering or augmenting their relevance. Experimental results show that an evolved AMR augmentation function capable of increasing the significance of the specific memories is able to further increase the stability and convergence speed of the learning algorithms dealing with the complexity of continuous action domains.
ALGORITHM FOR FINDING EXPLICIT SOLUTIONS OF OVERDETERMINED SYSTEMS OF DIFFERENTIAL EQUATIONS

Previously, the authors proposed a general method for finding particular solutions for overdetermined systems of partial differential equations (PDE), where the number of equations is greater than the number of unknown functions. In this paper, an algorithm for finding solutions for overdetermined PDE systems is proposed, where the authors use a method for finding an explicit solution for overdetermined algebraic (polynomial) equations. Using this algorithm, some overdetermined PDE systems can be solved in explicit form. The main difficulty of this algorithm is the huge number of polynomial equations that arise, which need to be investigated and solved numerically or explicitly. For example, the overdetermined hydrodynamic equations obtained earlier by the authors give at least 10 million such equations. However, if the equations are solved explicitly, then it is possible to write out the solution of the hydrodynamic equations in a general form, which is of great scientific interest.
SoK: Fully Homomorphic Encryption Compilers

Fully Homomorphic Encryption (FHE) allows a third party to perform arbitrary computations on encrypted data, learning neither the inputs nor the computation results. Hence, it provides resilience in situations where computations are carried out by an untrusted or potentially compromised party. This powerful concept was first conceived by Rivest et al. in the 1970s. However, it remained unrealized until Craig Gentry presented the first feasible FHE scheme in 2009. The advent of the massive collection of sensitive data in cloud services, coupled with a plague of data breaches, moved highly regulated businesses to increasingly demand confidential and secure computing solutions. This demand, in turn, has led to a recent surge in the development of FHE tools. To understand the landscape of recent FHE tool developments, we conduct an extensive survey and experimental evaluation to explore the current state of the art and identify areas for future development. In this paper, we survey, evaluate, and systematize FHE tools and compilers. We perform experiments to evaluate these tools' performance and usability aspects on a variety of applications. We conclude with recommendations for developers intending to develop FHE-based applications and a discussion on future directions for FHE tools development.