Reviewerly/exHarmony huggingface dataset:
International system of certification of hotel services in Russia: problematic of implementation and development prospects

The object of this research is the &amp;ldquo;Hotel Industry and Hospitality&amp;rdquo;, while the subject is the international system of certification of hotel services. The article reviews the evolution of hotel industry in Russia and the application of such tools as standardization, certification, and compliance evaluation from the perspective of quality improvement. &amp;nbsp;Current trends and approaches towards the problems of certification of hotel services with consideration of the international and regional aspects are described. The authors explore the types of certification of hotel services in the Russian Federation and their peculiarities, key characteristics and tools that allow analyzing, systematizing, controlling, improving and adapting the quality standards of rendered services. The author elucidates the primary causes of low interest of the hotels in certification; outlines the prospects for the development of international system of certification of hotel services in Russia. The conclusion is made that despite the worldwide fame and popularity of hotel services certification system, including ISO standards, the prospects for implementation and advancement of the current system in the Russian hotel industry are not too encouraging due to multiple reasons discusses in the article. However, it would not be fair to deny the clear benefits of such certification. Therefore, taking into consideration the desire of hotel business and state standardization and certification authorities to establish a harmonious system of rendering hotel services of such level and quality of service that would not only meet the demands of visitors, but also promote the domestic tourism market on the international platforms of tourism industry, presses the need for popularization of certification system, as well as full state support of the business that would maintain high standards of rendered services in the international certification systems.
A web platform for generating graphical user interfaces

This paper is a general description of a Python-based web platform developed by the author that generates Graphical User Interfaces (GUIs) for software programs. It presents both technical and theoretical aspects of programming, Python libraries, chatbot development and auto-generating graphical interfaces. The article proposes an overview of a web system, explained with the help of diagrams.
Learning to Observe with Reinforcement Learning

We consider a decision making problem where an autonomous agent decides on which actions to take based on the observations it collects from the environment. We are interested in revealing the information structure of the observation space illustrating which type of observations are the most important (such as position versus velocity) and the dependence of this on the state of agent (such as at the bottom versus top of a hill). We approach this problem by associating a cost with collecting observations which increases with the accuracy. We adopt a reinforcement learning (RL) framework where the RL agent learns to adjust the accuracy of the observations alongside learning to perform the original task. We consider both the scenario where the accuracy can be adjusted continuously and also the scenario where the agent has to choose between given preset levels, such as taking a sample perfectly or not taking a sample at all. In contrast to the existing work that mostly focuses on sample efficiency during training, our focus is on the behaviour during the actual task. Our results illustrate that the RL agent can learn to use the observation space efficiently and obtain satisfactory performance in the original task while collecting effectively smaller amount of data. By uncovering the relative usefulness of different types of observations and trade-offs within, these results also provide insights for further design of active data acquisition schemes.
Construction of Side Channel Attacks Resistant S-boxes using Genetic Algorithms based on Coordinate Functions

Background and Objectives: Substitution-box (s-box) is one of the essential components to create confusion and nonlinear properties in cryptography. To strengthening a cipher against various attacks, including side channel attacks, these boxes need to have numerous security properties. In this paper, a novel method to generate s-boxes is introduced aimed at improving the resistance of s-boxes against side channel attacks. Methods: In the preprocessing phase of this approach, a suitable initial s-box which has some basic security properties is generated by adopting a fast algorithm. Then, in the main stage, using the initial s-box, we generate new s-boxes which not only have the properties of the initial S-box but also have been significantly improved under another set of security properties. To do this, new s-boxes are generated using a genetic algorithm on a particular subset of the linear combination set of coordinate functions of the initial s-box in the preprocessing stage. Results: The performed experiments demonstrate that the values of all security properties of these new s-boxes, especially the measures of transparency order, signal-to-noise ratio, confusion coefficient, bijection property, fixed point, and opposite fixed points, have been substantially improved. For example, our experiments indicate that 70, 220, 2071, 43, and 406 s-boxes are found better than the initial s-box, respectively, in the dimensions of 4x4 through 8x8 Conclusion: In this article, a new s-box construction method is introduced in which the properties related to side channel attacks are improved, without reducing other security properties. Besides, some results obtained from generated s-boxes in the dimensions of 4x4 through 8x8 demonstrated that the generated s-boxes are not only improved relative to the initial s-box, but in some cases, considerably better than some well-known s-boxes.
Use of the AppsGeyser application in the assessment of self-study activities in English for the equality education

Learning English as a subject that is taught independently to citizens learning non-formal education is one of the most important things to face the challenges of the future and global life, as targeted in SDGs-goal 4. One of the innovative learning strategies that support learning English independently is the use of internet applications. AppsGeyser application is an internet application that allows users to use it offline. With this application we can easily distribute content from websites, blogs and certain files that we want to share via the Android application. The use of android in the process of learning English activities independently. The purpose of writing this real work is to describe and explain the use of the AppsGeyser application in self-study activities in the English language equivalency education package C. The method used in this real work is quantitative descriptive. The population used was all citizens learning the chasing equivalence education package C in PKBM Ilmu Barokah, totaling 10 citizens learning from grade 3. The instruments used in obtaining data were in the form of pretest and posttest with percentage data analysis techniques. The results achieved by learning citizens after using the AppsGeyser application as a learning medium, namely learning citizens become easier to do, enthusiastic in doing quizzes, easier to remember material so that they can answer quizzes smoothly, are more independent in studying learning materials and the results of evaluation of learning citizens increase compared to before using the app.
Characteristics of Writing Explanation Text Enrichment Book Containing 21st Century Competence for Senior High School Students

The formation of student personalities that can be developed with writing explanatory texts enrichment book containing 21st century competencies includes aspects of knowledge, skills, and personality that are integrated with 21st century competencies that students must master. This study aims to analyze the need for enrichment book development in writing explanatory text with 21st century competencies and the characteristics of enrichment book development for writing explanatory text with 21st century competence. The research method uses the Research and Development and uses six steps out of ten steps in the R&amp;D method. The results obtained from this study were an analysis of the needs of students and teachers which were grouped based on question aspects, namely (1) material and content needs, (2) 21st century competency content needs, (3) presentation needs, (4) language needs. and (5) legibility and graphics needs. This needs analysis is to determine the tendency of the needs of students and teachers to the form of the enrichment book being developed. Then, the characteristics of the enrichment book are writing explanatory texts containing 21st century competencies according to the perceptions of students and teachers in accordance with the principles of content feasibility, presentation feasibility, linguistic feasibility, and graphic feasibility. In addition, teachers and students are very in accordance with the form of the book that is being made easy to carry. Therefore, the development of an enrichment book to write explanatory texts containing 21st century competencies is in accordance with the wishes of teachers and students in using a learning resource.
Multi-Agent Imitation Learning with Copulas

Multi-agent imitation learning aims to train multiple agents to perform tasks from demonstrations by learning a mapping between observations and actions, which is essential for understanding physical, social, and team-play systems. However, most existing works on modeling multi-agent interactions typically assume that agents make independent decisions based on their observations, ignoring the complex dependence among agents. In this paper, we propose to use copula, a powerful statistical tool for capturing dependence among random variables, to explicitly model the correlation and coordination in multi-agent systems. Our proposed model is able to separately learn marginals that capture the local behavioral patterns of each individual agent, as well as a copula function that solely and fully captures the dependence structure among agents. Extensive experiments on synthetic and real-world datasets show that our model outperforms state-of-the-art baselines across various scenarios in the action prediction task, and is able to generate new trajectories close to expert demonstrations.
Abelian Neural Networks

We study the problem of modeling a binary operation that satisfies some algebraic requirements. We first construct a neural network architecture for Abelian group operations and derive a universal approximation property. Then, we extend it to Abelian semigroup operations using the characterization of associative symmetric polynomials. Both models take advantage of the analytic invertibility of invertible neural networks. For each case, by repeating the binary operations, we can represent a function for multiset input thanks to the algebraic structure. Naturally, our multiset architecture has size-generalization ability, which has not been obtained in existing methods. Further, we present modeling the Abelian group operation itself is useful in a word analogy task. We train our models over fixed word embeddings and demonstrate improved performance over the original word2vec and another naive learning method.
Numerical simulation analysis of extrusion shield tunnel construction process based on virtual reality

The traditional numerical simulation analysis method lacks the detection of the matter-element model, which leads to the numerical simulation analysis results of the tunnel construction process under complex conditions, and it is difficult to find the risk factors. Therefore, based on the virtual reality technology, the numerical value of the extrusion shield tunnel construction process is studied. Simulation analysis method. This method constructs the matter-element model of the shield tunnel construction by calculating the temperature field of the extruded shield tunnel construction; uses virtual reality technology to detect the matching degree of the tunnel structure, and realizes the numerical analysis of the dynamic characteristics of the extruded shield tunnel. Test results: the numerical simulation analysis method of tunnel construction process in this study has higher expert evaluation results, which shows that the construction parameters obtained under the application of virtual reality technology are more practical.
A novel combined level set model for automatic MR image segmentation

Abstract Medical image processing comes along with object segmentation, which is one of the most important tasks in that field. Nevertheless, noise and intensity inhomogeneity in magnetic resonance images challenge the segmentation procedure. The level set method has been widely used in object detection. The flexible integration of energy terms affords the level set method to deal with variable difficulties. In this paper, we introduce a novel combined level set model that mainly cooperates with an edge detector and a local region intensity descriptor. The noise and intensity inhomogeneities are eliminated by the local region intensity descriptor. The edge detector helps the level set model to locate the object boundaries more precisely. The proposed model was validated on synthesized images and magnetic resonance images of in vivo wrist bones. Comparing with the ground truth, the proposed method reached a Dice similarity coefficient of &gt; 0.99 on all image tests, while the compared segmentation approaches failed the segmentations. The presented combined level set model can be used for the object segmentation in magnetic resonance images.
THE ESSENCE OF EDUCATIONAL PARADIGMS AND POLYPARADIGMAL MANIFESTATIONS IN MULTIDIMENSIONAL PEDAGOGICAL REALITY AND PERSONAL SELF-REALIZATION OF STUDENTS IN E-LEARNING

The article examines the educational paradigm as a genesis indicator of changes in the educational field caused by social development, paradigm as a result of the implementation of integration processes. Besides, the personal self-realization of students as a manifestation of the student-centric paradigm is studied. Іn accordance with the objectives of the study, the following is performed. It summarises the key ideas of paradigms of traditional pedagogy (knowledge, ZUN, scientific- technocratic, paradigm of explanatory-illustrative learning) and people- oriented paradigms (child-centric, anthropological, cognitive, pragmatic, humanitarian, humanistic, cultural, paradigms of developmental and adaptive learning). It is established that paradigm analysis of modern education should be carried out in two directions: 1) to reveal its polyparadigmal character; 2) to provide a thorough consideration of the didactic features of the organizing the educational process within the specific educational paradigm. Considering the above mentioned matter in the article, the examples of polyparadigmal manifestations of multidimensional phenomena and processes in pedagogical reality are given. Didactic features of organising educational process in realisation of student-centered paradigm are also revealed. It is characterised such didactic tools as topic-presentation matrix and author’s music-markers of the beginning and end of the learning process (lectures, seminars, lessons, etc.). The self-realization of students with the use of these means is investigated. The complex of research methods is used in the work: general scientific (analysis, synthesis, comparison, systematization, generalization) and empirical (observations, discussions, questionnaires). The complex of research methods is used in the work: general scientific (analysis, synthesis, comparison, systematization, generalization) and empirical (observations, discussions, questionnaires). 110 respondents were involved in the study. These are full-time and part-time students. Institution of higher education: Borys Grinchenko Kyiv University. As a result of the study it is established a significant potential of the studied tools for organization of the learning process; for emotional adjustment of students to the process of learning and for recreation; for their personal self- realization on the basis of imitation of the creative of Others.
Estimation of Camera Response Function using Prediction Consistency and Gradual Refinement with an Extension to Deep Learning.

Most existing methods for CRF estimation from a single image fail to handle general real images. For instance, EdgeCRF based on colour patches extracted from edges works effectively only when the presence of noise is insignificant, which is not the case for many real images; and, CRFNet, a recent method based on fully supervised deep learning works only for the CRFs that are in the training data, and hence fail to deal with other possible CRFs beyond the training data. To address these problems, we introduce a non-deep-learning method using prediction consistency and gradual refinement. First, we rely more on the patches of the input image that provide more consistent predictions. If the predictions from a patch are more consistent, it means that the patch is likely to be less affected by noise or any inferior colour combinations, and hence, it can be more reliable for CRF estimation. Second, we employ a gradual refinement scheme in which we start from a simple CRF model to generate a result which is more robust to noise but less accurate, and then we gradually increase the model's complexity to improve the result. This is because a simple model, while being less accurate, overfits less to noise than a complex model does. Our experiments show that our method outperforms the existing single-image methods for daytime and nighttime real images. We further propose a more efficient deep learning extension that performs test-time training (based on unsupervised losses) on the test input image. This provides our method better generalization performance than CRFNet making it more practically applicable for CRF estimation for general real images.
The electronic resources troubleshooting guide

"The electronic resources troubleshooting guide." Journal of the Australian Library and Information Association, 70(1), pp. 92–93
Moiré Artifacts Removal in Screen-shot Images via Multiple Domain Learning

We propose a deep learning-based moire artifacts removal algorithm for screen-shot images using multiple domain learning. First, we develop the pixel and discrete cosine transform (DCT) networks to estimate clean preliminary images by exploiting complementary information of the moire artifacts in different domains. Next, we develop a clean edge predictor to estimate a clean edge map for the input moire image. Then, we propose the refinement network to further improve the quality of the pixel and DCT outputs using the estimated edge map as the guide information and to merge the two refined results to provide the final result. Experimental results on a public dataset show that the proposed algorithm outperforms conventional algorithms in quantitative and qualitative comparison.
The Convolution Addressing the Conundrum of Liability and Privacy in the Age of Autonomous Vehicles

The Automotive Industry has registered an impeccable growth rate since the adoption of autonomous vehicles by vehicle manufacturers in their high-end models. These fully autonomous vehicles are poised to replace the traditional human driver. Hence, the whole set of laws defining liability in the event of an accident involving a vehicle have to be reformed. An autonomous vehicle being sued in lieu of a human driver, would be impractical. With the accidents involving autonomous vehicles increasing, newly minted laws like that of Michigan Harbor Lacunas are forming to address the question of liability and as a consequence of which the innocent (the manufacturer in so many cases) is held absolutely liable, despite his pleading defense. Such a harsh stance is unhealthy for the development of technology. Apart from the conundrum surrounding liability there are other dimensions which are equally unaddressed when it comes to automation. These autonomous vehicles rely on data, thereby adding to the vulnerability of protection of an individual’s privacy. These brimming chaos are likely to hamper the aggrandizement of technology and subsequent protection of commercial interests.This Article is an attempt to comprehensively analyze the uncertainty surrounding the questions of liability and privacy protection for autonomous vehicles. It takes into account the technology friendly interpretation of law, which will balance the diametrically opposite variables. It draws the laws from the existing set of principles available. Further, it proposes a new framework eliminate obscurity and concludes on a positive note with recommendations which are likely to accentuate the effectiveness of the current laws and lay down a steppingstone for the future development of laws.
THE INFLUENCE OF NEW TECHNOLOGIES ON THE PROTECTION OF PERSONAL DATA WITHIN THE FRAMEWORK OF THE EPIDEMIC COVID-19

SUMMARY Legislators legislate as needs arise; it is the present moment and society itself, through its demands, which sets the path and provides them with the keys as to what matters to legislate on and what aspects need to be developed in greater detail. Contemporary societies try, with greater or lesser success, to adapt to the changes that are taking place, both those reflected in daily customs and habits, and those related to the generation, dissemination and use of information and knowledge. Today's society consumes and handles an excessive volume of information and data, often without assessing its veracity or analysing the source from which it comes, without considering the importance of the data it provides at any given time, and much less thinking about the consequences that misuse of such data may have for privacy, for example. These are issues that, despite being the order of the day, have already given cause for concern. A fact that is reflected in an increasingly prolix jurisprudence. An example of this, as we will have the opportunity to point out below, is the SAN of 6 April 2018, which, with regard to the problems that arise in relation to medical records, highlights the importance of defending the right to the protection of personal data and the need to obtain consent in an appropriate manner. In these times of pandemic, it is important to seek a suitable approach and to know some fundamental aspects of the aforementioned right to data protection, starting from such extremely important concepts as: personal data or consent itself. Moreover, the development of this right, so much questioned lately due to the use of COVID applications, in terms of the possible effects on privacy or image, or any of the controversies that are arising around data protection in the management of the coronavirus, almost forces us to think about its limits. In this respect, we must bear in mind that many of the answers to the questions that are being raised about the problems associated with current practices lie in the legitimising bases of data processing. In this study, I conclude that despite the great importance of some personality rights, including privacy, honour or self-image, and among which is the right to data protection, the right that deserves the greatest protection is the right to life. Let us not forget that the function of law is to serve the person to whom the reason for its existence must be attributed. KEY WORDS Law and New Technologies; Data Protection; Fundamental Rights; Personality Rights; Data Protection; Right to privacy; Right to honour; Right to image; General Data Protection Regulation (GDPR); Organic Law on Data Protection and Guarantee of Digital Rights (LOPDyGDD); COVID-19 (Coronavirus).