Reviewerly/exHarmony huggingface dataset:
DIGITALIZATION OF MONEY AND PROBABILITY OF CENTRAL BANK DIGITAL CURRENCY

Monetary transactions between closely related individuals are simple and have very low costs. However, the internationalization of transactions increases both the time and financial costs of money transfers. The speed and cost of transactions have become important in the transition from commodity money to cryptocurrency. The development of the internet and technology has accelerated the transformation of money. When we look at the development of money, commodity money, coins, banknotes, paper money, representative currencies and finally cryptocurrencies draw attention respectively. In the digital money (cryptocurrency) age, the central bank’s digitalization and issuing its own digital money is one of the issues discussed. Algorithmic digital currencies such as Bitcoin seem to be suitable competitors for central bank price currency and their presence in the market forces central banks to pursue tighter monetary policy. This study examines the transformation of money and the central bank’s stance on digital money. The study concludes that monetary authorities should not remain insensitive to the financial movements that have developed in digitalization. The issuance of their digital currencies by central banks will reduce the cost of delay and enable them to keep pace with the developing technological age.
Quantitative evaluation of stereoscopic augmented reality visualization using an optical see-through head-mounted display

Purpose The objectives of the current study were to propose a calibration method for accurate augmented reality visualisation using an optical see-through head-mounted display, and to qualitatively evaluate visualisation accuracy for the application in computer assisted surgery. Methods An adaptation of stereo single-point active alignment method was proposed as the calibration procedure together with verification Three tests were performed: display of points in 3D space, on the plane, and on the surface of a skull phantom on inexperience users ( 5 participants) and experienced users ( 17 participants). Results The highest accuracy of visualization was obtained for skull phantom visualisation for an inexperienced user (3.00 mm, std 0.75 mm), while the lowest accuracy was obtained in a 3D visualisation test for an inexperienced user (22.95 mm, std 18.04 mm). The largest error was related to the depth component and amounted to 18.49 mm, std 18.10 mm for an inexperienced user. Conclusions It is possible to achieve relatively high visualisation accuracy (less than 5 mm for visualisation in space) for selected users but providing it for the group of inexperienced users seems to remain a major challenge. The accuracy of point indication can be substantially and statistically significantly increased by visualising objects on surfaces. The proposed methods and obtained results can serve as a basis for further implementation of augmented reality visualisation on an optical see-through head-mounted display in applications requiring high-quality augmented reality guidance of manual tasks.
Peter I and his time in the educational projects of the MAE RAS, XXI century

Excursions and educational activities of the MAE RAS are inextricably linked with the history of the Kunstkamera, which was created by Peter I as a public museum, so that everyone, regardless of rank and title, could “come, watch and study”. In recent decades, the MAE RAS had been creating various cultural and educational projects for visitors, representing the figure of Peter the Great and his legacy. In the 1990s, MAE RAS participated in intermuseum projects dedicated to the events of the XVIII century. In the 2000–2010s, inspired by the era of Peter I, the staff of the Excursion Department developed weekend programs for children and families, created museum itineraries and quests. In recent years, the museum had held events related to the image of Peter the Great and the history of that time as part of citywide actions, collaborated with St. Petersburg educational institutions in the implementation of common educational projects. The era of Peter the Great has become an important topic which is covered in the museum’s social networks through various text materials, videos and interactive quizzes.
Preparation of masters in the perspective of the requirements of the professional standard

The problem points are reflected in the implementation of the master’s program in the direction of «Library and Information Activities» in connection with the adoption of the professional standard «Specialist in Library and Information Activities». An analysis of the requirements for education and training outlined in the professional standard, practical experience for positions in generalized labor functions assigned to the 7th level of qualification was carried out. The controversial provisions of the document requiring further discussion were considered. The master’s program implemented at the East Siberian State Institute of Culture (VSGIK) was described in the context of labor actions reflected in the professional standard. A qualitative description of students in the master’s degree is presented, the heterogeneity of the composition of groups and the associated problems of organizing the educational process are indicated. The content of library and bibliographic, research, psychological and pedagogical, management blocks, educational and production practices included in the curriculum is presented.
Gratitude in a scientific work as a tool of scientometrics

The work is devoted to one of the components of a scientific work – acknowledgements. The description of this component, various means of its expression, possible addressees are given. The purpose of this article is to describe how to include this data in the search criteria of automatic search engines, as well as the analytical capabilities associated with this component. The analysis of publications in the professional literature is conducted, where expressions of аcknowledgements are given by the authors of scientific works. The technical methods of including information about gratitude into the bibliographic record are described on the example of the ABIS «Ruslan» and «Irbis». It was revealed that acknowledgments are considered mainly to assess the sources of research funding. Critical remarks are given regarding the value and objectivity of using this element in this capacity. It has been established that the expression of gratitude given in a scientific work, primarily in a scientific article, is of great research importance. A promising way to use this component to identify informal connections between scientists is proposed.
Professional training of library specialists: problem of priorities

The article considers the main factors determining the content of library specialists training under the conditions of libraries transformation. The author tries to reveal the main factors determining this training including public life realities, demands of the society to libraries, state of culture police, existing traditions of library activity, peculiarities of its self-development as well as professional standards requirements. The article considers the viewpoints of the most competent representatives of professional library community on a library and reveals the acutest problems of personnel training for the dynamically developing libraries and contradictions between theorists and practical workers of library services. The author shows the results of the “Personnel Partnership Workshop” study which has revealed the key discontinuity between the training process participants and library practical workers.
Digital collection of the Presidential Library as a basis for studying the history of education in Russia

The role of state policy in the formation and development of the system of education and enlightenment in Russia is considered. The concept of «mentoring» acquired its modern meaning from the mid1960s, when it began to be widely introduced into the system of vocational education, becoming part of state policy. Formation of the image of a teacher-mentor is an urgent issue of modernizing the system of Russian education. To recognize the special status of teaching staff, including those performing mentoring activities, 2023 has been declared the Year of the Teacher and Mentor. The experience of the Presidential Library in the formation of the digital collection «History of Education in Russia», timed to coincide with this event, is presented. The purpose of the collection is to provide informational support to the state policy in the field of education and enlightenment, as well as a comprehensive presentation of documents and materials reflecting the history of the development of the education system in Russia. The creation of the collection is aimed at popularizing the Russian education system in society.
Historical and biographical research of the Russian National Library in strengthening the cultural sovereignty of country

The current stage of development of society is characterized by an increase in the influence of destabilizing factors alien to our mentality on the part of unfriendly states. On the part of the state in the field of culture, measures are being taken to overcome the negative consequences and strengthen the cultural sovereignty of Russia. Libraries and their historical and biographical research have a special role to play in addressing these issues. Multidimensional historical and biographical studies of the Russian National Library are considered. Priority directions for their implementation have been identified. The leadership of the Library in their implementation was noted, further ways of improving the methodology for conducting such studies were outlined, which would make a certain contribution to the preservation of traditional moral values and historical truth.
Hardware Implementation of Fuzzy Logic Systems

Principles of using analog circuitry for implementing basic fuzzy logic operations are considered. A set of developed hardware modules, where operations are executed on an analog representation of fuzzy variables is presented. Modules for converting information from digital to continuous form and vice versa are presented in order to link fuzzy system with sensors and executing circuitry, for example, in the control system of a process or an object. The components of such modules are described, along with their pros and cons. The use of circuits based on these principles seems essential for the development of fuzzy electronics.
Image Restoration from Weather Degraded Images Using Markov Random Field

Images often suffer degradation by foggy weather conditions. Scene recovery from such degraded images poses a significant challenge and is often a time-consuming task. Single image haze removal remains one of the most challenging tasks in image processing. Two of the most efficient method used for image recovery are dark channel prior and colour attenuation prior. Both these methods require an extra filter, such as a guided filter, for refining the estimated transmission map. This paper proposes a single image dehazing method that combines both dark channel prior and colour attenuation prior and uses the Markov random field for refining the transmission map, thus evading the use of any extra filter.
DESIGN OF A COMPUTER MOUSE FOR PEOPLE WITH SPECIAL NEEDS (DISABLED OR CUT OFF HANDS)

Industrial design takes it upon itself to innovate and develop products that contribute to providing appropriate solutions that can interfere with human uses in the various aspects of his life. To practice some activities like their healthy-bodied peers، including the computer, whether portable or desktop, and from which the need emerged to find appropriate solutions to these problems and obstacles for the disabled person to practice his work efficiently and comfortably. Therefore، the research problem emerged in how to find the appropriate solution according to the foundations and rules of design through a design in which those obstacles that confront a group of people who suffer as a result of their physical condition are addressed computer for that of class The importance of the design included several aspects، whether at the level of the external appearance or at the level of functional performance and increasing the effectiveness of the design through form and function. Also، the electronic materials and parts used in the production of the mouse are from the available materials, as it relies on the foam sponge material in the area for the support of the foot, and it also included the electronic parts of the control panel associated with each of its functional parts.
CRYPTOCURRENCY EXPANSION AND DEVELOPMENT: A COMPETITIVE MODERN BANKING INVESTMENT AND PAYMENT OPTION

Since the emergence of cryptocurrencies, their adoption by the population is increasing, that said, the appreciation of this product is more important in developed countries than in developing countries and even less, if at all, in underdeveloped countries. The degree of appreciation varies from the population to the authorities; each government treats it differently from the others. Cryptocurrency can be seen as an innovative, secure and spreading means of payment that impacts the economy and the social life of individuals. However, our research raises several questions about the development and emergence of cryptocurrencies, including the identification of the impact of cryptocurrency as a payment option on the economy and the banking sector. This article analyses the inclusion of cryptocurrencies in the global economy and its effect on payment issues for banks. To do this, we analyze the speed of development of cryptocurrencies and compare its use to traditional means of payment based mainly on statistics, reports of banks and financial institutions, Research results from renowned research centres. We are therefore expecting results in this direction
Aspect Category Detection of Mobile Edge Customer Reviews: A Distributed and Trustworthy Restaurant Recommendation System

Mobile Edge Computing (MEC) enhances social media customer reviews by providing real-time processing and analysis at the network edge. Social media platforms have revolutionized how users communicate their thoughts, ideas, and opinions on various issues, yielding a wealth of valuable data that can be used to get insights into people’s attitudes toward various items. This data is especially relevant for Aspect Category Detection (ACD), which is finding specific aspects or features that people discuss or mention concerning products. These systems are used in various organizations that operate on various platforms. However, current approaches frequently need to generate promising and accurate outcomes. Thus, this research presents an innovative strategy for detecting ACD in user reviews of restaurants using federated learning. The approach harnesses the power of a federated deep neural network for accurate classification. Various data preparation methods were employed to preprocess the data before model training to ensure the construction of a reliable dataset for classification. The proposed approach includes data cleaning, balancing, TF-IDF feature extraction, and model prediction using federated learning. The experimental results demonstrate that the proposed approach achieved an impressive accuracy of 88.38%, recommending the proposed approach for aspect category detection.
An Anonymity Retaining Framework for Multi-party Skyline Queries Based on Unique Tags

While finding out dominant objects over multiple competing parties' sensitive datasets via multi-party skyline queries (MSQs), upholding ample data privacy with integrity, data and data owners' ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> . <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</i> ., parties) anonymity, verifiable deeds of entities, the robustness of framework, etc., is crucial. The existing works consider these criteria trivially or partially and may sacrifice data integrity due to malleable cipher data. This paper proposes a framework for MSQs that incorporates these requirements together and eventually makes a ranking of parties' data-objects. To enrich data privacy, it allocates separate decryption keys among mutual entities. To confirm data integrity, it unites encrypted unique tags ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">UT</i> s) to parties' encrypted datasets individually. To assure data and parties' anonymity, it re-encrypts and shuffles encrypted datasets, and uses anonymous credentials, respectively. These qualities and publicly exposed data reinforce the framework and assure the correct deeds of entities. Finally, evaluation results, analyses, comparisons with state-of-the-art works, etc., prove the efficacy of the proposed framework.
Blind Universal Denoising for Radar Micro-Doppler Spectrograms Using Identical Dual Learning and Reciprocal Adversarial Training

In practice, radar measurements are hindered by unavoidable noise, which lowers the signal-to-noise ratio (SNR) and raises the problem of radar signal denoising. Thanks to the development of deep learning techniques, recently proposed denoisers are progressively capable of blind denoising. On the other hand, due to the great fitting capacity of deep neural networks, the deep-learning-based denoising model would prefer to overfit on the training set, hence diminishing the generalization of a denoiser and impeding its use in a broader situation. This article focuses on this “blind universal denoising” problem for the first time and introduces a novel generative-adversarial-network-based (GAN-based) denoiser for radar spectrograms. The core idea of the proposed model lies in minimizing the generalization error during the model’s training, and to this end, our model incorporates a proposed identical dual learning (IDL) scheme and a reciprocal adversarial training (RAT) strategy to avoid the overfitting risk in the denoiser’s training. We perform the radar simulation using a motion capture database, and verify our model’s effectiveness under three different setups of training and testing datasets. For each setup, the noise level in the training and testing sets is configured to be different so to simulate the unknown measurement situations. Eleven algorithms are selected as comparisons, and the experimental results on two criteria illustrate that our method outperforms the others with a significant improvement.
Kullback-Leibler Divergence Based Regularized Normalization for Low Resource Tasks

Large pretrained models like Bert, GPT, and Wav2Vec have demonstrated their ability to learn transferable representations for various downstream tasks. However, obtaining a substantial amount of supervised data remains a challenge due to resource and time limitations. As a solution, researchers have turned their attention to using large pretrained datasets via techniques like fine-tuning, linear probing, or prompt tuning in low resource settings. Normalization techniques play a crucial role in speeding up training, style transfer, object detection, recurrent neural networks and improving the generalization of deep neural networks. Despite their success in various domains, their effectiveness in low resource NLP and speech tasks has been limited. A notable reason for this limitation is the difficulty in capturing expressiveness using affine parameters of normalization. To address this issue, we propose a novel approach called Kullback-Leibler (KL) Regularized normalization, or KL-Norm. The main objective of KL-Norm is to ensure that normalized data is well-behaved and to improve generalization by reducing overfitting by including a regularization loss function in the training process. It achieves this by promoting good performance on out-of-domain distributions and effectively filters relevant features while eliminating superficial features or biases present in the dataset or pretrained model. Remarkably, KL-Norm accomplishes these objectives with minimal increase in model parameters and memory overheads. Through extensive experimental analysis, we showcase the improved accuracy and performance of KL-Norm in comparison to other normalization techniques on low resource downstream NLP tasks. These tasks encompass a wide range of applications, including sentiment classification, semantic relationship characterization, semantic textual similarity, textual entailment, and paraphrase detection. Additionally, KL-Norm exhibits superior results in downstream speech tasks, specifically in keyword detection and emotion classification.
An Analysis of Students’ Lexical Choice in Writing Descriptive Text

Writing is become the one of difficult skill to learn especially in EFL context. Students have problems when formulating words while doing writing assignments. This very important to investigate student problem while do writing especially on lexical choice that student utilize in writing descriptive. The corpus can also be used for examines sentence writing structure and word selection that can be seen and synchronized very effectively. The importance of this research is to be able to know the capacity of students when doing writing task and how their writing product can be better. it can be ascertained that from student writing samples that have been analyzed, there are 10.2% high frequency, 2.5% mid frequency, and 87.3% low frequency. This identifies that in writing students still tend to use familiar words to make a sentence. Based on the aspects of discovery that have been mentioned, students' ability to write still needs to be improved again, especially in the selection of several adjectives and pronouns.
GAME-BASED ARABIC LEARNING AT MAN 2 BUKITTINGGI: BEST PRACTICE / BEST PRACTICE: PEMBELAJARAN BAHASA ARAB BERBASIS PERMAINAN DI MAN 2 BUKITTINGGI

The research aims to explore the implementation of game-based learning to improve Arabic achievement of students at MAN 2 Bukittinggi. This was a descriptive qualitative research. Data were collected by doing observation and test. Game-based Arabic learning was implemented to 30 students of grade X of IPA 3 at MAN 2 Bukittinggi. Results showed that the procedures of game-based Arabic learning are: determine basic competence and indicators; motivate students, inform the learning purpose; prepare games based on themes; explain the game manual; demonstrate the game in front of the class; explain the learning materials; give chances to students to join the game; ask students to do tasks; correct students’ answers; give feedback and clarification about the learning process; and give reward to the active students. By applying the game-based Arabic learning, more than 75% students got high scores (above KKM). The game-based Arabic learning encourages the improvement of students’ thinking skills, attract students’ interest and motivation to learn, and also overcome boredom in learning. However, on the other side, applying game-based learning makes the class noisy and it is quite difficult to control the students’ activity.