Reviewerly/exHarmony huggingface dataset:
Digitalization of Project Activities in the Management System of an Educational Organization

When studying the theoretical foundations of the transformation of the management system of an educational organization, the management system is understood as scientifically based actions on the part of the administration and the teaching staff of the organization, which are aimed at the rational use of available forces, time and material resources, in order to implement an effective pedagogical process within a specific educational organization. As practice shows, most educational organizations are characterized by a linear-functional organizational structure, as a result of which the management system is not mobile, it does not allow taking into account the peculiarities of the human capital of the teaching staff, weakly forms the interest of each member of the team in the final result. The article considers one of the most effective management tools in conditions when an educational organization faces the task of increasing its efficiency and effectiveness with limited resources – project management. Its implementation in the conditions of digitalization will allow educational organizations to carry out more effective strategic interaction, due to the formation of a network contact. The aim of the study is to improve the management system in a secondary school. To solve the tasks set in the work, the following research methods are used: theoretical methods – analysis and generalization of pedagogical, managerial, methodological and scientific-theoretical literature; normative documents regulating the management of an educational organization; teaching aids on the following aspects: management system, digital transformation of education, management of an educational organization, project management. In the course of our work, we came to the conclusion that the process of managing an educational organization in modern times is prone to a trend that manifests itself in a widespread, global transformation of the management system of an educational organization. One of the features of the management of the educational system is the departure from traditional forms of organizational structure, the restructuring of structures in accordance with the requirements of high efficiency in solving issues, the creation of conditions for participation in decision-making by all members of the workforce. Thus, project management is one of the most effective management tools in conditions when an educational organization faces the task of increasing its efficiency and effectiveness with limited resources.
THE ESSENCE AND CONCEPT OF PERSONALITY SELF-REGULATION IN PSYCHOLOGICAL SCIENCE

This article presents the result of a theoretical study of the essence and concept of personality self-regulation in psychological science. The relevance of the problem under consideration is shown, the modern understanding of the essence and concept of personality self-regulation is revealed, its main structural components are highlighted.
Federated Learning and Blockchain-enabled Fog-IoT Platform for Wearables in Predictive Healthcare

Over the years, the popularity and usage of wearable Internet of Things (IoT) devices in several healthcare services are increased. Among the services that benefit from the usage of such devices is predictive analysis, which can improve early diagnosis in e-health. However, due to the limitations of wearable IoT devices, challenges in data privacy, service integrity, and network structure adaptability arose. To address these concerns, we propose a platform using federated learning and private blockchain technology within a fog-IoT network. These technologies have privacy-preserving features securing data within the network. We utilized the fog-IoT network's distributive structure to create an adaptive network for wearable IoT devices. We designed a testbed to examine the proposed platform's ability to preserve the integrity of a classifier. According to experimental results, the introduced implementation can effectively preserve a patient's privacy and a predictive service's integrity. We further investigated the contributions of other technologies to the security and adaptability of the IoT network. Overall, we proved the feasibility of our platform in addressing significant security and privacy challenges of wearable IoT devices in predictive healthcare through analysis, simulation, and experimentation.
Surrogate Methods Applied to Hyperparameter Optimization Problem

Hyperparameters affects the performance of machine learning models. Hyperparameter optimization is an area that aims to find the best of them, but it deals with a considerable number of machine learning training, which can be slow. Thus, surrogates can be used to soften this slow process. This paper evaluates the performance of two surrogate methods, M1 and MARSAOP, applied to hyperparameter optimization. The surrogates are confronted with six hyperparameter optimization algorithms from the literature for classification and regression problems. Results indicate that the surrogate methods are faster than the traditional algorithms.
Basics of information security culture in the organization

The mass application of information and communication technologies (ICT) has facilitated the functioning of organizations, but has also increased their vulnerability and conditioned the development of the information security function. Attacks on ICT systems involve people as potential targets of vulnerability, highlighting the importance of paying close attention to an employee's behavior in interactions with elements of the ICT system and its environment, as well as developing an information security culture (ISC) as an integrative component of organizational culture and an important factor in the organization's information security. The paper attempts to set a comprehensive concept of ISC based on the unity of knowledge, perceptions, beliefs and attitudes of employees and their coordinated actions in the application of security measures, which emphasize the role of the organization and its management in creating, building and maintaining ISC. The focus of determining ISC is on understanding and applying information security policy measures, but it also includes the behavior of employees in situations that are not or could not be predicted, when employees are expected to protect the information assets of the organization. The paper identifies the most important external factors that are mostly objective, determined by the situation in the country in which the organization operates and contained in the elements of general social (national) culture and country's economic and technological development. As a specific impact on ISC, the activities of malicious individuals, groups and organizations in cyberspace - stand out, manifested through threats and endangerment to the integrity of the ICT system. Internal factors are mostly subjective and dependent on general organization; the knowledge, vision and actions of management in the field of information security; individual characteristics of people, their values, needs, knowledge, understanding and application of information security policy measures. Among the factors, the highest level of management stands out for its role and importance due to the greatest responsibility for organization's information security, but also as the creator of its strategy and policy, the holder of resource engagement policy, shaper of professional security teams, decisionmaker on hardware and software protection, and supporter, creator and implementer of programs for ISC level raising.
TYPES OF POLITENESS STRATEGIES AND DEGREES OF POLITENESS PERFORMED BY ENGLISH MAJOR STUDENTS IN REQUESTING FOR HELP

In social interaction, people need to pay attention to the face of others to maintain relationships and avoid losing their faces. To do this, people should use politeness strategies in communication. This study aims to investigate which type of politeness strategies are mostly used and the level of politeness shown by English major students in the High Quality Program in requesting help. This study is based on the theory of Brown and Levinson (1987). Based on the analysis of the data obtained from the questionnaire, negative politeness strategies were applied the most. This also performs a high degree of politeness. It shows that students majoring in English studies (High Quality Program) had an awareness of using politeness strategies in requesting help.&amp;lt;p&amp;gt; &amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;strong&amp;gt; Article visualizations:&amp;lt;/strong&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;img src="/-counters-/edu_01/0704/a.php" alt="Hit counter" /&amp;gt;&amp;lt;/p&amp;gt;
LiteLSTM Architecture Based on Weights Sharing for Recurrent Neural Networks

Long short-term memory (LSTM) is one of the robust recurrent neural network architectures for learning sequential data. However, it requires considerable computational power to learn and implement both software and hardware aspects. This paper proposed a novel LiteLSTM architecture based on reducing the LSTM computation components via the weights sharing concept to reduce the overall architecture computation cost and maintain the architecture performance. The proposed LiteLSTM can be significant for processing large data where time-consuming is crucial while hardware resources are limited, such as the security of IoT devices and medical data processing. The proposed model was evaluated and tested empirically on three different datasets from the computer vision, cybersecurity, speech emotion recognition domains. The proposed LiteLSTM has comparable accuracy to the other state-of-the-art recurrent architecture while using a smaller computation budget.
Participatory Design of External HMI Based on Explicit Human-Vehicle Interaction Features

In order to explore the design strategy of participatory design approach in the design of external human-machine interface (eHMI), this paper at the theoretical level researches the relevant literature and typical interfaces of eHMIs, and sorts out the basic concepts of explicit human-vehicle interaction features theory. Through the user participatory design method, we summarized the key design points of the eHMI and produced a design prototype, and optimized the prototype according to the participatory design experimental results and actual needs to obtain a design solution. The design was tested and evaluated at the practical level, and a strategy for user participation in the design of the external human-machine interface was concluded. The results show that the participatory design approach can improve the usability and acceptance of eHMIs, reduce the cognitive differences in the presentation of interface content, and provide a reference for the design of out-of-vehicle HCI in future work.
Customized Generation and Creative Practice of Asian Games Kinetic Sports Pictograms in Game Engine

Kinetic pictograms are more effective in communication and easier to attract attention compared to static pictograms. The kinetic sports pictograms of the 19th Asian Games continues the visual identity of the Games, showing the beauty of the flowing lines while also enhancing the overall publicity effect of the Asian Games visual design. Starting from the technical selection, this paper explains the process of creating and practicing the Customized Generation of kinetic sports pictograms in the game engine through the difficult breakthroughs in action design, graphic personalization and spatial deformation, combining the laws of sports. Thus, it also provides some reference and thinking for the expansion and innovative practice of game engines in different creative application scenarios.
Gender equality in library science and book history Italian journals: a focus on boards, authors and peer-reviewers

The presence of women in Italian open access journals in library science and book history has never been subject to quantitative evaluations. As in the case of other areas in the humanities, the study of the number of women on the boards and as authors has taken second place to analyses of gender positioning in academic careers. Starting from the data entered into Wikidata by the project "Riviste di biblioteconomia" managed by the Wikidata Group for Museums, Archives and Libraries, the contribution presents a focus on AIB Studi, Bibliothecae.it and JLIS.it regarding the gender balance in the scientific committees and board and the number of female contributors. In conclusion, a mention concerns the small number of articles from foreign countries, in particular from Africa and South-East Asia.
Selection of an Efficient Classification Algorithm for Ambient Assisted Living: Supportive Care for Elderly People

Ambient Assisted Living (AAL) is a medical surveillance system comprised of connected devices, healthcare sensor systems, wireless communications, computer hardware, and software implementations. AAL could be used for an extensive variety of purposes, comprising preventing, healing, as well as improving the health and wellness of elderly individuals. AAL intends to ensure the wellbeing of elderly persons while also spanning the number of years seniors can remain independent in their preferred surroundings. It also decreases the quantity of family caregivers by giving patients control over their health situations. To avert huge costs as well as possible adverse effects on standard of living, classifiers must be used to distinguish between adopters as well as nonadopters of such innovations. With the development of numerous classification algorithms, selecting the best classifier became a vital and challenging step in technology acceptance. Decision makers must consider several criteria from different domains when selecting the best classifier. Furthermore, it is critical to define the best multicriteria decision-making strategy for modelling technology acceptance. Considering the foregoing, this research reports the incorporation of the multicriteria decision-making (MCDM) method which is founded on the fuzzy method for order of preference by similarity to ideal solution (TOPSIS) to identify the top classifier for continuing toward supporting AAL implementation research. The results indicate that the classification algorithm KNN is the preferred technique among the collection of different classification algorithms for the ambient assisted living system.
Evaluating the Optimal Self-Checking Carry Propagate Adder for Cryptographic Processor

With the increasing number of invasive attacks, cryptographic processors are becoming more susceptible to failure. Therefore, the desire for reliable hardware is becoming increasingly important. Since an adder is a vital component in the hardware design of cryptographic protocols, a reliable adder can significantly improve the vulnerability against invasive attacks. Adders with different architectures have already been widely studied and analyzed and appropriate types have been proposed based on the application. This paper considers the design of adder most suitable for reliable cryptographic operation and investigates the optimal self-checking carry propagate adder design offering the best possible performance in terms of latency, delay, and area. In terms of area versus delay, the self-checking parallel ripple carry adder (PRCA) with 23.4% area overhead as compared to the self-checking ripple carry adder (RCA) provides a delay efficiency of 70.31%. However, the area-delay product for 64-bit self-checking designs showed that the hybrid adder is 71.2%, 21.4%, and 37.9% more efficient than the RCA, PRCA and carry look-ahead adder design, respectively.
Green Cloud Computing- Next Step Towards Eco-friendly Work Stations

Cloud computing is a solution to various computational problems by offering different services through the internet making use of various resources. IT industry always face energy consumption and carbon emission problems. Datacenters play crucial role as a support in cloud computing. That's why the urge to open more and more datacenters is increasing day by day. As a result of the higher power usage at data centers, this boosts the economic and environmental costs. Furthermore, the increased release of CO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> and other gases has resulted in an increase in carbon footprint and, as a result, the greenhouse effect. These are the forces that propel green computing technology forward. A brief introduction of cloud computing, related relevant researches and various approaches to use green computing is provided in this paper. Measurement, modelling and prediction of consumed energy by different organizations is necessary to maintain the environmental balance by reducing carbon emission as well as to make sure to avail the presently available energy resources for our upcoming future generations. The elaboration of several research issues in implementing green computing as well as their solutions is discussed in this paper.
‘Jigsaw fit’ analysis: The key to solving difficult forensic cases

This paper presents ‘jigsaw fit’ analysis, which is an aspect of mechanoscopy (tool mark examination) helpful in solving difficult forensic cases. Its use can lead to categorical conclusions in the reconstruction of the course of an incident. Examinations of this kind entail the matching of items separated due to breakage, fracture or tearing. The task of an expert in this field is to resolve the question of whether or not the items belonged together before they were separated. This paper describes three examples of cases involving ‘jigsaw fits’.
Evaluation of spoken English self-study system considering speech knowledge recognition algorithm

Abstract This paper builds and evaluates a self-learning system for spoken English pronunciation suitable for PC mobile terminal or mobile terminal users, and the core technology of speech recognition is built on Hidden Markov Model (HMM), which is used to decode the speech signal in spoken English learning. This paper studies the related speech recognition theory and signal processing technology, builds a comprehensive English self-learning system in more complex situations and more user types and conducts a comprehensive evaluation of the system. The results show that the overall accuracy of the HMM model in the spoken English recognition and evaluation system built in this paper is good, and the accuracy of the input audio for people of all ages is greater than 90%. In the younger population, the accuracy of male speech signals was the highest in both closed space and open space, reaching 98.12% and 96.53%, respectively. In addition, it is observed that the accuracy gradually decreases as more wrong judgements are made on the speech input signal. When the evaluation is poor, the accuracy of the scoring results decreases to 55%, and when there are fewer voice judgement errors, it is in the excellent range, where the accuracy reached 88%.
Transformações dos Pacotes de Informação na Cadeia de Custódia Digital Arquivística

This study synthesizes knowledge about the transformations of the information package of the Open Archival Information System (OAIS)model, within the scope of aChain of Custody for Digital Archives (CCDA). Thus, the importance of the file system being composed of management, preservation and access platforms is discussed. The methodology is based on a survey of previously published materials, including: books, technical publications and articles from scientific journals. The analysis of the collected data consists of a triangulation between Archival Science, the OAIS model and the CCDA. The discussion uses deductive logics, which results in an unsystematic review article. Finally, it is argued that establishing a CCDA will allow the transformations of the OAIS information package to be carried out by a reliable custodian capable of ensuring the maintenance of the authenticity and the preservation of digital archival records in the long term.
Exploring Patterns and Correlations Between Cryptocurrencies and Forecasting Crypto Prices Using Influential Tweets

The Crypto market, as we know, is a market full of various kinds of investors and influencers. We all know the pizza incident in 2010 where a guy purchased two pizzas at 10000 BTC, which ranges nearly around 80 million in current times. That describes how much the market has progressed in these 10–12 years. You can see drastic changes in the price of several coins in the past few years, which brings in many new investors to invest their money in this market. Crypto Market has highly volatile currencies. Bitcoin was around 5K INR in 2013, and by year 2021, it reached 48 Lakhs INR, which shows how volatile the market is. The dataset provides many fascinating and valuable insights that help us gather practical knowledge. As data scientists, we are very keen to understand such a market whose data is unstable and keeps changing frequently and making out new patterns with time. This introduction of new patterns with time makes this problem an interesting one and keeps on motivating us to find some valuable information. So, through this manuscript, we tried to analyze two specific crypto coins for a particular period, including more than 2900 records. We found several interesting patterns in the dataset and explored the historical return using several statistical models. We plotted the opening and closing prices of the particular coin by using NumPy, SciPy, and Matplotlib. We also tried to make predictions of the cost of the specific currency and then plot the predicted price line with the actual price line and understand the difference in the prediction model with the fundamental price mode. To do so, we used the Simple Exponential Smoothing (SES) model and performed sentiment analysis based on influencing tweets on Twitter. That makes our prediction more accurate and more reliable than existing techniques. Lastly, we used a linear regression model to establish the relationship between the returns of Ripple and Bitcoin.
Scalable Cryptography

Abstract In our modern digital society, cryptography is vital to protect the secrecy and integrity of transmitted and stored information. Settings like digital commerce, electronic banking, or simply private email communication already rely on encryption and signature schemes. However, today’s cryptographic schemes do not scale well, and thus are not suited for the increasingly large sets of data they are used on. For instance, the security guarantees currently known for RSA encryption—one of the most commonly used type of public-key encryption scheme—degrade linearly in the number of users and ciphertexts. Hence, larger settings (such as cloud computing, or simply the scenario of encrypting all existing email traffic) may enable new and more efficient attacks. To maintain a reasonable level of security in larger scenarios, RSA keylengths must be chosen significantly larger, and the scheme becomes very inefficient. Besides, a switch in RSA keylengths requires an update of the whole public key infrastructure, an impossibility in truly large scenarios. Even worse, when the scenario grows beyond an initially anticipated size, we may lose all security guarantees. This problematic is the motivation for our project “Scalable Cryptography”, which aims at offering a toolbox of cryptographic schemes that are suitable for huge sets of data. In this overview, we summarize the approach, and the main findings of our project. We give a number of settings in which it is possible to indeed provide scalable cryptographic building blocks. For instance, we survey our work on the construction of scalable public-key encryption schemes (a central cryptographic building block that helps secure communication), but also briefly mention other settings such as “reconfigurable cryptography”. We also provide first results on scalable quantum-resistant cryptography, i.e., scalable cryptographic schemes that remain secure even in the presence of a quantum computer.