Reviewerly/exHarmony huggingface dataset:
Automatic Modulation Recognition Based on Multi-Channel Neural Network Model

Aiming at the problem of low accuracy of existing wireless communication blind recognition methods, a novel multi-channel deep learning framework based on the Convolutional Long Short-Term Memory Fully Connected Deep Neural Network (MC-CLDNN) is proposed. We fully combine the advantages of convolution neural network (CNN), gated recurrent unit (GRU) and deep neural network (DNN) in feature extraction ability to improve the efficiency of network training. Furthermore, to alleviate the problem of gradient disappearance in the network training and reduce the negative effect of pooling layer processes time series data on the subsequent sequence model, the skip connection is added to the network model. We verify the feasibility of the model based on opensource dataset RadioML2016.10a. The simulation results show that the proposed model can identify most modulation modes effectively, and has the characteristics of high recognition accuracy and strong generalization ability.
Digital Forensics: Evidence Analysis via Intelligent Systems and Practices DigForASP - CA17124. Challenges and Achievements: Plenary Talk

The Action COST DigForAsp is composed of more than 250 specialists and researchers from 36 countries, which is focused on searching for and consolidating of synergies in order to face the challenges in digital forensics, improve processes and obtain more efficient results, throughout the application of Artificial Intelligence and Automatic Reasoning tools. DigForASP aims to create one of the largest European intergovernmental networks for the coordination of European scientific and technical research in Digital Forensic, under the support of the European Cooperation Program in Science and Technology (COST), funded by the European Commission, which seeks to strengthen scientific and technical research in Europe by financing the establishment of collaborative networks between researchers. In this talk, the description of digital forensic and the specific goals of the Action will be presented. Moreover, we will also pay attention to current challenges and achievements.
Question Answering on Agricultural Knowledge Graph Based on Multi-label Text Classification

Traditional search engines retrieve relevant web pages based on keywords in the entered questions, while sometimes the required information may not be included in these keyword-based retrieved web pages. Compared to the search engines, the question answering system can provide more accurate answers. However, traditional question answering systems can only provide answers to users based on matching the questions in a question answering pair. At the same time, the number of question answering pairs remain somewhat limited. As a result, the user’s requirements cannot be met well. In contrast, knowledge graphs can store information such as entities and their relationships in a structured pattern. Therefore, the knowledge graph is highly scalable as the data is stored in a structured form. Besides, the relationship between entities and the knowledge graph structure allows the desired answer to be found quickly. Moreover, the process of relation classification can also be regarded as an operation of text classification. Therefore, this study proposed a new approach to knowledge graph-based question answering systems that require a named entity recognition method and a multi-label text classification method to search for the answers. The results of entity name and question type are turned into a Cypher query that searches for the answer in the knowledge graph. In this paper, three models, i.e., TextCNN, bi-LSTM, and bi-LSTM + Att, are used to examine the effectiveness of multi-label text classification, demonstrating our method’s feasibility. Among these three models, TextCNN worked best, attaining an F1 score of 0.88.
THE POSSIBILITIES OF INFORMATION SEARCH USING THE NAME AUTHORITY FILE OF RESEARCH AGRICULTURAL INSTITUTIONS

The experience of the Central Scientific Agricultural Library (CSAL) in organizing search and access to information using the database “Authority file: research institutions in agricultural field” of its own generation is presented. The possibilities of searching based on authority data in the format of a separate information resource and in the bibliographic database “AGROS” are described. It is noted that the authority file provides unification of data, identification of objects, access to bibliographic and full-text information, serves as a source of reference and historical information about institutions. The growing role of authority files in the web environment is emphasized.
On the semi-simplicity conjecture for $\mathbb{Q}^\mathrm{ab}$

We show that the semi-simplicity conjecture for finitely generated fields follows from the conjunction of the semi-simplicity conjecture for finite fields and for the maximal abelian extension of the field of rational numbers.
Carbon Footprint and Market Value of Cryptocurrencies and the Real Economy

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Using Fuzzy Cognitive Maps to Explore the Dynamic Impact of Megaproject Governance on Performance

Megaprojects are facing great challenges and traditional project governance theories are gradually showing inadaptability. The purpose of this study is to investigate the dynamic impact of megaproject governance and project performance using a dynamic approach based on a fuzzy cognitive map (FCM). From the existing governance review, six governance factors for megaprojects were identified: government coordination, government supervision, risk sharing, revenue distribution, relationship maintenance, and cultural development. Then the causal relationships and weights between megaproject governance and performance were established through a questionnaire survey of experts, thus the FCM model was constructed. Finally, the dynamic interactions between megaproject governance factors and performance were investigated through predictive analysis, diagnostic analysis, and sensitivity analysis. The findings indicate that (1) each of the six governance factors are positively correlated with project performance; (2) revenue distribution has the greatest positive impact on the project performance of megaprojects, which is also the fundamental factor for changes in project performance; and (3) the impact of governmental governance on project performance cannot be ignored during the implementation of megaproject management. This study contributes to (1) analyzing the key factors influencing project performance by exploring dynamic interactions between governance factors and performance, and ultimately promoting project success; and (2) providing new perspectives to improve performance and guide governance practices for megaprojects.
Proving the Stability of the Rolling Navigation

In this paper, we propose to study the stability of a navigation method that allows a robot to move in an unstructured environment without compass by measuring a scalar function ϕ which only depends on the position. The principle is to ask the robot to roll along an isovalue of ϕ . Using an interval method, we prove the stability of our closed loop system in the special case where ϕ is linear.
Mediating Effect of Nursing Work Environment in Nurses' Perception of Patient Safety Culture as well as Patient Safety Nursing Activities

The research was conducted to understand the considering nursing's mediation impact working environment in the effect of nurses' perception about improved sufferer&nbsp;nurse practices in smaller or middle hospitals. The data for this study were collected from 192 registered nurses with more than 6 months or experience working in four smaller or middle clinics inside the metro region of U from August 17, 2020 to August 31, 2020.&nbsp; The data analysis of this study was performed using IBM SPSS ver.21.0 program. Mean, the average deviation, percentage t-test or Multiple Linear regression, Pearson's Coefficient, or Correlation, ANOVA, Scheffé test, or Sobel test were used as data analysis methods to achieve the purpose of this study. As a result, patient safety nursing activity and the attitude of medication satisfaction were shown to be significantly positively correlated.&nbsp; Awareness and the setting for professional nursing and this were discovered that the clinical workplace partially mediates the relationship mindset of medication satisfaction perception and patient safety nursing activity.
Blockchain in Psychological Health: The Future of Medical Records

Purpose-Electronic health records (EHRs) have replaced paper medical records due to their convenience, safety, and ability to lessen data duplication.Poor interoperability and unsolved privacy concerns are still difficulties with EHRs, though.Blockchain, a distributed ledger protocol made up of encrypted blocks of data grouped in chains, could be used to address the interoperability and confidentiality issues plaguing EHRs.In this paper, we explain what electronic health records (EHRs) are and how blockchain technology works, and we offer a blockchain-based future that will improve EHR interoperability and privacy.Methodology-There was a total of 424 health care workers from hospitals in the Andhra Pradeshincluded in the study's quantitative analysis, which included descriptive statistics, a t test, and an analysis of variance.Findings-Efficient data management, equitable access, and reliable systems are all topics the study examines.To this aim, we propose the continued need for research in health informatics, data sciences, and ethics in order to implement blockchain-based EHRs.Social implications-Concerns around blockchain's carbon footprint, inequitable access to healthcare, and patient mistrust all need to be addressed in any blockchain-based EHR plan.Originality-With the advent of blockchain technology, the groundwork is being laid for a completely new approach to healthcare.This study contributes to the literature on the use of blockchain technology in future healthcare because there are currently too few case studies examining the intersection of blockchain and contemporary medical practice.
Web API service recommendation for Mashup creation

Mashup refers to a sort of web application developed by reusing or combining web API services, which are very popular software components for building distributed applications. As the number of open web APIs increases, to find suitable web APIs for Mashup creation, however, becomes a challenging issue. To address this issue, a number of web API service recommendation methods have been proposed. Content-based methods rely on the description of the service candidates and the user's request to make recommendations. Collaborative filtering-based methods use the invocation records of services generated by a set of users to make recommendations. There are also some studies employing both the description and invocation records of services to make recommendations. In this paper, we survey the state-of-the-art web API service recommendation methods, and discuss their characteristics and differences. We also present some possible future research directions in this paper.
Authentication Based on Periocular Biometrics and Skin Tone

Face images with masks have a major effect on the identification and authentication of people with masks covering key facial features such as noses and mouths. In this paper, we propose to use periocular region and skin tone for authenticating users with masked faces. We first extract the periocular region of faces with masks, then detect the skin tone for each face. We then train models using machine learning algorithms Random Forest, XGBoost, and Decision Trees using skin tone information and perform classification on two datasets. Experiment results show these models had good performance.
Digital education in nursing

The coronavirus pandemic caused unprecedented changes in all spheres of life. Education has completely shifted from the dominantly traditional to the digital framework. With that, nurse educators in higher education also started applying different models of innovative digital technologies. For example, the recreational escape room (ER) game, which has gained global popularity in the last decade, has inspired nurse educators to apply it in an educational setting. According to the definition, ER is a game in which a team of players discovers clues solves puzzles and performs tasks in one or more rooms to achieve a specific goal in a limited time, usually "room escape". In educational ER, all problems, challenges and activities are called a puzzle, while the term room means the space in which it is realized. Therefore, educational ER can be on-site and online. ER has found its place in the learning environment because it brings time-limited authentic situations from the natural professional environment. To successfully complete the mission and "escape from the room", students, in addition to engagement that encourages critical thinking, intensively communicate and cooperate with each other. This paper presents the application of online educational ER in the subject Fundamentals of Nursing.
A Study on Decentralized Electronic-Voting Using Blockchain

Since the 1970s, several types of E-voting, have been employed with a number of important advantages over current voting systems, E-voting increased efficiency and reduced errors. At the same time cost of regular voting system is very compare to e-voting based on block chain is very low the current Electronic voting machine have lot of flaws the vote can be change after the election. The security of the machine secured by humans, so in block chain based system doesn't allow you to change the value which is enter by peoples. But there are also obstacles to overcome of worldwide adoption of such systems, significantly in relation of strengthening their susceptibility to possible flaws. The Ethereum block chain's benefits, such as its transparency and decentralized nature, are discussed in this article. The use of cryptographic foundations to build a reliable E-voting system.
Analysis of Different Losses for Deep Learning Image Colorization

Image colorization aims to add color information to a grayscale image in a realistic way. Recent methods mostly rely on deep learning strategies. While learning to automatically colorize an image, one can define well-suited objective functions related to the desired color output. Some of them are based on a specific type of error between the predicted image and ground truth one, while other losses rely on the comparison of perceptual properties. But, is the choice of the objective function that crucial, i.e., does it play an important role in the results? In this chapter, we aim to answer this question by analyzing the impact of the loss function on the estimated colorization results. To that goal, we review the different losses and evaluation metrics that are used in the literature. We then train a baseline network with several of the reviewed objective functions, classic L1 and L2 losses, as well as more complex combinations such as Wasserstein GAN and VGG-based LPIPS loss. Quantitative results show that the models trained with VGG-based LPIPS provide overall slightly better results for most evaluation metrics. Qualitative results exhibit more vivid colors when trained with Wasserstein GAN plus the L2 loss or again with the VGG-based LPIPS. Finally, the convenience of quantitative user studies is also discussed to overcome the difficulty of properly assessing on colorized images, notably for the case of old archive photographs where no ground truth is available.
FEATURES OF PSYCHOLOGICAL READINESS FOR PROFESSIONAL ACTIVITIES IN STUDENTS AT DIFFERENT STAGES OF STUDY IN UNIVERSITY

At present, as a result of the expansion of the use of the development of information and computer technologies, the increase in the situation of uncertainty in various spheres of a person's life (social, economic, professional), the problem of the formation and development of future specialists, which is directly related to their readiness for professional activity, is becoming more and more urgent. The purpose of this study was to identify and analyze differences in the structure of psychological readiness for professional activity among students at different stages of study at a university. The study involved students of the Faculty of Law of The Herzen State Pedagogical University of Russia (St. Petersburg) in the amount of 107 people. To study the components of psychological readiness were used: the technique "Who am I?" M. Kuhn and T. McPartland (translated and adapted by T.V. Rumyantseva), S. Schwartz’s method for studying personality values, R. Cattell’s method of multifactorial personality research (187), method of studying professional identity statuses (A.A. Azbel, A.G. Gretsov) and the methodology for diagnosing the socio-psychological attitudes of the individual in the motivational-demand sphere of O.F. Potemkina. The following methods were used to process the data obtained in the study: descriptive statistics, comparative statistics (parametric statistical tests of Student's t-test and non-parametric statistical test of U-Mann Whitney). Mathematical data processing was carried out using the Statistica package (Version 10). The study found that students of the 1st and 4th courses have the most pronounced socio-psychological attitudes “Orientation to freedom”, “Orientation to the process” and “Orientation to the result”, statistically significant differences were found only in the indicator “Orientation to the result”. The subjects are characterized by a similar personality profile, and statistically significant differences between the samples were established only for the indicator G - moral normativity. In the student environment, values that reflect personal success are more important than the interests of the group. Statistically significant differences were found only in the "Conformity" indicator. In the study of the cognitive component, it was found that the largest number of self-descriptions refer to the personal identity of students of both courses, to personal qualities, character traits, to an individual style of behavior ( "Reflexive Self").
CONSIDERATIONS CONCERNING ICT SPECIALISTS IN EUROPE

Today we need more than basic skills to use a computer. Due also to the current pandemic situation we have a lot of on-line activities - starting from school, work, training, shopping, paying the bills, exercising, watching a movie and many others. Fortunately, the Internet is offering us the possibility to stay safe. That is why we need to obtain digital skills - information, communication, problem-solving, and software skills. For that, besides the infrastructure, we need specialists that will be able in the end to also teach the large population to properly use a computer. We have analyzed in this paper six indicators referring to individuals' level of digital skills, the ways to obtaining ICT skills, the number of employed ICT specialists, the education attainment level of those specialists, and their age. We did that with the help of the data from the Eurostat database. We selected for the graphical analysis 5 countries with different national cultures and different companies cultures, as identified with Hofstede's Model: Romania, Bulgaria, Poland, Germany, Finland, and we also use the composite index EU-27 for the remaining 27 countries in the European Union. Unfortunately, for the moment, the ICT specialists are representing only a maximum of 7% of the employed persons. For sure this percent will become higher because society needs to adapt to the new realities, the new and dangerous crises. The discrepancies between the urban and the rural population, and of course, between the rich and the poor will be more accentuated.
CHATBOT TECHNOLOGY FOR SUPPORT LEARNING ACTIVITIES IN THE COVID-19 PANDEMIC

Most countries in the world have experienced the shock of the first three months during the COVID-19 pandemic. Lockdown affected all economic realms, turned the usual mode of life upside down, taught everyone, without exception, to live in a new way. Surprisingly, many spheres of personal, social and professional life have not only been able to resist, but also to adapt to the new reality. It is fair to say that Higher Education (HE) has become one of those that the pandemic has had the greatest impact on a global scale. Moreover, HE has become one of those prepared to move most of its processes online. Due to the popularization and growth of the mobile device market, as well as the convenience of using modern messengers, communication between people has become easier. Distance learning presupposes fast and efficient information transfer and feedback. The use of chatbots these days is reflected in almost all spheres: from e-commerce to industry and education. In the study, we will highlight some important features in the chatbots use in the learning process, get acquainted with their applicativity in universities to identify the main advantages and disadvantages of their use, as well as to form general recommendations aimed at improving the effectiveness of their appliance in the learning process. Among other things, the article will consider the prospects and theoretical aspects of applicability and effectiveness of chatbots in the learning process, acting as a tool to improve the interaction between teachers and students in organizational and methodological issues. The purpose of the study is to assess the effectiveness of modern messengers and chatbots. The authors conclude that the chatbot is a useful tool in organizing the learning process, as well as interesting and convenient to use for both students and teachers. Besides, it caters to the needs of the younger generation who are gaining knowledge in the context of digitalization.
ART TEACHERS READY FOR THE AUGUMENTED REALITY?

Most of the people, at least in developed countries, have access to mobile learning devices. It seems, in the new nomadism, it is difficult to differentiate between workers and learners. Many of the mobile full-time workers are, also, part-time students studying at home or online. Many of the adult students in day-time courses are, also, mobile part-time workers. Technology is and will be used to provide attractive digital to the tablet and smartphone users. The new trend: the augmented reality. The Augmented Reality (AR) is a variation of the virtual media or of the virtual reality allowing the user to see the real world, with overlapping virtual objects or completed with real objects. The AR is an imagined layer overlapping the real world, visible by means of devices such as computers, smartphones, tablets, display glasses and other devices allowing the users to recognise these media which can consist of images, videos, and sounds. As the tablet and smartphone use spread, the augmented reality started being used more and more in every-day life, but also in the educational environment. Are the teachers ready, however? We hereby present, in the first part of this paper, a comparative study based on data obtained within the JOYAR project - Joyful adult training using augmented reality financed by the European Union, data revealing both the degree, and the level of involvement of adults in 6 countries in using new technologies for educational purposes, as well as a possible list of key-competencies required for successfully applying them. Furthermore, we present - in the second part - the advantages of integrating this technology in the teaching activity, but also practical classroom examples, rendering the lessons more animated and much easier to understand; The AR usefulness is limited only by our imagination