Reviewerly/exHarmony huggingface dataset:
Should Influencers be Trusted? Analysis of Influencers’ Interaction with Children and Adolescents on Instagram and Youtube

Children and adolescents (in study it refers to age group 11 till 17) nowadays spend many hours online on social media following their favorite influencers. Children and adolescents are avid consumers of social media and constitute attractive target audiences for influencer marketing. Studies show that sponsored content from favorite social media influencers appears to be highly influential and may affect brand preferences of given audiences. Furthermore, influencer endorsements are observed to carry greater credibility and authenticity than traditional forms of advertising. This therefore raises questions about young consumers’ discernment of, and critical evaluation of the overall appropriateness when influencers act as conduits of commercial messages. The influencer interaction with young audiences in Latvian social media landscape still needs to be mapped. This paper reports on a quantitative study of the influencer communication on two social media – YouTube and Instagram. A total of 459 YouTube videos and 654 Instagram posts in time period from 01.01.2021 to 01.01.2022 were selected for analysis. The aim is to acquire knowledge on how influencers communicate with their young audiences, and do they use appropriate advertising disclosures when communicating commercial information, which is a requirement of Latvian legislation. This information is crucial for further discussion on advertising literacy of young audiences as well as legal regulation of influencer marketing. The research finds that influencers in most part do not properly mark the sponsored content. Thus, influencers both do not comply with the regulatory framework, and deny their young audience the tools to employ advertising skills.
Automatic Modulation Classification Based on Knowledge Graph

Recently, traditional methods and artificial intelligence methods have been applied to Information and Communication in various scenarios. As the benchmark of next-generation artificial intelligence, knowledge graph has also made achievements in the field of data mining and reasoning. In this paper, we hope to apply the knowledge graph to Automatic Modulation Classification (AMC), so as to better build the knowledge base of Modulation Mode under the Communication background and make a more effective and interpretable classification prediction of Modulation Mode.
Development of Teaching Materials for Fable Texts Assisted by Animated Films for Class VII Students of SMP Swasta Katolik Assisi Medan T.P 2021/2022

Teaching materials are all forms of tools used to assist teachers in carrying out teaching and learning activities.The teaching materials used by teachers will affect the achievement of students in achieving learning objectives.This study aims to produce teaching materials for modules assisted by animated films in fabled text learning in grade VII students of SMP Swasta Katolik Assisi Medan.Data analysis through questionnaires shows that students still depend on books produced by Kemendikbud with material content that has not been adapted to the local area of students and the teaching materials used are less innovative, creative and contemporary.The use of animated films can help visualize abstract material in an interesting way This is evidenced by the effectiveness test using the Gain Test on the animated film-assisted fable text module with an average pretest score of 60.94 students with the lowest score of 45 and the highest score of 70.Meanwhile, the average posttest score of students was 83.44 with the lowest score of 75 and the highest score of 95.Based on these data, it can be concluded that the fable story text module assisted by animated films is feasible and effective for use in learning to improve student learning outcomes, especially in fable text materials.
Application of intelligent teaching resource organisation model and construction of performance evaluation model

Abstract In the construction of intelligent teaching resources, a large number of resources are collected to meet the teaching needs, and its organisational structure, resource content and teaching quality are not fully recognised. At present, there are few studies on the performance evaluation of intelligent teaching, and the research angles are also different. Based on this, this paper constructs the application performance evaluation model of intelligent teaching resource organisation mode. Based on the simple analysis of intelligent teaching research and the development of big data mining algorithm, this paper uses data mining algorithm to realise resource mining, uses ant colony algorithm and association rules to mine information, carries out student evaluation on this basis, and uses ID3 algorithm to construct decision tree to analyse the main factors affecting teaching. Then the performance evaluation model is built, and the concept of fuzzy mathematics is introduced to realise the comprehensive evaluation based on analytic hierarchy process. Finally, simulation tests and experiments are used to analyse the effectiveness of the algorithm and the application of the model. The results show that the data mining algorithm based on association rules can mine more information and shorten the running time. The performance evaluation model based on fuzzy comprehensive evaluation can be applied to the evaluation of intelligent teaching, find the shortcomings in teaching, and confirm the effectiveness of the model.
De-anonymizing Online Social Network with Conditional Generative Adversarial Network

Nowadays, Online Social Network (OSN) private information leakage raises concerns. Studying the problem from both attackers' and defenders' perspectives provides valuable insights to researchers. Several novel anonymization mechanisms have been proposed, yet the innovation of de-anonymization mechanisms struggles with the complexity of graph structures and the difficulty of finding the global optimal mapping strategy. While existing de-anonymization mechanisms collect information by mapping users from the adversary's background knowledge to published data, this paper applies an inference attack based on the background knowledge and the published information. The high-level idea is learning graph properties from the published information to compensate the target area. In particular, the Generative Adversarial Network (GAN) ensures the generated graph is similar to the published data. The adversaries' background knowledge is embedded as conditional information into the GAN. Since the knowledge is embedded into the generated data through the deep learning models, it is hard to defend the proposed attacks. The evaluation of real-world OSN datasets proves that the proposed scheme de-anonymizes the edge information with high accuracy. Moreover, it also enhances the performance of existing user de-anonymization schemes.
PATCHWORK AS A TYPE OF APCYCLING IN THE CREATIVE WORKS OF STUDENTS

International scientific conference «Interaction between science and technology in modern conditions» : conference proceedings (November 3–4, 2022. Riga, the Republic of Latvia). Riga, Latvia : “Baltija Publishing”, 2022. 128 pages.
DISTANCE LEARNING AS ONE OF THE INNOVATIVE DIRECTIONS OF EDUCATION DEVELOPMENT

The need for digital transformation of Russian education presupposes the development of new, including online teaching methods, information and digital interactive technologies and means of communication. The purpose of the article is to summarize the experience of remote conducting of all types of classes in the discipline "Physics". The analysis of such experience and the results of testing various teaching methods and interactive technologies contributes to the identification of optimal methods of conducting classes of various types online and technical solutions for their implementation. The article provides systematic information on the organization of distance learning in the discipline "Physics" at the Don State Technical University; specific recommendations are given on the methodology of conducting all types of classes and the organization of control over the assimilation of material by students.
Adjust: An Online Resource Adjustment Framework for Microservice Programs

The categories of programs running in data centers are changing from the traditional monolithic program to loosely coupled microservice programs. Microservice programs are easy to update and can facilitate software heterogeneity. However, microservice programs have more stringent performance requirements. Estimating the resource requirements of each service becomes the key point to ensuring the QoS of the microservice programs. In this paper, we propose a QoS-aware framework Adjust for microservice programs. Adjust establishes a neural network-based microservice QoS prediction model. Moreover, Adjust identifies the causes of the abnormality of microservice programs, and determines performance assurance strategies on both system and microservice levels. By dynamically adjusting the resource allocation, Adjust can effectively guarantee the performance of microservice programs and improves system resource utilization at the same time.
Tools used in the Life Cycle of Data Science and their Features

Automated street lightning is advantageous to society as it decreases the rate of accidents, vandalism and street crimes. The ability to detect vehicles and smartly manage the street light system is among the major duties of electrical distribution companies. To recognize an objects of interest in an image by a classical technique called object detection. In order to recover the enactment and reduce the complexity of object detection, numerous computer vision methods have been proposed over the past decade years. Object detection has a wide variety of applications including vehicle detection especially in remote sensing applications. Vigorous and accurate detection of vehicles for such solicitations is a moderately stimulating problem because of discrepancy of color, size, aspect ratio and alignment of vehicles and complex backgrounds of satellite images. Nevertheless, the modern deep learning-based object detection frameworks and convolutional neural networks have great potential for improving the performance of vehicle detection methods in terms of exactness, sturdiness and detection time. This paper will review both As a result of digitization, data sets are fast expanding in various ways. When there are enormous amounts of data or information groups that are complicated in nature, typical data processing methods are unable to handle them. Researchers, scientists, businesses, government entities, advertising companies, and medical researchers all face more challenges when collecting and analyzing for decision-making. The data that is accessible for research must be analyzed utilizing a variety of data analytics methods. These solutions aid in dealing with large volumes of unstructured, organized, or semi-structured data material that is constantly changing and impossible to process using traditional database management tools. This paper goes over the most common uses of data analysis tools, as well as their characteristics towards data validation. This paper presents a review and analysis of various existing ways to supporting data analysis tools for users, with a focus on identifying critical qualities. Weaknesses, opportunities, and uses will be examined in future research.
Preface: International Conference on Advances in Multi-Disciplinary Sciences and Engineering Research: ICAMSER-2021

First Page
Research on Association Rules Data Mining Based on Improved K-means Algorithm

The process of data mining is essentially the process of finding value in huge and random data. With the development of the times, information technology has continuously entered various fields, which has greatly expanded the amount and types of data that can be used for mining. In data mining, association rules are the association relationships between data. By grasping the association rules between massive data, users can have a special understanding of the data to assist judgment. This paper improves the K-means algorithm based on the three selected test indicators, eliminates redundant rules through certain criteria, obtains the initial point through triangle iteration under the K-means rule, and clusters the rules. Through the research in this paper, it can be confirmed that the aggregation of similar rules can help data analysts quickly obtain useful rules and help the further advancement of the analysis process.
THE PECULIARITIES OF RELIABILITY ASSESSMENT OF INTERNET VIDEO MATERIALS IN A PROFESSIONAL ACTIVITY OF HISTORY TEACHER

The article deals with the specifics of the use of video materials as an additional information source by the teacher in history lessons. The textbook ceases to be a single source of scientific knowledge about the history of our state and the world in general. Ukrainian teachers and pupils are increasingly using the Internet as a powerful source of informational, methodological resources to obtain new data that haven’t been represented in school textbooks yet. On the Internet, they are looking for various materials (text, video, graphic information), which must be accurate, reliable, and verified. Among different types of information posted on the Internet checking videos for veracity is the most challenging task. Anyone with the lowest level of awareness may change the video by means of user-friendly programs.In the 21st century, most people, unlike previous generations, have mobile devices and are provided with photo and video cameras, a microphone, and access to the Internet allowing them to record a certain event witnessed by a person. That’s why the creation of video materials isn’t a complicated task. The number of photos and videos, and audio recordings posted on the Internet is constantly expanding, they are sent to acquaintances every minute, which constantly requires skills in working with information to detect fakes and manipulations. Pupils often mistakenly believe that the information posted on the Internet is valuable and reliable. They usually have no doubts about the information's reliability and the authors’ honesty. Previous pupils’ experiences of using reliable printed sources of information (textbooks, manuals) at school allow them to transfer these qualities to other sources. State educational standards and curricula of separate disciplines presuppose the formation of special skills in checking the information for reliability and veracity and the development of critical thinking, but, according to state documents, the content of such education, systems for diagnosing relevant skills, their assessment are not taken into consideration. Having realized the importance of these pieces of knowledge and skills formation, every teacher will be anxious to educate pupils in this direction and have to plan what he will have to teach, and how to check and assess the obtained knowledge and skills. If primary or secondary school pupils’ skills are not formed, the teacher should start from the very beginning even whether learners are school-leavers.&#x0D; Keywords: information and digital competence; Internet network; fake news; online services; Video metadata, plugin, media education, chatbots.
Peculiarities of personality development of the future in the context of information and communication technologies and education system reform (Polish experience)

Given the intensification of modernization processes in education, the problem of predicting the conditions in which the personality of the future will develop is relevant. Determining the vector of further movement is an important step in the renewal and improvement of educational interaction. In particular, significant for the organization of pedagogical interaction is compliance with the socio-cultural environment. Socio-political changes significantly modify the process of personal formation, which, in turn, requires an adaptive response from specialists in psychological and pedagogical direction. Accordingly, the object of the presented research work is determined by the context of future personality formation. The task of this study is to establish the content and measure of transformative influences in the situation of reforming the educational system, in particular the introduction of information and communication technologies in the educational process. The methodological basis of this work general scientific and scientific-pedagogical methods aimed at forecasting and modeling. The empirical basis for the conclusions provided in the work are the results of the conducted psychological survey and questionnaire survey of participants in the educational process. Accordingly, the article presents a theoretical model of personality development in modern information society, taking into account the peculiarities of the educational process in which it is located. The category of “information culture” is defined as an integrative concept for the study of the presented topic. The main directions of the modernization of the educational process in the crisis caused by sudden digitalization are defined. In particular, the work reflects the need to improve the digital competence of teaching staff, expanding the technical support of educational institutions, eliminating the limitations of interaction between students and teachers, as well as ensuring inclusiveness and humanistic principles of education. In addition, it is established that the new information context is favorable for the personal development of students. First of all, it is reflected in the increased level of actualization, self-efficacy, and ego-identity of the latter. In addition, the changes in the character profile of teachers are expressed.
The influence of users’ dark triad on knowledge contribution behaviour on social question and answer sites

The users' knowledge contribution behaviour is the driving force for the sustainable development of the social question and answer sites. This kind of user behaviour is affected by various factors, among which users' personality traits are the prominent ones. The dark triad is a theory on the dark side of personality. This article explores the influence and mechanism of users' dark triad on their knowledge contribution in social question and answer sites. A questionnaire survey and statistical methods such as hierarchical regression and Bootstrap analysis were adopted in this study. Information about 301 users with experience in Chinese social question and answer sites were collected through the questionnaire survey. The quantitative analysis of survey data employed the statistical package SPSS 26.0. The dark triad significantly affects knowledge contribution on social question and answer sites. Online self-disclosure plays a completely mediating role in the relationship between the dark triad and knowledge contribution. The relational psychological contract has a moderating role between online self-disclosure and knowledge contribution. This study argues that the dark triad has a positive effect on knowledge contribution behaviour in socialized question and answer communities by constructing a model of mediated effects that are moderated. The dark triad shows its altruistic side in the context of social question and answer sites. The role of the dark triad in different knowledge-intensive contexts should be viewed dialectically in future research. Based on these findings, we put forward some suggestions for encouraging users' knowledge contribution behaviour in the social media context.
Proposal of a method for human tracking of inverted two-wheeled vehicles

In recent years, with the declining birthrate and the aging society, the shrinking economy, the declining labor force, and the shrinking social security system have become problems. Therefore, the introduction of vehicles to assist people in their work and daily life has been promoted in the real world. The purpose of this study is to make the vehicle easier for people to use by controlling the speed of an inverted two-wheeled vehicle according to the pulling force of a person and making the lifting force of a person lighter than the weight of the vehicle. Simulations on a level ground and on a staircase are performed and evaluated.
Coexistence strategy of nuclear power equipment and wireless communication technology

The introduction of wireless communication technology in nuclear power plants faces challenges, although it can improve productivity and save cable costs. Firstly, wireless communication signals may cause electromagnetic noise interference to existing nuclear power equipment, and radio wave monitoring can lead to information leakage. Secondly, nuclear power plant equipment also generates noise in the working frequency band of wireless equipment, which affects its communication quality. Based on existing standards and test results, this paper discusses strategy about how nuclear power equipment and wireless technologies can coexist, and proposes recommendations to avoid mutual interference.
Adaptive Robust Parking Control of the Autonomous Vehicle with Ackerman Angle

This paper research on the parking control of the autonomous vehicle with Ackerman Angle. So as to achieve the accurate trajectory tracking control of the autonomous vehicle, on the basis of the Udwadia-Kalaba method, a leaky adaptive robust control is adopted. The dynamic model of the autonomous vehicle is first established. Then adopt the leakage type adaptive robust control to deal with the model, and the effectiveness of the method is proved by theory. Finally, the validity of the control is demonstrated by simulation result of a parallel parking trajectory.
OS IMPACTOS NA SAÚDE MENTAL DE IDOSOS DURANTE A PANDEMIA DE COVID-19

The present work deals with the following theme "Nursing assistance in relation to workers' health".It is required to present how important
Peningkatan Aktivitas Belajar PKN Melalui Penerapan Model Pembelajaran Bermain Peran Pada Siswa Sma Negeri 1 Kecamatan Payakumbuh

The purpose of this study was to increase PKN learning activities through the application of role playing learning models for grade X / 6 students of SMA Negeri 1 Payakumbuh District. This type of research is Classroom Action Research (CAR), by collecting data using observations and field notes. The results of this study indicate that there is a significant improvement using role playing learning models. This model is carried out in 2 cycles and each consists of two meetings. Based on the weaknesses or deficiencies seen in the implementation of learning in the first cycle, better learning is planned in the second cycle, so that the increase in student activity that occurs is truly significant. The increase in PKN learning activities seen in Prasiklus research results was 17.2% with low criteria, the first cycle the average number of students active in the learning process was 46.8% with sufficient criteria, and in the second cycle the average number of active students in the learning process is 60.9% with high criteria. The conclusion of this study is that there is an increase in students' learning after using role playing learning models.&#x0D; &#x0D; Keywords: Learning Activities, Role Playing Learning Models.&#x0D;