Reviewerly/exHarmony huggingface dataset:
Breaking Down BBC News Headlines: A Study of Structure Types

This study aims to find the structure types used in BBC News headlines. This research used Morley's (2000) theory for sentence types and Matthews' (1981) theory for phrase types as well as Brown &amp; Miller's (1991) theory to analyze its constituent structure. This research used descriptive qualitative method to explain the final result of the research. The data sources were obtained from 186 BBC headlines for the period July 2023 which were then presented in a table according to the frequency of occurrence. The results showed that based on the sentence types, there are three sentence types found, namely simple sentences, complex sentences, and compound sentences. Among the sentence types used, simple sentences are the most frequent, with 151 occurrences, followed by complex sentences with 20 occurrences, and compound sentences with three occurrences. Furthermore, based on the phrase types, 11 headlines with noun phrase structure and one headline with verb phrase structure were found. It is hoped that after this research is conducted, it can make a positive contribution to the development of science, especially in the field of syntax.
The Impact of Negative Attitudes toward Restaurant Service Robots on Trust, Perceived Risk, Intention to Use, and Revisit Intention

With the development of artificial intelligence robots, it is expected that in future restaurants, an appropriate relationship will not only be formed through a certain level of communication between humans and robots but various customer experiences will also be achieved simultaneously. In the future human-robot interaction process, it is important to understand the complex psychological state of customers that leads to restaurant performance. Exploring new possibilities for introducing social robots in restaurants by examining customer reactions is of great significance. To achieve the purpose of this study, meaningful results were derived using a structural equation model based on the perceptions of 320 evaluators. Negative attitudes toward interactions with robots (NARS1), negative attitudes toward the social influence of robots (NARS2), and negative attitudes toward emotional interactions with robots (NARS3) were found to have a negative relationship with trust. Trust was found to have a negative relationship with perceived risk and a positive relationship with intention to use and intention to revisit. It was confirmed that intention to use has a positive relationship with behavioral intention. This study contributes to the development of robotics and successful management by providing a basis for building a new model by verifying factors related to trust formation in human-robot interactions in the restaurant industry.
The Ultra-short-, Short- and Short-medium- Term Impact of Covid-19 Pandemic on Bitcoin Prices

The global outbreak of the COVID-19 pandemic has led to significant disruptions in financial markets, including the virtual currency market. This study examines the impact of the pandemic on Bitcoin prices across ultra-short, short, and short-medium time scales. Using ARIMA modeling, this paper analyze the dynamic behavior of Bitcoin prices in response to the effects of the pandemic. This findings illustrate distinct patterns of behavior in different time frames. First of all, from the ultra-short term perspective, after the local outbreak of the epidemic in China, compared with the control group constructed by the model, the price of Bitcoin has a relatively obvious upward trend during this period. In the short term, the outbreak of the global epidemic has led to a setback in investor confidence in all kinds of financial assets, and Bitcoin is no exception, and it is also facing a sharp decline. In the short to medium term, Bitcoin has acted as a safe haven asset in the context of the global pandemic of Covid-19. Understanding these intricate dynamics provides valuable insights into Bitcoin's multifaceted role during times of global uncertainty.
A Review of the Phenomenon of Algorithm-facilitated Systematic Price Discrimination

As the Internet environment has rapidly developed, algorithms and programs have contributed to an ever-increasing level of convenience in day-to-day life. However, it is of the utmost importance to put an end to discriminatory pricing practices that are brought about by improper application of algorithms. Some retailers employ a strategy known as algorithmic price discrimination in order to boost their profits; nevertheless, this strategy has unfavorable effects on both the consumers' right to privacy and the reputation of the Internet. In order to achieve social and economic justice, it is essential and urgent to do away with algorithmic price discrimination. The purpose of this study is to have a better understanding of the current situation of algorithmic price discrimination by analyzing its history and discussing it. In addition, the research offers actions that authorities can take and measures that might be implemented in order to combat algorithmic price discrimination.
#Palaver Platforms: An Ubuntu Initiative for National Unity and Social Media

Social media platforms are not politically neutral tools. For that reason this paper studies the polarizing influence of social media on national unity in Africa. From the social constructivist perspective it examines the conflictual interactions via social media between social movements, state and tech giants. Their polarization prompts a reflection on the validity of the non-dominating concepts of the African-rooted Ubuntu philosophy. The Ubuntu concept of consensus is presented as an addition to the perspectives of the Beijing consensus, Washington consensus and Bandung consensus. The author argues that Ubuntu philosophical orientations reclaim via social media the communal dimensions of serving cohesion within the domains of economy, technology, politics and culture. In the end, the author argues for Palaver Platforms as the alternative dialogue for social media promoting social cohesion.
Analysis of Data Leakage Detection Algorithms

Abstract: Data refers to information about a particular mention. There are several types of data and they can be stored either physically or virtually. The use of Cloud Computing has gained popularity in many IT organizations in order to store data effectively. With the growth of the population, data management becomes more critical. A management system relies heavily on the protection of data and preventing leakage. A data leak not only damages the company's reputation but also damages its customers' trust. It is high time to address the issue, especially considering previous incidents like Yahoo's data breach that compromised over 2 billion accounts, Friend Finder Networks’ leak that caused 412 million accounts to be compromised, and more. In this paper, we present methodologies for detecting and preventing data leakage in cloud computing. The cloud platform is being used to perform various algorithms, which will lead to an efficient detection of data leakage, as well as an immediate identification of guilt.
Elliptic interval Type-2 intuitionistic fuzzy logic system for non-linear system identification

An elliptic membership function has been proposed in the literature for interval type-2 fuzzy logic system. In this paper, elliptic non- membership function is incorporated into the conventional elliptic membership function model to obtain elliptic interval type-2 intuitionistic fuzzy sets for the first time. The elliptic interval type-2 intuitionistic fuzzy logic system so formed is applied for the prediction of two benchmark non-linear systems and results compared with Gaussian interval type-2 intuitionistic fuzzy logic system. Experimental results show that the elliptic interval type-2 intuitionistic fuzzy logic system outperforms the traditional Gaussian interval type-2 intuitionistic fuzzy logic system in the problem instances investigated.
The Issue of Formation of Junior Schoolchildren’s Mathematical Abilities

The article is devoted to the issiue of formation of junior schoolchildren’s mathematical abilities. The role of the primary school teacher in the formation of the mathematical abilities of younger schoolchildren is substantiat-ed. The analysis of scientific and methodical literature is carried out, the contradictions between the require-ments to the teacherэs competence and the directions of preparation for professional activity within a particular subject area are revealed. The identified contradictions determined the importance of developing in future pri-mary school teachers the skills of constructing and using a program of individual achievements for junior schoolchildren when designing mathematics lessons. The relationship between inclinations, abilities and types of activities aimed at developing the mathematical abilities of younger schoolchildren is revealed. The im-portance of building a program of individual achievements for junior schoolchildren when studying the module “Theories and Technologies of Primary Mathematics Education” is described. Recommendations are given for constructing a program of individual achievements for younger schoolchildren and selecting the main types of activities in mathematics lessons when teaching how to solve word problems.
The Influence of Dual Training on the Psychological and Pedagogical Characteristics of Readiness for Professional Activity of Teacher Training Colleges Graduates

The modern educational paradigm of the Republic of Kazakhstan is focused on the training of qualified spe-cialists-teachers who are able to actively and creatively integrate into the social and professional environment, and, therefore, be ready to apply theoretical knowledge in practice. The very concept o f readiness is very ex-tensive and includes, among other things, psychological and pedagogical characteristics that are important for a future teacher and characterize the level of his professional competence. Dual training entering the practice of educational institutions allows developing not only professional but also personal qualities that are most im-portant for a teacher. The article discusses the results of the experimental study, the aim of which is to identify qualitative changes in the level of a number of psychological and pedagogical characteristics of readiness of future primary school teachers for teaching activities in the conditions of dual education. The results obtained during the empirical research show an increase in the level of such characteristics as general educational skills and teaching abilities. The results of the study can become the basis for further research in this area, for the development of special training programs in the system of dual training technology. Research methods: sur-veys, testing, analysis of student work, interviews.
An Artificial Intelligence-based Proactive Network Forensic Framework

is at an all-time high in the modern period, and the majority of the population uses the Internet for all types of communication. It is great to be able to improvise like this. As a result of this trend, hackers have become increasingly focused on attacking the system/network in numerous ways. When a hacker commits a digital crime, it is examined in a reactive manner, which aids in the identification of the perpetrators. However, in the modern period, it is not expected to wait for an attack to occur. The user anticipates being able to predict a cyberattack before it causes damage to the system. This can be accomplished with the assistance of the proactive forensic framework presented in this study. The proposed system combines a reactive and proactive framework. The proactive part will use machine learning-based classification algorithms to forecast the attack. Once the assault has been predicted, the reactive element of the proposed framework is used to investigate who is attempting to initiate the attack. The suggested system further emphasizes integrity and confidentiality by proposing an encryption method that encrypts the proactive module's report before decrypting it in the reactive module. The suggested elliptical curve cryptography-based security model was compared to several existing security methods in this paper.A comparison of multiple machine learning-based categorization algorithms is also performed in order to determine which is the most suitable for the proposed Network Forensic Framework. Accuracy, recall, precision, and F1 value are the performance metrics used to evaluate the various machine learning-based algorithms. According to the analysis, the suggested Network Forensic Framework is best implemented using the Extreme Gradient Boosting (XGB) technique.
On the Strategic Competence of Specialists in the Context of the Success of Professional Activity

One of the types of professional competence that ensures the success and quality of professional activity of specialists today is strategic competence. Strategic competence is considered in two interrelated main aspects. In the first aspect, strategic professional competence implies intellectual activity aimed at identifying and select-ing new, effective strategic actions that ensure the success and effectiveness of activities, achieving competi-tive advantages of the organization. In the second aspect, strategic competence is considered as a key compo-nent in the framework of communication in the performance of professional activities and communication, and here such professional and personal competencies as communicative potential, readiness for professional interpersonal interaction, focus on creating relationships for the formation of a friendly community on a profes-sional basis, personal influence, positive self-image and self-esteem are important, high level of social (emo-tional) intelligence, customer focus in the state and in business (client-centricity). In modern conditions of socie-ty’s development, strategic competence is a professional new formation, thanks to which the selection of the necessary communicative strategies is carried out, in accordance with the goals and objectives of professional activity.
Image Splicing Detection Based on Discrete Wavelet Transform and co-occurrence Matrix

In this paper a method to determine whether an image is forged (spliced) or not is presented. The proposed method is based on a classification model to determine the authenticity of a tested image. Image splicing causes many sharp edges (high frequencies) and discontinuities to appear in the spliced image. Capturing these high frequencies in the wavelet domain rather than in the spatial domain is investigated in this paper. Correlation between high-frequency sub-bands coefficients of Discrete Wavelet Transform (DWT) is also described using co-occurrence matrix. This matrix was an input feature vector to a classifier. The best accuracy of 92.79% and 94.56% on Casia v1.0 and Casia v2.0 datasets respectively was achieved. This performance is reached when Cb and Cr channels in YCbCr color space only are utilized to form this feature vector. The outcomes of the experiments showed that the proposed method achieved very good results in comparison with existing splicing detection approaches.
Algorithms for the Formation of the Personnel Reserve and Certification of the Heads of Educational Organizations

The article discusses Russian algorithms for the formation of a personnel reserve and certification of managers (school principals), the effectiveness of which is based on objective criteria for assessing the competencies of leaders, taking into account professional standards, methodological manuals, recommendations, programs for working with the personnel reserve and pedagogical experience. The formation of a personnel reserve and certification of leaders in the educational field are based either on holding competitions in the selection for the position of school principal, or on completing training courses in general educational organizations for subse-quent work in leadership positions. Certification is an important component of the personnel reserve formation process. It is implemented to assess professional competence and qualifications as well as to determine the development needs of the principal.
Cyber Protect: A Robust Cybersecurity System for Fraudulent Scam and Phishing Detection Using Machine Learning Techniques

Abstract: In today’s digital age, ensuring cyber-security is critical to protecting computer systems, networks, devices, and programs against cyber threats. The proposed project intends to create a comprehensive cybersecurity system that uses machine learning techniques to detect and prevent fraudulent scams and phishing URLs. A large dataset of emails and messages will be collected and processed to extract key features using the Python programming language and its tools. These characteristics will be used as inputs for training and assessing a machine learning model, which will be trained and evaluated using labeled datasets specifically curated for fraudulent scams and phishing attempts. The research will entail optimizing and fine-tuning the machine learning model to improve its accuracy and efficacy in detecting fraudulent activities. The expected outcome of this project is an efficient and reliable cybersecurity solution that safeguards sensitive information and significantly reduces the risks associated with fraudulent scams and phishing attacks.
STOCK MARKET DEVELOPMENT IN NIGERIA: DO INSTITUTIONAL QUALITY AND FDI NET INFLOW MATTERS?

This study examines the effect of institutional quality and FDI net inflow on the stock market development in Nigeria for the period spanning 1996 to 2018. Symmetric method through autoregressive distributed lag model is used for the estimation of the relationship and cointegration. Stock market development is proxy by the annual stock market capitalization, while institutional quality is measured by the average of the composite index covering six categories; control of corruption, government effectiveness, political stability, regulatory quality, rule of law and finally, voice and accountability. Bound test confirms the validity of linear of variables under investigation. We found sufficient and significant evidence, affirming the role of institutional quality on stock market development both in the long run and short run. Similarly, FDI net inflow matters for the development of the stock market in the long run but not significant as expected while in the short it exerts negative and significant impact on the stock market development. This implies that foreign investors in form of portfolio investment will retard the development of the stock market in the short run if not properly managed.
Independent Creative Learning in Painting as a Factor to Improve Students’ Spiritual and Moral Education

The article examines the urgent problem of improving the spiritual and moral education of future artist-teachers through the activation of their independent educational and creative work in painting amidst modern-day Rus-sia. The most important aspect of spiritual and moral education is the orientation of student youth to participate in international exhibitions and scientific-practical conferences devoted to patriotic themes. Due to the ongoing events in the world and modern Russia, changes in the system of art and pedagogical education are inevitable, aimed at solving global problems related to the formation of a socially active, creative and harmonious person-ality of the future teacher of fine arts. In 2022–2023, we developed a pedagogical technology of spiritual and moral education (SME) for students of art and graphic faculties, the results of the implementation of which we consider in this publication. As the pedagogical experiment showed, this technology proved to be effective, identifying new problematic issues that take into account the realities of today. Further improvement of the technology will make it possible to create a full-fledged methodological system. The results of the study showed that the implemented innovative content and methods of art education, especially in independent fine arts activities, significantly affected not only the quality of learning, but also the development of the spiritual component of students’ personality.
SISTEM ANALISIS PENYAKIT MATA BERBASIS PHP DAN MYSQL MENGGUNAKAN METODE TF-IDF

The development of information technology has had a positive impact on the healthcare sector, particularly in disease analysis. Eye diseases are among the health issues that require early detection for effective prevention and treatment. In this context, this research proposes the development of a PHP and MySQL-based Eye Disease Analysis System utilizing the Term Frequency-Inverse Document Frequency (TF-IDF) method. The system is designed to provide a web platform facilitating the analysis of textual data related to eye diseases. Involving PHP as the programming language and MySQL as the database, the system allows efficient storage, management, and retrieval of medical information. The TF-IDF method is employed to analyze unique characteristics within textual data, enabling the identification of symptoms, diagnosis, and treatment of eye diseases. Context Diagram, Data Flow Diagram (DFD), and Entity-Relationship Diagram (ERD) serve as visual guides in designing this system. The Context Diagram provides a general overview of the system's interaction with its external environment, while DFD illustrates the flow of data within the system. ERD is used to represent the data structure within the database.&#x0D; The research results are expected to significantly contribute to the efficiency of eye disease analysis, providing faster information to medical professionals and enhancing the general public's understanding of eye diseases. This system is anticipated to serve as a foundation for further developments in the application of information technology in the healthcare sector, particularly in disease analysis.
Grey Wolf Optimization Algorithm: A Survey

The Gray Wolf Optimizer (GWO) is a population-based meta-heuristic algorithm that belongs to the family of swarm intelligence algorithms inspired by the social behavior of gray wolves, in particular the social hierarchy and hunting mechanism. Because of its simplicity, flexibility, and few parameters to be tuned, it has been applied to a wide range of optimization problems. And yet it has some disadvantages, such as poor exploration skills, stagnation at local optima, and slow convergence speed. Therefore, different variants of GWO have been proposed and developed to address these disadvantages. In this article, some literature, especially from the last five years, has been reviewed and summarized by well-known publishers. First, the inspiration and the mathematical model of GWO were explained. Subsequently, the improved GWO variants were divided into four categories and discussed. After that, each variant's methodology and experiments were explained and clarified. The study ends with a summary conclusion of the main foundation of GWO and suggests some possible future directions that can be explored further.
FAILURE AS AN INTEGRAL PART FOR TEACHING THE DESIGN OF COMPLEX MECHATRONIC SYSTEMS

Appears in: ICERI2023 Proceedings Publication year: 2023Pages: 1928-1933ISBN: 978-84-09-55942-8ISSN: 2340-1095doi: 10.21125/iceri.2023.0559Conference name: 16th annual International Conference of Education, Research and InnovationDates: 13-15 November, 2023Location: Seville, Spain