Reviewerly/exHarmony huggingface dataset:
Network Intrusion Detection to Mitigate Jamming and Spoofing Attacks Using Federated Leading

Network intrusions through jamming and spoofing attacks have become increasingly prevalent. The ability to detect such threats at early stages is necessary for preventing a successful attack from occurring. This survey chapter thoroughly overviews the demand for sophisticated intrusion detection systems (IDS) and how cutting-edge techniques, like federated learning-enabled IDS, can reduce privacy risks and protect confidential data during intrusion detection. It explores numerous mitigation strategies used to defend against these assaults, highlighting the significance of early detection and avoidance. The chapter comprehensively analyzes spoofing and jamming attacks, explores mitigation techniques, highlights challenges in implementing federated learning-based IDS, and compares diverse strategies for their real-world effects on network security. Lastly, it presents an unbiased evaluation of contemporary IDS techniques, assessing their advantages, disadvantages, and overall effect on network security while also discussing future challenges and prospects for academia and industry.
OpenAlex: breve guía de consulta a través de R

OpenAlex is a free and open index of interconnected entities in the scholarly information ecosystem: papers, authors, journals, institutions, topics, etc. This guide describes its main functionalities and provides examples of querying its API through the openalexR package developed using the R programming language.
Sentiment Analysis, Social Media and Urban Economics: The Case of Singaporean HDB and Covid-19

Twitter sentiment analysis has been employed as a prognostic tool for predicting prices and trends in both stock and housing markets. Early studies in this domain drew inspiration from behavioural economics, establishing a link between sentiments or emotions and economic decision-making. However, recent investigations in this field have shifted their focus from the data utilized to the algorithms employed. A comprehensive literature review, with an emphasis on the data aspect, reveals a scarcity of research considering the influence of sentiments arising from external factors on stock or housing markets, despite abundant evidence in behavioural economics suggesting that sentiments induced by external factors impact economic decisions. To bridge this gap, this study explores the impact of Twitter sentiment related to the Covid-19 pandemic on housing prices in Singapore. Employing SNSCRAPE for tweet collection, sentiment analysis is conducted using VADER. Granger Causality is applied to investigate the relationship between Covid-19 cases and sentiment, while neural networks serve as prediction models. The research compares the predictive capacity of Twitter sentiment regarding Covid-19 with traditional housing price predictors, such as structural and neighbourhood characteristics. Findings indicate that utilizing Twitter sentiment related to Covid-19 yields superior predictions compared to relying solely on traditional predictors, outperforming two specific traditional predictors. Consequently, this study underscores the significance of considering Twitter sentiment related to external factors as crucial in economic predictions, demonstrating practical applications of sentiment analysis on Twitter data in real-world economic scenarios.
Media Educational Potential of I.A. Bunin's Journalism in the System of Professional Training of Future Journalists

The paper is related to the problematic space of journalistic education strategies that are being modernized in the context of sociocultural convergence and general digitalization of life. The relevance of the research is determined by the objective need for a constant search for new methods and technologies for training future specialists, who are capable of carrying out efficient activities in a rapidly changing, technically capacious information environment. It is noted that the professionalism of a modern journalist is not limited only to a high level of proficiency in special techniques and multimedia skills. It is traditionally determined by a thorough philological base, which allows creating a high-quality media text at all times. In this regard, the author's methodology of working with classical text sources, called "media reading", is presented here. It is implied that students' comprehension of the features of the text is carried out with the help of, on the material and in the context of the media. Based on the works of I.A. Bunin, the media educational possibilities of Russian journalism are revealed. The choice of the writer is determined by the facts of his biography, which is typical for the Russian literature of the turn of the XIX–XX centuries and which echoes the current situation in the moments of multifunctional realization of human creative abilities. The educational potential of the writer's journalism is emphasized, the presence of which in the journalistic educational process contributes to the formation of moral and aesthetic values and professional guidelines of future media specialists. Bunin's numerous connections with the newspaper and magazine world of Russia and the Russian abroad allow us to consider his journalistic heritage as a serious resource of professional media education. Examples of the involvement of individual journalistic works of the writer as a means to solve the main media educational tasks are given in the paper. They are the development of skills of search, purposeful selection, critical analysis and comprehension of the information received, verification of the reliability of facts, the creation of independent media products in traditional and new popular formats. It is concluded that the integration of the methodology of media reading of classical journalism into the process of training journalistic personnel orients future specialists to the perception and development of the traditions of Russian literature in accordance with the requirements of the modern information age.
QR Multilevel Codes to Reduce Cybersecurity Risks in the Logistics of Freight Transport in Ports

A country's national security depends on many combined and constantly changing factors. However, one of the most preponderant aspects is the access control of goods and people entering and leaving the country through its customs, as a result of mobility and international trade currently taking place. Throughout the territory of a country, the entry and exit of both merchandise and people of different natures or nationalities, respectively, are carried out by different means of transport. Therefore, it is necessary to establish more efficient control points that manage, supervise, and, where appropriate, tax this activity, because otherwise products, materials, or people that pose a risk to human health may enter the country. In this context, this chapter shows a practical tool, based on multilevel QR codes, to improve the identification and supervision of goods entering a country through its port customs to show a technology that reduces cybersecurity risks in freight transport logistics.
Modeling Cognitive Problem-Solving Processes

Modeling cognitive and meta-cognitive problem-solving processes is a systems approach to understanding how individuals solve problems using their thinking and reasoning. These models attempt to represent the mental steps and mechanisms involved in solving complex problems. Moreover, modeling cognitive problem-solving processes can contribute to a more efficient and adaptive design of intelligent tutorial systems, as it would enable instructional designers of e-learning environments to set up individualized support, relevant feedback, and learning activities tailored to the needs and preferences of each learner, thus promoting a more enriching and successful learning experience. The aim of this chapter is to provide readers with the theoretical underpinnings and an in-depth understanding of how cognitive and metacognitive models work in the first place, and how they can be applied to design effective and adaptive expert problem-solving systems in a variety of application domains.
AI-Based Eye Tracking Applications in Collaborative E-Learning Environments

In collaborative e-learning environments, we need to understand individual differences of each learner like behavior, motivation, learning style, interest level, cultural background, performance, relaxation, and more. Learners' eyes can be a major source of data, and eye-tracking methods can be used in collaborative e-learning environments to measure these differences in real-time and provide insightful feedback. AI-based eye tracking can help to increase motivation by predicting learners' areas of interest to create effective interaction between learners and collaborative e-learning environments. The main goal of this chapter is to study the feasibility and the potentials of predictive eye tracking systems in collaborative e-learning environment. Results can help to design an adaptive collaborative e-learning environment able to analyze and understand learners' individual differences and then generate new customized learning situations.
Harnessing Advanced Logical Models for Pedagogical Innovation in Educational Recommender Systems

This chapter presents a groundbreaking approach to educational recommender systems, underpinned by the integration of advanced logical models. The authors delve into how situational logic can be ingeniously applied to revolutionize pedagogical strategies within educational recommender systems. By transcending traditional rule-based adaptation models, the approach offers a nuanced and dynamic method for personalizing learning paths, catering to diverse learner profiles and styles. They explore the application of these logical models in formulating sophisticated algorithms that not only adapt to individual learning trajectories but also predict and respond to evolving educational needs. The chapter demonstrates how such an integration leads to a significant leap in pedagogical innovation, offering educators and learners a more engaging, effective, and responsive educational experience. The ensuing discussion highlights the transformative potential of these logical models in reshaping the educational landscape, providing a roadmap for future advancements in educational technology.
Recent Trends in High Speed Computing

In recent years, the issue of internet congestion management and modelling has been a hot topic of study. Following the development of the transfer control protocol (TCP) and mathematical models, which treat the underlying resource allocation in congestion control as an optimization issue, this study has focused on modelling and analysis of congestion control methods. On this basis, subsequent research has suggested and evaluated numerous primal, dual, and primal-dual algorithms.
Augmented and Virtual Reality for Mathematics Education

Augmented reality (AR) and virtual reality (VR) have emerged as groundbreaking technologies across various domains, notably in the realm of mathematics education, providing learners with novel opportunities for immersive, interactive, and easily comprehensible learning experiences. This narrative review delves into the potential applications of AR and VR technologies in mathematics education, examining numerous recent studies incorporating AR and VR-based applications to enhance mathematical learning. The objective is to elevate learners' levels and skills, transitioning from traditional teaching methods to a more advanced and effective educational approach. The authors underscore the challenges and prospects presented by these immersive tools, emphasizing the imperative of conducting in-depth research to assess their impact on mathematics education in Morocco.
Postdigital Argumentation

This entry provides an overview of different aspects and functions of postdigital argumentation, defined as a dynamic and strategic discourse activity akin to take place with or without the use of digital technologies. The passage from nondigital to digital discourse has caused an increase in the multimodality and polyphony of postdigital argumentation. The issue of whether artificial agents are able to genuinely engage in an argumentative discussion or writing is also highly relevant. Postdigital epistemological concerns related to the meaning of non-human agents’ positionality and intersubjectivity are raised.
Federated Learning and Fusion of IoT for Smart Healthcare Applications

Federated learning is also called collaborative learning which uses the decentralized approach to train the machine learning models. Federated learning, a groundbreaking approach in the field of machine learning, has immense potential to transform healthcare as we know it. By harnessing the power of distributed facts from IoT sensors and devices, federated learning enables healthcare providers to train AI models without compromising patient privacy. Key assistances of federated learning in health care are its skill to overcome data sharing limitations. In traditional approaches, sensitive patient data must be centralized for training AI models. However, with federated learning, hospitals and clinics can keep their data secure within their own premises while contributing to a collective intelligence.
Digital Library Services and Their Importance in Academic Libraries

The purpose of the study is to highlight digital library services and their importance in academic libraries. Digital libraries are a group of files in digital form accessible on the net or CD-ROM disk. Depending on the precise library, a consumer may be able to get admission to magazine articles, books, newspapers, snapshots, sound documents, and films. The virtual library is one of the maximum cutting-edge trends in library and statistics technology, which helps its users to seek information via the internet. A digital library is prepared for greater ideas and statistics and guides different offerings and places wherein the order is saved in digital format and can be retrieved over networks. Digital libraries are systems presenting the person with resources and getting the right of entry to a very big range; the digital library information prepared storeroom of the records awareness digital library is an international digital library.
Harnessing Digital Technologies for References Services in Academic Libraries

Academic libraries' reference services have continued to diversify thanks to digital technologies. The use of digital technologies to support reference services in academic libraries is covered in this chapter. The study is a review of published works in scholarly journals. The study's conclusions indicate that there is a shift toward digital references globally. Emails, Facebook, and Twitter were the most widely used technologies, although real-time reference services powered by artificial intelligence technology were rarely used. Some users favoured in-person reference services they concurred that digital reference services were superior. The chapter highlighted how academic libraries frequently struggle with inadequate financing, outdated infrastructure, and a lack of user and staff education. The study suggests making investments in the infrastructure of digital technology and educating library users on the advantages of utilizing digital reference services.
The Impact of Federated Learning on AI-Enhanced Healthcare Delivery

Federated learning has recently emerged as a promising methodology in healthcare, seamlessly integrating with machine learning models to glean insights from distributed healthcare databases while prioritizing data privacy and security. This systematic literature review provides a comprehensive analysis of federated learning's current state in healthcare, highlighting trends in its fusion with AI and its advancements in analyzing medical reputation and predicting potential gains. The ethical and technical aspects of successful implementation and adoption to drive AI in healthcare are discussed. In conclusion, the integration of AI in healthcare is an evolutionary force, revolutionizing medical practices, treatment, patient care, and diagnosis, with federated learning playing a pivotal role in enabling collaborative, privacy-preserving, and data-driven healthcare transformations.
Screen Reading Regions in Social Media Comments: An Eye-Tracking Analysis of Visual Attention on Smartphones

Our study examines how formatted text influences reading behavior concerning the smartphone screen regions users utilize on social media comments. Aiming to research visual attention in scrollable content, we investigate the differences in the distribution of visual attention in screen regions between social media comment sections and the users’ preferred reading regions across all cases examined. An experiment was conducted with participants (n = 47) engaging in reading activities on the comment section of four social media -Twitter, YouTube (in two versions), Facebook, and Instagram- chosen due to their popularity and the users’ familiarity with them. Results showed that users’ visual attention is distributed differently between social media. Different reading styles were observed, with users not utilizing the entirety of the screen but instead focusing on specific screen regions that varied between users.
Enhancing User Experience: Virtual Assistants in Greek University Helpdesk Service

It is commonly accepted that we live in a digital era of constant changes. Digital revolution has brought significant changes in the way we live, work, and interact with each other, with messaging apps turning to the centerpiece of our communication. Individuals and especially youngsters are constantly connected through devices for both social and entertainment reasons. This growing enthusiasm for messaging apps brought the use of bots as supplementary virtual assistants into the spotlight. Examples of companies employing bots into their business chats examples marked that chatbots contribute to a better user experience while at the same time reduce personnel workload. The results raised the question whether the introduction of virtual assistants will benefit the everyday life of Greek Universities. To examine our hypothesis in the realms of University of Western Macedonia, we introduced the “bot-UoWM”, a zero- code conversational chatbot that supports Greek Natural Language, in well-known social media platforms. To evaluate the system, we conducted an empirical study using a questionnaire on 80 participants. The obtained survey data were analyzed using a combination of quantitative and qualitative techniques. The evaluation results show that our system improves user acceptance and understanding of the results. They also indicate that bots could help different users with their seeking tasks. Our results and discussions highlight the impact of using visual and interactive features as assistants for higher education.
GR-UMUX and GR-UMUX-LITE: A First Step Towards Standardization of the Usability Metric for User Experience and its LITE Version in Greek

Users' perceptions of their experience with interactive systems is particularly important for the product's success. The Usability Metric for User Experience (UMUX) is a four-item questionnaire used for the subjective assessment of a system's perceived usability. The UMUX-LITE is a shorter version that includes only the two positively worded questions of UMUX. UMUX has been developed in English, but has also been adapted into various other languages, such as Arabic, Chinese, Slovene and Turkish. This paper is a first step towards standardization of the UMUX and UMUX-LITE in Greek. First, two HCI experts and native Greek speakers adapted the UMUX questions into Greek. Subsequently, the items were pretested in a pilot study involving 12 participants. Finally, a psychometric evaluation of the GR-UMUX and GR-UMUX-LITE was conducted. To this end, 389 participants were asked to interact with two websites. After interacting with each website, they completed the System Usability Scale (SUS) and the GR-UMUX, which also includes the questions of the GR-UMUX-LITE. For both Greek UMUX questionnaires and evaluated websites, we found Cronbach's alpha values of at least 0.752, significant correlations with SUS scores of at least 0.789 and a single-factor solution. These results provide support that both the GR-UMUX and its LITE variation are reliable and valid instruments for measuring perceived usability.
Large Language Models versus Natural Language Understanding and Generation

In recent years, the process humans adopt to learn a foreign language has moved from the strict "Grammar –Translation" method, which is based mainly on grammar and syntax rules, to more innovative processes, resulting to the more modern "Communicative approach". As its name states, this approach focuses on the coherent communication with native speakers and the cultivation of oral skills, without taking into consideration, at least at the first stages, the rules that govern the language.
Can Large Language Models Revolutionalize Open Government Data Portals? A Case of Using ChatGPT in statistics.gov.scot

Large language models possess tremendous natural language understanding and generation abilities. However, they often lack the ability to discern between fact and fiction, leading to factually incorrect responses. Open Government Data are repositories of, often times linked, information that is freely available to everyone. By combining these two technologies in a proof of concept designed application utilizing the GPT3.5 OpenAI model and the Scottish open statistics portal, we show that not only is it possible to augment the large language model’s factuality of responses, but also propose a novel way to effectively access and retrieve statistical information from the data portal just through natural language querying. We anticipate that this paper will trigger a discussion regarding the transformation of Open Government Portals through large language models.
Postdigital Ethnography

Postdigital ethnography refers to ethnographic research of the postdigital condition in which ‘the digital’ or ‘the technical’ can no longer be separated from ‘the physical’, ‘material’, ‘social’ or ‘analog’. Postdigital ethnography also refers to a critical perspective within ethnographic research on digital technology, digital culture, and digital education. Postdigital ethnography ties cultural theory and/or theories of the (post)digital down to glitchy situated lived experiences and opens up accounts of lived experience to theoretical exploration. In this way, postdigital ethnography slows down faster cultural analysis to add nuance and complexity to analyses of emerging issues in the contemporary world.
Summary on the Multimodal Information Based Speech Processing (MISP) 2022 Challenge

The Multimodal Information based Speech Processing (MISP) 2022 challenge aimed to enhance speech processing performance in harsh acoustic environments by leveraging additional modalities such as video or text. The challenge included two tracks: audio-visual speaker diarization (AVSD) and audio-visual diarization and recognition (AVDR). The training material was based on previous MISP 2021 recordings, but we have accurately synchronized audio and visual data. Additionally, a new evaluation set was provided. This paper gives an overview of the challenge setup, presents the results, and summarizes the effective techniques employed by the participants. We also analyze the current technical challenges and suggest directions for future research in AVSD and AVDR.