bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving AppSec Resiliency, Monitoring, Risk Assessment, and Compliance by Bridging DevSecOps With SOCs
Authors: Jones Angel Justo
Published: December 2024

This chapter examines the evolution and integration of DevSecOps and Security Operations Centers (SOCs), emphasizing enhanced cybersecurity management through collaborative models. This study explores the theoretical underpinnings of DevSecOps using the Development and Cybersecurity Adoption Model (DCAM) and the Information Systems Development Acceptance Model (ISDAM), derived from the Theory of Planned Behavior (TPB). It investigates how these models facilitate the adoption of DevSecOps in SOCs, aiming to reduce vulnerabilities and enhance operational efficiency. The quantitative analysis focuses on identifying barriers to DevSecOps implementation and evaluating the effectiveness of bridging DevSecOps with SOCs in organizational settings. Results suggest that integrated approaches can significantly mitigate cybersecurity risks and foster a resilient digital infrastructure. This chapter contributes to academic and practical knowledge of cybersecurity by highlighting the benefits of merging development, operations, and security practices within organizational cybersecurity strategies.
An In-Depth Investigation on Hardware Trojans Testing Into Cyber Security Concerns Using Machine Learning Models
Authors: Hariharasitaraman S. , Bhanpurkar Ajinkya , Singh Madhu , Mishra Nilamadhab
Published: December 2024

The current study comprehensively investigates hardware Trojan testing using traditional and machine learning models. It highlights the challenge posed by the uniqueness of each Hardware Trojan and emphasizes the need for reliable solutions. The study recommends using machine learning models with feature extraction to detect patterns in different Hardware Trojans. However, the study also identifies limitations in the existing models, including reliance on the XGBoost algorithm. The study suggests exploring hybrid mechanisms and newer languages, such as LightBGM, for model development as potential areas for further research. The study also underscores the significance of addressing security concerns in IoT technology.
An In-Depth Analysis of a Cyber Attack
Authors: Pakshad Puya
Published: December 2024

Nation-sponsored cyberattacks pose a severe threat to national security, targeting critical infrastructure and disrupting essential services. Among the most impactful attacks on South Korea's banking sector and infrastructure was the DarkSeoul cyberattack, believed to have been conducted by North Korea state-sponsored hackers. Using spear phishing, DNS poisoning, and malware, this attack caused widespread disruption across critical systems. This paper presents an in-depth analysis of the DarkSeoul incident, detailing the techniques involved and offering insights and recommendations for the global cybersecurity community. The motivations and strategic objectives behind the attack are examined, as well as South Korea's response and the broader implications for cybersecurity policy. Our analysis highlights key vulnerabilities and underscores the urgency for enhanced defenses against state-sponsored cyber threats. This study emphasizes the necessity for robust national cybersecurity measures to counter such sophisticated attacks effectively.
Researcher Positionality in Qualitative Research With a Reflexive Dive With the Santals
Authors: Roy Parimal Kumar
Published: December 2024

This case report presents the experiences through a PhD thesis and highlights the researcher's positionality. The researcher's positionality and reflexivity were interconnected to accomplish an ethnographic study with the Santals of Bangladesh. Against this backdrop, a qualitative research design was utilized that involved participant observation, a type of qualitative approach for data collection from the Santals hamlet of northern Bangladesh. One component of the methodology demonstrated how the researcher is embedded with the target population and illustrates the embedded context via a lengthy involvement prior to the qualitative research to demonstrate the use of reflexivity and positionality.
Navigating the Path
Authors: Salimi Nahal , Gere Bryan , Mora Elaine , Chen Roy K.
Published: December 2024

Higher education can be challenging for many students, but for those with disabilities, it presents additional hurdles. Oftentimes, students with disabilities must navigate both their academic responsibilities and the unique challenges posed by their disabilities. This chapter provides a comprehensive overview of the most frequently reported challenges and barriers to academic success for students with disabilities in higher education. The chapter focuses on several key issues, including but not limited to societal attitudes surrounding disability and provision of academic accommodation, students' willingness to disclose their disabilities in their institutes, and difficulties with social integration. Each of these challenges is explored in depth, highlighting the critical areas where students with disabilities may require additional assistance. Furthermore, the chapter discusses the importance of acknowledging and embracing diversity in higher education as it results in promoting knowledge, understanding, and social justice for both students with and without disabilities.
Effects of Social Media Marketing Elements on Online Buying Decisions of Vietnamese Generation Z
Authors: Le Tan Trinh , Tran Minh Tung
Published: December 2024

This research intends to explore how social media marketing impacts the shopping habits of Vietnam's Generation Z, particularly through elements such as the content's usefulness, engagement level, appeal, shareability, trustworthiness, and entertainment value, employing structural equation modeling for detailed investigation. By conducting an online questionnaire using Google Forms aimed at a minimum of 197 respondents, the study will use Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) via AMOS and SPSS tools. Measures' reliability will be confirmed through Cronbach's Alpha, Exploratory Factor Analysis (EFA), and CFA. Anticipated outcomes should provide crucial insights for companies and institutions to formulate more effective marketing strategies, especially in understanding the interaction of this age group with social media advertisements and its influence on consumer behavior shifts.
Evaluating the Effectiveness of Leadership Decision Making by Data Analytics and Reporting Technologies
Authors: Dwivedi Deeksha , Agarwal Shivani
Published: December 2024

Data analytics and reporting technologies play an important role in leadership decision-making. This chapter examines how data analytics and reporting technology help decision-making in leadership. Previous research shows that modern data analytics tools have been incorporated to enhance decision-making processes, improve reporting accuracy, and drive business performance. Organizations using advanced analytics tools tend to see huge benefits in speed, accuracy, improved reporting, and strategic decision-making. Modern technical analytical and reporting tools help leadership understand data by interacting with dashboards, graphs, and real-time data, which helps make a strategy based on the data. There are great benefits of using data analytics and reporting technology in leadership decision-making, it improves efficiency, productivity, and overall organizational growth.
Exploring the Applications of Natural Language Processing in Precision Health and Healthcare Research
Authors: Salve Margaret Joseph , Bais Vandana R. , Brahmane Preeti Vikas , Shikalgar Nilofar Feroz Khan
Published: December 2024

Precision medicine (PM) seeks to create customized diagnostic or treatment plans by integrating a patient's specific characteristics like biological data from imaging, laboratory testing, clinical phenotypes and health records. It can be useful to reduce disease-related health issues and financial burden on the individuals. If valid and accurate clinical data is gained it can help in developing applications to improve patient care and enhance personalized care. PM has undergone a revolution due to AI-driven decision support systems, which provide doctors the ability to customize patient care. These systems use ML algorithms to get meaningful insights by analyzing large datasets, like genomes, imaging and clinical data. NLP has a potential to transform patient care by enabling more accurate and efficient data analysis and communication. NLP can interpret, analyze and search through vast amounts of clinical data more easily and accurately. It can do this by understanding human language, process unstructured data, map out important information, and extract key concepts and meanings.
'Just AI' or 'AI Is Just'?
Authors: Al Naseri Heba
Published: December 2024

In the exploration of Artificial Intelligence's (AI) transformative role in precision medicine, it is evident that AI has the potential to revolutionize healthcare by enabling personalized and precise treatment strategies tailored to individual patient profiles. The integration of AI in healthcare, not only enhances the efficacy of treatments but also ensures a higher degree of safety by minimising adverse reactions. Through case studies and detailed analysis, the chapter “Just AI, or AI is just?” compellingly illustrates the benefits and challenges of AI in the realm of precision medicine.
AI Applications in Cardiovascular Disease Diagnosis and Management
Authors: Bouris Vasileios , Avgerinos Efthymios
Published: December 2024

Cardiovascular disease (CVD) encompasses a variety of heart and blood vessel conditions, including coronary artery disease (CAD), stroke, peripheral artery disease (PAD), aortic and peripheral artery aneurysms and venous pathology including deep vein thrombosis (DVT) and pulmonary embolism (PE). Artificial intelligence (AI) is increasingly being integrated into the diagnosis and management of cardiovascular diseases (CVD), offering innovative solutions that can enhance clinical decision-making, improve patient outcomes, and optimize healthcare processes. AI can make imaging diagnostics more reliable, easier and faster as well as accessible to wider and remote communities. AI can help clinicians make more accurate predictions for patients and implement an accurate medical plan that customizes healthcare individually.This is a review of evolving AI applications in cardiovascular disease diagnosis and management and how this disruptive technology will likely impact the training of doctors, medical research, and the practice of cardiovascular medicine substantially in the coming years.
Artificial Neural Network Algorithm in Nutritional Assessment
Authors: Oyekunle David Oyewumi , Esseme Alain Claude Bah , Oladipupo Matthew Abiola , Oseni Victoria Enemona , Adebola Nabeela Temitayo , Nwaiku Morgan , Nwanakwaugwu Andrew Chinonso , Matthew Ugochukwu Okwudili
Published: December 2024

In the current study, we used an artificial neural network (ANN) machine learning algorithm to construct an artificial intelligence-based nutritional assessment system. The algorithm used information from a user's regular meals as well as their preexisting health indicators to formulate a machine based nutritional assessment requirement. ANN-based nutritional evaluation approaches will make it possible to assess eating habits, recommend daily meals, and improve general health. In particular, we develop a machine learning technique to identify multiple food items by classifying them using an ANN machine algorithm and identifying suitable nutritional assessments using anthropometric, biochemical, clinical, and dietary (ABCD) data. Using an ANN machine learning model, the artificial intelligence system initially creates a number of proposals from the input. Next, using information from the unique ABCD nutritional evaluation, it creates feature maps for each proposal and used the ANN machine learning algorithm to classify diet interval and its composition.
Online Counselor Education, Technology, and Inclusion
Authors: Golden Sarah H. , Test Traci , Haley Melinda
Published: December 2024

Technology plays a multifaceted and integral role in online counselor education programs. It serves as a platform for curriculum and content dissemination and provides tools for developing skills and personalizing the online classroom. As technology is integrated in online counselor education programs, it is important for counselor educators to develop awareness, skills, and strategies to promote equity and inclusive practices using technology in teaching. Further, counselor educators need to be cognizant of skills and potential barriers that impact access when using technology in the online classroom. The purpose of this chapter is to provide an overview of how technology is used in online counselor education, professional practice, and examine how technology is used in preparing students for using and leveraging technology in practice. The authors share professional experiences and expertise as online counselor educators throughout the content. Finally, the chapter concludes with some practical implications for using technology in online counselor education.
Cultivating Compassion
Authors: Williams Jazzmine K. , Porter J'Briel E.
Published: December 2024

This chapter explores practical strategies and best practices for integrating cultural competence into online graduate counseling programs and supervision models. It emphasizes the critical role of counselor educators in modeling and fostering self-awareness among counselors-in-training, highlighting ethical considerations and the importance of cultural competence. The chapter broadens the understanding of minority identities beyond traditional demographics, expanding on the inclusion of diverse cultural characteristics and experiences into the concept of identity. It underscores the significance of self-awareness in education and practice by offering case studies and self-assessment tools for continuous improvement. The chapter provides a comprehensive guide for improving self-awareness and cultural competency in online curricula by integrating cultural awareness and ethical adherence and highlighting the need for continuous professional development.
Beyond Memorization
Authors: Nguyen Ha T. V. , Javorsky Kristin
Published: December 2024

This chapter examines the limitations of Vietnam's National Foreign Language Project 2020, particularly the ongoing struggle of many students to communicate effectively in English despite years of instruction. The chapter argues that the heavy reliance on rote memorization of vocabulary, a widespread practice in Vietnamese EFL education, leads to superficial learning and favors certain students over others. It explores key challenges in Vietnam's EFL landscape, such as teachers' pedagogical content knowledge, the quality of instructional materials, and the lack of effective student learning strategies. The chapter advocates replacing rote memorization with more equitable and effective approaches along with embedding the four-part processing model for word recognition and the four strands principle. It concludes with practical pedagogical strategies to illustrate how these methods can be applied in the Vietnamese context.
Fostering Pre-Service Teachers' Appreciation of Students' Linguistic Strengths via Translanguaging
Authors: Hibbs Brian
Published: December 2024

This chapter overviews the impact of a course unit on translanguaging within an ESOL teaching methodology course which was designed to advance pre-service elementary education teachers' awareness of the translanguaging approach in an effort to support their understanding and appreciation of the importance of acknowledging multilingual learners' linguistic funds of knowledge. The chapter begins with a review of the concepts of identity and power and the role translanguaging plays with respect to these phenomena. The chapter provides a summary of relevant literature concerning the integration of translanguaging into teacher education and then moves into a description of the components of the course unit on translanguaging, the research context for the study, and preliminary findings. Finally, the chapter ends with a description of the relevancy of the investigations' findings for both researchers and teacher educators.
Fostering Inclusivity in English Speaking Assessment
Authors: Ngo Duyen Nguyen Thien , Nguyen Mi Ha Thao , Duong Tham My
Published: December 2024

The present study explores the potentially beneficial washback effects of e-portfolio intervention for speaking assessment in an EFL class with a focus on inclusivity. Such data were obtained from the narrative form and semi-structured interviews with ten teachers and four administrators. The study's findings revealed positive washback effects. The teachers claimed a change of perceptions regarding the utilization of the e-portfolio assessments for students and the welcoming university climate that embraces all students' input while the administrators agreed on the possible advantages. This study pulls together stakeholder considerations showing that mutual influence, constant iteration and a high level of administrative support are required to maximize learning outcomes and maintain the deployment of e-portfolios as an assessment method for assessing students' English-speaking competence inclusively.
Enhancing EFL Writing Performance Through Differentiated Positive Psychology Interventions
Authors: Ariyanti Ariyanti , Setiawan Slamet , Munir Ahmad , Suhartono Suhartono , Anam Syafi'ul
Published: December 2024

The emergence of positive psychology interventions in foreign language classrooms has shown improvements in learner outcomes. However, more research is needed on how positive psychology can optimize second language acquisition experiences and writing performance. This mixed-methods study investigated the efficacy of positive psychology techniques in improving Indonesian university students' English writing skills across multiple areas. 60 students were randomly assigned to experimental and control groups. Assessments captured quantitative and qualitative performance differences before and after the intervention. Large effect size gains occurred for the treatment group. Students favored hope-based activities like feedback and consultations. Findings imply more positive versus negative feedback enhances writing motivation and outcomes. Further research is warranted on how positive psychology manifests in learners' complex experiences during foreign language acquisition and influences multifaceted writing performance.
The Correlation between Students' Learning Engagement and Their Academic Achievement
Authors: Ho Tien Xuan , Duong Tham My
Published: December 2024

The inclusion in English language education was evaluated by examining the relationship between academic achievement and high school students' engagement in EFL classrooms in this study. The grade point average (GPA) of students and the four components of their involvement—the cognitive, behavioral, affective, and agentic—were explored by the mixed-methods approach. The GPAs of 188 eleventh graders and levels of engagement in the EFL classrooms, were gathered through a closed-ended questionnaire. In-depth information was also obtained through a semi-structured interview. The results revealed that students frequently engaged in all four aspects of learning in EFL classes; however, the agentic component had the least impact on students' engagement. There was a noticeable correlation between the students' academic achievement and their learning engagement. The agentic dimension was closely linked to the affective aspect, which experienced the greatest influence. The study also offers some recommendations for teachers and learners to improve the quality in teaching and learning English.
The Implementation of Outcome-Based Education in EFL Courses in Vietnamese Higher Education
Authors: Van Le Tuyen , Vo Hieu Tran Minh , Tran Hong Kim
Published: December 2024

This chapter demonstrates teachers' practices and beliefs about the implementation of OBE in English as a foreign language (EFL) courses in Vietnamese Higher Education; particularly, they are the EFL courses for non-English majored students at a private university in Vietnam. The chapter begins with the introduction mentioning the objectives of the study. Second, a review of literature is provided with a theoretical background for the research problem under investigation. It consists of 1) a discussion of the concepts of outcome-based education and learning outcomes, 2) a discussion of constructive alignment of teaching, learning and assessment as a principle of OBE, and 3) beliefs about OBE. The chapter next turns to the research study that examines EFL teachers' practices and beliefs about the implementation of OBE in EFL courses, including a summary of the results, and recommendations for further research.
Empowering Change Through the Transformative Impact of Women Green Entrepreneurs on Our Sustainable Future
Authors: Ahmed Neetu
Published: December 2024

India's pursuit of sustainable development hinges on the role of women green entrepreneurs, who are pivotal in addressing environmental challenges while fostering economic growth. These entrepreneurs innovate with eco-friendly solutions, contributing to sustainability and creating socio-economic opportunities. However, they face barriers such as limited access to finance, inadequate support systems, and gender bias. Collaboration with corporate partners, academia, and international organizations is crucial for overcoming these obstacles and scaling their impact. By empowering women in green entrepreneurship, India can advance ecological goals and promote inclusive economic development.
Women's Entrepreneurship in Promoting Sustainable Development Goals Through Digital Space in Africa
Authors: Mumbire Ronika
Published: December 2024

This chapter explores transformative potential of women's entrepreneurship in advancing Sustainable Development Goals (SDGs) in Africa's digital landscape. Despite facing numerous challenges, women entrepreneurs leverage digital technologies to overcome barriers, drive innovation, and promote sustainable development. Through a comprehensive review of literature and empirical insights, this chapter highlights the pivotal role of women's entrepreneurship in achieving SDGs, particularly Goal 5 (Gender Equality), Goal 8 (Decent Work and Economic Growth), and Goal 12 (Responsible Consumption and Production). The chapter examines the opportunities and challenges faced by women entrepreneurs in Africa's digital space. It also showcases successful initiatives and policies supporting women's entrepreneurship and digital inclusion. The chapter concludes by emphasizing the need for stakeholders to empower women entrepreneurs, foster inclusive digital ecosystems, and unlock the full potential of women's entrepreneurship in driving sustainable development and achieving SDGs in Africa.
Constrained Portfolio Optimization Using Hybrid Nature-Inspired Metaheuristic Algorithm in Stock Market
Authors: Ashraf Zubair , Shamim Mohd Sarim , Noman Raghib , Shahid Mohammad , Ahmad Faisal , Sami Lamaan
Published: December 2024

The optimal financial allocation has long been considered one of the essential aspects of risk-budgeted financial sector investment, maximizing returns and minimizing risks. Therefore, optimization techniques have been proposed to maximize the Sharpe ratio, to solve risk-budgeted-constrained portfolio selection problem. This paper presents a hybrid optimization method by embedding stochastic fractal search (SFS) in the artificial bee colony (ABC) to solve risk budgeted portfolio selection model. The diffusion and updating phases of SFS in collaboration with the employed bees, onlooker bees, and scout bee phases of ABC have significantly improved the ability to exploit the search in the proposed hybrid algorithm. The efficacy of the proposed hybrid algorithm is evaluated by using the NSE 50 of the Indian Stock Exchange market. The optimal Sharpe ratio of the assets has been obtained for several levels of risk budgeting, and the results are compared with the well-known metaheuristic optimization algorithms.
Enhancing Cybersecurity by Deep Learning Models for QR Code Image-Based Attack Detection Using Lion Optimization Algorithm
Authors: Jambulingam Umamageswaran , Ganesan Indumathi , Chandrasekar T. , Shobana J. , Nalini S. , Lalitha S. D.
Published: December 2024

In today's digital landscape, the protection of sensitive data against rising cyber threats is paramount. Traditional methods for detecting cyber-attacks often fall short due to their limitations in accuracy and efficiency. This study proposes a pioneering solution: a hybrid approach integrating lightweight deep learning models like MobileNetV2 and ShuffleNet V2 with the Lion Optimization algorithm for feature selection. By leveraging these advanced technologies, the proposed method addresses the shortcomings of conventional approaches. It significantly enhances both the accuracy and efficiency of cyber-attack detection processes. Notably, the hybrid model achieves an impressive 99.82% accuracy in classifying and detecting various types of cyber-attacks, surpassing the performance of traditional CNN models.
VM Placement in Cloud Computing Using Nature-Inspired Optimization Algorithms
Authors: Shah Monali , Rajwar Dipankar , Dehury Jitendra Pratap , Kumar Dinesh
Published: December 2024

Cloud computing implements various techniques for the efficient utilization of computing resources. These resources are delivered over the internet, allowing users to access and manage them remotely. Often, these resources are provided to the users in the form of virtual machines (VMs). VMs are essentially software-based emulations of physical computers. In a cloud data center, numerous physical machines (PMs), also called servers, host various VMs. Placement of these VMs in Physical Machines is a critical task as there are many factors that need to be considered. Nature-inspired optimization algorithms such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony Optimization are inspired by natural phenomena and behaviour. These algorithms have been used in the past to generate near-optimal solutions in polynomial time for computationally intractable problems like VM Placement Problems (VPP). This chapter discusses how virtual machines are placed in cloud data centers using Nature-Inspired Optimization Algorithms.
Advanced Data Analysis on Global Suicidal Trends
Authors: Roy Apash , Sinha Rahul
Published: December 2024

This work utilizes an Exploratory Data Analysis (EDA) on global suicide data. Suicide is a multifaceted public health concern with complex determinants, necessitating a comprehensive investigation into its patterns and correlations. Through the application of various statistical techniques and visualization methods in R, this study aims to uncover temporal trends, demographic disparities, and socio-economic factors associated with suicide rates worldwide. By leveraging the flexibility and versatility of R programming, the work seeks to elucidate critical insights into the dynamics of suicide, including risk factors and protective measures. The ultimate objective is to contribute to evidence-based interventions and policies aimed at preventing suicide and promoting mental well-being. As a student pursuing a master's degree in data analytics, the utilization of R in this project represents an opportunity to apply cutting-edge analytical tools to address real-world challenges and make meaningful contributions to public health research.
Artificial Intelligence in Education
Authors: Çela Eriona , Fonkam Mathias M. , Vajjhala Narasimha Rao , Vedishchev Alexey
Published: December 2024

This chapter explores the transformative role of artificial intelligence (AI) in education, focusing on secondary and higher education contexts. This chapter provides a comprehensive overview of how AI technologies are reshaping educational practices through personalized learning, adaptive curriculum design, and enhanced student engagement. By examining current trends, such as AI-driven assessment tools, learning analytics, and adaptive learning systems, the chapter highlights both the opportunities and challenges AI presents for educators and institutions. Key ethical considerations, including algorithmic bias, data privacy, and equitable access, are addressed, emphasizing the need for responsible AI deployment in educational settings. The chapter also examines the evolving role of educators in AI-enhanced classrooms, where traditional teaching roles are augmented by AI's ability to support personalized learning experiences.
Emerging Trends of AI Technologies in the Higher Education Sector
Authors: Potluri Rajasekhara Mouly , Kilaru Madhavi
Published: December 2024

This chapter explores the transformative integration of artificial intelligence (AI) in education, examining how AI methodologies have reshaped teaching and learning practices in India and Kazakhstan. By analyzing trends such as data analytics for informed decision-making, language learning and translation tools, virtual assistants, and collaborative learning platforms, this chapter provides insights into the evolving applications of AI across these diverse educational landscapes. Through comparative analysis, it highlights both the similarities and unique approaches in AI adoption within the educational systems of India and Kazakhstan. Additionally, the chapter discusses the opportunities and challenges associated with implementing AI in education, focusing on ethical considerations and the regulatory mechanisms needed to ensure responsible and effective use of AI technologies in educational settings.
AI in Assessment and Feedback
Authors: Shivshankar Smitha , Acharya Nirmal
Published: December 2024

This chapter examines AI's transformative role in educational assessment and feedback, focusing on enhancing teaching and learning through technology. As AI reshapes traditional practices, the chapter emphasizes that AI in assessment should extend beyond automation, advocating for designs that encourage deep learning and student engagement. Using adaptive feedback, educators can support skill development and promote meaningful engagement with the material. The chapter presents a framework for AI-integrated assessments, stressing clear guidance, ethical considerations, and the active roles of both educators and students. It discusses tools like plagiarism detectors and adaptive learning platforms, underscoring the need to align AI with learning objectives and integrity standards. The framework also emphasizes the collaborative nature of AI in assessment—educators mentor students in using AI responsibly while students engage critically with technology. This approach balances AI's benefits with human insight, offering a model for inclusive, adaptive assessments.
Integrated Use of AI Educational Platforms
Authors: Sa Liow Melissa Li
Published: December 2024

This chapter addresses a critical gap in educational psychology concerning the integrated use of Artificial Intelligence Educational Platforms (AIEPs) and presents four key research objectives. Firstly, it investigates the effectiveness of AIEPs in supporting educators, school administrators, and students—collectively termed “AI users”—who work collaboratively on these platforms within educational settings. Secondly, the chapter analyzes the potential risks of AIEP usage among these users. Thirdly, it examines how AIEPs influence users' sense of relatedness, autonomy, and competence, developing a research framework informed by the Technology Acceptance Model (TAM) and Self-Determination Theory (SDT). Lastly, the chapter explores factors impacting users' perceived use and sustained adoption of AIEPs, expanding the existing literature. This chapter provides essential insights for educators, policymakers, and AIEP developers, offering a forward-looking perspective on the evolving role of AI in education and fostering a new generation of proficient users.
Student Adoption of AI Writing Tools
Authors: Malmous Mouad , Zaidoune Said
Published: December 2024

This chapter examines the rapid adoption of artificial intelligence (AI) technologies in higher education, focusing specifically on students' perceptions and attitudes toward AI writing tools within the Department of English Studies, Faculty of Letters and Humanities Ben M'sik, Morocco. Grounded in the Technology Acceptance Model (TAM), this study addresses a significant research gap in the Moroccan context, where few quantitative studies have explored factors influencing technology acceptance. To fill this gap, Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze survey data from 253 participants. The results reveal strong, positive relationships among TAM variables, identifying perceived usefulness and attitudes towards AI writing tools as primary predictors of actual usage. The findings suggest that educational institutions should highlight the potential benefits of AI tools, design accessible and user-friendly systems, and offer training to enhance student engagement and adoption of AI technologies.
AI-Powered Virtual Mouse Control Through Hand Gestures With Computer Vision
Authors: Paramarthalingam Arjun , Janarthanan Ashokkumar , Arivunambi Amirthasaravanan , Ariyangavu Srinivas Saravanan , Senthamaraikannan Hariprasath , Ganapathy Rekha
Published: December 2024

This article introduces an Artificial Intelligence (AI) enabled virtual mouse system that utilizes hand gestures and fingertip detection to operate computer mouse functions through AI and computer vision techniques. It serves as a convenient alternative to traditional physical mouse, offering users increased flexibility and accessibility in navigating and controlling their devices. In this article, the proposed work uses three modules such as OpenCV, MediaPipe and PyautoGUI to create the virtual mouse system. OpenCV library is used for its real-time computer vision functionality to help us to capture the hand using the web camera. The MediaPipe framework is used to detect the hand region using KLT Tracking Algorithm and then the K-cosine border tracking algorithm is used to identify various types of hand gesture movements to mimic the computer mouse cursor movement and scrolling operations. The PyAutoGUI module is used to perform appropriate mouse actions based on the recognized hand gestures.
AI in Identifying Climate Vulnerabilities in Urban Areas in Zambales
Authors: Mobo Froilan Delute
Published: December 2024

This study aims at identifying the potential of using artificial intelligence (AI) in estimating climate risks for the urban areas in Zambales, which are often affected by climate change risks. This study has used machine learning models and data analytics to establish regions and populations most vulnerable to flooding, extreme temperatures, and other climate shocks. Based on the collected data of weather conditions, population, social, and economic characteristics of the region, as well as the availability of necessary infrastructure, the AI framework is designed to make recommendations for further actions and improvements to the local governments and interested parties. The results help address concerns in sustainable urban development, behavioral change, and improvements in Zambales' likelihood of adapting to the emerging uncertainties of climate risks.
Cross-Cultural Gamification
Authors: Asrifan Andi , Kaddas Badruddin , Mulyadi Mulyadi , Pratiwi Widya Rizky , Supriadi Supriadi , Jabu Baso
Published: December 2024

Digital technologies have changed cultural production and consumption, making gamified apps important cultural artifacts. Despite their global reach, little is known about how cultural differences affect system design and user experience. Research has mostly ignored cross-cultural user interactions. We use Hofstede's cultural dimensions to analyze cross-cultural gamification to fill this knowledge gap. Our study shows that cultural differences considerably affect user engagement and gamified system effectiveness. In one culture, motivational affordances may work, but not another. We share case studies showing how culturally adaptive design improves user experiences. Our findings show that cultural sensitivity in design makes gamified apps more inclusive and effective. This has major ramifications for designers and researchers trying to maximize gamification tactics across cultures.
Gamifying the Classroom by Mediation of Technological Innovations in Enhancing Student Engagement and Learning in Ethiopia
Authors: Adula Metasebia , Kant Shashi
Published: December 2024

With an emphasis on the mediating function of technological advancements in Ethiopia, this study examines the impact of gamification in education on learning outcomes and student engagement. A survey was conducted with 400 participants, comprising educators, students, and professionals working in education technology. Confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) were used to determine the underlying characteristics of gamification in education, technological advancements, and learning results as well as student engagement. The data's appropriateness for factor analysis was evaluated using Bartlett's test of sphericity and the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy. The mediating impact of technology advancements in the link among gamification in education and student engagement and learning outcomes in Ethiopia was then investigated using structural equation modeling (SEM). The study's conclusions offer insightful information on how gamification in the classroom might raise student interest and boost academic performance.
Systemic Barriers and Support Mechanisms for Black Male Educators
Authors: Baranidharan S. , Chandrakala G.
Published: December 2024

This study investigates the challenges faced by Black male educators in K-12 education, focusing on recruitment, retention, and career advancement strategies. It reveals that Black male teachers experience systemic racism, lack of institutional support, and social isolation. To address these challenges, the study suggests targeted recruitment, better support systems, and community engagement. Additionally, it emphasizes the positive impact of Black male educators on student outcomes and calls for policies promoting equity and inclusion. Using a qualitative review of studies published between 2018 and 2024, thematic analysis identifies key issues and provides actionable insights for policymakers and educators.
Role of Hybrid Entrepreneurship in the Gig Economy
Authors: Singh Sandeep Kumar , Sharma Parth , Rohit
Published: December 2024

Hybrid entrepreneurship, where individuals balance full-time employment with entrepreneurial ventures, is reshaping the gig economy. This evolving model provides significant benefits, including increased flexibility, diversified income sources, and enhanced innovation. However, it also presents challenges, such as the need for updated labor laws, tax regulations, and adequate support structures. As technology advances and the nature of work changes, hybrid entrepreneurs will play a crucial role in driving economic growth and fostering new business opportunities. Addressing the regulatory and support needs of this growing workforce segment will be essential for maximizing the benefits of hybrid entrepreneurship and ensuring a balanced and resilient labor market.
Factors Influencing Social Media Privacy
Authors: Selvakumar P.
Published: December 2024

Social media privacy is a multifaceted issue encompassing the protection of personal information, the management of digital footprints, and the understanding of how data is used by various entities. This extensive data collection enables platforms to offer personalized experiences and targeted advertisements, but it also raises significant privacy concerns. Users often share personal details without fully realizing the potential implications, including the risk of their information being exploited by third parties for purposes beyond their control.One major concern in social media privacy is the issue of data security. Social media platforms are frequent targets for cyberattacks, and breaches can expose users' personal information to unauthorized parties. Additionally, the practices of data aggregation and selling by some platforms further complicate privacy issues. Data brokers collect and trade information, sometimes leading to misuse or identity theft.
Measuring the Systematic Literature Review of Social Media Impact on E-Government Innovation
Authors: Younus Muhammad , Nurmandi Achmad , Mutiarin Dyah , Prianto Andi Luhur , Manaf Halimah Abdul , Harini Ririn , Muntahanah Muntahanah , Ekowati Sri , Darmi Titi , Angraini Wulan
Published: December 2024

This study explores the characteristics of Government Innovation Through Social Media trends. Research related to government social media management has been carried out in the last ten years, and the primary goal of the government's own social media is to utilize social media technology in the public sector so that the government can be more transparent, open, accessible, and collaborative. It used Citespace and NVivo software to analyze 50 articles from 2012 to 2022. It found that the number of publications on Government Innovation Through social media has increased in the last ten years, with China having the most published research. However, it can also become problematic if the government's social media is not managed correctly. Research related to government social media management has been carried out in the last ten years, and the primary goal of the government's own social media is to utilize social media technology in the public sector so that the government can be more transparent, open, accessible, and collaborative.
From the Oversight of Power to the Culture of Voluntary Surveillance With Digitalization Omnipticon
Authors: Köseliören Mihrali , Ayhan Bünyamin
Published: December 2024

In the historical process from modernity to postmodernity, surveillance has changed with new communication technologies and brought new criticisms. With modernity, asymmetrical surveillance, defined by the metaphor of the panopticon, the surveillance apparatus of power, has been replaced; The omniopticon, the last point of surveillance in post-modern societies, has taken the metaphor and masked the supervisory function of power. The supervision function of the panopticon based on external pressure and coercion has turned into a 'pleasurable and entertaining' quality when it comes to the omniopticon. In order to elaborate these relationships, the study makes a conceptual discussion of surveillance culture before creating a narrative about the historical origin of the concept of panopticon. Based on these discussions, as a result of the effects created by new media, the concept of omniopticon as a form of voluntary surveillance is discussed within the scope of the research in order to reveal the appearance of surveillance culture in all areas of daily life within the voluntary effect.
Cybersecurity Measures for Protecting Data
Authors: Adeyinka Kehinde Iyioluwa , Adeyinka Taye Iyinoluwa
Published: December 2024

The base of this chapter rests on the basics of fundamental concepts and modern cryptography techniques and their use in secure communication systems. Moreover, apart from their role in ensuring data confidentiality, integrity, authenticity, and non-repudiation, some key cryptographic algorithms discussed include hashing, digital signature, symmetric encryption, and asymmetric encryption. It also points out the real use of the technology that has gained much momentum with blockchain technology, e-commerce, and encrypted communications, besides new developments in post-quantum security and quantum cryptography. It also considers the challenges of deploying cryptographic solutions within a high-stakes, dynamic environment and discusses how defenses can be hardened against evolving threats.
Data Privacy in E-Commerce
Authors: Mannan Mamun Abdul
Published: December 2024

To explore the challenges of data privacy in e-commerce and to identify best practices for protecting consumer data in online transactions. The chapter uses library and document analysis to review case studies, industry reports, and academic literature on data privacy in e-commerce.The chapter assesses how e-commerce platforms handle consumer data and the effectiveness of various privacy measures. The major findings of the chapter is that e-commerce platforms face significant challenges in protecting consumer data, including issues related to data breaches, inadequate privacy policies, and evolving threats. Best practices include implementing strong encryption, regular security audits, and transparent data handling practices. The discussion focuses on the importance of robust privacy practices in e-commerce and the need for platforms to stay ahead of emerging threats. The chapter recommends adopting comprehensive privacy practices, including encryption, regular security assessments, and privacy policies. E-commerce platforms should also prioritize transparency and user education.
A Emenda Constitucional 95 e seus impactos nos investimentos em MDE
Authors: Martins Michele Aparecida , Deitos Roberto Antonio , Reis Luiz Fernando
Published: December 2024

Este estudo objetiva compreender quais as principais consequências oriundas da Emenda Constitucional nº 95/2016 (Brasil, 2016a) em relação ao cumprimento das metas propostas pelo Plano Nacional da Educação (PNE/2014) (Brasil, 2014), dando ênfase à meta 20, que propõe destinação de recursos públicos para a educação. Para atingir o objetivo deste estudo, foi realizada uma análise qualitativa das legislações nacionais que amparam a educação, além de revisões e análises bibliográficas em artigos científicos que discorrem acerca da política de financiamento da educação brasileira e da austeridade fiscal sustentada pela Emenda em tela ou também denominada “PEC do Teto de Gastos”. Em suma, constatou-se que o estabelecimento de um limite de gastos destinados às despesas públicas primárias – despesas não financeiras – do Poder Executivo determinado pela EC nº 95 tem resultado numa mudança profunda nas contas nacionais no que se refere, de forma específica e particular, ao orçamento público da esfera federal do país, permitindo ao Estado brasileiro a destinação de parcelas significativas do orçamento da União para o pagamento da dívida pública em detrimento dos investimentos em políticas sociais e, consequentemente, em educação, o que inviabiliza a efetivação da meta 20 do PNE.
Assessment of oxidative stress biomarkers in patients before pharmacological treatment for rheumatoid arthritis
Authors: Hermann Emelli Fin , Kleibert Karine Raquel Uhdich , Nunes Paula Lorenzoni , Staudt Keli Jaqueline , Husein Raida Ahmad Musa Mheisen , Colet Christiane de Fátima
Published: December 2024

Rheumatoid Arthritis (RA) significantly decreases the functional capacity of 1% of the world's population, and it is believed that oxidative stress may be one of its triggering factors. Thus, the present study evaluated the biomarkers of oxidative stress in patients with rheumatoid arthritis before pharmacological treatment and their relationship with the DAS 28 score. This is an observational, cross-sectional study with a quantitative and analytical approach. Patients treated at a rheumatology clinic in the city of Ijuí/RS, with a diagnosis of rheumatoid arthritis, were selected and compared with the control group. Data collection took place between August and September 2020. In the 18 patients who participated in the research, higher values of SOD (p = 0.045), NP-SH (p ≤ 0.000) and TBARS (p = 0.005), and reduced levels of CAT (p ≤ 0.000) were found, when compared to the control. The enzymatic levels of the patients showed a significant association with body mass index. Furthermore, in this study, the pain complaint did not correlate with oxidative stress markers. This study showed changes in oxidative stress biomarkers in patients with RA before pharmacological treatment, demonstrating that these are indicative of a worse prognosis, which is estimated to be minimized with adequate pharmacological treatment.