bluuebunny/crossref_metadata_2025 huggingface dataset:
Top of the C.L.A.S.S.
Authors: Johnson Natasha N. , Johnson Thaddeus L.
Published: May 2024

This chapter highlights the direct correlation between effective leadership and student achievement. The development – and execution – of a concrete leadership framework is necessary for organizational structure and serves as a standard of excellence that surpasses any potentially harmful influences (such as race, socioeconomic status, family structure, gender, culture, and disability, among others). The establishment of this agenda occurs as individuals continually strive for self-fulfillment. Through this process, one can effectively guide others while working towards their own personal and professional objectives. Ultimately, this distinguishes successful leaders from the rest and represents the goal to which leaders should aspire: the ability to consistently serve as a reflective thinker and practitioner in all aspects of life. Only then can one's daily efforts toward self-fulfillment be evident in professional practice. Therefore, as underscored here, understanding the direct connection between leadership and student success is paramount.
Understanding and Creating a Sense of Belonging in Immigrant-Hispanic Students
Authors: Villarreal Angello , Pulliam Nicole , Londoño Juliana
Published: May 2024

The surge in immigrant-student populations in schools has disrupted conventional education approaches, presenting both challenges and opportunities. Language barriers, coupled with a dearth of support systems, mentors, financial aid, and health services, hinder the academic and socio-economic growth of these students. Mental health support, crucial for their well-being, faces disproportionate access challenges compounded by cultural stigmas. The cultural assimilation process further compounds the hurdles for immigrant students in American classrooms. Balancing academic rigor, social integration, and reconciling new knowledge with their backgrounds strains their adaptation. Educators' lack of understanding exacerbates these challenges, hindering effective teacher-student connections. This chapter aims not only to delineate the challenges faced by Hispanic-immigrant students but also to highlight overlooked aspects such as mental health support, counseling, and the imperative need for a sense of belonging within educational environments.
A Comparison Between Natural and Artificial Intelligence in the Context of Learning
Authors: McNamara Sean , Rajkumar Lakshmi
Published: May 2024

Teachers strive to give their best to impart knowledge to students, to help improve their knowledge, and to help find success in academic endeavors. Keeping up with current trends and evolving changes in teaching and learning are two of the biggest challenges in education. This chapter explores early ideas about making sense of the world, neuroanatomy and brain structure, the functioning of the human mind as it pertains to learning and memory, aspects of natural intelligence, what is artificial intelligence, the comparison between generative AI (Artificial Intelligence) and natural learning processes, and a brief discussion on the possibility of artificial intelligence replacing natural human intelligence. The chapter consists of three major “parts,” early ideas of knowledge and understanding, a more “modern” scientific summary of how learning works (which we will refer to as “natural learning”), and finally a brief look at how AI learning works.
Artificial Intelligence and Machine Learning and Its Application in the Field of Computational Visual Analysis
Authors: Pandey Digvijay , Nassa Vinay Kumar , Pandey Binay Kumar , Thankachan Blessy , Dadheech Pankaj , Mahajan Darshan A , George A. Shaji
Published: May 2024

Artificial intelligence and machine learning applications in image processing are examined in this chapter. It covers AI methods including supervised, unsupervised, reinforcement, and deep learning. Genetic algorithms, rule-based systems, expert systems, and fuzzy logic are AI methods. SVM, decision trees, random forests, K-means clustering, and PCA are machine learning methods. CNN, RNN, and GANs are utilised for object recognition, classification, and segmentation. The chapter discusses how artificial intelligence and machine learning affect accuracy, efficiency, and decision-making. The need to choose proper measurements and procedures for assessment and performance analysis is also stressed. Ethics like justice, privacy, transparency, and human-AI cooperation are covered in the chapter.
Advanced Digital Data Processing Using Cloud Cryptography
Authors: Pandey Digvijay , Pandey Binay Kumar , Paramashivan Mukundan Appadurai , Mahajan Darshan A. , Dadheech Pankaj Dadheech , George A. Shaji , Hameed A. Shahul
Published: May 2024

Cloud computing uses the internet instead of discs or memory. Computing services include servers, databases, networks, and programmes. The primary benefit of cloud computing is easy and cheap data backup and access from anywhere. Cloud storage doesn't store consumer data, raising safety concerns. Cloud backup and storage users may not know how data is transported. The user is unaware a third party is secretly accessing their data. For safety, we offer numerous encryption algorithms. This book chapter covered cryptography and cloud computing.
The Impact Child Abuse Has on Well-Being Throughout the Life Course
Authors: Haug Stacey Marie
Published: May 2024

In this exploration of child abuse and its impact on survivors' lives and well-being, well-being was defined as feeling physically, mentally, and emotionally well and functioning positively as an individual and a member of society. The primary categories of child abuse addressed were physical, psychological, and sexual abuse and neglect. Intimate personal violence as a form of child abuse was also addressed. Short- and long-term physical, psychological, social, and individual outcomes for child abuse survivors throughout the life course were explored. Interventions and strategies aimed at helping child abuse survivors and their caregivers recover from the aftermath of child abuse were explored. This work focused on what child abuse survivors and their caregivers found the most helpful on their journeys to well-being. While well-being outcomes for survivors of childhood abuse were found to be deleterious in many psychological, social, and individual areas, recovery and improvement in overall well-being were found to be possible for both child abuse survivors and their caregivers.
Strengthening Families Through Crisis Management
Authors: Gamez Ana Maria , Harrell Aamber
Published: May 2024

Strengthening families through crisis management in high-risk situations can prevent a catastrophe and save lives. This chapter defines a crisis and high-risk behaviors such as self-harm, suicidality, and harm against others that affect children's safety and disrupt the family system. It discusses the important role that medical professionals play in managing crises in children, youth, and their families. This chapter discusses some of the risk factors that increase the risk of a crisis and protective factors that mitigate and increase resiliency in children and adolescents. Communication strategies and other recommendations for supporting high-risk children and family systems are provided to help support the family system.
Understanding the Impact of Mental Illness on Parenting in Single-Mother Households
Authors: Sisay Thomasina Mosley , Gordon Kristina West
Published: May 2024

This chapter explores the intricate relationship between mental illness and parenting in the context of single-mother households. Mental health issues can significantly affect a parent's ability to provide emotional support, maintain consistency, and promote educational success and overall well-being in their children. By examining the strains, traumas, theories, impacts, and challenges faced by single mothers coping with mental illness and the experiences of their children, this chapter aims to shed light on the importance of support systems, coping strategies, and interventions to enhance the outcomes for both mothers and their children.
Academics in Exile
Authors: Aldous Sara Mohammed , Ismail Ghaith
Published: May 2024

Education is the most potent weapon that can be used to alter the world; this is a well-known adage in today's society. Individuals are increasingly interested in acquiring diverse information that they may apply in their future undertakings. Afghan professors and students faced risks to their lives and well-being, as well as academic losses. They were and still are repressed between resistance and the possibility of survival. Exiles frequently suffer from mental trauma as a result of being exposed to violent, contentious, and abusive settings. Different international NGOs and donor organisations give such services to Afghan exile professors and students so that they may cope with the mental disturbance much better. Scholarships, language development programs, recognition, accreditation, and financial assistance support such groups to deal with the challenges.
Educational Challenges in Refugee Camps and Conflict Zones
Authors: Kayyali Mustafa
Published: May 2024

This chapter embarks on an intricate exploration of the manifold educational challenges that confront individuals in the tumultuous and often perilous realms of refugee camps and conflict zones. In these settings, education takes on a profound and multifaceted significance, serving not only as a means of acquiring knowledge but as a beacon of hope and a cornerstone of resilience. The authors delve into the distinct and daunting obstacles faced by educators, students, and entire communities as they navigate the turbulent waters of such environments. Through a comprehensive lens, they examine the critical roles educators play in these challenging landscapes, where they often find themselves contending with limited resources, security concerns, and the immense responsibility of nurturing the minds of the next generation. It calls upon educators, policymakers, and the global community to recognize the significance of addressing these educational challenges and nurturing the human spirit's enduring pursuit of knowledge, irrespective of the adversity it faces.
Teachers' Professional Development in the Emergency Contexts
Authors: Shohel M. Mahruf C. , Rashedujjaman S. M. , Sofin Mahbuba Rahman , Saurav Kaysar , Siddik Mohammad Abu Bakar , Akter Tahmina
Published: May 2024

This book chapter explores the critical role of professional development in equipping teachers to navigate the challenges and barriers of emergency contexts. It focuses specifically on the resilience exhibited by teachers in teaching the Rohingya refugees in Bangladesh. The Rohingya refugee crisis, characterised by forced displacement and limited access to education, presents unique challenges and barriers for both teachers and students. Drawing upon secondary sources and theoretical frameworks, this chapter unpacks the various dimensions of teachers' professional development for both the Rohingya and the host community teachers in such adverse circumstances in refugee camps in Bangladesh. It highlights the adaptive strategies employed by the Cox's Bazar Education Sector and the teachers themselves to enhance their pedagogical skills, foster socio-emotional well-being, and address the diverse needs of the Rohingya learners. Furthermore, the chapter analyses the organisational support systems, policies, and interventions aimed at promoting teacher resilience and effectiveness in emergency settings.
The Russian-Ukrainian Conflict
Authors: Al Badawi Habib , Zreik Mohamad
Published: May 2024

After a long military buildup, Russian recognition of the unilaterally declared Donetsk People's Republic and the Lugansk People's Republic, and entry of the Russian Armed Forces into the Donbass region of Eastern Ukraine on February 21, 2022, the Russian forces launched a military campaign against Ukraine on February 24, 2022. Kyiv and other cities around Ukraine were bombed on February 24 after Russian President Vladimir Putin announced a military action to “disarm and de-Nazify Ukraine” in a speech. The purpose of this research is to shed light on why Russia and Ukraine are at odds and how NATO has played a part in fueling this old war. Since Ukraine was a part of the Soviet Union, this study gives some context for understanding both Russia and Ukraine. In order to better comprehend the nature of the conflict, this study employs a descriptive analytical approach based on narrative and connections between data points.
AI in Academic Libraries
Authors: Tzanova Stefka
Published: May 2024

This chapter discusses the implementation of artificial intelligence (AI) in academic libraries and the impact of AI related technologies on various library services. AI impacts research and educational activities in academic institutions so they can provide adequate operations and collaborative technologies in order to support diverse curricula and research. The complexity of research workflows and their variability couples with increasing demand for effective personalized education, so it acts as a driving force for application of AI related technologies. AI assisted library services demand reimaging traditional libraries' roles, so that librarians would become not only users of AI technologies but also co-creators and experts capable of conceptualizing AI driven services to library patrons. That requires librarians to promote AI literacy as a framework encompassing research literacy and data literacy, and understood as a necessary skill set for effectively communicating in an AI driven medium.
Optimizing Library Services Through the Integration of Artificial Intelligence Tools and Techniques
Authors: Bairagi Mandira , Lihitkar Shalini Ramdas
Published: May 2024

The use of artificial intelligence (AI) has transformed several industries, including research and education. Due to relevance and global competitiveness, in the present scenario incorporation of artificial intelligence in library workflow is inevitable. Libraries are changing in the age of information explosions to keep up with technological improvements and provide access to the greatest information while avoiding obstacles. This chapter provides a thorough description of the use of artificial intelligence (AI) tools and techniques in distinct sections of Library management and services. Creating devices that can imagine and work like humanoid brains is the aim of artificial intelligence. Artificial intelligence integration has the potential to improve library space intelligence and eliminate physical obstacles. The chapter offers a complete grasp of how AI could alter library infrastructure and services in the future, leading to better outcomes for readers, educators, researchers, and students.
AI-Driven Innovation in Higher Education Marketing
Authors: AlBalushi Ammar Abdulrahman , Al Bolushi Ali Younis
Published: May 2024

This book chapter systematically reviews AI's transformative impact on higher education marketing. It further explores the challenges of integrating AI within existing educational frameworks, emphasising the importance of AI literacy in curricula and addressing ethical considerations like data privacy and the balance between technology and human interaction. Moreover, it synthesises diverse literature to develop a framework for utilising AI in marketing, focusing on strategy, stakeholder experiences, and AI-driven initiatives. The research addresses AI integration challenges, AI literacy, and ethical concerns and aligns with Oman's Vision 2040 and digital strategies. It highlights the current state of AI in education and pinpoints gaps in existing literature, paving the way for future investigations within the Omani context. It emphasises strategic planning, campaign execution, and balancing technology with human aspects, offering insights for Oman's institutions to effectively utilise AI, highlighting current trends and future research directions in the Omani context.
Mapping Redox Conditions and pH in Indian Drinking Water System Using Machine Learning Models
Authors: Umamaheswari P. , Ramaswamy V.
Published: May 2024

The successful utility of groundwater resources requires estimation of contaminants occurring at a regional scale and for the risk estimation of drinking water supplies. Based on the patterns and predictions of the ground water age and temperature conditions, areas and volumes of the locations throughout India have been verified, and they have opted for the proportion making of the drinking water resources. The data from 300 to 500 drinking water wells have been collected from the government dataset belonging to 18 states in India. The pH and oxygen levels of the drinking water have been considered for the project and are used for the classification of data and this classified data is being used for the mapping of locations over the Indian map. Thus, the results are to be visualized at the end of the project. Accuracy modulations have been done based on the machine learning models used for the execution.
Unravelling Climate Dynamics
Authors: Gupta Neha , Tanwar Priya
Published: May 2024

The scientific community is under pressure to investigate novel methods for understanding and forecasting the complex behaviors of the changing climate, as the modern era is characterized by hitherto unseen problems. The aim of this chapter is to examine the predictive power of machine learning algorithms for climate change, with the goal of advancing proactive and well-informed approaches to mitigating the effects of global environmental changes. The chapter is based on a thorough evaluation of prior research, empirical evaluations, and case studies that highlight effective ML applications in climate change prediction. The combination of these results offers insightful information on how machine learning (ML) could be used in addition to conventional climate models to promote a more comprehensive understanding of climate dynamics and improve our capacity to predict and respond to environmental changes in the future.
Time Series Forecasting Techniques for Climate Trend Prediction
Authors: Zakari Rufai Yusuf , Lawal Zaharaddeen Karami , Kalinaki Kassim , Maiwada Umar Danjuma
Published: May 2024

Climate change is a pressing global issue that profoundly impacts ecosystems, economies, and societies. Accurate climate trend prediction is crucial for informed decision-making and mitigation strategies. This study focuses on time series forecasting techniques as vital tools in predicting climate trends. It explores the complexities of climate time series data and the challenges associated with the data. The study explores traditional methods like Autoregressive Integrated Moving Average (ARIMA), highlighting their applicability and limitations. It also showcases the power of machine learning and statistical techniques in addressing climate data intricacies through real-world examples. In the era of technology, deep learning (DL) approaches, including recurrent neural networks, Long short-term memory (LSTM), Gated Recurrent Unit (GRU), and transformer-based models, are emerging for climate change forecasting. The study looks ahead to ongoing research and trends in climate time series forecasting, outlining challenges and promising areas for exploration.
Identifying a Research Problem
Authors: Nguyen Thuy Ho Hoang , Cao Thanh-Hai L. , Le Hai Thi Thanh
Published: May 2024

The current chapter concentrates on both the theoretical and practical aspects of identifying a research problem, one of the most important steps in the research process. Based on the scholarship in the disciplines of applied linguistics and language education, this chapter attempts to provide a thread covering key concepts, characteristics, stages and strategies in facilitating researchers to identify a research problem. The final objective is to outline a methodical approach to developing a specific research question that could be useful for data collection and even data analysis procedure. It is expected that the chapter would be able to equip researchers and practitioners with a thorough set of guidelines on how to identify a research problem in the targeted disciplines, thus contributing to the existing body of knowledge of the research process.
Experimental Research
Authors: Truong Tran Minh Nhat , Mahmood Rizgar Qasim
Published: May 2024

Nowadays, researching and innovating teaching processes is vital for teachers at higher education to improve their teaching quality, especially in applied linguistics and language education. experimental research is a useful approach for researchers, educators, teachers and managers at universities. The chapter may aim to achieve the following objectives: (1) Present a comprehensive overview of experimental research methodologies; (2) Provide guidelines for designing experiments, including defining research questions, selecting appropriate variables, and establishing control conditions; (3) Discuss various data collection methods, including observation, surveys, and laboratory experiments; (4) Detail the importance of random assignment and statistical analysis techniques to ensure robust results; (5) Highlight ethical considerations and potential limitations in experimental research; (6) Showcase examples of successful experimental studies in different disciplines to provide practical insights.
Antecedents and Pitfalls of Blended Learning for a Cogent Group of Students Post COVID-19
Authors: Dam Supriya
Published: May 2024

This study explores the implementation of blended learning in Tripura by observing undergraduate students across the state. Based on statistical tests such as X2, and one-way ANOVA, post-hoc Tukey's HSD, a considerable number of students consider blended learning an essential part of the curriculum. The usability response to online learning tools and resources demonstrates a strong correlation between usability variables. The results also suggest that students react favorably to online learning tools and materials, which are preferred over face-to-face interactions for storing, accessing, and retrieving information. Blending has proved effective at minimizing learning losses, but the amount of technological support required for its implementation has implications for available resources and societal needs.
The Development of Blue Economy on the Local Level
Authors: Roziqin Ali , An-Nafisah Shofiyya , Romadhan Ach Apriyanto , Rivaldan Muh. Januar Galang
Published: May 2024

Indonesia has a fantastic chance to develop sustainable marine resources. The blue economy is the umbrella term for sustainable economic growth in the maritime industry. This study locus uses the Sumenep Regency as an example to illustrate the potential for creating a blue economy in regions with an abundance of marine resources. Even though many countries have developed the blue economy concept in marine management, in Indonesia there are still limited studies that discuss the blue economy, especially in the local context. This study indicates that Sumenep Regency has great opportunities for developing blue economy practices, with abundant biodiversity and marine resources including salt production, carbon absorption, marine fisheries and marine aquaculture, and marine tourism. Referring to the sub-sectors that have been successfully identified, in the future Sumenep Regency can develop the blue economy more intensively through strengthening policy and institutional design aspects, including strengthening implementing human resources and target groups.
Future Trends in Finance and Technology Towards an AI-Integrated Digital Economy
Authors: Boopathi S.
Published: May 2024

In this chapter, the evolving landscape of finance and technology, focusing on the integration of artificial intelligence (AI) into the digital economy, has been explored. The transformative impact of AI on financial services, highlighting key trends and opportunities, is discussed. Advanced data analytics have been personalized for learning customer experiences and AI-driven innovations in traditional banking, investment, and insurance sectors. The chapter also examines the challenges and ethical considerations accompanying this technological shift, including data privacy concerns and algorithmic biases. Future prospects for AI in finance, emphasizing the importance of collaboration between industry stakeholders and regulatory bodies, have been explored through AI adoption and the sustainable digital economy.
Sustainable Development Goals (SDGs), Halal Supply Chain Management, and the Role of ESG in Promoting Ethical and Eco-Friendly Practices
Authors: Ghalih Muhammad , Chang Chia-Hua , Johennesse Lee-Anne Cassandra
Published: May 2024

The chapter delves into the convergence of Sustainable Development Goals (SDGs); halal supply chain management (HSCM); and environmental, social, and governance (ESG) principles, highlighting the potential of ESG integration into HSCM to advance key SDGs, notably poverty reduction, sustainable agriculture, gender equality, and responsible consumption and production. It critically analyzes the hurdles and prospects in embedding ESG values in the halal supply chain, offering strategic insights for stakeholders to bolster their sustainability initiatives.
Approaches to Agricultural Education Research Informed by Diversity, Equity, Inclusion, and Access
Authors: Leman Amy M. , Martin Michael J. , Hartmann Katherine A. , Griffith Aisha N.
Published: May 2024

To adequately research school-based agricultural education (SBAE), it is important to recognize the diversity of viewpoints. This chapter takes an ecological view, proposing the Ecological Model of Agricultural Education. The model considers levels of influence significant and the diversity within. The core are SBAE teachers and students, their identities, and interactions. Surrounding the core are connections between individuals and FFA chapters, such as differences in geographic locations. The exosystem includes policies and procedures governing national agricultural education, including FFA. The macrosystem is the global agricultural industry. The ecological system describes the interplay of factors influencing SBAE and offers a lens to explore the diversity, equity, inclusion, and access in the system. The chapter explores trends in SBAE research, organized by the ecological model and encourages the use of critical approaches and participatory methods in future SBAE research.
Exploring the Consumer Profile of the Museum of Futebol Clube do Porto Through Online Reviews
Authors: Carvalho Martins Raquel Alexandra , Ramos Célia M. Q.
Published: May 2024

For effective strategic planning and focused marketing campaigns, it is essential to understand the museum's target audience and how cultural tourism can influence sports tourism. The study aims to investigate the satisfaction and experience of international visitors to the Museum of Futebol Clube do Porto and their profiles. The TripAdvisor reviews were considered to gather information on the Museum of Futebol Clube do Porto's target audience using a business intelligence tool to process, analyze, and draw conclusions from the data. Insights regarding the geographic and gender distribution of reviewers and their overall evaluations of the museum were discovered by analysing TripAdvisor reviews.
Tomorrow's Travel Companion
Authors: Al-Romeedy Bassam Samir
Published: May 2024

This chapter investigates the impact of artificial intelligence (AI) on shaping the future of the tourism industry. Given the advancements in AI technology, its transformative potential in various facets of the tourism sector is substantial. The chapter delves into the applications of AI, including personalized travel recommendations, chatbot customer service, demand forecasting, and smart destination management. It explores both the advantages and challenges linked to implementing AI in tourism, covering ethical considerations and workforce implications. The findings emphasize AI's capability to enhance customer experiences, streamline operational processes, and foster more sustainable and resilient tourism practices. The chapter concludes with recommendations for industry stakeholders on maximizing the benefits of AI while addressing associated challenges to shape a future aligned with the potential of this technology.
Unlocking the Power of Data
Authors: Al-Romeedy Bassam Samir
Published: May 2024

Marketing knowledge and information systems (MKIS) are instrumental in the tourism industry, enabling organizations to collect, analyze, and leverage marketing data for strategic decision-making and gaining a competitive advantage. Their effective use is vital for modern marketing strategies, enhancing competitiveness, and meeting evolving customer demands. MKIS significantly impacts tourism destination management by improving branding, competitiveness, and visitor experiences. The chapter emphasizes the importance of continuous adaptation and innovation, urging tourism marketers to embrace MKIS as essential tools for staying ahead in the dynamic industry. It explores how MKIS empowers marketers to tailor strategies, personalize customer experiences, and optimize promotions based on real-time information. The chapter contributes valuable insights into the strategic application of MKIS in addressing challenges and capitalizing on opportunities within the competitive tourism environment, enriching the existing literature in the field.
Utilisation of Marketing Information Systems in the Tourism Marketing Sector
Authors: Abu Hmeidan Tahreer M.
Published: May 2024

This chapter examines marketing information systems (MKIS) crucial significance in tourism. Given the rapid changes in the tourism industry due to technological breakthroughs and evolving consumer behaviours, marketing professionals must prioritise efficiently using management information systems (MIS). This chapter thoroughly examines the basic principles of management information systems (MIS) and how they can be used to improve marketing tactics in the tourism industry. By thoroughly examining specific instances and current patterns within the field, the authors explore how management information systems (MIS) enhance decision-making procedures, customer relationship management, and overall marketing effectiveness in the ever-changing tourism business. The chapter includes background about marketing information systems and their influence on the tourism sector, the goals of adopting the MKIS for this sector, challenges and opportunities, and case studies.
Rainfall Prediction Using Machine Learning
Authors: Kumar A. V. Senthil , Roshan S. Antony , Dutta Amit , Ray Samrat , Masadeh Shadi R. , Lakshmi G. Prasanna , Michalopoulos Dimitris , Nyayapati Rakesh , Musirin Ismail Bin , Kaur Gaganpreet
Published: May 2024

Rainfall prediction is a crucial aspect of weather forecasting and plays a significant role in various fields, including agriculture, water resource management, and disaster preparedness. In this chapter, the authors explore the application of two machine learning algorithms, random forest and cat boost, for predicting rainfall events. They utilize historical weather data from a specific location to train and evaluate the performance of both models. The evaluation metrics employed include accuracy, precision, recall, and F1-score. The findings suggest that incorporating additional features, such as humidity, can enhance the predictive capabilities of both random forest and cat boost. Overall, this project demonstrates the effectiveness of random forest and cat boost in predicting rainfall events.
Filter-Based Feature Selection Using Machine Learning Algorithms and Physical Indicators for CAD Prediction
Authors: Subbulakshmi P. , Vijayaraj Anu Ragavi
Published: May 2024

Coronary artery disease (CAD) is a significant threat, especially in developing nations, demanding timely detection for effective intervention. Traditional tools like electrocardiography and angiography have been pivotal for CAD prediction, but the rise of machine learning (ML) introduces new possibilities for computer-aided diagnosis. This chapter unveils an innovative CAD detection method that synergizes filter-based feature selection with ML classifiers, notably enhancing their efficacy. Various filter-based techniques generate distinct feature subsets, and features commonly selected through majority voting significantly improve the accuracy of the k-nearest neighbor (KNN) classifier, rising from 88.31% to 89.61%. This underscores the positive impact of feature selection on the KNN classifier's accuracy, promising utility in broader medical datasets. The proposed method holds potential for advancing CAD diagnosis and prognosis, particularly in resource-constrained settings, by minimizing false positives.
Explainable AI (EXAI) for Smart Healthcare Automation
Authors: Shafik Wasswa , Lakshmi D.
Published: May 2024

The rapid integration of artificial intelligence (AI) into the healthcare sector has opened up new opportunities for smart healthcare automation, transforming medical diagnosis, treatment, and overall patient care. However, the widespread adoption of AI algorithms in healthcare comes with challenges, particularly regarding transparency and explainability. This chapter explores the concept of explainable AI (XAI) and its crucial role in smart healthcare automation. The authors discuss the significance of XAI, various techniques for achieving explainability, and their potential applications in healthcare. Through case studies and success stories, the authors showcase real-world applications of XAI in radiology and chronic disease management. Lastly, they highlight future directions in XAI research for smart healthcare automation and emphasize the implications for healthcare providers and policymakers. By embracing XAI, the healthcare industry can unlock the full potential of AI while ensuring transparency, fairness, and improved patient outcomes.
Bibliometric Perspectives on Sustainable Tourism and Future Research Agenda
Authors: Prakhar Prakhar , Jaiswal Rachana , Khan Mohammad Intkhab Alam
Published: May 2024

Tourism, a global economic engine, has faced escalating concerns regarding environmental and sociocultural repercussions amid its rapid expansion. This research explores the imperative paradigm shift towards sustainable tourism development, emphasizing the prioritization of enduring ecological equilibrium and conscientious resource management. Employing a robust bibliometric study utilizing the Scopus database, the investigation meticulously analyzes the vast landscape of academic scholarship. This comprehensive inquiry discerns influential contributors, unveils trending topics, and identifies emergent areas within sustainable tourism. From the intricate relationships between authors and countries to thematic clusters encapsulating diverse issues, the study provides a panoramic view of the sustainable tourism discourse. Serving as a compass for future research endeavors, this chapter not only addresses current concerns but also outlines a trajectory for a more responsible and environmentally conscious tourism industry. With its insights into social, managerial and policy implications, the research positions sustainable tourism as a catalyst for positive change, advocating for community empowerment, inclusivity, and gender equality. Ultimately, this research contributes to the evolving narrative of sustainable tourism, illuminating pathways for a harmonious coexistence between economic prosperity and environmental stewardship.
Scoping Sustainable Tourism Transformation in the Indian Himalayan Region
Authors: Rout Prakash Chandra , Madhurima
Published: May 2024

The Indian Himalayan region (IHR) is witnessing a burgeoning tourism industry, driven by its awe-inspiring landscapes and rich cultural heritage. However, this growth raises concerns about environmental degradation, cultural erosion, and socio-economic disparities. This research explores the imperative of sustainable tourism transformation in the IHR, aiming to balance economic development with environmental conservation and cultural preservation. Drawing on multidisciplinary literature, it examines the complexities and challenges inherent in sustainable tourism development and offers actionable recommendations for fostering sustainability in the region. The study underscores the need for collaborative efforts among stakeholders at all levels to enact transformative policies and create an enabling environment for sustainable tourism development in the IHR.
Doing Solo
Authors: Singh Niharika , Aier Bendangienla
Published: May 2024

There has been constant growth in female solo travellers across the globe along with India. But any possible discussion on solo women travellers in India cannot go without debates on safety and security concerns of travellers, as India is often mentioned as a dangerous and risky destination, mainly for women. And then there are indigenous women from Northeast India, who are often reported to be harassed during their stay in mainstream India, due to their Mongoloid looks. As such, this chapter is a qualitative approach to investigate experience of female solo travellers from Northeast India when they travel to Mainland India. In the study, the authors have used reflexive thematic analysis to examine the interview data. One overarching theme—being an Indian from the Northeast India—encapsulates four themes: (a) the ignorance among Indians, (b) Northeastern Indians are considered easy, (c) harassment is real, (d) safety is a genuine concern.
Informality and Tourist Development on the Ecuadorian Coast
Authors: Molina Myriam Yolanda Sarabia , Rodríguez-Pallas Ángel , Vaque Reyes Gianella Lissette
Published: May 2024

The informal economy is a complex phenomenon occurring in various forms and degrees worldwide. In Ecuador, the informal sector represents 46.5% of the economy. This research aimed to analyze the informal trade in the tourism sector of Playas Cantón, Ecuador and its relationship with the regional economic development. A quantitative approach through a structured survey with actors involved in tourism (tourists, residents, informal traders, tourism entrepreneurs, and local authorities) was used during March-April 2023, reaching a sample of 150 participants. Results showed that the informal sector is an essential part of the tourism economy in Playas. Multiple causes/factors drive and sustain it: lack of formal job opportunities, flexibility in working hours, lack of regulation and sanitary control, and insecurity in the area. Implementing policies and measures to address informality is necessary, including formalizing and training informal workers to strengthen regulation and control of informal activities and ensure sustainable development.
Effect of Curing Period, Plant Hormone and Storage Conditions on the Sensory Quality of Fried Potato (Solanum tuberosum L.) Chips
Authors: Ahmed M.
Published: May 2024

Purpose: In developing countries, 40-50% of horticultural produce is lost yearly due lack of adequate cold chain technology which necessitates the search for a means of storing this produce under ambient conditions with minimal loss to both nutritional and sensory qualities. This study was conducted to assess the effect of the curing period, Abscisic Acids (ABA) levels and storage conditions on the sensory attributes of fried potato chips after 12 weeks of storageResearch Method: The experiment was a Split-Split-Plot Design (SSPD) with curing period, storage condition and ABA rates allocated to the main plot, subplot and sub-sub-plot respectively. Treatments were replicated three times; each consisting of 20 potato tubers, and data on sensory properties were taken at the end of the storage period. The data were subjected to Analysis of Variance (ANOVA) using Genstat Discovery Edition. Means that showed significant differences were separated using Duncan’s Multiple Range Test (DMRT) at a 0.05% level of probability.Findings: The results showed that curing, storage conditions and ABA rates had a highly significant influence on the organoleptic quality of fried potato chips after storage for 12 weeks under ambient storage conditions. Thus for the best sensory quality of fried potato chips in the study area, tubers should be treated with 4 ppm ABA, cured for seven days, and stored under a shaded pit or heap storage method.Research Limitations: The study evaluated the influence of curing, ABA and storage methods on the sensory attributes of fried potato chips under ambient conditions. The experiment is limited to four curing periods, three ABA rates, three storage conditions and one potato variety (cv Marabel).Originality/Value: This research offers a solution to the distressing problem of huge postharvest loss of potatoes in most developing countries due to a lack of reliable power supply, financial resources and the technical know-how to deploy modern technologies for postharvest management of potato tubers.
AVG Treatment at Pre-harvest to Delay Ripeness on Booth7 Avocado Based on the Activity of ACC Synthases and ACC Oxidase Enzymes
Authors: Nguyen V. T. , Nguyen N. T. , Fayyaz F. A. , Tran D. T. , Le V. T. , Tran T. H.
Published: May 2024

Purpose: The Booth7 Avocado (Persea americana Mill.) is an unusual fruit, and one of the most rapidly ripening at about 5 to 7 days after harvest. The ripening period for climacteric fruit is triggered by ethylene production; changes in ethylene intensity appear together with events of other changes in the fruit, including changes in pigment and sugar content. Hence, delaying the ripeness of Booth7 Avocado is essential in the preservation.Research Method: Our study used aminoethoxyvinylglycine (AVG) treatments with 200 µL L-1, 400 µL L-1, and 600 µL L-1 to assess the impacts of AVG on Booth7 Avocado through respiratory rate, 1-amino-cyclopropane-1-carboxylic acid production, 1-aminocyclopropane-1-carboxylate oxidase (ACO) activity, and ethylene content, mass loss and spoilage ratio measured on 3-days cycle repeats of day of storage (DAS) until the fruit spoilage was not over 20%.Findings: Booth7 Avocado of the control treatment discovered a novel notice by the activity of Acetyl-CoA synthetase enzymes was recorded not concurrent with the activity of the ACO enzyme. The optimal significant inhibition of AVG (400 µL L-1) was determined, in which both ACC and ethylene biosynthesis was delayed to six days. The mass loss was the lowest, and the spoilage ratio was 16.67% on the 30th DAS, while the spoilage ratio in the control treatment was overloaded by 20% on the 24th DAS.Originality/Value: This study revealed that AVG treatment of the content 400 µL L-1 could effectively delay ripeness in Booth7 Avocados.
Assessing the Environmental Capacity of the Southern Caspian Sea for the Development of Agritourism with Emphasis on Rural Areas of Guilan, Mazandaran and Golestan Provinces of Iran
Authors: Chenari H. M. , Emami S. F. , Agha F. N. J. , Khodarahmi R.
Published: May 2024

Purpose: The purpose of this study is to assess the environmental capacity of the southern Caspian Sea to develop Agritourism in rural areas of Guilan, Mazandaran, and Golestan provinces. Agritourism is considered a service activity in providing currency and income for rural communities and is an economic strategy.Research Method: The present study is applied in terms of purpose and descriptive-analytical in terms of approach. Secondary data analysis was used to assess the agricultural situation and field data were used in the field of environmental landscape, human activities, and infrastructure. Data were collected and monitored, encoded, and analyzed in an SPSS environment.Findings: The results indicate that – according to the maps drawn in the field of agricultural products in these three provinces and to the opinions of relevant experts – Guilan Province, with an average of 3.47 in relation to the formation and development of Agritourism from the situation, is the best; Golestan Province, with an average of 3.38, is the next; and finally, with a very small difference, Mazandaran Province with an average of 3.24, is in the third place. As a result, the southern part of the Caspian Sea, especially its rural areas, is suitable for the development of agritourism.Research Limitations: The main challenges in the process of this research are the lack of easy access to experts related to agriculture, tourism and rural issues, as well as the lack of up-to-date statistical data in this field.Originality/Value: This research was conducted for the first time in the southern region of the Caspian Sea and could pave the way for further research.
Antifungal Activity of Chitosan Biofilms Enriched with Stingless Bee Honey Against Colletotrichum gloesporioides
Authors: García J. A. L. , Jarquin Y. C. , Flores V. A. , Conesa J. G.
Published: May 2024

Purpose: Pathogens that affect agricultural products after harvest are controlled using several strategies during the postharvest process. To accomplish this, refrigeration, controlled atmospheres, ethylene absorbers, coatings, and biofilms are used. The antifungal activity of chitosan biofilms added to other polymers (starch, wax and bovine serum albumin) mixed with stingless bee honey (Melipona beecheii, M. solani and Scaptotrigona mexicana) was evaluated.Research Method: The biofilm combinations were performed as follows; honey origin (M. beecheii, M. solani, and S. mexicana), concentration (10%, 20%, 30%), and polymers (starch, S. mexicana wax and bovine serum albumin). The overlay method against Colletotrichum gloesporioides was used to evaluate the antifungal activity, the same as the physical and mechanical characteristics.Findings: Biofilms made with a) 30% of M. beecheii honey + 3g of starch, b) 30% + 20g of S. mexicana honey and wax, and c) 20% of S. mexicana honey + 20g of S. mexicana wax registered the highest growth inhibition values against C. gloesporioides (77.6%, 76.6% and 73.4%). The one made with 20%of S. mexicana honey and wax showed the highest value in thickness (103,660.57 m), as well as a greater resistance in terms of breaking strength (20,133.95 N).Research Limitations: It was not easy to design biofilms with stingless bee honey, due to their humidity and pH content, until we got the exact combination.Value: This research provides information and knowledge to generate better biofilms with more feasible properties that keep the development of pathogens in postharvest fruit restricted.
Evidence of hidden leprosy diagnosed by active case finding in a highly endemic setting in Colombo district, Sri Lanka
Authors: Kalubowila K. , Dissanayake F. , Tilakarathne M. , Withanage S. , Anujan S. , Gajanayake C.
Published: May 2024

Background: To achieve the elimination of leprosy by 2030, improving case detection, contact tracing and early treatment is essential. However, the extent of hidden leprosy in pockets of endemic areas remains unexplored.Objective: To determine the prevalence of hidden leprosy and its associated factors.Methods: A household survey was conducted in the Divisional Secretariat (DS) area, Moratuwa over two months from 1st September 2023 using an interviewer-administered questionnaire. The data collection and screened were done by the public health staff attached to the Medical Officer of Health office after obtaining the written informed consent.Results: The socio-demographic data were presented as frequency distributions. The prevalence was calculated and presented as proportion with its 95% confidence interval (CI). The factors associated with leprosy were calculated using bivariate and multivariate logistic regression and p<0.05 was considered statistically significant. A total of 6486 people were screened in 2059 premises. Thirteen cases were confirmed as leprosy; thus, the prevalence of hidden leprosy was 20.1 (95% CI 11-34) per 10000 population. The majority (n=10, 77.0%) were multi-bacillary type, and two patients were under 15 years of age, while three were presented with grade II disability. Age above 15 years (p=0.001) and presence of another leprosy patient in the house (p=0.001) were statistically significant with the disease.Conclusion: High number of leprosy cases were hidden in pockets in DS area Moratuwa, therefore active case findings targeting populations of age 15 years or above and contact screening of the household/d members play a substantial role.