bluuebunny/crossref_metadata_2025 huggingface dataset:
Ethics of Health Research Data Ownership and Global Regulations
Authors: Daniel Nisha
Published: November 2024

In the era of Artificial Intelligence and Big Data, is data really the new oil? Within health research data governance, this chapter presents a compelling discussion of healthcare data ethics and the need for data safety and privacy. Data ownership debates public or private ownership and details an ethical society's global divergent perspectives and philosophical foundations. The building of a consistent data governance model may be beneficial to all and may address the issues of data bias, achieve data justice, and articulate individual autonomy and individual data rights.
Leadership “Qualities” and Gendered Social Cues
Authors: Robinson Seri C.
Published: November 2024

This chapter explores the lived experiences of the author as an intersex person with a nonbinary gender identity in higher education leadership, both at a smaller unit level and then within a larger, central administrative level. The first third will focus on the repercussions of presenting mixed gender social cues in leadership roles in a department level, while the second third will focus on how those same traits were valued in central administration leadership. The final third will offer suggestions for how to confront bias and conflict around mixed gender presentation both as a leader, and when experiencing it from leaders.
I Am Waving My “White” Flag
Authors: Chang Tsayli Lily
Published: November 2024

This narrative explores the challenges faced by a female Chinese-American educator in securing senior leadership roles in international schools. Despite a successful career and extensive experience, she encountered repeated rejections, highlighting issues of belonging and representation. The narrative underscores the rigorous recruitment process and the observed racial bias in hiring, as positions were filled predominantly by white candidates. It delves into experiences of racism, microaggressions, emphasizing the impact of unconscious bias on hiring practices. Despite the multicultural environment of international schools, leadership roles remain predominantly white and male. It advocates for more inclusive recruitment strategies, mentorship programs, and professional development opportunities to prepare diverse candidates for leadership. It calls for addressing unconscious bias and promoting equity to create inclusive, globally competent educational environments, aiming to highlight systemic issues and advocate for diversity, equity, and inclusion in educational leadership.
Harnessing Sadaqa to Achieve Inclusivity and Progressiveness of Islamic Banking
Authors: Ismail Ahmad Yani
Published: November 2024

Sadaqa is a charitable donation encouraged by Islam. It is donated to the marginalized society or for community empowerment initiatives. The instrument can be deployed for inclusivity-motive projects. Empirical evidences on the programmes are well-documented. Islamic Banking Industry (IBI) has shown to be successful in the commercial sector but less pro-active in the welfare sector. The introduction of Sustainable Development Goals agenda and Value Based Intermediation (VBI) has inspired IBI to proactively embark on social empowerment initiatives positioning IBI in the inclusivity initiatives. Case study on Sadaqa House initiative by Bank Islam Malaysia Berhad showcasing how sadaqa can be harnessed and contribute to inclusivity programmes. Malaysia's Islamic Finance sector is progressive with a top-down agenda by the regulatory bodies. Bank Negara Malaysia's VBI, Malaysia International Islamic Finance Centre (MIFC) Leadership Council's Position Paper and other initiatives proof the progressiveness of IBI. This includes Sadaqa House's blended financing instruments.
Global Trends in Waste Management Research Within the Tourism and Hospitality Sector
Authors: Sucheran Reshma
Published: November 2024

This chapter presents a bibliometric analysis of 280 research publications on waste management in the tourism and hospitality industry. Using Bibliometric R and the Web of Science database, this study examined several key factors, including publication and citation trends, author productivity and influence, leading organisations, countries, journals, and common themes in the field. The data show a steady rise in the number of publications and citations over time, reflecting the growing recognition of the importance of waste management in the tourism sector. This increase has been especially noted in recent years and is driven by a broader societal shift toward environmental awareness and the need for sustainable practices. The analysis of author productivity highlights varying levels of impact within the field, with some individuals making particularly significant contributions. Additionally, the study identifies key organizations, countries, and journals essential for advancing research on waste management in tourism.
Sustainable Waste Management in Tourism and Hospitality Sectors
Authors: Singh Amrik , Kumar Vipan
Published: November 2024

Waste management significantly impacts the sustainable state of the environment, public health, and economic stability. This study thoroughly analyses the many waste streams produced, with particular attention on solid waste, wastewater, hazardous waste, e-waste, and food waste. Every category has different difficulties and consequences for waste management procedures and regulations. Food waste has serious negative effects on the environment and the economy and is frequently caused by overproduction and consumer behaviour. Solid waste, including various materials, needs efficient recycling and disposal techniques to reduce its impact. Because of the speed at which technology is developing, e-waste pollutes ecosystems with harmful materials. Understanding waste streams will help stakeholders create more long-lasting and efficient solutions to safeguard the environment and public health.
Waste Management in Protected Areas
Authors: Mearns Kevin
Published: November 2024

The worldwide demand for wildlife tourism-based experiences has driven a global increase in demand for wildlife tourism experiences within protected areas. Tourism within protected areas has both positive and negative effects. The positive effects relate to the increased financial support for conservation initiatives that provide concrete substantiation for the long-term survival and conservation of protected areas. The negative effects, however, relate to the increased tourism infrastructure and the environmental impacts of accommodating guests and their hospitality staff within the protected areas. Of particular interest in this chapter is the issue of Waste management in protected areas, specifically recyclable waste. A mixed method single case study research design was employed to determine baselines and benchmarks of recyclable waste at a wildlife tourism lodge in the Greater Kruger Park area. Reflections on general waste management were also made regarding proposed principles for responsible waste management in protected areas.
Navigating The Path to Sustainability and Overcoming Environmental Barriers in the Egyptian Hotel Industry
Authors: Fathy Eslam Ahmed , Fouad Amr Mohamed , Kahly Abdallalh Mohamed
Published: November 2024

This chapter presents the specific environmental practices of Egyptian hotels and identifies potential barriers to implementing sustainable initiatives. The aim was to gain a holistic perspective on the factors affecting hotel environmental sustainability practices rather than merely discussing ecological problems. The analysis was based on qualitative data from 42 semi-structured interviews with top management from a sample of four- and five-star hotels in Egypt. The chapter reveals seven internal barriers: staff capabilities, physical limitations, the attitudes of top management, cost concerns, access to resources, owner attitudes, and day-to-day activities. External factors include government regulations, incentives, and guest attitudes. This chapter also examines the theoretical implications and discusses how future research might address environmental challenges in hospitality.
Constructed Wetlands as a Greywater Management Alternative in the Tourism Industry
Authors: Rani. J Reena Esther , Chandran Anu
Published: November 2024

The exponential increase in tourism escalates greywater production from laundry, gardening, bathing, and sewage treatment, leading to water scarcity. Simple physical and biological processes can purify greywater for reuse, leading to water conservation. Constructed wetlands offer new approaches to dealing with greywater, especially in polluted tourist areas, through plant, soil and microbial activity filtration processes. These systems are feasible for tropical regions with limited water resources. This chapter examines the suitability of constructed wetlands for greywater treatment, highlighting techniques, performance evaluations and environmental benefits. By integrating these systems, tourism facilities can reduce their ecological footprints with significant savings on water consumption. Constructed wetlands aid in improving greywater management and promoting sustainable water use because they have numerous advantages, such as low maintenance costs and adaptability, which are crucial in ecological preservation amidst rising tourism numbers.
A Comprehensive Review of Food Waste Management Strategies in the Food Service Industry
Authors: Crocker Ronelle
Published: November 2024

Food waste presents a severe sustainability challenge. Of the food produced globally, 30% is wasted, and if no significant improvement is made, this figure is expected to double by 2050. With the continuous growth of the hospitality sector, an increasing amount of waste, particularly food waste, is generated. Globally, the hospitality industry is the third-largest contributor to food waste. Food waste mitigation is fundamental to the sustainable improvement of the food service industry, owing to its adverse consequences and ethical concerns. For this reason, there is an increasing demand for practical solutions in the food service industry. Establishments in the food service industry can make a significant contribution to global sustainability efforts by creating partnerships with stakeholders and providing educational programs aimed at waste reduction to employees and consumers. Several food service establishments actively implement measures to minimize waste and recognize and accept their responsibilities.
Fostering a Circular Economy in Tourism
Authors: Elsawy Tamer M.
Published: November 2024

This chapter examines the state of the Circular Economy (CE) in Egypt's tourism sector, revealing both challenges and opportunities. The chapter uses a multi-faceted approach, combining secondary data analysis with a literature review. It systematically reviews and synthesises existing data from government reports, industry statistics, and prior research studies. It analyses barriers, demographic influences, and organisational dynamics and explores how technology can aid in overcoming these challenges. The chapter also draws on best practices from successful transitions elsewhere. Findings highlight the need for robust policies, targeted educational campaigns, and technological adoption. Effective CE transition in Egypt will require structured approaches, international collaboration, and tailored practices, such as adapting strategies to the Red Sea and promoting agritourism in the Nile Delta. This chapter is novel for its detailed analysis of CE adoption in Egypt's tourism sector, offering strategic pathways for advancing circularity.
Turning the Waste Into Wealth
Authors: Karim Rejaul , Waaje Abdul , Roshid Md. Mustaqim , Yeamin Md. Bony
Published: November 2024

Increasing waste production presents substantial environmental and public health obstacles, necessitating inventive and sustainable waste management approaches. This chapter explores the fundamental concepts of circular economy and how it may be used to change waste management systems from linear disposal methods to sustainable and efficient models that make the most of resources. It explores the influence of efficient waste management on diminishing environmental deterioration, fostering resource preservation, and bolstering economic development through waste materials' reuse, recycling, and repurposing. The chapter highlights the importance of adopting comprehensive strategies that combine technology advancements, policy restructuring, and community involvement to enable a shift toward circular waste management practices that will support attaining global sustainability.
The Impact of Artificial Intelligence on Education
Authors: Degni Fabrizio
Published: November 2024

AI in education has become one of the most significant innovations that has the potential of improving the quality of education, adapting teaching and learning to individual needs, and optimizing the management of educational institutions. The research seeks to explore the impact of AI on education, examining both the benefits and challenges associated with its integration. By employing a mixed-methods approach, this study will analyze the effectiveness of AI-driven educational tools and assess their implications for students, educators, and institutions. The findings will contribute to a better understanding of how AI can be harnessed to improve educational outcomes and address existing gaps in the education system.
Teaching, Learning, and Coaching Using Generative AI Tools
Authors: Ramya R.
Published: November 2024

Artificial intelligence technologies are developing at a rapid pace, creating new opportunities to improve coaching, teaching, and learning in educational settings. It looks at how artificial intelligence may be used to create customized course materials, offer instant feedback, and facilitate flexible learning environments. The first section of the study discusses open-access and emergency online learning as they exist today, emphasizing the difficulties that both teachers and students confront in these situations. The study also looks at the drawbacks and hazards of implementing AI in the classroom, including worries about prejudice, privacy, and the possibility that technology would eventually supplant human teachers. Overall, the study makes the case that generative AI technologies could completely transform education by offering students tailored, flexible, and interesting learning opportunities. It does, however, stress the significance of cautious application and continuous assessment to guarantee AI is applied in ways that are advantageous to all students and teachers.
AI Innovations in Market Risk Analysis and VaR Modelling
Authors: Saravanakrishnan V. , Nandhini M. , Palanivelu P.
Published: November 2024

This chapter examines how AI is transforming financial risk analysis and valuation. Traditional models often overlook tail risks and complex market dynamics, but AI introduces innovative techniques that enhance risk assessment and monitoring, addressing the shortcomings of VaR models. It delves into AI fundamentals, particularly deep learning and machine learning. It offers advanced methods for data processing, predictive modeling, and feature engineering, all crucial for integrating AI into the VaR estimation process. The chapter also emphasizes the significance of AI in risk management, especially in regulatory compliance, by exploring capabilities like natural language processing and portfolio optimization, which are vital for adapting to evolving regulations. The chapter provides a comprehensive overview of AI-based market risk analysis, highlighting AI's essenAI's role in helping financial institutions navigate volatile markets and increased regulatory scrutiny. It discusses current challenges and future directions, showcasing AI's pivotAI'sontribution to the industry.
Datalyse
Authors: Menezes Tejal Alwyn , Dokaniya Tina , Desouza Elainne William , Rai Ishaan , Vijayalakshmi A.
Published: November 2024

Having robust financial markets is important for economic development. Using statistical analysis and data visualization on financial data helps identify trends and understand the underlying factors affecting various aspects of the economy. This allows policymakers to make better decisions. In this chapter, we aim to introduce 'Datalyse,' an R programming developed website capable of performing various statistical tests and analyses. 'Datalyse' intends to solve this complexity by integrating statistics and web development. It accepts user-input data, computes the summary statistics, validates assumptions, and performs t-tests, F-tests, and z-tests. It checks the basic assumptions and generates a regression model, both simple and multiple linear regression. Additionally, residual analysis is performed to check model adequacy. The chapter demonstrates the application of 'Datalyse' in analyzing data and deriving insights through statistical methods, mainly regression analysis.
Comparing the Exact and Approximate Solutions of Financial-Type Stochastic Differential Equations
Authors: Cyrille Audrey Nzotem Tchoumi , Henri Claver Jimbo , Zourmba Tizi Boris , Paul Tchoua , Donatien Eze Eze
Published: November 2024

In financial engineering, stock price prediction remains one of the most interesting problems of stock market analysis. One approach to solution consists of using historical data of the underlying asset to predict future prices while relying on stochastic differential equations for modeling stock price dynamics. The analytical solutions of financial-like stochastic differential equations are not always obvious; numerical methods for approximating the solutions are often considered. In this work, we propose the Euler-Maruyama method to compute the approximate solutions on both geometric Brownian motion and Heston-type models. We first perform the parameters estimation of the models and then compare the exact and approximate solutions of the models. We investigate the convergence of numerical solutions to analytical solutions for various situations and uncover interesting behaviors as we increase the time steps. Additionally, we discuss the impact of the volatility in price prediction with the specific case of stochastic volatility from the Heston model.
Ito's Calculus for Stock Price Prediction for the Johannesburg Stock Exchange Market
Authors: Audrey Nzotem Tchoumi Cyrille , Claver Jimbo Henri , Tizi Boris Zourmba , Paul Tchoua , Donatien Eze Eze
Published: November 2024

The Johannesburg Stock Exchange is positioned as the leading African stock market and listed among the top twenty in the world, considering market capitalization. Price prediction remains at the center of concerns for stock markets in Africa and the world. Ito's calculus has extended the calculation methods to stochastic processes, Brownian motion, and stochastic differential equations with some relevant applications in mathematical finance. This work aims to present a rigorous mathematical justification for the models used by financial practitioners for pricing derivatives and managing risk. Additionally, this research will develop mathematical models, background of pricing models with comprehensive proofs, and test their reliability with historical data collected from the Johannesburg Stock Exchange for future decision-making.
Novel Applications of Data Analytics in Financial Markets
Authors: Shivashankar Adithya , Lokesh Chirag , Adhikary Chethan , Balaji Vaishnavi
Published: November 2024

The world of stocks is ever-changing and implementing predictive analytics is a cornerstone for making astute investment decisions. This paper delves into the effectiveness of advanced machine learning algorithms, notably Long Short-Term Memory, Artificial Neural Networks, and Linear Regression, in analyzing historical data to possibly project future trends while documenting existing papers and providing a breakdown of the most popular and sought-after machine learning algorithms. The objective is to find intricate, underlying patterns that offer invaluable insights for analysis and gauging risk for analysts and potential investors. By looking into such topics, this paper contributes novel ideas to the ongoing research surrounding utilizing machine learning algorithms in the dynamic world of financial markets. The paper consists of two segments: one provides a detailed review of recent methodologies used for market prediction on a region-wise basis, while the other focuses on using Long Short-Term Memory, Artificial Neural Networks, and Linear Regression.
Random Matrix Approach for Analysis of the Johannesburg Stock Exchange
Authors: Zourmba Boris Tizi , Claver Jimbo Henri , Audrey Nzotem Tchoumi Cyrille , Tchoua Paul , Nguefack-Tsague Georges
Published: November 2024

Random Matrix Theory gives us the theatrical framework to analyze computational and statistical properties of cross-correlation matrix. Usually, the cross-correlation matrix is noisy because of the estimation's error for the length and the finite nature of the underlying time series. The present work studies the Johannesburg Stock Market and the effects of eigenvalues filtering techniques on portfolio optimization in the mean-variance framework. The data stock prices are scraped on the Yahoo Financial website from 1st January 2020 to 1st January 2024. Further, we applied the LCPB, PG+, and KR cleaning techniques and observed that the predicted risk was closer to the realized risk in the prediction period. We conclude that the KR method is the best technique. In addition, the Johannesburg Stock Exchange reacts more to bad events than to good ones. This result considerably improves the constructive approach often used by practitioners in this market.
The Art of Digital Engagement
Authors: Ahmad dar Amir , Malhotra Mehak , Albalawi Olayan , Jain Akshat , Yadav Shipra Shivkumar , Rather Yasir Ahmad
Published: November 2024

In today's digital world, social media platforms are busy centers of connectedness, where marketers compete for users' attention with abundant material. This chapter explores the art of using social media sites like YouTube, Instagram, and others to develop and execute marketing plans that effectively connect and engage target consumers. By thoroughly examining each platform's distinct characteristics and dynamics and providing insights on optimization strategies, this research seeks to provide marketers with the knowledge and resources they need to succeed in the cutthroat world of social media marketing. Instagram is a visual playground where smart captions and eye-catching photos rule the day. Instagram allows marketers to connect emotionally with their audience by emphasizing visual storytelling and immersive experiences. Through creating engaging images and tools like Reels and Stories, marketers can effectively utilize Instagram to develop their brand's identity and encourage significant interaction.
An NLP Approach to Enrich Biomedical Research Through Sentiment Analysis of Patient Feedback
Authors: Saha Soumitra , Lilhore Umesh Kumar , Simaiya Sarita
Published: November 2024

This chapter consults the trajectory committed by utilizing patient feedback (PF) in the wake of biomedical research through sentimental analysis (SA) in natural language processing (NLP). PF has been compared to a gold mine for the healthcare industry as it delivers clinical efficacy and preserves quality. Analyzing these patient responses is vastly more time-consuming and subjective. SA employment can efficiently extract beneficial insights from this feedback by automating patients' positive, negative, or neutral sentiments. By systematically examining millions of remarks to identify familiar themes, distinct concerns, and patient satisfaction levels, researchers can employ these sentiments to understand disease status and assist in making intelligent decisions. SA can work with structured and unstructured sentiment data from mixed social media posts and electronic health records to produce favorable results, allowing researchers to improve biomedical research. Eventually, this chapter uncloses worthwhile wisdom to enrich biomedical research by employing PF through SA.
Enhancing Assistive Technologies With Neuromorphic Computing
Authors: Anil Chandra G. V. S. , Ananthakumar Bhanuprakash , Raghavan Ramya
Published: November 2024

The development of intelligent neuroprosthetics, which promise to augment human brain function is vital for augmentative assistive technologies. Neuromorphic sensors and processors are particularly adept at mimicking the brain's efficient sensory processing, offering assistive devices an advanced capability to perceive and interpret complex environmental stimuli. The application of these technologies in brain computer interfaces suggests a future where transformative advancements are not only possible but imminent, facilitating novel methods of human-computer interaction and providing insights into the intricate workings of the brain through advanced AI and machine learning techniques. This paper explores the integration of neuromorphic technologies with brain-computer interfaces (BCIs), highlighting the potential to enhance assistive devices and revolutionize communication and healthcare. However, the realization of neuromorphic computing's full potential within BCIs is contingent upon overcoming significant technological and ethical challenges.
Integrating Neuromorphic Designs in Two-Wheeled Self-Balancing Robots
Authors: Mahapatro Soumya Ranjan , Majumdar Debaditya , Banerjee Debarghya , Santhosh Ramya , Kumar Satrughan , Singh Charanjeet
Published: November 2024

This research aims to investigate the implementation of neuromorphic designs into two-wheeled self-balancing robots (TWSBRs) with the objective of improving their performance, power consumption and flexibility. The paper further looks at the evolution of TWSBRs, the problem of stability, and opportunities for neuromorphic computing. The integration is supposed to enhance the sensory acquisition and processing in real time, control adaptability, energy consumption, and insensitivity to external disturbances. Neural networks are implemented in the proposed neuromorphic TWSBR architecture with the use of Spiking neural networks (SNNs) and event-based sensors. This could make a lot of things better, such as self-driving delivery systems, industrial automation, and personal mobility.
Neuromorphic Advancements
Authors: Kumar Krishan
Published: November 2024

The healthcare industry has recently experienced an increasing need for miniaturization, low power consumption, rapid treatments, and non-invasive clinical approaches. To fulfil these requirements, healthcare professionals actively search for innovative technological frameworks to enhance diagnostic precision while guaranteeing patient adherence. Neuromorphic computing, which employs hardware and software neural models to imitate brain-like behaviors, can facilitate a new era in medicine by providing energy-efficient solutions, having minimal delay, occupying less space, and offering high data transfer rates. Neuromorphic plays a vital role in healthcare, i.e., image processing, drug discovery, and disease prediction. This chapter provides a comprehensive overview of Neuromorphic advancements and their application in healthcare using intelligent computing.
Pharmacy Science and Neurological Drug Discovery
Authors: Tanwar Neha , Kumar Sandeep , Verma Deepika
Published: November 2024

In this chapter, we set out on a journey to explore the complex relationship between pharmaceutical science, computational drug discovery, and the world of natural food products. We will deeply investigate the crucial role of food components in shaping the landscape of pharmaceutical research and development. By highlighting the importance of integrating food-based methods into drug discovery processes, our goal is to emphasize the transformative potential of utilizing the abundant resources found in nature. Taking a multidisciplinary approach, we aim to bridge the traditional gap between conventional pharmaceutical practices and the rapidly advancing field of nutraceuticals. In doing so, we are paving the way for a more unified and holistic approach to healthcare innovation.
Analyzing Destination Branding Themes Using Co-Word Analysis
Authors: Derviş Hamid
Published: November 2024

The chapter provides practical strategies for leveraging Social Network Analysis (SNA) in destination branding, offering insights on using interconnected keywords to create a cohesive brand identity extracted from Clarivate Analytics Web of Science (WOS). Using Istanbul, Konya, and Kastamonu showcased as destination brands, the chapter demonstrates how SNA can be applied in real-world contexts, providing insights into the benefits of a strategic branding approach through SNA. The author emphasizes the significance of a connected keyword network and offers practical strategies for leveraging these connections to establish a sustainable destination brand identity. The findings serve as a guide for tourism and hospitality practitioners, assisting them in creating compelling, sustainable destination brands. Similarly, this methodology can be applied to investigate the complex relationships among stakeholders, including local communities, businesses, government agencies, and tourists.
Eco-tourism Branding Balancing Conservation and Community
Authors: Pandey Uma , Dar Hafizullah
Published: November 2024

Balancing conservation and community development is a significant challenge, especially where natural resources are protected and serve as livelihoods for locals. This study focuses on Kanha National Park in central India, which conserves diverse flora and fauna, including tigers and swamp deer. Conservation efforts often conflict with the livelihoods of locals living in buffer zones, leading to socioeconomic issues. Eco-tourism offers an alternative income source, leveraging the park's natural beauty and biodiversity. This chapter analyzes Kanha's eco-tourism branding, highlighting sustainable tourism practices and their ecological importance. Sustainable measures, like eco-friendly lodging and income reinvestment in community projects, align local interests with conservation goals. Despite challenges, the chapter suggests Kanha's model as an example of effective eco-tourism branding, promoting conservation and regional development through inclusive management.
Developing Destination Brand Identity Through Stakeholder Collaboration
Authors: Gün Serkan
Published: November 2024

The brand helps make a significant difference in distinguishing goods and services and acts as an edge over the closest rivals (Aaker, 1991). Govers et al. (2007) claim that the consumption experience of travel “determines aspects of consumer behavior related to multiple emotional, sensory, and fantasy aspects of consumer behavior” (Hirschman and Holbrook, 1982). Morgan et al. (2004) state that location branding is a potent tool for marketing that can aid travellers in developing positive affective attachments and impressions. As they explain, the summation of perceived experiences that a tourist will encounter at a destination is the so-called “most important repertoire of beliefs that support the branding of a destination.” (Barnes et al., 2014).
Ecotourism and Sustainable Development in Chania
Authors: Poulaki Panoraia , Rachiotis Theodoros , Vasilakis Nikolaos
Published: November 2024

This study investigates the potential of ecotourism in fostering sustainable development in Chania, Crete, focusing on environmental conservation, cultural preservation, and economic growth. A mixed-methods approach combines secondary research to establish a global and local theoretical framework with qualitative interviews with key stakeholders in Chania. The study assesses the current state of ecotourism, its impact on natural and cultural heritage, and barriers to sustainable tourism. Findings highlight ecotourism's role in raising environmental awareness and supporting local economies. However, challenges such as infrastructure, stakeholder cooperation, and ecological management persist. The study concludes that strategic planning and stakeholder collaboration are essential for ecotourism's success, balancing growth with resource preservation. Theoretical implications suggest ecotourism as a sustainable tourism model, while practical recommendations call for targeted policies, employee training, and marketing strategies to position Chania as a top ecotourism destination.
The Role of Corporate Governance in Driving Technological Innovation for Sustainable Development
Authors: Jain Vishal , Mitra Archan
Published: November 2024

This study examines how corporate governance promotes sustainable development-focused technical innovation. It links governance mechanisms including board diversity, executive compensation, and shareholder activism to UN Sustainable Development Goal-aligned innovation strategies. Long-term sustainable technology R&D investments are driven by effective governance structures. The research shows how well-structured governance frameworks can enable innovation that addresses global sustainability concerns, contributing to environmental stewardship, social equity, and economic growth through case studies of successful firms. Harmonised global standards and collaborative governance methods are needed to overcome regulatory discrepancies and short-termism and enable a more sustainable and equitable future. This chapter emphasises the need to integrate corporate governance with sustainability goals to promote technology that benefits businesses and society.
Territorial Governance in Relation to Territorial Administration
Authors: Touhami Fatima , Qassid Ayoub
Published: November 2024

This chapter explores the complex relationship between territorial governance and territorial administration, highlighting the issues of coordination, decentralisation, and participation of local actors. It should be noted that territorial governance involves not only the state and its administrative structures, but also local and regional actors, such as local authorities, businesses and civil society organisations. What sets it apart is its collaborative approach. This mode of governance aims to consolidate the effectiveness of public policies by taking account of the specific nature and diversity of territories. Territorial administration is the institution responsible for implementing these policies at the local level, often within a framework of decentralisation in which powers are transferred from central levels to local authorities. However, this dynamic raises a number of challenges, such as the coherence of actions between the different administrative levels, the autonomy of local entities and their ability to mobilise resources. The research is a theoretical analysis that highlights the importance of multi-level governance mechanisms. This makes it possible to coordinate interactions between the different levels of governance. The aim is therefore to ensure more appropriate territorial management that promotes social inclusion, sustainable development and resilience in the face of economic, social and environmental challenges. Ultimately, territorial governance aims to create synergies between public administration and the needs of territories, while guaranteeing citizen participation and transparency in decision-making processes.
Managing AI in the Workplace to Enhance Collective Intelligence and Resilience
Authors: Steggemann Michael
Published: November 2024

This chapter examines the integration of artificial intelligence (AI) in the workplace and its impact on collective intelligence (CI), collective resilience (CR), and experienced integrity (EI)—the alignment of individual and organizational values. Building on CI and CR concepts, it explores how AI shapes collaboration, trust, and meaning-making for individuals and teams. While AI boosts efficiency and innovation, its integration requires balancing technology with human values, focusing on ethical considerations, transparency, and maintaining integrity. The chapter presents a conceptual framework, enriched by the author's experiences, to guide managers and teams in effectively managing AI to enhance CI, CR, and EI. It offers practical strategies for addressing AI-related uncertainties, fostering collaboration, trust, and adaptability. In doing so, it highlights AI's potential to strengthen both individual and collective capabilities, supporting a more resilient and intelligent workforce.
Synergizing Success the Dynamics of Collaborative Business Ecosystems
Authors: Chandratreya Abhijit
Published: November 2024

The chapter explores the transformative impact of collaborative business ecosystems on organizational success and innovation. Collaborative business ecosystems, comprising interconnected organizations, suppliers, customers, and stakeholders, are reshaping traditional business models by fostering cooperation, co-creation, and shared value. This chapter delves into the key dynamics of these ecosystems, including trust-building, shared governance, resource integration, and digital connectivity, highlighting their role in enhancing competitiveness and resilience. It examines how businesses can leverage these ecosystems to drive innovation, reduce costs, and adapt to rapidly changing market conditions. The chapter addresses the challenges associated with managing collaborative ecosystems, such as balancing competition with collaboration and navigating complex stakeholder relationships.
Collective Intelligence Approach for New Mobility
Authors: Pérez-Moure Hugo , Lampón Jesus F. , Cabanelas Pablo
Published: November 2024

This chapter examines how collective intelligence is transforming the mobility industry into the era of “new mobility.” Collective intelligence—the collaborative problem-solving and knowledge-sharing of groups—is reshaping traditional paradigms, business models, and global value chains (GVCs). Furthermore, this explores new business models emerging from digitalization and collective intelligence, such as mobility as a service (MaaS) and car-sharing platforms. The shift from traditional mobility to new mobility that emphasizes alternative energy sources, sustainability, connectivity, and user-centric services, is driven by advancements in electric vehicles (EVs), connected and autonomous vehicles (CAVs), digital platforms, big data, and artificial intelligence. Collective intelligence is redefining relationships within the mobility value chain, moving from OEM-dominated hierarchies to collaborative networks involving diverse stakeholders like tech companies and public entities. This necessitates shared knowledge, data exchange, and cooperative innovation.
Cellular Ceramics Used as Catalytic Supports for Heterogeneous Catalyst Synthesis
Authors: Hairch Youssef , Nosseir Ahmed E. S. , Atamanov Meiram , Amrousse Rachid
Published: November 2024

Cellular ceramics have become essential in various industrial applications. This chapter explores the types, shapes, and characteristics of cellular ceramics, and their potential uses in space propulsion and catalysis. There are different varieties, including foams, honeycombs, and reticulated structures, classified by their composition, structure, and production processes. These materials are favored for their high porosity, low density, excellent mechanical strength, and thermal stability. Their large surface area and enhanced mass transfer capabilities make them effective as catalyst supports in processes like hydrocarbon reforming, oxidation, and hydrogenation, where they immobilize catalytically active species to boost activity and selectivity. In space propulsion, cellular ceramics are used in thruster components due to their ability to withstand high temperatures and maintain structural integrity under harsh conditions.
Model Matrices for Nuclear Waste Storage
Authors: Mabrouk Assia , Bachar Ahmed , Canizarès Aurélien , Vaills Yann , Hampshire Stuart
Published: November 2024

Glasses enriched with rare earth elements hold significant promise for nuclear waste storage, especially for immobilizing high-level waste (HLW) containing minor actinides. This chapter delves into the structural intricacies of peraluminous lanthanum-rich sodium aluminoborosilicate glasses, where lanthanum serves as a surrogate for lanthanides and minor actinides typical of HLW. Given the imperative to accommodate higher concentrations of HLW, the aluminum/boron substitution emerges as a pivotal factor influencing the glass matrix's properties. Employing a combination of infrared (IR), nuclear magnetic resonance (NMR), and Brillouin spectroscopy, we unravel the intricate interplay between composition and structure. Our investigation sheds light on the effects of aluminum/boron substitution on phase separation phenomena and structural rearrangements within the glass network. This in-depth analysis provides critical insights into the design and optimization of novel glass matrices tailored for advanced nuclear waste immobilization strategies.
Synthesis and Characterization of Activated Carbon From Biomass
Authors: Kunarbekova Makhabbat , Busquets Rosa , Sapargali Inabat , Seimukhanova Laura , Zhantikeyev Ulan , Kudaibergenov Kenes , Azat Seitkhan
Published: November 2024

This chapter discusses current practices and new developments in the preparation of activated carbons for the adsorption of pollutants. There is widespread pollution such as pharmaceuticals and heavy metals in global surface water that needs to be mitigated and carbon sorbents made for it can be part of the solution. Preparing carbons for such challenge requires tailoring carbon's structure and surface chemistry to maximise interaction with low concentrations (part per billion level) of a variety of pollutants. The preparation of effective carbon sorbents constitutes a technical challenge. This chapter explores treatments and analytical approaches for the preparation and development of modified carbons to remove water pollutants. Effective carbons will help to control global contamination problems but should not be the source of more pollution: carbon dioxide emissions during the production and maintenance of carbon sorbents are a concern.
AI-Based Solutions for Malware Detection and Prevention
Authors: Gundoor T. K. , Sridevi  , Mulimani Rajeev
Published: November 2024

One of the biggest cybersecurity threats worldwide is malware. As cyber-threats evolve, traditional methods become less effective. Leveraging Artificial Intelligence (AI) can improve detection and prevention. Modern malware bypasses signature-based detection, necessitating adaptive AI solutions. Techniques like supervised, unsupervised, and reinforcement learning recognize malware patterns in large datasets. Neural networks outperform regular methods by learning complex features. Integrating AI with network behavior analysis, anomaly detection, and threat intelligence creates robust systems. AI is crucial for stopping zero-day malware and predicting threats. Ethical considerations, such as data privacy and algorithm bias, highlight the need for responsible AI use. Real-world applications by top cybersecurity companies show AI's effectiveness. The future looks promising with AI combined with edge computing, blockchain, and quantum computing, enhancing cybersecurity resilience.
Real-Time Threat Detection in Cybersecurity
Authors: Jain Vishal , Mitra Archan
Published: November 2024

The rapid evolution of cyber threats necessitates advanced real-time detection systems capable of identifying anomalies as they arise. This study explores the effectiveness of machine learning algorithms in enhancing real-time anomaly detection in cybersecurity. Using datasets such as CICIDS2017, UNSW-NB15, and simulated data, various models including Random Forest, SVM, and LSTM were trained and tested. The results highlight that LSTM networks exhibit superior performance in accuracy, precision, and recall, particularly in scenarios requiring temporal data analysis. However, the study also identifies challenges related to latency and computational demands, emphasizing the need for scalable and efficient solutions. The importance of feature selection and hyperparameter tuning in optimizing model effectiveness is also discussed. Comparative analysis and real-world testing validate the potential of machine learning to significantly improve the speed and accuracy of threat detection in cybersecurity, offering valuable contributions to the field.
Future Trends and Innovation in Machine Intelligence for Cyber Risk Management
Authors: Kolhar Amrutha , Sridevi
Published: November 2024

This chapter looks at how machine intelligence affects cyber risk management, emphasizing both present developments and potential future applications. It investigates the ways in which artificial intelligence in particular helps identify, address, and lessen sophisticated cyberthreats. The chapter discusses contemporary methods and tools, moral issues, and practical uses. It has sections on the condition of cyber risk management today, machine learning developments, and difficulties encountered. The goal of this chapter is to inform practitioners, academics, and policymakers on the advantages and difficulties of machine intelligence in protecting digital environments by fusing industry standards, professional viewpoints, and new research.
Right-Based Approach to Reproductive Autonomy
Authors: Joseph Jipson , Pandey Ananya
Published: November 2024

Discussion on reproductive health became prominent in the second half of the 20th century. The Declaration of the universality of human rights energized a right-based approach to reproductive health. Many women realized that without reproductive rights the questions on their dignity, equality, liberty, and life would become meaningless. This right-based approach got momentum in USA and extended to other countries, including India. But both these countries did not consider right to abortion as an absolute right. In India, the enactment of Medical Termination of Pregnancy Act, 1971 considered it as a limited right. The US judiciary in its Roe judgment in 1973 considered it under right to privacy in the ambit of right to liberty but only as a limited right. However, this judgment was overruled by the Dobbs judgment in 2022. In this context, this chapter attempts to compare the perspectives of both USA and India on reproductive health.
Big Data Cyber Security Analytics
Authors: Agrawal Prerna , Gandhi Savita
Published: November 2024

The prevalence of social media usage is rapidly escalating. In January 2024, India alone recorded a total of 462 million social media users. The rise in online users has led to a corresponding surge in cybersecurity frauds. Cybersecurity experts can utilize big data analytic tools to identify, prevent, and mitigate cyber assaults, as these technologies are capable of handling the enormous amounts of data collected from diverse sources. This chapter examines cybercrimes that can be identified using Big Data Analytics (BDA). The primary aim of this chapter is to offer readers a comprehensive understanding of how Big Data Analytics (BDA) is applied in the field of cybersecurity. It also aims to enlighten readers about current advancements in the application of BDA in cybersecurity and the challenges that are encountered in this domain.
Unlocking the Power of Software-Defined Networking (SDN) in Revolutionizing Network Management
Authors: Kulkarni Manasa , Goswami Bhargavi , Paulose Joy , Malakalapalli Lavanya
Published: November 2024

This chapter delves into the transformative impact of SDN on modern network management. By decoupling the control and data planes and centralizing network intelligence, SDN enables unprecedented flexibility, programmability, and efficiency in managing network infrastructures. The chapter examines various use cases, including data center network management, WAN optimization, and network security. These use cases demonstrate SDN's ability to dynamically allocate resources, optimize traffic flows, enforce security policies, and automate network provisioning. Despite challenges related to scalability, reliability, and security, SDN's benefits in providing a comprehensive, real-time view of the network, enabling adaptive adjustments, and fostering innovation are emphasized. Overall, this chapter underscores SDN's role in revolutionizing network management, paving the way for more agile, efficient, and secure networks that can meet the ever-evolving demands of today's digital landscape.