bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy Security in Pakistan and Bangladesh
Authors: Nandy Debasish
Published: December 2023

The issue of energy security has been one of the pertinent issues to the study of international relations. The South Asian states are facing a tremendous energy security crisis due to a lack of conventional energy sources. The high demands for energy and shortage of supply have posed an immense challenge to the states of South Asia. In this chapter, a comparative study will be done between Pakistan and Bangladesh to understand the energy security policy of the two states to address the sustainable development goals. Pakistan and Bangladesh have a huge crisis of energy due to their vast population. A power cut has been very common for both countries. This chapter will attempt to highlight the governmental initiatives to introduce green energy and will also shed light on the administrative lack to fulfill the sustainable development goals (SDGs). The lack of policy implementation by both governments will be investigated in this chapter. The content analysis method will be applied in this chapter.
Gender Discrimination in the Workplace
Authors: Pal Shrabanti
Published: December 2023

The present chapter is an attempt to highlight and address the issue of gender disparities and the socio-economic problems of women in India. Indian society is patriarchal and driven by men's ideology where women are restricted to being the part of formal workforce, and also experience a high level of domestic violence. The status of Indian women is primarily dependent on various factors like demographic location, basic education, social status, etc. Indian women are restricted in various aspects like access to health facilities, proper education, lessening decision-making power, etc. Despite political reservations, women are hindered to be political participants at local, national, and international levels. Indian government frames various policies for women's welfare and empowerment. However, there is significant gap exists between the framing and execution of such policies. Hence, the main focus of the chapter is to examine the various issues faced by Indian women to achieve economic development and gender equality.
Sustainable Development Goals and European Two-Tier Corporate Governance Framework as a Model for Limited Liability Partnerships
Authors: Nadarajan Ravindran , Rahman Hamizah Abdul
Published: December 2023

A two-tier model of corporate governance is perceived to be suitable for the corporate governance of liability partnerships (LLP) in Malaysia because the ownership and management of LLPs are both asserted on the partners, and there is the absence of a board of directors (unlike a company). As such, there is a need for a body to supervise the members/partners to ensure good governance for an LLP. All the corporate governance theories – namely agency theory, ethical theory, stakeholder theory, and corporate social responsibility (CSR) – are also relevant to LLPs in ensuring a good corporate governance framework. As such, the legal justifications and theories to support a corporate governance framework for LLPs should be similar to a company. However, due to the internal regulations of LLPs (which have overlaps between ownership, management, and decision-making structures), this chapter would propose a two-tier model of corporate governance with perceptive view on sustainability's development goals to be adopted for LLPs.
Integrating Generative AI Into K-12 Curriculums and Pedagogies in India
Authors: Sharma Durgesh M. , Venkata Ramana K. , Jothilakshmi R. , Verma Rakesh , Uma Maheswari B. , Boopathi Sampath
Published: December 2023

Generative artificial intelligence (AI) can revolutionize K-12 education in India by enhancing curriculums and pedagogies. This chapter explores the principles of generative AI, including generative adversarial networks (GANs), variational autoencoders (VAEs), and natural language generation (NLG), and its potential to create content indistinguishable from human-generated materials. Generative AI addresses challenges like resource scarcity, linguistic diversity, and personalized learning experiences, while emphasizing ethical considerations, data privacy, and bridging the digital divide. The future of K-12 education in India will see personalized learning journeys, inclusivity, and empowered educators. A comprehensive policy framework, infrastructure support, and teacher training are needed to realize the full potential of generative AI in shaping the educational landscape.
Exploring the Potential of Generative AI in English Language Teaching
Authors: Ironsi Chinaza Solomon
Published: December 2023

Integrating artificial intelligence (AI) technologies in education has shown remarkable potential in revolutionizing various aspects of teaching and learning. In English language teaching (ELT), generative AI has emerged as a powerful tool to enhance language acquisition, foster learner engagement, and provide personalized instruction. While the potential of generative AI in ELT is promising, it is important to provide insights into certain challenges and considerations. Ethical concerns related to data privacy, bias in AI algorithms, and the potential displacement of human instructors need to be carefully navigated. The successful implementation of generative AI in ELT relies on careful consideration of ethical implications, human oversight, and the continuous refinement of AI algorithms to ensure optimal language learning outcomes. On these premises, this chapter explores the potential of generative AI in ELT and its implications for language learners and educators.
Leveraging Generative AI for Cross-Cultural Knowledge Exchange in Higher Education
Authors: Mahboob Khalid , Asif Raheela , Umme Laila
Published: December 2023

The integration of generative artificial intelligence (AI) has the potential to revolutionize cross-cultural knowledge exchange in higher education. By leveraging its ability to create culturally sensitive and contextually relevant learning materials, generative AI can enhance personalized education for students from diverse backgrounds. Overcoming language barriers through real-time translation, this technology promotes inclusive collaboration and co-creation of knowledge. However, ethical considerations such as cultural authenticity, bias mitigation, and data privacy must be carefully navigated to ensure equitable and respectful cross-cultural interactions. In essence, generative AI offers a transformative avenue for fostering a culturally enriched learning environment in higher education, necessitating a balanced approach that maximizes benefits while upholding ethical principles.
Exploring the Challenges and Applications of Generative AI on Engineering Education in Mexico
Authors: Orduño-Osuna Jesús Heriberto , Cota-Rivera Elia Ivette , Raygoza-L. María E. , Jimenez-Sanchez Roxana , Limón-Molina Guillermo M. , Bravo-Zanoguera Miguel E. , Mercado-Herrera Abelardo , Rico Fabian N. Murrieta
Published: December 2023

This chapter explores the potential and challenges of implementing generative artificial intelligence (AI) in engineering education in Mexico. It highlights the relevance of developing broader competences like critical thinking, collaboration, and cognitive processing to prepare students for the Fourth Industrial Revolution. Integrating generative AI and STEM education can foster collaboration, communication, critical thinking, and creativity. Challenges include the gap between demand and supply of skilled engineers and the need to enhance education quality. The chapter proposes personalized learning experiences, enhanced student engagement, workload reduction for teachers, and the use of large language models and simulated environments as key applications of generative AI. Leveraging learning analytics and generative AI can tailor content to students' needs. Ethical considerations and human oversight are crucial for successful integration.
IoT Sensors for Smart Automation
Authors: Chayalakshmi C. L. , Kakkasageri Mahabaleshwar S. , Pujar Rajani S. , Hegde Nayana
Published: December 2023

The internet of things (IoT) has changed the comforts of every individual. Sensors and communication models play an important role in the effective implementation of IoT systems for any applications. Sensors can be classified based on the parameters to be measured and on the working principles. The second significant component in IoT-based systems is communication models, which help to exchange the data between the two IoT devices. Basically, there are four types of communication models that are commonly used: device to device, device to cloud, device to the gateway, and backend data sharing communication models. This chapter explains various sensors that can be connected to the internet for transferring data between IoT devices, application areas and communication models. The classification of IoT application areas is based on the scope of functionality, use, and adaptation. Sensors are classified on the basis of types of measurement such as vision, position, physical, and others. Basic communication models and open research challenges are explained at the end.
Blockchain and Artificial Intelligence for Cyber Security in the Era of Internet of Things and Industrial Internet of Things Applications
Authors: Tyagi Amit Kumar
Published: December 2023

As the internet of things (IoT) and industrial internet of things (IIoT) continue to expand, the need for robust cyber security solutions becomes increasingly critical. The convergence of blockchain technology and artificial intelligence (AI) offers promising opportunities to address the security challenges posed by IoT and IIoT applications. This chapter provides an overview of the potential synergies between blockchain and AI in the context of cyber security for IoT and IIoT. Blockchain technology, with its decentralized and immutable nature, can provide enhanced security and trust in IoT and IIoT networks. It offers features such as data integrity, transparency, and tamper resistance, making it well-suited for securing critical data and transactions. Additionally, blockchain can facilitate secure device identity management, access control, and secure communication among IoT and IIoT devices.
Artificial Intelligence and Blockchain Technology for Secure Smart Grid and Power Distribution Automation
Authors: Tabassum Zahira , Samantaray Rashmi Rani , Mohammadi Syeda Husna , Fathima Anees
Published: December 2023

A country's growth is gauged with reference to its power consumption and energy use, both of which are fast expanding. Energy consumption management improves energy generation and delivery. The smart grid is a tremendous improvement over the power system of the 20th century, using two-way electrical and communication exchanges to create a sophisticated, distributed, computerized energy delivery network. The fields of artificial intelligence (AI) and block chain distributed ledger technology (BDLT) are the most fascinating areas of study in the field of green energy and related power automation. An in-depth analysis of the most advanced automated planning, governance, optimization, confidentiality, and safety methods for the distribution of power and smart grid using integrated artificial intelligence and block chain is presented in this chapter.
Blockchain Technology
Authors: Kamble Shridevi , Kounte Manjunath , M. S. Saujanya
Published: December 2023

Intelligent internet of vehicles is an emerging technology and has an impact on all smart vehicles on the road due to rapid development in satellite communication integrated with internet technology and enables the integration of smart vehicles with system components like inbuilt vehicle sensors and internet, surrounding vehicles, and smart devices. This integration creates a safe and better platform for vehicles to travel on the road and at the same time be connected to the surrounding environment and vehicles for better performance. Integrating blockchain technology with vehicular communication and smart vehicles is the latest emerging concept. In this chapter, the authors present the survey and latest advancement in block chain technology for intelligent transport systems. This chapter's main highlight is on the application scenario of the internet of vehicles using block chain after a decent review of the literature survey. Also, the authors focus on key challenges and explore further research paths in the intelligent internet of vehicles using block chain technology.
Building a Secure and Transparent Online Conversation Platform
Authors: Tauseef Md , Jana Sayak , Gouda Aashish Rayangouda , Mishra Ashutosh , Srivastava Utkarsh Raj
Published: December 2023

This chapter explores the integration of artificial intelligence (AI) and blockchain technology to create a secure and transparent online conversation platform. Advancements in AI have given rise to virtual assistants capable of human-like interactions and versatile task execution. By harnessing blockchain technology, these virtual assistants enhance security and response times, making them invaluable in applications ranging from healthcare to gaming. The chapter presents a project that enhances virtual assistant capabilities through blockchain integration, featuring a self-learning module and a Solana-based blockchain network with smart contracts. Implementation employs Vanilla JavaScript, Express.js, and Node.js, offering end-to-end customer support and adapting to modern lifestyles. The fusion of AI and blockchain showcases the potential for a robust and secure online conversation platform.
Machine Learning and Blockchain Integration in Industrial Robotics
Authors: Gowda V. Dankan , Kumar Pullela S. V. V. S. R. , S. B. Manojkumar , Junnarkar Aparna Atul , Kawale Sheetalrani Rukmaji
Published: December 2023

Machine learning and blockchain have the potential to completely change the landscape of industrial robots. Learning and adaptation give robots an edge in functionality and independence. Blockchain, on the other hand, provides a decentralized and secure platform for information exchange and transaction verification. In this chapter, the authors look at the potential benefits and drawbacks of integrating machine learning and blockchain technology for use in manufacturing robots. The study begins with a brief introduction to machine learning, blockchain, and their respective industrial robot applications. Some of the possibilities and advantages that will be covered in the next sections include better data security, more transparent and auditable decision making, and the use of decentralized control systems. The importance of collaboration between academic institutions, businesses, and government agencies is emphasized in order to speed up the process of mainstreaming machine learning and blockchain integration in industrial robots.
IIoT Design Methodology and Its Applications
Authors: Alphonse Sherly , Abinaya S. , Mary Ani Brown
Published: December 2023

Information and communication technology (ICT) is being used in industrialised countries to develop a range of cutting-edge services and apps that address the problems affecting sustainable communities and improve people's quality of life. Additionally, IoT improves interpersonal communication. Internet protocols, sensor networking, communication technologies, embedded systems, technology, pervasive computing, sensor, etc. are all included in the broad group of techniques known as the internet of things (IoT). Operational technologies (OT), information technologies (IT), robotics, auto augmenting systems, digital supply chain data management, and smart decentralised manufacturing are all seen as catalysts for this change. The provision of a digital tracking capability for source chain assets is the second example of a use scenario. The development of IoT, its frameworks, protocols, technologies, design process for IIoT, its framework, and many applications are all covered in this chapter.
Digital Twins AR and VR
Authors: Anitha K. , Ghosal Indrajit , Khunteta Ajay
Published: December 2023

The term “metaverse” has taken off in the tech world. No day goes by when it isn't mentioned in the media, particularly when huge firms enter this area of digital engagement. Unquestionably, a 3D virtual world is gaining enormous momentum, which will likely go down in history as a watershed moment for the metaverse. Even though the idea has not fully developed yet, it is likely that cutting-edge technologies like blockchain, IoT, AI, AR/VR/MR, and 5G will become a driving force behind the development of a fully developed, interconnected virtual world. Since VR (virtual reality)/AR (augmented reality) technologies are necessary to the building of metaverses, the market is expected to grow quickly in the future. The immersive virtual environment that metaverse seeks to create will not only be focused on user interaction, but may also be seen as an extension of the physical world where businesses and individuals interact to collaborate, build, and exchange goods and services. This chapter discusses the functional importance and recent developments of digital twins in the metaverse.
Synergistic Play Design
Authors: Chen Pua Shiau
Published: December 2023

The development and implementation of dynamic learning strategies as a means to enhance student engagement and retention have contributed to a promising resurgence in the field of education. One innovative educational strategy aimed at fostering student motivation is 'game-based learning' (GBL). GBL is designed to integrate subject matter with gameplay, facilitating the application of this knowledge to real-world situations. It harnesses the principles of gaming to achieve specific educational objectives, whether they relate to knowledge, skills, or behaviours. Through the amalgamation of these approaches, it is intended to increase student participation and empower them to cultivate cognitive abilities and behaviours that are conducive to their learning. This chapter explores the potential benefits of effective GBL implementation and delves into the numerous pitfalls and potential issues that can arise when incorporating game elements and mechanics into the educational, alongside the requisite institutional conditions for students to fully immerse themselves in the provided context.
Exploiting Simulation Games to Teach Business Program
Authors: Tran Minh Tung , Thi Thu Trinh , Hoai Lan Duong
Published: December 2023

The research goal was to present an organized overview of literature related to games-based learning as a tool for improving the excellence and distinctiveness of the teaching courses as a whole and, specifically, hotel management teaching, which provided the significance of problems within higher education. The research essentially sought out the most acceptable teaching resources on games-based application. The project's empirical evaluation based on the games assigned to business students at FPT university, together with their qualitative and quantitative surveys, produced incredibly significant results. The key study outcomes include the creation of an empirical structure that incorporates several findings and lays the platform for future, more in-depth research. Another significant breakthrough is the ongoing incorporation of various forms of gamified studying events into tourism and curricula for hotel administration. The implications suggest that the academic and actual worlds should be combined to make teaching and learning more fascinating, motivating, and successful.
Adopting Effective Leadership Strategies for Managing Diversity
Authors: Diene Amdy , Baporikar Neeta , Obuobisa-Darko Theresa T.
Published: December 2023

In this study, 15 participants from a West African organization participated in interviews and surveys. The themes that emerged from the data analysis were organization conflict, cultural diversity, cultural competency, and the effects of nationalism and ethnocentrism on diversity management. The interview and survey data analysis revealed challenges and opportunities to achieve organizational objectives. These challenges include implementing policies that promote diversity, equity, and inclusion in an organization. Leadership strategies for diversity management may fail, decreasing worker satisfaction, retention, organizational success, and the representation of women and minorities in senior positions. Based on the literature review and empirical research findings, effective management strategies promote an effective working environment, promoting employees' well-being and an organization's sustainability. Descriptive statistical analysis was conducted using SPSS and NVivo to analyze the data per the discovered themes.
Cultural Competencies
Authors: Obuobisa-Darko Theresa , Wiafe-Kwagyan Millicent , Brenyah Ricard , Alhassan Moro
Published: December 2023

The chapter explores how public sector leadership could adopt the responsible leadership orientation for employee engagement through a responsible leader's cultural competence and proper diversity management practices. The chapter reviewed secondary data and established that responsible leadership is more likely to be culturally competent and, as such, put in place diversity management practices that enhance diversity management and, to a large extent, increase employee engagement, resulting in organizational success. Responsible leaders achieve this by readily learning to be culturally competent and relate well with diverse subordinates, leading to a feeling of belongingness and engagement. The chapter, therefore, advocates for adopting responsible leaders who are culturally competent and thus embrace diversity, manage diversity, and contribute to employee engagement in the public sector, which is essential in achieving national growth.
The CEO's Moral Values and Leadership Strategies for Managing Diversity
Authors: Diene Amdy
Published: December 2023

This study provides insights into the interconnections between a CEO's moral values and leadership strategies for managing an organization's diverse workforce. Using interviews and surveys, the authors collected data from 15 participants from a high-tech organization in the security industry in Senegal, West Africa. SPSS descriptive statistical analysis to analyze the survey data and NVivo coding methods for the interview data led to the exploration and discovery of the themes. In this chapter, the authors examined the theme 'CEO's moral values,' which aligns with the research question 'How do CEOs' moral values contribute to workplace diversity management?' The findings show that CEOs' moral values affect diversity management, influencing the interconnection between CEOs' moral values and leadership strategies for managing diversity. The study contributes to the literature by examining a novel context, the CEO's moral values, and diversity management in changing, uncertain environments.
Quantum Computing for Dengue Fever Outbreak Prediction
Authors: Chinnathambi Dhaya , Ravi Srivel , Matheen Mohammed Abdul , Pandiaraj Saravanan
Published: December 2023

Dengue virus infection originates from the Aedes mosquito species. The authors propose a novel paradigm to revolutionize dengue fever detection and recommendation systems by leveraging the potential of quantum computing. Using meteorological data and past dengue cases, they create a prediction framework that goes beyond traditional constraints. Quantum machine learning methods are proposed for discovering hidden patterns within enormous datasets, allowing them to identify detailed relationships between environmental conditions and illness occurrences. Traditional machine learning algorithms are all part of our strategy. Quantum optimization techniques further optimize these models, enhancing predictive accuracy while minimizing resource consumption. As we navigate challenges such as data integrity, model validation, and quantum hardware constraints, interdisciplinary collaboration between epidemiologists, quantum scientists, and healthcare experts becomes paramount. The analytical results from data show improvement in more cases of dengue prediction in the various districts of Tamil Nadu.
Understanding Biomedical Engineering for Quantum Computing
Authors: Agrawal Rashmi , Diaz Vicente Garcia
Published: December 2023

Engineers working in the biomedical field have a wide range of responsibilities, such as helping to introduce a new medical imaging technology or to create assiduous devices to assist someone with a disability. Many people consider what exactly constitutes biomedical engineering reasonably clear. Still, there are many differences of opinion regarding this field that can be traced to differences concerning the definition of the field. This chapter aims to provide an understanding of the ground of biomedical engineering and its relevance in quantum computing. The authors are discussing various areas of biomedical engineering where research is constantly happening. With the combination of quantum computing, biology, engineering, and computer science, researchers always strive to be the best.
Algorithmic FinTech Pioneering the Financial Landscape of Tomorrow
Authors: Aggarwal Kapil Kumar , Sharma Atul , Kaur Rumit , Lakhera Girish
Published: December 2023

Algorithmic FinTech emerges as a pioneering force transforming the financial landscape in an era of fast technical breakthroughs and a new financial worldview. This study examines Algorithmic FinTech in-depth, providing light on its transformational potential, essential applications, and profound impact on the future of finance. Algorithmic FinTech is applying cutting-edge technology such as artificial intelligence, machine learning, and data analytics to optimize financial processes. This chapter examines algorithms' numerous roles in the financial industry, ranging from risk assessment and trading methods to personal financial management and lending solutions. This chapter provides an in-depth introduction to comprehending the transformational potential of Algorithmic FinTech, its applications, and its influence on traditional banking while emphasizing the importance of responsible innovation in ensuring a robust and equitable financial future.
Contribution of Disruptive Technologies in Computational Finance
Authors: Bhatt Arvind Kumar , Rai Anand Kumar , Tiwari Rajesh
Published: December 2023

Disruptive technologies have ignited a profound transformation in the landscape of computational finance. As the realms of finance integrate cutting-edge technologies like quantum computing, artificial intelligence, blockchain, and big data analytics, the limits of financial possibilities are continually being pushed further. As artificial intelligence, blockchain, big data analytics, and quantum computing find their place in the financial realm, the boundaries of what is possible in finance are constantly expanding. This chapter explores the impact of these disruptive technologies on computational finance, dissecting their applications, benefits, challenges, and ethical considerations. By navigating this ever-evolving intersection of technology and finance, the authors gain insights into a future where financial services are more efficient, accessible, and adaptable than ever before. The chapter analyzes the tools for better understanding of the technology in finance domain and provide the trends of research in computational finance space using bibliometric analysis.
Artificial Intelligence
Authors: P. Sathyaraj , G. Nirmala , S. Vijayalakshmi , S. Rajakumar
Published: December 2023

Earth observations have become a developing trend over the last decade because of their ability to enable real-time tracking and forecasting of various environmental phenomena, including landslides, drought, floods, and wildfires. However, conventional approaches in Earth observation have relied on guide processing or human interpretation of the statistics. Via the mixing of AI, the Earth statement's achievement has progressed significantly. AI offers automatic and timely analysis of significant volumes of faraway sensing and satellite TV for computer facts, considering progressed tracking of various natural events and approaches. The software of AI in Earth Remark has enabled several advantages, including improved accuracy in mapping and classification of gadgets, detection of hobby gadgets, which include homes, roads, and forests, and tracking of changes in land use and land cover.
Reinforcement Learning-Based Earth Observation System
Authors: J. Jeno Jasmine , N. Padmavathi , M. Theodore Kingslin , Akram Faiz
Published: December 2023

This chapter gives a reinforcement learning (RL)-based earth observation device for figuring out exciting occasions in satellite imagery. The device is based totally on a Markov selection system, with the RL set of rules supplying a means to optimize the choice-making technique by maximizing the expected reward. To effectively create the MDP surroundings, numerous photo features such as contrasting colors, item boundaries, and textures are applied to detect occasions of hobby. Then, movements and zooming in or converting the standpoint are taken to inspect the event further. The RL set of rules is constantly updated, primarily based on the rewards acquired from every movement taken. The chapter also describes a simulation set-up with a natural satellite TV for PC imagery that's used to illustrate the capacity of the proposed gadget. Ultimately, the system is evaluated by comparing its overall performance with baseline algorithms. Results show that the proposed gadget performs better for detecting exciting activities in satellite imagery.
Nearest Neighbor-Based Earth Observation and Monitoring
Authors: J. Sutha , S. Meenakshi , C. Esakkiappan , G. Anitha
Published: December 2023

The objectives of this chapter are multifaceted and directed towards a comprehensive understanding of Earth's land cover and environmental changes. First and foremost, the aim is to provide accurate and reliable land cover mapping of the Earth's surface, ensuring that the information is timely and comprehensive, thereby facilitating a better grasp of environmental transformations. Furthermore, a key objective is to enhance our knowledge of climate change and its far-reaching impacts, with a specific focus on improving the precision of monitoring the natural environment and habitats. In addition to this, the study aims to investigate and analyze the patterns of land use change and the associated impacts on the environment. This involves a thorough examination of the resources involved and the repercussions resulting from alterations in land cover. Moreover, the objective is to gain a comprehensive understanding of areas with significant environmental vulnerability, pinpointing regions that are particularly sensitive to environmental changes.
Development of a Neuro-Inspired Algorithms for Monitoring and Prediction of Earthquakes
Authors: M. Rekha , A. Chilambuchelvan , M. Dinesh Babu , V. Vasudhevan
Published: December 2023

This chapter offers the improvement of a robust neuro-stimulated algorithm for monitoring and prediction of earthquakes. The designed machine, gaining knowledge of a new algorithm, can successfully filter the critical functions from seismic data and locate numerous seismic activities in actual time. This algorithm is custom-designed for seismic facts analysis and designed for supervised studying. The key feature of this set of rules is its capacity to discover and classify seismograms, which can be new to the model, making it notably predictive. The outcomes of the tracking and prediction show that the advanced neuro-inspired set of rules should successfully discover various seismic activities with a quick latency and low fake positive rate. Furthermore, the proposed algorithm presents an optimal aggregate of binary classification for earthquake monitoring and prediction. This set of rules is a promising tool to enhance earthquake chance assessment and early warning structures.
Earth Sciences Unleashed
Authors: S. Shobana , A. Muthumari , S. Subashree , G. Elumalai
Published: December 2023

The emergence of synthetic artificial intelligence (AI) in recent years has revolutionized numerous sectors, which includes Earth Sciences. AI has recently emerged as a powerful tool in Earth Sciences, enabling scientists to analyze enormous amounts of records, broaden models, and make more accurate predictions. AI offers powerful analytical gear to process large quantities of facts and perceive complicated patterns that might, in any other case, be challenging to discover. This ability to investigate and link disparate information assets permits scientists to benefit from complete insights into Earth's structures, assisting us in understanding the using forces at the back of herbal phenomena like earthquakes hurricanes. The episode discusses numerous AI techniques, inclusive of machine getting-to-know, deep mastering, and statistics mining and their application in Earth Sciences. It explores how these strategies can decorate statistics processing, automate complex obligations, and uncover hidden styles in massive datasets.
Fuzzy Logic-Based Monitoring of Earth Observations
Authors: R. Karthiga , V. Saravanan , Kumar Sunil , S. Rajakumar
Published: December 2023

Monitoring Earth observations performs a crucial role in expertise and predicting numerous phenomena, including weather trade, herbal disasters, land use adjustments, and commercial pollutants. This chapter explores the use of fuzzy logic strategies for monitoring earth observations, considering its capability, blessings, and challenges. Fuzzy logic-based total decision support structures have been established to be adequate gear in monitoring earth observations. One of the key advantages of this method is its ability to deal with vague and unsure data. One of the key findings is the potential of fuzzy good judgment-based monitoring to handle and incorporate uncertainty in earth observations. Conventional monitoring methods frequently battle with uncertainties associated with sensor noise, atmospheric situations, and ambiguous class standards. Fuzzy logic-based systems, alternatively, excel in handling such uncertainties by presenting bendy and adaptive reasoning strategies.
Deep Learning Approaches for Earth Science
Authors: Virmani Deepali , K. S. Ananda Kumar , L. P. Sajitha , Parveen Nikhat
Published: December 2023

Earth science, a multidisciplinary field that explores diverse components of the Earth, has also been significantly encouraged with the aid of the creation of deep studying procedures. The summary starts by highlighting the increasing availability of large datasets inside the Earth's technological know-how domain, frequently observed by way of complicated relationships and patterns, which can be challenging to find the use of traditional analytical strategies. Deep studying techniques have additionally revolutionized geoscience information evaluation with the aid of permitting the identification of complex styles and relationships within massive datasets. Deep mastering algorithms have been verified as powerful in extracting significant statistics from such datasets, mainly to improve understanding of geological processes, aid exploration, and danger assessment. This review includes a vast range of programs, such as far-flung sensing, weather modeling, and earthquake prediction.
Sensory Intelligence-Integrating MBA Touch Into Earth Observation Systems for Enhanced Machine Learning
Authors: V. Saravanan , N. Golden Stepha , K.R. Chairma Lakshmi , S. Karthika
Published: December 2023

Sensory intelligence is the capacity of machines to procedure information from their outside and inner environment through the use of sensory fact inputs and making use of system getting-to-know algorithms. This chapter focuses on integrating touch into Earth remark systems to extend the functionality of machines and beautify machine mastering. Standard, the mixing of touch into earth observation systems, presents a way for machines to emerge as more intelligent and higher apprehend and interact with their environment. Machines are capable of soaking up an extra amount of sensory facts and using it to enhance the gadget, studying algorithms to create accurate and reliable fashions. The consequences of this era are some distance-achieving and allow for improved tracking, prediction, and decision-making. With advances in system studying, artificial intelligence, and robotics, the blessings of incorporating touch into earth commentary structures will only keep growing and become more treasured.
Risk Factors of Mental Health of Students in Higher Education Institutions
Authors: Opotamutale Daniel Opotamutale , Albanus Fillemon Shekutamba
Published: December 2023

Students' mental well-being plays an important role in academic achievement in higher educational institutions. A good mental state enables us to fully enjoy and appreciate our environment and the people around us. We can resist stress better and tackle daily life challenges with a positive frame of mind. Good mental health also allows one to be productive and to use one's mental abilities to the full. However, being a student brings about a number of events that can lead to stress, such as living away from home, giving up a good job to be a student, and organising your finances, deadlines and exams, to name just a few. The content of this chapter can be used by divison of student support affairs in higher education institutions worldwide to develop targeted interventions and strategies for alleviating the risk factors of concern to the mental health of students in higher education institutions.
External Factors Affecting the Well-Being of Students in Higher Education Institutions
Authors: Onyango Pamela Awuor
Published: December 2023

Studies have revealed that several factors affect the well-being of students in higher education institutions. The current chapter investigates some of the factors which include sexual harassment, student unrest, role of the family, and institutional environment. The main purpose of this chapter is to explore how the factors affect the well being of learners in higher education institutions. The chapter presents introduction of the study, its background, as well as the external factors affecting well being of students in higher education institutions together with future direction and the conclusion of the study.
Gender Differences in Stress Among Students of Higher Education During the COVID-19 Pandemic
Authors: Tomas Nestor , Awala-Nashima Atanasia Nangula , Tomas Theolinda Nuugwanga
Published: December 2023

The impact of the stress during COVID-19 pandemic among students of different genders is clear. However, there is lack of review on the extent of how students of various genders were affected, and the strategies used during COVID-19 pandemic within higher education setting. Using a textual narrative synthesis, this chapter searched databases for primary articles to explore the extent to which students of different genders were affected and the strategies used to cope during COVID-19 pandemic. The review used a priori tool for inclusion and exclusion criteria. Out of the total of 16,308 citations, 11 were identified from six different countries in the final review.
Psychological Well-Being of Students in Higher Education Institutions
Authors: Hako Anna Niitembu , Mbongo Emilia Ndapandula
Published: December 2023

Psychological well-being is a multifaceted and multidimensional concept. It includes essential elements such as happy emotions, autonomy, satisfying relationships, little negative emotion, a sense of meaning in life, and personal development. Psychological well-being is essential for overall health and happiness and has been associated with greater physical and mental health as well as a longer life span. This study attempts to gain theoretical knowledge about psychological well-being and knowledge of the various studies conducted in the area of psychological well-being. To alleviate stress and enhance students' psychological well-being, higher institutions of learning must prioritize proactive, resilience-focused, and mental health promotion efforts to assist students.
The Benefits of Self-Talk and Imagination for Your Mental Health and Happiness Adolescence in Higher Education
Authors: Pathak Vijendra Nath , Chatterjee Prattusha
Published: December 2023

In the contemporary, fast-paced world, adolescents are confronted with unparalleled challenges and pressures to excel. The core objective of this chapter is to furnish readers, particularly mental health professionals and adults, with pragmatic methodologies to aid adolescents in navigating the challenges that beset their lives. In conclusion, this chapter serves as a valuable reservoir of knowledge for those who are concerned about the well-being of adolescents in today's fiercely competitive and demanding milieu. It furnishes a comprehensive comprehension of self-talk and its various manifestations, elucidating their profound influence on an individual's thoughts, emotions, and actions. Ultimately, the chapter advocates for a proactive approach to adolescent well-being, underscoring the primacy of prevention over remediation.
Flourishing on Campus
Authors: Vetrivel S. C. , Mohanasundaram T.
Published: December 2023

Mental health concerns among college students have become a growing issue in higher education institutions worldwide. The transition to college life often comes with various stressors, such as academic pressure, social adjustments, and financial challenges, which can negatively impact students' well-being. To address this issue, higher education institutions are increasingly focusing on promoting mental health and coping skills to foster student flourishing. This abstract explores the importance of implementing initiatives and programs that support mental health and coping skills on college campuses. Firstly, it is essential to understand the concept of flourishing, which encompasses positive emotions, engagement, meaning, positive relationships, and accomplishment. Promoting flourishing on campus involves creating an environment that not only addresses mental health issues but also nurtures students' overall well-being.
Institutional Support Available to Enhance the Mental Health of Students in Higher Education Institutions
Authors: Odhiambo Janet Auma , Mukadi Enos Barasa
Published: December 2023

Mental health is important in every individual's life right from childhood through to adulthood. A state of good mental health accounts for an individual's ability to cope with life stressors and attain quality life. Students at the institutions of higher learning are exposed to a range of psychological variables ranging from financial constraints, family problems, and sicknesses, to social relations, which adversely affect their mental well-being. A majority of students are not able to deal with the risk factors or challenges that may affect their mental health. Some feel overwhelmed and experience various adjustment problems, which may eventually lead to mental illness. The services that are provided at school need to take care of all the areas that can be productive and counterproductive to the learning environment. There is a need for human resources who are experts in shaping the student's behavior and overall adjustment at school.
Institutional Support Available to Enhance the Mental Health of Students at the University of Namibia
Authors: Ashipala Daniel Opotamutale , Ntjamba Fransisco Chindongo
Published: December 2023

This chapter critically examines the institutional support systems aimed at supporting the mental health of students within the University of Namibia. The shift from childhood to adulthood brings with it special difficulties, leaving students open to a range of stresses that can negatively impact their mental health. This research examines common mental health problems among students, such as stress and anxiety, with a particular focus at the University of Namibia. The study highlights the necessity of an all-encompassing strategy that considers social, emotional, and intellectual aspects in order to create an environment where students can flourish both academically and mentally. This chapter adds to the continuing conversation on mental health in higher education by advocating for additional improvements and identifying successful initiatives. This chapter adds to the continuing conversation on mental health in higher education by advocating for additional improvements and identifying successful initiatives.
Cross-Checking-Based Trademark Image Retrieval for Hot Company Detection
Authors: Wu Hao , Zhang Zhiyi , Zhu Zhilin
Published: December 2023

A trademark is an essential symbol of a company, consisting of a semantically rich image under ordinary circumstances. The popularity of a company can be measured by the frequency of its trademark being used. Therefore, efficiently retrieving trademark images would directly contribute to the detection of popular companies. However, most mainstream retrieval methods are not especially pertinent to trademark image retrieval. To solve this problem, a combination of the ResNet50 network and Autoencoder with local sensitive hashing (LSH) is used to conduct full cross-checking, which significantly improves the effectiveness of trademark image retrieval. Meanwhile, image super-resolution-based sparse coding is also proposed to achieve high-precision trademark image retrieval and its effect is particularly significant for challenging trademark images. Finally, the authors conduct extensive experiments on a high-quality database to demonstrate the substantial effectiveness of the proposed methods.
Antimicrobial Activity of African Walnut (Tetracarpidium conophorum) Oil against Bacterial and Fungal Species Causing Food Spoilage and Food Poisoning Diseases
Authors: Fakile O. D. , Solana O. I. , Okolosi J. E.
Published: December 2023

This study evaluated the antibacterial and antifungal activity of African walnut (Tetracarpidium conophorum) oil against species causing food poisoning and food spoilage. African walnut oil was extracted using the solvent extraction method. The fatty acid profile of the oil was determined using gas chromatography mass spectrometry (GC-MS). The agar disc diffusion method was used to determine the antibacterial activity of the oil before using it for further tests. Minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were also determined using the disc diffusion assay. The result indicates that palmitic (1.53%), linoleic (13.5%), linolenic 80.59%, stearic (4.41%), and eicosenoic acid (0.42%) were present in the oil with higher polyunsaturated fatty acid values. African walnut oil showed remarkable activity against all the Gram positive organisms (Bacillus cereus ATCC 33018, Staphylococcus aureus ATCC 25923, Clostridium perfringes NCTC 8799, and Listeria monocytogenes ATCC 13932) with the inhibition zones ranging from 21.6 ± 0.27 mm to 26.3 ± 0.23 while the Gram negative organisms (Pseudomonas fluorescens ATCC 13883, Pseudomonas fragi ATCC 4973, Escherichia coli ATCC 12806, Salmonella enterica subsp. enterica serovar Typhimurium strain ATCC 14028) were less sensitive and resistant to the oil chromatography-mass with inhibition zones ranging from 6.3 ± 0.31 to 9.9 ± 0.21 mm. Out of the tested oil concentrations from 100 – 0.39 mg/mL, MIC obtained for the Gram positive organisms was 1.56 mg/mL while it was 3.13 mg/mL for Gram negative bacteria (except L. monocytogenes). The antifungal test reveals the MIC range of 100 - 0.78 mg/mL in all the fungal isolates tested. African walnut oil has proved to be potentially active against the Gram positive bacterial and fungal species tested indicating that it can be used as a natural alternative to control food spoilage and food poisoning diseases.