bluuebunny/crossref_metadata_2025 huggingface dataset:
Émile Combes ministre de l’Instruction publique (1895-1896)  : un réformateur radical
Authors: Verneuil Yves
Published: July 2024

Le passage d’Émile Combes au ministère de l’Instruction publique entre le 1er novembre 1895 et le 29 avril 1896 fut marqué par un réformisme très affirmé. Furent notamment déposés un projet de loi de réforme du baccalauréat et un autre sur le Conseil supérieur de l’Instruction publique (CSIP). Ces initiatives suscitèrent d’intenses débats au sein du corps universitaire. Cet article s’interroge d’une part sur la portée du passage d’Émile Combes à la tête du ministère de la rue de Grenelle dans le cadre d’une séquence marquée, entre 1880 et 1902, par l’importance des débats relatifs à la direction à donner à l’enseignement secondaire  ; et d’autre part, dans la mesure où Émile Combes fit partie du premier cabinet radical homogène, sur la question de savoir si l’on peut discerner une adéquation entre sa politique scolaire et les idées politiques développées par les radicaux à la fin du XIXe siècle.
CNNFDNF: CONVOLUTIONAL NEURAL NETWORK AND CASCADE NEURO FUZZY NETWORK FOR SEVERITY LEVEL OF COVID-19 DETECTION USING CHEST X-RAY IMAGES
Authors: Kalpana Gotlur , Durga A. Kanaka
Published: July 2024

Chest X-ray (CXR) images are the most important imaging modality to monitor and detect several lung diseases and Coronavirus Disease 2019 (COVID-19) disease. This is the first imaging method in the detection of COVID-19. Since the limited availability of interpreted medical images, and the accuracy are the biggest challenges in the conventional methods. Hence, a novel framework is designed for the severity level of COVID-19 detection using CXR images named Convolutional Neural Network and Cascade Neuro-Fuzzy Network (CNNFDNF). Initially, the input CXR image is allowed to the preprocessing phase that is done utilizing the Kalman filter and Region of Interest (ROI) extraction. Then, the lung lobe segmentation is executed by Psi-Net. After that, the extraction of Convolutional Neural Network (CNN) features is conducted from the interested lobe region. Moreover, the extracted image features are subjected to COVID-19 detection, where it is achieved by Deep Generative Adversarial Network (Deep GAN) trained by Henry Gas Water Wave Optimization (HGWWO). Here, HGWWO is blended by Water Wave Optimization (WWO) and Henry Gas Solubility Optimization (HGSO). The detection phase is categorized into COVID and non-COVID. If the detected image is COVID, then the CXR images are given to the second level classification. Finally, it is accomplished by employing the proposed CNNFDNF to classify them into low, moderate, or high COVID-19 infection affected at lungs. The proposed CNNFDNF is the newly devised scheme by modifying the layers of CNN and cascaded neuro-fuzzy network (DNF) structure. The measures employed for this scheme namely, accuracy, sensitivity and specificity acquired are 93.0%, 94.1%, and 93.8%. The proposed method is essential for keeping the situation under control. Because, in the severe cases may have severe pneumonia, other organ failure, and possible death.
Techno-Economic Feasibility Study of Multi-Energy-Based Hybrid Power System at an Industrial City
Authors: Prasad Dharmbir , Singh Rudra Pratap , Gupta Gaurav , Khan Md. Irfan
Published: July 2024

Energy is crucial for economic growth and is necessary for the progress of all nations. The demand for renewable energy sources with very low environmental impact and reduction in hazardous gases emission has increased due to the need for sustainable industrial city solutions in energy supply. This study presents a proposed advanced multi-energy-based hybrid system for meeting the electric needs of an industrial belt at Jamnagar industrial city. The proposed system aims to enhance the existing infrastructure by integrating additional energy generation sources, energy storage, and a converter to achieve significant cost reductions. The proposed system comprises a 31 kW PV system, 121 kWh of battery capacity, and 6.0 kW of wind generation capacity. By incorporating these elements, the operating costs are projected to decrease to $14,497 per year. This reduction translates to a considerable payback period of 4.7 years and an IRR of 8.3%.
Performance Evaluation of a Low Head Hydraulic Air Compressor
Authors: Roy Apurba Kumar , Kumar Kaushik
Published: July 2024

Hydraulic air compressor is a device that utilizes the energy of falling water, with entrained air bubbles, onto a downcomer pipe to compress the air within it. This concept to harness hydropower to compress air and its use dates back to the Iron Age. It was discarded after the evolution of fossil fuel due to its bulkiness. The concept has revived again after the global cry for renewable sources of energy. In this work an experimental setup was made to study the hydrodynamic characteristics of downward air-water two-phase flow through the downcomer pipe of the hydraulic air compressor. It was observed that the results were quite comparable to the theoretical predicted values and hydraulic air compressor has many useful interesting applications and can also be used as an alternative air compression system.
Realization of Demand Side Management in Smart Grid
Authors: Nanibabu Sampatirao , Baskaran Shakila , Marimuthu Prakash
Published: July 2024

The concept of demand side management (DSM) must be emphasized in the current era, foreseeing the drastic escalation of energy demand and depleting fossil fuels. DSM ensures effective facility utilization by controlling clients' energy resources and carefully adjusting their energy demand profiles. In this study, the day-ahead load-shifting DSM technique is modeled as a minimization problem to achieve better load profile. The whale optimization algorithm (WOA) is provided for resolving the DSM optimization problem. The proposed work has been tested on three demand zones with various controllable loads: residential, commercial, and industrial. With the suggested WOA method, a comparison analysis based on peak demand and operational expenses was made. Finally, it is demonstrated that in the different load sectors, the DSM strategy based on the WOA technique provides better cost savings and also helps in achieving flat load profile while reducing peak to average ratio (PAR).
The Implications of Technology Usage in the Treatment of Behavior Disorders in Children
Authors: Tyler-Wood Tandra , Potnuru Rohan Paul , Tyler Molly Nicole
Published: July 2024

Technology is a prevalent part of life in the 21st century. The COVID-19 pandemic made technology even more critical in providing services to school-aged children. Children with behavioral disorders were particularly impacted as mental healthcare services often used by children with behavior disorders were strained by the stressors related to the pandemic. This chapter reviews the technologies currently used to provide services and support to children identified with behavior disorders, their teachers, and their families. Cautions concerning the use of technology with this highly vulnerable population are explored. Suggestions for the future use of technology for students with behavior disorders are made.
Effective Behavior Intervention Strategies in Special Education
Authors: R. Krishna Kumari
Published: July 2024

This chapter presents a comprehensive guide for special education professionals, offering a deep dive into effective behavior intervention strategies tailored to the needs of students in special education. In a post-COVID-19 world, educators are increasingly challenged with addressing behavior issues, and this chapter aims to provide impactful solutions. The primary objective is to connect researchers with practitioners in the special education field, offering evidence-based strategies that are both timely and effective.
Advanced Joining Methods for Lightweight Materials in Sustainable Manufacturing
Authors: S. Suresh , D. Velmurugan , J. Balaji , S. Sudhagar , R. Elayaraja
Published: July 2024

In today's rapidly evolving industrial landscape, the pursuit of sustainability and lightweight materials has become paramount. The rising demand for such materials across various industries, including automotive, aerospace, and renewable energy, will be underscored. As industries seek to reduce their environmental footprint while enhancing product performance, the importance of advanced joining methods for lightweight materials cannot be overstated. The primary goal of employing these advanced joining techniques is to enhance the efficacy of the joining process and mitigate the risk of failure. In this chapter, a concise exploration is undertaken to grasp the intricacies of cutting-edge joining methods, including friction stir welding, microwave hybrid heating, electron beam welding, laser beam welding, and ultrasonic welding. This chapter aims to offer a comprehensive understanding of the underlying principles, contemporary developments
Industry 4.0 in the Textile Sector
Authors: Awasthi Kanchan , Padwekar Krunal , Misra Subhas Chandra
Published: July 2024

Industry 4.0 is a phenomenon that describes technological advancement in all sectors to bring the best business practices and to create a sustainable society. Textile sector which remained at the forefront in the past three industrial revolutions is lacking its spot in the fourth industrial revolution, making it difficult to sustain in the competitive environment. The sector can realize the benefits of Industry 4.0 by following a systematic strategy to implement it. To follow a systematic strategy, it is important to have the necessary background knowledge and ongoing trends in the field. For this purpose, we reviewed and analyzed the current literature to know the status of Industry 4.0 in Textile sector. This review mainly focused on three categories: the type of research, focused technology in Industry 4.0, and focused dimensions (i.e., applications, influencing factors, and opportunities). This review will prepare researchers to conduct the research in the field and will suggest solutions to implement Industry 4.0 in textile sector
Roadmap to Achieve Sustainable and Eco-Friendly Metal Additive Manufacturing Processes
Authors: Baskaran Jagadeesh
Published: July 2024

As the global manufacturing landscape undergoes a paradigm shift towards sustainability, the metal additive manufacturing industry faces the imperative to align its practices with environmental, economic, and social considerations. This chapter outlines a comprehensive roadmap towards sustainability in metal AM, addressing key challenges and proposing strategic interventions. Through a thorough analysis of current practices and their environmental impact, the paper identifies opportunities for improvement in material usage, energy consumption, and waste reduction. Additionally, the study explores the economic viability of sustainable practices, emphasizing the potential cost savings and market advantages. The integration of social responsibility within the metal AM ecosystem is also examined, emphasizing the importance of ethical and inclusive approaches. By synthesizing these elements, this chapter offers a framework to navigate the transition towards a more sustainable future.
Review on Machine and Deep Learning Techniques
Authors: Mohan Amrita , Ojha Soni
Published: July 2024

In the field of AI, ML, and DL are the most revolutionary technologies in many areas like image recognition, ranging from detection to segmentation, healthcare diagnostics, autonomous vehicles, etc. Both techniques have made considerable contributions to innovation by transforming the interaction. For writing the review, the article selection is based on a comprehensive literature search including conferences, academic databases, journal publications, and reputed online sources covering significant points such as history, applications, procedures, etc. Each article was critically analysed to extract the insights, findings, and arguments to meet review objective. A comprehensive overview is presented in the chapter including fundamentals along with recent emerging trends applications, qualitative and quantitative analysis timeline growth, and future directions to explain these topics easily to early-stage researchers.
A Comprehensive Analysis of Drone Regulations in India and the European Union
Authors: Thombare Vishwanand
Published: July 2024

The rapid growth of the drone industry and the increasing use of unmanned aircraft systems (UAS) across various sectors have necessitated the development of comprehensive regulations and airspace management practices. This chapter provides a comparative analysis of drone regulations and airspace structures in India and the European Union (EU), two significant domains that have taken proactive steps to regulate the UAS industry and facilitate its growth. India's drone regulations, governed by the Directorate General of Civil Aviation (DGCA), categorize UAS based on their weight and type, with the airspace divided into red, yellow, and green zones. The EU has adopted a risk-based approach, categorizing drone operations into open, specific, and certified categories, with specific operational limitations and authorization requirements for each. The comparative analysis highlights the similarities and differences between the two regions, offering insights for policymakers, industry stakeholders, and researchers.
Revisiting Digital India 2.0
Authors: Zehra Farheen , Khan Farhina Sardar , Mazhar Syed Shahid , Khan Ambrina Sardar
Published: July 2024

Technology has become a crucial part of people's lives. Digitization has become essential for its seamless communication and omnipresent access to information. This chapter delves into the transformative landscape of technology and its impact on India's digital progression. This topic encapsulates a diverse range of facets essential for understanding the ever-evolving digital paradigm in the country. It aims to provide new insights into innovative advancements and the potential for growth in various sectors. This chapter is an in-depth examination of complex technological advancements that have been and will continue to change India's socioeconomic landscape. The report covers integrating emerging and disruptive technologies, such as artificial intelligence, machine learning, blockchain, and the internet of things (IoT), in various domains. This chapter illustrates the profound transformation held in various segments, namely, digital technology, online infrastructure, internet connectivity, smart cities, digital literacy, knowledge-driven economy and e-services
Impact of Workplace Conflict on Job Satisfaction of Civil Aviation Authority
Authors: Jaiswal Roshni , Shrivastava Sarika
Published: July 2024

The field of aviation is expanding quickly. Due to its advantages over other forms of transportation in terms of both time and passenger comfort, the quickly expanding aviation sector has begun to gain popularity. The purpose of the research is to examine how workplace conflict affects employees' job satisfaction and to determine the causes of conflict in the workplace and ultimately, its detrimental impact on job satisfaction. The primary methodologies of the study include a review of the literature already in existence and data gathering utilizing a questionnaire that was approved and distributed to a sample of supporters of the India Civil Aviation Authority for aircraft operation. Among the samples, which were chosen using the cluster sampling approach, 144 questionnaires in total were delivered. The Indian Civil Aviation Authority's Aircraft operation supporters provide the unique case study for this research article. The Indian Civil Aviation Authority's aircraft operation supporters as well as other professions in the same sector might explicitly use the findings.
Basic Concepts of Sensory Technology
Authors: Imamou Hassani Mouandhe , Bilgin Hakki , Jūrienė Laura
Published: July 2024

It has become increasingly challenging for food and beverage industries to manufacture products that meet consumers' demands and preferences. Safety, quality, and convenience are among the top priorities for today's smart consumers. On one hand, food manufacturers need to understand how their products are perceived by consumers at first glance in order to succeed in the market. For instance, an unusual appearance or a bizarre smell of a food product can ultimately lead to a total rejection by customers. On the other hand, uncovering the fundamental concepts of sensory science will advance food processing by targeting specific needs and expectations. This chapter reviews the primary attributes of sensory evaluation, the human senses and their role in sensory science, and applications of sensory technology in product development.
Human Gustatory System
Authors: Maganti Deepika , Madhan Prathesh , Viswanathan Rohan S. , Kachhi Zidan
Published: July 2024

The five primary flavors are sweet, sour, bitter, salty, and umami. The tongue plays a crucial role in discerning the various flavors. Gustation refers to the sensory perception of taste and plays a crucial role in shaping our flavor sensations. This chapter discusses gustation, commonly referred to as taste, and its significance in food preparation and our perception of flavor. The text commences by providing an explanation of gustation and offering a concise overview of its significance within the realm of sensory science. This text elucidates the process by which signals are conveyed from our taste buds to the brain, as well as the molecular constituents of many flavors. Age, genetics, and culture are crucial influences in our perception of flavour. The study examines the ways in which taste perception might be influenced in contexts where individuals may experience altered taste sensations, as well as the techniques used to measure and quantify flavour. It examines the actual application of this knowledge, specifically in the creation of distinctive food items that take into account consumer preferences and health considerations.
Sense of Touch
Authors: Aktar Tugba
Published: July 2024

This chapter discusses the sense of touch in terms of food sensory and texture sensation aspects. The sense of touch is an important aspect of food perception that impacts consumer preferences and acceptance. It will cover the definition of tactile perception, the structure and physiology of receptors, and the mechanism of texture perception. A thorough discussion of the factors that affect texture perception, including the phase of oral processing, was provided. Finally, the chapter will explore the application of texture and rheology measurement in different food sectors, including dairy, meat, bakery, and confectionery. This chapter on tactile perception and its applications for food production will provide readers with the necessary information on the sensory science of texture perception, and measurement. It will cover the current state of research and application, along with the potential for future development in this area of science within food production. This chapter will be valuable tool for food industry professionals and researchers of food science and technology
Strategies for Advancing Indian Higher Education
Authors: Barnikana Narasinga Rao , Padmaja C. V.
Published: July 2024

Social innovation in Indian higher education is becoming increasingly crucial as institutions seek to address the diverse challenges facing society. This chapter explores innovative strategies employed within the Indian higher education sector to foster social impact and address societal needs. Drawing on a range of case studies and examples, it examines initiatives that integrate social responsibility, community engagement, and sustainability into the fabric of higher education institutions. These strategies encompass various dimensions, including curriculum development, research initiatives, community outreach programs, and partnerships with stakeholders from diverse sectors. The chapter highlights the importance of collaboration among academia, government, industry, and civil society in driving social innovation in higher education. Furthermore, it discusses the role of technology and digital platforms in enhancing the reach and effectiveness of these initiatives.
Metaverse Integration in Healthcare
Authors: Gupta Princi
Published: July 2024

This chapter explores the metaverse's impact on healthcare, questioning its lasting transformation or temporary trend. It introduces metaverse concepts in healthcare, discussing its potential to revolutionize training, telemedicine, therapeutic interventions, and global collaboration. Challenges like technical issues and ethical concerns are addressed, evaluating the metaverse's sustainability. Real-world case studies showcase its lasting value, suggesting a meaningful role in healthcare. Historical parallels assess its potential longevity, determining if it drives enduring change or rapid obsolescence. The conclusion offers a forward-looking perspective on the metaverse's evolution, critically analyzing its transformative potential in healthcare, aiming to distinguish between a lasting catalyst and a momentary fad.
Navigating Transnational Higher Education Management
Authors: Morris Gareth Richard , Mo Junhua , Berhanu Tesema Fiseha , Wang Katherine , Li Lei
Published: July 2024

Transnational Higher Education (TNHE) has experienced many challenges in recent years. From the pandemic, and its legacy, to the emergence of generative AI, universities are faced with the prospect of bouncing from one issue to another. Making life additionally complex is the fact that regional instability is increasingly common globally now, with issues occurring in locations that had previously experienced periods of relative long-term stability. This chapter will consider some of the most pressing challenges that middle managers face in TNHE providers today by drawing on the insights of experienced middle managers who work at well regarded TNHE providers in eastern China prior to, during and immediately after the pandemic.
Exploring the Influence of Leadership on Job Satisfaction in Universities and International Schools
Authors: Ma Xuan , Zhang Ji
Published: July 2024

This study aims to explore the influence of leadership styles on the job satisfaction of teachers at a Chinese transnational higher education university and at an international school. This study uses qualitative research methods and in-depth interviews to investigate the job satisfaction and dissatisfaction among four educators working at transnational higher education providers. The findings suggest that teachers working at a private university are generally satisfied with their work, especially when it comes to leadership providing guidance and trust. However, work load and wage equity are sources of concern, along with disorganization, punitive fines and interpersonal relationships in a K12 school. This study advocates the provision of employee-friendly working conditions and the enhancement of the teacher welfare to improve workplaces.
Leadership in English for Academic Purpose(EAP)
Authors: Cui Kevin
Published: July 2024

This chapter examines leadership's role in English for Academic Purposes (EAP) within Sino-foreign universities, focusing on overcoming linguistic and cultural challenges through adaptable, culturally sensitive leadership. It highlights the shift from traditional to contemporary leadership theories and the importance of innovation and inclusivity in response to challenges like online learning transitions during the COVID-19 pandemic. Additionally, it explores transformational and transactional leadership models, emphasizing cultural sensitivity in merging Eastern and Western educational practices. The chapter suggests future research directions for enhancing leadership effectiveness in EAP contexts, aiming to improve student engagement and success in the complex landscape of Sino-foreign higher education.
Artificial Intelligence in Education
Authors: Delello Julie A. , Watters Jennifer Bailey , Garcia-Lopez Arlene
Published: July 2024

This chapter explores artificial intelligence (AI) and its potential to revolutionize the field of education by enhancing teaching and learning. It further highlights ways in which AI technologies can support educators and students, including content creation encompassing voice and video, task automation, and the provision of personalized learning through adaptive learning platforms. Potential benefits to leveraging AI technology include improved learner engagement, automated administrative processes, and more robust data-driven insights. As AI advances, a unique opportunity emerges for schools to prepare educators to use AI in the classroom and for educators to redefine traditional teaching methodologies. Nonetheless, balancing AI innovation with ethical considerations includes considering issues in transparency and privacy in AI algorithms as well as mitigating biases in the data.
Digital Skills Through the Prism of European and Spanish Supranational Frameworks
Authors: Gil Casadomet Aránzazu
Published: July 2024

This research delves into the importance of digital citizenship and skills in contemporary society shaped by the digital revolution. It critically analyzes digital skills frameworks like DigCompEdu, DigComp 2.2, UNESCO's ICT-CFT, and Spain's MCCDD, highlighting their strengths and limitations and emphasizing adaptation to learners' needs. An innovative pedagogical approach integrating virtual interaction and AI into foreign language instruction is examined, aligning with European Reference Frameworks and UN Sustainable Development Goals. The challenges, opportunities, and ethical considerations in these educational dynamics within the digital landscape are explored. Ten axes are proposed to outline this approach, including interactive virtual environments, AI-driven e-learning platforms, virtual reality integration, AI-driven assessments, collaboration between educational institutions and tech companies, and promoting AI ethics awareness. It highlights the need for a current reference framework and standardized quality criteria to guide ICT utilization in the classroom.
Case Study on the Performance Evaluation of Graduates in the Field of Artificial Intelligence for Ethiopian Universities
Authors: Mishra Nilamadhab , Habtemariam Getachew Mekuria , Aebissa Berhanu , Nayak Rudra Kalyan , Tripathy Ramamani , Thakur Amit , Rout Saroja Kumar
Published: July 2024

In this study, an evaluation of the performance of AI graduates at an Ethiopian university was conducted. This evaluation focused on the extent to which graduates develop their work-ready skills, how well artificial intelligence graduates are performing at the workplace, the skills that hiring organizations expect from artificial intelligence graduates, and the challenges that hiring organizations are facing concerning artificial intelligence graduates. The survey also revealed that respondents advocated enhancing the induction and training programs in businesses to be complete (like manuals) and lengthy, and to utilize seasoned experts as mentors for the recently hired. This recommendation was made in response to the finding that respondents supported strengthening the programs. Plans were made to improve the performance of artificial intelligence graduates at Ethiopian University. Further research is needed to go deep into the curricular and methodological aspects, and decisions can be made to improve the performance of artificial intelligence graduates at Ethiopian University.
Cheating and Prevention Strategies in Online Assessment
Authors: Taşkın Necati
Published: July 2024

Increasing interest in online learning has increased the need for online assessment. However, academic dishonesty is a significant problem in online assessment. Cheating is one of the leading forms of academic dishonesty. Cheating is a serious problem with negative consequences that should be avoided by educators and students. Therefore, cheating emerges as a major problem in online assessment that requires an urgent solution. Understanding students' cheating behaviors will help determine steps to prevent this problem. This information will provide important clues for more reliable online assessments. In this context, this book chapter is presented to readers as a comprehensive resource on online assessments and cheating. In addition, important strategies were presented to all stakeholders such as designers, administrators, instructors, and students to prevent cheating on online assessments.
Technology Inclusive Adult Education (TIAE) Model Validation and SWOT Analysis
Authors: Bohra N. S. , Singh Praveen , Verma Vivek
Published: July 2024

Education for non-educated means education for individuals who have not had formal education or who are considered non-educated, and is often referred to as adult education or adult literacy programs. Most of the adult education programs across the globe are designed on three basic themes that are reading, writing, and numeracy skills. Such adult education approach is characterized by several drawbacks, and these limitations are hindering the attainment of the intended outcomes in adult education programs. This study is proposing technology inclusive adult education (TIAE) model for adult education. TIAE refers to educational programs for adults that intentionally incorporate technology as a fundamental part of the learning process, which includes online courses, digital resources, e-learning platforms, and other technological tools to make education more accessible and effective for adult learners.
Photogrammetry
Authors: Tychola Kyriaki A. , Tsimperidis Ioannis , Papakostas George A.
Published: July 2024

The use of new technologies in combination with automated systems is leveraged in various ways; increasingly, in education offering innovative learning techniques. Especially using drones' technology for instructional purposes, the knowledge and metacognitive process take on other dimensions. Drone-based photogrammetry is a powerful and effective tool for 3D reconstruction of realistic, accurate, and high-resolution models through various methods and techniques. In this light, some issues about the exploitation of Photogrammetry in the class from a learning aspect and pedagogy value, have emerged. Drone technology can be applied to various educational subjects, such as computer science, geography, history, and language. It is found in a wide range of educational levels, from early childhood development to academic research. This chapter investigates the photogrammetry contribution to all learning aspects, indicates a case study of a 3D reconstruction model through photogrammetric software, and highlights the impact of the learning results on the students' psychology and emotions.
Pedagogical Optimization of FSP for Trainees in Business Management (Commerce and Marketing) in Morocco
Authors: Sahraoui Mariam
Published: July 2024

This chapter explores the use of pedagogical engineering in teaching French for specific purposes (FSP) to commerce-focused trainees at OFPPT in Morocco under the context of Education 5.0. It emphasizes the need to adapt teaching and evaluation methods to address linguistic requirements. The chapter proposes interactive teaching modules incorporating educational technologies to enhance engagement and contextualize FSP learning in commerce, emphasizing effective use of digital platforms. It discusses evaluation methods in Education 5.0, advocating for innovative approaches aligned with linguistic objectives and personalized learning. The chapter also examines teacher training requirements for successful implementation, contributing to an enriched educational experience for biology students in Morocco. This exploration is a valuable contribution at the intersection of pedagogical engineering, Education 5.0, and the specific needs of life sciences students.
Artificial Intelligence in Costumer Acquisition
Authors: Elhissoufi Mustapha , Alla Lhoussaine
Published: July 2024

The objective of this chapter is to explore publications that have addressed the applicability of AI to boost customer acquisition, via bibliometric analysis via VOSViewer. These results reveal an acceleration of research since 2018, a predominance of American institutions, a concentration of publications in marketing and computer science journals, a trend towards the decentralization of research on the uses of AI in customer acquisition and an absence of the emergence of predominant author groups.
Artificial Intelligence Applications in Marketing
Authors: Zejjari Ibtissam , Benhayoun Issam
Published: July 2024

This study aims to provide a review of current research on artificial intelligence use in marketing by examining 661 papers related to AI and marketing from the Web of Science database published in the last twenty years. Using bibliometric analysis, the study sheds light on the present research status, identifies trends, and explores future directions in AI and marketing research. Keyword co-occurrence analysis is utilized to uncover patterns and themes within the literature, offering insights into the field's evolution and emerging research areas. The analysis reveals several significant findings. Notably, it emphasizes the growing importance of AI in marketing, with China and the USA emerging as key contributors. Additionally, a considerable number of papers are funded by agencies and universities, underlining the topic's significance. Based on keyword co-occurrence analysis, four primary research themes are identified: Application of AI in marketing, AI in Marketing Analysis and Forecasting, AI in decision making and optimization, and AI and data analysis.
Factors Affecting Citizen Intention to Use Smart City Services in Morocco
Authors: Rhardas Tarik , Rochdane Hanane
Published: July 2024

In many developing countries, smart city initiatives are in their infancy. Like many other developing countries, smart projects in Morocco have been facing several challenges since their launch in 2016. The adoption of smart services requires the commitment and involvement of Moroccan citizens. This chapter focuses on a systematic literature review of the main studies dealing with factors that appear to improve end-user acceptance of services provided by Moroccan smart cities. A specific method known as PRISMA is being adopted to select and synthesize relevant studies in this field. The results obtained from the systematic review indicate that the unified theory of acceptance and use of technology (UTAUT) is the most utilized theory in the literature. Additionally, the examination of existing studies has revealed that successful implementation of smart projects requires decision-makers to consider the following factors: performance expectancy, ease of use, social influence, perceived cost, awareness, trust in technology, and trust in the government.
Categorising Students' Academic Performance and Sentiments Using Voting Machine Learning Techniques
Authors: Singh Neha , Jaiswal Umesh Chandra , Singh Ritu
Published: July 2024

The growth of numerous statistical approaches used to evaluate data in educational settings has caused machine learning to recently become a novel subject of research. In this chapter, authors present a novel voting model for performance prediction that incorporates machine learning techniques and additional variables known as “student sentiment attributes.” The proposed voting system was also employed to boost student test scores and improve the effectiveness of the strategies. In terms of the parameters of correlation coefficient, mean absolute error, root mean square error, time taken to build the model, relative absolute error, and root relative squared error, the supplied test set with voting method outperforms the four model evaluation methods of cross validation, use training set, supplied test set, and percentage split models. Given this, the result shows the applicability of the proposed model and computes the cost analysis of the proposed voting procedure.
Intelligent Automation in Marketing
Authors: Dhawas Pranali , Bondade Aparna , Patil Sandhya , Khandare Kiran Shyam , Salunkhe Ramadevi V.
Published: July 2024

This chapter explores the pivotal role of cutting-edge technologies in reshaping the landscape of contemporary marketing practices. This chapter delves into how artificial intelligence, machine learning, and data analytics are revolutionizing traditional marketing strategies, enabling unprecedented levels of personalization, efficiency, and effectiveness. Through real-world case studies and theoretical frameworks, the chapter elucidates the transformative impact of intelligent automation on various facets of marketing, including customer segmentation, targeting, content creation, and campaign optimization. Moreover, it examines the ethical considerations and challenges inherent in deploying intelligent automation solutions in marketing contexts, such as privacy concerns and algorithmic biases. This chapter equips marketers, business leaders, and scholars with the knowledge and tools needed to navigate the evolving landscape of intelligent automation in marketing and drive sustainable business growth in the digital age.
Innovation Journey
Authors: Francis Shimmy , Rangasamy Sangeetha
Published: July 2024

This chapter gives a thorough framework for understanding the dynamics and applications of innovation in the business environment. In today's fast-paced and competitive world, innovation is essential for organizational growth, adaptation, and sustainability. This study takes a descriptive approach, addressing the complexities of creativity across multiple dimensions. This chapter offers a conceptual overview before examining the various aspects of innovation and its function as a driving force behind strategic initiatives and a means of fostering competitive advantage. It provides a thorough study that clarifies the various stages of the innovation process, from ideation to optimization, emphasizing key challenges and opportunities at each level. It provides a road map for businesses looking to foster an innovative culture and use it as an outlet for value creation and competitive advantage by adopting a comprehensive viewpoint.
Revocation of Article 370 Changing Global Media Landscapes in India
Authors: Thankachan Keerthana , Eapen Thomas Peedikayil , Menon Vishnu Achutha
Published: July 2024

In this study, the authors investigate how the revocation of Article 370 is framed in the media and how the newspapers frame the types of conflicts by examining the coverage in three prominent newspapers: The Hindu, Dawn, and The New York Times. Employing a non-experimental ex-post facto research design, we utilize a qualitative content analysis to categorize and analyze the various frames used in media coverage. The analysis encompasses a total of 1,117 stories published over the course of one month, from August 5, 2019, to September 5, 2019, spanning different formats such as news reports, articles, feature stories, editorials, opinions, and cartoons.
Engaging With the News
Authors: Ahmed Sameera Tahira
Published: July 2024

News literacy (NL) is an increasingly important aspect of media literacy as it emphasises the role that news plays in our daily lives and asks questions about production, consumption, understanding and impact of information garnered from news in contemporary digital media environments. The news consumption of young people is of great interest for both academic and industry sectors as it is often misunderstood or stereotyped yet is key in helping understand future trends. This chapter seeks to apply the 5Cs model of NL to examine the news consumption of university students in a Gulf state. Using data obtained from an online survey (n = 435), it examines context, creation, content, circulation and consumption. In doing so it demonstrates that young people are aware of and practice news literacy behaviours (NLB) which are critical for operating in today's global digital news media environments.
Can Pruning Make Large Language Models More Efficient?
Authors: Gholami Sia
Published: July 2024

Transformer models have revolutionized natural language processing with their unparalleled ability to grasp complex contextual relationships. However, the vast number of parameters in these models has raised concerns regarding computational efficiency, environmental impact, and deployability on resource-limited platforms. To address these challenges, this chapter investigates the application of weight pruning—a strategic reduction of model parameters based on their significance—as an optimization strategy for transformer architectures. Through extensive experimentation, the authors explore various pruning methodologies, highlighting their impact on model performance, size, and computational demands.
Do Generative Large Language Models Need Billions of Parameters?
Authors: Gholami Sia
Published: July 2024

This chapter presents novel systems and methodologies for the development of efficient large language models (LLMs). It explores the trade-offs between model size, performance, and computational resources, with the aim of maximizing the efficiency of these AI systems. The research explores novel methods that allow different parts of the model to share parameters, reducing the total number of unique parameters required. This approach ensures that the model remains compact without sacrificing its ability to learn and represent complex language structures. This study provides valuable insights and tools for creating more efficient and effective LLMs, contributing to a more sustainable and accessible future for AI language modeling.
Enhancing IoT Security
Authors: Jones Rebet Keith
Published: July 2024

This chapter explores the application of advanced deep learning architectures, namely convolutional neural networks (CNNs) and recurrent neural networks (RNNs), for the detection of botnet activities in internet of things (IoT) networks. Addressing the growing concern of IoT security, the study develops and evaluates deep learning models to identify complex patterns of botnet behavior. The models demonstrate high accuracy and precision, outperforming traditional machine learning methods in botnet detection. However, challenges related to the computational demands of these models and the evolving nature of cyber threats are also acknowledged. Future research directions include optimizing these models for diverse IoT environments and enhancing their adaptability to new cyber threats. This research provides valuable insights into the application of neural networks in cybersecurity, offering a promising approach to enhancing IoT security.
Investigating the Limitations of Adversarial Training for Language Models in Realistic Spam Filter Deployment Scenarios
Authors: Albtosh Luay
Published: July 2024

Adversarial training has emerged as the prevailing approach for fortifying natural language processing (NLP) models against adversarial attacks, bolstering their accuracy and overall performance. However, little research has investigated the long-term viability of adversarial training. Upon deployment, models are often updated with fresh, non-adversarial data samples. This research seeks to systematically assess the longitudinal effects of adversarial training on language models, particularly as they undergo organic evolution over periods of time, emphasizing the task of spam detection. Extensive experiments are conducted using multiple spam classification models on various benchmark dataset. The findings reveal that the effectiveness of adversarial training is contingent upon the task and dataset. When trained on a consistent dataset, models often exhibit commendable predictive accuracy. However, their efficacy tends to wane when subjected to novel datasets, a trend observed.
From Interaction to Immersion
Authors: Jayawardena Nirma Sadamali , Bandyopadhyay Chinmoy , Bibi Gulshan
Published: July 2024

In recent times, marketers have started using augmented and virtual reality (AR-VR) to offer unique customer experiences and enhance engagement. While the use of AR-VR in marketing has become the ‘new normal', businesses are still struggling to use these tools to effectively attract and retain customers. Building on the existing literature, this chapter argues that overcoming these challenges requires understanding how to seamlessly integrate these tools throughout the customer journey. This will help businesses in curating AR-VR-enabled spaces that are aligned with customers' experiential preferences at different stages. In this chapter, the authors first summarize the impact of AR-VR technologies on customer engagement. Secondly, the challenges related to integrating these immersive technologies are highlighted. The authors then integrate the literature on AR-VR technologies and the customer journey and propose a framework and encourage academicians and practitioners to focus more on the different stages of the customer journey while designing AR-VR enabled marketing strategies.
Business Models Updated for a Digitalized and Sustainable World
Authors: Chilba Simona
Published: July 2024

The mission of this chapter is to reinforce the need to adapt current business models to the new type of economy, which is influenced by the new digitalized world and constant sustainable requirements from external stakeholders. The final outcome of the chapter will be reframing the current business models to fit this current eco-system. The chapter also clarifies the factors that drove this change, the transformations, automation of processes, streamlining of structures, and demanded corporate transparency. The competition is not at a certain level of similar-sized businesses anymore but at an unequal clash of business power intelligence. Being able to understand it and adapt the business models to the newly created reality involves trends understanding and supremacy perfection. This chapter will dive into the business frameworks used nowadays, compare them, and highlight the necessity of adaptation of such to the new type of economic markets. Suggestions for reframing are given, supporting the lean transition to stability in a volatile and continuously progressive economy.
Enhancing Academic Credential Verification Through Blockchain Technology Adoption in University Academic Management Systems
Authors: A. N. Raghavendra , G. Vijayakumar , Subramanian Shanmugam
Published: July 2024

Blockchain technology has emerged as promising solution in various sectors, including higher education. This research investigates the impact of usage of blockchain technology in student credential verification within university academic management system. This study employs a descriptive research through quantitative analysis of data collected from universities that have integrated or planning to integrate blockchain technology into their academic management systems. Key parameters examined include awareness and familiarity with blockchain, extent of blockchain usage, user experience and satisfaction, the perceived impact and benefits. The findings suggest that blockchain technology positively influences academic credential verification process, streamlining data sharing and reducing administrative burdens. As blockchain continues to transform the academic management landscape, this study offers timely guidance for stakeholders navigating the intersection of technology and education.