bluuebunny/crossref_metadata_2025 huggingface dataset:
'Teachers as historical agents' : An interview with Maria Nikolakaki
Authors: Kazamias David
Published: March 2024

In this interview with Maria Nikolakaki, Professor of Pedagogy and Education at the University of Peloponnese, we explore her career influences, the evolution of critical pedagogy, and global trends in teaching and schools. A prominent figure in critical pedagogy, Nikolakaki combines
elements from the writings of Paulo Freire and from Greek philosophy in her work. Her recent publication, The Anatomy of Neoliberalism and Education: imperialism, class struggle and pedagogy (2022), examines the impact of neoliberal policies on education, ranging from standardised tests
to the erosion of holistic education. Her sober analysis finds room both for the bleak and the hopeful.
A socialist manifesto for education and beyond
Authors: Whiting James , Duckett Ian
Published: March 2024

This article outlines the damage done by more than a decade of Conservative education policy and offers a set of arguments by which Labour could win support for a radical reconfiguration of formal education in England. It sets out elements from the Socialist Educational Association's
Manifesto for Education in an attempt to inspire a bolder and more thoroughgoing approach than the Labour Party currently offers. Finally, it argues a fully comprehensive education system should be Labour's goal.
Ordonner le clergé sur le terrain. La réorganisation de la vie religieuse à Sithiu après les conciles de 816-817
Authors: Meijns Brigitte
Published: March 2024

Durant son abbatiat, l'anglo-saxon Fridogise (r. 820-d. 833), chancelier de Louis le Pieux et également abbé de Saint-Martin de Tours, réorganisa radicalement la vie institutionnelle de l'abbaye de Sithiu, qui se composait de deux noyaux religieux. Désormais, l'église Notre-Dame, située dans la ville naissante de Saint-Omer, serait desservie par trente chanoines, tandis que le monastère de Saint-Bertin, situé dans les marais tous proches de l'Aa, accueillerait soixante moines. La seule source historique décrivant les actions de Fridogise sont les Gesta abbatum Sithiensium , écrites plus d'un siècle plus tard par Folcuin, et ce moine de Saint-Bertin a dépeint Fridogise dans les tons les plus sombres. L'objectif de cette contribution est d'analyser de manière critique la description proposée par Folcuin de ce moment charnière de l'histoire de son abbaye, et d'interpréter les efforts de réforme de Fridogise dans leur contexte historique particulier, à savoir la mise en œuvre sur le terrain des règlements des conciles d'Aix-la-Chapelle de 816-817.
Appliquer la « réforme » carolingienne ? Retour sur quelques établissements communautaires de Bourgogne ( viii e - x e siècle)
Authors: Deflou-Leca Noëlle
Published: March 2024

Cet article se propose de mettre en évidence la difficulté à mesurer les mutations induites par la correction carolingienne dans quelques grands monastères bourguignons. Ténus, les indices de la réception de la « réforme » sont aussi contrastés laissant entrevoir un positionnement hétérogène des frères qui ne sont pas tous réceptifs aux consignes de correction. Après avoir mis en évidence que l’abbaye de Bèze fut la seule dont les évolutions peuvent être mises en relation chronologique directe avec le capitulaire d’Aix, nous envisageons les formes et les évolutions de la vie cléricale puis monastique des communautés de Saint-Bénigne de Dijon et de Saint-Marcel de Chalon. À Auxerre, Flavigny ou Réôme, l’analyse d’indices dispersés sur l’application de la règle et ses conséquences sur la charge abbatiale ou la propriété conventuelle permet d’approcher une mise en œuvre relative des prescriptions de 817. In fine , avant le xi e  siècle pour l’espace concerné, il convient de souligner que la catégorisation séculier/régulier ne rend pas pleinement compte de la pluralité des « réalités » médiévales et de la porosité que les sources laissent entrevoir entre monde des clercs et monde des moines.
De l’imitation à la vénération : le culte de saint Wandrille et la réforme monastique au ix e siècle à Fontenelle
Authors: Mattingly Todd Matthew
Published: March 2024

L'abbaye de Fontenelle (Saint-Wandrille) était l'un des monastères les plus grands et les plus prospères du royaume franc dans les premières décennies du ix e  siècle. Cette étude examine de près deux versions de la Vie du fondateur et saint patron du monastère, Wandrille de Verdun, l'une composée vers la fin du vii e  siècle, l'autre dans les années 830. Cette comparaison met en évidence la transformation du monastère d'une enclave isolée destinée à une élite spirituelle et axée sur la vie ascétique, en un grand complexe liturgique au centre d'une communauté chrétienne plus large, et axé sur le culte des reliques de saint Wandrille. Il est en outre montré que la réforme de l'abbaye qui introduisit la Règle de saint Benoît au ix e  siècle, ne peut être pleinement comprise en dehors du contexte du développement du culte de saint Wandrille.
De l’analyse de la pratique professionnelle au praticien réflexif
Authors: Ghilas Karim
Published: March 2024

Analyse des pratiques professionnelles dans un établissement qui accueille des adolescents en souffrance. Quels sont les enjeux et les difficultés liées à cette pratique ? Qu’est-ce que les praticiens qui les animent peuvent apporter à une équipe éducative ? De quelle manière les pistes de travail engagées par le praticien permettent-elles de prendre de la hauteur, de s’extirper du quotidien et des « réflexes professionnels » ? Coopération, intelligence collective, praticien réflexif, autant de termes qui s’invitent en filigrane dans le texte.
Un éducateur spécialisé dans un service hospitalier de cancérologie pour adolescents et jeunes adultes ? Mais encore ?
Authors: Poidatz-Morin Fanny
Published: March 2024

Quelle place atypique pour une éducatrice spécialisée de travailler dans un service d’oncopédiatrie ! Auprès des adolescents et jeunes adultes atteints de cancer de l’hôpital Gustave Roussy, faut-il un accompagnement éducatif au sens strict du terme ? Quelle participation au soin ? Et quid des interstices du quotidien ou des moments informels qui sont les outils privilégiés des éducateurs dans la construction du lien avec les jeunes ? Mise en perspective de ces questions fondamentales dans une expérience de terrain auprès des jeunes patients. Ce témoignage rend hommage à tous les jeunes que accompagnés à l’hôpital et qui se battent jour après jour contre le cancer.
La « démocratisation » de l’analyse de la pratique professionnelle comme symptôme de l’hypermodernité
Authors: André Damien
Published: March 2024

Le marché de l’analyse de la pratique s’étend. Nous adopterons une posture critique pour analyser la manière dont la commande de ces dispositifs d’étayage de la subjectivité croit en parallèle de la montée en puissance des dispositifs de contrôle, de surveillance et d’individualisation de la vie professionnelle.
« Une espérance nouvelle pour le Liban ». 25 ans après
Authors: Sicking Thom
Published: March 2024

L’Exhortation apostolique « Nouvelle Espérance pour le Liban » (1997), issue du Synode des évêques convoqué par le pape Jean-Paul II en 1995 après la guerre civile libanaise, continue de refléter la réalité des Églises et de la situation politique du pays. Malgré les recommandations pour affronter les défis, les problèmes persistent, aggravés par des changements politiques et sociaux. Ce texte expose les difficultés des Églises libanaises et leur lien étroit avec le contexte politique du pays, insistant sur une transformation profonde urgente. La collaboration entre diverses communautés chrétiennes et avec les musulmans est soulignée. Il met l’accent sur la participation active de tous les fidèles, remettant en question la hiérarchie traditionnelle de l’Église pour encourager une Église synodale. Cependant, la mise en œuvre de ces recommandations exige un changement profond de mentalité, un processus long et difficile. Néanmoins, des signes de renouveau se manifestent, comme des initiatives œcuméniques informelles, une théologie contextuelle répondant aux défis actuels, des actions humanitaires collaboratives, et une reconnaissance croissante du rôle des femmes dans l’Église.
The relationship between students’ perception to the learning media, digital literacy skills, and self-regulated learning with students’ learning outcomes in the rural area
Authors: Bahri Arsad , M Wahyu Hidayat , Putra Kurnia Prima , Ainun Nur Aisyah , Arifin Nurheni
Published: March 2024

This study aims to determine the relationship between students’ perception to the learning media, digital literacy skills, and self-regulated learning with students’ cognitive learning outcomes in the rural area. This study was the ex post facto with quantitative data. The method used was differential causal comparative with multiple linear regression analysis. The three variables were measured using a questionnaire, cognitive learning outcomes was measured by test. The results showed that students’ perception to the learning media, digital literacy skills, and self-regulated learning on students' cognitive learning outcomes had a moderate simultaneous relationship. The findings also showed that the contribution of self-regulated leraning to the cognitive learning outcomes was the higher (71.42%). The contribution of the three variables to cognitive learning outcomes was 86.41%. Based on related facts, research recommendations can be expanded by measuring from several other rural areas and examining several other variables, especially those that support the learning process oriented towards empowering 21st century competencies by utilizing the latest technological developments and that can reach all regions of Indonesia, especially in rural areas so as to minimize the gap in the quality of education in Indonesia.
JOTSE's editorial: Reflection on how artificial intelligence can affect journal
Authors: Amante García Beatriz , Martínez Martínez María
Published: March 2024

As is customary in JOTSE, the first editorial of the year encapsulates our examination of the progression of JOTSE. In this edition, moreover, we offer a brief reflection on the potential impact of Artificial Intelligence (AI) on various journals, recognizing its utility as an invaluable and inexorable tool.
Dispersive optical soliton solutions with the concatenation model incorporating quintic order dispersion using three distinct schemes
Authors: Zayed Elsayed M. E. , El-Shater Mona , Alurrfi Khaled A. E. , Arnous Ahmed H. , Shah Nehad Ali , Chung Jae Dong
Published: March 2024

This paper addresses the new concatenation model incorporating quintic-order dispersion, incorporating four well-known nonlinear models. The concatenated models are the nonlinear Schrödinger equation, the Hirota equation, the Lakshmanan-Porsezian-Daniel equation, and the nonlinear Schrödinger equation with quintic-order dispersion. The model itself is innovative and serves as an encouragement for investigating and analyzing the extracted optical solitons. These models play a crucial role in nonlinear optics, especially in studying optical fibers. Three integration algorithms are implemented to investigate the optical solitons with the governing model. These techniques are the Weierstrass-type projective Riccati equation expansion method, the addendum to Kudryashov's method, and the new mapping method. The solutions obtained include various solitons, such as bright, dark, and straddled solitons. Additionally, the paper reports hyperbolic solutions and Weierstrass-type doubly periodic solutions. These solutions are novel and have never been reported before. Visual depictions of some selected solitons illustrate these solutions' dynamic behavior and wave structure.
A dual-brain therapeutic approach using noninvasive brain stimulation based on two-person neuroscience: A perspective review
Authors: Takeuchi Naoyuki
Published: March 2024

Our actions and decisions in everyday life are heavily influenced by social interactions, which are dynamic feedback loops involving actions, reactions, and internal cognitive processes between individual agents. Social interactions induce interpersonal synchrony, which occurs at different biobehavioral levels and comprises behavioral, physiological, and neurological activities. Hyperscanning—a neuroimaging technique that simultaneously measures the activity of multiple brain regions—has provided a powerful second-person neuroscience tool for investigating the phase alignment of neural processes during interactive social behavior. Neural synchronization, revealed by hyperscanning, is a phenomenon called inter-brain synchrony- a process that purportedly facilitates social interactions by prompting appropriate anticipation of and responses to each other's social behaviors during ongoing shared interactions. In this review, I explored the therapeutic dual-brain approach using noninvasive brain stimulation to target inter-brain synchrony based on second-person neuroscience to modulate social interaction. Artificially inducing synchrony between the brains is a potential adjunct technique to physiotherapy, psychotherapy, and pain treatment- which are strongly influenced by the social interaction between the therapist and patient. Dual-brain approaches to personalize stimulation parameters must consider temporal, spatial, and oscillatory factors. Multiple data fusion analysis, the assessment of inter-brain plasticity, a closed-loop system, and a brain-to-brain interface can support personalized stimulation.
AT: Asynchronous Teleconsultation for Health Centers in Rural Areas of Peru
Authors: Mauricio David , Bendita Walter , Flores Ronaldo , Castañeda Vargas Pedro Segundo , Chuquimbalqui-Maslucán Robert , Rojas-Mezarina Leonardo , Maculan Nelson
Published: March 2024

Currently, telehealth services in rural regions of Peru primarily rely on telephone and text message communication between rural physicians and specialists based in cities, leading to delays in accessing specialized healthcare services. To overcome this limitation, we propose an information and communication technology (ICT) model for asynchronous teleconsultation in rural areas of Peru. This model, implemented through a system called SITEA, coordinates city-based specialists with treating physicians in rural areas and integrates care phases along with electronic clinical records. A case study conducted in a rural Peruvian healthcare facility, which had limited Internet connectivity and lacked teleconsultation services, revealed significant outcomes. Within 23 days of implementing SITEA, the facility began offering specialized care services, leading to a 60% reduction in patient transfers to specialized urban healthcare facilities. Furthermore, a satisfaction survey conducted with 50 patients resulted in overwhelmingly positive feedback regarding the quality of medical care and future expectations for healthcare services. These positive outcomes can be attributed to the implementation of specialized services, the shift from physical to electronic records, and improved diagnostic accuracy. Importantly, healthcare personnel found the system easy to navigate and highly beneficial, despite the area’s connectivity limitations.
The Role of Artificial Intelligence in the Diagnosis of Neoplastic Diseases: A Systematic and Bibliometric Review
Authors: Espinoza Villavicencio Hector , Gamboa-Cruzado Javier , López-Goycochea Jefferson , Soto Soto Luis
Published: March 2024

Artificial intelligence (AI) has significantly transformed the medical field, especially in the diagnosis, treatment, and management of oncological diseases. It has had a profound impact on clinical decision-making and has enhanced the quality of life for various populations. This study aims to comprehensively assess the inherent relationship between AI and medicine and to uncover both its positive and negative implications. To achieve a comprehensive understanding, a thorough systematic review of articles was conducted, examining a total of 80 papers published between 2017 and 2023. These articles were carefully selected from well-known open-access databases, such as Scopus, IOPscience, IEEE Xplore, Google Scholar, ResearchGate, and ProQuest. A key finding from this review is that the majority of research on this topic has been published in scientific journals ranked in the first-quartile (Q1), underscoring the importance and high quality of research in this field. The United States, China, India, the United Kingdom, and Canada are the foremost countries in publishing on this topic. Most of the research is published in first-quartile (Q1) journals, representing 51% of the studies. Only 1% of articles appear in third-quartile (Q3) journals. IEEE Xplore is renowned as the primary database for accessing high-impact studies in this field. Future research should prioritize investigating the long-term impact of AI on patient clinical outcomes. International collaborative research could promote innovation and fairness in the implementation of artificial intelligence (AI) in oncology.
CNN-Based Approach for Non-Invasive Estimation of Breast Tumor Size and Location Using Thermographic Images
Authors: Khomsi Zakaryae , El Fezazi Mohamed , Bellarbi Larbi
Published: March 2024

The characterization of tumors is crucial for guiding appropriate treatment strategies and enhancing patient survival rates. Surface thermography shows promise in the non-invasive detection of thermal patterns associated with the existence of breast tumors. Nevertheless, the precise prediction of both tumor size and location using temperature characteristics presents a critical challenge. This is due to the limited availability of thermal images labeled with the corresponding tumor size and location. This work proposes a deep learning approach based on convolutional neural networks (CNN) in combination with thermographic images for estimating breast tumor size and location. Successive COMSOL-based simulations are conducted, including a 3D breast model with various tumor scenarios. Thus, different noise levels were included in the development of the thermographic image dataset. Every image was accordingly labeled with the corresponding tumor location and size to train the CNN model. Mean absolute error (MAE) and the coefficient of determination (R²) were considered as evaluation metrics. The results show that the proposed CNN model achieved a reasonable prediction performance with MAE–R² values of 0.872–98.6% for tumor size, 1.161–96.8% for x location, 1.086–97.1% for y location, and 0.954–96.7% for z location. This study indicates that the combination of surface thermography and deep learning is a convenient tool for predicting breast tumor parameters.
Une nouvelle étude architecturale du temple romain de Harf Chlifa, Btedai (Liban)
Authors: Kahwagi-Janho Hany
Published: March 2024

Résumé – Le sanctuaire de Harf Chlifa, connu localement sous le nom de Qasr el-Banat, occupe la pointe d’une formation rocheuse qui se détache des flancs orientaux du Mont-Liban et s’avance dans la plaine de la Békaa. Le site associe un temple distyle in antis d’époque romaine et quelques vestiges tardifs, parmi lesquels un bâtiment absidial d’époque byzantine, installés au sein d’un téménos antique. Le site a été documenté par D. Krencker et W. Zschietzschmann en 1903 et en 1933. Endommagé pendant la guerre du Liban (1975-1990), il a fait l’objet d’une nouvelle étude réalisée dans le cadre d’un atelier académique de l’université Saint-Esprit de Kaslik (USEK), qui a permis de mieux documenter et de comprendre le site et ses transformations. Cette nouvelle étude architecturale a mené à l’identification de l’ordre ionique du temple et à une nouvelle restitution de son élévation, ainsi qu’à la confirmation de sa datation haute, par comparaison avec d’autres édifices de la région.
La guerre en Arabie au iiie siècle de l’ère chrétienne, d’après les faits d’armes d’un prince ḥimyarite
Authors: Robin Christian Julien
Published: March 2024

Résumé – La ville de Waʿlān (aujourd’hui le site d’al-Miʿsāl), sur les Hautes-Terres du Yémen, était dans l’Antiquité la capitale de la commune de Radmān, l’un des principaux protagonistes dans les guerres entre Ḥimyar, Sabaʾ et le Ḥaḍramawt au iiie siècle de l’ère chrétienne. Les banū Maʿāhir, princes de Radmān, avaient choisi comme divinité protectrice de leur lignage la déesse Soleil Très-Haute à laquelle ils avaient consacré au iie siècle un piton granitique à la périphérie de la ville. Un premier prince commémore l’aménagement de ce sanctuaire rupestre dans une inscription gravée sur la paroi verticale du piton. Au iiie siècle, trois princes ajoutent cinq longues inscriptions pour célébrer la divinité et la remercier de ses bienfaits lors d’expéditions guerrières dont ils sont revenus sains et saufs et couverts de gloire. Le deuxième de ces princes, Laḥayʿathat Awkan, a commandité deux inscriptions. L’article publie la seconde (al-Miʿsāl 3), inédite. Ce prince, dans les années 250, commande une armée ḥimyarite qui fait un raid en territoire sabéen, puis des troupes communales engagées dans plusieurs opérations contre le Ḥaḍramawt.
Les pavements de la cathédrale de Hama : nouvelles découvertes et nouvelle approche
Authors: Saad Houmam , Abdallah Komait , Alpi Frédéric
Published: March 2024

Résumé – À l’automne 2020, l’église byzantine située dans le quartier d’al-Madinah, dans la vieille ville de Hama (Épiphanie d’Apamène), en partie connue depuis les années 1980-1990, a fait l’objet de travaux conduits par le service des fouilles de la Direction des antiquités (DGAMS). Les anciennes fouilles effectuées par A. Zaqzouq ont identifié deux édifices, dont une basilique à bas-côtés et narthex dotée de pièces annexes datées par les inscriptions entre 412 et 416. Le sol de ce complexe religieux est pavé de mosaïques à figures géométriques, sauf une qui comporte une scène figurée. Au niveau supérieur, le deuxième édifice présente un sol couvert par un dallage. Il remonte à l’époque médiévale ; peut-être s’agit-il d’une église, selon l’interprétation de M. Piccirillo. Les fouilles récentes de la DGAMS avaient pour objectif de dégager les remblais accumulés au cours des années et de déterminer les limites de l’édifice. Elles ont mis au jour plusieurs éléments architecturaux et de nouvelles mosaïques dans la nef centrale et les pièces annexes. Ces mosaïques présentent des motifs géométriques variés d’une grande finesse, dont certains sont uniques dans la région, et des citations bibliques inscrites en grec. Ces nouvelles découvertes confirment le statut particulier de ce complexe religieux, notamment à l’époque paléochrétienne, et apportent l’un des rares témoignages sur la ville d’Épiphanie d’Apamène, siège d’un évêché à l’époque byzantine.
Facial Emotion Recognition Using Osmotic Computing
Authors: Aurchana P. , Indhumathi R. , Revathy G. , Ramalingam A.
Published: March 2024

Emotion recognition refers to the process of identifying the emotions expressed by an individual, typically through their facial expressions, speech, body language, and sometimes physiological signals like heart rate or skin conductance. In this chapter, facial expression is used to recognise. Emotions like happiness, sadness, anger, fear, surprise, and disgust are typically recognized. This chapter aims at developing a real-time approach to classification of facial emotions such as happy, normal, yawn, and sleep in a real-time context. For this, images are captured using sensors and stored in a cloud storage bucket in which the processing is done. The facial emotions are identified through the use of Haar cascade classifiers. The histogram-oriented gradients features are extracted in the detected facial emotion images, and the extracted features are classified by using machine learning models support vector machine and k-nearest neighbour classifiers as happy, normal, yawn, and sleep. The suggested system outperforms other current systems when tested with real-time datasets.
Speech Emotion Recognition With Osmotic Computing
Authors: Manoj Praphakar T. , Dhenu D. S. , Gavash D. , Mega Shree M. , Divesh S.
Published: March 2024

Speech emotion recognition is a critical component of human-computer interaction and affective computing. This chapter presents a comprehensive study on the application of deep learning techniques for the task of speech emotion recognition. Emotions conveyed through speech play a crucial role in understanding human behavior and are essential in various domains, including human-robot interaction, customer service, and mental health assessment. This chapter also investigates the impact of different feature extraction methods and data pre-processing techniques on the recognition accuracy. Basically, RNN algorithm is used for speech emotion recognition to identify the emotion through audio, but this chapter will accomplish this with CNN algorithm because the time complexity of RNN algorithm is high and to analyze the audio takes more time where CNN will be converted into spectrograms from each dimension of emotions, which will be recognized by augmenting it. And finally, it is used in the medical field, security, and surveillance management.
Cloud Computing and Machine Learning in the Green Power Sector
Authors: Agrawal Anurag Vijay , Sujatha G. , Sasireka P. , Ranjith P. , Cloudin S. , Samp B.
Published: March 2024

The chapter explores the potential of cloud computing, machine learning, and the green power sector in promoting sustainable energy production and consumption. Cloud computing offers efficient data storage and processing, while machine learning algorithms optimize energy production, distribution, and consumption. It highlights how cloud-based infrastructure can enhance renewable energy forecasting, energy grid management, and demand response systems. Edge computing brings intelligence closer to renewable energy sources, reducing latency and energy consumption. The chapter also addresses challenges like data privacy, security, and regulatory compliance in the green power sector. It reviews case studies and emerging trends to demonstrate how these technologies can optimize renewable energy production and contribute to a more sustainable power sector.
An Enhanced Real-Time Automatic Speech Recognition System for Tamil Language Using Wav2Vec2 Model
Authors: Sangeetha J. , Rekha D. , Priyanka M. , Dhivya M.
Published: March 2024

Automatic speech recognition (ASR) is a vital technology that transforms spoken language into written text, facilitating effective accessibility and communication. Despite the ongoing development of deep learning approaches, speech recognition remains a formidable task, especially for languages with limited data resources, such as Tamil. This work presents the development of an ASR system by utilizing the real-time spontaneous Tamil speech data collected from various types of people's communications in public places. The corpus is trained by fine-tuning the pre-trained wav2vec2 XLSR model. This model captures the diverse acoustic features and patterns and even applied to multiple dialects, making it adaptable to real-world speech. The implemented model is evaluated on various noisy environments like markets, hospitals, shops, etc. In terms of various evaluation metrics such as word error rate (WER) and character error rate (CER), the designed model exhibits an optimal performance by achieving a lower error rate when compared to the baseline ASR models.
Explainable Artificial Intelligence in Consumer-Centric Business Practices and Approaches
Authors: Trivedi Sonal
Published: March 2024

The review begins by discussing the fundamental concepts of XAI, highlighting its significance in enhancing consumer trust and engagement in AI-driven services and products. The authors explore various dimensions of XAI, such as interpretability, transparency, and accountability, and their implications in consumer-centric contexts. This study identifies a range of methods and techniques adopted by businesses to implement XAI, including rule-based systems, model-agnostic approaches, and interpretable machine learning models. Content analysis is employed as the primary research method in this review. The findings of this SLR provide a holistic overview of the current state of XAI in consumer-centric business practices and approaches, helping businesses and researchers gain a better understanding of the field's evolution and the challenges that lie ahead. It also underscores the importance of ethical considerations and regulatory frameworks in fostering responsible AI adoption within consumer-focused domains.
AI-Personalization Paradox
Authors: Jindal Priyanshi , Gouri Harshit
Published: March 2024

The integration of AI into various aspects of our lives has significantly reshaped how we access information, products, and services. AI-driven personalization, a key feature of many platforms, aims to enhance user experiences by tailoring content to individual preferences. Advancement of AI personalization has given rise to the filter bubble and echo-chamber phenomena. Filter bubbles expose consumers to content that reinforces their existing beliefs and preferences, creating a paradox. This chapter explores the multifaceted implications of AI-personalization paradox on digital consumer behavior in the context of the filter bubble era investigating how AI algorithms shape the content users encounter, impact of algorithms on information diversity, and consequences for consumer decision-making. The chapter concludes speculating on future of personalization, emphasizing the need to balance customization with information diversity, encouraging critical thinking about AI ethics among consumers.
Small Steps, Big Impact
Authors: Islam Md. Tariqul , Kumar Jeetesh , Konar Rupam
Published: March 2024

Small and medium-sized enterprises (SMEs) are businesses that fall within a specific range of criteria related to their size, which may include factors such as revenue, assets, or number of employees. Bangladesh has experienced a tremendous increase in SMEs in the past two decades. SMEs are the backbone of the Bangladeshi economy, and they play a significant role in the country's economic growth. Social media plays a significant and multifaceted role in the operations and growth of SMEs. This conceptual study delves into the transformative role of social media marketing adoption by SMEs in Bangladesh. Additionally, the study explores the increasing significance of artificial intelligence (AI) in social media marketing within the SME context. As technology, particularly AI, continues to reshape the business landscape, this chapter offers valuable insights for academia and stakeholders invested in the dynamic and burgeoning SME industry in Bangladesh.
Transforming Pharma Supply Chains Using Data Analytics Unleashed for Enhanced Visibility and Competitiveness
Authors: Rajesh Kumar K. V. , Bodhimisetty Tezovalli
Published: March 2024

Supply chain visibility brings transparency and real-time information to the various stages of the supply chain. It gives a strategic advantage that empowers businesses to operate more efficiently, respond to changes quickly, and build more resilient and customer-focused supply chains. It contributes to overall supply chain excellence and competitiveness in the marketplace. This chapter explores different types of data analytical methods to enhance supply chain visibility in pharmaceutical industries. Methodology involves qualitative research study, where the data is derived from existing research papers, articles, and other web-based sources. The verified data is filtered and included in the chapter. A few potential analytical methods and their applications were described which were proven to enhance supply chain visibility. The methods focused are IoT, RPA, ANFIS, RFID, and blockchain along with their practical applications.
Artificial Intelligence and Machine Learning in Healthcare
Authors: Sarkar Nilanjana , Goel Sumit
Published: March 2024

Artificial intelligence (AI) systems are systems designed by humans that, given a complex goal, act in the physical or digital dimension by perceiving their environment through data acquisition, interpreting the collected structured or unstructured data, reasoning on the knowledge, or processing the information, derived from this data and deciding the best action(s) to take to achieve the given goal. It is precisely AI's ability to carry out speedy processing and analysis of datasets that is one of its key strengths. The recent renaissance in AI largely has been driven by the successful application of deep learning — which involves training an artificial neural network with many layers (that is, a ‘deep' neural network) on huge datasets. The rise and dissemination of AI in clinical medicine will refine our diagnostic accuracy and rule-out capabilities. In this Book Chapter, we focus on the AI applications that could augment or change clinical practice, identify the impact arising from the development of AI diagnostic systems and suggest future research directions.
Harnessing the Potential of Metabolomic Biomarkers for Metabolic Health
Authors: Gupta Shifali G. , Kaur Paranjeet , Kaur Rajwinder G. , Singh Thakur G.
Published: March 2024

Metabolomics is a fascinating area that specializes in analyzing the small molecules in our frame, like hormones and enzymes, that play an important role in our metabolism. With the aid of reading these molecules, scientists can gain insights into our metabolic fitness and the way our body processes nutrients. It entails different factors such as energy production, nutrient usage, and waste elimination. Through metabolomics, researchers can become aware of precise metabolic biomarkers that imply the state of our fitness. Through studying these markers, they are able to hit upon early symptoms of metabolic disorders like diabetes, obesity, and cardiovascular ailment. This knowledge can then be used to broaden customized interventions and treatments to improve metabolic health. It is able to assist in the development of centered treatment plans, personalized nutrition plans, and preventive strategies. In this chapter, we will attempt towards achieving and maintaining optimal health with the study of metabolomics biomarkers.
Transformative Insights
Authors: Komalasari Rita
Published: March 2024

This chapter explores the transformative role of artificial intelligence (AI) in ovarian cancer prediction and prognosis. It aims to analyze complex datasets, predict patient outcomes, and optimize treatment pathways. The study critically examines existing research on ovarian cancer, highlighting gaps and challenges in current prognostic methodologies. The findings demonstrate significant advancements in AI application in ovarian cancer prediction, highlighting its transformative potential in research and clinical practice. AI not only enhances understanding of ovarian cancer complexities, but also offers personalized and optimized treatment strategies, offering hope for improved patient outcomes and overall survival rates.
Optimization of Processing Sequence and Computation Mode in IoT for Mobile Edge Computing
Authors: Gupta Shashi Kant , Mehta Shilpa , Tripathi Rajendra Kumar , Siddiqui Shavej Ali
Published: March 2024

The advent of mobile computing offloading paradigms, such mobile-edge computing (MEC), has allowed several internet of things (IoT) applications to use end devices' processing capabilities to do local tasks independently of a centralized server. A practical method for extending the amount of duration needed to finish computing tasks is computation off-load. This in-depth study investigates the complicated world of IoT systems, MEC paradigms, and the supplementary advantages gained by properly coordinating processing phases and compute modes. End-device execution is better for some application tasks due to reduced processing and greater connection expenses. In contrast, the MEC topology extends cloud capabilities to the network edge to speed up data processing near mobile devices. Symmetric propagation is the strategy the authors use in the cloud computing layer to shorten the time it takes for data to go from edge devices to cloud servers. In conclusion, they address computation latency in the cloud computing layer by tailoring our approach to its unique properties.
Application of a TID Controller for Assessing Frequency Stability in a Thermal Power System With Renewable Energy Sources
Authors: Murugesan D. , Jagatheesan K. , Shah Pritesh , Sekhar Ravi
Published: March 2024

This chapter presents a supplementary controller, the tilt integral derivative (TID) controller, for load frequency control in a single-area thermal power system integrated with renewable energy sources. The tilt integral derivative controller's optimal parameter values are determined through state-of-the-art cohort intelligence optimization techniques, using performance indices such as ITAE as evaluation criteria. The suggested tilt integral derivative control method exhibits notable advantages, including ease of parameter adjustment and robust performance in the face of system parameter fluctuations. The effectiveness of the proposed method is showcased through a comparative analysis with recently published heuristic approaches, such as PID controllers optimized using differential evolution (DE), genetic algorithm (GA), and ant colony optimization (ACO). The simulations were conducted using MATLAB. A comparative examination with prior research reveals that the proposed tilt integral derivative controller outperforms the other methods.
The Transformation of Human Existence Through the Integration of Artificial Intelligence
Authors: Sidhu Navpreet , Gupta Swati , Sharma Renuka , Mehta Kiran , Taneja Sanjay
Published: March 2024

Technology is undoubtedly reshaping our global landscape. Existing are robots that possess human-like speech, appearance, and attire, readily serving us in restaurants. The prevalence of such instances provides ample proof. The field of digital art is witnessing a surge in creations by artists utilizing artificial intelligence (A.I). The inclination towards improving cognitive abilities is apparent in the ongoing development of smartphones and smartwatches. Artificial intelligence is causing a revolution in the way businesses operate. How enterprises engage with their customers, employees, and stakeholders is transforming due to A.I.'s ability to automate tasks, derive insights from data, and craft personalized interactions. A.I. enhances human intelligence, streamlines processes, and makes work more productive and efficient.
Robo-Finance Unveiled
Authors: Goswami Divya , Verma Balraj
Published: March 2024

The study aims to correlate financial investment advice with investors, using Scopus and VOS viewer to analyze prominent authors and journals. Gomber emerged as a leading writer, with journals like The Journal of Management Information Systems and Journal of Behavioral and Experimental Finance standing out. These journals have gained significant citations for research on financial advice. Future studies should focus on cognitive biases, financial technology, roboadvisors, financial behavior, and AI. Conducting longitudinal research on market efficiency, decision-making dynamics, information asymmetries, and investor intelligence can enhance financial advice quality. This research provides a foundation and suggestions for future studies in financial advising, especially for investors.
Innovative Technologies for Healthcare Service Productivity
Authors: Kaur Gaganjot , Sharma Shalini , Reepu
Published: March 2024

The world is changing rapidly, especially with a speedy increase in global population. More than ever, for all service-related functions, the organizations are looking for methods to enhance their service throughput. Technological innovations in every industry have been helpful in achieving this growth. In hospitals too, the power of technology has been harnessed for better patient outcomes which directly translates to patient satisfaction. New healthcare technologies have provenly increased the efficiency of care services and operational processes by removing repetitive tasks and providing personalized care to the patients. A successful digital healthcare ecosystem provides clinical decision support which enables both high degree of efficiency (bandwidth and throughput) and high degree of effectiveness (quality patient health outcomes).
Quantum-Based Robotics in the High-Tech Healthcare Industry
Authors: Khang Alex , Rath Kali Charan , Anh P. T. N. , Rath Sunil Kumar , Bhattacharya Srijan
Published: March 2024

This chapter explores the emerging field of quantum robotics and its innovative applications in the healthcare or medical ecosystem. Quantum robotics combines the principles of quantum mechanics and robotics to enable advanced medical technologies and improve patient care. The chapter provides an overview of the fundamental concepts of quantum robotics, including quantum computing, sensing, and communication and discusses their potential impact on healthcare. Various applications of quantum robotics in healthcare are presented, including medical imaging, drug discovery, surgical robotics, and personalized medicine. The chapter also addresses the challenges and future directions in the field, highlighting the need for interdisciplinary collaborations and advancements in quantum technologies. Overall, this chapter sheds light on the promising role of quantum robotics in revolutionizing healthcare and fostering advancements in medical science.
Multi-Modal MRI Images Analysis for Improved Herniated Disc Diagnosis Using Deep Learning
Authors: Saji Princy K. , Krishnachalitha K. C. , Kannan M.
Published: March 2024

Herniated discs are a common medical condition that can cause severe back pain and lead to serious complications if not diagnosed and treated correctly. MRI is the preferred imaging modality for diagnosing herniated discs, providing detailed images of the spine and surrounding structures. A herniated disc, also known as a slipped or ruptured disc, occurs when the soft inner portion of a spinal disc protrudes through a tear in the more rigid outer layer. This can cause pain, numbness, and weakness in the affected area, typically the lower back or neck. The most common cause of a herniated disc is age-related degeneration of the spine, which can weaken the disc's outer layer and cause it to bulge or rupture. However, other factors such as improper lifting, repetitive strain, or trauma can also contribute to developing a herniated disc. Early detection of a herniated disc is vital because it allows for prompt treatment, preventing the condition from worsening and potentially causing permanent nerve damage.
Brain Interaction Assessment Using EEG Source Localization
Authors: Narendra Kumar Rao B. , Sailaja G.
Published: March 2024

In standardized low-resolution brain electromagnetic tomography (SLORETA), the electrical activity recorded by the electroencephalogram (EEG) electrodes, is transformed into a three-dimensional source distribution within the brain. It helps us in understanding the internal details of human brain and its working. It helps us in visualizing and analyzing the activity of the brain electrically with exceptional precision. The EEG recordings along with mathematical algorithms (advanced) help in reconstruction of neural foundational blocks for the recorded brain signals. This transformation is achieved by solving an inverse problem using linear, weighted minimum norm estimation. By solving this inverse problem, SLORETA estimates the locations and strengths of neural sources underlying the measured EEG signals. The accuracy and reliability of sLORETA have been validated through comparisons with other neuroimaging techniques, such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET).
Challenges Exist in Translating Brain Signals Into Words Using Brain-Computer Interfaces (BCIs)
Authors: Janapati Ravichander , Reddy Sudula Sriram , Anitha Gajji , Shivani Rebelli , Sreya Vempati
Published: March 2024

The field of translating brain signals into words is rapidly developing and has great potential to improve the lives of those who have speech problems. Notwithstanding the encouraging developments, there are still many obstacles in this field to overcome, including the complexity and variety of brain signals, the requirement for big datasets, the intrusiveness of existing interfaces, and the desire to mimic the speed and fluidity of natural speech. This chapter explores these issues in general as well as current developments, such as the creation of a “speech neuroprosthesis.” These obstacles are gradually being removed by the ongoing study in this area, opening the door to a time when brain signals can be easily converted into language. Neuroscience and technology are at a fascinating and challenging stage in their quest to transform brain signals into speech. This procedure entails translating the intricate, multimodal cerebral signals produced by speech into understandable words by decoding them.
Precision Medicine
Authors: Swathi N. L. , Chakrabarti Madhurita , Muzzamil Muhammad , Hamdar Hiba , Jaber Ahmad , Chamoun Amarelle , Al Amin Fatima , Rathod Pooja
Published: March 2024

Precision medicine has emerged as a transformative approach to healthcare, leveraging advancements in genomics, data analytics, and personalized treatments. Case studies have played a pivotal role in unraveling the potential of precision medicine. Through the analysis of individual patient profiles, these studies have showcased how tailoring medical interventions to a person's unique genetic makeup, lifestyle, and environmental factors can yield superior clinical outcomes. The authors present a selection of compelling case studies that exemplify the successes and challenges encountered in the pursuit of precision medicine. Furthermore, the integration of cutting-edge technologies has significantly accelerated progress and also by drawing on real-world case studies and the latest technological innovations.
The Role of Predictive Analytics in Personalizing Education
Authors: Dwivedi Dwijendra Nath , Mahanty Ghanashyama , Dwivedi Varunendra nath
Published: March 2024

Predictive analytics is a crucial tool in changing teaching and learning practices in the ever-changing field of educational technology. This study examines the dynamic function of predictive analytics in customizing education, with a specific emphasis on its ability to adapt learning paths to improve individual student achievement. The study examines how predictive models might identify distinct learning patterns and demands by assessing many data sources, such as academic achievement, learning habits, and engagement indicators. It showcases the capabilities of these analytics in generating adaptive learning experiences, thereby providing a more focused approach to teaching. This article investigates how predictive analytics facilitates the early detection of educational hazards, allowing for timely interventions to support students who are at danger of academic underperformance or dropping out.
Enriching EFL Teaching Through Multimodal Integration of QR Codes
Authors: Zeybek Gülin
Published: March 2024

The purpose of this in-depth chapter is to present the multimodal integration of quick response (QR) codes in the field of foreign language education, with a particular emphasis on English language skills. This chapter presents practical applications and ideas for introducing QR codes into teaching practices in a seamless manner, which will improve the experiences of language learners. All aspects of language abilities, including listening, speaking, reading, and writing, are included in the scope of this analysis. The chapter also notes that there are challenges associated with the incorporation of QR codes. In conclusion, the chapter suggests that the use of QR codes into language instruction might be a paradigm change in terms of pedagogical approach. The presentation of QR code integration in this chapter is framed within a multimodal approach, which acknowledges the value of mixing many modes of communication, such as verbal, visual, auditory, gestural, and spatial modes, in order to produce an experience that is both comprehensive and immersive for language acquisition.