bluuebunny/crossref_metadata_2025 huggingface dataset:
Ni breaking bad ni prison break . À qui profite le trafic de stupéfiants en détention ?
Authors: Olivier Charline
Published: March 2024

N’importe quel intervenant professionnel ou associatif qui accède aux coursives d’un centre pénitentiaire en France est témoin de la circulation permanente de produits stupéfiants entre détenu.e.s. Des organisations criminelles complexes sont à l’œuvre : il s’agit d’introduire la matière, la stocker, la débiter, la vendre et la distribuer. Les lieux privatifs de liberté pourraient apparaitre particulièrement dédiés à combattre ce phénomène criminel, alors même que par leur organisation et leur fonctionnement, ils permettent le développement de ce type d’activités illicites. La responsabilité du trafic de stupéfiants en détention ne peut être attribuée aux seul.e.s détenu.e.s, car pour qu’un système perdure, il doit réguler des contraintes internes, mais aussi externes, afin de maintenir une stabilité de fonctionnement. Quatre théories explicatives de ce phénomène criminel seront mobilisées.
L’hystérie discrète
Authors: Sirois François
Published: March 2024

Sous la couverture de la notion d’hystérie discrète, le texte élabore la question du contre-investissement dans l’hystérie. Cette question est restée imprécise dans la pensée de Freud en regard du maintien du refoulement dans l’hystérie. La question est élaborée en regard des deux types de contre-investissements ; celui tourné vers l’extérieur qui caractérise l’hystérie, celui tourné vers l’intérieur comme mécanisme du moi pour se protéger de l’excitation. Le propos avance que, dans l’hystérie discrète, la composante du contre-investissement tourné vers l’intérieur en stabilise la présentation, notamment dans une particularité de l’usage du corps. Sur un autre axe, l’hystérie discrète se particularise par une double polarité, celle de la nostalgie du prégénital et celle de l’intrication masochiste.
Suffocation de la matrice, grande hystérie et cure psychanalytique : la permanence des signes
Authors: Lepastier Samuel
Published: March 2024

Cet article analyse le noyau invariant des expressions hystériques. À l’occasion d’une excitation sexuelle non consentie, ou, à l’inverse, lorsque l’objet du désir s’éloigne, le sujet ressent une douleur abdominale qui se propage dans l’ensemble du corps alors que s’installe l’angoisse ; des difficultés respiratoires apparaissent qui vont s’atténuant quand il « reprend ses esprits » en s’exprimant dans un discours affecté. Quelquefois subsistent des symptômes permanents pour lesquels est ressentie une « belle indifférence » formant une paire contrastée avec le débordement anxieux de l’accès. Ces troubles sont accompagnés d’amnésie. Bien davantage qu’un saut mystérieux du psychique dans le somatique, l’hystérie est une chute du psychique dans le langage. En dehors de la psychanalyse, dont la métapsychologie – théorie la plus générale – est déduite de cette crise, les autres conceptions psychopathologiques ne proposent pas de modèles pour en rendre compte. Cette méconnaissance est à l’origine d’impasses thérapeutiques aux conséquences parfois dramatiques.
Retour aux images freudiennes et à la figurabilité de l’accès hystérique
Authors: Dellanoce Filippo
Published: March 2024

Dans L’interprétation du rêve, Freud distingue précisément entre trois types d’images psychiques : les représentations ou Vorstellungen ; les figures ou Darstellungen, et les images de nature hallucinatoire ou Bilder qui composent le rêve manifeste. La fonction de figurabilité ou mise en figure intervient pour transformer les représentations en images. Puisque, selon Freud, le travail du rêve est le paradigme du travail de formation du symptôme hystérique, nous devons nous attendre à retrouver, aussi dans ce cas, trois types d’images et une fonction de transformation. L’hystérie est, effectivement et selon Freud, une maladie de représentations ou fantaisies sexuelles qui sont mises en figures de manière pantomimique lors de l’accès hystérique. La fonction de figurabilité laisse sa place à la fonction psychique de conversion (Konversion) qui permet le passage du registre représentationnel au registre de la visibilité somatique de l’accès.
Les conférences dites « Nazareth »
Authors: Jesberg Bettina
Published: March 2024

L’article présente les conférences « Nazareth » initiées pour explorer les relations entre les Allemands, les Juifs israéliens et d’autres groupes en relation avec l’Holocauste ou d’autres conflits. Ces conférences ont été créées dans le but de mieux comprendre comment les sentiments et les fantasmes liés à l’identité nationale influencent les relations entre les groupes et comment ils affectent les perceptions du futur. L’article décrit également l’évolution de ces conférences depuis leur commencement en 1994, en élargissant leur thème pour inclure d’autres groupes et en se déplaçant dans différents pays. L’auteur fait part de ses expériences personnelles, mettant en lumière les défis et les prises de conscience qu’elle a rencontrés, elle souligne l’importance du travail psychanalytique dans la compréhension des conflits intergroupes et la nécessité de promouvoir le dialogue pour prévenir de futurs cycles de haine et de violence.
Multidimensional determinants of academic performance: Insights from undergraduate students in Moroccan universities
Authors: Alj Zakaria , Bouayad Anas
Published: March 2024

This research investigates the multifaceted determinants of academic performance in a large-scale study of 5,092 undergraduate students across diverse Moroccan universities. We delved into demographic, academic, psychological, societal, and lifestyle factors, providing a comprehensive analysis of potential influencers on academic success. These dimensions were identified as significant predictors of academic performance, as gauged by the students' Grade Point Average (GPA). The findings reveal the intricate and interconnected nature of these factors and their cumulative influence on a student's academic trajectory. Our study emphasizes the necessity for a holistic approach that integrates not only traditional academic strategies, but also psychological support, balanced lifestyle practices, and effective societal engagement. Our research underscores the rich interplay among these variables and offers a profound understanding of their collective impact on academic performance. The derived insights could be instrumental for educators, policymakers, and researchers striving to create strategies that amplify student success. While acknowledging the inherent limitations of the study, we believe the results serve as a pivotal guidepost in the ongoing quest to optimize student academic outcomes and overall well-being.
A stochastic Gilpin-Ayala nonautonomous competition model driven by mean-reverting OU process with finite Markov chain and Lévy jumps
Authors: Gao Meng , Ai Xiaohui
Published: March 2024

The Ornstein-Uhlenbeck (OU) process was used to simulate random perturbations in the environment. Considering the influence of telegraph noise and jump noise, a stochastic Gilpin-Ayala nonautonomous competition model driven by the mean-reverting OU process with finite Markov chain and Lévy jumps was established, and the asymptotic behaviors of the stochastic Gilpin-Ayala nonautonomous competition model were studied. First, the existence of the global solution of the stochastic Gilpin-Ayala nonautonomous competition model was proven by the appropriate Lyapunov function. Second, the moment boundedness of the solution of the stochastic Gilpin-Ayala nonautonomous competition model was discussed. Third, the existence of the stationary distribution of the solution of the stochastic Gilpin-Ayala nonautonomous competition model was obtained. Finally, the extinction of the stochastic Gilpin-Ayala nonautonomous competition model was proved. The theoretical results were verified by numerical simulations.
The impact of digital economy on the financial risk ripple effect: evidence from China
Authors: Huang Zimei , Li Zhenghui
Published: March 2024

The impact of the digital economy on the ripple effect of financial risks has attracted attention. Based on the data of flow of funds statements (financial accounts), spanning from 2011 to 2020, the fund flow analysis method was used to build a model measuring financial risk ripple effect. Second, we built a panel regression model, which studies the impact of the digital economy on the ripple effect of financial risks. In addition, we explored the heterogeneous effects of different dimensions of the digital economy on the ripple effect of financial risks. Our findings revealed several key conclusions. First, the total financial risk ripple effects between 2011 and 2020 continued to change, and the ripple effects of different types of financial risks have heterogeneity. Second, the digital economy has a negative impact on the ripple effect of financial risks. Third, the different dimensions of the digital economy have heterogeneity in the ripple effect of financial risks. Specifically, the digital economy user index and the digital economy innovation index have a negative impact on financial risk ripple effect. The digital economy platform index and the digital economy industry index have insignificant effects on financial risk ripple effect.
La performance territoriale des transports collectifs à Mila (Algérie)
Authors: Adjeroud Heythem , Chapelon Laurent , Lammoglia Adrien
Published: March 2024

Mila est un exemple de ville moyenne particulièrement intéressant à analyser pour appréhender les enjeux de concurrence/complémentarité des transports publics et privés en Algérie. Notre travail met en exergue les particularités du système de transport collectif dans cette ville moyenne algérienne et l’évaluation de sa performance, ainsi que les perspectives d’amélioration des services offerts aux usagers.Après avoir présenté le contexte et posé les fondements méthodologiques de la démarche adoptée, cet article s’attachera à analyser la performance territoriale des réseaux de transport collectif sous l’angle de leur capacité à répondre aux besoins de mobilité des habitants puis à dégager un certain nombre de leviers d’action pour accroître l’efficience des réseaux public et privé.En effet, malgré l’existence d’une complémentarité, notamment sur le plan spatial, entre services publics et privés, cette organisation hybride assure une desserte et une qualité de service qui ne sont pas en adéquation avec les besoins des usagers. Il nous semble indispensable de repenser la forme de coexistence public/privé afin de renforcer la compétitivité et la complémentarité des deux offres à Mila.
Albâtres, calcaires, granits en Arabie du Sud-Ouest
Authors: Breton Jean-François
Published: March 2024

Résumé – L’Arabie du Sud-Ouest, disposée en arc-de-cercle autour du désert d’as-Sabʿatayn, est constituée de plusieurs ensembles géologiques différents, des massifs calcaires, des socles primaires et des coulées volcaniques. Chacun de ces ensembles produit des pierres différentes – albâtres, calcaires, calcédoine, granits, ardoises – qui ont été utilisées soit dans la construction des édifices soit dans leur décoration. Cette étude a pour objet les pierres qui ont été transportées d’une région à une autre. Elle s’appuie principalement sur les chantiers de Mâʾrib, de Tamnaʿ et de Shabwa et sur des prospections autour du jabal al-Nisîyîn. Selon la documentation disponible – de nombreuses pièces étant hors contexte stratigraphique – une tentative de classement chronologique de ces échanges est proposée.
Cleared for Takeoff
Authors: Ceken Seda
Published: March 2024

Digital assistants work with the support of artificial intelligence-supported systems and automation technologies. Due to the conveniences provided by digital assistants, they provide great benefits in many areas such as ensuring flight control in aviation operations, air traffic management, pilot training, and facilitating passenger services. Errors in flight operations and passenger experiences are reduced to a minimum with features such as voice commands transmitted through virtual assistants, artificial intelligence-based guidance system and automatic warnings. This book chapter has been created to cover the development of digital assistants in aviation and their impact on practice, with particular emphasis on key subtopics. In the content of the book chapter, the application of digital assistants in flight operations and passenger experiences in the field of aviation and future projects are evaluated based on current literature.
Online Engagement: From Public Relations Perspectives
Authors: Ulaş Sevilay
Published: March 2024

The aviation industry can be said to be one of the industries whose star has been shining more and more recently. In its simplest form, can be defined as a process that includes all activities, details and industries related to aviation. Aviation industry institutions aim to carry out effective and sustainable communication activities with their target audience/customers and followers. Social media tools and environments are also the preferred media in this communication process. Social media influencers, which can be specified as an increasingly remarkable communication element, are also in the aviation field and their effective use is seen. Its applications are seen in many different areas such as aircraft-aviation, travel, food and beverage, destination. In the effectiveness of the communication process, online engagement is also a factor that is mentioned. Therefore, the two-way communication process that takes place in this study, which focuses on influencers in the aviation field and online engagement, is also mentioned in the specified communication process.
A Survey of Machine Learning and Cryptography Algorithms
Authors: Indira M. , Mohanasundaram K. S. , Saranya M.
Published: March 2024

The intersection of machine learning and encryption has emerged as a key area in technology. A model shift in technology and data security has brought the combination of machine learning and encryption. In order to provide insight on the underlying algorithms and techniques, this survey was taken between the domains. It presents an overview of machine learning and cryptography algorithms. A wide variety of algorithms are examined in the field of machine learning. This survey also clarifies the interaction between machine learning and cryptography, demonstrating how these two fields work together to produce privacy-preserving ML, secure authentication, anomaly detection, and other benefits. A new era of data privacy and security has methods like secure multi-party computation (SMPC) and homomorphic encryption, which allow calculations on encrypted data. An updated overview of machine learning techniques used in cryptography is presented in this survey. The report offers recommendations for future study initiatives and summarizes the work.
Minimizing Data Loss by Encrypting Brake-Light Images and Avoiding Rear-End Collisions Using Artificial Neural Network
Authors: M. S. Abirami , Kushwaha Manoj
Published: March 2024

Rear-end collisions are a threat to road safety, so reliable collision avoidance technologies are essential. Traditional systems present several issues due to data loss and privacy concerns. The authors introduce an encrypted artificial neural network (ANN) method to prevent front-vehicle rear-end collisions. This system uses encryption techniques and ANN algorithm to recognize the front vehicle brake light in real time. Information can't be deciphered without the appropriate key using encryption. Intercepting data during transmission prevents reading. The system works day and night. ANN outperforms LR, SVM, DT, RF, and KNN in accuracy. An encrypted ANN-based ML model distinguishes between brake and normal signals. ANN accuracy was 93.7%. Driver receives further alerts to avoid rear-end collisions. This work proposes a lightweight, secure ANN-based brake light picture encryption method. The proposed approach may be applied to other collision circumstances, including side and frontal strikes. The technique would be more adaptable and applicable to many road safety circumstances.
Homomorphic Encryption and Machine Learning in the Encrypted Domain
Authors: Krishna Neethu , Raju Kommisetti Murthy , Dankan Gowda V. , Arun G. , Suneetha Sampathirao
Published: March 2024

In cryptography, performing computations on encrypted material without first decrypting it has long been an aspiration. This is exactly what homomorphic encryption (HE) accomplishes. By allowing computation on encrypted data, the associated privacy and security of sensitive information are beyond imagination to date. This chapter delves into the vast and intricate realm of HE, its fundamental theories, and far-reaching implications for machine learning. As a result of the sensitive nature of the data on which machine learning is based, privacy and security issues often arise. In this vein, homomorphic encryption, which allows algorithms to learn from and predict encrypted data, emerges as a possible panacea. The authors thus set out in this chapter to prepare the ground for a deeper understanding of that synergy, showing how it is there but also what lies ahead.
An Effective Combination of Pattern Recognition and Encryption Scheme for Biometric Authentication Systems
Authors: Mahesh Vijayalakshmi G. V.
Published: March 2024

Authentication based on biometric technology is largely preferred in providing access control to the systems. This technology has gained wider attention due to the rise in data generation and the need of data security. The authentication depends upon the physiological traits of human such as face, fingerprint, hand geometry, iris scan, retinal scan, and voice. Depending upon the level of security required, a single trait or multiple traits could be utilized. The key features or patterns extracted from the biometric data play a significant role during authentication process that involves pattern recognition. That is, the patterns that exist in the database are matched with the patterns provided during log on. The access is provided based on complete match. Though biometry-based authentication systems provide an effective way of accessing the system, still it is affected by attacks that try to get unauthorized entry into the system. Thus, this chapter focuses on working with the methodologies that provide additional security to the biometric authentication system by utilizing encryption algorithm.
Role of Osmotic Computing in Civil Engineering
Authors: Kumaravel B. , Indirani G.
Published: March 2024

IoT is a trending technology, and it can be combined with various other technologies like cloud computing, machine learning, and deep learning to use it in versatile applications in real-time world for the past two decades. Usually, IoT sensors are used to collect data from the real-time environment, and the collected data from the sensors are usually large in volume. Here, cloud computing plays its vital role to store the collected data. Therefore, in IoT, the required data acquired from the sensors need to be scrutinized in real-time for providing quick control action for the industrial IoT devices.
From Theory to Practice
Authors: Umamaheswari P.
Published: March 2024

In the evolving landscape of distributed computing, the integration of edge devices with traditional cloud infrastructures necessitates innovative approaches to harness their combined computational prowess. Osmotic computing, a paradigm that promises such integration, has transitioned from theoretical frameworks to tangible implementations. This chapter provides a comprehensive examination of osmotic computing, tracing its journey from conceptual underpinnings to its current real-world applications. Central to osmotic computing is the deployment of microservices—modular, autonomous units of computation—strategically positioned across the edge-cloud continuum based on immediate needs and resource availabilities. This review elucidates the foundational principles of osmotic computing, its distinguishing characteristics, the challenges encountered in its practical adoption, and its demonstrable benefits in current computing scenarios.
Food Items Moving From Restaurants to Online Platforms in the Developing Gig Economy
Authors: Shanthi K. , Suganya V.
Published: March 2024

The newest trend is to order food online while lounging at home rather than dining out. Additionally, they browse the different food options when ordering an online meal. Gig workers profit from the opportunities for employment, independence, and flexibility that this rapidly expanding gig economy provides. Giving people the freedom to choose from various food items makes trying new things enjoyable, but it also has some drawbacks. Technological integration makes real-time ordering and online payment processing possible, which raises consumer happiness. This chapter discusses the advantages and disadvantages of online meal delivery services. It will conclude by emphasizing the influence of social, economic, and individual factors on food delivery platforms.
Creator's Economy in the Metaverse
Authors: Khanal Krishna , Khanal Pushkar , Bala Manju
Published: March 2024

The creator's economy in the metaverse is poised to revolutionize the retail industry by offering an array of benefits to its stakeholders. In this emerging landscape, creators, brands, and retailers alike stand to gain substantially. Creators can leverage the metaverse's limitless creative potential to craft unique and immersive shopping experiences, fostering deeper connections with consumers. Brands can tap into the metaverse's vast and diverse user base to reach new audiences, drive engagement, and experiment with innovative marketing strategies. It is essential to bring various stakeholders together and to integrate the physical and virtual world together to leverage potential synergies and cross-channel benefits. Retailers should adopt a comprehensive and all-encompassing retailing strategy keeping customers and creators in the center and enabling customers to select their preferred shopping channel throughout their entire customer journey.
Identity Influence in Consumer Behavior on the Internet
Authors: Vats Ritu , Clonia Reeta
Published: March 2024

Consumers today have several ways to express who they are, including social media and digital networks in addition to their assets and purchasing habits. The identity signalling phenomena and identity strength are the main topics of this essay, which seeks to comprehend these digital consumer behaviors. To explain the scope and nature of behaviors associated with digital identities, the authors build a conceptual model that integrates internal and external influences. They base the study hypotheses on the example of gender identification because it is one of the topics that is discussed the most and most heatedly in online consumer forums. Additionally, they analyse the internet habits of trans customers and propose how offline and online identity signalling behaviors are connected. This underlines the distinctive characteristics of digital identity signalling behaviors as well as the variety of identities, including gender, and offers insightful information for academics and marketers.
A Review
Authors: Gugale Anisha , Majumdar Anindita
Published: March 2024

Any consumer's sentiment associated with a product is the most important aspect in determining the future selling prospect of that product. And there's no other way better than conversation to find that out. AI facilitates the makers of a product in finding out exactly what the consumers need and what he/she does not want. The provision of ‘writing reviews' on a website or an app is unidirectional and helpful in limited ways. To understand the sentiment of the consumer, an efficient understanding of their needs and wants is required – and this we get through collecting ‘conversational data'. Conversation between human beings is not simply just the exchange of words. There is a deeper meaning to it. Emotions are greatly involved. Is AI fully capable of understanding consumer sentiments and getting the exact required data from them? The AI chatbots must have the ability to find out the triggers of their consumers. And the aim of this research is the same – finding out how efficient conversational data is in analysing consumers' sentiments.
Segmenting Social Media Users Based on Ongoing Brand Activities to Track Consumer Behavior Change
Authors: Choi Youngtae , Kroff Michael W. , Penagos-Londoño Gabriel Ignacio , Ruiz-Moreno Felipe
Published: March 2024

In this study, the authors segment Facebook users based on their responses to brands' ongoing activities, including content relevance, personalization, responsiveness, and user empowerment, alongside user demographics and social media behavior. They examine variations in electronic word-of-mouth (eWOM) and purchase intentions across four distinct user segments detected: busy lurkers, selective seekers, active enthusiasts, and hesitators. Each segment displays unique responses to the brand activities, shedding light on demographic differences and diverse reactions. The research contributes both theoretically and empirically to understanding these user segments and offers valuable insights for brands and social media managers in effectively managing the relationship with their Facebook users.
COVID-19 Pandemic Personal Safety Is Revolutionized by the Smart Mask
Authors: Raghu N. , Swetha G. , Druva  , Shruthishree  , Rekha  , Niranjan Kannanugo  , Hemanth Kumar
Published: March 2024

In light of the massive use of face masks during the COVID-19 pandemic, it is clear that these protective gears are crucial in reducing the spread of respiratory viruses. Our research unveils the Smart Mask, a cutting-edge platform built on the Internet of Things (IoT) that aims to proactively regulate and prevent the spread of illnesses such as COVID-19. The Smart Mask creates an all-encompassing environment for monitoring and analysing data in real-time about health by using sophisticated sensor technologies, smart algorithms, wireless connection, and state-of-the-art materials. The Smart Mask gathers and analyses data pertaining to the wearer's and their immediate surroundings' health via the seamless integration of Internet of Things capabilities. Accurate diagnoses, individualised treatment programmes, and health trajectory prediction are all made possible by processing this data using artificial intelligence. By combining individual data with massive public databases.
Understanding the Multifactorial Background of Attention-Deficit/Hyperactivity Disorder
Authors: Kapoor Payal , Khutarkar Simran Sunil
Published: March 2024

Attention-Deficit/Hyperactivity Disorder (ADHD), a common neuro-behavioral disorder, affects children at an early age and its symptoms may continue in adults. The disorder impacts the individual's social as well as academic development. The multifactorial nature of ADHD is likely due to the combination of genetic, environmental, and neurological factors. Family history poses a great risk for ADHD development and is known to involve genes that regulate neurotransmitters associated with attention, impulses, and behavior. Maternal smoking during pregnancy, metal ion and toxin exposure and traumatic brain injury are some of the environmental factors that increase the risk of ADHD. Further, brain imaging studies in ADHD have shown altered structure and brain activity specifically in the prefrontal cortex. Reduced prefrontal cortex volume and altered brain connections in ADHD patients result in impulsivity, poor behavioral control, and difficulty in maintaining attention. Although with no cure, ADHD can be successfully managed, and some symptoms may improve as the child ages.
Green Energy Harvesting for Supply Autonomy of a Tourist Town With Solar and Wind Energy Resources
Authors: Prasad Dharmbir , Singh Rudra Pratap , Tanuja ­ , Roy Ranadip , Khan Md. Irfan
Published: March 2024

The accelerating demand for clean and sustainable energy sources has led to increased interest in harnessing solar and wind energy. This study suggested an integrated energy harvesting system consisting of solar and wind resources in the tourist town Manali, Himachal Pradesh. The goal of this system is to make use of the ample amount of sunlight and wind resources available in this area. The solar modules are positioned in such a manner that they capture maximum sunlight across Manali's varying terrains. Simultaneously, wind turbines are located to leverage the region's wind turbine to ensure continuous and wind ranging energy supply. The combined output from solar and wind is then directed to a sophisticated super capacitor-based energy storage system. The study also focuses on economic feasibility, environmental impact, and long-term sustainability.
Revolutionizing Creative Tourism
Authors: Sharma Ishani , Aggarwal Arun
Published: March 2024

This chapter provides a comprehensive review of hospitality and tourist (HAT) AI literature. The analysis identified relevant themes, pros, and cons, as well as suggested future research possibilities in this discipline. HAT is rapidly adopting AI technology to improve customer service, operational efficiency, travel experiences, and sustainability. There is a growing body of research on this topic, but a thorough and systematic understanding is needed to determine the most effective AI applications and recommend areas for further investigation. This chapter discusses how machine learning, natural language processing, and robotics may improve tourist and hospitality consumer experiences and efficiency. This chapter covers AI in travel, from chatbots for customer service to autonomous cars to VR/AR for immersive experiences. AI disrupts customers and companies in personalisation, decision-making, and predictive analytics. These AI technologies' ability to revolutionise the business provides a futuristic view of travel and tourism.
Social Media Marketing Strategies for Innovating Relationship Marketing in the Digital Era
Authors: Batta Aaruni , Pahuja Pallavi , Sharma Ruby
Published: March 2024

Utilizing social media for real-time communication and feedback is crucial in the evolving landscape of business communication in the digital era. It's not enough to simply acquire new customers through lead generation or sales; you must also foster connections with them on social media and online to ensure their continued loyalty and advocacy for your brand. Traditional word-of-mouth marketing has transformed, and the key to sustaining customer relationships and driving repeat business lies in building strong, lasting connections with your clientele. The absence of verbal marketing underscores the significance of cultivating robust client relationships. Enthusiastic customers who feel a genuine connection to your company will not only continue to patronize your business but will also enthusiastically recommend your products or services to their friends and family. Consequently, both marketing and business operations prioritize the establishment of solid customer connections.
Service Quality and Innovation in Air Transport
Authors: Lakshmanan Ravi
Published: March 2024

Passenger services at airports are coproduced by many organizations - airports, airlines, ground handlers, immigration, customs, aviation security, and commercial establishments. Service performance on subjective parameters is evaluated primarily through customer satisfaction surveys at frequent intervals through third parties with varying parameters and methodology. The objective parameters as defined by the airports are measured and reported by the airports. Thus, there is no standardized set of parameters and methodology for airport services performance. With the increased passenger's awareness about quality of services and reporting platforms like social media, airports have started to innovate the processes and introduce advanced technologies and exceed the service quality paradigm to passenger experience. Also, the importance attached to the services by the passengers differs based on the travel purpose. It is seen that airports compete with each other to add value to passenger services and experience on a continual basis. This book chapter describes these aspects of airport services.
The Impact of Innovative Strategies on a Small-Scale Service Industry in Ghana
Authors: Afedzie Richard H.
Published: March 2024

A lot of research studies have shown that a direct and positive relationship exists between innovative strategies (IS) and an organisational performance. However, the relationship may not be simple and clear to understand. This study used a qualitative, simple descriptive case study approach to critically investigate the level of innovative strategies approach to the growth of Compressor Techniques Limited, Ghana. A semi-structured questionnaire was utilised to interview employees (participants) at Compressor Techniques Limited to gather primary data for the study. Purposeful sampling was used to select twenty (20) participants who have worked in the organisation five years and above to gather rich data for the data analysis. The research findings showed the company organizes workshops and seminars to improve upon the abilities of employees. It was recommended that the organization should regularly review and update their internal structures and decision-making processes for approving innovative projects so that the company can reach its productivity goals.
Diabetes and Pre-Diabetes Prediction by AI Using Tuned XGB Classifier
Authors: Kathirvel A. , Naren A. K.
Published: March 2024

The great majority of diabetes patients in India provide a unique set of challenges, and the prospective availability of data may significantly present a unique opportunity for efficiently addressing these challenges. If all doctors use electronic medical records to obtain this data, India may have a great chance to become a leader in this field of study. In this endeavor, the necessary electronic devices are routinely used to collect patient data. Artificial intelligence would help identify upcoming problems and perhaps even assist in developing solutions that are especially geared to make dealing with them a possibility. The possibility of a diabetic patient having a problem might be fixed by using different kinds of machine learning algorithms, which would boost the success rate of therapy. Along with XGboost and support vector machines (SVM), random forest is a well-known technique for making this prediction and managing the therapy, similar to the decision tree. In comparison to other classifiers, tuned XGB classifier produces the best results with an accuracy of 91%.
Real-Time Sign Language Recognition
Authors: Varshney Pankaj Kumar , Kumar Shrawan Kumar , Thakur Bharti
Published: March 2024

Speaking with someone who has hearing loss may be quite challenging. Systems that can recognize different signs and alert regular people are thus required. Recognition of sign language is a big development in assisting deaf-mute persons. With the exception of J and Z, which require motion detection for recognition, the objective of this study is to create a model based on neural networks for precise and user-friendly sign language identification that can identify finger spelling-based hand gestures representing the ASL alphabets.
Hepatitis C Prediction Using Feature Selection by Machine Learning Technique
Authors: Majumder Jeet , Ghosh Suman , Khang Alex , Debnath Tridibesh , Chaudhuri Avijit Kumar
Published: March 2024

This study suggests a prediction framework for the Hepatitis C virus that is based on machine learning techniques. The authors made use of a dataset available on Kaggle. In this dataset, 564 patients with 12 distinct features are present. They tested two cases, the first one without feature selection and with feature selection based on gain ratio attribute evaluation (GRAE), to guarantee the strength and dependability of the suggested framework. Additionally, an evaluation is conducted on the feature subset that was chosen using the GRAE-generated features. For model evaluation, induction methods and classifiers such as logistic regression (LR), naive bayes (NB), decision tree (DT), support vector machine (SVM), random forest (RF), and multilayer perceptron (MLP) are used. According to the experimental findings, the suggested framework outperformed the others in terms of all accuracy matrices following GRAE selection. According to the experimental findings, the suggested framework outperformed the unfeatured one in terms of accuracy after GRAE selection.
Identification of Insecurity in COVID-19 Using Machine Learning Techniques
Authors: Kar Somashri Pal , Molla Afiur Rahaman , Das Sayak , Rajak Ritam , Sil Soumyadeep , Chaudhuri Avijit Kumar
Published: March 2024

During the pandemic COVID-19, many people died due to the infection caused by the deadly virus, and many affected people in the isolated ward developed mental trauma and feelings of insecurity. In this chapter, the authors study 90 features of collected data from 207 concerned people during what they faced in lockdown period using machine learning about the insecurity to obtain key features. They have chosen seven ML algorithms like logistic regression, naïve bayes, stochastic gradient descent J48, multi-layer perceptron, random forest, and random tree. These algorithms are used on the features to identify appropriate features on insecurity. Data splitting with 10-fold cross validation reduced 90 features into seven features by comparative analysis. In 66-34 split, 50-50 split, 80-20 split, LR and NB achieved above 90% accuracy with these seven features. 80-20 and in 10-fold we get approximately 100% accuracy in J48, MLP, RF, and RT algorithms. Three feature selection techniques, Information Gain, ReliefF and OneR, were used for ranking features based on model performance.
Security Challenges in Storing and Exchanging Medical Information
Authors: Vashishth Tarun Kumar , Sharma Vikas , Sharma Kewal Krishan , Kumar Bhupendra , Chaudhary Sachin , Panwar Rajneesh
Published: March 2024

The healthcare industry is undergoing a profound transformation driven by the integration of medical robotics and AI leading to remarkable advancements in diagnosis and treatment. However, as the industry embraces these high-tech innovations, it faces a burgeoning challenge in ensuring the security of medical information throughout its lifecycle. This chapter provides an in-depth analysis of the security challenges in storing and exchanging medical data within this rapidly evolving healthcare landscape, with a specific focus on the emerging role of AI-assisted diagnostics and medical robotics. The utilization of AI in diagnostic procedures offers unprecedented precision and speed, but it also raises significant security concerns. Threats to patient data, confidential records, and the functionality of AI systems have intensified, demanding a robust security framework. This chapter explores the vulnerabilities associated with AI-assisted diagnostics and discusses the potential consequences of security breaches, which may extend to misdiagnoses and harmful interference in robotic surgeries.
Enhancing Education With Information and Communication Technologies
Authors: Mahlangu Bongi G. , Goosen Leila
Published: March 2024

The purpose of this chapter is to present the methodology that will be used to collect data for the study reported on. Against the background of enhancing education with intelligent systems and data-driven instruction, methodology is important in research because it offers legitimacy to research. The research methodology shows that universally accepted data collection methods and procedures were adopted, which contributes to the veracity of the research process. Additionally, the research methodology also acts as a guide to researchers so that they stay on track regarding whatever they will be doing. This chapter further seeks to define and defend the methodological basis used to answer the research questions outlined.
Gamification in Teacher Education
Authors: Prakasha G. S. , Rawat Sanskriti , Basak Ishani , Mathai Sebastian
Published: March 2024

Gamification emerged as a teaching-learning pedagogy in recent years. Its usage increased during the Covid-19 lockdown and continued post-pandemic time. Its usage ranges from online to offline tools; teachers lack its awareness as a pedagogy. The present study aimed to understand perspectives of teacher educators and teacher trainees on inclusion of gamification pedagogical training in teacher preparation programmes. The study employed a mixed-method approach and included qual-quant sequential explanatory research design. Researchers conducted semi-structured interviews with six teacher educators and six trainee teachers and collected the opinion of 200 teacher educators and trainee teachers. The study employed inductive thematic analysis and Chi-square analysis for qualitative and quantitative data respectively. Findings revealed six main themes and twelve sub-themes. Chi-square revealed a gender science-stereotype amid association between teacher educators and teacher trainees' opinion. Senior teacher educators did not believe in the importance of gamification inclusion in teacher preparation.
E-Mobility as a Service and Its Economic Impact
Authors: John Leo , Patro Rojalini , Padmakala S. , Madhumala R. B.
Published: March 2024

This study presents a systematic review of the studies and a comprehensive assessment of the ongoing implementation of e-mobility, evaluating social, monetary, policy, and sustainability factors associated with the circular economy (CE) ecosystems framework. It also discusses the current difficulties and proposes methods to address them to improve urban quality of life and the sustainability of electro-mobility. The objective of this study is to discover the particular explanation as to why industrialized countries are able to efficiently introduce cutting-edge electric fuel automobiles (e.g., electric vehicles) while underdeveloped economies cannot find it extremely difficult to implement these vehicles, particularly in terms of infrastructure and downstream activities and how these issues can be addressed effectively.
Electrifying Transportation and Pioneering the Future of Sustainable Electricity Mobility
Authors: Bharti Anil , Gupta Neha
Published: March 2024

The journey of electric vehicles (EVs) involves myriad challenges and opportunities amid their widespread adoption. EVs, powered by rechargeable batteries and electric motors, are transforming the automotive industry, offering environmental benefits like zero tailpipe emissions, improved air quality, and reduced noise. With instant torque and acceleration, EVs provide a responsive driving experience. The realm of e-mobility holds a promising future with dynamic challenges, opportunities, and emerging trends. Challenges include establishing robust charging infrastructure, addressing range anxiety, ensuring ethical supply chains, and advancing battery technology. Integration with autonomous and connected technologies, supportive policies, and creating a more sustainable transportation landscape are also vital. This chapter explores technical obstacles and opportunities in the industry's pursuit of greater electrification of energy conversion systems in mobile platforms, often referred to as e-mobility.
Real-Time Event Detection and Predictive Analytics Using IoT and Deep Learning
Authors: Ganesan Indumathi , Ponnuviji N. P. , Siva Kumar A. , Nithya M. , Jambulingam Umamageswaran , Lalitha S. D.
Published: March 2024

The internet of things (IoT) has led to an explosive increase in connected devices, generating a massive volume of data. Real-time analytics in IoT systems is crucial for timely decision-making, enhancing system efficiency and reliability. This involves processing discrete IoT data series within a bounded completion time, providing services like data classification, pattern analysis, and tendency prediction. However, the continuous and heterogeneous generation of IoT data poses significant technical challenges. Designing IoT systems to handle this data in a timely manner becomes critical. This chapter comprehensively explores real-time data analytics in IoT systems, elucidating its characteristics and analysing suitable architectures. A survey of existing applications highlights system design perspectives and performance shortcomings. Lastly, challenges in applying real-time analytics in IoT systems are identified, paving the way for future research directions.
The Transformation of Manufacturing by Artificial Intelligence
Authors: Das Dipan Kumar , Mallick Priyambada , Parthasarathy Siddharth , Satpathy Santosh Ku , Patnaik Padmaja
Published: March 2024

The combination of artificial intelligence (AI) and industrial momentum heralded a revolution in product design, manufacturing, and optimization. This summary provides an overview of the transformative changes brought by the business through the integration of AI technology and explores the various factors influencing the process of quality and innovation. Faced with the need for precision and efficiency, companies have adopted AI as a revolutionary tool. Through a real-world case study, this research explores how AI-based optimization can modify turbine blades to improve aerodynamic efficiency while reducing associated design and testing costs. The summary will also take a closer look at the field of AI-based additive manufacturing, showing how 3D printing based on artificial intelligence algorithms is revolutionizing traditional manufacturing processes.
Revolutionizing Trust Manufacturing Integrating Real-Time Data and AI Innovations for Enhanced Efficiency
Authors: Sudha K. , Balakrishnan C. , Anish T. P. , Nithya T. , Gracelin Sheena B. , Maheswari B. , Siva Subramanian R.
Published: March 2024

The revolutionary synergy of AI and real-time data in transforming trust manufacturing processes is explored in this research study. The use of AI technology has unparalleled prospects for augmenting productivity in the ever-changing realm of contemporary production. The study looks at a number of significant issues, such as the automation of document processing, the use of AI to optimise shipping and buying, and the development of strong lines of communication between manufacturers and suppliers. With a focus on the future, the report explores how AI and machine learning are changing the trust manufacturing environment and provides insights into possible advancements and obstacles. Besides this, the chapter provides instances demonstrating effective use of AI powered technologies and describes the complex influence of AI on day to day operations. In summary, this study adds to a more complex knowledge of how manufacturing processes may be streamlined and opportunities for innovation and optimisation in the industrial environment can be generated by integrating real-time data with AI.
The Future of Artificial Intelligence in Manufacturing Industries
Authors: Archana T. , Kingsly Stephen R.
Published: March 2024

The future of artificial intelligence (AI) in manufacturing heralds a transformative era marked by unprecedented efficiency, innovation, and sustainability. This chapter explores the impending evolution of AI within manufacturing industries. Anticipated advancements include the widespread integration of machine learning for adaptive production systems, predictive maintenance, and intelligent supply chain management. Human-machine collaboration, facilitated by augmented reality and AI-driven robotics, promises to redefine the manufacturing workforce, enhancing skills and optimizing operational workflows. This chapter encapsulates the multifaceted impact of AI on the future of manufacturing, where intelligent systems not only streamline processes and boost productivity but also contribute to sustainable practices and resilient, forward-thinking industrial landscapes. The journey ahead involves navigating challenges, embracing innovation, and harnessing the full potential of AI to shape the manufacturing industries of tomorrow.