bluuebunny/crossref_metadata_2025 huggingface dataset:
Female Leadership in Pediatric Ophthalmology: A Descriptive Analysis
Authors: Lam Laurel , Nelson Leonard B. , Bayraktutar Betul N. , Lee Karen E.
Published: August 2024

Purpose

To examine female representation among current chiefs of pediatric ophthalmology services of academic medical centers and children's hospitals, as well as program directors of ophthalmology residency and pediatric ophthalmology fellowship programs in the United States.

Methods

Data collection for this cross-sectional study occurred between December 2023 and February 2024, using publicly available sources to compile a list of academic medical centers and children's hospitals, as well as ophthalmology residency programs and pediatric ophthalmology fellowship programs that participated in the 2023–2024 San Francisco Match. Chi-squared analyses were performed using Excel 2021 software, where a
P
value less than .05 was considered statistically significant.

Results

Of the dedicated pediatric ophthalmology services across academic medical centers and children's hospitals in the United States, 38.3% (64/167) are led by a female chief. Female representation was greater at children's hospitals (40.0%, 36/90) than at academic medical centers (36.4%, 28/77), although no significant difference was observed (
P
= .69). Gender distribution was near equivalent at both academic training program levels, with slightly more female directors of fellowship programs (45.7%, 21/46) than ophthalmology residency programs (42.3%, 52/123) (
P
= .33).

Conclusions

The authors report near equivalent female representation in the leadership of academic training programs at the residency and fellowship level. However, the proportion of female pediatric ophthalmology division chiefs lags behind the actual gender composition of the workforce. Given the increasing prevalence of female pediatric ophthalmologists, promotion of concordant representation in leadership is necessary to reflect the changing sociocultural landscape and to close the gender gap.

[
J Pediatr Ophthalmol Strabismus
. 2024;61(6):391–396.]
Botulinum Toxin A Augmentation of Strabismus Surgery for Large-Angle Strabismus: A Retrospective Case Series and Literature Review
Authors: Dikkaya Çiçek Funda , Karaman Erdur S Sevil , Karaaslan Nisa
Published: August 2024

Purpose

To report the results of botulinum toxin A (BTA)–augmented bilateral recession or monocular recession/resection surgery in a case series of patients with large-angle strabismus and review the relevant literature.

Methods

This retrospective study reviewed the medical records of 24 patients treated with BTA-augmented strabismus surgery for large-angle horizontal strabismus (55 prism diopters or greater) with a minimum 6-month follow-up. Patients underwent unilateral recession-resection or bilateral rectus muscle recession surgery with intraoperative BTA injection into the recessed muscle(s). Main outcome measures were postoperative angle of deviation and success rate, defined as a final deviation of 10 prism diopters or less.

Results

Of 24 patients (20 esotropia, 4 exotropia), the mean age was 9.2 years (range: 1 to 64 years). Mean preoperative deviation was 61.2 prism diopters for esotropia and 66.2 prism diopters for exotropia. Mean final postoperative deviation was 6.6 prism diopters for esotropia and 14.5 prism diopters for exotropia. Successful outcomes were achieved in 75% of patients with esotropia and 50% of patients with exotropia.

Conclusions

BTA augmentation of conventional strabismus surgery dosages is a promising approach for managing large-angle strabismus, particularly esotropia. Optimal patient selection and follow-up are needed to maximize surgical success rates.

[
J Pediatr Ophthalmol Strabismus
. 2025;62(1):5–11.]
RESEARCH INTO A STABLE DIFFUSION-BASED HUMAN-MACHINE-HUMAN TEACHING MODEL FOR ARCHITECTURAL DESIGN COURSES
Authors: Du Sheng , Lu Xiaoyue , Chen Zimo , Cai Zixiao , Chen Lei
Published: August 2024

Conventional methods of teaching architectural design have flaws like fuzzy information exchange, limitations of thought dispersion, and disconnection of theory and practice because of the different cognitive levels of teachers and students. This paper explores the interactive and collaborative “human-machine-human” mode of utilizing Stable Diffusion image generation technology to teach architectural design and achieve artificial intelligence. To enhance the quality and effectiveness of instruction, the model uses artificial intelligence for image generation, optimization, and presentation in accordance with the three stages of architectural design teaching that are developed in this paper. Mainly using the Northeastern University youth hostel design course as an example, this paper compares the new “human-machine-human” mode with the traditional “human-human” mode, assesses the necessity and viability of the AI intervention, and offers examples for future architectural course teaching reform and the comprehensive integration of AI and architecture. In the interim, it offers resources and recommendations for the deep integration of AI and architecture, as well as recommendations for future teaching reform of architecture courses.
RESILIENCE OF GREEN BUILDING SUPPLY CHAIN: CAPABILITIES, RISKS AND INFLUENCE MECHANISM
Authors: Jiang Yongsheng , Zhang Yunjia , Yeganeh Armin , Zhao Dong
Published: August 2024

Green buildings are more effective in saving energy and reducing carbon dioxide emissions than conventional buildings. However, the long-term development of green buildings depends heavily on the resilience of their supply chain. This study examines how capability factors (readiness, response, and recovery) and risk factors (technological, organizational, and environmental) interact to influence the resilience of the green building supply chain, using a third-order partial least squares structural equation model. The results indicate that response capability and technological risk significantly impact resilience, while readiness capability mitigates organizational and environmental risks. The study suggests three strategies to enhance supply chain resilience: strengthening readiness capabilities and increasing resistance to organizational or environmental risks. The findings provide green building project managers with practical insights and tools to make informed decisions that improve supply chain resilience.
Advancements in Metal Additive Manufacturing Technology for Biomedical Applications
Authors: Baskaran Jagadeesh
Published: August 2024

Metal additive manufacturing, commonly known as metal 3D printing, plays a pivotal role in the fabrication of biomedical implants. This advanced manufacturing technique utilizes layer-by-layer deposition of metal powders or wire to create intricate and customized structures. It contributes significantly to the field of biomedical applications, particularly implant fabrication. It allows for creating highly complex and patient-specific implant geometries that would be challenging or impossible to achieve with traditional manufacturing methods. This capability is particularly advantageous in developing implants tailored to individual patients' unique anatomies, optimizing the implant's fit and functionality. This chapter discusses the fundamentals and advanced concepts of metal AM, their applications in biomedical engineering, and the challenges in their adoption.
An Enhanced Taxi Demand Perception System Leveraging Fusion and Automated Sensor Integration
Authors: Kelagadi Hemantaraj M. , Billady Ravikiran Kamath , Shanmugasundaram Ravivarman , Thilak K. Raj , Karthick L , Patil Narhar K.
Published: August 2024

Academia has recently focused on taxi demand prediction, seeing its potential in intellectual transference systems. Older methodologies often overlooked nuanced journey conditions, mainly forecasting from origin locations. This approach lacks efficiency, disregarding demand dynamics between origins and destinations. The research introduces taxi origin-destination demand prediction, leveraging mechanical automation. The authors aim to anticipate future demand across all potential area pairings, acknowledging complex location interplay. A crucial challenge is efficiently collecting diverse contextual data for effective analysis. They employ a sophisticated mechanical automation system integrating deep neural networks (DNNs) to classify journey starting and ending points, outperforming traditional methods in accuracy and performance. Through extensive testing on large-scale datasets, the DNN-based system excels in predicting taxi demand. Leveraging advanced technologies like mechanical automation, the authors pave the way for more efficient transportation systems.
Biaxial and Multi Axial Stress Behavior of Composites Insights and Methodologies
Authors: Mohammed Abdul Mateen , Dasari Venkata Ravi Shankar , Mohammed Manzoor Hussain , Mohammed Tajuddin
Published: August 2024

The utilization of fiber-reinforced composites has experienced a significant surge in various industries, such as aviation, marine, civil engineering, and automotive. This is mostly due to their exceptional strength and stiffness. However, the design of these structural components is usually based on the uniaxial test data, which has been found to be insufficient. This is due to the fact that real-world engineering materials often experience complex loading conditions that uniaxial testing cannot depict. To create structures that can withstand multiple loads, one must understand how composites react to biaxial or multiaxial loading. Multi-axial and biaxial loads cause different failure processes than uniaxial loading. The current study examines the behavior of FRP when subjected to biaxial loading. The study encompasses the examination of testing protocols, specimen design, and sensing techniques utilized for the measurement of stress and strains under biaxial loading.
Churu's 100MW Solar Dream
Authors: Padhi S. N. , G. Prudhvi Teja , Rout Trilochan , Rao S. S. , Choudhury Mamata
Published: August 2024

Every nation is actively seeking alternative energy sources to diminish reliance on fossil fuels, natural gas, and coal. Countries worldwide are striving for environmentally friendly and sustainable energy solutions, aiming to reduce dependence on fossil fuels. This chapter explores the feasibility of establishing a 100MW photovoltaic power plant in Churu city, Rajasthan, utilizing RET screen software. RET screen facilitates feasibility, benchmark, financial, and emission analyses, covering various renewable energy sources such as geothermal, bioenergy, solar, and wind power. Specifically, this project conducts a feasibility analysis of photovoltaic cells, converting solar energy into usable power. Given the abundance of solar energy, the study focuses on the viability of a solar or photovoltaic power plant, yielding positive outcomes. Consequently, this project emerges as a financially feasible and environmentally sustainable endeavor, contributing to the reduction of greenhouse gas emissions and advancing the nation towards cleaner energy production.
Integrating Mechanical Systems With Biological Inspiration
Authors: Prabakaran P. , Choudhary Mukesh , Kumar Kaushal , Loganathan Ganesh Babu , Salih Idris Hadi , Kumari Khushboo , Karthick L.
Published: August 2024

The healthcare system, viewed as an organization, demands robust security and privacy measures. These encompass safeguarding patient medical data, ensuring prescription drug safety, establishing secure connections with vehicles like ambulances, and deploying intelligent e-health monitoring systems. Blockchain technology has emerged as an innovative solution to enhance the security and integrity of medical data. It offers a potential resolution to the dilemma of balancing anonymity and secure data exchange. The study introduces a privacy-centric approach for blockchain and internet of things (IoT) integration, leveraging the advantages of cloud computing alongside blockchain. This approach not only integrates IoT functionalities and provides solutions for blockchain nodes but also manages identity authentication for health data. It addresses the computational limitations of certain blockchain routers, ensuring the validity of information. Through simulation experiments, the proposed technique demonstrates its effectiveness in tackling challenges such as complex computation, data exchange, and privacy preservation, while upholding the quality of medical data.
Nurturing Trust in Human-Robot Interaction and the Crucial Role of Dialogue and Explicit AI
Authors: Vadivukarasi L. , Babu L. Ganesh , Hasan Dler Salih , R. Rajesh Sharma , Devi N. Durga , Karthick L.
Published: August 2024

Modern technology has improved to the level that robots are possible to interact like human beings. Therefore, human-robot interaction has gradually become a part of human society. At the same time, technology is still in the process of refinement for better interaction with humans. Therefore, AI for content detection and dialogue AI has developed as a device for improving human and robot interface. An increase in the online presence of people triggered a change of gratified and explicit AI helps to analyse and filter explicit content according to age set. Conversely, dialoguer AI aids in the process of responding in accordance with the input given, making it important for human-robot interface. In order to analyse the importance of the role of explicit AI and voice AI for human interface, the succeeding study takes the working process and significance of the same. Furthermore, for a complete understanding, problems are mentioned in a table formation. Moreover, a complete discussion is done for describing the role of open and dialogue Artificial intelligence in human relations.
Advancing Health Monitoring With Cognitive IoT, Rapid Machine Learning, and Mechanical Systems
Authors: Yeruva Ajay Reddy , Jadhav Renuka Shankar , Roopa R. , Preetha S. , Priya R. , Mishra Krishna Nand , Karthick L.
Published: August 2024

Enhancing health monitoring for diabetes patients requires routine surveillance. Integrating IoT, embedded software, data analytics, intelligent systems, and smart devices can alleviate healthcare costs. Improved communication technologies enable remote exercise therapies. An intelligent healthcare infrastructure and expanded network packages are crucial for evolving e-health applications. Integration with 5G ensures higher bandwidth and energy efficiency. Real healthcare programs need seamless integration. In this study, an intelligent infrastructure for diabetes patient tracking using machine learning, smart gadgets, sensors, mobile phones, and mechanical systems ensure comprehensive data collection. Machine learning algorithms analyze patient data for efficient monitoring and prediction. Rigorous testing confirms system effectiveness.
Detection of Turned Features in an Autonomous Manner
Authors: Baluguri Ashwini Kumar , Seeram Srinivasa Rao , Padhi Surya Narayan , Choudhury Mamata
Published: August 2024

Automatic feature recognition (AFR) is a crucial process in manufacturing, aiming to extract and interpret design information without human intervention. Leveraging the “Java2” programming language, a software package equipped with Java Advanced Imaging (JAI) capabilities has been developed for this purpose. This package consists of four main modules. The first module is responsible for extracting geometrical data from the source material. Subsequently, the second module utilizes this extracted data to identify machine-turned features. Following identification, the third module generates process plans based on the recognized features. Finally, the fourth module employs these process plans to generate NC (numerical control) part programs. Through this systematic approach, AFR streamlines the machining process, reducing the reliance on manual intervention and enhancing efficiency in manufacturing operations.
Flexible Tree Trimming Tool
Authors: Rao Seeram Srinivasa , Padhi Surya Narayan , Baluguri Ashwini Kumar , Jagannadh J. Y. Durga Sai , Reddy P. Arjun , Kumaar K. Y. Pavan , Choudhury Mamata
Published: August 2024

The adjustable cutting device for trees and branches addresses a crucial need in the field of arboriculture by aiming to reduce both the financial burden and potential risks associated with tall branch trimming. This innovative device is designed to offer a versatile solution, capable of accommodating varying tree heights and branch sizes. Its adaptability ensures efficiency across different problem statement for tree cutters instead in human tree types, promoting a more inclusive and effective approach to tree maintenance. One of the key features of this device is its enhanced mobility, allowing it to be easily transported between different locations. This not only improves the overall convenience for users but also contributes to the reduction of manual labour and the associated risks. By integrating safety mechanisms and considering the diverse challenges posed by different tree species, the adjustable cutting device seeks to revolutionize the tree-cutting process.
Assessing the Dependence of Sustainability and Market Indices in India
Authors: Mathew Vineetha , Akbar Haseena , Kumar P. K. Santhosh , Serzhanov Vitaliy
Published: August 2024

This chapter delves into a novel exploration of the non-linear interdependence between the conventional market index and selected sustainability indices in India. While socially responsible investing has gained traction globally, its impact on emerging markets like India is less explored. This study assesses the relationship between the market index- Sensex and sustainability indices - ESG, Carbonex, and Greenex through copula models. By scrutinizing the relationship between them, this study breaks new ground in understanding investor preferences and market dynamics. Results indicate a strong positive association between Sensex and sustainable indices, underscoring investors' growing inclination towards sustainable investments. Moreover, the copula models reveal various degrees of dependency, with Carbonex demonstrating the highest dependency on Sensex. The findings of the study show the popularity of sustainable indices in the Indian landscape and provide insights for investors, companies and policymakers.
Sustainable Synergy
Authors: Sajeev Aparna , Kaur Harpreet
Published: August 2024

Understanding the interrelationships between economic growth, environmental quality, and sustainable development is pertinent for India. This connection is marked by reciprocal causation and feedback mechanisms-energy consumption stimulates economic growth by providing the necessary fuel for production and consumption. However, economic expansion influences energy consumption patterns by altering the industrial structure, adopting new technologies, and changing income levels. This study investigates the relationship between economic growth, energy transition, and sustainable development in India from 1990 to 2020. It also estimates the impact of industrialisation and trade openness on economic growth using an Auto Regressive Distributed Lag (ARDL) approach. The results show a positive and significant relationship between environmental degradation (CO2) and economic growth. Policymakers and stakeholders must develop efficient energy policies and effective, sustainable development strategies. The policies should facilitate economic expansion and safeguard energy stability, ecological endurance, and social well-being.
Techno-Economic Analysis for Energy Supply to Sustainable Pilgrimage Market
Authors: Prasad Dharmbir , Singh Rudra Pratap , Tanuja ­ , Roy Ranadip , Khan Md. Irfan
Published: August 2024

Globally, the use of renewable energy sources has increased significantly in recent years. As an attempt to achieve environmental sustainability, a number of efforts are being implemented to lower the carbon footprint of rapidly growing economies. The objective of reaching zero emissions is essential for this project. Particularly in Varanasi, a promising future is emerging as the areas of renewable energy, technology, and economy come together. The initiatives to electrify the pilgrimage market through innovative technology solutions for the production of renewable energy are a prime example of this combination. There is a 197,146,136 watt hour need for energy in Varanasi, the proposed location. The solar and grid together in the proposed system generate 263,979 kWh, of which 30,615 kWh are produced by photovoltaic cells, 233,364 kWh by the grid itself and 19,334 kWh by grid sales. This system emits 140 kg of CO2 annually. In the present study, ROI is 54.3%, IRR is 58.5%, and the simple payback period is 1.71 years, according to the economics.
Food Security Challenges
Authors: Al-Dulaimi Fahad K. Y. , Al-Tarjuman Janan K.
Published: August 2024

The subject of food security and sustainable development has occupied great attention at all global levels, both theoretical and applied aspects. The World Health Organization defines the concept of food security as “all the necessary conditions and standards required during the processes of production, manufacturing, storage, distribution, and preparation of food to ensure that it is safe, reliable, healthy, and suitable for human consumption. The causes of the global food crisis are due to several factors, the most important of which are weather fluctuations, the worsening phenomenon of drought, the decline in food stocks, the decline in agricultural sector productivity, the growing and unprecedented rise in the prices of basic foodstuffs, the rise in fuel prices, and the use of agricultural products to produce alternative fuels. Given the multiple causes of this crisis, experts agree that it will be long-term, as they consider it an intertwined and difficult problem.
Water Resources, Crises, and Sustainability
Authors: Ali Alaa H. , Taher Noor Al-Huda Ahmad Mohamed , Ahmad Hiba Fares
Published: August 2024

The world faces multiple water-related crises. These crises threaten not only ecosystems but also human health, food security, and economic development. However, there are increasing efforts towards sustainability aimed at addressing these challenges. Most countries in the world suffer from water scarcity, as a result of several combined reasons, including the water policies that the riparian countries have embarked on to reduce the amounts of incoming water, and the establishment of irrigation projects, in addition to climate changes such as a rise in temperatures and a decrease in the rate of rainfall. As a result of the population increase, the water problem has turned into a water crisis that worsens over time, which has affected the process of agricultural production and thus achieving sustainable agricultural development, as there is an inverse relationship between it and the water crisis. To solve this problem is to know the real causes that cause the crisis and find appropriate solutions and treatment for it. The researchers concluded that the nature of the water problem lies in a simple equation, which is that the available water is less than the demand for it. To solve this problem, it is either to increase the amount of water available versus the demand for it, or to reduce the demand for it around the quantity supplied. Many experiences in managing their water resources under conditions of scarcity, drought, and desertification, and the location of these countries in dry and semi-arid climate zones have led to the development of foundations, concepts, and principles that are widely applicable through the application of ideas for integrated management of water resources. Water resources management aims to develop and implement policies, processes, technologies, leadership, and organizations to understand, distribute, and improve the movement and characteristics of water resources to meet the multiple needs of human communities and ecosystems in an economically viable and environmentally sustainable manner.
Abiotic Threats of Agriculture
Authors: Ghazala Al Sadek Mohamed
Published: August 2024

The agricultural sector is important in the economy of the world in different ways, from increasing to promotion of food production. The increase in population faces the challenge of increasing the food supply to meet future demand. This challenge is compounded by the effect of abiotic threats on agriculture. Abiotic stressors factors include drought, soil salinity, heat and cold, water stress, heavy metal stress, desertification, and floods. These are major threats affecting agriculture both qualitatively and quantitatively. These threats will probably become more significant under climate change; therefore, climate change is a serious challenge for agriculture and its efforts to meet the growing need for food worldwide. Compared to yield record, abiotic stress can minify yields by more than half on average. On the other hand, abiotic threats can combine with other threats such as biotic stress, weather extremes, and detonation of disease /pests, outbreak of disease, and insect pest detonation.
The Role of Nanotechnology in the Treatment of Agricultural Problems
Authors: Mohammed Amjad Abdul-Hadi , Yahya Rana Tariq
Published: August 2024

The authors highlight the use of this advanced technology in the treatment of agricultural issues. As it contributes to increasing production agricultural productivity and reduces costs, the authors suggest creating a department in the scientific agricultural research specialist to conduct useful scientific research in this field and then transfer those studies to take their share practical application to achieve new added value to the agricultural sector and the economy the perfect national.
Sustainable Production of Some Fruit Species in the Tropical Highlands of Colombia, South America
Authors: Fischer Gerhard , Casierra-Posada Fánor , Magnitskiy Stanislav
Published: August 2024

The tropical highlands, which are less affected by global warming than lower areas, offer land suitable for the cultivation of fruit trees. These fruit species are mostly native to the Andes themselves, belonging to the families Solanaceae, Passifloraceae, Mirtaceae, Rosaceae, and Ericaceae. They are cultivated in the Colombian Andes, in areas with increased solar radiation, between 1600 and 3200 m above sea level and temperatures between 11 and 24°C. For better adaptation to these conditions, fruit growers use local and native germplasm to achieve sustainable cultivation except of some introduced varieties. Good adaptation is shown by the cape gooseberry, Andean blackberry, banana passionfruit, feijoa, apple, peach, pear, and Japanese plum. In addition, other genera and species of Ericaceae stand out for their adaptation and sustainability. Studies on the adaptation and sustainability of these fruit trees have been carried out by fruit growers, technical advisors, universities, and Agrosavia, and have focused on phytosanitary control, genetic resources, and cultural management.
Sustainable Production of Some Vegetable Species in the Tropical Highlands of Colombia, South America
Authors: Casierra-Posada Fánor , Fischer Gerhard
Published: August 2024

In the Colombian highlands, the use of native and/or improved varieties of vegetables, adapted to the elevation range and the adversities of climate change, are of great importance. To increase vegetable production, quality, and sustainability, new cultivation practices that are easy to implement have been proposed. These include enriching the spectrum of incident light in a given range, and the use of different substrates, which can be a more sustainable alternative to soil cultivation. The problem of heavy metal contamination in crops near rivers, industrial and mining sites, and roads must be solved through legal regulation, appropriate instructions to farmers, and the use of species and varieties that accumulate lower quantities of heavy metals. Also, in order to improve the sustainability of vegetable quality, work is being done on harvesting at the optimum degree of maturity, the use of suitable packaging, and the use of pesticides of natural origin.
Zero Knowledge Proofs and Their Applications in Cryptography
Authors: Aggarwal Tanish , Kumar Sudhakar , Singh Sunil K. , Gupta Brij B. , Nedjah Nadia , Castiglione Arcangelo
Published: August 2024

Zero Knowledge Proofs (ZKPs), cryptographic protocols that allow a party to authenticate a transaction to another without disclosing additional information beyond the authenticity of the transaction, continue to have a significant impact on privacy, security, and integrity in applications. It addresses constraints such as computing costs, trust dimensions, and integration complexity, and proposes possible methods and techniques for future research. It emphasizes the importance of ZKP for improving privacy and security in digital systems highlights, the article emphasizes the importance of continuous innovation and further development of their standardization efforts. Proofs (ZKPs) have emerged as a powerful tool in cryptography, offering innovative solutions to privacy, security, and authentication challenges. This article provides an in-depth review of ZKPs, exploring their progress, challenges and future prospects in cryptography. It examines the basic concepts of ZKPs, their applications, and their impact on cryptographic protocols.
Quantum Computing for Cybersecurity
Authors: Alauthman Mohammad , Almomani Ammar , Al-Qerem Ahmad , Al Khaldy Mohammad A. , Aldweesh Amjad , Al Maqousi Ali Younis , Alkasassbeh Mouhammd
Published: August 2024

This chapter explores the impact of quantum computing on cybersecurity, comparing classical and quantum techniques. It provides an overview of the current quantum landscape, focusing on the threats posed by quantum algorithms to traditional encryption methods. The study examines defensive strategies, such as quantum key distribution and post-quantum cryptography, presenting real-world examples and implementation challenges. It also discusses the main quantum algorithms relevant to cybersecurity and the various approaches within post-quantum cryptography. The chapter highlights the implications for governments, businesses, consumers, and researchers, stressing the need for proactive preparation and collaboration. The authors conclude by discussing the future role of quantum computing in cybersecurity, acknowledging the challenges while emphasizing the potential for quantum-safe solutions. The analysis underscores the importance of navigating the transition to a post-quantum era through strategic planning, research investment, and the adoption of hybrid classical-quantum approaches.
Next Gen Security With Quantum-Safe Cryptography
Authors: Singh Nipun , Singh Sunil K. , Kumar Sudhakar , Rawat Yash , Arya Varsha , Bansal Ritika , Chui Kwok Tai
Published: August 2024

With the rise and development of quantum computing, there is a high scope in the development of encryption methods increasing the security and integrity of data manyfolds. To safeguard user's data, quantum safe cryptography needs to be implemented in the different aspects of transmission of data. This study takes different algorithms into account that are being used for quantum safe encryption and discusses how they can be implemented in the current industries and systems. This chapter examines quantum safe cryptography algorithms—lattice-based, hash-based, and code-based—assessing their pros and cons against quantum threats. It explores the impact on finance, healthcare, and government, and discusses implementation challenges such as performance and compatibility. The need for global standardization and collaboration for widespread adoption is also explored.
Secure Key Generation and Management Using Generative Adversarial Networks
Authors: Al Khaldy Mohammad , Aburub Faisal , Al-Qerem Ahmad , Aldweesh Amjad , Almomani Ammar
Published: August 2024

The generation and control of cryptographic keys are the most important things when it comes to the security and integrity of encrypted data. The traditional key generation methods including pseudorandom number generation often fail to generate truly random values and become predictable as well. This chapter explores the potential of generative adversarial networks (GANs) for secure key generation and management. GANs, a very powerful deep learning architecture, can produce the statistical properties of true randomness utilizing adversarial training, thus generating key sequences that are random and unpredictable. The chapter proceeds with the essence of cryptographic key generation, key management lifecycle, GAN architectures, training strategies, and evaluation techniques for key randomness and security. Furthermore, it explores how this approach is applied for key distribution, synchronization, revocation, and updates, and these issues are analyzed, with a special focus on scalability and performance.
Revolutionizing Cryptography Blockchain as a Catalyst for Advanced Security Systems
Authors: Aldweesh Amjad , Alauthman Mohammad , al-Qerem Ahmad , Ishtaiwi Abdelraouf , Almomani Ammar , Al Khaldy Mohammad A.
Published: August 2024

Blockchain's decentralized trust models are spurring rapid advances in applied cryptography. This chapter explores the accelerating convergence between cryptographic innovations and next-gen blockchain platforms. The authors provide background on modern cryptography and the distributed ledger tech behind blockchains. They then analyze how blockchain architectures are driving progress in zero-knowledge proofs, digital signatures, and secure multiparty computation. In turn, these advancing cryptographic mechanisms enable critical blockchain capabilities around privacy, scalability, accountability, and governance. The authors highlight gaps in existing cryptography-blockchain integration and present post-quantum research directions that fulfill decentralized ledgers' unique security needs. Their work frames a symbiotic blockchain-cryptography ecosystem where progress in both fields builds on each other to overcome limitations. This interdisciplinary synergy will catalyze more secure, functional, and efficient decentralized technologies.
Cryptographic Techniques for Securing Blockchain-Based Cryptocurrency Transactions Against Botnet Attacks
Authors: Almomani Ammar , Al-Qerem Ahmad , Al Khaldy Mohammad , Alauthman Mohammad , Aldweesh Amjad , Nahar Khalid M. O.
Published: August 2024

This chapter analyzes the most sophisticated cryptography methods which are used to protect blockchain-based cryptocurrency transactions against attacks by botnets. First, a background will explain blockchain, cryptocurrencies, and threat space for bots is going to sing in. Core cryptographic building blocks such as hash functions and digital signatures are outlined. The chapter furthermore outlines methods to confront botnet threats in blockchain ecosystems, including two processes to sign the user charting, a sign policy standard, code signing, attestation, multi-party computation for private transactions, and zero-knowledge proofs. Finally, we present some obstacles and ideas for research along the way. Conclusively, the systematic incorporation of cryptographic defenses would be the providing layer of security as well as the guarantee of the integrity of cryptocurrency transactions. Continual improvements in scalable cryptographic algorithms and their implication in blockchain platforms will make secure mechanisms against botnets possible.
Cryptography in Business Intelligence and Data Analytics
Authors: Al Khaldy Mohammad A. , Ishtaiwi Abdelraouf , Al-Qerem Ahmad , Aldweesh Amjad , Almomani Ammar , Alkasassbeh Mouhammd
Published: August 2024

This chapter aims to determine the role of cryptography in the provision of secure applications of business intelligence and data analytics. Through this, the legal implications for weak cryptographic systems are illustrated in areas such as safeguarding customer information, trade secrets, and intellectual property in the context of data-driven businesses. Among the key areas explained are the various data encryption methods in transit (HTTPS/TLS) and at rest (database/disk encryption), including more advanced techniques such as homomorphic encryption which allows the calculations to be performed on encrypted data without the need to decrypt it. Searchable encryption, privacy retrieval, and multi-party sub-computation will also be examined as means of analysis over encrypted datasets. These technologies encompass, but are not limited to, secure outsourcing of analytics, privacy-preserving machine learning, blockchain-based data sharing, and safekeeping of personally identifiable information (PII).
Applying Visual Cryptography to Decrypt Data Using Human Senses
Authors: Rajput Dikshant , Singh Sunil K. , Kumar Sudhakar , Manro Divyansh , Bansal Shavi , Arya Varsha , Chui Kwok Tai
Published: August 2024

In the era of cryptographic advancement, integrating human workflow with technology is a natural progression. Traditionally, cryptographic advancements have focused on mathematical robustness and computational security. This research delves into combining cryptographic methods with human workflow to explore the foundations of visual cryptography and its practical implementation in decrypting sensitive information. Challenges related to usability, such as complex concepts, key management, user authentication, cross-platform compatibility, social engineering attacks, and balancing privacy with functionality, are evaluated with proposed solutions across various domains. Additionally, the study suggests methods to enhance the accessibility of cryptographic tools, including iterative design processes, user research, user-friendly interfaces, and error handling. Visual cryptography, leveraging the capabilities of the human visual system, presents a unique approach to data decryption that circumvents traditional reliance on computational algorithms.
Textual Analysis for Detection of Cyberstalking in Social Media Networks Using Federated Learning Technique
Authors: Sameera M. Bhargavee , Mariappan Ramasamy , Gurumurthy Kishan
Published: August 2024

The casual sharing of personal information on social media that seems harmless can pose significant risks when combined with other publicly available data. This aggregation can lead to the identification of individuals and the disclosure of their private activities leading to misuse by stalkers and illegal instances of online harassment. In terms of textual identification of such behaviors, employing advanced technologies like deep learning and machine learning algorithms is quite beneficial. This book chapter proposes a novel method to train computer systems using federated learning approach to mimic human behavior patterns to forecast and examine future occurrences. Federated learning utilizes edge devices' computational power to train machine learning models without transferring client data to a remote server, in contrast to traditional machine learning techniques that train on centralized datasets. This research work compares the application and accuracy of federated learning with conventional approaches to evaluate federated learning's efficacy in cyberstalking detection.
AI in Hospitality and Tourism Promotion
Authors: Sharma Vikas
Published: August 2024

The integration of artificial intelligence (AI) in the hospitality and tourism industry presents significant opportunities and challenges. This research explores how AI technologies, such as chatbots, predictive analytics, and personalized recommendations, are transforming the way businesses promote their services and engage with customers. AI-driven tools can enhance customer experiences by providing real-time information, personalized travel recommendations, and efficient service management. They enable businesses to analyze vast amounts of data, predict trends, and tailor marketing strategies to individual preferences, thereby increasing customer satisfaction and loyalty. However, the adoption of AI also presents challenges, including concerns over data privacy, the need for substantial initial investments, and the potential displacement of human jobs. The findings underscore the importance of strategic AI adoption in achieving competitive advantage and enhancing the overall customer experience in the rapidly evolving hospitality and tourism sector.
Embracing Technological Disruption
Authors: Sharma Milan , Singh Amrik , Rohit ­
Published: August 2024

In recent years, the tourist and hospitality business has undergone substantial technological disruption due to the rapid progress and use of artificial intelligence (AI) based solutions. This research study seeks to investigate the present status of AI implementation, namely chatbots, in the tourism and hospitality industry. It will analyze the primary factors that motivate the acceptance of these revolutionary technologies, as well as the obstacles encountered, and the services offered in accepting them. The article examines the use of AI in improving the customer experience, streamlining operations, and fostering innovation in different parts of the tourist and hospitality business. This is done by doing a thorough study of relevant literature and analyzing case studies from the industry. The results of this study can provide valuable insights for decision-making, influence future research priorities, and ultimately assist the industry in effectively utilizing AI to remain competitive and adaptable to the changing demands of customers in the digital era.
Smart Tourism
Authors: Bhatt Sagar , Dani Rakesh , Abdullah Khairul Hafezad , Singh Ajit Kumar
Published: August 2024

The tourism industry has progressively relied on big data analytics to improve guest service, optimize the effectiveness of operations, and boost profitability. This research outlines five significant discoveries about the potential and obstacles of utilizing big data in the tourism industry. Discoveries about the potential of big data in the tourism industry encompass the capacity to customize advertising strategies, optimize pricing techniques, improve client service, expedite operations, and minimize fraud. These chances are crucial for firms to maintain their competitiveness and fulfill customer demands. Nevertheless, harnessing big data in the hotel sector also poses substantial obstacles. The identified problems encompass the effective management of data size and effectiveness, guaranteeing robust security and privacy of the informative data, bridging the talent gap in big data analytics, cost management, and seamless integration of diverse software systems.
Redefining the Nodes of Metaverse and Luxury Hospitality
Authors: Singh Bhupinder , Kaunert Christian
Published: August 2024

The luxury hospitality renowned for its firm commitment to providing exceptional service and indulgent experiences has long been a hallmark of opulence and refinement. As the metaverse gains momentum and recognition, a new dimension of luxury is introduced that fuses the tangible and intangible, the physical and digital to create immersive encounters that resonate deeply with discerning guests. Also, some guests may still prefer traditional in-person experiences, so luxury hotels would need to strike a balance between offering both virtual and physical options. So, the use of AI and data analytics to tailor guest experiences raises concerns about potential discrimination and bias. This chapter explores the provide hospitality professionals with a roadmap to harness the power of emerging technologies, steering the industry towards personalized guest experiences, operational excellence and accelerated revenue growth.
Navigating the Digital Landscape With the Integration of Social Media and Artificial Intelligence (AI) in Tourism Industry
Authors: Kaur Harjot , Sharma Shikha , Guleria Sandeep
Published: August 2024

The tourism sector is currently experiencing a significant paradigm shift as a result of the integration of artificial intelligence and social media. Social media platforms influence traveler decisions and preferences through user-generated content and peer evaluations. AI technology like chatbots, automated customer service, and personalized suggestions are improving travel sector efficiency and customisation. This chapter analyses current patterns to investigate social media and AI's symbiosis. It also shows how these two technologies can work together to make travel more enjoyable, personalized, and smooth. It also addresses the issues that arise while applying these remarkable advances. This chapter summarizes the effects of social media and AI on travel and tourism. It predicts future advances and offers advice on adapting to the changing digital landscape.
Exploring Tech-Enabled Solutions
Authors: Kumar T. K. Sateesh , P. Thomas Lijo , Menon Vishnu Achutha , Thomas Juby
Published: August 2024

This study explores passenger satisfaction and airline service quality within the travel and hospitality sector. The dataset offers valuable insights into customer sentiments and provides essential data for customer service enhancements and predictive modeling. Various data analysis techniques, including confusion matrix, multinomial regression, and specificity sensitivity analysis, are employed to thoroughly examine patterns, correlations, and predictive factors related to passenger satisfaction and airline service quality. The analysis reveals exceptional accuracy in sentiment classification, with perfect precision, recall, and F1-score across all sentiment categories. Multinomial regression analysis shows impressive accuracy, surpassing the baseline and remaining robust across various sentiment categories. Metrics like sensitivity, specificity, precision, and negative predictive value affirm the model's effectiveness in sentiment classification. Word cloud analysis reveals prominent themes in customer reviews, including “flight,” “service,” and other pertinent keywords.
Leveraging AI for 24/7 Support
Authors: Kaur Mandeep , Pandey Uma , Kaur Amandeep
Published: August 2024

Throughout the post-pandemic period, the hospitality and tourism industry has experienced phenomenal growth in the number of customers with a growing need for excellent customer service. In the tourism and hospitality industry, customer service may be revolutionized in the hotel business by implementing chatbots. These AI chatbots increase client trust through customization, anonymity, and empathetic answers. Their advantages, including contextual awareness and natural language processing, are revolutionizing how consumers look for information and make decisions. Their perceived usefulness, humor, and ease of use are key criteria that make them preferable. AI chatbots positively affect consumer behavior by raising the caliber of interactions and willingness to pay for hotel services. For example, KLM Royal Dutch Airlines uses a chatbot named Blue-Bot to answer questions about booking, boarding, and other travel-related inquiries; the City of San Francisco uses a chatbot called Muni Bot to provide information about public transportation options; Hilton Hotels uses a chatbot to answer questions about reservations, amenities, and other hotel-related inquiries. Understanding these aspects and successfully utilizing AI technologies will enable hotels to improve client experiences, offer round-the-clock assistance, and expedite service delivery in the hospitality sector. Therefore, this chapter is aimed at examining the current uses and obstacles associated with Chatbots, implementing generative artificial intelligence (AI) and other related symbols as well as suggesting a roadmap for potential research under this area.