Browse Items (16481 total)
Sort by:
-
Exploring best practices in mobile app design patterns and tools: A user-centered approach
Design patterns are reusable solutions to common design problems that provide a consistent user experience across different apps. This article explores the best practices in mobile app design patterns and tools with a focus on the user-centered approach to design. Design patterns such as navigation bars, tab bars, list views, and card views are discussed, along with design tools such as Sketch, Figma, Adobe XD, and InVision. The problem is to ensure that mobile app design is centered around the needs and preferences of the user, rather than the designer or the technology, and that the right design patterns and tools are used to create interfaces that are familiar and easy to use. The chapter emphasizes the importance of conducting user research to understand the needs and preferences of the target audience and using design patterns and tools to create interfaces that are familiar and easy to use. Mobile apps have become an integral part of our lives, and designing a successful mobile app is a challenging task that requires a thorough understanding of user needs and preferences. 2023, IGI Global. All rights reserved. -
Revolutionizing lifelong learning AI, virtual, and augmented reality in education
The purpose of this chapter is to investigate the revolutionary effects that artificial intelligence (AI), virtual reality (VR), and augmented reality (AR) have had on the educational environment, specifically with regard to the revolutionization of lifelong learning. It investigates the ways in which the incorporation of cuttingedge technology is changing conventional instructional approaches, therefore providing students with individualized and immersive educational experiences. The conversation focuses on the inclusive and dynamic character of education that is made possible by artificial intelligence, virtual reality, and augmented reality, while also addressing problems such as the limitations of technology and ethical implications. It is emphasized that in order to fully realize the potential of modern technologies in the field of education, it is necessary for educators, legislators, and technologists to work together. This abstract offers a succinct overview of the ways in which artificial intelligence, virtual reality, and augmented reality are profoundly changing paradigms of lifelong learning. 2024, IGI Global. All rights reserved. -
Designing an efficient and scalable relational database schema: Principles of design for data modeling
Relational databases are a critical component of modern software applications, providing a reliable and scalable method for storing and managing data. A well-designed database schema can enhance the performance and flexibility of applications, making them more efficient and easier to maintain. Data modeling is an essential process in designing a database schema, and it involves identifying and organizing data entities, attributes, and relationships. In this chapter, the authors discuss the principles of designing an efficient and scalable relational database schema, with a focus on data modeling techniques. They explore the critical aspects of normalization, data types, relationships, indexes, and denormalization, as well as techniques for optimizing database queries and managing scalability challenges. The principles discussed in this chapter can be applied to various database management systems and can be useful for designing a schema that meets the demands of modern data-intensive applications. 2023, IGI Global. All rights reserved. -
Natural Language Processing (NLP) in chatbot design: NLP's impact on chatbot architecture
The creation and development of chatbots, which are the prevalent manifestations of artificial intelligence (AI) and machine learning (ML) technologies in today's digital world, are built on Natural Language Processing (NLP), which serves as a cornerstone in the process. This chapter investigates the significant part that natural language processing (NLP) plays in determining the development and effectiveness of chatbots, beginning with their beginnings as personal virtual assistants and continuing through their seamless incorporation into messaging platforms and smart home gadgets. The study delves into the technological complexities and emphasizes the problems and improvements in natural language processing (NLP) algorithms and understanding (NLU) systems. These systems are essential in enabling chatbots to grasp context, decode user intent, and provide replies that are contextually appropriate in real time. In spite of the substantial progress that has been made, chatbots continue to struggle with constraints. 2024, IGI Global. All rights reserved. -
Stormy minds and the long-term mental health impact of climate-linked natural disasters
This chapter delves into the enduring psychological ramifications stemming from climate-linked natural disasters, encapsulated in the term "Stormy Minds." As our planet grapples with an escalating frequency of such events, understanding the protracted effects on mental health becomes imperative. This abstract provides an insightful overview of the research, focusing on the intricate interplay between climate-induced disasters and the long-term well-being of individuals. Drawing on interdisciplinary perspectives, the study explores the psychological dimensions of enduring stress, anxiety, and trauma caused by these disasters. By assessing and documenting the persistent mental health impact, the research aims to contribute valuable insights for policymakers, mental health professionals, and communities striving to build resilience in the face of an increasingly turbulent climate. 2024, IGI Global. All rights reserved. -
Stir Speed and Reinforcement Effects on Tensile Strength in Al-Based Composites
This study focuses on the preparation of Al-based hybrid composites using AA7475 as the main alloy reinforced with two materials, ZrO2 and SiC. The combination of stir-squeeze processing techniques was employed to create various specimens by varying four parameters: Stir-speed, Stir-time, reinforcements, and squeeze pressure. Taguchi design was utilized to generate specimens for analyzing their mechanical properties, specifically tensile strength, hardness, and porosity.The results indicated that the highest porosity (4.44%) was observed in the L16 test, with a combination of 700rpm stir speed, 25 mins stir time, 2wt% reinforcements, and 80MPa squeeze pressure. On the other hand, the lowest porosity (2.61%) was found in the L7 test, with 800rpm stir speed, 30 mins stir time, 2wt% reinforcements, and 100 MPa squeeze pressure.Regarding tensile strength (UTS), the maximum value (285.23MPa) was achieved in the L13 experiment, while the minimum value (187.58 MPa) was observed in the L1 experiment. This variation in UTS can be attributed to the applied load, the strengthening effect of the reinforcements, and the grain size of SiC. 2024 E3S Web of Conferences -
Application of AI in Determining the Strategies for the Startups
Startups face unique challenges in developing viable strategies to create a competitive advantage and achieve long-term success in today's rapid and global business climate. Using tools powered by AI and algorithms, startups may harness massive amounts of data, generate relevant insights, and make intelligent choices across a variety of business processes. The research begins with an examination of the fundamental concepts beneath AI and how they are used in the business sector. It illustrates how organizations may simplify and improve important activities such as market research, customer segmentation, and trend analysis using artificial intelligence (AI), natural language understanding (NLU), as well as predictive analytics. The report also delves into extensive case studies and real-world examples of businesses that have effectively integrated AI into their business decision-making processes. These examples highlight the practical benefits of AI-driven insights that include enhanced resource allocation, customer targeting, as well as operational performance. It highlights the importance of ethical AI methodologies, transparency, and safeguards to ensure unbiased and fair decision-making. Finally, this study demonstrates how AI has the potential to profoundly transform how entrepreneurs design and implement their strategies. By leveraging AI-driven perspectives, startups may handle complex market dynamics with more precision and agility, increasing their chances of enduring and succeeding in a competitive business climate. The study's findings provide a road map for organizations wishing to apply AI in strategic decision-making processes. 2024 IEEE. -
Content analysis of Shyamprasad films /
Shyamaprasad is a renowned Malayalam film maker popular for his unique and refreshing style of film making. He is well known for the themes he employs in his films which make them stand apart. This research consists of an in depth analysis of all twelve films made by the film maker using various parameters. The parameters that are considered are themes, characters, underlying ideas, setting, conflicts and emotions. -
Handbook of Nutraceuticals: Science, Technology and Engineering
This book explores the complete development cycle of nutraceuticals and nano-nutraceuticals, with particular focus on manufacturing techniques and formulation strategies. It discusses their physicochemical behavior and presents innovative analytical characterization methods. The text also includes a variety of formulation approaches along with pharmacologic and pharmacokinetic evaluations. Several chapters address the controlled delivery of nutraceutical components, and the use of natural and biodegradable polymers in delivery systems is thoroughly reviewed. In vitro evaluation techniques for assessing nutrient delivery effectiveness are covered in detail, along with discussions on bioavailability, food additives, and encapsulation technologies. A dedicated chapter on the future of controlled-release technologies rounds out the volume. Springer Nature Switzerland AG 2026. -
Quantum Network Attacks in Urban IoT Infrastructures
With urban spaces increasingly networked via the internet of things (IoT), the advent of quantum computing brings with it both potential and major security threats. Quantum network attacks are a serious risk to urban IoT systems by targeting weaknesses in conventional cryptographic protocols. In contrast to classical cyber threats, quantum-powered attacks can decrypt commonly used encryption schemes, leaving vital smart city networks, such as traffic management systems, power grids, and public surveillance, vulnerable. The emergent nature of quantum computing calls for an active response to securing urban IoT systems from prospective vulnerabilities that can impair critical services and undermine public security. The inherent complexity of urban IoT infrastructures renders them extremely susceptible to quantum-based cyberattacks. Quantum decryption, man-in-the-middle attacks, and quantum-boosted malware pose risks that can expose sensitive information and facilitate large-scale cyber intrusions. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Reconfigurable Intelligent Surface-Aided Physical Layer Security Techniques: Applications and Future Trends
Reconfigurable Intelligent Surfaces (RIS) are emerging as a groundbreaking technology in the realm of wireless communications, with significant implications for enhancing physical layer security. This chapter delves into the integration of RIS with advanced security techniques, exploring how this innovative technology can be harnessed to address the growing challenges of securing wireless networks. this chapter delves into the future trends and advancements in RIS technology, including next-generation RIS architectures and their potential integration with emerging technologies like 6G. It explores how RIS could pave the way for innovative security protocols and play a pivotal role in advancing secure wireless network infrastructures. RIS technology enables the dynamic and intelligent modification of radio environments through programmable surfaces, which can adjust and optimize signal paths to improve both communication efficiency and security. This chapter provides valuable insights into the current applications and future prospects of RIS in enhancing wireless network security. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Leveraging social media and natural language processing for early detection of depressive disorders
Depression is a prevalent mental health disorder impacting over 280 million people worldwide, according to recent World Health Organization (WHO) estimates. It poses a substantial burden on individuals and societies, emphasizing the need for early detection and timely intervention. Despite the availability of treatment options, many affected individuals do not seek professional help due to barriers such as stigma, lack of awareness, and insufficient access to mental health services. With the widespread adoption of social media, people increasingly share their thoughts, feelings, and daily experiences online, providing an abundant source of user-generated content. This information can be harnessed to detect early signs of depression. In recent years, advancements in Natural Language Processing (NLP) and Machine Learning (ML) have paved the way for innovative approaches to analyzing social media data for mental health insights. By processing text-based content from platforms such as Twitter, Facebook, and Reddit, NLP techniques can identify linguistic patterns. 2025 by IGI Global Scientific Publishing. All rights reserved. -
AI-Powered Threat Detection and Response for Future 6G Networks
As 6G networks come into existence, there will be ultra-low latency, high bandwidth, seamless integration of billions of devices, and a revolution of connectivity. But with these great strides, new challenges about the securing of these systems against very sophisticated cyber attacks have come up. This book discusses how AI can benefit the 6G system to detect and respond threats better. Through the utilization of AI algorithms, machine learning, and deep learning, 6G networks will autonomously identify and mitigate security risks in real time while adapting to dynamic and everevolving attack vectors. AI systems can monitor network traffic in real-time, analyze anomalies, and predict possible vulnerabilities before they are exploited, hence reducing the detection-to-mitigation cycle. As 6G networks become more complex and pervasive, AI will become an indispensable component in maintaining security and enabling a trustworthy digital ecosystem, thereby becoming a core component of the future network defense. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Traffic management and congestion control in vehicular adhoc networks
Urban traffic congestion is a growing concern worldwide. Vehicular Adhoc Networks (VANETs) offer a glimpse into a future with smoother traffic flow and reduced congestion. These networks enable real- time communication between vehicles and infrastructure, creating a dynamic traffic management system. Imagine traffic signals that adjust based on real- time data, congestion being predicted and alleviated before it builds, and emergency services receiving faster response times. This is the potential of VANETs. Ensuring reliable communication and data integrity among constantly moving vehicles is crucial. Researchers are developing protocols and algorithms to address this, focusing on efficient routing, data dissemination, and network stability. The integration of emerging technologies like 5G, edge computing, and artificial intelligence holds promise for further enhancing network performance and robustness. While significant progress has been made, widespread adoption of VANETs faces hurdles. Scalability, security, privacy, and infrastructure development costs are significant concerns. 2025, IGI Global Scientific Publishing. All rights reserved. -
AI Solutions for Complex Communication Network Challenges
As communication networks balloon in size and complexity, managing them effectively becomes a monumental task. This chapter explores how Artificial Intelligence (AI) offers a powerful toolkit for tackling the intricate challenges faced by these systems. By leveraging machine learning, deep learning, and neural networks, AI can significantly enhance network performance, optimize resource allocation, and bolster security. Outlining the major hurdles plaguing modern communication networks, such as scalability limitations, latency issues, congestion bottlenecks, and ever- evolving cybersecurity threats. The chapter also acknowledges the ethical considerations and potential risks associated with AI deployment, emphasizing the need for responsible practices. Ultimately, this chapter provides a comprehensive perspective on how AI can become the cornerstone of resilient and efficient communication networks, paving the way for future advancements in this critical field. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Reconfigurable Intelligent Surface for mMIMO and NOMA Networks: Applications and Research Challenges
Reconfigurable Intelligent Surfaces are emerging as a transformative technology in wireless communication, particularly in the context of massive Multiple-Input Multiple-Output (mMIMO) systems and Non-Orthogonal Multiple Access (NOMA) networks. This chapter provides an in-depth exploration of how RIS can enhance the performance of mMIMO and NOMA networks, focusing on both practical applications and research challenges. RIS technology enables dynamic control over the wireless environment by adjusting signal reflections and enhancing signal propagation, which can significantly improve the efficiency and effectiveness of mMIMO and NOMA systems. For mMIMO, RIS can optimize spatial beamforming and mitigate interference, leading to enhanced capacity and coverage. In NOMA networks, RIS can This chapter offers a comprehensive overview of the potential of RIS to revolutionize mMIMO and NOMA networks, while also addressing the critical research challenges that must be overcome to fully realize its benefits. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Improved Random Forest Algorithm for Cognitive Radio Networks' Distributed Channel and Resource Allocation Performance
Modified Random Forest (MRF) machine learning algorithm aimed at improving the distributed channel allocation and resource allocation performance in cognitive radio networks (CRNs). The purpose of this research is to enhance the efficiency and effectiveness of CRNs by optimizing the allocation of channels and resources. The proposed MRF algorithm is developed by adapting and modifying the random forest technique to address the specific challenges of CRN allocation. Experimental evaluations demonstrate that the MRF algorithm achieves higher accuracy and efficiency compared to existing routing techniques and channel allocation algorithms like ACO and PSO. It exhibits a high packet delivery ratio, increased throughput, and reduced delay in channel selection, thus improving the overall performance of CRNs.The implications of this research are twofold. On a theoretical level, this study contributes to the field by extending the capabilities of the random forest algorithm and adapting it to the domain of CRNs. The modified algorithm demonstrates the potential of machine learning techniques in addressing allocation challenges in wireless communication systems. The findings emphasize the importance of advanced algorithms in improving the efficiency and effectiveness of channel and resource allocation processes. 2023, Success Culture Press. All rights reserved. -
Stiffness of a single layered cable assembly over a sheave with internal friction
The stiffness response of a single layered helical strand with a straight core surrounded by a layer of six helical wires has been made with improved relations of wire curvatures & twist and with internal friction considerations. The stranded cable undergoes a constant curvature bending over a sheave/pulley under static loading conditions and experiences the combinations of tension, torsion and bending loadings. A new analytical model has been developed for the cable in contact with the pulley/sheave using thin rod theory under linear elastic conditions. The stiffness coefficients of the cable are evaluated in free bending and constrained bending modes. The resulting wire strains are evaluated and compared with the experimental results. IAEME Publication -
Lung Cancer Detecting using Radiomics Features and Machine Learning Algorithm
Lung Cancer Incidence across the globe is the second leading cancer type tallying to about 2,206,771 during 2020 and is estimated to rise to about 3,503,378 by 2040 for both male and female sexes and for all ages accounting to 11.4% as per Globocan 2020 [1]. It is the leading death-causing cancer. Lung Cancer [2] in broad terms encompasses Trachea, bronchus as well as lungs. Purpose: The study is aimed to understand Radiomics based approach in the identification as well as classification of CT Images with Lung Cancer when Machine Learning (ML) algorithms are applied. Method: CT Image from LIDC-IDRI [4] Dataset has been chosen. CT Image Dataset was balanced and image features by PyRadiomics library were collected. Various ML features classification algorithms are utilized to create models and matrices adopted in judging their accuracies. The models, distinctive capacity is assessed by receiver operating characteristics (ROC) analysis. Result: The Accuracy scores and ROC-AUC values obtained for various Classification Model are as follows, for Ada Boosting, the accuracy score was 0.9993 ROC-AUC was 0.9993 and followed by GBM, the accuracy score was 0.9993, was 0.9992. Conclusion: Extracting texture parameters on CT images as well as linking the Radiomics method with ML would categorize Lung Cancer commendably. 2023 IEEE. -
Testing of long run association between crude oil and gold commodities: An empirical study in India /
Test engineering & Management, Vol.82, pp.2902-2906, ISSN No: 0193-4120.