Estimating Prevalence Bounds of Temporal Association Patterns to Discover Temporally Similar Patterns

Radhakrishna, Vangipuram; Kumar, P. V.; Janaki, V.; Rajasekhar, N.

doi:10.1007/978-3-319-58088-3_20

Cited by 73 publications

(8 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Its primary focus is the systematic and mathematical exploration of brain networks and graphs. When used appropriately, graph theory techniques can provide significant new understandings of the building design, growth and development, the existence of evolution, and medical conditions of networked brain systems [38][39][40].…”

Section: Future Directions and Emerging Trendsmentioning

confidence: 99%

Expanding Horizons: Graph Theory’s Multifaceted Applications

Saxena,

Lalitha

et al. 2024

E3S Web of Conf.

View full text Add to dashboard Cite

A subfield of mathematics called graph theory studies networks of points interconnected by lines. Researchers may model and examine the structure of a network using graph theory. Mostly topological in nature, graph theory supports both qualitative and quantitative methods. Important scientific findings have been made possible by graph theory, including a better understanding of how electrical distribution systems malfunction and how health problems spread through social networks. Although network analysis typically conjures images of graph theory, complex network theory, and network optimisation, geographers employ a variety of techniques to study networks. This study emphasises the foundational significance of graph theory in modelling and analysing complicated networks by methodically exploring the many applications of graph theory throughout several fields. It starts with a review of the fundamental roles that graph theory plays in mathematical information, computational science, and chemistry. The discussion then moves to cutting-edge applications in the fields of social media, means of transport, and the field of neuroscience, demonstrating graph theory’s versatility. The research emphasises its new application in improving traffic flow projections and assessing cultural environmental amenities employing social media data. The present article validates the crucial role of graph theory in addressing contemporary issues through an extensive overview and methodological study.

show abstract

Section: Future Directions and Emerging Trendsmentioning

confidence: 99%

Expanding Horizons: Graph Theory’s Multifaceted Applications

Saxena,

Lalitha

et al. 2024

E3S Web of Conf.

View full text Add to dashboard Cite

show abstract

“…Advancements in the field of eco-friendly materials have presented interesting alternatives to traditional plastics and metals, with particular attention on biodegradable, recycled, and renewable materials [59]. The use of energy-efficient printing technology and the addition of renewable energy sources have the possibility to greatly reduce the negative ecological effects associated with energy consumption in the printing industry [60]- [63]. The adoption of additive manufacturing always results in a reduced amount of waste compared to conventional manufacturing methods.…”

Section: Challenges and Opportunities In Sustainable Additive Manufac...mentioning

confidence: 99%

Towards Sustainable Additive Manufacturing: Exploring Ecofriendly Materials for Green 3D Printing

Kumar,

Reddy,

Nagpal

et al. 2024

E3S Web Conf.

View full text Add to dashboard Cite

The area of additive manufacturing, usually referred to as 3D printing, has recently experienced major growth and advancement, leading to dramatic changes across different industries like as healthcare and aerospace. But the issue of environmental sustainability remains to be of extreme significance, considering the significant utilization of resources and production of waste that relates to conventional 3D printing materials and methods. The objective of this research study is to examine the potential and efficacy of environmentally friendly materials in the wider context of 3D printing. This study examines recent advances in sustainable materials, with a focus on analysing their environmental effects, efficacy, and feasibility comparative to conventional equivalent. The research also investigates the implementation of environmentally friendly techniques within the method of additive manufacturing, covering aspects such as obtaining of materials, energy usage, and management of waste. The results of our investigation indicate that making use of environmentally friendly materials, combined with green production techniques, has the potential to considerably decrease the ecological impact of 3D printing. This progress holds promise for furthering the sustainability of additive manufacturing and designing a more sustainable future.

show abstract

“…The quintessence of these systems rests upon their capacity to provide timely and accurate visual data, which is contingent upon the seamless execution of data acquisition, processing, and visualization in a synchronous loop. The computational architecture required to sustain such operations must be predicated on high-performance computing principles, optimized for speed and reliability, while ensuring that image fidelity is not compromised [9]. Therefore, the architecture of real-time systems must be designed to handle high throughput with minimal delay.…”

Section: Computational Demands and Real-time Processingmentioning

confidence: 99%

Real-Time Biomedical Imaging for Surgical Guidance: A Review of Challenges and Solutions

Alekhya,

Reddy,

Sobti

et al. 2024

E3S Web Conf.

View full text Add to dashboard Cite

The domain of real-time biomedical imaging has seen remarkable technological advances, enhancing the efficacy of surgical interventions. This paper addresses the critical challenges associated with the implementation of real-time biomedical imaging systems for surgical guidance and discusses comprehensive solutions to mitigate these issues. It outlines the substantial computational demands for real-time processing and the necessity for high-fidelity image synthesis. The intricacies of integrating multimodal imaging data, ensuring minimal latency, and maintaining spatial accuracy for augmented reality applications are also examined. Solutions leveraging cutting-edge machine learning algorithms for image segmentation and enhancement, as well as the application of parallel processing architectures for expediting computational tasks, are presented. This manuscript also explores the potential of quantum computing paradigms in transcending conventional processing limitations. Also, the paper addresses the importance of interoperability standards for seamless integration of imaging systems in diverse surgical environments. It concludes with a discussion on the ethical implications and privacy considerations in deploying artificial intelligence in surgical settings. This paper highlights the importance of interdisciplinary innovations necessary for the advancement of real-time biomedical imaging for surgical guidance. The machine learning techniques such as CNNs, helps the trade-off with accuracy and computational speed. Whereas transfer learning procedures take 20 seconds and Federated Learning in 15 seconds represents the better performance.

show abstract

Estimating Prevalence Bounds of Temporal Association Patterns to Discover Temporally Similar Patterns

Cited by 73 publications

References 9 publications

Expanding Horizons: Graph Theory’s Multifaceted Applications

Expanding Horizons: Graph Theory’s Multifaceted Applications

Towards Sustainable Additive Manufacturing: Exploring Ecofriendly Materials for Green 3D Printing

Real-Time Biomedical Imaging for Surgical Guidance: A Review of Challenges and Solutions

Contact Info

Product

Resources

About