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Physical Sciences · Computer Science

Advanced Technologies and Applied Computing
Research Guide

What is Advanced Technologies and Applied Computing?

Advanced Technologies and Applied Computing is a research cluster in computer networks and communications that develops efficient and intelligent methods for image transmission in wireless sensor networks, with applications in healthcare monitoring, IoT security, and machine learning.

The field encompasses 4,299 papers on topics including cooperative communication, security, machine learning, and data analytics for image transmission over IoT devices. Research addresses challenges in wireless sensor networks and MANETs for reliable data handling in dynamic environments. Growth data over the past 5 years is not available.

Topic Hierarchy

100%
graph TD D["Physical Sciences"] F["Computer Science"] S["Computer Networks and Communications"] T["Advanced Technologies and Applied Computing"] D --> F F --> S S --> T style T fill:#DC5238,stroke:#c4452e,stroke-width:2px
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4.3K
Papers
N/A
5yr Growth
4.3K
Total Citations

Research Sub-Topics

Why It Matters

These technologies enable secure and efficient data transmission critical for healthcare applications, such as stroke risk prediction using machine learning, where Ηλίας Δρίτσας and Μαρία Τρίγκα (2022) achieved predictive models for early symptom recognition in "Stroke Risk Prediction with Machine Learning Techniques" with 253 citations. In MANETs, protocols like the improved hybrid secure multipath routing by Uppalapati Srilakshmi et al. (2021) with 169 citations protect data across intermediary nodes in disaster response and military scenarios. Energy-efficient routing in wireless sensor networks, as in Xingsi Xue et al. (2023)'s Harris-hawk-optimization approach with 140 citations, supports prolonged IoT deployments in healthcare monitoring.

Reading Guide

Where to Start

"Stroke Risk Prediction with Machine Learning Techniques" by Ηλίας Δρίτσας and Μαρία Τρίγκα (2022), as it provides a clear entry into machine learning applications for healthcare image and data transmission in sensor networks.

Key Papers Explained

Ηλίας Δρίτσας and Μαρία Τρίγκα (2022)'s "Stroke Risk Prediction with Machine Learning Techniques" establishes ML for healthcare prediction, which aligns with Neenavath Veeraiah et al. (2021)'s "Trust Aware Secure Energy Efficient Hybrid Protocol for MANET" extending security to energy-constrained networks. Uppalapati Srilakshmi et al. (2021)'s "An Improved Hybrid Secure Multipath Routing Protocol for MANET" builds on these by enhancing multipath security, while Xingsi Xue et al. (2023)'s "A Hybrid Cross Layer with Harris-Hawk-Optimization-Based Efficient Routing for Wireless Sensor Networks" integrates bio-inspired routing for WSN efficiency.

Paper Timeline

100%
graph LR P0["An Improved Hybrid Secure Multip...
2021 · 169 cites"] P1["Trust Aware Secure Energy Effici...
2021 · 141 cites"] P2["Research on the Natural Language...
2021 · 131 cites"] P3["Spatial differentiation of tradi...
2021 · 130 cites"] P4["Stroke Risk Prediction with Mach...
2022 · 253 cites"] P5["A Secure Optimization Routing Al...
2022 · 155 cites"] P6["A Hybrid Cross Layer with Harris...
2023 · 140 cites"] P0 --> P1 P1 --> P2 P2 --> P3 P3 --> P4 P4 --> P5 P5 --> P6 style P4 fill:#DC5238,stroke:#c4452e,stroke-width:2px
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Most-cited paper highlighted in red. Papers ordered chronologically.

Advanced Directions

Jiahong Cai et al. (2023)'s "GTxChain: A Secure IoT Smart Blockchain Architecture Based on Graph Neural Network" advances IoT security with graph neural networks, targeting vulnerability in scaled deployments. Xingsi Xue et al. (2023)'s hybrid routing in WSNs pushes cross-layer QoS frontiers.

Papers at a Glance

Latest Developments

Recent developments in advanced technologies and applied computing research include breakthroughs in AI, such as generative coding, mechanistic interpretability, and human-like memory systems, as highlighted in MIT's 2026 list (MIT Technology Review), and emerging trends like AI-native development platforms and confidential computing identified by Gartner (Gartner). Additionally, innovations such as analog optical computers for AI inference and quantum AI applications are also notable (Nature, News.microsoft.com).

Frequently Asked Questions

What methods secure routing in MANETs?

Uppalapati Srilakshmi et al. (2021) proposed an improved hybrid secure multipath routing protocol in "An Improved Hybrid Secure Multipath Routing Protocol for MANET" that prevents hostile node interference during data traversal across intermediary nodes. Uppalapati Srilakshmi et al. (2022) developed a secure optimization routing algorithm in "A Secure Optimization Routing Algorithm for Mobile Ad Hoc Networks" addressing dynamic topologies in disasters and military use.

How does machine learning predict stroke risk?

Ηλίας Δρίτσας and Μαρία Τρίγκα (2022) applied machine learning techniques in "Stroke Risk Prediction with Machine Learning Techniques" to recognize early symptoms from blood flow interruptions, enabling prediction based on affected brain areas. The model provides valuable information for preventing disability through timely intervention.

What clustering improves energy efficiency in wireless sensor networks?

Xingsi Xue et al. (2023) introduced k-medoids with improved artificial-bee-colony clustering and Harris-hawks-optimization routing in "A Hybrid Cross Layer with Harris-Hawk-Optimization-Based Efficient Routing for Wireless Sensor Networks" to enhance QoS. This cross-layer approach manages energy in sensor nodes for sustained operation.

How does blockchain secure IoT networks?

Jiahong Cai et al. (2023) presented GTxChain, a graph neural network-based blockchain architecture in "GTxChain: A Secure IoT Smart Blockchain Architecture Based on Graph Neural Network," protecting against expanding security threats in large-scale IoT. It ensures privacy through distributed ledger mechanisms.

What is the role of neural networks in natural language recognition?

Li Guang et al. (2021) used cluster analysis with neural networks in "Research on the Natural Language Recognition Method Based on Cluster Analysis Using Neural Network" for dynamic knowledge system updates. The method applies clustering to various domains including language processing.

Open Research Questions

  • ? How can finite-time convergence be achieved in time-delay force feedback teleoperation systems for precise control?
  • ? What graph neural network optimizations best secure large-scale IoT against evolving attacks?
  • ? Which hybrid protocols maximize trust and energy efficiency in dynamic MANET topologies?
  • ? How do cross-layer optimizations with bio-inspired algorithms extend WSN lifetime under varying loads?

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