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2,492 papers
Technology ecosystems often reward whichever firm first controls a tightly held physical or infrastructural asset -the "anchor" -because that control reduces uncertainty, sets de facto standards, and buys market access for a higher-margin software, service, or workflow layer -the "expansion."Existing strategy research...
Edge computing has gained significant traction in recent years, promising enhanced efficiency by integrating artificial intelligence capabilities at the edge. While the focus has primarily been on the deployment and inference of Machine Learning (ML) models at the edge, the training aspect remains less explored. This s...
The analysis emphasizes the value of oversight by humans, transparency, accountability, protection of privacy, fair treatment, documentation, local validation, auditing, and compliance with regulations in the context of high-impact applications in the context of high-impact applications.
Advances in smart and intelligent unmanned systems: innovations, applications and future directionsThis special issue focuses on state-of-the-art research in intelligent unmanned systems across aerial, marine, and edge computing technologies.The selected manuscripts outline cohesive advancements in autonomous technolog...
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Continuous Monitoring of animals is hard when the people who take care of them are not around.Changes in how they are eaten, how much they drink, the way they stand and what they do during the day can show if their health is changing or if their normal routine is different.This paper talks about an Edge AI-based Smart...
In the world of rapidly evolving communication networks, network demand and traffic are increasing, which makes efficient network slicing and resource allocation techniques a requirement. The existing models for network slicing and resource allocation lack efficient algorithms, limited generalization, and practical imp...
The findings show that CPS-IoT-cloud systems support improved patient monitoring, enhanced data analytics, real-time decision support, remote healthcare delivery, personalized care, and operational efficiency, but a gap between technical feasibility and deployment readiness is revealed.
Abstract In the Internet of Vehicles (IoV), edge computing supports computation-intensive tasks through roadside unit servers. However, guaranteeing reliable task execution remains challenging in dynamic environments with limited resources. We propose a reliability-oriented computation offloading strategy based on the...
Automated shiitake pre-grading in forest-understory production environments is challenged by non-uniform illumination, cluttered backgrounds, occlusion, fine-grained appearance differences, and limited edge-computing resources. This study proposes LGB-YOLOv11n, a lightweight detector that assigns modules to feature lev...
Edge computing processes data near sources for low latency but faces cybersecurity risks in decentralized data aggregation from resource-constrained devices. This paper proposes a blockchain-enabled framework with homomorphic encryption and lightweight validation to ensure confidentiality, integrity, and authenticity....
Non-Destructive Testing (NDT) has been extensively used for the inspection of hydropower components in Nepal. Hydropower component penstock pipes are fabricated by rolling mild steel plate. The edges of the rolled plate are arc welded or submerged arc welded (SAW) along its longitudinal or spiral direction. These pipes...
Cloud computing&s;s growth exposes vulnerabilities like data breaches, unauthorized access, and single points of failure in centralized architectures. Blockchain addresses these via decentralized ledgers, cryptography, and consensus for secure data integrity and efficient resource allocation. This study integrates bloc...
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Associate Professor Cathy Wu uses reinforcement learning to help map out improvements to transportation and other multifaceted systems.
Announcing Gemini 4 Argon, our frontier model for real-world coding, enterprise knowledge work and cyber defense, rolling out soon.
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